Abstract
The trend of digitalization has led to disruptive changes in production and supply chain planning, where autonomous machines and artificial intelligence gain competitive advantages. Besides, the satisfaction of customers’ wishes has reached top priority for demand-driven companies. Consequently, companies implement digital applications, for instance neural networks for accurate demand forecasting and optimized decision-making tools, to cope with nervous operational planning activities. Since planning tasks require human-machine interaction to increase performance and efficiency of planning decisions, this analysis focuses on forms of interaction to determine the right level of collaboration. The paper outlines various levels of interaction and analyses the impact of human reactions in the context of an industrial demand planning algorithm use case at Infineon Technologies AG conducting a behavioral experiment. The results show that a variance in the levels of human-machine interaction has influence on human acceptance of algorithms, but further experiments need to be conducted to outline an overall framework.
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References
Chapman, S., Ettkin, L., Helms, M.: Supply chain forecasting – collaborative forecasting supports supply chain management. Bus. Process Manage. J. 6, 392–407 (2000)
Goodwin, P., Önkal, D., Thomson, M.: Do forecasts expressed as prediction intervals improve production planning decisions? Eur. J. Oper. Res. 205, 195–201 (2010)
Holden, K., Peel, D., Thompson, J.: Economic Forecasting. Cambridge University Press, Cambridge (1991)
O’Connor, M., Webby, R.: Judgmental and statistical time series forecasting - a review of the literature. Int. J. Forecast. 12, 91–118 (1996)
Anderson, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., Makridakis, S., Newton, J., Parzen, E., Winkler, R.: The accuracy of extrapolation (time series) methods - results of a forecasting competition. J. Forecast. 1, 111–153 (1982)
Clemen, R.: Combining forecasts: a review and annotated bibliography. Int. J. Forecast. 5, 559–583 (1989)
Armstrong, J.S., Collopy, F.: Integration of statistical methods and judgment for time series forecasting - principles from empirical research. In: Wright, G., Good-win, P. (eds.) Forecasting with Judgment, pp. 269–293. Wiley, New York (1998)
Armstrong, S., Collopy, F.: Rule-based forecasting: development and validation of an expert systems approach to combining time series extrapolations. Manage. Sci. 38, 1394–1414 (1992)
Allen, G., Fildes, R.: Econometric forecasting. In: Armstrong, J.S. (ed.) Principles of Forecasting - A Handbook for Researchers and Practitioners. Springer, Norwell (2001)
Edmundson, R., Lawrence, M., O’Connor, M.: The accuracy of combining judgmental and statistical forecasts. Manage. Sci. 32, 1521–1532 (1986)
Bunn, D., Wright, G.: Interaction of judgmental and statistical forecasting methods - issues & analysis. Manage. Sci. 37, 501–518 (1991)
Leitner, J., Leopold-Wildburger, U.: Experiments on forecasting behavior with several sources of information – a review of the literature. Eur. J. Oper. Res. 213, 459–469 (2011)
Goodwin, P., Lawrence, M., O’Connor, M., Önkal, D.: Judgmental forecasting: a review of progress over the last 25 years. Int. J. Forecast. 22, 493–518 (2006)
Fildes, R., Goodwin, P., Lawrence, M.: The design features of forecasting support systems and their effectiveness. Decis. Support Syst. 42, 351–361 (2006)
Edmundson, R., Lawrence, M., O’Connor, M.: The accuracy of combining judgemental and statistical forecasts. Manage. Sci. 32, 1521–1532 (1986)
Sheridan, T., Verplank, W.: Human and Computer Control of Undersea Teleoperators. MIT Man-Machine Systems Laboratory, Cambridge (1978)
Parasuraman, R., Sheridan, T., Wickens, C.: A model for types and levels of human interaction with automation. IEEE Trans. Syst. Man Cybern. - Part A: Syst. Hum. 30, 286–297 (2000)
Johannsen, G.: Human-Machine Interaction. Control Systems, Robotics, and Automation. Encyclopedia of Life Support Systems (EOLSS). EOLSS Publishers, Oxford (2007)
Zheng, N., Liu, Z., Ren, P., Ma, Y., Chen, S., Yu, S., Xue, J., Chen, Ba., Wang, F.: Hybrid-augmented intelligence: collaboration and cognition. Front. Inf. Tech. Electron. Eng. 18, 153–179 (2017)
Johnson, M., Bradshaw, J.M., Feltovich, P.J.: Tomorrow’s human-machine design tools: from levels of automation to interdependencies. J. Cogn. Eng. Decis. Making 12, 77–82 (2017)
Bonaccio, S., Dalal, R.: What types of advice do decision-makers prefer? Organ. Behav. Hum. Decis. Process. 112, 11–23 (2010)
Fischer, I., Harvey, N.: Taking advice - accepting help, improving judgment, and sharing responsibility. Organ. Behav. Hum. Decis. Process. 70, 117–133 (1997)
Kahneman, D., Tversky, A.: Judgment under uncertainty - heuristics and biases. Science 185, 1124–1131 (1974)
Kleinberger, E., Yaniv, H.: Advice taking in decision making - egocentric discounting and reputation formation. Organ. Behav. Hum. Decis. Process. 83, 260–281 (2000)
Fischer, I., Harvey, N.: Taking advice - accepting help, improving judgment, and sharing responsibility. Organ. Behav. Hum. Decis. Process. 70, 117–133 (1997)
Önkal, D., Goodwin, P., Thomson, M., Gönül, S., Pollock, A.: The relative influence of advice from human experts and statistical methods on forecast adjustments. J. Behav. Decis. Making 22(4), 390–409 (2009)
Dietvorst, B., Massey, C., Simmons, J.: Algorithm aversion - people erroneously avoid algorithms after seeing them err. J. Exp. Psychol. Gen. 144, 114–126 (2015)
Bonaccio, S., Dalal, R.: Advice taking and decision-making - an integrative literature review, and implications for the organizational sciences. Organ. Behav. Hum. Decis. Process. 101, 127–151 (2006)
Dijkstra, J.: User agreement with incorrect expert system advice. Behav. Inform. Technol. 18, 399–411 (1999)
Logg, J.: Theory of machine - when do people reply on algorithms? Hav. Bus. Sch. 17-086, 1–92 (2017)
Madhavan, P., Wiegmann, D.: Effects of information source, pedigree, and reliability on operator interaction with decision support systems. Hum. Factors 49, 773–785 (2007)
Kleinberger, E., Yaniv, H.: Advice taking in decision making - egocentric discounting and reputation formation. Organ. Behav. Hum. Decis. Process. 83, 260–281 (2000)
Dietvorst, B., Massey, C., Simmons, J.: Overcoming algorithm aversion - people will use imperfect algorithms if they can (even slightly) modify them. Manage. Sci. 64, 1–17 (2016)
Griggs, K., O’Conner, M., Remus, W.: Does feedback improve the accuracy of recurrent judgmental forecasts? Organ. Behav. Hum. Decis. Process. 66, 22–30 (1996)
Fildes, R., Goodwin, P.: Judgmental forecasts of time series affected by special events - does providing a statistical forecast improve accuracy? J. Behav. Decis. Making 12, 37–53 (1983)
Schiller, C., Yachi, G.: Introduction to Demand Planning. Supply Chain Academy, Infineon Technologies AG, Munich (2017)
Schiller, C., Yachi, G.: Production Program, Demand Planning, Target Stock Entry in SPLUI. Supply Chain Academy, Infineon Technologies AG, Munich (2014)
Andersen, A., Carbone, R., Corriveau, Y., Corson, P.: Comparing for different time series methods the value of technical expertise individualized analysis, and judgmental adjustment. Manage. Sci. 29, 559–566 (1983)
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Lauer, T., Welsch, R., Ramlah Abbas, S., Henke, M. (2020). Behavioral Analysis of Human-Machine Interaction in the Context of Demand Planning Decisions. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2019. Advances in Intelligent Systems and Computing, vol 965. Springer, Cham. https://doi.org/10.1007/978-3-030-20454-9_13
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