Search results

The current work reviews all retailing articles published in four prominent retailing journals – Journal of Retailing, Journal of Retailing and Consumer Services, International Journal of Retail & Distribution Management, and International Review of Retail, Distribution and Consumer Research – in the 2009-2015 period, picking up where Runyan and Hyun (2009) left off. The purpose of this paper is to identify leading authors and institutions in retailing research based on overall impact.

Content analysis/literature review/descriptive research.

In total, 1,392 articles were published during this time period, and through a procedure of weights and adjustments for author count, journal impact, journal quality, and journal publishing opportunity, the findings reveal that research collaboration is highly prevalent, as evidenced by the high number of multi-authored papers and cross-university/international partnerships. Additionally, some authors and institutions remain influential, while others have emerged as highly influential in the last seven years. This shows the dynamic nature of the field and the need to remain active in quality publishing.

Scholars must understand that several factors influence impact judgments, which cannot be assessed using raw counts alone. Journal quality, impact, and publishing opportunity as well as author counts are important elements to consider.

These reviews are vital to the field in that they provide status updates on scholarship, so these reviews should be done periodically. Additionally, the findings in this paper provide a more holistic understanding of research impact and permit better assessment for scholars and administrators.

The main purpose of this paper is to provide an analytical conceptual framework to help business marketers to identify the effect of consumer's online purchase cost on a firm's performance in a dual‐channel competitive market.

A structural model using game theory is developed to search the optimal strategies for both online and traditional channel retailers.

Our model results show that consumer's online purchase cost consistently has a valuable impact on a firm's profit, and consumer's online purchase cost shows a much more valuable impact on firm's profit when the traditional retail transaction cost and the product web‐fit change. We also find that consumer's online purchase cost has a greater impact on the firm's profit in a Stackelberg competition than in a Bertrand competition.

The present study holds the assumption that all information is known to the online retailers and the traditional retailers. However, information could be incomplete and asymmetric. It is recommended that future research explores the value of consumer's online purchase cost under information asymmetry.

Our paper provides a comprehensive model framework for business managers who currently use or plan to use internet channel to sell their products.

Our research model fills a conceptual and practical gap with a structured analysis of the current state of knowledge about consumer's online purchase cost. The paper provides practical and solid advice and examples demonstrating the application of the different types of optimal marketing strategies for business managers.

The purpose of this paper is to provide a framework to help the manufacturer and the giant retailer to obtain optimal service level, pricing strategy, and market structure in order to maximize their respective profits.

A profit‐maximization model is developed to determine the optimal service level, pricing strategy, and market structure for supply chain players.

Using a profit‐maximization model, it is demonstrated that optimal service level and pricing strategy exist under different market structures in a manufacturer‐giant retailer supply chain. In order to maximize their respective profits, the manufacturer and the giant retailer should cooperatively employ a coordinative market structure as an optimal market structure and a bargaining model can be utilized to implement profit sharing for the manufacturer and giant retailer to optimize their profits. Furthermore, it is also shown that the value of coordinative structure always increases with the customers' sensitivity of service, the number of customers preferring to purchase from giant retailer, and the decreasing price sensitivity.

The study assumes that all supply chain players have perfect market information. However, market information to the supply chain players could be incomplete and asymmetric. It is recommended that future research explores optimal service level and pricing strategy under incomplete and asymmetric information setting.

The paper provides a very useful model framework to study optimum service level, pricing strategy, and market structure for business managers who are working in the manufacturer‐giant retailer supply chain.

The paper fills a conceptual and practical gap for a structured analysis of the current state of knowledge about service level, pricing strategy, and market structures in a manufacturer‐giant retailer supply chain. The paper provides practical, solid advice and business examples that demonstrate the application of the optimal strategies for supply chain management.

The purpose of this paper is to provide a framework to help the manufacturers to find the optimal decisions regarding the choice of channel member for information sharing.

A game‐theoretical model plus Bayesian forecasting is developed to determine the optimal decisions for the manufacturer.

The results show that the optimal strategy for the manufacturer is to engage in information sharing with one small retailer exclusively, such that the manufacturer can gain the most benefit from information sharing arrangement in a marketing channel with a dominant retailer.

The present study is analyzed by a theoretical model. Future research can explore the same study by collecting data to engage in an empirical test.

This paper provides a useful model framework and pricing strategy for upstream manufacturers who are engaging or planning to engage in information sharing with their retailers.

This paper provides practical and solid advice and examples demonstrating the optimal decisions regarding the choice of channel member for information sharing to best benefit of the manufacturer.

The purpose of this paper is to provide a framework to help business marketers with a mixed online and traditional retail channel (multi‐channel company) to find the optimal pricing strategy and market structure in order to maximize their profits.

A game theory model is developed to determine the optimal pricing strategy for the multi‐channel company.

It was demonstrated that an optimal pricing strategy exists under different market structures for a multi‐channel company. When a company uses multiple channels to sell its product, the optimal pricing strategy is to use a low‐high pricing strategy if the online marginal cost is equal to or less than the traditional marginal cost, or a high‐low pricing strategy if the online marginal cost is far larger than the traditional marginal cost. Furthermore, in order to maximize its profit, the company using multiple channels should adopt channel integration as the optimal market structure.

The present study assumed that all consumers have perfect information. However, information with the consumers could be incomplete. It is recommended that future research explore the pricing strategy under incomplete information settings.

The paper provides a very useful model framework, pricing strategy, and market structure for business managers who are using or planning to use multiple channels to sell their products.

This paper fills a conceptual and practical gap for a structured analysis of the current state of knowledge about multi‐channel pricing strategies. It provides practical and solid advice and examples demonstrating the application of the different types of pricing strategies for business managers.

The purpose of this paper is to provide a framework to help e‐marketers to find an optimal returns policy and pricing strategy in order to maximize their profits.

A profit‐maximization model is developed to determine the optimal returns policy and pricing strategy for e‐marketers.

The author demonstrates that an optimal returns policy and pricing strategy exists when firms sell products through an e‐market. When a firm uses an e‐market to sell its product, its optimal returns policy and pricing strategy is to offer a more generous returns policy and to charge a higher price when the product web‐fit is strong. Furthermore, the results also show that while the returns policy always is valuable for the e‐marketer, the value of returns policy increases with the product web‐fit.

The present study assumed that all consumers have perfect information. However, information to the consumers could be incomplete. It is recommended that future research explores returns policy and pricing strategy under an incomplete information setting.

This paper provides a very useful model framework, returns policy and pricing strategy for business managers who are using or planning to use the e‐market to sell their products.

This paper fills a conceptual and practical gap for a structured analysis of the current state of knowledge about returns policy and pricing strategy in e‐business. The paper provides practical, solid advice and examples that demonstrate the application of the optimal strategies for e‐business managers.

The purpose of this paper is to provide a framework to help competitive firms find optimal pricing and brand management strategies in order to maximize their respective profits.

A game‐theoretic model is developed to determine optimal pricing and brand management strategies for competitive firms.

The study demonstrates that optimal pricing and brand management strategies exist for firms in a competitive market. The optimum marketing strategy for competitive firms to employ is the cooperative alliance pricing and brand management strategy, particularly when market competition is very intense.

The present study assumes that all information is known to all parties. However, information could be incomplete. It is recommended that future research explore pricing and brand management strategies under incomplete and asymmetric information settings.

The paper provides a very useful model framework and pricing and brand management strategy for business managers when they are doing business in a competitive market.

The paper fills a conceptual and practical gap for a structured analysis of the current state of knowledge about alliance brand. It provides practical and solid advice and examples demonstrating the application of cooperative alliance pricing and brand management strategies for business managers.

The purpose of this paper is to provide a framework to help business marketers with online and traditional retail channels (multi‐channel retailers) to find the optimal branding strategy and market structure in order to maximize their profits.

A game‐theoretic model is developed to determine the optimal branding strategy and market structure for the dual‐channel stores of a multi‐channel retailer.

The paper demonstrates that an optimal branding strategy and market structure exists for the dual‐channel stores of a multi‐channel retailer. When a retailer uses multiple channels in parallel to sell its product, the optimal branding strategy is to employ as large as possible brand differentiation between the dual‐channel stores, particularly when the price is less sensitive for consumers and the market base size is larger. Furthermore, it is also found that the optimal market structure is the Stackelberg mode, especially when the product brands between the two channels are less differentiated.

The present study assumed that all information is known to both the online and traditional channels of a multi‐channel retailer. However, information could be incomplete. It is recommended that future research explore the value of product brand differentiation under incomplete information settings.

The paper provides a very useful model framework, branding strategy, and market structure for business managers who are using or planning to use multiple channels to sell their products.

This paper fills a conceptual and practical gap for a structured analysis of the current state of knowledge about multi‐channel branding strategies. The paper provides practical and solid advice and examples demonstrating the application of product brand differentiation strategies for business managers.