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The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

This study investigates the influence of social trust on the attainment of corporate environmental, social and governance (ESG) objectives.

This study conducts panel regression analysis on a distinctive dataset for 2009–2017 on Chinese firms.

The analysis reveals a significant positive association between social trust and firm-level ESG practices. Moreover, the impact of social trust on shaping ESG outcomes is further amplified by factors such as economic growth, corporate governance standards and institutional quality. This relationship remains statistically positive when the authors employ alternative measures and methodologies, such as the instrumental variables, propensity score matching and difference-in-differences approaches. Notably, the results of heterogeneity tests indicate that the Trust–ESG nexus is more prominent for state-owned enterprises and firms with substantial market capitalization, superior profitability and higher leverage.

This study expands the comprehension of the determinants of ESG and underscores the influential role of social trust as an informal institution in enhancing a firm's ESG performance.

This case is mainly about the development journey of Tujia, a unicorn in China's accommodations-sharing sector, as well as the development status of the sector. On December 1, 2011, Tujia.com—China's first medium- and high-end vacation apartment booking platform—was formally launched, and it announced the first round of capital injection in less than half a year after its launch. It completed D and D+ round of financing on August 3, 2015, securing $300 million with an estimated value exceeding $1 billion. The completion of this financing round meant that Tujia formally entered the $1 billion club composed of “unicorn” Internet companies. In June 2016, it announced the strategic M&A of Mayi; in October 2016, it announced its strategic agreement with Ctrip.com and Qunar.com for the M&A of their apartment and homestay businesses. The completion of these transactions manifested the matrix with the four major platforms Tujia, Mayi, Ctrip, and Qunar. Since then, Tujia has become the absolute pacesetter in China's online accommodations-sharing sector.

This paper aims to assess the readiness of retail workers to use blockchain technology (BCT) to improve supply chain performance. The assessment was made via a quantitative approach taken using a theoretical framework based on Keller’s motivation model and self-determination theory in the BCT context.

The authors collected data from 567 retail workers from an emerging country through a structured survey questionnaire. The authors tested the hypotheses of the proposed model using Warp PLS 7.0 and controlled firm age, industry type and technological intensity.

Our findings may help firms in making the process of digital transformation inclusive. The authors found that supplier-based attention and motivation through BCT lead to supply chain performance, and that supplier-based satisfaction and trust achieved through BCT positively impact supply chain performance. Further, supplier-based relevance on raw material selection with the higher trust and motivation levels achieved through BCT was found to have a positive impact on supply chain performance.

IT supply chain applications are referred to as “lean” rather than “rich” because they still rely mainly on written and numerical means to present data. When the environment is less ambiguous, then less rich media can be used to facilitate communication. IT supply chain applications allow suppliers to spend time building relationships with other suppliers instead of focusing on administrative tasks, thus enhancing such relationships.

This study can be considered the first to assess retailer readiness to use BCT to improve supply chain performance through the theoretical lens of Keller’s motivation model and self-determination theory.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

This study aims to focus on the impact of multi-level knowledge sharing between and within organizations on the risk control of rural inclusive finance. The paper presents a synergistic risk control system integrating external and internal factors for rural inclusive finance by constructing different knowledge-sharing platforms in an environment, which is full of many uncertainties.

This study is based on survey methods. To achieve the research objectives, the authors adopt a single case study approach. For data collection, the authors apply a wide variety of methods such as semi-structured interviews, field visits, second-hand databases and official websites.

The results emphasize that using multi-level knowledge sharing such as the inter- and intra-organizational level, can facilitate the risk control of rural inclusive finance during the post-COVID-19 era. Furthermore, it is also noted that achieving knowledge sharing at different levels by building diverse knowledge-sharing platforms can promote the risk control of rural inclusive finance from the individual-organization level to the chain level of multi-organization collaboration, which contributes to the formation of symbiotic risk control ecology.

The authors have formed the “Chinese wisdom” to deal with inclusive financial risks and to promote in-depth development in relation to the “last mile” practice of inclusive finance, which means the final and the most important phase of a project. The conclusions contribute to enriching the outcomes regarding the risk control of rural inclusive finance, provide experiences to its sustainable development and offer a reference to other countries with their risk control of rural inclusive finance.

Drawing on the knowledge-sharing approach, this study creatively resolves the persistent problems in the risk control of rural inclusive finance, which forms a powerful supplement to the extant literature. Meanwhile, the paper combines the two contextual factors of the post-COVID-19 era and emerging economies, which can be deemed as a novel attempt.

This study aims to provide further insights into the connection between corporate social responsibility (CSR) and companies’ credit ratings, while also exploring the role of corporate governance as a moderating factor. The hypotheses for this relationship are rooted in both legitimacy and stakeholder theories.

Using a sample of French non-financial listed firms from 2007 to 2020, this paper uses the ordered probit model introduced by Greene (2000). The issue of endogeneity has also been addressed.

The study reveals that CSR practices positively impact companies’ credit ratings by enhancing solvency and financial performance. Specifically, firms that prioritize CSR, particularly in the social and environmental dimensions (such as community relations, diversity, employee relations, environmental performance and product characteristics), tend to have higher credit ratings and a reduced risk of default. This suggests that credit rating agencies likely incorporate CSR performance when assigning credit ratings. Furthermore, the quality of corporate governance acts as a moderator, strengthening the relationship between CSR and credit ratings. The findings remain robust even after accounting for key firm attributes and addressing potential endogeneity between CSR and credit ratings.

This research provides valuable guidance for policymakers, corporate managers, investors and other stakeholders, as it offers insights into the influence of CSR activities on risk premiums and financing costs. For financial institutions, expanding credit decisions to encompass non-financial factors such as CSR can result in more accurate predictions of firm credit quality compared to relying solely on financial indicators.

To the best of the authors’ knowledge, this study stands out as the first to systematically examine the relationship between CSR and credit ratings within the French context. Moreover, it distinguishes itself by investigating the moderating influence of corporate governance on this relationship, setting it apart from prior research.

Construction education rarely addressed the importance of disseminating knowledge on infrastructure equity, thus impeding progress toward creating equitable and sustainable developments. This study aims to investigate the existing sustainability courses under the American Council for Construction Education (ACCE) accredited construction management (CM) programs to examine the integration of infrastructure equity topics and assess improvement in CM students’ knowledge and awareness to address this issue through an intervention.

To achieve these objectives, this research reviewed the sustainability course descriptions of the ACCE-accredited undergraduate and graduate CM curricula. Furthermore, the study implemented a workshop within a CM sustainability course that taught the students about the key concepts of infrastructure equity as well as how to address this issue by leveraging the Envision infrastructure rating system.

The course review results showed that most sustainability courses lack topics such as infrastructure equity and social sustainability. Moreover, the analysis of pre- and postworkshop surveys indicated that guided training could improve the students’ understanding as well as boost their confidence to address and mitigate infrastructure inequity issues.

The findings of the study are valuable for increasing awareness of infrastructure equity and facilitating the future construction workforce with the required expertise to develop equitable infrastructure systems.

To predict the future of the business and implement successful changes, a credit analyst must make quick decisions about the economics and assets of their clients. Because the marketplace is constantly changing, companies that lack the interpersonal skills necessary to communicate with their customers run the risk of falling behind the competition and becoming obsolete. The objective of this research was to assess whether credit analysts in Peruvian banks that used digital resources also improved their communication and interpersonal skills. The study was quantitative in nature, with an applied and correlational design that lacked an experimental component. The sample consisted of 109 credit analysts from four different Peruvian banks (Interbank, Scotiabank, BBVA, and BCP). Two questionnaires were used in this survey; both were submitted to expert review for validation before being submitted for use, and their reliability was determined using Cronbach's alpha. In terms of use of digital resources (59.5%) and mastery of interpersonal skills (61.3%), credit analysts were at the average. Conclusions the p-value for the correlation between credit analysts' use of digital resources and their soft skills in Peruvian banks was less than 0.05, indicating a direct and strong link between these two factors. The Rho correlation coefficient was 0.738.