Search results

Taking tournament and agency theories as theoretical bases, this study aims to examine whether and when industry tournament incentives affect corporate social irresponsibility (CSiR).

This study focuses on publicly listed companies in China from 2003 to 2018, with a total of 26,638 observations across 3,013 firms. Based on this dataset, the study employs a high-dimensional fixed effects model to empirically investigate the impact of industry tournament incentives on CSiR. Additionally, it explores the moderating effects of founder chief executive officers, multiple large shareholders and state-owned enterprises on this relationship.

This study demonstrates that industry tournament incentives have a significant positive impact on CSiR. Additionally, the findings reveal that founder-chief executive officers and multiple large shareholders weaken the above relationships, whereas state-owned enterprises have no moderating effect on the above relationships.

By analyzing and testing the relationship between industry tournament incentives and CSiR for the first time, this study contributes to the literature on industry tournament incentives, the CSiR literature and tournament theory.

Using recent US regional data associated with food system operations, this study aims at building optimization and econometric models to incorporate varying influential factors on food hub location decisions and generate effective facility location solutions.

Mathematical optimization and econometric models have been commonly used to identify hub location decisions, and each is associated with specific strengths to handle uncertainty. This paper develops an optimization model and a hurdle model of the US fresh produce sector to compare the hub location solutions between these two modeling approaches.

Econometric modeling and mathematical optimization are complementary approaches. While there is a divergence between the results of the optimization model and the econometric model, the optimization solution is largely confirmed by the econometric solution. A combination of the results of the two models might lead to improved decision-making.

This study suggests a future direction in which model development can move forward, for example, to explore and expose how to make the existing modeling techniques easier to use and more accessible to decision-makers.

The models and results provide information that is currently limited and is useful to help inform sustainable decisions of various stakeholders interested in the development of regional food systems, regional infrastructure investment and operational strategies for food hubs.

This study sheds light on how the application of complementary modeling approaches improves the effectiveness of facility location solutions. This study offers new perspectives on elaborating key features to encompass facility location issues by applying interdisciplinary approaches.

The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners’ computational thinking.

By analyzing the mechanism of action of ITF on the development of computational thinking, an ITF strategy and corresponding ITS acting on the whole process of programming problem-solving were developed to realize the evaluation of programming problem-solving ideas based on program logic. On the one hand, a lexical and syntactic analysis of the programming problem solutions input by the learners is performed and presented with a tree-like structure. On the other hand, by comparing multiple algorithms, it is implemented to compare the programming problem solutions entered by the learners with the answers and analyze the gaps to give them back to the learners to promote the improvement of their computational thinking.

This study clarifies the mechanism of the role of ITF-based ITS in the computational thinking development process. Results indicated that the ITS designed in this study is effective in promoting students’ computational thinking, especially for low-level learners. It also helped to improve students’ learning motivation, and reducing cognitive load, while there’s no significant difference among learners of different levels.

This study developed an ITS based on ITF to address the problem of learners’ difficulty in obtaining real-time guidance in the current programming problem-solving-based computational thinking development, providing a good aid for college students’ independent programming learning.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

The purpose of this paper is to delve into the intricate link between job satisfaction and employees’ turnover intentions. To accomplish this, a detailed structural model was constructed, incorporating five essential constructs: job satisfaction, turnover intention, satisfaction with financial factors, satisfaction with non-financial factors and external factors.

The research used a questionnaire with 28 items based on established tools, focusing on five different constructs. The model’s validation involved applying structural equation modelling to 147 non-managerial employees in microfinance institutions.

The findings reveal a significant negative correlation between job satisfaction and turnover intention. Satisfaction with financial factors significantly outweighs satisfaction with non-financial factors in shaping job satisfaction. In addition, the impact of external factors on turnover intention was observed to be minimal and inconsequential.

This review highlights the importance of investigating the moderating factors in the job satisfaction–turnover relationship, distinguishing between types of satisfaction and conducting longitudinal studies across diverse contexts. It notably presents a diverse range of recent findings in this field, emphasising the breadth of the results that have emerged in this area of research.

Understanding job satisfaction and turnover intention is crucial for microfinance institutions. By prioritising efforts to enhance job satisfaction through improved financial offerings and non-financial factors like a supportive work environment and opportunities for growth, organisations can effectively mitigate turnover rates and foster success.

The study underscores the societal value of supportive work environments beyond just benefits and career opportunities. By understanding the external influences on employee satisfaction, organisations can contribute to building more decent workplaces and promote social well-being, while advocating for social considerations in organisational practices.

This paper uses a novel integrated model comprising five distinct constructs not previously used together. It stands among the pioneering works that not only elucidate the correlation between job satisfaction and turnover intention but also delineate the constituents of job satisfaction itself.

Dual design for additive manufacturing (DfAM) takes into account both the opportunities and constraints of AM simultaneously, which research shows is more effective than considering them separately. Unlike existing reviews, this paper aims to map DfAM research within the engineering design process, focusing solely on studies adopting dual DfAM. Additionally, it aims to suggest future research directions by analysing prominent research themes and their inter-relationships. Special emphasis is on theme inter-relationships concerning the conceptual, embodiment and detail design phases.

The study is based on a systematic literature review of 148 publications from January 2000 to February 2024. After screening, prominent research themes were identified and systematically analysed. Theme inter-relationships were explored using quantitative analysis and chord diagrams.

The findings reveal that studies either span the entire design process, the early design phases or the later design phases. Most research focuses on the later design phases, particularly within themes of design optimisation, design evaluation and AM-specific manufacturing constraints. The most frequent theme inter-relationship occurs between design optimisation and AM-specific manufacturing constraints. Overall, the findings suggest future research directions to advance dual DfAM research, such as development of design rules and guidelines for cellular structures.

This review proposes a model by mapping prominent themes of dual DfAM research in relation to the engineering design process. Another original contribution lies in analysing theme inter-relationships and visualising them using chord diagrams – a novel approach that did not exist before.

The purpose of this article is to illustrate an emerging typology that theoretically links work values with personal values and to provide evidence of construct validity for this typology.

A hypothesis was developed that four types of work values – intrinsic, extrinsic, prestige and affective – underlie the relative importance that individuals place on aspects of work. Evidence of construct validity was provided using triangulation analysis. Data from three different samples in Japan were analysed with three different techniques; exploratory factor analysis (N = 229), hierarchical cluster analysis (N = 244) and smallest space analysis (N = 203).

The results demonstrate acceptable internal consistency and a coherent structure that fits the theoretical model across methods and samples. These findings lend strong support to the use of the intrinsic, extrinsic, affective and prestige typology for studying work values. This will hopefully encourage field scholars to adopt the typology in future values-based explorations in the context of work.

The study adds to the emergent literature in business research that stresses the importance of triangulation analysis to enhance the reliability and validity of findings. In this sense, it is an innovative paradigm of a multiple triangulation approach, which combines both data and within-method triangulation. The methods employed covered – for the first time – all commonly applied techniques for exploring the structure underlying the data and provided inductive, deductive and spatial evidence to corroborate the observed structure of work values.

This study investigates firms' innovation behaviour under environmental change. Therefore, it examines the effect of trade disputes on corporate technological innovation and how product market competition moderates this relationship.

This research tests the hypotheses using the fixed effects model based on panel data of publicly listed enterprises in China from 2007–2020.

The empirical results validate the positive association between trade disputes and corporate research and development (R&D) intensity as well as the U-shaped relationship between trade disputes and radical innovation. Additionally, the moderating effect of product market competition is verified: a concentrated market with less competition flattens the U-shaped curve of radical innovation induced by trade disputes; as the market becomes more concentrated and less competitive, the U-shaped relationship eventually turns into an inverted U.

First, this study contributes to the corporate innovation and trade dispute literature by expanding the environmental antecedents of technological innovation and the firm-level consequences of trade disputes. Second, this study enriches the theoretical framework of the environment–innovation link through an integrated perspective of contingency theory and dynamic capabilities view. Third, instead of the traditional linear mindset which had led to contradictory results, this study explores a curvilinear effect in the environment–innovation relationship.

The impact of enterprise social media (ESM) on employees is not always beneficial. The constant connectivity of ESM can trigger emotional issues, threatening employees' psychological states. This study aims to explore the potential risks of ESM usage on thriving at work by examining how ESM usage affects thriving and for whom this relationship is amplified.

Drawing on Affect Event Theory, this study proposes a research model for investigating the underlying mechanisms and boundary conditions of the negative impacts of different ESM usage patterns on employees' thriving at work. This study employed Smart-PLS 4.0 with structural equation modeling to analyze multi-wave survey data from 255 employees, testing the proposed model.

The results indicate the following: (1) ESM usage triggers employees' workplace fear of missing out (WFoMO), increasing their online vigilance and consequently hindering their thriving at work. (2) The impact of ESM usage on employees' WFoMO and thriving at work varies with their ambition levels, with high-ambition employees being more susceptible to negative effects and (3) Different types of ESM usage exert distinct effects on employees.

This study substantiates the potential negative impact of ESM usage on employees' thriving at work, contributing to the literature on the “dark side” of ESM usage and thriving at work. This study confirms the critical mediating role of emotion, offering a novel theoretical perspective on understanding the mechanisms linking ESM usage and its outcomes. Additionally, this study identifies the moderating role of employee ambition, complementing the boundary conditions of ESM usage.

This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.

Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.

The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.

The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.