1
Effect of rejecting subordinates’ suggestions on propensity to engage
in new ideas.
Master Thesis, MSc Human Resource Management University of Groningen, Faculty of Economics and Business
February 9, 2020.
JAVIER I. FERNÁNDEZ. University of Groningen (RUG)
Javieribafer@gmail.com
Supervisor: Dr. BART VERWAEREN University of Groningen (RUG)
2 Abstract
This study concerns the effect of rejecting employees’ ideas and suggestions that could actually improve processes and overall productivity in the company. I argue that rejecting said ideas decreases worker’s creativity and finally, the propensity to engage in new ideas and suggestions. The premise was that this propensity is moderated by distributive and procedural justice, which are two different dimensions of organizational justice perception. At the same time, the worker’s attitude towards the generation of new ideas is also affected by how big the reward for the suggestion could be in case it was accepted, and how specific the request for suggestions is. The company’s negative to accept a suggestion within a scheme with high rewards can affect workers in a more extreme way than in a low-rewards situation.
To assess these predictions, I reported the results of an ideation experiment. The empirical data assessed showed that task specificity by itself did not have by itself a positive effect in the propensity to engage in new ideas and neither had the justice moderators
explored. On the other hand, reward levels actually affected the employee’s propensity to engage in new ideas when they were assessed in conjunction with high task specificity.
3 INTRODUCTION
In general, companies try to improve their productive systems by encouraging workers to have ideas and submit their suggestions. Prior research shows that firms with suggestion systems in place and many workers proposals in number, create important improvements in quality and quantity of production. (Womack & Jones, 1996; Hackman & Wageman, 1995). For instance, data from US companies suggests that net savings per suggestion are in excess of 7.000 USD on average (Verespej, 1992). A good example about how employees’
suggestions can affect the whole direction of a company is seen in the multinational company Sony. Ken Kutaragi was a junior Sony employee working for the engineering. After buying his daughter a Nintendo gaming console he became interested in game consoles and shared his ideas with Sony. At first, the company was not interested and dismissed his suggestions, but after a couple of years he accepted secretly and by his own initiative a small Nintendo’s project to develop part of their new console without informing his bosses. That irreverent behaviour (that caused him problems with his superiors) finally led Sony to develop the first PlayStation system with 102 million consoles sold around the world. This example illustrates how important it can be to keep employees engaged in idea suggestions, even after a first idea was rejected.
As employee idea suggestions systems are important for organizational success, it follows that an important challenge for organizations is to maintain or increase worker motivation to participate in these systems. Especially when ideas are not selected, it may be difficult to maintain continued participation (Franke, Keinz & Klausberger, 2013; Piedzunka & Dahlander, 2019). I argue that there is a connection between how workers react to idea
rejection (term used from now on in this paper) and the willingness to propose new
4 this may not always be the case. Specifically, in this paper, I will mainly examine three
conditions that may ameliorate or exacerbate the negative effect of idea rejection on future engagement in idea generation.
First, I will examine the perceived justice of the idea selection system. This concept created by Greenberg in 1987, enacts employee creativity, including patents and contributions when it is related to a suggestion program. A negative justice perception in the company can cause a lack of initiative and, therefore, create a decrease in the number and quality of ideas (Li, Bingham & Umphress, 2007; Simons et al. 2003). I affirm that a low justice perception will directly decrease satisfaction and commitment with the organization affecting directly the intentions to submit new ideas.
A second condition that may exacerbate the negative effect of rejection is the amount of rewards that are associated with the idea suggestion system. One way that many
organizations have used to gain sustained employee participation is through incentive systems that reward successful idea suggestions. However, in this paper, taking a justice perspective I argue that this tactic may have unintended consequences and can actually reduce employee motivation to continue engaging in idea suggestions. While incentives may be positive when one’s idea is selected, I propose that that motivation to participate may be diminished, more than without such incentive system, when workers do not see their ideas taken into
consideration. When there are high rewards in play, unsuccessful idea submitters may
perceive the system as more unfair (Verespej, 1992), and therefore reduce subsequent effort in idea suggestions, compared to when there is no such reward.
5 objectives, etc. If the suggestions for company improvements are submitted without any type of plan established by the company on how to receive them (just having a typical electronic mailbox for it for example), then the value of the suggestion itself will decrease, as well as the received information amount (Schuring et al. 2001). A set of guidelines is needed to be sure companies achieve the best interaction possible and therefore, the best outcome.
Finally, the contributions this paper provides regarding theory is shown in the fields of idea rejection and propensity to deliver new ideas to the organization. First of all, it will start a not very researched field over how worker’s ideas can be affected by the organizational environment surrounding him. No previous research has been done with regards to high/low amount of rewards and their connection with perceived justice mixed with task specificity. Also, negative response to idea rejection will be assessed since the current literature is contradictory over rewards and their general effects on creativity. As an example, reward systems in companies could be affected by the answers given by this study in the sense of the negative effect they can have in their workforce when there is an idea rejection. Knowing these effects, companies could decide to create ESS with high task specificity to drop the idea rejection rate, instead of just increasing rewards as per the traditional models.
THEORY AND HYPOTHESES
Nowadays, literature has already achieved a consensus about the utility and usefulness of having suggestion schemes in place (Lasrado et al, 2016). These Employee Suggestion Schemes (ESS) provide a win-win situation to take advantage of employees’ creativity and is identified as a critical success factor for organizations (Vijayarani et al, 2013).
6 suggestion systems and the employee’s motivation was conducted through a survey in a German manufacturing company (Buech et al. 2014). The aim of the paper was to investigate how the subjacent processes in suggestion systems affect workers. The researchers correlated the suggestion system efficacy with employees’ wellbeing and organizational justice to discover how to increase the motivation of the employees to keep suggesting. They found a significant indirect positive relationship between interactional justice and the employee’s motivation to submit suggestions in an ESS, and also, explained that the relationship between interactional justice and the motivation to submit suggestions was directly and positively related when the worker’s general wellbeing in the company was moderate or higher than moderate but not for those of lower wellbeing. Several papers also demonstrate that a proper motivation and task characteristics is a fundamental part of the factors leading to innovation from the workers side (Choi, 2004; Franken, 2002). There are of course other factors like the organizational climate perception, and the specific job traits that affect this engagement in suggestions (Clegg et al. 2002). Rank (2004) also supports this idea, putting emphasis on the difficulties to discover what are the specifics of the employee’s motivations to be innovative and to express it accordingly in ESS. This also matches with the work of Clegg et al (2002) who explains that “personal and job variables predict idea suggestion, whereas organizational variables predict implementation. (p. 411)” The authors found a positive relationship between the worker’s suggestions and the trust built between the worker and the company” (that can be in fact a kind of fairness perception). One of these variables is the perceived organizational justice, which helps build the trust and motivation necessary to be innovative.
7 this research I will examine the possibility of submitted ideas not being selected by the
company and how it affects the willingness or propensity of the workers to engage in new idea generation.
In this study, the interest is focused on what effects are elicited after the idea is rejected as presented previously. The time employees spend on idea suggesting is a clear indicator on how engaged they are in the ESS (Hannam & Anupama, 2015). Therefore, more time invested in the idea generation is a simple way to determine the amount of motivation in order to fulfil a certain task. Understanding this time spent as the main quantifiable tool that helps to assess motivation, the dependent variable is clear. The DV to analyse in this study will be the amount of time spent by the employees on idea suggestion after a first idea is rejected. This is simply the difference between two rounds of ideation taken by hypothetical employees (the second round minus the first one). The rejection is introduced between these two rounds to force the employees to submit a new idea with the possible effects that we are studying.
Expanding on this dependent variable choice, I will explore the context of idea rejection, and when and why it leads to decreased or increased engagement in subsequent ESS. Although there is scarce research on this topic, earlier research has found that the way rejection feedback is given changes future engagement in ideas generation (Piezunka et al, 2019). This study finds that receiving some type of feedback from the company increases employee’s willingness to re-submit more ideas, even if the first outcome was negative. This effect is stronger when said rejection includes an explanation, and is reinforced if the rejection matches the linguistic style of the employee. The reason for this is that company explanations given after a negative outcome make the employee feel heard by the organization even if the outcome was undesired. On the other hand, some organizations deny feedback to the
8 While others implement special teams to evaluate the quality of the ideas, including managers from all across the organization to be sure ideas and feedback are correctly assessed (Dekier et al. 2014).
It is important to mention that I will always refer to a voluntary suggestion submission from the employees. Some companies include mandatory systems that ask for suggestions periodically (Amazon for example). The reason to do so is to ensure that the workers are always delivering feedback and alternative solutions to their task problems even if they would not do so freely. It is a solution for companies seeking for improving their processes but not achieving enough participation in their ESS. This situation (having mandatory systems) would affect the perception of the employees towards the system itself and therefore alter the
premise of the study, since “a free and voluntary environment will affect positively the suggestion system itself” (Lasrado et al. 2015, p. 12).
In this paper, I will further contribute to our understanding of the effects of rejection by examining the interplay of justice perceptions (mediator), incentives for ideas and task specificity (predictors).
The role of justice.
The defined concept of justice is based on how an employee judges the behaviour of the organization and the employee's resulting attitude and behaviour towards the firm. This concept, created by Greenberg in 1987, has three main components:
9 decisions are made. In this research I will focus on procedural justice and distributive justice. The reason for choosing these two types, is the direct relation literature has established (Buech et al. 2014) with the desired outcome and the procedures to pick the proposal (engage in new ideas and enacting intrinsic motivation).
Research has shown that positive justice perceptions are predictors of job satisfaction and individual motivation to engage in new ideas (Bakhshi et al, 2009). Moreover, both Colquitt (2001) and Bakhshi (2009) show in their studies that both distributive justice and procedural justice were found to be related to organizational commitment. This type of commitment is needed for employees to implicate themselves in the company by making suggestions, and could directly apply to the propensity to engage in new ideas after the first rejection. The employee motivation/commitment area has been researched before (Shalley and Gilson, 2004) showing that it has a huge impact in creativity but nevertheless these
studies do not explore this with the motivation of getting into ESS being the paper from Buech (2014) one of the few exploring this positive connection as explained before.
In addition, it is clear that the propensity to engage in new ideas is linked to Perceived Organizational Justice (from now on Justice) as said previously, since having an
understanding, supportive and fair manager has been signalled by literature as one of the main factors of employee creativity, including patents and contributions to a suggestion program (Oldham & Cummings, 1996). For example, Bartol and Srivastava (2002) found that when ideas are shared through informal mechanisms, the key enabling factor is trust between employee and company, facilitated through perceived company fairness. As an example, Hannam & Anupama (2015) present a clear explanation about the connection between justice and new ideas. In their study they explore the relations between intrinsic motivation,
10 a certain task or requirement with innovation. As the study itself explains, “perceptions of distributive and interpersonal justice significantly mediate the relationship between intrinsic motivation and individual creativity. Individuals intrinsically motivated in a task perceive the interpersonal interactions and distribution of rewards in their environment to be fair, which in turn leads to better creative performance” (Hannam & Anupama, 2015: p.222). This
connection between organizational justice, worker’s engagement in tasks and creativity is also supported by Deschamps, who sustains that employee’s creativity and motivation for tasks is affected directly by the level of procedural justice in the company (Deschamps et al, 2016). These results are also supported by Simmons (2011), who points out that there is a lack of research over the context of a company and their relationship with organizational justice influencing creativity. This relates to the study independent variable, which is the propensity to engage in new idea generation, by exploring justice as one of the main causes of the employee’s engagement in ESS.
Rewarding for ideas when ideas are rejected
Often organizations make use of monetary incentives to motivate employees to engage in idea suggestions. It refers to the pecuniary value of the benefit, prize or gift that the
company would give to the employee in case they would accept the worker’s proposal. The vast majority of companies have rewards in their ESS. According to recent research (Dekier et al. 2014) 85,1% of a sample of Polish companies, had reward systems when submitting
suggestions, although this number also changes depending on the field and type of company. For example, manufacturing companies had these systems implemented in 89,5% of cases while service companies only included this in 57,2% of the total.
11 improvement once its implemented. Literature shows that worker’s creativity, which is the necessary first step for submitting an idea, is positively impacted by creativity-contingent rewards (Byron & Khazanchi, 2012). Moreover, “Creativity-contingent and performance-contingent rewards […] are positively related to creativity when individuals are provided with feedback that is more positive, specific, task focused.” (Byron & Khazanchi, 2012: 812). It is important to remember that, above all, reward systems are known to be one of the main reasons for employee engagement in suggestions, counting for 80.4% of the employee’s motivation for submit one, according to Dekier et al (2014).
However, in this paper I argue that rewards may decrease the propensity to engage in subsequent idea generation, after being rejected the first time. I expect this negative effect because the worker may perceive that there was much at stake when there’s a substantial reward as a compensation for the best idea, and the rejection will cause a decrease in the perceived organizational justice due to the decision taken. Research made by Lawler (1976) and other academics (Ahmed et al, 2019, Cainarca et al, 2019) supports this vision by explaining that satisfaction with a certain reward is subjected to how much is received in the end for the idea, and how much the individual feels should have received. This is indeed a principal point since the lack of satisfaction with the ESS outcome may bring a sense of lack of justice to the employees participating on it.
Furthermore, building on the concept of justice (Buech et al. 2014, Clegg et al, 2012), I propose in this study that using incentives may have unintended negative consequences in some cases, related with the lack of sense of justice described above, especially if there is a negative answer (rejecting the idea). This will cause a decrease in worker’s creativity (Lawler, 1976). In this case, the worker will not receive any feedback reasoning why the idea has been rejected and the negative effect will be increased and amplified by the amount of the
12 incentives in fact decrease employees’ creativity, if they reward bad ideas or they are given arbitrarily, or they are perceived by employees as indiscriminate. On the other hand, if
rewards are given to few but good ideas, creativity will raise. This makes specific reference to the perception of the employee about rewards and the possibility to lose a desirable reward, mostly when said reward is generous enough. It is also important to mention that companies usually reward employees in a monetary/financial way (45%) but there are also other ways to do so (products/non-monetary with 20,5% or a mix of both, 29,8%). In this study I performed the research with the monetary reward, being the most used type of payment from the
companies (Dekier et at. 2014). The reason for this is that most of the studies exploring over this topic also focused on the monetary system, leaving aside others as residual/minoritarian.
On the other hand, if there is no reward at all, the employees will probably maintain a similar approach to suggestions before and after the submission. But also, lack of reward may decrease the initial worker’s propension to engage in idea suggestions (Franken, 2002), as a high level can elicit high amounts of idea submission but also be perceived as negative if those ideas are not accepted. Knowing this, I put the focus of the study in this possibility to assess to what point rewards affect the submission of new ideas from the worker once they had a previous rejection.
Summarizing, I propose that negative consequences for new ideation will happen due to the perceived loss of the opportunity to win a sum of money without a clear reasoned cause, creating a feeling of arbitrariness (and damaging the perception of organizational justice in the process). This will happen independently of the quality of the worker’s idea since no feedback has been provided. Therefore, I hypothesis that:
Hypothesis 1. 1a “Rewards for ideas will have a negative effect on idea generation after
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1b: “The relationship between rewards and idea generation after rejection is mediated by
justice”
The effect of task specificity
The second predictor in this model is task specificity, defined as “how detailed and concrete a request to perform a task is” (Cerdan et al. 2019). Task specificity is very present in the literature regarding job design. It has been shown (Van den Broeck et al. 2017) that a detailed and focused job design/task design improves the employee wellbeing, job
satisfaction, commitment, and productivity. I take a step forward in this study, theorizing that task specificity impacts the final outcome of the suggestion, being the factor that through perceived justice, affect the ESS.
14 information amount will also cause to have better propensity to engage in new idea
suggestion. Furthermore, the communication mechanisms in the organization and how the opportunities to give suggestions are presented, affect the employee’s propensity and encouragement to suggest (Lasrado et al. 2015).
Lastly, another study backing this is the one performed by Davis (2005). In this paper, he studies feedback and specificity with undergraduate students. He discovered that
specificity and feedback have greater impact over the participants depending on the phase when the specificity was established. As several phases, David established the information and feedback before the task as a briefing, during the task after having completed a part, and almost at the end. In the final phase, the ones with performance internal orientation (who wanted to be the elite performers) were the ones most affected by the feedback. This shows not only that the setup of the ESS can affect the outcome, but also that you can motivate high performers modifying the specificity of the task and the feedback received. Summarizing, the main idea is that the amount of information given by the company to the employees affect not only the value of the suggestion given, but also the quality of the outcome and the general engagement.
Finally, in this study I hypothesize that not only a better explained scenario or a more developed question can channel better employee’s suggestions, but also create a feeling of procedural fairness. This increased feeling of procedural fairness is due to a better
15 justice. In the same way, a more transparent petition in ESS will be perceived by employees as a decision made by the firm to facilitate a fair process. As Greenberg (1987) himself explained in his organizational justice model, the perception of equal opportunities and resources to fulfil a task is a main internal concern of the workers, especially in the
Distributive Justice dimension. If the decision outcomes are perceived as negative since the company request for ideas was unclear, (and this has a relation with Procedural justice, since accuracy in the process is fundamental) worker’s engagement in new ideas will be reduced. Therefore, we hypothesize that:
Hypothesis 2. Task specificity has a positive effect in the propensity to engage in new ideas.
2b. The relationship between Task specificity and worker’s propensity to engage in new ideas is mediated by Justice perception.
Task specificity and rewards may also influence each other in predicting the time individuals spend on idea generation after rejection. Specifically, when instructions and procedures are low in specificity, having high rewards associated with having an idea selected may increase the perceptions of unfairness, because there are then significant consequences attached to being selected or not. The fact that the way to ask for suggestions entangles with the reward levels is a hypothesis coming collaterally from available literature (Lasrado et al. 2015). Finalizing, since both specificity and reward levels are flexible in different
organizations and can change under different scenarios or ESS, I globally hypothesize that: Hypothesis 3: “There is a positive interaction between task specificity and rewards, such that
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Conceptual model of varying conditions when ideas are rejected
METHODOLOGY
Design of the experiment and sample
The methodology chosen for this study is based in a lab experiment conducted in the University of Groningen. The reason for conducting an experiment was mainly the need for a source of primary data to test the hypothesis, in contraposition to a survey study, where the research would have been more descriptive (Jürgen, 2009). Moreover, we wanted to study the cause-effect relationships between variables, while controlling external factors other than the hypothesized ones so they don't distort the results. Another reason was the creation of a sense of realism in the experimental phases so the participants would feel that they are being actually going through a real-time judgment of their responses, which was needed to elicit meaningful testing of our hypothesis, in contraposition with other types of studies.
This experiment was conducted in English language using the Qualtrics platform. The sample for analysis was 135 students. I aimed for this number to be evenly and randomly split between four groups of 34 participants and one group with 33 participants for the four
different conditions established. From the 135 students, 52 were males (38,52%) and 83 females (61,48%). On the nationality side, 30 were Dutch and 105 were international students.
17 Average age of the students was 22.55 years old. The average time to complete the
experiment was 36,16 minutes per participant. Overall, participants in each of the study groups were exposed to similar information and treatment, having the same initial briefing, with the same measurement methods, and the same debriefing.
Procedure and manipulations
The study was based on four different scenarios presented with two common variables that were manipulated for each one; the specificity of the task to develop and the presence of the reward. In order to do so, two short business cases about marketing and logistics were created with two versions (high and low specific) and two different rewards (none and 4 euros over the standard reward of the experiment).
The four possible scenarios (specified in Appendix A) for the participants were: a low specific task with low reward, high specific task with low reward, low specific task with high reward and low specific task with low reward. In this sense, a participant started the
experiment and automatically was randomly redirected to one of these scenarios. After the main task, measurement scales for fairness, risk taking, personality trait assessment, and demographics were presented.
18 Participants first had to answer the marketing scenario either in high or low specificity, and when they submitted their solution, the second scenario about logistics was presented, also either in high or low specificity. Therefore, two phases of idea suggestion were in place for each participant. The high or low reward mechanism was embedded in the two marketing and logistics business information. In the high reward condition, a sentence was introduced at the end of the phrasing (signalled in bold letters in Appendix A) stating that “If your idea is selected, you will receive a bonus of 4 euros”. On the other hand, in the low reward one the money was simply implicit by doing the experiment but no extra quantity was mentioned.
There was no judge evaluating the answers but we presented a text saying that indeed that happened after the first phase and also after the second phase of ideation. Said text, asking for the participants to wait until the answer was examined, was fundamental for the study of the hypothesis presented. We had to create a feeling of appraisal which was
necessary to elicit the response we wanted to study when the idea is finally rejected. To help this, a countdown was put in place after they responded to the first marketing scenario phase with a counter where the participants could not go forward until a certain amount of time had passed (40 seconds), mimicking the judge appraisal. After this, they reached the second phase with the logistic scenario and another counter was added at the end of it to elicit the same response with the same timer.
Measures
This experiment has been designed by the author but takes certain measurement scales from well tested sources in literature. This is to be able to specifically adapt the testing to my hypothesis in a detail manner. Organizational justice is a very well researched field with several measurement scales to choose (Greenberg 1990) in all its variants so I wanted to elicit a response which was measurable for two of them. The focus was put specifically for
19 and a 5 being fully agree, created by Colquitt (Colquitt 2001). The reason for this is that I hypothesized that those two types of organizational justice would be the most affected ones in this specific setup. The participants had to choose a grade of agreement between “Strongly disagree” and “Strongly agree” on ten sentences (4 distributive and 6 procedural ones).
The second measurement I took in the experiment was about risk taking (Meertens et al. 2008). There was an inherent need to check if the participants who answered differently in the scenarios had some bias towards risk. This was assessed by a lottery decision-making set where the participant had to choose 10 times between two possibilities with different
percentages of risk. In one of the possibilities there was always a high possibility to achieve a monetary prize but very low in quantity, while the other choice presented showed low
possibility to achieve monetary prize but high in quantity.
Finally, and before the debrief of the experiment, the participants took a simple 5-question assessment over demographics. This included gender, age, Dutch/international nationality, current employment status, and if they were participating for money or credits.
In order to operationalize the results from the experiment, three measurements were taken to be examined in detail. The first one was the total time spent in the first round of ideation. The second measurement was the total time spent in the second round of ideation, after the first rejection of the suggestion. Finally, the third measurement was the difference between the total time spent in round 2, and the total time spent in round 1. The reason to use these measurements as the main study pillars for the experiment was the necessary
20 other hand, having a positive number in said measurement means that participants spent more time and effort in the second round of ideation (after rejection).
TheCronbach’s Alpha analysis over Distributive Justice and Procedural Justice scales was .918 and .651 respectively, demonstrating a high level of reliability on both scales. Finally, the Risk-Taking scale showed a relevant reliability with .795 overall Cronbach Alpha index.
Data analysis:
I proceeded to use SPSS (v 25.0) Process mod with ANOVA statistical analysis to assess the possibilities of correlation between the DP and the mediators. Model 8 was used for Process, with a confidence interval of 95% and 5.000 bootstrap samples. Deviation, and general statistics measures (mean, mode, quantiles, etc) were also run via descriptive statistics in the same program
RESULTS
Assumptions
The mediators (Distributive justice and Procedural justice) being explored in the analysis show that there are no outliers (+3SD or -3SD). There is no missing data on the sample.
The statistical analysis for skewness over the mediators shown that the data for both is approximately symmetric (Distr. Justice Skewness= -.490, SE= .209 and Proc. Justice
Skewness = -.335, SE= .209) and slightly skewed to the left in both cases. The kurtosis analysis show that mediators have a central peak lower and broader than a normal
K=-21 .246, Std Error=.414). I infer from this that the mediators show a certain degree of normality in their distribution (George & Mallery, 2010).
Descriptive statistics
23 Main Analysis
I have used ANOVA for the main effects test and the interaction, and SPSS Process model 8 (Hayes, 2018) for analyses relating to the mediators in the model.
Firstly, the information presented in Table 2 and Figure 1 relates to hypothesis 1a, which predicted that rewards for ideas will have a negative effect on idea generation after rejection. It also relates to hypothesis 2a, which stated that Task specificity has a positive effect in the propensity to engage in new ideas. It is evident in the table data that both F and significance show that hypothesis 2a is not supported, while hypothesis 1a is not entirely supported (Reward F=2.939, p=0.089; Specificity F=1.530, p=0.218). However, there is a ‘borderline significant’ effect (p=.089) for rewards (hypothesis 1a).
24 hypothesis 1 was partially supported and hypothesis 2a, according to Table 2 data was not supported by the available evidence.
In order to examine the interaction of hypothesis 3 (the correlation between task specificity and rewards is positive towards time spent in the ideation phase) pairwise comparisons were analysed in conjunction with the ANOVA. The interaction is not conventionally significant on the ANOVA analysis for Reward*Specificity (F = 2.159, p = .144). This is only borderline significant, but the relatively low p-value suggests that some probing of the interaction may be appropriate. Hence, we further explored the interaction via pairwise comparisons to see if the effects of rewards are different at different levels of specificity.
26 Mediators
The next statistical analysis was done in order to test the mediators in relation to the dependent variable via SPSS Process (model 8), and how they affect hypothesis 1b which addresses that the relationship between rewards and idea generation after
rejection is mediated by justice. The same analysis also tests hypothesis 2b, which concerns the relationship between Task specificity and worker’s propensity to engage in new ideas, affirming that is mediated by Justice perception.
According with the analysis, it’s apparent that organizational perceived justice is not significant since it is not the main mechanism mediating (p =.98). The dependent variable is not substantially affected by the levels or types of organizational justice studied. Only one of the two justices, Distributive justice, was the only predictor that was significant and correlative (p=0.012). About the interaction of specificity on procedural justice, the statistical process analysis corroborates the same confirmed above with an out of range p value (p>0.05).
Now, I will be using Process data to report procedural and distributive justice as outcome variables. The available data tell us that rewards (B. Procedural justice = .039, p = .793; B. Distributive justice = .050, p = .838) and specificity (B. Procedural justice = .020, p = .891; B. Distributive Justice = .123, p = .62) do not predict justice. This explains why, although distributive justice predicts staying engaged in idea generation in the second round, it does not mediate the effect of rewards, specificity, nor their interaction. Hence, there is no mediating effect of any of the justice measures.
27 significance of Justice as a mediator. Thus, hypothesis 2b cannot be totally supported and will be discarded, happening also the same with hypothesis 1b.
DISCUSSION
The present study evaluated the effect of rejecting subordinates’ suggestions on propensity to engage in new ideas through perceived organizational justice. In order to do so, two main conditions were established, task specificity and rewards for said suggestions. Upon the review of the data from the case analysis done, it is safe to say that organizational perceived justice had no impact over the results. It was not
substantial both for Procedural justice and for Distributive justice. This invalidated hypothesis 1b and 2b. On the other hand, the data showed that rewards have relevance over the ideation phases of the study. Therefore, hypothesis 1a (partially), and
hypothesis 3 were sustained as explained by the data presented in the results section. Finally, hypothesis 2a was not supported since Task specificity did not have by itself a positive effect in the propensity to engage in new ideas. Summarizing, only hypothesis 1a and 3 were sustained in this study.
28 understanding of their arguments. This may have happened specially in the high specific scenario when there was no reward, since they probably felt “cheated” and involved in an overly complicated study to achieve just the normal monetary outcome (even
minding that many participated for credits), with a very quick judgement involved. This is relevant because at a certain point in the experiment, when presented said long ideation phases and a quick evaluation from a supposed judge, the feeling of unfairness may have augmented more than if they actually perceived the judges in a closer way/in front of them, appraising their work. This situation was minimized in the case of the two rewarded scenarios since it was clear that an extra prize could be won and probably that made the participants relatively ignore the judgement part since they probably were expecting a sort of lottery to determine the winners. But even in said case, the connection with perceived justice was not enough to infer a clear relation within the model and the engagement in new ideas.
On the other hand, the supported hypothesis, 2a and 3, were also the most logic and expected ones in the model since they did not involve mediators/moderators and just simple interactions. Hypothesis 2a, related to the positive effect of task specificity on new ideas was in line with literature (Bartol et al, 2002) and also with the model. Also, hypothesis 3 was sustained but in this case, there was almost no available
bibliography to sustain it since it took a very concrete perspective when it stated that the effect of different levels of rewards are different under different levels of specificity. Nevertheless, the data showed a clear consistency for the effect of these two factors.
29 Theoretical Implications
This study innovates in the field of idea suggestions under specific conditions (subjected to reward schemes and having specific requirements for the task) in a
substantial way, since it is not a very developed niche of research currently. The effects of task specificity mixed with reward has not been yet explored by literature and the finding that rewarded and specific schemes work better for the final outcome than non-rewarded and specific ones can help ESS future researchers.
Moreover, the literature explored (Bartol et al, 2002, Dekier et al, 2014) support the argument of rewards as a fundamental motivator for employees. This means that both this research and the one examined in the theoretical part have the same outcome, even if my study gives a further step into a very concrete topic (reward and specificity altogether).
Practical Implications
According to the outcome found in this study, and the already available literature quoted, I can advise for a better, more accurate wording and specification of the
suggestion requests from the company side. The more concrete a petition of ideas is, the more engaged will the employee show. Of course, this has to come with the other half of the condition, which is to establish a defined reward. If companies do very complex petitions (high task specificity) but do not offer any reward, the engagement from the workers side will be low. On the other hand, a high engagement in the ESS will be achieved if both rewards and specificity merge together from the beginning.
30 schemes, but the fact of having at least some reward indeed. The companies itself will be the ones who will run the costs and eventual benefits of investing in these policies. It is also important to notice that it is not possible to provide practical information about the benefits of organizational justice in ESS schemes since they were not sustained as a valid hypothesis factor.
Limitations and Future Research
31 this, I would suggest that new studies about this topic are made taking into account that currently active workers may respond differently to this very same research.
Finalizing, the number of participants was limited, considering that the 135 students had to be subdivided in 4 groups in order to cover all the possible categories for specificity and rewards. This may have causes statistical interferences in the data analysis, not being statistical representative enough. On the other hand, since the data sample and Power depends on the type of study, this sample may have been enough (Mason, 2010) to elicit a response solid enough to the hypothesis presented.
CONCLUSION
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36 APPENDIX A
Idea suggestion experiment (2 phases)
Description provided to participants Levels of Reward and Specificity First ideation phase: A new clothing
company was created 2 years ago. They are struggling to acquire new clients outside their current pool of customers, who are young people between 16 and 20 years old. What would be your
suggestion to face this challenge? Please take your time to think about this and come up with a good idea to solve this issue.”
Second ideation phase: A transport and logistics company is having problems delivering the packages in time. This happens even with more frequency in Christmas season due to the amount of people sending parcels. What would be your suggestion to fix this issue?
Low Reward and Low Specificity
First ideation phase: A new clothing company called "Spix" was created in 2017, located in London, UK. Their sales were modest but good, achieving a total revenue after taxes of 234.000 Euros in 2018. Now the marketing department is struggling to acquire new clients outside their current pool of customers, who are young people between 16 and 20 years old. Their main target audience since the company started was a young male between 18 and 26 years old. The company wants to explore new ways to attract new types of customers.
What would be your suggestion to face this challenge, given that you can only change company advertisement policies? Please take your time to think about this and come up with a good idea to solve this issue. Note that your idea will be evaluated by an evaluator (a judge) who is trained to make a good assessment of solutions to this business problem. From experience, we know that these judges select about one in five ideas that are submitted. Hence, you have about 20%
37 chance of having your idea being
selected. If your idea is selected, you will receive a bonus of €4. The bonus will be payed-out immediately when you leave the lab. Even if you participate for research credits you can still receive the bonus payment.”
Second ideation phase:
A transport and logistics company founded in 1999 is having problems delivering the packages in time. This happens even with more frequency in Christmas season due to the amount of people sending parcels. Moreover, this has been a constant problem over the years, but since mid-2000's the situation is going worst. Around 50% of the clients have left to go to rival companies, and downsizing may be in need if the situation does not change soon. What would be your suggestion to fix this issue in the next 6 months, with a maximum cost of 20.000 Euros? Note that your idea will be evaluated by an evaluator (a judge) who is trained to make a good assessment of solutions to this business problem. From experience, we know that these judges select about one in five ideas that are submitted. Hence, you have about 20% chance of having your idea being selected. If your idea is selected, you will receive a bonus of €4. The bonus will be payed-out
immediately when you leave the lab. Even if you participate for research credits you can still receive the bonus payment.”
First ideation phase: A new clothing company was created 2 years ago. They are struggling to acquire new clients outside their current pool of customers, who are young people between 16 and 20 years old. What would be your
suggestion to face this challenge? Please take your time to think about this and come up with a good idea to solve this issue. Note that your idea will be
evaluated by an evaluator (a judge) who is trained to make a good assessment of
38 solutions to this business problem. From
experience, we know that these judges select about one in five ideas that are submitted. Hence, you have about 20% chance of having your idea being
selected. If your idea is selected, you will receive a bonus of €4. The bonus will be payed-out immediately when you leave the lab. Even if you participate for research credits you can still receive the bonus payment.”
Second ideation phase: A transport and logistics company is having problems delivering the packages in time. This happens even with more frequency in Christmas season due to the amount of people sending parcels. What would be your suggestion to fix this issue? Note that your idea will be evaluated by an evaluator (a judge) who is trained to make a good assessment of solutions to this business problem. From experience, we know that these judges select about one in five ideas that are submitted. Hence, you have about 20% chance of having your idea being selected. If your idea is selected, you will receive a bonus of €4. The bonus will be payed-out immediately when you leave the lab. Even if you participate for research credits you can still receive the bonus payment.”
First ideation phase: A new clothing company called "Spix" was created in 2017, located in London, UK. Their sales were modest but good, achieving a total revenue after taxes of 234.000 Euros in 2018. Now the marketing department is struggling to acquire new clients outside their current pool of customers, who are young people between 16 and 20 years old. Their main target audience since the company started was a young male between 18 and 26 years old. The company wants to explore new ways to attract new types of customers.
What would be your suggestion to face this challenge, given that you can only change company advertisement policies?
39 Please take your time to think about this
and come up with a good idea to solve this issue. Note that your idea will be evaluated by an evaluator (a judge) who is trained to make a good assessment of solutions to this business problem. From experience, we know that these judges select about one in five ideas that are submitted.
Second ideation phase:
