ABSTRACT
Manufacturers utilize dual-channel supply-chain to cope with customer preferences. This structure allows manufacturer’s online facility and conventional retailer to deliver their products more efficiently. However, this mechanism also brings up anew internal competition between manufacturers and retailers. To observe the price effect within this system, response surface methodology is used to model the customer preference. The independent variables are online and retailer prices, while the dependent variables are price and cross-price sensitivities. To simulate proposed model into real-practice, game theory is employed. The strategies are the priority of each channel price and cross-price sensitivities. Based on this game model, a Nash equilibrium is obtained. This research proposes anovelty by means of the usage of response surface results as game theory payoffs to represent the uncertainty in a competitive environment. The integration of response surface model and game matrix can be used as managerial implication in predicting competitors’ behaviour.
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No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Erwin Widodo
Erwin Widodo is currently an associate professor of Quantitative Modeling and Industrial Policy Analysis (QMIPA) Laboratory in the Department of Industrial and System Engineering at Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia. He was granted his Master's Degree from Ritsumeikan University of Kyoto and his Doctoral Degree from Hiroshima University both in Japan, in 2006 and 2012 respectively. He actively joins several international associations related to his field, i.e. IDGS, Informs, IAEng, IEOM, and the likes. Moreover, he also joins as board member in several international journals such as IJISE, OSCM, IJTech, Cogent Engineering, etc. His research activities include multi-player decision-making in industry especially by using game theory.
Januardi
Januardi is a master of engineering graduate from Industrial and System Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia. He received a Bachelor’s degree in Agroindustrial Technology from the IPB University, Bogor, Indonesia, in 2017. Currently, he continues his doctoral study in and the Ph.D. degree in Industrial Management at the National Taiwan University of Science and Technology, Taipei, Taiwan. His present research interests include quantitative modeling in operation research, decision making using statistical approach, and experimental design especially the application of response surface methodology.