Retailer's EOQ Model with Limited Storage Space Under Partially Permissible Delay in Payments

The main purpose of this paper wants to investigate the optimal retailer's lot-sizing policy with two warehouses under partially permissible delay in payments within the economic order quantity (EOQ) framework. In this paper, we want to extend that fully permissible delay in payments to the supplier would offer the retailer partially permissible delay in payments. That is, the retailer must make a partial payment to the supplier when the order is received. Then the retailer must pay off the remaining balance at the end of the permissible delay period. In addition, we want to add the assumption that the retailer's storage space is limited. That is, the retailer will rent the warehouse to store these exceeding items when the order quantity is larger than retailer's storage space. Under these conditions, we model the retailer's inventory system as a cost minimization problem to determine the retailer's optimal cycle time and optimal order quantity. Three theorems are developed to efficiently determine the optimal replenishment policy for the retailer. Finally, numerical examples are given to illustrate these theorems and obtained a lot of managerial insights

Model with Limited Storage Space Under Partially Permissible Delay in Payments

The main purpose of this paper wants to investigate the optimal retailer's lot-sizing policy with two warehouses under partially permissible delay in payments within the economic order quantity (EOQ) framework. In this paper, we want to extend that fully permissible delay in payments to the supplier would offer the retailer partially permissible delay in payments. That is, the retailer must make a partial payment to the supplier when the order is received. Then the retailer must pay off the remaining balance at the end of the permissible delay period. In addition, we want to add the assumption that the retailer's storage space is limited. That is, the retailer will rent the warehouse to store these exceeding items when the order quantity is larger than retailer's storage space. Under these conditions, we model the retailer's inventory system as a cost minimization problem to determine the retailer's optimal cycle time and optimal order quantity. Three theorems are developed to efficiently determine the optimal replenishment policy for the retailer. Finally, numerical examples are given to illustrate these theorems and obtained a lot of managerial insights

A business model predicting the impact of live-stream marketing on firms' stock price - An event study

Live stream marketing in China has been in the rage since 2019, and the e-commerce industry has expanded dramatically since the start of the pandemic. Internet celebrities, a growing number of people from different walks of life, movie stars, and TV hosts are now joining as live streamers. In February 2020, China's A-share stock market's Internet celebrity live streaming index rose by more than 20%. However, does adopting live stream marketing really have positive and significant impact on stock prices of listed companies? This study used event study analysis to investigate the impact of live stream marketing on stock prices of listed companies. After computing the normal rate (NR), abnormal rate (AR), cumulative average abnormal return (CAAR) of the subjects using EXCEL and SPSS and conducting a significant analysis of the CAAR, this study found that live stream marketing events have a positive influence on stock prices of listed companies.Live streaming has brought new economic vitality, however, with the existence of chaos phenomenon on the unmatured industry standards, access thresholds, and industry management at the same time. This study tries to organize a conceptual framework for discussion, and from a practical perspective, to summarize the reasons why companies use live stream marketing to influence stock prices: (1) Live stream marketing can boost sales in a short amount of time. (2) The stock price is influenced by live stream marketing's dramatic sales. (3) Brand awareness, which helps forecast the stock price, is promoted.At the same time, live stream provides significant advantages for companies. However, there is no certain supporting business model predicting how live stream marketing significantly affects the companies' stock price. Therefore, the authors, from a theoretical perspective, tried to solve the problem by seeking a stable business model for predicting the influence of live stream marketing on the stock price.In short, the influence of internet celebrity marketing has become a new significant variable and greatly impacted the firm's stock market price and the relevant research regarding this phenomenon is still scarce; it is necessary to study this hot topic at this stage, which is the research motive of this study