The Effect of Corporate Application Use on Employee Productivity with Employee Performance as a Mediating Variable
Keywords:
corporate application use, employee performance, employee productivity, digitalization
Abstract
This study examines the effect of corporate application use on employee productivity and the mediating role of employee performance. A quantitative survey was conducted among employees who use corporate applications in their work, and the data were analyzed using regression/path analysis and bootstrapping. The results indicate that corporate application use has a positive direct effect on productivity (β = 0.319, p < 0.001) and a positive effect on employee performance (β = 0.497, p = 0.001). Employee performance also has a positive effect on productivity (β = 0.389, p < 0.001). The indirect effect of corporate application use on productivity through employee performance is 0.193, with a 95% confidence interval of [0.089, 0.321], indicating a significant mediation effect. These findings suggest that the benefits of corporate applications may be strengthened when their use is accompanied by support for employee performance.
The findings indicate that corporate application use is associated with higher employee productivity both directly and indirectly through employee performance. The results highlight the importance of supporting employees in using workplace applications effectively.
References
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MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99–128. https://doi.org/10.1207/s15327906mbr3901_4
Mangkunegara, A. A. P. (2017). Manajemen sumber daya manusia perusahaan [Corporate human resource management] (14th ed.). PT Remaja Rosdakarya.
Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322. https://doi.org/10.2307/25148636
Muzakki, M. H., Susilo, H., & Yuniarto, S. R. (2016). Pengaruh penggunaan teknologi informasi terhadap kinerja karyawan [The effect of information technology use on employee performance]. Jurnal Administrasi Bisnis, 39(2), 8–14. http://administrasibisnis.studentjournal.ub.ac.id/index.php/jab/article/view/1561
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Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879
Rucker, D. D., Preacher, K. J., Tormala, Z. L., & Petty, R. E. (2011). Mediation analysis in social psychology: Current practices and new recommendations. Social and Personality Psychology Compass, 5(6), 359–371. https://doi.org/10.1111/j.1751-9004.2011.00355.x
Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological Methods, 7(4), 422–445. https://doi.org/10.1037/1082-989X.7.4.422
Suhartini, E., & Nurariansyah, I. (2021). Pengaruh teknologi informasi terhadap kinerja pegawai dengan kepuasan kerja sebagai variabel mediasi pada Kantor Wilayah Badan Pertanahan Nasional Provinsi Sulawesi Selatan [The effect of information technology on employee performance with job satisfaction as a mediating variable at the South Sulawesi Provincial Office of the National Land Agency]. Study of Scientific and Behavioral Management, 2(2), 1–15. https://doi.org/10.24252/ssbm.v2i2.21822
Sulistya, R. D., & Zain, D. (2020). Pemanfaatan teknologi informasi dan produktivitas kerja karyawan [The utilization of information technology and employee work productivity]. Jurnal Ilmu Manajemen dan Akuntansi Terapan, 11(1), 78–91. https://jurnal.stietotamaktar.ac.id/index.php/jimat
Tarafdar, M., Cooper, C. L., & Stich, J.-F. (2019). The technostress trifecta—Techno eustress, techno distress and design: Theoretical directions and an agenda for research. Information Systems Journal, 29(1), 6–42. https://doi.org/10.1111/isj.12169
Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328. https://doi.org/10.2753/MIS0742-1222240109
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/j.lrp.2018.12.001
Zhao, X., Lynch, J. G., Jr., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37(2), 197–206. https://doi.org/10.1086/651257
Zhou, Y., Lyu, Y., & Li, Z. (2025). Digital transformation and labor productivity: Evidence from Chinese enterprises. PLOS ONE, 20(1), Article e0312456. https://doi.org/10.1371/journal.pone.0312456
Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196. https://doi.org/10.2307/3250983
Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471–482. https://doi.org/10.25300/MISQ/2013/37:2.3
Brynjolfsson, E., & Hitt, L. M. (2000). Beyond computation: Information technology, organizational transformation and business performance. Organization Science, 11(4), 449–466. https://doi.org/10.1287/orsc.11.4.449.14692
Campbell, J. P., & Wiernik, B. M. (2015). The modeling and assessment of work performance. Annual Review of Organizational Psychology and Organizational Behavior, 2, 47–74. https://doi.org/10.1146/annurev-orgpsych-032414-111427
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Ghozali, I. (2018). Aplikasi analisis multivariete dengan program IBM SPSS 25 [Multivariate analysis applications with the IBM SPSS 25 program] (9th ed.). Badan Penerbit Universitas Diponegoro.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213–236. https://doi.org/10.2307/249689
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hanelt, A., Bohnsack, R., Marz, D., & Antunes Marante, C. (2021). A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change. Journal of Management Studies, 58(5), 1159–1197. https://doi.org/10.1111/joms.12639
Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76(4), 408–420. https://doi.org/10.1080/03637750903310360
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8
Humaidi, N., & Harjanto, A. (2022). Pengaruh penggunaan aplikasi digital terhadap produktivitas pegawai [The effect of digital application use on employee productivity]. Transpublika: Jurnal Administrasi Publik, 3(1), 45–56. https://transpublika.co.id/ojs/index.php/Transpublika
Judge, T. A., Thoresen, C. J., Bono, J. E., & Patton, G. K. (2001). The job satisfaction–job performance relationship: A qualitative and quantitative review. Psychological Bulletin, 127(3), 376–407. https://doi.org/10.1037/0033-2909.127.3.376
Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., Schaufeli, W. B., de Vet, H. C. W., & van der Beek, A. J. (2011). Conceptual frameworks of individual work performance: A systematic review. Journal of Occupational and Environmental Medicine, 53(8), 856–866. https://doi.org/10.1097/JOM.0b013e318226a763
Koopmans, L., Bernaards, C. M., Hildebrandt, V. H., de Vet, H. C. W., & van der Beek, A. J. (2014). Measuring individual work performance: Identifying and selecting indicators. Work, 48(2), 229–238. https://doi.org/10.3233/WOR-131659
Kusuma, D. A., & Prayogi, I. (2022). Efektivitas penggunaan aplikasi digital dalam meningkatkan kinerja pegawai [The effectiveness of using digital applications in improving employee performance]. Transekonomika: Akuntansi, Bisnis dan Keuangan, 2(3), 109–122. https://transekonomika.com/
Leonardi, P. M. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly, 35(1), 147–167. https://doi.org/10.2307/23043493
MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99–128. https://doi.org/10.1207/s15327906mbr3901_4
Mangkunegara, A. A. P. (2017). Manajemen sumber daya manusia perusahaan [Corporate human resource management] (14th ed.). PT Remaja Rosdakarya.
Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322. https://doi.org/10.2307/25148636
Muzakki, M. H., Susilo, H., & Yuniarto, S. R. (2016). Pengaruh penggunaan teknologi informasi terhadap kinerja karyawan [The effect of information technology use on employee performance]. Jurnal Administrasi Bisnis, 39(2), 8–14. http://administrasibisnis.studentjournal.ub.ac.id/index.php/jab/article/view/1561
Ozimek, A. (2020). The future of remote work. Upwork Research Institute. https://www.upwork.com/research/future-of-remote-work
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879
Rucker, D. D., Preacher, K. J., Tormala, Z. L., & Petty, R. E. (2011). Mediation analysis in social psychology: Current practices and new recommendations. Social and Personality Psychology Compass, 5(6), 359–371. https://doi.org/10.1111/j.1751-9004.2011.00355.x
Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological Methods, 7(4), 422–445. https://doi.org/10.1037/1082-989X.7.4.422
Suhartini, E., & Nurariansyah, I. (2021). Pengaruh teknologi informasi terhadap kinerja pegawai dengan kepuasan kerja sebagai variabel mediasi pada Kantor Wilayah Badan Pertanahan Nasional Provinsi Sulawesi Selatan [The effect of information technology on employee performance with job satisfaction as a mediating variable at the South Sulawesi Provincial Office of the National Land Agency]. Study of Scientific and Behavioral Management, 2(2), 1–15. https://doi.org/10.24252/ssbm.v2i2.21822
Sulistya, R. D., & Zain, D. (2020). Pemanfaatan teknologi informasi dan produktivitas kerja karyawan [The utilization of information technology and employee work productivity]. Jurnal Ilmu Manajemen dan Akuntansi Terapan, 11(1), 78–91. https://jurnal.stietotamaktar.ac.id/index.php/jimat
Tarafdar, M., Cooper, C. L., & Stich, J.-F. (2019). The technostress trifecta—Techno eustress, techno distress and design: Theoretical directions and an agenda for research. Information Systems Journal, 29(1), 6–42. https://doi.org/10.1111/isj.12169
Tarafdar, M., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328. https://doi.org/10.2753/MIS0742-1222240109
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/j.lrp.2018.12.001
Zhao, X., Lynch, J. G., Jr., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37(2), 197–206. https://doi.org/10.1086/651257
Zhou, Y., Lyu, Y., & Li, Z. (2025). Digital transformation and labor productivity: Evidence from Chinese enterprises. PLOS ONE, 20(1), Article e0312456. https://doi.org/10.1371/journal.pone.0312456
Published
2026-10-29
How to Cite
Muhammad Zyrull Esa Ardy Wibowo, & Mohammad Khusnu Milad. (2026). The Effect of Corporate Application Use on Employee Productivity with Employee Performance as a Mediating Variable. International Journal of Economics, Business and Innovation Research, 5(06), 2112-2127. https://doi.org/10.63922/ijebir.v5i06.7163
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