1. Introduction
Workaholism is a reality for contemporary society in most fields of activity. However,
Clark et al. (
2016) explain that the scientific research on the phenomenon is still currently at an early stage because, at present, there is not yet an agreement in terms of defining the gaze and measuring the adequacy of the phenomenon; however, their study showed that workaholism is not related to demographic issues such as gender, marital status, or parental status. Recent research (
Molino et al. 2016) has shown that the trend of working in excess is significantly correlated with negative outcomes in three important areas of life: health, family, and employment. So far, this view has also been confirmed by
Clark et al. (
2016), whose results provide evidence that overwork and workaholism generate negative results at an individual, interpersonal, and organizational level.
Advanced research in the field of psychology (
Aziz and Burke 2015) has shown that behavioral aspects related to a person’s appetite for hard work include stable individual traits or predispositions. In addition to individual predispositions, situational factors also play an important role in encouraging development of the workaholism syndrome. In a similar context,
Stoeber and Damian (
2016) show that at the employee level, the workaholism syndrome manifests itself in three approaches related to work: work engagement, work in excess in the form of workaholism, and job burnout.
The results obtained by
Hakanen and Peeters (
2015) indicate that, beyond its suggested benefits for organizations, active involvement in work can stimulate the positive interactions between work and family for an individual, while workaholism can lead in time to conflicts between work and family needs. It is important for companies to make a clear distinction between a commitment to work and workaholism; the seven-year research study recommends that organizations encourage a firm commitment to work and discourage workaholism so that they can have employees with sustainable work arrangements and happy family lives.
Workaholism can have multiple causes and motivations.
Clark et al. (
2016) show that often, workaholism is related to one’s own personality traits (perfectionism, a type A personality) that are achievement-oriented; on the other hand, workaholism has no significant connection with other personality traits such as self-esteem and conscientiousness.
Regarding the analysis of workaholism, we found that there are some studies on this issue in the literature for different domains such as agriculture, construction, consulting services (
Taris et al. 2012), and the banking industry (
Andreassen et al. 2012). During an analysis of a specialized bibliography on relevant research from the past 15 years, it was highlighted that no relevant analysis was conducted on the factors that determine the phenomenon of workaholism in IT companies, and only individual studies were carried out focusing on Romania (
Negrila 2019;
Butucescu and Uscatescu 2013;
Nistor 2014) to highlight the effects of the phenomenon.
Considering the importance of the IT sector in Romania (turnover, number of employees, premises for development, number of students pursuing IT specializations) on the one hand, and the lack of research on workaholism in this field on the other hand, we consider that our research is relevant because it aims to analyze the factors influencing workaholism in the IT sector in Romania. The multiple linear regression analysis we performed highlights the factors that are determinant in the phenomenon of workaholism, as well as their levels of importance for different aspects of the phenomenon.
The research questions we answer in this scientific article are the following: what are the main factors influencing the phenomenon of workaholism in IT? What is the individual importance of each influencing factor in the overall phenomenon of workaholism in IT?
The article is organized into the following sections: the abstract, introduction, literature review, materials and methods, and results and discussions. The introduction section presents the general context of the research problem, while the literature review section presents the previous relevant research and the state of the IT industry in Romania. Then, the materials and methods section presents the research hypotheses. Finally, the results and discussions section presents the results obtained in detail, as well as the managerial implications and future directions for the research.
4. Results and Discussion
The values of descriptive statistics are presented in
Table 4. We took into consideration all the seven independent factors selected from the scientific literature and for the dependent variable (workaholism level).
As it can be seen from
Table 4, the respondents considered that the level of workaholism was mainly affected by the following variables: the fear of losing the job (M = 4.64), the feeling of responsibility towards one’s family (M = 4.42), and intrinsic pleasure of working (M = 4.21). According to the means of the survey’s answers, the level of workaholism was less affected by the support from one’s life partner (M = 2.43), the remuneration component (M = 3.91), and the need to demonstrate competence in work (M = 4.15). These values partially confirm some previous research conducted in the literature on workaholism.
In order to test the validity of H1–H7 hypotheses, we used the analysis based on multiple linear regression. In this econometrical model, the dependent variable is the level of workaholism in the Romanian IT industry, and the independent variables are employee remuneration, intrinsic pleasure to work, support from one’s life partner, the feeling of responsibility towards one’s family, the need to demonstrate competence at work, the desire for hierarchical advancement, the fear of losing the job. All variables were included in the multiple linear regression model by using the Enter method; we also used linear association. Following the calculations performed using IBM SPSS Statistics, the data from
Table 5 were obtained. The Beta column contains the coefficients with standardized values. For the elaboration and validation of the econometric model in this article, a significance threshold of less than 5% was taken into account for the values of the coefficients to be considered relevant.
It should be noted that, as a result of the performed calculations, the R-Square indicator has the value of 0.444, and F = 19.360,
p < 0.01. Values from
Table 5 lead us to conclude that workaholism is significantly statistically influenced by some of the analyzed indicators. This affirmation is also supported by the values of the multicollinearity test for independent variables (VIF = variance inflation factor) which are presented analytically in
Table 6.
Given that the VIF values for all the independent variables are less than 2.00, we certainly conclude that the variables are not collinear. The result of this multicollinearity analysis is strong evidence to support the model’s validity.
Based on the indicators’ contribution from
Table 5, we note that workaholism in the IT industry is positively determined by employee remuneration (Beta = 0.334), the intrinsic pleasure of working (Beta = 0.215), the feeling of responsibility towards one’s family (Beta = 0.201), and the desire for hierarchical advancement (Beta = 0.150).
Based on the research conducted and the results obtained, we can conclude that the research hypotheses H1, H2, H4, and H6 are confirmed. So we can affirm that the correlations related to the variables about the employee remuneration, the intrinsic pleasure of working, the feeling of responsibility towards one’s family, and the desire for hierarchical advancement are confirmed. The assumptions are not supported for indicators of support from one’s life partner for workaholism, the need to demonstrate competence at work, and the fear of losing the job.
In order to test the hypotheses about the demographic variables (Ha1–Ha3), we implemented the multivariate analysis of variance. The purpose was to highlight whether the level of workaholism in terms of remunerative component, the intrinsic pleasure of working, the feeling of responsibility towards one’s family, and the desire for hierarchical advancement depends on the socio-demographic factors: gender, age, and marital status.
The data and significance thresholds presented in
Table 7 as a result of the performed calculations reveal the fact that only the Ha1 hypothesis is partially supported. Additionally, the hypotheses Ha2 and Ha3 are not supported. According to the results of the multivariate analysis of variance, the age indicator generates differences that are statistically significant for the variables remuneration component (F = 3.548,
p < 0.10), intrinsic pleasure of working (F = 5.747,
p < 0.05), and desire for hierarchical advancement (F = 6.353,
p < 0.05). Gender generates significant differences only for the variable intrinsic pleasure of working (F = 20.006,
p < 0.01). In the developed model in our research, marital status does not generate statistically significant differences for the factors included. This means that the model of the linear multiple regression equation is generally valid for all demographic categories in the IT industry.
Based on the analysis performed in this study, it is clear that the following factors have a significant influence on the workaholism in the IT industry: employee remuneration, the intrinsic pleasure of working, the feeling of responsibility towards one’s family, and the desire to advance in the professional hierarchy. According to the analysis conducted in this research, the linear regression model that contains only statistically relevant variables is shown in the following equation:
where:
X1 = the remunerative component;
X2 = the intrinsic pleasure of working;
X3 = the feeling of responsibility towards the family;
X4 = the desire to advance in the professional hierarchy.
The results also show that only age generates some statistically significant differences in terms of motivation for workaholism in the IT industry. The other demographic factors do not have any relevant influence.
The article is relevant because it is the first one of this kind which comprehensively addresses the factors influencing workaholism, presenting a concise and scientifically documented picture. The previous research mostly focused on individual indicators or groups of indicators, while our research provides a complex analysis of the factors influencing workaholism in the IT industry. The results of the study are useful to human resource managers in IT companies because they provide an objective and representative tool that can help identify employee motivators, possibly by including them in an existing framework (
Tofan et al. 2015).
Based on the results of this article, human resources departments can assess the condition of employees by placing them in a relevant profile. Depending on the dynamics and organizational culture, companies can recruit employees whose attitude towards work is compatible with the long-term objectives of the company. If the attitude of employees towards work and their individual performance do not converge with the company’s objectives, the influencing factors highlighted in this research can be a scientific benchmark in assessing the causes of the problem.
Given that the research was conducted in a country where the IT industry is very competitive, the results of the study are also an important benchmark for IT companies operating in other countries.
Regarding the limitations of the article, we note that the research results are limited to the cluster of Romanian IT companies. As we described above, we analyzed only seven variables that can influence workaholism in IT together with three socio-demographic variables. Therefore, the research is constrained by these limited numbers.
Based on the results obtained in this article, we identify several future research directions. One of these could be the analysis of workaholism in a comparative manner by including other countries or geographical regions. Another future direction could be related to the analysis of the influence on workaholism according to several relevant indicators at regional level. The inclusion of many socio-demographic factors in the comparative analysis could be a new additional research direction. Another direction for the future could be analysis performed on clusters of types of occupations in the IT industry (programmers, database administrators, network administrators, web developers, etc.).