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Employees’ opportunities, preferences, and practices in telecommuting adoption
Information & Management 41 (2004) 469–482
Employees’ opportunities, preferences, and practices in telecommuting adoption Pascale Petersa,1, Kea G. Tijdensb,*, Ce´cile Wetzelsc,2 a
b
Department of Sociology, University of Utrecht, Utrecht, The Netherlands Amsterdam Institute for Labour Studies (AIAS), University of Amsterdam, Amsterdam, The Netherlands c Delft TNO Institute of Strategy, Technology and Policy, Delft, The Netherlands Received 3 January 2002; received in revised form 7 February 2003; accepted 26 June 2003
Abstract This study uses three separate models for the opportunity, preference, and practice of telecommuting to analyze employee telecommuting adoption. Explanatory clusters relate to organizational, job, household, and individual characteristics derived from the combined insights from literature on telework management and employees’ telecommuting decisions and behavior. Data was collected from 849 employees using a personal computer at the workplace, selected from a representative sample of the Dutch labor force. Multivariate analyses were applied. Opportunity largely depended on organizational and job characteristics. Preference was dependent on all explanatory clusters. Practice was especially dependent on job and individual characteristics. # 2003 Elsevier B.V. All rights reserved. Keywords: Organizational factors; Job characteristics; Household factors; Individual factors; Multivariate analyses; Cross-section data; Telework
1. Introduction Many articles and books on telecommuting, the substitution of working at home or at an office close to home instead of commuting to the usual work site, start out listing the advantages of this new work concept. Organizations may view telecommuting as a solution to problems of housing their expanding staff, a means to reduce overheads, or as a way to cut absenteeism. Moreover, it is assumed to lead to higher *
Corresponding author. Tel. þ31-20-525-4347; fax: þ31-20-525-4254. E-mail addresses: [email protected], [email protected] (P. Peters), [email protected], [email protected] (K.G. Tijdens), [email protected] (C. Wetzels). 1 Tel.: þ31-30-253 4306; fax: þ31-30-253-4405. 2 Tel.: þ31-15-269 5439; fax: þ31-15-269 5460.
commitment and productivity, to improve customer service, enhance organizational flexibility, or—once introduced as an employee benefit—attract scarce personnel. In an attempt to expand their market shares, telecom companies try to convince consumers of the benefits of telecommuting. National governments in the European Union advocate telecommuting both as a means to reduce traffic congestion and increase women’s labor force participation. Yet, there is reluctance to adopting telecommuting. Employer organizations stress the need for a careful look into the costs of this new work form, including tax implications and benefits, as well as data security. Labor unions are concerned about the working conditions in telecommuting, such as the provision of furniture, reimbursement of wages, workplace design, the monitoring of productivity, and career prospects. Telecommuting
0378-7206/$ – see front matter # 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0378-7206(03)00085-5
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was recently criticized as a process by which contemporary society becomes more autistic and that only a balanced mix of telecommuting and work in the office could prevent this from occurring [3]. Many employees, however, show a preference for it. In order to facilitate the uptake of telework in Europe, the European Commission consulted the social partners, the employers’ and workers’ representatives, at the European level. In July 2002, these representatives signed an agreement on teleworking to enhance business flexibility and modernize work organization, while ensuring better protection and higher job quality for teleworkers. Thus, actors in the field are multiple, their interests diverse, and their expectations high. The past decade has shown a gradual introduction of telecommuting. In the US, on the basis of a household study it was shown that one in five employees currently participate in some type of teleworking [7]. In the European Union, these percentages were lower. According to a 1999 representative survey of 7700 individuals aged 15 and older in 10 European Union member states, 6% of the labor force did some telework. Two-thirds of this group spent at least one full working day a week at home or in the field, having access to their employer or client/principal via datacommunication [12]. In 2000, a Eurobarometer survey came up with a similar percentage [10]. However, employee interest in telecommuting is much higher than employer interest. Thus, a model of employers’ telecommuting adoption may underestimate the employees’ telecommuting practices. A further increase of telecommuting can be expected. Any forecasts of the spread of telecommuting require an analysis of the factors that influence telecommuting adoption, both by employers and employees. Why do employers give their employees the opportunity to work from home? Does it depend on the nature of the job, the state of technology, or the willingness of establishments to change their management practices? These factors are characterized as supply-side issues [16]. At least equally important are the demand-side issues. Why do employees, given the opportunity to telecommute, prefer to do so and why? Does the employee’s preference and actual telecommuting practice depend on household or individual characteristics? Therefore, employees’ and employers’ adoption of telecommuting must be studied as complements, for the two actors may have
different agendas and assign different weights to the factors considered in the choice process [26]. The relationship between employees’ and employers’ decisions may in fact require employer–employee-related data. To overcome this complex research design, the most common solution is to question employees about management support. Our study aims to gain a better understanding of the factors influencing the telecommuting adoption, and combines both supply-side and demand-side factors. Using a large-scale questionnaire of employees, employer-side issues were measured through the employee. Based on a review of the literature we modeled four explanatory clusters, related to the employee’s organization, job, household, and personal characteristics, that may affect employees’ telecommuting adoption. The adoption of telecommuting was assumed to consist of three related issues: the telecommuting opportunity, preference, and practice.
2. Telecommuting adoption: a review of the literature Employee adoption of telecommuting has been investigated in a number of studies in the US and Europe. The methodologies varied from interviews with teleworkers to large-scale questionnaires of employees. The predicting variables mostly included socio-demographic characteristics and attitudinal measures. The dependent variables ranged from the perceived benefits to the location for telecommuting work. Patricia Mokhtarian took the initiative in modeling employees’ telecommuting adoption (e.g. [20,22]). 2.1. The impact of organizational characteristics Management literature stresses the benefits of telecommuting. The development of telecommuting is believed to be strongly related to changes in organizational structures, in coordination systems and, in task specifications within organizations. These changes include downsizing, delayering, business process reengineering, project-based structures, the shift to a core/periphery model, and a growth in inter-organizational networks [6]. The changes are associated with new styles of control, with close supervision being replaced by mechanisms of internal motivation.
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The emergence of a new type of employee with a wider span of control and accountability facilitates control by positive reinforcement. Traditional concurrent control has to be replaced by new forms, such as ex ante control by selection and education, ex post control by output and outcome management, and meta control through the creation of a specific work culture implicitly motivating and committing employees to their job, coworkers and organization [13]. As companies become more used to a dispersed and relatively autonomous workforce, they may be more comfortable with telecommuting. However, little empirical evidence has been found to underpin these organizational conditions. The empirical evidence available from employee surveys does not refer to organizational characteristics other than company size. A study based on telephone interviews with 1170 households, a representative sample of all US households, revealed that telecommuting was most often found among people working in either a very small or a very large company. In contrast to the management literature, organizations seem to be reluctant to adopt telecommuting. In a survey of establishments in EU member states, 76% of the companies neither practiced telework, nor were interested in it [8]. Among the barriers, data security problems ranked first and problems concerning productivity and work quality ranked second. A survey of 66 managers of market services businesses in the Tokyo area found nearly 70% against telecommuting, the major arguments relating to additional responsibility for managers, decreased interaction between employer and employee, the high costs involved in IT, security concerns over official documents, and erosion of the traditional work style [14]. The perceived barriers may lead to informal teleworking, as is shown in a study of 1201 Amsterdam citizens, who were asked to classify their job as ‘teleworkable’, i.e. being suitable for telecommuting; the employers were also asked about telecommuting. While the employers had not yet developed a telework policy, the employees had already realized their preferences, and, once confronted with the research on their employees’ behavior, the employers were very surprised [31]. One Dutch case study showed that organizations benefit from telecommuting because they save in office space by creating flexi workplaces, particularly when they plan to build new premises [11]. A case study of a marketing company in the US, introducing
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telecommuting for its salespeople as part of a program to reduce paper-based procedures and transform voice communication into automated procedures and fullscale connectivity, provided an example of an organization trying to better position its strategic goals [32]. A few case studies have shown that employers opt for telecommuting as an employee benefit [17]. Employee interest in telecommuting in Europe is high. Throughout the European Union, an average of 60% of employees show an interest in it. The interest among those looking for work is even stronger. Employers giving their employees the opportunity to telecommute may be regarded as attractive. A study of 285 employees of an IT company in Singapore confirmed that employees would be less likely to end the employment relationship if the company offered telecommuting as an option [28]. Similarly, a study of 300 employees in Canadian companies found that both managers and employees expected that the employees were more likely to stay at the company when they were given the opportunity to telework [19]. Experimental research with students reaffirmed the claim that the concept of telecommuting will attract well-qualified individuals to join the organization [18]. Thus, particularly in a tight labor market, organizations may develop telecommuting policies as an employee benefit, because (potential) employees perceive the opportunity as attractive. 2.2. The impact of job characteristics The discrepancy between employers’ and employees’ interests in telecommuting finds its focal point in the notion of ‘‘job teleworkability’’, i.e. is the job suited for telecommuting? By nature, jobs that demand a physical presence are not appropriate, whereas the knowledge or information workers’ jobs are typically suited for telecommuting. This leaves room for a large range of jobs where the suitability for telecommuting is not clear and therefore may be subject to different interpretations by employers and employees. This must lead to discrepancies between telecommuting opportunities and preferences. Two thirds of employees in European Union member states carry out activities suitable for telework at least 1 day a week. In contrast, only one third of the companies practice telework, and the number of teleworkers per establishment is rather low. A study of 314 employers
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in five industries in The Netherlands revealed that their major argument against telecommuting related to job suitability, leading to a much higher percentage of employees not having the opportunity that would have been expected from employee surveys [33]. In comparing the telecommuting opportunity and telecommuting preferences, a self-administered questionnaire of employees in the Dutch IT industry showed that differences between occupational categories and sectors within the industry were significant, pointing to different definitions of job teleworkabily used by employers and employees [29]. Not surprisingly, attempts have been undertaken to come up with lists of occupational categories that are suitable for telecommuting [5]. In a study of 628 employees of the City of San Diego, teleworkability was measured by a factor constructed on the basis of variables indicating self-defined suitability, location independency, task independency, task scheduling autonomy, and supervisory position, i.e. having a managerial job [1,23]. In other attempts to overcome measurement problems, a proxy for job suitability was used, for example job autonomy. Employees with less autonomy are assumed to be less likely to be given a telework opportunity. Other studies assumed a job to be particularly appropriate for telecommuting in the case of a relatively high number of so-called ‘longduration’ tasks, or where such tasks can be grouped into 1 or 2 days a week [24]. Some studies have used a straightforward indicator, such as education. In line with expectations, well-educated individuals are more likely to express a preference for telecommuting from home. In the EU member states survey, teleworkers were mostly highly qualified in comparison with nonteleworkers. Strikingly, the use of IT equipment on the job, or the frequency of IT use, was hardly used as an indicator, although information workers’ jobs are said to be typically suited for telecommuting. Only a few studies relate telecommuting to the dependence on IT, or to jobs that were created by information and communication technology [27]. According to the Eurobarometer survey 2000, telework was most widespread among managers, who used it frequently in addition to computer use in their office. Some attention has been paid to another important argument for telecommuting adoption, notably that it reduces the frequency of distractions in a hectic workplace. In the study of Amsterdam citizens, this argu-
ment ranked first both among the citizens currently telecommuting and those desiring to do so. Apparently, the office workplace offers insufficient opportunity for working in a concentrated way. Office workplaces are too busy for writing reports, working out drafts, or other activities that require concentration. Telecommuting offers the opportunity for a quiet workplace. This is in line with a study of 62 telecommuting professionals and managers in the UK, where the major advantage was better performance conducted under telecommuting conditions, both in quantity and quality of work [2]. This finding was also supported in a US study of 71 employees of a large high technology organization, slightly over half of them being teleworkers [4]. Telecommuting employees reported significantly greater productivity. In the US study on households, almost three-quarters of home-based teleworkers reported a major increase in productivity and work quality. Similar results were reported in the Eurobarometer survey 2000, where teleworkers overwhelmingly indicate that this form of work enhanced their productivity. This finding may be related to workaholism. In the San Diego study, workaholism was shown to be the second highest contributor to the preference of telecommuting, particularly from a telecenter. This variable and a second one, i.e. ‘‘stress’’, captured the importance of being able to work productively and comfortably when telecommuting. The opposite probably is expressed in the variable ‘‘workplace interaction’’, indicating a person’s need for the social and professional interaction obtained at the regular workplace. This variable was positively correlated with the preference not to telecommute. In conclusion, interpretations of job suitability may vary across employers and employees. Yet, when education or job level was used as an indicator, the well-educated and managerial employees were found to be more likely to practice telecommuting. 2.3. The impact of household characteristics Employed parents may value the timesaving effects of telecommuting. A Dutch study revealed that the number of households that experienced a ‘‘time squeeze’’ had increased. Both men’s and women’s time spent in the workplace and time spent with children had increased. As a consequence, free time had become more vulnerable [25]. Working parents
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may highly value the time-savings of telecommuting due to the elimination of commuting time or because telecommuting may allow a parent to stay at home with a sick child. In their national policies, EU member states stressed the benefits of telecommuting with respect to reconciliation work and family life, because telecommuting was assumed to increase the flexibility in working hours. Indeed, according to the Amsterdam study, time flexibility ranked third in telecommuting preferences. Yet, little empirical evidence confirmed whether time flexibility was a synonym for improved reconciliation of work and family life. The UK study of telecommuting professionals even concluded that work–home interference may be a hindrance to further growth in telecommuting, and that the availability of extra workspace at home emerged as a key factor of success of telecommuting programs. This was in line with findings in the San Diego study, where household interaction, defined as a concern when performing home-based telework, increased the likelihood of preferring to work from the regular office. The US survey of households reported that both teleworkers and non-teleworkers who work at home after normal work hours experienced a work–family role conflict, but that the type of conflict was different. Teleworkers reported less interference between work and family roles, leading researchers to conclude that teleworkers may be better able to manage some key aspects of the work–family conflict. In the Eurobarometer survey 2000, similar results were reported. Twice as many teleworkers as non-teleworkers regarded combining work and private life as an advantage. Thus, although telecommuting may reduce the work–family conflict, it was not clear whether this could be related to the presence of children in the home, or that it applied equally to households with and without children. The EU member states survey showed only slight differences in household composition between teleworkers and non-teleworkers. In the US, teleworkers and non-teleworkers were equally distributed across marital status. 2.4. The impact of individual characteristics Socio-demographic variables, such as age and gender, are found to influence telecommuting adoption, particularly the preference for it. The San Diego study shows that as age increases the likelihood that an
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individual preferred to telecommute decreases. The US study of a high technology organization, however, does not reveal significant age differences between those practicing telework and those not doing so. The US study of households confirmed this. Bivariate analyses of the EU member states survey data, however, indicated that the age group 30–49 was overrepresented among teleworkers. The same study showed that three out of four teleworkers were male, and that this stands in sharp contrast to the widespread opinion that telework was predominantly female. The US study of households also confirmed that men were telecommuting more often. At first sight, commuting time is the most important factor in telecommuting. This is fully in line with local or national policies to reduce traffic congestion by promoting telecommuting. Transportation researchers particularly have great interests in the topic. In many studies, commuting time was indeed found to have a large positive effect on telecommuting adoption. The EU member states survey indicated that every 6th teleworker against every 27th non-teleworker has a commuting distance of more than 50 km. In the Amsterdam study, reduction of commuting time was the most important argument among the 20% currently telecommuting and 26% desiring to do so. In a study of IT employees in Singapore, avoiding the hassle of commuting ranks first, and reducing commuting time ranks second in its perceived advantages. It is the reduced commuting time and not the reduced commuting costs that makes telecommuting attractive. The reduced commuting time may partly be devoted to additional working hours. The UK study of telecommuting professionals revealed that for nearly half of this group the time spent on work had increased after moving to telecommuting. The EU member states survey indicated that 80% of teleworkers work more hours than contractually agreed, compared with 50% non-teleworkers. Compared to non-teleworkers, teleworkers more often had positive attitudes with regard to the benefits of telecommuting. Moreover, attitudes may influence both preferences and practices, but the relationship is not straightforward. Not all employees in an organization that gives its employees the opportunity to telecommute choose to do so. In the same vein, not every worker who prefers to telecommute has the opportunity to do so. In fact, the relationship between being given the opportunity, preferring and actually practicing
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telecommuting may be a dynamic one. Perceived restrictions, resources and opportunities both affect intended and overt behavior [15,21]. Restrictions may influence an individual’s telecommuting preference and practice. Given the individual’s environment and the long or short-term constraints faced, the individual worker makes a choice. We assumed that positive attitudes separately affect preferences and practices. Compared with non-teleworkers, teleworkers more often have positive attitudes with regard to the benefits of telecommuting.
3. Model, assumptions and data 3.1. Definition of telework Several attempts have been undertaken to identify telework [9]. Most cases use criteria such as the legal status of the teleworker, the work location, the distinction between regular and occasional telework, and the use of IT as a precondition to exclude the ‘traditional’ home workers or the home-based self-employed not using the new technologies. Based on these criteria, four groups of teleworkers can be distinguished, homebased teleworkers, mobile or multi-site teleworkers, freelancers and self-employed teleworkers, and supplementary or marginal teleworkers [30]. The focus in our study is on home-based teleworkers; i.e. employees who have the opportunity, who prefer or who practice remote information work for one employer at least 1 day a week. 3.2. Modeling employees’ telecommuting opportunities, preferences, and practices Here, the employees’ telecommuting adoption was considered to consist of three related issues: opportunity, preference, and practice. The study sought to answer the questions: Which employees are given the opportunity to telecommute? Which employees prefer to telecommute? Which employees practice telecommuting? Four clusters of explanatory variables were expected to affect telecommuting adoption. These clusters were related to the employee’s organization, job, household, and individual characteristics. On the basis of the literature review, some variables were expected to affect telecommuting opportunities in
particular. Furthermore, some would influence telecommuting preferences, and others would influence telecommuting practices. As regards the impact of organizational characteristics, the following hypotheses were tested empirically: 1. The more business localities within an organization, the more likely it is that employees are given an opportunity to telecommute. Business localities will influence the telecommuting preferences and practice to a minor extent. 2. The larger the size of the business, the more likely it is that employees are given an opportunity to telecommute. The size of the business will influence the telecommuting preferences and practice to a minor extent. 3. The flatter the organizational hierarchy, the more likely it is that employees are given an opportunity to telecommute. The organizational hierarchy will influence the telecommuting preferences and practice to a minor extent. 4. Employees who have no direct supervisor will be more likely employees are given an opportunity to telecommute. The absence of a supervisor will influence the telecommuting preferences and practice to a minor extent. 5. The lower the percentage of women in the unit, the more likely it is that employees are given an opportunity to telecommute. The percentage of women will influence the telecommuting preferences and practice to a minor extent. 6. The better the collegial atmosphere, the more likely it is that employees are given an opportunity to telecommute. A collegial atmosphere will influence the telecommuting preferences and practice to a minor extent. 7. The more colleagues in the department using a computer, the more likely it is that employees are given an opportunity to telecommute. Colleagues using a computer will influence the telecommuting preferences and practice to a minor extent. As regards the impact of job characteristics, the following hypotheses were tested empirically: 8. Frequent computer users will be more likely to practice telecommuting. Computer use will influence the telecommuting opportunity and preferences to a minor extent.
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9. Employees with good career opportunities will be more likely to practice telecommuting. Career opportunities will influence the telecommuting opportunity and preferences to a minor extent. 10. Employees who have attended Internet courses will be more likely to practice telecommuting. The attendance of Internet courses will influence the telecommuting opportunity and preferences to a minor extent. 11. Higher educated employees will be more likely to practice telecommuting. Education will influence the telecommuting opportunity and preferences to a minor extent. 12. Employees with high levels of IT skills will be more likely to practice telecommuting. IT skills
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will influence the telecommuting opportunity and preferences to a minor extent. 13. Employees in a supervisory position will be more likely to practice telecommuting. A supervisory position will influence the telecommuting opportunity and preferences to a minor extent. 14. Employees with long working hours will be more likely to practice telecommuting. Working hours will influence the telecommuting opportunity and preferences to a minor extent. As regards the impact of household characteristics, the following hypotheses were tested empirically: 15. The more children an employee has, the more likely it is that employees have a preference for telecommuting. The number of children will
Fig. 1. Research model to predict three modes of telecommuting from four clusters of explanatory variables.
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influence the telecommuting opportunity and practices to a minor extent. 16. Employees with young children in the household will be much more likely to prefer telecommuting. The presence of young children will influence the telecommuting opportunity and practices to a minor extent. 17. Employees with a partner will be more likely to prefer telecommuting. A partner will influence the telecommuting opportunity and practices to a minor extent. As regards the impact of individual characteristics, the following hypotheses were tested empirically: 18. Male employees will be more likely to prefer telecommuting. Gender will influence the telecommuting opportunity and practices to a minor extent. 19. Young employees will be much more likely to prefer telecommuting. Age will influence the telecommuting opportunity and practices to a minor extent. 20. Fully or partly disabled employees will be much more likely to prefer telecommuting. Disability will influence the telecommuting opportunity and practices to a minor extent. 21. Employees with long commuting times will be much more likely to prefer telecommuting. Commuting time will influence the telecommuting opportunity and practices to a minor extent.
16–64 in paid work were selected. The questionnaire consisted of 74 questions, of which seven directly addressed telework, five addressed IT use at work, five addressed locations of work and commuting, 13 addressed characteristics of the workplace, and the remaining questions addressed individual and household characteristics. As regards telecommuting adoption, the following questions were posed: ‘Does your employer give you the opportunity to telecommute’, ‘Do you prefer to telecommute’, and ‘Do you currently practice telecommuting’ all applied to the situation in which the employee worked at home for at least 1 day a week. The self-reported teleworker status may represent a variable mixture of time spent at the regular workplace and at home during the course of a given week. In total, 1335 working men and women responded. Since the hypotheses focused on employees in an organizational setting, the self-employed and freelancers, and the respondents reporting to be working alone were deleted from the analyses. Since telecommuting by definition was only possible when working with a personal computer or laptop, only employees using this equipment were selected (82% of the employees not working alone). After excluding outliers and missing data for the relevant variables, the data set included 849 observations. The independent variables were controlled for multicollineairity, i.e. correlations that are too high.
3.3. Sample and data
4. Opportunities, preferences, and practices
The data used for our analyses came from the Work & IT 2001 survey. This computer-designed questionnaire was part of the computerized telepanel, which is a representative sample of the Dutch population. For the Work & IT 2001 survey, only respondents aged
Table 1 shows that out of the 849 respondents, 202 (24%) were given the opportunity to telecommute, 466 (55%) preferred to telecommute and 213 (25%) were actually practicing telecommuting. Notice that this percentage is much higher than the 4% estimated in
Table 1 Number and percentages of the respondents by three telecommuting modes (employed persons using a personal computer at work only) Opportunity Preference Practice No practice Total
No opportunity
Total
No preference
Preference
No preference
66 (8%) 50 (6%)
18 (2%) 68 (8%)
83 (10%) 267 (31%)
46 (5%) 251 (30%)
213 (25%) 636 (75%)
116 (14%)
86 (10%)
350 (41%)
297 (35%)
849 (100%)
Source: Work & IT 2001 survey.
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the EU member states survey for The Netherlands, probably because of our selection of employees using a personal computer at work. The majority of the employees that were given the opportunity to telecommute, were not telecommuting, mostly because they preferred not to do so. A small group was given the opportunity to telecommute, did not prefer to, but was telecommuting anyway. The vast majority of nontelecommuting employees were not given an opportunity to telecommute, but half would prefer to do so. Almost one in five non-teleworkers was given the opportunity, but the majority of them preferred not to do so. There was also a small group who were given the opportunity to telecommute, preferred to do so, yet were currently not telecommuting. Table 1 reveals that more than half of the employees who preferred telecommuting are not able to realize their preferences because they are not given the opportunity to do so. A small, puzzling group was not given the opportunity and did not prefer to telecommute, but for whatever reason this group of employees did telecommute. In exploring the differences between employees given the opportunity, preferences, and practices of telecommuting, Table 2 presents the mean scores for the three groups with regard to the four explanatory clusters in the model for organizational, job, household, and individual characteristics. A first look at the relationships reveals that working hours and commuting time are higher for those practicing telecommuting than for those given the opportunity. Organizational characteristics seem to be important, particularly factors such as: more than one business locality and more hierarchical levels. With regard to job characteristics, employees given the opportunity to telecommute were, on average, more highly educated than those practicing telecommuting and these employees were more highly educated than those preferring to do so. Levels of IT skills hardly vary between the three groups of employees. Strikingly, telework practitioners have the lowest frequency in computer use than those with both employees with preferences for telecommuting and employees given the opportunity. With regard to household characteristics, the three groups do not seem to differ much. With regard to individual characteristics, employees practicing telecommuting were slightly older than those in the other two groups. In exploring which employees were given an opportunity to telecommute, preferred to telecommute and
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practiced telecommuting multivariate analyses are needed. In the first step, all variables of the four explanatory clusters were entered into a logistic regression analysis. In a second step, the non-significant variables were deleted one by one. This was performed for the three telecommuting modes separately. The results of the final model estimations are shown in Table 3. Management literature often suggests that telecommuting is an expression of modern management and, therefore, related to major organizational characteristics. Our analyses showed that some organizational characteristics did affect telecommuting opportunities, preferences, and practices. As expected, the results showed that employees in organizations with more than one business locality were more likely both to be given the opportunity and to prefer telecommuting. These effects were rather large. Compared with employees whose organization had only one locality, employees in organizations with more than one business locality were 70% more likely to be given the opportunity to telecommute and 50% more likely to prefer it. Strikingly, the number of business localities had no impact on telecommuting practices. The size of the organization had no impact on the opportunity, the preference, or the practice of telecommuting. As expected, organizational hierarchy did have an impact. The flatter the organization, the more likely an employee preferred and practiced telecommuting, although the effect was not large. Organizational hierarchy had no influence on the opportunity. As expected, having a supervisor at the workplace negatively affected the opportunity to telecommute, although it did not affect the employee’s preference and practice. Finally, neither the collegial atmosphere nor working in a computerized departmental setting affected any of the three modes of telecommuting (Fig. 1). Table 3 reveals that frequent daily computer use positively affected the preference for telecommuting. An extra 2 h of computer use a day increased the preference for telecommuting by 13%. Strikingly, however, frequent computer users were less likely to practice telecommuting. Every two additional hours of computer use a day decreased the likelihood of practicing telecommuting by 14%. Thus, frequent computer users may have a greater desire to telecommute, but they are less likely to do so. When it comes
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Table 2 Mean scores for employees being given the opportunity, preferring and practicing telecommuting (employed persons using a personal computer at work) Given opportunity to telecommute
Prefer telecommuting
Practice telecommuting
202 1.00 0.57 0.42
466 0.25 1.00 0.32
213 0.39 0.70 1.00
Cluster 1: organizational characteristics More than one business locality [0, 1] Size of the organization [1: <100 employees; 3: >500 employees] Organizational hierarchy [1–20 levels] Supervisor present [0, 1] Proportion of women in the department [range 0–1] Collegial atmosphere [1: bad; 3; good] Majority of colleagues use a personal computer [0, 1]
0.79 1.81 4.60 0.93 0.40 1.79 0.82
0.75 1.82 4.43 0.96 0.44 1.75 0.78
0.73 1.76 4.08 0.95 0.44 1.81 0.81
Cluster 2: job characteristics Frequency of computer use [1: never; 7: all day] Career opportunities [0: none; 7: many] Internet course [0, 1] Level of education [1: low; 3: high] Level of IT skills [1: low: 4: high] Supervisory position [0, 1] Working hours [1: <20 h; 3: >34 h]
4.33 4.75 0.05 2.08 3.24 0.46 2.54
4.41 4.63 0.04 1.93 3.22 0.40 2.67
3.95 4.65 0.07 2.22 3.23 0.42 2.64
Cluster 3: household characteristics Number of children in the household [0–5] Age youngest child [0: no child; 4: youngest >12 years] Spouse [0, 1]
1.00 1.06 0.80
0.94 0.99 0.78
0.96 1.01 0.77
Cluster 4: individual characteristics Male [0, 1] Age group [1: <30 years; 3: 45 years] (partly) Disabled for work [0, 1] Commuting time one way [1: <30 min; 3: 1 h] Attitude: telecommuting saves travel time [0, 1] Attitude: telecommuting facilitates work and family life [0, 1] Attitude: telecommuting reduces commuting and parking expenses [0, 1] Attitude: telecommuting enables a quiet work environment [0, 1] Attitude: telecommuting enables flexible scheduling of the day [0, 1]
0.64 2.13 0.04 1.61 0.85 0.70 0.53 0.82 0.83
0.63 2.14 0.03 1.55 0.89 0.77 0.61 0.86 0.91
0.67 2.26 0.02 1.62 0.85 0.69 0.56 0.85 0.90
N Opportunity for telecommuting [0, 1] Preferences for telecommuting [0, 1] Practicing telecommuting [0, 1]
Source: Work & ICT 2001 survey. Note: All dichotomous variables are coded 0: no and 1: yes.
to career opportunities, it is often suggested that telecommuting would reduce them. However, a t-test for differences in perceived career opportunities did not reveal any significant difference. In line with this finding, career opportunities do not influence any of the three modes of telecommuting. Employees having attended an Internet course are much more likely to practice telecommuting than employees who have not done so. However, attending an Internet course neither affects the opportunity nor the preference for tele-
commuting. As expected, Table 3 shows that compared with highly educated employees, the loweducated were less likely to be given the opportunity to practice telecommuting. Education, however, did not influence employees’ preferences. As expected, levels of IT skills did affect telecommuting. On a fourpoint scale of IT skills, employees with one extra level are 23% more likely to be given the opportunity to telecommute, they more often preferred telecommuting (35%), and they practiced telecommuting more
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479
Table 3 Coefficients, T-values and Exp(B) of the logistic regression analyses for the three telecommuting modes opportunity, preference and practice (employed persons using a personal computer at work, N ¼ 849)
Cluster 1: organizational characteristics More than one business locality [0, 1] Size of the organization [reference >500 employees] <100 employees 100–500 employees Organizational hierarchy [1–20 levels] Supervisor present [0, 1] Proportion of women in the department [range: 0–1] Collegial atmosphere [reference good] Atmosphere bad Atmosphere moderate Majority of colleagues use a personal computer [0, 1] Cluster 2: job characteristics Frequency of computer use [1: never; 7: all day] Career opportunities [0: none; 7: many] Internet course [0, 1] Level of education [reference high] Low education Middle education Level of IT skills [1: low; 4: high] Supervisory position [0, 1] Working hours [reference full-time] <20 h a week 20–34 h a week
Opportunity
Preference
B
B
T-value Exp(B)
0.534
2.64 1.705
0.735
1.98 0.479
2
w (d.f.), significant value Percentage correct predicted Missing values
T-value
0.406
Exp(B)
0.123
B
T-value Exp(B)
2.37 1.502
0.052 1.83 0.949
2.64 1.131
0.089 2.24 0.915
0.147 2.82 0.864 1.354
0.464 0.266 0.208 0.365 0.827 0.247
2.11 1.31 2.25 2.08
0.629 0.766 1.231 1.440
2.80 2.287 1.19 1.280
Cluster 3: household characteristics Number of children in the household [0–5] Age of youngest child [reference >12 years] No child Youngest child <4 years Youngest child 4–12 years Spouse [0, 1] Cluster 4: individual characteristics Male [0, 1] Age group [reference 45 years] <30 years 30–44 years (partly) Disabled for work [0, 1] Commuting time one way [reference 1 h] 0–30 min 30–60 min Attitude: telecommuting saves travel time [0, 1] Attitude: telecommuting facilitates work and family [0, 1] Attitude: telecomm, reduces commuting and parking expenses [0, 1] Attitude: telecommuting enables a quiet work environment [0, 1] Attitude: telecommuting enables flexible scheduling of the day [0, 1] Constant
Practice
0.297
3.80 1.346
3.21 3.874
1.330 5.67 0.264 0.475 2.41 0.622 0.295 3.13 1.343
0.752 2.49 0.471 0.149 0.80 0.862 0.265 1.98 0.767 0.423 1.36 0.655 0.528 1.89 1.696 0.184 0.69 1.202
0.942 3.51 0.390 0.171 0.90 0.843
0.802 0.256
2.97 0.449 0.89 0.774
0.515 0.430
2.98 0.598 2.01 1.538
1.027
1.75 0.358
63.25 75.8 2
12
0.000
1.117 3.72 0.327 0.683 2.14 0.505
1.081 5.84 2.948 1.093 4.60 2.983 1.690 2.93 0.184 145.04 76.3 2
14
0.000
1.023 3.71 0.359 0.597 2.02 0.551 0.773 3.00 0.462
0.561
2.49 1.752
0.750
1.34 2.118
118.79 76.2 2
12
0.000
Source: Work & ICT 2001 survey. Note: All dichotomous variables are coded 0: no and 1: yes. Note: The empty fields indicate that the variable is deleted from the analysis because it did not have a significant influence on the dependent variable under study.
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often (34%). As expected, employees in a supervisory position were more likely to be given the opportunity to telecommute, but no effect was found for telecommuting preferences and practices. Our findings with respect to working hours are puzzling. Compared with full-time working employees, employees working less than 20 h a week were far less likely to prefer telecommuting. This is in accordance with face-value expectations. However, compared with full-time employees, employees with less than 20 working hours were more likely to be given the opportunity to telecommute. Maybe part-time jobs were less integrated in regular work processes and could therefore be performed more easily in isolation. Finally, working hours did not affect telecommuting practices. For household characteristics, none of the variables influenced telecommuting opportunities and telecommuting practices: they did affect telecommuting preferences. The more children in the household, the less likely an employee preferred to telecommute. Although it has been argued that telecommuting facilitates work and family life, it is understandable that this is not the case with many children in the house. Although not significant, employees with a child under the age of four prefer to telecommute more often than employees with a child over 12 years of age. Finally, the presence of a spouse did not influence any of the telecommuting modes. We unexpectedly did not find any gender impact. Age group had no impact on the opportunity or preferences, but it did affect practices of telecommuting. In contrast to expectations, employees up to the age of 30 were less likely to practice telecommuting than employees aged 45 and over. Also unexpectedly, partly disabled employees were not given the opportunity to telecommute more often, they did not prefer to do so, and they did not practice telecommuting more often. The impact of commuting time on telecommuting adoption was large, as expected. Compared with employees whose one way commuting time is less than half an hour, employees who commuted more than 1 h were 50% more likely to be given an opportunity to telecommute, they were nearly 70% more likely to prefer telecommuting and they were 65% more likely to practice it. Strikingly, employees who practiced telecommuting disagreed that telecommuting saved travel time, but this attitude did not affect telecommuting opportunities or preferences.
The statement ‘telecommuting facilitates the combination of work and family life’ was not significantly supported more often by employees given the opportunity, preferring, or practicing telecommuting. Employees preferring and practicing telecommuting did not perceive the reduction of commuting and parking expenses as a benefit more often than other employees. Strikingly, employees who were given the opportunity to telecommute disagreed on the statement that telecommuting saved commuting and parking expenses more often. The statement ‘telecommuting facilitates a quiet work environment’ was supported more often by employees who were given the opportunity to telecommute, by employees who had a preference for telecommuting and by employees who practiced telecommuting. This item obviously revealed a major drive for telecommuting. Particularly employees with preferences for telecommuting agree with the statement. Employees who practiced telecommuting were 70% more likely to agree. In total, five statements were asked, the final one being ‘telecommuting enables a flexible scheduling of the day.’ Employees that were given the opportunity and employees that practiced telecommuting did not support this statement more often than others. Yet, employees with a preference for telecommuting supported this statement far more often than employees who did not.
5. Discussion and conclusion The data for this study comes from a representative sample of the Dutch labor force, the final selection was of 849 employees who use a personal computer at work. This data was gathered through a computer-designed questionnaire. The study revealed that 55% of employees working with a computer prefer telecommuting, 24% were given the opportunity, and 25% practiced it. These categories did not fully overlap. Hence, opportunity does not necessarily go together with preference and practice and vice versa. The study contributes in five ways to existing knowledge in this area. First, the adoption of telecommuting was considered to consist of three related issues, namely opportunity, preference and practice. Previous studies usually focused on only one aspect. Second, insights from literature detailing management telecommuting decisions and literature concerning
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employee telecommuting behavior were fruitfully combined, leading to four clearly distinguished explanatory clusters, notably organizational, job, household, and individual characteristics. Third, as information workers are central in the definition of teleworkers, the use of IT equipment and the frequency of IT use were taken as indicators for the three modes of telecommuting adoption. Fourth, most large-scale studies of the telecommuting adoption have only been investigated by using bivariate statistical analysis. This multivariate study aims to fill this gap. Fifth, a number of empirical studies of employees’ opportunities, preferences, or practices were based on self-selected respondents, for example when evaluating a telecommuting experiment. Our study, however, was based upon a large, representative sample of the labor force.
Acknowledgement The authors are grateful to the anonymous reviewers and the editor of Information & Management for their comments and editing. References [1] M.N. Bagley, P.L. Mokhtarian, Analyzing the preference for non-exclusive forms of telecommuting: modeling and policy implications, Transportation 24, 1997, pp. 203–226. [2] Y. Baruch, Teleworking: benefits and pitfalls as perceived by professionals and managers, New Technology Work and Employment 15 (1), 2000, pp. 34–48. [3] Y. Baruch, The autistic society, Information and Management 38 (3), 2001, pp. 129–136. [4] F. Be´ langer, Workers’ propensity to telecommute: an empirical study, Information and Management 35 (3), 1999, pp. 139–153. [5] G. Bosch, J. Webster, H-J. Weisbach, New organizational forms in the information society, in: K. Ducatel, J. Webster, W. Herrmann (Eds.), The Information Society in Europe, Rowman & Littlefield Publishers, Lanham, 2000. [6] K. Daniels, D.A. Lamond, P. Standen, Managing Telework. Perspectives from Human Resource Management and Work Psychology, Thomson Learning, London, 2000. [7] D.D. Davis, K.A. Polonko, Telework in the United States: Telework America Survey, ITAC, Washington DC, 2001 (http://www.telecommute.org/twa/twa2001/newsrelease.htm). [8] EcaTT, Benchmarking Progress on New Ways of Working and New Forms of Business across Europe. EcaTT Final Report August 2000, Empirica, Bonn, 2000 (http://www.empirica.com/ ecatt).
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[9] European Commission, Status Report on European Telework. New Methods of Work 1999, European Commission, Brussels, 1999. [10] European Commission, Benchmarking Report following-up the ‘‘Strategies for jobs in the Information Society’’, Commission of the European Communities, SEC(2001)222, Brussels, 2001. [11] B.J. Frederiks, D.O. Limburg, Teleworking for technical functions: how different are software developers from sales persons? in: Paper Presented at the 6th International ITF Workshop and Business Conference, Department of Technology and Management, University of Twente, Amsterdam, 26–30 August 2001. [12] K. Gareis, N. Kordey, The Spread of Telework in 2005, Empirica, Bonn, 2000. [13] C. Hales, A. Klidas, Empowerment in five-star hotels: choice, voice or rhetoric? International Journal of Contemporary Hospitality Management 10 (3), 1998, pp. 88–95. [14] A.A.K. Hamsa, M. Miura, Do Managers favor for Teleworking in Japan? Shibaura Institute of Technology, Tokyo, in: Paper Presented at the 6th International ITF Workshop and Business Conference, 26–30 August, 2001. [15] S.L. Handy, P. Mokhtarian, Planning for telecommuting. Measurement and policy issues, Journal of the American Planning Association 61 (1), 1995, pp. 97–111. [16] S.L. Handy, P.L. Mokhtarian, The future of telecommuting, Futures 28 (3), 1996, pp. 227–240. [17] V. Illegems, The economic and managerial analysis of telework adoption: drives, impediments and road externality impacts in the Brussels context, Ph.D. thesis, Faculty of Economic, Social and Political Sciences Solvay Business School University of Brussels, Brussels, 2001. [18] M. Kerrin, K. Hone, Job seekers’ perceptions of teleworking: a cognitive mapping approach, New Technology Work and Employment 16 (2), 2001, pp. 130–143. [19] M. Khalifa, J. Etezadi, Telecommuting: a study of employees’ beliefs, Journal of Computer Information Systems 38 (1), 1997, pp. 78–85. [20] J.S. Mannering, P.L. Mokhtarian, Modeling the choice of telecommuting frequency in California: an exploratory analysis, Technological Forecasting and Social Change 49, 1995, pp. 49–73. [21] P.L. Mokhtarian, Factors in the adoption of telecommuting, in: F. van Reisen, M. Tacken (Eds.), A Future of Telework. Towards a New Urban Planning Concept? Nederlandse Geografische studies, Utrecht/Delft, 1995, pp. 39–53. [22] P.L. Mokhtarian, M.N. Bagley, Modeling employees’ perceptions and proportional preferences of work locations: the regular workplace and telecommuting alternatives, Transportation Research Part A 34 (4), 2000, pp. 223–242. [23] P.L. Mokhtarian, I. Salomon, Modeling the desire to telecommute: the importance of attitudinal factors in behavioral models, Transportation Research Part A 31 (1), 1997, pp. 35–50. [24] J.M. Nilles, Managing Telework. Strategies for Managing the Virtual Workforce, Wiley, New York, 1998. [25] C.P. Peters, The vulnerable hours of leisure. New patterns of work and free time in The Netherlands 1975–1995, Thela Thesis, Amsterdam, 2000.
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[26] I. Salomon, Technological change and social forecasting: the case of telecommuting as a travel substitute, Transportation Research Part C 6 (1–2), 1998, pp. 17–45. [27] C. Stanworth, Telework in the information age, New Technology Work and Employment 13 (1), 1997, pp. 51–62. [28] T.S.H. Teo, V.K.G. Lim, S.H. Wai, An empirical study of attitudes towards teleworking among information technology (IT) personnel, International Journal of Information Management 18 (5), 1998, pp. 329–343. [29] K.G. Tijdens, M. Van Klaveren, C. Wetzels, Wie kan en wie wil telewerken? Een enqueˆ te in de ICT-sector [Who is able and willing to telework? A survey in the IT industry], Tijdschrift voor Arbeidsvraagstukken 17 (2), 2001, pp. 152–164. [30] M. Van Klaveren, A. Van de Westelaken, Thuiswerk— Telethuiswerk—Telewerk. Een verkenning van het werken thuis [Homework—Home-based telework—Telework. An exploration of working at home], FNV Bondgenoten, Utrecht, 2000. [31] V.C. Van Vuuren, W.G. van Arkel, A. van den Bosch, E. Schol, W. Bosveld, Telewerken in Amsterdam. Telewerkpotentieel en milieu-effecten [Teleworking in Amsterdam. Telework potential and environmental effects], ECN/OþS Amsterdams Bureau voor Onderzoek en Statistiek, Amsterdam, 1998. [32] M.M. Watad, F.J. DiSanzo, Case study the synergism of telecommuting and office automation, Sloan Manangement Review 41 (2), 2000, pp. 85–96. [33] C. Wetzels, K.G. Tijdens, A Digital Dutch Miracle in Households and Firms, TNO-STB, Delft, 2001. Pascale Peters is a postdoctoral researcher in the Department of Sociology, Utrecht University, The Netherlands. She received her PhD from Tilburg University, The Netherlands. She is currently involved in a comprehensive research program called Time Competition. Her research interests within this program include home-based telework and its relationships
with labor-market developments, organizational change, humanresource management, household developments, work-home balance, time allocation and time pressure. She has published in Leisure and Society, Time & Society and several Dutch sociological journals and in books on IT and work. Kea G. Tijdens is an associate professor at the Department of Economics and research coordinator at the Amsterdam Institute of Labor Studies, both at the University of Amsterdam in The Netherlands. She received her PhD from Wageningen University, The Netherlands. She has published in journals such as: Economic and Industrial Democracy, Acta Sociologica, Journal of Family Issues, Feminist Economics, as well as numerous IFIP conference proceedings, books and research reports. Her research interests include IT-use at the workplace, telework, women’s wages, women’s re-entry in the labor market, working hours, timing of work. Cecile Wetzels is a senior researcher at the Institute of Applied Scientific Research, with the group on strategy, technology and policy, Delft, The Netherlands. She received her PhD from the University of Amsterdam. Her research interests include gender, information and communication technology, labour force participation, wages and fertility. She has published in the European Journal of Population Economics, Journal of Public Finance and Management and contributed to books published by Macmillan, Edward Elgar and Policy Press. Furthermore, her book ‘‘Squeezing birth into working life, household panel data analyses on four European countries’’, has been published by Ashgate.
Employees’ opportunities, preferences, and practices in telecommuting adoption Pascale Petersa,1, Kea G. Tijdensb,*, Ce´cile Wetzelsc,2 a
b
Department of Sociology, University of Utrecht, Utrecht, The Netherlands Amsterdam Institute for Labour Studies (AIAS), University of Amsterdam, Amsterdam, The Netherlands c Delft TNO Institute of Strategy, Technology and Policy, Delft, The Netherlands Received 3 January 2002; received in revised form 7 February 2003; accepted 26 June 2003
Abstract This study uses three separate models for the opportunity, preference, and practice of telecommuting to analyze employee telecommuting adoption. Explanatory clusters relate to organizational, job, household, and individual characteristics derived from the combined insights from literature on telework management and employees’ telecommuting decisions and behavior. Data was collected from 849 employees using a personal computer at the workplace, selected from a representative sample of the Dutch labor force. Multivariate analyses were applied. Opportunity largely depended on organizational and job characteristics. Preference was dependent on all explanatory clusters. Practice was especially dependent on job and individual characteristics. # 2003 Elsevier B.V. All rights reserved. Keywords: Organizational factors; Job characteristics; Household factors; Individual factors; Multivariate analyses; Cross-section data; Telework
1. Introduction Many articles and books on telecommuting, the substitution of working at home or at an office close to home instead of commuting to the usual work site, start out listing the advantages of this new work concept. Organizations may view telecommuting as a solution to problems of housing their expanding staff, a means to reduce overheads, or as a way to cut absenteeism. Moreover, it is assumed to lead to higher *
Corresponding author. Tel. þ31-20-525-4347; fax: þ31-20-525-4254. E-mail addresses: [email protected], [email protected] (P. Peters), [email protected], [email protected] (K.G. Tijdens), [email protected] (C. Wetzels). 1 Tel.: þ31-30-253 4306; fax: þ31-30-253-4405. 2 Tel.: þ31-15-269 5439; fax: þ31-15-269 5460.
commitment and productivity, to improve customer service, enhance organizational flexibility, or—once introduced as an employee benefit—attract scarce personnel. In an attempt to expand their market shares, telecom companies try to convince consumers of the benefits of telecommuting. National governments in the European Union advocate telecommuting both as a means to reduce traffic congestion and increase women’s labor force participation. Yet, there is reluctance to adopting telecommuting. Employer organizations stress the need for a careful look into the costs of this new work form, including tax implications and benefits, as well as data security. Labor unions are concerned about the working conditions in telecommuting, such as the provision of furniture, reimbursement of wages, workplace design, the monitoring of productivity, and career prospects. Telecommuting
0378-7206/$ – see front matter # 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0378-7206(03)00085-5
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was recently criticized as a process by which contemporary society becomes more autistic and that only a balanced mix of telecommuting and work in the office could prevent this from occurring [3]. Many employees, however, show a preference for it. In order to facilitate the uptake of telework in Europe, the European Commission consulted the social partners, the employers’ and workers’ representatives, at the European level. In July 2002, these representatives signed an agreement on teleworking to enhance business flexibility and modernize work organization, while ensuring better protection and higher job quality for teleworkers. Thus, actors in the field are multiple, their interests diverse, and their expectations high. The past decade has shown a gradual introduction of telecommuting. In the US, on the basis of a household study it was shown that one in five employees currently participate in some type of teleworking [7]. In the European Union, these percentages were lower. According to a 1999 representative survey of 7700 individuals aged 15 and older in 10 European Union member states, 6% of the labor force did some telework. Two-thirds of this group spent at least one full working day a week at home or in the field, having access to their employer or client/principal via datacommunication [12]. In 2000, a Eurobarometer survey came up with a similar percentage [10]. However, employee interest in telecommuting is much higher than employer interest. Thus, a model of employers’ telecommuting adoption may underestimate the employees’ telecommuting practices. A further increase of telecommuting can be expected. Any forecasts of the spread of telecommuting require an analysis of the factors that influence telecommuting adoption, both by employers and employees. Why do employers give their employees the opportunity to work from home? Does it depend on the nature of the job, the state of technology, or the willingness of establishments to change their management practices? These factors are characterized as supply-side issues [16]. At least equally important are the demand-side issues. Why do employees, given the opportunity to telecommute, prefer to do so and why? Does the employee’s preference and actual telecommuting practice depend on household or individual characteristics? Therefore, employees’ and employers’ adoption of telecommuting must be studied as complements, for the two actors may have
different agendas and assign different weights to the factors considered in the choice process [26]. The relationship between employees’ and employers’ decisions may in fact require employer–employee-related data. To overcome this complex research design, the most common solution is to question employees about management support. Our study aims to gain a better understanding of the factors influencing the telecommuting adoption, and combines both supply-side and demand-side factors. Using a large-scale questionnaire of employees, employer-side issues were measured through the employee. Based on a review of the literature we modeled four explanatory clusters, related to the employee’s organization, job, household, and personal characteristics, that may affect employees’ telecommuting adoption. The adoption of telecommuting was assumed to consist of three related issues: the telecommuting opportunity, preference, and practice.
2. Telecommuting adoption: a review of the literature Employee adoption of telecommuting has been investigated in a number of studies in the US and Europe. The methodologies varied from interviews with teleworkers to large-scale questionnaires of employees. The predicting variables mostly included socio-demographic characteristics and attitudinal measures. The dependent variables ranged from the perceived benefits to the location for telecommuting work. Patricia Mokhtarian took the initiative in modeling employees’ telecommuting adoption (e.g. [20,22]). 2.1. The impact of organizational characteristics Management literature stresses the benefits of telecommuting. The development of telecommuting is believed to be strongly related to changes in organizational structures, in coordination systems and, in task specifications within organizations. These changes include downsizing, delayering, business process reengineering, project-based structures, the shift to a core/periphery model, and a growth in inter-organizational networks [6]. The changes are associated with new styles of control, with close supervision being replaced by mechanisms of internal motivation.
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The emergence of a new type of employee with a wider span of control and accountability facilitates control by positive reinforcement. Traditional concurrent control has to be replaced by new forms, such as ex ante control by selection and education, ex post control by output and outcome management, and meta control through the creation of a specific work culture implicitly motivating and committing employees to their job, coworkers and organization [13]. As companies become more used to a dispersed and relatively autonomous workforce, they may be more comfortable with telecommuting. However, little empirical evidence has been found to underpin these organizational conditions. The empirical evidence available from employee surveys does not refer to organizational characteristics other than company size. A study based on telephone interviews with 1170 households, a representative sample of all US households, revealed that telecommuting was most often found among people working in either a very small or a very large company. In contrast to the management literature, organizations seem to be reluctant to adopt telecommuting. In a survey of establishments in EU member states, 76% of the companies neither practiced telework, nor were interested in it [8]. Among the barriers, data security problems ranked first and problems concerning productivity and work quality ranked second. A survey of 66 managers of market services businesses in the Tokyo area found nearly 70% against telecommuting, the major arguments relating to additional responsibility for managers, decreased interaction between employer and employee, the high costs involved in IT, security concerns over official documents, and erosion of the traditional work style [14]. The perceived barriers may lead to informal teleworking, as is shown in a study of 1201 Amsterdam citizens, who were asked to classify their job as ‘teleworkable’, i.e. being suitable for telecommuting; the employers were also asked about telecommuting. While the employers had not yet developed a telework policy, the employees had already realized their preferences, and, once confronted with the research on their employees’ behavior, the employers were very surprised [31]. One Dutch case study showed that organizations benefit from telecommuting because they save in office space by creating flexi workplaces, particularly when they plan to build new premises [11]. A case study of a marketing company in the US, introducing
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telecommuting for its salespeople as part of a program to reduce paper-based procedures and transform voice communication into automated procedures and fullscale connectivity, provided an example of an organization trying to better position its strategic goals [32]. A few case studies have shown that employers opt for telecommuting as an employee benefit [17]. Employee interest in telecommuting in Europe is high. Throughout the European Union, an average of 60% of employees show an interest in it. The interest among those looking for work is even stronger. Employers giving their employees the opportunity to telecommute may be regarded as attractive. A study of 285 employees of an IT company in Singapore confirmed that employees would be less likely to end the employment relationship if the company offered telecommuting as an option [28]. Similarly, a study of 300 employees in Canadian companies found that both managers and employees expected that the employees were more likely to stay at the company when they were given the opportunity to telework [19]. Experimental research with students reaffirmed the claim that the concept of telecommuting will attract well-qualified individuals to join the organization [18]. Thus, particularly in a tight labor market, organizations may develop telecommuting policies as an employee benefit, because (potential) employees perceive the opportunity as attractive. 2.2. The impact of job characteristics The discrepancy between employers’ and employees’ interests in telecommuting finds its focal point in the notion of ‘‘job teleworkability’’, i.e. is the job suited for telecommuting? By nature, jobs that demand a physical presence are not appropriate, whereas the knowledge or information workers’ jobs are typically suited for telecommuting. This leaves room for a large range of jobs where the suitability for telecommuting is not clear and therefore may be subject to different interpretations by employers and employees. This must lead to discrepancies between telecommuting opportunities and preferences. Two thirds of employees in European Union member states carry out activities suitable for telework at least 1 day a week. In contrast, only one third of the companies practice telework, and the number of teleworkers per establishment is rather low. A study of 314 employers
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in five industries in The Netherlands revealed that their major argument against telecommuting related to job suitability, leading to a much higher percentage of employees not having the opportunity that would have been expected from employee surveys [33]. In comparing the telecommuting opportunity and telecommuting preferences, a self-administered questionnaire of employees in the Dutch IT industry showed that differences between occupational categories and sectors within the industry were significant, pointing to different definitions of job teleworkabily used by employers and employees [29]. Not surprisingly, attempts have been undertaken to come up with lists of occupational categories that are suitable for telecommuting [5]. In a study of 628 employees of the City of San Diego, teleworkability was measured by a factor constructed on the basis of variables indicating self-defined suitability, location independency, task independency, task scheduling autonomy, and supervisory position, i.e. having a managerial job [1,23]. In other attempts to overcome measurement problems, a proxy for job suitability was used, for example job autonomy. Employees with less autonomy are assumed to be less likely to be given a telework opportunity. Other studies assumed a job to be particularly appropriate for telecommuting in the case of a relatively high number of so-called ‘longduration’ tasks, or where such tasks can be grouped into 1 or 2 days a week [24]. Some studies have used a straightforward indicator, such as education. In line with expectations, well-educated individuals are more likely to express a preference for telecommuting from home. In the EU member states survey, teleworkers were mostly highly qualified in comparison with nonteleworkers. Strikingly, the use of IT equipment on the job, or the frequency of IT use, was hardly used as an indicator, although information workers’ jobs are said to be typically suited for telecommuting. Only a few studies relate telecommuting to the dependence on IT, or to jobs that were created by information and communication technology [27]. According to the Eurobarometer survey 2000, telework was most widespread among managers, who used it frequently in addition to computer use in their office. Some attention has been paid to another important argument for telecommuting adoption, notably that it reduces the frequency of distractions in a hectic workplace. In the study of Amsterdam citizens, this argu-
ment ranked first both among the citizens currently telecommuting and those desiring to do so. Apparently, the office workplace offers insufficient opportunity for working in a concentrated way. Office workplaces are too busy for writing reports, working out drafts, or other activities that require concentration. Telecommuting offers the opportunity for a quiet workplace. This is in line with a study of 62 telecommuting professionals and managers in the UK, where the major advantage was better performance conducted under telecommuting conditions, both in quantity and quality of work [2]. This finding was also supported in a US study of 71 employees of a large high technology organization, slightly over half of them being teleworkers [4]. Telecommuting employees reported significantly greater productivity. In the US study on households, almost three-quarters of home-based teleworkers reported a major increase in productivity and work quality. Similar results were reported in the Eurobarometer survey 2000, where teleworkers overwhelmingly indicate that this form of work enhanced their productivity. This finding may be related to workaholism. In the San Diego study, workaholism was shown to be the second highest contributor to the preference of telecommuting, particularly from a telecenter. This variable and a second one, i.e. ‘‘stress’’, captured the importance of being able to work productively and comfortably when telecommuting. The opposite probably is expressed in the variable ‘‘workplace interaction’’, indicating a person’s need for the social and professional interaction obtained at the regular workplace. This variable was positively correlated with the preference not to telecommute. In conclusion, interpretations of job suitability may vary across employers and employees. Yet, when education or job level was used as an indicator, the well-educated and managerial employees were found to be more likely to practice telecommuting. 2.3. The impact of household characteristics Employed parents may value the timesaving effects of telecommuting. A Dutch study revealed that the number of households that experienced a ‘‘time squeeze’’ had increased. Both men’s and women’s time spent in the workplace and time spent with children had increased. As a consequence, free time had become more vulnerable [25]. Working parents
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may highly value the time-savings of telecommuting due to the elimination of commuting time or because telecommuting may allow a parent to stay at home with a sick child. In their national policies, EU member states stressed the benefits of telecommuting with respect to reconciliation work and family life, because telecommuting was assumed to increase the flexibility in working hours. Indeed, according to the Amsterdam study, time flexibility ranked third in telecommuting preferences. Yet, little empirical evidence confirmed whether time flexibility was a synonym for improved reconciliation of work and family life. The UK study of telecommuting professionals even concluded that work–home interference may be a hindrance to further growth in telecommuting, and that the availability of extra workspace at home emerged as a key factor of success of telecommuting programs. This was in line with findings in the San Diego study, where household interaction, defined as a concern when performing home-based telework, increased the likelihood of preferring to work from the regular office. The US survey of households reported that both teleworkers and non-teleworkers who work at home after normal work hours experienced a work–family role conflict, but that the type of conflict was different. Teleworkers reported less interference between work and family roles, leading researchers to conclude that teleworkers may be better able to manage some key aspects of the work–family conflict. In the Eurobarometer survey 2000, similar results were reported. Twice as many teleworkers as non-teleworkers regarded combining work and private life as an advantage. Thus, although telecommuting may reduce the work–family conflict, it was not clear whether this could be related to the presence of children in the home, or that it applied equally to households with and without children. The EU member states survey showed only slight differences in household composition between teleworkers and non-teleworkers. In the US, teleworkers and non-teleworkers were equally distributed across marital status. 2.4. The impact of individual characteristics Socio-demographic variables, such as age and gender, are found to influence telecommuting adoption, particularly the preference for it. The San Diego study shows that as age increases the likelihood that an
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individual preferred to telecommute decreases. The US study of a high technology organization, however, does not reveal significant age differences between those practicing telework and those not doing so. The US study of households confirmed this. Bivariate analyses of the EU member states survey data, however, indicated that the age group 30–49 was overrepresented among teleworkers. The same study showed that three out of four teleworkers were male, and that this stands in sharp contrast to the widespread opinion that telework was predominantly female. The US study of households also confirmed that men were telecommuting more often. At first sight, commuting time is the most important factor in telecommuting. This is fully in line with local or national policies to reduce traffic congestion by promoting telecommuting. Transportation researchers particularly have great interests in the topic. In many studies, commuting time was indeed found to have a large positive effect on telecommuting adoption. The EU member states survey indicated that every 6th teleworker against every 27th non-teleworker has a commuting distance of more than 50 km. In the Amsterdam study, reduction of commuting time was the most important argument among the 20% currently telecommuting and 26% desiring to do so. In a study of IT employees in Singapore, avoiding the hassle of commuting ranks first, and reducing commuting time ranks second in its perceived advantages. It is the reduced commuting time and not the reduced commuting costs that makes telecommuting attractive. The reduced commuting time may partly be devoted to additional working hours. The UK study of telecommuting professionals revealed that for nearly half of this group the time spent on work had increased after moving to telecommuting. The EU member states survey indicated that 80% of teleworkers work more hours than contractually agreed, compared with 50% non-teleworkers. Compared to non-teleworkers, teleworkers more often had positive attitudes with regard to the benefits of telecommuting. Moreover, attitudes may influence both preferences and practices, but the relationship is not straightforward. Not all employees in an organization that gives its employees the opportunity to telecommute choose to do so. In the same vein, not every worker who prefers to telecommute has the opportunity to do so. In fact, the relationship between being given the opportunity, preferring and actually practicing
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telecommuting may be a dynamic one. Perceived restrictions, resources and opportunities both affect intended and overt behavior [15,21]. Restrictions may influence an individual’s telecommuting preference and practice. Given the individual’s environment and the long or short-term constraints faced, the individual worker makes a choice. We assumed that positive attitudes separately affect preferences and practices. Compared with non-teleworkers, teleworkers more often have positive attitudes with regard to the benefits of telecommuting.
3. Model, assumptions and data 3.1. Definition of telework Several attempts have been undertaken to identify telework [9]. Most cases use criteria such as the legal status of the teleworker, the work location, the distinction between regular and occasional telework, and the use of IT as a precondition to exclude the ‘traditional’ home workers or the home-based self-employed not using the new technologies. Based on these criteria, four groups of teleworkers can be distinguished, homebased teleworkers, mobile or multi-site teleworkers, freelancers and self-employed teleworkers, and supplementary or marginal teleworkers [30]. The focus in our study is on home-based teleworkers; i.e. employees who have the opportunity, who prefer or who practice remote information work for one employer at least 1 day a week. 3.2. Modeling employees’ telecommuting opportunities, preferences, and practices Here, the employees’ telecommuting adoption was considered to consist of three related issues: opportunity, preference, and practice. The study sought to answer the questions: Which employees are given the opportunity to telecommute? Which employees prefer to telecommute? Which employees practice telecommuting? Four clusters of explanatory variables were expected to affect telecommuting adoption. These clusters were related to the employee’s organization, job, household, and individual characteristics. On the basis of the literature review, some variables were expected to affect telecommuting opportunities in
particular. Furthermore, some would influence telecommuting preferences, and others would influence telecommuting practices. As regards the impact of organizational characteristics, the following hypotheses were tested empirically: 1. The more business localities within an organization, the more likely it is that employees are given an opportunity to telecommute. Business localities will influence the telecommuting preferences and practice to a minor extent. 2. The larger the size of the business, the more likely it is that employees are given an opportunity to telecommute. The size of the business will influence the telecommuting preferences and practice to a minor extent. 3. The flatter the organizational hierarchy, the more likely it is that employees are given an opportunity to telecommute. The organizational hierarchy will influence the telecommuting preferences and practice to a minor extent. 4. Employees who have no direct supervisor will be more likely employees are given an opportunity to telecommute. The absence of a supervisor will influence the telecommuting preferences and practice to a minor extent. 5. The lower the percentage of women in the unit, the more likely it is that employees are given an opportunity to telecommute. The percentage of women will influence the telecommuting preferences and practice to a minor extent. 6. The better the collegial atmosphere, the more likely it is that employees are given an opportunity to telecommute. A collegial atmosphere will influence the telecommuting preferences and practice to a minor extent. 7. The more colleagues in the department using a computer, the more likely it is that employees are given an opportunity to telecommute. Colleagues using a computer will influence the telecommuting preferences and practice to a minor extent. As regards the impact of job characteristics, the following hypotheses were tested empirically: 8. Frequent computer users will be more likely to practice telecommuting. Computer use will influence the telecommuting opportunity and preferences to a minor extent.
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9. Employees with good career opportunities will be more likely to practice telecommuting. Career opportunities will influence the telecommuting opportunity and preferences to a minor extent. 10. Employees who have attended Internet courses will be more likely to practice telecommuting. The attendance of Internet courses will influence the telecommuting opportunity and preferences to a minor extent. 11. Higher educated employees will be more likely to practice telecommuting. Education will influence the telecommuting opportunity and preferences to a minor extent. 12. Employees with high levels of IT skills will be more likely to practice telecommuting. IT skills
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will influence the telecommuting opportunity and preferences to a minor extent. 13. Employees in a supervisory position will be more likely to practice telecommuting. A supervisory position will influence the telecommuting opportunity and preferences to a minor extent. 14. Employees with long working hours will be more likely to practice telecommuting. Working hours will influence the telecommuting opportunity and preferences to a minor extent. As regards the impact of household characteristics, the following hypotheses were tested empirically: 15. The more children an employee has, the more likely it is that employees have a preference for telecommuting. The number of children will
Fig. 1. Research model to predict three modes of telecommuting from four clusters of explanatory variables.
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influence the telecommuting opportunity and practices to a minor extent. 16. Employees with young children in the household will be much more likely to prefer telecommuting. The presence of young children will influence the telecommuting opportunity and practices to a minor extent. 17. Employees with a partner will be more likely to prefer telecommuting. A partner will influence the telecommuting opportunity and practices to a minor extent. As regards the impact of individual characteristics, the following hypotheses were tested empirically: 18. Male employees will be more likely to prefer telecommuting. Gender will influence the telecommuting opportunity and practices to a minor extent. 19. Young employees will be much more likely to prefer telecommuting. Age will influence the telecommuting opportunity and practices to a minor extent. 20. Fully or partly disabled employees will be much more likely to prefer telecommuting. Disability will influence the telecommuting opportunity and practices to a minor extent. 21. Employees with long commuting times will be much more likely to prefer telecommuting. Commuting time will influence the telecommuting opportunity and practices to a minor extent.
16–64 in paid work were selected. The questionnaire consisted of 74 questions, of which seven directly addressed telework, five addressed IT use at work, five addressed locations of work and commuting, 13 addressed characteristics of the workplace, and the remaining questions addressed individual and household characteristics. As regards telecommuting adoption, the following questions were posed: ‘Does your employer give you the opportunity to telecommute’, ‘Do you prefer to telecommute’, and ‘Do you currently practice telecommuting’ all applied to the situation in which the employee worked at home for at least 1 day a week. The self-reported teleworker status may represent a variable mixture of time spent at the regular workplace and at home during the course of a given week. In total, 1335 working men and women responded. Since the hypotheses focused on employees in an organizational setting, the self-employed and freelancers, and the respondents reporting to be working alone were deleted from the analyses. Since telecommuting by definition was only possible when working with a personal computer or laptop, only employees using this equipment were selected (82% of the employees not working alone). After excluding outliers and missing data for the relevant variables, the data set included 849 observations. The independent variables were controlled for multicollineairity, i.e. correlations that are too high.
3.3. Sample and data
4. Opportunities, preferences, and practices
The data used for our analyses came from the Work & IT 2001 survey. This computer-designed questionnaire was part of the computerized telepanel, which is a representative sample of the Dutch population. For the Work & IT 2001 survey, only respondents aged
Table 1 shows that out of the 849 respondents, 202 (24%) were given the opportunity to telecommute, 466 (55%) preferred to telecommute and 213 (25%) were actually practicing telecommuting. Notice that this percentage is much higher than the 4% estimated in
Table 1 Number and percentages of the respondents by three telecommuting modes (employed persons using a personal computer at work only) Opportunity Preference Practice No practice Total
No opportunity
Total
No preference
Preference
No preference
66 (8%) 50 (6%)
18 (2%) 68 (8%)
83 (10%) 267 (31%)
46 (5%) 251 (30%)
213 (25%) 636 (75%)
116 (14%)
86 (10%)
350 (41%)
297 (35%)
849 (100%)
Source: Work & IT 2001 survey.
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the EU member states survey for The Netherlands, probably because of our selection of employees using a personal computer at work. The majority of the employees that were given the opportunity to telecommute, were not telecommuting, mostly because they preferred not to do so. A small group was given the opportunity to telecommute, did not prefer to, but was telecommuting anyway. The vast majority of nontelecommuting employees were not given an opportunity to telecommute, but half would prefer to do so. Almost one in five non-teleworkers was given the opportunity, but the majority of them preferred not to do so. There was also a small group who were given the opportunity to telecommute, preferred to do so, yet were currently not telecommuting. Table 1 reveals that more than half of the employees who preferred telecommuting are not able to realize their preferences because they are not given the opportunity to do so. A small, puzzling group was not given the opportunity and did not prefer to telecommute, but for whatever reason this group of employees did telecommute. In exploring the differences between employees given the opportunity, preferences, and practices of telecommuting, Table 2 presents the mean scores for the three groups with regard to the four explanatory clusters in the model for organizational, job, household, and individual characteristics. A first look at the relationships reveals that working hours and commuting time are higher for those practicing telecommuting than for those given the opportunity. Organizational characteristics seem to be important, particularly factors such as: more than one business locality and more hierarchical levels. With regard to job characteristics, employees given the opportunity to telecommute were, on average, more highly educated than those practicing telecommuting and these employees were more highly educated than those preferring to do so. Levels of IT skills hardly vary between the three groups of employees. Strikingly, telework practitioners have the lowest frequency in computer use than those with both employees with preferences for telecommuting and employees given the opportunity. With regard to household characteristics, the three groups do not seem to differ much. With regard to individual characteristics, employees practicing telecommuting were slightly older than those in the other two groups. In exploring which employees were given an opportunity to telecommute, preferred to telecommute and
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practiced telecommuting multivariate analyses are needed. In the first step, all variables of the four explanatory clusters were entered into a logistic regression analysis. In a second step, the non-significant variables were deleted one by one. This was performed for the three telecommuting modes separately. The results of the final model estimations are shown in Table 3. Management literature often suggests that telecommuting is an expression of modern management and, therefore, related to major organizational characteristics. Our analyses showed that some organizational characteristics did affect telecommuting opportunities, preferences, and practices. As expected, the results showed that employees in organizations with more than one business locality were more likely both to be given the opportunity and to prefer telecommuting. These effects were rather large. Compared with employees whose organization had only one locality, employees in organizations with more than one business locality were 70% more likely to be given the opportunity to telecommute and 50% more likely to prefer it. Strikingly, the number of business localities had no impact on telecommuting practices. The size of the organization had no impact on the opportunity, the preference, or the practice of telecommuting. As expected, organizational hierarchy did have an impact. The flatter the organization, the more likely an employee preferred and practiced telecommuting, although the effect was not large. Organizational hierarchy had no influence on the opportunity. As expected, having a supervisor at the workplace negatively affected the opportunity to telecommute, although it did not affect the employee’s preference and practice. Finally, neither the collegial atmosphere nor working in a computerized departmental setting affected any of the three modes of telecommuting (Fig. 1). Table 3 reveals that frequent daily computer use positively affected the preference for telecommuting. An extra 2 h of computer use a day increased the preference for telecommuting by 13%. Strikingly, however, frequent computer users were less likely to practice telecommuting. Every two additional hours of computer use a day decreased the likelihood of practicing telecommuting by 14%. Thus, frequent computer users may have a greater desire to telecommute, but they are less likely to do so. When it comes
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Table 2 Mean scores for employees being given the opportunity, preferring and practicing telecommuting (employed persons using a personal computer at work) Given opportunity to telecommute
Prefer telecommuting
Practice telecommuting
202 1.00 0.57 0.42
466 0.25 1.00 0.32
213 0.39 0.70 1.00
Cluster 1: organizational characteristics More than one business locality [0, 1] Size of the organization [1: <100 employees; 3: >500 employees] Organizational hierarchy [1–20 levels] Supervisor present [0, 1] Proportion of women in the department [range 0–1] Collegial atmosphere [1: bad; 3; good] Majority of colleagues use a personal computer [0, 1]
0.79 1.81 4.60 0.93 0.40 1.79 0.82
0.75 1.82 4.43 0.96 0.44 1.75 0.78
0.73 1.76 4.08 0.95 0.44 1.81 0.81
Cluster 2: job characteristics Frequency of computer use [1: never; 7: all day] Career opportunities [0: none; 7: many] Internet course [0, 1] Level of education [1: low; 3: high] Level of IT skills [1: low: 4: high] Supervisory position [0, 1] Working hours [1: <20 h; 3: >34 h]
4.33 4.75 0.05 2.08 3.24 0.46 2.54
4.41 4.63 0.04 1.93 3.22 0.40 2.67
3.95 4.65 0.07 2.22 3.23 0.42 2.64
Cluster 3: household characteristics Number of children in the household [0–5] Age youngest child [0: no child; 4: youngest >12 years] Spouse [0, 1]
1.00 1.06 0.80
0.94 0.99 0.78
0.96 1.01 0.77
Cluster 4: individual characteristics Male [0, 1] Age group [1: <30 years; 3: 45 years] (partly) Disabled for work [0, 1] Commuting time one way [1: <30 min; 3: 1 h] Attitude: telecommuting saves travel time [0, 1] Attitude: telecommuting facilitates work and family life [0, 1] Attitude: telecommuting reduces commuting and parking expenses [0, 1] Attitude: telecommuting enables a quiet work environment [0, 1] Attitude: telecommuting enables flexible scheduling of the day [0, 1]
0.64 2.13 0.04 1.61 0.85 0.70 0.53 0.82 0.83
0.63 2.14 0.03 1.55 0.89 0.77 0.61 0.86 0.91
0.67 2.26 0.02 1.62 0.85 0.69 0.56 0.85 0.90
N Opportunity for telecommuting [0, 1] Preferences for telecommuting [0, 1] Practicing telecommuting [0, 1]
Source: Work & ICT 2001 survey. Note: All dichotomous variables are coded 0: no and 1: yes.
to career opportunities, it is often suggested that telecommuting would reduce them. However, a t-test for differences in perceived career opportunities did not reveal any significant difference. In line with this finding, career opportunities do not influence any of the three modes of telecommuting. Employees having attended an Internet course are much more likely to practice telecommuting than employees who have not done so. However, attending an Internet course neither affects the opportunity nor the preference for tele-
commuting. As expected, Table 3 shows that compared with highly educated employees, the loweducated were less likely to be given the opportunity to practice telecommuting. Education, however, did not influence employees’ preferences. As expected, levels of IT skills did affect telecommuting. On a fourpoint scale of IT skills, employees with one extra level are 23% more likely to be given the opportunity to telecommute, they more often preferred telecommuting (35%), and they practiced telecommuting more
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Table 3 Coefficients, T-values and Exp(B) of the logistic regression analyses for the three telecommuting modes opportunity, preference and practice (employed persons using a personal computer at work, N ¼ 849)
Cluster 1: organizational characteristics More than one business locality [0, 1] Size of the organization [reference >500 employees] <100 employees 100–500 employees Organizational hierarchy [1–20 levels] Supervisor present [0, 1] Proportion of women in the department [range: 0–1] Collegial atmosphere [reference good] Atmosphere bad Atmosphere moderate Majority of colleagues use a personal computer [0, 1] Cluster 2: job characteristics Frequency of computer use [1: never; 7: all day] Career opportunities [0: none; 7: many] Internet course [0, 1] Level of education [reference high] Low education Middle education Level of IT skills [1: low; 4: high] Supervisory position [0, 1] Working hours [reference full-time] <20 h a week 20–34 h a week
Opportunity
Preference
B
B
T-value Exp(B)
0.534
2.64 1.705
0.735
1.98 0.479
2
w (d.f.), significant value Percentage correct predicted Missing values
T-value
0.406
Exp(B)
0.123
B
T-value Exp(B)
2.37 1.502
0.052 1.83 0.949
2.64 1.131
0.089 2.24 0.915
0.147 2.82 0.864 1.354
0.464 0.266 0.208 0.365 0.827 0.247
2.11 1.31 2.25 2.08
0.629 0.766 1.231 1.440
2.80 2.287 1.19 1.280
Cluster 3: household characteristics Number of children in the household [0–5] Age of youngest child [reference >12 years] No child Youngest child <4 years Youngest child 4–12 years Spouse [0, 1] Cluster 4: individual characteristics Male [0, 1] Age group [reference 45 years] <30 years 30–44 years (partly) Disabled for work [0, 1] Commuting time one way [reference 1 h] 0–30 min 30–60 min Attitude: telecommuting saves travel time [0, 1] Attitude: telecommuting facilitates work and family [0, 1] Attitude: telecomm, reduces commuting and parking expenses [0, 1] Attitude: telecommuting enables a quiet work environment [0, 1] Attitude: telecommuting enables flexible scheduling of the day [0, 1] Constant
Practice
0.297
3.80 1.346
3.21 3.874
1.330 5.67 0.264 0.475 2.41 0.622 0.295 3.13 1.343
0.752 2.49 0.471 0.149 0.80 0.862 0.265 1.98 0.767 0.423 1.36 0.655 0.528 1.89 1.696 0.184 0.69 1.202
0.942 3.51 0.390 0.171 0.90 0.843
0.802 0.256
2.97 0.449 0.89 0.774
0.515 0.430
2.98 0.598 2.01 1.538
1.027
1.75 0.358
63.25 75.8 2
12
0.000
1.117 3.72 0.327 0.683 2.14 0.505
1.081 5.84 2.948 1.093 4.60 2.983 1.690 2.93 0.184 145.04 76.3 2
14
0.000
1.023 3.71 0.359 0.597 2.02 0.551 0.773 3.00 0.462
0.561
2.49 1.752
0.750
1.34 2.118
118.79 76.2 2
12
0.000
Source: Work & ICT 2001 survey. Note: All dichotomous variables are coded 0: no and 1: yes. Note: The empty fields indicate that the variable is deleted from the analysis because it did not have a significant influence on the dependent variable under study.
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often (34%). As expected, employees in a supervisory position were more likely to be given the opportunity to telecommute, but no effect was found for telecommuting preferences and practices. Our findings with respect to working hours are puzzling. Compared with full-time working employees, employees working less than 20 h a week were far less likely to prefer telecommuting. This is in accordance with face-value expectations. However, compared with full-time employees, employees with less than 20 working hours were more likely to be given the opportunity to telecommute. Maybe part-time jobs were less integrated in regular work processes and could therefore be performed more easily in isolation. Finally, working hours did not affect telecommuting practices. For household characteristics, none of the variables influenced telecommuting opportunities and telecommuting practices: they did affect telecommuting preferences. The more children in the household, the less likely an employee preferred to telecommute. Although it has been argued that telecommuting facilitates work and family life, it is understandable that this is not the case with many children in the house. Although not significant, employees with a child under the age of four prefer to telecommute more often than employees with a child over 12 years of age. Finally, the presence of a spouse did not influence any of the telecommuting modes. We unexpectedly did not find any gender impact. Age group had no impact on the opportunity or preferences, but it did affect practices of telecommuting. In contrast to expectations, employees up to the age of 30 were less likely to practice telecommuting than employees aged 45 and over. Also unexpectedly, partly disabled employees were not given the opportunity to telecommute more often, they did not prefer to do so, and they did not practice telecommuting more often. The impact of commuting time on telecommuting adoption was large, as expected. Compared with employees whose one way commuting time is less than half an hour, employees who commuted more than 1 h were 50% more likely to be given an opportunity to telecommute, they were nearly 70% more likely to prefer telecommuting and they were 65% more likely to practice it. Strikingly, employees who practiced telecommuting disagreed that telecommuting saved travel time, but this attitude did not affect telecommuting opportunities or preferences.
The statement ‘telecommuting facilitates the combination of work and family life’ was not significantly supported more often by employees given the opportunity, preferring, or practicing telecommuting. Employees preferring and practicing telecommuting did not perceive the reduction of commuting and parking expenses as a benefit more often than other employees. Strikingly, employees who were given the opportunity to telecommute disagreed on the statement that telecommuting saved commuting and parking expenses more often. The statement ‘telecommuting facilitates a quiet work environment’ was supported more often by employees who were given the opportunity to telecommute, by employees who had a preference for telecommuting and by employees who practiced telecommuting. This item obviously revealed a major drive for telecommuting. Particularly employees with preferences for telecommuting agree with the statement. Employees who practiced telecommuting were 70% more likely to agree. In total, five statements were asked, the final one being ‘telecommuting enables a flexible scheduling of the day.’ Employees that were given the opportunity and employees that practiced telecommuting did not support this statement more often than others. Yet, employees with a preference for telecommuting supported this statement far more often than employees who did not.
5. Discussion and conclusion The data for this study comes from a representative sample of the Dutch labor force, the final selection was of 849 employees who use a personal computer at work. This data was gathered through a computer-designed questionnaire. The study revealed that 55% of employees working with a computer prefer telecommuting, 24% were given the opportunity, and 25% practiced it. These categories did not fully overlap. Hence, opportunity does not necessarily go together with preference and practice and vice versa. The study contributes in five ways to existing knowledge in this area. First, the adoption of telecommuting was considered to consist of three related issues, namely opportunity, preference and practice. Previous studies usually focused on only one aspect. Second, insights from literature detailing management telecommuting decisions and literature concerning
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employee telecommuting behavior were fruitfully combined, leading to four clearly distinguished explanatory clusters, notably organizational, job, household, and individual characteristics. Third, as information workers are central in the definition of teleworkers, the use of IT equipment and the frequency of IT use were taken as indicators for the three modes of telecommuting adoption. Fourth, most large-scale studies of the telecommuting adoption have only been investigated by using bivariate statistical analysis. This multivariate study aims to fill this gap. Fifth, a number of empirical studies of employees’ opportunities, preferences, or practices were based on self-selected respondents, for example when evaluating a telecommuting experiment. Our study, however, was based upon a large, representative sample of the labor force.
Acknowledgement The authors are grateful to the anonymous reviewers and the editor of Information & Management for their comments and editing. References [1] M.N. Bagley, P.L. Mokhtarian, Analyzing the preference for non-exclusive forms of telecommuting: modeling and policy implications, Transportation 24, 1997, pp. 203–226. [2] Y. Baruch, Teleworking: benefits and pitfalls as perceived by professionals and managers, New Technology Work and Employment 15 (1), 2000, pp. 34–48. [3] Y. Baruch, The autistic society, Information and Management 38 (3), 2001, pp. 129–136. [4] F. Be´ langer, Workers’ propensity to telecommute: an empirical study, Information and Management 35 (3), 1999, pp. 139–153. [5] G. Bosch, J. Webster, H-J. Weisbach, New organizational forms in the information society, in: K. Ducatel, J. Webster, W. Herrmann (Eds.), The Information Society in Europe, Rowman & Littlefield Publishers, Lanham, 2000. [6] K. Daniels, D.A. Lamond, P. Standen, Managing Telework. Perspectives from Human Resource Management and Work Psychology, Thomson Learning, London, 2000. [7] D.D. Davis, K.A. Polonko, Telework in the United States: Telework America Survey, ITAC, Washington DC, 2001 (http://www.telecommute.org/twa/twa2001/newsrelease.htm). [8] EcaTT, Benchmarking Progress on New Ways of Working and New Forms of Business across Europe. EcaTT Final Report August 2000, Empirica, Bonn, 2000 (http://www.empirica.com/ ecatt).
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[9] European Commission, Status Report on European Telework. New Methods of Work 1999, European Commission, Brussels, 1999. [10] European Commission, Benchmarking Report following-up the ‘‘Strategies for jobs in the Information Society’’, Commission of the European Communities, SEC(2001)222, Brussels, 2001. [11] B.J. Frederiks, D.O. Limburg, Teleworking for technical functions: how different are software developers from sales persons? in: Paper Presented at the 6th International ITF Workshop and Business Conference, Department of Technology and Management, University of Twente, Amsterdam, 26–30 August 2001. [12] K. Gareis, N. Kordey, The Spread of Telework in 2005, Empirica, Bonn, 2000. [13] C. Hales, A. Klidas, Empowerment in five-star hotels: choice, voice or rhetoric? International Journal of Contemporary Hospitality Management 10 (3), 1998, pp. 88–95. [14] A.A.K. Hamsa, M. Miura, Do Managers favor for Teleworking in Japan? Shibaura Institute of Technology, Tokyo, in: Paper Presented at the 6th International ITF Workshop and Business Conference, 26–30 August, 2001. [15] S.L. Handy, P. Mokhtarian, Planning for telecommuting. Measurement and policy issues, Journal of the American Planning Association 61 (1), 1995, pp. 97–111. [16] S.L. Handy, P.L. Mokhtarian, The future of telecommuting, Futures 28 (3), 1996, pp. 227–240. [17] V. Illegems, The economic and managerial analysis of telework adoption: drives, impediments and road externality impacts in the Brussels context, Ph.D. thesis, Faculty of Economic, Social and Political Sciences Solvay Business School University of Brussels, Brussels, 2001. [18] M. Kerrin, K. Hone, Job seekers’ perceptions of teleworking: a cognitive mapping approach, New Technology Work and Employment 16 (2), 2001, pp. 130–143. [19] M. Khalifa, J. Etezadi, Telecommuting: a study of employees’ beliefs, Journal of Computer Information Systems 38 (1), 1997, pp. 78–85. [20] J.S. Mannering, P.L. Mokhtarian, Modeling the choice of telecommuting frequency in California: an exploratory analysis, Technological Forecasting and Social Change 49, 1995, pp. 49–73. [21] P.L. Mokhtarian, Factors in the adoption of telecommuting, in: F. van Reisen, M. Tacken (Eds.), A Future of Telework. Towards a New Urban Planning Concept? Nederlandse Geografische studies, Utrecht/Delft, 1995, pp. 39–53. [22] P.L. Mokhtarian, M.N. Bagley, Modeling employees’ perceptions and proportional preferences of work locations: the regular workplace and telecommuting alternatives, Transportation Research Part A 34 (4), 2000, pp. 223–242. [23] P.L. Mokhtarian, I. Salomon, Modeling the desire to telecommute: the importance of attitudinal factors in behavioral models, Transportation Research Part A 31 (1), 1997, pp. 35–50. [24] J.M. Nilles, Managing Telework. Strategies for Managing the Virtual Workforce, Wiley, New York, 1998. [25] C.P. Peters, The vulnerable hours of leisure. New patterns of work and free time in The Netherlands 1975–1995, Thela Thesis, Amsterdam, 2000.
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P. Peters et al. / Information & Management 41 (2004) 469–482
[26] I. Salomon, Technological change and social forecasting: the case of telecommuting as a travel substitute, Transportation Research Part C 6 (1–2), 1998, pp. 17–45. [27] C. Stanworth, Telework in the information age, New Technology Work and Employment 13 (1), 1997, pp. 51–62. [28] T.S.H. Teo, V.K.G. Lim, S.H. Wai, An empirical study of attitudes towards teleworking among information technology (IT) personnel, International Journal of Information Management 18 (5), 1998, pp. 329–343. [29] K.G. Tijdens, M. Van Klaveren, C. Wetzels, Wie kan en wie wil telewerken? Een enqueˆ te in de ICT-sector [Who is able and willing to telework? A survey in the IT industry], Tijdschrift voor Arbeidsvraagstukken 17 (2), 2001, pp. 152–164. [30] M. Van Klaveren, A. Van de Westelaken, Thuiswerk— Telethuiswerk—Telewerk. Een verkenning van het werken thuis [Homework—Home-based telework—Telework. An exploration of working at home], FNV Bondgenoten, Utrecht, 2000. [31] V.C. Van Vuuren, W.G. van Arkel, A. van den Bosch, E. Schol, W. Bosveld, Telewerken in Amsterdam. Telewerkpotentieel en milieu-effecten [Teleworking in Amsterdam. Telework potential and environmental effects], ECN/OþS Amsterdams Bureau voor Onderzoek en Statistiek, Amsterdam, 1998. [32] M.M. Watad, F.J. DiSanzo, Case study the synergism of telecommuting and office automation, Sloan Manangement Review 41 (2), 2000, pp. 85–96. [33] C. Wetzels, K.G. Tijdens, A Digital Dutch Miracle in Households and Firms, TNO-STB, Delft, 2001. Pascale Peters is a postdoctoral researcher in the Department of Sociology, Utrecht University, The Netherlands. She received her PhD from Tilburg University, The Netherlands. She is currently involved in a comprehensive research program called Time Competition. Her research interests within this program include home-based telework and its relationships
with labor-market developments, organizational change, humanresource management, household developments, work-home balance, time allocation and time pressure. She has published in Leisure and Society, Time & Society and several Dutch sociological journals and in books on IT and work. Kea G. Tijdens is an associate professor at the Department of Economics and research coordinator at the Amsterdam Institute of Labor Studies, both at the University of Amsterdam in The Netherlands. She received her PhD from Wageningen University, The Netherlands. She has published in journals such as: Economic and Industrial Democracy, Acta Sociologica, Journal of Family Issues, Feminist Economics, as well as numerous IFIP conference proceedings, books and research reports. Her research interests include IT-use at the workplace, telework, women’s wages, women’s re-entry in the labor market, working hours, timing of work. Cecile Wetzels is a senior researcher at the Institute of Applied Scientific Research, with the group on strategy, technology and policy, Delft, The Netherlands. She received her PhD from the University of Amsterdam. Her research interests include gender, information and communication technology, labour force participation, wages and fertility. She has published in the European Journal of Population Economics, Journal of Public Finance and Management and contributed to books published by Macmillan, Edward Elgar and Policy Press. Furthermore, her book ‘‘Squeezing birth into working life, household panel data analyses on four European countries’’, has been published by Ashgate.