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A study on the relationship between task, information, and individual performance

Author

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  • Cayir, Sinan
  • Basoglu, Nuri
  • Daim, Tugrul U.

Abstract

The goal of this study was to find an abstract model that would address the relationship between information and task and thus lead to better business performance. The relationships among information, task, and performance are analyzed in the natural environment against job-related beliefs and technology. The final instrument was applied to professionals mainly from the Finance and Information and Communication Technology (ICT) sectors. Statistical analyses were used to quantify the relationships. The goal of the study was also to develop a model of task information fit (TIF). Results indicate that the tool has been successful and models the underlying structure between system characteristics, task characteristics, information characteristics, and their impact on perceived business success to some degree. A reduced TIF model was targeted to discover the relation between task characteristics, information characteristics, and their effect on business performance on a per-item basis. The correlations between the items supported the proposed relations.

Suggested Citation

  • Cayir, Sinan & Basoglu, Nuri & Daim, Tugrul U., 2016. "A study on the relationship between task, information, and individual performance," Technology in Society, Elsevier, vol. 46(C), pages 1-9.
    • Handle: RePEc:eee:teinso:v:46:y:2016:i:c:p:1-9
    DOI: 10.1016/j.techsoc.2016.02.002
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    References listed on IDEAS

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    1. Hau L. Lee & Kut C. So & Christopher S. Tang, 2000. "The Value of Information Sharing in a Two-Level Supply Chain," Management Science, INFORMS, vol. 46(5), pages 626-643, May.
    2. Raya Fidel & Annelise Mark Pejtersen & Bryan Cleal & Harry Bruce, 2004. "A multidimensional approach to the study of human‐information interaction: A case study of collaborative information retrieval," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 55(11), pages 939-953, September.
    3. Satya S. Chakravorty & Douglas N. Hales & James I. Herbert, 2008. "How problem-solving really works," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 1(1), pages 44-59.
    4. William H. DeLone & Ephraim R. McLean, 1992. "Information Systems Success: The Quest for the Dependent Variable," Information Systems Research, INFORMS, vol. 3(1), pages 60-95, March.
    5. Katriina Byström & Preben Hansen, 2005. "Conceptual framework for tasks in information studies," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(10), pages 1050-1061, August.
    6. Schulte, Elisabeth & Peter Gruner, Hans, 2007. "Speed and quality of collective decision making: Imperfect information processing," Journal of Economic Theory, Elsevier, vol. 134(1), pages 138-154, May.
    7. Sinan Cayir & A. Nuri Basoglu & Tugrul U. Daim, 2010. "Users and information technology: analysis of task information fit model," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 2(4), pages 401-426.
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    Cited by:

    1. Spatar, Daria & Kok, Orhun & Basoglu, Nuri & Daim, Tugrul, 2019. "Adoption factors of electronic health record systems," Technology in Society, Elsevier, vol. 58(C).
    2. Yavuz, Merve & Çorbacıoğlu, Eda & Başoğlu, Ahmet Nuri & Daim, Tugrul Unsal & Shaygan, Amir, 2021. "Augmented reality technology adoption: Case of a mobile application in Turkey," Technology in Society, Elsevier, vol. 66(C).

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