On the background of an online/offline dual channel, this paper studies contract coordination of centralized and decentralized dual-channel closed-loop supply chains. With the feature of recycle rate fluctuation, we develop a revenue-sharing mechanism by taking the relationship between the recycle rate and the recycle revenue sharing ratio into consideration. After comparing of centralized decision and the manufacturing led decentralized decision, the optimal online/offline price, wholesale price and advertising investment are derived. The influence of revenue sharing ratio in forward and reverse channels on the online/offline prices and wholesale prices is discussed. The numeric example is used for observing the relationship between variables, and between the optimal profit and variables through analysis of changing parameter valuations.
Purpose The online direct selling mode has been widely accepted by enterprises in the O2O era. However, the dual-channel (online/offline, forward/backward) operations of the closed-loop supply chain (CLSC) changed the relationship between manufacturers and retailers, thus resulting in channel conflict. The purpose of this paper is to take a dual-channel operations of CLSC as the research target, where a manufacturer sells a single product through a direct e-channel as well as a conventional retail channel; the retailer are responsible for collecting used products in the reverse supply chain and the manufacturer are responsible for remanufacturing. Design/methodology/approach The authors build a benchmark model of dual-channel price and service competition and take the return rate, which is considered to be related to the service level of the retailer, as the function of the service level to extend the model in the reverse SC. The authors then analyze the optimal pricing and service decision under centralization and decentralization, respectively. Finally, with the revenue-sharing factor, wholesale price and recycling price transfer payment coefficient as contract parameters, the paper also designs a revenue-sharing contract led by the manufacturer and explores in what situation the contract could realize the Pareto optimization of all players. Findings In the baseline model, the results show that optimal price and service level correlate positively in centralization; however, the relation relies on consumers’ price sensitivity in decentralization. In the extension model, the relationship between price and service level also relies on the relative value of increased service cost and remanufacturing saved cost. When the return rate correlates with the service level, a recycling transfer payment can elevate the service level and thus raise the return rate. Through analyzing the parameters in revenue-sharing contract, a point can be reached where lowering the wholesale price and raising the transfer payment coefficient will promote retailers to share revenue. Practical implications Many enterprises establish the dual-channel distribution system both online and offline, which need to understand how to resolve their channel conflict. The conflict is especially strong in CLSC with remanufacturing. The result helps the node enterprises realize the coordination of the dual-channel CLSC. Originality/value It takes into account the fact that there are two complementary relationships, such as online selling and offline delivery; used product recycling and remanufacturing. The authors optimize the strategy of product pricing and service level in order to solve channel conflict and double marginalization in the closed-loop dual-channel distribution network.
Purpose The purpose of this paper is to investigate and understand China’s rural farmers’ financing intention of inclusive finance, and it examines related drivers like knowledge of inclusive finance, perceived benefits and perceived risks of ordering finance. Besides, the social enterprise embeddedness and digital finance are integrated into the conceptual model to further investigate their moderating impact. Design/methodology/approach The authors designed an inclusive finance intention model to examine the relations between dependent variable knowledge of inclusive finance, intermediary variables perceived benefits and perceived risks of ordering finance and the independent variable financing intention of inclusive finance. The embeddedness of social enterprise and digital finance were identified as modifying factors. Both exploratory and conclusive research strategies were applied. A structured questionnaire was developed to collect empirical data from the rural areas of China. Findings It suggests that knowledge of inclusive finance can strengthen both perceived benefits and perceived risk of ordering finance. Interestingly, the embeddness of social enterprise can significantly reduce risk perceptions and improve perceived benefits of ordering finance. Furthermore, perceived benefits of ordering finance can positively enhance rural farmers’ financing intention of inclusive finance, whereas perceived risks can negatively influence the financing intention. Moreover, digital finance as a modifying factor can significantly strengthen the positive correlation between perceived benefits of ordering finance and financing intention of inclusive finance. Practical implications The research indicates that a systematic inclusive finance educational project is needed to enhance rural farmers’ understanding of inclusive finance and its components. Moreover, the study reveals that it is crucial to promote social enterprise participation and digital finance to develop inclusive finance in rural China, as the service attributes of social enterprise and efficiency of digital finance can greatly reduce the existing transaction cost of farmers. Originality/value The conceptual model would potentially contribute to researchers interested in investigating the financing intention of inclusive financial services relating to rural population. The integration of social enterprise embeddedness and digital finance is the uniqueness of this research conceptual model.
This research develops a forecasting model that can predict the quantity, time and probability of product return, recyclable parts/components/materials and disposal. It adopts the Graphical Evaluation and Review Technique (GERT) by translating the remanufacturing operational process into a stochastic network. This stochastic network possesses two characteristics: activities having a probability of occurrence associated with them; and time to perform an activity. Together with the GERT method, Mason's rule is applied to calculate the equivalence transfer function of the system, therefore predicting the desired outcomes. A generic eight-step process on how to implement this method in any structure of return products and remanufacturing network is provided. A numerical example is presented to demonstrate the result of using GERT on forecasting printer remanufacturing outcomes. The main contribution of this research is: Instead of giving one result such as either return quantity, or time, or probability, our research can forecast three of these outcomes simultaneously, and the algorithm is generalised to be applicable to any product structure and remanufacturing network.
The digital economy plays an important role in promoting regional green innovation. Based on the panel data of 30 provincial administrative regions in mainland China (except Tibet) from 2011 to 2018, this paper constructs a comprehensive development index of the digital economy and explores the potential path of the digital economy affecting regional green innovation through factor analysis and regression analysis. The results show the following: Firstly, the digital economy can effectively promote regional green innovation capability. The causal relationship is mainly realized through scientific research funds and human resources. Secondly, in terms of regional heterogeneity, the role of the digital economy in promoting green innovation and R&D investment in eastern China is stronger than that in central and western China. Thirdly, further analysis showed that the digital economy has a significant nonlinear influence on regional green innovation capability. This feature is mainly reflected in the influence of R&D personnel on regional green innovation. Therefore, the rational allocation of R&D resources is conducive to the development of regional green innovation. Finally, it is suggested to improve the two mechanisms of R&D funds and personnel investment to actuate regional green innovation development.
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