Rewarding effort and outcome; an exploratory research into an economically viable perspective of reward systems

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Rewarding effort and outcome; an exploratory research into an

economically viable perspective of reward systems.

MASTER’S THESIS

Author: Stuart van den Bos

Student number: 5947189

Msc Business Studies, Strategy Track

Thesis Supervisor: Drs. A. El Haji

Second Examiner: Dr. K.J.P. Quintelier

University of Amsterdam, Amsterdam Business School

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Abstract

Currently employees are rewarded for their work based on what competing firms offer for a similar job title. Some scholars in the literature argue this is a faulty economic logic. The reason here for is that this practice is disconnected with the input of an employee or, more importantly, one’s output. What’s more is that jobs are becoming ever less comparable due to increasing dynamism of the competitive environment. This paper argues, in conjunction with other scholars, for reward systems based on measurable

(economic) input and output. This will result in greater fairness perceptions of rewards – with all accompanying benefits for both the employee and the organization for whom one works. This research predicts, based on the literature, that effort provided and value created in one’s job determine to a great extent what amount of reward is deemed as fair. Specifically, the more effort provided, measured by the hours spent working, or the more value created by an employee the fairer a high reward is considered to be. This relationship is moderated by political preference, social value orientation, congruency of one’s own situation with the vignette and education of the respondents. The hypothesis were tested by

conducting an experiment in which effort provided and value created were manipulated. The experiment was performed through the use of a vignette in a survey. The survey was distributed through Amazon Mechanical Turk. This yielded a sample of 233 respondents. Despite strong arguments derived from the literature in favor of the hypotheses the empirical evidence was not found in this study. There was insignificant proof found for the relationship between effort and fairness perceptions or amount of value created and fairness perceptions. Similarly, there was no significant moderating effect found between any of the moderating variables and fairness perceptions.

Statement of originality

This document is written by Student Stuart van den Bos who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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1. Introduction

Perceptions of fairness have a profound effect on a variety of factors such as motivation, productivity and general wellbeing (Sandel, 2010; Cook & Hegtvedt, 1983; Cropanzano, Byrne, Bobocel & Rupp, 2001). Within an economic context compensation, or reward, for provided work is paramount to forming fairness perceptions.

Research has indicated that most of the current reward systems are based on market pay; employees receive a reward for their labor based on what competitors are paying for a similar job title (Gerhart et al., 1995; Baker, Jensen & Murphy, 1988). Baker et al. (1988, p.593) argue that these reward systems “are based on equality notions rather than viable economic arguments” and are thus sub-optimal. Additionally, one can argue that the shifting paradigm towards an economy based on knowledge has amplified this distinction. The argument is that there is a vast number of occupations that are becoming more unique thus, by definition, less comparable to one another. As such, these reward systems are proving to be suboptimal for the lesser generic occupations and has made this way of organizing reward systems an outdated practice for those jobs in particular (Martin & Moldoveanu, 2003).

A possible solution for an economically viable reward system is to base reward on productive contribution; input into- or output of the work one provides. Following economic logic it would only make sense to hire someone if this person creates more value than he or she costs. From this perspective rewarding labor based on outcome seems like a more fair system than basing them on market pay (Fehr, Klein, Schmidt, 2007). Research has recognized a shifting paradigm from employees, specifically among knowledge workers. They are increasingly demanding a greater ownership of their labor, which is exemplified by the increasing relative size of variable pay (Kurdelbusch, 2002; Martin & Moldoveanu, 2003). This indicates a need for a different outlook on reward systems than currently employed.

For some occupations the outcome of labor is difficult to determine which makes reward systems based on outcome less feasible. For these occupations, support staff for instance, effort provided can be considered a more practical alternative on which to determine reward rather than value created, especially within a team (Gerhart et al., 1995). Previous research found that, in a team setting, basing rewards on market pay is perceived as unfair by many in the team (Dulebohn & Martocchio, 1998).

Previous research has never specifically investigated the relationship between value created, effort and fairness perceptions; whether increased effort and/or value will allow for a higher reward that is considered to be fair. This research explores this relationship by conducting an experiment – and will provide a starting point for rewards optimization. It will do so by firstly reviewing current relevant literature. After which a theoretical framework and accompanying hypotheses is presented. Following this

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the research design is further specified. The results are discussed in section five only to be followed by a discussion of the findings in chapter six. The last chapter concludes the research and it’s findings.

2. Literature review

Below relevant literature is discussed. This section starts with an overview of fairness perceptions in economics. Secondly, the concept of value creation is introduced and explained. After which the concept of effort in relation to rewards is discussed. This section describes contemporary thinking and explains relevant concepts. In doing so, it forms the basis for the theoretical framework and hypothesis

development that will follow in section three.

2.1 Fairness perceptions in economics

Fairness perceptions determine our perception of all social and economic interactions; they determine how to respond and how to guide future behaviors (Cook & Hegtvedt, 1983; Cropanzano et al., 2001; Colquit et al, 2001). Below fairness perceptions in an economical context are discussed.

Arguably the most significant part of effectively managing an organization is the management of human resources. From a strategic standpoint human resources and knowledge the employees possess are the most unique components of an organization. Therefore, they are the most difficult for any

organization to copy and thus it is argued that they are the only source of sustained competitive advantage (Grant, 1996). Motivating employees to provide their utmost effort then is critically important to the overall performance of any organization. Indeed, research has shown that a more highly motivated workforce will allow for great benefits such as higher retention rates, -organizational commitment and innovative behavior (Bloom, 2004; Cropanzano et al., 2001; Janssen, 2000).

Fairness perceptions have considerable impact on an employees’ motivation (Bloom, 2004; Janssen, 2000; Cropanzano et al. 2001; Colquit et al, 2001). When efforts are fairly rewarded employees are willing to reciprocate by behaviors that go beyond contractually determined job achievements or specifications (Janssen, 2000). The most noticeable reward one receives for labor is monetary in the form of one’s salary (Baker et al., 1988; Gerhart et al., 1995; Bridoux, Coeurderoy & Durand, 2011; Fleck, Glaser & Sprague, 2011). Due to it’s impact, it is important to understand what is considered a fair reward.

The most noticeable researches measured fairness perceptions of rewards by asking the question what reward is justified according to the respondents (i.e. what one should get as reward). These

researches asked respondents how fair they rated a hypothetical persons’ reward based on the notion of ‘merit’ and ‘need’. Merit consisted of occupation and education and need was divided into marital status and number of children. It found that the demographics of respondents influenced fairness perceptions. Specifically, it was found that education, occupation, sex, marital status and knowledge of family

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earnings influence perceptions of fairness (Alves & Rossi, 1978; Baker et al., 1980; Faia, 1980; Shepalak & Alwin, 1986; Kelley & Evans, 1983).

Moreover, later research found that there is broad agreement on the amount of pay low-status ordinary jobs should receive and that high-status elite occupations should be paid more than the minimum. Dissensus however existed on how much the difference between these jobs ought to be. The variation in the amount of pay is dependent on political preference and social structure, with older & politically more conservative respondents preferring higher pay for high-status employees (Kelley & Evans, 1983; Alves & Rossi, 1978).

Although insightful, these researches do not apply the economic logic that we argue should be at the basis of rewards. Specifically, we argue that it is not relevant what reward one should get based on their occupation as every person is idiosyncratic in one’s added value or effort provided for one’s employer. It is precisely these components that should be at the center of any effective reward system.

2.2 Effort

Previous research has thus identified merit and need of an employee to be a determinant of height of fair compensation for labor. Merit refers to the amount of previous effort one has previously undertaken in order to gain a specific skill-set for a job, for instance education or previous experience. Need refers to situational aspects which determine fixed (living) costs, such as amount of children or marital status. The higher the merit and need, the higher the amount of compensation which is deemed as fair, according to respondents (Alves & Rossi, 1978; Kelley & Evans, 1983; Kuhn, 2011).

We argue that this research is inherently flawed; the effort one has provided in the past is not necessarily relevant for the amount of value one creates currently. Rather it is the amount of effort one is currently providing. It is precisely this effort which will benefit one’s current employer. Previous efforts such as education are likely to positively influence the amount of value one can generate but ultimately the outcome of labor is determined by the current effort (Adams, 1963). This argument can be made more explicit by considering the following example: two students have studied mathematics and have both graduated from the same university with the same GPA. Suppose they were asked to solve random mathematical equations in two hours, we would expect them both to solve an equal amount of questions. However, if one decided to undertake more effort, say work for four hours, we would expect this person to solve more equations than the other. It would seem only fair that this person would be rewarded more than the other person who has invested less effort and thus solved fewer equations.

Effort remains a highly understudied phenomenon within the rewards paradigm. This is

especially odd considering contemporary reward systems are largely based on hourly wages which are, by definition, disconnected from the actual outcome of an employees’ effort (Baker et al, 1988; Dulebohn &

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Martocchio, 1998). Moreover research indicated that employees expect an annual pay increase based on merit, regardless of the actual performance of that year (Gerhart et al., 1995; Fehr et al., 2007). By implication, this contradicts the theoretical importance of the added value concept.

One particular study that investigated the relationship between job demands and innovative behavior and found the effort-reward relationship to be a moderating variable within this relationship. Thus, if rewards for effort were perceived as fair one would attempt to be more innovative (Janssen, 2000). Another research investigated the intention to reciprocate and found that this was determined by the effort provided rather than the outcome of that effort (Sorica, 2013). Another research found that increased effort is deemed to signal increased product quality, even when this extra effort did not actually improve the product (Kruger, Wirtz, van Boven, Altermatt, 2004; Morales, 2005).

2.3 Value creation

Value creation is essentially the purpose of any organization, regardless of what it produces. The organization that has the best value proposition in the eyes of it’s customers will have superior

performance. In order to achieve this a firm needs to be distinctively different from other organizations and provide a distinctively different offering. Theoretically it can do so by either increasing a buyers’ willingness-to-pay or by decreasing it’s opportunity cost (Brandenburger & Stuart, 1996). In reality, this means that it must offer a product which better meets customer needs than competitors or operate at a lower cost base (Peteraf & Bergen, 2003).

Given the theoretical importance of added value it seems logical that one would include the concept in determining appropriate reward for labor. In practice most reward systems do have a

performance based component as part of their compensation. For most occupations however, the size of variable pay is still significantly smaller than the relative size of base pay (Baker et al., 1988; Gerhart et al., 1995). Additionally, more recently in Europe the height of the variable pay for bankers is linked to the height of ‘base-salary’ (i.e. salary based on effort) through legislation to be at a 1:1 ratio or a highly exceptional 1:2 ratio with shareholders’ approval (European Commission, 2014).

Through research however signs are showing that some occupations, especially knowledge workers, are ever more demanding of a reward system that grants them an increased share of the fruits of their labor (Martin & Moldoveanu, 2003). It is expected that this trend will continue especially

considering that the growth in inflation-adjusted hourly compensation has lagged behind growth in labor productivity for the last several decades. In other words, the relative division of welfare has become skewed to favor the share of the businesses and their shareholders at the cost of employees (Martin & Moldoveanu, 2003; Fleck et al., 2011).

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Previous research indicates that most organizations determine the amount of reward through market pay surveys per specific job title (Gerhart et al., 1995). This is odd considering the fact that each employee is idiosyncratic in his/her added value to the organization. We argue that in order to achieve superior performance firms should compensate an employee relative to the amount of value created by that employee. What specific share of this added value is then considered to be fair compensation? Remarkably, this has not been researched previously.

2.4 Individual Characteristics

There are many individual characteristics at the basis of how one constitutes fairness perceptions. Kuhn (2011) empirically investigated the determinants of perceived fair wage inequality. Unsurprisingly, he finds that the more liberal a person, the less one favors redistribution of wealth by the state – and the more he favors wage inequality. Political preference, so he argues, is a good predictor of attitude towards wage inequality. This notion is also supported by other researches (Kelley & Evans, 1983; Berman et al, 1985; Linos & West, 2003).

Additionally, these motives are also partially driven by self-interest. The more one stands to benefit from redistribution the more one favors it and vice versa (Kuhn, 2011). In addition, one

continuously evaluates others with oneself, this effect strengthens with more congruency between the two in comparison (Pratto et al., 1994; Dornstein, 1988). Ariely (2009) found this effect to be cognitively hardwired – humans consistently take bad decisions because of it. Taken together, it is expected that one compares a hypothetical situation with one’s own and bases perceptions of fairness on this. Congruency is then important to consider in the research as well.

Social Value Orientation is also recognized by the literature as being indicative of fairness perceptions; the more sociable one is, the more likely one favors an egalitarianism (De Dreu & Boles, 1998; Van Lange, 1999). Social value orientation refers to a framework for understanding differences of perspectives and normative valuations. It categorizes any individual into one of three categories: pro-social, individualistic and competitive. Pro-socials are characterized by cooperation through which the combined value for all involved is maximized. Individualistic people are highly self-interested and only cooperate when it enhances their results, while disregarding the effect on others’ results. Competitively oriented people seek relative advantage over others. They will only engage in group activities if it makes them relatively more better off than the rest of the group. It is found that the more pro-social an individual is, the more he or she favors cooperation and, more importantly, equality (Van Lange, 1999; Murphy, Ackermann & Handgraaf, 2011).

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Further research has indicated that a respondent’s education also influences perceptions of fairness. The higher education one has enjoyed the more one favors wage inequality (Kuhn, 2011; Kelley & Evans, 1983; Linos & West, 2003). This effect can also be related back to self-interest; the more educated the more likely one is to gain a high wage and thus would benefit from an uneven distribution of wealth (Kuhn, 2011). Interestingly, education is also seen as a justification of a high reward; the higher educated a person the higher reward is considered as justified (Alves & Rossi, 1978).

This research attempts to explore the relationship between value created, effort and fairness perceptions. As indicated above, this research is the first that directly links these concepts to one another in order to explore the relationships between them. In order to explain the greatest amount of variance we shall include different moderators that were identified in the literature. Explicitly, this research attempt to answer the following question:

To what extent are fairness perceptions of rewards for labor dependent on value created and effort?

By answering this question we will provide insight into what the preferred determinant of fairness perceptions within reward systems is. It adds to the literature by creating a better understanding of how effort and value created influence the amount of reward that is deemed fair. In doing so, it creates a starting point for a more effective and economically sound reward system. This in turn allows for a better management of human resources and a more profitable business overall.

3. Conceptual framework

In the section below the hypotheses and theoretical framework will be presented. Firstly the conceptual framework that is assumed by this research will be discussed. Secondly, hypotheses with regard to effort and value creation will be presented. The section which follows discusses potential moderators identified by the existing literature that might influence the relationship of effort and value towards fairness

perceptions of rewards.

The conceptual framework that is basis for this research can be found below in Figure 1. It assumes that fairness perceptions are influenced by effort and value created within a certain job. This means that the more effort provided and the more value created the more fair a high reward is considered to be. Additionally, the model states these relationships are influenced by one’s political preference, social value orientation, congruency and education. The model serves as an illustration of the manner in which this research is setup. The concepts and arguments on which this model is based is described in the following sections.

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Figure 1: Conceptual framework

3.1 Effort & Value Creation

At the basis of this research lays equity theory and it is used to explain fairness perceptions. Equity theory states that an action or reward is seen as fair when the inputs match the outputs. Inputs can be anything ranging from education to effort. Similarly, rewards can be anything ranging from salary to social or formal recognition. According to the theory, the appropriate output is determined through benchmarking with a reference person or group. Moreover, these perceptions are normative. Inequity exists when one’s rewards do not match ones’ input in comparison to the reference group, as perceived by the observer (Adams, 1963; Huang, Lu, Tang & Huang, 2004). Equity theory has provided the fundaments for distributive justice theory, which is similarly relevant to this research.

Distributive justice theory is similar to equity theory with an important distinction. Whereas equity theory requires one to provide inputs in order to have any explanatory significance distributive justice theory also includes the allocation of resources, regardless of one’s input. Whether one is directly involved in the generation of these resources is a secondary consideration (Cook & Hegtvedt, 1983). To make this distinction more explicit, consider someone on welfare who hasn’t worked in the past and isn’t working at the present, for whatever the reason. Assume ‘work’ is the only input this person can provide. According to equity theory it is unfair for this person to receive any welfare as he or she has not provided any input. Distributive justice concludes the opposite as this person is part of society and that in itself grants the right to a piece of the wealth generated by society, or welfare.

This is an important distinction between the two theories. Equity theory states that input must match output thus it can be considered that the reward one gets for labor is directly related to the outcome of that labor. Conversely, distributive justice theory states that anyone has a right to the output regardless of the outcome, or actual input, of labor. As such it is interesting to see whether respondents of this research appreciate value created (i.e. equity) more than effort provided (i.e. distributive justice) or vice versa.

A commonality between these theories is that they stress the importance of equality of rewards in relation to their reference person or group (Adams, 1963; Cook & Hegtvedt, 1983). In such comparison,

Political Preference

Effort

Value Created

SVO Congruency Education

Fairness

Perceptions

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the value that is actually generated and the undertaken effort are assumed to be equal among those who are contributing as well, which is unlikely at the least. Another important criticism states that distributive justice theory is illusory due to the fact that each of the inputs is inherently subjective as it is determined by the one undertaking the effort (Wegener, 1987). We consider these to be valid criticisms which we shall overcome in this research by undertaking an experiment with four scenarios in which effort and value are manipulated (c.f. chapter 4).

In line with these theories we then expect that the higher one’s inputs, the higher the absolute amount of reward is deemed justified. Or as Bloom (2004; p.150) states “if someone does twice the work, distributive justice principles would argue that the person deserves more compensation, perhaps even twice the pay”. This leads us to our first hypothesis:

H1: The higher the effort provided, the more fair a higher reward is considered to be.

By using similar argumentation we would expect an increase in value created by the employee to be coupled to an increased amount of value to be appropriated to this employee. The logic here is that value created can be seen as a function of inputs such as education (Adams, 1963; Alves & Rossi, 1978; Kelley & Evans, 1983). As a result, the rewards should be increased accordingly for a situation of inequity to be prevented. As a result our second hypothesis is:

H2: The higher the amount of value created, the more a higher reward is considered to be fair.

There are however some arguments that limit this relationship. Previous research on fairness perceptions has found that there is a certain amount of minimum reward that is necessary, regardless of the inputs provided (Kelley & Evans, 1983; Alves & Rossi, 1978). On the opposite side research has implied that there is a ceiling on what reward can be justified. According to the diminishing marginal utility of income rewards which supersede a certain subjective limit will cause no additional happiness (Easterlin, 2005; Layard & Mayraz, 2008). It is then likely that any reward gained above this limit will not be deemed as fair. When regarding the morality of CEO compensation, Harris (2009) argues that current CEO compensation in the U.S. exceeds any justification due to its gross & comparative magnitude.

It is important to stress that this limit is subjective and thus differs from one person to another (Wegener, 1987; Kuhn, 2011). Moreover, it also differs from one culture to another (Kelley & Evans, 1983; Linos & West, 2003). The most recognized individual characteristics will be included in this research, which will be described below in section 3.2.

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One of the main goals of this research is to determine whether fairness perceptions are justifiable based on effort, added value, or both. The other goal is to give more clarity on what factors influence this fairness division. Theoretically both components are supported by some valid and powerful arguments yet to our knowledge there are no useable researches to shed light on this relationship previous to this writing.

3.2 Potential moderators

Within the value/effort paradigm there can be several moderators that influence the relationship with regard to fairness perceptions. These shall be discussed in the following paragraph.

One factor that is likely to moderate the relationship is the respondents’ political preference. Previous research on fairness perceptions of the distribution of wealth in the United States in the 1980’s found that older more politically conservative respondents preferred considerably higher compensation for elite occupations than those of a more progressive persuasion. Interestingly enough, these

conservative respondents did not prefer lower pay rates for those in lower-status occupations. High-status jobs are considered high status because of the relative amount of responsibility an individual has within the function (Kelley & Evans, 1983). Logic would suggest that the more responsibility a person has the more he or she gets evaluated on their performance rather than their effort.

In addition, recent research into redistribution of wealth by the state found that people who believe that a low level of (wage) inequality is acceptable to favor redistribution by the state. What is more is that people who think that effort undertaken prior to obtaining the job, such as education and experience, and acquired skills should be important for wage determination favor more inequality of wages (Kuhn, 2011). In line with this reasoning we would expect politically conservative, or liberal, people to appreciate value over effort with regard to their fairness perceptions. This becomes more evident when we consider that effort can be increased by any one worker regardless of capabilities and can therefore be considered to be more of an equal opportunity than value creation, which is more dependent on other factors such as skill. This is also supported by prior research which states that the more inequality is favored, the more meritocratic their fairness perceptions are (Pratto et al., 1994). As a result, we would expect political preference to moderate whether effort or value is the more influential determinant of fairness perceptions.

It is also important to consider the context of this political preference as well. There are great cultural differences between nations which, in turn, affect the political differences. For instance, the United States has a culture based more on meritocracy and individualism than Norway, which has an extensive social system with a multitude of social securities and grants (Berman, Murphy-Berman & Singh, 1985; Linos & West, 2003; Sachweh & Olafsdottir, 2010). In addition, Sachweh & Olafsdottir (2010) found that the higher the perceived inequality of a country the more this inequality is perceived as

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fair. We expect this cultural heritage to influence fairness perceptions as well: the more individualistic, thus liberal, the culture the more value created as opposed to effort is the preferred mechanism of fairness perception. As such we expect to find support for the following hypothesis:

H3: Liberals consider rewarding value created fairer than rewarding effort.

In a similar vein as political preference one can argue that social value orientation can explain some of the variance of the relationship between effort, value and fairness perceptions. Research has indeed found that social value orientation is a significant predictor in determining social attitudes, among which are fairness perceptions. The more prosocial one is the more one favors egalitarianism (Pratto et al.1994). Extending these findings to our research will suggest that prosocials will favor effort over value due to it’s more egalitarian basis and the individualists to do the opposite; effort can be increased by any one regardless of their skill set while the creation of additional value is likely to require more than just effort alone.

Although political preference and social value orientation seem similar they are distinctively different. Previous research however indicated both political preference as well as social value orientation to have a distinct effect on fairness perceptions. Moreover, both concepts were researched within different contexts which might not be interchangeable (Kelley & Evans, 1983; Kuhn, 2011; Pratto et al., 1994; Van Lange, 1999). We have therefore chosen to treat these both as distinct variables, leading to the following hypothesis:

H4: Pro-socials will prefer rewarding effort over value created.

Expected levels of reward are derived from referential comparisons with others of a general social type. Strikingly, it is here that issues of distributive justice arise according to Shepalak & Alwin (1986: p32). Empirical research found that the most important frames of reference for an employee within a certain organization are average earnings of all employees, inside and outside the organization, as well as those performing a similar occupation (Dornstein, 1988; Sweeny, McFarlin & Inderrieden, 1990; Sachweh & Olafsdottir, 2010). Interestingly, employees will compare themselves with those similar in skills and productive contribution (Dornstein, 1988). According to the theory then, average pay of workers and the corresponding contribution must be included in the frame of reference. In addition to this, research has indicated that respondents are prone to compare the situation described in the vignette with themselves (Sachweh & Olafsdottir, 2010; Kuhn, 2011)

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Congruency within one’s own situation then becomes important to consider. How much does one work him/herself, how much value does he or she create, what kind of job does one do? Previous research on redistribution of welfare has indicated that (potential) beneficiaries are more likely to favor

redistribution than the contributors (Linos & West, 2003). Moreover, Kuhn (2011) states that self-interested motives as well as perceptions and normative beliefs are important in explaining observed differences in the desire to equalize market wages. What is more is that in previous research insider-outsider differences have been observed with regard to fairness perceptions. An insider is someone who works and contributes to the social system while an outsider does not work and does not contribute (Sachweh & Olafsdottir, 2010; Kuhn, 2011). Interestingly, outsiders do tend to have deeply rooted beliefs on fairness perceptions within organizations they are not part of (Bloom, 2004). Considering the above we expect congruency with ones’ own profession compared to the situation described in the vignette to moderate the relationship on fairness perceptions. Own profession should give us an indication of the amount of value created. For instance, a cleaner is likely to create less value than a strategy consultant. We expect that the more effort one provides in his/her job the more he or she favors effort to be the determinant of reward. The more responsibilities the respondents’ job has however, the more he or she will favor value over effort. The vignette that is used in this research describes a well-earning CEO (cf. section 4). Relating back to self-interest and comparison, this leads us to the fore last hypothesis:

H5: The more congruent one’s own situation with the vignette the more one favors value over effort.

The last potential moderator identified by previous studies is education of respondents (Kelley & Evans, 1983; Linos & West, 2003). For instance, it was found that those individuals that were well-educated generally favor more pay for high-status occupations, each year of education of increasing legitimate income by 1%. In addition, social class seems to influence the amount of appropriate pay (Kelley & Evans, 1983). Moreover, the more education respondents had enjoyed, the less favorable position was taken for redistribution of wealth by the state. However, this effect was lessened after college (Linos & West, 2003). This suggests that the more educated the individual, the more value is preferred over effort. This culminates to our final hypothesis:

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4. Methodology

In the following section the methodology that is employed for this study will be presented. Firstly the method in which data was gathered will be discussed. After which, the sample and it’s characteristics are described. Lastly, the specific research design will be presented.

4.1 Method

Vignette method was chosen in order to obtain the necessary data to test the hypotheses. This method employs vignettes which describe a hypothetical situation through which an opinion or thought process is asked from the respondent. Within vignettes it is possible to manipulate a number of independent

variables and in doing so we are able to determine the effect of these changes in variables on the

dependent variable (Saunders & Lewis, 2011; Jasso, 2006). It was explicitly mentioned in the cover letter that these responses were confidential and anonymous, minimizing the social desirability of answers (Saunders & Lewis, 2011).

The vignette described a hypothetical situation of a CEO of a medium-sized enterprise who introduced a new strategy which created [high/low] value while spending [high/low] effort. This resulted in a fixed reward. We also added that this reward corresponded with the average within the sector conditioning for a same frame of reference for all (Dornstein, 1988; Kahneman, 2011). To this end we have also specifically chosen to describe a CEO as most respondents are unable to directly relate to this (Dornstein, 1988). This allows us to be able to generalize our findings to a maximum extent.

In our research we asked respondents how fair a fixed reward was thought to be while

manipulating the effort provided and the value created. As such we randomly distributed four different vignettes with high and low effort and value created in order to find the variation in fairness perceptions. Respondents were asked to rate their fairness perception on a 7-point Likert scale after which they were asked explicitly what they thought rewards should be most dependent on based on a 5-point Likert scale; either effort, value or both equally. To check the validity of our vignette respondents were asked to what extent a CEO could influence profits of a company, of which less than 2% replied that this was unlikely. This proved that the presented vignette is valid (Saunders & Lewis, 2011; Rutte & Messick, 1995).

Additionally, we posed two questions to check for political preference. The questions asked the respondents’ opinion on the current distribution of income in their country of residence and whether or not the respondents think it is the governments’ responsibility to reduce the differences between high and low incomes (cf. Appendix).

To measure SVO we adopted the “SVO Slider” method developed by Murphy, Ackermann & Handgraaf (2011; p.772), which asks respondents to hypothetically allocate money between oneself and an anonymous other person. Within each allocation one can ‘sacrifice’ some of the maximum personal

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payout to benefit the others’ payout. This allows a classification of each respondent based on how ‘social’ the allocations (i.e. the extent of sacrificing).

A number of various questions asked respondents about one’s profession, such as work hours, work experience, (management) position and industry. This allowed us to create an image which could be compared to the vignette – in order to determine congruency. From these variables we would later create a dummy variable. Additionally, education for hypothesis 6 was asked through highest completed education and what area so as to be able to control for study directions.

The survey was created conform the outline presented by Jasso (2006) for vignette studies. This outline stipulates the necessary steps in order to create the most valid vignette; selection & measurement of factors/vignette characteristic, full factorial vignette characteristics, deletion of logically impossible vignettes, drawing random samples from the vignette population and shuffling the vignette pack.

4.2 Sample

Firstly, we conducted a pilot with peers to see if the survey would create relevant results and to receive criticisms. The survey was tweaked after discussions to incorporate legitimate comments and was tested afterwards so as to check whether the survey was improved. This is conform the method outlined by Saunders & Lewis (2011). Our sample meets the requirements set by Jasso (2006) with regard to sample size; each vignette needs to be responded by minimally 40 – 60 respondents (c.f. table 2). Additionally, the sample was randomly gathered through Amazon Mturk, increasing generalizability (Saunders & Lewis, 2011).

The sample (n=233) was mostly gathered through the use of Amazon Mechanical Turk in the U.S. and through acquaintances. The average age is 32 years. 59.2% of the sample is male. A significant part of the sample studied Business & Economics (26.6%) and IT (14.6%), while the remainder was diversified. The biggest part of the sample have completed a Bachelors’ degree (38.2%) while 28.3% has completed High School or equivalent, 15.5% has completed a Vocational/Technical school and 14.2% of the respondents finished a Masters’ degree. Most respondents have less than ten years work experience (60.8%) and most spend 40 hours or less, weekly, on their jobs (81.1%) with an average of 29.4hours per week spent on the job. The majority of respondents is employed (57.9%), while 16.7% are students and 16.3% is self-employed. A significant part of the sample earns less than the median of U.S. income ($53.046, 2014 U.S. Census); 68.2% earned less than $50.000, 42.1% of which earns less than $30.000 on yearly basis – most of which are students. Relatedly, just over half (51.5%) indicated that they have been in a situation where their reward was dependent on outcome of the task, i.e. had bonus experience.

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4.3 Design

Effort and value provided were manipulated in each of the vignettes, totaling four, to allow for analysis of their effect on the dependent variable; fairness perceptions. The vignette describes a hypothetical CEO of a medium sized enterprise who works either 40 or 80 hours and introduces a new strategy resulting in either $200.000 or $400.000 in extra profit for the company. His total compensation is fixed at $300.000.

Vignette Imagine a CEO of a medium sized enterprise who spends [low/high effort] hours per week working. This year, he has introduced a new strategy that has resulted in an extra profit of [low/high value] for the company. His total compensation equals $300.000 for that same year. This corresponds with the average in the sector.

Effort Low High

40 hours per week 80 hours per week

Value created Low High

$200.000 $400.000

Question How fair do you rate this reward?

Table 1: Vignette design (c.f. Appendix)

Following the vignette six different slider allocations were asked based on the method designed by Murphy et al. (2011). This method allows each respondent to be classified into either one of four categories based on their level of altruism versus individualism. Following which the respondents were asked about their political preferences and relevant demographic- and background information.

5. Results

Below the results of the study will be presented. Firstly, the sample characteristics and correlation matrix is shown. Afterwards the hypotheses will be tested and the findings are discussed.

5.1 General Descriptives

The sample of n=233 consists of 138 males (59.2%) and 95 females (40.8%). The average age is 32 years (σ = 10.47 years). Most of the respondents live in the U.S.A. (n=203, 87.1%), while 10.7% (n=25) are living in the Netherlands and the remainder varies. Most respondents are employed (57.9%) and most have between ten and twenty years work experience. Additionally, most respondents have finished a Bachelors’ degree (38.2%) while 28.3% indicated high school to be the highest education completed. The most studied discipline is Economics & Business (26.6%) followed by IT (14.6%). Most respondents earn between $50k & $75k (17.6%) and just over half the respondents indicated to have experienced a

situation in which their reward was dependent on their output (51.5%). The largest part of respondents works as support staff (32.6%) or administrative staff (18.9%) in a lot of varied industries, other (56.2%)

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being the most marked out of twenty outlined options. Lastly, most respondents are prosocial (58.8%). All relevant variables are summarized in Table 2 below.

n % Cum. n % Cum.

Gender Current income

Male 138 59.2% 59.2% Rather not say 10 4.3% 4.3%

Female 95 40.8% 100.0% < $10.000 23 9.9% 14.2% $10.000 > $19.999 33 14.2% 28.3% Main occupation $20.000 > $29.999 32 13.7% 42.1% Student 39 16.7% 16.7% $30.000 > $39.999 38 16.3% 58.4% Employed 135 57.9% 74.7% $40.000 > $49.999 23 9.9% 68.2% Self-Employed 38 16.3% 91.0% $50.000 > $74.999 41 17.6% 85.8% Unemployed 18 7.7% 98.7% $75.000 < $99.999 17 7.3% 93.1% Other 3 1.3% 100.0% $100.000 < $150.000 13 5.6% 98.7% > $150.000 3 1.3% 100.0% Work Experience

< 3 years 43 18.5% 18.5% Bonus Experience

3 > 5 years 16 6.9% 25.4% Yes 120 51.5% 51.5%

5 > 10 years 56 24.0% 49.4% No 113 48.5% 100.0%

10 > 20 years 82 35.2% 84.6%

> 20 years 36 15.4% 100.0% Industry role

Upper Management 10 4.3% 4.3%

Highest Education Middle Management 30 12.9% 17.2%

High school/equivalent 66 28.3% 28.3% Junior Management 39 16.7% 33.9% Trade/Technical school 36 15.5% 43.8% Administrative Staff 44 18.9% 52.8%

Bachelors’ degree 89 38.2% 82.0% Support Staff 76 32.6% 85.4%

Masters’ degree 33 14.2% 96.1% Student 34 14.6% 100.0%

Doctoral degree (PhD) 1 0.4% 96.6%

Professional degree 5 2.1% 98.7% Industry

Other 3 1.3% 100.0% Retail 32 13.7% 13.7%

IT 26 11.2% 24.9%

Study Background Finance & Insurance 24 10.3% 35.2%

Economics & Business 62 26.6% 26.6% Education 20 8.6% 43.8%

IT 34 14.6% 41.2% Other 131 56.2% 100.0%

Psychology 18 7.7% 48.9%

Other 118 51.1% 100.0% SVO

Prosocial 137 58.8% 58.8%

Individualist 96 41.2% 100.0%

Table 2: General Descriptives

Each respondent was asked to indicate on a 7-point Likert scale how fair the reward was perceived in one of the four scenarios. These scenarios were randomly distributed among participants, conform the method outlined by Jasso (2006; p. 340). Afterwards a question was asked to indicate on a 5-point Likert scale what they thought reward should be most dependent on; either effort, outcome or both. The results of which are summarized in Table 3 below:

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Vignette 1 Vignette 2 Vignette 3 Vignette 4 Low Effort, Low Outcome High Effort, Low Outcome Low Effort, High Outcome High Effort, High Outcome

How fair do you rate this reward?

1. Very Fair 16.7% 5.9% 8.6% 13.8% 2. Fair 31.8% 43.1% 27.6% 36.2% 3. Somewhat Fair 21.2% 27.5% 12.1% 13.8% 4. Neutral 7.6% 5.9% 20.7% 8.6% 5. Somewhat Unfair 13.6% 7.8% 24.1% 19.0% 6. Unfair 7.6% 2.0% 5.2% 5.2% 7. Very Unfair 1.5% 7.8% 1.7% 3.4% Mean 2.98 3.04 3.47 3.12 SD 1.60 1.59 1.54 1.68

What should reward be most dependent on?

1. Solely on effort 1.5% 2.0% 0.0% 0.0%

2. Mostly dependent on effort & a significantly smaller part dependent on outcome

16.7% 11.8% 12.1% 17.2%

3. On both effort & outcome equally 53.0% 62.7% 55.2% 56.9%

4. Mostly dependent on outcome & significantly a smaller part dependent on effort

27.3% 21.6% 29.3% 24.1%

5. Solely on outcome 1.5% 2.0% 3.4% 1.7%

Mean 3.11 3.10 3.24 3.10

SD 0.75 0.70 0.71 0.69

Table 3: Fairness- and effort/reward perceptions

5.2 Correlations

The correlation matrix can be found below. Several variables have been transformed into dummy variables: Effort importance (0 = not most important, 1 = most important), Outcome importance (0 = not most important, 1 = most important), Prosocial (0 = individualist, 1 = prosocial), Gender (0 = male, 1 = female), High income (0 = low income, 1 = high income), Political preference (0 = liberal, 1 = democrat). Additionally, a dummy variable is created out of multiple other variables to indicate whether a respondent is similar in profession to the situation described in the vignette.

From the correlation matrix it can be read that fairness perceptions are positively correlated with bonus experience (r = 0.142, p = 0.031) which means that if a respondent has had the total reward dependent on outcome of their work they favor a higher reward. Additionally, effort importance seems to be negatively correlated with work experience (r = 0.152, p = 0.021) indicating that the less experienced respondent favors a reward based on effort. Moreover, outcome importance is negatively correlated with gender (r = -0,266, p = 0.011) which means that men favor rewards based on outcome more than women do. Interestingly, outcome importance is positively correlated with Business & Economics (r = 0.188, p =

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0.004) meaning those who are in this study direction appreciate rewards based on outcome more than other respondents from other disciplines. In addition the matrix shows that age is positively correlated with being prosocial (r = 0.151, p = 0.021) which corresponds with the findings of Kelley & Evans (1983) that the older people get the less altruistic they become. Interestingly work experience is positively correlated to a prosocial orientation (r = 0.138, p = 0.036), thus the more work experience one has the more likely this person is to be prosocial. Political preference is negatively correlated with a high income (r = -0.141, p = 0.031) stating that the more income one has the less likely one favors redistribution by the state. Adding to this, high income is positively correlated with high education (r = 0.249, p = 0.000) confirming that higher education leads to a higher income. Moreover, high income was positively

correlated with Business & Economics, suggesting that this discipline leads to a higher income than other disciplines (r = 0.132, p = 0.045). Another interesting observation is that employee is positively related to political preference (r = 0.133, p = 0.006) which suggests that the respondents working for a boss are more likely to favor redistribution by the state than those that do not. Table 4 on the following page displays the matrix.

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 1. Fairness Perception 1 2. Effort Importance .109 1 3. Outcome importance -.040 -.266** ₁ 4. Gender (1 = female) -.027 .008 -.166* ₁ 5. Age -.078 -.110 .068 .215** ₁ 6. Work Experience -.104 -.152* _.065 _.160* _.911** ₁ 7. Bonus Experience .142* _.037 _-.067 _.121 _.032 _.018 ₁ 8. High Income .094 -.037 .090 .109 -.017 -.065 -.072 1

9. Business & Economics .032 -.123 .188** _-.164* _.041 _-.016 _-.098 _.132* ₁

10. Employee .052 -.093 .065 .052 .023 .054 .079 .096 .179** ₁ 11. Liberal -.072 -.099 -.045 -.004 .038 .077 -.003 -.141* -.026 .133* 1 12. Prosocial .042 -.101 -.063 .127 -.151* _.138* _-.008 _-.066 _-.029 _-.042 _.090 ₁ 13. Congruency .115 -.001 .125 -.010 -.060 -.071 -.010 .583** _.167* _.452** _-.066 _-.140* ₁ 14. High Education .052 -.006 .086 .116 -.038 -.122 .077 .249** _.140* _.265** _-.058 _-.071 _.337** ₁ *. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

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5.3 Hypotheses testing

In order to test the hypothesis we ran multiple binary regressions. The results of these regressions can be found in Table 5 and includes all variables relevant to this research. The dependent variable, fairness perception, is a dummy variable created to benefit the regression analysis (Jasso, 2006). As such it is either ‘1’ for any positive response including neutral or ‘0’ for any negative response. The independent variables, effort and outcome, as well as the moderating variables, liberal, prosocial, congruency and high education have been standardized for the regression. This is in accordance with the method outlined by (Field, 2013; Saunders & Lewis, 2011). The moderators are all dummy variables created for the regression. Congruency specifically is a dummy variable created out of several variables and one gets rated congruent (=1) when all the following conditions are met; is in management, has high income and work more hours than the mean of the sample.

The first model explains depicts the relationship between the various control variables and fairness perceptions. It explains 8.4% of the variance within this relationship however is statistically insignificant (r = 0.084, p = 0.144). In model two the moderators have been included. The variance explained increased to 10% however remains statistically insignificant (r = 0.100, p = 0.243).

Model three tests the main hypotheses of this study, respectively; the higher the effort provided, the more fair a higher reward is considered to be and the higher the amount of value created, the more a higher reward is considered to be fair. We find no evidence to support hypothesis one and is therefore rejected (β = 0.104, p = 0.524). We cannot conclude that more effort leads to a higher justified reward. Similarly, we find no significant evidence for hypothesis two either and is also rejected as a result (β = -0.247, p = 0.132). Although insignificant the direction of the β remains interesting to note. The results suggest that the more value one creates the less reward is deemed justified. From an economic reasoning this is impossible to explain. One possibility is that higher value created might be linked to less ‘need’ for a high reward. If one can instantly create a high value it is likely that he or she has already earned a lot of money previously and thus has less need for a high reward (Kelley & Evans, 1983).

In models four to eight the remaining hypotheses are tested. The moderating effects are tested using interaction variables. In doing so we were able to find the probability of one preferring effort over outcome or vice versa – and under what conditions (Field, 2013; Saunders & Lewis, 2011).

Hypothesis 3, Liberals consider rewarding value created fairer than rewarding effort, is tested using a dummy variable which is computed from several questions in the survey to indicate a favorable (=’0’) or unfavorable (=’1’) attitude towards redistribution of welfare by the state. The regression yields insufficient evidence to support this notion. It suggests mainly that liberals prefer outcome over value,

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however the moderation effect is insignificant for both effort (β = 0.024, p = 0.889) and outcome (β = 0.273, p = 0.129) respectively.

The fourth hypothesis, pro-socials will prefer rewarding effort over value created, is tested by using a variable indicating SVO conform the method designed by Murphy et al. (2011). This method categorizes a person in one of four categories depending on their level of altruism. The results suggest a negative relationship for effort and prosocials (β = -0.154, p = 0.361). Conversely, outcome is suggested to have a positive effect on prosocial’s perceptions of fairness (β = 0.160, p = 0.334). This is the opposite of what we expected. The results are however insignificant and as such hypothesis four is also rejected.

There is also insufficient evidence to support the fifth hypothesis, the more congruent one’s own situation with the vignette the more one favors value over effort. The regression finds a positive effect of rewarding effort (β = 0.166, p = 0.382) as well as outcome (β = 0.209, p = 0.242) however these are both statistically insignificant. This leads us to also reject hypothesis five.

Although the results suggest in favor of hypothesis six the relationship is found to be statistically insignificant. The regression hints that the higher educated do favor effort less in determining their fair reward than their less educated peers (β = -0.044, p = 0.791). Additionally, it suggests that outcome is rather used as a metric the more higher educated one becomes (β = 0.098, p = 0.558). As indicated, the results were insignificant and thus no evidence has been found to support hypothesis six; the higher educated respondent favors value created over effort, and is thus also rejected.

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Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8

B Sig. B Sig. B Sig. B Sig. B Sig. B Sig. B Sig. B Sig.

Effort Importance .772 .152 .781 .154 .776 .156 .705 .204 .820 .136 .867 .119 .761 .165 .875 .125 Outcome Importance -.050 .892 -.040 .915 .007 .985 .046 .904 -.013 .974 .084 .828 .043 .910 .193 .637 Gender -.183 .602 -.208 .564 -.167 .645 -.126 .729 -.152 .679 -.135 .711 -.159 .661 -.054 .883 Age .007 .860 .003 .945 -.003 .940 -.003 .932 -.007 .868 -.004 .920 -.001 .978 -.007 .870 Work Experience -.025 .552 -.022 .609 -.015 .729 -.013 .761 -.011 .808 -.015 .737 -.017 .697 -.013 .781 Bonus Experience .767 .019 .766 .020 .777 .019 .728 .030 .736 .028 .740 .028 .776 .020 .623 .071 High Income .523 .153 .341 .456 .306 .507 .311 .498 .283 .543 .366 .434 .313 .498 .367 .440 Employee .252 .441 .193 .611 .161 .672 .158 .681 .139 .717 .164 .667 .154 .686 .123 .753 Economics .129 .738 .147 .709 .118 .766 .087 .827 .159 .693 .103 .795 .129 .745 .104 .802 Liberal -.119 .479 -.120 .480 -.175 .337 -.115 .501 -.138 .422 -.121 .477 -.184 .320 Prosocial .229 .162 .223 .176 .214 .199 .194 .250 .260 .122 .225 .174 .226 .194 Congruency .153 .524 .184 .448 .162 .503 .197 .419 .185 .458 .181 .457 .150 .546 High Education -.007 .968 -.030 .865 -.030 .866 -.029 .871 -.023 .899 -.049 .787 -.036 .846 Effort .104 .524 .087 .594 .113 .494 .135 .423 .107 .515 .119 .489 Outcome -.247 .132 -.281 .097 -.257 .121 -.220 .188 -.246 .136 -.264 .131 EffortxPolitcalPref .024 .889 .064 .716 OutcomexPoliticalPref .273 .129 .298 .105 EffortxSVO -.154 .361 -.166 .349 OutcomexSVO .160 .334 .168 .332 EffortxCongruency .166 .381 .187 .374 OutcomexCongruency .209 .242 .298 .132 EffortxEducation -.044 .791 -.143 .429 OutcomexEducation .098 .558 .031 .861 χ2 _13.424 _16.123 _18.667 _21.115 _20.295 _20.917 _19.054 _26.249 df 9 13 15 17 17 17 17 23 Sig. .144 .243 .229 .221 .259 .230 .325 .289 Nagelkerke R² .084 .100 .115 .129 .125 .128 .117 .159

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5.4 Additional results

The only statically significant result in the model is bonus experience in relationship to fairness perceptions. The research indicates that when one is currently experiencing, or has experienced, a situation in which the total reward appropriated was dependent on the outcome the fairer one perceives a high reward to be (β = ~0.750, p < 0.05).

6. Discussion

In this section the interpretation of the results will be discussed; we will discuss possible explanations of the lack of evidence. After which the limitations of this research and with that possible avenues for further research shall be considered.

6.1 interpretation of results

The fact that all results were statistically insignificant is surprising considering the suggestions from contemporary literature. Each hypothesis shall be discussed below and we shall contemplate on possible reasons for the lack of results.

Both hypothesis 1 and 2 were rejected – there has been no support for either higher effort of higher value created leading to increased fairness perceptions. This contradicts the contemporary literature that exists on the subject. Morales (2005) for instance found that when a product was

communicated to have cost more effort for a company to make the product quality was perceived to be higher than a comparable product – regardless of actual influence on quality. Moreover, research indicated that people are more influenced by effort when the quality of the object was difficult to ascertain (Kruger et al., 2004). The effort in itself thus was enough to influence or reinforce the perceptions of quality. Additionally, research in psychology found that workers withdraw effort when their perceptions of fairness fall short of what is perceived as fair (Akerlof & Yellen, 1990). The opposite effect seems logical, that one rates fairness of reward based on the effort provided, especially when considering equity theory on which this research was based.

It was similarly surprising that value created did not yield any significant relationship towards fairness perceptions. It follows basic economic logic that one gets rewarded based on their output. It is only when output is difficult to measure that another metric, such as team-output, is relevant (Gerhart et al., 1995). Moreover, considering the ever increasing complexity of knowledge-based jobs this becomes even more evident as comparisons versus other jobs are more difficult to make. And, as a result,

employees are more demanding of rewards which reflect their achievements (Martin & Moldoveanu, 2003). This effect is supported by the fact that this increased complexity inherently increases the

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bargaining power of specialty employees versus the employer (Brandenburger & Stuart, 1996; Bowman & Ambrosini, 2000).

The lack of effect found in this research may be due to a variety of reasons. A potent reason could be the fact that even though the arguments in favor of the investigated effects are rational while the actors are inherently irrational (Ariely, 2009; Kahneman, 2011). There is much to be said for bringing reward systems closer to an economic logic from the economic viewpoint. In reality however, research has shown that people compare themselves to their peers (Dornstein, 1988; Ariely, 2009). For instance, Ariely (2009) researched the relative importance of income by asking respondents whether they preferred a $100.000 salary while their college classmates were earning $250.000 or a situation in which the respondent was earning $50.000 while their antagonists were earning $75.000. The results indicated that roughly 80% of the respondents preferred the latter over the first. These results stand to no logical reasoning as in such situation one is worse off in absolute terms. It may be then, that this research is ‘ahead of it’s time’ and that fairness perceptions based on relativity are much more ingrained than an economic would like and research into this concept will become useful when this stress on relativity relaxes.

Another explanation is that the vignette might be difficult to relate to for most respondents due to the fact the CEO is the most unique position one can attain within any company. Additionally, two extremes were chosen for effort (40/80hours) and value created ($200.000/$400.000). Previous research indicated that one evaluates a situation relative to others within the same context however this context may be more complex than assumed by this research (Dornstein, 1988; Sweeny et al., 1990). Although the vignette did explicitly state that the CEO’s reward corresponded with the average in the sector so as to include the frame of reference this might however been a wishful oversimplification in hindsight. Other researches namely indicate that one continuously relates a particular situation to one’s own situation, especially when lacking a relevant frame of reference (Ariely, 2009; Kahnemann, 2011). In such situation, one tends to evaluate fairness perceptions of rewards relative to one’s own position in the reward hierarchies (Wegener, 1987).

An argument which follows this reasoning which might have contributed to the lack of results is that of the normative ceiling on reward. Some scholars argue that CEO compensation is too high from a normative standpoint (Bloom, 2004; Harris, 2008). This point of view has gained traction due to the financial crises and accompanying political responses that followed it, such as the institution of ceiling on variable pay for bankers in the EU (Cook & Hegtvedt, 1983; European Commission, 2014). The reward of $300.000 used in the vignette was transferrable to a real-life situation so as to counter limitations of

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previous researches but it might be that this reward was evaluated too high from a normative rather than realistic standpoint (Baker et al., 1980).

Another, yet more unlikely, factor might be the relatively small sample of this study. Although the sample met the requirements set forth by Jasso (2006) for vignette studies more respondents will reduce statistical deviations (Saunders & Lewis, 2011; Kahnemann, 2011). Additionally, cultural differences between respondents might have amplified this effect as just shy of 13% of the sample was not from the U.S.A. Various researches indicated that cultural differences have a profound effect on perceptions of fairness possibly further diluting the sample (Kuhn, 2011; Sachweh & Olafsdottir, 2010). The sample might have also consisted of too many differing backgrounds leading to an even greater divergence (Saunders & Lewis, 2011). Any future research is recommended to increase sample size.

Some possible pitfalls with regard to the measurement and/or operationalization of the moderators can also be identified as none of the supporting hypothesis were supported either. The two questions specifically designed to measure whether one was in favor of redistribution by the state passed the factor analysis test and were seemingly well designed so as to specifically ask to only this component of political preference (Saunders, 2011). This created a useable simplification identified in the literature (Pratto et al., 1994). One possible flaw is that the question referred to the country of residence which was not the same for all respondents. As indicated above, this might have diluted the relationship due to cultural differences (Kuhn, 2011; Sachweh & Olafsdottir, 2010). The arguments for political preference influencing fairness perceptions are widespread and observable in everyday politics – the more

liberal/republican parties are in favor of market economics and accept whatever rewards this result in (Kuhn, 2011).

The measuring of the SVO followed the method developed by Murphy et al. (2011) which has passed scientific scrutiny. Thus the specific research design of this research might have influenced the relationship due to the aforementioned factors. It might also be that SVO is not directly related towards the height of a reward or the input/output required to gain these rewards. The literature does however raise a compelling argument against this reasoning (cf. section 3.2).

Admittedly, own profession and congruency herein is difficult to determine due to the vast number of differences that can be observed. This becomes even more explicit when considering the increasing complexity of occupations (Martin & Moldoveanu, 2003). In order to react to this complexity this research measured several separate variables which we perceived as important and enter them as such in the analysis. Although no alternatives exist to our knowledge, this method might be inherently flawed due to its ‘unscientific’ (i.e. untested) basis (Saunders & Lewis, 2011).

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In order to measure education it was chosen to ask respondents for their highest level of education and to control for field of education. Although this is considered a valid conceptual approach it might have provided flawed results when transferred to the sample used in this research (Saunders & Lewis, 2011). Consider, for instance, the fact that 28.3% had high school as highest completed education which slightly contradicts the U.S. statistics, even when controlling for current students (2014 U.S. Census).

6.2 Limitations & recommendations for further research

The first limitation future research is to overcome is to include a relevant frame of reference. As discussed above, although the frame of reference in this research is conceptually sound and practical it might not be ideal for research. A possible solution is to explicitly compare a person A with a person B while

manipulating only the effort and reward components of one of the two. In doing so the frame of reference is provided and is less likely to be idiosyncratic (Sweeny et al., 1990). The unintended consequences is that this design implicitly limits the practical implications. If a manager wants to modify the salary of say employee A the manager must also include a frame of reference against which to benchmark this

modification. This can lead to increased perceptions of unfairness when differences between the two are ill understood (Bloom, 2004). Including a more relatable frame of reference will also reduce the

possibility of the normative argument against too high reward (Harris, 2003).

Another potential limitation of this research is the hypothetical nature that is at the basis. There tends to be a divergence of what one states to do in a hypothetical situation versus what one actually does. As such, the most valid research would distribute a survey in a real-life situation rather than completely random and hypothetical. Initially these results are less generalizable they will provide a good starting point for a general framework (Saunders & Lewis, 2011).

It would also be interesting to see what would happen if one were to introduce variable reward within a relatively generic occupation. The frame of reference would change and would be more

egalitarian precisely because of their nature. Would one find it fair to reward say, a cleaner, based on their effort and or how many houses they have cleaned? Previous research indicated that a minimum income is deemed fair, yet remains vague on how to reward the ‘overachievers’ in generic occupations except the possibility of promotion (Gerhart et al., 1995).

In a similar vein, how would these fairness perceptions change when output is difficult to observe? How then is effort measured, and how does that influence perceptions of fairness of rewards? It seems logical that effort would be a factor of skill as well as hours worked and fairness perceptions. This would make for an interesting further research.

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Lastly it is important to recognize that fairness perceptions are the result of very complex (un)conscious deliberations (Colquit et al., 2001). As a result, the moderators chosen or the model in general might have not had the most explanatory power as possible, despite the arguments in favor indicated by the literature. Future research should attempt to overcome these limitations through scientific scrutiny.

7. Conclusion

Contemporary reward systems are based on the price mechanic of supply and demand, yet within the wrong paradigm. Companies are offering rewards based on their competitors’ offering rather than what each employee is worth to them. The shift towards a knowledge-based economy is likely to cause this theoretical mismatch to sow discontent among employees, especially in the more unique occupations. This can have severely negative consequences for the productivity of a companies’ workers and the profitability of the company itself.

This research has attempted to explore fairness perceptions of rewards based on their input (i.e. effort) and output (i.e. value created) rather than market pay. In doing so, it has attempted to form the basis of any future reward system based on rational economic arguments rather than notions of equality or benchmarking. By basing rewards on productive contribution rather than equality one is able to optimize rewards much in a similar fashion as big data is used to optimize online shopping, for instance.

Value created and effort provided were identified as being rational economic metrics on which to base a reward. The fairness perceptions of rewards based on these metrics were investigated in this study by conducting an experiment through a vignette study. The survey was distributed through Amazon Mechanical Turk resulting in a sample of 233 respondents. Despite strong arguments provided by the literature the regressions did not find significant evidence in support of any of the hypotheses, causing all hypotheses to be rejected. As such, we cannot conclude that fairness perceptions are influenced by either value created or effort provided. Additionally, we find no proof in support of any moderation effects of political preference, social value orientation, congruency or education. Future research is encouraged to overcome the current limitations and attempt to find significant results.

The topic of this study remains interesting as the workforce is becoming more demanding of the fruits of their labor. Current reward systems will not suffice in the future, especially for the more complex occupations. Additionally, multiple variations on this research are identified so as to be able to create a generalizable model that can be at the heart of an economically viable reward system, such as research of these components in a more generic occupations.

Rewarding effort and outcome; an exploratory research into an economically viable perspective of reward systems