Informatie Management

Does Telework increase productivity? Assignment 2: The proposition Bachelor Thesis “ Does Telework increase productivity” Erasmus University Rotterdam Boudewijn Schuitmaker348393bs Robin Kettenes335450rk Marlot Sep 337273ms Bachelor Thesis “Does Telework increase productivity” Erasmus University Rotterdam Team: Group 6 (BA-02-06) Assignment number: 9 Date: 13-06-2012 Disclaimer: “This document is written by Marlot Sep, Robin Kettenes and Boudewijn Schuitmaker, who declare that each of them takes responsibility for the full contents of the whole document.

We declare that the text and the work presented in this document is original and that no sources other than mentioned in the text and its references have been used in creating it. RSM is only responsible for supervision of completion of the work but not for the contents. ” Index Summary of the research proposal4 1. Preface6 2. Abstract7 3. Introduction8 4. Literature review12 5. Methods17 6. Results19 7. Discussion26 Appendix28 Bibliography35 * Summary of the research proposal In this chapter a summary of the research proposal can be found. Summary| | Name instructor| Dhr. Nick van der Meulen| Team number| 6| Name student 1| Robin Kettenes|

Name student 2| Boudewijn Schuitmaker| Name student 3| Marlot Sep| Proposition| Telework will lead to an increase in productivity| Focal unit| Employees who perform their work at other places than at the office itself, for at least one day a week| Theoretical domain| All employees who work at other places than at the office itself, for at least one day a week, in the Netherlands. | Concept 1 | Telework| Concept 2 | Employees’ Productivity| Type of relation | Causal| Minimum size of the effect for having managerial relevance| The minimal size of effect for having managerial relevance is 20 % increase of productivity. Typical parameter of effect size used in previous tests| Items scales difference in productivity means is used between teleworkers and non-teleworkers. | Range of effect sizes obtained in the replication history| In the replication history on average an effect of productivity increase of 20% is measured by teleworking. (Newman, 1989), (Dubrin, 1991) and (Hartman, 1992)| Preferred research strategy| Longitudinal survey| Actual research strategy| Considering the research time (two months time) and the context of this research (a Bachelor thesis project) a cross-sectional survey is chosen. | Population that is surveyed, or from hich subjects are recruited| Population that is surveyed are executive employees of the department of Operations & Services of the organization of TNT Express Benelux in Houten, the Netherlands. The number of subjects is 22. | Expected pattern (or “hypothesis”)| The expected pattern for the hypothesis “teleworking will lead to more productivity” is a regression of 0. 20, meaning that an increase in teleworking will lead to an increase of 0. 20 in an amount of productivity. The expected pattern for the hypothesis “distraction will have a negative influence on the relation between teleworking and productivity” is a regression of -0. 0, meaning that an increase in distraction will lead to an decrease of 0. 20 in a amount of productivity, when teleworking. | Observed pattern| The observed pattern for the hypothesis “teleworking will lead to moreproductivity” is a negative relation with a regression beta score of -1,311,meaning that if the degree of teleworking increases with one unit, the productivity will decrease with 1,311. The observed pattern for the hypothesis “distraction will have a negative influence on the relation between teleworking and productivity” is a positive relation with a regression beta score of 0,188.

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Thus, for the increase of one unit distraction, the productivity will increase with 0,188. | Test result| Teleworking has a negative effect on productivity and distraction has a positive relation on productivity. | Non-response bias assessment (worst case analysis)| The number of missing cases is 5. The worst case analysis show that if the five respondents joined the survey, and where very different form the obtained ones, a positive effect of teleworking on productivity (2,775) and a negative effect of distraction on productivity (-0,173) could be found. Your contribution to what is known about the proposition| Our contribution to the proposition “Telework will lead to an increase in productivity” is that teleworking does not always lead a positive change in productivity such as suggested in many scientific articles. In our research a negative relation is found on productivity when teleworking. | Most important recommendation for further research| The most important recommendation is, in order to do a replication study, a longitudinal survey.

The longitudinal survey enables the future researchers to measure the change in productivity that takes place at a later point in time when employees telework. In this research the measure of productivity towards teleworking is only done once. | Preface This bachelor thesis is written as part of our studies Business Administration at the Erasmus University Rotterdam. The main subject of this thesis is “Telework”. We selected this subject out of many other subjects because we wanted to write our thesis about a topical subject and teleworking has become a major hype in the last few years.

Many businesses implement teleworking in their company for various reasons. So, is assumed that teleworking will lead to cost reduction, more productive employees and more satisfied employees. But, the main question is does telework provide all these benefits? In this thesis we will look at the effect of teleworking on the productivity of employees. Abstract The relation between teleworking and productivity is of critical concern for organizations that might be planning to implement teleworking of for those who have already done.

In this research the relation between teleworking and productivity is examined, controlling for age, gender and family status. The effect of distraction on the productivity of employees was also measured. A survey among 17 teleworkers at TNT express was conducted online to gather data. In result of different multiple regression analysis’, a negative impact of teleworking on productivity was discovered. Furthermore, a slight positive impact of distraction on productivity was found. The results look paradoxical, but there are several reasons to explain these results and shed a new light on the telework-productivity research.

Introduction In the last few years there has been an increasing demand for flexible work and flexible organizations. The concept of teleworking offers a solution to this increasing demand. At this moment 20 to 30 million people in the U. S. currently work from home at least one day a week (Telework Research Network, 2011). In the literature several definitions of telework are used. The most common definition of telework defines telework as work performed at home, a satellite office or other places than the office itself, to reduce commuting (Shin, 2000).

There are several motives companies could have to adopt the concept of telework. Obvious motives are cost reduction and increased productivity. Additional benefits for teleworking employees are increased job satisfaction and a better work-life balance (Harpaz, 2002). In this thesis a proposition, regarding telework and productivity, will be tested. The proposition that will be tested is: “Telework will lead to an increase in productivity”. In general this means that this research measures if employees have a higher productivity if they telework, and thus have the opportunity to work besides the office, than if they are office-bound.

The increase in productivity is often measured due the comparison of output produced by a given amount of input, often office hours. If the employee, who teleworks, uses exact the same time as an office-bound employee for a job, while delivering a greater amount of work, an increase in productivity due telework can be concluded. The first who formulated the concept of telework in 1973 was Jack M. Nilles from the University of Southern California, Los Angeles. He defined Teleworking as "any form of substitution of information technologies for work-related travel" (Madsen, 2003).

The one clear motive for the expansion of teleworking, mentioned by Nilles, was the reduction of transportation congestion, particularly in overcrowded urban areas. Although these public benefits were not sufficient enough to implement teleworking. Economic benefits like cost reductions, space savings and reduced rental rates for office space ensured that companies were more likely to introduce the concept of teleworking. According to Nilles productivity will increase as a result of working harder and working more hours per day, because of less distraction, interruptions and stress (Nillis, 1988).

After Nilles formulated the proposition that telework increases productivity for the first time, it has often been examined. Some articles stated that telework increased productivity. For example at AT&T, a telecommunication company, telework increased productivity with almost 10 percent, according to AT&T's annual telework survey among 1,500 employees. Another example of increased productivity is IBM where 87 percent of the employees report that they believe that their productivity have increased significantly (Apgar, 1998).

In fact several articles stated that the productivity of employees is higher when they work at home. Only one research shown a decrease in productivity. However this decrease was later followed by an increase of productivity (Bailey, 2002). Despite several articles have examined the relation between telework and productivity, it is dificult to measure productivity. Like mentioned earlier, productivity is based on the relation between input and output. There have been problems when measuring the productivity of today’s knowledge workers. First of all, most knowledge workers do not produce “units” per given period (e. . per hour, day or month). Because output is often measured in “units”, the productivity of knowledge workers is hard to measure. Secondly, there is not a direct correlation between units of labor and units of output for these knowledge workers. Extra input from one additional worker does not necessary lead to more output. The classic definition does not enable to measure knowledge workers’ productivity, certainly not when measuring besides the office (Gordon, 1997). In the research on the relation between telework and productivitity a number of methodological weaknesses have been discovered.

Most studies use self-report suverys to collect data from teleworkers. These self-report surveys can result in false responses from teleworkers in their productivity evaluations. This so called self-response bias has not been taken into account in many productivity research. Data collection from both, teleworker and manager will be a better way to measure productivity. Next to that sample populations are selected under specific personality and task criterea, which could be related to a higher work motivation and therefore contributes to increased productivity.

Another explanation for increased productivity could be the relegation of other tasks to office-bound employees. Higher productivity can also be explained by the increase in working hours, due less commuting (Shin, 2000). Due the difficulties of measuring productivity some articles falsly claim the fact that telework increase productivity. Like mentioned earlier, productivity measurement for knowledge workers has been a dilemma. In measuring input and output the term “productivity” is inadequate for knowledge workers.

Therefore this research measures “productivity” not only due the quantity of work, but due several concepts. The concepts used in this research to measure productivity are: quantity, quality, timeliness and multiple priorities. The questions how much can be done (quantity), how well it is done (quality), when it is done (timeliness) and how many things can be done at once (multiple priorities) are being covered. Using multiple concepts enables to put the quantity factor in the context of a bigger picture and not just simply focus on an increase in output (Gordon, 1997).

As stated earlier, there are several definitions for teleworking. Most definitions focus on the fact that employees have the possibility to work everywhere and not as much on the fact that employees can work whenever they want. In this research the most common definition of Shin, Sheng and Higa will be used. Shin et al. defines telework as work performed at home, a satellite office or other places than the office itself, to reduce commuting (Shin, 2000). Figure 1 Causality Model The causality model of this thesis, shown in figure 1, consist of two concepts: teleworking and productivity.

The independent concept in the causality model is teleworking and the dependent concept is productivity. The focal unit of this research theory is the entity of which the range of values of one or more variable attributes is explained by the theory (Hak, 2011). The focal unit consists of employees who perform their work at other places than at the office itself, for at least one day a week. The minimum number of days teleworkers work besides the office is chosen because several instances use this minimum, like the Telework Research Network.

The national average number of days a teleworker works besides the office is 2,4 days a week (Telework Research Network, 2011). The productivity of teleworkers is measured due the comparison of their productivity when working besides the office and when working at the office. There is not chosen for the comparison of the productivity of teleworkers and office bound employees, because this is not valid. The variation in productivity between teleworkers and office-bound employees should not necessarily come from teleworking, but can be explained by several other factors for instance by personal ifferences. The theoretical domain of this research, the universe of instances of the focal unit, consist of all employees who work at other places than at the office itself, for at least one day a week, in the Netherlands. Literature review After Nilles claimed that productivity increased as a result of teleworking in 1973, it has often been examined. In 1982 Olson researched the effect of telework on productivity. Although there were no measures of performance data, employees and managers pronounced that teleworkers are more productive than office-bound employees.

The study also revealed that teleworkers are more responsible and conscientious about schedules, had better documentation and scheduled their time better. Employees felt that they worked more efficiently or produced higher quality work, when working at home. Few employees found the office very distracting and therefore could be more productive at home (Olson, 1982). This results are consistent with Olson’s later longitudinal study of three pilot teleworking programs, which revealed that teleworkers believed that their performance was enhanced due teleworking (Olson, 1989).

In 1989 Bailyn also researched the effect of telework on productivity among 89 system developers, including 49 teleworkers. More than a quarter of the software developers reported that their most productive work times fell out of the traditional office days. Bailyn assigned this productivity increase to the fact that teleworkers have individual control over time and the ability to allocate work over all time periods, including the weekends. The survey also indicated that employees needed quiet and privacy to be productive (Bailyn, 1989).

Bailyn also noted that only tasks that do not require extensive interaction will benefit from teleworking (Bailyn, 1988). One year later Newman stated that teleworking is ideally for those whose jobs require them to handle a flow of information, like programmers, engineers, speechwriters and business analysts. The personality of the teleworker must include being capable of handling autonomy. According to Newman, experienced workers make the best candidates for teleworking. Similar to Olson, Newman stated that the work-at-home programs often result in increased output from staff, naming eing less distracted meant being more productive. In Newman’s study at the Travelers Insurance Company productivity increased with 20 percent. Despite of the increased productivity, limiting the geographic boundaries of the company’s hiring pool due offering work-at-home arrangements to employees was the prime reason for teleworking (Newman, 1989). In Dubrin’s research the reasons for teleworking were to solve staffing, space, and other business problems including keeping motivated employees away from the distractions of other workers (McKee, 1988).

According to Dubrin an implicit assumption about teleworking programs is that employees who work at home will be equally more productive that office-bound employees. Dubrin’s observation of company records suggests that home workers increased their productivity from 5 to 100 percent (Dubrin, 1991). Dubrin tested the hypothesis “ telecommuters are more productive than are employees performing comparable work on company premises” among employees of the NPD Group. The participants in this research were mainly women.

The fact that only women are represented in Dublin’s studies makes it difficult to separate findings between males and females. The degree of distraction was measured due different statements in the questionnaires. The questionnaire items ‘Being able to keep busy all the time’ show that telework has a positive influence on the productivity. The work-at-home group scored significantly higher (13. 81) than the group in-house workers (6. 36) at the t-value of 4. 20. The research found that productivity was increased by 30% when projects were moved from company premises to homes.

The productivity was measured in transactions per hour, occurred when a project was shifted from in-house to at-home. The results are consistent with findings of Newman. In Dubrin’s research the productivity findings showed that people who worked at home part-time are more productive than those who worked at home full-time. It is concluded that productivity increases when work is structured, repetitive and measurable. In order to conclude evidence that telecommuting increases productivity, it is necessary to move in-house workers into their homes and then measure the productivity changing (Dubrin, 1991).

Accoring to Frolick, Wilkes, Urwiler productivity is expected to increase when teleworkers work according to a flexible schedule in an informal setting. The question whether telecommuters are more productive than office-bound employees was researched in a semi-structured telephone interview among 45 individuals in 10 organizations. The average time that each of the interviewees had spent in the telework programs was 2,3 years. The results of the interviews revealed that every teleworker and every telework manager reported that productivity had increased as a result of their telecommuting programs.

In each case the respondents stated that teleworker productivity was higher than the productivity of office-bound employees. The average increase of productivity was approximately 20 percent. This result is consistent with other researches like Niles 1990 (Frolick, 1993). Frolick et al. attributed this productivity increase to lack of interruption and the ability of the teleworker to schedule his or her work in a flexible manner. In this study all the teleworkers cited ‘fewer interruptions’ as a contributing factor to their productivity and 17 of them cited ‘greater flexibility’ in performing their jobs (Frolick, 1993).

Hartman, Stoner and Arora noticed two fundamental problems in the previous study, namely an extraordinary small sample size and maintaining a broad, non restrictive definition of telecommuting that leads to clouded outcomes and conclusions. In their study telecommuters were selected from 11 different organizations, both public and private, including telecommunications, insurance, banking, publishing, and city an state governmental units. The research was done due a self-report survey among 262 telecommuters.

Telecommuting productivity was measured by the respondent’s feeling about how the output per hour was changed, working at the office versus working at home. An overwhelming 84 % reported that productivity was increase while working at home, 12 % reported no change and just 4% reported a lower productivity. Hartman recognized that the self-reported perceptions of comparative productivity might be biased, but the outcomes were consistent with the productivity increase in other studies (Hamilton, 1987)(Moody, 1986). Neufeld and Fang focused on the influence of distraction, gender and family status on teleworker’s productivity.

Their research assumed that gender and family status (defined as social factors) are negatively correlated with teleworker productivity. When working at home, the family status is important because family is often around. Therefore they may have a large effect on the teleworkers, and their productivity. The results of the study are obtained by semi-structured interview. For measuring the social factors, direct questions are used (such as do you have children at home? ). For measuring distraction, questions are used like; is your environment distraction free?

The results showed that teleworker productivity is not associated with family status and gender, but on the other hand, a distraction free environment was associated with teleworker productivity (Neufeld, 2005). Another study of Derrick J. Neufeld, which examined productivity among four different kinds of organizations, showed that claims of a higher productivity correlated to teleworking are overblown. In this study, productivity is measured among 200 Canadian employees, and the results show that the increase in productivity is statistically insignificant.

Cynics predicted that distractions from working at home will reduce productivity. But despite these distractions, productivity is not reduced, but slightly increased. This study of Neufeld shows that teleworking is significantly more correlated with organizational flexibility than with productivity (Cassiani, 2000). Kelley Butler also looked at the relation between distraction and teleworker productivity. Butler stated that the top 6 distractions, while working at home, are household chores, television, pets, errands, internet and children.

The data was collected from a CareerBuilder survey. Some of the teleworkers (17%) was so distracted by these factors, that the distraction costs one hour of their working hours (Butler, 2011). Thompson, Vivien and Lim examined the differences in gender on the perception of teleworking. Their data was collected from a questionnaire survey among IT professionals in Singapore. Results showed that males perceived that teleworking improved the quality of life and their productivity in a greater extent than females.

Also, in this research productivity increases while teleworking, because an employee can plan the work schedule during the hours when one is most productive. But on the other hand, the study also shows that distractions at home may be harder to solve than distractions at the office. An analysis of the covariance was used to measure the difference between gender, and the relation to the advantages and disadvantages of teleworking. The results show that there is no significant difference in gender (Thompson, 1998). Author| Literature effect found|

Olson, 1983| Preliminary evidence from the exploratory study shows that individuals can be as or more productive when working at home| Olson, 1988| Telecommuting experts and practitioners regularly cite at-home productivity gains ranging from 15-25%| Newman, 1989| Work-at-home programs often result in increased output from staff| Newman, 1989| The Travelers Insurance Company productivity increased with 20 percent among 80 commuting staff| Di Martino, 1990| A two-year pilot project (... ) reported productivity gains averaging 43 per cent per participant.

Teleworkers (…) noted productivity increases varying from 12 per cent to 20 per cent. State employees working at home have been rated (…) as 3 to 5 per cent more effective than they would have been if they worked from nine to five in the office. | Dubrin, 1991| Productivity was increased by 30% when projects were moved from company premises to homes| Dubrin, 1991| Observation of company records suggests that home workers increased their productivity from 5 to 100 per cent| Hartman, 1991| A significant negative correlation between the ratio of telecommuting hours to total work hours and telecommuting productivity was revealed. Hartman, 1991| The full-time employed telecommuters reported higher levels of productivity (3. 59) in comparison with part-time employed telecommuters (2. 65). | Hartman, 1992| Telecommuters were asked whether they felt their productivity (output per hour) at home was higher or lower than at the office. An overwhelming percentage (84%) reported higher productivity while working at home, only 4 % of the telecommuters reported lower productivity, and 12 % reported no change. Frolick, 1993| The findings indicate a significant increase in productivity (20%) among teleworkers| Apgar, 1998| 87 per cent of employees (…) report that they believe their productivity and effectiveness have increased significantly| Baruch, 2000| How teleworking influences the way people work after opting to telework were examined (…).

Compared with previous arrangements of work effectiveness 34 per cent and 42 per cent felt it was much better or better (respectively), totaling a positive impact for 76 per cent, with just 5 per cent suggesting no difference and 3 per cent worse. | Pearlson, 2001| A survey in 2001 of 150 executives in large U. S. companies found that 36 percent saw no difference in productivity levels between telecommuters and onsite employees, while 26 percent felt that telecommuting could compromise job performance| Table 1 Reported effect sized of the effect of Teleworking on Productivity

Author| Effect| Olson, 1983| Some of the individuals interviewed cited problems with motivation and numerous distractions at home that made concentration difficult| Newman, 1989| Work-at-home programs often result in increased output from staff, naming being less distracted meant being more productive| Hartman, 1991| Family disruptions and their association with telecommuting productivity and satisfaction, the correlation with productivity is -. 20 (p = . 06). Frolick, 1993| Most claims of productivity to date have been attributed to a lack of interruption and the ability of the teleworker to schedule his or her work in a flexible manner. | Baruch, 2000| Better performance was attributed mostly to the elimination of distractions, which are typical at the workplace and subsequently the ability to focus on work. | Young Lee, 2005| The results indicated no significant effect of perceived distractions on perceived performance| Wilson, 2004| Could be more productive without such ‘distractions’. Fonner, 2010| Results show that working remotely the majority of the time alleviates forms of stress and distraction including acting as a buffer from workplace injustice which may provide a more productive and satisfying work environment| Table 2 Reported effect sized of the effect of Distraction on Productivity Methods The research strategy is to test the proposition that assumed that teleworking will lead to an increase of productivity. The replication history research has indicated that this theory has empirically been confirmed for various populations.

If the proposition is true in the domain, then it must be true for the population in the domain. In order to claim whether a proposition is true, empirical evidence is required to show its correctness. This research deduces a hypotheses regarding teleworking, distraction and increasing productivity by an empirical research. Ideally a causal relationship between teleworking, distraction and productivity is measured in a longitudinal survey. The longitudinal survey is defined as a research strategy in which a change in value of the relevant concepts is observed in all members (or in samples) of a population of instances of a focal unit.

In a longitudinal survey it is possible to find a population of comparable cases in the theoretical domain in which the value of teleworking (named here as variable X) has changed over time. A causal relation “X influences Y” (variable Y is employees’ productivity) is observed in the cases, if the value of Y has changed after the change of value X. Considering the research time (two months) and the context of this research (a bachelor thesis), this research uses a cross-sectional design to measure the relationship between teleworking, distraction and employees’ productivity.

A scatter plot is a useful tool to show a possible correctness of the proposition. The cross-sectional design enables to concentrate on variations of cases within one particular population. In this research the population is a department within an organisation. The population consists of all executive employees of the department Process ; Policies of TNT Express Benelux in Houten, the Netherlands. The number of employees/cases is 22. #| Name employee:| | | | | 1| Bert Schut | 14| Koos Jansen | 2| Corne Vroegh | 15| Marielle Sitskoorn | | David Roofthoofd | 16| Marina Elegeert | 4| Erik van Duin| 17| Martijn Otte | 5| Geug Leendertse | 18| Maurice Hidma | 6| Guy Gevaers | 19| Mette Kok| 7| Harrie Dasselaar| 20| Michiel Bierman| 8| Henk Jansen | 21| Tessa Koster | 9| Jack Beks| 22| Thomas Goossens | 10| Jan Harmen Hietbrink| 11| Jef Kleinschmidt | 12| John Meisters| 13| John van Oeffel | Figure 2 Employees of the Process ; Policies department at TNT express In the cross-sectional research, qualitative and quantitative data of respondents is collected more or less simultaneously.

The self-report survey will be sent out to all cases at the same moment and held during the same time of period. The independent variable (teleworking) is a quantitative variable measured in percentages. The other independent variable (distraction) is a qualitative variable, measured in likert schales with categories like: never, sometimes, regularly, often and always. Productivity is a qualitative variable. The controlling variables are gender, age and family status. Gender is divided into male and female (0=male and 1= female).

Family status is measured in four different values, namely single, single with children, married or co-habiting, and married or co-habiting with children. The conceptual model of this research can be found in Figure 3. To test the five different hypothesis based on the conceptual model, a multiple regression analysis will be used. Figure 3 Conceptual Model The hypothesis concentrates on the relation between teleworking and the productivity. Assumed is that teleworking lead to an increase in productivity. This means that employees can do more work, do their work better, schedule their own work and do multiple things at once.

The hypothesis is formulated as following: There is a positive relation between teleworking and productivity if the ? is ? 0,20. In the conceptual model age, gender, family status are taken into account as controlling variables. Gender could have an influence on productivity. Women, for example, are better in multitasking and could therefore have a higher score on “multiple priorities”, which influences the productivity. Family status could have an impact on distraction, therefore it is also used as controlling variable. This also accounts for age. The assumption is that lder employees are less productive compared to younger employees, which are more involved with technology. Two different regression analyses’ with different variables are plotted. * The variables teleworking / gender / distraction / age / family status in relation to productivity. (nain regression) * The variables teleworking / distraction in relation to productivity The main regression model is shown below: Productivity = ? + ? 1 Teleworking + ? 2 Gender + ? 3 Family status + ? 4 Age + ? 5 Distraction + ? ? ~ iin( 0, ? )

The regression analysis will show which variable will have the highest influence on the dependent variable productivity, corrected for the influences of the other variables. The expectation is therefore that the beta of teleworking will be the highest in the model. Results The data in this research is collected due a self-report survey among employees of the Process ; Policies department of TNT Express Benelux. The self-report survey was conducted online on the Belgian website of “enquetemaken. be”. A textual version of this survey can be found in appendix 2.

A link to this survey was send to the 22 employees of the department by mail. This research chose for an anonymous survey in order to ensure that respondents could be honest about their answers. This would secure the reliability of this survey. Besides that the interview was conducted in Dutch because all employees at TNT are Dutch. The employees filled in questions concerning telework and productivity. Several non-related questions, concerning job satisfaction and work-life balance, were added in order to cover the real purpose of the research.

In order to guarantee the reliability and validity of this research, the questions of the survey are based on questions used in other research. The productivity measurement is divided into four determents that are each tested individually. These four determents are quantity, quality, timeliness and multiple priorities (Gordon, 1997). Lee and Brand used questions like “Compared to my typical work right now, I would rate the quality of my work as” and “Compared to my typical performance right now, I would rate my job performance as” are being used.

In the survey of this research four questions are used in order to measure work productivity. The exact questions can be found in the appendix. The questions in the survey concerning distraction, were like “How frequently are you unable to concentrate because of interruptions from your family? ”. These questions were extended to other factors, like distractions from colleagues, phone calls/e-mails/texts, sounds and other factors (Neufeld, 2005). According to Young Lee ; J. L. Brand, is noise one of the main distractions (Lee et all, 2010). Therefore, we devoted one question on noise.

Also, the question ‘I am easily distracted from my work’ is used in their research, which we decided to put in our own survey. In the article ‘from knowledge to distraction’, written by Jonathan Spira in 2007, is stated that knowledge workers are often distracted by e-mails, phonecalls, instant messages etc. For this reason, there is decided to investigate the amount of distractions by these influences in the survey. In this article, also is stated that ‘colleagues popping in’ might be a factor of distraction. This factor is also added to the survey.

The last question regarding distraction, is about ‘other distractions’. This is to make sure that there are not any parts of distraction missed. The non-response bias of this survey was 22,7 percent. Five employees did not fill in the survey because they were not available in the two weeks the survey was online. If the non-response bias is very high it can effect the representativeness for the population. A data grid of the results of this survey can be found in table 4. A detailed calculation of the degree of productivity and distraction can be found in appendix 3.

Total Work hours| Telework hours| Degree of distraction (1=low, 5=high)| Degree of Productivity (1=low, 5= high)| Gender (1=male, 0=female)| Age| Family status * | 40| 20| 3. 2| 4| 1| 58| 3| 50| 33| 3. 4| 3. 75| 1| 40| 1| 50| 30| 2. 4| 3. 5| 1| 53| 3| 42| 7| 2. 4| 3. 75| 1| 54| 3| 40| 5| 2. 4| 4. 5| 1| 48| 4| 50| 25| 2. 2| 4| 1| 44| 4| 40| 15| 2. 2| 3. 75| 0| 40| 4| 40| 25| 2| 3. 75| 1| 28| 3| 40| 32| 2. 4| 3. 5| 0| 32| 3| 40| 8| 3. 2| 4| 1| 42| 3| 45| 8| 2. 4| 4| 0| 32| 3| 40| 2| 2. 4| 3| 1| 32| 1| 45| 8| 2. 4| 3. 75| 1| 51| 4| 60| 36| 2. 6| 4| 1| 31| 3| 45| 8| 2. 6| 3. 5| 1| 36| 4| 45| 35| 3. 8| 4| 1| 38| 4| 50| 5| 2. | 4. 75| 1| 40| 3| 44. 82353| 17. 76471| 2. 623529| 3. 852941| -| 41. 11765| -| *= (1= single, 2=single with children, 3=married or co-habiting, 4= married or co-habiting with children)| Table 3 Data Grid of the survey at TNT Express The expected pattern Hypothesis 1: Teleworking will lead to more productivity The expected pattern for the first hypothesis “teleworking will lead to more productivity” is a regression of 0. 20, meaning that an increase of an hour teleworking will lead to an increase of 0. 20 in an amount of productivity. In the literature review several articles reported that teleworking increase productivity.

However, there are also articles that claim a negative effect of teleworking on productivity. A summary of the reported effect sizes can be found in table 1 in the literature review section. The effect sizes of the relation between teleworking and productivity, found in the literature, vary from a negative relation to a positive relation. The majority of effects are positive, which means that productivity was increased due to teleworking. Although the majority of effects were positive, the claimed productivity increase ranges from 5 % to 20 %, up to 100 %.

There is one article by Hartman (1991) that claims a negative correlation between telecommuting and telecommuting productivity. Derived from the literature review the expected pattern, in which the hypothesis is true, is a regression coefficient of 0. 20 or more. This means that if the degree of teleworking increases with one hour, the productivity will increase with 0,20. The hypothesis 2: Distraction has a negative influence on productivity The second hypothesis is aimed at the independent variable distraction on the dependent variable productivity.

The correlation is expected to be -0. 20, meaning that an increase of one unit distraction will have a decrease of 0. 20 in the amount of productivity. In the literature several effects of distraction on productivity are found. A summary of the reporter effects can be found in table 2 in the literature review section. The effects found in the literature review suggest that distraction has a negative influence on productivity. The effects vary from no significant effect on performance to being more productive when distraction is eliminated.

The expected effect of distraction on productivity is expected to be negative in this research. The correlation is expected to be -0. 20, meaning that an increase of one unit distraction will have a decrease of 0. 20 in the amount of productivity. The observed pattern Hypothesis 1: Teleworking will lead to more productivity The results of the main multiple regression analysis show that 26 per cent of the variance is declared by the model. The correlation between the observed and expected values of dependent variable is 0,509. In appendix 4 the SPSS output of this research is shown.

Surprisingly, the degree of teleworking has a negative influence on productivity. This can be interpreted by the beta of the quantity of teleworking, which is -1,311. This means that if the degree of teleworking increases with one hour, the productivity will decrease with 1,311. The hypothesis 2: Distraction has a negative influence on productivity Another surprising output is the influence of distraction on productivity, which has a beta of 0,188, where a negative beta is expected. Thus, for the increase of one unit distraction, the productivity will increase with 0,188.

A partial regression analysis, without the controlling variables gender, age and family status, shows that there is a slight difference in the variance declared by the model and the correlation between the observed and expected values of the dependent variable. These figures fall to 0,259 and 0,067. The betas of the degree of teleworking and distraction fall to -1,287 and 0,148. For this reason, the controlling variables will be added to the other regression analyses. There are several ways to explain the surprising betas of teleworking and distraction.

First of all, the results are based on the answers of only 17 respondents. In the partial regression plot (with the variables distraction and productivity) is clear that because of a few amount of outliners, the R2 linear is climbing a little. Without these outliers, there is a large possibility that the distraction beta will be negative, which was expected. Another explanation is that the employees of TNT express do not relate distraction to their productivity. They tend to give themselves a high overall score on productivity, regardless of the degree of distraction and teleworking.

Another possibility is that the amount of distraction actually does not influence the productivity. Figure 4: The relation between distraction and productivity Because of the little number of respondents, the few outliers pull the mean of the productivity up. These respondents have a small quantity of teleworking, but tend to give themselves high scores on productivity. Therefore, the linear line of the quantity of teleworking is declining, where it would have been rising without these three outliners. This can be an explanation for the negative effect of teleworking on productivity.

But on the other hand, it might be possible that the teleworking does have a negative effect on productivity. In a worst-case analysis, the five missing respondents could dramatically influence the results of the regression analysis. This would be, if the respondents all would score low on productivity and on high distraction (or vice versa), or if degree of teleworking among the employees is high and their productivity is high too (or vice versa). Figure 5: The relation between teleworking and productivity

The worst-case analysis of the effect of telework on productivity shows that, when the five missing respondents would have been very different from the ones obtained, there is a positive effect (2,775) of telework on productivity. This positive effect is shown in figure 6. This in contrast with the results of this research, without the missing five respondents, where a negative effect was discovered. If the five missing respondents participated in this research and were very different from the ones obtained they could have a drastic impact of the results of this research.

The expected positive effect of telework on productivity could be discovered in this scenario. Figure 6: Worst-case analysis of the effect of telework on productivity The worst-case analysis of the effect of distraction on productivity shows that, when the five missing respondents would be very different from the ones obtained, there is a negative effect (-0,173) of distraction on productivity. The worst-case analysis is shown in figure 7. This negative effect corresponds to the expected effect of distraction on productivity, but not to the observed effect in this research.

This means that if the five missing respondents participated in this research, the outcomes of this research could be dramatically different and the expected negative effect of distraction on productivity could be measured. Figure 7: Worst-case analysis of the effect of distraction on productivity Overall can be concluded that if the five missing respondents participated in this survey they could have changed the outcomes of this research dramatically. The expected effects of this research could be found when adding the five missing respondents.

Discussion The test results found in the multiple regression analysis? , claim roughly that TNT express should increase the distraction among employees, and decrease the degree of teleworking. But, as shown in the results chapter, the results only show a slight negative relation. Which can be easily influenced by the missing data, as shown in the worst case scenario analysis?. Therefore, the results should be interpreted as if distraction does not have a high influence on the productivity of employees.

There is not a valid relationship in the test results showing that distraction has a positive influence on productivity, because of the very low negative beta (as a result of the regression analysis’) and the possible influence of the missing values on the test results. The relationship between teleworking and productivity did show a large coherency. This large coherency was interpreted as if teleworking is not productive for TNT express. Thus, in this research, distraction is recommended and teleworking is discouraged.

But it is recommended to keep in mind that the worst case scenario analysis’ (showing the missing values can turn around findings as much as possible) presume a positive influence of teleworking on productivity, and a negative influence of distraction on productivity. For further investigation it will be recommended to use more respondents, as much as possible. When more respondents are used, the results will be less influenced by outliers. A very low response bias is also recommended, so that a worst case analysis’ are not necessary and therefore will not show complete opposite results compared to the research.

In this research, the response bias was 28 per cent. Another recommendation would be to make a connection between distraction and productivity for the respondents themselves. In this research, the respondents did not link distractions to their productivity (which can explain the divergent relation between distraction and productivity). When questions are formulated with the factors of distraction and productivity in one sentence, the link is automatically made for the respondents. Theorems for example like ‘when I am distracted by phonecalls, I feel like I can do less work’.

Besides that all respondents report that they were very productive, even if they suffered from a lot of distraction. A solution for this self-response bias, that often occurs in self-report surveys, is to involve the opinion of the manager of the respondents in the research as well. Because of time constraints this was not possible in this research, but it will be a good way to eliminate the self-response bias in future research. In previous research, many positive effects of teleworking on productivity were found. This research contradicts this and reveals a negative effect.

Although the worst case analysis showed that there could be a positive effect, when the five missing respondents were very different from the ones obtained, the observed negative effect could also be an indication that there really is a negative relation between teleworking and productivity. In 1991 Hartman also claimed a negative correlation between teleworking and productivity. Because the research of Hartman also reported this negative effect, it could be true that teleworking has a negative impact on productivity.

This would generate a new insight into the telework-productivity research, in which was assumed that teleworking increased productivity. In contradiction to earlier research on the effect of distraction on productivity, this research shows a slightly positive effect of distraction on productivity. The fact that more distraction leads to more productive employees seems contradictory, but interruptions are not necessarily bad. Little interruptions, for example, could provide a fresh new insight into someone’s work.

Therefore the observed positive effect could be real and is interesting to further investigation. Because the observed effect is slightly positive and in the worst case analysis slightly negative, it could also be an indication that distraction has no effect on productivity. This is supported by the research of Lee and Brand, which indicated that there was no significant effect of perceived distractions on perceived performance. This finding could also contribute to the research on the effect of distraction of productivity.

In conclusion the findings of this research do not fully correspond to the main findings in the literature. This is actually very interesting because a new insight in the research on teleworking and productivity is generated. It can be questioned if the main findings in the literature are true. Maybe teleworking is not good for the productivity of employees and distractions are not as bad as everybody’s thinking. In order to do a replication research towards the effect of teleworking on productivity in the future a replication strategy is useful.

The preferred replication strategy for the future is a longitudinal survey. The longitudinal survey enables the future researchers to measure the change in productivity that takes place at a later point in time when employees telework. In the longitudinal survey all members of a focal unit can be observed over time. Additional theoretical insight is advised in order to determine how much time should elapse between the change in value of productivity and the subsequent change in the value of teleworking. * Appendix Appendix 1: Several definitions of Telework and/or Productivity | Author(s)| Definition of telework| Definitions of productivity| 1| Newman (1989)| Working home with the aid of computers, modems and facsimile machines. | | 2| Dubrin (1991) | Performing job-related work at a site away from the company, then electronically transferring the output to another location| | 3| Frolick, Wilkes, Urwiler (1993)| | The number of tasks effectively completed in a given timeframe| 4| Hartman, Stoner and Arora (1992) | Work arrangement where organizational employees regularly work at home or at a remote site one or more complete workdays a week instead of working in the office. Telework managers reported using ‘deadlines’ or ‘agreed upon deadlines’, and ‘on-time work and quality’ to manage and measure teleworker productivity. | 5| Nilles (1975)| Telework is any form of substitution of information technologies for work-related travel| | 6| Mokhtarian (1991)| Telework is defined as the use of telecommunications technology to partially or completely replace the commute to and from work. | | 7| Sing, Sheng, Higa (2000)| Telecommuting is the reduction of commuting distance by working home, in nontraditional satellite offices, in telecottages, or in neighborhood offices. | * Appendix 2: Self-report survey at TNT express. Onderzoek Het Nieuwe Werken bij TNT express. Voor onze bachelor thesis, onderdeel van de studie bedrijfskunde, doen wij onderzoek naar Het Nieuwe Werken bij TNT Express. Dit onderzoek is onderdeel van ons afstuderen aan de Erasmus Universiteit te Rotterdam. Voor ons onderzoek willen we graag uw medewerking vragen door middel van het invullen van een vragenlijst. Het invullen van de vragenlijst zal ongeveer 5 minuten duren. Deze vragenlijst is geheel anoniem. Alvast bedankt, Robin Kettenes, Boudewijn Schuitmaker en Marlot Sep __________________________________________________________________________ Het Nieuwe Werken is een breed begrip voor het tijd en plaats ongebonden werken, als gevolg van het gebruik van moderne communicatie technologieen. In ons onderzoek spitsen wij ons echter alleen toe op het plaatsongebonden werken. Het plaatsongebonden werken houdt in dat u zelf kunt bepalen waar u werkt. ___________________________________________________________________________ 1) Hoeveel uur werkt u over het algemeen per week? ………. uur 2) Heeft u de mogelijkheid om buiten kantoor te werken? Ja Nee ) Hoeveel uur per week werkt u over het algemeen buiten uw kantoor ? …. ….. uur 4) Op welke plaatsen werkt u als u buiten uw vaste werkplek werkt? Thuis Onderweg Internet Cafe Elders 5) Waar vindt u het het prettigst om te werken? Op kantoor Buiten kantoor 6) Ik ben makkelijk afgeleid van mijn werk Nooit Soms Regelmatig Vaak Altijd 7) Ik word tijdens mijn werk afgeleid door geluid Nooit Soms Regelmatig Vaak Altijd 8) Ik word tijdens mijn werk afgeleid door telefoontjes/e-mails/berichten etc. Nooit Soms Regelmatig Vaak Altijd 9) Ik word tijdens mijn werk afgeleid door collega’s

Nooit Soms Regelmatig Vaak Altijd 10) Ik word tijdens mijn werk afgeleid door andere factoren Nooit Soms Regelmatig Vaak Altijd 11) Ik zou de hoeveelheid werk dat ik kan opleveren werk beschrijven als Erg veel Erg weinig 12) Ik zou de kwaliteit van mijn werk beschrijven als: Erg goed Erg slecht 13) Ik heb mijn werk altijd op tijd af Helemaal juist Helemaal onjuist 14) Ik ben in staat meerdere taken tegelijk uit te voeren Helemaal juist Helemaal onjuist 15) Ik vind het erg fijn om op kantoor te werken Helemaal juist Helemaal onjuist 6) Ik vind het erg fijn om thuis te werken Helemaal juist Helemaal onjuist 17) Ik vind het prettig werk en prive gescheiden te houden Helemaal juist Helemaal onjuist 18) Het is makkelijk voor mij werk en prive gescheiden te houden als ik op kantoor werk Helemaal juist Helemaal onjuist 19) Kunt u een schatting geven van de verhouding tussen de tijd dat u op uw op kantoor werkt en de tijd dat u buiten kantoor werkt? (Bijvoorbeeld; 40-60 / 50-50 ) …. / …. 20) Wat is u geslacht? Man Vrouw 21) Wat is u leeftijd? …….. jaar 22) Wat is u burgerlijke staat? Alleenstaand

Alleenstaand met kinderen Getrouwd/samenwonend Getrouwd/samenwonend met kinderen Appendix 3: Detailed calculation of the degree of productivity and distraction Calculation: The Degree of Distraction|  |  | 3| 3| 4| 3| 3| 3. 2| 3| 4| 4| 4| 2| 3. 4| 2| 3| 3| 2| 2| 2. 4| 2| 2| 3| 3| 2| 2. 4| 2| 2| 3| 3| 2| 2. 4| 2| 2| 2| 3| 2| 2. 2| 2| 2| 3| 2| 2| 2. 2| 2| 2| 2| 2| 2| 2| 2| 2| 4| 2| 2| 2. 4| 4| 3| 3| 3| 3| 3. 2| 2| 2| 3| 2| 3| 2. 4| 3| 2| 2| 3| 2| 2. 4| 3| 2| 2| 3| 2| 2. 4| 3| 2| 3| 3| 2| 2. 6| 3| 2| 3| 2| 3| 2. 6| 4| 4| 3| 4| 4| 3. 8| 3| 2| 4| 2| 2| 2. 6| 2. 647059| 2. 11765| 3| 2. 705882| 2. 352941| 2. 623529| Calculation: The Degree of Productivity|  | 4| 4| 3| 5| 4| 4| 5| 2| 4| 3. 75| 4| 4| 2| 4| 3. 5| 5| 4| 2| 4| 3. 75| 4| 4| 5| 5| 4. 5| 4| 4| 3| 5| 4| 3| 4| 4| 4| 3. 75| 4| 4| 3| 4| 3. 75| 4| 4| 2| 4| 3. 5| 4| 4| 4| 4| 4| 4| 4| 4| 4| 4| 3| 3| 3| 3| 3| 4| 4| 3| 4| 3. 75| 4| 4| 4| 4| 4| 4| 4| 3| 3| 3. 5| 4| 4| 4| 4| 4| 4| 5| 5| 5| 4. 75| 3. 941176| 4. 058824| 3. 294118| 4. 117647| 3. 852941| * Appendix 4: The SPSS Ouput Model Summaryb| Model| R| R Square| Adjusted R Square| Std. Error of the Estimate| 1| . 509a| . 259| -. 078| 1. 64400| a.

Predictors: (Constant), SumDistr, Leeftijd, Status, MateTelewerk, Geslacht| b. Dependent Variable: SumProductiviteit| Coefficientsa| Model| Unstandardized Coefficients| Standardized Coefficients| t| Sig. | | B| Std. Error| Beta| | | 1| (Constant)| 10. 929| 3. 105| | 3. 519| . 005| | MateTelewerk| -1. 311| 1. 749| -. 212| -. 750| . 469| | Geslacht| . 288| 1. 177| . 071| . 244| . 811| | Leeftijd| -. 002| . 052| -. 013| -. 042| . 967| | Status| . 764| . 474| . 448| 1. 613| . 135| | SumDistr| . 188| . 193| . 287| . 972| . 352| a. Dependent Variable: SumProductiviteit| * Bibliography

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