Clarifying the effects of Internet monitoring on job attitudes: The mediating role of employee trust

Information & Management 43 (2006) 894–903 www.elsevier.com/locate/im

Clarifying the effects of Internet monitoring on job attitudes: The mediating role of employee trust G. Stoney Alder a,*, Terry W. Noel b, Maureen L. Ambrose c a

Department of Management, University of Nevada, Las Vegas, 4505 Maryland Parkway, Box 456009, Las Vegas, NV 89154-6009, United States b California State University, Chico, CA, United States c Management Department, University of Central Florida, FL, United States

Received 15 April 2005; received in revised form 28 July 2006; accepted 20 August 2006

Abstract The Internet is a fast growing mechanism for providing workplace monitoring. We examined how its implementation affects employees’ trust in the organization. We hypothesized that giving employees advance notice of monitoring and providing them a justification for it would enhance their trust. We investigated how employees’ perceptions of organizational support prior to monitoring moderated these relationships by conducting a longitudinal field experiment. We found that advance notice and perceived organizational support exerted significant main and interactive effects on post-implementation trust. In turn, trust significantly affected employees’ job satisfaction, organizational commitment, and turnover intentions. # 2006 Elsevier B.V. All rights reserved. Keywords: Internet monitoring; Trust; Perceived organizational support; Job attitudes

In 2001, it was estimated that at least 63% of companies monitor their employees’ Internet connections [8]. More recently, a survey of 840 US companies by the American Management Association showed that 60% now use some type of software to monitor their employees’ incoming and outgoing e-mail, up from 47% in 2001. The growing popularity of Internet and e-mail monitoring is reflected in the exploding market for monitoring software. Forrester Research reported that the industry for monitoring software is growing at a rate of about 30% a year, now about US$ 250–300 million [45]. Although the specifics of monitoring systems differ, Internet systems typically allow employers to track the * Corresponding author. Tel.: +1 702 895 2052; fax: +1 702 895 4370. E-mail address: [email protected] (G.S. Alder). 0378-7206/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.im.2006.08.008

sites an employee accesses and control their access. Although some Internet control systems were originally designed to manage traffic on organizational networks, more recent systems focus on restricting employee access to objectionable sites (e.g., pornographic) or restricting access to a broader range of ‘‘time-wasting’’ non-work sites including gambling, games, and travel. The increase in Internet monitoring has generated considerable debate [24]. Organizations that utilize monitoring cite the need to curtail employee Internet abuse. Although the Internet may potentially boost productivity by enhancing communications, collaboration, and research capabilities, it may also undermine efficiency if employees spend time surfing the web for personal ends. In addition, employee downloading songs and movie trailers can clog corporate networks. Cyberloafing (using Internet access for personal

G.S. Alder et al. / Information & Management 43 (2006) 894–903

purposes during work hours) is a prevalent and pressing issue [27]. Over 60% of workers surf the web at least once a day for personal reasons, according to Cyber Protect [37]. And a Websense [48] survey found that employees admitted spending 1.5 h per week visiting non-work-related web sites in the office. In contrast, HR managers reported that workers spend 8.3 h accessing non-work web sites each week. Websense estimated that Internet misuse costs American corporations more than US$ 85 billion annually in lost productivity. More serious forms of Internet abuse may threaten organizations or expose them to legal liability. Only one employee accessing sexually explicit material can embroil a firm in an expensive lawsuit. A recent FBI survey revealed that 78% of companies found that some of their employees had abused their Internet privileges, such as by downloading pornography or software [26]. According to SexTracker, a service that monitors usage of pornographic web sites, 70% of the traffic on porn sites occurred during office hours [18]. ComScore Networks reported that 37% of Internet-enabled employees in US had visited an ‘‘X-rated’’ web site while at work. In sum, employers use Internet monitoring to discourage productivity loss, avoid legal liability, eliminate downloading of pirated software, protect intellectual property, and preserve bandwidth. Although Internet monitoring may benefit organizations, it raises concerns about employee privacy and micro-management. Some employees feel degraded, stressed, and dehumanized by being closely monitored [9]. As a result, the decision to monitor employees’ Internet activity remains highly emotional and intensely controversial [50]. Many workers’ rights advocates are angered and offended by the trend toward increased Internet monitoring. Arguments voiced by opponents typically focus on several primary concerns about monitoring: 1. It is unfair and abusive. 2. It is like Big Brother, unnecessarily infringing employee rights. 3. It creates an atmosphere of mistrust. As a result, critics contend that the implementation of electronic monitoring has a detrimental effect on employee morale, increases worker stress, and engenders negative job attitudes [25]. Despite the attention Internet monitoring has received, academic research is lacking [13]. In view of the prominent place trust often takes in discussions of Internet monitoring, we argue that this is an important gap in the literature. We therefore examined one type of

895

electronic monitoring: that of employee access to the Internet. Here, we present the results of a field experiment that measured the effect of advance notification, justification, and perceived organizational support on organizational trust following the implementation of Internet monitoring. We also examined the effect of post-monitoring trust on employees’ job attitudes. 1. Internet monitoring and organizational trust Trust influences employee reactions and affects the success and effectiveness of human resource activities. Although research on organizational trust has traditionally focused on its effect on the success of organizational activities, human resource activities may also affect its development. Using exchange theory, Whitener [49] argued that trust was a consequence of the content and process of human resource activities and a mediator of the impact of HR practices on important outcomes. The implementation of Internet monitoring may be a salient event that affects employee trust. Monitoring is mooted as creating an atmosphere of mistrust [32]. Strickland’s [44] classic research indicated that extensive surveillance and monitoring of employees may erode trust. Luhmann [30] adopted a control perspective to explain the relationship between monitoring and trust. He argued that monitoring and trust serve as alternative mechanisms of control. Mayer et al. [33] further suggested that a strong organizational control system may inhibit the development of trust. Previous research found that low trust in terms of expected performance led to increased monitoring [6]. Piccoli and Ives [38] found that organizational monitoring negatively affected trust in virtual teams and that team members more closely monitored teammates that had proven unreliable. Employees may be naturally suspicious of organizations whose actions indicate that management does not trust them. As a result, the implementation of Internet monitoring may have a detrimental effect. However, electronic monitoring research indicates that employees’ behavioral and attitudinal reactions to monitoring depend on a number of factors including the manner in which the organization implements and utilizes the monitoring technology [7]. 2. Model and hypotheses Fig. 1 depicts our model relationships. We expected that perceived organizational support (POS) prior to implementation of monitoring, advance notice, and

896

G.S. Alder et al. / Information & Management 43 (2006) 894–903

Fig. 1. Effects of notice, POS, and justification on organizational trust and employee attitudes.

justification would affect organizational trust following its implementation. We further hypothesized that postimplementation trust mediated the relationship between them and job attitudes. 2.1. Advance notice Silent or covert monitoring, when supervisors monitor employees without informing them, is widespread and may be the most controversial aspect of electronic monitoring. Although many employee advocacy groups favor a complete prohibition against electronic monitoring in the workplace, they contend that as a ‘‘bottom line’’ minimum, companies must give proper notice in advance of any monitoring [36]. In response, US federal laws designed to restrict electronic monitoring do not aim to prohibit monitoring of employees but eliminate secret, covert monitoring [41]. Monitoring research has examined the effect of advanced notice on fairness perceptions: HovorkaMead et al. [23] found that advance notice enhanced the perceived procedural fairness of video monitoring among high school and college student seasonal employees. However, the only empirical study that we found on the effect of advance notice of Internet monitoring saw no relationship between advance notice and perceptions of fairness [4]. This suggests that the focal variables mediating between electronic monitoring and employee attitudes may vary as a function of the system characteristics.

One critical monitoring system characteristic may be its focus; when monitoring focuses exclusively on employee performance, individuals may be concerned about justice and fairness. Performance monitoring will ultimately play a role in how employees are evaluated and thus they are likely to have a keen interest in the fairness of performance monitoring. In contrast, Internet monitoring focuses on aspects of employee behavior that are less directly tied to taskspecific performance. As a result, constructs other than fairness may become salient. We argue that employee trust will be critical and therefore sensitive to variations in the implementation and utilization of Internet monitoring including whether or not advance notice is given. Research indicates that advance notice may enhance post-monitoring trust [15]. Sonnenberg [42] explains this relationship by arguing that employee trust will increase as management conducts HR activities with clear and open communication. Covert, secret monitoring is clearly an antithesis to the open communication critical to establishing and maintaining trust. Critics suggest that open communication with employees about monitoring forestalls litigation and improves employee relations [16]. We predicted: H1. Post-monitoring employee trust will be higher when employees receive advance notice of monitoring than when they are informed of monitoring after the fact.

G.S. Alder et al. / Information & Management 43 (2006) 894–903

2.2. Justification Explanations and justifications can improve reactions to a pay freeze, mitigate the negative impact of layoffs on survivors, increase retention, and foster organizational trust and support. Participants in Hovorka-Mead et al.’s scenario-based laboratory experiment rated video surveillance procedures as fairer when a justification was given. Stanton [43] found justification for monitoring increased the perceived interactional fairness of both traditional and electronic monitoring. We therefore predicted that explanations for Internet monitoring would increase trust. H2. Post-monitoring employee trust will be higher when employees are provided with a justification for monitoring than when they receive no justification. 2.3. Perceived organizational support In addition to monitoring system design and implementation characteristics, employee reactions to monitoring may be influenced by the organizational climate and social context in which the monitoring occurs [2]. We suggest that POS is an important aspect of the organizational context; it describes the quality of employee–organization relationship as indexed by employee perceptions of the extent to which the organization cares about them and values their contribution [10]. Settoon et al. [39] argued that ‘‘positive, beneficial actions directed at employees by the organization and/ or its representatives contribute to the establishment of high-quality exchange relationships that create obligations for employees to reciprocate in positive, beneficial ways.’’ Eisenberger et al. [20] found that POS related positively to employee diligence, commitment, and innovation; they reasoned that trust may explain their findings. They later [21] proposed that POS would influence employees’ interpretation of organizational motives underlying its treatment of employees. Thus, we predicted: H3. Perceived organizational support prior to the implementation of Internet monitoring will be positively related to post-implementation organizational trust. 2.4. Advance notice and justification A number of factors may influence the effectiveness of social accounts [22]. For example, justifications lose their efficacy and may even be counterproductive unless

897

they are deemed sincere and believable [11]. We believed that behavioral integrity, the perception that management’s words align with its deeds, was a critical determinant of the credibility of monitoring justifications. Indeed, word-deed misalignment could seriously undermine trust in organizations [40]. Advance notice and justifications for monitoring are consistent with each other. Providing both justifications and notice may therefore enhance perceived behavioral integrity and post-implementation trust. In contrast, implementing Internet monitoring without notifying employees may be considered a breach of trust: a justification for monitoring may then be viewed with suspicion, considered manipulative, and have little credibility. In sum, we expected an interaction between advance notice and justification and predicted: H4. Notice will moderate the effect of Internet monitoring justifications. Justifications will have a greater effect on post-implementation trust when employees receive advance notice of the monitoring than when they are informed of Internet monitoring after the fact. 2.5. POS and advance notice Alder [3] argued that elements of the organizational culture interact with monitoring system design and implementation features to determine employee attitudes. Consistent with this, we suggested that POS interacted with advance notice. We based this prediction on the group value model [28], which proposes that employees want to feel that they are valued [46]. If they are concerned about their relationship with the organization, then they will evaluate specific procedures and policies in terms of how they feel members are viewed by the organization. In contrast, when individuals feel valued by the company, they become less concerned about the implication of specific procedures. HIGH POS employees probably feel more valued and are more secure in their relationship with the organization than are low ones. Hovorka-Mead et al. proposed that secret monitoring contributes to feelings of unimportance. This may therefore prove particularly troublesome for low POS employees. In contrast, providing advance notice of monitoring may signal that the company values its employees. Thus, we predicted that advance notice would have a greater impact on employees’ attitudes and perceptions of the organization among low POS employees. H5. POS will moderate the effect of advance notice. The enhancing effect of advance notice on

898

G.S. Alder et al. / Information & Management 43 (2006) 894–903

post-implementation trust will be stronger when POS is low than when POS is high. 2.6. Post-implementation trust and job attitudes Blau [12] argued that, ‘‘The establishment of exchange relationships requires others to reciprocate. Since social exchange requires others to reciprocate, the initial problem is to prove oneself trustworthy.’’ Actions that establish and reinforce trust therefore engender an obligation on the part of employees to reciprocate. Indeed, trust is an important predictor of a number of key organizational outcomes including organizational commitment [29], organizational citizenship behavior [47], and employees’ intentions to leave the organization [19]. We expected a similar effect for trust following implementation of Internet monitoring and hypothesized: H6. Employee trust in the organization following the implementation of monitoring will be positively related to job satisfaction and organizational commitment, and negatively related to intentions to quit. 3. Method A longitudinal field experiment was initiated. Employees of a heavy equipment sales and service center were randomly assigned to one of four experimental groups: advanced or post-notice provided and justification given or not. (The experiment grouping was consistent with past practice in the company.) Prior to the implementation of Internet monitoring, we collected information about employees’ attitudes, including their trust in the organization and their perceptions of organizational support. One hundred and eighty-six employees received a survey through the company mail system and 98 (53%) responded before Internet monitoring began. Following this initial survey, the company implemented an Internet monitoring and filtering system. The system, cutting edge artificial intelligence filtering and monitoring software, was used to detect, track, and block access to adult web sites. Employees attempting to access content that the filter deemed inappropriate received a message that the site had been blocked and that they must notify the system administrator if they felt that the blocking was in error. The filtering software had been shown to be over 99% accurate in preimplementation tests. Employees were not consulted before management decided to implement the system.

Two weeks after the implementation of monitoring, employees were sent Survey 2 which again assessed employees’ trust in the organization, etc. Sixty-two employees of the original 98 (63%) responded to the second survey. We included only those employees who responded to both surveys in our analyses. Respondents mailed both surveys directly to the researchers in sealed, preaddressed envelopes. We opted to have respondents reply to the surveys in this manner rather than through the company e-mail or Internet system to alleviate employees’ concerns that the company might monitor electronic responses, 77% of the final 62 respondents were male. The average age of respondents was 41.8 years. Supervisors constituted 34% of respondents, while 66% held non-supervisory positions. The average length of tenure at the company was 9.1 years, while the average tenure in the current department was 6.2 years. Participants in the Advanced Notice condition were informed about Internet monitoring via the company mail system prior to implementation of the system. Two weeks following the implementation of Internet monitoring and just prior to receiving the second survey, employees in the post-notice condition were informed about the monitoring. Justification was manipulated within the notification message. Individuals in the No justification condition were simply informed that an Internet monitoring system was to be implemented (or ‘‘had been’’ for the post-implementation individuals). In the justification condition, a rationale for the implementation of the system was provided. Following the post-notice manipulations, employees’ trust in the organization and organizational attitudes were assessed. 3.1. Perceived organizational support POS was assessed with eight items from Eisenberger et al.’s perceived organizational support scale (Cronbach’s alpha = 0.90). Sample items included, ‘‘My company would forgive an honest mistake on my part’’ and ‘‘My company shows very little concern for me’’ (reverse scored). Table 1 presents scale reliabilities, standard deviations and intercorrelations for all dependent variables. 3.2. Organizational trust Trust was assessed with McAllister’s [34] organizational trust scale (Cronbach’s alpha = 0.86). Sample items included, ‘‘I can confidently use management’s word as the basis for my decisions.’’ and ‘‘The more I

G.S. Alder et al. / Information & Management 43 (2006) 894–903

899

Table 1 Means, standard deviations, and intercorrelations among variables No.

Variable

Mean

S.D.

1

2

3

4

5

1. 2. 3. 4. 5.

POS Post-monitoring trust Job satisfaction Commitment Turnover intentions

5.17 4.79 5.62 4.77 2.70

1.08 1.12 1.09 1.14 1.31

(0.91) 0.77** 0.59** 0.73** 0.50**

(0.91) 0.61** 0.67** 0.55**

(0.85) 0.76** 0.77**

(0.85) 0.81**

(0.91)

Note: scale reliabilities are shown in parentheses on the diagonal. ** p < 0.01.

know about management’s motives, the more cautious I become.’’ 3.3. Job attitudes We used the five-item scale developed by Brayfield and Rothe [14] (Cronbach’s alpha = 0.84) to measure employees’ job satisfaction (e.g., ‘‘I consider my job rather unpleasant’’). We used seven items from Meyer and Allen [35] with a Cronbach’s alpha = 0.78 to assess employees’ organizational affective commitment (e.g., ‘‘This organization has a great deal of personal meaning to me.’’). Finally, turnover intentions were assessed by a five item scale [17] with Cronbach’s alpha = 0.87. A sample item from this scale is, ‘‘I view this job as something I would like to continue doing for the foreseeable future.’’ 3.4. Control variables Employees who frequently used the Internet at work are more affected by the implementation of Internet monitoring than those who used it infrequently. Therefore, we asked participants to report the percentage of time they typically spent per day on both work- and nonwork-related Internet sites. In addition, we were interested in the effects of our independent variables on organizational trust beyond the effects of baseline trust. Therefore, when analyzing the effects of our independent variables, we controlled for Time 1 organizational trust. 3.5. Manipulation checks The efficacies of our manipulations were assessed by asking:  For advance notice, when they had learned about the Internet monitoring system (prior to or following implementation).  For justification, whether management fully explained to them why the company was monitoring Internet connections.

4. Results We conducted ANOVA tests on our manipulation checks. The results indicated the manipulation was successful for advance notice (F = 20.6; p < 0.001). Individuals in the advance notice condition confirmed that they learned about the monitoring system prior to implementation, while the post-notice condition participants learned about it after implementation. Similarly, the manipulation was successful for justification (F = 4.2; p < 0.05). Participants in the justification condition felt that management fully explained to them why the company was implementing an Internet monitoring system whereas those in the no justification condition felt as though they were not given an adequate explanation (means = 4.4 and 3.5, respectively). There has been discussion about the appropriate way of testing mediation. Mackinnon et al. [31] conducted a Monte Carlo simulation to compare 14 methods. Based on their results, they strongly recommend the test of joint significance for experimental investigations involving simple intervening variable models. Using the joint significance test approach, one can conclude mediation occurs when: (1) the independent variable predicts the mediator and (2) the mediator predicts the dependent variable controlling for the independent variables. We followed this approach by conducting two regressions. The first assessed the relationship between advance notice, justification, and POS and post-monitoring organizational trust. To mitigate a concern for multicollinearity, we centered the independent variables (by subtracting the means from the variables) prior to creating the interaction terms [1]. This tested the first condition for mediation and Hypotheses 1–5. The results for this step are shown in Table 2, which provided support for three of our first five hypotheses. As predicted by Hypothesis 1, notice was a significant predictor of organizational trust. Consistent with our third hypothesis, POS prior to monitoring also significantly affected post-monitoring organizational.

900

G.S. Alder et al. / Information & Management 43 (2006) 894–903

Table 2 Multiple regression analysis: the effects of POS, notice, and justification on post-implementation trust in the organization Independent variables

Dependent variable: organizational trust (T2) B

Time on non-workrelated Internet sites Time on work-related Internet sites Organizational trust (T1) POS Notice Justification Notice X justification Notice X POS Justification X POS Constant Multiple R R2

Beta 0.007 (0.02)

0.03

0.004 (0.003)

0.11+

0.41** (0.14) 0.45*** (0.14) 0.29* (0.16) 0.08 (0.17) 0.11 (0.34) S0.33* (0.15) 0.08 (0.15) 2.95*** (0.64) 0.93*** 0.86***

0.43** 0.45*** 0.12* 0.03 0.02 S0.17* 0.04

B, unstandardized regression coefficients (standard errors are in parentheses); Beta, standardized coefficients. * p < 0.05. ** p < 0.01. *** p < 0.001. + p < 0.10.

Consistent with our fifth hypothesis, POS and advance notice interacted to predict organizational trust. However, the results failed to support Hypotheses 2 and 4, as there was no significant main or interaction effect for monitoring justification on post-monitoring trust. We examined the interactions further by splitting POS at the median and conducting post hoc analyses. Fig. 2 graphically depicts the nature of this interaction; when POS prior to the implementation of monitoring was low, providing employees advance notice of

Fig. 2. Advance notice and POS interaction effect on post-monitoring trust.

monitoring enhanced post-monitoring trust such that low POS employees who received advance notice reported higher trust in the organization following the implementation of Internet monitoring than did low POS employees who were informed of monitoring after the fact. In contrast, when POS was high, providing advance notice did not significantly affect postimplementation trust. There was no significant difference in the reported levels of organizational trust among high POS employees who received advance notice of Internet monitoring and those who were informed of monitoring after the fact. This pattern of results supported Hypothesis 5. The second regression assessed the relationship between post-monitoring organizational trust and job attitudes and assessed Hypothesis 6. Table 3 depicts the results of this analysis. The results provided support for Hypothesis 6. Post-monitoring organizational trust was positively related to job satisfaction and organizational commitment and negatively related to employees’ turnover intentions. 5. Discussion Our study examined the effect of advance notice, justification, and POS on employee trust in the organization following the implementation of Internet monitoring. Consistent with our predictions, advance notice and pre-implementation POS affected postimplementation trust. Also as expected, advance notice of monitoring interacted with POS to affect trust. However, contrary to our expectations, there was no effect for monitoring justification on post-monitoring trust. Our predictions regarding the relationship between post-implementation trust and job attitudes were supported. Trust affected employees’ job satisfaction, turnover intentions, and organizational commitment. Our study extends monitoring research by recognizing the importance of trust as a mediator between monitoring implementation characteristics and employee attitudes. Results suggested that post-implementation trust mediates the relationship between implementation characteristics and employees’ job attitudes following the implementation of Internet monitoring. Previous monitoring research suggested that the way monitoring systems are designed and implemented determines their acceptability [5]. In contrast, our study indicated that the effects of monitoring implementation characteristics are not straightforward and that it is not sufficient to examine the presence or absence of certain implementation characteristics. Specifically, our results indicated in the field – where employees have both a

G.S. Alder et al. / Information & Management 43 (2006) 894–903

901

Table 3 Results of multiple regression analyses post-monitoring trust and job attitudes Independent variables

Dependent variable Job satisfaction (Time 2) B

Time on non-workrelated Internet sites Time on work-related Internet sites Post-monitoring trust Constant Multiple R R2

Beta *

S0.05 (0.02)

S0.27

*

Organizational commitment (Time 2)

Turnover intentions (Time 2)

B

B

Beta

Beta

0.002 (0.02)

0.01

0.02 (0.03)

0.08

0.001 (0.004)

0.001

0.002 (0.004)

0.05

0.004 (0.006)

0.11

0.60*** (0.11) 3.17*** (0.53) 0.67*** 0.45***

0.66***

0.72*** (0.11) 1.25* (0.54) 0.74*** 0.54***

0.73***

0.55*** (0.15) 5.12*** (0.75) 0.51** 0.26**

S0.50***

B, unstandardized regression coefficients (standard errors are in parentheses); Beta, standardized coefficients. * p < 0.05. ** p < 0.01. *** p < 0.001.

history and future with the organization – the organizational context (e.g., POS) affects the relationship between the implementation of Internet monitoring and employee attitudes and behaviors. Employees who use the Internet for legitimate business reasons may use search engines and do a considerable amount of surfing with the intent of finding information relevant to their task. In the process, the worker may ‘‘call’’ up a number of web sites with little or no relevance to the problem at hand. As a result, the line between personal and business activity may be blurred for Internet monitoring. Our study suggests several practical implications. Organizational efforts to maintain employee trust will enhance attitudinal reactions to Internet monitoring. One way this may be done is by informing employees prior to implementation of monitoring. The results of our study also indicate that organizations considering the implementation of Internet monitoring may benefit from an organizational climate assessment. If POS is high, then employees will likely respond to the monitoring with favorable attitudes regardless of whether or not they are informed in advance of the monitoring. On the other hand, if POS is low, the implementation of Internet monitoring may erode trust and engender strong negative reactions. However, our results also indicated that advance notice enhanced trust among low POS employees. Therefore, organizational efforts to communicate with employees in advance regarding Internet monitoring may offset the damaging effects of low POS to employee trust. As with all research, this study has some limitations. First, we assessed POS, trust in the organization, and job

attitudes with paper and pencil surveys. This raises the issue of common method variance. However, this is alleviated somewhat by the fact that POS was measured with a different survey at a different point in time than were trust and job attitudes. A second potential limitation concerned whether or not employees in different conditions talked to one another about the monitoring prior to the second survey. Specifically, the effects of advance notice may have been mitigated if employees in the late notice condition learned of it from employees in the advance notice condition. This concern is mitigated by the success of our notice manipulation check. 6. Conclusion Organizations have a number of legitimate reasons to monitor their employees’ Internet activities. At the same time, there are valid concerns regarding the impact of Internet monitoring on employee attitudes and behaviors. Therefore, a critical task facing organizations and researchers is to identify the factors that improve employees’ attitudinal and behavioral reactions to Internet monitoring. Consistent with previous work, our study suggested that the implementation of monitoring systems played an important role in employee reactions to the system. However, the relationship was more complex than previously conceived. Implementation characteristics interacted with the broader organizational context to determine individuals’ reactions to Internet monitoring. The prevailing level of support workers believe that they receive from management and specific implementation characteristics combine to influence employee reactions.

902

G.S. Alder et al. / Information & Management 43 (2006) 894–903

References [1] L. Aiken, S. West, Multiple Regression: Testing and Interpreting Interactions, Sage Publications, Newbury Park, CA, 1991. [2] J.R. Aiello, Computer-based work monitoring: electronic surveillance and its effects, Journal of Applied Social Psychology 23, 1993, pp. 499–507. [3] G.S. Alder, Employee reactions to electronic performance monitoring: a consequence of organizational culture, Journal of High Technology Management Research 12, 2001, pp. 323–342. [4] G.S. Alder, M.L. Ambrose, T.W. Noel, The effects of formal advance notice and justification on Internet monitoring fairness: much ado about nothing? Journal of Leadership and Organizational Studies 13, 2006, pp. 93–107. [5] B.J. Alge, Effects of computer surveillance on perceptions of privacy and procedural justice, Journal of Applied Psychology 86, 2001, pp. 797–804. [6] B.J. Alge, G.A. Ballinger, S.G. Green, Remote control, Personnel Psychology 57, 2004, pp. 377–410. [7] M.L. Ambrose, G.S. Alder, Designing, implementing, and utilizing computerized performance monitoring: enhancing organizational justice, in: G. Ferris (Ed.), Research in Personnel and Human Resource Management, JAI Press, Greenwich, 2000, pp. 187–220. [8] American Management Association, AMA Survey Workplace Monitoring & Surveillance, 2001. [9] S.S. Ariss, Computer monitoring: benefits and pitfalls facing management, Information & Management 39, 2002, pp. 553–558. [10] S. Aryee, P.S. Budhwar, X.C. Chen, Trust as a mediator of the relationship between organizational justice and work outcomes: test of a social exchange model, Journal of Organizational Behavior 23, 2002, pp. 267–285. [11] R.J. Bies, D.L. Shapiro, L.L. Cummings, Causal accounts and managing organizational conflict: is it enough to say it’s not my fault? Communication Research 15, 1988, pp. 381–399. [12] P.M. Blau, Exchange and Power in Social Life, Wiley, New York, 1964. [13] S. Boehle, They’re watching you, Training 37, 2000, pp. 68–72. [14] A.H. Brayfield, H.F. Rothe, An index of job satisfaction, Journal of Applied Psychology 35, 1951, pp. 307–311. [15] J.K. Butler Jr., Toward understanding and measuring conditions of trust: evolution of a conditions of trust inventory, Journal of Management 17, 1991, pp. 643–683. [16] N.B. Casarez, Electronic mail and employee relations: why privacy must be, Public Relations Quarterly 37 (2), 1992, pp. 37–39. [17] J. Chalykoff, T.A. Kochan, Computer-aided monitoring: its influence on employee job satisfaction and turnover, Personnel Psychology 42, 1989, pp. 807–834. [18] D.E. Corbin, Keeping a virtual eye on employees, Occupational Health & Safety 69, 2000, pp. 24–28. [19] R.D. Costigan, S.S. Itler, J.J. Berman, A multi-dimensional study of trust in organizations, Journal of Managerial Issues 10, 1998, pp. 303–317. [20] R. Eisenberger, P. Fasolo, V. Davis-LaMAstro, Perceived organizational support and employee diligence, commitment, and innovation, Journal of Applied Psychology 75, 1990, pp. 51–59. [21] R. Eisenberger, R. Huntington, S. Hutchison, D. Sowa, Perceived organizational support, Journal of Applied Psychology 71, 1986, pp. 500–507. [22] J. Greenberg, Looking fair vs. being fair: managing impressions of organizational justice, Research in Organizational Behavior 12, 1990, pp. 111–157.

[23] A.D. Hovorka-Mead, W.H. Ross, T. Whipple, M.B. Renchin, Watching the detectives: seasonal student employee reactions to electronic monitoring with and without advance notification, Personnel Psychology 55, 2002, pp. 329–362. [24] A. Inam, Big brother is here, Global Finance 14, 2000, p. 31. [25] C.L. Kemper, Big brother, Communication World 18, 2000, pp. 8–12. [26] J. Krim, Firms curbing employees’ web access, Washington Post (March), 2003, p. A01. [27] V.K.G. Lim, T.H.S. Teo, Prevalence, perceived seriousness, justification and regulation of cyberloafing in Singapore: an exploratory study, Information & Management 42, 2005, pp. 1081–1093. [28] E.A. Lind, T.R. Tyler, The Social Psychology of Procedural Justice, Plenum, New York, 1988. [29] T.K. Liou, Understanding employee commitment in the public organization: a study of the juvenile detention center, International Journal of Public Administration 18, 1995, pp. 1269–1295. [30] N. Luhmann, Trust and Power, Stanford University Press, Stanford, CA, 1979. [31] D.P. Mackinnon, C.M. Lockwood, J.M. Hoffman, S.G. West, V. Sheets, A comparison of methods to test mediation and other intervening variable effects, Psychological Methods 7, 2002, pp. 83–104. [32] R.C. Manning, Liberal and communitarian defenses of workplace privacy, Journal of Business Ethics 6, 1997, pp. 817–823. [33] R.C. Mayer, J.H. Davis, F.D. Schoorman, An integrative model of organizational trust, Academy of Management Review 20, 1995, pp. 709–734. [34] D. McAllister, Cynicism at work: the social dynamics of extreme distrust in organizations, Paper Presented at the Annual National Academy of Management Meetings, Chicago, Illinois, 1999. [35] J.P. Meyer, N. Allen, Testing the ‘‘side bet theory’’ of organizational commitment: some methodological considerations, Journal of Applied Psychology 69, 1984, pp. 372–378. [36] National Workrights Institute, Electronic monitoring in the workplace. http://www.workrights.org/issue_electronic/em_legislative_brief.html, accessed December 14, 2004. [37] New Media Age, Three-fifths of employees do personal surfing at work, November 27, 2003, p. 14. [38] G. Piccoli, B. Ives, Trust and the unintended effects of behavior control in virtual teams, MIS Quarterly 27, 2003, pp. 365–395. [39] R.P. Settoon, N. Bennett, R.C. Liden, Social exchange in organizations: perceived organizational support, leader-member exchange and employees reciprocity, Journal of Applied Psychology 81, 1996, pp. 219–227. [40] T. Simons, Behavioral Integrity: the perceived alignment between managers’ words and deeds as a research focus, Organization Science 13, 2002, pp. 18–35. [41] D. Simpson, Shadowing cyberslackers, Federal Computer Week 22, 2000, http://www.fcw.com/civic/articles/2000/oct/civ-shadow-10-00.asp, accessed December 22, 2004. [42] F. Sonnenberg, Trust me, trust me not, Industry Week 242 (August (16)), 1993, pp. 22–26. [43] J.M. Stanton, Traditional and electronic monitoring from an organizational justice perspective, Journal of Business and Psychology 15, 2000, pp. 129–148. [44] L.H. Strickland, Surveillance and trust, Journal of Personality 26, 1958, pp. 200–215. [45] P.W. Tam, E. White, N. Wingfield, K. Maher, Snooping email by software is now a workplace norm, Wall Street Journal (March), 2005, p. B1.

G.S. Alder et al. / Information & Management 43 (2006) 894–903

903

Review, Journal of Business Ethics, and the Journal of High Technology Management Research among others.

[46] T.R. Tyler, E.A. Lind, A relational model of authority in groups, in: M. Zanna (Ed.), Advances in Experimental Social Psychology, vol. 24, Academic Press, New York, 1992, pp. 115–192. [47] L. Van Dyne, D. Vandewalle, T. Kostova, M.E. Latham, L.L. Cummings, Collectivism, propensity to trust and self-esteem as predictors of organizational citizenship in a non-work setting, Journal of Organizational Behavior 21, 2000, pp. 3–23. [48] Websense, Workplace Web Abuse Costs Corporate America $85 Billion This Year, Reports Websense Inc., accessed via Internet on March 2, 2005 at http://www.websense.com/company/news/ pr/Display.php?Release=02111267. [49] E.M. Whitener, The impact of human resource activities on employee trust, Human Resource Management Review 7, 1997, pp. 389–404. [50] E. Zimmerman, HR must know when employee surveillance crosses the line, Workforce 81 (2), 2002, pp. 38–45.

Terry W. Noel is associate professor of management at California State University, Chico. He teaches classes in entrepreneurship and manages the Center for Entrepreneurship. Dr. Noel’s work has been published in such places as The Academy of Management Journal, the Journal of Management Education, and the Journal of Entrepreneurship Education. His research focuses on the process of entrepreneurial learning and how entrepreneurial thinking can benefit both start ups and established organizations. He also does research in the field of employee reactions to computer monitoring.

G. Stoney Alder is assistant professor of management in the College of Business at the University of Nevada, Las Vegas. He received his PhD from the University of Colorado at Boulder. His research interests include organizational justice and electronic monitoring. Dr. Alder’s work has appeared in a number of journals including Organizational Behavior and Human Decision Processes, Human Resource Management

Maureen L. Ambrose is professor of management in the College of Business at the University of Central Florida. She received her PhD from the University of Illinois at Urbana-Champaign. Dr. Ambrose’s research interests include organizational justice, electronic monitoring, employee deviance and ethics. Her work on electronic monitoring has appeared in several leading management journals.