Supplier selection framework to evade pseudo-resilience and to achieve sustainability in supply chains

PurposeDue to increasing uncertainty in the global business scenario, research on supply chain resilience is gaining significance. The outbreak of the COVID-19 pandemic has accelerated and magnified the issues already pertaining in the supply chain thereby increasing the vulnerabilities in the network. This study attempts to build the concept of pseudo-resilience in supplier selection and evaluation for supply chain sustainability.Design/methodology/approachA combination of multi-criteria decision-making methods AHP and R is adopted, and an integrated method called Combined AHP–R method is used to identify and include the property of pseudo-resilience into supplier selection processes.FindingsThe authors identified various factors contributing to pseudo-resilience considering supplier selection process and found the most important attribute. Using the combined AHP–R method, the suppliers were evaluated, considering the attributes contributing to the pseudo-resilience of supply chains and best supplier was selected.Originality/valueTo the best of our knowledge, this is the first study addressing a supplier selection problem for sustainable supply chains, considering pseudo-resilience. Also, this is the first study to apply the AHP–R method for supplier selection in the resilience or sustainability context.

Guest editorial: Post-COVID-19 sustainable supply chain management in emerging markets

Since the early 2000s, emerging markets have become the heart of global supply chains hosting a large volume of industrial productions. The second article looked into the barriers to attaining sustainability in supply chain of the Bangladeshi pharmaceutical sector and developed a hierarchical structure of those barriers using interpretive structural modeling and MICMAC analysis. The eleventh article explored a new way to assess suppliers' suitability by considering pseudo-resilience factors to achieve SSC in the post-COVID-19 era using an analytical hierarchy process and R. It also provided a case study of three smartphone processor suppliers (Jessin et al., 2023).

Supply chain analytics and post-pandemic performance: mediating role of triple-A supply chain strategies

PurposeThe abrupt outbreak of coronavirus disease (COVID-19) hit every nation in 2020–2021, causing a worldwide pandemic. The worldwide COVID-19 epidemic, described as a "black swan”, has severely disrupted manufacturing firms' supply chain. The purpose of this study is to investigate how supply chain data analytics enable the effective deployment of agility, adaptability and alignment (3As) strategies, resulting in improving post-COVID disruption performance. It also analyses the indirect effect of supply chain data analytics on disruption performance through the 3As supply chain strategies.Design/methodology/approachThe hypothesis and theoretical framework were tested using a questionnaire survey. The authors employed structural equation modelling through the SMART PLS version 3.2.7 to analyse data from 163 textile firms located in Pakistan.FindingsThe results revealed that the supply chain data analytics contributed positively and significantly to the agility and adaptability, while all 3As supply chain strategies impacted the PPERF substantially. Further, the connection between supply chain data analytics (SCDA) and disruption performance has substantially been influenced through 3As supply chain strategies.Practical implicationsThe results imply that in the event of low likelihood, high effect disruptions, managers and decision-makers should focus their efforts on integrating data analytics capabilities with 3As supply chain policies to ensure long-term company success.Originality/valueThis research sheds fresh light on the importance of data analytics in effectively implementing 3As strategies for sustaining company performance amid COVID-19 disruptions.

Key supply chain strategies for post-COVID-19 recovery: evidence from an Indian smart furniture industry

PurposeSmart furniture is an essential part of research that has been designed to best complement easy and safe human interaction. The purpose of smart furniture is to save the space of the house and make the products unique, awesome and safe, functional, strong and also make it works better so the people can live better with it. This research aims to explore the key supply chain strategies implemented by the Indian smart furniture industry to reduce the impact of a post-COVID-19 pandemic.Design/methodology/approachThis work utilized a case study and conducted semi-structured interviews with the top leadership of the smart furniture manufacturing industry to explore key supply chain strategies to reduce the influence of the post-COVID-19 pandemic. Additionally, key supply chain strategies have been analyzed using a multi-criteria decision-making technique known as grey relational analysis (GRA) to determine their ranking significance in the smart furniture industry.FindingsThe results of this study discovered that "Inventory-Categorization” is essential in ensuring business continuity during the COVID-19 pandemic and helps reduce the amount of stock they have on hand. It enhanced the opportunity for employees to properly focus on their work and an opportunity for better work-life balance. The results of the study can also help supply chain stakeholders in their establishment of critical strategies.Research limitations/implicationsThe implications of this research work help the Indian furniture industry to make supply chain investment decisions that benefit the organization to sustain itself.Originality/valueThis is the first study to explore key supply chain strategies for the post-COVID-19 era. This work will assist managers and practitioners in helping the organization decide which supply chain strategies are more critical to the betterment of the organization.

Drivers of digital supply chain transformation in SMEs and large enterprises – a case of COVID-19 disruption risk

PurposeDigital transformation in supply chains (SCs) has emerged as one of the most effective ways to minimize SC disruption risks. Given the unprecedented impact of the COVID-19 pandemic on global SCs, this study aims to identify and provide empirical evidence about the drivers of digital SC transformation, considering the interactivity between environmental dynamism, technology, and organizational capabilities during the pandemic era.Design/methodology/approachUsing partial least squares structural equation modeling (PLS-SEM), this study examines 923 firms in Vietnam to ascertain the drivers of digital SC transformation between small- and medium-sized enterprises (SMEs) and large enterprises, based on the technology–organization–environment (TOE) as an overarching framework.FindingsThis study finds that greater digital SC transformation adoption could be achieved under the interactivity between the TOE components of firms' technological competencies, learning capabilities, and disruptions in socioeconomic environments due to the COVID-19 pandemic. Moreover, a multigroup analysis shows that the drivers of digital SC transformation differ between SMEs and large enterprises. SMEs were found to be more motivated by the COVID-19 disruption risk when adopting digital SC models.Originality/valueThis study represents an original and novel contribution from Vietnam as an emerging market to the literature on the impact of COVID-19 on the global value chain. Apart from the unique dataset at the firm level, the analysis of interactions between external and internal drivers of digital SC transformation could provide crucial managerial implications for SMEs to survive major disruptions, such as those caused by the COVID-19 pandemic.

Post COVID-19's opportunities for customer-centric green supply chain management and customers' resilience, the moderate effect of corporate social responsibility

PurposeThis research aims to profoundly investigate the post-COVID-19's opportunities for customer-centric green supply chain management (GSCM) and perceived customer resilience by studying the correlation between fear-uncertainty of COVID-19, customer-centric GSCM, and the perceived customers' resilience. Moreover, to examine how the perceived corporate social responsibility (CSR) activities moderates the relationship among the variables.Design/methodology/approachIn this study partial least squares structural equation modeling (PLS-SEM) was adopted on a sample of 298 managers and customers in the Egyptian small and medium enterprises (SMEs) market for data analysis and hypotheses testing.FindingsPreliminary results indicate that the fear-uncertainty of COVID-19 positively affects customer-centric GSCM. Also, external CSR moderates the association between fear-uncertainty towards COVID-19 and customer-centric GSCM. However, internal CSR does not moderate this relationship. Customer-centric GSCM has a significant positive impact on the perceived environmental and social resilience. However, it has an insignificant effect on the perceived financial resilience. Also, customer-centric GSCM has a significant mediation outcome on the relation between fear-uncertainty of COVID-19 and the perceived environmental and social resilience. However, this relation is insignificant regarding the perceived financial resilience.Practical implicationsManagers could develop a consistent strategy for applying CSR practices, providing clear information and focusing on their procedures to meet their customer needs during COVID-19. Governments and managers should develop a consistent strategy to apply customer-oriented green practices to achieve customers' resilience, especially during the pandemic.Originality/valueBased on the "social-cognitive,” "stakeholder” and "consumer culture” theories, this study shed light on the optimistic side of the COVID-19 pandemic, as it also brings the concepts of social responsibility, resilience and green practices back into the light, which helps in solving customers' issues and help to achieve their resilience.

Developing a resilient healthcare supply chain to prevent disruption in the wake of emergency health crisis

PurposeThe study aims to identify and analyse the drivers of resilient healthcare supply chain (HCSC) preparedness in emergency health outbreaks to prevent disruption in healthcare services delivery in the context of India.Design/methodology/approachThe present study has opted for the grey clustering method to identify and analyse the drivers of resilient HCSC preparedness during health outbreaks into high, moderate and low important grey classes based on Grey-Delphi, analytic hierarchy process (AHP) and Shannon's information entropy (IE) theory.FindingsThe drivers of the resilient HCSC are scrutinised using the Grey-Delphi technique. By implementing AHP and Shannon's IE theory and depending upon structure, process and outcome measures of HCSC, eleven drivers of a resilient HCSC preparedness are clustered as highly important, three drivers into moderately important, and two drivers into a low important group.Originality/valueThe analysis and insights developed in the present study would help to plan and execute a viable, resilient emergency HCSC preparedness during the emergence of any health outbreak along with the stakeholders' coordination. The results of the study offer information, rationality, constructiveness, and universality that enable the wider application of AHP-IE/Grey clustering analysis to HCSC resilience in the wake of pandemics.

Measuring the supply chain competitiveness of e-commerce industry in Indonesia

PurposeThe purpose of this study is to measure the supply chain competitiveness of the e-commerce industry in Indonesia.Design/methodology/approachThe study used a multi-criteria decision-making model based on the analytic hierarchy process. Four main criteria are used to measure the supply chain competitiveness, i.e. cost, differentiation, sustainability and infrastructure.FindingsThe findings of this study show that cost is the most important criterion with a degree of importance of 33.19%, followed by infrastructure of 29.40%, differentiation of 27.96% and sustainability of 9.45%. It shows that the internally controlled strategy contributes about 70% of supply chain competitiveness. The internal infrastructure criterion that consists of software and hardware contributes 65.92% to the whole infrastructure criterion. The internal infrastructure then contributes 19.38% to supply chain competitiveness. Therefore, the internally controlled strategies and internal infrastructure contribute up to 90.08% to the supply chain competitiveness of e-commerce in Indonesia. This result implies that to attain the supply chain competitiveness, the company must carry out strategies focusing on the performance such as cost, differentiation, sustainability as well as on the internal infrastructure such as software and hardware.Research limitations/implicationsIn this paper, the authors limited their study to the business to business (B2B) and business to consumer (B2C) players because these two platforms have been experiencing a very rapid growth. While e-commerce business can take many platforms besides B2B and B2C, the future research should include other platform such as consumer to consumer as well. Because the focus in this study is more the information and material flows, it will be of great interest if the future research covers the platform of mobile payment as well that guarantee the ease of cashflows within supply chains. Also, with the occurrence of the Covid-19 pandemic when this paper was written, in the near future, it is then of great interest to incorporate the pandemic context into the proposed model used in this study. The further study should analyze long-term changes happened as the result of pandemic such as behavioral changes of online shopping from customer side or shift in e-commerce supply chain infrastructure and inventory practice.Practical implicationsWith this study, it is expected that it can be determined which criteria contribute the most to the supply chain competitiveness of the e-commerce industry in Indonesia that will be useful for industry player.Originality/valueE-commerce development in Indonesia is still facing serious challenges. The multi-criteria decision making approach used in this research lays a foundation of how supply chain competitiveness is determined based on the judgment of experts coming from major companies within the supply chain.

Antecedents of freight transportation for sustainable supply chain in the post-COVID era: an emerging market study

PurposeIn past years, the global supply chain has witnessed devastating effects of coronavirus (COVID-19) disease. However, the COVID-19 pandemic has renewed the interest of the Sustainable Supply Chain (SSC) stakeholders on sustainability. The stakeholders are now rethinking their business processes and strategy to make them sustainable. In this context, the relevant literature is required to support emerging markets to formulate sustainability-focussed strategies. The purpose of this study is to provide a comprehensive analysis of potential antecedents that leads towards sustainable development of freight transportation in emerging markets.Design/methodology/approachInitially, the antecedents of the Sustainable Freight Transport (SFT) system are derived from the literature survey followed by verification from the experts. Then, the potential antecedents are categorized under four (social, organizational, operational and environmental) broad categories. Afterwards, a Neutrosophic Analytic Network Process (N-ANP) method is employed to obtain the priority weights of the identified potential antecedents.FindingsThe paper identified and ranked 17 antecedents of the SFT system. According to the study's findings, the top three antecedents of SFT are "the presence of a multimodal transportation system,” "circularity in SFT” and "traffic congestion management”. The results from the study advocate the promotion of existing multi-modal transport facilities which is promising to achieve sustainability. The results suggested the adoption of the digital twin to manage the transport operations.Originality/valueThis study sheds light on how to achieve sustainability in the freight transportation system post-COVID era highlighting the potential antecedents. The study's findings will assist practitioners in developing SFT strategies in the face of such pandemics in future.

Analyzing the effects of COVID-19 pandemic on supplier performance evaluation factors via fuzzy cognitive map with a hybrid learning system

PurposeThe COVID-19 pandemic has proven that how supply chain management (SCM) can become a crucial process for sustainability of the world's production/service. The global supply chain crisis during pandemic has affected most of the sectors. Home and personal care products manufacturers are among them. In this study (1) the problems at SCM of personal and home care products manufacturers during pandemic are discussed with the help of medium-size manufacturer and (2) the factors affecting suppliers' performance for the relevant sector during COVID-19 are analyzed comprehensively.Design/methodology/approachThe importance of the factors is evaluated using fuzzy cognitive maps that can help to reveal hidden casual relationships with the help of expert knowledge. In order to eliminate subjectivity due to usage of expert knowledge, the maps are trained with a hybrid learning approach that consists of Non-linear Learning and Extended Great Deluge Algorithms to increase robustness of the analysis.FindingsThe findings of the study indicate that the factors such as general quality level of products/services, compliance to delivery time, communication skills and total production capacity of suppliers have been crucial factors during pandemic.Originality/valueWhile the implementation of the hybrid learning approach on supply chain can fill the gap in the relevant literature, the promising results of the study can prove the convenience of the methodology to model the of complex systems like supply chain processes.

Identifying and analysis of key flexible sustainable supply chain management strategies toward overcoming the post-COVID-19 impacts

PurposeThe emerging markets are facing a lot of risks and disruptions across their supply chains (SCs) due to the deadly coronavirus disease 2019 (COVID-19) pandemic. To mitigate the significant post-COVID-19 consequences, organizations should modify their existing strategies and focus more on the key flexible sustainable SC (SSC) strategies. Still now, a limited number of studies have highlighted about the flexible strategies what firms should adopt to reduce the rampant effects in the context of emerging markets.Design/methodology/approachThis study presents an integrated approach including Delphi method, Bayesian, and the Best-Worst-Method (BWM) to identify, assess and evaluate the importance of the key flexible SSC strategies for the footwear industry in the emerging market context.FindingsThe results found the manufacturing flexibility through automation integration as the most important flexible SSC strategy to improve the flexibility and sustainability of modern SCs. Also, developing omni-channel distribution and retailing strategies and increasing the level of preparedness by using artificial intelligent are crucial strategies for overcoming the post-COVID-19 impacts.Originality/valueThe novelty of this research is that the research connects a link among flexible strategies, SCs sustainability, and the impacts of the COVID-19 pandemic. Moreover, the research proposes a novel and intelligent framework based on Delphi and Bayesian-BWM to identify and analyze the key flexible SSC strategies to build up sustainable and robust SCs which can withstand in the post-COVID-19 world.

Impact of COVID-19 and government interventions on Bursa Malaysia sectors

PurposeThe purpose of this paper is to examine the influence of the daily growth in confirmed COVID-19 cases in Malaysia and government interventions on the daily returns of financial times stock exchange Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) and eight selected Bursa Malaysia sectorial indices for the period January 29, 2020 to March 31, 2021.Design/methodology/approachThis paper adopts the multivariate generalized autoregressive conditional heteroscedasticity model to determine the effects for the entire study period and four sub-periods, i.e. pre-government intervention, movement control order (MCO), conditional MCO (CMCO) and recovery MCO phases.FindingsThis paper finds no evidence of the effect of the daily growth in confirmed COVID-19 cases on the returns of FBMKLCI and eight Bursa Malaysia sectorial indices for the full study period. However, the former has exerted different effects over the four sub-periods. Sectors that are positively affected for the MCO period are financial services and real estate investment trust. Yet, these sectors are negatively affected for the CMCO period along with the industrial products and services and technology sectors. Sectors that consistently demonstrate statistically insignificant results are construction, energy, plantation and utilities.Originality/valueThis study makes an initial attempt to investigate the influence of the COVID-19 pandemic on the returns of Bursa Malaysia sectorial indices over different phases of government interventions in Malaysia.

Household Savings and Negative Interest Rates

This paper analyses determinants of household savings in a model based on an extension of the disequilibrium savings theory. These extensions follow from the life-cycle, permanent-income and Ricardian-equivalence theories. Based on panel data of 20 countries from the period 2000–2020, fixed-effect least squares estimation procedures are used. The analysis provides evidence that negative interest rates lead to a statistically and economic significant increase in savings. This implies that stimulating household consumption with a monetary policy of negative interest rates is counter-productive. The positive effect of income uncertainty and lagged saving rates gets smaller for negative interest rates, weakening the support for the disequilibrium-savings theory. Larger government deficits increase savings even more when rates are negative, strengthening the Ricardian equivalence effect. The effect of negative interest on the predictions of the life-cycle and permanent-income theories is mixed.

How well does government microcredit serve the investment needs of small and medium enterprises? An impact analysis on handloom weavers in Bangladesh

PurposeThe purpose of this study is to empirically estimate the impact of a government microcredit program on the handloom weavers to promote small and medium enterprises (SMEs) in Bangladesh.Design/methodology/approachThe data were collected from 311 handloom weavers from the Sirajganj District of Bangladesh from July to December 2015 using a multistage sampling technique. The analysis was conducted using a two-stage least squares regression model incorporating instrumental variables to control for the probable endogeneity problem associated with the study.FindingsThis study finds that government microcredit had no significant impact on borrowers' investment in their business, whereas credit received from multiple sources other than government credit had a significant negative impact. Additionally, literacy level, household assets and the number of operational handloom units positively affected investment, while the number of non-operational handloom units and distance negatively affected the investment.Research limitations/implicationsThis study's findings are more specific for the selected case and may not be generalizable to all kinds of SMEs.Practical implicationsThe policy implications are targeted at increasing loan size based on the number of operational handloom units to improve the performance of government and other microcredit programs to facilitate the growth of SMEs in Bangladesh.Originality/valueThis study specifically focuses on estimating the financial performance of government microcredit programs for SME development within the handloom industry, which has not been sufficiently explored in the literature.

Impact of US-China trade war on Asian economies: neural network multilayer perceptron approach

PurposeThis study aims to find the impact of the trade war between the USA and China on Asian economies. Apart from macroeconomic variables associated with trade, this study explicitly creates a trade war scenario and trade war participant dummies. Using the neural network multilayer perceptron, this study checks for the causal linkages between the predictors and target output for the panel of Asian economies and the USA.Design/methodology/approachA conceptual model of the after effects of trade war in a quadrant is developed. Variables related to trade and tariffs are included in the study for a panel of 19 Asian economies. The feedforward structure of neural network analysis is used to identify strong and weak predictors of trade war.FindingsThe hidden layers of the multilayer perceptron reveal the inconsistency in linkages for the predictors' services exports, tariff measures, anti-dumping measures, trade war scenario dummy with gross domestic product. The findings suggest that to curtail the impact of the trade war on Asian economies, predictors with neural evidence must be paid due weightage in policy determination and trade agreements.Originality/valueThe study applies a novel and little explored AI/ML technique of Neural Network analysis with training of 70% observations. The paper will provide opportunity for other researchers to explore techniques of AI/ML in trade studies.

Social Distancing, Vaccination and Evolution of COVID-19 Transmission Rates in Europe

This paper provides estimates of COVID-19 transmission rates and explains their evolution for selected European countries since the start of the pandemic taking account of changes in voluntary and government mandated social distancing, incentives to comply, vaccination and the emergence of new variants. Evidence based on panel data modeling indicates that the diversity of outcomes that we document may have resulted from the nonlinear interaction of mandated and voluntary social distancing and the economic incentives that governments provided to support isolation. The importance of these factors declined over time, with vaccine uptake driving heterogeneity in country experiences in 2021. Our approach also allows us to identify the basic reproduction number, R0, which is precisely estimated around 5, which is much larger than the values in the range of 2.4–3.9 assumed in the extant literature.

Internationalization and innovation orientation as factors of employee learning and development adaptation during Covid-19: Evidence from Polish SMEs

Objective: The driving aim of this study is to test whether small and medium-sized enterprises (SMEs) with a higher level of internationalization and innovation orientation were able to adapt their training and development activities during Covid-19 quicker and better than others. With no or very few studies investigating employee learning and development adaptation in SMEs, we address an important research gap. Research Design & Methods: We tested the hypothesized relationships on a sample of 214 Polish SMEs. Data was collected using the computer-assisted telephone interview (CATI) method. The logit model and ordered probit model were employed to analyse the data. Findings: While the results clearly indicate that innovation orientation had an impact on the adaptation of training and development for Polish SMEs during the first year of the Covid-19 pandemic, internationalization did not exhibit any significant impact on the number of training sessions conducted during the first year of Covid-19. However, the existence of prior experience with online technologies may have moderated the relationship between internationalization and adaptation of learning and development. Implications & Recommendations: To become quick adapters, SMEs should develop an innovation orientation, implement online learning practices and foster mutual learning within the organization, and take every opportunity to learn from external partners. Contribution & Value Added: With this study, we contribute to the body of knowledge investigating SME adaptation during Covid-19. This research implies that innovation orientation can positively influence how firms adapt their training and development in times of crisis. This pioneering contribution is an important piece of the puzzle of what might determine the competitive advantage of some SMEs over others in years to come.

Who Obtained More Bank Loans after the Outbreak of COVID-19? Evidence from Chinese Listed Companies

One of the most serious risks from COVID-19 is a financial crisis for a company. Governments and central banks have used both fiscal and monetary tools on a large scale to alleviate the financial crises of companies. We build a cross-sectional model to explore who obtained more bank loans after the outbreak of COVID-19. Using data from China's listed companies, we find that real estate companies and state-owned companies obtained more bank loans. In addition, there is no evidence that industries more severely affected by the virus obtained more bank loans. Our findings demonstrate that the misallocation of credit in China worsened after the outbreak of COVID-19.

Systemic Risk of China's Financial Industry during the Spread of the COVID-19 Epidemic and the Breakdown of Crude Oil Negotiation

This research first adopts three indicators to measure the systemic risk of different financial industries in China. Second, we employ the Time Varying Parameter-Stochastic Volatility-Vector Auto Regression (TVP-SV-VAR) model to investigate the time-varying relationship among COVID-19 epidemic, crude oil price, and financial systemic risk. The results herein not only help us grasp the current level of systematic risk in China, but also can assist at improving the early warning risk indicators and enhance the risk management system. Lastly, this research can also help investors to make reasonable asset planning.

The Impact of COVID-19 Pandemic on Emerging Country Stock Markets: Evidence of the Value Effect

We examine the impact of the COVID-19 pandemic on seven emerging stock markets by focusing on the value effect. Our results show that there are significant differences in the value premia before and during the pandemic. Furthermore, the traditional value proxies are no longer good predictors of future stock returns. To further capture the impact the pandemic's progress on stock returns, we estimate Fama-MacBeth regressions by introducing proxies of the pandemic. We uncover heterogeneous responses of emerging markets to the pandemic. These findings provide a wealth of insights on the presence and driving force relevant to the value effect.