St. Petersburg State University
Graduate School of Management
Master in Management Program
CEO INCENTIVE PLANS IMPROVEMENT IN
INTERNATIONAL PUBLIC COMPANIES
Master’s Thesis by the 2nd year student
Concentration - International Business
Boris V. Yanauer
Research advisor:
Nikolay A. Zenkevich, Associate Professor
St. Petersburg
2017
ЗАЯВЛЕНИЕ О САМОСТОЯТЕЛЬНОМ ХАРАКТЕРЕ ВЫПОЛНЕНИЯ
ВЫПУСКНОЙ КВАЛИФИКАЦИОННОЙ РАБОТЫ
Я, Янауэр Борис Всеволодович, студент второго курса магистратуры направления
«Менеджмент», заявляю, что в моей магистерской диссертации на тему «Моделирование
величины материального вознаграждения для генеральных директоров компаний на примере
международных публичны компаний», представленной в службу обеспечения программ
магистратуры для последующей передачи в государственную аттестационную комиссию для
публичной защиты, не содержится элементов плагиата.
Все прямые заимствования из печатных и электронных источников, а также из
защищенных ранее выпускных квалификационных работ, кандидатских и докторских
диссертаций имеют соответствующие ссылки.
Мне известно содержание п. 9.7.1 Правил обучения по основным образовательным
программам высшего и среднего профессионального образования в СПбГУ о том, что «ВКР
выполняется индивидуально каждым студентом под руководством назначенного ему
научного руководителя», и п. 51 Устава федерального государственного бюджетного
образовательного учреждения высшего образования «Санкт-Петербургский государственный
университет»
о том, что «студент подлежит отчислению из Санкт-Петербургского
университета за представление курсовой или выпускной квалификационной работы,
выполненной другим лицом (лицами)».
_______________________________________________ (Подпись студента)
_____28.09.2017_________________ ________________ (Дата)
STATEMENT ABOUT THE INDEPENDENT CHARACTER OF
THE MASTER THESIS
I, Boris V. Yanauer, second year master student, master program «Management», state that
my master thesis on the topic «CEO Incentive Plans Improvement in International Companies»,
which is presented to the Master Office to be submitted to the Official Defense Committee for the
public defense, does not contain any elements of plagiarism.
All direct borrowings from printed and electronic sources, as well as from master theses, PhD
and doctorate theses which were defended earlier, have appropriate references.
I am aware that according to paragraph 9.7.1. of Guidelines for instruction in major
curriculum programs of higher and secondary professional education at St.Petersburg University «A
master thesis must be completed by each of the degree candidates individually under the supervision
of his or her advisor», and according to paragraph 51 of Charter of the Federal State Institution of
Higher Education Saint-Petersburg State University «a student can be expelled from St.Petersburg
University for submitting of the course or graduation qualification work developed by other person
(persons)».
________________________________________________ (Student’s signature)
_____28.09.2017_________________ ________________ (Date)
2
АННОТАЦИЯ
Автор
Название
магистерской
диссертации
Факультет
Направление
подготовки
Год
Научный
руководитель
Описание цели, задач
и
основных
результатов
Ключевые слова
Янауэр Борис Всеволодович
Моделирование величины материального вознаграждения для
генеральных директоров компаний на примере международных
публичны компаний
Высшая
школа
менеджмента,
Санкт-Петербургский государственный университет
Менеджмент
2015
Зенкевич Николай Анатольевич
Цель: на основе анализа существующих теоретических моделей и
подходов к определению размера переменной части материального
вознаграждения для генеральных директоров компаний
усовершенствовать методику определения размера такого
вознаграждения и проверить возможность ее практического
применения на примерах публичных компаний
Задачи: обосновать требования к методике формирования
переменной части вознаграждения, проанализировать практику
принятия решений по определению размера переменной части на
примере
международных
публичных
компаний;
усовершенствовать модель оценки оптимального размера
переменной части вознаграждения генеральных директоров;
провести сравнительный анализ результатов теоретического
моделирования и реальных размеров переменной части
вознаграждения
генеральных
директоров
на
примерах
международных публичных компаний и сформулировать
предложения по
Основные результаты: были обоснованы требования к методике
формирования переменной части вознаграждения; была выбрана и
усовершенствована модель оценки оптимального размера
переменной части вознаграждения; был проведён сравнительный
анализ результатов теоретического моделирования и реальных
размеров переменной части вознаграждения генеральных
директоров на примерах международных публичных компаний
Корпоративное управление, агентская проблема, вознаграждение
генеральных директоров, оптимальный контракт, размер и
структура вознаграждения, теоретико-игровое моделирование
3
ABSTRACT
Master Student's Name
Master Thesis Title
Faculty
Main field of study
Year
Academic
Advisor's
Name
Description of the goal,
tasks and main results
Keywords
Yanauer Boris Vsevolodovich
CEO Incentive Plans Improvement in International Public Companies
Graduate School of Management, Saint-Petersburg University
Management
2015
Zenkevich Nikolay Anatolievich
Goal: Improving the mechanism of forming the variable part of CEO
compensation and test the applicability of the mechanism on
international public companies.
Tasks: based on the scientific literature substantiate the requirements
for the mechanism of forming the variable part of compensation;
analyze CEO compensation value and practice of forming the variable
part of compensation on example of international public companies in
specific industries; improve the theoretical model of forming the
variable part of CEO compensation; carry out a comparative analysis of
the results of theoretical modeling and practice of forming the variable
part of the CEO compensation in international public companies in
specific industries.
Main results: the requirements to the methodology for forming the
variable part of the compensation were justified; the model for
estimating the optimal size of the variable part of the compensation was
chosen and improved; a comparative analysis of the results of
theoretical modeling and the actual size of the variable part of the
remuneration of CEOs on the examples of international public
companies was made.
Corporate governance, agency problem, CEO compensation, optimal
contracting; compensation structure and value, game-theoretical
modeling
4
Table of Contents
Introduction ......................................................................................................................... 7
Chapter 1. CEO compensation problem ............................................................................... 9
1.1 Evolution of agency problem ..................................................................................... 9
1.2. Theoretical approaches for compensation modeling ................................................ 12
1.3. Optimal contract modeling approach ....................................................................... 14
1.4. Managerial power approach .................................................................................... 17
1.5. Conclusion .............................................................................................................. 18
Chapter 2. Research Methodology ..................................................................................... 19
2.1. The compensation model ........................................................................................ 19
2.2. Specification of parameters for the model ............................................................. 26
2.3. Conclusion ........................................................................................................... 32
Chapter 3. Practical aspects of CEO compensation on the example of U.S. public companies
..................................................................................................................................................... 34
3.1. Introduction into corporate governance system of US public companies .................. 34
3.2. Evolution of CEO compensation in US public companies ....................................... 37
3.3. Normative regulation of CEO compensation in the US public companies ................ 39
3.4. The decision making process for material compensation of CEOs in the US public
companies ................................................................................................................................. 42
3.5. The structure of material compensation of CEOs in the US public companies ......... 42
3.6. The practice of forming the material remuneration of CEOs in the IT industry and the
retail industry ............................................................................................................................ 44
3.7. Conclusion .............................................................................................................. 48
Chapter 4. Modeling of CEO incentive plans on the example of the U.S. public companies 49
4.1. Modeling of CEO incentive plans for the companies of IT industry ......................... 49
4.1.1. The compensation system at Yahoo Inc. .............................................................................. 49
4.1.2. The compensation system at Blackbaud Inc. ........................................................................ 54
5
4.1.3. The compensation system at Blucora Inc. ............................................................................ 58
4.1.4. The compensation system at Linkedin Corporation.............................................................. 61
4.1.5. The compensation system at CA Technologies Inc. ............................................................. 65
4.2. Modeling of CEO incentive plans for the companies of retail industry .................... 68
4.2.1. The compensation system at Fred’s Inc. .............................................................................. 68
4.2.2 The compensation system at Dollar Tree Inc. ....................................................................... 71
4.2.3. The compensation system at Kohl’s Corporation ................................................................. 74
4.2.4. The compensation system at Barnes & Noble, Inc. .............................................................. 77
4.2.5. The compensation structure at Lowe´s Companies, Inc. ....................................................... 80
4.3. Analysis of the results ............................................................................................. 83
4.4. Conclusion .............................................................................................................. 89
Conclusions ....................................................................................................................... 91
Limitations and further research ..................................................................................... 92
List of References .............................................................................................................. 94
Appendices ...................................................................................................................... 100
Appendix 1. Modified game tree .................................................................................. 100
Appendix 2. Solution of the modified game ................................................................. 101
Appendix 3. Sensitivity analysis on the example of CA Technologies Inc. ................... 102
Appendix 4. Performance histories of CEOs for case analysis ...................................... 103
Appendix 5. IT-industry company data on CEO compensation .................................... 107
Appendix 6. Retail industry company data on CEO compensation ............................... 116
6
Introduction
The study will deal with the problem of CEO compensation value modeling which is one of
the core issues of corporate governance. Contracts should attract and retain talented CEOs, incentivize
them to exert high level of efforts to implement the company's strategy and ensure its competitive
advantage.
To begin with, CEO compensation structure usually consists of base salary and variable part.
Base salary of CEO is less dependent on performance compared to variable part of compensation and
is usually determined by the reputation of a manager, his experience at managing companies, size of
a considered company, certain industry specifics and the level of CEO base salary across the chosen
industry. Contrary, variable part of CEO compensation is directly dependent on performance of a
company. According to Frydman and Saks (2010), a variable part of top management compensation
in form of option grants and cash bonuses has been prevalent since 1950s in the U.S. public
companies.
Traditionally, a variable part of executive compensation is considered as a tool for solving the
agency problem, that is caused by the conflict of interests between an agent (CEO) and a principal
(company owners). The principal owns the capital and instructs it to manage the agent. However, an
agent may have a tendency to opportunistic behavior due to the fact that there is a conflict of interests
between the principal and the agent in the division of profits. That is why the mechanism of forming
the variable part of CEO compensation, which eliminates motivation for opportunistic behavior,
should be worked out.
There are quite a lot of scientific studies on the topic of creation and solving models of
«optimal contract». However, we still do not have any models, which are practically viable and tested
for real companies. Thus, the goal of the research paper was to improve the mechanism of forming
the variable part of CEO compensation based on the existing theoretical models and approaches, and
test the applicability of this mechanism for the international public companies.
The research problem: development of methodology for improving the mechanism of
forming the variable part of CEO compensation, which should incentivize CEO to exert high level of
efforts to implement the company's strategy and ensure its competitive advantage.
Research gap: The mechanism of forming the variable part of CEO compensation, which
can be applied on practice.
7
Goal of the research paper is improving the mechanism of forming the variable part of CEO
compensation and test the applicability of the mechanism on international public companies.
The following tasks were to be solved:
Based on the scientific literature substantiate the requirements for the mechanism of forming
the variable part of compensation;
Analyze CEO compensation value and practice of forming the variable part of compensation
on example of international public companies in specific industries;
Improve the theoretical model of forming the variable part of CEO compensation;
Carry out a comparative analysis of the results of theoretical modeling and practice of forming
the variable part of the CEO compensation in international public companies in specific
industries
The subject of this research is the size of the incentive part of CEO compensation.
The object of this research is international publicly traded companies in specific industries.
Following research methods were used: scientific literature review, current practice review
and statistical analysis, theoretical modeling, case study analysis
The master thesis will consist of introduction, four chapters, conclusions, list of references
and appendices.
8
Chapter 1. CEO compensation problem
Significant part of scientific papers on the topic of CEO compensation focus on the analysis
of differences for compensation contract values across industries and countries. But it happened to be
that the best statistical data and research on CEO compensation originates from the U.S., therefore
this country will be in focus of our analysis. According to publications in this field [Jensen, Murphy,
2004], [Gabaix, Landier, 2007] a substantial growth in CEO compensation in U.S. was noticed in the
recent decades after a calm period of 1970-s. In their research, Frydman and Saks, demonstrated
statistics on executive compensation starting from 1930-s. It was presented that the compensation
value decreased significantly after the World War II and was growing on average at 0,8% per year at
the following 30 years. However, in the period of 1998-2007 froth rates were overcoming 10% per
year, and the total value of compensation reached a median of $7.9 mln in 2005 [Frydman, Saks,
2007; Murphy, 2013].
Publicly traded companies with dispersed ownership structure will be in the focus of our
research. When ownership and control are divided in such way, management can accumulate a
significant managerial power. From the very beginning of analysis of this fact, a problem of excessive
managerial power has been considered in science as agency problem [Jensen, Meckling, 1976].
Management of companies can utilize their privileged position in private goals with the help of, for
instance, ineffective distribution of cash flows. In addition, they can find themselves entrenched on
their positions, so that it becomes difficult to substitute them even in case of low productivity.
Therefore, every research in the field of managerial compensation should be conducted in the context
of agency problem.
As it can be seen from the introduction, executive compensation problem requires following
analysis.
1.1 Evolution of agency problem
The problem of managerial compensation is considered as one of the sides of corporate
governance, which itself is a system of relationships between managers and owners of the company
on the ensuring effectiveness of operations and protection of owner’s rights, and other stakeholders.
It is important to mention that in corporate governance a topic of interrelationships of stakeholder is
one the main ones. It could be explained by the fact that stakeholders determine a success of the
company in the market (for instance, suppliers and consumers), which impact the value for owners
[Bukhvalov, 2012].
9
One of the main contradictions and classic problems of corporate governance is agency
problem, which is focuses on the conflict of interest between owner and manager [Denis, McConnel,
2003]. The interest of owners in company is associated with its value, which most commonly is
represented as market capitalization. However, the ownerships stake in the company may be one of
many investments of that owner’s investment portfolio. Therefore, even a strong decrease in market
capitalization of the company is only partly influence owner’s wealth. The opposite position is take
by the manager of the company: his reputation and wealth are closely connected with the success of
that company he manages, which means that possible risks are very significant [Bukhvalov, 2012].
In our case under agent we will understand CEO (Chief Executive Officer), and under principal we
will understand shareholders and, as representatives of their interests, board of directors.
If we look back at the history of research of agency problem, it was firstly mentioned
explained by Ross [Ross, 1973]. He stated that, because of the separation of ownership and control
and the inclination for opportunistic behavior, a manager can pursue an opportunity to decrease his
efforts or rather make unnecessary work from principal for higher compensation. So, the manager
aims to maximize his own wealth, rather than the value of shares. Thus, the key problem is how to
align the interests of the principal and agent.
Utility of a principal depends on actions of the agent and he wants agent to maximize his
principal’s utility. Such issue as the information asymmetry prevents the principal from interpreting
the exact information on activities and decision of the principal. The utility function of the agent is
supposed to be his remuneration less his costs put in the value creation. Contrary, the utility function
of principal is his return from investments in the company.
Separation of ownership and control was one of the central concern from the beginning of the
20th century and one of the main topics of analysis of public companies. This problem is about
difference in interests of owners and managers in public companies, and corporate governance tends
to resolve this problem [Kenneth, Nofsinger, 2004].
The market capitalization value as a benefit for a principal, receives various treatments in
different models. Thus, early models were aimed at seeing the company's profit as a value that needs
to be maximized, while modern models usually follow the path of value-oriented management (value
management). However, nowadays such metric as market capitalization gains more popularity over
profits. The problem of financial effectiveness will be in detail considered by us later.
10
Traditionally, within an agency problem, compensation contract of the CEO is considered as
the tool of the solution of an agency problem (theoretical approaches to determination of the optimum
contract) or in itself as a part of an agency problem (the theory of managerial power).
To begin with, there was a concept of the optimum contract firstly time designated in works
[Holmstrom, 1979], [Grossman, Hart, 1983] which claimed that the compensation contract of CEOs
can be designed in such way so that interests of shareholders and the managers were equally
considered. Next, free market mechanisms will allow attracting the most capable CEOs for the fair
remuneration, which will bring the company a necessary combination of talent and dedication to put
significant efforts to improve and the company.
On the other hand, the theory of managerial power [Bebchuk, 2003] was pushed. In that theory
the main hypothesis is that that observed practice of establishment of a certain level of remuneration
of the CEOs is explained better by the fact that managers are capable to influence this process in the
company, and thus can establish certain amounts of remuneration, effective for them. In this case,
remuneration of the CEOs can be considered as the mechanism, via which some CEOs can take a rent
from shareholders. As a result, the stronger position the CEO has, the larger remuneration and smaller
duties he is inclined to establish to himself [Choe, Tian, 2008]. Following the assumption that there
is managerial power, remuneration of top management is considered not only as the tool for the
solution of an agency problem, but also as a component of this problem itself.
Therefore, considering the contract for the manager in practice, it is necessary to understand
that for the solution of an agency problem we need to structure the stimulating components. In this
regard, four principles of creation of the contract, which could solve an agency problem, were offered
[Milgrom, Roberts, 1992]:
When the complete information about results of work of the manager is unknown, the
principle of maximum informational content should be applied [Holmström, 1979]. It
means that any value for measurement of effectiveness of manager’s, which reflects
his level of the efforts, should be considered in remuneration. These metrics could
include relative assessment of effectiveness in comparison with other similar to
differentiate internal factors from factors of the external environment, such as, for
example, fluctuations in demand in the market. Because of the fact that influence of
external arbitrary factors is omitted, the change of remuneration happens mainly
thanks to actions of the manager that increases his incentives to acceptance of risk;
11
However, the establishment of tough incentives for the agent is not always an optimum
path for a principal. The principle of intensity of incentives claims that optimum
intensity of incentives depends on four factors: the additional income created by
additional efforts; accuracy with which the analyzed actions are estimated; extent of
acceptance of risk from the manager and sensitivity of the agent to stimulation;
The principle of intensity of monitoring supplements the previous principle when high
intensity of incentives has big coefficient of correlation with situations when the
optimum level of monitoring is also high. Thus, the principal can effectively choose
strategy from sets of combinations of contributions for incentives and monitoring.
The principle of equality of remuneration means that activities, equally valuable to a
principal, shall be equally valuable to the agent. It belongs to the problem when the
agent can be involved in several actions simultaneously, and, if one of them is exposed
to smaller monitoring from a principal, then the agent will neglect it, as the agent
prefers the actions, which are bringing him higher marginal income.
1.2. Theoretical approaches for compensation modeling
Nowadays in theoretical approaches of optimal contract determination [Core, Gray, 2001], the
optimal contract is constituted in such a way that the agent earns effective reward to maximize value
for shareholders, and that the optimal contract maximizes the net expected value for shareholders
after all transactional expenses (such as costs of contract creation) and remuneration payments.
Specialists in finance did considerable work in this direction, trying to put the theory into practice.
However, it is very difficult to do because of impossibility to observe and consider all possible
parameters in such model at the same time, such as a marginal product of work of the CEO, tendency
of the CEO to avoid of risk, fair value of work and general wealth of the manager.
Theoretically, managers receive effective financial incentives to maximize value for
shareholders through a compensation program and reduce the possibility of opportunistic behavior
on the part of the manager. The optimal contract does not mean that it is ideal, but rather it simply
means that it is the best of all possible alternatives chosen within the company, which would exclude
the possibility of opportunistic behavior on the part of the agent and would encourage him to act in
the interests of the principal. In addition, the optimal contract does not necessarily excludes agency
costs, but it rather compares the marginal effect of the contract with the marginal costs of its creation.
In conclusion, parameter of optimality itself may vary depending on changes in the business
12
environment and period. All these factors, given a rise to many hardly observable variables that need
to be taken into account for the formation of the optimal contract in practice, limit its implacability.
The first attempts to evaluate an optimal size of the contract began in the mid-20th century,
when the main method of its study was linear programming. Later, in 1960, statistical models of the
relationship between the various parameters were developed, and some research in particular
[Grossman, Hart, 1983] [Holmstroem, 1979], have helped to develop a tool to solve the problem of
assessing the optimal contract - to maximize the utility function of the principal depending on various
limitations. However, as it was previously mentioned, it is impossible to take into consideration all
the options and limitations of statistical models.
In addition, an analysis of interdependency between the management fees and the
effectiveness work was conducted at that time. For this purpose, it was important to come up with the
right assessment tools to evaluate managerial performance. Thus, it was demonstrated that proper
material measure of CEO incentive plan is a degree of his influence on the increase in the value (size)
of company [Baker, Hall, 2004]. However, it was also proven that the relationship between company
size and CEO remuneration is very sensitive to the selected period of the analysis, and, in general, it
is not objectively possible to determine this relationship, as we have seen rapid growth in the amount
of remunerations and the sizes of the companies since the 1970s [Frydman, Saks, 2010].
Moreover, a principal usually cannot directly observe the level of efforts applied by CEO
because such efforts are difficult to estimate based on external analysis. It is difficult to determine the
level of effort because the physical monitoring is quite expensive itself, which is especially crucial
for small shareholders in the conditions of diluted ownership structure in US companies. The financial
and business results of the company for these structural reasons may be subject to manipulation by
the CEO. As a result, we face the problem that, in fact, it is almost impossible to observe the level of
management effort, which means that there are favorable conditions for opportunistic behavior by the
CEO.
Besides that, one of the problems in theoretical approaches for estimation of the level of
management effort is the fact that almost all the work evaluated only by two states efforts (high and
low), while, in fact, they should be described in much more complex mathematical models. The use
of a high-level efforts associated with some costs (the opportunity cost of lost opportunities), and the
higher the level of effort, the more significant the marginal increase in costs is
Modeling the level of effort was applied in the research, in which two levels of effort of the
manager were considered: high and low, in addition to the fact that the company could get low or
13
high income [Tirole, 1998]. One of the assumption of the model was that the level of income
determines the amount of remuneration of CEO, however, the considered the utility function was
unchanged, which ultimately means that the CEO has no incentive to use high-level efforts.
In the 20th century, a number of theories and models that sought to determine the optimal
contract were developed, but many of them turned out to be inapplicable in practice. A more detailed
look at practical approaches to modeling the optimal contract is presented in the next paragraph.
1.3. Optimal contract modeling approach
In this paragraph, we consider the theoretical works that try to explain the factors influencing
constant growth of the CEO remuneration, low sensitivity of this remuneration from the actual impact
and the high sensitivity from luck. This will help to form an idea of what obstacles exist in modeling
the optimal contract.
To begin with, one of the biggest drawbacks of the optimal contract models is that they do not
differentiate agents by their quantitative characteristics. Some researchers tried to introduce CEO
talent into the model as a variable. According to the theory, CEO talent has a great value in large
companies, which means that large companies will attract more talented CEO and pay them higher
remuneration [Rosen, 1981]. Moreover, they developed appropriate models, which assume that the
talent has a multiplier effect on the value of the company [Edmans, Gabaix, 2009]. Unfortunately,
any practical models that take into account the potential management talent still have not been
developed.
The increasing competition between companies for managerial talent derives not only from
increased size of firms. In recent studies [Murphy, Zabojnik, 2007] the theory and the empirical
results were presented, that confirmed the growing importance of generic skills of CEO in comparison
with specialized skills of CEO to the company. Moreover, even more detailed conclusions were
obtained [Giannetti, 2012], which stated that increasing probability of possible job changes (which
may be a result of the large number of generic skills) encourages managers to choose to be hired for
short-term projects rather than long-term projects, which enhances their attractiveness on the labor
market for CEOs. To prevent this behavior from the CEO, the shareholders should take a decision to
allocate a greater portion of the company’s revenue from long-term projects to CEO, which overall
will increase the expected rewards to CEO. In addition, such factors as the increase in international
trade volumes, contributed to the fact that foreign companies are more actively entering the labor
14
market of CEO talent, which further stimulate the growth of managerial remuneration [Marin,
Verdier, 2012].
However, increasing sizes of companies stimulate increases in the remuneration of CEOs
through not only the search and hiring managers that are more talented. Thus, it demonstrated,
theoretically and empirically, that large companies are more difficult to manage, and, therefore, CEO
in such companies deserve a higher reward. In addition to this, the problem of agency relationships
is more acute in large companies, which lead to stimulating manager with company stock, and hence
the larger reward for risk-taking [Miller, Gayle, 2009].
A reversed approach was suggested in another study, showing that, if the market makes
conclusions about the performance of CEO based on his remuneration, companies may intentionally
increase the size of CEO pay to improve the company's image and even temporarily stimulate the
growth of the share price. This leads to the fact that all firms seek to pay its CEO more than the
average for the market, thereby stimulating growth to the average level of executive compensation in
the industry [Schaefer, Hayes, 2008].
Another essential element in the studies of CEO pay is its (compensation) sensitivity to the
performance of the company. As performance measures usually indicators of profitability and market
valuation are used. However, numerous scientific papers, representing multiple attempts to figure out
what is the relationship between the change in the level of remuneration of the CEO and the stock
price, have been criticized, because in these models only the compensation of the current period was
accounted for, not accumulated wealth of managers [Murphy, 1985]. Later [Jensen, Murphy, 1990]
combined several approaches in evaluation of the relationship between the effectiveness of the CEO
and the wealth of large US public companies between 1974 and 1986, namely the change in wealth
to changes in the value of the company counting on one US dollar.
The relatively low sensitivity of CEO welfare to the company's financial result was
demonstrated by the example that the CEO loses only $ 3.25 per every $ 1,000 in the loss of value of
the company [Jensen, Murphy, 1990]. Also, this study was the beginning of a number of major works,
which were aimed on proving that there is a decreasing dependence of CEO welfare to the company's
value in one-dollar value by increasing the size of the company.
While CEOs of companies, as it has already been shown, suffer not enough losses in the case
of the low company performance, additional complexity in modeling the incentive plan is that
management is often encouraged for the result triggered by growth of the market, in other words,
external factors that are outside of the scope area of responsibility of management. In other words,
15
those managers are rewarded for good luck [Bertrand, Mullainathan, 2001]. This practice calls into
question the theory linking the remuneration of top management with their effectiveness.
Then [Hall, Liebman, 1998] continued research in the direction of identifying the relationship
between CEO ownership share in the company and the remuneration level. However, the hypothesis
of the relationship between effectiveness of communication and the level of remuneration was also
put under question mark, remaining one of the main problems in the theory of compensation.
Among other interesting approaches to modeling the optimal contract it is necessary to
identify attempts to explain a growth of CEO remuneration in recent years through the strengthening
of institutions of corporate control and closer monitoring of CEO job, which are suffering from more
serious requirements [Hermalin, 2005]. In addition, the relationship of remuneration CEO and the
company's corporate strategy was studied. The authors of this study showed that the higher
remuneration encourages managers to execute more ambitious strategies [Dow, Raposo, 2005].
Moreover, returning to the problem of managerial efforts evaluation, it is worth mentioning
that it would be logical to tie CEO remuneration to shareholder value in case when a principal cannot
fully observe the efforts of the agent. For comparison, in the case if a manager had only a fixed
payment, it would not be enough to spur on the use of a high level of effort, which is associated with
higher costs, without additional compensation [Holmstrom, 1979]. Therefore, the two-part structure
has been designed with two main components of the remuneration: a fixed and a variable part, which
stimulates the CEO on the use of high-level efforts.
In recent years, increasing attention was addressed to such element of remuneration as
severance package, especially in light of the recent financial crisis. Mostly this element is paid to the
CEO, who were fired, compared with those who left the company on their own. Therefore, very often
this compensation rewards CEO for the low effectiveness of the company [Yermack, 2006].
Finally, severance package can hardly be considered in the context of agency problem, when
the CEO controls only its own level of effort, but can be explained by a broader approach. It was
shown that the possibility to get a severance package may hold the CEO from entrenchment by him
concealing negative information, which may lead to the dismissal [Inderst, Mueller, 2008]. However,
for example, some cases were also considered, when search for and introduction of new technologies
compared with existing ones were considered as more important element in the work of the CEO,
and, moreover, allowed sometimes a compensation for non-successful results [Ederer, Manso, 2008].
16
1.4. Managerial power approach
On the example of works by Jensen and Murphy in the previous section we saw that only
weak dependences between company performance and executive compensation were discovered in
1990s. So this conclusion led to new approaches which focus on different aspect of principal-agent
problem. Due to the fact that in the case of weak corporate governance, a powerful CEO can extract
additional bonuses from his position and independently establish the desired compensation, in
executive power executive compensation is considered as part of the agency's own problem.
In this approach it is assumed that CEO is «controlling» the board of directors and that board
and CEO are cooperating with each other, setting each other extra compensation (more that needed
to provide rational incentive for CEO to work successfully), and protecting each other. Possible
constraints include reputational loss for CEO in case of being caught extracting excessive
compensation. The real life form of that is market cost of reputation devaluation and other social
costs.
Some of researches looked at how managerial power influence on executive compensation
design. In the management power hypothesis [Bebchuk, Fried, 2004] it is said that the form of
compensation, which allows to extract from the rent, is either related to the value (options for shares,
fund rewards, pensions), or not observed. When stock options are given to general directors before
the release of good reports or news, the phenomenon of denial takes place (Yermack, 1997).
There are multiple studies where various aspects of managerial influence over their own
compensation are examined. In one of those, researchers came to the conclusion that companies
where CEO just receives his compensation for siting out have a negative influence on the companies
with strong corporate governance in the labor market for CEO [Acharya, Volpin, 2010]. Another one
tends to explain that companies select highly paid peers for selecting CEO compensation at the
competitive level. The effect gets even stronger in case CEO is a chairman of the board of directors
or peer group is too small [Faulkender, Yang, 2010].
In addition, some researchers are considering cases of forgery of reporting documents. CEO
may try to manipulate the disclosed reports with necessary results if his compensation depends on
company performance. Some authors present the evidence that there is a positive relationship between
using stock-based awards and manipulation of reporting [Burns, Keida, 2006].
Recent studies argue that payment of performance and corporate governance are in addition
to solving the agency problem, thus harmonizing managerial authority and optimal approaches to
17
contracts [Dicks, 2012]. As a conclusion, the companies with weak governance provoke usage of
excessive compensation.
Also, more and more attention is paid upon CEO’s bargaining power. Thus, it was shown that
corporate strategies that increase CEO bargaining power relative to other stakeholders, will lead to
an increase in CEO equity, cash and total compensation [Pandher, 2013].
1.5. Conclusion
There is a large amount of research papers on modeling the value of CEO remuneration and,
in particular, the size of the variable part of the remuneration, through the studies of the structure and
determinants of compensation. However, there is still a number of contentious issues.
Based on the analysis of theoretical approaches, we can formulate some of the requirements
for the procedure of formation of the variable part of the remuneration CEO.
First, game-theoretic approach should be chosen as a method of modeling the variable part of
the CEO compensation. This decision is motivated by the fact that determining the size of the variable
part of the CEO compensation is directly connected with solution of opportunistic behavior problem,
which is better simulated by game-theoretical models. In our analysis, it was also shown that the
statistical model estimating the size variable remuneration CEO showed the inconsistency.
Second, it worth mentioning that some of the actions of an agent cannot be observed, and the
results of his actions can be random. Moreover, the amount of remuneration is affected by a large
number of specific conditions, such as industry affiliation, time interval of solution, changes in the
legal environment, fluctuations in market conditions, changes in technology, etc.
The model should also take into account the personal characteristics of the CEO such as talent
or reputation that affect the value of the manager and, thus, the expected rewards to achieve high
performance of the company. There are currently no practical models that take into account the talent
of manager. Therefore, a chosen model should take into account, at least, the reputation of CEO in a
historical perspective.
18
Chapter 2. Research Methodology
The purpose of this chapter is to discuss and justify research methods to be used in the
empirical part of the thesis. As was discussed in the previous chapter, most of current research studies
on executive compensation present various dependencies of compensation on other variables. An
obvious limitation of these studies is that these models are used for theoretical purposes to obtain
qualitative results. Consequently, there is a lack of studies which explain the compensation evolution
starting from 1960s-70s and present practical recommendations for constructing compensation
packages.
In accordance with the requirements mentioned in the first chapter of the document, a special
theoretical model developed by Casamatta and Guembel will be used.
2.1. The compensation model
In their paper Casamatta and Guembel consider two variants of compensation models. The
first model assumes that the company performs the same strategy for two periods. The second one
assumes that the can change a manager or strategy after the first period. We will use the second model,
since it is more realistic in view of the fact that usually after the first phase of execution of the strategy
board of directors may call into question the efficacy of the strategy itself and the level of effort of
the company's CEO in the event of failure to achieve their strategic goals. However, some of the
conclusions of the first models will be also used by us in the analysis, and the model itself will be
presented in the Appendix later.
As was shown in the previous report [Yanauer, 2016], this model represents a theoretical
interpretation of the game of agency problem, whose goal is to simulate the incentive compensation
plan for the CEO (based on the efficiency component of the payroll) to encourage the implementation
of the strategy. The principal (owner, shareholder, investor) hires an agent (CEO, manager) who
select the company's strategy to be implemented in the following period, and then by a decision of
the principal contract with current CEO is to terminated or not. To develop the model, the following
assumptions have been considered:
1.
The game involves two players - the principal (owner / investor / shareholder; in some cases,
the board of directors) and the agent (CEO, manager). All interactions between them occur within the
company itself.
2.
All communication between two players (principal and agent) happens during two periods,
t ∈ {1,2}.
19
3.
The principal hires the agent at the start of the first period and arranges a contract with certain
amount of compensation, 𝑤(𝑅), where 𝑤 is an incentive part of overall compensation of agent and 𝑅
is the performance of the company in the first period.
4.
The hired agent can be of two types: H – high type and L – low type. A high-level manager
always chooses a successful strategy 𝑆0 = 𝐺 whereas a low-level manager chooses a poor,
unsuccessful strategy 𝑆0 = 𝐵. The likelihood that the CEO has a high type of H (prior to the
implementation of the strategy in the Company) is referred to as the reputation of the CEO 𝑞0 ≥ 0.5
and called CEO reputation. The type of CEO is unknown to the principal or agent. The agent's
reputation after the 2nd and 1st periods is denoted as follows:: 𝑞 𝑖,𝑗 = 𝑝𝑟𝑜𝑏(𝑀 = 𝐻 | 𝑅1 =
𝑅𝑖 𝑎𝑛𝑑 𝑅2 = 𝑅𝑗 ) and 𝑞 𝑖 = 𝑝𝑟𝑜𝑏(𝑀 = 𝐻 | 𝑅1 = 𝑅𝑖 ), 𝑖, 𝑗 ∈ {𝑙, ℎ} respectively.
5.
To execute the chosen strategy, the agent must choose whether to undertake high or low efforts
𝑒1 ∈ {𝑒1 , 𝑒1 }; For the principal there are no efforts (which reflect the essence of the problem). High
level of efforts 𝑒1 means individual costs 𝑐 for the manager. The difference between high and low
levels of effort is expressed by the following formula:
∆𝑒1 = 𝑒1 − 𝑒1 .
6.
If CEO chooses the successful strategy 𝑆0 = 𝐺, then the Company performance is high 𝑅ℎ
with probability 𝑒1 and low 𝑅𝑙 = 0 with probability (1 − 𝑒1 ). If the chosen strategy is unsuccessful,
𝑆0 = 𝐵, the Company performance is low 𝑅𝑙 = 0 with probability equal to 1.
7.
At the end of the 1st period the principal receives an information signal 𝑠𝐺 with respect to the
needed strategy. We assumed that 𝑝𝐺 = 𝑃𝑟𝑜𝑏(𝑠𝐺 = 𝐺) is probability that the signal identifies the
successful strategy.
8.
The principal decides on the choice of strategy for the second period. If the Company's
performance after the 1st period is high 𝑅ℎ , there is no value in changing the strategy, thus 𝑆1 = 𝑆0 =
𝐺. However if the Company performance is low 𝑅𝑙 = 0, the principal considers the signal 𝑠𝐺 : he
observes whether the signal confirms the choice of the strategy. If 𝑠𝐺 = 𝑆0 , the strategy is not to be
amended; otherwise 𝑆1 ∈ {𝑠𝐺 , 𝑆0 }.
9.
Subsequently, the owner decides whether to leave the CEO or to terminate the contract with
him, and hire a new CEO.
10.
In the second period, the CEO (old or new) decides whether to undertake high or low
efforts𝑒2 ∈ {𝑒2 , 𝑒2 }; A similar effort for the owner is not observed. Again, the manager's high efforts
20
correspond to the individual expenses c for the manager. The difference between high and low levels
of effort is expressed by the following formula:
∆𝑒2 = 𝑒2 − 𝑒2
11.
If the applied strategy is successful 𝑆1 = 𝐺, the Company performance is high 𝑅ℎ with
probability 𝑒2 and low 𝑅𝑙 with probability (1 − 𝑒2 ). In case of the unsuccessful strategy 𝑆1 = 𝐵 the
Company performance is low 𝑅𝑙 with probability equal to 1.
As already mentioned, the CEO cares not only about his monetary contract, but also about his
reputation after the implementation of the strategy or termination of the contract. Denote the CEO's
reputation after period i as 𝑞𝑖 , the definition of reputation is the likelihood that the manager has a high
type H, if the Company will work well or badly (𝑅ℎ or 𝑅𝑙 respectively) and whether the Company's
strategy is changing or not in the second period.
Denote the CEO value as f (q), provided that he/she has a reputation for q; the formula is
presented below:
𝑓(𝑞) = 𝛼𝑞,
(2.1)
where 𝛼 > 0.
The agent's reputation is constantly updated, even if the contract with him was terminated
after the 1st period. The model considers only the reputation of the first, "old", CEO, who made a
strategic decision to implement. The "new" CEO does not have reputational risks, because he does
not choose a strategy.
Let us find the value of reputation 𝑞 with Bayes’ formula:
1.
If 𝑅1 = 𝑅ℎ , also 𝑆1 = 𝑆0 and 𝑅2 = 𝑅ℎ , then 𝑞 = 𝑞 ℎ = 1.
2.
If 𝑅1 = 𝑅𝑙 , 𝑆1 = 𝑆0 and 𝑅2 = 𝑅𝑙 , then
𝑞 = 𝑞0𝑙,𝑙 = 𝑞
𝑞0 (1−𝑒1 )(1−𝑝𝐺 )(1−𝑒2 )
0 (1−𝑒1 )(1−𝑝𝐺 )(1−𝑒2 )+1−𝑞0
3.
If 𝑅1 = 𝑅𝑙 , 𝑆1 ≠ 𝑆0 and 𝑅2 = 𝑅𝑙 , then
𝑞 = 𝑞1𝑙,𝑙 = 𝑞
𝑞0 (1−𝑒1 )(1−𝑝𝐺 )
0 (1−𝑒1 )(1−𝑝𝐺 )+(1−𝑞0 )(𝑝𝐺 (1−𝑒2 )+(1−𝑝𝐺 ))
4.
(2.2)
(2.3)
If 𝑅1 = 𝑅𝑙 , 𝑆1 ≠ 𝑆0 and 𝑅2 = 𝑅ℎ , then 𝑞 = 𝑞1𝑙,ℎ = 0.
The interaction between the owner and the CEO is presented in the form of a decision tree in
Appendix 1. Dotted lines include the same sets of information, in other words, a player with a stroke
can not distinguish nodes in a set of information. Several branches are not shown in detail because
the result will never happen. Branches where the CEO makes small efforts are similar to those in
21
which he makes great efforts; the only difference in probability. Also. There are 4 alternatives for the
owner: A - do not change the strategy, nor the CEO; B - do not change strategy, hire a "new" CEO;
C - change the strategy and hire a "new" CEO; D - change the strategy, leave the "old" CEO.
Payoffs of each player are described as follows:
1.
If the contract with the agent does not stop, he receives the amount of payments for two
periods. If he is dismissed, he receives compensation only for the first period, and the "new" manager
receives compensation for the 2nd period.
Let us denote the following:
𝑤 𝑖 is CEO’s compensation for the 1st period provided 𝑅1 = 𝑅𝑖 , where 𝑖 ∈ {ℎ, 𝑙 };
𝑤 𝑖,𝑗 is CEO’s compensation for the 2nd period provided 𝑅1 = 𝑅𝑖 , 𝑅2 = 𝑅𝑗 where 𝑖, 𝑗 ∈ {ℎ, 𝑙 };
𝑖,𝑗
𝑤𝑛𝑒𝑤 is a «new» CEO’s compensation for the 2nd period provided that a «new» manager is
hired and 𝑅1 = 𝑅𝑖 , 𝑅2 = 𝑅𝑗 where 𝑖, 𝑗 ∈ {ℎ, 𝑙 }.
2.
The principal payment is equal to the sum of the Company's performance indicators for two
periods, less the remuneration of the agent(s).
Solution of the model. Compensation contract takes into account the decision of the model.
Equilibrium strategies for the principal and the agent form the general equilibrium of Nash; the model
is solved by inverse induction [Yanauer, 2016].
Let's look at the last move of the game, where the top manager makes a decision about the
level of effort. In each subhead, the manager has 2 alternatives: exert high level of efforts 𝑒2 or exert
low level of efforts 𝑒2 . High efforts mean higher returns for the principal.
Let's designate the conditional probability that the executed strategy of the second period is
successful (taking into account the Company's performance in the 1st period and the fact of the
strategy change or not) as 𝑝:
1 𝑖𝑓𝑅1 = 𝑅ℎ 𝑜𝑟 𝑠𝐺 = 𝑆0
𝑝 = [ 𝑝 𝑖𝑓𝑅1 = 𝑅𝑙 , 𝑠𝐺 ≠ 𝑆0 𝑎𝑛𝑑 𝑆1 = 𝑆0
𝑝1 𝑖𝑓 𝑅1 = 𝑅𝑙 , 𝑠𝐺 ≠ 𝑆0 𝑎𝑛𝑑 𝑆1 = 𝑠𝐺
0
where
𝑃0 = 𝑞
𝑞0 (1−𝑒1 )(1−𝑝𝐺 )
0 (1−𝑒1 )(1−𝑝𝐺 )+1−𝑞0
𝑃1 = 𝑞
𝑝𝐺 (1−𝑞0 )
0 (1−𝑒1 )(1−𝑝𝐺 )+1−𝑞0
(2.4)
(2.5)
(2.6)
22
To find the compensation value, we need to solve the linear programming problem: the
principle maximizes the expected gain in the second period, minimizing the expected compensation
of the agent. The objective function is as follows:
min[𝑝(𝑒2 𝑤 𝑖,ℎ + (1 − 𝑒2 )𝑤 𝑖,𝑙 ) + (1 − 𝑝)𝑤 𝑖,𝑙 ]
Subject to:
𝑐
𝑤 𝑖,ℎ − 𝑤 𝑖,𝑙 ≥ 𝑝∆𝑒 − ∆𝑓
2
𝑝(𝑒2 𝑤 𝑖,ℎ − (1 − 𝑒2 )𝑤 𝑖,𝑙 + (1 − 𝑝)𝑤 𝑖,𝑙 ≥ 𝑐
𝑤 𝑖,ℎ ≥ 0, 𝑤 𝑖,𝑙 ≥ 0
There are four possible outcomes:
1. 𝑅1 = 𝑅ℎ . It is not feasible to change the strategy and therefore results are equivalent to the Base
game:
𝑤ℎ,ℎ =
𝑐
(2.7)
∆𝑒2
𝑤ℎ,𝑙 = 0
(2.8)
Compensation is the same for the «old» and «new» CEOs.
2. R1 = R l , sG = S0 , then p = 1. Compensation for the «old» CEO is the following:
𝑤𝑆𝑙,ℎ
= max [
1 =𝑠𝐺 =𝑆0
𝑐
𝑝∆𝑒2
𝑐
− ∆𝑓; ]
(2.9)
𝑒2
𝑤𝑆𝑙,𝑙1 =𝑠𝐺 =𝑆0 = 0
(2.10)
(1.12)
3. 𝑅1 = 𝑅𝑙 , 𝑠𝐺 ≠ 𝑆0 but 𝑆1 = 𝑆0 , then p = 𝑝0 , compensation for the «old» CEO is:
𝑤𝑆𝑙,ℎ
= max [
1 =𝑠𝐺 =𝑆0
𝑐
𝑝0 ∆𝑒2
𝑤𝑆𝑙,𝑙1 =𝑆0 = 0
− ∆𝑓;
𝑐
𝑝0 𝑒2
]
(2.11)
(2.12)
4. 𝑅1 = 𝑅𝑙 and the strategy was changed (𝑆1 ≠ 𝑆0 ).
The contract with «old» CEO is not terminated:
𝑤𝑆𝑙,ℎ
=
1 ≠𝑆0
𝑐
𝑝1 ∆𝑒2
− ∆𝑓
(2.13)
23
where ∆𝑓 = 𝑓(𝑞 𝑖,ℎ ) − 𝑓(𝑞 𝑖,𝑙 )
(2.14)
𝑤𝑆𝑙,𝑙1 ≠𝑆0 = 0
(2.15)
The contract with «new» CEO is the following:
𝑤𝑆𝑙,ℎ
=
1 ≠𝑆0 ,𝑛𝑒𝑤
𝑐
𝑝1 ∆𝑒2
𝑤𝑆𝑙,𝑙1 ≠𝑆0 ,𝑛𝑒𝑤 = 0
(2.16)
(2.17)
In accordance with these values of compensation for the 2nd period, the CEO will always
make great efforts, as his expected gain is high effort than in the case of low efforts. Now let us
consider the principal’s move.
1.
If after the 1st period the Company performance is high 𝑅ℎ or the performance is low 𝑅𝑙 = 0
but the signal identifies that the initial strategy should be maintained 𝑠𝐺 = 𝑆0 , the owner has two
alternatives: pursue the initial strategy with the "old" or "new" CEO. The basic solution for the game
shows that hiring a new manager within the initial strategy is not optimal; so we assume that in this
case the owner always prefers to leave the "old" CEO in the Company.
2.
If or the performance is low 𝑅𝑙 and the signal confirms that the initial strategy will fail 𝑠𝐺 ≠
𝑆0 , the owner has four alternatives:
A – not change the strategy nor the CEO
B – not change the strategy, hire a «new» CEO (non-optimal)
C – change the strategy and hire a «new» CEO
D – change the strategy, leave the «old» CEO (non-optimal)
The decision of the base game, presented in the study, demonstrates that option B is not
optimal. Consider alternatives C and D, provided that the strategy is changed, 𝑆1 ≠ 𝑆0 . In this case
compensation for the «old» and «new» CEOs should be compared (formulas (1.15) and (1.19)
respectively, taking into account ∆𝑓 < 0 in formula (1.16)). Compensation of the "old" CEO is higher
than for the "new" CEO; therefore, when a new strategy is adopted, the owner prefers to hire a new
manager. Therefore, alternative D is not optimal, so the owner chooses between options A and C.
Provided that the expected gain of the owner in the case of the initial implementation of the
strategy is higher than if the new strategy is implemented in the second period, he decides to follow
the original strategy (and leave the old CEO).
24
Consider the first step of the manager. He has 2 options in 2 subgames: apply high or low
effort. To find the optimal compensation, stimulating efforts, it is necessary to solve the following
linear programming problem:
min[𝑞0 (𝑒1 𝑤 ℎ + (1 − 𝑒1 )𝑤 𝑙 ) + (1 − 𝑞0 )𝑤 𝑙 ]
Subject to:
𝑤ℎ − 𝑤𝑙 ≥ 𝑞
𝑐
0 ∆𝑒1
) − (1 − 𝑒2 )∆𝑓
− 𝑒2 (𝑤 ℎ,ℎ − w𝑆𝑙,ℎ
1 =𝑆0
𝑤ℎ ≥ 0
𝑤𝑙 ≥ 0
The problem solution is the following:
𝑐
𝑤ℎ = max [0;
𝑞0 ∆𝑒1
− 𝑒2 (𝑤ℎ,ℎ − w𝑙,ℎ
𝑆1 =𝑆0 ) − (1 − 𝑒2 )∆𝑓]
(2.18)
𝑤𝑙 = 0
(2.19)
Given these results, it is transparent that the manager will make great efforts in every
subheading in the first period in order to maximize the expected compensation. Therefore, the Nash
equilibrium strategies for both players look like this:
1. For the manager: in both periods he should exert high efforts 𝑒1 and 𝑒2 .
2. For the owner: accounted for
0
1
𝑃 ≥𝑃 −
𝑃 1w𝑙,ℎ
𝑆 ≠𝑆
1
0,𝑛𝑒𝑤
−𝑃 0 w𝑙,ℎ
𝑆 =𝑆
1
0
𝑅2
(2.20)
He should not change the strategy or the manager. Otherwise, he should change the strategy
and hire a new manager.
Let us calculate expected payoff for the owner for both periods:
1.
If 𝑆1 = 𝑆0 :
(2.21)
𝑞0 (𝑒1 (𝑅 − 𝑤 ℎ + 𝑒2 (𝑅 − 𝑤 ℎ,ℎ )) + (1 − 𝑒1 )(𝑝𝐺 𝑒2 (𝑅 − w𝑆𝑙,ℎ
+ (1 − 𝑝𝐺 )𝑒2 (𝑅 − w𝑆𝑙,ℎ
)) )
1 =𝑠𝐺 =𝑆0
1 =𝑆0
2.
If 𝑆1 ≠ 𝑆0 :
))) +
𝑞0 (𝑒1 (𝑅 − 𝑤 ℎ + 𝑒2 (𝑅 − 𝑤 ℎ,ℎ ) + (1 − 𝑒1 )𝑝𝐺 𝑒2 (𝑅 − w𝑆𝑙,ℎ
1 =𝑠𝐺 =𝑆0
+ (1 − 𝑞0 )𝑝𝐺 𝑒2 (𝑅 − w𝑆𝑙,ℎ
)
1 ≠𝑆0 ,𝑛𝑒𝑤
(2.22)
The game solution tree is demonstrated in Appendix 2.
25
The presented above game composition and solution was based on the previous research on
the topic [Yanauer, 2016].
2.2. Specification of parameters for the model
To make the appropriate calculations using the model, we needed to get data for the
corresponding variables or to develop methods for approximating some variables.
Principal role. In the theoretical model, we assume that the director can take an active part in
the game and can make decisions regarding the choice of strategy and the CEO. Let's start with the
fact that in the real practice of corporate governance the shareholders have the right to monitor the
activities of CEO but with significant limitations. If the company has a major shareholder that owns
more than 50% of the company, there is an opportunity to assess the likelihood of intervention in the
above-mentioned strategic decisions based on the individual characteristics of behavior, such as
participation in strategic decision-making in the company in previous years. However, as mentioned
the US public companies have almost always dispersed ownership structure, and therefore do not
have the majority shareholder.
For the above mentioned reason, the function of the operational monitoring of the
management activities are transferred to Board of Directors, therefore, we accept the Board of
Directors as a principal, as it is obliged to act in the interests of shareholders. Moreover, there are
certain expectations of shareholders in relation to the activities of the members of the Board of
Directors: proper care (duty of care), loyalty (duty of loyalty), disclosure (duty of disclosure)
[Forrester, Ferber, 2011]. We can get information on whether the chairman of the independent
director of the Board of Directors and on the term of his tenure, to test the hypothesis that the
independent directors act solely in the interests of shareholders and are not subject to undue influence
by the CEO [Gutierrez-Urtiaga, 2000]. The initial hypothesis is the that the longer the chairman of
the board of directors retains its place, the more entrenched and dependent becomes CEO.
In each of the practical cases, we will analyze the ownership structure individually.
Agent role. In the theoretical model, by the agent we understand a member, which has been
delegated the asset management of the principal in order to maximize the utility (value) for the
principal, such as to increase the value for shareholders. Therefore, we make a valid assumption to
understand CEO as agent in the model.
Strategy. To apply the model considered necessary to define the difference between a
successful and unsuccessful strategies. The high economic results depend not only on the chosen
strategy, but also on the external (economic, political, social and technological) factors, and various
26
internal factors (eg, the level of efforts being made). In fact, as a result of a successful strategy, we
understand some long-term (more than 3 years) performance of the company that exceeds the industry
average performance in the same period of time. More precisely, in order to apply the model, we are
interested in financial incentives CEO on strategy execution.
There are different classifications of strategies that can be found in academic sources on
strategic management. Thus, in public companies, strategies can be divided into four levels of strategy
(with an indication of responsible parties in brackets): corporate (CEO), divisional (business unit
manager or executive vice president (the VP)), functional (director of marketing, finance, logistics
and so on) and operational (plant manager, office, branch, etc.). Of course, the strategy should be
coordinated at all levels, from operational to corporate levels. In our research we focus on corporate
strategies in public companies.
In other approaches, the strategy is divided into the following types depending on the scale
of coverage of markets (market penetration, market development, product development, market
development, diversification), from the vertical and geographical scale (vertical integration "forward"
and "back", the geographical expansion), the degree of diversification (related, unrelated), the
elimination strategy, cost savings and reductions and combined strategies [Grant, 2010].
According to another classification [Porter, 1980], there are four basic competitive strategies
in the industry: cost leadership, differentiation, focus on costs and focus on differentiation. Leadership
Strategy in cost or price leadership refers to the ability of the company to provide low costs,
differentiation strategy is focused on creating a unique product in the industry and competitive
strategy focus is the concentration of all the company's efforts on a specific niche of consumers.
The model helps to stimulate the CEO for the implementation and enforcement of effective
and successful strategies.
Financial performance. In general, shareholders pay attention to two aspects, evaluating the
performance of the company: their income (current and future) and the riskiness of their investments.
To assess these parameters, it is necessary to measure the company's financial or non-financial
performance. However, we assume that the company's non-financial performance can be indirectly
assessed from a financial point of view; therefore, continue to consider the types of financial
indicators. Also it is worth noting is that in the model, at the end of the period, financial results will
be evaluated in relation to the targets. Typically, the operating performance of the company is
measured by profitability, such as operating income or revenues and are used for setting targets for
27
the monetary incentive programs. With regard to the shares and options on shares of the company, in
this case, it is generally considered market indicators, such as earnings per share.
There are several possible groups of financial indexes. The first group profitability indicators
(EBIT, operating income, net income, revenues, cost), including profitability (ROI, ROE, ROA,
ROIC) and market indices and multipliers (EPS, P / E, P / B). You can also select value-oriented
indicators, such as a fundamental value, market capitalization, cash flow. Operating indicators include
indicators of business activity, liquidity, efficiency and independence. In addition, some companies
measure results of operations in terms of the ratio of borrowed funds and equity.
Compensation. There are two approaches to identify the unknown variable that is responsible
for the material rewards:
1. If it is directly connected to performance (short or long), and targets are clearly mentioned
in the form of annual reports (DEF 14A) to the Securities and Exchange Commission of the USA, it
is considered a cash incentive fee (Non-equity incentive plan) (SEC);
2. We consider a monetary incentive fee (Non-equity incentive plan) and remuneration in the
form of equity, depending on the result (Performance-based stock units), as elements of a single
stimulus package. The targets for the company's shares are also listed in our reports to the SEC.
Other components of the remuneration, such as options on the company's shares (stock
options) and shares of restricted circulation period (time-based restricted stock units) are not
considered in this study due to the fact that, as a rule, are used as periodic encouragement CEO of,
and not connected directly to performance.
To calculate the size of the incentive fee for the initial CEO after the 1st and 2nd periods using
the formula (1.7) - (1.13) (1.14) (1.18) - (1.19). In order to calculate the remuneration for the new
CEO's remuneration by formula (1.16) - (1.17), if it was decided to reject the initial CEO after the 1st
period. Our approach for CEO compensation planning process analysis is fully correspondent with
generally accepted scheme presented in the Figure 1.
28
Figure 1. CEO Compensation Planning Process. Source: [Longnecker, Henke, 2010].
Other variables. A full list of variables that are used in the model can be found in Tab. 1
Table 1. Additional model variables. Source: [Yanauer, Zenkevich, 2016]
Variable
q
Description
CEO reputation
𝑓
∆𝑓
𝑐
CEO value
Change in CEO value
Cost of using high efforts
e
Efforts exerted by CEO
𝑝
The conditional probability of
implementing a successful strategy in
the second period
Probability of successful strategy
pG
identification through signaling
Condition for changing the strategy
Calculation method
See additional calculation methods for
𝑞 0 below;
Formulas (2.2) and (2.3)
Formula (2.1)
Formula (2.14)
Bonus (planned) the relevant period
In the absence of bonus payments, use
the average bonus in the industry
See additional calculation methods
below
Formulas (2.4) - (2.6)
See additional calculation methods
below
Formula (2.20)
Further clarifications should be made regarding evaluation of probabilities in the model.
Reputation of CEO. here are two methods of estimating the parameter:
29
1. It is estimated the entire previous history of the manager's job at the post CEO. In this
case, the following parameters should be calculated:
The total number of years during which the company, in which the manager
worked as the CEO of, have been successful;
The total number of years during which the manager worked as CEO of various
companies.
The ratio of these two parameters is the desired probability.
2. Evaluated only the last place of the manager to the position of CEO. Similarly, we find
additional options:
The number of years during which the latter company, in which the manager
worked as the CEO of, has been successful;
The number of years during which the manager worked as the CEO of the latter
company.
The ratio of these two parameters is the desired probability.
However, these methods have some practical limitations. Thus, in the analysis of real-world
examples using the model we found that some CEO until his appointment worked on less high
managerial positions, such as, for example, the CFO or vice president. Therefore, we have adapted
the calculations and calculates the probability based on experience in other positions, and where
possible to use the corresponding target metrics.
Also, there were cases when some CEO before taking the office of public company, worked
in private structures, respectively, the information on them is very small. In that case only information
from the last place of work is used for the calculation, if possible.
In addition, if the manager considered in the period of time the model and responsible to the
implementation of the strategy has worked in the same company, we evaluated his performance in
the previous period as if he worked in a private company (relative to the number of successful and
unsuccessful years).
Efforts of CEO. For this variable may allocate two evaluation methods:
1. Similarly, to CEO to reputation calculation, we estimate the historical success of the
companies that the manager led. We believe that in order for the company to be successful, it
should show results above the industry average. Therefore, you must use the following
additional parameters:
30
The number of years over which the company, led by CEO of, shows the result of
higher than average for the industry;
The number of years during which the manager worked as the CEO of the company.
The ratio of these two parameters is the desired probability. Such calculations are made for a
number of indicators, and we pick the highest probability as the probability of high effort and the
least, as the probability of low effort.
2. In accordance with the fact that a high level of effort leads to additional costs from the CEO ,
we can assume that during such periods the manager is paid with a cash bonus. Accordingly,
we can estimate the probability as the ratio of years, when the bonus has taken place to the
total number of years. Maximum likelihood will give us the highest probability of effort and
the least - the likelihood of low effort.
You can also highlight some of the limitations of the methods used. Thus, in some cases, the
available information may only allow to evaluate the performance of the CEO at the same place. In
that case we compare results with that of industry average. Then, by analogy with the above methods,
we take the highest probability for probability of high effort and the least - the likelihood of low
effort. Similarly, with the CEO reputation, if he worked for the company before the period considered
in the model, we take some time back, as if he was working in another company and assesses the
performance of these years.
Probability of successful strategy identification. This option is estimated on the basis of the
analysis of the Board of Directors. That proportion of independent directors on the total number of
Board of Directors can give us an approximate probability of correct strategy recognition. Such
authors as Core (1999) and Gutierrez-Urtiaga (2000) state that the independence of directors
stimulates the improvement in implementation of responsibilities of the executive. And, since, their
area of responsibility includes monitoring the strategy and CEO of compensation, we assume that the
corresponding coefficient reflects the desired probability.
Adjustment coefficients. The fact that the model considers the finished game within two
periods determines the distribution of high reputational risks for these periods. In real practice,
strategies are introduced over a longer period and it is worthwhile to consider several more periods
in order to more accurately assess the probability of outcomes and more accurately predict the
outcomes for the players and distribute the reputation risks more evenly. Also, because of the limited
play in two periods, the reputational stimulation of the second period is significantly less than the
31
first, but, in fact, it is similarly important for the CEO to show a high result both in the first and second
period in order to receive a greater compensation.
In order for the theoretical model to be more accurate in cases of a low result in the company's
current operations, it may be necessary to introduce an additional parameter that determines the
degree of payment of the monetary bonus depending on the degree of achievement of the targets
individually for each company.
So, we can consider a situation in which the company receives a low income of 0, which does
not imply the payment of incentive compensation, the target minimum income level of the company
𝑅𝑙 , established by the company itself as satisfactory, and also the desired target level of income 𝑅ℎ .
The company can determine the coefficients 𝜀 and 𝐸, which would establish the percentage of the
remuneration paid from the target value 𝑤(𝑅ℎ ).
Thus, if the company receives an income equal to 𝑅𝑙 < 𝑅 < 𝑅ℎ , then the expected size of the
CEO incentive reward in a particular period will be:
𝑤 𝑖 = 𝜀[𝑤(𝑅ℎ )]
(2.23)
0<𝜀 ≤1
In the event that the high income of the company 𝑅ℎ was observed, then the expected size of
the CEO's incentive reward in a particular period would be:
𝑤 𝑖 = 𝐸[𝑤(𝑅ℎ )]
(2.24)
𝐸 ≥1
Note that the coefficients, as well as the possible more detailed description of targets, are
established by each company and are subject to individual adjustment. As a result, such a modification
of the considered model will allow to adapt the model to modern incentive reward practices,
considered in Chapter 4 of this work, and to increase the practical applicability and accuracy of the
model.
2.3. Conclusion
Chapter 2 has reviewed the improved model for evaluating the optimum size of the variable
part of CEO compensation in accordance with the procedure of deciding its value [Casamatta,
Guembel, 2007]. This model has several advantages.
Firstly, the model itself is a two-step decision-making process between the principal and the
agent, when on the first stage the implementation of the strategy by the CEO is considered. After the
principal knows the results after the first year, he/she can change the strategy or CEO. Theoretical
32
model argues that the strategic inertia and entrenchment of current CEO may actually be the best
solution even in case of low performance of the company because the costs to replace the strategy
assume also the costs to replace the CEO (in accordance with the decision of the model), which can
be very significant. If a change of CEO occurs, the new CEO will not be burdened with reputational
risks, which are important for the current CEO.
It is important to mention that the model takes into account the non-material incentives to
execute the high level of effort, such as the reputation of CEO. Comparatively recent studies confirm
[Apreda, 2005] that reputation is one of the key external mechanisms of corporate governance.
Research in the field of administrative powers also consider reputational loss as a stopping factor for
the CEO to increase their own wealth at the expense of the company. This finding correlates with the
works, which deals with management talent as one of the factors of non-financial incentives for
executives.
On the basis of the results contained in Chapters 1 we were able to formulate recommendations
on the specifications of parameters of the model for the example of public companies in the US. The
relative simplicity of the model and the availability calculation methodology allow for the use of the
model in the future to assess the value of non-equity incentive plans of the CEO and for the conduction
of comparative analysis of the practice of such incentives plans on the examples of US and non-US
public companies.
In following parts of the paper it will be crucial to consider a real practice of executive
compensation in international public companies. As for the model testing and application it will be
necessary to determine industries, markets and countries for the analysis. Our hypothesis is that
companies from mature and young, fast-growing industries will have different composition of equity
and non-equity compensation plans all over different markets, but the model should be able to explain
either case. To show the applicability of the model several case studies will be presented in the
Chapter 4.
33
Chapter 3. Practical aspects of CEO compensation on the example of U.S. public
companies
In this chapter we will consider general formation principles of corporate governance system
and executive compensation in the U.S. public companies, main regulatory documents and industry
specificity. We chose this country for a detail analysis, because it has by far the most mature and
regulated approach to executive compensation in public companies. Besides that it is possible to
extract substantial sample of comparable public companies within one industry to be able to make
general conclusions. Paragraph 3.1 represents the definition of public company and considers major
roles in a system of corporate governance. Paragraph 3.2 represents the analysis of historical
development and current state of executive compensation regulation in US public companies. In the
paragraph 3.3 we will more closely consider the procedure of decision making as for financial
stimulation of CEO. Paragraphs 3.5 and 3.6 will be devoted to the industry analysis of the formation
of material remuneration of CEOs in the retail and IT industries.
3.1. Introduction into corporate governance system of US public companies
Under the new definition of 2013 from the FASB (Financial Accounting Standards Board),
an organization that sets GAAP standards in the United States, a public company is a company that
meets at least one of the following criteria:
The company is required to publish its financial statements or provide for subsequent
publication in the Securities and Exchange Commission (SEC);
In accordance with the Securities Exchange Act of 1934 (the Securities Exchange Act
of 1934), as well as its amendments and related statutory acts, the company is obliged
to provide its financial statements to state regulatory bodies;
The company is obliged to provide financial reporting to state regulatory authorities
in case of sale of existing shares or issue of new shares;
Securities of the company are traded freely and without restrictions on the stock
market;
If the securities of a company's paper are freely traded on the stock market, it regularly
publishes its financial statements in accordance with US GAAP and other legal
regulations. [FASB - proposed guidance, 2013]
More briefly, a public company is a company that issued securities during in the IPO process
and trades on at least one stock exchange or over-the-counter market. Although a small percentage of
34
shares could initially be traded, a company becomes fully public when the market determines the
value of the entire company as a result of daily trading [Public Company, Investopedia].
The first regulatory document regulating public companies in the United States was the 1933
Securities Act of 1933, issued after the Great Depression crisis (The Securities Act of 1933) [Federal
regulation of publicly traded companies, Reporters Committee]. According to this law, investors
could obtain financial, as well as other information about the company that issued securities to the
stock exchange. The law forbade the publication of incorrect or distorted information [Act of 1933,
SEC U.S.].
Further, the Securities Exchange Act of 1934 was adopted, which enforced the mechanisms
of the 1933 law in the activities of the established Securities and Exchange Commission. Also, this
law tightened the requirements for reporting of public companies. The size of the companies to which
this law applies has changed over the years, but at the moment it is applied to public companies with
more than 500 shareholders and a total assets value of $ 10 million. Currently the law also requires
the company to provide annual (10-K) and quarterly 10-Q) reports to EDGAR's open electronic
database on the website of the Securities and Exchange Commission [Act of 1934, SEC US].
Before moving to description of organizational structures, it is necessary to make a note on
the structure of ownership in public companies in the United States. Historically, a high level of
shareholder protection was provided, which contributed to a gradual shift from concentrated
ownership to dispersed one. According to the mid-1990s, the United States was ranked first in the
world in terms of the share of companies with dispersed ownership structure (90%), while the share
of companies with concentrated (family property) was 10%.
One of the reasons for this type of distribution was, among other things, the adoption of the
Glass-Steagall Act in 1933, which divided banks into commercial and investment banks and limited
the ability of banks, engaged primarily in credit and deposit operations, to deal with securities and
investment transactions. Thus, institutional restrictions were imposed on the development of the
banking-oriented system in the US, and the departure from the European model of property in
companies [Bukhvalov, 2012].
By the 1990s, through the definition of a controlling owner through ownership of at least 20%
of the company's shares, the percentage of companies with dispersed property among the 500 largest
US companies was 80% [Gadhoum, Lang, Young, 2009].
The development of the corporate governance system in the United States was also influenced
by the growth of the share of professional portfolio investors among shareholders. So, by the
35
beginning of the 1990s institutional investors as a whole owned 45% of shares outstanding in the US
market [Bukhvalov, 2012].
Due to the prevalence of companies with dispersed property in the US, it is necessary to
examine in detail the corporate governance system as a system of interaction between the owner and
the manager of the company on ensuring efficiency and its functioning and protecting the interests of
the owner and other interested parties, as well as the stakeholders themselves. In corporate
governance, it is common to consider the "shareholders - board of directors - management" triangle
(including the CEO), in which the role of the principal relates to the shareholders, and the role of the
agent in the company to CEO. However, the interaction between shareholders and the CEO is not
direct, and the responsibility for resolving the conflict of interests between these stakeholders lies
with the board of directors. Therefore, in the future, we will treat shareholders and the Board of
Directors equally as a principal. We will look at all three stakeholders separately.
Shareholders (investors) of the company are the owners of the company, and can be either
individuals, financial institutions or the state. All these shareholders can have different priorities and
strategic vision, but, in general, they expect that they will receive a return on invested capital, which
they can control through the shareholders' meeting. At the shareholders 'meeting, the results of the
company's activities are monitored, nominees are approved for positions on the board of directors,
questions regarding directors' remuneration and other issues are resolved. Shareholders have the right
to exercise their voice through the board of directors, which, among other things, establishes a system
for remuneration of the CEO in the company, and generates performance targets for management. 1
A board of directors, on the one hand, is the highest level of management in the company, on
the other hand, it acts in the interests of shareholders and is monitored by shareholders. Moreover,
shareholders have expectations about the activities of the board of directors: proper care of duty, duty
of loyalty, duty of disclosure (Forrester, Ferber, 2011). In general, the following functions of the
board of directors can be distinguished: approval of the company's strategy, identification of key
performance indicators, identification of risks for the company, appointment of new managers,
determination of management fees, ensuring reliability of published reports, approval of major
transactions, protection of the company's reputation, representation of shareholders' interests and
ensuring activities in accordance with the current laws [Larcker, 2011].
Directors are elected by voting at a meeting of shareholders. The board consists of 5 to 20
members, depending on the company, which are then divided into executive directors (directly hired
1
Based on the analysis of the researched companies in the paper
36
by the company, for example, the CEO) and independent directors, who should constitute the majority
of the board, for example, according to the rules of the NYSE and NASDAQ [SEC Approves NYSE
and NASDAQ Proposals Relating to Director Independence, Findlaw].
The compensation committee on the board of directors determines the remuneration of the
CEO and suggests it for approval by all independent directors or shareholders (using the Say on Pay
system, introduced under the Dodd-Frank [Wall Street Reform and Consumer Protection Act, SEC
U.S.]). Therefore, the reward system should be built in such a way as to promote the creation of
additional value for shareholders.
Finally, the CEO of the company, as a representative of management, is a third party in the
triangle of corporate governance. He is appointed by the board of directors in order to directly perform
administrative and representative functions in the company's activities and be responsible for them,
to choose the strategic direction of development. In US public companies, as a rule, CEO performance
is assessed on the basis of the targets set by the remuneration committee. The following main
functions of the CEO can be singled out: development and implementation of the company's strategy,
risk management of the company, monitoring and management of operational activities, execution of
decisions of the board of directors, ensuring the reliability of the internal reporting and control
systems [Roles and Responsibilities CEO, Electronic resource].
3.2. Evolution of CEO compensation in US public companies
Until the 1950s, remuneration of executives was formed mainly in the form of wages and
annual bonuses, which were paid in the form of cash or shares. In addition, the size of bonuses was
set objectively according to a predetermined scale of compliance with the results of operating activity
[Frydman, Saks, 2010]. In the 1960s, long-term incentive payments, based on performance over
several years, became a significant element in the compensation system.
It can also be noted that before the year of 1950, a practice of using options as a reward was
unpopular, but this pattern changed with the introduction of a tax reform that established a much
lower capital gains tax. In general, the average remuneration of directors of companies remained
unchanged until the 1970s. So, as shown in Figure 1, the increase in the average (median) reward was
0.8 (0.7) percent per year from 1946 to 1976, but then showed a significant increase of 6.5 (5.3)
percent annually during the period from 1976 to 2003. By the end of the analyzed period in 2003, the
real size of the total remuneration was more than 5.5 times higher than in 1940.
37
Figure 2. The median and median values of the CEO's total compensation in the United States,
1936-2003. Source: [Frydman, Saks, 2005].
In comparison with the average level of wages in the US before the World War II, the average
compensation of top management was 63 times higher than that. This ratio declined sharply during
the war, amounting to only 41 times. Then, after such a significant decrease, the ratio continued to
decline gradually until the mid-1970s, when it was half the pre-war level. Inequality in the
remuneration of ordinary workers and top management continued to grow and overcame the
importance of the Great Depression in 1987, but showed the maximum historical value in 2000, when
the ratio became 330 to 1.
Figure 3. The median and median values of the CEO's total compensation in the United States
relative to the average wage, 1936-2003. Source: [Frydman, Saks, 2005].
38
Such a significant increase in compensation in the 1990s is due, in large part, to the growth in
option payments to CEOs, as can be seen in Figure 3, which shows the structure of the median
compensation of companies included in the S&P 500 index. This incentive reward element was
considered extremely effective for reasons that it was directly related to the market price of the
company's shares.
The crisis in the stock market in the early 2000s led to a decline in remuneration, however, by
2007, when it seemed that the markets had fully recovered, the growth rate returned to its pre-crisis
levels. However, the financial crisis in 2008 contributed to a reduction in the amount of CEO
compensation by various estimates up to 45% by 2009. In 2012, the stock market recovered its
position, as well as the CEO's remuneration, whose median value, as seen in Figure 4, was $8.9
million. This value is not a historical high, but still exceeds the values of the mid-1990s.
Figure 4. The structure of the median compensation of the CEO of the companies included in
the S & P 500 index, 1992 - 2011. Source: [Murphy, 2013].
The significant increase in the CEO's remuneration since the mid-1980s, as already discussed,
is directly related to the growth in the popularity of option incentive schemes. However, it is possible
that this trend has institutional reasons, and the growth in the popularity of options is related to the
benefits in terms of taxes and accounting [Murphy, 2002]. But, as can be seen in Figure 4, the options
fee has become less popular in recent years, and a certain reason for this is difficult to be called.
3.3. Normative regulation of CEO compensation in the US public companies
Apart from the already mentioned Securities Act of 1933 and the Securities Exchange Act of
1934, there are also other laws regulating financial law in the United States of America. For example,
the most significant law since the Great Depression, the law that amended the regulation of
39
remuneration for top management, was the Dodd–Frank Wall Street Reform and Consumer
Protection Act adopted in 2010 and designed to reduce the risks to the US financial system.
In particular, the section E - Accountability and Executive Compensation (paragraphs 951953) states that at least every 3 years the shareholders meeting should review or approve the executive
directors remuneration system. Also, the Dodd-Frank law approved the mandatory Say on Pay
procedure, which means that not less than every 3 years, shareholders must approve a specific amount
of remuneration for the CEO at a general meeting. [Dodd-Frank Wall Street Reform and Consumer
Protection Act, SEC US]. As the analysis of companies in Chapter 4 has shown, this practice is often
of an annual nature, and, unfortunately, targets are set increasingly as targets for the next year ahead,
which may be negative for the introduction of long-term strategies. Also, the law ruled that the
Securities and Exchange Commission should check the transparency and fairness of incentive reward
systems in the US public companies.
In addition to federal legislation, this area is directly regulated by the rules of listing on the
US stock exchanges. Thus, the New York Stock Exchange (NYSE) and the NASDAQ established
that executive directors' compensation should be approved only by independent directors [New York
and Nasdaq Compensation Committee Listing Standards, LexisNexis]. Moreover, the NYSE requires
that the compensation committees in companies consist of only independent directors. For example,
NASDAQ understands an independent director as a director who does not accept any additional
reward in any form from the company as a member of the compensation committee, with the
exception of the fixed salary of a member of the board of directors of that company. Both stock
exchanges also consider as a factor of independence the absence of any material interest of the director
in the company's ownership.
Besides the conditions for the independence of directors in a compensation committee, from
July 1st of 2013, a compensation committee should annually assess the independence of its external
consultants on the basis of the degree of interaction between the consultant company and the public
company, ownership interest, and close relations with committee members [New NYSE and Nasdaq
Compensation Committee Listing Standards, LexisNexis].
Also, the Sarbanes-Oxley Act, adopted in 2002, could be noted, which established that the
CEO and CFO of the company may be deprived of cash, securities, as well as income from the sale
of the company's securities for a period of 12 months in case of inadequate financial reporting to the
SEC because of the malfeasance. If the compensation was received before the SEC makes an
40
indictment, then the directors are required to return the full amount of the received compensation
[Sarbanes-Oxley Act of 2002. SEC U.S.].
In general, the following state bodies are responsible for regulating the remuneration of
executive directors of public companies in the US: [Government Regulation of Executive
Compensation, Execomp.org]:
US Department of Labor. The Employee Retirement Income Security Act establishes
basic rules and norms for remuneration of labor in the United States, including the
fiduciary duties of pension funds to act in the interests of their beneficiaries.
US Treasury Department. Primarily, the influence of this body is limited to testing the
system of remuneration for compliance with US tax law in matters of remuneration
with deferred payment of taxes, as well as other ways of avoiding taxation.
US Internal Revenue Service is a division of the US Treasury Department, and one of
the key tasks in regulating the remuneration of top management by this body is to
verify compliance with the IRC (Internal Revenue Code) principles. In accordance
with Section 162 (m) of the IRC, remuneration of executive directors in public
companies may not exceed $ 1 million, unless there is a qualified incentive system in
the company, which implies: the existence of targets, a compensation committee,
shareholder approval, Certification committee remuneration [Section 162 (m): Limit
on Compensation, Practical Law Company].
Securities and Exchange Commission. The functions of the body include general
supervision of public companies, observance of federal laws that we have previously
considered.
As a result, we see that in the last 20 years due to the increase in the volume of compensation
managers and the number of corporate scandals, for example, in the company Enron, the US
government introduces increasingly stringent laws that establish requirements for the process of
forming remuneration for top management, especially focusing on the independence of directors on
the compensation committee of public companies.
41
3.4. The decision making process for material compensation of CEOs in the US public
companies
Usually CEOs of public companies receive compensation comparable to competitors in the
industry, so that the company can retain a talented manager; reward, in its structure that takes into
account the interests of both the manager and shareholders.
As previously discussed, a decision on the appointment of a specific remuneration to
management is made by the board of directors. Thus, the committee on remuneration of the board of
directors prepares recommendations on the structure and size of the compensation package of the
CEO (usually with the help of independent external consultants and with the help of benchmarking
for remuneration in competitive companies). Then these recommendations are reviewed and
approved at a meeting of independent directors at the next meeting of the board of directors.
Besides the internal approval, public companies are required to disclose information on
management's remuneration to the Securities and Exchange Commission (SEC). In accordance with
the requirements, the information in full, accessible form should be presented in the following forms
of public reporting [Forms List, SEC U.S.]:
1. Form Report DEF 14A. Annually published report, which contains information on all issues
requiring the vote of shareholders. Including, discloses information on the formation, size and type
of remuneration for management. It is in the report DEF 14A that the summary tables on the
remuneration components of all executive directors for the last 3 years are presented (if the company
is public for more than 3 years). These tables were actively used by us during the implementation of
the theoretical part of the study.
2. Annual report form 10-K and quarterly report form 10-Q. Disclose information on annual
and quarterly remuneration, respectively.
3.5. The structure of material compensation of CEOs in the US public companies
Typically, the CEO's compensation consists of a fixed and a variable part. The fixed part is a
well-known salary in Russia, which is established by contract and paid in cash annually. At the same
time, the variable part is designed to stimulate the CEO to improve management effectiveness and
improve the company's performance, and represents two elements: short-term and long-term
incentives.
42
Table 2. CEO compensation structure in the U.S. public companies [Taxes and executive
compensation, Economic Policy Institute].
Components of compensation
Elements of compensation
Fixed compensation
Base salary
Short-term and long-term incentives
Cash Bonus
Non-equity incentive plan
The long-term incentives
Restricted Stock Units, Performance Stock Units, Stock
Grants
Stock Options
Other compensation
Pension and deferred compensation
All other compensation
In more detail, consider the elements of each category [Taxes and executive compensation,
Economic Policy Institute]:
1. Base salary is a fixed compensation component, the size of which does not depend on the
effectiveness, therefore it is not included in the list of tax exemption in accordance with
Section 162 (m) of the IRC (the amount of remuneration not depending on the effectiveness
and not exceeding 1 million dollars in the amount, is not subject to taxation). The size of
wages, as a rule, is determined by the level of responsibility, previous experience and the level
of wages in competitive companies.
2. Bonuses can depend on the effectiveness of a particular manager, a group or the whole
company. Also one of the peculiarities of them is that they depend on the performance in the
past period and are accordingly paid at the beginning of the next year. But despite the
dependence on the results of the activity, bonuses can be assigned without approval, which
means that this element is not legally dependent on the result in accordance with Section 162
(m) of the IRC.
3. Non-equity incentive plan may also depend on the effectiveness of a particular manager,
group or the whole company. But the difference from the bonus is that the targets are spelled
out in the company's reports (can be found in the form of DEF 14A), which means that this
element of compensation will be treated as a performance-based compensation in accordance
with the Section 162 (m) IRC.
43
Prior to the introduction of the relevant rule, companies indicated a cash bonus and a cash
incentive reward under one category, but under the new rule, companies should share the bonus paid
at the discretion of the board of directors and incentive compensation paid strictly in accordance with
the documented performance targets. Moreover, companies began to divide the monetary (non-equity
incentive plan) incentive compensation and remuneration in the form of equity-based incentives.
4. Stock remuneration means that literally a manager is assigned a share of the company's shares
that have some value while their market price is greater than zero. Such shares may be free or
restricted (Restricted Stock Units), which is the most popular option (in this case, you can sell
shares only after a certain period, for example, 3 years). There is also a scheme according to
which a manager can receive shares only upon achievement of performance targets
(Performance Stock Units). Moreover, at achievement of indicators and reception of actions
in the property, the manager can dispose of them at once. In accordance with Section 162 (m)
of the IRC, the type of remuneration dependent on the result is only Performance Stock Units,
which fall under the abbreviation PBRSUs (Performance based restricted stock units).
5. Stock options act like ordinary options, that is, in the case of an option call, the manager is
profitable to execute it if the strike price is less than the market price, and vice versa in the
case of a put option. If the option fee program is approved by shareholders, then such
consideration will be treated as a performance-based remuneration in accordance with Section
162 (m) of the IRC.
6. Deferred compensation is a reward earned in one period, but paid in another period in the
future. A classic example of deferred remuneration is a pension. It is worth noting that such a
remuneration is taxable if it is received before retirement, and is not taxed upon receipt after
formal retirement under the law.
Other types of benefits, such as the use of personal transport, travel expenses, etc., that do not
depend on the results of activities, also apply to other remuneration.
3.6. The practice of forming the material remuneration of CEOs in the IT industry and
the retail industry
In order to illustrate the applicability of the theoretical approach considered in the paper, it is
necessary to narrow the field of research and select several industries for a deeper analysis. Despite
the fact that a particular company is being considered for modeling, it is necessary to obtain the entire
data for the industry in order to obtain industry-wide indicators, as well as to select companies for
44
analysis in empirical part of the work. As the remuneration features may differ from industry to
industry, we decided to choose two industries, and then compare the results of the analysis.
The industry should be representative, which means that companies need to vary in size. Thus,
that conclusions can possibly be extrapolated to other industries.
In reality, not only public companies are included in specific industries. However,
information on the results of activities, as well as compensation of management of private companies
is not available in public, so the subject of our analysis are public companies in the United States.
Moreover, corporate conflicts in private companies, as a rule, are not so serious because of the more
concentrated nature of property.
In addition, for a serious industry analysis, it is necessary to compile an extensive sample of
performance and reward in the company, which is hindered by the lack of access to relevant databases,
for example, ExecuComp. As a result, because of the complexity in the collection of data, a sample
was collected that, with certain assumptions, can be considered representative.
Also, it is necessary to consider a stable period of time in the absence of any major crises.
Therefore, in this section we use for analysis the period from 2011 to 2013, which is characterized by
the recovery of the US economy without significant market fluctuations. In Chapter 4, in analyzing
specific situations, the time period can be extended because the model discussed in Chapter 2 assumes
analysis over two periods.
So, all public companies in the U.S. can be divided on average in 14 key industries, when
analyzing which, the largest number of "external2" CEOs we observed in industries such as retail and
the IT industry.
The choice in favor of retail and the information sector was made because retail is a fairly
mature industry with well-established players, while the IT industry is a fast-growing segment.
Therefore, parameters such as demand, competition and the products themselves are very different,
hence the factors and strategies necessary for success will also differ. It is generally accepted that the
key factors of success in developing industries are: brand development, rapid product development
and marketing, innovations, while for mature industries such factors as efficiency from scale and
diversity, low costs can be key success factors. We will analyze the various strategies of the company,
illustrating their diversity.
In the retail industry, we considered 80 companies from such sectors as Hypermarkets & Super
Centers, Home Improvement Retail, General Merchandise Stores, Apparel Retail, Automotive Retail,
2
It is about the CEO, who had not work in the company before
45
Department Stores, Computer & Electronics Retail, Specialty Stores, Homefurnishing Retail, Food
Retail3. These industries in themselves are also very different in terms of demand, marginal, cost
structure, but we decided to merge them, because in case of considering individual sectors, the number
of companies in the sample would be too small.
The following information on companies' performance in the period from 2013 to 2015 was
taken from the sources of Yahoo Finance and Thomas Reuters Datastream:
Market capitalization, billions of USD
Return on assets, %
Total Assets size, billions of USD
Data on the CEO's compensation in the period from 2013 to 2015 were obtained and
independently aggregated on the basis of the EDGAR database of the Securities and Exchange
Commission (SEC) of the USA:
Base Salary, USD
Bonus, USD
Stock Awards, USD
Stock Options, USD
Non-equity incentive plan, USD
All other compensation, USD
Total compensation, USD
The table below presents the statistics on a sample of 77 retail industry companies for the year of
2015:
Table 3. Descriptive statistics on the compensation of CEO in the retail industry. Source: compiled
independently
Base Salary,
Stock awards,
Stock
Bonus, USD
USD
USD
Options, USD
Average value
Median value
Standard dev.
Minimum
Maximum
Quantity
999123
1000000
486061
1
3867981
77
188699
0
578554
0
3500000
77
3194794
2070029
3681209
0
14200512
77
1130309
86747
1573433
0
6750011
77
Non-equity
incentive
plan, USD
1105263
630000
1230439
0
6050370
77
All other
Total
Market
Age of CEO,
compensatio compensation capitalisation,
years
n, USD
, Million USD Billion USD
237617
86573
447952
0
3033082
77
7,26
6,01
5,45
0,64
21,77
77
9,80
2,62
25,65
0,03
207,54
77
58
58
8
42
86
77
CEO tenure in
the company,
years
7
5
6
0
29
77
Total CEO
tenure, years
9
8
6
0
29
77
As can be seen from Table 2, the gap in the amount of total remuneration in the industry is
very significant. So in TJX Companies Inc. CEO in 2015 received 21.77 million dollars, and in Alco
Stores Inc. - 0.64 million dollars. In general, there is a normal distribution according to industry data.
3
In accordance with the Global Industry Classification Standard (GICS)
46
It is also worth noting that the data provide information on the personal characteristics of the
CEO, who will also help in the analysis of practical situations. So, in 2015, in the retail industry, the
average age of the CEO is 58 years, the seniority in the position of CEO in the company in question
is 7 years, and the total seniority of management of various companies is 9 years.
The distribution of remuneration components in the industry is as follows (average values for
2013): 13.7% - wages, 2.6% - bonus, 44% - shares, 15.6% - options, 15.2% - incentive reward, 8.9%
- another reward. This information does not represent an accurate distribution, but it allows us to draw
conclusions about the main trends. So, still, one of the main types of remuneration in retail is
rewarding shares.
Next, consider the descriptive statistics for a sample of 82 companies in the IT industry in
2015:
Table 4. Descriptive statistics on the remuneration of CEO in the IT industry. Source: compiled
independently
Base Salary,
Stock awards,
Stock
Bonus, USD
USD
USD
Options, USD
Average value
Median value
Standard dev.
Minimum
Maximum
Quantity
513461
491806
290022
1
1500000
82
230592
0
806000
0
5969863
82
3345314
1415501
5676549
0
38035712
82
2449150
475463
5942644
0
38054126
82
Non-equity
incentive
plan, USD
500078
305000
866273
0
6500000
82
All other
Total
Market
Age of CEO,
compensatio compensation capitalisation,
years
n, USD
, Million USD Billion USD
84331
19018
228035
68436
1645421
82
7,13
4,05
9,99
0,25
57,81
82
14,22
1,67
49,26
0,19
376,40
82
52
52
9
30
72
82
CEO tenure in
the company,
years
7
6
6
0
19
82
Total CEO
tenure, years
10
9
7
0
37
82
Here the distribution of remuneration components in the industry is as follows (average values
for 2015): 7.2% - wages, 3.2% - bonus, 46.9% - shares, 34.3% - options, 7% Incentive reward, 1.4%
- another reward. This information does not represent an accurate distribution, but it allows us to draw
conclusions about the main trends. So, still, one of the main types of remuneration in the information
industry is remuneration with shares and options, as, in general, many of the companies under
consideration are young enough.
It is also interesting to consider the fact that the average age of the CEO in the IT industry is
52 years compared to 58 years in the retail industry, which confirms our assumption that the industry
itself is younger, dynamic and requires management of the company knowledge and application of
modern information technologies. We also see that here a greater part of the remuneration is paid to
shares and options - 81.2% compared to 60.6% in the retail industry, and a fixed part of the reward is
almost 2 times less. But, on the whole, the average value of total remuneration is comparable in both
sectors.
47
3.7. Conclusion
Chapter 3 analyzes the practice of forming a material compensation for CEOs of the U.S.
public companies in terms of regulation, decision-making process for the amount of material
incentives for CEOs, and its structure in US public companies. Separately, the analysis of the practice
of material compensation of CEOs in the retail industry and the IT industry of the United States was
conducted.
For further research, two industries have been selected: the retail industry and the IT industry.
In these industries, there is a high level of income and growth rates. However, the compensation of
CEO in the industries is structured differently in many ways because of differences in the stages of
the life cycle of companies. The size of the remuneration in the retail industry, where mature
companies predominate, are different from those in the growing information technology sector.
In addition to the requirements for the model for forming the variable part of the CEO's
remuneration in Chapter 1, you can add the following:
First, in the theoretical model it makes sense to consider the company's strategy, the results of
its implementation in quantitative form and their comparison with the target performance of the
company. As it was shown, the remuneration committee establishes such indicators for performance
evaluation in order to reconcile the amount of incentive reward depending on the degree of
achievement of the targets.
Secondly, the model for the formation of the variable part of the CEO remuneration should be
specified to one or more elements of the structure of the variable part of the remuneration. Here it is
a question of monetary stimulating remuneration, or compensation of shares and bonds of the
company.
In practice, the size of CEO compensation is affected by random factors in the macro
environment. Therefore, it is highly desirable that the desired theoretical model takes into account the
influence of such external factors.
Taking into account all the requirements for the model for the formation of variable part of
remuneration, for the further comparative analysis, a game-theoretic model was chosen, which is an
application of modeling the size of the incentive reward to the CEO, which would stimulate him to
successfully execute the company's strategy [Casamatta, Guembel, 2007].
48
Chapter 4. Modeling of CEO incentive plans on the example of the U.S. public
companies
In this chapter, we will consider several examples of the theoretical model application for
modeling compensation size for general directors on examples of the retail industry and the IT
industry (case analysis method). A retrospective application of the model to specific situations will
be presented and a comparison will be made with real historical compensation data in order to test
the practical applicability of the model and evaluate the reward system in the particular situation
under consideration. In conclusion, recommendations for improving the remuneration systems under
consideration in the cases in question will be presented.
Each case will be considered according to the following plan: company description, ownership
structure, description of the board of directors in the company, biography and profile of the general
director, description of the situation, reward system at the time of analysis, solution of the theoretical
model and comparison of its results with real historical data. At the end of the section, a conclusion
will be presented based on the results of the analysis.
4.1. Modeling of CEO incentive plans for the companies of IT industry
4.1.1. The compensation system at Yahoo Inc.
Until the buyout from Verizon Communications in 2017, Yahoo was a public company
headquartered in Sunnyvale, USA and one of the world leaders in the Internet services industry.
Search engine Yahoo took the 4th place in the world with a market share of 7.68% (as for 2015) on
the personal computer platform and the 2nd place in the world with a market share of 5.2% (as for
2015) on the mobile platform Devices [Desktop Search Engine Market Share]. Yahoo was founded
in 1995 and is one of the oldest companies in the Internet services market. Later in 1996, the company
began to bargain on the US NASDAQ. In addition to the search engine, Yahoo offers users more than
60 other services [Yahoo Finance], such as, for example, financial portal (Yahoo! Finance), service
for storing photos (Yahoo! Flickr), instant messaging (Yahoo! Messenger).
Ownership structure. At the moment of the case, 69.7% of the company's property belonged
to institutional investors, 29.8% to mutual investment funds and only 0.5% belongs to the company's
insiders. The top 20 shareholders held 34% of the company, while the largest shareholder - Vanguard
Group, Inc. - does not exceed 5% [Morningstar]. Thus, we can conclude that the concentration of
property was rather low. Due to the dispersed ownership structure, we will use the board of directors
as the principal when using the theoretical model.
49
The annual shareholders' meeting mainly addresses the issue of selecting board members by
a majority vote, recommendations on remuneration to members of the board of directors, approval of
an external auditor, review and approval of various other policies and decisions [10-SEC Filings
Yahoo Inc.]. However, due to the low concentration of ownership and the frequency of meetings, it
is difficult to consider the shareholders meeting as a management body actively involved in strategic
planning.
Board of Directors. During 2010, the Board of Directors meeting took place 10 times, and the
number of its members was equal to 10. According to the guidelines of the company's management,
members of the board of directors must attend at least 75% of all meetings for the duration of their
mandate.
According to the Company's Management, the compensation committee consists of four
independent directors who are engaged in the issues of reviewing and proposing to the general
meeting of compensation systems for executive directors in accordance with the company's goals and
objectives, options and share compensation systems, evaluation of the work of the CEO and other
executive directors for the past period, the establishment of target criteria for the payment of
remuneration, the conclusion of the extension and cancellation of contracts with potential and current
executives E directors. Also, the remuneration committee deals with the remuneration for
independent directors.
From June 2007 to April 2011, all members of the board of directors, with the exception of
the CEO and COO of the company, were independent directors. Also, according to the company's
management, each member of the Remuneration Committee, the Audit and Management were
independent directors. In total, 8 out of 10 Directors are independent. The share of independent
directors on Yahoo's board of directors will be used by us as the probability of recognizing a
successful strategy for the theoretical model in this case [DEF 14A SEC Filings Yahoo Inc.].
Description of the problem. Carol Bartz was appointed CEO for Yahoo Inc. In 2009, as a
candidate with a brilliant resume and successful work experience for 14 years as CEO in the IT
industry (Autodesk), in order to bring new ideas to the company and return it to one of the leading
positions in the market. After joining the company, Carol took over the negotiations with Microsoft,
which tried to buy Yahoo, but, as a result, it turned into a partnership agreement between the
companies. Under this agreement, Yahoo refused to use its own search engine, and used the Microsoft
Bing search system, which, moreover, transferred all the technology, and would receive 12% of the
total revenue generated in the search and advertising services [The Microsoft-Yahoo Search Deal, In
50
Simple Terms]. Thus, Carol Bartz planned to focus the company's development on third-party
services and invest in them, and give back the development of Microsoft's search engine. In addition
to this strategy, Bartz has introduced a number of innovations aimed at saving, and cuts, which left
the company many talented managers and developers [Carol Bartz Fired as Yahoo's CEO]. In the
end, despite the agreement with Microsoft, the company's revenue continued to fall, new products
were not so successful, and experts noted the strategic shortsightedness and inability of Bartz to retain
leading specialists and overcome the organizational crisis.
The new strategy in 2013: after the dismissal of Carol Bartz, under the management of the
new CEO, Yahoo bought about 40 promising start-up companies in order to develop new services on
the market, with the same purpose increased the headquarters of mobile platform engineers in 10
times.
Profile of the general director. Carol Bartz, 60, CEO at Yahoo from 2009 to 2011. Fortune
magazine included Bartz in the list of the most influential women in the global business, both during
her work in Autodesk and after joining Yahoo! [Carol Bartz dismissed from the post of Yahoo! CEO].
Experience [Bloomberg]:
Jan. 2009 - Sep. 2011 - CEO of Yahoo Inc.
2008 - 2009 - Director, Member of the Audit Committee and Finance Committee of Intel
Corporation
Apr. 2006 - Jan. 2009 - Chairman of the Board of Directors of Autodesk, Inc.
1992 - Apr. 2006 - CEO, Chairman of the Board of Directors and President of Autodesk, Inc.
The performance history of Carol Bartz in Autodesk is presented in Table. 41. Based on these
data, the reputation and likelihood of making high and low efforts for the theoretical model were
calculated.
Table 5. CEO compensation structure in Yahoo! Inc. In US dollars. Compiled by: Annual Proxy
Statements (DEF 14A) Yahoo Inc., 2009-2011.
Type of compensation
2009
2010
2011
2012
2013
969,872
1,000,000
735,025
454,862
1,000,000
0
0
0
0
2250
Stock awards
12,974,722
6,626,995
9,414,211
35,000,002
8,312,316
Stock Options
29,169,334
2,114,474
2,601,376
0
13,847,283
Non-equity incentive
1,500,000
2,000,000
477,534
1,120,000
1,700,000
Base Salary
Bonus
plan
51
All other
2,615,345
5,365
3,141,389
40,540
73,863
47,229,273
11,946,834
16,369,535
36,615,004
24,936,000
compensation,
Total compensation
Non-equity incentive plan. Additional material remuneration in the form of cash bonuses is
established by the compensation committee in accordance with the developed program EIP
(Executive Incentive Plan), by which the cash bonus is determined by 70% of the company's operating
cash flow, and by 30% - by individual performance. In accordance with this plan, each executive
director is assigned a target value of the monetary bonus as a percentage of the base salary by
category. This distribution by category occurs depending on the size of the actual operating cash flow
at the end of the period. For 2010, the scheme for determining the monetary incentive fee is as follows:
[Annual Proxy Statements (DEF 14A) Yahoo Inc.]:
Table 6. Yahoo! Inc.: scheme of non-equity incentive plan distribution. Compiled by: Annual Proxy
Statements (DEF 14A) Yahoo Inc., 2009-2011.
Result/Target KPI
EIP bonus coefficient
85% or less
50%
100%
100%
105%
120%
115%
170%
120% or above
200%
Individual performance indicators are set jointly by the compensation committee and
management. In general, these indicators include the achievement of strategic goals for the planning
period and general estimates with recommendations on the results of the CEO [Annual Proxy
Statements (DEF 14A) Yahoo Inc.].
Long-term incentives through stock awards and stock options. Historically, the company has
attached great importance to this type of remuneration of executive directors in order to motivate
them to achieve long-term financial goals. In assessing the size of this kind of compensation, Yahoo
is guided by the best practices of other public companies. Just as for the cash bonus (EIP plan), the
company used a target of $ 1.825 billion in operating cash flow at the end of 2009,
Target and historical indicators for the CEO in the period from 2009 to 2011:
52
Table 7. Yahoo Inc! Target and historical indicators for the CEO. Compiled by: Annual Proxy
Statements (DEF 14A) Yahoo Inc., 2009-2011.
Year
Index
Target value
Historical value
Weight
2009
Operating cash flow
1,825 USD
1,688 USD Billions
100%
748 USD Billions
50%
6,548 USD Billions
50%
3.4%
6.1%
50%
19.6%
17.6%
50%
Billions
2010
Operating profit
630 USD
Billions
2010
Revenue
6,625 USD
Billions
2013
Revenue growth rate
ex-TAC
2013
Operating profit
margin ex-TAC
Solution of the model and comparison of the results. This case was divided into two periods:
the first period from 2009 to 2010, the second period - 2012 - 2013 years.
In accordance with the model presented in Chapter 2, we introduced the parameters necessary
to assess the material remuneration of the CEO and assess the likelihood of changing the strategy and
changing the CEO.
So, in order to assess the reputation of the CEO, Carol Bartz, we used data on revenue and
operating profit of Autodesk, Inc., in which the CEO worked earlier (Table 42). The initial reputation
of the general director is 𝑞0 = 0.67 (8 successful years out of 12). As successful years, we consider
the company's growth period (positive growth in revenue and operating profit, highlighted in green
in Table 42).
The level of effort is estimated by industry average indicators in terms of growth rates and
operating margin of profit. The probability of applying high effort is 𝑒1 = 0.83 (10 successful years
out of 12), and 𝑒1 = 0.67 (8 successful years out of 12). In the second period, we use the level of
effort of Marissa Mayer, the new CEO of the company, for which 𝑒2 = 1, and 𝑒2 = 0.83.
The company did not pay cash bonuses (as implied in the model), so the average cash bonus
for the industry was selected from the sample in (c = 0.19).
53
As a result of the solution of the model, which is presented in Table 8, the company's board
of directors was to fire the CEO and change the strategy to improve the financial performance of the
company. In addition, the board of directors had to hire a new CEO, who could implement a new
successful strategy. The material reward for the current CEO in the first period was 0, while for the
new CEO it could be $ 1.490 million (the company showed an operating profit growth of up to $ 800
billion and a successful strategy in the second period).
In reality, Yahoo, as it follows from the simulation results, dismissed the company's CEO,
Carol Bartz, and hired Merissa Mayer as CEO. This appointment had a positive effect on the
company's value (the stock price increased by 37%), and the financial targets were met (operating
profit margin of 16.4% vs. the target value of 13.3% %). The amount of real material non-issue
incentives Melissa Mayer made in the second period 1.7 million dollars (against 1.490 million dollars
on the theoretical model). However, despite the first signs of recovery, Yahoo is still lagging behind
its main competitors and has not achieved high financial performance indicators.
Applying adjustment coefficients, first period compensation of Carol Bartz should be equal
to $1,90 million due to the 118% beat on KPI of Operating profit in 2010, which results in the
coefficient of 170% due to the table presented before multiplied by 1.117 modeled (𝜀[𝑤(𝑅ℎ )]). The
second period compensation of Merissa Mayer should be equal to 1.788 million dollars (120% EIP
bonus coefficient, due to operating profit margin beat in 2013, multiplied by the modeled value of
1,490).
Table 8. Results of modeling for Yahoo! Inc.
0,66667 0,833333 0,666667
0,16667
0,17
0,0625
1
0,83
0,8
c
190
30
R
748
0,75
0
0
30
0,25
7,5
1460,2
Change?
Yes
1117,65 17852,35 1490,196 18444,7
4.1.2. The compensation system at Blackbaud Inc.
Blackbaud was founded in New York in 1981, and from the very beginning it focused only
on non-profit organizations, and has such clients as social and educational institutions, hospitals,
cultural, religious, art institutions, etc. The company is the world leader in software development for
54
this type of customers. After a series of mergers and acquisitions, Blackbaud expanded its activities
to charitable funds and corporate CSR programs. At the end of 2015, the company had more than
30,000 customers in 69 countries.
Ownership structure. Institutional investors of the company own 65% of the property, mutual
investment funds - 34.5%, insiders - 0.5%. Considering the list of the 20 largest shareholders, it should
be noted that only three of them have a share exceeding 5%, with a maximum value of 6.39%
[Morningstar]. This information may lead to the conclusion that in the company the property is
sputtered. As already mentioned in Section 2.2., we then use the company's board of directors as a
principal for use in the model of the theoretical modeling of the CEO's material compensation.
Board of Directors. The size of the board of directors of the company is 7 people. It includes
audit committees, remuneration, corporate governance, whose members are exclusively independent
directors. Only 6 out of 7 members of the board of directors, except for the CEO and the company's
president, are independent directors of [Annual Proxy Statements (DEF 14A), Blackbaud Inc,].
Blackbaud has adopted the Say-on-Pay rule, which consists in the fact that the board of
directors prepares recommendations for the remuneration of executive directors, which are then
considered at a shareholders' meeting, which in turn can vote for certain amendments. Due to the fact
that the ownership structure is deferred, the practice of applying such a mechanism for determining
remuneration has proved to be the best.
Description of the problem. In January 2012, Blackbaud entered into an agreement worth $
293.9 million to buy a competitor, Convio, which also deals with software for non-profit
organizations. As a result of this transaction, the management of Blackbaud intended to significantly
improve its client services to raise funds in the Internet, the most growing segment in this market. It
is also worth noting that the main customers of Convio were large customers, while Blackbaud
concentrated on medium-sized organizations.
However, the results at the end of 2012 showed that the financial result of the merged company
went below the planned level, although this deal was originally considered as an investment with a
long payback period. The company announced its plans to grow into a company with revenues of $
1 billion, but this forecast did not come true. Mark Chardon has been at the head of the company
since 2005, and since then the company more than tripled its revenue and became the world leader in
its industry, however, in the last year the company's growth slowed and internal organizational
problems arose in connection with the acquisition of Convio.
55
Profile of the general director. Mark Chardon, 57, CEO of Blackbaud Inc. From 2005 to 2013
Experience [Bloomberg]:
2005 - Aug. 2013 - CEO and President, Blackbaud Inc.
2001 - 2005 - CFO, Microsoft Information Worker Business
1998 - 2011 - GM and VP, Microsoft France
1984 - 1996 - Partner (office of CEO), Digital Equipment (HP)
The structure of compensation. Compensation package of the company is designed in such a
way that all types of remuneration, with the exception of wages, are associated with clear quantitative
metrics that are associated with creating value for the shareholders of the company, and that the
company remains competitive in the labor market of highly professional managers. These metrics
will be mentioned in the following sections.
Table 9. Structure of CEO compensation, Blackbaud Inc, in US dollars. Compiled by: Annual Proxy
Statements (DEF 14A), Blackbaud Inc, 2012-2014.
Type of compensation
2012
2013
2014
608,925
408,933
600,000
0
0
0
Stock awards
942,827
0
1,500,000
Stock Options
0
0
2,000,000
Non-equity incentive plan
589,421
436,693
870,000
All other compensation,
42,026
30,340
0
2,183,199
875,966
4,970,000
Base Salary
Bonus
Total compensation
Non-equity incentive plan. This type of compensation is indicated in the company's reporting
as non-issue material incentives. In 2013, the compensation committee set a 100% bonus to the CEO's
salary to meet the planned targets
Long-term incentives through stock awards and stock options. Based on the recommendation
of shareholders in the process of Say-on-Pay program implementation, since 2010 the compensation
committee has been paying considerable attention to this type of material incentive for the general
director. The size of the compensation package is determined based on the results of work for 3
calendar years (for example, 2011-2013), and is determined by the achievement of targets in the
following categories: annual growth rate of revenue, EBIT at the end of the year, retention rate.
56
Table 10. Performance targets for Blackbaud Inc. Compiled by: Annual Proxy Statements (DEF
14A), Blackbaud Inc, 2012-2014.
Year
Index
Target value
Historical value
Weight
2012
Revenue
197,7 USD
193,35 USD
25%
millions
millions
106.7 USD
108.94 USD
millions
millions
Orders for next
95,0 USD
92,245 USD
year
millions
millions
Revenue
516 USD
498,98 USD
millions
millions
282.2 USD
274 USD millions
2012
2012
2013
2013
EBIT
EBIT
50%
25%
50%
50%
millions
Solution of the model and comparison of the results. By the first period we referred the period
from 2012 to 2013, and to the second period - 2014. Similar to the example of Yahoo, we assessed
all the parameters based on the information on the CEO's biography (Table 43) and the remuneration
history (Table 9) and financial performance at Blackbaud (Table 10). The level of effort for the second
period was calculated for the new CEO of the company - Mike Gianoni. The cash bonus in the
company was not paid, therefore
Based on the results of the simulation, we can conclude that the company should have changed
the strategy and the CEO. The revenue used as a financial result showed that the strategy was
unsuccessful in the first period (498 out of 516 million dollars), and in the second period was more
successful, as the revenue was already 564 million dollars.
In reality, Mark Chardon was also dismissed after the first period in 2013 with a cash bonus
of 0 and an ineffective incentive fee of $ 437 thousand, whereas according to the theoretical model
his incentive reward should be 0. New CEO, Mike Gianoni received an incentive fee of $ 870
thousand in the second period, while the theoretical model offers him $ 1.37 million. This discrepancy
could have occurred because we used the average cash bonus for modeling, while Blackbaud is a
relatively small company in the sample.
Applying adjustment coefficients, first we see from the form DEF 14A of the year 2013 that
the achievement against the corporate performance measures was 96.7% with respect to Adjusted
57
Revenue and 97.5% with respect to Adjusted EBIT, for a corporate performance factor of 97.1%
[Annual Proxy Statements (DEF 14A), Blackbaud Inc, 2013]. Thus, for the first period we can apply
apply the average coefficient of 97% to the modeled result of 0,23, getting $0,22 million. As for the
second period, in 2014, the result against the corporate performance measures was 101.5% with
respect to Adjusted Revenue and 104.3% with respect to Adjusted EBIT, for a corporate performance
factor of 102.7% [Annual Proxy Statements (DEF 14A), Blackbaud Inc, 2014]. Thus, for the second
period we can apply apply the average coefficient of 103% to the modeled result of 1,37, getting 1.41
million dollars.
Table 11. Results of modeling for Blackbaud Inc
0,71429 0,857143 0,428571 0,85714 0,71429 0,85714286
c
0,16
31,67
R
498
0,42857 0,142857 0,048544 0,81553 0,00724 0,22916064 31,4408 0,16129 5,10806
1,12
3,845333 1,373333
0
0,22889
Change?
Yes
4.1.3. The compensation system at Blucora Inc.
The company Blucora (until 2012 Infospace) is a public company that was founded in 1996,
its headquarters is in Delaware, USA. Blucora is represented in three segments of Internet services:
information retrieval (three leading sites: Dogpile, WebCrawler and MetaCrawler), preparation of tax
reporting (through the TaxACT unit) and e-commerce. The company cooperates in the field of search
engines with such players of the market as Google.
Ownership structure. Institutional investors own 61% of the company's ownership, mutual
investment funds - 38%, company insiders - 1%. Of the 20 largest shareholders of Blucora, only two
own shares that exceed 5% of the property, and respectively equal to 5.02% and 5.01% [Morningstar].
From these data, you can draw a preliminary conclusion about the dispersed nature of the ownership
in the company. Accordingly, we consider it legitimate to use the board of directors as a principal in
the model of theoretical modeling of the amount of material incentives for the CEO.
Board of Directors. The board of directors includes 9 people who are on such committees as
an audit committee, a remuneration committee, a corporate governance committee, and a committee
on mergers and acquisitions. According to the requirements of the Securities Commission (SEC) and
58
the NASDAQ exchange, all members of the committees are independent directors, of whom 8 out of
9 are on the Board of Directors (𝑝𝐺 = 0,89).
The compensation committee evaluates the activities and contributions to the overall
performance of the company's executive directors, the recommendations to the general board of
directors on changes in the structure of fees, the tracking of compensation trends in other companies,
and the involvement of external consultants to assist in the previously listed responsibilities [Annual
Proxy Statements (DEF 14A), Blucora Inc].
Description of the problem. During and after the end of the World Financial Crisis, Infospace's
performance was extremely low, numerous reductions followed, and business, due to its lack of
diversification, was threatened by the sale. For example, revenue in 2008 in percentage terms was
50% of 2005 revenue, in 2009 - 60%, and in 2009 - 65% [Thomson Reuters Datastream]. The
company needed to find new growth drivers, one of which was entering the emerging market of tax
services through the purchase of TaxACT Holdings, Inc. in 2011. However, this transaction was more
expensive than anticipated ($ 287.5 million), and its effectiveness was only to be assessed in the
coming year. In addition, it was after the purchase of TaxACT that the company changed its name to
Blucore and re-branded it.
Profile of the general director. William Rukelshaus, 47, CEO of Blucora Inc. Since 2010.
Experience [Bloomberg]:
2010 - Present - CEO and President, Blucora Inc.
2007 - 2010 - Director, Blackbaud Inc.
2002 - 2006 - Senior Vice President, Corporate Development, Expedia Inc.
The structure of compensation.
Table 12. Blucora Inc.: CEO's compensation structure in US dollars. Compiled by: Annual Proxy
Statements (DEF 14A), in Blucora Inc, 2012-2014.
Type of compensation
2011
2012
2013
Base Salary
Bonus
400,000
415,192
450,000
150,000
0
0
Stock awards
371,200
506,800
823,140
Stock Options
2,325,087
634,379
1,094,270
540,000
613,311
450,450
8,748
4,873
10,515
Non-equity incentive
plan
All other compensation,
59
Total compensation
3,795,035
2,174,555
2,828,375
Non-equity incentive plan. The target value of the bonus, as a certain percentage of the base
salary, is consistent with the executive director at the conclusion of the contact. Thus, managers who
have greater responsibility and weight in making operating decisions, in general, have a higher
percentage of the cash bonus on the company's performance. The targets for the 2011 results were
revenue and EBITDA [Annual Proxy Statements (DEF 14A), Blucora Inc.]
Long-term incentives through stock awards and stock options. As an incentive reward for the
long-term perspective, three elements are used: Restricted Stock Units, Performance Stock Units,
Stock Grants.
Table 13. Performance targets in Blucora Inc. Compiled by: Annual Proxy Statements (DEF 14A), in
Blucora Inc, 2012-2014.
Year
Index
Target value
Historical value
Weight
2011
Revenue
198,147 USD
193,35 USD
50%
millions
millions
21,830 USD
33,783 USD
millions
millions
260,264 USD
344,814 USD
millions
millions
31,213 USD
50,648 USD
millions
millions
2011
2012
2012
EBITDA
Revenue
EBITDA
50%
50%
50%
Solution of the model and comparison of the results. As the first period we accept 2011, and
as the second period - 2012. All parameters were evaluated similarly to other cases and in accordance
with the model specifications given.
According to the results of the theoretical simulation, we can see that the non-equity
incentives of William Rukelshaus should be equal to 216.8 thousand dollars, while in real life it was
equal to 540 thousand dollars. Thus, the model showed that in a situation where potentially successful
strategy did not show itself in the first period, the board of directors could overestimate its potential,
or the CEO's contribution. However, such a strategy paid off to the company, as in 2012 it showed a
significant increase in financial results.
60
As we can see from the form DEF 14A for 2011, EBITDA was used as the two Companybased performance measures of the annual bonus plan with the maximum maximum target of 135%
[Annual Proxy Statements (DEF 14A), Blucora Inc, 2011]. Using the data from the table on
performance targets, we can extract that EBITDA in 2011 was 1,54 times higher the target value, so
the maximum bonus of 135% should be applied in this case. Applying adjustment coefficient, we get
the compensation for the first period equal to 337,5 thousand dollars. As for the second period, the
maximum possible bonus target was increased to 150% by the compensation committee [Annual
Proxy Statements (DEF 14A), Blucora Inc, 2012]. EBITDA for the year of 2012 was 1,54 times
higher the target value leading to a 50% bonus over the modeled value of 216 thousand dollars
resulting in 325 thousand dollars.
Table 14. Result of modeling for Blucora Inc.
0,5
0,75
0,55
0,6
0,25
0,2
0,8
0,2
0,88888889
c
0,15
31,67
R
238
0,027027 0,86486 0,00552 0,17497238 31,495 0,08772 2,77807
6,9375
0,289063
0
0,2168
Change?
No
4.1.4. The compensation system at Linkedin Corporation
Linkedin Ltd was founded in 2003, then changed its name to Linkedin Corporation in 2005,
and acquired its public status after entering the IPO in 2011 on the NYSE. The company represents
the world's largest professional social network with more than 300 million users in more than 200
countries. Linkedin allows users to create and maintain a list of business contacts. The company
divides its profit sources into three areas: solutions for companies to search for employees (placement
of vacancies, access to the resume database, official page of the company), marketing direction
(mainly contextual advertising), premium subscription (special status that opens additional
capabilities). On average, over the past 3 years, these directions create, respectively, 50%, 30% and
20% of the company's total revenues. Linkedin is the leader in its field, far ahead of its competitors,
for example, Viadeo c 50 million users [Annual Proxy Statements (DEF 14A), Linkedin Corporation].
Ownership structure. Institutional investors own 64.5% of the company's ownership, mutual
investment funds - 35%, company insiders - 0.5%. Of the 20 largest shareholders of Linkedin
61
Corporation, 14 own shares of less than 1%, and the largest shareholder holds 2.93% [Morningstar].
In general, we can draw a preliminary conclusion about the dispersed nature of property in the
company. Accordingly, we will use the board of directors as a principal in the model of theoretical
modeling of the amount of material incentives for the CEO.
Board of Directors. This management body of the company is represented by 7 directors.
According to the company's corporate agreement, the board of directors is divided into three subgroups, whose directors' powers expire with a difference of one calendar year. As in many of the
companies under consideration, the members of the board of directors represent three core
committees: an audit committee, a remuneration committee, and a corporate governance committee.
In addition, 5 out of 7 members of the board of directors are independent directors (𝑝𝐺 = 0,71)
[Annual Proxy Statements (DEF 14A), Linkedin Corporation].
Description of the problem. Linkedin successfully listed its shares during the IPO in 2011 at
a price almost 3 times higher than the placement price. However, many analysts were skeptical about
this assessment of the company due to the lack of its real prerequisites and new sources of revenue
for LinkedIn [LinkedIn share price more than doubles in NYSE debut]. At the same time, the
company itself noted that almost all revenue in previous years came from companies interested in
recruiting services on the site. A paid subscription service existed, but only 1% of users used it, while
the main competitors of Viadeo and Xing had 10% and 18% of subscribers, respectively [Does it beat
global in the professional-networking business?]. Linkedin decided to develop this direction,
however, it was necessary to find a balance between free and paid services, and not to lose users.
Profile of CEO. Jeffrey Weiner, 42, CEO of LinkedIn since 2009. Experience [Bloomberg]:
2009-present - CEO, Linkedin
2008-2009 - Executive Director, Greylock
2001-2008 - EVP, Yahoo!
1994-2000 - VP Online, Warner Bros.
Table 15. Linkedin Corporation: the structure of the CEO's compensation in US dollars. Compiled
by: Annual Proxy Statements (DEF 14A), at Linkedin Corporation, 2011-2013.
Type of compensation
2011
2012
2013
422,500
535,000
450,000
0
0
0
Stock awards
6,638,000
0
18,709,690
Stock Options
0
0
28,678,729
Base Salary
Bonus
62
Non-equity incentive
507,000
636,650
1,094,531
3750
3750
4664
7,571,250
1,175,400
4,907,1363
plan
All other compensation,
Total compensation
In accordance with the company's 2011 Executive Bonus Plan, half of the CEO's targeted
remuneration was based on the achievement of corporate goals, and the other half on achieving
individual goals. As corporate goals metrics such as revenue for the year, the number of users of the
social network, the number of unique visitors to the site, the number of page views, and EBITDA
were used. Individual results were evaluated by the remuneration committee on the basis of subjective
assessments with an emphasis on such a CEO quality, as a manifestation of leadership abilities.
Non-equity incentive plan. In accordance with the company's 2011 Executive Bonus Plan, half
of the CEO's targeted remuneration was based on the achievement of corporate goals, and the other
half on achieving individual goals. As corporate goals metrics such as revenue for the year, the
number of users of the social network, the number of unique visitors to the site, the number of page
views, and EBITDA were used. Individual results were evaluated by the remuneration committee on
the basis of subjective assessments with an emphasis on such a CEO quality, as a manifestation of
leadership abilities.
Table 16. Performance targets for Linkedin Corporation. Compiled by: Annual Proxy Statements
(DEF 14A), at Linkedin Corporation, 2011-2013.
Year
Index
Target value
Historical value
Weight
2011
Revenue
450 USD
522 USD millions
20%
millions
2011
Number of users
133 millions
145 millions
20%
2011
Number of unique
38 millions
44 millions
20%
visitors (per
month)
2011
Page views
28,000
33,000
20%
2011
EBITDA
48 USD
99 USD millions
20%
millions
63
Solution of the model and comparison of the results. This case was divided into two periods:
the first period in 2011, the second period in 2012. All parameters were evaluated similarly to other
cases and in accordance with the model specifications provided.
Based on the results of theoretical modeling, we can see that the company (the principal)
should not have changed either the strategy or the CEO after the first period. However, the model
indicates that Jeffrey Weiner's remuneration in the first period should be equal to 0, despite the high
performance. In fact, he received a cash incentive fee of $ 507 thousand dollars. This discrepancy
may be connected with the fact that the element of reputational risk for Jeffrey Weiner is very high
(initially high reputation and effort level), therefore irrespective of the size of the incentive reward,
he will seek to maintain and improve its reputation in the second period. In such a situation, it is more
profitable for a principal (board of directors) not to pay a bonus to the general director.
In the second period Jeffrey Weiner received a non-equity incentive fee of $636 thousand,
whereas according to the modeling results we got a value of $450 thousand. This discrepancy can be
explained, firstly, by the fact that the average bonus size was used for calculations of cash bonus in
the industry, as well as the fact that the company has recently become public and does not yet have a
well-functioning mechanism for remunerating top management in accordance with the rules of public
companies in the United States.
Due to complicated system of individual performance metrics based on 5 KPIs for each
executive, we just see from the report that Jeffrey Weiner was assigned a 120% bonus to his base
cash incentive [Annual Proxy Statements (DEF 14A), at Linkedin Corporation, 2011]. Applying this
coefficient to our resulting value of 0,450 we got that he should have received a non-equity incentive
of 540 thousand dollars in the first period. As we the next year, Jeffrey was assigned with 119% bonus
[Annual Proxy Statements (DEF 14A), at Linkedin Corporation, 2012], resulting in 535 thousand
dollars of non-equity incentives.
Table 17. Simulation results for Linkedin Corporation
0,875
0,875
0,500
0,889
0,556
0,714
c
0,150
0,375
0,333
0,200
0,571
0,027
0,856
30,814
0,295
Change?
No
0,450
0,844
0,788
0,000
R
31,670 500,000
0,406
12,872
64
4.1.5. The compensation system at CA Technologies Inc.
CA Technologies is a public American company founded in 1973, headquartered in New
York. The company is developing software for managing the information infrastructure of
enterprises, operations, databases, portfolios of projects in order to increase the productivity and
efficiency of these systems. The company's clients are more than half of the representatives of the
Global Fortune 500 list, 20 largest global banks and 25 largest federal agencies. CA Technologies
manages a development team of 13,000 people in 45 countries worldwide [Company Information,
CA Technologies].
Ownership structure. Institutional investors own 64% of the company's property, mutual
investment funds - 35.8%, insiders of the company - 0.2%. The largest shareholder of CA owns a
share of 2.15%, and the average share of the top 20 shareholders does not exceed 1% [Morningstar].
From this we can conclude that the dispersed nature of ownership in the company.
Board of Directors. In 2011, 10 out of 11 directors were independent on the company's board
of directors (𝑝𝐺 = 0,91). The governing body itself is divided into four core committees: Audit,
Compensation and Human Resource Management Committee, Corporate Governance, Legal Affairs
and Risk Management [Annual Proxy Statements (DEF 14A), CA Technologies].
Description of the problem. William McCracken joined the company in 2005 and became
CEO in 2010. At that time, the company had a number of developments and patents in the field of
information technology, but existing products did not allow it to increase revenue. Therefore, CA
spent more than $500 million on the purchase of 3 promising companies (the most well-known 3Tera) in 2010, working in the field of cloud services, storage and protection of information [Our
strategy's to both build and buy: CA Tech's McCracken]. Thus, the company changed its course from
the large-scale development and sale of universal software to the provision of cloud services and
virtualization services [CA to acquire cloud platform provider 3Tera]. It should be noted that the
market reacted negatively to this strategy of the company, and its shares fell in price by 20% in 2011.
The new strategy in 2012: with the arrival of Michael Gregoire as CEO, the company once
again focused on internal development and development (the creation of 40 profile research units),
introduced a program to attract talented engineers, began adapting products from large companies to
medium-sized businesses, improving the software itself, rather than cloud services [Q&A: CA CEO
Gregoire at the one-year mark].
Profile of CEO. William McCracken, 69, CEO of CA Technologies since 2010. Experience
[Bloomberg]:
65
2005-2012 - Director and CEO, CA Technologies, Inc.
2002-2010 - President, Executive Consulting Group, LLC.
1993-2001 - Various management positions, IBM Corporation
Michael Gregoire, 46, CEO of CA Technologies since 2012. Experience:
2005-2012 - CEO and Chairman of the Board of Directors, Taleo Inc.
2000-2005 - EVP Global Services, PeopleSoft / Oracle
1998-200 - Managing Director, EDS Information Solutions Organization
The system of compensation. The company in its compensation strategy adheres to the
principle of stimulating the long-term performance of executive directors, for example, by replacing
the remuneration with shares by the results of one year for a reward based on the results of three
years. Also, on average, only 18% of the total remuneration is wages, and 82% (20% - monetary
bonus, 67% - shares and stock options) depend on the achievement of the directors of the delivered
indicators.
Table 18. CA Technologies: CEO compensation structure in US dollars. Compiled by: Annual Proxy
Statements (DEF 14A), at CA Technologies, 2010-2012.
Type of compensation
2010
2011
2012
1,114,584
1,000,000
1,000,000
1,300,000
0
0
Stock awards
561,879
4,073,518
3,909,219
Stock Options
492,621
1,473,826
821,710
Non-equity incentive
242,507
1,266,000
1,764,000
36,627
214,091
282,672
3,748,218
8,027,435
7,777,601
Base Salary
Bonus
plan
All other compensation,
Total compensation
Non-equity incentive plan. The compensation committee at the end of the year reviews and
coordinates with the CEO and CFO performance targets needed to determine which bonus awards
are divided into corporate goals (operating income and revenue growth rate) and separately the same
indicators for the technology development group and client solutions. In addition to financial results,
some qualitative or visual goals are taken into account, such as observing delivery dates, localizing
products, adding new options to applications, and so on. [Annual Proxy Statements (DEF 14A), CA
Technologies].
66
Long-term incentives through stock awards and stock options. The company is moving from
a one-year to three-year program of capital incentives. As the metrics for payment of options is the
company's share price, for the payment of shares - revenue growth rate, operating profit margin,
operating cash flow [Annual Proxy Statements (DEF 14A), CA Technologies].
Table 19. Targets in CA Technologies. Compiled by: Annual Proxy Statements (DEF 14A), at CA
Technologies, 2010-2012.
Year
2011
Index
Operating profit
Target value
1,527
Billions
2011
Revenue growth 6,0%
Historical value
USD 1,498
Weight
USD 60%
Billions
4,3%
40%
8,1%
40%
34,8%
60%
rate
2012
Revenue growth 8,3%
rate
2012
Operating profit 34,1%
margin
Solution of the model and comparison of the results. This case was divided into two periods:
the first period in 2010-2011, the second period in 2012. All parameters were evaluated similarly to
other cases and in accordance with the model specifications given. The level of efforts for the second
period was calculated for the new CEO.
Based on the results of the modeling, we conclude that the former CEO's compensation in the
first period should be 0 due to the execution of the unsuccessful strategy. However, the company,
according to the rules of remuneration, pays a bonus in any case, which is equal to the proportional
value of the achieved result from the target value. In fact, in 2010 and 2011, William McCracken
received a cash award of $ 1.5 million. After the second period, the new CEO (Michael Gregoire),
according to the model, was about to receive 1,79 million dollars, while in fact received $1,764
million in cash financial compensation.
Applying adjustment coefficient approach for the first period, we took an operating profit and
revenue growth rate as main KPIs stated by the company for determining «Annual Performance Cash
Incentive Award Payouts» [Annual Proxy Statements (DEF 14A), CA Technologies, 2011]. The final
weighted average coefficient for modeled value of 1,157 is 87,5%, therefor the payout of the first
67
period should be equal to 1,33 millions of dollars. As for the second period, the weighted average
coefficient is equal to 100%, which implies that the payout will remain equal to 1,79 million dollars.
Table 20. Results of modeling for CA Technologies Inc.
0,8
0,8
0,4
0,857
0
0,909
c
1,3
0,4
0,857
0,068
0,847
0,010
0,326
31,344
1,790
Change?
Yes
1,517
22,371
1,790
17,460
31,67
R
1500
0,248
7,847
4.2. Modeling of CEO incentive plans for the companies of retail industry
4.2.1. The compensation system at Fred’s Inc.
The company Fred's was founded in 1947 as a regional chain of low price stores in the
southeastern United States. To date, the trading network has approximately 700 stores, 300
pharmacies in 15 US states, and Fred's headquarters are located in the city of Memphis, Tennessee.
As follows from the description, the chain stores serve low- and middle-income families in small
towns (85% of stores are located in towns with a population of less than 15,000 people). The
company's product portfolio includes pharmaceutical products (36.3%), household goods (22.6%),
food and tobacco products (16.7%), cleaning products (8.8%), beauty and health products (7,5%),
clothing (6.3%), sales to other franchise stores (1.8%) [10-to SEC Filings Fred's Inc.].
Ownership structure. The most significant part of the shares belongs to institutional investors
- 60%, mutual investment funds - 36.5%, insiders of the company - 3.5%. Of the company's 20 largest
shareholders, 8 hold stakes of 5% or more, with the largest share of 11.68% [Morningstar]. Thus, we
can conclude that the dispersed nature of ownership in the company, and this means that there is
reason to consider the board of directors of Fred's as a principal in the implementation of gametheoretic modeling.
Board of directors. The board of directors includes 7 people, including the Chairman of the
Board of Directors and the CEO of the company. Members of the Board of Directors represent
committees on corporate governance, on elections, on audit, on compensation, on pharmaceutical
issues (deals with the strategy and development of the pharmaceutical business of the company). The
compensation committee is responsible for establishing a unified system of material remuneration in
68
the company, as well as for monitoring and evaluating the activities of the directors and management
of the company. In the board of directors, 5 out of 7 directors are independent (𝑝𝐺 = 0,71).
Description of the problem. Due to increased competition and the specifics of its business
model, by 2010 Fred's faced extremely low profitability of the business (operating margin of 2.4%)
for the possibility of further expansion. Therefore, under the guidance of the CEO, the introduction
of a strategy was made focusing on 5 key areas (Core 5 Program), such as interior items, holiday
products, pet products, pharmaceuticals, chemicals and cleaning products, in which the company still
had competitive advantages over independent sellers in small settlements. The company was moving
away from daily consumption goods to more marginal and expensive categories. For this purpose,
within two years the company has planned significant capital expenditures to increase the floor space
for expensive types of goods by 50% [10-SEC Filings Fred's Inc.].
Profile of CEO. Bruce Efird, 52, CEO of Fred's since 2010. Experience [Bloomberg]:
2007-2014 - President and CEO, Fred's, Inc.
1998-2005 - Executive Vice President, Merchandising, Mejer, Inc.
The structure of compensation.
Table 21. CEO compensation structure in Fred's, Inc. In US dollars. Compiled by: Annual Proxy
Statements (DEF 14A), in Fred's, Inc, 2010-2013.
Type of
2010
2011
2012
2013
Base Salary
Bonus
650,000
650,000
682,692
700,000
0
0
0
0
Stock awards
318,138
340,379
395,000
0
Stock Options
0
106,500
965,000
0
354,250
227,500
0
0
13,742
14,483
44,464
22,277
1,336,130
1,338,862
2,087,156
722,277
compensation
Non-equity incentive
plan
All other
compensation,
Total compensation
Non-equity incentive plan. The company has approved a special program for financial incentives
management (MIP), which sets the target value of the bonus for CEO, CFO, EVP and SVP, depending
on the value of earnings per share (EPS).
69
Long-term incentives through stock awards and stock options. Fred's pays options to top managers
based on performance (EPS) this year. Call options can be executed by the manager when the same
EPS target is reached in the future.
Table 22. Targets in Fred's, Inc. Compiled by: Annual Proxy Statements (DEF 14A), in Fred's, Inc,
2010-2013.
Year
Index
Target value
Historical value
Weight
2010
EPS
0,86 USD
0,75 USD
100%
2011
EPS
0,86 USD
0,86 USD
100%
2012
EBIT
59,6
millions
2013
EBIT
48.9
millions
USD 51,31
USD 100%
millions
USD 39,08
USD 100%
millions.
Solution of the model and comparison of the results. This case was divided into two periods:
the first period from 2010 to 2011, the second period - 2012 - 2013 years. The results of theoretical
modeling show that after the first period the CEO had to receive a reward of $1,3 million, while in
fact his cash bonus for 2011 was $ 0.23 million, in the whole variable part of compensation for 20102011 is $ 1,345 million. In the second period, due to poor performance, the CEO remuneration should
be equal to 0, as in reality the board of directors considered that the strategy was unsuccessful, and
the CEO does not need to be stimulated financially.
Applying adjustment coefficients, EPS is the only target KPI used for determining cash
incentives for executives in the company in 2011 and EBIT in 2012 and 2013 [Annual Proxy
Statements (DEF 14A), in Fred's, Inc, 2010-2013]. As for the first period, we see that the target EBIT
and historical EBIT are equal, therefore the bonus will have the adjustment coefficient of 1 and is not
changed from $1,3 million. However, in the second period, as EBIT for both 2013 and 2012 is less
than target value, the average coefficient is 0,83. Taking the maximum possible reward from the
model of $0,25 million multiplied by 0,83, we get $0,2 million.
Table 23. Results of modeling for Fred's Inc.
70
0,750
0,750
0,250
0,800
0,200
0,714
c
150
0,500
0,600
0,176
0,588
0,041
1,233
28,767
396,233
Change?
No
250,000 1387,900
425,000
1304,566
30
R
500
0,333
10,000
4.2.2 The compensation system at Dollar Tree Inc.
Dollar Tree Inc. - an American company included in the list of Fortune 500, which owns a
network of inexpensive stores, in which goods cost $ 1 or less. For 2016, the company has about 5100
stores in 48 US states and in Canada, as well as 10 major distribution centers. Dollar Tree is one of
the most growing companies in the retail industry in the US, opening every year from 2011 to 2016.
About 300 stores. In addition, since 1995, the company bought 695 stores from local competitors
through acquisitions. In the grocery portfolio, the store chain has home care products, decorations,
gifts, beauty and health products, various stationery products and fast food products [10-SEC Filings
Dollar Tree Inc.].
Ownership structure. Institutional investors own 67.5% of the company's property, while
mutual investment funds - 31%, and company insiders - 1.5%. Among the twenty largest shareholders
of the company Dollar Tree, only one has a share of property exceeding 5% and equal to 7.2%
[Morningstar]. According to this information, it can be concluded that the property in the company is
sprayed, which means that for the purposes of theoretical modeling, we can accept the board of
directors as a principal from the company.
Board of directors. The principles of corporate governance of the company establish rules for
the board of directors, according to which they must act in the interests of the company and its
shareholders. The size of the board of directors is dictated by the need of the company at a particular
moment in time. Also, according to the norms of public companies, the majority of the board of
directors should consist of independent directors. In addition, the board of directors includes the CEO
and several other executive directors, which ensures the representation of management on the board
of directors [Annual Proxy Statements (DEF 14A), Dollar Tree Inc].
The board of directors has the following committees: Audit Committee, Compensation
Committee, Corporate Governance Committee. According to the charter of the board of directors, the
71
compensation committee establishes remuneration for the CEO, conducts an evaluation of his
activities with the involvement of external consultants.
For 2010, the board is represented by 11 directors, 8 of which are independent (𝑝𝐺 = 0,73).
This parameter will be used as the probability of recognizing a successful strategy in the theoretical
model. In particular, therefore, the CEO, Bob Susser, is not the chairman of the board of directors,
since this would reduce the likelihood of correctly recognizing the nature of the strategy, as the CEO
was able to dictate his terms.
Description of the problem. Due to the high concentration of other low-cost stores of
companies such as Dollar General Corporation and Family Dollar Stores Inc., Dollar Tree is forced
to look for additional ways to expand its business. One such path was the entry into the Canadian
market in 2010, where the company had not previously been introduced. This exit came through the
purchase of the Canadian company Dollar Giant with 86 stores in 4 provinces of the country. By the
end of 2011, the number of stores in Canada increased to 99 [Dollar Tree's Canadian expansion plans
a good sign for Dollarama]. The company's management plans to expand its presence in this market
to 1,000 stores in the next five years.
Profile of CEO. Bob Sasser, 60, has been CEO of the company since 2004. Experience
[Bloomberg]:
2004-2014 - CEO and President, Dollar Tree, Inc.
1999-2004 - COO, Dollar Tree, Inc.
1994-1996 - VP, General Merchandising, Michaels Stores, Inc.
The structure of compensation. The company practices a system known as "Say on Pay," when
the board of directors asks shareholders to approve the remuneration of an executive director. For
2011, the company used the following compensation structure: basic salary (17.6%), cash bonus
(29.5%), long-term capital compensation (52%) and other types (0.9%).
Table 24. Dollar Tree Inc.: the structure of the CEO's compensation in US dollars. Compiled by:
Annual Proxy Statements (DEF 14A), Dollar Tree Inc., 2010-2013.
Type of
2010
2011
2012
2013
971,154
1,080,769
1,301,923
1,410,577
0
0
0
0
Stock awards
2,178,000
3,193,858
13,676,384
3,839,768
Stock Options
0
0
0
0
compensation
Base Salary
Bonus
72
Non-equity incentive
1,948,750
1,813,020
1,847,813
1,909,929
58,236
56,769
63,670
58,089
5,963,640
6,144,416
16,889,790
7,218,363
plan
All other
compensation,
Total compensation
Non-equity incentive plan. In accordance with the Management Incentive Compensation Plan
(MICP), the bonus is paid at the beginning of the next year based on the results of achieving personal
targets and the company's performance. This bonus is expressed as a percentage of wages.
Long-term incentives through stock awards and stock options. The compensation committee
appoints this type of remuneration based on the Omnibus Incentive Plan. Since 2009, the main
element of long-term incentives has been restricted stock units. These shares are paid on the basis of
achieving the target results (operating profit) for the last 3 years, which helps the company to ensure
a stable growth of value for shareholders in the interests of executive directors.
Table 25. Targets in Dollar Tree Inc. Compiled by: Annual Proxy Statements (DEF 14A), in Dollar
Tree Inc., 2010-2013.
Year
Index
Target value
Historical value
Weight
2011
Operating income
727,572 USD
782,1 USD
100%
millions
millions
992,492 USD
993,6 USD
millions
millions
2013
Operating income
100%
Solution of the model and comparison of the results. This case was divided into two periods:
the first period from 2010 to 2011, the second period - 2012 - 2013 years.
Based on the results of theoretical modeling, we can say that the CEO should receive a nonequity compensation in both the first and second periods. So, after the first period, he should get $3
million, and after the second - $0,45 million, while in reality these amounts were equal to $1,8 and
$1,9 million. It is worth noting, that in sum the model gives a result of $3,45 million for 2 periods,
while the historical value is $3,7 million. A significant difference in the second period is due to the
fact that the theoretical game is limited to two periods, and in life the principal continues Stimulate
the CEO for further periods.
73
With the application of adjustment coefficients, we took operating income as a performance
target for both periods. As you can see from the table presented above, the company achieved its
target performance metric with the coefficient of 1,07 in 2011, so that the adjusted incentive become
$3,21 million. As for the second period, the coefficient is 1, therefore the payout remains $0,45
million.
Table 26. Results of modeling for Dollar Tree Inc.
0,545
0,909
0,545
0,917
0,583
0,727
c
0,15
0,364
0,333
0,029
0,706
0,002
0,074
29,926
0,232
Change?
No
0,450
5,66
0,637
3,042
30
R
780
0,082
2,458
4.2.3. The compensation system at Kohl’s Corporation
Kohl's Corporation was founded in 1988 in Wisconsin, USA, and is the largest chain of
department stores in the country. In 1998, the company's shares were included in the S & P 500 index,
and also Kohl's Corporation is on the Fortune 500 list. By 2017, this chain of department stores has
1162 stores in 39 states of the United States, as well as the popular online store of the same name.
Kohl's product portfolio includes the clothing of well-known brands, footwear, accessories, beauty
products and household goods [10-SEC Filings Kohl's Corporation].
Ownership structure. In Kohl's Corporation, 63.7% of shares belong to institutional investors,
36% to mutual investment funds, and only 0.3% to company insiders. Among the 20 largest
shareholders, 4 have a share exceeding 5% with the largest value of 9.28%, which indicates a
dispersed ownership structure in the company. Thus, we can once again use the board of directors as
a principal role.
Board of directors. The board consists of 12 directors, 10 of whom are independent directors
(𝑝𝐺 = 0,83). Members of the board of directors hold positions in the committees on audit, corporate
governance and remuneration. In turn, the duties of the compensation committee include setting up a
remuneration structure and evaluating the CEO's performance in accordance with the key objectives
of personal and corporate performance [Annual Proxy Statements (DEF 14A), Kohl's Corporation].
74
Description of the problem. Kohl's Corporation needed new drivers for growth, as every year
the opportunity to open a new store in a good location is getting harder. So the company planned to
open only 20 small shops (from 55 to 68 thousand square pounds). However, the main strategy for
2011 was the gradual re-planning of all the chain stores in a fast scheme, which reduces construction
and repair work by more than 50% compared to 2007. The main idea was to reduce the warehouse
space to increase the sales area, organize additional fitting rooms, and re-design the store for the new
design of the company. Strategically, the company decided to invest in the renovation of existing
assets to ensure a steady increase in sales and success in the competitive struggle in the future. By
2012, the company has updated 200 of its stores, and plans to complete the management program by
the end of 2013 [10-SEC Filings Kohl's Corporation]. The first reports say that this strategy has made
it possible to achieve significant sales growth in the cosmetic departments [Kohl's Gets a Beauty
Boost from the Store Remodels Dollarama].
Profile of CEO. Kevin Mansell, 61, CEO of Kohl's Corporation since 2008. Experience
[Bloomberg]:
2008-present - CEO, Kohl's Corporation
1999-present - President, Kohl's Corporation
1982-1999 - Various managerial positions, Kohl's Corporation
The structure of compensation. In 2011, the remuneration structure of Kevin Mansell looked
as follows: 14.2% - basic wage, 59.5% - long-term incentives, 22.7% - short-term monetary
incentives, 3.6% - another compensation.
Table 27. The compensation structure of the CEO in Kohl's Corporation. Compiled by: Annual Proxy
Statements (DEF 14A), at Kohl's Corporation, 2011-2013.
Type of compensation
2011
2012
2013
Base Salary
Bonus
1,339,300
1,329,300
1,339,300
0
0
0
Stock awards
2,799,984
2,800,011
6,000,119
Stock Options
2,806,198
2,800,003
0
Non-equity incentive plan
2,145,000
531,720
535,720
371,261
355,758
303,165
9,422,443
7,816,792
8,178,304
All other compensation,
Total compensation
75
Non-equity incentive plan. The main idea of short-term cash reward in the company is to
stimulate the CEO to achieve the set performance targets. In accordance with the Annual Incentive
Plan for 2011, the net profit and the competitor selection index were chosen as indicators, which
should be lower than Kohl's effectiveness for obtaining the Annual Proxy Statements (DEF 14A)
bonus, Kohl's Corporation]
Long-term incentives through stock awards and stock options. Determination of annual longterm incentives occurs through the same targets as in the case of short-term bonuses, however, they
are considered over a longer time period of 3 years [Annual Proxy Statements (DEF 14A), Kohl's
Corporation].
Table 28. Targets in Kohl's Corporation. Compiled by: Annual Proxy Statements (DEF 14A), at
Kohl's Corporation, 2011-2013.
Year
Index
Target value
Historical value
Weight
2011
Net profit
1,050 USD
1,196 USD
50%
Billions
Billions
2011
ROI
17,92%
18,65%
30%
2011
The company is ahead
N/A
N/A
20%
1,045 USD
0,889 USD
50%
Billions
Billions
of the competitors'
performance index
2013
Net profit
2013
ROI
17,22%
15,5%
30%
2013
The company is ahead
N/A
N/A
20%
of the competitors'
performance index
Solution of the model and comparison of the results. The period of the case analysis was
divided into two periods: 2011 and 2012-2013. All parameters of the model have been estimated in
accordance with the procedure dismantled in Chapter 2.
Based on the results of the game-theoretical modeling, we received that due to the
implementation of a successful strategy in the first period (2011), in which the CEO surpassed the
established targets for net profit and return on investment, Kevin Mansell was to receive a reward of
$1,75 million. whereas in real life it short-term stimulating bonus was $2,145 million in the second
76
period due to lack of effectiveness and completeness of the game, the model assumes a fee 0, whereas
in reality principal left the agent and continued to encourage a high level of effort for a further period
of $0,535 million.
With the application of adjustment coefficient method for this case, we can calculate weighted
average coefficients for both periods given the data for performance metrics. Therefore, for the first
period the weighted average coefficient (without «The company is ahead of the competitors'
performance index») is 1,1 and for the second period is 0,87, while the adjusted payouts are $1,9
million and $0,84 million respectively.
Table 29. Results of modeling for Kohl's Corporation
0,750
0,917
0,750
0,923
0,769
0,833
c
0,15
0,167
0,154
0,040
0,800
0,003
0,096
29,904
0,203
Change?
No
0,975
4,06
1,219
1,750
30
R
1100
0,153
4,588
4.2.4. The compensation system at Barnes & Noble, Inc.
Barnes & Noble, Inc. is included in the Fortune 500 list and is the largest book sales network
in the US and the leading player in the market for sales of information, electronic media products and
educational benefits in the country. As of May 2017, the company serves 1,361 bookstores in 5 US
states, including 700 stores on university campuses, and also sells through one of the largest themed
online stores in the country. In addition, the company owns the publishing company Sterling
Publishing Co., Inc., a division of NOOK, which develops e-books, sells and adapts content, and
develops reading software for mobile and fixed platforms [10-SEC Filings Barnes & Noble, Inc].
Ownership structure. Institutional investors own shares of the company in the amount of 62%,
mutual investment funds - 26%, company insiders - 12%. Only 3 of the 20 largest shareholders hold
a stake with a stake of more than 5%, with a maximum value of 8,19%, from which it can be
concluded that the ownership structure is dispersed in the company [Morningstar]. This means that,
similar to other examples of theoretical modeling, we will take the board of directors of the company
as a principal.
Board of Directors. The board of directors includes 10 directors, 8 of whom are independent
directors (𝑝𝐺 = 0,8) [Annual Proxy Statements (DEF 14A), at Barnes & Noble, Inc.], excluding the
77
company's CEO and chairman of the board of directors. Traditionally, three profile committees have
been singled out in this corporate governance structure: audit committee, competition committee,
corporate governance.
Description of the problem. As you know, sales of print media are shrinking yearly due to the
appearance of electronic reading formats. In such circumstances, Barnes & Noble, Inc. were forced
to change their expansion strategy to cut more than 10 stores annually from 2009, and focus on their
e-book business as publications and devices (NOOK). In 2012, Barnes & Noble entered into an
agreement with Microsoft Corporation, in which it sells a stake in NOOK, affiliated with the
technology giant, for the right to create official software for reading. Under this agreement, NOOK
will receive $ 60 million annually from Microsoft. After a number of other deals, it was safe to say
that Barnes & Noble, Inc. focused on e-commerce with printed materials and device development,
and reading software [10-SEC Filings Barnes & Noble, Inc].
New strategy in 2014. The new CEO came to the company when the NOOK division showed
a serious drop in sales. It was decided to divide the printed and electronic business into different
companies [Barnes & Noble Heads Back to the Future]. At the same time, management Barnes &
Noble believed that it is possible to restore sales of printed books due to large marketing efforts and
new ideas in merchandising. This year may become decisive in the further development of the
company.
Profile of CEO. William L. Lynch, J, 42, CEO of the company since 2009. Experience
[Bloomberg]:
2009-2013 - CEO, Barnes & Noble, Inc.
2004-2008 - CEO, Gifts.com (a division of IAC Inc.)
Michael Huseby, 58 years old. Experience:
2013 - present time - CEO, Barnes & Noble, Inc.
2004-2011 - EVP and CFO, Cablevision Systems Corporation
1999-2002 - EVP, AT & T Broadband
The structure of compensation. In the structure of the CEO's remuneration in 2011, the base
salary is 12%, the short-term incentive package 4.5%, the long-term incentive package 83.2%, the
other compensation 0.3%.
Table 30. CEO remuneration structure in Barnes & Noble, Inc. In US dollars. Compiled by: Annual
Proxy Statements (DEF 14A), at Barnes & Noble, Inc., 2012-2014.
Type of compensation
2012
2013
2014
78
Base Salary
Bonus
1,142,308
850,000
997,208
450,000
1,275,000
0
Stock awards
3,098,340
500,000
6,637,500
Stock Options
5,285,000
0
0
0
0
2,604,000
32,750
35,783
41,025
10,008,398
2,660,883
10,279,733
Non-equity incentive plan
All other compensation,
Total compensation
Non-equity incentive plan. The compensation committee appoints bonuses to the CEO
depending on the achievement of EBITDA targets for the company as a whole, and separately for
business lines such as Retail, Digital, College. In addition to the incentive bonus, the company
sometimes pays a so-called trust bonus, which managers can be encouraged, for example,
successfully implementing a successful transaction.
Table 31. Targets in Barnes & Noble, Inc. Compiled by: Annual Proxy Statements (DEF 14A), at
Barnes & Noble, Inc., 2012-2014.
Year
Index
Target value
Historical value
Weight
2012
Consolidated
242,3 млн.
164,4 млн. долл.
100%
EBITDA
долл.
Consolidated
148 млн. долл.
251 млн. долл.
100%
2014
EBITDA
Solution of the model and comparison of the results. The period of analysis of the case was
divided into two periods: 2012 and 2013-2014. All parameters of the model have been estimated in
accordance with the procedure presented in Chapter 2.
Based on the results of game-theoretic modeling, we received that, as a result of the
unsuccessful implementation of the strategy in the first period, the CEO should have received a shortterm incentive reward equal to 0. In fact, the board of directors was also not impressed with the
performance for 2012 and did not reward William L. Lynch. Further to the end of the second period,
the company's profitability situation improved and, as a result of the overfulfilment of the plan, the
new CEO, Michael Huseby, was to receive a compensation of $2,848 million, while the board of
directors was more cautious and rewarded the CEO of $ 2.604 million.
79
Applying adjustment coefficients approach and consolidated EBITDA as a main performance
metric, we got the coefficient be equal to 0,68 and 1,17 (1,17 is a limit set by the compensation
comittee) respectively, while the final adjusted payouts are $0,1 million and $3,33 million.
Table 32. Simulation results for Barnes & Noble, Inc
0,625
0,625
0,000
0,889
0,667
0,800
c
0,45
0,625
0,222
0,111
0,711
0,014
0,411
29,589
2,025
4,56
2,848
0,114
0,712
Change?
Yes
30
R
160
0,302
9,060
4.2.5. The compensation structure at Lowe´s Companies, Inc.
Lowe's Companies is an American public company (since 1961), which is on the Fortune 500
list (# 43) and is the world's second-largest retailer of materials for construction and repair. As of
January 2017, the company had 1,749 stores in the US, 37 in Canada and 10 in Mexico, its staff
employs more than 175,000 employees. The main competitor of Lowe's and part-time world leader
in the industry is the American Home Depot [10-SEC Filings Barnes & Noble, Inc].
Ownership structure. Institutional investors own 66.5% of the company's shares, mutual
investment funds - 33.3%, company insiders - 0.2%. Of the 20 largest shareholders of Lowe's
Companies, three hold stakes in excess of 5%, and the largest shareholder holds a 6.08% stake
[Morningstar]. In general, we can draw a preliminary conclusion about the dispersed nature of
property in the company. Accordingly, we will use the board of directors as a principal in the model
of theoretical modeling of the amount of material incentives for the CEO.
Board of Directors. The board of directors includes 11 people who are on such committees as
an audit committee, a remuneration committee, a committee on corporate governance. All members
of the board, with the exception of the company's CEO, are independent directors, of whom 10 out
of 11 are on the board of directors (𝑝𝐺 = 0,91).
The compensation committee evaluates the activities and contributions to the overall
performance of the company's executive directors, recommendations to the general board of directors
on changes in the structure of fees, monitoring remuneration trends in other companies, and by
recruiting external consultants to assist in the previously listed responsibilities [Annual Proxy
Statements (DEF 14A), Lowe's Companies].
80
Description of the problem. After being appointing Robert Niblock as CEO in 2005, the
company pursued an aggressive expansion strategy, increasing the number of chain stores from 1,300
in 2007 to 1,700 in 2011. And this strategy showed itself successful before the crisis in 2008-2009,
which had a particularly strong impact on the real estate market. However, despite the obvious signals
of declining demand, Lowe's Companies continued aggressive expansion, which led to a record fall
in margins in 2009-2011. In this situation, investors decided to invest in a more profitable Home
Depot, which in time adapted to the new market conditions.
New strategy since 2011. The company almost ceased to implement capital expenditures for
the construction of new stores, and for the first time in 8 years the number of stores decreased
compared to last year. Lowe's Companies have changed their strategy from increasing sales and
places to the development of e-commerce. For example, the mobile application MyLowes, which
allows you to order goods and services via the Internet [Why Lowe's Is One For The Future], has
become very popular.
Profile of CEO. Robert Niblock, 49, has been CEO of Lowe's Companies since 2005.
Experience [Bloomberg]:
2005-present - CEO and President, Lowe's Companies
2000-2003 - CFO, Lowe's Companies
1999-2000 - Senior Vice President of Finance, Lowe's Companies
1997-1998 - Vice President & Treasurer, Lowe's Companies
The compensation structure. Lowe's Companies apply the practice of Say-on-Pay for
additional approval of shareholder compensation programs. What distinguishes the company from its
competitors is that the remuneration committee set a fixed ratio in the remuneration structure of the
CEO in 2010: the base salary is 10%, the target cash bonus is 20%, the target long-term incentive is
70%. According to the committee, it is this structure that allows maximally stimulating the CEO to
increase value for shareholders through their own performance.
Also, the company attracts consultants from Farient Advisors so that they annually assess how
much the Performance-Adjusted Compensation (PAC): 1) is adequate in comparison with the growth
of the company's revenue and competitors; 2) is sensitive in the total return of shareholders. These
indicators are estimated on the basis of the last three years [Annual Proxy Statements (DEF 14A),
Lowe's Companies].
Table 33. Structure of CEO compensation in Lowe's Companies in US dollars. Compiled by: Annual
Proxy Statements (DEF 14A), in Lowe's Companies, 2009-2012.
81
Type of compensation
2009
2010
2011
2012
Base Salary
Bonus
1,100,000
1,100,000
1,155,000
1,185,000
0
0
0
0
Stock awards
3,864,960
4,340,380
5,599,700
5,343,893
Stock Options
3,658,200
4,189,230
2,232,749
3,740,675
Non-equity incentive
2,839,683
2,225,036
1,494,732
1,664,996
204,515
195,052
160,562
201,878
11,667,358
12,049,698
11,642,743
12,136,442
plan
All other
compensation,
Total compensation
Non-equity incentive plan. In the last few years (in 2010 and onwards), the company used EBIT (75%)
and revenue (25%) as metrics to reward the CEO of the company with a cash bonus. The
Remuneration Committee believes that these indicators are an effective performance evaluation, as
they assess the overall profitability of the company and encourage management to both revenue
growth and cost optimization. In 2011, the committee added three additional strategic goals, set at the
beginning of the year, as an additional metric. So in 2011 the strategic goals were: the hobby of the
share of Internet sales in the revenue structure, the increase in the productivity of operational
personnel, effective leadership.
Table 34. Targets in Lowe's Companies. Compiled by: Annual Proxy Statements (DEF 14A), in
Lowe's Companies, 2009-2012.
Year
2010
Index
EBIT
Target value
3,487
Historical value
Weight
USD 3,560 USD Billions
75%
USD 48,815 USD Billions
25%
USD 3,630 USD Billions
60%
USD 50,208 USD Billions
20%
Billions
2010
Revenue
49,493
Billions
2011
EBIT
3,559
Billions
2011
Revenue
50,521
Billions
2011
Strategic goals
N/A
3/3
successfully
20%
achieved
82
Solution of the model and comparison of the results. As a first period, we accept the period of
analysis of the first strategy - 2009-2010, and as the second period - 2011. All parameters were
evaluated similarly to other cases and in accordance with the model specifications given.
Based on the results of the theoretical simulation, we can see that the material compensation
of Robert Niblock after the first period should be equal to $ 2,181 million, while in real life it was
equal to $ 2,225 million. Then, the company changed its strategy, which, apparently from
performance metrics, turned out to be successful, although the model did not assume a change of
strategy. In any case, the CEO's cash bonus in 2011 was $ 1,5 million, while the model gives a result
of $ 0,525 million. Thus, the model showed that in a situation where a potentially successful strategy
proved itself in the first period, the board Directors could take into account the reputational risks of
the CEO and reduce his real financial reward. However, the company changed its strategy in 2011,
and the reputational risks of the CEO became less, respectively.
With the application of adjustment coefficient method for this case, we can calculate weighted
average coefficients for both periods given the data for performance metrics. Therefore, for the first
period the weighted average coefficient is 1,01 and for the second period is 1,01, while the adjusted
payouts are $2,2 million and $0,53 million.
Table 35. Results of modeling for Lowe's Companies
0,600
0,800
0,600
0,857
0,571
0,909
c
0,15
0,200
0,286
0,027
0,885
0,004
0,116
29,884
0,198
Change?
No
0,525
6,59
0,593
2,181
30
R
3500
0,110
3,298
4.3. Analysis of the results
Based on the results of our modeling, as well as historical data obtained, a comparative table
was compiled, as well as the graphs presented below:
Table 36. Summary table on the results of modeling
83
Company
𝑞0
Fred’s, Inc.
Dollar Tree, Inc.
Kohl’s Corporation
Barnes & Noble, Inc.
Lowe's Companies, Inc.
Yahoo, Inc
Blackbaud, Inc.
Blucora, Inc.
Linkedin Corporation
CA Technologies, Inc.
0,75
0,545
0,75
0,625
0,6
0,67
0,72
0,5
0,875
0,8
Change of strategy
Fact
No
No
No
Yes
No
Yes
Yes
No
No
Yes
Model
No
No
No
Yes
Yes
Yes
Yes
No
No
Yes
Sum of compensation
Compensation after
Compensation after
for two periods, million
1st period, million $ 2nd period, million $
$
Fact
Model
Fact
Model
Fact
Model
1,345
1,300
0,000
0,000
1,345
1,300
1,800
3,000
1,900
0,450
3,700
3,450
2,145
1,750
0,535
0,000
2,680
1,750
0,000
0,000
2,604
2,848
2,604
2,848
2,225
2,181
1,500
0,525
3,725
2,706
1,500
0,000
1,120
1,490
2,620
1,490
0,437
0,000
0,870
1,370
1,307
1,370
0,540
0,000
0,450
0,216
0,990
0,216
0,507
0,000
0,636
0,450
1,143
0,450
1,500
0,000
1,764
1,790
3,264
1,790
Compensation for the second period
3,000
2,500
2,000
1,500
Compensation after 2nd period,
million $ Fact
1,000
0,500
Compensation after 2nd period,
million $ Model
0,000
Figure 5. Compensation comparison for the 2nd period
Sum of compensations for two periods
4,000
3,500
3,000
2,500
2,000
1,500
1,000
0,500
0,000
Sum of compensation for two
periods, million $ Fact
Sum of compensation for two
periods, million $ Model
84
Figure 6. Compensation comparison for the sum of two periods
Figure 7. Comparison between industries on % variance of modeled value to actual
As we see, in general, for the sum of two periods, the model shows a good result by the
example of five companies (Fred's, Dollar Tree, Barnes & Noble, Lowe's Corporation, Blackbaud),
but has some deviations in certain periods, and, in general, better Works for the retail industry.
In addition, it should be noted that the model works best if the strategy and CEO change after
the first period, which can be explained by the fact that the new model assumes no reputation risks
for the new manager, and the historical effects in this case practically do not affect the formation of
the amount of compensation.
The general trend among all the examples considered is that, based on the results of theoretical
modeling in eight examples, companies overpaid the CEO in terms of incentive compensation, which
is especially noticeable in the IT industry.
Of course, companies could save money in case of the CEO's dismissal, but, most likely, such
a move would seriously damage the company's reputation in the labor market for top management.
Also in real practice the company introduces more than one strategy at the same time, and business
is very often diversified, so the board of directors decides to appoint a CEO award based on a wider
range of factors than those considered by us.
In addition, the fact that the model considers the finished game for 2 periods determines the
distribution of high reputational risks for these periods. In real practice, strategies are introduced over
a longer period and it is worthwhile to consider several more periods in order to more accurately
assess the probability of outcomes and more accurately predict the winnings for the players and
distribute the reputation risks more evenly. Also, because of the limited play in two periods, the
85
reputational stimulation of the second period is significantly less than the first, but, in fact, it is
important for the CEO of a lonely person to show a high result both in the first and second period in
order to receive a greater reward.
In order for the theoretical model to be more accurate in cases of a low result in the company's
current operations, it was necessary to introduce and test additional parameter that determines the
degree of payment of the monetary bonus depending on the degree of achievement of the targets
individually for each company. As we described earlier in Chapters 2 and 3, in almost all public
companies, there is a practice of partial bonus payment (less than 100%) even if the target
performance indicators are not reached, although the model assumes that the manager does not
receive incentive compensation at a low result in the company's current activity. To account for that
fact we and to improve our modeling accuracy introduced adjustment. The results are presented
below:
Table 37. Summary table on the results of modeling with adjustment coefficients
Company
𝑞0
Fred’s, Inc.
Dollar Tree, Inc.
Kohl’s Corporation
Barnes & Noble, Inc.
Lowe's Companies, Inc.
Yahoo, Inc
Blackbaud, Inc.
Blucora, Inc.
Linkedin Corporation
CA Technologies, Inc.
0,75
0,545
0,75
0,625
0,6
0,67
0,72
0,5
0,875
0,8
Change of strategy
Fact
No
No
No
Yes
No
Yes
Yes
No
No
Yes
Model
No
No
No
Yes
Yes
Yes
Yes
No
No
Yes
Sum of compensation
Compensation after
Compensation after
for two periods, million
1st period, million $ 2nd period, million $
$
Fact
Model
Fact
Model
Fact
Model
1,345
1,300
0,000
0,200
1,345
1,500
1,800
3,210
1,900
0,450
3,700
3,660
2,145
1,900
0,535
0,840
2,680
2,740
0,000
0,100
2,604
3,330
2,604
3,430
2,225
2,200
1,500
0,530
3,725
2,730
1,500
1,900
1,120
1,788
2,620
3,688
0,437
0,220
0,870
1,410
1,307
1,630
0,540
0,337
0,450
0,325
0,990
0,662
0,507
0,540
0,636
0,535
1,143
1,075
1,500
1,330
1,764
1,790
3,264
3,120
86
Compensation for the second period (with adj.)
3,500
3,000
2,500
2,000
1,500
1,000
0,500
0,000
Compensation after 2nd
period, million $ Fact
Compensation after 2nd
period, million $ Model
Figure 8. Compensation comparison for the 2nd period with adjustments
Sum of compensations for two periods (with adj.)
4,000
3,500
3,000
2,500
2,000
1,500
1,000
0,500
0,000
Sum of compensation for two
periods, million $ Fact
Sum of compensation for two
periods, million $ Model
Figure 9. Compensation comparison for the sum of two periods with adjustments
87
Figure 10. Comparison between industries on % variance of modeled value to actual with adjustments
This methodology slightly improves overall accuracy of modeling for the suggested
methodology, especially concerning IT-industry, where there were several cases when CEO got
nothing in the first period according to basic model. Some extremes are also appeared with adjustment
coefficients because not always in reality the board of directors is willing to pay a manager the whole
proportional bonus after his achievements. As we see there three more companies in the adjusted
scenario which should have paid their managers more according to modeling results.
Also, the chart below helps to emphasize that real practice adjustment in all of the cases lead
to the increase of overall incentive payments as in real practice very rarely companies pay nothing to
top executives.
88
Figure 11. Adjusted results % variance to non-adjusted results
Note that the coefficients, as well as the possible more detailed scaling of targets, are
established by each company and are subject to adjustment. As a result, such a modification of the
considered model as we suggested will allow to adapt the model to modern incentive reward practices,
considered in Chapter 4 of this work, and to increase the practical applicability and accuracy of the
model.
4.4. Conclusion
In this chapter of my research work, we presented an analysis of 10 examples of modeling of
the incentive part of compensation for companies from the retail industry and the IT industry in order
to check whether the model considered in Chapter 2 can be used as a real management tool for
evaluating the range of incentive awards for the CEO.
Using the example of these 10 companies, we demonstrated the applicability of the theoretical
model as a tool for quantifying the incentive reward to motivate a high level of CEO efforts during
the implementation of the strategy in cases of: failure of strategy and CEO change, strategy success,
evaluation of both short- and long-term incentive packages, One, and several targets, evaluation of
the reputation of the CEO for work experience in other companies or separately in the company in
question.
As a result, we can conclude that the theoretical model considered, with some amendments,
can be used as an auxiliary and recommendatory tool for public companies headquartered in the
United States in terms of material incentives for general directors. In addition to companies,
researchers like me may be interested in such a technique. And, finally, companies engaged in
business consulting services can expand their tools by using the method of forming the variable part
89
of remuneration for CEOs of public companies headquartered in the United States. If the decision
making process, regulation, transparency of executive compensation in any country can be compared
to the US, the model could be applied to international public companies from this country with some
adjustments. In terms of our research, it was only possible to show the applicability of the modeled
on the US headquartered companies due to access to all of the data for model specification.
90
Conclusions
In this Master thesis the following tasks were accomplished:
Based on the analysis of scientific literature on the topic of the CEO compensation, the
requirements to the mechanism of forming the variable part were justified;
The practice of decision making and regulation on forming the size of the variable part of
compensation of CEOs on examples of international public companies from the retail and IT
industries was analyzed;
The model of forming the variable part of CEO compensation was selected and improved in
accordance with the requirements;
The chosen model introduced reputation as an important factor of influence on manager’s
efforts application;
A comparative analysis of the results of theoretical modeling and real practice of forming the
variable part of CEO compensation on examples of international public companies was made
and applicability of the mechanism was proven;
The suggested mechanism can be used as a tool by board of directors in public companies or
researchers with possibilities for individual adjustments.
As a result, the goal of this Master thesis was completely achieved, namely, based on the
analysis of existing theoretical models and approaches to determining the size of the variable part of
material compensation for CEOs, the methodology for determining the amount of such remuneration
was improved and the possibility of its practical application on examples of public companies in the
U.S.
I would like point out that the theoretical model presented in the work uses reputation as one
of the parameters that influence what level of effort the manager can use in the future. So, the CEO
takes into account not only monetary compensation, but also reputational risks in case of low
performance of the company's current activity. This approach is very relevant in the light of modern
research in the field of accounting and measurement of talent manager. Due to the fact that reputation
is the determining factor for successful execution of the strategy, the manager will try to maintain his
reputation with all his will.
In addition, the theoretical model explains the process of managerial entrenchment when he
remains in the company even after achieving a low result in the company's current activity in the first
period, because changing the strategy and hiring a new CEO is a costlier option for the owners.
91
The developed methodology was used in the analysis of 5 cases on examples of companies from the
retail industry and 5 cases on examples of companies from the IT industry.
In 10 cases, we demonstrated the applicability of the model as a tool for assessing the variable
part of the CEO's remuneration in order to stimulate high efforts in implementing the strategy in
several cases:
Strategic disruption and change of the CEO;
Short-term non-equity incentive plan evaluation;
A performance indicator consisting of a single indicator;
A performance indicator, consisting of several indicators;
The CEO working in several companies before the current tenure;
The CEO working in the current company in different positions
The resulting estimates, as a rule, correspond to the actual values of compensation in the
companies. The developed mechanism can be applied to other state-owned US companies in the retail
and information technology industries and, with special changes and inspections, in other
environments.
The system of corporate governance in Russia differs significantly and partially lags behind
in the development of institutions from the corporate governance system in U.S. public companies.
However, with the development of relevant institutions, especially the institute of independent
directors, it is possible to develop a similar methodology for the formation of variable part of the
remuneration of CEOs of Russian public companies.
Limitations and further research
The research was conducted on the example of U.S public companies in retail and IT
industries. However, there are more countries with publicly traded companies and more industries
where such companies are represented. But given the number of industries in U.S. alone, it is hardly
possible to cover them all in one paper. Moreover, as we explained earlier only data for U.S.
headquartered companies was enough for us to test the applicability of the mechanism. Second, we
could not test the chosen mechanism on every company from the sample. Third, part of the companies
has multiple strategies implemented with different time frames which makes it a more complicated
task to evaluate them all. Additionally, only non-equity incentive plans were modeled using the
mechanism, thus the results of incentive plans improvement are limited to only one of the part from
a compensation structure.
92
There is a room for improvement for this research by expanding the analysis into more
industries in U.S. and possibly other countries with the similar systems of corporate governance. With
more results it would be possible to conclude to exact applicability of the mechanism for certain
environments. Also, this research can be also extended to improving the mechanism for other
compensation components.
93
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61. SEC Approves NYSE and NASDAQ Proposals Relating to Director Independence. 2003.
Findlaw. Accessed 10.06.17. http://corporate.findlaw.com/finance/sec-approves-nyseand-nasdaq-proposals-relating-to-director.html
62. Section 162(m): Limit on Compensation, Practical Law Company. Skadden. Accessed
10.06.17.http://www.skadden.com/sites/default/files/publications/Publications2574_0.pd
f
63. Securities Exchange Act of 1934. 2017. U.S. Securities and Exchange Commission.
Accessed 10.06.17. https://www.sec.gov/about/laws/sea34.pdf
64. Taxes
and
executive
compensation.
2012.
Economic
Policy
Institute.
http://www.epi.org/publication/taxes-executive-compensation/
65. The Microsoft-Yahoo Search Deal, In Simple Terms. 2009. Search Engine Land.
Accessed
10.06.17.
http://searchengineland.com/microsoft-yahoo-search-deal-
simplified-23299
66. Why Lowe's Is One
For
The Future.
2012.
Forbes.
Accessed 10.06.17.
http://www.forbes.com/sites/greatspeculations/2012/11/16/why-lowes-is-one-for-thefuture/
67. Yahoo Finance. Accessed 10.06.17. http://finance.yahoo.com/
98
68. Yanauer, B., Zenkevich N. and Syrunina, E. 2016. CEO incentive plans improvement in
the U.S. public companies on the base of game theoretical modeling. Contributions to
Game Theory and Management 9: 287–327.
69. Yermack, D. 2006. Flights of fancy: Corporate jets, CEO perquisites, and inferior
shareholder returns. Journal of Financial Economics 80 (1): 211-242.
99
Appendices
Appendix 1. Modified game tree
Figure 14. The modified game tree. Source: [Casamatta, Guembel, 2007].
100
Appendix 2. Solution of the modified game
Figure 15. The modified game solution. Source: [Casamatta, Guembel, 2007].
101
Appendix 3. Sensitivity analysis on the example of CA Technologies Inc.
Table 38. Sensitivity analysis to change of q0
0,5
0,6
0,7
0,8
0,9
0,01786
0,02655
0,0407
0,0678
0,14063
0,89286
0,88496
0,87209
0,84746
0,78125
0,08205
0,12291
0,19078
0,32566
0,72343
31,588
31,5471
31,4792
31,3443
30,9466
Change?
Yes
Yes
Yes
Yes
Yes
Payoff
1787,351
1923,268
2059,178
2195,07
2235,046
Change?
Yes
Yes
Yes
Yes
Yes
Payoff
1634,1716
1750,8951
2072,3639
2195,07
2308,2267
38,35
3,068 6,65811
31,9583 2,55667 9,62761
27,3929 2,19143 12,6394
23,9688 1,9175 15,6943
21,3056 1,70444 18,7934
Change?
Yes
Yes
Yes
Yes
Yes
Payoff
1682,116
1825,77
1969,403
2113,015
2256,606
3,62315
3,88646
4,225
4,67639
5,30833
6,25625
7,83611
10,9958
20,475
Change?
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Payoff
1986,535
1986,82
1987,073
1987,274
1987,385
2059,332
2105,23
2150,271
2191,856
2,409674 -30,071 84,9333 1,69867 73,4874
3,482042 -30,03 57,1278 1,71383 48,5766
5,104704 -29,963 37,2667 1,73911 30,7887
7,847434 -29,828 22,3708 1,78967 17,4597
13,48115 -29,43 10,7852 1,94133 7,13462
Table 39. Sensitivity analysis to change of
0,5
0,6
0,7
0,8
0,9
0,1
0,2
0,3
0,4
0,5
0,15385
0,12698
0,09836
0,0678
0,03509
0,76923
0,79365
0,81967
0,84746
0,87719
0,80177
0,64468
0,48598
0,32566
0,16367
30,86823
31,02532
31,18402
31,34434
31,50633
14,3026
12,5782
10,4735
7,84743
4,47859
-29,3516
-29,5087
-29,6673
-29,8277
-29,9897
9,85833 1,97167 6,802753
11,9438 1,911 8,567812
15,4194 1,85033 11,52431
22,3708 1,78967 17,45974
43,225
1,729 35,3116
Table 40. Sensitivity analysis to change of
0,5
0,6
0,7
0,8
0,9
0,5
0,6
0,7
0,8
0,9
w_hh
1,11123 30,5588 3,72588
2,6
-27,959
0,89527 30,7747 4,36828 2,166667 -28,608
0,67623 30,9938 5,27833 1,857143 -29,137
0,45405 31,2159 6,66737 1,625
-29,591
0,22866 31,4413 9,04857 1,444444 -29,997
Table 41. Sensitivity analysis to change of
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
0,4186
0,39024
0,35897
0,32432
0,28571
0,24242
0,19355
0,13793
0,07407
0,05814
0,12195
0,19231
0,27027
0,35714
0,45455
0,56452
0,68966
0,83333
2,95368
2,65298
2,34593
2,0323
1,71189
1,38448
1,04983
0,70771
0,35785
28,7163
29,017
29,3241
29,6377
29,9581
30,2855
30,6202
30,9623
31,3121
13,95252
13,80171
13,61254
13,36824
13,04059
12,57816
11,87625
10,68386
8,210741
w_hh
-27,2
-27,5
-27,807
-28,121
-28,441
-28,769
-29,103
-29,446
-29,795
26,0867
12,4367
7,88667
5,61167
4,24667
3,33667
2,68667
2,19917
1,82
1,76572
1,94846
2,19478
2,53688
3,03277
3,7985
5,10486
7,76432
15,8393
102
Appendix 4. Performance histories of CEOs for case analysis
Table 42. Performance history of CEO in Yahoo Inc. Source: [Thomas Reuters, Bloomberg].
Carol Bartz, CEO, Autodesk Inc.
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
1995
534167
0,174995381
129027
0,201245682
24,15
5,2
1996
1997
1998
1999
2000
496693 617126 740167 820182 936324
-0,07015409 0,24247 0,199377 0,108104 0,141605
64555 103442 136822
35511 138780
-0,499678362 0,602386 0,322693 -0,74046 2,908085
13
16,76
18,49
4,33
14,82
6,95
25,7
29
14,13
7,84
2001
2002
2003
2004
2005
2006
947491 824945 951643 1233767 1523200 1839800
0,011926427 -0,12934 0,153584 0,29646 0,234593 0,207852
131804
53849 109420 261573 381800 391300
-0,050266609 -0,59145 1,031978 1,390541 0,459631 0,024882
13,91
6,53
11,5
21,2
25,07
21,27
7,75
10,2
9,9
9,8
11,75
15,07
Table 43. Performance history of CEO in Yahoo Inc. Source: [Thomas Reuters, Bloomberg].
Marissa Mayer, Google Vice President of Search Products and User Experience
2005
2006
2007
2008
2009
2010
Net Sales, bln
6138560
10604917 16593986 21795550 23325858 29118000
Growth rate, %
73%
56%
31%
7%
25%
Operating Income, bln
2107278
3590796 5084400 6631969 7987481 10178000
Growth rate, %
0,703997289 0,415953 0,304376 0,204391 0,274244
Operating margin, %
34,33
33,86
30,64
30,43
34,24
34,95
Indusrty average, %
9,9
10,2
10,3
11,3
10,8
11
2011
37862000
30%
12199000
0,198565534
32,22
15,5
Table 44. Performance history of CEO in Blackbaud Inc. Source: [Thomas Reuters, Bloomberg].
Mark Chardon, CEO, Blackbaud Inc.
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2005
166296
0,198572922
45724
1,115676476
27,5
11,75
2006
2007
2008
2009
2010
191959 257038 302495 309338 327094
0,15432121 0,339026 0,176849 0,022622
0,0574
47709
52407
47401
45792
45904
0,04341265 0,098472 -0,09552 -0,03394 0,002446
24,85
20,39
15,67
14,8
14,03
15,07
19,8
22,4
20,16
19,5
2011
370868
0,133826973
53728
0,170442663
14,49
20,01
Table 45. Performance history of CEO in Blackbaud Inc. Source: [Thomas Reuters, Bloomberg].
Mike Gianoni, President, fiserv Investment Services
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2007
3922000
-0,136912484
758000
0,018432554
19,33
19,8
Group President, Financial Institutions Group
2008
2009
2010
2011
2012
2013
4739000 4077000 4133000 4337000 4482000
4814000
0,208312086 -0,13969 0,013736 0,049359 0,033433 0,074074074
927000 946000 1007000 1031000 1056000
1061000
0,222955145 0,020496 0,064482 0,023833 0,024248 0,004734848
19,56
23,2
24,36
23,77
23,56
22,04
22,4
20,16
19,5
20,01
19,6
19,96
Table 46. Performance history of CEO in Blucora Inc. Source: [Thomas Reuters, Bloomberg].
103
William Rukelshaus, Predisdent и CEO, Blucora Inc.
2007
140537
-0,621945085
-75285
6,041904406
-53,57
10,3
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2008
2009
2010
2011
156727 207646 214343 238791
0,115200979 0,32489 0,032252 0,11406
5512
9616
5800
21479
-1,073215116 0,744557 -0,39684 2,703276
3,52
4,63
2,35
9,39
11,3
10,8
11
15,5
Table 47. Performance history of CEO in Linkedin Corporation.
Bloomberg].
Source: [Thomas Reuters,
Jeffrey Weiner, EVP, Yahoo!
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2001
717422
-0,353777502
-96049
-1,299586719
-13,39
14,8
2002
2003
2004
2005
2006
953067 1625097 3574517 5257668 6425679
0,328460794 0,705124 1,199571 0,470875 0,222154
88188 295666 688581 1107725 940966
-1,918156358 2,352678 1,328915 0,608707 -0,15054
9,25
18,19
19,26
21,07
14,64
9,9
10,2
14,96
14,2
7,65
2007
2008
6969274 7208502
0,084597285 0,034326
695413 607354
-0,260958419 -0,12663
9,98
8,43
10,3
11,3
Table 48. Performance history of CEO in CA Technologies. Source: [Thomas Reuters, Bloomberg].
William McCracken, EVP, CA Technologies
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2005
3530000
0,077533578
374000
0,32155477
10,59
11,75
2006
2007
2008
2009
3796000 3943000 4277000 4271000
0,075354108 0,038725 0,084707 -0,0014
253000 412000 969000 1229000
-0,323529412 0,628458 1,351942 0,268318
6,66
10,45
22,66
28,78
14,85
20,08
21,3
19,9
Table 49. Performance history of CEO in CA Technologies. Source: [Thomas Reuters, Bloomberg].
Michael Gregoire, CEO, Taleo Inc.
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2005
78410
-0,013548
1392
-0,31431
1,78
8,02
2006
2007
2008
2009
2010
97043 127941 168419 198412 237275
0,237635506 0,318395 0,31638 0,178086 0,19587
-5129
3682
-6502
-510
4163
-4,684626437 1,717879 -2,76589 0,921563 9,162745
-5,29
2,88
-3,86
-0,26
1,75
8
8,1
8,3
7,7
9,98
2011
315395
0,329238226
-1135
-1,272639923
-0,36
14,86
Table 50. Performance history of CEO in Fred's Inc. Source: [Thomas Reuters, Bloomberg].
104
Bruce Efird, CEO, Fred's Inc.
2007
1780923
0,007743152
22657
-0,458601161
1,27
4,9
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2008
2009
2010
2011
1798840 1788136 1841755 1879059
0,010060514 -0,00595 0,029986 0,020255
26418
38694
44723
49355
0,165997264 0,464683 0,155812 0,103571
1,47
2,16
2,43
2,63
4,52
1,98
3,06
6,54
Table 51. Performance history of CEO in Dollar Tree Inc. Source: [Thomas Reuters, Bloomberg].
Bob Sasser, COO, Dollar Tree Inc.
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
1999
1197960
0,303821151
163463
0,326993173
13,65
3,9
CEO
2000
2001
2002
2003
2004
1688105 1987271 1929468 2799872 3126009
0,409149721 0,17722 -0,02909 0,451111 0,116483
207402 203865 -101136 293597 293551
0,268800891 -0,01705 -1,49609 -3,90299 -0,00016
12,29
10,26
-5,24
10,49
9,39
4
3,9
3,4
3,1
3,7
2005
2006
2007
2008
2009
2010
3393924 3969400 4242600 4644900 5231200 5882400
0,085705128 0,169561 0,068827 0,094824 0,126224 0,124484
283239 311300 331100 367000 514100 631100
-0,035128479 0,099072 0,063604 0,108426 0,400817 0,227582
8,35
7,84
7,8
7,9
9,83
10,73
4,2
4,8
4,9
4,52
1,98
3,06
Table 52. Performance history of CEO in Kohl's Corporation. Source: [Thomas Reuters, Bloomberg].
Kevin Mansell, Президент, Kohl's Corporation
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
CEO
1999
4557112
0,237752674
448275
0,32758105
9,84
3,4
2000
2001
2002
2003
2004
6151996 7488654 9120287 10282094 11700619
0,349976915 0,217272 0,217881 0,127387 0,137961
651315 850749 1090383 1023304 1236702
0,452936256 0,306202 0,281674 -0,06152 0,208538
10,59
11,36
11,96
9,95
10,57
3,7
2,9
3,1
2,85
2,7
2005
13402217
0,145428032
1416181
0,14512712
10,57
2,4
Table 53. Performance history of CEO in Barnes & Noble, Inc.
Bloomberg].
William L. Lynch, CEO, Gifts.com
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
2004
4188279
-0,338147772
166078
-0,585016642
3,97
8,1
2006
15544184
0,159822
1814801
0,281475
11,68
4,4
2007
16473734
0,059801
1804477
-0,00569
10,95
4,8
2008
16389000
-0,00514
1536000
-0,14878
9,37
4,1
2009
17178000
0,048142
1712000
0,114583
9,97
2,4
2010
18391000
0,070614
2092000
0,221963
11,38
2,6
Source: [Thomas Reuters,
CEO, Barnes & Noble, Inc.
2005
2006
2007
2008
2009
2010
2011
5753671 6277638 6373410 1445095 4420608
5810564 6998565
0,373755426 0,091067 0,015256 -0,77326 -0,1369 0,314426432 0,204455
344906 442456 371067
-50361
-12896
102446
-62402
1,076771156 0,282831 -0,16135 -1,13572 -1,08318 8,944013648 -1,60912
5,99
7,05
5,82
-3,48
-0,29
1,76
-0,89
9,4
10,2
10,3
11,3
2,4
2,6
6,6
Table 54. Performance history of CEO in Barnes & Noble, Inc.
Bloomberg].
Source: [Thomas Reuters,
Michael Huseby, EVP и CFO, Cablevision Systems Corporation
2004
2005
2006
2007
2008
2009
Net Sales, bln
4932864
5175911 5927462 6484481 7230116 7773276
Growth rate, %
0,18091674 0,049270971 0,145202 0,093973 0,114988 0,075125
Operating Income, bln
43908
510263 612596 917605 1141515 1429632
Growth rate, %
0,31347034 10,62118521 0,20055 0,497896 0,244016 0,252399
Operating margin, %
0,89
9,86
10,33
14,15
15,79
18,39
Indusrty average, %
8,7
8,1
9,2
10,8
11,1
10,2
Table 55. Performance history of CEO in Lowe´s Companies.
Bloomberg].
2010
7231249
-0,069729545
1522400
0,064889426
21,05
8,4
2011
6700848
-0,07335
1248496
-0,17992
18,63
8,6
Source: [Thomas Reuters,
105
Robert Niblock, CFO, Lowe´s Companies
Net Sales, bln
Growth rate, %
Operating Income, bln
Growth rate, %
Operating margin, %
Indusrty average, %
CEO
2000
18778559
0,180626
1402265
0,196117702
7,47
6
2001
22111108
0,17746564
1797788
0,282060096
8,13
4,9
2002
26491000
0,198086
2541000
0,413404
9,59
4,8
2003
30838000
0,164093
3178000
0,250689
10,31
6,3
2004
36464000
0,182437
3743000
0,177785
10,26
6,2
2005
43243000
0,185909
4680000
0,250334
10,82
5,8
2006
46927000
0,085192979
5157000
0,101923077
10,99
6,5
2007
2008
2009
48283000 48230000 47220000
0,028896 -0,0011 -0,02094
4733000 3815000 3226000
-0,08222 -0,19396 -0,15439
9,8
7,91
6,83
5,7
3,9
3,8
106
Appendix 5. IT-industry company data on CEO compensation
Company
LINKEDIN
CORP
TRIPADVISOR
INC
PANDORA
MEDIA INC
YAHOO INC
COMPUTER
SCIENCES
CORP
PRICELINE
GROUP INC
INTL
BUSINESS
MACHINES
CORP
EBAY INC
Year
Base
Salary,
USD
Bonus,
USD
Stock
awards,
USD
Stock
Options,
USD
Non-equity
incentive
plan, USD
All other
compensat
ion, USD
Total
compen
sation,
million
USD
Market
capitalisati
on, Billion
USD
2015
2014
2013
2015
2014
583750
535000
422500
500000
469231
0
0
0
450000
750000
18709690
0
6638000
0
0
28678729
0
0
38054126
5126804
1094531
636650
507000
0
0
4664
3750
3750
10101
47440
49
1
8
39
6
26,100
12,590
6,076
11,780
5,989
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
300000
153425
400000
325000
1000000
454862
700000
1250000
48077
1107692
500000
150000
330000
175000
2250
0
0
0
0
0
0
10690000
0
0
8312316
35000002
7728320
13656687
0
4602406
3345249
18153321
0
0
13847283
0
3135514
2936580
0
2703160
0
0
0
0
1700000
1120000
420000
3002000
0
1314000
51802
20642
2425
3829
73863
40540
4365
442921
1442
2819090
4
29
1
1
25
37
12
21
0
13
3,101
5,198
1,561
1,615
41,240
23,150
19,960
8,756
7,512
4,824
2015
550000
0
8000326
0
6500000
7974
15
61,190
2014
2013
550000
550000
0
0
4499707
4500097
0
0
5250000
4000000
7824
7674
10
9
30,040
24,110
2015
1500000
0
11703869
0
0
761808
14
201,260
2014
2013
1500000
715000
0
0
9259000
5109845
0
0
3915000
1470000
1510727
1047425
16
8
216,890
217,990
2015
2014
2013
993269
970353
945577
0
0
0
8855064
23729962
8854607
2199263
2000000
3799993
1620270
2844346
2688984
165508
160420
167367
14
30
16
69,990
65,010
39,920
Age of
CEO,
years
CEO
tenure in
the
company
, years
Total
CEO
tenure,
years
43
42
41
49
48
47
53
52
51
37
36
62
58
57
59
5
4
3
13
12
11
1
8
7
1
0
2
1
0
4
5
4
3
13
12
11
8
8
7
1
0
17
8
7
4
56
55
54
11
10
9
11
10
9
62
61
60
53
52
51
10
9
8
5
4
3
10
9
8
28
27
26
MONSTER
WORLDWIDE
INC
IAC/INTERACTI
VECORP
COGNIZANT
TECH
SOLUTIONS
UNITED
ONLINE INC
ZILLOW INC
TRULIA INC
VERISIGN INC
YELP INC
ATHENAHEALT
H INC
2015
1098077
2375000
9690004
0
0
66827
13
0,744
2014
2013
2015
2014
2013
1000000
1000000
500000
500000
500000
0
0
2750000
3000000
2500000
0
0
0
0
0
0
0
0
0
4815000
0
0
0
0
0
66577
66327
753090
790268
1007611
1
1
4
4
9
0,666
1,013
5,622
4,060
3,518
2015
608000
0
9882687
0
844812
12177
11
30,080
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
590000
566500
109315
997750
997750
473570
331333
281667
351314
278917
241667
752885
752885
326730
37501
300000
220000
540000
530000
475000
1
806175
0
0
1275000
0
0
0
101
100101
0
0
0
0
0
340625
0
0
0
0
0
0
0
0
9594952
10285710
569605
0
0
0
0
0
6270600
0
0
6810008
4500792
3999978
0
0
0
0
0
0
5999971
5466255
0
0
0
528650
1960581
10113600
6754184
376915
2841390
0
674654
0
0
0
8010363
0
6624459
6967506
7813482
1525418
1492579
1770370
405780
908248
0
1106595
2039352
0
0
0
310000
0
0
957750
593550
0
0
0
0
491076
719600
592000
2
1730661
21687
1500
160624
12689
27080
0
0
0
0
0
0
20484
9650
20180
50100
40657
6741
28551
7801
5012
139027
0
11
12
2
3
5
11
7
1
10
0
1
9
6
5
8
0
7
8
9
3
8
10
21,960
19,390
0,185
0,098
0,095
3,220
0,940
0,620
1,252
0,447
0,607
8,179
5,869
5,765
4,887
1,197
1,472
4,977
2,723
1,740
8,466
7,321
59
58
57
71
70
69
6
5
4
3
2
1
8
7
6
17
16
15
44
43
42
38
57
56
37
36
35
39
38
37
58
57
56
35
34
33
44
43
42
56
52
19
18
17
0
12
11
3
2
1
9
8
7
5
4
3
9
8
7
17
16
15
16
7
19
18
17
0
18
17
3
2
1
9
8
7
5
4
3
9
8
7
17
16
15
16
7
108
AKAMAI
TECHNOLOGIE
S INC
SERVICENOW
INC
IHS INC
GROUPON INC
COSTAR
GROUP INC
CORELOGIC
INC
BAZAARVOICE
INC
AOL INC
TERADATA
CORP
LIMELIGHT
NETWORKS
INC
2013
756843
0
9799922
1199994
119988
0
12
5,779
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
350000
300000
200000
507928
617796
602154
0
757
757
561267
542789
500122
800000
800000
790000
307008
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4413000
0
0
1010700
4181038
4084000
7109996
0
0
3432576
1741575
1006016
2414959
2639969
1619991
316026
2210460
0
8527384
0
0
0
0
0
0
1919830
875283
900769
1208495
971999
1071230
6136560
413604
273548
153718
505544
0
0
0
0
0
1127500
1100000
1025000
953650
1774600
525000
0
441
1005
0
-68436
299887
5372
0
4534
7186
20677
38245
6104
61661
573866
746279
630
7
1
9
2
5
5
7
0
0
7
4
3
5
7
5
7
7,861
3,795
2,959
7,749
5,901
5,581
7,570
3,193
13,160
5,302
2,454
1,691
3,301
2,653
1,341
0,561
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
235833
131061
1000000
1000000
1000000
786849
700000
700000
488611
90000
416000
0
60000
0
500000
0
0
0
0
0
0
133266
0
0
2255092
2757575
0
2491131
6161043
2455132
1695000
133500
1768500
917799
1363799
1043088
5051163
0
2611170
2428243
2247278
3057200
283425
298040
138000
60519
2176000
2750000
2204000
367188
951125
1392125
181500
0
0
799
5485
7650
12684
12534
14809
15236
14986
16753
5000
23841
1
2
6
12
3
6
10
7
5
1
3
2015
557230
40692
3211040
1246512
139308
37061
5
0,533
1,130
3,589
2,508
1,505
7,302
10,330
8,296
0,187
0,233
0,329
51
54
53
52
54
70
69
45
31
30
49
48
47
51
50
49
54
40
39
42
41
40
60
59
58
51
50
45
6
2
1
0
0
6
5
0
4
3
17
16
15
3
2
1
0
7
6
4
3
2
6
5
4
1
0
5
6
8
7
6
0
12
11
0
4
3
17
16
15
5
4
3
11
9
8
4
3
2
6
5
4
1
0
5
1,262
45
13
13
109
SYNCHRONOS
S
TECHNOLOGIE
S
CIBER INC
WEB.COM
GROUP INC
HOMEAWAY
INC
LIFELOCK INC
EARTHLINK
HOLDINGS
CORP
INFOBLOX INC
BOOZ ALLEN
HAMILTON
HLDG CP
ENERNOC INC
DEMAND
MEDIA INC
2014
541000
40575
801360
0
211948
34080
2
0,798
2013
525000
65625
1322332
2685016
758438
35697
5
1,195
2015
2014
2013
675000
662885
600000
0
0
0
4089440
0
2088000
0
0
0
436488
488374
259500
1524
3048
37584
5
1
3
0,321
0,239
0,291
2015
560000
771400
2678002
1050539
0
139161
5
1,650
2014
2013
2015
2014
2013
2015
2014
2013
560000
560000
509375
487500
420833
477340
450038
408462
784000
1250000
0
0
0
0
0
0
1367268
872716
1522686
0
0
0
0
0
608381
408828
2283467
1491056
10769000
3133620
815312
0
0
0
523383
449767
501480
860000
671460
212790
24778
24105
3893
2451
4047
17552
21259
20567
3
3
5
2
12
4
2
1
0,733
0,569
3,776
1,836
1,874
1,468
0,704
0,632
2015
825001
0
1680001
1118211
668251
34643
4
0,507
2014
2013
2015
2014
2013
825000
805288
405833
358750
280000
0
0
0
0
0
1250002
2160001
2443060
0
0
1253125
0
815550
1308400
0
669900
814100
410716
249984
125000
26072
284760
0
0
0
4
4
4
2
0
0,669
0,682
1,690
0,961
0,937
2015
1162500
0
431385
0
612266
1645421
4
3,211
2014
2013
2015
2014
2013
2015
2014
1162500
1162500
602931
411588
409096
360570
475792
0
0
0
0
0
40900
56490
376887
0
2934200
1662400
1589500
714900
0
0
0
0
0
0
0
0
439379
1081846
99995
65000
350000
0
397710
634107
640267
2740
0
0
12906
25623
3
3
4
2
2
1
1
1,865
2,302
0,524
0,345
0,270
0,198
0,320
44
12
12
43
50
49
48
11
3
2
1
11
14
13
12
60
59
58
54
53
52
46
45
44
13
12
11
9
8
7
8
7
6
15
14
13
10
9
8
8
7
6
57
56
55
64
63
62
6
5
4
9
8
7
14
13
12
15
14
13
68
67
66
45
44
43
41
43
14
13
12
10
9
8
0
6
14
13
12
10
9
8
0
113
110
INTRALINKS
HOLDINGS INC
J2 GLOBAL INC
ANGIE'S LIST
INC
BLUCORA INC.
SYNTEL INC
BLACK BOX
CORP
NIC INC
ELLIE MAE INC
TRAVELZOO
INC
PERFICIENT
INC
2013
450000
90000
0
0
360000
23335
1
0,221
42
5
12
2015
475000
0
1645000
806025
475000
6033
3
0,680
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
475000
19792
625672
575000
509000
418881
372839
355692
450000
415192
400000
249999
250000
250000
449231
351346
358750
478333
460458
402167
410000
365000
350000
562000
562000
556500
386667
350000
0
0
78000
32492
0
0
0
0
0
0
150000
0
0
0
0
0
0
0
58566
0
30504
450000
140000
60000
17500
43500
0
0
2121250
0
1621184
1511560
0
0
0
0
823140
506800
371200
0
0
0
992533
813423
694500
1006760
739614
567000
980000
5678200
0
0
0
0
1400001
1135416
0
4269200
0
0
0
2089853
0
0
1094270
634379
2325087
0
0
0
278622
348641
467424
0
0
0
494255
0
305484
1415250
0
0
0
0
228000
0
1058071
829133
749625
374084
339194
508950
450450
613311
540000
0
0
0
0
123000
371000
759738
292831
503717
410000
450000
400000
184364
0
40000
414982
259200
4750
0
22377
34891
17674
24266
24116
20609
10515
4873
8748
21053
16933
82952
58129
158525
5373
115661
67701
92377
34138
33988
42093
24429
46327
46555
15184
21274
3
4
3
3
1
3
1
1
3
2
4
0
0
0
2
2
2
2
2
2
2
7
1
2
1
1
2
2
0,342
0,339
2,277
1,410
1,343
0,886
0,694
0,895
1,205
0,622
0,459
3,811
2,229
1,979
0,368
0,366
0,454
1,559
1,048
0,842
0,742
0,723
0,117
0,328
0,302
0,409
0,787
0,384
52
51
50
57
56
55
48
47
46
49
48
47
41
40
39
52
51
50
54
53
52
72
71
70
42
41
40
50
49
2
1
0
5
4
3
14
13
12
3
2
1
3
2
1
6
5
4
5
4
3
16
15
14
3
2
1
4
3
8
7
6
5
4
3
14
13
12
3
2
1
37
36
35
6
5
4
5
4
3
16
15
14
3
2
1
4
3
111
VIRTUSA
CORP
COMPUTER
TASK GROUP
INC
CARBONITE
INC
FACTSET
RESEARCH
SYSTEMS INC
REACHLOCAL
INC
BLACKBAUD
INC
INCONTACT
INC
LIVEPERSON
INC
KEYW
HOLDING
CORP
2013
315000
0
1089000
0
0
20490
1
0,311
2015
2014
2013
421475
393193
331269
0
0
0
1431000
1657478
962000
0
0
0
324000
176000
187500
0
0
10000
2
2
1
0,966
0,612
0,439
2015
630000
0
545952
332746
515723
101336
2
0,348
2014
505000
0
579040
301170
758233
92772
2
0,330
2013
478781
0
456000
233685
1024995
58480
2
0,265
2015
2014
2013
340000
340000
297500
0
0
0
0
0
0
1141137
1282701
2024430
240975
0
100706
51684
154572
11890
2
2
2
0,307
0,239
0,279
2015
300000
705000
0
666667
0
41424
2
4,508
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
275000
275000
216696
400000
400000
408933
608925
595500
300000
280000
250000
500271
500189
457025
496742
415002
412502
715000
800000
0
251320
100528
0
0
0
0
40000
26000
0
0
0
0
0
0
0
400000
150121
102180
0
0
942827
1987244
0
157500
0
0
0
0
281750
111150
94705
600000
133333
649000
390000
2267300
0
0
0
904620
475439
153927
332360
855030
2911040
364693
61318
353694
0
0
0
242273
0
436693
589421
436859
66000
145200
26650
412500
268200
178000
300000
366875
0
35808
35752
0
7169
6697
30340
42026
69445
15444
14028
13321
6887
6907
5831
85478
77961
43480
2
2
1
1
3
1
2
3
1
1
0
1
2
4
2
1
1
4,099
4,024
0,347
0,372
0,192
1,714
1,023
1,268
0,441
0,284
0,194
0,794
0,725
0,691
0,485
0,432
0,197
48
47
46
45
2
13
12
11
2
13
12
11
62
61
12
11
12
11
60
65
64
63
10
8
7
6
10
10
9
8
51
51
49
64
41
40
58
57
56
44
43
42
45
44
43
69
68
67
13
12
11
0
8
7
8
7
6
8
7
6
18
17
16
5
4
3
13
12
11
0
10
11
8
7
6
8
7
6
18
17
16
7
6
5
112
CONVERSANT
INC (Valueclick)
XO GROUP INC
QUINSTREET
INC
RACKSPACE
HOSTING INC
FACEBOOK
INC
TECHTARGET
INC
RENTRAK
CORP
HEALTHSTREA
M INC
SHUTTERSTO
CK INC
MORNINGSTA
R INC
2015
583333
0
0
0
300000
5100
1
1,561
2014
2013
2015
2014
2013
2015
2014
2013
400000
450000
400000
395000
370000
512425
512425
497500
0
0
0
0
0
0
0
0
8707500
573600
369600
0
333300
0
0
0
0
0
0
0
0
0
0
0
800000
545625
0
103488
276460
246095
244545
611045
2772400
4900
85743
18257
13479
28713
966
200
13
2
1
1
1
1
1
1
1,469
1,403
0,403
0,237
0,246
0,347
0,409
0,566
2015
400000
0
0
0
332000
35515
1
5,384
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
400000
400000
1
503205
483333
600000
600000
600000
199650
181500
165000
265567
253000
240000
250000
250000
250000
100000
100000
100000
0
0
0
266101
445500
0
0
0
125000
100000
75000
0
20151
0
0
0
0
0
0
0
1312423
2468148
0
0
0
0
2496000
0
0
304986
0
108500
0
0
0
0
0
0
0
0
437455
820105
0
0
0
0
0
0
0
1448939
1854588
0
0
0
0
0
0
0
0
0
388000
461000
0
0
0
0
28489
134111
100000
100000
100000
35209
0
85750
0
0
0
0
0
0
2361
2403
653164
1221408
783529
2000
2000
2000
82409
82018
65527
0
0
0
0
0
0
5295
5295
4831
3
4
1
2
2
1
3
1
1
2
2
0
0
0
0
0
0
0
0
0
9,897
5,754
132,020
63,140
81,740
0,220
0,207
0,239
0,728
0,262
0,254
14,690
11,340
10,360
2,867
0,871
0,711
3,666
2,946
3,011
53
52
66
47
46
45
53
52
51
1
0
10
17
16
15
14
13
12
1
0
20
17
16
15
14
13
12
42
41
40
30
29
28
51
50
49
59
58
57
47
46
45
40
39
38
56
55
54
13
12
11
9
8
7
14
13
12
4
3
2
12
11
10
10
9
8
13
12
11
13
12
11
9
8
7
14
13
12
13
12
11
12
11
10
10
9
8
26
25
24
113
GOOGLE INC
CA
TECHNOLOGIE
S INC
LEIDOS
HOLDINGS INC
ZYNGA INC
CACI
INTERNATION
AL INC
IGATE CORP
PROTO LABS
INC
SRA
INTERNATION
AL INC
ACXIOM CORP
PROGRESS
SOFTWARE
CORP
2015
1
0
0
0
0
0
0
376,400
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
1
1
234849
1000000
1000000
1119808
1000000
1000000
481109
300000
300000
275503
780000
0
0
500000
0
0
0
0
0
5969863
0
3750
400000
0
0
0
1826459
3909219
4073518
1875003
1750000
1693607
38035712
0
0
15870000
2419200
0
0
2900588
821710
1473826
1125000
1870208
1381683
13327036
0
0
0
0
0
0
0
1764000
1266000
1248000
710000
1077750
0
0
0
0
1982220
0
0
342151
282672
214091
0
14847
0
371
810
1374764
2813
202216
0
0
6
8
8
5
5
5
58
0
2
17
6
233,400
209,200
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
756300
379167
1041667
980417
270000
241084
240017
840000
790192
680000
637500
409321
0
28000
365000
1130000
0
0
0
2000000
5500000
0
0
0
1999850
10840000
0
6606778
0
0
0
0
1000000
200600
2468039
3155052
0
1534110
0
0
0
0
0
0
3803158
511484
824304
2176476
2211665
147000
0
0
508433
200919
273331
0
546000
419220
858000
300000
219634
0
151746
99873
0
0
0
8750
16750
12625
51320
77151
5
13
2
9
1
0
1
3
12
2
5
6
2013
2015
2014
2013
2015
630000
637885
646154
550000
637778
0
0
0
0
785742
2355880
12738276
4216000
1224132
1540212
623143
0
5148900
1740955
0
0
767000
0
11315
0
2630210
96074
47815
106445
7650
6
14
10
4
3
12,790
11,665
12,195
4,485
5,998
7,406
1,630
1,629
1,782
1,575
0,989
0,980
0,535
0,753
14,813
12,299
13,106
1,149
1,359
1,390
1,502
1,771
1,351
0,775
40
39
38
47
71
70
67
63
62
50
47
46
58
64
63
45
48
47
53
52
51
46
45
60
45
44
54
61
43
51
57
6
5
4
0
2
1
1
3
2
0
5
4
0
5
4
0
4
3
12
11
10
1
0
4
1
0
3
0
0
2
17
114
6
5
4
7
2
1
1
3
2
15
16
15
2
5
4
0
4
3
12
11
10
4
3
4
1
0
7
12
0
2
23
2014
570554
427916
0
0
0
11250
1
MANHATTAN
ASSOCIATES
INC
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
570554
495000
495000
369115
773846
1000000
1000000
876923
840501
850000
475000
500000
484000
290429
371200
158400
148500
0
0
0
0
0
0
0
0
0
0
111400
0
2896000
3000018
1530001
750016
4996994
4453150
4577935
3039094
1204996
1060612
0
456671
0
2441061
2999985
1530002
2249993
4982180
0
0
0
0
0
0
0
0
0
1300000
3000000
3000000
1437978
1613670
1554075
508250
500000
494000
6125
74178
70765
61412
57755
75991
68554
23819
34169
22350
11193
10118
5707
1
2
1
6
8
7
8
12
7
1
4
2
2
ASPEN
TECHNOLOGY
INC
2015
2014
2013
600000
600000
550000
0
0
0
2624990
2014000
1171696
981476
737000
700920
800000
750000
750000
9322
5713
5887
5
4
6
MEDASSETS
INC
INTELIQUENT
INC
VERISK
ANALYTICS
INC
INGRAM
MICRO INC
0,885
1,246
0,392
0,475
0,603
7,530
4,525
3,559
2,847
3,160
2,953
0,997
0,644
0,597
1,959
1,363
0,957
56
55
63
62
61
57
63
62
61
60
55
53
56
55
51
50
49
16
15
2
1
0
0
12
11
4
3
6
0
8
7
8
7
6
115
22
21
9
8
7
0
12
11
5
4
6
0
9
8
16
15
14
Appendix 6. Retail industry company data on CEO compensation
Company
TARGET CORP
MACY'S INC
BON-TON
STORES INC
KOHL'S CORP
DOLLAR
GENERAL
CORP
DOLLAR TREE
INC
DILLARDS INC
WALMART
Bonus,
USD
Stock
awards,
USD
Stock
Options,
USD
Nonequity
incentive
plan,
USD
1500000
1500000
1500000
0
0
1250000
10224120
5285245
4857502
0
5248573
3696982
0
2880000
2205000
All
other
compe
nsatio
n,
USD
1229094
5733646
6197623
2015
2014
2013
2015
2014
2013
2015
2014
1600000
1591667
1541667
1000000
976923
1000000
1339300
1329300
0
0
0
1000000
1000000
0
0
0
4762258
4630824
4649988
6330500
1789750
1410300
6000119
2800011
3100000
3099994
3099998
0
0
0
0
2800003
1850200
1907200
5105100
0
500000
0
535720
531720
718513
2610846
3253949
125087
148983
89185
303165
355758
12,03
13,84
17,65
8,46
4,42
2,50
8,18
7,82
2013
1300000
0
2799984
2806198
2145000
371261
9,42
2015
2014
2013
2015
1291515
1235626
1196947
1410577
0
0
0
0
3440634
16554441
0
3839768
2059459
3091549
0
0
0
1591956
1850386
1909929
855567
686688
785036
58089
7,65
23,16
3,83
7,22
2014
1301923
0
13676384
0
1847813
6367
16,83
2013
2015
2014
2013
2015
2014
2013
1080769
1000000
950000
900000
1315731
1264775
1232670
0
0
0
0
0
0
0
3193858
238796
686491
602205
13649520
13066877
12652363
0
0
0
0
0
0
0
1813020
2405300
3000700
3248100
4373180
2878305
3852059
56769
3033082
253303
7046538
1355114
921781
975629
6,14
6,68
4,89
11,80
20,69
18,13
18,71
Base
Salary,
USD
2015
2014
2013
Year
Total
compens
ation,
USD
12,95
20,65
19,71
Market
capitalis
ation,
Billion
USD
38,78
34,65
39,41
16,54
9,74
8,84
0,15
0,23
0,18
11,81
15,33
16,96
15,30
10,19
8,72
10,89
6,60
4,93
2,88
2,20
1,60
207,54
183,51
210,85
Age of
CEO,
years
CEO
tenure in
the
company,
years
Total
CEO
tenure,
years
57
56
55
5
4
3
5
4
3
60
59
58
45
44
64
61
60
10
9
8
1
0
7
5
4
10
9
8
13
12
8
5
4
59
3
3
59
58
57
61
5
4
3
9
10
9
8
9
60
8
8
59
68
67
66
63
62
61
7
11
10
9
4
3
2
7
11
10
9
4
3
2
116
FAMILY
DOLLAR
STORES
2015
1115046
0
1953291
1650621
686336
47283
5,45
2014
2013
1051346
1030289
0
0
1721723
1435958
1464998
1197158
942006
982253
47175
101737
5,23
4,75
COSTCO
WHOLESALE
CORP
2015
650000
88800
4527994
0
0
118681
5,39
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
662500
649999
678461
1453846
1400000
88271
475377
450000
568480
544000
506667
810606
1500000
1864583
700000
682692
650000
600000
623564
600000
492596
1121154
1061540
548901
878096
795430
168233
99200
0
0
0
0
200000
200000
0
0
0
0
0
0
0
0
0
0
0
3000000
3500000
0
0
320000
0
0
3870300
2496024
2714418
10524000
10280000
37500
132360
0
3216800
0
0
0
0
64056935
0
395000
340379
0
8696129
0
11801306
3632679
0
2179408
255082
0
0
0
1407945
0
0
691651
150345
0
0
0
0
0
0
3600006
0
965000
106500
0
0
0
3750002
2265594
3206125
2400027
1445034
1819500
0
0
0
0
0
0
0
0
192500
220000
200000
0
0
2111302
0
0
227500
0
240000
0
0
1140000
746667
548901
867013
1108071
109740
90642
562405
341920
244662
0
11905
11240
126293
122901
156440
1582024
388587
16210001
22277
44464
14483
564
586
48062
6788
55532
15168
43577
0
41740
4,81
3,34
5,36
12,32
11,92
8,17
9,70
0,66
4,10
0,89
0,86
2,39
18,89
87,84
7,22
2,09
1,34
6,01
9,56
3,65
19,55
8,21
5,03
6,04
3,45
3,76
BIG LOTS INC
TUESDAY
MORNING
CORP
PRICESMART
INC
PENNEY (J C)
CO
FREDS INC
FIVE BELOW
INC
BEST BUY CO
INC
ULTA BEAUTY
INC
6,65
6,48
4,96
53
10
10
52
51
9
8
9
8
39,17
30,87
26,75
2,99
3,10
3,03
0,15
0,20
0,24
2,06
0,99
0,69
8,07
8,57
7,41
0,52
0,49
0,41
2,00
2,00
1,43
9,21
12,43
17,14
5,61
2,78
1,26
60
3
3
59
58
58
62
61
75
63
62
46
45
44
53
52
51
54
53
52
59
58
57
53
54
53
52
52
51
1
0
0
7
6
0
12
11
3
2
1
2
1
0
4
3
2
8
7
6
1
8
7
0
2
1
2
0
0
14
13
11
12
11
3
2
1
2
1
0
4
3
2
9
8
7
11
8
7
3
2
1
117
SALLY BEAUTY
HOLDINGS INC
OFFICE DEPOT
INC
AARON'S INC
LUMBER
LIQUIDATORS
HOLDINGS INC
BARNES &
NOBLE INC
FRANCESCA'S
HOLDINGS
CORP
STAGE
STORES INC
BUILD-A-BEAR
WORKSHOP
INC
CHRISTOPHER
& BANKS
CORP
GNC
HOLDINGS INC
2015
997077
0
1084064
3387480
441379
13904
5,92
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
959154
921923
1400000
1200000
1646154
850000
850000
500000
655769
567308
471154
1200000
1142308
0
0
2350000
0
0
0
0
0
0
7187
60000
1800000
450000
0
569500
12500000
2000700
4284000
2926000
2489000
0
1469911
0
329982
0
3098340
3188030
2584961
4473000
0
0
0
0
0
3374996
0
4399997
3865000
5285000
1351197
1928522
0
1267200
815015
323000
718797
921433
1350000
654063
66563
630000
0
9333
15542
148581
38687
71766
4511
333
234359
16207
14195
7191
31228
32750
5,51
6,02
20,87
4,51
6,82
4,10
4,06
1,66
6,87
1,24
5,33
7,53
10,01
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
900000
550000
336058
375000
932693
850000
841346
336538
659200
654031
800000
153846
675000
0
162500
175000
0
0
0
168867
0
0
0
200000
0
0
0
0
2195856
2638923
2207765
656289
475949
510760
0
0
0
0
5618908
6079144
0
0
595265
770317
0
169954
0
3751900
0
365750
349038
375000
0
1488945
0
628086
0
0
0
0
28181
50000
45000
45711
289878
95107
175667
117744
3508
4273
45496
32817
1,60
0,97
6,40
7,05
3,40
4,94
3,82
2,68
1,14
1,34
0,85
4,14
2013
2015
2014
2013
2015
187692
1070596
1049039
983192
1066000
0
223678
0
0
0
315484
843758
1687500
487963
4865877
3457350
0
843750
4763673
2374991
0
577816
1680000
1327310
2618076
2077
145756
161505
50564
122837
3,96
2,86
5,42
7,61
11,05
4,52
2,41
1,54
1,02
1,40
2,13
1,98
1,91
0,20
0,68
0,65
0,68
0,86
0,54
1,32
1,36
0,00
0,00
0,50
0,65
0,58
0,09
0,12
0,13
0,08
0,22
0,29
3,57
0,00
0,00
75,30
61
7
7
60
59
60
73
72
72
71
59
48
47
46
42
41
6
5
0
3
2
1
0
3
2
1
0
3
2
6
5
16
14
13
12
11
3
6
5
4
5
4
40
57
42
41
65
64
51
50
64
63
60
59
1
0
5
4
1
0
3
0
15
14
1
0
3
0
5
4
13
12
3
0
15
14
6
5
65
61
60
59
64
1
8
7
6
6
1
8
7
6
6
118
HOME DEPOT
INC
LOWE'S
COMPANIES
INC
TJX
COMPANIES
INC
ROSS STORES
INC
STAPLES INC
FOOT LOCKER
INC
WILLIAMSSONOMA INC
DICK'S
SPORTING
GOOD INC
TRACTOR
SUPPLY CO
INC
CABELA'S INC
2014
1086500
0
4591142
2624997
2499386
291889
11,09
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
1066000
1220000
1185000
1155000
1426924
1320000
1575000
1299837
1238024
1203114
1249208
1203386
1174035
0
0
0
0
0
0
0
0
0
0
299810
0
0
4477108
9801340
5343893
5599700
10872000
0
12559150
3000040
7000078
8500014
8225007
2467504
2272908
2624997
4120364
3740875
3232749
654630
708954
947524
0
0
0
0
2467502
3401201
2385516
3299258
1664996
1494732
6050370
4309576
4127571
1844576
2145785
2224032
667415
0
1427996
241332
273231
201878
160562
48550
48660
43495
86573
177941
99580
326440
336212
584964
10,79
18,71
12,14
11,64
21,77
11,09
23,08
6,23
10,56
12,03
10,77
6,47
8,86
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
1100000
1100000
1100000
1350000
1280769
1156731
1000000
1019231
961538
831154
999912
995667
0
0
500000
0
0
0
0
0
0
0
0
0
3496281
1925017
2867015
6999976
5960024
2738699
4499990
5250015
3800000
701980
375373
376334
5669402
3040800
2878750
0
0
2691081
1499993
2249965
2698110
1637042
886668
715130
3290375
4233625
5954052
3500000
2800000
2600000
1240842
2010766
3351187
1591267
1361834
1270786
218739
247120
238856
72826
69579
25020
117238
104909
103187
24283
28558
28333
14,09
11,05
14,06
11,92
10,11
9,21
8,53
10,83
11,11
4,79
3,25
2,92
2015
2014
2013
2015
2014
989000
989000
834885
1
1019231
0
0
0
0
0
967290
844080
645360
4309523
0
2022205
1638560
459200
0
0
1580422
1874155
1189000
0
0
10200
10000
141217
0
278741
5,57
5,36
3,27
4,31
1,30
58,39
55,03
38,32
36,16
36,48
29,02
18,96
17,60
12,87
8,18
6,63
11,64
14,32
17,31
4,62
2,89
2,28
3,96
4,00
2,56
4,61
3,68
2,34
6,24
3,92
2,15
2,56
1,69
1,17
8,51
8,87
63
5
5
62
51
50
49
59
58
57
63
62
61
56
55
54
4
8
7
6
6
5
4
17
16
15
16
15
14
4
8
7
6
6
5
4
17
16
15
16
15
14
62
61
60
45
44
43
59
58
57
58
63
62
4
3
2
3
2
1
29
28
27
0
5
4
4
3
2
3
2
1
29
28
27
0
9
8
60
59
58
51
47
4
3
2
0
1
15
14
12
1
1
119
SEARS
HOLDINGS
CORP
BELK INC
VITAMIN
SHOPPE INC
ALCO STORES
INC
L BRANDS INC
O REILLY
AUTOMOTIVE
INC
AUTOZONE
INC
GAP INC
BED BATH &
BEYOND INC
CARMAX INC
2013
930769
150000
8000118
0
0
852037
9,93
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
1050192
986552
895415
400000
400000
450000
471000
450000
450000
1924000
1924000
1924000
571154
546154
525000
1019231
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2070029
2000028
3600410
399976
199978
0
0
0
0
7509032
8605824
8822133
287586
275034
262527
90043
0
0
0
0
0
0
162489
127773
106621
2256513
2681763
2596103
0
0
0
2513124
1099170
1376000
1360047
59390
436590
326953
0
0
0
2839670
4970885
4899158
0
0
0
1509736
215307
167485
115126
360
360
1410
5805
5654
11701
936302
677571
649172
32802
28517
27097
173031
4,60
4,70
6,05
1,10
1,11
0,78
0,64
0,58
0,55
15,88
19,23
19,23
0,89
0,85
0,81
5,31
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
1000000
992308
1500000
1500000
1500000
3867981
3478846
2894231
1086154
1037308
993077
700000
0
0
0
0
0
0
0
0
0
0
0
0
88997
6609251
14200512
18267270
3119506
6750034
5999994
5225036
1152682
955904
760025
1375028
2142316
1575207
0
0
3174120
6750011
5749992
5000003
3458082
2905722
2280068
1375018
1316000
2009424
2675567
4500000
823500
1753736
684106
790392
1203088
898560
1507500
774962
194168
173829
350833
360542
210968
22993
22211
17572
283140
319390
262693
57926
4,74
11,36
18,73
24,63
9,71
19,14
15,94
13,93
7,41
6,47
5,91
4,28
11,90
1,37
1,10
0,84
1,26
0,92
0,59
0,03
0,05
0,05
13,67
9,74
7,98
11,41
7,81
5,78
14,72
11,10
8,40
12,81
12,78
16,02
15,88
11,61
11,50
7,83
7,47
5,27
6,48
46
0
0
58
57
56
61
60
59
51
50
49
77
76
75
63
62
61
48
9
8
7
4
3
2
3
2
1
17
17
16
8
7
6
8
9
8
7
4
3
2
3
2
1
18
17
16
8
7
6
8
47
46
52
51
50
54
53
52
48
47
46
48
7
6
6
5
4
10
9
8
7
6
5
5
7
6
13
12
11
10
9
8
7
6
5
5
120
ADVANCE
AUTO PARTS
COACH INC
AUTONATION
INC
CARTER'S INC
KATE SPADE &
CO INC
GAMESTOP
CORP
HSN INC
DSW INC
BUCKLE INC
CHICO'S FAS
INC
LITHIA
MOTORS INC
2014
700000
0
687505
2062503
0
56726
3,51
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
700000
1500000
1500000
1452350
1150000
1150000
1150000
882692
818846
760000
1300000
1300000
1300000
0
0
0
0
0
0
0
0
0
0
0
0
0
687500
2549991
2549968
2549992
0
0
0
4445250
5752350
3408800
0
4567500
0
2062502
4390932
4082738
4306001
3323093
3163567
3578048
1004273
1068900
960000
2218120
2190000
2047504
601650
2335125
3672750
3630875
1645420
2055126
1506040
1293800
2103750
855000
2154750
0
1950000
117541
348763
470549
452256
164951
179752
194273
23000
22500
22000
179927
177562
151584
4,17
11,12
12,28
12,39
6,28
6,55
6,43
7,65
9,77
6,01
5,85
8,24
5,45
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
1059423
1049808
1027692
1200000
1200000
1200000
1050000
1062500
1000000
988800
960000
950000
975000
1515000
2254445
0
0
0
0
0
0
1634576
3401728
5228163
3002227
7164087
1042500
8327269
0
0
269871
225172
146172
0
3901500
3203100
998757
0
0
3000000
3000012
3000002
558283
604204
456945
0
0
0
2120000
1545000
1545000
1273085
1140000
1800000
623700
755950
975000
0
0
0
193692
163299
5743
0
0
7951
0
0
0
229057
273502
190681
8,35
11,44
5,88
13,80
5,63
6,18
2,15
2,25
2,21
2,85
8,54
9,57
2015
2014
2013
2015
2014
968269
950000
950000
800000
741333
0
0
0
0
0
4100012
2738000
1378000
3318571
1132656
0
0
0
0
0
1423356
1048800
1426900
1158000
1055520
9058
8126
12888
277846
220065
6,50
4,74
3,77
5,56
3,16
5,19
3,99
22,51
14,74
11,89
4,47
4,97
3,15
2,82
1,56
1,79
1,22
0,48
0,68
3,28
3,17
3,48
2,19
1,76
1,67
1,80
0,65
0,42
2,30
1,68
1,68
2,62
2,46
2,53
0,57
0,32
47
4
4
46
67
66
65
64
63
62
52
51
50
51
50
49
3
18
17
16
14
13
12
5
4
3
7
6
5
3
18
17
16
14
13
12
5
4
3
7
6
5
49
48
47
55
54
53
62
61
60
63
62
61
3
2
1
5
4
3
4
3
2
16
15
14
3
2
1
14
13
12
8
7
6
16
15
14
63
62
61
46
45
4
3
2
2
1
16
15
14
2
1
121
ASBURY
AUTOMOTIVE
GROUP INC
TECH DATA
CORP
MATTRESS
FIRM HOLDING
CORP
GROUP 1
AUTOMOTIVE
INC
ABERCROMBIE
& FITCH INC
GENESCO INC
ANN INC
CATO CORP
FINISH LINE
INC
ZUMIEZ INC
2013
624000
0
402120
0
819000
100115
1,95
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
916667
750000
735346
1024230
986769
500000
500000
424940
1000000
1000000
1000000
1500000
0
0
0
750375
985000
1878113
0
0
0
0
0
0
0
2248571
1748896
1499954
2380508
2300009
2105406
275460
0
0
2583900
2467350
2015750
0
0
0
0
0
0
0
559255
0
1477620
0
0
0
0
1586500
1035000
705000
0
0
0
0
166002
606100
666667
1250000
1000000
0
32423
26799
22338
47113
40725
39116
29971
22922
19989
259173
242084
243145
696321
4,78
3,56
2,96
4,20
4,31
4,98
1,36
0,69
2,53
4,65
5,07
4,34
2,24
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
1528846
1500000
810500
794500
778500
1200000
1200000
1200000
1119402
1092100
1065375
950000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1771161
2134219
1835968
2696498
1236000
1328000
1210583
813981
690796
478750
0
43201893
0
0
0
1165589
1236000
1328000
86747
0
0
1258750
1731600
1188000
3790198
3675887
2164230
3336200
6706200
4734285
462897
0
1591920
495513
800538
719182
31344
26274
28860
441339
285091
98780
36132
423170
140714
69906
8,16
48,07
6,47
6,64
4,91
8,83
12,70
10,80
2,92
2,33
3,49
7,53
2014
2013
2015
2014
2013
950000
775000
649769
631324
606456
0
56250
0
0
0
1187500
562063
0
0
0
1187500
562063
0
0
0
1460000
1583750
61581
199290
348758
32130
79282
6679
8421
8646
4,82
3,62
0,99
0,51
0,66
957000
0,15
0,84
0,56
0,46
2,22
2,26
2,26
1,18
0,00
0,00
1,26
0,95
0,82
4,48
4,62
3,87
1,80
0,88
0,70
1,37
1,45
1,17
0,75
0,64
0,59
1,22
0,89
0,74
1,11
0,72
0,59
44
0
0
56
55
54
58
57
56
44
43
42
59
58
57
68
2
1
0
7
6
5
3
2
1
8
7
6
21
2
1
0
12
11
10
3
2
1
8
7
6
21
67
66
59
58
57
58
57
56
62
61
60
62
20
19
5
4
3
9
8
7
15
14
13
5
20
19
9
8
7
9
8
7
15
14
13
6
61
60
53
52
51
4
3
13
12
11
5
4
13
12
11
122
STEIN MART
INC
TIFFANY & CO
RENT-ACENTER INC
PIER 1
IMPORTS INC
SONIC
AUTOMOTIVE
INC
HIBBETT
SPORTS INC
RUSH
ENTERPRISES
INC
STAMPS.COM
INC
2015
563835
0
0
0
364813
39032
0,69
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
2015
2014
553200
215715
997315
997315
997315
983250
950000
865700
1050000
1050000
1050000
1161333
1127500
0
0
0
0
0
0
0
0
0
0
248719
0
318400
0
0
1883925
1569229
1569700
1616686
1484252
0
11842575
1226250
406250
1673609
1228362
0
0
1939516
1505835
1514352
630388
539506
84900
0
0
0
0
0
280287
0
1200000
140000
1150000
511803
1726746
1099326
1837500
2625000
2100000
1451880
1091183
641052
135504
126365
141158
172178
15066
9775
10028
279712
135631
62172
113166
98250
1,47
0,35
6,15
6,14
8,98
3,76
4,71
2,06
18,76
8,48
6,46
4,40
3,86
2013
2015
2014
2013
2015
2014
2013
2015
2014
2013
1100000
440000
420000
400000
1100016
1100016
900016
443000
425834
412500
0
0
0
0
1300000
1500000
1000000
118689
26498
0
614290
504691
400128
408588
652500
352200
281100
0
0
0
0
0
0
0
475699
821558
651300
0
0
1195000
1760000
458150
420000
350000
0
0
0
438311
353502
370000
95390
11250
10625
10857
199785
164879
167690
5100
5000
4600
3,57
1,41
1,25
1,17
3,73
3,94
3,00
1,01
0,81
1,98
0,28
0,43
0,39
9,26
7,24
5,88
2,08
2,10
1,49
1,94
1,09
0,78
0,73
0,53
0,48
1,39
0,84
0,75
0,21
0,17
0,12
0,44
0,18
0,14
67
2
14
66
65
61
60
59
55
54
53
60
59
58
86
85
1
0
14
13
12
12
11
10
6
5
4
16
15
13
12
14
13
12
12
11
10
6
5
4
16
15
84
55
54
53
55
54
53
45
44
43
14
4
3
2
7
6
5
13
12
11
14
4
3
2
7
6
5
13
12
11
123
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