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Based on the attention-based view (ABV), this study examines the mechanism of external pressure and internal managerial interpretation affecting the promotion of green entrepreneurial orientation (GEO) of agricultural enterprises.

Based on data collected from 208 agricultural enterprises in China, the conceptual model was tested by using hierarchical regression.

The results show that managerial interpretation can affect the promotion of GEO. Command and control regulation, market-based regulation and green market pressure are important external pressures that affect the promotion of GEO. In addition, managerial interpretation mediates the relationship between command and control regulation and GEO, market-based regulation and GEO, as well as green market pressure and GEO.

This study proposes a key path for promoting the adoption and implementation of GEO by agricultural enterprises. The research results provide experience for emerging and developing countries to promote the GEO of agricultural enterprises, which is helpful to alleviate the environmental problems caused by the development of agricultural enterprises.

For the first time, this study introduced the ABV into the research of GEO. The research results enrich the theoretical perspective of GEO and expand the research field of the ABV. In addition, this study fills the research gap that existing research has not paid enough attention to the internal driving factors of GEO and opens the black box between the external pressure and GEO.

The purpose of this paper is to propose a research model in which coworker service sabotage influences hospitality employees’ service creativity via work engagement. It also aims to test the moderating effect of sensitivity to the interpersonal mistreatment of others (SIMO).

A time-lagged questionnaire study was performed in hotels in China. The hypotheses were tested via hierarchical multiple regression.

Coworker service sabotage is indirectly associated with hospitality employees’ service creativity via work engagement. The trait of SIMO buffers the harmful effect of coworker service sabotage.

Although our research design helps mitigate common method bias, it could still exist. Other coworker behaviors that might influence employees were not included in this research. The findings may also be biased due to the restricted sample from China.

Hospitality organizations should take measures to curb service sabotage. Organizations could also provide supportive resources to suppress the negative impacts of coworker service sabotage. Moreover, organizations should motivate those low in SIMO to care more about customers.

The research takes the lead in investigating the outcomes of service sabotage from a third-party perspective. Work engagement is identified as the mechanism for transmitting the impact of coworker service sabotage to employees. Moreover, a new moderator that attenuates the negative effects of coworker service sabotage is found.

Drawing on organizational justice theory, this study aims to investigate how perceived organizational exploitation induces frontline hospitality employees’ organizational and interpersonal deviance. Specifically, this study explored the mediating effect of distributive and procedural justice, as well as the moderating effect of justice sensitivity.

The focal research analyzed multiphase survey data from 267 frontline service employees with structural equation modeling.

The results revealed that perceived organizational exploitation induced frontline hospitality employees’ organizational and interpersonal deviance through their perceptions of distributive and procedural justice. Moreover, employees’ justice sensitivity amplified perceived organizational exploitation’s harmful impact on justice perceptions and its conditional influence on organizational and interpersonal deviance.

Organizations should take actions to reduce the occurrence of exploitation to prevent employees’ workplace deviance behaviors. Moreover, organizations can foster employees’ justice perceptions and take care of employees with strong justice sensitivity to reduce the destructive behaviors triggered by organizational exploitation.

By investigating frontline employees’ workplace deviant behaviors, this research identifies new outcomes of exploitation by hospitality organizations. Moreover, the research contributes by offering a justice-based perspective to understand the effects of perceived organizational exploitation. Furthermore, this research helps identify a new boundary condition of being exploited by organizations.

This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger.

The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis.

The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency.

This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management.

Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations.

In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment.

This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

This study aims to examine the relationship between contextual factors and career exploration. Career adaptability mediates the relationship between social support, sense of belonging and career exploration.

This quantitative study involved 291 undergraduates recruited from two universities in China. Data were analyzed using structural equation modeling.

The results indicated that social support and sense of belonging were positively related to career adaptability. Career adaptability was found to be a mediator between relational predictors and career exploration. Contrary to our hypothesis, the direct path from sense of belonging to career exploration was insignificant.

This study highlights the importance of career adaptability in connecting contextual indicators and career exploration in the Chinese context.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

Suning Group launched Suning.com when its chain stores were developing at the highest speed, realizing the transformation to an Internet retailer. Suning continued to follow the growth strategy of “Technological transformation and Smart Services”, and was renamed Suning Commerce Co. Ltd. It launched a business model of “e-commerce + stores + retail service providers”. Riding on the brand new O2O business model, Suning is thinking and practicing from simple donation to actual implementation, from constructing public welfare network to extending CSR ecosystem in a bid to advance towards deeper and more extensive Internet economy, and to create greater social value.

This study aims to compare machine learning models, datasets and splitting training-testing using data mining methods to detect financial statement fraud.

This study uses a quantitative approach from secondary data on the financial reports of companies listed on the Indonesia Stock Exchange in the last ten years, from 2010 to 2019. Research variables use financial and non-financial variables. Indicators of financial statement fraud are determined based on notes or sanctions from regulators and financial statement restatements with special supervision.

The findings show that the Extremely Randomized Trees (ERT) model performs better than other machine learning models. The best original-sampling dataset compared to other dataset treatments. Training testing splitting 80:10 is the best compared to other training-testing splitting treatments. So the ERT model with an original-sampling dataset and 80:10 training-testing splitting are the most appropriate for detecting future financial statement fraud.

This study can be used by regulators, investors, stakeholders and financial crime experts to add insight into better methods of detecting financial statement fraud.

This study proposes a machine learning model that has not been discussed in previous studies and performs comparisons to obtain the best financial statement fraud detection results. Practitioners and academics can use findings for further research development.