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Sustainable supplier selection is of vital importance in sustainability decision of supply chain under carbon neutrality. Multi-criteria decision-making approaches are widely used in sustainable supplier selection and generally classified the involved criteria into three sustainable development (SD) dimensions: Environmental, Social and Economic. During the assignment of appropriate weighted scores to the criteria, most of the methods considered mutually exclusive criteria. However, some criteria cover multidimensions since ambiguity vagueness makes them difficult to classify into one dimension exclusively. The purpose of this paper is to find proper approaches addressed to multidimensional overlapping criteria in the evaluation of suppliers’ sustainability performance.

This study proposes three approaches to resolve the multidimensional overlapping criteria issue by data envelopment analysis (DEA) methods. The first approach uses all dimensional criteria and “dimensional overlapping criteria” in a single DEA model. The second approach consists of two-stage DEA. The first stage is to find SD dimensional performances, which are used in the second stage. The third approach uses an aggregate weight-constrained DEA model with additional constraints. Such approaches are applied to an empirical case study with six dimensions.

Results indicate that the third approach is better than the first two approaches in balancing the development among all dimensions instead of focusing on the superiority dimension to obtain high performance.

Discussing overlapping criteria in the context of sustainable supplier evaluation and other multi-criteria evaluation have a noticeable impact on evaluation systems, but appropriate approaches for this issue are currently under-researched.

This paper aims to classify journal papers in the context of hybrid quality function deployment QFD and multi-criteria decision-making (MCDM) methods published during 2004–2021.

A conceptual classification scheme is presented to analyze the hybrid QFD-MCDM methods. Then some recommendations are given to introduce directions for future research.

The results show that among all related areas, the manufacturing application has the most frequency of published papers regarding hybrid QFD-MCDM methods. Moreover, using uncertainty to establish a hybrid QFD-MCDM the relevant papers have been considered during the time interval 2004–2021.

There are various shortcomings in conventional QFD which limit its efficiency and potential applications. Since 2004, when MCDM methods were frequently adopted in the quality management context, increasing attention has been drawn from both practical and academic perspectives. Recently, the integration of MCDM techniques into the QFD model has played an important role in designing new products and services, supplier selection, green manufacturing systems and sustainability topics. Hence, this survey reviewed hybrid QFD-MCDM methods during 2004–2021.

The present study aims to provide a practical and robust assessment technique for assessing countries' investability in global supply chains to practitioners. Thus, the proposed approach can help decision-makers evaluate and select appropriate countries in the expansion process of the global supply chains and reduce risks concerning country (market) selection.

The present study proposes a novel decision-making approach, namely the REF-Sort technique. The proposed approach has many valuable contributions to the literature. First, it has an efficient basic algorithm and can be applied to solve highly complicated decision-making problems without requiring advanced mathematical knowledge. Besides, some characteristics differentiate REF-Sort apart from other techniques. REF-Sort employs the value or value range that reflects the most typical characteristic of the relevant class in assignment processes. The reference values in REF-Sort and center profiles are similar in this regard. On the other hand, class references can be defined as ranges in REF-Sort. Secondary values, called successors, can also be employed to assign a value to the appropriate class. REF-Sort can also determine the reference and successor values/ranges independently of the decision matrix. In addition, the proposed model is a maximally stable and consistent decision-making tool, as it is resistant to the rank reversal problem.

The current papers' findings indicate that countries have different features concerning investment. Hence, the current paper pointed out that only 22% of the 95 countries are investable, whereas 19% are risky. Thus, decision-makers should make detailed evaluations using robust, powerful, and practical decision-making tools to make more reasonable and logical decisions concerning country selection.

The current paper proposes a novel decision-making approach to evaluate. According to the authors' information, the proposed model has been applied to evaluate investable countries for the global supply chains for the first time.

As the COVID-19 epidemic ravages the world in the fourth industrial revolution era, the manufacturing sector faces its worst situation in a century. Lean philosophy, renowned as a “warrior philosophy,” can be an able rescuer to these industries. This study aims to identify the hurdles to lean strategy implementation and conduct an analysis to provide cognizance to policymakers, practitioners and decision-makers.

This study aims to identify the obstacles that obstruct lean implementation into seven primary barriers/components, with the fuzzy DEMATEL approach being used to evaluate the critical factors as well as the cause and effect factors among them. Expert opinions are sought to obtain the relevant data for evaluation purposes.

The results reveal that a firm should focus on firm cultural conflict scenario, resources–responses incapability, improve on suppliers’ attitude and execute a proper planning and logistics equation to alleviate the hindrances of implementing lean. As these causal factors influence the effect factors, namely, top management vision, management–employee relationship and human resource building, focusing on them automatically improves the effect factors; thus, the surge to overcome resistance to lean implementation is alleviated.

This research aids in identifying and analyzing lean implementation issues in the manufacturing and industrial sectors. The observations, results and insights drawn can act as a guiding force to rupture the resistance envelope covering the domain of lean implementation and possibly reinstating industries to survive and excel in the business post-COVID era.

This research introduces barriers to lean implementation in a unique way, as it articulates all sections of an industry and group the barriers based on the classification. It further prioritizes the barriers for their importance in the Indian industrial scenario. This would help the industry professionals and managers access the barriers and generate insight on how and where to start implementing lean.

This study aims to develop a comprehensive green supplier governance (GSG) concept and explore whether specific GSG approaches (green supplier assessment, green supplier assistance and green strategic partnership with suppliers (GSPS)) bring environmental and economic performance. Moreover, this study aims to reveal a synergistic effect of three GSG approaches on performance improvement.

Using data collected from 200 Chinese manufacturing firms, regression analysis was employed to reveal the relationship between specific GSG approaches and firm performance. Further, cluster analysis was used to identify groupings of firms regarding implementation levels of three GSG approaches and compare the performance of the firm groups.

Green supplier assessment (GSA) can bring environmental performance, but GSA is not associated with economic performance. Green supplier assistance is positively associated with economic performance, while green supplier assistance cannot improve environmental performance. Only GSPS leads to improvement for both environmental and economic performance. Furthermore, firms with high implementation levels of GSA and GSPS (whether with high or low implementation levels of GSAS) can achieve the best environmental and financial performance.

This study provides implications for firms to more strategically and comprehensively implement GSG approaches, which can be more effective in bringing environmental and economic performance.

The authors' study extends the GSG concept with two approaches by subdividing the collaborative approach into green supplier assistance and GSPS based on the collaboration levels. This study also sheds light on how to improve firm performance by different GSG approaches and reveals a synergistic effect of three GSG approaches on performance.

Contractor selection is critical in green buildings (GBs) since the preferred contractor has the responsibility to achieve construction sustainability as well as relationship sustainability. The developer satisfaction reflecting requirements can boost the cooperative relationship among stakeholders and act as an evaluation scale for the success of GB projects, which needs to be emphasized in the selection process but little involved in the existing research. This study explores improving GB contractor (GBC) selection by integrating developer satisfaction into selection procedures.

A systematic framework of GBC selection including twenty-five criteria from literature review and experts survey is firstly constructed. Both tactical and strategic criteria are further classified into Kano categories (must-be, one-dimensional, and attractive categories) using the fuzzy Kano model (FKM), and weighted by the developer satisfaction index. The model proposed by this study combining FKM and TOPSIS divides the selection process into the filtration phase and selection phase by Kano categories. The proposed model is finally verified through performance comparison among multiple methods in a case.

Selection criteria are measured linearly and nonlinearly, showing criteria having nonlinear satisfaction change accounts for two-thirds of all. Criteria at tactical level tend to be must-be or one-dimensional categories for the developer, and most strategic criteria are classed as the attractive category, indicating that adding strategic criteria is necessary for long-term cooperation. The proposed model, using developer satisfaction to improve the selection process, ensures the selected GBC to be the most satisfactory with requirements of the developer and makes the performance of GBCs easily distinguishable.

This study contributes to the existing body of knowledge for promoting relationship sustainability by supplementing an integrated model with emphasis on developer satisfaction in GBC selection, so as to establish a good initial foundation due to the match between performances of GBCs and needs of developers. It not only helps maximize developer satisfaction in GBC selection by applying satisfaction to pre-construction management, but also instructs GBCs to prioritize performance improvements. The framework is also conducive for developers to classify selection criteria and select other participants (like green suppliers) from the satisfaction perspective in GBs.

The authors empirically examine purchasing strategy typologies based on strategic intent (i.e. competitive priorities) and practices used to achieve these priorities. The authors further investigate the implementation conditions of such strategies based on perceived uncertainty and strategic purchasing.

The authors utilize case study data from 11 international service and manufacturing firms with global supply chains. Each company was profiled based on the level of perceived environmental uncertainty, the characteristics of strategic purchasing, the use of relevant purchasing practices and its ability to create value through purchasing.

The study findings show that four purchasing strategy types exist: Purchasing Rationalization, Supply Base Optimization, Purchasing as a Service and World-Class Supply Base Management. Lower levels of perceived environmental uncertainty favor the adoption of rationalization strategies (i.e. Purchasing Rationalization and Supply Base Optimization), while increased uncertainty leads companies to switch to relationship-focused strategies (i.e. Purchasing as a Service and World-Class Supply Base Management). Further, that specific components of strategic purchasing (i.e. strategic planning, maturity, status and report level) enable the successful implementation of different strategy types.

This research contributes to the existing literature by outlining the different types of purchasing strategies and the external and internal factors that need to be considered to achieve strategic alignment and value creation in purchasing, and by classifying purchasing strategy types at the functional level based on empirical evidence.

In developing countries such as India, start-ups play an essential role in “industrial output,” “Gross Domestic Product ” and “employment creation.” Evidence suggests that pandemics have risen over the last century due to rising global travel and assimilation, urbanization, alterations in land use, and significantly larger exploitation of the natural environment. These trends are likely to continue and intensify. These pandemic episodes affect businesses, especially start-ups. Supplier selection is among the vital critical elements that start-ups must include in start-ups' strategy procedures during the pandemic episodes. This study's focus is to “identify,” “analyze,” and “categorize” the factors affecting supplier selection in start-ups during frequent pandemic episodes like coronavirus disease 2019 (COVID-19).

Through “literature review” and “experts' opinion” from various start-ups in India, ten affecting factors were identified. Total Interpretative Structural Modeling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) were employed to analyze the interrelationship among the factors affecting the supplier selection on start-ups during frequent pandemic episodes, and these factors were ranked as “autonomous,” “independent,” “linkage,” and “dependent” factors.

The findings show that “performance history,” “service levels,” “technical capability,” and “financial stability” are the most critical factors affecting the supplier selection on start-ups during frequent pandemic episodes. The next importance should be safety and environmental concern” and “quality.”

The factors affecting supplier selection on start-ups during frequent pandemic episodes are the current focus of this study. This study is mainly performed on Indian start-ups and can be extended to other countries.

The start-ups can rely on this study to clearly understand the factors affecting the supplier selection on start-ups during frequent pandemic episodes.

There is no research regarding factors affecting supplier selection on start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to supplier selection in start-ups. This gap inspired the present study, which employs the “Total Interpretive Structural Modeling (TISM)” technique to uncover supplier selection determinants and investigate hierarchical interconnections among factors influencing/affecting supplier selection in start-ups during frequent pandemic episodes.

This paper aims to examine the customer-based and supplier-based trade credit gaps for USA firms from 1970 to 2020.

The authors' study examines USA companies from 1970 to 2020. The authors begin with an analysis of the trends in aggregate working capital, the capital's components and the trade credit gaps. Various regression models are used to estimate the impacts of identified firm characteristics and unidentified sources on customer-based and supplier-based trade credit gaps over time. The authors then decompose the impacts of firm characteristics to further understand whether changing firm characteristics and/or changing sensitivity to firm characteristics drive the variation in trade credit gaps.

There is a gradual reduction in the customer-based trade credit gap and a substantial expansion in the supplier-based trade credit gap. Though identified firm characteristics have dominant impacts on observed trade credit gaps, there is evidence of the effects of time and unobservable factors. The main source of changes in customer-based and supplier-based trade credit gaps lies in changes in sensitivity to firm characteristics. In addition, the authors find that firm age is the factor with the largest average effect on both trade credit gaps when examining the full sample period. However, different firm characteristics appear to be the key driver of variations in trade credit gaps over time and across the two types of trade credit gaps. The authors also find that financial distress has the least impact on both customer-based and supplier-based trade gaps. There are variations in the firm characteristics with the largest impacts when evaluating decade-long evaluation periods.

To the authors' knowledge, this is the first paper to examine the customer-based and supplier-based trade credit gaps. The connection between trade credit and the trade credit's corresponding inventory (INV) component extends prior literature on the joint management of trade credit and INV. The authors analyze both identified firm characteristics and unidentified sources in the search for explanations of the trade credit gaps. Furthermore, the authors' study explores the channels through which firm characteristics affect different types of trade credit gaps. The authors' findings help identify relevant and irrelevant risk factors of corporate working capital policy.

In this age of extremely well-developed social media, it is necessary to detect any change in the corporate image of an enterprise immediately so as to take quick action to avoid the wide spread of a negative image. However, existing survey-based corporate image evaluation methods are costly, slow and static, and the results may quickly become outdated. User comments, news reports and we-media articles on the internet offer varied channels for enterprises to obtain public evaluations and feedback. The purpose of this study is to effectively use online information to timely and accurately measure enterprises’ corporate images.

A new corporate image evaluation method was built by first using a literature review to establish a corporate image evaluation index system. Next, an automatic text analysis of online public information was performed through a topic classification and sentiment analysis algorithm based on the dictionary. The accuracy of the topic classification and sentiment analysis algorithm is then calculated. Finally, three internet enterprises were chosen as cases, and their corporate image was evaluated.

The results show that the author’s corporate image evaluation method is effective.

First, in this study, a new corporate image evaluation index system is constructed. Second, a new corporate image evaluation method based on text mining is proposed that can support data-driven decision-making for managers with real-time corporate image evaluation results. Finally, this study improves the understanding of corporate image by generating business intelligence through online information. The findings provide researchers with specific and detailed suggestions that focus on the corporate image management of emerging internet enterprises.