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Counterproductive work behavior (CWB) has grown into a significant problem in the tourism industry, for both individual employees and organizations. Employees who feel ostracized in their workplace often engage in negative and disruptive behaviors. The purpose of this study is to explore the psychological mechanism between workplace ostracism and CWB among tourism employees.

Drawing on psychological contract theory and social cognitive theory, the study proposed a research framework to explain tourism employees’ counterproductive behavior. Data were collected from 228 hotel employees at two time points in Huangshan, China. Hierarchical regression and SPSS-PROCESS Macro were used to test all the hypotheses.

Findings show that workplace ostracism significantly increases employee CWB, mediated by psychological contract violation. Workplace ostracism increases perceptions of psychological contract violation when employee self-esteem is higher. The mediating effect of psychological contract violation is also moderated by self-esteem.

Using the framework of psychological contract theory and social cognitive theory, the authors advance the organizational behavior literature in the tourism field. The authors contextualize the uniqueness of Chinese workplace behavior and highlight the need to understand “losing face (mianzi) view” in workplace relationships. This research contributes to better understanding the dark side of tourism workplace behavior by examining the effects of psychological contract violation and employee’s self-esteem on workplace ostracism and CWB.

旅游业中的反生产行为（CWB）已经成为一个重要问题, 反生产行为对员工和组织都会产生影响。在工作场所感到被排斥的员工往往会从事消极和破坏性的行为。本文的目的是研究旅游业员工工作场所排斥与反生产行为之间的心理机制。

基于心理契约理论和社会认知理论, 本研究提出了一个研究框架来解释旅游业员工的反生产行为发生机制。我们在中国黄山景区对228名酒店员工进行了两个时间点的问卷调查。采用分层回归和SPSS PROCESS Macro来测试所有假设。

结果表明 工作场所排斥显著增加员工反生产行为, 心理契约违背在其中起着中介作用。当员工自尊心较高时, 职场排斥对心理契约违反的感知影响更强。心理契约违背的中介效应也受到自尊心的调节。

我们运用心理契约理论和社会认知理论的框架, 推动了旅游领域的组织行为研究进展。我们讨论了中国情境下职场行为的独特性, 并强调在职场关系中需要考虑“面子观”。我们通过展示心理契约违背和员工自尊心对工作场所排斥和反生产行为（CWB）的影响, 有助于更好地理解旅游工作场所行为的负面影响。

El comportamiento laboral contraproducente (CLC) en la industria turística se ha convertido en un problema significativo tanto para los empleados individuales como para las organizaciones. Los empleados que se sienten marginados en su lugar de trabajo suelen participar en comportamientos negativos y disruptivos. El objetivo de este trabajo es examinar los efectos de la violación del contrato psicológico y la autoestima del empleado en el ostracismo en el lugar de trabajo y en el comportamiento laboral contraproducente CLC y agregar nuevos conocimientos para comprender mejor el lado oscuro del comportamiento laboral turístico.

Realizamos una encuesta de cuestionario a 228 empleados de hotel en dos momentos en Huangshan, China. Se utilizaron la regresión jerárquica y el SPSS PROCESS Macro para probar todas las hipótesis.

Los resultados muestran que 1) el ostracismo en el lugar de trabajo aumenta significativamente la CLC de los empleados. 2) La violación psicológica del contrato juega un papel mediador entre el ostracismo en el lugar de trabajo y CLC. 3) El ostracismo en el lugar de trabajo aumenta las percepciones de violación psicológica del contrato cuando la autoestima de los empleados es mayor. 4) El efecto mediador de la violación psicológica del contrato también es moderado por la autoestima.

Utilizando el marco de la teoría del contrato psicológico y la teoría cognitiva social, avanzamos en la literatura del comportamiento organizacional en el campo del turismo. Contextualizamos la singularidad del comportamiento en el lugar de trabajo chino y destacamos la necesidad de comprender la 'pérdida de la visión de la cara (mianzi)' en las relaciones laborales. Esta investigación contribuye con nuevos conocimientos para comprender mejor el lado oscuro del comportamiento turístico en el lugar de trabajo al examinar los efectos de la violación psicológica del contrato y la autoestima de los empleados en el ostracismo en el lugar de trabajo.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

This study examines the relationship between internal control and corporate environmental responsibility.

Unlike US studies that concentrate solely on internal control over financial reporting, this study uses a comprehensive index that encompasses internal control over financial reporting, operations, and compliance. Corporate environmental responsibility is measured by environmental investments. Our research sample comprises Chinese listed firms from 2010 to 2018.

The results demonstrate a positive correlation between internal control and corporate environmental investments. Furthermore, we find that firms with high-quality internal control can improve their financial and environmental performance through environmental investments. After decomposing internal control into its five components, we show that the control environment, control activities, and information and communication components exhibit stronger effects on environmental investments than the risk assessment and monitoring components. Finally, the cross-sectional analyses reveal that the positive effect of internal control is more pronounced in private firms and in firms that are subject to weaker environmental regulation.

By focusing on the effect of a comprehensive internal mechanism on corporate environmental responsibility in China, this study contributes to the literature in developed-country settings that overwhelmingly focuses on the impact of external stakeholders and regulations.

The purpose of this study is to investigate the influencing mechanism of consumers' continuous purchase intention toward the subscriber-based knowledge payment platforms (SBKPPs).

This study obtained 226 valid samples through questionnaire surveys and used partial least square structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods to elucidate the complex causal patterns of consumers' continuous purchase intention toward the SBKPPs.

The findings revealed that perceived utilitarian value, perceived hedonic value and perceived social value directly affected consumers' continuous purchase intention, while content quality and service quality indirectly affected consumers' continuous purchase intention. In addition, this study also demonstrated that all factors must be combined to play a role, and there exist four configurations resulting in consumers' continuous purchase intention toward the SBKPPs.

The results can help researchers and practitioners better understand the causal patterns of consumers' continuous purchase intention toward the SBKPPs.

This study contributes to the knowledge payment literature by investigating consumers' continuous purchase intention toward the SBKPPs. This study also provides practical enlightenment for the SBKPPs' marketing.

The main aim of this paper is to establish a reasonable and scientific evaluation index system to assess the high quality and full employment (HQaFE).

This paper uses a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria framework to evaluate the quality and quantity of employment, wherein the integrated weights of attributes are determined by the combined the Criteria Importance Through Inter-criteria Correlation (CRITIC) and entropy approaches.

Firstly, the gap in the Yangtze River Delta in employment quality is narrowing year by year; secondly, employment skills as well as employment supply and demand are the primary indicators that determine the HQaFE; finally, the evaluation scores are clearly hierarchical, in the order of Shanghai, Jiangsu, Zhejiang and Anhui.

A scientific and reasonable evaluation index system is constructed. A novel CRITIC-entropy-TOPSIS evaluation is proposed to make the results more objective. Some policy recommendations that can promote the achievement of HQaFE are proposed.

Digitalization is one of the major factors that fosters economic growth across the world. However, the level of digitalization varies significantly between developed and developing countries, with the latter often lagging behind. To bridge this gap, it is crucial to pinpoint the drivers of digitalization, specifically from the macroeconomic and country-level governance dimensions. Therefore, this study aims to investigate the determinants of digitalization, particularly for countries in Asia and the Pacific region.

Our study utilizes unbalanced panel data from 46 Asian and Pacific countries for the period of 2001–2021. Initially, we analyzed the data using conventional econometric methods, such as pooled ordinary least squares (POLS), random-effects model (REM) and fixed-effects model (FEM). Moreover, we employed endogeneity-corrected techniques and alternative proxies to enhance the robustness and reliability of our findings.

Our findings reveal that economic development progress, government expenditure relative to country size and political stability are key drivers of digitalization. In contrast, corruption at the country level emerges as a significant impediment. Notably, our results remain robust to endogeneity-corrected techniques and alternative proxies of digitalization. Overall, these insights can inform policymakers, helping them to understand the macroeconomic and governance factors shaping digitalization and guide their decision-making toward effective policy interventions.

This study’s empirical findings add significant value to the existing literature by quantifying the impact of macroeconomic and governance factors on digitalization in selected countries. This offers valuable insights for policymakers, particularly in nations with lower levels of digitalization.

This study aims to investigate the influence mechanism of expatriates' cultural intelligence (CQ) on expatriate effectiveness (task performance and premature return intention), identifying work engagement as a mediator and cultural distance as a boundary condition.

Drawing on the conservation of resource theory and the person–environment fit (P–E fit) theory, a moderated mediation model is built. Working with a sample of 303 international construction expatriates collected by snowball sampling, the hypotheses are tested by using the structural equation model analysis.

Work engagement partially mediates the relationship between expatriates' CQ and task performance, as well as fully mediates the relationship between expatriates' CQ and premature return intention. Cultural distance moderates the positive relationship between CQ and work engagement, as well as moderates the mediating effects of work engagement.

The impacts of potential moderators (e.g. work–family conflict and organizational culture) on the relationship between CQ and expatriate effectiveness have not been considered in this study.

This study is useful for international construction firms to optimize the allocation of human resources.

This study contributes to the expatriate literature by adding empirical evidence to explain the influence mechanism of expatriates' CQ on expatriate effectiveness.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

This study aims to propose and develop a new digital collaborative supply chain (CSC) model completely based on the emerging Industry 4.0 technologies. The digital model aims to support the main factors likely to affect CSC. This proposed model combines the most well-known digital tools such as blockchain technology, Internet of Things (IoT) and cloud computing (CC).

Motivated by its effective solution to enhance trust, traceability, transparency and minimize costs and risks, the combination of the most well-known digital tools such as blockchain technology, IoT and CC to develop a new digital CSC model is addressed in this research. This study first investigates and conducts a deep review analysis that explores how Industry 4.0 technologies can enable collaboration mechanisms. Second, based on an analysis of literature review, the main factors likely to affect CSC have been identified and analysed. Finally, the authors combine digital tools to support the identified factors to enhance transparency, traceability and trust by proposing a new digital CSC model. This proposed model will be used as a referential guide to encourage and motivate SC actors to collaborate in digital CSC.

This work provides many important contributions to theory and practice. First, role and impacts of the most well-known digital tools such as blockchain technology, IoT and CC for digitizing CSC have separately presented and developed. Second, the authors conceptualized a framework by developing a new digital CSC model. This conceptual digital model can be used as a referential guide for all SC actors in order to motivate them to collaborate in a modern, intelligent, secure and reliable SC. It can also support all factors affecting CSC.

The originality of this study is first investigating separately the roles and impacts of each digital tool on CSC performance. Second, the authors combine the most well-known digital tools such as blockchain technology, IoT and CC in order to develop an efficient, smart, modern and new digital CSC model. In this combination, CC is used as platform as a service enabling to link and connect the blockchain and IoT to support the main factors affecting CSC. Unlike to digital CSC model with only one digital tool, the proposed model is more realistic since depending on the information to be shared with other actors, the most appropriate tool will be automatically detected and used. This solution offers a large choice to SC actors for real time data and information sharing. In addition, the proposed model will largely enhance traceability, transparency and trust in CSC.

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.