以系統動力學方法模擬零售業線上線下跨平台營運

Abstract

零售業不斷發展，線上與線下界限逐步模糊，單純選擇線上或線下的顧客逐步 減少，更多的顧客在全通路上購物。潛在消費者的流向變化受多個因素影響，並形 成一個系統，在系統中影響因素相互之間存在聯繫，改變其中一項會如蝴蝶效應一 般對其他量產生影響。 本論文建立一個基於 Bass 擴散模型的系統動力學模型，通過對線上或線下顧 客的轉換進行系統動力學分析，改變其中的迴圈狀態數量值進而調控整個系統的 變化，在隨著時間推移的動態模擬中發現客流的變化，並找尋相關的影響因素。並 且通過利潤模型反應改變系統迴圈的狀態量之後對於利潤的影響效果。 研究的結果發現線上或線下顧客在向全通路顧客轉換過程中，轉移使用場景 所引起的延遲效應會對線下顧客數量帶來一定影響，社交網路平台傳播的可觸及 的人數會影響顧客轉換的速率。引導潛在顧客消費對於利潤的影響較大，零售商在 投入在引導顧客全通路購物同時也需要引導潛在消費者購物進而確保利潤最大化。 本研究的意義在於通過系統動力學方法對線上線下轉換過程簡化模型進行動 態模擬，從而展現短期到長期的不同狀態下的變化，也是第一次將 Bass 擴散模型 應用在線上線下轉化的系統動力學模擬中。在後繼研究中可以提供模型基礎，通過 增加模型複雜度展開研究，同時也為企業提供了系統動力學對於本身零售線上線 下預測及分析的模型基礎。

With the continuous development of the retail industry, the boundaries between online and offline are gradually blurred, and the customers who simply choose either online or offline to shopping are gradually decreasing. More customers are shopping in both ways. The preferences of the potential consumers is affected by multiple factors in a form of system. The factors in the system are corelated to each other, and changing one of them will have an impact on others. The research has conducted a system dynamics analysis based on the Bass diffusion model. The model can simulate the consumer flow between the online and offline in the timeline, by controlling the loop’s status value, the variances can help to explore the key influencing factors. And through the profit model shows the change of the profit. The results of the study found that the online or offline customers in the process of transitioning to full-channel customers, the delay effect caused by the transfer of usage scenarios will have an impact on the number of offline customers, the number of reachable persons of social network platforms will affect the rate of conversion. Leading potential customers to consumption has a greater impact on profitability. Retailers invest in directing customers' full-channel shopping. They also need to lead potential consumers to purchase and thus ensure profit maximization. This research use dynamic simulation of the simplified model of the online and offline conversion process through system dynamics, to show the changes in different conditions from short-term to long-term, and it is also the first time that the Bass diffusion model is applied online and offline conversion system. In the follow-up studies, the model foundation can be provided, and the research can be carried out by increasing the complexity of the model. At the same time, it also provides the model foundation for system dynamics for the online offline forecasting and analysis of retail sales.