Next Article in Journal
Fabrication of Earth-Abundant Electrocatalysts Based on Green-Chemistry Approaches to Achieve Efficient Alkaline Water Splitting—A Review
Previous Article in Journal
Evaluation of the Laboratory Degradation Performance of a Straw Drainage Board
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Heavy-Work Investment, Its Organizational Outcomes and Conditional Factors: A Contemporary Perspective over a Decade of Literature

1
School of Organizational Behavior, Tel-Hai College, Qiryat Shemona 1220800, Israel
2
School of Management, 3000 Chem. de la Côte-Sainte-Catherine, HEC Montréal, Montréal, QC H3T2A7, Canada
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(24), 16362; https://doi.org/10.3390/su142416362
Submission received: 31 October 2022 / Revised: 28 November 2022 / Accepted: 30 November 2022 / Published: 7 December 2022
(This article belongs to the Section Sustainable Management)

Abstract

:
The construct of heavy-work investment (HWI) is bi-dimensional, revolving around the investment of both time and effort at work. The current paper expands the research thinking and joins the pioneering studies that explore HWI as a relatively new concept in the work-related literature (since 2012). The prime aim of this conceptual paper is to develop a model regarding the intricate relationships between the dimensions of HWI and their work outcomes (with emphasis on possible conditional factors). In particular: (1) we refine the definition of HWI by accounting for the different levels of time and effort investment and (2) we outline multiplex propositions with regard to possible (positive and negative) outcomes of HWI, considering different moderators that can potentially impact these associations. Finally, we offer practical implications for human resource management.

1. Introduction

In recent years there has been a considerable increase in the time invested in work, especially in professional and managerial roles, which is also a byproduct of greater accessibility to technology, industrial competition, and more recently, the COVID-19 pandemic [1,2]. The exploration of heavy-work investors can be traced back to as early as the 1970s (e.g., [3]). Since then, a term coined by Oates [3]—workaholism—has been considered in both academic and non-academic circles as the prominent representation of heavy-work investment (e.g., [4,5,6,7]).
However, the umbrella concept of heavy-work investment (HWI; see Appendix A for a glossary of the acronyms used throughout the paper) was introduced by Snir and Harpaz ([8], after [9]) as generally revolving around (1) working long hours and (2) investing increased effort at work. These two dimensions of HWI are, respectively, titled: (1) time commitment (HWI-TC) and (2) work intensity (HWI-WI; see also the term work intensification used by Fein et al., [10]). Following this typology, further research has addressed it differently, such as the work of Rabenu and Aharoni-Goldenberg [11]. They described three types of workers who work long hours (HWI-TC) but vary in their level of work effort (HWI-WI): (1) the excessive work investor (EWI), who is characterized by time investment (HWI-TC) and high levels of effort at work; (2) the moderate work investor (MWI), who is characterized by HWI-TC and moderate levels of effort at work, namely, working long hours but balancing work demands with other personal needs (e.g., social and physical, such as taking breaks to eat) and (3) the low work investor (LWI), who is characterized by HWI-TC and low levels of effort at work. For other examples of work investment typology, see Astakhova and Hogue [12,13].
Additionally, Snir and Harpaz [14] proposed a conceptual model in which HWI mediates between its different predictors (external predictors, such as basic financial needs and employer demands and internal predictors, such as passion to work, work engagement, and addiction to work) and individual, family and workplace outcomes (e.g., physical and mental health, work satisfaction, productivity, work–life conflict, etc.), with potential moderators (e.g., job type, fairness, etc.) (see [14], p. 6).
The phenomenon of HWI has both positive and negative sides (e.g., [1,15]). On the positive side, Shamai et al. [16] demonstrated that heavy-work investors report higher levels of affective happiness than moderate workers. Employees may view their work as a place for self-fulfillment and enjoyment (e.g., [17,18]). In the same vein, Tziner et al. [19] and Rabenu et al. [20] found that HWI-WI is negatively related to burnout (i.e., an increase in effort at work corresponds to a decrease in experienced burnout). On the other hand, those working longer hours may be perceived as “heroes” at their place of work and be held as role models [6]. On the negative side, Dembe et al. [21] found negative effects of overtime on health, and Rabenu and Aharoni-Goldenberg [11] pointed to the possibility of investing long working hours (HWI-TC) but, in tandem, exerting minimal effort in the job (i.e., presenteeism; see Appendix B).
To reiterate, the concept of HWI elaborates on the characteristics of workers who overwork—mainly educated workers, managers, and professionals [1]—by exerting a high investment of time, effort, or both. In this regard, Snir and Harpaz [14] raised the question of “whether a heavy work investor has to be high on both dimensions in order to be classified as such” (p. 7). Embracing this notion, we stipulate that both high temporality/frequency (i.e., time) and intensity (i.e., effort) are core dimensions of HWI (see also [14], p. 8). Following Rabenu and Aharoni-Goldenberg’s [11] work, in which HWI-TC was held constantly high, and therefore, not all HWI scenarios were discussed we, therefore, propose a fresh look at the construct by categorizing levels of HWI on a two-dimensional 3 × 3 grid. This is presented in Figure 1, where one axis reflects the investment of time, and the other reflects work intensity. Importantly, we stress that, hierarchically, higher investment of either (time commitment or work intensity) takes precedence or priority over lower investment. For instance, a combination of low HWI-TC and moderate HWI-WI results in a moderate heavy-work investor, while a combination of high HWI-TC and moderate HWI-WI results in a high heavy-work investor. It is important to note that by TC we mean the work hours per day an employee invests in their job (i.e., not relative to the working hours of colleagues). As such, we suggest the following categorization of the HWI-TC dimension, based on the rationale provided in Rabenu and Aharoni-Goldenberg [11]: (1) low TC = 0–6 working hours, per day; (2) moderate TC = 6–10 working hours, per day and (3) High TC = 10+ working hours, per day.
As can be seen in Figure 1, out of nine HWI categories, there are five (=around 55.6%) high HWI groups, hinting at the prevalence and proliferation of a heavier investment at work as a default in the work domain. Before elaborating further, we draw attention to two unique configurations: low TC + high WI and, vice versa, high TC + low WI. Employees ascribed to the former or latter groups are still considered as high heavy-work investors, as they invest either a great deal of time at work or significant effort. For example, low TC + high WI workers can be considered part-timers (limited by their contract to certain daily or weekly hours, but may work extra-hard during the shift, e.g., part-time nurses). On the other hand, a combination of high TC + low WI can be considered as presenteeism (see Appendix B), but, regardless of the supposed discrepancy in performance, this is still another example of a heavy-work investor.
Furthermore, it is important to note that engaging in HWI is critical only for certain employee populations—those who are primarily in professional and managerial positions (as mentioned above). They often work at least 60 weekly hours (or more) [22,23], while others struggle to find sufficient work. Jacobs and Gerson [24] described this phenomenon: “In fact, while a large segment of the labor force is working longer and harder than ever, another group of workers is confronting the problem of finding enough work” (p. 13). This gap in the amount of work performed may become even greater in the future, due to increased automatization and reliance on cyber-entities such as robots, artificial intelligence, and algorithmic management, among others. These are thought to easily sustain the demand for routine and easy-to-computerize human work in certain jobs and industries, and even to replace human employees and managers altogether (e.g., [25,26,27,28,29]). As such, it is expected that manufacturing, for instance, will involve fewer humans and more autonomous systems in the future [30].
Finally, a disclaimer: when we refer to the concept of HWI, this reflects allocating time and effort in a particular manner. However, in principle, a person can work at more than one job: for example, working part-time in two places, one on some days and another on other days, or working self-employed in addition to another work arrangement or, alternatively, working as an employee in the morning and as a freelancer in the evening. Such situations invariably drive the individual to a considerable investment of time, and most likely, effort as well. We suggest that these specific and complex situations should be investigated in future research.

2. Goals and Contributions of the Current Paper

The current paper offers important goals and contributions to the known HWI literature. HWI is a relatively new construct, gaining more scholarly attention since 2012 [8,14]. Recently, Tabak et al. [31] suggested that “a fruitful area for future research would be to investigate potential moderators of the relationships between HWI types and outcomes. Future research should explore how these factors may change the relationships between HWI types and their outcomes” (p. 10). We agree with this notion and, thus, accept the challenge: our proposed model is a direct response to this recommendation, and the main contention is that there is still much more empirical and theoretical research warranted to unveil the complexity of relationship(s) between HWI and other constructs. Based on this, we outline the goals and contributions of the paper as follows:
First, we offer a more elaborate and nuanced stance on HWI, arguing that it is not as simple as it may seem at first glance. By portraying the possible categories of HWI, taking the levels of HWI into consideration (see Figure 1), this creates a more multiplex definition of the concept. The notion expands on Rabenu and Aharoni-Goldenberg’s [11] conceptualization of heavy-work investors.
Second, we propose an elaborated HWI model that zooms in on its original dimensions (time commitment—investment of time at work—and work intensity—investment of effort at work), their possible outcomes, and different important moderators on the HWI–outcomes relationships (rarely discussed in the literature). To be precise, this is an expansion on Snir and Harpaz’s HWI model ([14], p. 6; see also [20]). It is critical to emphasize that this original division (time vs. effort) was found to be extremely important in predicting work-related outcomes, such as job burnout, with differentiating effects (e.g., [19,20]).
Third, this conceptual paper has a different focus from Tabak et al.’s [31] model, which described HWI by proxies (i.e., workaholism, and work engagement). While Tabak et al.’s [32] model further explored the outcomes of these proxies, the current paper explains the outcomes by the original dimensions of HWI.
Fourth, from an analytical perspective, Tabak et al.’s [31] propositions outline bivariate relationships. We believe that this might oversimplify the complex associations between HWI and its outcomes, and, therefore, propose a novel multivariate outlook that comprises different interesting moderators and differentiating viewpoints on HWI.
Last, since HWI is a particularly important and prevalent topic in our work–life domains (e.g., [14,31,32]), we offer practical recommendations to bolster the understanding of human resource management of the concept and challenges surrounding HWI.
That being said, the main goal of the current paper is to develop propositions regarding the intricate associations between the dimensions of HWI (time and effort) and their positive/negative outcomes. Notably, the choice of variables/constructs, described in the following sections, draws inspiration from Tabak et al.’s [31] model propositions, but with an emphasis on the dimensions of HWI (and possible moderators).

3. HWI and Positive Outcomes for Organizations

The association between HWI and positive outcomes has already been elaborated in Snir and Harpaz’s conceptual model of HWI ([14], p. 6). They proposed different types of heavy-work investors, such as dispositional (e.g., workaholics are “addicted to their work” and the work-devoted are “those with high passion for their work”, p. 12) and situational (e.g., the needy and the employer-directed heavy-work investors). Moreover, these ‘types’ may experience different personal work outcomes, including positive outcomes such as work satisfaction and productivity ([14], p. 6). Following Snir and Harpaz’s Proposition 1b ([14], p. 14), positive personal work outcomes will be highest among work-devoted investors, lowest among workaholics and needy heavy-work investors, and moderate among employer-directed heavy-work investors. Their proposition was based on the level of control one has over one’s HWI, namely, higher control over HWI leads to higher positive results.
Very recently, Snir and Harpaz [33] have found, as expected by their model and earlier propositions, that the work-devoted heavy-work investors had the most positive well-being and health-related outcomes (i.e., stronger positive feelings, better current health, better body mass index [BMI], adequate hours of sleep). On the contrary, the needy type had the worst outcomes regarding well-being and health (i.e., a higher level of stress, physical pain, weariness throughout the day, and aches that interfere with regular activities).
As another example, Shimazu et al. [34] researched two types of HWI (i.e., job-engaged employees and workaholics) and found that job engagement positively predicted work performance, while no significant association was found between work performance and workaholism. In addition, Su [35] researched workers in the US and found that workaholism was negatively related to job satisfaction, while work engagement was positively related to it. Similar results with regard to job satisfaction were found in Shimazu et al.’s [34] research in Japan (although their job satisfaction measure relied on a single item only). As the last example, workaholics who are addicted to work have lower work satisfaction and psychological well-being than workers who are passionate about their work (e.g., [36,37]; see also [38]).

3.1. HWI and Job Performance

Campbell [39] defined performance as “a set of behaviors, the implementation of which is relevant to achieving the goals of a company organization” ([40], p. 4). An investment of effort in the job can be regarded as an indirect (role-specific) performance [39]. As HWI includes two dimensions—heavy investment of time and effort—it becomes more apparent why HWI-WI (investing high effort) contributes, by definition, to job performance. Indeed, Popa et al. [41] have found that HWI-WI has a positive impact on work-related performance in two samples from Romania and Japan. Therefore, we propose the following:
Proposition 1a.
HWI-WI is positively associated with job performance.
Furthermore, according to Campbell [39], there is another component that is regarded as indirect performance: self-discipline. This component is expressed, among other things, by meticulously following instructions and timetables, even if this means investing long hours. Therefore, this component (HWI-TC) might foster a positive relationship with performance at work. However, as already understood in the literature, the relationship between hours of work and performance is not unequivocal.
There are two main reasons for this. First is presenteeism, which may be defined as attending work but not being fully functioning during that working time (e.g., [11,42]) (for further elaboration and new definitions of presenteeism, see Appendix B at the end of this paper). Astakhova and Hogue [12,13] regarded this phenomenon as pseudo-heavy-work investment (P-HWI), meaning there is apparent HWI without the internal commitment to do the job, de facto. Rabenu and Aharoni-Goldenberg [11] considered this an example of the low-work investor (LWI): in these “working hours” the employee might play computer games, shop online, chat on the phone, etc. The reasons workers engage in presenteeism are many, such as illness, overtime pay, need to impress, organizational culture, and unwillingness to go home for personal reasons, among others (e.g., [11,14,42]).
Second, there is a decrease in hourly returns, as, normally, fatigue increases as time flows (e.g., [43,44,45,46]). Rabenu and Aharoni-Goldenberg [11] reviewed the literature regarding overwork and found that those who work more than 12 h per day have fewer opportunities for recovery, and moreover, that overworked employees are more prone to burnout. Following this, Rabenu [1] stated: “It is of paramount importance to alert managers and employees that long working hours do not indicate high job performance” (p. 265). Moreover, Popa et al. [41] found a negative impact of HWI-TC on work performance. These perceptions point to a three-way moderation effect. To elaborate, the effect that investment of time (i.e., HWI-TC) may have on job performance is conditioned by the degree of effort put into the work itself (i.e., HWI-WI): one might invest a great deal of time at work but with little effort (e.g., presenteeism, see Appendix B). However, this moderation effect is, by itself, conditioned by the extent of recovery: the more intensely an employee works, the greater the need for recovery in order to maintain a sustained level of work performance. Thus, we argue that increased time investment combined with low-intensity work does not promote better performance, but high-intensity work necessitates a certain degree of recovery for the worker to keep functioning well (for further reading about recovery at work, see [47]). Therefore, we propose:
Proposition 1b.
The relationship between HWI-TC and job performance is moderated by (a) the degree of HWI-WI, which is conditioned by (b) the level of recovery.

3.2. HWI and Job Satisfaction

Working time is visible to managers, especially when working at the organizational site, and therefore, they use it as a convenient, though inaccurate, proxy for job performance. On the other hand, effort is more internal and harder to observe [48]. Thus, heavy-work investors more frequently obtain positive feedback from their managers with regard to their HWI-TC (and are sometimes idolized as “heroes”; e.g., [6]) and less (if at all) regarding their effort (HWI-WI). As such, effort investment is more intrinsically appraised by the employees themselves and less so by managers who mostly look for visible (“objective”) criteria, such as working hours, and organizational outcomes/results (e.g., sales, program rating, etc.). This emphasizes the role of the supervisor’s feedback and its impact on the employee.
Bem’s self-perception theory [49] claims that in the absence of an existing stance or in situations where the stance is weak, people develop their attitudes by observing their own behavior and drawing conclusions from it (similar to the way they try to explain the behavior of others). Applying Bem’s theory [49], it is plausible that the workers may conclude, based on their HWI-WI, that they are satisfied with their work (see also [20]). In this regard, HWI-WI is perceived as something that the employee is more autonomous about, in relation to its execution, even though there is less objective/concrete feedback from others (in comparison to HWI-TC). Indeed, positive relationships between HWI-TC, HWI-WI and job satisfaction (based on the positive relationship between passionate and engaged HWI with job satisfaction) can be hypothesized. In contradistinction, Popa et al. [41] found a negative impact of HWI-TC on job satisfaction, while HWI-WI had a positive effect on job satisfaction in two samples (Romania and Japan). The inconsistencies underlying the relationship between HWI-TC and job satisfaction may be explained by an indirect effect—a conditional (moderating) factor, such as a manager’s positive feedback. We hope our explanation adds another perspective to Popa et al.’s [41] results. Therefore, we propose:
Proposition 2a.
HWI-WI is positively associated with job satisfaction.
Proposition 2b.
The relationship between HWI-TC and job satisfaction is moderated by the extent of positive feedback from the manager.
Proposition 3.
The relationship between HWI-WI and job satisfaction will be greater than between HWI-TC and job satisfaction.

3.3. HWI and Positive Affect

The literature connecting HWI and positive affect is based mainly on three theories: activity theory, flow theory [18] and the IKEA effect [50,51]. Activity theory “points to the fact that interesting activities can supplement the pleasures that are achieved through people’s emotions and physical comforts” ([52], p. 41). Flow theory revolves around being involved in an interesting activity that is experienced as enjoyable because there is a balance between challenge and skill, and in which “people describe their thoughts and actions when they are in that context as spontaneous and effortless, even though what they are doing is often difficult and risky” ([53], p. 387). Shamai [18] postulated that since heavy-work investors invest more hours at work, they might experience more activities with flow than other workers and are, therefore, expected to exhibit higher levels of positive affect than other employees (for further reading, see [18], Proposition 1a, p. 214). The third rationale is based on the IKEA effect: those who have made an effort to build furniture by themselves (bought from IKEA, hence the name), appreciate, love it and attribute more sentimental value to it than people who bought ready-made furniture [50,51]. In support of this, Shamai et al. [16] found that heavy-work investors reported higher levels of affective happiness than moderate-work investors. Additionally, they suggested that heavy-work investors might experience less negative affect since positive and negative affects “vary inversely in frequency” ([18], p. 214).
However, as we saw in Section 3.1, working hours do not always indicate work that has flow (see, for example, presenteeism in Appendix B). The question is whether there is another explanation for the link between HWI and positive emotions.
Ng et al. [54] demonstrated that the act of working assuages unpleasant feelings (e.g., anxiety, depression, and/or guilt) that arise when not working (see also [55,56]). Therefore, “the act of working might play a role as a mood modifier…working in order to escape or avoid dysphoria” ([57], p. 194). Moreover, Baruch [58] argued that workaholism is a means to escape from problems at home. Avoiding these problems by working for longer hours may generate positive outcomes (for the worker), or at the very least, prevent negative consequences related to these employees’ challenges. The propositions regarding assuaging unpleasant feelings and/or avoiding unpleasant issues while working overtime are consistently referred to with regard to heavy-work investors who are addicted to work (workaholics). If we also take into account their lives outside of work, they may even be addicted to just “doing” things (doingism; [48], p. 12). Indeed, Snir and Zohar [59] found that workaholics do experience more positive affect while working than they do during leisure activities.
We believe that if we take this proposition one step further, we can assume that the important component of alleviating negative emotions is the de facto ‘doing’ and not the number of working hours alone. The act of doing might be expressed more in the effort invested and less in the working hours themselves, as working on something (not necessarily work-related) may cause someone to develop positive attitudes towards the object of the action (e.g., [20,50,51]). As was presented earlier, one can work long hours but with a low level of effort (e.g., presenteeism, LWI, P-HWI). Therefore, we postulate that long working hours will assuage negative emotions and manifest in flow only if it also involves high effort. Working long hours, without a substantial investment in effort, will not necessarily reduce negative emotions and, invariably, does not induce the feeling of challenge that is needed for flow because the act of doing interesting activities may be low or even absent. Therefore, we propose:
Proposition 4a.
HWI-WI is positively associated with positive affect.
Proposition 4b.
The relationship between HWI-TC and positive affect is moderated by the degree of HWI-WI.

3.4. Cultural Context

Culture may moderate associations related to HWI and the degree of HWI (e.g., [2,32]). There are cultures that endorse and promote long working hours and those working increased hours may even be idolized or perceived as role models [34], based on their research in Japan). These kinds of working climates and cultures encourage employees to invest more time at work on the one hand and place fewer limitations on routines of excessive time commitment on the other (see [4]). For example, Shkoler and Kimura [2] found interesting results between Israel and Japan, while Shkoler et al. [48] found differences between Israel and Romania regarding investing effort in work:
As Israel is known to have an overworking job culture, working much more hours than the OECD’s average [60], investing time in working (even on breaks) may seem normative. However, in Romania, one must probably have a high drive for work (i.e., being a workaholic) in order to be enthusiastic about pouring effort into it on breaks. ([48], p. 12)
In cross-cultural research of five countries (Japan, Israel, USA, Belgium, and the Netherlands) Snir and Harpaz [61] found that, although in Japan employees were working more hours than in the other countries, work centrality (for instance) was similar across all countries. Therefore, different countries can still share the same level of orientation toward working long hours (“working long hours might be the behavioral outcome of attributing high centrality to work”; [61], p. 385), and this orientation will manifest in the efforts invested at work (for further reading on workaholism and culture, see [58]).
As an expression of culture, heavy-work investors in countries with high annual working hours (i.e., oriented towards working long hours: see, for example, [60]) may feel good about themselves and feel more positive affect while working than if they are the “aberration” in their own working culture. Therefore, we put forward the following proposition:
Proposition 5.
In countries with high (as opposed to low) annual working hours, HWI-TC is positively associated with positive affect.

3.5. HWI and Turnover Intentions

According to Festinger’s cognitive dissonance theory [62], when people experience inconsistencies between their beliefs, attitudes and behaviors, they feel an unpleasant disharmony (dissonance). To eliminate/balance this dissonance, individuals might change their attitudes. One of the situations in which dissonance becomes very intense is when we invest great effort to achieve a certain goal which we find, in the end, to be negative or not valuable for us. In this instance, we might change our attitude and begin to see it in a positive way (i.e., effort justification by matching attitude to behavior).
Related to cognitive dissonance is the economic phenomenon of sunk cost, which can help us understand the interrelation between investment in work and turnover intentions. Based on the sunk cost rationale, we may postulate that as employees invest more resources at work, they will have less intention to leave the organization they have invested in so much. To elaborate, as the employee invests more resources (e.g., time and energy) at work, they will be more inclined to remain. This argument is based on “sunk costs”, namely, an expense that has already been incurred, that is non-refundable and that is, therefore, no longer relevant for future decision-making. An example of this phenomenon is managers who continue with failed projects even when there is no merit in doing so [63].
Nevertheless, as can be seen in recent events, the economic rationale of sunk cost is not always realized. Returning to Festinger [62], it is possible to avoid cognitive dissonance by matching the behavior to the attitude, and not the other way around. To elaborate, of late, we have witnessed the phenomenon of the ‘Great Resignation’ (e.g., [64,65,66]), whereby employees who (probably) have negative attitudes towards the work domain (for example, a sense of imbalance in demands between leisure, family and work, unfair pay, etc.) leave work (i.e., turnover) as a way to cope and reduce the dissonance they experience. Hence, there are two possibilities for the relationship between turnover intentions (and actual turnover) and HWI—positive or negative. However, the direction and extent of this association are conditioned by plausible moderators, such as the generation to which the employees belong (e.g., Gen X, Gen Y, etc.), their financial obligations/needs, and so on. That being said, it is clear that HWI-TC is linked to turnover intentions, but this relationship is unclear, or indirect. Therefore, given the plethora of indirect variables (moderators/mediators) that could potentially impact this association, we propose:
Proposition 6a.
HWI-TC is associated with turnover intentions.
In addition, Popa at al. [41] found that work intensity (HWI-WI) may encourage employees to work with greater intensity in their organization. Indeed, making an effort may result in mainly positive consequences for the individual, and, thus, the probability of turnover intention is lower than in the case of negative outcomes. This is supported by the rationale outlined throughout the current paper, and Propositions 4 and 9, specifically (see also [20,50,51]), therefore, we propose:
Proposition 6b.
HWI-WI is negatively associated with turnover intentions.

4. HWI and Negative Outcomes for Organizations

Conversely, what would be the case should job demands outweigh the job resources? Or, in other words, what are the detrimental effects of HWI, having discussed its many positive aspects?
Generally, empirical evidence shows that HWI can lead to negative outcomes. For instance, Dembe et al. [21] found negative effects of overtime work on health. In fact, there is extant research regarding the individual and organizational outcomes of workaholism [67] as workaholics are typically associated with poorer mental and physical health; emotional and cognitive exhaustion; poor sleeping habits; cardiovascular problems; poor social relationships and work–life conflict (e.g., [7,54,68,69]). Furthermore, Clark et al.’s [70] review noted several work-related, family, and individual outcomes of workaholism, such as higher levels of job stress; counterproductive work behaviors and distrust of co-workers; poor family relationships; family dysfunction; greater work–life conflict; as well as lower satisfaction with life outside of work, increased burnout, and health issues. In fact, as workaholics experience feelings of guilt and anxiety when not working (as mentioned above), and thus, often work longer than others, they tend to suffer from emotional exhaustion, cynicism, and depersonalization.
However, many areas of disagreement also exist with regard to the affective experiences of workaholics. For example, one area of research discourse is work enjoyment [70], whereby, while some argue that true workaholics really do enjoy the act of working and experience positive emotions, others emphasize that they have low work enjoyment (for further reading, see [48,57]). In the next section, a few possible negative outcomes of HWI will be presented.

4.1. HWI and Counterproductive Work Behaviors (CWB)

One possible negative outcome of HWI may be counterproductive work behaviors (CWB). In recent years, CWB (e.g., [71,72,73]) or workplace misbehaviors (e.g., [32,71,74]) have received considerable attention from researchers, as these manifestations have significant psychological, sociological, and economic implications for the organizational environment [74,75]. CWB might be directed at the organization or its members (workers and management alike), and hence are costly for both the organization and the individual [76]. These behaviors almost always infringe upon important organizational norms and cause damage to an organization’s objectives, procedures, productivity, profitability, and employees themselves [15,75,77]. CWB include employees reducing or withdrawing their input to balance the negative social exchange process [78]; feeling negatively towards the organization; feeling less motivated; exhibiting distrust (toward to the manager and/or the organization) and even retaliating against the organization [79], which might manifest as harassment, theft, sabotage, or worse [77,80].
It is plausible that the relationship between HWI and CWB is indirect by default. For example, if EWIs perceive their workplace as unfair based on their investment, they might try to reach an equilibrium by, for instance, reducing productivity, stealing office items, arriving late to work, and engaging in presenteeism, among others (e.g., [81,82]). In this case, the perceived unfairness is a conditional factor, a buffer effect—a moderator in statistical terms—on the relationship between HWI and CWB. Therefore, we propose:
Proposition 7a.
The relationship between HWI and CWB is indirect.
Proposition 7b.
Perceived (un)fairness/(in)justice moderates the association between HWI and CWB, such that the greater the unfairness/injustice, the stronger (and more positive) the relationship between HWI and CWB becomes.

4.2. HWI and Work–Life Balance/Conflict (WLB/WLC)

Another possible negative outcome of HWI may be work–life conflict, which is regarded as a work stressor.
The fundamental logic behind stress is the relationship between a person and their environment, which is appraised as taxing and endangering their well-being [83]. Thus, psychological stress is defined as the feeling of emotional strain and pressure and physiological reactions to stressors. It is a state of fatigue caused by being exposed to heavy work-related stressors or loads [84,85,86,87,88] to the individual [89]. There are many different stressors, including (1) interpersonal relationships (e.g., relationships between friends and neighbors, the poor relationship among work teams, and work–life conflict); (2) task-related (e.g., role ambiguity, large workload, unclear tasks, and task conflicts); (3) organization-related (e.g., the organizational pattern/culture, management model, and organizational support) and (4) physical and mental stressors (e.g., daily life, inconvenient transport, and unfair treatment) (e.g., [84,90]).
Work–life balance (WLB) and work–life conflict (WLC) are often used interchangeably (e.g., [91,92,93,94,95,96]). Work–life balance is usually defined as the absence of conflict between work and family or personal roles (e.g., [92,95,97]). Generally speaking, WLB is the degree to which an individual can simultaneously balance the emotional, behavioral and time demands of (a) paid work; (b) family and (c) personal duties [92,93,94]. Conversely, WLC manifests when at least one domain (e.g., work or personal life) interferes with the other [98]. This interference may occur because an individual’s attitudes, emotions, skills, and behaviors in one domain tend to flow into the other, and this can work both ways—for instance, from work to family and vice versa (work–life spillover theory; see [91,99]). WLC has been linked to a plethora of negative outcomes, such as reduced job satisfaction; lower organizational commitment; lower productivity and performance; lower career satisfaction and success and higher absenteeism and intention to quit; as well as employee burnout, job stress, poorer physiological and psychological health, substance abuse, and diminished family functioning, among others. In addition, workaholics (a type of heavy-work investor) have been found to exhibit higher WLC than others (e.g., [36,91,97,100,101]).
The theory that best explains the relationship between HWI and WLC is the conservation of resources theory (COR; [102,103,104] see also [105]). This widely used theory (e.g., [20,72]) illustrates the motivations that drive individuals to both maintain their current resources and pursue new ones. They are defined as things that we value, specifically: objects, states, and conditions (e.g., promotions at work, good relationships, energy, time, and money, etc.).
Capitalizing on COR theory, the relationship between HWI and its possible negative outcome of WLB becomes clearer. It is a simple linkage: the higher the investment in one’s work (be it time or effort), the higher the propensity for resources loss, and the increased probability of experiencing stress and WLC (i.e., work interfering with other life domains) (e.g., [41]). Notwithstanding, we must emphasize the cardinal role of time in relation to WLC. First, Rabenu [1] stated that “individuals working reduced hours (including those working remotely from home) might find that…they have to do the same amount of work in less time (Kelliher and Anderson, 2010). Consequently, these employees experience excessive effort (work intensification) in their jobs (Burchell, 2002; Fein et al., 2017)” (p. 276). In addition, Fein et al. [10] concluded that “working hours do not stand alone when employers consider work–life balance programs and policies…[and that] work intensification should be monitored along with total working hours as a strong predictor of work–life interference” (p. 369). As we can deduce, the time aspect of HWI is of paramount importance and relevance in relation to WLC. A simple example: an employee working for 12 h (regardless of the effort exerted during these hours) is fundamentally different from an employee who works for three hours (again, regardless of the effort invested) in terms of how the devotion of time can (and to what extent) interfere with WLB. To conclude, the time dimension of the job is key to understanding WLC, above and beyond the effect that HWI-WI may have on WLC (for further reading on WLC, we encourage reviewing [1]), Therefore, we propose:
Proposition 8a.
HWI-TC is positively associated with WLC.
Proposition 8b.
HWI-TC moderates the relationship between HWI-WI and WLC, such that HWI-WI is positively associated with WLC only when HWI-TC is high, but as HWI-TC decreases, the relationship between HWI-WI and WLC decreases.

4.3. HWI and Work Burnout

Work burnout is usually described as a psychological chronic stress syndrome (see [102,106]) comprising (1) emotional exhaustion (individuals feel drained, with no energy to face another day); (2) feelings of distance from others (cynicism or depersonalization: generally following emotional exhaustion, employees develop a state of mind that serves as a defense mechanism that nurtures negative or cynical attitudes about their organization and/or colleagues) and (3) feelings of reduced personal accomplishment/efficacy (in practice and in their subjective consciousness, individuals’ levels of performance decline) [19,107].
Burnout is positively associated with a variety of negative outcomes, from employee health, such as cardiovascular diseases [108], hyperlipidemia [109], to risk of diabetes [110] and even depression [111]. Moreover, burnout may have detrimental effects on attitudes toward the organization, employee performance [112] and work misbehaviors ([82,113]; see also [114,115,116]). Moreover, burnout may also be affected by job demands (e.g., physical demands, risks and hazards) and/or job resources (e.g., knowledge, autonomy, supportive environment) (e.g., [116]), and work stressors (e.g., [82,116]). For further reading on this topic, please see Schaufeli et al.’s [117] extensive work.
The COR theory ([102,103,104]; see also [105]) emphasizes that loss of the above-mentioned resources (Section 4.2) will drive individuals to certain levels of stress, and if balance is not resumed and sustained, in time, the person will also experience burnout (a consistent and chronic deficit of resources). Specifically, the theory states that: (1) individuals with higher resources will likely gain in resources, but similarly, individuals with fewer resources are more likely to experience resource losses; (2) initial resource loss will lead to resource loss in the future; (3) initial resource gains will lead to resource gains in the future; (4) a lack of resources will invariably lead to defensive attempts to conserve the remaining resources (sometimes expending more resources, leading to an ever-increasing cycle, a positive feedback loop, of resources loss that, ultimately, ends in burnout). For further reading on the theory, see Hobfoll [102,103,104] and Halbesleben et al. [105].
However, extant research is ambivalent about the association between HWI and burnout. For example, Tziner et al. [19] and Rabenu et al. [20] found that HWI-WI is negatively related to burnout. Their findings show that the commitment of time is not necessarily associated with burnout, but rather the investment of effort that may indicate job meaningfulness (e.g., IKEA effect: see Section 3.3; [50,51]), which in turn may act as a job resource to help the individual mitigate experienced work burnout. Ivancevic et al. [118] have put forward the proposition that HWI has negative consequences on all dimensions of burnout in their study of Serbian respondents. Overall, this line of research is still in its infancy and future scholarly work should investigate contexts and conditions where desirable positive outcomes of HWI are more or less likely. So, in line with extant research, we might conclude that the investment of time at work (HWI-TC) has a direct impact on burnout—the more time we spend at work, the more resources we may lose and the greater propensity to experience stress and burnout.
Nevertheless, what can be said about the investment of effort at work (HWI-WI)? The COR theory suggests that the more effort we exert at work, the more resources we lose in doing so, and hence it is more probable that we would experience stress and burnout. Tziner et al. [19] and Rabenu et al. [20] have found contradictory relationships, meaning the relationship between HWI-WI and burnout was negative (more effort resulted in less burnout). Nonetheless, how can three different samples from three different countries (i.e., cultural contexts: Romania, Israel and the USA) exhibit the same direction of association between HWI-WI and burnout? Is the IKEA effect so prolific? We propose that the level of recovery may also have a buffering effect in this instance: the recovery may help the employee gain/gather more resources (depleted or not; [102]), and, hence, makes it less probable that an employee would experience burnout, even after having invested a great deal of effort at work. In other words, recovery may help to balance resources for the individual, thus reducing experienced burnout. Therefore, we propose:
Proposition 9a.
HWI-TC is positively associated with burnout.
Proposition 9b.
The association between HWI-WI and burnout is moderated by the level of recovery.

5. Conclusions

The current theoretical paper is an ambitious attempt to make sense of a (re)surfacing phenomenon—heavy-work investment—and to provide some meaningful insights into its two dimensions: HWI-TC and HWI-WI—the devotion of time and exertion of (physical and cognitive) effort at work, respectively. However, observing the concept of HWI as a whole (i.e., unidimensional construct) might lead us to lose a great deal of information. As such, investigating and researching these two dimensions may result in a broader, yet more precise, the picture regarding the outcomes of HWI. As discussed, these relationships can be fundamentally different with regard to positive and negative organizational outcomes.
To summarize, Table 1 lists our propositions in an ordinal (and orderly) fashion, while Figure 2 presents our overall model, based on our propositions, such that empirical research may be drawn from it and corroborate it. We encourage scholars and practitioners worldwide to make use of the current paper in order to provide empirical evidence for our propositions and model.

5.1. Practical Implications for Human Resource Management (HRM)

Human resource management (HRM) practitioners and other management in organizations, seeking to carry out intervention processes and policies, are recommended to examine the effort invested at work separately from the “objective” working hours. Furthermore, it is vital to scrutinize the effort exerted in the job during the period of time invested at work in order to obtain critical results for the betterment of the working environment. As can be inferred from the propositions, considerable effort, rather than long working hours, is the cardinal factor that needs to be addressed more carefully and in greater depth with more research and organizational attention. Therefore, even when effort is more challenging to measure and assess than working hours, this is the path that performance appraisals should take. The idea of the importance of effort can be integrated with additional HRM practices, besides performance appraisals, such as:
(1) Job crafting—which “captures the active changes employees make to their job designs in ways that can bring about numerous positive outcomes, including engagement, job satisfaction, resilience, and thriving” ([119], p. 1).
(2) Construction of the meaning of work—managers may serve as architects (or catalysts) of meaning at work for their employees (e.g., [120,121]). This occurs as the managers’ actions and relationships with employees “feed” the process that creates the latter’s meaning at work, alongside job crafting and work culture [1].
(3) Autonomy for employees—employees today, especially knowledge workers and smart creatives, have a high need for autonomy (e.g., [122,123]). Therefore, micromanagement of working time is likely to taint their relationship with their managers and prevent them from realizing their full potential [1].
All three examples encourage employees to engage in tasks that they perceive as significant and therefore may also encourage them to invest more effort in their working time (and even beyond), for all the benefits postulated in this paper.

5.2. Future Research Directions

The current study unveiled several intricate relationships related to the investment of both time and effort in the workplace. However, as this is a theoretical paper, we highly recommend translating our propositions into empirical hypotheses (followed by testing them, de facto).
Moreover, the focus of the present paper is the outcomes of HWI, and therefore, to expand the scope of our understanding of HWI as a construct, we suggest investigating its predictors, and other possible moderators, such as personality dispositions and workplace fairness, among others (see [14], p. 6). Additionally, there are important HWI predictors that reflect different levels of work demands and resources to perform a job, and they may have a considerable impact on HWI [14]. These are, for example, the type of (1) sectors (e.g., private vs. public); (2) industries (low-tech, high-tech, services, etc.); (3) jobs (nurse, truck driver, manager, engineer, etc.) and (4) work arrangements (e.g., part-time, full-time, self-employed). We highly recommend that future research (empirical and/or theoretical) take these contextual factors into account.
Furthermore, as we followed the suggestions of and review by Tabak et al. [31], the number of outcomes proposed in the current study was limited, and we strongly recommend that future research explores different and other consequences of HWI, such as health-related outcomes, organizational profitability, organizational commitment, and performance appraisals, among others (see [14], p. 6).
In addition, it would be beneficial to explore different avenues of control variables that could potentially confound or have a significant impact on the associations outlined in Figure 2. For example, job tenure, personality dispositions, financial situation at home, generation gap (Gen X, Gen Y, Gen Z, etc.), managerial level, national and organizational cultures, and leadership style of management, among others.
Finally, as HRM utilizes new technologies in its service (for a review, see [124]), it would be worthwhile investigating whether the introduction of various technological measures to HRM will enable, in the near future, the measurement/monitoring of the effort invested at work in a way that will be reliable on one hand, and will not negatively impact the employees (such as stress and fatigue; see, for example, [40], on the other.

Author Contributions

Conceptualization, Writing—Original Draft, Supervision, Writing—Review and Editing—E.R.; Writing—Original Draft, Writing—Review and Editing, Visualization—O.S.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

This paper did not report any data.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Glossary of abbreviations.
Table A1. Glossary of abbreviations.
CORConservation of resources theory
CWBCounterproductive work behaviors
EWIExcessive work investor
HRMHuman resource management
HWIHeavy-work investment
HWI-TCHeavy-work investment (time commitment dimension)
HWI-WIHeavy-work investment (work intensity dimension)
LWILow work investor
MWIModerate work investor
OB/IOPOrganizational behavior/industrial and organizational psychology
P-HWIPseudo-heavy-work investment
WLBWork–life balance
WLCWork–life conflict

Appendix B. Presenteeism

Presenteeism is defined as “attending work while ill” ([125], p. 521). Presenteeism is a problem in the workplace because it is “the problem of workers’ being on the job but, because of illness or other medical conditions, not fully functioning—can cut individual productivity by one-third or more” ([42], p. 1). In addition, presenteeism might lead to perceptions of ineffectiveness as a result of reduced productivity. Rabenu and Aharoni-Goldenberg [11] noted the possibility of investing long working hours (time) but with minimal effort. It is possible that individuals with HWI may show up at work only to not be able to work to their full potential.
However, there is many a disagreement as to the definition of presenteeism (see [126]), and, as such, we argue that presenteeism is more than “going to work while ill”, as being ill is but one manifestation of presenteeism, in our humble opinion; attending work while sick will invariably make the employees work less, or less effectively. Additionally, being present at work, while exerting low efforts, may stem from formal work requirements (e.g., a very demanding supervisor who appreciates an employee by the time invested at work, rather than actual performance) and even a lack of motivational drive to invest more effort (e.g., perceived inequity at the job, such as unequal pay and rewards; see [81]). Ergo, we define presenteeism as:
Attending work for the main purpose of being “present” on-site, investing time at the job, without necessarily increasing productivity and/or performance. In other words, being present at work, is de facto, but this renders the individual an absent-presentee for different reasons (e.g., work requirements, lack of motivation, being ill).
It is of paramount importance to discuss, even briefly, the motivational basis for presenteeism. An absent-presentee, as per our definition, is at work, but for different reasons, he/she will make an emphasis on the “being present” aspect at the job, as the time commitment is easy to gauge and measure by the organization (as an act of showing off that “hey, I am here on my work desk”). This employee is a high-work investor, indeed, although the investment is focused on the time aspect, and not the efforts. As such, presenteeism might have a negative impact on the organization. For example, being present at work but using the internet or mobile phones, for personal uses instead of working, is not a new phenomenon. Following our definition, absent-presentees (people who engage in presenteeism) will use phones more often than others, just for the sake of passing the time but displaying an attendance to work. In this manner, using mobile phones at work might have detrimental effects on the job (e.g., [127,128]). Furthermore, a recent study made by Dietz et al. [129] has demonstrated that presenteeism can crossover from the management/leaders to the workers, which highlights the profound effect that presenteeism might have on work.
As a general notion, exerting vast quantities of time and effort at work (i.e., HWI or presenteeism), has been linked to a number of negative factors, such as increased burnout ([20]; only the time dimension of HWI), job stress, work-family conflict [130], reduced recovery at work [131], reduced satisfaction from work, increased turnover intentions and work-family conflict, reduced performance ([86]; only the time dimension of HWI), and more.

References

  1. Rabenu, E. 21st-Century Workplace Challenges: Perspectives and Implications for Relationships in New Era Organizations; Lexington Books: Washington, DC, USA, 2021. [Google Scholar]
  2. Shkoler, O.; Kimura, T. How does work motivation impact employees’ investment at work and their job engagement? A moderated-moderation perspective through an international lens. Front. Psychol. 2020, 11, 38. [Google Scholar] [CrossRef] [PubMed]
  3. Oates, W. Confessions of a Workaholic: The Facts about Work Addiction; World Publishing: Cleveland, NA, USA, 1971. [Google Scholar]
  4. Mazzetti, G.; Schaufeli, W.B.; Guglielmi, D. Are workaholics born or made? Relations of workaholism with person characteristics and overwork climate. Int. J. Stress Manag. 2014, 21, 227–254. Available online: https://psycnet.apa.org/doi/10.1037/a0035700 (accessed on 1 November 2022). [CrossRef] [Green Version]
  5. Mazzetti, G.; Schaufeli, W.B.; Guglielmi, D.; Depolo, M. Overwork climate scale: Psychometric properties and relationships with working hard. J. Manag. Psychol. 2016, 31, 880–896. [Google Scholar] [CrossRef]
  6. Shimazu, A.; Kubota, K.; Bakker, A.B. How workaholism affects employees and their families. In Heavy Work Investment: Its Nature, Sources, Outcomes, and Future Directions; Harpaz, I., Snir, R., Eds.; Routledge: New York, NY, USA, 2015; pp. 171–186. [Google Scholar]
  7. Taris, T.; Van Beek, I.; Schaufeli, W. The beauty versus the beast: On the motives of engaged and workaholic employees. In Heavy Work Investment: Its Nature, Sources, Outcomes, and Future Directions; Harpaz, I., Snir, R., Eds.; Routledge: New York, NY, USA, 2015; pp. 121–139. [Google Scholar]
  8. Snir, R.; Harpaz, I. Beyond workaholism: Towards a general model of heavy work investment. Hum. Resour. Manag. Rev. 2012, 22, 232–243. [Google Scholar] [CrossRef]
  9. Brown, S.P.; Leigh, T.W. A new look at psychological climate and its relationship to job involvement, effort, and performance. J. Appl. Psychol. 1996, 81, 358–368. Available online: https://psycnet.apa.org/doi/10.1037/0021-9010.81.4.358 (accessed on 1 November 2022). [CrossRef] [PubMed]
  10. Fein, E.C.; Skinner, N.; Machin, M.A. Work intensification, work–life interference, stress, and well-being in Australian workers. Int. Stud. Manag. Organ. 2017, 47, 360–371. [Google Scholar] [CrossRef]
  11. Rabenu, E.; Aharoni-Goldenberg, S. Understanding the relationship between overtime and burnout. Int. Stud. Manag. Organ. 2017, 47, 324–335. [Google Scholar] [CrossRef]
  12. Astakhova, M.; Hogue, M. A heavy work investment typology: A biopsychosocial framework. J. Manag. Psychol. 2014, 29, 81–99. [Google Scholar] [CrossRef]
  13. Astakhova, M.; Hogue, M. Applying the biopsychological model to examine cross cultural similarities and differences in heavy work investment behaviors and outcomes. In Heavy Work Investment: Its Nature, Sources, Outcomes, and Future Directions; Harpaz, I., Snir, R., Eds.; Routledge: New York, NY, USA, 2015; pp. 322–341. [Google Scholar]
  14. Snir, R.; Harpaz, I. A general model of heavy work investment. In Heavy Work Investment: Its Nature, Sources, Outcomes, and Future Directions; Harpaz, I., Snir, R., Eds.; Routledge: New York, NY, USA, 2015; pp. 3–30. [Google Scholar]
  15. Vardi, Y.; Weitz, E. Misbehavior in Organizations: A Dynamic Approach, 2nd ed.; Routledge: London, UK, 2016. [Google Scholar]
  16. Shamai, O.; Harpaz, I.; Snir, R. Towards advancing well-being in organizations: An examination of happiness underlying overwork. In Academy of Management Proceedings; Atinc, G., Ed.; Academy of Management: New York, NY, USA, 2018; Volume 2018, p. 14443. [Google Scholar]
  17. Harpaz, I. The current state of heavy work investment and future development. In Heavy Work Investment: Its Nature, Sources, Outcomes, and Future Directions; Harpaz, I., Snir, R., Eds.; Routledge: New York, NY, USA, 2015; pp. 361–373. [Google Scholar]
  18. Shamai, O. The relationship between heavy work investment and employees’ happiness. In Heavy Work Investment: Its Nature, Sources, Outcomes, and Future Directions; Harpaz, I., Snir, R., Eds.; Routledge: New York, NY, USA, 2015; pp. 204–222. [Google Scholar]
  19. Tziner, A.; Buzea, C.; Rabenu, E.; Shkoler, O.; Truța, C. Understanding the relationship between antecedents of heavy work investment (HWI) and burnout. Amfiteatru Econ. 2019, 21, 153–176. [Google Scholar] [CrossRef]
  20. Rabenu, E.; Shkoler, O.; Lebron, M.; Tabak, F. Heavy-work investment, job engagement, managerial role, person-organization value congruence, and burnout: A moderated-mediation analysis in USA and Israel. Curr. Psychol. 2021, 40, 4825–4842. [Google Scholar] [CrossRef]
  21. Dembe, A.E.; Erickson, J.B.; Delbos, R.G.; Banks, S.M. The impact of overtime and long work hours on occupational injuries and illnesses: New evidence from the United States. Occup. Environ. Med. 2005, 62, 588–597. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Hewlett, S.A.; Luce, C.B. Extreme jobs: The dangerous allure of the 70-hour workweek. Harv. Bus. Rev. 2006, 84, 49–59. Available online: https://hbr.org/2006/12/extreme-jobs-the-dangerous-allure-of-the-70-hour-workweek (accessed on 1 November 2022). [PubMed]
  23. Miller, J.G.; Miller, M. The rise of the supertemp. Harv. Bus. Rev. 2012, 90, 50–62. Available online: https://hbr.org/2012/05/the-rise-of-the-supertemp (accessed on 6 November 2022).
  24. Jacobs, J.A.; Gerson, K. The Time Divide; Harvard University Press: Cambridge, MA, USA, 2004. [Google Scholar]
  25. Dyer-Witheford, N.; Kjøsen, A.M.; Steinhoff, J. Inhuman Power: Artificial Intelligence and the Future of Capitalism; Pluto Press: London, UK, 2019. [Google Scholar]
  26. Kellogg, K.C.; Valentine, M.A.; Christin, A. Algorithms at work: The new contested terrain of control. Acad. Manag. Ann. 2020, 14, 366–410. [Google Scholar] [CrossRef]
  27. Méda, D. Three scenarios for the future of work. Int. Labour Rev. 2019, 158, 627–652. [Google Scholar] [CrossRef]
  28. Parent-Rocheleau, X.; Parker, S.K. Algorithms as work designers: How algorithmic management influences the design of jobs. Hum. Resour. Manag. Rev. 2021, 32, 100838. [Google Scholar] [CrossRef]
  29. Wood, A.J. Algorithmic Management Consequences for Work Organisation and Working Conditions. JRC Working Papers Series on Labour, Education and Technology, No. 2021/07. 2021. Available online: http://hdl.handle.net/10419/233886 (accessed on 1 November 2022).
  30. Baruch, Y. Managing Careers & Employability; Sage: London, UK, 2022. [Google Scholar]
  31. Tabak, F.; Tziner, A.; Shkoler, O.; Rabenu, E. The complexity of heavy work investment (HWI): A conceptual integration and review of antecedents, dimensions, and outcomes. Sustainability 2021, 13, 7803. [Google Scholar] [CrossRef]
  32. Shkoler, O.; Rabenu, E.; Iqbal, M.Z.; Ferrari, F.; Hatipoglu, B.; Roazzi, A.; Kimura, T.; Tabak, F.; Moasa, H.; Vasiliu, C.; et al. Heavy work investment: Its dimensionality, invariance across 9 countries and levels before and during the COVID-19’s pandemic. J. Work Organ. Psychol. 2021, 37, 67–83. [Google Scholar] [CrossRef]
  33. Snir, R.; Harpaz, I. Beyond workaholism: Differences between heavy work investment (HWI) subtypes in well-being and health-related outcomes. Int. J. Workplace Health Manag. 2021, 14, 332–349. [Google Scholar] [CrossRef]
  34. Shimazu, A.; Schaufeli, W.; Kamiyama, K.; Kawakami, N. Workaholism vs. work engagement: The two different predictors of future well-being and performance. Int. J. Behav. Med. 2015, 22, 18–23. [Google Scholar] [CrossRef]
  35. Su, J. Working Hard and Work Outcomes: The Relationship of Workaholism and Work Engagement with Job Satisfaction, Burnout, and Work Hours. Ph.D. Thesis, Illinois State University, Normal, IL, USA, 2019. Available online: https://www.proquest.com/docview/2272318086?pq-origsite=gscholar&fromopenview=true (accessed on 1 November 2022).
  36. Bonebright, C.A.; Clay, D.L.; Ankenmann, R.D. The relationship of workaholism with work–life conflict, life satisfaction, and purpose in life. J. Couns. Psychol. 2000, 47, 469–477. Available online: https://psycnet.apa.org/doi/10.1037/0022-0167.47.4.469 (accessed on 3 November 2022). [CrossRef]
  37. Burke, R.J.; Fiksenbaum, L. Work motivations, work outcomes, and health: Passion versus addiction. J. Bus. Ethics 2009, 84, 257–263. [Google Scholar] [CrossRef]
  38. Houlfort, N.; Philippe, F.L.; Vallerand, R.J.; Ménard, J. On passion and heavy work investment: Personal and organizational outcomes. J. Manag. Psychol. 2014, 29, 25–45. [Google Scholar] [CrossRef]
  39. Campbell, J.P. The definition and measurement of performance in the New Age. In The Changing Nature of Performance: Implications for Staffing, Motivation and Development; Ilgen, D.R., Pulakos, E.D., Eds.; Jossey-Bass: San Francisco, CA, USA, 1999; pp. 339–429. [Google Scholar]
  40. Tziner, A.; Rabenu, E. Improving Performance Appraisal at Work: Evolution and Change; Edward Elgar Publishing: Cheltenham, UK, 2018. [Google Scholar]
  41. Popa, I.; Ştefan, S.C.; Albu, C.F.; Popa, Ş.C.; Vlad, C. The impact of national culture on employees’ attitudes toward heavy work investment: Comparative approach Romania vs. Japan. Amfiteatru Econ. 2020, 22, 1014–1029. [Google Scholar] [CrossRef]
  42. Hemp, P. Presenteeism: At work—but out of it. Harv. Bus. Rev. 2004, 82, 49–58. Available online: https://hbr.org/2004/10/presenteeism-at-work-but-out-of-it (accessed on 29 October 2022).
  43. Hanna, A.S.; Taylor, C.S.; Sullivan, K.T. Impact of extended overtime on construction labor productivity. J. Constr. Eng. Manag. 2005, 131, 734–739. [Google Scholar] [CrossRef]
  44. Holman, C.; Joyeux, B.; Kask, C. Labor productivity trends since 2000, by sector and industry. Mon. Labor Rev. 2008, 131, 64–82. Available online: https://www.jstor.org/stable/monthlylaborrev.2008.02.064 (accessed on 1 November 2022).
  45. London, C.W. Proof That You Should Get a Life. The Economist. Available online: https://www.economist.com/free-exchange/2014/12/09/proof-that-you-should-get-a-life (accessed on 10 November 2022).
  46. Shepard, E.; Clifton, T. Are longer hours reducing productivity in manufacturing? Int. J. Manpow. 2000, 21, 540–553. [Google Scholar] [CrossRef]
  47. Sonnentag, S.; Venz, L.; Casper, A. Advances in recovery research: What have we learned? What should be done next? J. Occup. Health Psychol. 2017, 22, 365–380. [Google Scholar] [CrossRef]
  48. Shkoler, O.; Rabenu, E.; Vasiliu, C.; Sharoni, G.; Tziner, A. Organizing the confusion surrounding workaholism: New structure, measure, and validation. Front. Psychol. 2017, 8, 1803. [Google Scholar] [CrossRef] [Green Version]
  49. Bem, D.J. Self-perception theory. In Advances in Experimental Social Psychology, 6th ed.; Berkowitz, L., Ed.; Academic Press: Cambridge, MA, USA, 1972; pp. 1–49. [Google Scholar]
  50. Mochon, D.; Norton, M.I.; Ariely, D. Bolstering and restoring feelings of competence via the IKEA effect. Int. J. Res. Mark. 2012, 29, 363–369. [Google Scholar] [CrossRef] [Green Version]
  51. Norton, M.I.; Mochon, D.; Ariely, D. The IKEA effect: When labor leads to love. J. Consum. Psychol. 2012, 22, 453–460. [Google Scholar] [CrossRef]
  52. Diener, E.; Suh, E.; Oishi, S. Recent findings on subjective well-being. Indian J. Clin. Psychol. 1997, 24, 25–41. Available online: https://psycnet.apa.org/record/1997-43193-002 (accessed on 2 November 2022).
  53. Csikszentmihalyi, M. The contribution of flow to positive psychology. In The Science of Optimism and Hope: Research Essays in Honor of Martin; Seligman, E.P., Gillham, J.E., Eds.; Templeton Foundation Press: West Conshohocken, PA, USA, 2000; pp. 387–395. [Google Scholar]
  54. Ng, T.W.; Sorensen, K.L.; Feldman, D.C. Dimensions, antecedents, and consequences of workaholism: A conceptual integration and extension. J. Organ. Behav. 2007, 28, 111–136. [Google Scholar] [CrossRef]
  55. Andreassen, C.S.; Griffiths, M.D.; Hetland, J.; Pallesen, S. Development of a work addiction scale. Scand. J. Psychol. 2012, 53, 265–272. [Google Scholar] [CrossRef] [PubMed]
  56. Van Beek, I.; Hu, Q.; Schaufeli, W.B.; Taris, T.W.; Schreurs, B.H. For fun, love, or money: What drives workaholic, engaged, and burned-out employees at work? Appl. Psychol. 2012, 61, 30–55. [Google Scholar] [CrossRef] [Green Version]
  57. Shkoler, O.; Rabenu, E.; Tziner, A. The dimensionality of workaholism and its relations with internal and external factors. J. Work Organ. Psychol. 2017, 33, 193–203. [Google Scholar] [CrossRef]
  58. Baruch, Y. The positive wellbeing aspects of workaholism in cross cultural perspective. Career Dev. Int. 2011, 16, 572–591. [Google Scholar] [CrossRef]
  59. Snir, R.; Zohar, D. Workaholism as discretionary time investment at work: An experience-sampling study. Appl. Psychol. 2008, 57, 109–127. [Google Scholar] [CrossRef]
  60. OECD. Hours Worked. 2021. Available online: https://data.oecd.org/emp/hours-worked.htm (accessed on 1 November 2022).
  61. Snir, R.; Harpaz, I. The workaholism phenomenon: A cross-national perspective. Career Dev. Int. 2006, 11, 374–393. [Google Scholar] [CrossRef]
  62. Festinger, L. A Theory of Cognitive Dissonance; Stanford University Press: Redwood City, CA, USA, 1957. [Google Scholar]
  63. Mankiw, N.G. Principles of Economics, 8th ed.; Cengage Learning: Boston, MA, USA, 2018. [Google Scholar]
  64. Jiskrova, G.K. Impact of COVID-19 pandemic on the workforce: From psychological distress to the Great Resignation. J. Epidemiol. Community Health 2022, 76, 525–526. [Google Scholar] [CrossRef] [PubMed]
  65. Sheather, J.; Slattery, D. The Great Resignation—how do we support and retain staff already stretched to their limit? Br. Med. J. 2021, 375, 2533. [Google Scholar] [CrossRef] [PubMed]
  66. Sull, D.; Sull, C.; Zweig, B. Toxic culture is driving the Great Resignation. MIT Sloan Manag. Rev. 2022, 63, 1–9. Available online: https://sloanreview.mit.edu/article/toxic-culture-is-driving-the-great-resignation/ (accessed on 2 November 2022).
  67. Di Stefano, G.; Gaudiino, M. Workaholism and work engagement: How are they similar? How are they different? A systematic review and meta-analysis. Eur. J. Work Organ. Psychol. 2019, 28, 329–347. [Google Scholar] [CrossRef]
  68. Andreassen, C.S. Workaholism: An overview and current status of the research. J. Behav. Addict. 2014, 3, 1–11. [Google Scholar] [CrossRef] [PubMed]
  69. Di Stefano, G.; Gaudiino, M. Differential effects of workaholism and work engagement on the interference between life and work domains. Eur. J. Psychol. 2018, 14, 863–879. [Google Scholar] [CrossRef] [Green Version]
  70. Clark, M.A.; Michel, J.S.; Zhdanova, L.; Pui, S.Y.; Baltes, B.B. All work and no play? A meta-analytic examination of the correlates and outcomes of workaholism. J. Manag. 2016, 42, 1836–1873. [Google Scholar] [CrossRef]
  71. Cohen-Charash, Y.; Mueller, J.S. Does perceived unfairness exacerbate or mitigate interpersonal counterproductive work behaviors related to envy? J. Appl. Psychol. 2007, 92, 666–680. Available online: https://psycnet.apa.org/doi/10.1037/0021-9010.92.3.666 (accessed on 4 November 2022). [CrossRef] [Green Version]
  72. Shkoler, O.; Rabenu, E.; Tabak, F.; Lebron, M. Leader-and team-member exchanges and their relationships with organizational and interpersonal counterproductive work behaviors: Moderation by envy and group size in a cross-cultural case. J. Work Organ. Psychol. 2019, 35, 145–156. [Google Scholar] [CrossRef] [Green Version]
  73. Tziner, A.; Fein, E.C.; Kim, S.-K.; Vasiliu, C.; Shkoler, O. Combining associations between emotional intelligence, work motivation and organizational justice with counterproductive work behaviors: A profile analysis via multidimensional scaling (PAMS) approach. Front. Psychol. 2020, 11, 851. [Google Scholar] [CrossRef]
  74. Bodankin, M.; Tziner, A. Constructive deviance, destructive deviance and personality: How do they interrelate? Amfiteatru Econ. 2009, 11, 549–564. Available online: https://www.econstor.eu/bitstream/10419/168681/1/aej-v11-i26-p549.pdf (accessed on 4 November 2022).
  75. Aubé, C.; Rousseau, V.; Mama, C.; Morin, E.M. Counterproductive behaviors and psychological well-being: The moderating effect of task interdependence. J. Bus. Psychol. 2009, 24, 351–361. [Google Scholar] [CrossRef]
  76. Bennett, R.J.; Robinson, S.L. The past, present, and future of workplace deviance research. In Organizational Behavior: The State of the Science 2nd ed; Greenberg, J., Ed.; Lawrence Erlbaum Associates: Mahwah, NJ, USA, 2003; pp. 247–281. [Google Scholar]
  77. Spector, P.E.; Fox, S.; Penney, L.M.; Bruursema, K.; Goh, A.; Kessler, S. The dimensionality of counterproductivity: Are all counterproductive behaviors created equal? J. Vocat. Behav. 2006, 68, 446–460. [Google Scholar] [CrossRef]
  78. Greenberg, J.; Scott, K.S. Why do workers bite the hands that feed them? Employee theft as a social exchange process. In Research in Organizational Behavior: An Annual Series of Analytical Essays and Critical Reviews; Staw, B.M., Cummings, L.L., Eds.; Elsevier Science: Amsterdam, The Netherlands; JAI Press: Stamford, CT, USA, 1996; Volume 18, pp. 111–156. [Google Scholar]
  79. Skarlicki, D.P.; Folger, R. Retaliation in the workplace: The roles of distributive, procedural, and interactional justice. J. Appl. Psychol. 1997, 82, 434–443. [Google Scholar] [CrossRef]
  80. Bennett, R.J.; Robinson, S.L. Development of a measure of workplace deviance. J. Appl. Psychol. 2000, 85, 349–360. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  81. Adams, J.S. Inequity in social exchange. Adv. Exp. Soc. Psychol. 1965, 2, 267–299. [Google Scholar] [CrossRef]
  82. Shkoler, O.; Tziner, A. The mediating and moderating role of burnout and emotional intelligence in the relationship between organizational justice and work misbehavior. J. Work Organ. Psychol. 2017, 33, 157–164. [Google Scholar] [CrossRef] [Green Version]
  83. Lazarus, R.S.; Folkman, S. Stress, Appraisal, and Coping; Springer: Berlin/Heidelberg, Germany, 1984. [Google Scholar]
  84. Chen, M. The impact of expatriates’ cross-cultural adjustment on work stress and job involvement in the high-tech industry. Front. Psychol. 2019, 10, 2228. [Google Scholar] [CrossRef]
  85. Lloyd, C.; King, R.; Chenoweth, L. Social work, stress and burnout: A review. J. Ment. Health 2002, 11, 255–265. [Google Scholar] [CrossRef]
  86. Maslach, C.; Jackson, S.E.; Leiter, M.P. MBI: Maslach Burnout Inventory; CPP, Incorporated: Sunnyvale, CA, USA, 1996. [Google Scholar]
  87. Milbourne, C.C.; Wilkinson, J.S. Chasing infinity: The fear of disconnecting. Am. Commun. J. 2015, 17, 1–14. [Google Scholar]
  88. Zastrow, C. Understanding and preventing burn-out. Br. J. Soc. Work 1984, 14, 141–155. [Google Scholar] [CrossRef]
  89. Hardie, E.; Kashima, E.; Pridmore, P. The influence of relational, individual and collective self-aspects on stress, uplifts and health. Self Identity 2005, 4, 1–24. [Google Scholar] [CrossRef]
  90. Yu, X.; Ren, G.; Huang, S.; Wang, Y. Undergraduates’ belief in a just world and subjective well-being: The mediating role of sense of control. Soc. Behav. Personal. Int. J. 2018, 46, 831–840. [Google Scholar] [CrossRef]
  91. Bell, A.S.; Rajendran, D.; Theiler, S. Job stress, wellbeing, work-life balance and work-life conflict among Australian academics. Electron. J. Appl. Psychol. 2012, 8, 25–37. Available online: https://psycnet.apa.org/record/2013-27004-004 (accessed on 31 October 2022). [CrossRef]
  92. Guest, D.E. Perspectives on the Study of Work-life Balance. Soc. Sci. Inf. 2002, 41, 255–279. [Google Scholar] [CrossRef]
  93. Hill, E.J.; Hawkins, A.J.; Ferris, M.; Weitzman, M. Finding an extra day a week: The positive influence of perceived job flexibility on work and family life balance. Fam. Relat. 2001, 50, 49–58. [Google Scholar] [CrossRef]
  94. Kalliath, T.; Brough, P. Work–life balance: A review of the meaning of the balance construct. J. Manag. Organ. 2008, 14, 323–327. [Google Scholar] [CrossRef]
  95. Quick, J.D.; Henley, A.B.; Quick, J.C. The balancing act: At work and at home. Organ. Dyn. 2004, 33, 426–438. [Google Scholar] [CrossRef]
  96. Reiter, N. Work life balance: What DO you mean? The ethical ideology underpinning appropriate application. J. Appl. Behav. Sci. 2007, 43, 273–294. [Google Scholar] [CrossRef]
  97. Peters, P.; Blomme, R.J. Forget about “the ideal worker”: A theoretical contribution to the debate on flexible workplace designs, work/life conflict, and opportunities for gender equality. Bus. Horiz. 2019, 62, 603–613. [Google Scholar] [CrossRef]
  98. Hanson, G.C.; Hammer, L.B.; Colton, C.L. Development and validation of a multidimensional scale of perceived work-family positive spillover. J. Occup. Health Psychol. 2006, 11, 249–265. [Google Scholar] [CrossRef]
  99. Balmforth, K.; Gardner, D. Conflict and facilitation between work and family: Realizing the outcomes for organizations. N. Z. J. Psychol. 2006, 35, 69–76. Available online: https://psycnet.apa.org/record/2006-12284-002 (accessed on 1 November 2022).
  100. Tytherleigh, M.Y.; Webb, C.; Cooper, C.L.; Ricketts, C. Occupational stress in UK higher education institutions: A comparative study of all staff categories. High. Educ. Res. Dev. 2005, 24, 41–61. [Google Scholar] [CrossRef]
  101. Wang, J.L. Perceived work stress, imbalance between work and family/personal lives, and mental disorders. Soc. Psychiatry Psychiatr. Epidemiol. 2006, 41, 541–548. [Google Scholar] [CrossRef] [PubMed]
  102. Hobfoll, S.E. Conservation of resources: A new attempt at conceptualizing stress. Am. Psychol. 1989, 44, 513–524. [Google Scholar] [CrossRef] [PubMed]
  103. Hobfoll, S.E. The influence of culture, community, and the nested-self in the stress process: Advancing conservation of resources theory. Appl. Psychol. 2001, 50, 337–421. [Google Scholar] [CrossRef]
  104. Hobfoll, S.E. Conservation of resource caravans and engaged settings. J. Occup. Organ. Psychol. 2011, 84, 116–122. [Google Scholar] [CrossRef]
  105. Halbesleben, J.R.; Neveu, J.P.; Paustian-Underdahl, S.C.; Westman, M. Getting to the “COR”: Understanding the role of resources in conservation of resources theory. J. Manag. 2014, 40, 1334–1364. [Google Scholar] [CrossRef]
  106. Maslach, C. Job burnout: New directions in research and intervention. Curr. Dir. Psychol. Sci. 2003, 12, 189–192. [Google Scholar] [CrossRef]
  107. Jackson, S.E.; Maslach, C. After-effects of job-related stress: Families as victims. J. Organ. Behav. 1982, 3, 63–77. [Google Scholar] [CrossRef]
  108. Toker, S.; Melamed, S.; Berliner, S.; Zeltser, D.; Shapira, I. Burnout and risk of coronary heart disease: A prospective study of 8838 employees. Psychosom. Med. 2012, 74, 840–847. [Google Scholar] [CrossRef] [PubMed]
  109. Shirom, A.; Toker, S.; Melamed, S.; Berliner, S.; Shapira, I. Burnout and vigor as predictors of the incidence of hyperlipidemia among healthy employees. Appl. Psychol. Health Well-Being 2013, 5, 79–98. [Google Scholar] [CrossRef] [PubMed]
  110. Melamed, S.; Shirom, A.; Toker, S.; Shapira, I. Burnout and risk of type 2 diabetes: A prospective study of apparently healthy employed persons. Psychosom. Med. 2006, 68, 863–869. [Google Scholar] [CrossRef] [PubMed]
  111. Toker, S.; Biron, M. Job burnout and depression: Unraveling their temporal relationship and considering the role of physical activity. J. Appl. Psychol. 2012, 97, 699–710. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  112. Tourigny, L.; Baba, V.V.; Han, J.; Wang, X. Emotional exhaustion and job performance: The mediating role of organizational commitment. Int. J. Hum. Resour. Manag. 2013, 24, 514–532. [Google Scholar] [CrossRef]
  113. Lebrón, M.; Tabak, F.; Shkoler, O.; Rabenu, E. Counterproductive work behaviors toward organization and leader-member exchange: The mediating roles of emotional exhaustion and work engagement. Organ. Manag. J. 2018, 15, 159–173. [Google Scholar] [CrossRef]
  114. Anthony-McMann, P.E.; Ellinger, A.D.; Astakhova, M.; Halbesleben, J.R. Exploring different operationalizations of employee engagement and their relationships with workplace stress and burnout. Hum. Resour. Dev. Q. 2017, 28, 163–195. [Google Scholar] [CrossRef]
  115. Maslach, C. Burnout and engagement in the workplace: New perspectives. Eur. Health Psychol. 2011, 13, 44–47. Available online: https://www.ehps.net/ehp/index.php/contents/article/view/ehp.v13.i3.p44 (accessed on 1 November 2022).
  116. Nahrgang, J.D.; Morgeson, F.P.; Hofmann, D.A. Safety at work: A meta-analytic investigation of the link between job demands, job resources, burnout, engagement, and safety outcomes. J. Appl. Psychol. 2011, 96, 71–94. [Google Scholar] [CrossRef]
  117. Schaufeli, W.B.; Maslach, C.; Marek, T. (Eds.) Professional Burnout: Recent Developments in Theory and Research; Taylor & Francis: Milton Park, UK, 2017. [Google Scholar]
  118. Ivancevic, S.; Ivanovic, T.; Maricic, M.; Cudanov, M. Student heavy work investment, burnout, and their antecedents: The case of Serbia. Amfiteatru Econ. 2020, 22, 1182–1205. [Google Scholar] [CrossRef]
  119. Berg, J.M.; Dutton, J.E.; Wrzesniewski, A. What Is Job Crafting and Why Does It Matter? Center for Positive Organizational Scholarship, Ross School of Business. 2008. Available online: http://positiveorgs.bus.umich.edu/wp-content/uploads/What-is-Job-Crafting-and-Why-Does-it-Matter1.pdf (accessed on 1 November 2022).
  120. Carton, A.M. “I’m not mopping the floors, I’m putting a man on the moon”: How NASA leaders enhanced the meaningfulness of work by changing the meaning of work. Adm. Sci. Q. 2018, 63, 323–369. [Google Scholar] [CrossRef]
  121. Pereg, D. Management promotes meaning. Psychoactuality 2020, 79, 41–45. (In Hebrew) [Google Scholar]
  122. Burke, R.J.; Ng, E. The changing nature of work and organizations: Implications for human resource management. Hum. Manag. Resour. Rev. 2006, 16, 86–94. [Google Scholar] [CrossRef]
  123. Pink, D.H. Drive: The Surprising Truth about What Motivates US; Riverhead Books: New York, NY, USA, 2009. [Google Scholar]
  124. Vrontis, D.; Christofi, M.; Pereira, V.; Tarba, S.; Makrides, A.; Trichina, E. Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. Int. J. Hum. Resour. Manag. 2022, 33, 1237–1266. [Google Scholar] [CrossRef]
  125. Johns, G. Presenteeism in the workplace: A review and research agenda. J. Organ. Behav. 2010, 31, 519–542. [Google Scholar] [CrossRef]
  126. Lohaus, D.; Habermann, W. Presenteeism: A review and research directions. Hum. Resour. Manag. Rev. 2019, 29, 43–58. [Google Scholar] [CrossRef]
  127. Bittman, M.; Brown, J.E.; Wajcman, J. The mobile phone, perpetual contact and time pressure. Work Employ. Soc. 2009, 23, 673–691. [Google Scholar] [CrossRef]
  128. Mullan, K.; Wajcman, J. Have mobile devices changed working patterns in the 21st century? A time-diary analysis of work extension in the UK. Work Employ. Soc. 2019, 33, 3–20. [Google Scholar] [CrossRef]
  129. Dietz, C.; Zacher, H.; Scheel, T.; Otto, K.; Rigotti, T. Leaders as role models: Effects of leader presenteeism on employee presenteeism and sick leave. Work Stress 2020, 34, 300–322. [Google Scholar] [CrossRef]
  130. Butnaru, R.C.; Anichiti, A.; Haller, G.I.B.A.P. Heavy work investment from the perspective of cultural factors and outcomes by types of investors. Amfiteatru Econ. 2020, 22, 1159. [Google Scholar] [CrossRef]
  131. Acosta-Prado, J.C.; Sandoval-Reyes, J.G.; Sanchís-Pedregosa, C. Job demands and recovery experience: The mediation role of heavy work investment. Amfiteatru Econ. 2020, 22, 1206–1226. [Google Scholar] [CrossRef]
Figure 1. Heavy-Work Investment (HWI) categorization grid. L = low HWI. M = moderate HWI. H = high HWI. A subscript p indicates “pure” type.
Figure 1. Heavy-Work Investment (HWI) categorization grid. L = low HWI. M = moderate HWI. H = high HWI. A subscript p indicates “pure” type.
Sustainability 14 16362 g001
Figure 2. Overall research model (based on research propositions).
Figure 2. Overall research model (based on research propositions).
Sustainability 14 16362 g002
Table 1. Summary of the propositions in the current paper.
Table 1. Summary of the propositions in the current paper.
No.Proposition
1aHWI-WI is positively associated with job performance.
1bThe relationship between HWI-TC and job performance is moderated by (a) the degree of HWI-WI, which is conditioned by (b) the level of recovery.
2aHWI-WI is positively associated with job satisfaction.
2bThe relationship between HWI-TC and job satisfaction is moderated by the extent of positive feedback from the manager.
3The positive relationship between HWI-WI and job satisfaction will be greater than between HWI-TC and job satisfaction.
4aHWI-WI is positively associated with positive affect.
4bThe relationship between HWI-TC and positive affect is moderated by the degree of HWI-WI.
5In countries with high (as opposed to low) annual working hours, HWI-TC is positively associated with positive affect.
6aHWI-TC is associated with turnover intentions.
6bHWI-WI is negatively associated with turnover intentions.
7aThe relationship between HWI and CWB is indirect.
7bPerceived (un)fairness/(in)justice moderates the association between HWI and CWB, such that the greater the unfairness/injustice, the stronger (and more positive) the relationship between HWI and CWB becomes.
8aHWI-TC is positively associated with WLC.
8bHWI-TC moderates the relationship between HWI-WI and WLC, such that HWI-WI is positively associated with WLC only when HWI-TC is high, but as HWI-TC decreases, the relationship between HWI-WI and WLC decreases.
9aHWI-TC is positively associated with burnout.
9bThe association between HWI-WI and burnout is moderated by the level of recovery.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Rabenu, E.; Shkoler, O. Heavy-Work Investment, Its Organizational Outcomes and Conditional Factors: A Contemporary Perspective over a Decade of Literature. Sustainability 2022, 14, 16362. https://doi.org/10.3390/su142416362

AMA Style

Rabenu E, Shkoler O. Heavy-Work Investment, Its Organizational Outcomes and Conditional Factors: A Contemporary Perspective over a Decade of Literature. Sustainability. 2022; 14(24):16362. https://doi.org/10.3390/su142416362

Chicago/Turabian Style

Rabenu, Edna, and Or Shkoler. 2022. "Heavy-Work Investment, Its Organizational Outcomes and Conditional Factors: A Contemporary Perspective over a Decade of Literature" Sustainability 14, no. 24: 16362. https://doi.org/10.3390/su142416362

APA Style

Rabenu, E., & Shkoler, O. (2022). Heavy-Work Investment, Its Organizational Outcomes and Conditional Factors: A Contemporary Perspective over a Decade of Literature. Sustainability, 14(24), 16362. https://doi.org/10.3390/su142416362

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop