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This study aims to use corporate social responsibility (CSR) reporting focused on poverty alleviation in China as a case to demonstrate a unique interplay between the state and private enterprises. It illustrates how CSR reporting has influenced both the mechanisms and outcomes of their interactive relationship, contributing to the construction of symbolic power.

Drawing on Bourdieu’s theory of symbolic power, this study explores how symbolic power has been constructed and reinforced between the state and private enterprises. It highlights the unique role of CSR reporting in facilitating an alignment between private enterprises objectives and state goals, ultimately reinforcing symbolic and social order. The empirical materials examined are the CSR reports prepared by the top 20 private enterprises in China from 2017 to 2022.

Major private business enterprises in China actively engage with the state’s objectives on poverty alleviation as reflected through their CSR reporting practices. This engagement is evidenced by shifts in keywords, dominant language and reporting structure, which closely align with the state’s stance on the issue. As a result, these enterprises receive heightened public recognition, which in turn helps reinforce the symbolic power and its influence on corporate behaviour.

This paper contributes to the CSR accounting literature by revealing a strategic role of CSR reporting that extends beyond conventional compliance levels commonly observed in Western liberal democratic societies. It serves as a function that facilitates interaction between the state and private enterprises in a symbolic power relationship, where both parties mutually benefit from the alignment of interests in poverty alleviation and social positioning.

This study explores how egoism and altruism as knowledge sharing motivations influence consumers’ electronic word of mouth (eWOM) intentions on food platforms. It also investigates the interaction effect of egoism and altruism on eWOM intentions through attitude toward use (ATU).

A survey was conducted with 523 consumers who posted reviews on Taiwan’s two leading food platforms. The data were analyzed using structural equation modeling to examine the relationships between knowledge sharing motivations, ATU, and eWOM intentions.

Egoism and altruism influence eWOM intentions through ATU, with altruism having a more substantial impact. Their interaction further enhances the positive relationship between ATU and eWOM intentions.

This study fills the empirical gap by demonstrating the interaction effect of egoism and altruism on eWOM intentions. It highlights the role of intrinsic motivations in shaping consumer behavior on digital platforms and offers insights for businesses aiming to foster consumer engagement.

The purpose of this study was to explore Taiwanese consumers attitudes toward upcycled food as a viable and economically sustainable solution to food waste within the context of global environmental pressures caused by the food system. This study applied the theory of planned behavior (TPB) and the value-attitude-behavior (VAB) model to explore the factors shaping consumer behavior toward upcycled food.

A survey was conducted using convenience sampling to collect 295 valid responses from Taiwanese consumers. The questionnaire was designed to measure the relationships among dietary values, moral attitudes, subjective norms, perceived behavioral control and consumers intentions toward the consumption of upcycled food. The data were analyzed using statistical methods to verify the hypotheses derived from the TPB and VAB models.

The findings revealed that dietary values significantly influence moral attitudes, subjective norms and perceived behavioral control, highlighting their pivotal role in consumer behavior toward upcycled food. Moral attitudes, subjective norms, perceived behavioral control, perceived responsibility and thriftiness were positively associated with the intention to consume upcycled food, indicating the potential of these factors in fostering sustainable consumption practices.

This study is unique in its application of the TPB and VAB models to examine the acceptance of upcycled food among Taiwanese consumers, contributing fresh insights into the field of sustainable consumer behavior. This highlights the significance of aligning dietary values and moral attitudes of consumers with sustainable consumption practices, offering a new perspective on promoting upcycled food in Taiwan and potentially in other regions with similar cultural and environmental frameworks.

The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners’ computational thinking.

By analyzing the mechanism of action of ITF on the development of computational thinking, an ITF strategy and corresponding ITS acting on the whole process of programming problem-solving were developed to realize the evaluation of programming problem-solving ideas based on program logic. On the one hand, a lexical and syntactic analysis of the programming problem solutions input by the learners is performed and presented with a tree-like structure. On the other hand, by comparing multiple algorithms, it is implemented to compare the programming problem solutions entered by the learners with the answers and analyze the gaps to give them back to the learners to promote the improvement of their computational thinking.

This study clarifies the mechanism of the role of ITF-based ITS in the computational thinking development process. Results indicated that the ITS designed in this study is effective in promoting students’ computational thinking, especially for low-level learners. It also helped to improve students’ learning motivation, and reducing cognitive load, while there’s no significant difference among learners of different levels.

This study developed an ITS based on ITF to address the problem of learners’ difficulty in obtaining real-time guidance in the current programming problem-solving-based computational thinking development, providing a good aid for college students’ independent programming learning.

The study aims to examine diabetic patients’ switching intentions toward self-monitoring blood glucose devices, incorporating perceived usefulness and perceived ease of use, with switching cost as a moderator.

A self-administered questionnaire was developed using established measuring scales. Data from 321 respondents was collected and analyzed using the partial least squares structural equation modeling approach.

Results indicate that perceived usefulness and perceived ease of use influence switching intention. Switching cost does not moderate the perceived usefulness, perceived ease of use and switching intention. This study reveals important information for healthcare practitioners and device manufacturers.

The significance and originality of this study stem from its pioneering investigation into the switching intentions of diabetic patients regarding self-monitoring glucose devices through the application of the technology acceptance model, thereby addressing a notable gap in the existing literature on diabetes management and technology adoption, which has lacked comprehensive examination of patients’ transition behaviors in this specific context.

Recent worldwide developments have altered how businesses operate. As a result, when making business decisions, the emphasis for many industries has shifted towards digital adoption to ensure sustainability, and the food supply chain is no exception. However, a substantial gap exists in assessing the barriers to a digitised food supply chain enabled by Industry 5.0 technologies. This study strives to bridge the gap by identifying and assessing the barriers to improved traceability.

For this study, a mixed method approach was used encompassing both qualitative and quantitative techniques, including an online survey, exploratory factor analysis (EFA), and the fuzzy evidential reasoning approach (FERA). The literature survey and expert opinion first yielded a list of 18 barriers, which were subsequently examined using EFA. As a result, four barriers were removed. The remaining 14 barriers were then assessed using FERA from the perspectives of the Technology, Organisation and Environment (TOE) framework. Further, a sensitivity analysis was performed to test the model’s reliability.

The present study resulted in the prioritisation of barriers from the TOE perspective. According to the findings, the top three barriers that impede the traceability of Industry 5.0-enabled digital food supply chains are Limited Digital and Physical Infrastructure, Inadequate Capital Investment, and the Intricate Supply Chain Framework.

The findings from this research will prove valuable for decision-makers, practitioners and policymakers in developing methods for improving traceability within the digital food supply chain. Concerned stakeholders may use the findings to identify and take immediate action for better decision-making.

This study’s originality lies in its position as one of the first to identify and examine the challenges to better traceability in an Industry 5.0-enabled digital food supply chain. It also adds value by broadening the TOE framework’s scope in the Industry 5.0-enabled digital food supply chain context.

This research endeavors to conduct a thorough and holistic analysis of the foundational elements that empower the cultivation of dynamic capabilities in micro, small and medium-sized enterprises (MSMEs). The purpose of this study is to determine whether these capabilities have a noticeable impact on the sustainable performance of these enterprises. The study aims to support future research efforts in understanding this phenomenon by filling this knowledge gap and presenting a conceptual framework, thereby enhancing the scholarly discourse in this field.

The study consists of a systematic review of 126 articles meticulously chosen through a series of screening stages employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. This examination is conducted within the organized framework of antecedents, decisions and outcomes-theory, context and methods (ADO-TCM), ensuring a structured and comprehensive analysis.

The study uncovers significant insights, identifying four key antecedents: resource base, organizational learning, managerial expertise and external environment management. These factors are instrumental in fostering dynamic capabilities within the enterprise, leading to sustainable entrepreneurial success and a competitive advantage over rivals.

By comprehending the mechanisms by which dynamic capabilities are established within the enterprise, this study provides a valuable resource for entrepreneurs, professionals and managers, offering them practical insights to leverage.

This systematic literature review is the initial attempt to explain how dynamic capabilities can be used to enhance and accomplish sustainable performance in the context of MSMEs.

As China is on an inevitable march into the digital era, firms have accumulated abundant digital assets, such as algorithms and data. Facing the possibility of using digital assets as a new type input, besides traditional inputs such as capital and labor, would powerful managers perform better? Would managerial power help managers increase the efficiency of how a firm combines traditional and digital inputs and converts them into outputs? Thus, the purpose of this study is to investigate whether powerful managers promotes corporate productivity by using digital assets as a new input.

Using data from listed Chinese firms between 2008 and 2020, the authors constructed panel regressions with three-way fixed effects to examine whether and how managerial power influences corporate productivity in the current digital context, particularly under market uncertainty.

The findings reveal no consistent relationship between managerial power and corporate productivity. The results explain this from two contrasting effects: while managerial power promotes technological change it hinders technical efficiency – two components of total productivity. Moreover, this study identifies market uncertainty as a significant external contingency. In uncertain markets, strong managerial power positively impacts corporate productivity.

The results extend extant theoretical insights in the literature on how managerial power might influence corporate productivity.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

This paper aims to examine the impact of tax avoidance on the cost of debt. It also investigates the effect of tax risk on the relationship between tax avoidance and the cost of debt.

Two hypotheses are tested on a sample of nonfinancial French firms listed in the société des Bources Françaises 120 index from 2010 to 2022 using the feasible generalized least squares. To ensure the robustness of the findings, the authors changed the measures of tax avoidance and tax risk and used instrumental variable regression to effectively address concerns related to endogeneity. Additional analysis is conducted to examine if the relationship between tax avoidance and the cost of debt varies based on the magnitude of tax risk.

The authors found that tax avoidance negatively affects the cost of debt. However, when tax avoidance is associated with a high risk, it impacts positively the cost of debt.

This study’s findings are relevant to firms, creditors and French lawmakers. Creditors must make their decision to grant credit based simultaneously on proxies of tax avoidance and tax risk. Managers must effectively manage tax risks to protect their financial decisions, urging French policymakers to implement new regulations on corporate tax risk management.

To the best of the authors’ knowledge, this study is the first to have investigated the joint impact of tax avoidance and tax risk on the cost of debt in the French context.