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Restrictiveness and guidance in support systems

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  • Goodwin, Paul
  • Fildes, Robert
  • Lawrence, Michael
  • Stephens, Greg

Abstract

Restrictiveness and guidance have been proposed as methods for improving the performance of users of support systems. In many companies computerized support systems are used in demand forecasting enabling interventions based on management judgment to be applied to statistical forecasts. However, the resulting forecasts are often 'sub-optimal' because many judgmental adjustments are made when they are not required. An experiment was used to investigate whether restrictiveness or guidance in a support system leads to more effective use of judgment. Users received statistical forecasts of the demand for products that were subject to promotions. In the restrictiveness mode small judgmental adjustments to these forecasts were prohibited (research indicates that these waste effort and may damage accuracy). In the guidance mode users were advised to make adjustments in promotion periods, but not to adjust in non-promotion periods. A control group of users were not subject to restrictions and received no guidance. The results showed that neither restrictiveness nor guidance led to improvements in accuracy. While restrictiveness reduced unnecessary adjustments, it deterred desirable adjustments and also encouraged over-large adjustments so that accuracy was damaged. Guidance encouraged more desirable system use, but was often ignored. Surprisingly, users indicated it was less acceptable than restrictiveness.

Suggested Citation

  • Goodwin, Paul & Fildes, Robert & Lawrence, Michael & Stephens, Greg, 2011. "Restrictiveness and guidance in support systems," Omega, Elsevier, vol. 39(3), pages 242-253, June.
  • Handle: RePEc:eee:jomega:v:39:y:2011:i:3:p:242-253
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    1. Eroglu, Cuneyt & Croxton, Keely L., 2010. "Biases in judgmental adjustments of statistical forecasts: The role of individual differences," International Journal of Forecasting, Elsevier, vol. 26(1), pages 116-133, January.
    2. Lee, Wing Yee & Goodwin, Paul & Fildes, Robert & Nikolopoulos, Konstantinos & Lawrence, Michael, 2007. "Providing support for the use of analogies in demand forecasting tasks," International Journal of Forecasting, Elsevier, vol. 23(3), pages 377-390.
    3. Kottemann, Jeffrey E. & Davis, Fred D. & Remus, William E., 1994. "Computer-Assisted Decision Making: Performance, Beliefs, and the Illusion of Control," Organizational Behavior and Human Decision Processes, Elsevier, vol. 57(1), pages 26-37, January.
    4. Yaniv, Ilan & Kleinberger, Eli, 2000. "Advice Taking in Decision Making: Egocentric Discounting and Reputation Formation," Organizational Behavior and Human Decision Processes, Elsevier, vol. 83(2), pages 260-281, November.
    5. Fagerholt, Kjetil & Christiansen, Marielle & Magnus Hvattum, Lars & Johnsen, Trond A.V. & Vabø, Thor J., 2010. "A decision support methodology for strategic planning in maritime transportation," Omega, Elsevier, vol. 38(6), pages 465-474, December.
    6. Harvey, Nigel, 1995. "Why Are Judgments Less Consistent in Less Predictable Task Situations?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 63(3), pages 247-263, September.
    7. Goodwin, Paul, 2000. "Improving the voluntary integration of statistical forecasts and judgment," International Journal of Forecasting, Elsevier, vol. 16(1), pages 85-99.
    8. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    9. Mark S. Silver, 1990. "Decision Support Systems: Directed and Nondirected Change," Information Systems Research, INFORMS, vol. 1(1), pages 47-70, March.
    10. G.Y. Tütüncü & B.M. Carreto Baker, 2009. "A visual interactive approach to the classical and mixed vehicle routing problems with backhauls," Post-Print hal-00581628, HAL.
    11. Yaniv, Ilan, 2004. "Receiving other people's advice: Influence and benefit," Organizational Behavior and Human Decision Processes, Elsevier, vol. 93(1), pages 1-13, January.
    12. Webby, Richard & O'Connor, Marcus & Edmundson, Bob, 2005. "Forecasting support systems for the incorporation of event information: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 21(3), pages 411-423.
    13. Willemain, Thomas R., 1991. "The effect of graphical adjustment on forecast accuracy," International Journal of Forecasting, Elsevier, vol. 7(2), pages 151-154, August.
    14. Harvey, Nigel & Bolger, Fergus, 1996. "Graphs versus tables: Effects of data presentation format on judgemental forecasting," International Journal of Forecasting, Elsevier, vol. 12(1), pages 119-137, March.
    15. O'Connor, Marcus & Remus, William & Griggs, Ken, 1993. "Judgemental forecasting in times of change," International Journal of Forecasting, Elsevier, vol. 9(2), pages 163-172, August.
    16. Remus, William, 1986. "Graduate students as surrogates for managers in experiments on business decision making," Journal of Business Research, Elsevier, vol. 14(1), pages 19-25, February.
    17. Igal Hendel & Aviv Nevo, 2003. "The Post-Promotion Dip Puzzle: What do the Data Have to Say?," Quantitative Marketing and Economics (QME), Springer, vol. 1(4), pages 409-424, December.
    18. Sanders, Nada R. & Graman, Gregory A., 2009. "Quantifying costs of forecast errors: A case study of the warehouse environment," Omega, Elsevier, vol. 37(1), pages 116-125, February.
    19. Remus, William & O'Connor, Marcus & Griggs, Kenneth, 1998. "The impact of incentives on the accuracy of subjects in judgmental forecasting experiments," International Journal of Forecasting, Elsevier, vol. 14(4), pages 515-522, December.
    20. Robert C. Blattberg & Stephen J. Hoch, 1990. "Database Models and Managerial Intuition: 50% Model + 50% Manager," Management Science, INFORMS, vol. 36(8), pages 887-899, August.
    21. YazgI Tütüncü, G. & Carreto, Carlos A.C. & Baker, Barrie M., 2009. "A visual interactive approach to classical and mixed vehicle routing problems with backhauls," Omega, Elsevier, vol. 37(1), pages 138-154, February.
    22. Bonaccio, Silvia & Dalal, Reeshad S., 2006. "Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 127-151, November.
    23. Goodwin, Paul, 2002. "Integrating management judgment and statistical methods to improve short-term forecasts," Omega, Elsevier, vol. 30(2), pages 127-135, April.
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    2. Baecke, Philippe & De Baets, Shari & Vanderheyden, Karlien, 2017. "Investigating the added value of integrating human judgement into statistical demand forecasting systems," International Journal of Production Economics, Elsevier, vol. 191(C), pages 85-96.
    3. Chi-Wen Chen & Marios Koufaris, 2015. "The impact of decision support system features on user overconfidence and risky behavior," European Journal of Information Systems, Taylor & Francis Journals, vol. 24(6), pages 607-623, November.
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      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Syntetos, Aris A. & Kholidasari, Inna & Naim, Mohamed M., 2016. "The effects of integrating management judgement into OUT levels: In or out of context?," European Journal of Operational Research, Elsevier, vol. 249(3), pages 853-863.
    6. Hewage, Harsha Chamara & Perera, H. Niles & De Baets, Shari, 2022. "Forecast adjustments during post-promotional periods," European Journal of Operational Research, Elsevier, vol. 300(2), pages 461-472.
    7. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    8. Abolghasemi, Mahdi & Hurley, Jason & Eshragh, Ali & Fahimnia, Behnam, 2020. "Demand forecasting in the presence of systematic events: Cases in capturing sales promotions," International Journal of Production Economics, Elsevier, vol. 230(C).
    9. Mălăescu, Irina & Sutton, Steve G., 2015. "The effects of decision aid structural restrictiveness on cognitive load, perceived usefulness, and reuse intentions," International Journal of Accounting Information Systems, Elsevier, vol. 17(C), pages 16-36.
    10. Arvan, Meysam & Fahimnia, Behnam & Reisi, Mohsen & Siemsen, Enno, 2019. "Integrating human judgement into quantitative forecasting methods: A review," Omega, Elsevier, vol. 86(C), pages 237-252.
    11. Alvarado-Valencia, Jorge & Barrero, Lope H. & Önkal, Dilek & Dennerlein, Jack T., 2017. "Expertise, credibility of system forecasts and integration methods in judgmental demand forecasting," International Journal of Forecasting, Elsevier, vol. 33(1), pages 298-313.
    12. Van den Broeke, Maud & De Baets, Shari & Vereecke, Ann & Baecke, Philippe & Vanderheyden, Karlien, 2019. "Judgmental forecast adjustments over different time horizons," Omega, Elsevier, vol. 87(C), pages 34-45.
    13. Önkal, Dilek & Zeynep Sayım, K. & Lawrence, Michael, 2012. "Wisdom of group forecasts: Does role-playing play a role?," Omega, Elsevier, vol. 40(6), pages 693-702.
    14. Fildes, Robert & Goodwin, Paul, 2021. "Stability in the inefficient use of forecasting systems: A case study in a supply chain company," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1031-1046.
    15. Plaza, Malgorzata, 2016. "Balancing the costs of human resources on an ERP project," Omega, Elsevier, vol. 59(PB), pages 171-183.

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