Structural Model to Predict Satisfaction and Performance Users of SIKD at Government Organizations in South Kalimantan
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Abstract
The successful adoption of ICT by local governments still requires evaluation because of several issues related to the use and utilization of the SIKD. The variety of SIKD applications, limited server, and network capacity, limited human resource personnel, and lack of technical guidance because regulatory changes put pressure on user satisfaction and performance. Academic evaluation of SIKD adoption from the user's perspective is needed to explore advanced concepts of e-government development. The research model was analyzed with the Partial Least Square (SEM-PLS) approach. The results showed the perceived usefulness, perceived ease of use, subjective norms, and facilitating conditions influenced user satisfaction and subsequently, user satisfaction affected user performance. The conceptual framework tested in this study was able to show that under conditions of ICT mandatory use by organizations, behavioral beliefs influence user satisfaction and have an important impact on user performance.
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References
Agarwal, R., & Prasad, J. (1997). The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies. Decision Sciences, 28(3), 557-582.
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes(50), 179-211.
Amoako-Gyampah, K. (2007). Perceived usefulness, user involvement and behavioral intention: an empirical study of ERP implementation. Computers in Human Behavior, 23(3), 1232-1248. doi: https://doi.org/10.1016/j.chb.2004.12.002
BPK RI. (2018). IHPS I: Ikhtisar Hasil Pemeriksaan Semester I Tahun 2018 Retrieved from http://www.bpk.go.id/assets/files/ihps/2018/I/ihps_i_2018_1538459607.pdf
Brown, S. A., Massey, A. P., Montoya-Weiss, M., & Burkman, J. (2002). Do I really have to? User acceptance of mandated technology. European Journal of Information Systems, 11, 283. doi: https://doi.org/10.1057/palgrave.ejis.3000438
Chan, F., Thong, J., Venkatesh, V., A. Brown, S., Jen-Hwa Hu, P., & Tam, K. (2010). Modeling Citizen Satisfaction with Mandatory Adoption of an E-Government Technology. Journal of the Association for Information Systems 11(10), 519-549.
Chandrarin, G. (2017). Metode Riset Akuntansi Pendekatan Kuantitatif. Jakarta: Penerbit Salemba Empat.
Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research. Mahwah, New Jersey: Lawrence Erlbaum Associates.
Chopra, S., & Rajan, P. (2016). Modeling Intermediary Satisfaction with Mandatory Adoption of E-government Technologies for Food Distribution. Information Technologies & International Development, 12(1), 15-34.
Dahlbom, B. (1996). The New Informatics. Scandinavian Journal of Information Systems, 8(2), 29-47.
Davenport, T. H. (2000). The Future of Enterprise System-Enabled Organizations. Information Systems Frontiers, 2(2), 163-180. doi: https://doi.org/10.1023/A:1026591822284
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease Of Use, and User Acceptance of Information Technology. MIS Quarterly, 13, 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoritical Models. Management Science, 35(8), 982-1003.
DeLone, W. H., & McLean, E. R. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research, 3(60-95).
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information System, 19(4), 9-30. doi: 10.1080/07421222.2003. 11045748
DeLone, W. H., & McLean, E. R. (2016). Information Systems Success Measurement. Foundations and Trends(R) in Information Systems, 2(1), 1-116.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behaviour: An Introduction to Theory and Research: Addison-Wesley Publishing Company.
Galletta, D., & Zhang, P. (2006). Applications of Human-Computer Interaction in Management Information Systems: An Introduction. In D. Galletta & P. Zhang (Eds.), Human–Computer Interaction and Management Information Systems: Applications (Vol. 6). Armonk NY: M.E. Sharpe.
Goodhue, D. L. (1995). Understanding User Evaluations of Information Systems. Management Science, 41(12), 1827-1844.
Govindaraju, R., & Gondodiwirjo, L. (2008). Studi Mengenai ERP System Adoption Berbasis Technology Acceptance Model. Jurnal Manajemen Teknologi, 7(1), 35-45.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM): SAGE Publications, Inc.
Hartwick, J., & Barki, H. (1994). Explaining the Role of User Participation in Information System Use. Management Science, 40(4), 440-465. doi: http://dx.doi.org/10.1287/mnsc.40.4.440
Hirschheim, R. (2007). Introduction to the Special Issue on “Quo Vadis TAM – Issues and Reflections on Technology Acceptance Research". Journal of the Association for Information Systems, 8(4), 203-205.
Hou, C.-K. (2012). Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan’s electronics industry. International Journal of Information Management, 32, 560-573. doi: 10.1016/j.ijinfomgt.2012. 03.001
Huang, S.-H., & Hsu, W.-K. (2010). The Acceptance of Workplace Users for a New IT with Mandatory Use. Asia Pacific Management Review, 15(4), 549-565.
Hwang, Y., Al-Arabiat, M., & Shin, D.-H. (2015). Understanding technology acceptance in a mandatory environment: A literature review. Information Development, 32(4), 1266-1283. doi: DOI: 10.1177/0266666915593621
Kaplan, R. S., & Norton, D. R. (2000). Having Trouble with Your Strategy? Then Map It. Harvard Business Review, 78(5), 167-176.
Kim, C., Jahng, J., & Lee, J. (2007). An empirical investigation into the utilization-based information technology success model: integrating task-performance and social influence perspective. Journal of Information Technology, 22, 152-160. doi: doi:10.1057/palgrave.jit.2000072
Kock, N. (2017). WarpPLS User Manual: Version 6.0 Retrieved from http://cits.tamiu.edu/WarpPLS/UserManual_v_6_0.pdf
Kock, N., & Lynn, G. S. (2012). Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations. Journal of the Association for Information Systems, 13(7), 546-580.
Koh, C. E., Prybutok, V. R., Ryan, S. D., & Wu, Y. A. (2010). A Model for Mandatory Use of Software Technologies: An Integrative Approach by Applying Multiple Levels of Abstraction of Informing Science. Informing Science: The International Journal of an Emerging Transdiscipline, 13, 177-203. doi: https://doi.org/10.28945/1326
Lim, W. M. (2018). Dialectic Antidotes to Critics of the Technology Acceptance Model: Conceptual, Methodological, and Replication Treatments for Behavioural Modelling in Technology-Mediated Environments. Australasian Journal of Information Systems, 22. doi: 10.3127/ajis.v22i0.1651
Maillet, É., Mathieu, L., & Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT. International Journal of Medical Informatics, 84(1), 36-47. doi: https://doi.org/10.1016/j.ijmedinf.2014.09.004
Peppard, J. (2016). The Evolving Role of Information Systems and Technology in Organizations: A Strategic Perspective.
Rubin, H. (2004, 06 August 2004). Into the Light. CIO. 2004, from http://www.cio.com.au/article/166537/into_light/
Sanusi, A. (2011). Metodologi Penelitian Bisnis. Jakarta: Penerbit Salemba Empat.
Shih, Y.-Y., & Chen, C.-Y. (2013). The study of behavioral intention for mobile commerce: via integrated model of TAM and TTF. Quality and Quantity, 47(2), 1009-1020. doi: 10.1007/s11135-011-9579-x
Staples, D. S., & Seddon, P. (2004). Testing the Technology-to-Performance Chain Model. Journal of Organizational and End User Computing, 16(4), 17-36.
Sun, Y., Bhattacherjee, A., & Ma, Q. (2009). Extending technology usage to work settings: The role of perceived work compatibility in ERP implementation. Information & Management, 46, 351-356. doi: doi:10.1016/j.im.2009.06.003
Taylor, S., & Todd, P. A. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176. doi: http://dx.doi.org/10.1287/isre.6.2.144
Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 342-365. doi: https://doi.org/10.1287/isre.11.4.342.11872
Venkatesh, V., & Davis, F. D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27(3), 451-481. doi: DOI: 10.1111/j.1540-5915.1996.tb00860.x
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.