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This paper seeks to apply a framework of collaborative planning, forecasting and replenishment (CPFR) to develop a procurement model for agricultural products.

Considering the biological nature, seasonality and perishable characteristics of agricultural raw materials and products, the paper revises the CPFR reference model. Then, the paper constructs a n‐tier CPFR procurement model by extending a two‐echelon supply chain to a multi‐echelon supply chain and incorporating upstream suppliers in the supply chain. Moreover, the concept of collaborative transportation management (CTM) is integrated into the n‐tier CPFR procurement model. Finally, a case study is analysed and the efficacy of the proposed model is also validated.

The finding suggests that CPFR approach is applied in the procurement of agricultural products. The case results show that the service level is increased and inventory variance is reduced. The proposed model can thus improve the accuracy of forecasting and reduce inventory losses.

The paper offers a useful insight into procurement of agricultural products. The proposed model is a useful development for the agricultural industry in implementing CPFR in the future.

This research investigates the impact of learners' non-substantive responses in online course forums, referred to as online listening responses, on e-learning performance. A common type of response in online course forums, online listening responses consist of brief, non-substantive replies/comments (e.g. “agree,” “I see,” “thank you,” “me too”) and non-textual inputs (e.g. post-voting, emoticons) in online discussions. Extant literature on online forum participation focuses on learners' active participation with substantive inputs and overlooks online listening responses. This research, by contrast, stresses the value of online listening responses in e-learning and their heterogeneous effects across learner characteristics. It calls for recognition and encouragement from online instructors and online forum designers to support this activity.

The large-scale proprietary dataset comes from a leading MOOC (massive open online courses) platform in China. The dataset includes 68,126 records of learners in five MOOCs during 2014–2018. An ordinary least squares model is used to analyze the data and test the hypotheses.

Online listening responses in course forums, along with learners' substantive inputs, positively influence learner performance in online courses. The effects are heterogeneous across learner characteristics, being more prominent for early course registrants, learners with full-time jobs and learners with more e-learning experience, but weaker for female learners.

This research distinguishes learners' brief, non-substantive responses (online listening responses) and substantive inputs (online speaking) as two types of active participation in online forums and provides empirical evidence for the importance of online listening responses in e-learning. It contributes to online forum research by advancing the active-passive dichotomy of online forum participation to a nuanced classification of learner behaviors. It also adds to e-learning research by generating insights into the positive and heterogeneous value of learners' online listening responses to e-learning outcomes. Finally, it enriches online listening research by introducing and examining online listening responses, thereby providing a new avenue to probe online discussions and e-learning performance.

The purpose of this study is to explore the effects of recommendation algorithm, product reputation, new product novelty, privacy concern and privacy protection behavior on users’ satisfaction and continuance intention to use short-form video application (APP).

Based on the existing theories, the research model of this study was developed and 445 valid data were collected through a questionnaire survey. The partial least squares structural equation modeling (PLS-SEM) was employed for data analysis to test the research model and hypotheses.

The results reveal that the recommendation algorithm has a significant positive effect on user satisfaction, new product novelty and privacy concern. The influence of recommendation algorithm on privacy concern is negatively moderated by product reputation. Privacy concern has a significant and positive impact on privacy protection behavior, and privacy protection behavior has a significant and positive impact on user satisfaction. New product novelty also has significant impact on user satisfaction.

This study is one of the earliest studies to incorporate recommendation algorithm as a construct into the college students’ continuance intention to use short-form video APP. The influence of reputation as a moderator variable on the relationship between algorithm and privacy concerns is also investigated.

This study aims to explore how subsidiary capabilities collectively configure for performance. Additionally, it seeks to examine whether these configurations of capabilities can provide equifinal solutions through developing a comprehensive research framework that focuses on subsidiaries in China.

With a data set collected through a questionnaire from 172 Korean multinational enterprises (MNEs) in China, this study used a fuzzy-set qualitative comparative analysis to detect the capability conditions and configurations. These configurations represent combinations of various subsidiary capabilities linked to high performance.

This study identified several complex pathways with distinct configurations for high subsidiary performance. The findings demonstrate the importance of configurations over individual conditions. Thus, the results highlight that the effectiveness of diverse capabilities, which are widely believed to singularly contribute to the high performance of MNE subsidiaries, depends on how each combines with other capabilities. Overall, the findings provide a richer and fine-grained understanding of the role and relative importance of various forms of MNE subsidiary capabilities and how the joint effect of these subsidiaries contributes to high performance.

This study suggests that MNE managers should comprehensively understand how subsidiary capabilities are configured to produce subsidiary performance outcomes. This specifically illustrates the importance of understanding the mutually conflicting yet collectively exhaustive results of multi-selective solutions and aims to align with China’s industrial and regional heterogeneity.

By examining the role of MNE subsidiary capability configurations, which may collectively influence the subsidiary’s performance, this study contributes to the literature. It elucidates how MNE subsidiaries may achieve superior performance by developing and possessing various capabilities tailored to the local context.

For decades, financing constraints have been a major obstacle to corporate performance. Volumes have been written about the probable factors that can help firms alleviate such financial constraints. Nonetheless, empirical evidence concerning the various perspectives on how inventory control may influence financing constraints has been surprisingly scant. Using the resource- and region-based view as theoretical lenses, this study seeks to estimate the relationship between lean inventory, regional financial technology (fintech) and financing constraints.

Utilizing a large-scale sample of small- and medium-sized enterprises (SMEs) in China's manufacturing sector, the authors empirically test their hypotheses by using hierarchical linear regression models with multiple high-dimensional fixed effects.

Results indicate that firms with higher levels of inventory leanness and those located in more fintech-developed regions are less likely to encounter financing constraints. Furthermore, inventory leanness and regional fintech ecosystem development interact with each other to mitigate financing constraints. Moreover, inventory leanness significantly decreases firms' financing constraints when the regional fintech ecosystem is highly developed.

The present research contributes to the literature on the interface of supply chain management and financial management. It also provides managerial implications for policymakers and SME stakeholders.

China's increasing income inequality might cause a series of problems, such as the slowdown of economic growth, social and economic tension, the decline of the ecological environment quality and the threat to citizens' health. Consequently, income inequality will inevitably affect the ecological well-being performance (EWP) level of China's provinces through the above aspects. Analyzing the impact of income inequality on EWP and its spatial spillover effects are conducive to improving the level of EWP in China. Therefore, the research purpose of this paper is to use China's provincial data from 2001 to 2017 to analyze the impact of income inequality on EWP and the spatial spillover effect based on the evaluation of the EWP value of each province.

At first, this study utilizes the super efficiency slacks-based measure model (Super-SBM model) to calculate the EWP values of 30 provinces in China, which can evaluate and rank the effective decision units in the SBM model and make up for the defect that the effective decision units cannot be distinguished. Then this study applies the spatial Durbin model and Tobit regression model (SDM-Tobit model) to explore the impact of income inequality and other influencing factors on EWP and the spatial spillover effects in adjacent areas.

Firstly, the average EWP in China fluctuated slightly and showed a downward trend from 2001 to 2017. In addition, the EWP values of the provinces in the western region are usually weaker than those in the eastern and central regions. Moreover, income inequality is negatively correlated with EWP, and the EWP has a spatial spillover effect, which means the EWP level in a region is affected by EWP values in the adjacent regions. Furthermore, the industrial structure and urbanization level are both negatively related to EWP, while technology level, investment openness, trade openness and education level are positively related to EWP.

Compared with the existing research, the possible contribution of this research is that it takes income inequality as one of the important influencing factors of EWP and adopts the SDM-Tobit model to analyze the impact mechanism of income inequality on EWP from the perspective of time and space, providing new ideas for improving the EWP of various provinces in China.

This study aims to explore the impact of chief executive officers’ (CEOs) values on the socially responsible behaviors (SRBs) of top management teams. Drawing from the social learning framework, it examines the mechanisms through which CEOs’ values shape SRBs within organizational leadership.

Using the hierarchical regression model, this study assesses direct effects, while the Monte Carlo method is used to evaluate indirect effects. The analysis is based on time-lagged data collected from 122 CEOs and 287 corresponding top managers from small- and medium-sized enterprises in China.

The results indicate a positive correlation between CEOs’ self-transcendent values and their own SRBs (i.e. doing-good and avoiding harm behavior). This, in turn, promotes top managers’ SRBs.

By highlighting the micro-foundations of corporate social responsibility, this study enriches the understanding of SRBs enhancement in management teams. It reveals the significance of CEO self-transcendent values as a precursor to SRBs and elucidates the learning processes involved.

The current paper aims to develop a reduced order discontinuous Galerkin method for solving the generalized Swift–Hohenberg equation with application in biological science and mechanical engineering. The generalized Swift–Hohenberg equation is a fourth-order PDE; thus, this paper uses the local discontinuous Galerkin (LDG) method for it.

At first, the spatial direction has been discretized by the LDG technique, as this process results in a nonlinear system of equations based on the time variable. Thus, to achieve more accurate outcomes, this paper uses an exponential time differencing scheme for solving the obtained system of ordinary differential equations. Finally, to decrease the used CPU time, this study combines the proper orthogonal decomposition approach with the LDG method and obtains a reduced order LDG method. The circular and rectangular computational domains have been selected to solve the generalized Swift–Hohenberg equation. Furthermore, the energy stability for the semi-discrete LDG scheme has been discussed.

The results show that the new numerical procedure has not only suitable and acceptable accuracy but also less computational cost compared to the local DG without the proper orthogonal decomposition (POD) approach.

The local DG technique is an efficient numerical procedure for solving models in the fluid flow. The current paper combines the POD approach and the local LDG technique to solve the generalized Swift–Hohenberg equation with application in the fluid mechanics. In the new technique, the computational cost and the used CPU time of the local DG have been reduced.

The financial crisis, which broke in the USA has impacted greatly on the world economy, especially on China's cotton supply chain. It is necessary to understand the welfare change of the cotton chain under this shock of financial crisis in order for relevant policy decisions to be made. The purpose of this paper is to measure the welfare change of all the consumers, producers, circulation and farmers in the cotton supply chain under the shock of financial crisis.

There is no existing mature method to calculate the welfare change of a special supply chain, such as the cotton supply chain. The method most used in such situations is the equilibrium displacement model, created by Muth, and developed by Gardner.

The financial crisis has had important impacts on China cotton industry. Farmers' losses are bigger than people estimate. Circulation link's loss is a little lower than cotton farmers'. Producers' loss is far lower than circulation and cotton farmers. Consumers' loss is the biggest loss in the whole cotton supply chain: however, some of these are foreign consumers – especially foreign wholesalers and retailers.

This paper is the first to study the quantitative welfare change of China's cotton supply chain under the shock of financial crisis, providing useful information for government and company decision making.

Spatial integration and industrial clustering have become an important feature of the culture tourism business. When the core elements in both the culture industry and tourism industry are integrated, a model based on system science is constructed that combines the resources and capacity of the two entities to envisage the ways of creating integrated products and services from the two sectors. Guided by the system science, this study proposes a culture tourism system revealing the clustering and hierarchical structure of the industrial elements. The system contains two subsystems: internal system and external system. The agglomeration model of the system includes 26 indices and the PEF methods, which involved the Parallelogram Law, Entropy-weight Method, and Fuzzy Membership Function. Finally, this study deploys an empirical study involving all provincial territories (N=31) in mainland China. It analyzes the variability and degree of balanced development of the system. In addition, through the resultant data this research adds a typology of culture tourism system along with policy recommendations.