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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.

We investigated consumers’ environmental, social and local beliefs and their impact on attitudes, subjective norms and willingness to pay for sustainable coffee in the understudied context of Thailand.

The study is based on a survey of 253 Thai consumers, analysed through an extended model of the theory of planned behaviour (TPB).

The study validates the TPB model in the Thai demographic, finding a significant positive impact of environmental and local beliefs and subjective norms on willingness to pay for sustainable coffee. More importantly, it proposes an extended model of TPB, stressing the central role of “local beliefs” in sustainable consumption in a Global South context.

This study demonstrates the importance of “localness” in the practice of sustainable consumption in Thailand, namely the beliefs in the support for the local economy and prosperity for the local community. This expands our understanding of the heterogeneous meanings associated with the practice of sustainable consumption in a South-East Asian context.

The purpose of this paper is to unveil the efficacy of coaching leadership within Chinese organizations and bolster employees’ work engagement.

The sample data were collected through employing the questionnaire method. The participants consisted of 234 employees and 53 supervisors in Chinese enterprises. Hypothesis testing was conducted using multiple regression analysis and the Bootstrap method.

The coaching leadership exhibited a positive association with employees’ work engagement, psychological safety and self-efficacy. It was observed that employees’ psychological safety and self-efficacy played a dual-mediation role between coaching leadership and work engagement. Additionally, employees with power distance orientation (POD) amplified the positive effects of coaching leadership on psychological safety and self-efficacy.

This study contributes to the literature on coaching leadership and work engagement by elucidating their direct influence, as well as the dual-mediating roles of psychological safety and self-efficacy. Besides, our findings underscore the moderating effect of POD in amplifying the impacts of coaching leadership. However, the nonlongitudinal survey design adopted by our study should be noted for its potential limitations in establishing causality.

The findings demonstrate that coaching leadership, psychological safety and self-efficacy play a crucial role in fostering work engagement. Employees with higher POD are more likely to benefit from coaching leaders.

This study contributes to coaching leadership literature and provides insights into how and when coaching leadership affects work engagement in Chinese organizations.

As an ancient art form, embroidery has strong practicality and artistic value. However, current embroidery style migration models produce images with unclear textures and a lack of stitch detail. So, in this paper, we propose a cyclic consistent embroidery style migration network with texture constraints, which is called Texture Cycle GAN (TCGAN).

The model is based on the existing Cycle GAN network with an additional texture module. This texture module is implemented using a pre-trained Markovian adversarial network to synthesize embroidery texture features. The overall algorithm consists of two generative adversarial networks (for style migration) and the Markovian adversarial network (for texture synthesis).

Qualitative and quantitative experiments show that, compared with the existing convolutional neural network style transfer algorithm, the introduction of the texture-constrained embroidery style transfer model TCGAN can effectively learn the characteristics of style images, generate digital embroidery works with clear texture and natural stitches and achieve more realistic embroidery simulation effects.

By improving the algorithm for image style migration and designing a reasonable loss function, the generated embroidery patterns are made more detailed, which shows that the model can improve the realism of embroidery style simulation and help to improve the standard of embroidery craftsmanship, thus promoting the development of the embroidery industry.

Digital transformation and innovation-driven development have become an international consensus. The purpose of this paper is to examine the effects of relationships, mechanisms and economic consequences between digital transformation and enterprise innovation quality in order to provide a benchmark for developing countries to implement digital transformation strategies and innovation-driven strategies and provide a major support for economic recovery in the post-coronavirus disease 2019 (COVID-19) era.

Using microdata from A-share listed enterprises in Shanghai and Shenzhen from 2010 to 2021, this study examines the relationship between digital transformation and enterprise innovation quality and further reveals the internal logic and economic consequences of digital transformation to improve enterprise innovation quality through the mediating effect and moderating effect models.

The results demonstrate that digital transformation is beneficial for improving enterprise innovation quality. The heterogeneity test demonstrates that digital transformation has a larger effect on improving enterprise innovation quality in non-state-owned enterprises and eastern enterprises in China. The mechanism test demonstrates that digital transformation can improve enterprise innovation quality by improving internal control quality and analyst attention. Furthermore, with the increase in enterprise innovation inputs, digital transformation plays a significantly stronger role in improving enterprise innovation quality. The extended analysis demonstrates that digital transformation can significantly improve enterprise financial performance by improving innovation quality.

First, the construction of the core explanatory variable digital transformation index in this study is based on the Python data analysis software, which calculates the frequency of digital transformation in the text of the business situation analysis portion of the annual report of the listed companies and then obtains the degree of digital transformation of the company in this year. There may be some deviation from the degree of digital transformation in the actual production and operation of enterprises. Second, in addition to internal control quality and analyst attention, are there other mediating mechanisms for the impact of digital transformation on the quality of enterprise innovation? Third, whether the moderating effect of innovation input on digital transformation and innovation quality is related to human capital factors of the research and development (R&D) team, such as the technical background of R&D personnel, etc.

This study enriches the relevant theories of digital transformation and broadens the research boundaries of digital transformation and enterprise innovation. This study's result provides an empirical basis for enterprises to improve enterprise innovation quality and financial performance from the perspective of digital transformation at the micro level and points out specific practical directions, combining theory with practice.

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.