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This paper attempts to analyze the relationship between the complementarity degrees of imperfect complementary products and sales strategies and give appropriate sales strategies for a two-stage supply chain.

With respect to two-stage supply chain consisting of two manufacturers who produce imperfect complementary products and one retailer who sells the products, aiming at bundling sales strategy, the authors define complementarity elasticity of products and use it to measure the degree of complementary between two products. Based on Stackelberg game and cooperation, the authors analyze the relationship between the complementarity degrees of imperfect complementary products and appropriate sales strategies.

As the impact of complementarity degree on sales strategy decision-making is better, the authors can pinpoint out which sales decision-making is optimal and which bundling sales strategy is the best for a two-stage supply chain. Considering that the degree of complementarity has a significant impact on the product sales strategy, the authors can point out which sales decision-making is optimal, that is, which bundled sales strategy is the optimal in the secondary supply chain of selling complementary products.

An innovative bundling can expand the sales of existing products and new products. It helps a retailer transcend and defeat competitors by reducing marketing expenses while increasing profits. Proper use of bundling can improve consumers utility and create an overall positive effect for both the enterprises and consumer.

The research can help some retailers to make many appropriate bundling sales strategies.

This paper aims to deal with the coordination problem of the supply chain through cost sharing of corporate social responsibility (CSR) and government subsidy.

With respect to the coordination problem of the supply chain with CSR, this paper constructs a three-stage game model consisting of a dominant retailer, n suppliers and government. From the perspective of cost sharing and government subsidies, this paper discussed the decentralized and centralized decision-making, respectively. On this basis, this paper designed a coordination mechanism considering both cost sharing and government subsidies and explore the impact of cost sharing rate and government subsidy rate on CSR efforts, members’ profits and social welfare.

CSR can improve the profits of supply chain members and the overall performance of the supply chain. Then the profits of supply chain nodal enterprises will be affected by the fulfillment level of CSR of their partners. Furthermore, excessive CSR will erode the supply chain profits and cause resource waste. High CSR costs often make retailers low CSR effort level, while a high CSR cost sharing rate can reduce the profits of suppliers and the supply chain. In addition, excessive government subsidies will lead to the decline of social welfare. Excessive government subsidies will cause the dependence of enterprises and affect their operating efficiency.

The proposed coordination mechanism can effectively do with the coordination problem of the supply chain.

The proposed coordination mechanism considering cost sharing and government subsidies simultaneously can effectively deal with conflict problems and guarantee the supply chain members and the supply chain to maximize their profits and social welfare.

The purpose of this paper is to solve new pricing issues faced by low-carbon companies in the Yellow River Basin, which is caused by the change of key pricing factors in the mixed appliance background of Big Data and blockchain, such as product quality and carbon-emission reduction CER level (hereafter, CER level).

We choose a low-carbon supply chain with a low-carbon manufacturer and a retailer as our research object. Then, we propose that using the ineffective effect of the CER level and the quality and safety level to reflect the relationships among the CER level, the quality and safety level and the market demand is more suitable in the new environment. Based on these, we revise the demand equation. Afterwards, by using Stackelberg game, four cost-sharing situations and their pricing rules are analyzed.

Results indicated that in the four cost-sharing situations, the change trends and the magnitudes of the best retail prices were not affected by the changes of the inputs of the demand information and the traceability services costs (hereafter, DITS costs), the proportion about retailer's DITS costs undertaken by the manufacturer, the ineffective effect coefficient of the CER level and the quality and safety level and the cost optimization coefficient. However, the cost-sharing situations could affect the change magnitudes of the best revenues.

This paper has two main contributions. First, this paper proposes a demand function that is more suitable for the mixed appliance background of Big Data and blockchain. Secondly, this paper improves the cost-sharing model and finds that demand information sharing and traceability service sharing have different impacts on key pricing factors of low-carbon product. In addition, this research provides a theoretical reference for low-carbon supply chain members to formulate pricing strategies in the new background.

This paper aims to conduct research to examine the impact of Internet adoption on the productivity of firms in non-urban China.

The study investigates the impact of Internet adoption on firms' productivity in non-urban China. More specifically, the authors conduct a comprehensive and rigorous study while addressing concerns related to firm-level endogeneity by utilizing firm-level panel data. Information on firms in non-urban areas is collected from China's Annual Surveys of Industrial Firm data. For robustness, the authors implement the instrumental variables approach and propensity score matching estimations to strengthen the evidence for suggestive causal inference. Furthermore, the authors also examine the mechanisms and group heterogeneity.

Evidence indicate that the adoption of Internet technology positively impacts the total factor productivity (TFP) of firms in non-urban areas. According to the heterogeneity analysis, the marginal effect of Internet adoption is more significant and pronounced for labor-intensive, private and small-scale manufacturing firms. Moreover, additional evidence suggest that Internet adoption is beneficial for non-urban firms in expanding their business and enlarging their market. It has also been found that the positive effect of Internet adoption on firms' TFP is amplified by expanding public infrastructure.

The current study supports that the informatization strategy benefits non-urban firms and promotes rural revitalization. The findings suggest the possibility of firms borrowing market size from the closest cities and supporting the ongoing policies of investing in broadband infrastructure to narrow the urban-rural digital gap in China.

Three types of PbTe samples, e.g. nanoparticles, nanowires and bulk ingots, have been prepared. The investigation of the Seebeck coefficient of PbTe nanoparticles and nanowires clearly shows the sign change in the temperature range of 575~650 K, which is not observed for bulk ingots. Unfortunately, this temperature range is within the proposed operation temperature range for thermoelectric devices using PbTe and hence, such a change will affect their proper performance. The observed sign change of Seebeck coefficient is not simply caused by the composition variation at high temperature. It is mainly attributed to the extrinsic-to-intrinsic-semiconductor transition for PbTe nanocrystals due to the competing factors between quantum size effect increasing band gap and self-purification process decreasing their charge carrier concentration, which shift the transition point of nanocrystals to lower range as compare to that of bulk samples. Thus, such phenomenon should be considered carefully in the design of thermoelectric devices using semiconductor nanocrystals, which have attracted much attention recently.

The primary aim of this study is to detail the use of soft computing techniques in business and management research. Its objectives are as follows: to conduct a comprehensive scientometric analysis of publications in the field of soft computing, to explore the evolution of keywords, to identify key research themes and latent topics and to map the intellectual structure of soft computing in the business literature.

This research offers a comprehensive overview of the field by synthesising 43 years (1980–2022) of soft computing research from the Scopus database. It employs descriptive analysis, topic modelling (TM) and scientometric analysis.

This study's co-citation analysis identifies three primary categories of research in the field: the components, the techniques and the benefits of soft computing. Additionally, this study identifies 16 key study themes in the soft computing literature using TM, including decision-making under uncertainty, multi-criteria decision-making (MCDM), the application of deep learning in object detection and fault diagnosis, circular economy and sustainable development and a few others.

This analysis offers a valuable understanding of soft computing for researchers and industry experts and highlights potential areas for future research.

This study uses scientific mapping and performance indicators to analyse a large corpus of 4,512 articles in the field of soft computing. It makes significant contributions to the intellectual and conceptual framework of soft computing research by providing a comprehensive overview of the literature on soft computing literature covering a period of four decades and identifying significant trends and topics to direct future research.