IDEAS home Printed from https://ideas.repec.org/a/sae/fbbsrw/v12y2023i1p10-19.html
   My bibliography  Save this article

Back from the Future: Mediation and Prediction of Events Uncertainty through Event-Driven Models (EDMs)

Author

Listed:
  • Samuel Ogbeibu
  • James Gaskin

Abstract

The event-driven model (EDM) is an emerging concept in human behavioural research, and understanding how EDMs can promote theory development remains a fundamental quest of predictive science. Traditionally, researchers have heavily depended upon theory confirmation and the inclusion of mediating constructs to clarify uncertainty associated with plausible events (e.g. political, socio-economic, technological, environmental). Though this approach has pushed the field forward, it has also steered mediation research towards largely ignoring the fundamental role of prediction as a key for better understanding future events represented by EDMs. Additionally, emerging research using partial least squares structural equation modelling to execute prediction-oriented analysis continues to overlook problematic endogeneity bias and plausible type IV errors due to omitted paths and neglect of indirect effect size estimation in mediation models that embrace the transmittal or segmentation mediation approaches. We aim to introduce prediction as a fundamental option for estimating EDMs and recommend that researchers employ the segmentation mediation approach when estimating EDMs. We further emphasize a novel direct and indirect ( v ) effect size measure, types of prediction and cases when they are useful. Best practices and practical implications are provided to foster a more useful interpretation of findings.

Suggested Citation

  • Samuel Ogbeibu & James Gaskin, 2023. "Back from the Future: Mediation and Prediction of Events Uncertainty through Event-Driven Models (EDMs)," FIIB Business Review, , vol. 12(1), pages 10-19, March.
  • Handle: RePEc:sae:fbbsrw:v:12:y:2023:i:1:p:10-19
    DOI: 10.1177/23197145221121084
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/23197145221121084
    Download Restriction: no

    File URL: https://libkey.io/10.1177/23197145221121084?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Edward E. Rigdon & Marko Sarstedt & Jan-Michael Becker, 2020. "Quantify uncertainty in behavioral research," Nature Human Behaviour, Nature, vol. 4(4), pages 329-331, April.
    2. Samuel Ogbeibu & Charbel Jose Chiappetta Jabbour & James Gaskin & Abdelhak Senadjki & Mathew Hughes, 2021. "Leveraging STARA competencies and green creativity to boost green organisational innovative evidence: A praxis for sustainable development," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2421-2440, July.
    3. John Antonakis & Samuel Bendahan & Philippe Jacquart & Rafael Lalive, 2010. "On making causal claims : A review and recommendations," Post-Print hal-02313119, HAL.
    4. Soukaina Zaoui & Safae Ait Hamou-ou-Brahim & Haiwei Zhou & Amina Omrane & Dechun Huang, 2021. "Consumer Purchasing Behaviour Towards Strategic Innovation Management Practices in Morocco During COVID-19 Health Crisis," FIIB Business Review, , vol. 10(2), pages 158-171, June.
    5. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    6. Kanupriya, 2020. "COVID-19: A Socio-economic Perspective," FIIB Business Review, , vol. 9(3), pages 161-166, September.
    7. Shalini Sahni & Shyama Kumari & Prachi Pachaury, 2021. "Building Emotional Resilience with Big Five Personality Model Against COVID-19 Pandemic," FIIB Business Review, , vol. 10(1), pages 39-51, March.
    8. Peter J Jordan & Ashlea C Troth, 2020. "Common method bias in applied settings: The dilemma of researching in organizations," Australian Journal of Management, Australian School of Business, vol. 45(1), pages 3-14, February.
    9. Ilan Alon, 2020. "COVID-19 and International Business: A Viewpoint," FIIB Business Review, , vol. 9(2), pages 75-77, June.
    10. Shmueli, Galit & Ray, Soumya & Velasquez Estrada, Juan Manuel & Chatla, Suneel Babu, 2016. "The elephant in the room: Predictive performance of PLS models," Journal of Business Research, Elsevier, vol. 69(10), pages 4552-4564.
    11. V S Kesaraju & F W Ciarallo, 2012. "Integrated simulation combining process-driven and event-driven models," Journal of Simulation, Taylor & Francis Journals, vol. 6(1), pages 9-20, February.
    12. Gurleen Kaur & Chanpreet Kaur, 2020. "COVID-19 and the Rise of the New Experience Economy," FIIB Business Review, , vol. 9(4), pages 239-248, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mahadzirah Mohamad & Asyraf Afthanorhan* & Zainudin Awang & Morliyati Mohammad, 2019. "Comparison Between CB-SEM and PLS-SEM: Testing and Confirming the Maqasid Syariah Quality of Life Measurement Model," The Journal of Social Sciences Research, Academic Research Publishing Group, vol. 5(3), pages 608-614, 03-2019.
    2. Evermann, Joerg & Tate, Mary, 2016. "Assessing the predictive performance of structural equation model estimators," Journal of Business Research, Elsevier, vol. 69(10), pages 4565-4582.
    3. Dirk De Clercq & Eugene Kaciak & Narongsak (Tek) Thongpapanl, 2023. "Full circle support: unpacking the relationship between women entrepreneurs’ family-to-work support and work interference with family," International Entrepreneurship and Management Journal, Springer, vol. 19(1), pages 343-367, March.
    4. Jörg Henseler, 2018. "Partial least squares path modeling: Quo vadis?," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 1-8, January.
    5. Hair, Joseph F. & Astrachan, Claudia Binz & Moisescu, Ovidiu I. & Radomir, Lăcrămioara & Sarstedt, Marko & Vaithilingam, Santha & Ringle, Christian M., 2021. "Executing and interpreting applications of PLS-SEM: Updates for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 12(3).
    6. Dash, Ganesh & Paul, Justin, 2021. "CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    7. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    8. Chavez, Daniel E. & Palma, Marco A. & Nayga, Rodolfo M. & Mjelde, James W., 2020. "Product availability in discrete choice experiments with private goods," Journal of choice modelling, Elsevier, vol. 36(C).
    9. Salzmann, Leonard, 2020. "The Impact of Uncertainty and Financial Shocks in Recessions and Booms," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224588, Verein für Socialpolitik / German Economic Association.
    10. Bryan Cheng-Yu Hsu & Yu-Feng Wu & Hsin-Wei Chen & Man-Lai Cheung, 2020. "How Sport Tourism Event Image Fit Enhances Residents’ Perceptions of Place Image and Their Quality of Life," Sustainability, MDPI, vol. 12(19), pages 1-14, October.
    11. Joel M. David & Venky Venkateswaran, 2019. "The Sources of Capital Misallocation," American Economic Review, American Economic Association, vol. 109(7), pages 2531-2567, July.
    12. Bakas, Dimitrios & Triantafyllou, Athanasios, 2020. "Commodity price volatility and the economic uncertainty of pandemics," Economics Letters, Elsevier, vol. 193(C).
    13. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    14. Shahzad, Syed Jawad Hussain & Raza, Naveed & Balcilar, Mehmet & Ali, Sajid & Shahbaz, Muhammad, 2017. "Can economic policy uncertainty and investors sentiment predict commodities returns and volatility?," Resources Policy, Elsevier, vol. 53(C), pages 208-218.
    15. Juan M. Londono & Mehrdad Samadi, 2023. "The Price of Macroeconomic Uncertainty: Evidence from Daily Options," International Finance Discussion Papers 1376, Board of Governors of the Federal Reserve System (U.S.).
    16. Kautish, Pradeep & Paço, Arminda & Thaichon, Park, 2022. "Sustainable consumption and plastic packaging: Relationships among product involvement, perceived marketplace influence and choice behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    17. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
    18. Wensheng Kang & Ronald A. Ratti & Joaquin Vespignani, 2020. "Impact of global uncertainty on the global economy and large developed and developing economies," Applied Economics, Taylor & Francis Journals, vol. 52(22), pages 2392-2407, May.
    19. Taisuke Nakata & Hiroatsu Tanaka, 2020. "Equilibrium Yield Curves and the Interest Rate Lower Bound," CARF F-Series CARF-F-482, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    20. Shin, Minchul & Zhang, Boyuan & Zhong, Molin & Lee, Dong Jin, 2018. "Measuring international uncertainty: The case of Korea," Economics Letters, Elsevier, vol. 162(C), pages 22-26.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:fbbsrw:v:12:y:2023:i:1:p:10-19. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.