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Despite the growing interest in micro-celebrities in destination marketing, their role in transferring cognitive, emotional and behavioral outcomes to destination psychological ownership (DPO) is underexplored. This study aims to address this void by investigating how the perceived characteristics of micro-celebrities influence travel intentions through interactive engagement, perceived information quality and DPO. It highlights three pathways for fostering DPO.

A survey-based design was developed with 302 samples collected and analyzed using partial least squares structural equation modeling and artificial neural network to examine the hypothesized model.

Findings reveal that the expertise and attractiveness of micro-celebrities enhance their perceived personal trustworthiness. This perception encourages social media users to view travel information from micro-celebrities as higher quality and to engage more with them, leading to DPO. Consequently, when social media users experience this psychological ownership, they show a stronger intention to travel to the destination, influenced partly by micro-celebrity marketing.

This study provides a psychological–developmental perspective on micro-celebrity marketing-induced travels. It underscores the importance of fostering micro-celebrity-induced DPO to establish a sustained, mutually beneficial relationship between tourists and destinations.

尽管微名人在目的地营销中的作用已引起学术界的关注, 但他们在传递认知、情感和行为结果至目的地心理所有权中的作用尚未得到充分探索。本研究通过调查微名人的感知特征如何通过互动参与、感知信息质量及目的地心理所有权影响旅行意图, 填补了这一研究空白。此外, 本研究还强调了促进目的地心理所有权的三条途径。

本研究采用基于调查的设计, 收集并分析了302个样本, 并使用偏最小二乘结构方程模型（PLS-SEM）和人工神经网络（ANN）对假设模型进行了检验。

研究结果表明, 微名人的专业知识和吸引力增强了其感知个人可信度。这一感知促使社交媒体用户将微名人分享的旅行信息视为更高质量的信息, 并与他们进行更频繁的互动, 从而促进了目的地心理所有权的形成。由此, 当社交媒体用户体验到这种心理所有权时, 他们表现出更强烈的旅行意图, 这在一定程度上受到微名人营销的影响。

本研究从心理发展的角度探讨了微名人营销引发的旅行意图, 强调了通过微名人激发目的地心理所有权的重要性, 以建立游客与目的地之间持续且互利的关系。

A pesar del creciente interés por las micro-celebridades en el marketing de destinos, su papel en la transferencia de resultados cognitivos, afectivos y conductuales a la apropiación psicológica del destino (DPO) está poco explorado. Esta investigación aborda esta laguna de investigación analizando cómo las características percibidas de las micro-celebridades influyen en las intenciones de viaje a través del compromiso interactivo, la calidad de la información percibida y la DPO. Se destacan tres vías para fomentar la DPO.

Se desarrolló un diseño basado en encuestas, recogiéndose y analizándose 302 observaciones. Se utilizó modelización de ecuaciones estructurales por mínimos cuadrados parciales y redes neuronales artificiales para analizar el modelo propuesto.

Los resultados revelan que la experiencia y el atractivo de las micro-celebridades mejoran su credibilidad personal percibida. Esta percepción anima a los usuarios de redes sociales a considerar la información sobre viajes proporcionada por las micro-celebridades como de mayor calidad y a interactuar más con ellas, lo que conduce a la formación de la apropiación psicológica del destino. Como resultado, cuando los usuarios de redes sociales experimentan esta apropiación psicológica, muestran una mayor intención de viajar al destino, influenciados en parte por el marketing de micro-celebridades.

Este estudio aporta una perspectiva de desarrollo psicológico sobre los viajes inducidos por el marketing de micro-celebridades. Subraya la importancia de fomentar la propiedad psicológica del destino inducida por micro-celebridades para establecer relaciones sostenidas y mutuamente beneficiosas entre los turistas y los destinos.

Although the literature recognizes that coopetition plays a significant role in the success of international construction joint ventures (ICJVs), the impacts of coopetition on the performance outcomes of ICJVs remain largely unknown. This study extends this line of research by theorizing coopetition from three dimensions, i.e. coopetition intensity, coopetition balance and coopetition structure, and examining the relationships between coopetition and ICJV performance outcomes from both the contingency and configuration perspectives.

The hypotheses were tested using survey data from a sample of 188 ICJVs. Structural equation modelling was employed for the contingency approach to estimate the relationships between the three dimensions of coopetition and performance. For the configuration approach, cluster analysis was utilized to identify coopetition patterns. Subsequently, an analysis of variance was employed to analyse the relationships between these coopetition patterns and performance.

The contingency results indicate that while coopetition intensity is positively related to all types of performance, coopetition balance is only positively related to project performance and partner performance. Moreover, coopetition structure is only related to partner performance and socioenvironmental performance. The configuration approach identifies six patterns of coopetition, manifesting different levels of project, partner and socioenvironmental performance.

These findings, therefore, contribute to the ICJV literature by extending the understanding of how coopetition dimensions individually and jointly influence ICJV performance.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

Despite the global success of Lean Six Sigma (LSS) operations, they are frequently criticised for failing to improve a company’s financial performance. This study investigated and contrasted the financial advantages of LSS, Industry 4.0 (I4.0) and Lean Six Sigma 4.0 (LSS4.0) practices in China and the United States.

We conducted statistical analyses using online databases. We applied regression analysis to quantitatively analyse 32,813 responding organisation data from 3,691 A-share manufacturing companies in China and 5,931 responding organisation data from 570 publicly traded manufacturing firms in the United States.

This study discovered the following findings: (1) American companies are paying less attention to LSS, which is gradually becoming more important in Chinese business strategy. (2) There is a strong positive relationship between LSS implementation and financial performance in China. Nonetheless, the financial impact of LSS is less significant in post-industrial countries such as the United States. (3) There is compelling evidence in the Chinese context for the significant impact of higher LSS maturity levels on the financial performance of publicly traded manufacturing firms. However, the financial benefits of higher LSS maturity levels in the United States are less pronounced. (4) Despite frequent discussions in China and the United States, implementing I4.0 and related technologies has yet to yield the desired results, particularly in the United States. (5) LSS4.0 significantly improves organisational financial performance.

This study explored the impact of LSS, I4.0 and LSS4.0 on financial performance and conducted an international comparative study from a big data perspective.

This paper aims to investigate how implementing lean six sigma and Industry 4.0 (LSSI4.0) can influence a company’s financial performance and discusses the current trend involving LSSI4.0 in China.

For statistical analysis, financial data was sourced from the China Stock Market and Accounting Research database. Keywords used to assess the implementation status of LSSI4.0 were extracted from the 2007 to 2020 annual reports of A-share manufacturing companies. Regression analysis was applied to the quantitative analyses of 5,041 observational data points from 945A-share manufacturing companies in China.

LSSI4.0 implementation in the manufacturing industry boosts the firms’ financial performance. However, the former outperforms the latter in terms of long-term advantages. Meanwhile, incorporating lean six sigma (LSS) into Industry 4.0 (I4.0) can lead to long-term improved financial performance compared to solely implementing the I4.0.

The findings possess limited international representativeness because all empirical data were derived from Chinese large manufacturing companies. In addition to return on assets and return on equity, financial performance can also be measured using other financial metrics, such as return on investment. In this study, only listed manufacturing companies were considered as research samples.

Top management must acknowledge the positive impact of LSSI4.0 on financial performance and prioritize implementing I4.0 based on LSS implementation.

Empirical results concerning the effectiveness of LSS implementation in enhancing financial performance are inconclusive, particularly in China. In addition, most studies collected data through surveys and interviews, so the representativeness of their outcomes is limited. Overall, this study evaluated the impact of LSSI4.0 implementation with large sample size.

This study aims to investigate the relationship between individual-level psychological resources and team resilience in the context of expatriate project management teams. It seeks to understand how personal psychological resources contribute to team resilience and explore the dynamic evolution mechanism of team resilience. The goal is to enhance team resilience among expatriates in a BANI (Brittle, Anxious, Nonlinear, and Incomprehensible) world, where organizations face volatile and uncertain conditions.

An online survey was applied for data collection, and 315 valid samples from Chinese expatriates in international construction projects were utilized for data analysis. A structural equation model (SEM) examines the relationships between personal psychological resources and team resilience. The study identifies five psychological factors influencing team resilience: Employee Resilience, Cross-cultural Adjustment, Self-efficacy, Social Support, and Team Climate. The hypothesized relationships are validated through the SEM analysis. Additionally, a fuzzy cognitive map (FCM) is constructed to explore the dynamic mechanism of team resilience formation based on the results of the SEM.

The SEM analysis confirms that employee resilience, cross-cultural adjustment, and team climate positively impact team resilience. Social support and self-efficacy also have positive effects on team climate. Moreover, team climate is found to fully mediate the relationship between self-efficacy and team resilience, as well as between social support and team resilience. The FCM model provides further insights into the dynamic evolution of team resilience, highlighting the varying impact effects of antecedents during the team resilience development process and the effectiveness of different combinations of intervention strategies.

This study contributes to understanding team resilience by identifying the psychological factors influencing team resilience in expatriate project management teams. The findings emphasize the importance of social support and team climate in promoting team resilience. Interventions targeting team climate are found to facilitate the rapid development of team resilience. In contrast, interventions for social support are necessary for sustainable, long-term high levels of team resilience. Based on the dynamic simulation results, strategies for cultivating team resilience through external intervention and internal adjustment are proposed, focusing on social support and team climate. Implementing these strategies can enhance project management team resilience and improve the core competitiveness of contractors in the BANI era.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

We aim to provide a systematic literature review of the determinants and consequences of labor investment efficiency in an international context. First, we offer a theoretical discussion of labor investment efficiency, followed by an examination of its measurement. Next, we review the determinants of labor investment efficiency, categorizing them into firm fundamentals including financial reporting quality, governance and controls, corporate social responsibility/environmental regulation and macroeconomic determinants. Finally, we review the limited empirical literature on the consequences of labor investment efficiency. We also provide some suggestions for future research.

We perform a systematic literature review using the Preferred Reporting Items for a Systematic Review of Meta-Analysis (PRISMA) guidelines to examine archival studies investigating the determinants and consequences of labor investment efficiency. Using a Boolean search strategy on the Scopus and PRISMA selection criteria, we review 86 published archival research articles from 2014 to the end of August 2024.

Our review highlights that firm-level fundamental factors including financial reporting quality have profound implications for labor investment efficiency. Effective governance mechanisms also help mitigate agency conflicts and information asymmetries and alleviate labor investment inefficiencies. Furthermore, the influence of regulations including ESG-related regulations and macroeconomic factors play a crucial role in shaping labor investment decisions. We find very little research on the consequence of labor investment efficiency.

Our review has highlighted that well-functioning corporate governance tools are effective in mitigating inefficient labor investments. Stakeholders, therefore, should ensure that firms have effective internal governance mechanisms in place and that external governance regulations complement and where necessary act as substitutes for internal governance mechanisms to optimize labor investments.

To the best of our knowledge, this study represents the first systematic review of extant research on labor investment efficiency. Our review highlights some research gaps, particularly about the consequences of labor investment efficiency and offers some suggestions for future research.

This paper aims to identify the effects of two types of teaching approaches, namely, project-based learning and place-based learning, on the development of pro-environmental behaviors among university students.

This study used a pre-test–post-test experimental design to evaluate the efficacy of project- and placed-based learning in promoting pro-environmental behaviors among university students. Participants were randomly allocated to either the project-based learning cohort (consisting of 50 participants) or the place-based learning cohort (also consisting of 50 participants). The pre-test assessments evaluated the initial pro-environmental behaviors of the participants. Then, interventions were conducted with the help of instructors. The project-based learning intervention necessitated participants to collectively take part in real-life problem-solving endeavors about environmental matters. On the other hand, the place-based learning intervention prompted participants to record and contemplate their interactions with the surrounding environment. Both interventions sought to augment participants’ understanding, beliefs and actions related to the environment. After the interventions, post-test assessments were carried out to assess any alterations in participants’ pro-environmental behaviors. Mean analysis and paired sample t-test were performed to examine the differences among the pre-test and post-test for both project- and place-based learning.

The findings of this study indicate that the participants have exhibited improved pro-environmental behaviors, including environmental activism, non-activist behaviors and private sphere green behaviors.

This research is original in its analysis of project- and place-based learning approaches for fostering pro-environmental behaviors. By using a pre-test–post-test experimental design, this study provides empirical evidence on the effectiveness of these active learning strategies in shaping environmental attitudes and actions.

This study aims to investigate the impact of corporate social responsibility (CSR) on green innovation by considering the three dimensions of green innovation cognition, behavior and outcomes and to explore the role of situational and measurement factors in this relationship.

This study adopts a meta-analysis method to integrate 208,997 observations from 48 independent empirical studies on CSR and green innovation.

CSR positively affects green innovation cognition, behavior and outcomes. Additionally, the relationship between CSR and green innovation is stronger in Western cultural background than in Eastern ones. The impact of CSR on green innovation is also more significant in small and medium-sized enterprises (SMEs). Moreover, this study shows that the correlation between CSR and green innovation is stronger when the source of data is primary data and when green innovation is measured by non-patent methodologies.

This study elucidates the impact of CSR on green innovation and further clarifies the potential reasons for the divergent findings in existing related studies. The article enriches the theoretical results related to CSR and green innovation and provides valuable insights and references for corporate decision-makers.