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The rapidly growing e-commerce industry with its special characteristics brings new challenges to the optimization of the supply chain and inventory management. This study aims to investigate the inventory-related optimization of an e-marketplace official store that works on a business-to-customer system when cashback promotion is used to attract more customers. Also, it proposes a new inventory model to maximize the e-commerce profit by optimizing the cashback amount and delivery period.

The proposed model assumes that customer demand is a function of price and delivery time and that price is affected by the cashback amount. The e-commerce operator has a profit-sharing contract with an e-payment company that facilitates the payment. E-commerce also builds collaboration under a cost-sharing contract with a supplier to ensure product delivery. A mathematical model is developed and the related theories are investigated. A numerical example illustrates the validity of the model and a sensitivity analysis is carried out to give useful insights.

A new inventory model for an e-market system has been introduced which shows the impact of a cashback promotion on the e-commerce business. This study shows that managers can optimize the cashback amount and its delivery time to get the maximum profit. In certain cases, the manager may set a high cashback amount (e.g. 100%) to attract customers to place more orders.

This study presents a new inventory model for today’s fast-growing e-commerce business; therefore, the results contribute to the understanding of promotion program practices and inventory management and provide insights to develop efficient e-commerce managerial decisions.

This article aims to explore the impact of interpersonal relationship stimuli and click-like on purchase intention across different generations of bank customers, with a focus on the moderating effect of online trust.

The sample consists of 435 online bank customers from the Facebook community and the data collection was conducted using an online survey method. The model estimation utilized the partial least squares technique, along with multigroup analysis and importance-performance map analysis.

The empirical evidence supports the hypothesized relationships between interpersonal relationship stimuli, click-like and purchase intention, but varies across different generations and is contingent upon online trust. The analysis reveals commonalities in how Generation Z, Millennials and Generation X respond to interpersonal relationship stimuli while exhibiting distinct responses to click-like.

The empirical evidence confirms the hypothesized relationships between interpersonal relationship stimuli, click-like and purchase intention. However, these relationships exhibit variations across different generations and are contingent upon the level of online trust. The analysis highlights shared responses to interpersonal relationship stimuli among Generation Z, Millennials and Generation X, while also revealing distinct reactions to click-like within these generational groups.

This research investigates the collective impact of interpersonal relationship stimuli and click-like on purchase intention, taking into account the moderating role of online trust within various generational cohorts in the banking sector.