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This paper analyzes the advance selling and pricing strategies of fresh products supply chain where the e-retailer provides wholesale contract or agency contract to the fresh products supplier.

This paper constructed a two-period sequential-move game of fresh products supply chain members.

This analysis showed that the supply chain members had different preferences for contracts under different market conditions. The advance selling of fresh products was not a decision of the seller, but also required the support of other supply chain members. And the advance selling strategy was not always beneficial to all supply chain parties. Under the two contracts, there were market conditions in which the profits of supply chain members were Pareto-improved through the implementation of advance selling.

The model presented in this study focuses solely on the context of monopoly, overlooking the competition from alternative suppliers or retailers. Consequently, exploring the competitive landscape within the fresh products supply chain, particularly in relation to pre-sale pricing, emerges as a crucial avenue for further investigation. By employing empirical research methods, valuable insights are gleaned, thereby significantly augmenting the existing body of relevant theories.

The decision to pre-sell fresh products should be based on market conditions. Supply chain members can control production costs and fresh products circulation losses to maximize profits.

From the perspective of game theory, this study analyzed the optimal advance selling and pricing strategies of fresh products supply chain members under two kinds of contracts. These results can provide practical implications for fresh products suppliers and e-retailers.

The return behavior of customers has a great impact on the e-retail industry and has resulted in the emergence of return-freight insurance (RI). Additionally, customer loss aversion arising from returns affects e-retailers' decisions and manufacturers' profits. Therefore, the main purpose of the authors' study is to determine how e-retailers and manufacturers choose their RI strategy and pricing according to customers' loss aversion.

The authors propose three scenarios: no RI, customer purchase RI and free e-retail RI (FRI). Meanwhile, the authors also model a Stackelberg game between e-retailers and manufacturers for analysis. Then, according to customer return behavior and loss aversion, the authors study the optimal pricing decision and RI premium allocation scheme for e-retailers and manufacturers under different scenarios.

It was found that the loss sensitivity reduces customers' willingness to buy RI, which is not conducive to the development of e-retailers and manufacturers. Additionally, with higher loss sensitivity, e-retailers and manufacturers offer FRI to gain higher profits, which supports the implementation of the FRI strategy.

The authors introduce customers' loss aversion into RI to analyze the optimal pricing decisions and profits of e-retailers and manufacturers, enriching the application of loss aversion theory. In addition, this study analyzes the two-way cost-sharing mechanism between manufacturers and e-retailers to provide FRI, which provides a theoretical basis for RI premium sharing.

In the marketing and consumer behavior literature, much remains to be explained about customer citizenship behavior in a highly technological e-retailing context. The purpose of this paper is to present the results of a survey of 186 e-shoppers which was conducted grounded in the social exchange theory.

Structural equation modeling is used to test the proposed model.

The results provide support that e-customer familiarity with an e-store and facilitating conditions provided by an e-retailer influence e-customers ' e-satisfaction, e-loyalty, and e-commitment with an e-retailer, all of which exert different effects on three dimensions of e-customer citizenship behavior.

The results of this study offer e-retailers a way to stay ahead of their competitors by focusing on online attributes that are difficult to duplicate when it comes to customer relationship such as e-loyalty, e-commitment and e-customer citizenship behavior.

This study represents one of the initial attempts to validate a customer citizenship behavior model in an e-retailing setting using e-store familiarization and facilitating conditions as the primary determinants for developing e-store attitudes and behaviors among e-shoppers.

An uncertain product demand in online retailing leads to loss of opportunity cost and customer dissatisfaction due to instances of product unavailability. On the other hand, when e-retailers store excessive inventory of durable goods to fulfill uncertain demand, it results in significant inventory holding and obsolescence cost. In view of such overstocking/understocking situations, this study attempts to mitigate online demand risk by exploring novel e-retailing approaches considering the trade-offs between opportunity cost/customer dissatisfaction and inventory holding/obsolescence cost.

Four e-retailing approaches are introduced to mitigate uncertain demand and minimize the economic losses to e-retailer. Using three months of purchased history data of online consumers for durable goods, four proposed approaches are tested by developing product attribute based algorithm to calculate the economic loss to the e-retailer.

Mixed e-retailing method of selling unavailable products from collaborative e-retail partner and alternative product's suggestion from own e-retailing method is found to be best for mitigating uncertain demand as well as limiting customer dissatisfaction.

Limited numbers of risk factor have been considered in this study. In the future, others risk factors like fraudulent order of high demand products, long delivery time window risk, damage and return risk of popular products can be incorporated and handled to reduce the economic loss.

The analysis can minimize the economic losses to an e-retailer and also can maximize the profit of collaborative e-retailing partner.

The study proposes a retailer to retailer collaboration approach without sharing the forecasted products' demand information.

The purpose of this paper is to investigate how an E-retailer's assistive intent impacts the perceptions and behaviours of online shoppers. The paper introduces a model that explains and examines the process through which the perceived assistive intent of an E-retailer leads to improved patronage intentions towards the web site.

A survey on the most recent e-purchase experiences of more than 600 individuals in North America was conducted. Structural equation modelling based on EQS 6.1 was used to assess the measurement and structural models.

Results indicated that customers’ impressions of an E-retailer's assistive intent positively impact web site patronage intentions both directly and indirectly through two key constructs of e-shopping, including web site involvement and web site attitudes.

The student sample is not representative of the population. Students are familiar with internet and feel less need for assistance online. Another shortcoming might be its settings. Since the survey was on the respondents’ most recent online experiences, the data quality depends on the amount and accuracy of the information they could retrieve from memory.

The findings suggest that E-retailers would highly benefit from investing in the development of an assistive image. To do so, E-retailers should leverage the interactive nature of the web and provide supportive tools that facilitate the e-shopping task of clients.

Developing impressions of the site's assistive intent is highly rewarding for E-retailers that are new to the business.

This paper represents the first effort to link the newly developed construct of E-retailer's assistive intent to two fundamental variables of online shopping, including web site involvement and web site attitudes. This work would also be an extension of the past studies that call for further investigation of the link between customer orientation and customer's loyalty intentions.

Social media facilitates consumer exchanges on product opinions and provides comprehensive knowledge of online products. The interaction between consumers and e-retailers evolves into a collective set of dynamics within a complex system. Agent-based modeling is well suited to stimulate such complex systems. The purpose of this paper is to integrate agent-based model and technique for order performance by similarity to ideal solution (TOPSIS) to simulate decision behaviors of e-retailers in competitive online markets.

An agent-based network model using the TOPSIS driven by actual price data is developed. The authors ran an experimental model to simulate interactions between online consumers and e-retailers and to record simulation data. A nonparametric test is used to conduct data analysis and evaluate the sensibility of parameters.

Simulation results showed that different profits could be obtained for various brands under different social network structures. E-retailers could achieve more profits through cross-selling than single-selling; however, the highest profits can be achieved when some adopt cross-selling, whereas others use single-selling. From a game perspective, the equilibrium for price-adjustment frequency can be determined from the simulation data. Thus, price adjustment differences significantly affect e-retailer profit.

This study provides new insights into the evolutionary dynamics of online markets. This work also indicates how to build an integrated simulation model with an agent-based model and TOPSIS and how to use an integrated simulation model and interpret its results.

Limited knowledge exists on the difference in the antecedents and outcomes of relationship quality's cognitive and emotional aspects for e-retailers. This research tests how utilitarian and hedonic shopping values differentially affect “cognitive and emotional” relationship quality components and how the latter differentially affects word-of-mouth and brand evangelism.

Online survey data were collected from 450 Jordanian online shoppers. Structural equation modeling (AMOS 24.0) was employed to analyze the data.

First, e-retailer's informativeness and transaction convenience (i.e. utilitarian values), drive more strongly cognitive than emotional relationship quality, whereas e-retailer's escapism and social presence (i.e. hedonic values) drive more strongly emotional than cognitive relationship quality. Second, emotional relationship quality has a strong significant effect on brand evangelism, whereas cognitive relationship quality's effect is insignificant. Third, there are no statistically significant differences concerning the effect of cognitive and emotional relationship quality on word-of-mouth.

The findings of our research are expected to enhance our understanding of e-retailer relationship quality, its emergence and consequences. They would also provide e-retailers with guidance on how to execute growth strategies by focusing on specific types of brand relationship quality, on the other hand.

The success of e-retailers is intrinsically linked to the effectiveness of their logistics processes which, inevitably, involve third party service providers. As the most tangible representative of the e-retailers it is inevitable that customers expect the e-retailer to resolve delivery queries, including on social media platforms. The purpose of this paper is to investigate the effectiveness of e-retailers’ logistics-related customer service interactions on Twitter with a view towards identifying effective and ineffective social media customer service strategies.

The design and public nature of Twitter encourages organic conversations between e-retailers and customers as well as between customers and other customers. The methodology applied here accounts for this by collecting and analysing interactions within and as part of conversations, not as independent observations. In total, 203,349 tweets were collected from 22 of the most popular e-retailers. A random sample of 5,000 logistics-related conversations (16,998 tweets) is used for the analysis presented here and forms a foundation for future research.

Conversations are initiated by customers on the basis of 24 event triggers which can be categorised as occurring either before or after an order is delivered. These can be general queries or related to a specific order or delivery issue. The paper identifies a number of significant findings such as the extent to which e-retailers and logistics providers redirect customers to other channels to resolve queries, ignoring the implicit preference by customers to use Twitter to resolve their problem. Similarly, the lack of interactions between e-retailers and their logistics providers within the Twitter platform to help resolve customer queries results in ineffective customer service.

The study identifies the way in which e-retailers can substantially improve the effectiveness of the customer service they provide on Twitter by ensuring that customer queries can be resolved within the platform and by working with their logistics partners to do the same. This is critical since problems may be directed to the e-retailer or the logistics provider but both companies jointly suffer the consequences of poor customer service.

The study examines a hitherto underexplored aspect of retail logistics – the social media-based customer service activities of e-retailers. Methodologically, the study is rooted in the acknowledgement that interactions on Twitter form conversations and analyses should take this into account. This is a distinctly different approach from existing Twitter-related studies which conduct an automated sentiment analysis of tweets. This approach reveals a rich picture of interactions and, importantly, identifies where conversations between e-retailers begin, how they develop and how they conclude.

The purpose of this paper is to introduce a research exploring the important strategic elements and their prioritisation for e-retailers’ home delivery logistics process efficacy improvement.

The research was completed through focus group, survey and importance-performance analysis.

The research identified, confirmed and prioritised a set of explicitly important strategic elements currently deemed important by e-retailers for ensuring the efficacy of their home delivery logistics process in Chinese marketplace, and also referential to the other similar emerging marketplaces.

The research contributes positively to the enrichment of the theoretical knowledge pool of e-retailers’ logistics performance improvement.

The research findings guide/inform the strategy development and implementation for e-retailers entering and/or operating in Chinese marketplace. And the findings can also be referential to the e-retail strategy development for entering and operating in other emerging markets similar to China’s. This point is particularly meaningful for those e-retailers that want to expand the outreaching and increase the popularity of their businesses in the global marketplace.

Corresponding to the much needed further research on e-retailing home delivery performance improvement, the research provides findings that add substantial new insights into the field, with a particular focus on China, as one of the emerging developing marketplaces.

The focus of this study is on how online-only retailers, known as pure-play e-retailers, leverage e-commerce platforms to identify and pursue market opportunities. Through the perspective of entrepreneurial marketing, this study aims to explore the influence of e-commerce technologies on the decision-making process of entrepreneurial marketing. This exploration is conducted via a case study of pure-play e-retailers based in China.

This study utilised a qualitative case study methodology to examine the complex processes of entrepreneurial marketing in an online environment. The study gathered detailed insights from both owner-managers and staff members of eight pure-play e-retail businesses. Additionally, the research involved a careful review of the firms' webpages and social media pages. This holistic approach facilitated a comprehensive understanding of their marketing strategies and practices.

The case study findings indicate that while many core aspects of entrepreneurial marketing remain important, there are distinct factors influencing the entrepreneurial marketing decision-making in the online marketplace. The online EM framework can be visualised as follows: (1) trend-orientated as well as innovative-orientated (2) data-orientated and entrepreneur-orientated (3) innovative-driven customer stimulation (4) orientated towards both platforms and proactiveness.

The paper provides an initial understanding of how digitalisation is enabling and transforming entrepreneurship in companies with high level digitalisation but low level digital development. Building on current entrepreneurial marketing literature, this paper develops an online entrepreneurial marketing framework to enhance understanding of the interaction between e-commerce technology and entrepreneurial marketing decision making.