Search results

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 purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA), based on the previous study of grey relational decision-making model, and it considers the advantages of the decision-making schemes and the subjective preferences of decision makers.

First of all, through AHP, the preference of each index is analyzed and the index weight is determined. Second, the DEA model is adopted to obtain the index weight from the perspective of the most beneficial to each scheme and objectively reflect the advantages of different schemes. Then, assign the comprehensive weights to each index of the grey relational decision-making model of three-parameter interval grey number, and calculate the grey relation degree of each scheme to rank the schemes.

The effectiveness of the model is proved by an example of carrier aircraft selection.

The applicability of this model is analyzed by taking carrier aircraft selection as an example. In fact, this model can also be widely used in agriculture, industry, economy, society and other fields.

In this paper, the combination of AHP and DEA is used to determine the index weight. Based on which, the grey relation degree under the three-parameter interval grey number is calculated. It intended the application space of the grey relational decision-making model.

This chapter reviews graphical modeling techniques for estimating large covariance matrices and their inverse. The chapter provides a selective survey of different models and estimators proposed by the graphical modeling literature and offers some practical examples where these methods could be applied in the area of health economics.

Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the problem of resource scheduling in the private cloud environment, the purpose of this paper is to propose a resource scheduling approach from an efficiency priority point of view.

To measure the computational efficiencies for the resource nodes in a private cloud environment, the data envelopment analysis (DEA) approach is incorporated and a suitable DEA model is proposed. Then, based on the efficiency scores calculated by the proposed DEA model for the resource nodes, the 0-1 programming technique is introduced to build a simple resource scheduling model.

The proposed DEA model not only has the ability of ranking all the decision-making units into different positions but also can handle non-discretionary inputs and undesirable outputs when evaluating the resource nodes. Furthermore, the resource scheduling model can generate for the calculation tasks an optimal resource scheduling scheme that has the highest total computational efficiency.

The proposed method may also be used in studies of resource scheduling studies in the environments of public clouds and hybrid clouds.

The proposed approach can achieve the goal of resource scheduling in private cloud computing platforms by attaining the highest total computational efficiency, which is very significant in practice.

This paper uses an efficiency priority point of view to solve the problem of resource scheduling in private cloud environments.

In the current highly competitive market, most organizations are moving away from reactive and compliance-based to proactive environmental management. This proactive approach to environmental management calls for taking a strategic approach to adoption of green practices beyond an organization’s internal borders. In this respect, incorporating green practices into a firm’s supply chain has attracted interest of operations management scholar and practitioners. The influence of external pressures on the adoption of green supply chain management (GSCM) practices has been established in the literature. This research posits that the adoption of GSCM practices is also driven by a firm’s internal strategic factors including its key resources and competitive strategy. It also suggests that these direct effects are further mediated by the green strategies (GSs) adopted in companies. Theoretically, these relationships are supported by combining the institutional theory with the natural resource-based view. A structural equation modeling is applied to formulate and analyze the relationships and the mediating effect using a survey data collected from 139 ISO14001-certified manufacturers in Malaysia. The results verified the mediating effect of GS adoption on the relationship between internal and external strategic factors, and GSCM practices. This research has made an original contribution to knowledge by bridging the fields of strategic environmental management and GSCM.

Overconsumption of resources has become a global issue. To deal with resource depletion and mitigate these impending crises, the circular economy (CE) holds some promise. A wide range of performance measurements for CE have emerged over the years. However, with increasing complexity of supply chains, appropriate and potentially new performance measurements are needed for effective CE management. Blockchain is an innovative technology that may advance CE development. This chapter provides an overview of the potential linkages between blockchain technology and CE from sustainability perspectives – the specific focus will be on the performance measurement of reverse logistics activities. One of the main findings indicates that both blockchain and CE performance measurements – especially reverse logistics processes – are still evolving in both theory and practical developments. Future directions with a critical analysis including research and theoretical applications will conclude this chapter.

Small and medium enterprises (SMEs) are expected to be more creative and innovative to survive in the business competition and to make their businesses environmentally friendly, to develop global supply chain strategies, and to make innovations in products and business processes to become indispensable. This study discusses the effect of green supply chain integration (GSCI) and environmental uncertainty on performance through the moderation of green innovation. Structural equation modeling and maximum likelihood estimation were used to analyze a sample of 130 SMEs in East Java, Indonesia. The result shows that GSCI and environmental uncertainty significantly affect performance, and green innovation significantly moderates the effect. This research found that SME’s performance is influenced by GSCI concept and green innovation application as well as SME’s understanding about recent and future environmental uncertainties; this fits the market demand.

For many of the current leadership theories, models, and approaches, the answer to the question posed in the title, “Is leadership more than ‘I like my boss’?,” is “no,” as there appears to be a hierarchy of leadership concepts with Liking of the leader as the primary dimension or general factor foundation. There are then secondary dimensions or specific sub-factors of liking of Relationship Leadership and Task Leadership; and subsequently, tertiary dimensions or actual sub-sub-factors that comprise the numerous leadership views as well as their operationalizations (e.g., via surveys). There are, however, some leadership views that go beyond simply liking of the leader and liking of relationship leadership and task leadership. For these, which involve explicit levels of analysis formulations, often beyond the leader, or are multi-level in nature, the answer to the title question is “yes.” We clarify and discuss these various “no” and “yes” leadership views and implications of our work for future research and personnel and human resources management practice.

The purpose of this paper is to threefold. The first purpose is to review and critically analyze corporate sustainability development (CSD) research in China. Second, the paper extracts a unified theoretical framework among CSD drivers, CSD practices, and corporate performance in China. Finally, it seeks to identify links between CSD and industrial management and data systems (IMDS) topics.

A comprehensive and structured review of the research literature investigating CSD in China was completed. Categorizations and classifications of the literature were summarized. A critical analysis of the literature resulted in a generic theoretical framework that can be used for evaluation of the literature and further investigation.

The literature review found over 189 papers on CSD in China published from 1997 to 2013. The framework developed focussed on relationships among drivers, practices, and performance within a CSD in China context. The framework provides useful insights into the implementation of CSD practices. The integration of the three dimensions of sustainability and decision-making methodology are still rare. Specific features of CSD are also reviewed with a linkage to IMDS research around information technology, business process modeling, and supply chain management.

This is one of the first works to provide a comprehensive focus on CSD in China. The theoretical framework was developed for CSD in China to clarify the relationships between the drivers, the corporation’s characteristics, CSD practices, and corporation performance and will prove useful for future research development and investigation. The linkage to IMDS topics is novel and will help further research related to CSD in China for this journal.