Pricing of Product Line Along With Its Value-Added Services With Consideration of Effects of Reference Price

IF 4.5 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Wei Qi;Nan Li;Junwei Wang;Xinggang Luo
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引用次数: 0

Abstract

Customers’ price comparison behavior and search cost evaluation play a pivotal role in shaping purchasing utility and enterprise pricing strategies. This study employs the multinomial logit (MNL) model to integrate the reference price and search cost into product line design. We probe into pure bundle and mixed bundle pricing decisions for the product line and value-added services in monopolistic settings and delve into the impacts of the reference price and search cost on pricing, profit, product variety, and strategy. Based on model analysis and numerical simulations, the results show that the reference price effect benefits low-priced offerings but undermines high-priced products, overall market share, and profit. As the reference price effect or search cost increases, product variety diminishes. In scenarios where the reference price effect and the proportion of bundled purchases are minimal, the pure bundling strategy is preferable; otherwise, the mixed bundling strategy is more advantageous. When enterprises overlook the reference price effect, there is an imbalance in the pricing of various products and services within the product line, which results in the actual market share and profit consistently falling below the ideal expectations.
考虑参考价格影响的产品线及其增值服务定价
顾客的比价行为和搜索成本评价在采购效用和企业定价策略的形成中起着举足轻重的作用。本研究采用多项logit (MNL)模型,将参考价格与搜寻成本整合到产品线设计中。我们探讨了在垄断环境下的产品线和增值服务的纯捆绑和混合捆绑定价决策,并深入研究了参考价格和搜索成本对定价、利润、产品种类和策略的影响。基于模型分析和数值模拟的结果表明,参考价格效应有利于低价产品,但不利于高价产品的整体市场份额和利润。随着参考价格效应或搜索成本的增加,产品种类减少。在参考价格效应和捆绑购买比例最小的情况下,纯捆绑策略更可取;否则,混合捆绑策略更为有利。当企业忽略参考价格效应时,产品线内各种产品和服务的定价不平衡,导致实际市场份额和利润持续低于理想预期。
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来源期刊
IEEE Transactions on Computational Social Systems
IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)
CiteScore
10.00
自引率
20.00%
发文量
316
期刊介绍: IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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