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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.

The novel COVID-19 supply chain disruption has globally altered the environmental needs of society. Against this backdrop, this paper aims to examine how top managers are environmentally committed to integrating green supply chain management (GSCM) practices in the operational performance of small- and medium-scale enterprises (SMEs) in Ghana, within the post-pandemic economy.

The study used a cross-sectional survey to obtain data from 270 SMEs in Ghana, using partial least squares (PLS) structural equation modelling to test seven hypothesized relationships.

The outcome of the analysis revealed that top management environmental commitment has a significantly positive effect on supply chain operational performance. The structural model also revealed that top management environmental commitment has a positive and significant effect on both internal and external GSCM practices. The results further revealed that both internal and external GSCM practices have positive and significant effects on supply chain operational performance. Finally, both internal and external GSCM practices mediate the path between top management environmental commitment and supply chain operational performance.

The study provides a novel framework which contributes to both theoretical studies and managerial decisions on COVID-19 related supply chain management issues. However, the study was limited to the Ghanaian context, thus, further related studies are required in other contexts.

This study provides a novel framework by elucidating the intervening role of GSCM practices in the path between top management environmental commitment and supply chain operations in an emerging post-pandemic world context.

This study aims to investigate the mediating role of attachment to social media influencer between authenticity and enjoyment and then travel intention while watching social media influencer video.

This study used the survey approach to collect responses from respondents who have watched the social media influencer video. Partial least squares structural equation modeling technique was applied for the data analysis.

The results indicated that authenticities positively impact tourist attachment to social media influencer, enjoyment and hence visit intention. Attachment to social media influencer mediates the relationships between authenticities and enjoyment.

This study proposes and examines the role of attachment to social media influencers as a mediator between authenticities and tourist responses, which provided meaningful theoretical and practical insights for the future research on social media influencers.

本研究旨在调查网络红人依赖在真实性和享受之间的中介作用, 以及在观看网络红人视频时的旅行意愿。

本研究采用问卷调查方法, 收集观看网络红人视频的受访者的回答, 使用PLS结构方程模型技术进行数据分析。

结果表明, 真实性对游客对网络红人的依赖、享受和参观意愿具有积极影响。网络红人依赖在真实性和享受之间起到中介作用。

本研究提出并检验了网络红人依赖作为真实性和游客反应之间的中介角色, 为未来关于网络红人的研究提供了有意义的理论和实践基础。

Failures in both followership and leadership become inevitable as mega construction projects are directed and controlled by toxic leaders. Consequently, team member's desire for knowledge hoarding silence is triggered and goal alignment between the leader and team members suddenly fades away to realize success in mega projects. Considering the growing importance of these rarely examined constructs and fragmented literature on toxic leadership (TL), team silence and mega project success (PS) in the global construction industry, the present study aimed to examine the effects of TL and project team member's silence (PTMS) on the success of mega construction projects. Moreover, the mediating influence of PTMS to link TL and mega construction PS has also been explored.

Drawing on survey data of 326 project professionals directly associated with mega construction projects worth US$62bn under the China–Pakistan Economic Corridor (CPEC), the conceptual model was tested with covariance-based structural equation modeling (CB-SEM) using Mplus program. Scales were adapted from previous research to measure TL (with its five-dimensions including abusive supervision, authoritarian leadership, self-promotion, narcissism and unpredictability), PS (with its three-dimensions including project management success, project ownership success and project investment success) and project team members' silence. Reflective–formative second order assessments were specifically applied to measure the multi-dimensional nature of TL and PS, respectively.

Mplus estimations revealed that TL negatively influences PS, besides forcing a culture of silence among project team members. Interestingly, the relationship between TL and PS is also negatively mediated by the PTMS.

The present study's findings are derived from data of project professionals (N = 326) to examine success in megaprojects under the CPEC. Hence, these findings may be re-validated through future studies on similar megaprojects (e.g. China's Belt and Road Initiative (BRI) worth US$8tn) that may also be predicated by TL tendencies, silent cultures and high-stakes involved to seize PS.

Policymakers, construction practitioners and other key stakeholders (e.g. departmental heads/supervisors) can take advantage of this new evidence to better interpret the success paradox in mega projects, and to reduce the spread and long-term damage of TL on team members and eventually create opportunities for PS.

The present study's novelty is manifested within this first empirical evidence on TL that breeds team silence in underperforming mega projects. Notably, present study offers alarming evidence on mega projects that can be easily derailed from success, as they continue to suffer from team silence and TL.

The study aims to investigate the effects of pre-loading histories (pre-shearing and pre-consolidation) on the liquefaction behaviour of saturated loose sand via discrete element method (DEM) simulations.

The pre-shearing history is mimicked under drained conditions (triaxial compression) with different pre-shearing strain levels ranging from 0% to 2%. The pre-consolidation history is mimicked by increasing the isotropic compression to different levels ranging from 100 kPa to 300 kPa. The macroscopic and microscopic behaviours are analysed and compared.

Temporary liquefaction, or quasi-steady state (QSS), is observed in most samples. A higher pre-shearing or pre-consolidation level can provide higher liquefaction resistance. The ultimate state line is found to be unique and independent of the pre-loading histories in stress space. The Lade instability line prematurely predicts the onset of liquefaction for all samples, both with and without pre-loading histories. The redundancy index is an effective microscopic indicator to monitor liquefaction, and the onset of the liquefaction corresponds to the phase transition state where the value of redundancy index is one, which is true for all cases irrespective of the proportions of sliding contacts.

The liquefaction behaviour of granular materials still remains elusive, especially concerning the effects of pre-loading histories on soils. Furthermore, the investigation of the effects of pre-consolidation histories on undrained behaviour and its comparison to pre-sheared samples is rarely reported in the DEM literature.

This study aims to explore how emerging SMEs respond to the multifaceted contents of CSR-related code of conduct (COC) from external stakeholders and the underlying constraining forces and mechanisms shaping such responses.

This study opted for a qualitative methodology using the content analysis, and the data were collected from the auditing reports on Chinese export-oriented SMEs carried out by a public and independent third-party agency.

The findings showed that SMEs from emerging markets present a short-termism orientation in the response to external CSR-related COC, and the study developed a threefold response typology implemented by SMEs, capturing economic interest and moral rightness as two dimensions shaping such responsive patterns. The study furthermore showed that whether SMEs' responses are more symbolic or substantive depends on managers' beliefs regarding the economic-moral conflict tension involved in the implementation of CSR-related COC.

This paper explores emerging SMEs' response strategy to CSR-related issues formulated by external stakeholders and clarifies the underlying decision-making road map to alleviate the tension involved in corporate social responsibility implementation.

This study aims to investigate the negative interpersonal antecedents, emotional mediators and boundary conditions of knowledge sabotage behavior.

The authors collected data from 275 Chinese employees using convenience sampling and snowball sampling across three stages. Subsequently, the authors used both hierarchical regression and bootstrap methods to test the proposed hypotheses.

The results confirmed that workplace ostracism has positive effects on employee knowledge sabotage behavior both directly and via employee anger. In addition, the authors found that employee bottom-line mentality (BLM) moderates not only the direct effect of workplace ostracism on employee anger but also the indirect effect of employee anger in this context. Employee conscientiousness moderates only the direct effect of workplace ostracism on employee anger and does not moderate the indirect effect.

To the best of the authors’ knowledge, this study not only explores the influence of workplace ostracism on employee knowledge sabotage behavior for the first time but also elucidates the underlying emotional mechanisms (anger) and boundary conditions (employee BLM and conscientiousness) by which workplace ostracism influences employee knowledge sabotage behavior, thus deepening the understanding of how knowledge sabotage emerges in organizations.

This study explores the intricate relationship between inventory leanness, financial constraints and digital transformation in listed Chinese manufacturing firms.

Using a large panel data collected from 2,563 Chinese listed manufacturing enterprises over the period from 2012 to 2021, this research employs the instrumental variable method combined with two-stage least squares estimators to explore the U- shaped relationship between inventory leanness and financial constraints. Furthermore, the moderating role of digital transformation is demonstrated.

Contrary to traditional assumptions, our research uncovers a U-shaped relationship between inventory leanness and financial constraints, indicating that excessive inventory reduction can exacerbate financial constraints. Digital transformation plays a significant moderating role, particularly in highly digitalized environments.

Our findings have practical significance for top managers and policymakers. We advocate for a balanced approach to lean inventory management to mitigating financial constraints. The study emphasizes the pivotal role of digital transformation in alleviating the impact of inventory leanness on financial constraints, highlighting the need for digital transformation strategies.

This research provides a comprehensive analysis of inventory leanness, financial constraints and digital transformation dynamics. It challenges conventional thinking by revealing the nonlinear nature of the inventory leanness–financial constraints relationship. The concept of moderation highlights the moderating effect of digital transformation. This study offers practical guidance for practitioners and policymakers.

This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’ person-goods matching process and how the platform firm’s similar strategies moderate the effects of TPSs’ strategies.

Using data collected from the top ten TPSs from a Chinese e-commerce platform, the fixed effect model is used to validate the conceptual model and hypotheses.

The study results show that both market detection strategy and matching optimization strategy can help large TPSs improve their sales performance. Moreover, the similar market detection strategy applied by the platform firm weakens the effect of large TPSs’ customer acquisition strategies, while the similar matching optimization strategy applied by the platform firm strengthens the effect of large TPSs’ customer acquisition strategies.

This study provides firsthand evidence on the performance of large TPSs’ and the platform firm’s strategies. It demonstrates the effectiveness of large TPSs’ market detection strategy and matching optimization strategy, which can be adopted to meet consumers’ search and evaluation motivations in their person-goods matching process respectively. Moreover, it identifies the role of platform firms by showing the moderating effect of similar strategies adopted by the platform firm on the effect of large TPSs’ customer acquisition strategies.

The multisource uncertainties, including material dispersion, load fluctuation and geometrical tolerance, have crucial effects on fatigue performance of turbine bladed disks. In view of the aim of this paper, it is essential to develop an advanced approach to efficiently quantify their influences and evaluate the fatigue life of turbine bladed disks.

In this study, a novel combined machine learning strategy is performed to fatigue assessment of turbine bladed disks. Proposed model consists of two modeling phases in terms of response surface method (RSM) and support vector regression (SVR), namely RSM-SVR. Two different input sets obtained from basic variables were used as the inputs of RSM, then the predicted results by RSM in first phase is used as inputs of SVR model by using a group data-handling strategy. By this way, the nonlinear flexibility of SVR inputs is improved and RSM-SVR model presents the high-tendency and efficiency characteristics.

The accuracy and tendency of the RSM-SVR model, applied to the fatigue life estimation of turbine bladed disks, are validated. The results indicate that the proposed model is capable of accurately simulating the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction strategy compared to RSM and SVR for fatigue analysis of complex structures.

The results indicate that the proposed model is capable of accurately simulate the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction compared to RSM and SVRE for fatigue analysis of turbine bladed disk.