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This study aims to apply the affective events theory and psychological contract theory to investigate how job satisfaction and psychological safety mediate the effect of the behavioral integrity of supervisors on the organizational commitment of employees.

A questionnaire survey was conducted using purposive sampling. In total, 500 questionnaire copies were distributed, and 453 responses were collected, of which 441 were valid (valid response rate = 88.2%).

The behavioral integrity of supervisors has a direct negative effect on organizational commitment but significant positive effects on job satisfaction and psychological safety, and job satisfaction and psychological safety have significant positive effects on organizational commitment. Job satisfaction and psychological safety have significant mediating effects on the association between the behavioral integrity of supervisors and the organizational commitment of employees.

Leaders and top management should “practice what they preach,” integrate honesty into organizational culture through training and establish a code of conduct to ensure that employees uphold their commitments. Companies should establish appropriate disciplinary systems and norms related to work and other aspects of organizational culture; they should also establish fair, just and open assessment systems to minimize the gap between their employees’ actual and expected earnings.

This study is the first to simultaneously consider the mediating effects of job satisfaction and psychological safety on the association between behavioral integrity and organizational commitment.

This study aims to highlight that security and flexibilities remain the main points of contention in the cordiality business. This research points to planning a framework that empowers hotel users to get to the room using a mobile access key. Advancing secured facilities, mobile phone “Near Field Communication” (NFC) innovation as the entrance device by carrying out an application containing an imitated mobile key for explicit verification access is used.

The proposed system is evaluated by triangulation of experimental, numerical and rational evaluation using partial least square structural equation modeling (PLS-SEM) with Malaysian hotel guests and employees.

The discoveries with the hypothesis supported validated that the suggested solution can eliminate physical cards, boost protection and encourage a contactless ecosystem. Theoretical, management and societal contributions are discussed here.

This experiment comes with the constraints that it was conducted in only two hotels and does not fully reflect the choices of a wider range of travellers. Secondly, the cost of existing NFC smart locks is still relatively high, and along with the development of technology, the price will decrease when supply exceeds demand.

To promote high-security attributes, NFC technology as the access system by implementing an application containing an emulated smart key for specific authentication access is used. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

To promote high-security attributes, NFC technology is used as the access system by implementing an application containing an emulated smart key for specific authentication access. The host-card emulation enables cost-effectiveness profit and initiating a defence system in the pandemic era.

The novelty of this study comes from the use of commonly available smartphone NFC features that are yet to be applied in the tourism ecosystem. The research provokes the applied concept of mobile smartkeys.

One of the significant components of a firm's overall sustainability is establishing and nurturing governance. This study attempts to understand how politically connected firms maintain sustainability measures in terms of risk-taking strategies. This paper has two purposes. The first purpose is to provide empirical evidence on the politically connected (PC) firms' corporate risk-taking and performance. The second purpose is to investigate the moderating impact of PC firms' risk on corporate performance.

To conduct the analysis to test our hypothesis efficiently, data has been collected from Bloomberg and annual reports of all Malaysian PC and non-PC companies. The final sample comprises 561 firms over the investigation period 2010–2019. The methodology entails Ordinary Least Squares (OLS) regressions of the impact of the PC firms on corporate risk-taking and performance. The authors also conduct t-tests of the equality of means of corporate risk-taking and performance between PC and non-PC companies.

The authors’ results show that politically connected firms undertake significant less corporate risk and relish higher financial performance than their counterparts. It implicatively insinuates that the presence of a politician on the board enables the management to mitigate the risk-taking, which makes the firms more profitable. The authors’ results corroborate network theory, suggesting that political ties alleviate the agency issue and safeguard the shareholders' interest.

The study's results were important as they highlighted the sustainable development of PC and non-PC companies, offering insights to researchers, policymakers, regulators, financial report users, investors, environmental unions, employees, clients and society.

This paper is novel since it is unique in evaluating sustainable practice in PC and non-PC firms.

Multi-view fuzzy clustering algorithms are not widely used in image segmentation, and many of these algorithms are lacking in robustness. The purpose of this paper is to investigate a new algorithm that can segment the image better and retain as much detailed information about the image as possible when segmenting noisy images.

The authors present a novel multi-view fuzzy c-means (FCM) clustering algorithm that includes an automatic view-weight learning mechanism. Firstly, this algorithm introduces a view-weight factor that can automatically adjust the weight of different views, thereby allowing each view to obtain the best possible weight. Secondly, the algorithm incorporates a weighted fuzzy factor, which serves to obtain local spatial information and local grayscale information to preserve image details as much as possible. Finally, in order to weaken the effects of noise and outliers in image segmentation, this algorithm employs the kernel distance measure instead of the Euclidean distance.

The authors added different kinds of noise to images and conducted a large number of experimental tests. The results show that the proposed algorithm performs better and is more accurate than previous multi-view fuzzy clustering algorithms in solving the problem of noisy image segmentation.

Most of the existing multi-view clustering algorithms are for multi-view datasets, and the multi-view fuzzy clustering algorithms are unable to eliminate noise points and outliers when dealing with noisy images. The algorithm proposed in this paper has stronger noise immunity and can better preserve the details of the original image.

Foreign subsidiaries incur substantial institutional conformity costs because they have to respond to host-country institutional pressures (Slangen & Hennart, 2008). The purpose of this paper is to study this type of cost from institutional and regulatory perspectives. The authors argue that these costs decrease when the host country adopts concepts of international regulations that multinationals may be familiar with due to their own home country regulation experience. This prior regulatory experience gives foreign subsidiaries an advantage of foreignness (AoF), which can offset their liability of foreignness (LoF).

This study compared the returns on assets of 35 domestic firms with those of foreign subsidiaries in the Brazilian energy industry between 2002 and 2021, using regression dynamic panel data.

The existence of a relationship between the international regulatory norm and the Brazilian regulator has transformed the LoF into an advantage of foreignness to compete with local energy firms. The results also suggest that the better the regulatory quality of the subsidiary’s country of origin, the better its performance in Brazil, as it can reduce compliance costs. Finally, the greater the psychic distance between Brazil and the foreign subsidiary’s home country, the worse its performance.

The research suggests that one of the keys to competitiveness in host countries is local regulatory ties. Prior international regulatory experience gives foreign subsidiaries an asset of foreignness (AoF). This result complements the current institutional and regulatory foreignness studies on emerging economies (Cuervo-Cazurra & Genc, 2008; Mallon et al., 2022) and the institutional asymmetry between home and host country (Mallon & Fainshmidt, 2017).

This research suggests that one of the keys to competitiveness in host countries is local regulatory ties. Prior international regulatory experience gives foreign subsidiaries an asset of foreignness (AoF). This result complements the current institutional and regulatory foreignness studies on emerging economies (Cuervo-Cazurra & Genc, 2008; Mallon et al., 2022) and the institutional asymmetry between home and host country (Mallon & Fainshmidt, 2017). The practical implication is that the relationship between conformity costs, capital budget calculation and strategic planning for internationalization will be related to the governance quality of the home country of multinationals. The social implication is that a country interested in attracting more direct foreign investment to areas that need foreign technology transfer and resources may consider adopting international regulatory standards.

The social implication is that a country interested in attracting more direct foreign investment to areas that need foreign technology transfer and resources may consider adopting international regulatory standards.

This research discuss firm and local regulator tie is one of core competitiveness in host countries (Yang and Meyer, 2020). This study also complements the current institutional and regulatory foreignness studies in emerging economy (Cuervo-Cazurra & Genc, 2008; Mallon et al., 2022). Second, prior regulatory experience of multinational enterprise in similar environment can affect its foreign affiliate performance (Perkins, 2014). Third, this study confirms current literature that argues that knowledge and ability to operate in an institutionalized country can be transferred from parent to affiliate. In the end, this study investigates whether AoF persists when host governments improve the governance of their industries.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

By building and examining an integral model, the principal objectives of this research are to systematically explore how indirect and direct network externalities lead to user loyalty toward WeChat through the mediating effect of perceived gratifications.

The data were collected through an online survey of 688 young people in Mainland China. To empirically assess the conceptual model, zero-order correlation analyses and structural equation modeling were carried out utilizing web-based data.

Path analysis results demonstrate that indirect network externalities and direct network externalities exert a significant impact on users' hedonic gratifications and utilitarian gratifications. Moreover, the study discovers the significant mediating influences of utilitarian gratifications on the association between indirect network externalities and user loyalty.

Theoretically, this article may extend the scope of diverse studies on the association between network externalities and perceived gratifications and offer fresh insights into how mobile social media could actually improve user loyalty through enhancing perceived values among younger generation. Practically, this research assists mobile social media practitioners in retaining users and gaining competitive advantages over rival applications.

Although the extraordinary growth of WeChat has successfully become the dominant media by which individuals develop interpersonal network and contact with others, the roles of perceived gratifications between network externalities and user loyalty toward WeChat have not yet been investigated in depth. These obtained outcomes not only enrich the existing literature regarding the relationship between network externalities and affective response, but also offer fresh insights to mobile social media designers, marketers and users.

This study aims to testify the effects of green marketing on peer-to-peer (P2P) accommodation consumers’ repurchase intention and positive word-of-mouth (WOM) towards P2P accommodation platforms through the mediation of trust and consumer identification.

A questionnaire survey was applied to collect data from a sample of 488 consumers in China who had used P2P accommodation platforms in the past six months. Partial least squares structural equation modelling was used to analyse the data.

The study found that consumers’ perception of green marketing orientation of P2P accommodation platforms significantly increased consumer trust in the platform and consumer identification with the platform, which in turn each positively influenced repurchase intention and positive WOM to the platform. Furthermore, consumer trust had a positive effect on consumer identification and both trust and identification mediated the relationship between green marketing and repurchase intention and that between green marketing and positive WOM.

The findings of this study provide P2P accommodation platform operators with important insights to apply green marketing and focus on consumer trust and identification in sustaining their business and coping with the intense market competition.

This study contributes to better understanding of the impact of green business practices on consumers in sharing economy and offers practical implications on sustainable P2P accommodation practices.

This paper aims to unravel the relationship between market-driven impacts of climate change and firms’ deployment of renewable energy (RE) innovation. The purpose is to understand how market-related forces, influenced by uncertainty, shape firms’ behaviour in response to climate change challenges.

Drawing on the behavioural theory of the firm (BTOF), the paper develops a conceptual model to decode the relationship between each category of market-driven impacts and the resulting RE innovation within firms. The model takes into account the role of uncertainty and differentiates between multinational enterprises (MNEs) and domestic firms.

The analysis reveals five key sources of market-driven impacts: investor sentiment, media coverage, competitors’ adoption of ISO 14001, customer satisfaction and shareholder activism. These forces influence the adoption of RE innovation differently across firms, depending on the level of uncertainty and the discrepancy between environmental performance and aspiration level.

This paper contributes to the literature in four ways. Firstly, it emphasises the importance of uncertainty associated with market-driven impacts, which stimulates different responses from firms. Secondly, it fills a research gap by focusing on the proactivity of firms in adopting RE innovation, rather than just operational strategies to curb emissions. Thirdly, the paper extends the BTOF by incorporating the concept of uncertainty in explaining firm behaviour. Finally, it provides insights into the green strategies of MNEs in the face of climate change, offering a comprehensive model that differentiates MNEs from domestic firms.

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.