Joint Optimization Decision of Online Retailers’ Pricing and Live-Streaming Effort in the Postepidemic Era

The isolation requirements of the coronavirus epidemic and the intuitive display advantages of live-streaming have led to an increasing number of retailers shifting to social live-streaming platforms and e-commerce live-streaming platforms to promote and sell their products in real time. However, the provision of live-streaming services will also incur high live-streaming effort costs. In this paper, we develop two decision models for retailers to sell goods through a single online shop and both online shop and live-streaming room; we also present the optimal decisions of pricing and live-streaming efforts. Furthermore, we identify the profitability conditions for retailers to determine when to provide live-streaming services. In addition, we examine the impact of the provision of live-streaming services on the optimal price and live-streaming effort. We obtain three findings. First, there is a unique optimal decision on the price and live-streaming effort under certain conditions. Second, when the effect coefficient of the live-streaming room reaches a certain threshold, there are enough customers who enter the live-streaming room to watch and buy and it is profitable for retailers to provide live-streaming service. Finally, the optimal price and live-streaming effort increase with the increase in average return loss, the effect coefficient of live-streaming effort, and the extra return rate and decrease with the increase in the proportion of customers who choose to buy in the online shop and the price discount coefficient in the live-streaming room.

Application of Value Stream Mapping in E-Commerce: A Case Study on an Amazon Retailer

In recent years, the e-commerce market has grown significantly, and the online retail market has become very competitive. Online retailers strive to improve their supply chain operations to reduce costs and to improve customer satisfaction. Value stream mapping (VSM), a tool created by the lean production movement to identify and reduce errors, losses, and lead time and to improve value-added activities, has been proven to be effective in many manufacturing processes. In this study, we investigate the application of value stream mapping (VSM) in the supply chain of an e-commerce retailer on Amazon. By visualizing the entire supply chain with VSM, the waste that is produced during the delivery process from the retailer to the customer was identified. The five whys method was then applied to find the root cause of the waste. Furthermore, a scoring method was developed to evaluate and compare two different supply chain logistic models to identify a strategy for improvement. This study provides a systematic methodology to understand, evaluate, and improve the entire e-commerce supply chain process utilizing VSM. It was demonstrated that the methodology could improve supply chain management efficiency, customer satisfaction, and cost reduction.

Repurchase intention behavior in B2C E-commerce

The intention to buy back is one of the objectives of the business strategy. This study aims to analyze the effect of mediating customer satisfaction on e-service and repurchase intention. This analytical study was conducted on e-commerce that is widely used by Indonesia, namely Shopee.co.id. The rapid growth of e-commerce, both C2C and B2B, has made online retailers compete in the online retail business. The intention to buy back is no longer solely due to the quality of service like an offline business. The purpose of this study is to analyze the role of mediating customer satisfaction from the quality of E-Commerce on repurchase intention in E-Commerce that has implemented a combination of C2B and B2B. Quantitative methods with structural equation analysis (SEM) and path analysis were used to analyze data using LISREL. The questionnaire is distributed to respondents used as samples taken from the population for this research. The researched population is user of Shopee.co.id in Indonesia, whereas samples of the population are randomly taken. The samples of this research are 279 respondents. The results of this study found that there is no significant direct effect of electronic service quality on repurchases intentions, but when customer satisfaction acts as a mediating variable, it shows that electronic service quality affects repurchase intention significantly through customer satisfaction. This study will help online retailers to find out what factors influence customers to make repeat purchases.

How does dataveillance drive consumer online payment resistance?

Purpose This study aims to examine the effect of dataveillance on resistance towards online payment. Using a moderated-mediation framework, the study also investigates the mediating effects of perceived privacy and security concerns and how these mediating effects are moderated by corporate credibility, consumer scepticism and consumer empowerment. Design/methodology/approach A scenario-based experimental design was performed to examine the proposed hypotheses. Analysis of covariance and PROCESS macro were used to examine the hypotheses by analysing 312 collected responses. Findings The results indicated the dataveillance positively affects consumer resistance towards online payment. The results also suggested that corporate credibility and consumer scepticism significantly moderates the association between dataveillance and resistance towards online payment. Practical implications The findings of this study will help online retailers to reduce consumers’ perceived privacy and security concerns, thereby reducing consumers’ resistance towards online payment. Originality/value Theoretically, the study contributes to privacy, consumer behaviour, online payment and cognitive-motivational-relational theory literature.

How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment

The findings underscore the important role of consumers’ consideration sets in mediating the positive effects of recommender systems on consumer purchases. Practical strategies can be developed to facilitate the formation of the consideration sets. For example, to reduce consumers’ search costs and cognitive efforts, online retailers can display the recommended products in a descending order according to the predicted closeness of consumers’ preferences. Online retailers can further indicate the predicted closeness scores of consumers’ preferences for the recommended products. Given such a placement arrangement, consumers can quickly screen the recommended products and add the most relevant alternatives to their consideration sets, which should facilitate consumers’ shopping process and increase the shopping satisfaction. The findings also suggest that a larger consideration set due to the use of recommender systems could induce consumers to buy. Yet, it is difficult for consumers to manage many alternatives when the consideration set is very large. To facilitate consumers’ shopping process, online retailers need to consider strategies and tools that help consumers manage the alternatives in the consideration set in a better-organized manner and facilitate the comparison across the alternatives.

A Colored Traveling Salesman Problem with Varying City Colors

A colored traveling salesman problem (CTSP) is a path optimization problem in which colors are used to characterize diverse matching relationship between cities and salesmen. Namely, each salesman has a single color while every city has one to multiple salesmen’s colors, thus allowing salesmen to visit exactly once the cities of their colors. It is noteworthy that cities’ accessibilities to salesmen may change over time, which usually takes place in the multiwarehouse distribution of online retailers. This work presents a new CTSP with dynamically varying city colors for describing and modeling some scheduling problems with variable city accessibilities. The problem is more complicated than the previously proposed CTSP with varying edge weights. In particular, the solution feasibility changes as the cities change their colors, that is, a feasible original solution path may become no longer feasible after city colors change. A variable neighborhood search (VNS) algorithm is presented to solve the new problem. Specifically, a dynamic environment simulator with an adjustable frequency and amplitude is designed to mimic such color changes. Then, direct-route encoding, greedy initialization, and appropriate population immigrant are proposed to form an enhanced VNS, and then its performance is evaluated. The results of extensive experiments show that the proposed VNS can quickly track the environmental changes and effectively resolve the problem.

Value of Online–Off-line Return Partnership to Off-line Retailers

Problem definition: This paper examines whether and, if so, how much an online–off-line return partnership between online and third-party retailers with physical stores (or “location partners”) generates additional value to location partners. Academic/practical relevance: Online shoppers often prefer to return products to stores rather than mailing them back. Many online retailers have recently started to collaborate with location partners to offer the store return option to their customers, and we quantify its economic benefit to a location partner. Methodology: We analyze proprietary data sets from Happy Returns (which provides return services for more than 30 online retailers) and one of its location partners, using a panel difference-in-differences model. In our study, a treatment is the initiation of the return service at each of the location partner’s stores, and an outcome is the store and online channel performance of the location partner. We then explore the mechanisms of underlying customer behavior that drive these outcomes. Results: We find that the partnership increases the number of unique customers, items sold, and net revenue in both store and online channels. We identify two drivers for this improved performance: (1) the location partner acquires new customers in both store and online channels, and (2) existing customers change their shopping patterns only in the store channel after using the return service; in particular, they visit stores more often, purchase more items, and generate higher revenue after their first return service. Managerial implications: To our knowledge, we provide the first direct empirical evidence of value to location partners from a return partnership, and as these partnerships become more prevalent, our findings have important managerial implications for location partners and online retailers alike.

Incentive Mechanism for Product Quality of Retailers Based on Platform-Based ECommerce

In order to explore the autonomous incentive mechanism of platform-based e-commerce to online retailers' products, a product quality incentive model based on deposit and commission management is established for single retailer single quality products, single retailer products at multiple quality levels and double-retailer different quality products in three cases. Comparative analysis of the equilibrium results in three cases reveals that the effectiveness of the incentive mechanism of platform discount in the first case depends on the deposit strategy of the platform and the influence of the unit cost of excellent and low-quality products. In the second case, the incentive mechanism of platform discount is completely effective. The platform price discount has a positive incentive effect on retailers. The online retailers' increasing the sales of high-quality products and reducing the sales of low-quality products improve the high-quality product rate in the market. In the third case, the effectiveness of the platform discount incentive mechanism is mainly affected by the unit cost of products.

CORRELATION OF COVID-19 IN THE ONLINE PURCHASING PROCESS

The paper establishes the central point for researching factors that influence buying decisions in the online purchasing process. The benefits of e-commerce for both buyers and sellers place it as the default method of shopping in the near future. Through empirical research, e-commerce growth is being established as rapidly rising through recent years, which has been accelerated by specific factors introduced by the COVID-19 pandemic. Data shows that e-commerce is dependent on several different factors during normal circumstances, which also include the level of development of the country as one of the main precursors. The beginning of the COVID-19 pandemic influenced greatly the importance of these established factors for online purchasing, rendering many of them obsolete. The paper structures the research to outline the most relevant factors influencing online purchasing decisions pre-pandemic and during pandemic times, and to draw relevant conclusions and recommendations for future practical implementations of e-commerce models. Research shows that new factors need to be introduce in these types of abnormal times, as the nature of the pandemic made non-contact interactions the norm in the past year. By introducing the six stages of pandemic behavior, online retailers can better understand the factors influencing online purchasing process in pandemic times. Finally, specific recommendations can be made to improve the e-commerce acceptance both at industry and company levels.

Impact of Consumer Perception of Online Ethics on Website Loyalty and Satisfaction in Morocco

The study aim, to explore the impact of consumers' perceptions concerning online retailers' ethics with website satisfaction and loyalty. A survey sample of 486 students was conducted to explore the relationships enrolled in various businesses undergraduate and postgraduate at universities of Morocco. To measurement the proposed model AMOS-23 is used to test the structural equation modeling. This study indicates that security fulfillment, non-deception, privacy, and security have a significant and positive impact on website satisfaction and loyalty. The study findings are consisted with the proposed model. The study implication suggested that ethical issues of internet retailers must be resolved regarding protection, personal information, and delivering. The prior researches on online retailing examine the impact among loyality, satisfaction and perceived online ethics. The conflict with the results in existing literature, the impact od security on satisfaction, consumers perceive as ethical online retailing with loyality and satisfaction has been confirmed.