The Effect of Internet Browsing on Librarians' Job Performance: The Mediating Role of Employees' Job Attitudes and the Moderating Role of Conscientiousness

Aghighi, Alireza; Biglari, Razieh

doi:10.22055/slis.2026.52168.2017

The Effect of Internet Browsing on Librarians' Job Performance: The Mediating Role of Employees' Job Attitudes and the Moderating Role of Conscientiousness

Document Type : Original Article

Authors

Alireza Aghighi ¹

Razieh Biglari ²

¹ Assistant Professor, Department of Management, Payame Noor University ,Tehran ,Iran.

² 2. Master's degree, Department of Management, Faculty of Management, Payame Noor University, Tehran, Iran.

https://doi.org/10.22055/slis.2026.52168.2017

Abstract

Background and Objectives: In today's IT-based workplaces, effective use of IT systems is crucial for enhancing user performance (Badda & Rahmouni, 2023). However, the inherent complexity of these systems can significantly affect how users interact with technology and, ultimately, their productivity (Verna et al., 2023). Perceived complexity refers to users' perceptions of the difficulty associated with understanding and using technology (Te'eni, 1989). Perceived IT complexity commonly occurs in organizational contexts characterized by distributed work environments, complex network structures, software projects involving multiple roles and interactions, high dependencies between subsystems, a diversity and multiplicity of applications, and changing and complex business needs (Storm & Scheepers, 2019). According to Stoica et al. (2024), organizations with networked structures, numerous applications, and high dependencies among IT components experience higher levels of perceived complexity. Accordingly, working across different locations and within distributed teams may further increase users' perceptions of IT complexity. Despite considerable attention to IT complexity and its potential consequences in previous research, the mechanisms through which perceived IT complexity translates into actual user performance have not yet been fully understood (Badda & Rahmouni, 2023). One potentially important mechanism is the frequency of information system use. While previous studies have examined system quality, service quality, user satisfaction, and performance, the mediating role of frequency of use in the relationship between perceived information system complexity and user performance requires further investigation. The existing evidence also suggests a complex relationship between these variables. On the one hand, perceived system complexity may discourage repeated use and consequently limit the development of users' skills and effective performance. On the other hand, frequent system use may increase users' familiarity with technology and thereby reduce some of the negative consequences associated with perceived complexity. Thus, frequency of use may serve as an important mechanism linking perceived complexity to user performance. Understanding this relationship is particularly important in educational organizations that rely on multiple information systems. Shahid Chamran University of Ahvaz, as one of the major universities in Iran, employs numerous information systems to support educational, research, student, cultural, financial, administrative, and knowledge-related activities. This multiplicity of systems may increase users' perceived complexity and influence their performance. Therefore, the present study aimed to investigate the effect of perceived IT complexity on the performance of users at Shahid Chamran University of Ahvaz, with particular emphasis on the mediating role of frequency of information system use.
Methodology: This study was applied in terms of purpose and employed a survey method with a causal-correlational approach to examine the relationships among the independent, dependent, and mediating variables. The statistical population consisted of 1,503 users of information systems at Shahid Chamran University of Ahvaz. Based on the criterion of 15 respondents per questionnaire item, the required sample size was estimated at 420 participants. Participants were selected using convenience sampling. Of the distributed questionnaires, 286 completed questionnaires were considered valid and included in the final analysis. The collected data were analyzed using SmartPLS software to examine the direct and indirect relationships among perceived IT complexity, frequency of information system use, and user performance.
Findings: The results showed that the mean score of perceived IT complexity was 3.33, indicating that users perceived the university's information technologies and information systems as moderately complex. This level of perceived complexity suggests that difficulties associated with understanding and using the systems may interfere with their effective utilization.
The hypothesis-testing results showed that perceived IT complexity had a negative effect on the performance of users at Shahid Chamran University of Ahvaz. A negative and significant relationship was observed between perceived complexity and user performance (reported coefficient = -0.221). Thus, higher levels of perceived complexity were associated with lower levels of user performance.
The results also showed that perceived IT complexity had a significant negative effect on the frequency of users' use of university information systems (β = -0.533). In other words, as users perceived information systems to be more complex, the frequency with which they used those systems decreased. This finding suggests that complexity may discourage continued interaction with information systems and consequently limit opportunities for users to develop familiarity and proficiency.
Furthermore, the analysis of the mediating relationship showed that perceived IT complexity had a significant negative indirect effect on user performance through frequency of information system use. The reported t-value for the indirect effect was 7.34, exceeding the critical value of 1.96 and indicating statistical significance at the 0.05 level. These findings demonstrate that frequency of use plays a significant mediating role in the relationship between perceived IT complexity and user performance. Accordingly, perceived complexity not only affects performance directly but may also reduce performance indirectly by decreasing users' frequency of interaction with information systems.
Discussion: The findings indicate that perceived IT complexity is an important factor affecting both the frequency of information system use and user performance. As users perceive organizational information systems to be more complex, they tend to use them less frequently, which in turn may negatively affect their performance. The significant mediating role of frequency of use highlights the importance of continuous interaction with information systems in reducing some of the adverse consequences associated with perceived complexity.
Therefore, improving the usability and simplicity of university information systems, reducing unnecessary complexity, enhancing integration among different systems, and providing appropriate user training may encourage more frequent system use and contribute to improved user performance. These findings can assist university managers and information system designers in developing more user-centered systems and improving the effective use of information technology in academic environments.

Keywords

Cyberloafing

Job Performance

Employees'

Job Attitudes

Conscientiousness

Subjects

Public Libraries

Abbasi, G. A., Jagaveeran, M., Goh, Y. N., & Tariq, B. (2021). The impact of type of content use on smartphone addiction and academic performance: Physical activity as moderator. Technology in Society, 64, 101521. https://doi.org/10.1016/j.techsoc.2020.101521

Agarwal, U. A. (2019). Impact of supervisors’ perceived communication style on subordinate’s psychological capital and cyberloafing. Australasian Journal of Information Systems, 23. https://doi.org/10.3127/ajis.v23i0.1765

Aidla, A., Irs, R., & Türk, K. (2012). Creating innovation in the education sector: Policy implications. In Innovation systems in small catching-up economies: New perspectives on practice and policy (pp. 371-388). Springer New York. https://link.springer.com/chapter/10.1007/978-1-4614-1548-0_19

Aitken, J. A., Baines, J. I., Wonders, M. E., Kaplan, S. A., & Clark, J. E. (2026). A meta-analytic review of the within-person relationship between affect and job performance. Journal of Organizational Behavior. Advance online publication. https://doi.org/10.1002/job.70035

Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918. https://doi.org/10.1037/0033-2909.84.5.888

Alfes, K., Shantz, A. D., Truss, C., & Soane, E. C. (2013). The link between perceived human resource management practices, engagement and employee behaviour: A moderated mediation model. The International Journal of Human Resource Management, 24(2), 330–351. https://doi.org/10.1080/09585192.2012.679950

Anandarajan, M., Simmers, C., & Igbaria, M. (2000). An exploratory investigation of the antecedents and impact of internet usage: An individual perspective. Behaviour & Information Technology, 19(1), 69-85. https://doi.org/10.1080/014492900118803

Andel, S. A., Kessler, S. R., Pindek, S., Kleinman, G., & Spector, P. E. (2019). Is cyberloafing more complex than we originally thought? Cyberloafing as a coping response to workplace aggression exposure. Computers in Human Behavior, 101, 124-130. https://doi.org/10.1016/j.chb.2019.07.013

Artistico, R., & Rothenberg, A. M. (2013). Assessing strengths and weaknesses in solving work problems: A Knowledge and Appraisal Personality Architecture (KAPA) analysis of the trait conscientiousness and self-efficacy. International Journal of Psychological Studies, 5(3), 84. https://doi.org/10.5539/ijps.v5n3p84

Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: a meta‐analysis. Personnel Psychology, 44(1), 1–26. https://doi.org/10.1111/j.1744-6570.1991.tb00688.x

Barringer, B. R., & Ireland, R. D. (2010). Entrepreneurship: Successfully launching new ventures (3rd ed.). Pearson Education. https://search.worldcat.org/title/26856260

Bennett, R. J., & Robinson, S. L. (2003). The past, present, and future of workplace deviance research. In Organizational Behavior: The State of the Science (2nd ed.). Lawrence Erlbaum Associates.

Blanchard, A. L., & Henle, C. A. (2008). Correlates of different forms of cyberloafing: The role of norms and external locus of control. Computers in Human Behavior, 24(3), 1067–1084. https://doi.org/10.1016/j.chb.2007.03.008

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen and J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage. https://www.scirp.org/reference/ReferencesPapers?ReferenceID=213477

Çınar, O., & Karcıoğlu, F. (2015). The relationship between cyber loafing and organizational citizenship behavior: A survey study in Erzurum/Turkey. Procedia-Social and Behavioral Sciences, 207, 444-453. : https://www.sciencedirect.com/science/article/pii/S1877042815052477

Costa Jr, P. T., McCrae, R. R., & Dye, D. A. (1991). Facet scales for agreeableness and conscientiousness: A revision of the NEO Personality Inventory. Personality and Individual Differences, 12(9), 887-898. https://doi.org/10.1016/0191-8869(91)90177-D

Craighead, C. W., Hult, G. T. M., & Ketchen Jr, D. J. (2009). The effects of innovation–cost strategy, knowledge, and action in the supply chain on firm performance. Journal of operations management, 27(5), 405-421. 10.1016/j.jom.2009.01.002

Farrington, S. M. (2012). Does personality matter for small business success? South African Journal of Economic and Management Sciences, 15(4), 382–401. https://doi.org/10.4102/sajems.v15i4.243

Gholipor, R., Vaezi, S. K., & Karimi, M. (2026). Providing a comprehensive model to control and reduce cyberloafing in organizations. Public Organizations Management, 14(2), 1-20. https://doi.org/10.30473/ipom.2026.74401.5178

Hu, Y., Chen, Y., & Ye, M. (2023). Eager to belong: Social cyberloafing as a coping response to workplace ostracism. Current Psychology, 42(4), 3372-3381. https://doi.org/10.1007/s12144-021-01690-y

Hurtz, G. M., & Donovan, J. J. (2000). Personality and job performance: The Big Five revisited. Journal of Applied Psychology, 85(6), 869–879. https://doi.org/10.1037/0021-9010.85.6.869

Jandaghi, G., Alvani, S. M., Zarei Matin, H., & Fakheri Kozekanan, S. (2015). Cyberloafing management in organizations. Iranian Journal of Management Studies, 8(3), 335-349. https://doi.org/10.22059/ijms.2015.54007

Karatepe, S., & Güngör, M. (2017). Organizational identification and cyberloafing: A research on public employees. ASSAM International Refereed Journal, 4(9), 79-93. http://yerbilimleri.cumhuriyet.edu.tr/en/pub/assam/issue/33151/349932

Kazemi, J., & Saeidian, N. (2025). The relationship between cognitive absorption, internet addiction and job dissatisfaction with cyberloafing among employees of Isfahan University of Medical Sciences. Journal of Isfahan Medical School, 42(799), 1215-1222. https://doi.org/10.48305/jims.v42.i799.1215

Khoorzaman, B. A., Esfahani Nia, A., Bay, N., & Ghorbani, S. (2025). The role of workplace ostracism on cyberloafing behavior with mediating role of emotional exhaustion in employees of Sports and Youth departments in Golestan province. Industrial and Organizational Psychology Studies. (in press). https://doi.org/10.22055/jiops.2025.47989.1435

Koay, K. Y., & Soh, P. C. H. (2018). Should cyberloafing be allowed in the workplace? Human Resource Management International Digest, 26(7), 4–6. https://doi.org/10.1108/HRMID-05-2018-0107

Koay, K. Y., & Soh, P. C. H. (2019). Does cyberloafing really harm employees’ work performance? An overview. In Proceedings of the Twelfth International Conference on Management Science and Engineering Management (pp. 901-912). Springer International Publishing. https://doi.org/10.1007/978-3-319-93351-1_71

Kularathne, H. M. R. D., & Senevirathne, Y. Y. (2021). Does cyberloafing adversely effect to employee performance? Asian Journal of Social Science and Management Technology, 3(2), 1–6. https://ajssmt.com/Papers/320106.pdf?utm_source=chatgpt.com

Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer Publishing Company.

Liao, C. W., Lu, C. Y., Huang, C. K., & Chiang, T. L. (2012). Work values, work attitude and job performance of green energy industry employees in Taiwan. African Journal of Business Management, 6(15), 5299–5318. https://doi.org/10.5897/ajbm11.1449

Liberman, B., Seidman, G., McKenna, K. Y., & Buffardi, L. E. (2011). Employee job attitudes and organizational characteristics as predictors of cyberloafing. Computers in Human Behavior, 27(6), 2192–2199. https://doi.org/10.1016/j.chb.2011.06.015

Lim, P. K., Koay, K. Y., & Chong, W. Y. (2021). The effects of abusive supervision, emotional exhaustion and organizational commitment on cyberloafing: a moderated-mediation examination. Internet Research, 31(2), 497–518. https://doi.org/10.1108/INTR-03-2020-0165

Lim, V. K., & Chen, D. J. (2012). Cyberloafing at the workplace: gain or drain on work? Behaviour & Information Technology, 31(4), 343–353. https://doi.org/10.1080/01449290903353054

Lim, V., & Chen, D. (2009). Browsing and emailing: Impact of cyberloafing on work attitudes. 23rd Australia and New Zealand Academy of Management (ANZAM) Conference, Melbourne, Australia.

Linz, S. J., & Semykina, A. (2008). How do workers fare during transition? Perceptions of job insecurity among Russian workers, 1995–2004. Labour Economics, 15(3), 442-458. https://ideas.repec.org/a/eee/labeco/v15y2008i3p442-458.html

Luo, X., Xu, F., Zhang, J., Xiao, S., & Xue, B. (2022). Effects of organizational controls on employees' cyber-loafing: The moderating effects of trait mindfulness. ACM SIGMIS Database, 53(1), 61-79. https://dl.acm.org/doi/10.1145/3514097.3514102

Martin, A. (2010). Individual and contextual correlates of managers' attitudes toward depressed employees. Human Resource Management, 49(4), 647-668. https://scite.ai/reports/individual-and-contextual-correlates-of-9ZL8M9

Mercado, B. K., & Dilchert, S. (2017). Family interference with work and its relationship with organizational citizenship and counterproductive work behaviors. International Journal of Selection and Assessment, 25(4), 406-415. https://www.semanticscholar.org/paper/1db3eab5a92d215a096ad76146a8655d24b86c4a

Moody, G. D., & Siponen, M. (2013). Using the theory of interpersonal behavior to explain non-work-related personal use of the Internet at work. Information & Management, 50(6), 322–335. https://doi.org/10.1016/j.im.2013.04.005

Moradzadeh, A., & Arab, A. (2025). Antecedents and consequences of cyberloafing in Iranian government organizations: A meta-analysis approach. Organizational Behavior Studies, e729092. https://obs.sinaweb.net/article_729092.html?lang=en

Nusrat, A., He, Y., Luqman, A., Waheed, A., & Dhir, A. (2021). Enterprise social media and cyber-slacking: A Kahn’s model perspective. Information & Management, 58(1), 103405. https://doi.org/10.1016/j.im.2020.103405

Olajide, O., Abdu, M., & Abdul-Qarir, A. B. (2018). Effect of cyberloafing on employee performance among deposit money banks in Kaduna metropolis. Management and Social Sciences (OJAMSS), 3(1), 27-37.

Oswalt, B., Elliott-Howard, F., & Austin, S. F. (2003). Cyberslacking—Legal and ethical issues facing IT managers. Issues in Information Systems, 4(1), 646-652.

Rahimi, S., Sedighi, H., & Moradi, M. (2023). The relationship between information literacy with organizational creativity and job performance of public librarians in Kermanshah province. Knowledge Retrieval and Semantic Systems. https://doi.org/10.22054/jks.2023.71482.1554

Rahimi, S., Soheily, F., Zarei, H., & Rahimi, F. (2024). The relationship between organizational citizenship behavior and organizational performance of librarians. Journal of Knowledge-Research Studies, 2(4), 83-96. https://doi.org/10.22034/jkrs.2024.59782.1054

Sampat, B., & Basu, P. A. (2017). Cyberloafing: The disguised digital way of loafing on the job. IUP Journal of Organizational Behavior, 16(1), 19-37.

Sheikh, A., Aghaz, A., & Mohammadi, M. (2019). Cyberloafing and personality traits: an investigation among knowledge-workers across the Iranian knowledge-intensive sectors. Behaviour & Information Technology, 38(12), 1213–1224. https://doi.org/10.1080/0144929X.2019.1585477

Sulaiman, W. S. W., Almsafir, M. K., & Ahmad, Z. A. (2013). Job performance: Relationship between competency and attitude towards achieving TNB’s vision. Journal of Advanced Social Research, 3(1), 1-11. https://www.semanticscholar.org/paper/5c2478604be1859993c00aede7bdef49e3422153

Vandenabeele, W. (2009). The mediating effect of job satisfaction and organizational commitment on self-reported performance: more robust evidence of the PSM—performance relationship. International Review of Administrative Sciences, 75(1), 11-34. https://www.semanticscholar.org/paper/07b2e15a68e9bf11796342752ce1aac73165c694

Weatherbee, T. G. (2010). Counterproductive use of technology at work: Information & communications technologies and cyberdeviancy. Human Resource Management Review, 20(1), 35–44. https://doi.org/10.1016/j.hrmr.2009.03.012

Webster, J. R., Beehr, T. A., & Christiansen, N. D. (2010). Toward a better understanding of the effects of hindrance and challenge stressors on work behavior. Journal of Vocational Behavior, 76(1), 68-77. https://eric.ed.gov/?id=EJ872577

Weiss, H. M., & Cropanzano, R. (1996). Affective events theory. Research in Organizational Behavior, 18(1), 1-74. https://www.semanticscholar.org/paper/4c6ebd49cb8413978e11a2e3a3eaba93ec0e9f98

Widiastuti, R., & Margaretha, M. (2016). Personality factors and cyberloafing of college students in Indonesia. International Journal of Applied Business and Economic Research, 14(13), 9227–9238.

Williams, L. J., & Anderson, S. E. (1991). Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. Journal of Management, 17(3), 601–617. https://doi.org/10.1177/014920639101700305

Yu, L., Cao, X., Liu, Z., & Wang, J. (2018). Excessive social media use at work: Exploring the effects of social media overload on job performance. Information Technology & People, 31(6), 1091–1112. https://doi.org/10.1108/ITP-10-2016-0239

Yu, L., Zhong, Y., Sun, Y., & Qin, G. (2022). The impact of excessive social media use at work: a usage experience–stressor–strain perspective. Behaviour & Information Technology, 1–20. https://doi.org/10.1080/0144929X.2022.2149418