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Causal Modeling Of Web-Advertising Effects By Improving Sem Based On Dematel Technique

Author

Listed:
  • PAO-LIEN WEI

    (Department of Management Science, National Chiao Tung University, 1001, Ta-Hsueh Road, Hsinchu 300, Taiwan)

  • JEN-HUNG HUANG

    (Department of Management Science, National Chiao Tung University, 1001, Ta-Hsueh Road, Hsinchu 300, Taiwan)

  • GWO-HSHIUNG TZENG

    (Institute of Project Management, Kainan University, No. 1, Kainan Road, Luchu, Taoyuan 338, Taiwan;
    Institute of Management of Technology, National Chiao Tung University, 1001, Ta-Hsueh Road, Hsinchu 300, Taiwan)

  • SHWU-ING WU

    (Department of Business Administration, National Chin-Yi University of Technology, 35, Lane 215, Section 1, Chungshan Road, Taiping, Taichung, Taiwan)

Abstract

Causal analysis greatly affects the efficiency of decision-making. Scholars usually adopt structural equation modeling (SEM) to establish a causal model recently. However, statistical data allow researchers to modify the model frequently to arrive at good model fitness, and SEM is often misapplied when the data are merely fitted to an SEM and the theory is then extended from the analytical result based on presumed hypotheses. This paper proposed SEM modified by DEMATEL technique, taking causal model of Web-advertising effects for example. Having revealed that the new model is the one that conforms to actual data and is better than initial model, the results confirm that the DEMATEL technique can be an efficient, complementary, and confident approach for reprioritization of the amended modes in a SEM model. In addition, the most important factor affecting the Web-advertising effects may be found via the modified model, which benefits the manager for making strategic marketing plans.

Suggested Citation

  • Pao-Lien Wei & Jen-Hung Huang & Gwo-Hshiung Tzeng & Shwu-Ing Wu, 2010. "Causal Modeling Of Web-Advertising Effects By Improving Sem Based On Dematel Technique," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 9(05), pages 799-829.
    • Handle: RePEc:wsi:ijitdm:v:09:y:2010:i:05:n:s0219622010004032
    DOI: 10.1142/S0219622010004032
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    Citations

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    Cited by:

    1. Gyan Prakash & Shefali Srivastava, 2019. "Developing a Care Coordination Model Using a Hybrid DEMATEL and PLS-SEM Approach," IIM Kozhikode Society & Management Review, , vol. 8(1), pages 34-49, January.
    2. Ikhlas F. Zamzami, 2021. "The key enabling criteria of e-entrepreneurship evolving practices and implementation in Saudi Arabia," SN Business & Economics, Springer, vol. 1(9), pages 1-22, September.
    3. Michnik, Jerzy, 2013. "Weighted Influence Non-linear Gauge System (WINGS) – An analysis method for the systems of interrelated components," European Journal of Operational Research, Elsevier, vol. 228(3), pages 536-544.
    4. Chandra Sekhar & Manoj Patwardhan & Vishal Vyas, 2017. "Study of Intellectual Capital Dimensions in IT Industry Using DEMATEL Method," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 1-23, September.
    5. Kumar, Anil & Luthra, Sunil & Khandelwal, Dinesh Kumar & Mehta, Rajneesh & Chaudhary, Nityanand & Bhatia, Sukhdev, 2017. "Measuring and improving customer retention at authorised automobile workshops after free services," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 93-102.
    6. Hiteshkumar G. Shah & Ravi Kant, 2018. "Knowledge Management Enablers: Metadata Analysis for KM Implementation," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1-29, December.
    7. Kurtz, Oliver T. & Wirtz, Bernd W. & Langer, Paul F., 2021. "An Empirical Analysis of Location-Based Mobile Advertising—Determinants, Success Factors, and Moderating Effects," Journal of Interactive Marketing, Elsevier, vol. 54(C), pages 69-85.
    8. Leonilde Varela & Adriana Araújo & Paulo Ávila & Hélio Castro & Goran Putnik, 2019. "Evaluation of the Relation between Lean Manufacturing, Industry 4.0, and Sustainability," Sustainability, MDPI, vol. 11(5), pages 1-19, March.
    9. Ching Ching Fang & James J. H. Liou & Sun-Weng Huang & Ying-Chuan Wang & Hui-Hua Huang & Gwo-Hshiung Tzeng, 2021. "A Hybrid, Data-Driven Causality Exploration Method for Exploring the Key Factors Affecting Mobile Payment Usage Intention," Mathematics, MDPI, vol. 9(11), pages 1-23, May.

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