Information systems and performance: the role of technology, the task and the individual

References

• Alter, S. 1999. “A General, Yet Useful Theory of Information Systems.” Communications of the Association for Information Systems 1 (3es).
   Google Scholar
• Alter, S. 2004. “Desperately Seeking Systems Thinking in the Information Systems Discipline.” Paper presented at the 25th International Conference on Information Systems ICIS 04, Washington, DC.
   Google Scholar
• Anderson, J. C., and D. W. Gerbing. 1988. “Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach.” Psychological Bulletin 103 (3): 411–423. doi: 10.1037/0033-2909.103.3.411
   Web of Science ®Google Scholar
• Anderson, J. R. 1989. “A Theory of the Origins of Human Knowledge.” Artificial Intelligence 40 (1–3): 313–351. doi: 10.1016/0004-3702(89)90052-0
   Web of Science ®Google Scholar
• Bacharach, S. B., and P. Bamberger. 1995. “Beyond Situational Constraints: Job Resources Inadequacy and Individual Performance at Work.” Human Resource Management Review 5 (2): 79–102. doi: 10.1016/1053-4822(95)90013-6
   Web of Science ®Google Scholar
• Bentler, P. M., and C. P. Chou. 1987. “Practical Issues in Structural Modeling.” Sociological Methods & Research 16 (1): 78–117. doi: 10.1177/0049124187016001004
   Web of Science ®Google Scholar
• Blumberg, M., and C. Pringle. 1982. “The Missing Opportunity in Organizational Research: Some Implications for a Theory of Work Performance.” Academy of Management Review 7 (4): 560–569.
   Google Scholar
• Borman, W. C., L. A. White, E. D. Pulakos, and S. H. Oppler. 1991. “Models of Supervisory Job Performance Ratings.” Journal of Applied Psychology 76 (6): 863–872. doi: 10.1037/0021-9010.76.6.863
   Web of Science ®Google Scholar
• Bostrom, R. P., and J. S. Heinen. 1977. “MIS Problems and Failures: A Socio-technical Perspective Part I: The Causes.” MIS Quarterly 1 (3): 17–32. doi: 10.2307/248710
   Google Scholar
• Boudreau, M. C., D. Gefen, and D. W. Straub. 2001. “Validation in Information Systems Research: A State-of-the-Art Assessment.” MIS Quarterly 25 (1): 1–16. doi: 10.2307/3250956
   Web of Science ®Google Scholar
• Brislin, R. W., and C. Freimanis. 1995. “Back-Translation: A Tool for Cross-cultural Research.” In An Encyclopaedia of Translation: Chinese-English, English-Chinese, Vol. 1, edited by C. Sin-wai and D. E. Pollar, 22–40. Hong Kong, CN: The Chinese University Press.
   Google Scholar
• Burton-Jones, A. 2009. “Minimizing Method Bias through Programmatic Research.” MIS Quarterly 33 (3): 445–471.
   Web of Science ®Google Scholar
• Campbell, D. J. 1988. “Task Complexity: A Review and Analysis.” Academy of Management Review 13 (1): 40–52.
   Web of Science ®Google Scholar
• Campbell, J. 1990. “Modeling the Performance Prediction Problem in Industrial and Organizational Psychology.” In Handbook of Industrial and Organizational Psychology, edited by M. Dunnette and L. Hough, 687–732. Palo Alto: Consulting Psychologists Press.
   Google Scholar
• Clegg, C. W. 2000. “Sociotechnical Principles for System Design.” Applied Ergonomics 31 (5): 463–477. doi: 10.1016/S0003-6870(00)00009-0
   PubMed Web of Science ®Google Scholar
• Curran, P. J., S. G. West, and J. F. Finch. 1996. “The Robustness of Test Statistics to Nonnormality and Specification Error in Confirmatory Factor Analysis.” Psychological Methods 1 (1): 16–29. doi: 10.1037/1082-989X.1.1.16
   Web of Science ®Google Scholar
• Davis, F. 1986. “A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results.” Doctoral diss., Massachusetts Institute of Technology, Cambridge, MA.
   Google Scholar
• Davis, F. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly 13 (3): 319–340. doi: 10.2307/249008
   Web of Science ®Google Scholar
• DeLone, W. H., and E. R. McLean. 1992. “Information Systems Success: The Quest for the Dependent Variable.” Information Systems Research 3 (1): 60–95. doi: 10.1287/isre.3.1.60
   Web of Science ®Google Scholar
• Dong, L., D. J. Neufeld, and C. Higgins. 2008. “Testing Klein and Sorra's Innovation Implementation Model: An Empirical Examination.” Journal of Engineering and Technology Management 25 (4): 237–255. doi: 10.1016/j.jengtecman.2008.10.006
   Web of Science ®Google Scholar
• Etezadi-Amoli, J., and A. F. Farhoomand. 1996. “A Structural Model of End User Computing Satisfaction and User Performance.” Information & Management 30 (2): 65–73. doi: 10.1016/0378-7206(95)00052-6
   Web of Science ®Google Scholar
• Fadel, K. J. 2012. “User Adaptation and Infusion of Information Systems.” Journal of Computer Information Systems 52 (3): 1–10.
   Web of Science ®Google Scholar
• Fadel, K. J., M. Tanniru, and S. P. Weisband. 2005. “Understanding Process Knowledge Change in Enterprise System Implementation: A Framework and Case Study.” Paper presented at the AMCIS 2005, Nebraska.
   Google Scholar
• Finch, J. F., S. G. West, and D. P. MacKinnon. 1997. “Effects of Sample Size and Nonnormality on the Estimation of Mediated Effects in Latent Variable Models.” Structural Equation Modeling: A Multidisciplinary Journal 4 (2): 87–107. doi: 10.1080/10705519709540063
   Web of Science ®Google Scholar
• Furneaux, B. 2012. “Task-Technology Fit Theory: A Survey and Synopsis of the Literature.” In Information Systems Theory, Vol. 28, edited by Y. K. Dwivedi, M. R. Wade, and S. L. Schneberger, 87–106. New York: Springer.
   Google Scholar
• Gable, G. G., D. Sedera, and T. Chan. 2008. “Re-conceptualizing Information System Success: The IS-Impact Measurement Model.” Journal of the Association for Information Systems 9 (7): 377–408.
   Web of Science ®Google Scholar
• Gartner-Inc. 2013. “Gartner Says Worldwide IT Spending Forecast to Reach $3.7 Trillion in 2013.” Press Release (Stamford, CT, 3 January 2013) http://www.gartner.com/newsroom/id/2292815.
   Google Scholar
• Gefen, D., E. Karahanna, and D. W. Straub. 2003. “Trust and TAM in Online Shopping: An Integrated Model.” MIS Quarterly 27 (1): 51–90.
   Web of Science ®Google Scholar
• Gefen, D., D. W. Straub, and M.-C. Boudreau. 2000. “Structural Equation Modeling and Regression: Guidelines for Research Practice.” Communications of the Association for Information Systems 4: Article 7.
   Google Scholar
• Gefen, D., D. W. Straub, and E. E. Rigdon. 2011. “An Update and Extension to SEM Guidelines for Administrative and Social Science Research.” MIS Quarterly 35 (2): ii–xiv.
   Web of Science ®Google Scholar
• Gill, T. G., and R. C. Hicks. 2006. “Task Complexity and Informing Science: A Synthesis.” Informing Science Journal 9: 1–30.
   Google Scholar
• Goodhue, D. 1992. “User Evaluations of MIS Success: What Are We Really Measuring?” Paper presented at the 25th Hawaii International Conference on Systems Sciences Kauai, Hawaii.
   Google Scholar
• Goodhue, D., and R. L. Thompson. 1995. “Task-Technology Fit and Individual Performance.” MIS Quarterly 19 (2): 213–236. doi: 10.2307/249689
   Web of Science ®Google Scholar
• Grover, V., S. R. Jeong, and A. H. Segars. 1996. “Information Systems Effectiveness: The Construct Space and Patterns of Application.” Information & Management 31 (4): 177–191. doi: 10.1016/S0378-7206(96)01079-8
   Web of Science ®Google Scholar
• Gupta, S., R. P. Bostrom, and M. Huber. 2010. “End-User Training: What We Know, What We Need to Know.” Database for Advances in Information Systems 41 (4): 9–39. doi: 10.1145/1899639.1899641
   Web of Science ®Google Scholar
• Gwizdka, J. 2008. “Revisiting Search Task Difficulty: Behavioral and Individual Difference Measures.” Paper presented at the 71st annual meeting of the American Society for Information Science and Technology, Columbus, OH.
   Google Scholar
• Gwizdka, J. 2009. “Assessing Cognitive Load on Web Search Tasks.” The Ergonomics Open Journal 2: 114–123. doi: 10.2174/1875934300902010114
   Google Scholar
• Gwizdka, J., and I. Spence. 2006. “What Can Searching Behavior Tell Us About the Difficulty of Information Tasks? A Study of Web Navigation.” Proceedings of the American Society for Information Science and Technology 43 (1): 1–22. doi: 10.1002/meet.14504301167
   Google Scholar
• Hair, J. F., W. C. Black, B. J. Babin, R. E. Anderson, and R. L. Tatham. 2006. Multivariate Data Analysis. 6th ed. Upper Saddle River, NJ: Prentice-Hall.
   Google Scholar
• Kanfer, R., and P. L. Ackerman. 1989. “Motivation and Cognitive Abilities: An Integrative/Aptitude-Treatment Interaction Approach to Skill Acquisition.” Journal of Applied Psychology 74 (4): 657–690. doi: 10.1037/0021-9010.74.4.657
   Web of Science ®Google Scholar
• Kim, Y. J., E. J. Garrity, and G. L. Sanders. 2003. “Success Measures of Information Systems.” In Encyclopedia of Information Systems Vol. 4, edited by H Bidgoli, 299–313. San Diego, CA: Academic Press.
   Google Scholar
• Kim, M., R. Sharman, C. P. Cook-Cottone, H. R. Rao, and S. J. Upadhyaya. 2012. “Assessing Roles of People, Technology and Structure in Emergency Management Systems: A Public Sector Perspective.” Behaviour & Information Technology 31 (12): 1147–1160. doi: 10.1080/0144929X.2010.510209
   Web of Science ®Google Scholar
• Koopmans, L., C. M. Bernaards, V. H. Hildebrandt, W. B. Schaufeli, H. C. W. de Vet, and A. J. van der Beek. 2011. “Conceptual Frameworks of Individual Work Performance: A Systematic Review.” Journal of Occupational and Environmental Medicine 53 (8): 856–866. doi: 10.1097/JOM.0b013e318226a763
   PubMed Web of Science ®Google Scholar
• Kositanurit, B., O. Ngwenyama, and K.-M. Osei-Bryson. 2006. “An Exploration of Factors that Impact Individual Performance in an ERP Environment: An Analysis using Multiple Analytical Techniques.” European Journal of Information Systems 15 (6): 556–568. doi: 10.1057/palgrave.ejis.3000654
   Web of Science ®Google Scholar
• Kraemmergaard, P., and C. Moller. 2000. “A Research Framework for Studying the Implementation of ERP Systems.” Paper presented at the 23rd Information Systems Research Seminar in Scandinavia, Lingatan, Sweden.
   Google Scholar
• Krathwohl, D. R. 2002. “A Revision of Bloom's Taxonomy: An Overview.” Theory into Practice 41 (4): 212–218. doi: 10.1207/s15430421tip4104_2
   Web of Science ®Google Scholar
• Lin, H. X., Y. Y. Choong, and G. Salvendy. 1997. “A Proposed Index of Usability: A Method for Comparing the Relative Usability of Different Software Systems.” Behaviour & Information Technology 16 (4): 267–278. doi: 10.1080/014492997119833
   Web of Science ®Google Scholar
• Liu, P., and Z. Li. 2011. “Toward Understanding the Relationship between Task Complexity and Task Performance.” In Internationalization, Design and Global Development, Vol. 6775, edited by P. Rau, 192–200. Berlin: Springer-Verlag.
   Google Scholar
• Lyytinen, K., and M. Newman. 2008. “Explaining Information Systems Change: A Punctuated Socio-technical Change Model.” European Journal of Information Systems 17 (6): 589–613. doi: 10.1057/ejis.2008.50
   Web of Science ®Google Scholar
• Mangos, P. M., and D. Steele-Johnson. 2001. “The Role of Subjective Task Complexity in Goal Orientation, Self-Efficacy, and Performance Relations.” Human Performance 14 (2): 169–185. doi: 10.1207/S15327043HUP1402_03
   Web of Science ®Google Scholar
• Markus, M., and C. Tanis. 2000. “The Enterprise Systems Experience – From Adoption to Success.” In Framing the Domains of IT Management: Projecting the Future through the Past, edited by R. W. Zmud, 173–207. Cincinnatti, OH: Pinnaflex Educational Resources.
   Google Scholar
• Maynard, D. C., and M. D. Hakel. 1997. “Effects of Objective and Subjective Task Complexity on Performance.” Human Performance 10 (4): 303–330. doi: 10.1207/s15327043hup1004_1
   Web of Science ®Google Scholar
• McCloy, R. A., J. P. Campbell, and R. Cudeck. 1994. “A Confirmatory Test of a Model of Performance Determinants.” Journal of Applied Psychology 79 (4): 493–505. doi: 10.1037/0021-9010.79.4.493
   Web of Science ®Google Scholar
• Moore, G. C., and I. Benbasat. 1991. “Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation.” Information Systems Research 2 (3): 192–222. doi: 10.1287/isre.2.3.192
   Web of Science ®Google Scholar
• Motowildo, S. J., W. C. Borman, and M. J. Schmit. 1997. “A Theory of Individual Differences in Task and Contextual Performance.” Human Performance 10 (2): 71–83. doi: 10.1207/s15327043hup1002_1
   Web of Science ®Google Scholar
• Muckler, F. A., and S. A. Seven. 1992. “Selecting Performance Measures: ‘Objective’ versus ‘Subjective’ Measurement.” Human Factors: The Journal of the Human Factors and Ergonomics Society 34 (4): 441–455.
   Web of Science ®Google Scholar
• Muhammed, S. 2007. “Antecedents and Impacts of Knowledge Management Practices Supported by Information Technology: An Empirical Study in Manufacturing Context.” Doctoral diss., The University of Toledo, Toledo, OH.
   Google Scholar
• Muhammed, S., W. J. Doll, and X. Deng. 2009. “A Model of Interrelationships Among Individual Level Knowledge Management Success Measures.” International Journal of Knowledge Management 5 (1): 1–16. doi: 10.4018/jkm.2009010101
   Google Scholar
• Napoleon, K., and C. Gaimon. 2004. “The Creation of Output and Quality in Services: A Framework to Analyze Information Technology-Worker Systems.” Production and Operations Management 13 (3): 245–259. doi: 10.1111/j.1937-5956.2004.tb00509.x
   Web of Science ®Google Scholar
• Orlikowski, W. J., and S. R. Barley. 2001. “Technology and Institutions: What Can Research on Information Technology and Research on Organizations Learn from Each Other?” MIS Quarterly 25 (2): 145–165. doi: 10.2307/3250927
   Web of Science ®Google Scholar
• Pan, S. L., S. Newell, J. C. Huang, and A. W. K. Cheung. 2001. “Knowledge Integration as a Key Problem in an ERP Implementation.” Paper presented at the 22nd International Conference on Information Systems, New Orleans.
   Google Scholar
• Peters, L. H., and E. J. O'Connor. 1980. “Situational Constraints and Work Outcomes: The Influences of a Frequently Overlooked Construct.” Academy of Management Review 5 (3): 391–398.
   Google Scholar
• Peterson, T., and R. Arnn. 2005. “Self-Efficacy: The Foundation of Human Performance.” Performance Improvement Quarterly 18 (2): 5–18. doi: 10.1111/j.1937-8327.2005.tb00330.x
   Google Scholar
• Petter, S., W. H. DeLone, and E. R. McLean. 2008. “Measuring Information Systems Success: Models, Dimensions, Measures, and Interrelationships.” European Journal of Information Systems 17 (3): 236–263. doi: 10.1057/ejis.2008.15
   Web of Science ®Google Scholar
• Petter, S., W. H. DeLone, and E. R. McLean. 2012. “The Past, Present, and Future of IS Success.” Journal of the Association for Information Systems 13 (5): 341–362.
   Web of Science ®Google Scholar
• Quinn, J. B., P. Anderson, and S. Finkelstein. 1996. “Managing Professional Intellect: Making the Most of the Best.” Harvard Business Review 74 (2): 71–80.
   PubMed Web of Science ®Google Scholar
• Rai, A., S. S. Lang, and R. B. Welker. 2002. “Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis.” Information Systems Research 13 (1): 50–69. doi: 10.1287/isre.13.1.50.96
   Web of Science ®Google Scholar
• Rangarajan, D., E. Jones, and W. Chin. 2005. “Impact of Sales Force Automation on Technology-Related Stress, Effort, and Technology Usage among Salespeople.” Industrial Marketing Management 34 (4): 345–354. doi: 10.1016/j.indmarman.2004.09.015
   Web of Science ®Google Scholar
• Schmitt, N., J. M. Cortina, M. J. Ingerick, and D. Wiechmann. 2003. “Personnel Selection and Employee Performance.” In Handbook of Psychology, Vol. 12, edited by W. C. Borman, D. Ilgen, and R. Klimoski, 77–105. Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Schmidt, F. L., and J. E. Hunter. 1998. “The Validity and Utility of Selection Methods in Personnel Psychology: Practical and Theoretical Implications of 85 Years of Research Findings.” Psychological Bulletin 124 (2): 262–274. doi: 10.1037/0033-2909.124.2.262
   Web of Science ®Google Scholar
• Seddon, P. B. 1997. “A Respecification and Extension of the DeLone and McLean Model of IS Success.” Information Systems Research 8 (3): 240–253. doi: 10.1287/isre.8.3.240
   Web of Science ®Google Scholar
• Seddon, P. B., and M.-Y. Kiew. 1997. “A Partial Test and Development of DeLone and McLean's Model of IS Success.” Australasian Journal of Information Systems 4 (1): 90–109.
   Google Scholar
• Soh, C., S. Kien Sia, W. Fong Boh, and M. T. Tang. 2003. “Misalignments in ERP Implementation: A Dialectic Perspective.” International Journal of Human-Computer Interaction 16 (1): 81–100. doi: 10.1207/S15327590IJHC1601_6
   Web of Science ®Google Scholar
• Sousa, R. D. 2004. “Complex Information Technology Usage.” Doctoral diss., University of Georgia, Athens, GA.
   Google Scholar
• Sousa, R. D., and D. L. Goodhue. 2003. “Understanding Exploratory Use of ERP Systems.” Paper presented at the Ninth Americas Conference on Information Systems, Tampa, FL.
   Google Scholar
• Stone, R. W., D. J. Good, and L. Baker-Eveleth. 2007. “The Impact of Information Technology on Individual and Firm Marketing Performance.” Behaviour & Information Technology 26 (6): 465–482. doi: 10.1080/01449290600571610
   Web of Science ®Google Scholar
• Sun, Y., A. Bhattacherjee, and Q. Ma. 2009. “Extending Technology Usage to Work Settings: The Role of Perceived Work Compatibility in ERP Implementation.” Information & Management 46 (6): 351–356. doi: 10.1016/j.im.2009.06.003
   Web of Science ®Google Scholar
• Thompson, R. L., C. A. Higgins, and J. M. Howell. 1991. “Personal Computing: Toward a Conceptual Model of Utilization.” MIS Quarterly 15 (1): 125–143. doi: 10.2307/249443
   Web of Science ®Google Scholar
• Urbach, N., and B. Muller. 2012. “The Updated DeLone and McLean Model of Information Systems Success.” In Information Systems Theory, Vol. 1, edited by Y. K. Dwivedi, M. R. Wade, and S. L. Schneberger, 1–18. New York: Springer.
   Google Scholar
• Urbach, N., S. Smolnik, and G. Riempp. 2009. “The State of Research on Information Systems Success.” Business & Information Systems Engineering 1 (4): 315–325. doi: 10.1007/s12599-009-0059-y
   Web of Science ®Google Scholar
• 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: 10.1287/isre.11.4.342.11872
   Web of Science ®Google Scholar
• Venkatesh, V., and H. Bala. 2008. “Technology Acceptance Model 3 and a Research Agenda on Interventions.” Decision Sciences 39 (2): 273–315. doi: 10.1111/j.1540-5915.2008.00192.x
   Web of Science ®Google Scholar
• Venkatesh, V., and F. D. Davis. 1996. “A Model of the Antecedents of Perceived Ease of Use: Development and Test.” Decision Sciences 27 (3): 451–481. doi: 10.1111/j.1540-5915.1996.tb01822.x
   Web of Science ®Google Scholar
• Venkatesh, V., and F. D. Davis. 2000. “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies.” Management Science 46 (2): 186–204. doi: 10.1287/mnsc.46.2.186.11926
   Web of Science ®Google Scholar
• Viswesvaran, C. 2001. “Assessment of Individual Job Performance: A Review of the Past Century and a Look Ahead.” In Handbook of Industrial, Work and Organizational Psychology: Personnel Psychology, Vol. 1, edited by N. Anderson, D. Ones, H. Sinangil, and C. Viswesvaran, 110–126. London: Sage.
   Google Scholar
• Viswesvaran, C., and D. S. Ones. 2000. “Perspectives on Models of Job Performance.” International Journal of Selection and Assessment 8 (4): 216–226. doi: 10.1111/1468-2389.00151
   Web of Science ®Google Scholar
• Waldman, D. A., and W. D. Spangler. 1989. “Putting Together the Pieces: A Closer Look at the Determinants of Job Performance.” Human Performance 2 (1): 29–59. doi: 10.1207/s15327043hup0201_2
   Google Scholar
• Wood, R. E. 1986. “Task Complexity: Definition of the Construct.” Organizational Behavior and Human Decision Processes 37 (1): 60–82. doi: 10.1016/0749-5978(86)90044-0
   Web of Science ®Google Scholar
• Yeo, G. B., and A. Neal. 2004. “A Multilevel Analysis of Effort, Practice, and Performance: Effects of Ability, Conscientiousness, and Goal Orientation.” Journal of Applied Psychology 89 (2): 231–247. doi: 10.1037/0021-9010.89.2.231
   PubMed Web of Science ®Google Scholar