結合人工智慧之產品生命週期價值與作業價值管理研究：以P通路代理商為例

Integrating Artificial Intelligence into Product Life Cycle Value and Activity Value Management: A Case Study of P Channel Agent

企業藉由提供產品與服務以獲利，並透過行銷策略追求利潤最大化。然而，產品在市場中能存續多久？其整個生命週期又能創造多少價值？相關研究仍付之闕如。本文旨在探討產品生命週期價值（Product Life Cycle Value；PLCV）之衡量方式，並結合作業價值管理（Activity Value Management；AVM）系統，以AVM產出的產品利潤資訊為基礎，建立PLCV的估算架構。本文也導入人工智慧（AI）技術建構與驗證預測模型，以提升預測準確性與實務應用價值。研究採實地實證法，以國內某知名通路代理商為對象，分析其代理產品的生命週期長度與價值，並結合通路區域的人口統計變數，探討影響高生命週期價值產品獲利的關鍵特徵，期能提供企業於產品組合管理與資源配置決策上之策略啟示。

Enterprises generate profits by providing products and services, aiming to maximize profits through effective marketing strategies. However, how long can a product survive, and how much profit can it generate throughout its entire life cycle? Related studies remain rare. As this area has not been thoroughly explored by scholars, this study aims to develop a method for measuring Product Life Cycle Value (PLCV). By integrating with Activity Value Management (AVM), this research utilizes profit information produced through AVM as the foundation for estimating PLCV. This study also incorporates Artificial Intelligence techniques to construct and validate predictive models for PLCV, thereby enhancing forecasting accuracy and practical applicability. We adopt the field-based empirical approach, with a well-known domestic channel agent serving as the research subject. From the perspective of the channel agent, the study investigates the life cycle duration and value of distributed products. Furthermore, for products with greater PLCV, the study combines demographic variables from the corresponding channel regions to identify the key population characteristics that influence profitability, thereby improving the effectiveness of resource allocation decisions.