Employee Shirking & Overworking: Model & Consequences - PDF

Ergonomics ISSN: 0014-0139 (Print) 1366-5847 (Online) Journal homepage: https://www.tandfonline.com/loi/terg20 Employee shirking and overworking: modelling the unintended consequences of work organisation Patrycja Antosz, Tomasz Rembiasz & Harko Verhagen To cite this article: Patrycja Antosz, Tomasz Rembiasz & Harko Verhagen (2020) Employee shirking and overworking: modelling the unintended consequences of work organisation, Ergonomics, 63:8, 997-1009, DOI: 10.1080/00140139.2020.1744710 To link to this article: https://doi.org/10.1080/00140139.2020.1744710 © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 06 Apr 2020. Submit your article to this journal Article views: 9441 View related articles View Crossmark data Citing articles: 5 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=terg20 ERGONOMICS 2020, VOL. 63, NO. 8, 997–1009 https://doi.org/10.1080/00140139.2020.1744710 ARTICLE Employee shirking and overworking: modelling the unintended consequences of work organisation Patrycja Antosza, Tomasz Rembiaszb and Harko Verhagenc a University College Groningen, University of Groningen, Groningen, Netherlands; bDepartment of Astronomy and Astrophysics, University of Valencia, Valencia, Spain; cDepartment of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden ABSTRACT ARTICLE HISTORY Underworking (i.e. shirking) and overworking of employees can have detrimental effects for the Received 28 February 2019 individual and the organisation. We develop a computational model to investigate how work Accepted 5 March 2020 structure, specifically the way in which managers distribute work tasks amongst employees, KEYWORDS impacts work intensity and working time. The model draws on theories from economics, psych- Task performance; shirking; ology and management, and on empirical observations. The simulations show that when man- agent-based model; social agers correctly estimate task difficulty, but undervalue the employee’s competence, simulations opportunities for shirking are provided due to longer deadlines. Similarly, if managers overvalue the employee’s competence, they set tighter deadlines leading to overwork. If task difficulty is misjudged, initially only influence on employee working time is observed. However, it gradually generates competence misjudgements, indirectly impacting the employee’s effort level. An inter- action between competence misjudgement and task uncertainty slows the manager’s ability to correctly estimate employee competence and prolongs initial competence misjudgements. The study highlights the importance of applying dynamic modelling methods, which allows for test- ing theory assumptions in silico, generating new hypotheses and offers a foundation for future research. Practitioner summary: A computational model was developed to investigate how the structure of work allocation influences opportunities for shirking and overworking by employees. The paper demonstrates how dynamic modelling can be used to explain workplace phenomena and develop new hypotheses for further research. Abbreviations: KSA: knowledge, skills, attitudes; MIT: motivation intensity theory Introduction empowerment (for review see Antosz 2018). In this study, we investigate how the structure of work organ- A century ago, Frederick Taylor (1911) predicted that isation is sufficient to create opportunities for shirking elimination of soldiering (i.e. working slowly) would and overworking. We combine results of empirical have profound effects in the forms of lowering produc- studies and assumptions from several theoretical per- tion costs, enlarging the market, reducing unemploy- spectives in a single mechanism, programmed as a ment and poverty, ensuring higher wages, and computational model. Agent-based modelling was decreasing working hours. Yet, shirking is still a phe- chosen because it draws attention to the emergent nomenon, which every single working person has been character of shirking and overworking, which can ori- guilty of, at one time or another. The opposite, over- ginate from interactions between managers and working, is also more common than we would wish employees. Simulations of the model allow us to assess for. Previous research, with the use of game theory, in silico the impact of (1) adverse selection, (2) task experiments, or quantitative studies in organisations, uncertainty, and (3) interactions between those two on stressed the importance of factors such as monitoring work intensity and working time of employees. The fol- practices, payment scheme, type of work, organisa- lowing section discusses the theoretical foundations of tional structure, personal engagement, or employee the model. CONTACT Patrycja Antosz [email protected] University College Groningen, University of Groningen, Groningen, Netherlands ß 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by- nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. 998 P. ANTOSZ ET AL. Theoretical background effective work. It refers to the time when an employee is at the disposal of his employer to perform work Work intensity and working time duties. This specific legal setting governs the structure Evaluating work performance is a difficult task. of work organisation where the employee sells to his Theoretical approaches guiding work performance employer his ability to perform work tasks in a con- evaluation have mainly focussed on the amount of tracted amount of time and it is the employer’s effort exerted by the employee1 (Albanese and van responsibility to plan an individual employee’s work to Fleet 1985; Demski and Feltham 1978; Gachter and use that time to the fullest.2 The remaining part of the Fehr 2000), although some more recent studies high- article focuses on the effects of this particular way of light the importance of time spent on performing organising labour practices on the opportunities to work tasks (Paulsen 2014). In fact, the two approaches shirk and/or overwork. considering the amount of effort and the amount of working time are related, given that effort has been Shirking and overworking conceptualised as having three main characteristics: direction, intensity and duration (Kanfer 1990). Work intensity and working time are two dimensions Direction of effort concerns the activity in which the in which aberrations can occur. Aberrations take place individual is engaged, e.g. a work task or a non-work when an employee’s actions deviate from the manag- task. Intensity of effort defines the level of engage- er’s expectations. They can take two forms: shirking or ment (i.e. work intensity). The temporal attribute refers overworking. Individual in-depth interviews with man- to the amount of time a person is engaged in the agers and white-collar lower-level employees showed activity (i.e. working time). A cautious reader would that discrepancies between existing legislation and surely point out that there is a relationship between managerial expectations occur (Antosz 2018; Antosz work intensity and working time. Indeed, ceteris pari- and Verhagen 2020). Most importantly, managers bus, exerting more effort results in decreasing the want their employees to complete work tasks.3 Yet, amount of time necessary for completing a task. the law obliges them to coin their expectations into However, since an employee can at most exert 100% eight-hour working days. Therefore, assuming best- of effort, there is a limit to the reduction of work- case scenario, managers define task deadlines based ing time. on their knowledge about task difficulty and employee This article focuses on the concepts of work inten- competences. Incorrect estimation of a deadline sity and working time, as these two represent rela- results in employees’ shirking (i.e. insufficient work tively easy to measure, historically applied and legally intensity or working time) or overworking (i.e. exces- meaningful dimensions of work performance. An sive work intensity or working time). employee cannot be dismissed on the basis of low work motivation, because it is not the employee’s Task performance legal obligation to be motivated. However, a lawful dismissal can occur if an employee did not work dur- Task performance, signifying the diligent performance ing the contracted hours. The importance of those of role-prescribed activities assigned by the manager concepts was also confirmed in an exploratory, empir- during a contracted period of time, is one dimension ical study carried out by the authors (Antosz and of a broader concept of work performance. Task per- Verhagen 2020). Work intensity and working time are formance focuses on the act of working rather than usually in some way present in legislation governing on the outcomes of work. employment. For instance, in Polish regulations work Inspired by research on performance determinants effort is related to the basic obligation of an employee and contemporary theories of motivated action, we to perform work conscientiously and carefully and to focus on two direct task performance determinants, comply with the instructions of superiors related to which are individual characteristics of employees, the work (art. 100 §1 of the Labour Code; Gersdorf, namely, competence and effort level (McCloy, Raczkowski and Ra˛czka 2014). Interestingly, an obliga- Campbell, and Cudeck 1994). tion of conscientiousness entails that the employer In the proposed computational model, competence customises work to the abilities of the employee level is considered broadly as resource of an individual (Baran 2016; Jaskowski and Maniewska 2016). Working needed for effective task performance. Competence time on the other hand, according to the Polish incorporates three domains of educational activities Labour Code, is not solely comprised of time of originally described by Benjamin Bloom, namely, ERGONOMICS 999 cognitive, affective and psychomotor (Bloom et al. performance and does not investigate the role 1956). The three domains became known in training of motivation. research and practice as the KSA (knowledge, skills The last factor assumed to influence task perform- and attitudes) approach (Winterton, Delamare-Le ance is difficulty. Studies in the MIT paradigm show Deist, and Stringfellow 2006). Since a body of research that task difficulty provides information about the indicates that an employee’s position in a network amount of resources needed to complete the task, influences work performance (Sparrowe et al. 2001), in and therefore is linearly related to the exerted effort our conceptualization, the domains were supple- (Richter, Gendolla, and Wright 2016). The computa- mented by social capital – resources embedded in tional model assumes task difficulty is characteristic of one’s social networks, which can be accessed or mobi- a task per se, not of an individual performing it, lised through ties in those networks (Lin 2001). The although individuals might differ with respect to how computational model we introduced further assumes they perceive the difficulty of a given task. The model a multi-method oriented rationalistic approach to states that the more difficult the task, the more effort competences, which means that competences are is needed to complete it. attributes (a characteristic of the rationalistic tradition, opposed to interpretive tradition highlighting that The role of informational advantages competences are constituted by the meaning the work takes for the worker in his/her experience of it) The above factors influencing task performance are possessed by workers needed for effective task per- associated with a certain informational advantage formance (multi-method oriented approach combining structure. The employee has better knowledge regard- worker- and work-oriented foci; for a review of ing competences and effort exerted during task per- approaches to the conceptualisation of competences, formance than the manager. However, neither actor see Sandberg 1994; Sandberg 2000). The chosen trad- knows the true task difficulty beforehand. The first ition of conceptualising competences is further two informational advantages are described using the reflected in the formalisation present in Equation 1. By principal-agent theory.4 The third one refers to a prob- definition, higher competence levels increase task lem of task uncertainty. performance. Principal-agent theory (Laffont and Martimort 2002) The second factor identified as an employee charac- is an economic theory which refers to the dilemma teristic directly influencing task performance is effort. that arises where one party - ‘the principal’, relies on A large body of research has shown that increasing another - ‘the agent’ to act on their behalf, in their effort positively affects task performance (e.g. Gardner best interests. A principle-agent problem arises where et al. 1989). Even though motivation is not a subject the interests of the two parties are not aligned and of this study, and is therefore absent in the computa- where they have access to different information. This tional model, it is important to conceptually clarify the problem has been the topic of previous research in relationship between motivation, effort and task per- employment situations where the principal is the formance. Motivation is a psychological state, while employer and the agent the employee (e.g. Biglaiser effort is a physical phenomenon. Initially, studies such and Mezzetti 1993; Gershkov and Perry 2012). It has as Deci’s (1971) classic self-determination theory also been applied in a range of other contexts such as experiments assumed that effort and motive strength project management (Mu €ller and Turner 2005) and are linearly related and measured motivation via natural resource management (Hotte, Mahony, and exerted effort, i.e. the amount of time subjects spent Nelson 2016). Applying principal-agent theory within working on a task. Contemporary approaches, such as an employment relationship assumes that the agent’s motivational intensity theory (MIT, hereafter) which and principal’s goals are conflicting (e.g. the manager uses psychophysiological indicators, question the lin- wants the employee to exert maximum effort at all earity of the relationship between the two (Richter, times, however, the employee is effort-averse). Gendolla, and Wright 2016). MIT studies show that Two types of principal-agent problems have been motivation impacts task performance only indirectly, studied: adverse selection, i.e. hidden information, and by limiting the maximum level of exerted effort moral hazard, i.e. hidden actions (Gaivoronski and (Wright and Brehm 1989). Since our model investi- Werner 2012; Hart and Holmstro €m 1987). In this paper, gates structural possibilities for shirking and overwork- we focus on the problem of adverse selection – ing, rather than utilisation of those possibilities, it employee’s private information about his true level of assumes a direct relationship between effort and task competences (Biglaiser and Mezzetti 1993; Gershkov 1000 P. ANTOSZ ET AL. and Perry 2012) and we investigate how it influences computational model programmed in an agent-based the intensity and time of exerted effort (i.e. the prob- framework. This particular method was chosen for sev- lem of moral hazard). It is worth pointing out that in eral reasons. The first reason involves the subject of the context of acquiring employment, low-skilled scientific inquiry. Shirking and overworking are shown agents pretend to be highly skilled to receive better as behaviours emerging from decisions of employees, terms at the time of contracting. However, the reverse which are influenced by various factors. is the case after the contract is signed. It is in the best Computational modelling enables (1) designing a rela- interest of the employee not to disclose how high his tively complex formal model in one environment and competences are because it lowers his marginal price (2) performing simulations of that model, allowing for of labour – he would have to perform more work for systematic variations in the factors of interest. The the same remuneration. second reason is related to the knowledge gap about Task uncertainty is the degree to which tasks are the dynamics of shirking and overworking. Employees open to chance-based, task-relevant influences (Hirst in the model gradually achieve excellence in their abil- 1987). In moral hazard, the unpredictability related to ity to handle day-to-day work tasks. Introducing a employed methods and task performance is repre- learning function to the model calls for a method that sented by the noisy environment influencing out- allows for dynamics, where analysing the temporal comes. In practice, managers estimate the time dimension is easily achieved. Third, the conceptualisa- sufficient to accomplish a task of certain difficulty by tion of this work should be considered as building a an employee possessing given competences. However, foundation for further scientific development. reality holds an informational advantage over manag- Although the model does not currently contain dis- ers and employees, as they merely guess the nature of tinctive elements of a traditional agent-based model, the task, with its true difficulty and complexity. e.g. social networks and space, it is possible to include these elements in the future. The model illustrates an organisation comprised of Research questions three employees and a set of tasks available for them Previous research on the principal-agent problem to complete (Figure 1). Each employee is characterised shows that possibilities for engaging in shirking stem by a certain level of competence, enabling him to from the imperfect observability of employee compe- complete work tasks. Initially, all employees are avail- tences, which generates informational advantages on able for receiving tasks. Once an employee is assigned the side of employees. Task uncertainty has also been a work task, a new task of random difficulty is added shown to influence performance (Belkaoui 1990). So to the pool, so that ten tasks await assignment at all far, no study has investigated the impact of those fac- times. Work tasks vary with respect to difficulty and tors by presenting a single, coherent mechanism of competence-dependence5 – a degree to which time task performance. Moreover, past analyses have for completing a task depends on employee compe- focussed on presenting a static picture of aberrations tence. Subsequent parts of this section explain the in work intensity and working time, even though the assumptions of the model regarding task assignment, latter is immanently a dynamic phenomenon. We task completion, and measuring work intensity and address three questions insufficiently answered by the working time aberrations. The next section describes existing scientific literature, namely, how to do: simulations of the model in various settings and ana- lysis of the dynamics of shirking and overworking. 1. adverse selection, 2. task uncertainty, and Task assignment 3. interactions between adverse selection and task uncertainty influence the aberrations in work The manager, who is not physically present in the intensity and working time of employees. model, assigns tasks to individual employees. Based on individual in-depth interviews with a group of managers, two rules of task allocation were identified Computational model of task performance (Antosz 2018). First, tasks are assigned to available To address the research questions, the process of task employees. Second, task difficulty corresponds to performance in organisations, utilising theoretical employee competence level, as it is perceived by the approaches from several disciplines described in the manager. Tasks are appointed starting from the least earlier sections, is operationalised in a form of a skilled employee. Such a rule ensures that a more ERGONOMICS 1001 Figure 1. Screenshot of the task performance model in Netlogo interface. competent employee does not receive an easier task Table 1. Informational advantages present in the computa- than his less experienced colleague. Once a task is tional model. assigned to an employee, a deadline for completion is Perspective established. The amount of time required for an Manager Employee Actuality employee to complete a task increases with the diffi- Competence level c j þ e cj 1 cj cj Effort 0.8 eij eij culty of tasks and how time-consuming they are, and Task difficulty bi þ ebi bi þ ebi bi decreases with employee effort and competence level. Competence level influences time to the eij – effort of employee j performing task i (assumes extent that a task is competence-dependent. The positive values between 0 and 1). manager estimates the amount of time required for The degree to which a task is time-consuming is accomplishing a task to an acceptable standard by expressed in units of time and was assumed to be a certain employee based on her perception of constant throughout the simulation (i.e. dij¼10 for all i employee competence, her perception of task diffi- and j). The manager’s expectations were set to 0.8 of culty, and an assumption regarding the amount of maximum effort. effort the employee will exert. Perception misjudge- ments correspond to adverse selection, task uncer- tainty and moral hazard. We assume that the time Task completion required for performing the task i by employee j is: Once the employee knows the deadline for task com- di b i tij ¼ (1) pletion, he can choose a minimum level of effort, aim- ð1 þ ai cj Þeij ing for the task to be accomplished on time. Yet, the where: employee, just as his manager, might misestimate the di – time-consumingness of task i, actual amount of time needed for task completion, as bi – difficulty of task i, he does not know the true task difficulty (the effect of ai – competence – dependence of task i, task uncertainty). We assume that employee’s and cj – competence level of employee j (note that the manager’s perceptions of task difficulty are the same. competence of employee j increases after completing Table 1 presents the informational advantages imple- each task), mented in the computational model. 1002 P. ANTOSZ ET AL. As employees gain experience by performing tasks on the learning curve according to function: in the organisation, they increase their competence E0j cj levels. The rate of this increase depends on the level ¼ arctanh Es cmax of already obtained competences. A novice consider- 1 cj cj ably increases his competences with each completed ¼ ln þ 1 ln 1 (4) 2 cmax cmax task. As the employee becomes more competent, the same task stimulates a smaller increase in competen- where: cj ces, to a point where increase in competences due to cmax – percentage of maximum competence level of performing additional tasks becomes insignificantly employee j. small (Minbashian and Earl 2013). Thus, we approxi- The simulation ends when the competence level of mate the employees’ learning curve by the hyperbolic every employee reaches 0.995 cmax , an arbitrary cut- tangent, which is a well-known function following the off point, which is close to a theoretical (asymptotical) described dynamics. The competence level of maximum of c ¼ cmax ¼ 10. Once all employees have employee j (cj ) is expressed as follows: mastered performing tasks, they do not learn signifi- cantly more after completing additional tasks. Ej cj ¼ cmax tanh (2) Es where: Aberrations in work intensity and working time cmax – maximum competence level, Ej – work experience of employee j, Employee’s actions can deviate from the manager’s Es – scaling parameter. expectations regarding exerted effort (work intensity) The scaling parameter (Es ) determines how fast and working time. Lower/higher than expected levels employees increase their competence levels. of effort and time correspond to shirking/overworking. Professions involving more complex tasks would be However, the degree of overworking with respect to characterised as having higher values of the scaling intensity is limited, as there is an upper limit on effort. parameter. Throughout the simulations, the scaling The employee can only exert a maximum of 100% of parameter was set to a value of 500. Such a setting it. Aberrations from the manager’s expectations assures adequate duration of each performed simula- regarding work intensity (aberration of effort, ae ) at tion and, in effect, allows for a sufficiently detailed each point in time are calculated by subtracting the level of observation. level of effort expected by the manager from the Note that an increase in experience level does not actual effort exerted by employee j performing task i: depend on a task’s competence-dependence nor on the aeij ¼ eoij em ij (5) level of employee effort. For example, when two equally where: competent employees perform equally difficult tasks eoij – objective effort exerted by employee j performing with different levels of effort, their work experience task i, increases by an equal amount. The increase simply takes emij – manager’s expectations regarding effort exerted place faster for the employee exerting a greater amount by employee j performing task i. of effort. Employee work experience is updated based Working time discrepancy manifests as working for on the true values of employee competence and task an inadequate amount of time. Devoting less time for difficulty. However, the manager updates her informa- work than expected is defined here as shirking with tion based on the values of employee competence and respect to time – a situation, when an employee fin- task difficulty that she perceives. ishes a task earlier but waits until the deadline to The overall experience level of employee j (Ej ) is a deliver it. A contrary situation, in which the employee function of his initial abilities (E0j ) and a sum of what works more time than he was expected to, comprises he has learned after having performed his first n tasks overwork with respect to time. It is assumed that the in the organisation: manager abides by the law and expects a maximum X n of legally defined working time from the employee. Ej ¼ E0j þ tij ai eij (3) Aberrations from the manager’s expectations regard- i¼1 ing the amount of working time (aberration of time, Employees enter the organisation with different at ) are expressed as a percentage of working time competence levels. The initial experience level of expected by the manager, which is spent shirking or employee j (E0j ) is translated into a specific position overworking: ERGONOMICS 1003 tijo tijm As the model is mainly focussed on determining atij ¼ 100 %, (6) tijm how informational advantages influence shirking/over- working behaviour, the control condition in the experimental design was defined by a true estimate of where: initial competence misjudgement and a true estimate tijo – objective working time of employee j performing of task difficulty. As expected, in the control condition, task i, no aberrations of time or effort occur, independently tijm manager’s expectations regarding working time of the initial competence level of employees. of employee j performing task i. Impact of adverse selection Results The simulations show that when task difficulty is esti- The simulations were performed in the BehaviorSpace mated correctly, the manager’s incorrect evaluation of of Netlogo 5.3.1, an integrated tool, which allows for an employee’s competences directly affects the level performing experiments with the computational of invested effort, but not the amount of time it takes model. All the tested factors, in addition to their cate- to complete a task. As anticipated by the principal- gories and respective values, are presented in Table 2. agent theory, undervaluing employee competences The design space of these (3 5 5) yielded 75 tested generates opportunities to shirk. On the other hand, a conditions – unique combinations of factor levels, belief that the employee is more competent than he which sufficiently covered the parameter space of the actually is results in a necessity for him to overwork in model. BahaviorSpace systematically runs each combin- order to complete a task on time. Naturally, similar ation of factors 10 times, recording the values of the misjudgement (expressed as a percent of employee dependent variables at every time step of competence level) generates larger aberrations of the simulation. effort for higher initial competence levels. The effects of adverse selection on exerted effort Table 2. Factors tested in the simulation. are only temporary, which is not predicted by the Factor Category label Value principal-agent theory. As time goes by and employ- Initial competence level Low 2 Medium 5 ees gain proficiency in completing daily tasks, their High 8 informational advantage decreases. Figure 2, present- Task difficulty misjudgement (ebi ) Large overestimation 0.3 bi ing the dynamics of effort aberrations, seems to super- Small overestimation 0.1 bi True estimation 0 ficially suggest that employees learn to correctly Small underestimation 0.1 bi estimate the amount of effort needed to perform a Large underestimation 0.3 bi Initial competence misjudgement (ecj ) Large overvaluation 0.2 cj task. This is not the case. Rather, during an employee’s Small overvaluation 0.1 cj career in the organisation, the manager learns to esti- True valuation 0 Small undervaluation 0.1 cj mate the competences of her subordinate better and Large undervaluation 0.2 cj is, therefore, able to set more realistic deadlines for performed tasks. Higher values of initial competence Figure 2. Dynamics of work intensity (work quality) aberrations depending on initial competence misjudgement, and employee’s initial competence level. Task difficulty misjudgement ¼ true estimation. 1004 P. ANTOSZ ET AL. Figure 3. Dynamics of working time (work quantity) aberrations depending on task difficulty, misjudgement, and employee’s ini- tial competence level. Initial competence misjudgement ¼ true estimation. misjudgement result in a longer time needed for the diminishes. Competence misjudgement, on the other discrepancy between perceived and actual competen- hand, causes a stronger effect when employees ini- ces to disappear. tially have higher competences. Interestingly, task uncertainty has a profound effect not only on working time aberrations but also on the Impact of task uncertainty manager’s perception of her subordinates’ competen- In comparison to adverse selection, the simulations ces. Through that mechanism, it affects the level of suggest that the relationship between task uncertainty effort aberrations. Even without initial competence and work aberrations is more complex. Generally, misjudgement, by overestimating task difficulty alone, underestimating task difficulty by either actor leads to the manager believes that completing a task causes a a necessity to work longer than expected by the man- higher increase in competence than it does in reality, ager. On the contrary, overestimating task difficulty thus requiring the employee to exert more effort than generates opportunities for employees to shirk expected combined with finishing the task earlier than (Figure 3). Yet, this relationship is not symmetric, as expected. On the contrary, believing that the task is was the case of the impact of adverse selection. A easier than it is creates an even a fool can do that atti- small underestimation (10% of task difficulty) results in tude, where the manager underestimates competence employees working for approx. 2.5% more than their development of her subordinates. The employees, manager expects. A large underestimation (30% of whose perceptions are also biased by task uncertainty, task difficulty) leads to working for approximately 10% underestimate the task difficulty and initially shirk more than expected. For small (10%) and large (30%) with respect to work intensity (i.e. even a fool could do overestimation, the values are significantly lower - 2 that). Over time, however, they realise that the task is and 5%, respectively. The asymmetry stems from the more difficult than expected, and have to work over- way, in which working time aberrations are measured time to finish it before the deadline. Even as employ- in the model. Namely, the discrepancy between actual ees reach proficiency, a mismatch between what their and expected working time is expressed as a percent- competences actually are and how the manager per- age of expected working time (Equation 6). Ceteris par- ceives them persists. Figure 4 shows the effects of ibus, in case of overestimating task difficulty the over- and under-estimating task difficulty on work expected working time (i.e. denominator) is higher, intensity, competence misjudgement and work- and the difference between actual and expected work- ing time. ing time (i.e. numerator) makes up a smaller fraction. Task difficulty misjudgement operates differently than Adverse selection and task uncertainty interaction competence misjudgement, as misestimating task diffi- culty causes more extreme values of time aberrations, Overestimating task difficulty prolongs the effect of the lower the competences in the beginning of the initially overestimating employee competences on organisational career. As employees become more adverse selection. The manager overestimates the experienced, the effect of the initial competence level competences of her subordinates for a longer time, ERGONOMICS 1005 Figure 4. Dynamics of work intensity (work quality), working time (work quantity), and competence misjudgement depending on task difficulty misjudgement. Initial competence level ¼ low, Initial competence misjudgement ¼ true estimation. compared to when no task uncertainty occurs. Such misjudgement, so that the manager does not end up overestimation results in lengthening the duration of making two opposite judgement errors throughout the overworking with respect to effort and causes shirking employee’s career (e.g. initially overvaluing employee with respect to working time. Similarly, underestimat- competences and, over time, undervaluing them). ing task difficulty prolongs the effect of initial under- Minor misestimations of task difficulty prohibit the valuing employee competences on competence manager from discovering the true levels of employee misjudgement. competences even after the employee has gained In the cases where perception errors are opposite proficiency. We also observe that overestimating task for managers and employees, initial competence mis- difficulty leads to smaller informational advantages judgement compensates for task difficulty misjudge- regarding competences, compared to underestimating ment only to a small degree. In rare cases, large them. This finding is a consequence of the asymmetry misevaluation of employee competences at initialisation in the effects of task difficulty misjudgement, (by 20%) decreases the effect of small misestimations which was described at the beginning of the previ- of task difficulties (by 10%) on competence ous section. 1006 P. ANTOSZ ET AL. Conclusions work depicted by the computational model takes place, i.e. components such as employees, manager, Shirking and overworking can have negative conse- tasks, deadlines, etc., and operations such as assigning quences for both individual employees and the organ- tasks, completing tasks, etc. are present. Contrary to isation providing employment. Studies show that the initial intuitions, the model is not only applicable in most popular activities employees engage in, instead the contexts of blue-collar work. Even though more of performing work tasks, include: browsing the flexible work arrangements are gaining popularity (e.g. Internet for personal use (anything from receiving task-based contracts, where working time is not a con- emails to online games or gambling), socialising with cern), the majority of employees in the western world co-workers and conducting personal business (Carroll are still contracted for working time (Katz and Krueger 2007; Poppick 2016; Salary.com 20146). However, in 2016; Ter Weel et al. 2018). Moreover, principals of real life, employees also have far more imaginative project work are becoming ever present – nowadays ways of spending time at work. In a survey for Careerbuilder.com, 2138 hiring managers and HR per- even doctors often have 15-minute deadlines per sonnel shared some stories. Actual examples included patient visit. All of the interviewed managers and blowing bubbles in sub-zero weather to see if the lower level employees, whose stories helped in speci- bubbles would freeze and break, shaving legs in the fying the assumptions of the computational model, women’s restroom, claiming to be praying while sleep- were white-collar workers, including doctors, lawyers ing or warming bare feet under a hand dryer. David and programmers (Antosz and Verhagen 2020). In this Bolchover (2005) offers even more graphic examples context, it is important to remember that the results such as using drugs or having sex with work col- of the simulations should be interpreted as acceptable leagues. Detrimental effects of such behaviours on possibilities within the system. Situation runs illustrate employee motivation and productivity are easy to maximum levels of shirking of an employee, whose imagine. Excessively long working hours negatively unaware manager is satisfied with work performance, impact employees’ health (e.g. cause disturbed sleep- or maximum levels of overworking due to a manager, ing patterns, increased incidence of cardiovascular dis- who, to the best of her knowledge, had no intentions ease, gastrointestinal and reproductive disorders, of delegating overtime. musculoskeletal disorders, chronic infections, mental With respect to adverse selection, the simulations health illnesses; Afonso, Fonseca, and Pires 2017; mirror the predictions of principal-agent theory (e.g. Tucker and Folkard 2012), their job performance (e.g. Hart and Holmstro €m 1987) and generate new plaus- burnout, occupational accidents; Tokuda et al. 2009), ible hypotheses. The results show that undervaluing and family/social life (Fagan et al. 2012). In extreme employee competences generates opportunities to cases, consequences are fatal. In Japan, where working shirk. The larger the undervaluation, the greater the long hours is relatively frequent, phenomena of kar- intensity of opportunistic behaviour. On the other oshi, i.e. sudden death due to overworking, usually a hand, a belief that the employee is more competent direct result of acute cardiovascular events such as than he actually is results in a necessity for him to stroke and karojisatsu, i.e. suicide due to overwork, are work harder than assumed by his manager in order to recognised (Hiyama and Yoshihara 2008). complete a task on time. New hypotheses predict that Numerous theories highlight that task performance adverse selection affects primarily one dimension of is decreased due to conflicts between employees and aberrations from managerial expectations, i.e. aberra- their supervisors. While shirking and overworking can tions of effort. Moreover, the effects of adverse selec- certainly be the effects of power struggles involving tion are only temporary – as the employees gain demotivated employees or overdemanding managers, experience, the managers learn their true abilities. studies suggest that it is often not the case (Paulsen Our research shows that task uncertainty is a very 2014). We presented a computational model to answer serious source of aberrations from managerial expecta- a deeply sociological question, namely, can the struc- tions, as it impacts both working time and, indirectly, ture of work organisation, in combination with adverse employee effort. Interestingly, if task difficulty mis- selection and task uncertainty, generate opportunities judgement is of equal level but in the opposite direc- for unintended functions, i.e. shirking and overworking tion, overworking is more severe than shirking. This (Merton 1996). Our model, ascribing no ill will to any finding portrays actors’ perception of time. For of the involved actors, shows that these phenomena example, let us consider a task that objectively can occur in any type of work contracted on the basis requires two days to finish. In the first scenario, the of working time, when the specific organisation of manager overestimates the difficulty of the task and ERGONOMICS 1007 sets the deadline for three days. In the second scen- though no quantitative empirical data was used to ario, she/he underestimates it and sets the deadline validate the predictions of the model, it does not for one day. Assuming the employee informs the man- mean that the model is completely unvalidated. The ager about completing a task immediately (after two existence of certain independent variables, the rela- days), in the first case, he/she only decreased the time tionships across and between these variables, as well of completion by 33%. In the second case, it took as the concept of shirking and overworking are him/her twice as long as it was expected. Such a strongly rooted in theoretical approaches (e.g. princi- setup results in managers experiencing poor perform- pal-agent theory) and empirical data (e.g. Antosz 2018; ance as unproportionally exaggerated, compared to Antosz and Verhagen 2020). This supports the concept superior performance. Another unanticipated result is and criterion validity of the model’s underlying that task uncertainty can create an effect of adverse assumptions. Also, the fact that some simulation selection (employee informational advantages regard- results are consistent with predictions occurring in ing competence levels). Misestimating task difficulty other studies (e.g. Hart and Holmstro€m 1987) strength- leads to the manager misestimating the increase in ens the validity of the proposed mechanism. employee competences, which in turn affects the Naturally, the presented computational model can effort aberrations. Moreover, the asymmetry of the become a foundation for further scientific advance- effects of opposite directions of task uncertainty ments. Future directions for development include, for influences the level of informational advantages. example, introducing interactions among employees. Specifically, overestimating task difficulty leads to In-depth interviews (Antosz 2018; Antosz and smaller informational advantages regarding competen- Verhagen 2020) suggest that employees increase their ces, compared to underestimating them. competence levels through interacting with others and use social learning to estimate the acceptable lev- els of shirking and overworking in their workplace. Limitations and further developments Another increase in model complexity entails introduc- Conceptualising models always entails a trade-off ing heterogeneity with respect to task uncertainty. between simplicity and applicability to real-life situa- There are two distinctive groups of managers, who dif- tions. Therefore, several decisions were made to fer in their personal experience of performing the reduce complexity and achieve the primary purpose same work tasks as their subordinates (Antosz 2018; of the model. Those decisions limit the scope of the Antosz and Verhagen 2020). Managers who previously model and further applicability of its results. This performed the same work tasks as their now- model should, therefore, be regarded as an ideal type subordinates are less prone to task uncertainty than (Weber 1949) or a typification (Boero and managers, who have not. Introducing trust and repu- Squazzoni 2005). tation is another attractive direction for further model The proposed mechanism is limited to the struc- development. Employees, whose violation of tural origin of shirking and overworking. It is debate- organisational norms regarding shirking is detected by able to what extent techniques, which are detached co-workers, could be punished by the means of from real-life data, can offer reliable estimates of phe- decreasing their reputation. This direction is especially nomena. Computational modelling belongs to a group interesting because reputation has previously been of in silico techniques, which allow for perfect control treated as a tool for social control in computational of all confounding factors. It must be emphasised that models (Hales 2002). Lastly, several studies suggest in real life, on top of structural, other factors influence that in some settings competences negatively impact the level of shirking and overworking. The impossibil- effort (Szumowska, Szwed, Kossowska and Wright ity of including all of them even in the most rigorously 2017). Yet, as both competences and effort positively controlled experiment points to the challenge of veri- affect task performance, the more subtle, direct rela- fying model validity. However, to cite the classic, the tionship between them is cancelled out and therefore, most that can be expected from any model is that it difficult to observe in experimental settings. can supply a useful approximation to reality: all models Computational modelling and simulation, allowing for are wrong; some models are useful (Box, Hunter, and more scrutiny in controlling the possible complex rela- Hunter 2005; 440). Hopefully, this model is, in fact, tionship between independent variables, could shed useful in making attempts to estimate the possibilities light on that relationship. 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