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    題名: 考量消費者適應學習與供應商洩密行為之零售商價格競爭模式之研究
    其他題名: The Research on Pricing Competitive Model for Retailers with Adaptive Learning Behavior of Consumers and Information Leakage Behavior of Suppliers
    作者: 林我聰
    貢獻者: 國立政治大學資訊管理學系
    行政院國家科學委員會
    關鍵詞: 售商價格競爭模式
    日期: 2011
    上傳時間: 2012-08-30 15:51:24 (UTC+8)
    摘要: 零售商面臨商品具同質性與成本結構差異性小的情況下，如何與供應商合作靈活應用價格調整， 一直是零售商的價格策略；然而由於目前大型化與連鎖化之零售商形成寡占競爭市場，每家零售商的 價格策略對市場都具有某種程度的影響力，因此在擬定價格決策時需同時考慮競爭對手的反應，再思 考最適策略。此以價格競爭做為互動策略，即為柏川（Bertrand）價格競爭模式（Pricing Competitive Model），已有許多相關研究應用此模式分析廠商的價格競爭。過去藉由Bertrand 價格競爭模式進行分 析時，簡化並假設消費者購買決策行為是以低價購買策略及靜態不變；然而文獻中指出消費者購買決 策並非如此，而應是根據購買經驗而動態的自我調適決策行為的適應模式。因此分析零售商價格競爭 模式時，考量消費者具有適應性學習的動態特性之購買決策行為，將有助於提供更貼近實務上的分 析。另一方面，過去研究較少考量到供應商與零售商進行合作時，其於價格競爭下所扮演的角色。較 新研究指出零售商進行需求預測資訊的分享時，所產生的供應商洩密行為，會影響供應商及零售商的 價格決策；然而其並未深入探討此現象將如何影響零售商價格競爭互動。緣此，為補足與擴展價格競 爭模式在文獻上的缺口，本研究以零售商之價格競爭為基礎，以動態的觀點，向下延伸納入「消費者 適應學習行為（Adaptive Learning Behavior）」，向上納入供應商，考量「供應鏈（Supply Chain）中 資訊分享（Information Sharing）與資訊洩密（Information Leakage）的互動行為」，以探究其將如何 影響零售商之價格競爭模式。同時在方法上，傳統之解析式模式（Analytical Model）已相當困難來處 理動態的互動模式，本研究選擇應用代理人基塑模與模擬方法（Agent-based Modeling and Simulation） 來建構本研究之動態適應性系統。 針對上述狀況，本研究提出一個二年期研究計畫：第一年針對納入消費者適應學習行為的零售商 價格競爭模式進行建模與探討，此階段以Bertrand 價格競爭模式做為零售商價格競爭之基礎，應用演 譯-歸納行為決策模式（模糊邏輯與基因演算法）詮釋零售商之價格競爭學習行為，並以強化學習 （Reinforcement Learning）與群體演算法（Particle Swarm Algorithm）模式化消費者購買決策之適應學 習行為。第二年再加入供應商，擴展成一供應鏈結構（包含消費者、零售商與供應商）；此結構中各 零售商擁有其私有需求預測資訊，並與供應商進行資訊分享；供應商根據資訊制定批發價格及洩密決 策，最後零售商根據批發價格進行定價與訂購行為。個體在最大化本身利益下，以重複訊息賽局 （Signaling Game）作為三方互動模式的基礎，模式化其動態地互動及演化的結果。 本研究所提出的價格競爭模式可幫助零售商於制定價格策略時，考量消費者適應學習行為及供應 商洩密行為，對價格競爭的影響；並可藉由模擬，分析所產生的最適策略及觀察最後價格競爭的均衡 或失衡特性，以提供零售商制定價格策略的具體建議。
    The pricing competitive model traditionally assumes that consumers will buy from the firm selling the (homogeneous) product at the lowest price, thus discarding any possibility of adaptive learning behavior on the demand side. But if, as in real competition, consumers learn adaptively and competition is a dynamic process, then some attention should be paid to consumers` behavior. In the recent years, supply chains are beginning to displace firms as the competitive entity in the global marketplace. Demand forecasting information sharing between suppliers and retailers can improve the accuracy of demand forecasts, which enables better pricing decisions on wholesale and retail price. However, in a supply chain environment, information transmitted from a retailer to the supplier can be leaked to other retailers and affects pricing decisions on wholesale and retail price. We are interest in this question: How does the adaptive learning behavior affect the pricing competitive model? How does the threat of leakage affect the pricing competitive model and their order quantities and sales? Therefore, this project attempts to study a version of the pricing competitive (Bertrand) model in which consumer exhibit dynamic adaptive learning behavior when deciding from what retailers they will buy and the impact of information leakage of the supplier on the pricing competitive model between retailers. This research will be a two-year project to study two main issues to reflect upon the above requests includes adaptive learning of consumer behavior and leakage of supplier. In the first year, for Adaptive Learning of Consumer Behavior stage, we propose a model which considers both competitive responses and adaptive learning consumer behavior. We use the competition theory, fuzzy logic, genetic algorithms to model the competitive behavior between firms and use reinforcement learning and particle swarm algorithms to model consumers’ adaptive learning behavior. Using agent-based modeling and simulation (ABMS) to construct the competitive market and can identify possible outcomes when pricing competitive model with Adaptive Learning of Consumer Behavior. In the second year, for leakage of supplier stage, we consider to join the supplier into the pricing competitive model to form a decentralized supply chain. Each retailer has some private forecasting information about the uncertain demand which he disclose to the supplier. The supplier then sets a wholesale price based on the information received or leakage to other retailers. The retailers decide the retail price and order quantity. We formulate above interaction as signaling games and to analyze the signaling effect and its impact on the pricing competition of retailers. The proposed pricing competitive model with adaptive learning of consumer behavior and leakage of supplier can help retailers to analyze pricing strategy and further discovery and design the more optimal pricing strategy.
    關聯: 應用研究
    學術補助
    研究期間:10008~ 10107
    研究經費:543仟元
    資料類型: report
    顯示於類別:[資訊管理學系] 國科會研究計畫

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