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Despite the important role that suppliers have in enhancing the environmental performance of a buyer firm, previous research has not investigated the individual-level motivations of supplier employees (representatives) in supplier-to-supplier environmental knowledge sharing. Thus, we use insights from the coopetition literature to examine how buyer firms can encourage supplier-to-supplier environmental knowledge sharing with the aim of improving the buyer’s environmental performance.

We empirically test our model using an online vignette-based experiment administered to supply chain managers. We contextualized our results using insights from interviews with senior managers representing firms operating in a broad array of industries.

We find that a supplier representative’s personal environmental values influence their commitment to an environmental consortium with a rival firm, and they are subsequently willing to share proprietary environmental knowledge. In turn, these relationships are moderated by situational factors including competitive intensity and buyer power.

The study of coopetition is an emerging stream of research in operations management. Our findings improve the understanding on how a focal actor within a buyer–supplier coopetitive network can promote environmental knowledge sharing behavior.

Supply chain (SC) professionals are increasingly working alongside business partners of diverse backgrounds, which has been argued to engender both innovation and creativity but also found as potentially detrimental to SC relationships and performance. To reconcile these views, this study explores two mechanisms – supplementary (similarity) and complementary fits – at the surface (observable traits) and deep (unobservable characteristics) levels and their impact on a focal firm representative’s perception of a SC partner’s trustworthiness.

Model was tested using survey data from 285 managers involved in interorganizational SC relationships.

Results indicate that a focal firm representative’s perception of supplementary and complementary fits with a SC partner positively impacts their perception of the partner’s trustworthiness. However, the effects of similarity at both surface and deep levels and complementarity weaken each other.

Understanding the mechanisms of diversity in SC relationships is crucial for fostering trustworthiness and achieving organizational objectives. Firms should evaluate both supplementary and complementary fits when hiring or assigning roles. Embracing a complementary fit not only promotes diversity but also mitigates the negative impact of similarity bias, ultimately strengthening trustworthiness within the organization's SC ecosystem.

By simultaneously examining individual and combined effects of two unique mechanisms of supplementarity and complementarity at the surface and deep levels, this study sheds light on inconsistent findings of the effects of diversity in the SCM literature.

This study aims to investigate the evolving travel intentions of tourists in the aftermath of the relaxation of international mobility restrictions in 2022. It aims to understand how the concept of “revenge travel” – travelling with the intent to make up for lost time during crisis periods – impacts tourists' travel intentions in the post-crisis era.

Employing a quantitative approach, the study uses Structural Equation Modelling (SEM). Data were collected through a survey of 320 respondents in 2022. This methodology enables a comprehensive understanding of travel intentions, including motivations, perceptions of destination safety and the influence of revenge travel.

The findings reveal that revenge travel is a significant predictor of travel intentions post-crisis. The results indicate that tourists are less concerned with health and safety and are more driven by the desire to compensate for lost travel opportunities. This shift suggests that travel intentions in the post-crisis era are not predominantly fear-induced. The study also offers insights into how these intentions can inform the recovery and sustainable planning of the tourism industry.

This paper recognises the impact of revenge travel on travel intentions following the lifting of crisis-related mobility restrictions. It provides novel insights into tourists' post-crisis travel behaviour, extending the understanding of travel motivations in extraordinary circumstances. The findings are valuable for tourism practitioners and researchers, offering guidance for future tourism development and marketing strategies within a post-crisis context.

The current study investigates the impact of directors' attributes on the extent of compliance with International Financial Reporting Standards (IFRS) fair value disclosure requirements. The attributes investigated include directors' human capital (accounting qualification) and social capital (political association), directors' share ownership and the power distance between the chief executive officer (CEO) and the rest of the board members.

The study uses disclosure analysis to measure the extent of compliance with the fair value disclosure requirements of IFRS. Ordinary least squares (OLS) regression is used to test the relationship between the disclosure score and directors' attributes. Data were collected from the annual reports and websites of the sample companies.

Contrary to conventional belief, this study's findings suggest that directors' social capital and the power distance between the CEO and the rest of the board act as more powerful factors than directors' human capital in explaining corporate mandatory disclosure. Specifically, the results indicate that powerful actors form a dominant coalition and co-opt influential constituents from the institutional domain to neutralize the effect of legal coercion and the accounting expertise of board members and Big Four audit firms on the extent of compliance with institutional (fair value) rules.

This study utilizes Oliver's (1991) framework of strategic response to institutional processes in the Bangladeshi context. Although the study provides new insights into corporate disclosure practices, findings are not generalizable due to different institutional settings in different countries. Therefore, future studies could replicate the approach in different institutional settings.

The findings of this study will be of interest to the International Accounting Standards Board (IASB) as it focuses on a developing country that has adopted IFRS 13 and other fair value-related standards relatively recently.

The disclosure analysis contained in this study represents the first comprehensive analysis of the extent of compliance with the fair value disclosure requirements of IFRS. Furthermore, this study considers the impact of directors' social capital and finds that it is a more powerful determinant of the extent of compliance with IFRS as compared to human capital.

Our study draws on gender role congruity theory to theorize and test an integrative conceptual model outlining how motives for entrepreneurial action explain the relationship between female entrepreneurship and innovation in nascent ventures.

To test our hypotheses, we employed structural equation modeling (SEM) in a sample of early-stage entrepreneurs (N = 533).

We found a positive relationship between nascent female entrepreneurs and innovation, and that this relationship is mediated by motives for recognition, respect, and autonomy.

By revealing a positive relationship between female entrepreneurship and innovation, our work provides a complementary perspective to the literature, which suggests that there are limits to innovation potential for female entrepreneurs. Further, we find that this relationship is explained by motives for recognition, respect, and autonomy, but not financial security. Finally, most empirical research focuses on the innovative outputs of established new ventures, while our work leverages a sample of early-stage entrepreneurs.

The purpose of this paper is to present an integrated data-driven framework for processing and analyzing large-scale vehicle maintenance records to get more comprehensive understanding on vehicle quality.

We propose a framework for vehicle quality analysis based on maintenance record mining and Bayesian Network. It includes the development of a comprehensive dictionary for efficient classification of maintenance items, and the establishment of a Bayesian Network model for vehicle quality evaluation. The vehicle design parameters, price and performance of functional systems are modeled as node variables in the Bayesian Network. Bayesian Network reasoning is then used to analyze the influence of these nodes on vehicle quality and their respective importance.

A case study using the maintenance records of 74 sport utility vehicle (SUV) models is presented to demonstrate the validity of the proposed framework. Our results reveal that factors such as vehicle size, chassis issues and engine displacement, can affect the chance of vehicle failures and accidents. The influence of factors such as price and performance of engine and chassis show explicit regional differences.

Previous research usually focuses on limited maintenance records from a single vehicle producer, while our proposed framework enables efficient and systematic processing of larger-scale maintenance records for vehicle quality analysis, which can support auto companies, consumers and regulators to make better decisions in purchase choice-making, vehicle design and market regulation.

We analyzed the effects of different combinations of organic soil amendments (OSAs) and chemical fertilizers on agrifood production, focusing on banana yields in China, the second-largest producer of bananas globally.

We computed these combinations by dividing the expenditures on OSAs by those on chemical fertilizers and called them OSA-CF ratios. First, we classified farmers based on quintiles of expenditures on chemical fertilizers. Then, we studied the association between OSA-CF ratios and banana yields for each quintile. We also considered an alternate specification in which farmers were grouped along the OSA-CF ratio continuum. The first group comprised farmers not using OSAs. Their OSA-CF ratio was zero. Farmers applying low, medium, and high OSA-CF ratios constituted groups two, three, and four; the groups were delineated based on the OSA-CF ratio tertiles, and the associations between tertiles of OSA-CF ratios and banana yields for each quintile were analyzed. The data used in this study were collected by surveying 616 households in three major banana-producing provinces (Guangdong, Hainan, and Yunnan) of China. Standard linear regressions and the two-stage predictor substitution method were employed to complete the analysis.

There were variations in the effects of OSA-CF ratios on banana yields obtained by farmers iifferent quintiles. For the first and second quintiles, low, medium, and high OSA-CF ratios improved banana yields relative to not using OSAs. For farmers in the first quintile using only chemical fertilizers, applying a low OSA-CF ratio was associated with an improvement of 792 kg/mu in banana yields. For their counterparts in the second quintile, the same transition was associated with a gain of 534 kg/mu. For the fifth quintile, comprising farmers spending 320 yuan/mu or more on chemical fertilizers, applying a high OSA-CF ratio instead of using only chemical fertilizers was associated with a 401 kg/mu decline in banana yields. Even so, for this group, no differences were observed between the yields of farmers not applying OSAs and those using low and medium OSA-CF ratios.

Banana farmers in southern China, using only chemical fertilizers, can improve yields by combining them with OSAs if their chemical fertilizer expenditures are less than 66.67 yuan/mu. Those using only chemical fertilizers and spending between 68 yuan/mu and 300 yuan/mu on them can maintain yields by applying OSAs in conjunction with chemical fertilizers. However, yields may decline for farmers using only chemical fertilizers and spending 320 yuan/mu or more on them if they incorporate OSAs such that the OSA-CF ratio reaches 0.78 or higher. Overall, combining OSAs with chemical fertilizers can improve yields while attenuating the adverse effects of chemical fertilizers on the environment. Policymakers should inform farmers of these benefits and accelerate the transition to sustainable agriculture through educational and awareness programs.

Farmers apply OSAs such as organic fertilizers and farmyard manure to adjust and remedy soil nutrition to improve farm productivity. However, little is known about how combining OSAs with chemical fertilizers affects banana yields. This study provided the first attempt to explore the associations between OSA-CF ratios and banana yields using cross-sectional data on farming households.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

Given the growing concern about employees' well-being, numerous researchers have investigated the causes and effects of occupational stress. However, a review study on identifying existing research topics and gaps is still deficient in the extant literature. To fill this gap, this review study aims to present a bibliometric and science mapping approach to review the state-of-the-art journal articles published on occupational stress in the construction industry.

A three-fold comprehensive review approach consisting of bibliometric review, scientometric analysis and in-depth qualitative discussion was employed to review 80 journal articles in Scopus.

Through qualitative discussions, mainstream research topics were summarized, research gaps were identified and future research directions were proposed as follows: versatile stressors and stress model; an extended subgroup of factors in safety behavior; adaptation of multiple biosensors and bio-feedbacks; evaluation and comparison of organizational stress interventions; and incorporation of artificial intelligence and smart technologies into occupational stress management in construction.

The findings of this review study present a well-rounded framework to identify the research gaps in this field to advance research in the academic community and enhance employees' well-being in construction.

The paper aims to study the effect of sintering temperature on the microstructure, shear strength and ratcheting fatigue life of nanosilver sintered lap shear joint. In addition, the Gerber model is used to predict the ratcheting fatigue lives of nanosilver sintered lap shear joints at different sintering temperatures.

In this paper, the nanosilver sintered lap shear joints were prepared at three sintering temperatures of 250 °C, 280 °C and 310 °C. The bonding quality was characterized by scanning electron microscopy, X-ray diffraction, transmission electron microscope and shear tests, and the long-term reliability was studied by conducting ratcheting fatigue tests. In addition, three modified models based on Basquin equation were used to predict the ratcheting fatigue life of nanosilver sintered lap shear joint and their accuracies were evaluated.

When the sintering temperature is 250°C, the nanosilver sintered lap shear joint shows the porosity of 22.9 ± 1.6 %, and the shear strength of 22.3 ± 2.4 MPa. Raising the sintering temperature enhances silver crystallite size, strengthens sintering necks, thus improves shear strength and ratcheting fatigue life in joints. In addition, the ratcheting fatigue lives of the joints sintered at different temperatures are effectively predicted by three equivalent force models, and the Gerber model shows the highest life prediction accuracy.

The sintered silver bondline is suffering a complex stress state. The study only takes the shear stress into consideration. The tensile stress and the combination of shear stress and tensile stress can to be considered in the future study.

The paper provides the experimental and theoretical support for robust bonding and long-term reliability of sintered silver structure.

The introduced model can predict the ratcheting fatigue lives of the joints sintered at different temperatures, which shows a potential in engineering applications.

The study revealed the relationship between the sintering temperature and the microstructure, the shear strength and the ratcheting fatigue life of the joint. In addition, the Gerber model can predict the ratcheting fatigue life accurately at different sintering temperatures.