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The purpose of this paper is to discuss how wind farms attract wind turbine manufacturers to get involved in wind turbines’ maintenance service with revenue sharing contract of bundled service under which the background of operation and maintenance (O&M) aftermarket of wind turbine exists. The authors also try to extend the results to the application of product plus service business mode on large-scale equipment O&M service. At present, Chinese wind power industry is suffering from production capacity redundancy. The profit levels for both wind farm and wind turbine manufacturers are relatively low. It is significant for Chinese wind power industry development to coordinate the supply chain of wind power in order to reduce O&M costs and increase revenues.

The present paper discusses product plus aftermarket service contract design on the background of closed-loop product service chain and uncertain equipment demand using revenue sharing contract model.

If centralized decision making is assumed, the authors find that the wind turbine order increases as the aftermarket service effort level and aftermarket service profit increase; aftermarket service effort level is positively correlative to the service efficiency. On the other hand, if decentralized decision making is assumed, the wind turbine order increases as share of the aftermarket service chain by manufacturer to wind farm increases and share of product supply chain by wind farm to manufacturer decreases. The optimal effort level of wind farm increases as the share of aftermarket service chain increases while the optimal effort level of the manufacturer is a concave function of share of aftermarket service chain if service quality linear correlates with effort level. Meanwhile, the authors find that the revenues of the product supply chain and aftermarket service chain have a concave relationship. This relationship is not affected by the format of relationship between service quality and effort level (linear or exponential).

The results could potentially be used to provide the wind turbine manufacturer with a greater profit space and satisfy wind farm’s equipment maintenance demand at the same time. It can also guide the practice of revenue sharing in the aftermarket service and manufacturing servitization.

In this model, the authors assumed that both the forward revenue sharing of power generation by wind farm to manufacturer and the backward revenue sharing of maintenance service by the manufacturer to wind farm exist in closed-loop product service chain. Then the authors discussed channel coordination of such cross-revenue sharing contract.

With the growing economic impact of e-commerce and the increasing trend of omnichannel mode, more considerate services can be provided to customers. This paper aims to explore the optimal practice of business strategies and enrich the research content of marine tourism omnichannel.

This paper studies the optimal practice of bundling pricing and service effort strategies between two tourism suppliers (TSs) and a travel agent (TA) who distributes complementary products in marine tourism omnichannel considering joint efforts of both sides. This study develops five models by Stackelberg and Nash game and introduces the revenue-sharing contract. All outcomes/results are analyzed and the corresponding numerical and sensitivity analyses are conducted to derive more managerial implications and business insights.

The main findings show that bundling price is directly proportional to inter-channel integration coefficient and service effort level coefficient, and inversely proportional to the price elasticity coefficient. TA tends to provide a higher level of service effort than TSs when TA plays a dominant role. Improving the service effort level unduly leads to a decline in profits. Moreover, TSs and TA can reach a win-win situation under the coordination mechanism and the marine tourism omnichannel can achieve the best performance.

A novel and useful approach towards joint equilibrium decisions of bundle pricing and service efforts in marine tourism omnichannel with complementary tourism products under different operational strategies is proposed.

Although the wind power industry has been booming in China during the last decade, the development of wind turbine aftermarket service is still lagging behind, which seriously affects the operational efficiency of wind farms. If wind turbine manufacturers get involved in the aftermarket, the service pricing policy will impact the profits of both the manufacturer and the wind farm. Therefore, it is necessary to discuss an optimal service pricing strategy in the wind turbine aftermarket and design a method to improve electricity generation efficiency through service contract design. The paper aims to discuss these issues.

In order to decide the maintenance quantity and channel effort level, the authors design a normal Stackelberg game and an efficiency value-added revenue-sharing contract and discuss two kinds of revenue increment sharing models under situations, in which the supply chain’s leaders are the wind farm and the wind turbine manufacturer, respectively.

The results show that in either case, there exist optimal power generation revenue-sharing ratios that can maximize profit. At the same time, the authors outline an optimal service pricing policy, maintenance demand policy and channel service effort-level policy. The results summarize the influences of wind aftermarket services on wind farms’ and wind turbine manufacturers’ profit, which provides managerial insights into the process of manufacturing servitization.

The manufacturer’s channel effort level will influence the power generation increments very much, so the authors have developed a mechanism to stimulate the manufacturer improving the efficiency of aftermarket services.

Taking the power generation increment revenue as the profit increment function, the authors discuss the influence of service price on the profit increment of the wind farm and the wind turbine manufacturer and also consider the influence of service price on the wind farms maintenance quantity and wind turbine manufacturers channel effort level.

The purpose of this paper is to apply customer lifetime value models to assess the overall value of the service encounter and to establish implications that such an assessment has for managing customer relationships under a fixed‐size salesforce.

Using a specific relationship between customer servicing activities and the buying rhythms of customers, an analytical model for assessing the overall value of a service encounter is developed.

A stochastic parameter is identified, characterizing the level of quality to compute the long‐term value of a given customer and stochastic ordering properties to determine the relative value of different customers.

The implications discussed are analytical to help service managers shaping their thought process in decision making. Future research can empirically test the model proposed.

The theorem specifies the optimal solutions to determine: how much capacity should be committed to a given customer; and how to choose a customer in the first place. These are important and useful tools for managers in making their managerial decisions in service marketing.

A general model of resource allocation is provided, under which those seminal models such as CALLPLAN, DETAILER are special cases. This is particularly valuable as key account management has become more important in globally operated businesses.

The authors address a two-dimensional (both customer acquisition and retention) incentive in a decentralized service chain consisting of a risk-neutral brand and agent (or averse). 

The authors focus on the relationship between acquisition and retention, that is, retained customers (repeated purchases) are based on and come from the acquired (new) customers in the former period. The authors also design a two-period separate incentive on both dimensions.

The authors found that a targeted incentive strategy should be applied for achieving more revenue when the incentive intensities are relatively small. Otherwise, the brand needs to adjust the targeted incentive strategy into incentivizing the opposite dimension, particularly on acquisition. Under the optimal contract, the brand needs to be very careful with deciding the fixed part of the incentive salary and the incentive intensities on both dimensions. For example, the fixed salary initially decreases and then increases in the incentive intensities. For the optimal incentive policies, the brand should incentivize acquisition but outsource retention if the agent is risk-neutral. When the agent is becoming risk-averse, the brand should lower its incentive intensity as the risk degree and variances become larger. Interestingly, the brand may benefit from introducing risks.

The study contributes to the literature by considering the following points. First, the authors extend the principal-agent incentive model by considering two-period decisions of customer acquisition and retention. Second, based on the two-period principal-agent problem, the authors design separate incentive intensities on acquisition and retention, respectively. While, most of the literature focused on acquisition incentives. Third, different from other works focusing on either risk-neutral or risk-averse environments, the authors consider both and compare the cases of risk-neutral and risk-averse to analyze the impact of risk on the optimal decisions and the brand's expected profit.

By studying the competition between a B2C platform and a third-party seller, the purpose of this paper is to analyze and compare their optimal decisions and profits between cases with and without sales effort of the platform or third-party seller.

This paper studies the competition between a B2C platform and a third-party seller. The platform sells a product directly, and allows the third-party seller to sell a competing product on the platform. Based on whether the platform or the third-party seller makes sales effort, there are four scenarios. The paper analyzes the optimal decisions and profits of platform and third-party seller under each scenario, respectively.

The transaction fee has a negative effect on third-party seller’s sales effort level. What is more, the platform can take a free riding from the third-party seller’s sales effort, but the platform’s sales effort has a negative effect on the profit of third-party seller.

These results provide managerial insights for the platform and the third-party seller to make decisions.

This paper is among the first papers to study the competition between B2C platform and third-party seller.

Value has been conceptualized as the result of co-creation involving service firms and customers. Currently, however, little is known about why and how customers engage in value co-creation with a service firm. Thus, the purpose of this paper is to explore the role of co-production in value co-creation in the context of banking services from the customers’ viewpoint. The literature has consistently examined the linear effects of trust and decision-making uncertainty on co-production. The study extends this research stream by considering the negative quadratic effects of trust and decision-making uncertainty on co-production. Therefore, this study not only examines the linear and negative quadratic effects of trust and decision-making uncertainty on co-production within a single, simultaneous model but also tests the effect of co-production on value co-creation. Moreover, this study includes and explores the moderating effects of service innovativeness and service effort on co-production in determining value co-creation.

The hierarchical moderated regression was used to test the hypotheses.

The findings support the positive linear effects and negative quadratic effects among trust, decision-making uncertainty and co-production. Meanwhile, the results indicate that co-production positively affect value co-creation. Service innovativeness and service effort enhance the effect of co-production on value co-creation.

This study shows the presence of the opportunity of trust and decision-making uncertainty, which confirms the existing literature, and the challenge of trust and decision-making uncertainty, which extends the literature. This study is the first one to shed light on the negative quadratic effects of trust and decision-making uncertainty on co-production. This study also offers insights into value co-creation and thus enhances the current understanding of value phenomena. Academics and practitioners would greatly benefit from a comprehensive understanding of co-production and the associated value co-creation for the parties involved.

Co-production is an important process that alters value creation and improves the relationships between service providers and their customers. Such practice allows customers and service employees to access and leverage resources residing in their relationships. Clearly, the marketing-related literature focuses on the bright side of co-production. Nevertheless, the costs and potential negative consequences associated with its dark side must be further investigated. Therefore, this study aims to present a conceptual framework that explores the relationships among co-production, co-production enjoyment, co-production intensity, service effort, and job stress, and their effects on value co-creation, value co-destruction and customer satisfaction.

This study was conducted on the basis of dyadic data; the process incorporates both the customer and the corresponding service employee into a single unit of analysis. The proposed model was tested by using a structural equation model that involves LISREL analyses.

The results of this study indicate that co-production influences co-production enjoyment, co-production intensity, service effort, and job stress. Co-production enjoyment and service effort increase value co-creation, whereas co-production intensity and job stress increase value co-destruction. Value co-creation and value co-destruction have different effects on customer satisfaction.

This study addresses the gap in the extant research and contributes to a better understanding of the double-sided effects of co-production by integrating employees and customers into a single dyadic and comprehensive model.

Many e-commerce firms suffer from high returns because of inaccurate and incomplete product information. Omnichannel and bundling settings can help firms improve operational efficiency and lower returns costs. However, no studies have been conducted on omnichannel supply chains considering bundling strategies. The purpose of this study is to examine the comparison between test-in-store-and-buy-online (TSBO) and online retail, comparing manufacturers’ bundling with retailers’ bundling.

The supply chain discussed here consists of two competitive manufacturers and one retailer. The retailer sells both manufacturers' products online and displays one manufacturer's product in a showroom who bears the display cost. Stackelberg game theory is used to develop mathematical models that help manufacturers and retailers make the most effective decisions. Here, the manufacturer is the Stackelberg leader, while the retailer is the follower. Using the backward induction approach, the authors determined the optimal values for selling price, wholesale price and service effort level.

The results show that the total TSBO retailing profit under manufacturer bundling is highest when the second manufacturer integrates with the online retailer. The result additionally establishes that when the bundling cost exceeds a certain threshold (1.5), the total profit is higher for the non-integrated type of supply chain channel as compared to the integrated retailer bundling-based configuration.

The operations and logistics manager will likely undertake the TSBO omnichannel strategy during manufacturers bundling and retailer bundling under the integrated strategy.

The main contribution of the study is to examine the effect of TSBO retailing on supply chains profit and individual decision-making under different bundling strategies. The authors developed different mathematical models in the TSBO retailing and bundling context and extended the earlier work in the area of integration frame.

In the new retail era, the supply chain synergy produced by quality integration has become the new direction of service supply chain research. The purpose of this paper is to study how to promote the sustainable development of the retail service supply chain (RSSC) by comparing and analyzing the optimal quality behavior, optimal returns, and the combination of conditions and strategies of the participating members of the RSSC.

From the perspective of quality function development and service quality concern, this paper considers RSSC as a two-level supply chain structure composed of functional service provider and retail service integrator. In this paper, a dynamic optimization model of quality input-cooperation-coordination of RSSC is proposed under two quality cooperation modes of decentralization and integration. This paper adopts the differential game method to compare and analyze the optimal quality behavior, optimal income, forming conditions and strategic combination of the participating members of the RSSC in different situations.

(1) Compared with quality dispersion, quality integration has more significant Pareto improvement effect on quality behavior and optimal revenue of RSSC. (2) In the case of quality integration, the optimal revenue obtained by the service sharing model is generally better than that obtained by the retail alliance collaboration model. (3) Benefit distribution ratio and quality cost allocation determine the optimal quality behavior of participating members of the RSSC, and also become the key factors for participating members to choose the collaborative mode in the case of quality integration.

Based on the quality function development of RSSC, this paper introduces the concept of steady service quality, and discusses the relationship between the quality cooperation stability and the mode selection of RSSC. This provides a theoretical basis for how to build a RSSC with efficient operation and stable quality.