Workaholics and employees who engage with their work (i.e., work engagement) all bring a significant level of commitment to their tasks. Both situations may generate similar consequences (Schaufeli, Taris, & van Rhenen, 2008). This has led to some conceptual confusion. Therefore, it is important to understand the difference between workaholism and work engagement on both a theoretical and practical level. On the one hand, Schaufeli, Taris, and Bakker (2006) have defined workaholism as the tendency to work excessively hard and being obsessed with work, in a compulsive way, and on the other hand, work engagement is a positive, fulfilling, work-related state of mind that is associated with vigor, dedication, and absorption (Schaufeli, Salanova, González-Romá, & Bakker, 2002). However, few researchers have paid attention to this topic, or, in particular, to the relationship between either work engagement or workaholism and employees’ organizational attitudes.

In this study, I have delineated the theoretical and empirical distinctiveness between workaholism and work engagement by devising an integrative model that includes these concepts’ antecedents and consequences. I used the Job Demands-Resources (JD-R) model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001) to apply this integrative model to the investigation of the differences between workaholism and work engagement using the same cluster of variables. To measure organizational outcomes, I chose turnover intention (TI) and organizational citizenship behavior (OCB) to represent in-role and extra-role organizational attitudes.

Hypotheses

Work Engagement

Antecedents. Previous researchers have consistently demonstrated that job resources, such as social support from colleagues and supervisors, performance feedback, skill variety, autonomy, and learning opportunities, are positively associated with work engagement (Bakker & Demerouti, 2007). For example, Hakanen, Schaufeli, and Ahola (2008) found that job resources influence work engagement through a motivational process in which employees satisfy basic needs such as autonomy, competence, and relatedness (Van den Broeck, Vansteenkiste, De Witte, & Lens, 2008). Mauno, Kinnunen, and Ruokolainen (2007) found job control, an important job resource, to be one of the best lagged predictors of work engagement. Therefore, I proposed the following hypothesis:
Hypothesis 1: Job resources will be positively related to work engagement.

Moderators. Underlying the JD-R model, is the premise that the characteristics of every work environment can be classified in two general categories, that is, job demands and job resources (Bakker, Demerouti, de Boer, & Schaufeli, 2003). Bakker and Demerouti (2007) used this overarching model to illustrate that job demands moderate the resources–engagement relationship. In addition, Hakanen et al. (2008) showed that variability in professional skills boosted work engagement when qualitative workload was high and mitigated the negative effect of qualitative workload on work engagement. Bakker, Hakanen, Demerouti, and Xanthopoulou (2007) reported conceptually similar findings in a study of Finnish teachers, finding that job resources act as buffers and diminish the negative relationship between pupil misbehavior and work engagement, and particularly influence work engagement when teachers are confronted with high levels of pupil misconduct. Therefore, I proposed the following hypothesis:
Hypothesis 2: Job demands will moderate the relationship between job resources and work engagement.

Consequences. Previous researchers have mainly indicated that work engagement is a positive predictor of employees’ performance. For example, Halbesleben and Wheeler (2008) found a positive relationship between work engagement and colleagues’ and supervisors’ ratings of performance in a study of American employees working in a wide variety of industries and occupations. Salanova, Agut, and Peiró (2005) showed that work engagement predicted service climate, which in turn predicted employee performance and resulting customer loyalty. Xanthopoulou, Bakker, Demerouti, and Schaufeli (2009) conducted a diary study among employees working in a Greek fast-food restaurant and found that daily levels of work engagement accurately predicted objective daily financial returns. Therefore, I proposed the following hypothesis:
Hypothesis 3: Work engagement will be positively related to organizational outcomes.

Workaholism

Antecedents. Previous researchers have consistently indicated that job demands (e.g., work pressure, a winner-take-all system, organizational emphasis on input rather than output, and peer competition) are positively associated with workaholism (Ng, Sorensen, & Feldman, 2007).

For example, a strong positive relationship was found between work overload and workaholism (Kanai & Wakabayashi, 2001). Johnstone and Johnston (2005) suggested that work pressure is an antecedent of the inner drive dimension of workaholism, and that if an organization implements a winner-take-all or star reward system, employees are more likely to exert greater effort because only the top performers are rewarded. Also, in the competitive atmosphere created by widespread workaholism in the workplace, peer competition can evoke workaholic behavior (Ng et al., 2007). Therefore, I proposed the following hypothesis:
Hypothesis 4: Job demands will be positively related to workaholism.

Moderators. Bakker and Demerouti (2007) stated that in the JD-R model it is proposed that the interaction between job demands and job resources is important for the development of job strain and motivation. More specifically, it is proposed that job resources may buffer the impact of job demands on job strain. This assumption is consistent with the demand-control model (Karasek, 1979), upon which it expands by claiming that several different job resources can play the role of buffer for several different job demands. Social support is probably the best known variable that has been proposed as a potential buffer against job strain (Haines, Hurlbert, & Zimmer, 1991), but other work characteristics (e.g., role clarity and performance feedback, information provided by supervisors, and job autonomy) may also act as moderators (Kahn & Byosiere, 1992).

From this perspective, researchers have focused on the buffer effect that job resources have on the relationship between job demands and burnout, and found evidence for the proposed interaction (Bakker, Demerouti, & Euwema, 2005; Xanthopoulou, Bakker, Demerouti, & Schaufeli, 2007).

Workaholism differs from burnout with respect to how it appears, but both are positively affected by the strain of job demands. Although job demands are not necessarily negative, they may turn into job stressors when meeting those demands requires high effort from which the employee has not adequately recovered (Meijman & Mulder, 1998). Bakker and Demerouti (2007) have suggested that job demands generate stress which influences burnout, and that job resources mitigate the stress generated by job demands. Job resources moderate the relationship between job demands and workaholism according to the same buffering effect that job resources have on the relationship between job demands and stress. Therefore, I proposed the following hypothesis:
Hypothesis 5: Job resources will moderate the relationship between job demands and workaholism.

Consequences. Most researchers of the consequences of workaholism have focused on its negative attributes (Schwartz, 1992). Burke (2001) includes depictions of workaholics as unhappy, obsessive, tragic figures not performing well at work and creating difficulties for their coworkers. Workaholism has also been reported to produce negative cognition-related outcomes such as poor mental health, perfectionism, and distrust of coworkers. If workaholics do not have sufficient time and opportunity to recover from their excessive work effort, and take part in leisure activities, for example, they may become emotionally or cognitively exhausted (Taris, Schaufeli, & Verhoeven, 2005). Other researchers have also noted the negative effects on mental or physical health when the work role dominates other life roles (Greenhaus, 1988; Kanai, Wakabayashi, & Fling, 1996).

Workaholism can also result in poorer social relationships outside work because excessive devotion of time and energy to work logically reduces the time and energy available for developing and maintaining social relationships outside the workplace (Bonebright, Clay, & Ankenmann, 2000; Robinson, Flowers, & Carroll, 2001). Therefore, I proposed the following hypotheses:
Hypothesis 6a: Workaholism will be negatively related to OCB, a positive organizational outcome.
Hypothesis 6b: Workaholism will be positively related to TI, a negative organizational outcome.

Method

Participants

In previous studies about work engagement or workaholism, the participants have included firefighters, insurance salesmen, and employees in innovation departments in telecommunication companies that emphasize the need for the employees to work independently (May, Gilson, & Harter, 2004). Therefore, in this study, I chose consultants as participants because they are required to work independently. Of the participants 71.9% were men, of whom 56.7% were aged between 20 and 29 years, 29.2% were aged between 30 and 39 years, and 14.1% were aged between 40 and 49 years. A total of 200 consultants in a local consulting company were invited to participate (response rate 89%, N = 178).

Measures

Job demands. Two types of job demands were measured: quantitative, that is, work overload (Cronbach’s α = .79), and qualitative, that is, emotional demands (Cronbach’s α = .81).

Job resources. I measured three job resources that apply at the task level, that is, performance feedback (Cronbach’s α = .79), the interpersonal level, that is, social support from colleagues (Cronbach’s α = .84), and the level of the organization of work, that is, supervisory coaching (Cronbach’s α = .89).

Work engagement. I assessed work engagement using the Utrecht Work Engagement Scale (UWES; Schaufeli et al., 2002). The items are grouped into three subscales that reflect the three underlying dimensions of engagement: vigor (Cronbach’s α = .85), dedication (Cronbach’s α = .83), and absorption (Cronbach’s α = .87).

Workaholism. I used two scales from the Workaholism Battery (WorkBAT; Spence & Robbins, 1992): work involvement/working excessively (Cronbach’s α = .88) and inner drive to work (Cronbach’s α = .85), to measure workaholism. (I have used the term working excessively in the present study because the original term work involvement became known as working excessively.)

Turnover intention. I used the three items (Cronbach’s α = .83) developed by Landau and Hammer (1986) to measure the level of intention to leave a job.

Occupational Citizenship Behavior. I measured OCB with items (Cronbach’s α = .88) from Wayne, Shore, and Liden (1997), in line with my focus on organizational attitudes in OCB, which supports the social and psychological environment in which task performance takes place (Organ, 1997).

Results

To test the hypotheses, I conducted a series of eight multiple regression analyses. It was proposed in Hypothesis 1 that job resources will be positively related to work engagement. Consistent with Hypothesis 1, it is shown in Table 1 that of the three job resources, supervisory coaching is positively related to the three subscales in work engagement and that colleagues’ support is positively related to two subscales, vigor and dedication, whereas performance feedback had no significance (Hypothesis 1 was partially supported). Hypothesis 2, in which it was proposed that job demands moderate the relationship between job resources and work engagement, was also partially supported; that is, work overload, one of the job demands, decreased the relationship between the job resources factors and work engagement subscales, as expected, whereas the other job demand, emotional demands had no effect (Hypothesis 2 was partially supported).

In Hypothesis 4 it was proposed that job demands will be positively related to workaholism. Consistent with Hypothesis 4, it is shown in Table 2 that work overload is positively related to both workaholism scales and that emotional demands are positively related to one workaholism scale, inner drive (Hypothesis 4 was partially supported). Hypothesis 5, in which it was proposed that job resources moderate the relationship between job demands and workaholism, was also partially supported. As expected, each job resource, that is, performance feedback, supervisory coaching, and colleagues’ support, decreased the relationship between both types of job demands and the work engagement subscales (Hypothesis 5 was partially supported).

It was proposed in Hypothesis 3 that work engagement will be positively related to the organizational outcomes, TI and OCB. As shown in Table 3, dedication, a subscale of work engagement, is positively related to OCB, and vigor, another subscale, is negatively related to TI, and positively related to OCB (Hypothesis 3 was partially supported). It was proposed in Hypothesis 6a that workaholism will be negatively related to OCB, a positive organizational outcome, and in Hypothesis 6b that workaholism will be positively related to TI, a negative organizational outcome. However, although the workaholism scale, working excessively, was negatively related to OCB as expected (Hypothesis 6a was supported), the other workaholism scale, inner drive, was also negatively related to TI. This was an unexpected result (Hypothesis 6b was not supported).

Discussion

I believe it is surprising that workaholism was found to be negatively related to TI, contrary to Hypothesis 6b. The reason for this result may be inferred from the characteristics of the participants. I chose consultants because, as they work independently, are fully occupied, and work intensively much of the time, they are more likely to display work engagement or workaholism characteristics. Consultants’ work may be seen as insecure rather than regular employment, leading to workaholism, which generates stress. For career development, they endure this stress, resulting in low performance. This increases their obsession to remain in their job instead of changing careers. The resulting increased stress drives workaholics to be more addicted to their work. Fassel (1990) suggests that at this stage, individuals’ personal lives become unmanageable, in a similar fashion to alcoholism, in which a person is addicted to drinking in spite of the physical and mental problems that this causes.

TI is generally regarded as a negative organizational outcome. Previous researchers of TI have focused on changing job circumstances that decrease employees’ TI. However, some individuals remain in their job in bad circumstances, whereas others tend to leave their companies regardless of the circumstances (Zimmerman, 2008). If job circumstances are not considered the reason for turnover, other factors need be investigated. Therefore, there are difficulties in explaining if workaholism has a positive or negative relationship with TI. In this study, taking into account the participants’ characteristics and the procedure of workaholism’s influence on TI, the results show that workaholism influences organizational outcomes as follows: The inner drive component of workaholism is negatively associated with TI, and the working excessively component of workaholism influences OCB negatively.

I have contributed to the literature through the identification and empirical investigation of the distinctions between job engagement and workaholism in the integrative model that includes their antecedents and consequences, and the explication of interaction effects among workaholism antecedents. To my knowledge, I am the first researcher to show that where levels of work-related resources are high, the effect of job demands on the core dimensions of workaholism, that is, working excessively and inner drive, is significantly reduced.

It is evident that the JD-R model can be used as a tool for human resource management. Whereas many researchers have used the JD-R model to reveal the distinctions between work engagement and burnout, in this study I have used the JD-R model to show the differences between work engagement and workaholism. Because workaholism was found to be a key negative factor in the model, future researchers should explore individual-based interventions or organizational-based programs to reduce workaholism symptoms.

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This study was supported by a 2013 research grant from Sangmyung University.

Youngkeun Choi, Division of Business Administration, College of Business, Sangmyung University, 20, Hongjimun 2-gil, Jongno-gu, Seoul 110-743, Republic of Korea. Email: [email protected]