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Credit risk evaluation is a crucial task for banks and non-bank financial institutions to support decision-making on granting loans. Most of the current credit risk methods rely solely on expert knowledge or large amounts of data, which causes some problems like variable interactions hard to be identified, models lack interpretability, etc. To address these issues, the authors propose a new approach.

First, the authors improve interpretive structural model (ISM) to better capture and utilize expert knowledge, then combine expert knowledge with big data and the proposed fuzzy interpretive structural model (FISM) and K2 are used for expert knowledge acquisition and big data learning, respectively. The Bayesian network (BN) obtained is used for forward inference and backward inference. Data from Lending Club demonstrates the effectiveness of the proposed model.

Compared with the mainstream risk evaluation methods, the authors’ approach not only has higher accuracy and better presents the interaction between risk variables but also provide decision-makers with the best possible interventions in advance to avoid defaults in the financial field. The credit risk assessment framework based on the proposed method can serve as an effective tool for relevant policymakers.

The authors propose a novel credit risk evaluation approach, namely FISM-K2. It is a decision support method that can improve the ability of decision makers to predict risks and intervene in advance. As an attempt to combine expert knowledge and big data, the authors’ work enriches the research on financial risk.

The purpose of this study is to develop a new mathematical model and an exact solution method for an assembly line rebalancing problem. When an existing assembly line has to be adapted to a new production context, the line balancing, resources allocation and component management solutions have to be revised. The objective is to minimize the number of modifications to be done in the initial line in order to reduce the time and investment needed to meet new production requirements. The proposed model is evaluated via a computational experiment. The obtained results the efficacy of the proposed method.

This paper develops a new mathematical model and an exact solution method for an assembly line rebalancing problem with the objective to minimize the number of modifications to be done in the initial line to reduce the time and investments needed to meet new production requirements.

The computational experiments show the efficacy of the proposed method.

These reconfiguration costs were analysed for different part-feeding policies that can be adopted in an assembly line.

The purpose of this study is use a bibliometric analysis to explore the relational nature of knowledge creation in WFM in operations. Companies live under constant pressure to find the best ways to plan their workforce, and the workforce emangement (WFM) is one of the biggest challenges faced by managers. Relevant research on WFM in operations has been published in a several range of journals that vary in their scope and readership, and thus the academic contribution to the topic remains largely fragmented.

To address this gap, this review aims to map research on WFM in operations to understand where it comes from and where it is going and, therefore, provides opportunities for future work. This study combined two bibliometric approaches with manual document coding to examine the literature corpus of WFM in operations to draw a holistic picture of its different aspects.

Content and thematic analysis of the seminal studies resulted in the extraction of three key research themes: workforce cross-training, planning workforce mixed methods and individual workforce characteristics. The findings of this study further highlight the gaps in the WFM in operations literature and raise some research questions that warrant further academic investigation in the future.

Likewise, this study has important implications for practitioners who are likely to benefit from a holistic understanding of the different aspects of WFM in operations.

Building supply chain resilience is increasingly recognized as an effective strategy to deal with supply chain challenges, risks and disruptions. Nevertheless, it remains unclear how to build supply chain resilience and whether supply chain resilience could achieve a competitive advantage.

By analyzing the data collected from 216 firms in China, the current study empirically examines how information technology (IT) capability and supply chain collaboration affect different forms of supply chain resilience (external resilience and internal resilience) and examines the performance implications of these two forms of supply chain resilience.

Results show that IT capability is positively related to external resilience, whereas supply chain collaboration is positively related to internal resilience. The combination of IT capability and supply chain collaboration is positively related to external resilience. In addition, internal resilience is positively related to firm performance.

This study used only cross-sectional data from China for hypothesis testing. Future studies could utilise longitudinal data and research other countries/regions.

The findings systematically assess how IT capability and supply chain collaboration contribute to supply chain resilience and firm performance. The results provide a benchmark of supply chain resilience improvement that can be expected from IT capability and supply chain collaboration.

The study findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

The present research paper is an attempt to study how COVID-19 can affect the global sourcing practices of various supply chain intermediaries across the demand chain. This study aims to explore and is an attempt to understand the overall impact of COVID-19 on the sustainable operations of the firm such as sourcing, procurement, economic performance, social responsibility, consumption and distributions.

This study uses a quantitative technique using data collected from 708 respondents. Structural equation modeling (SEM) has been applied to test the proposed model and hypothesis.

The findings of the study suggest that sourcing practices, distribution and sustainability considerations of manufacturers, suppliers, distributors and retailers are affected by COVID-19 to a great extent but the pandemic has also led to making supply chain intermediaries understand the changing dynamics of the business scenario which can help them in their own strategic and business evolution.

The current disruptions throughout global delivery chains caused by COVID-19 affect badly, the already poor-performing supply chains. Hence, the present study provides fresh insight on how organizations can limit the ill effects of COVID-19 by safeguarding some of their key sustainable operations in a post-pandemic business scenario.

The present study takes into consideration how core supply functions such as sourcing, distribution and manufacturing and various sustainable operations are disrupted by pandemic and its after-effects. This knowledge base can help business organizations to mitigate such problems/disruptions in the future.

The study examines the key drivers of the adoption of disruptive technologies (DTs) in the digital supply chain (DSC) in developing nations.

The data were collected using well-established measures grounded in the diffusion of innovation (DOI) theory. The hypotheses were tested using the structural equation modeling (SEM) approach using SmartPLS. The authors control for the demographics and apply the required statistical diagnostics for robust findings.

The compatibility and IT expertise were the two key factors in adopting the DTs in DSC in developing nations. The organizations with higher compatibility and internal IT expertise and competence witness a higher level of adoption of DT. The perceived cost and complexity were not found statistically significant. This may be probably because developing nations such as India do not perceive the technology adoption complex.

The research enhances DTs adoption, assuming it is organizational innovation. This study makes a theoretical contribution to the DOI literature.

The practicing managers should pay attention to addressing the existing technology compatibility issues and spend efforts on training employees to increase the IT expertise to improve the adoption of DT.

The greater adoption of the DTs in DSCs can reduce wastages in supply chains by a faster sense and response and greater technological flexibility with transparency and information sharing.

The key antecedent to the acceptance of the DTs in developing nations is compatibility than complexity and IT expertise than the cost. The study's originality lies in the fact that most studies on technology adoption study a single technology, but this study captures a holistic view on a group of technologies under industry 4.0.

Since firms are often puzzled with the adoption of proper governing mechanism to achieve their environmental benefits, this research examines how green supplier integration (GSI) affects environmental performance via environmental innovation and the moderating role of ambidextrous governance.

The authors tested the hypotheses by adopting two-waved survey data from 206 Chinese manufacturers and the hierarchical regression analysis.

The results revealed that GSI is positively linked with both incremental and radical environmental innovation, which further enhance environmental performance. Moreover, balanced ambidexterity enhanced the link between GSI and incremental environmental innovation, while combined ambidexterity alleviated the link between GSI and radical environmental innovation.

Firms should integrate suppliers into their activities of dealing with environmental issues to realize environmental benefits through facilitating environmental innovation. Moreover, the choice of different dimensions of ambidextrous governance can affect the environmental benefits of GSI.

This research enriches the authors’ understanding of how to achieve environmental benefits by engaging in GSI, and it provides a novel and insightful approach for better managing GSI from the perspective of ambidextrous governance.

This study aims to proposed that blockchain helps the organization improve supply chain (SC) performance by improving integration, agility and security through real-time information sharing, end-to-end visibility, transparency, data management, immutability, irrevocable information and cyber-security platforms.

This study has made an initial effort toward proposing a framework that shows the problems and challenges for the O&G SC under its segments (upstream, midstream and downstream) and provides the interlink among blockchain properties for SCM problems. SC managers were selected for survey questionnaires from the Pakistan O&G industries.

This study analyzes the impact of blockchain-enabled SC on firm performance with an understanding of the SC robustness capabilities as a mediator. The result revealed that the SC manager believes that the blockchain-enabled SC has a positive and significant on firm performance and robustness capabilities.

Blockchain technology is reflected as high-tech to support the firm process, responses and methods. The technology helps eliminate bottlenecks, avoid uncertainties and improve decision-making, leading to improved SC functions. This study guides managers about the potential problems of existing SC and how blockchain solves SC problems more effectively.

The oil and gas (O&G) sectors are neglected by researchers, and there are limited studies on O&G supply chain management (SCM). Additionally, no empirical evidence suggests implementing blockchain for O&G as a solution for potential problems. Furthermore, present the roadmap to other industries those having complex SC networks for the implication of blockchain to improve the SC performance.

This paper aims to explore the intellectual structure shaping the circular economy (CE) discourse within the built environment in Africa.

The study adopted a bibliometric analysis approach to explore the intellectual structure of CE in the built environment in Africa. The authors collected 31 papers published between 2005 and 2021 from the Scopus database and used VOSviewer for data analysis.

The findings show that there are six clusters shaping the intellectual structure: demolition, material recovery and reuse; waste as a resource; cellulose and agro-based materials; resilience and low-carbon footprint; recycling materials; and the fourth industrial revolution. The two most cited scholars had three publications each, while the top journal was Resources, Conservation and Recycling. The dominant concepts included CE, sustainability, alternative materials, waste management, lifecycle, demolition and climate change. The study concludes that there is low CE research output in Africa, which implies that the concept is either novel or facing resistance.

The data were drawn from one database, Scopus; hence, adoption of alternative databases such as Web of Science, Google Scholar and Dimensions could potentially have yielded a higher number of articles for analysis which potentially would result in different conclusions on the subject understudy.

This study made a significant contribution by articulating the CE intellectual structure in the built environment, identified prominent scholars and academic platforms responsible for promoting circularity in Africa.