Social Sustainability Challenges Towards Flexible Supply Chain Management: Post-COVID-19 Perspective

Impact of COVID-19 pandemic on the existence of social solidarity: evidence from rural-urban communities in Lombok Island, Indonesia

The COVID-19 pandemic that has hit the entire world since the beginning of 2020 is an unimaginable phenomenon. The pandemic is disastrous because it has caused loss of life and livelihood for a large part of the population. People lose their jobs, spaces for social interaction are closed, and social relationships are disrupted. Several studies show that social solidarity should be a major concern for people to sustain the future quality of their lives. Social solidarity dimensions in this study include gotong royong (local culture of mutual help), marriage banjars (local association), cooperation, and sharing of information. This study aims to examine the existence of social solidarity during the pandemic in rural and urban areas and to know the level of community exposure to COVID-19 in Lombok Island, Indonesia. This research adopted a quantitative approach to identify and analyse the existence of social solidarity in rural and urban communities during the COVID-19 pandemic. A set of questionnaires was distributed and shared by enumerators with 1,100 targeted-respondents from Lombok Island. The survey was carried out from 14th October to 28th October 2021, that is, during a recovery period from the pandemic while restrictions implemented by the government were still in full force. Chi square statistical analysis was used to test whether there were differences in social solidarity between those who lived in rural areas and those who lived in urban areas. This research found the existence of social solidarity in both rural and urban communities during the pandemic. The level of social solidarity in rural areas is higher than in urban areas. While related to the number of those who were exposed and died, conditions were higher in rural areas than in urban areas. However, in terms of the death rate, the level of death rate in urban areas is higher than in rural areas. This condition indicates differences in the characteristics of rural and urban communities, which can be considered in implementing policies during a future pandemic. This research provides evidence for local governments in formulating policies with a social solidarity perspective by taking into account the different characteristics of rural and urban communities.

The Consequences of COVID-19 Disruption on Sustainable Economy in the Top 30 High-Tech Innovative Countries

This study aims to investigate the effects of the COVID-19 pandemic on the innovation index, Gross Domestic Product (GDP), high technology exports, and human development (HDI) in the world's leading 30 high-tech innovative countries. Using grey relational analysis models, the association between COVID-19 and other economic development indices was investigated. The model selects the country least affected by the pandemic from the top 30 innovative countries through a conservative (maximin) method based on grey association values. Data was collected from World Bank databases and analyzed to compare pre- and post-COVID-19 periods (2019, 2020). The outcomes of this study provide essential recommendations for industries and decision-makers with suitable action plans to preserve economic systems from further harm caused by the global COVID-19 outbreak. The ultimate goal is to boost the innovation index, GDP, high-tech exports, and HDI of high-tech economies and pave the way for a sustainable economy. To the author's knowledge, this is the first study to develop a multidimensional framework to assess COVID-19's impact on the sustainable economy of top 30 high-tech innovative countries, and to conduct a comparative analysis to identify the strong and weak effects of COVID-19 on sustainable economic growth.

Prescriptive Analytics-Based SIRM Model for Predicting Covid-19 Outbreak

Predicting the outbreak of a pandemic is an important measure in order to help saving people lives threatened by Covid-19. Having information about the possible spread of the pandemic, authorities and people can make better decisions. For example, such analyses help developing better strategies for distributing vaccines and medicines. This paper has modified the original Susceptible-Infectious-Recovered (SIR) model to Susceptible-Immune-Infected-Recovered (SIRM) which includes the Immunity ratio as a parameter to enhance the prediction of the pandemic. SIR is a widely used model to predict the spread of a pandemic. Many types of pandemics imply many variants of the SIR models which make it very difficult to find out the best model that matches the running pandemic. The simulation of this paper used the published data about the spread of the pandemic in order to examine our new SIRM. The results showed clearly that our new SIRM covering the aspects of vaccine and medicine is an appropriate model to predict the behavior of the pandemic.

Demand and Supply Disruptions During the Covid-19 Crisis on Firm Productivity

This paper explores the supply chain (SC) disruption impacts to the performance outcomes of a semiconductor company during the Covid-19 pandemic and proposes appropriate risk mitigation strategies to overcome the crisis. The research uses a single case study methodology and 24 SC employees from Belgium and Germany who take part in the survey. To measure the effect of SC disruptions to the firm's financial performance, some quarterly financial statement data are used from 2018 to 2021. The regression analysis results show that there is no significant impact of SC disruptions to the firm's productivity and non-financial performance. The paired samples t-test suggests that there is no significant change in the firm's financial performance before and during Covid-19 either due to the market's political and economic stability or the semiconductor company develops effective SC risk management strategies.

Developing an evidence-based TISM: an application for the success of COVID-19 Vaccination Drive

The study illustrates an application of evidence data for performing Total Interpretive Structural Modeling (TISM). TISM is widely used to analyze the critical success factors or inhibitors and their interlinkages. This study uses learning from evidence data, specifically social media analytics, to identify the relationship between the elements. Thus, it leads to the advancement of the TISM-P methodology with evidence-based TISM (TISM-E). This study uses Twitter as a source of evidence data. Further, 2,60,297 tweets were used to illustrate the process of TISM-E. The paper demonstrates the application of TISM-E for the success of the COVID-19 vaccination drive. The pandemic effects are long-term; therefore, the hierarchical model developed shows a sustainable approach for vaccinating maximum population. Further, the framework developed will ensure the distribution efficacy of vaccines. In addition, it will aid practitioners in developing future vaccination policies. The enhanced model provides evidence for polarity (positive/negative) of relationships and can help to build propositions for theory development. The study contributes to healthcare, modeling research, and graph-theoretic literature.

Strategic drivers to overcome the impacts of the COVID-19 pandemic: implications for ensuring resilience in supply chains

The recent coronavirus (COVID-19) pandemic has affected the manufacturing industry’s entire supply chain system. It is important to investigate the strategic drivers to deal with the impacts of COVID-19 in the manufacturing industry. Accordingly, this study aims to identify the strategic drivers to overcome the impacts of the COVID-19 pandemic and improve the resiliency of the Bangladeshi footwear industry, an emerging economy. The strategic drivers are identified after reviewing research papers, reports, blogs, and discussions on social media platforms. The main drivers and their respective sub-drivers are finalized by discussing with domain experts. To offer strategic plans for building resiliency, it is crucial to know the importance of the main drivers and sub-drivers; therefore, the best–worst method is applied to determine the priority importance of the strategic drivers. The findings indicate that the top five drivers to defeat the impacts of COVID-19 are “high capability of reconfigurability,” “enhance the relationship with suppliers,” “develop health protocols to continue manufacturing,” “government support through incentives, subsidy, tax rebate, etc.,” and “set a policy to stable material supply”. Based on the findings, this study also provides practical implications with proposed research themes for policymakers and operations managers towards mitigating the impacts of the COVID-19 pandemic. The study’s contribution is unique and important for the footwear supply chain as the research on COVID-19 in the context of resiliency focusing on the footwear supply chain is non-existent.

Using emerging technologies to improve the sustainability and resilience of supply chains in a fuzzy environment in the context of COVID-19

In rapidly changing business conditions, it has become extremely important to ensure the sustainability of supply chains and further improve the resiliency to those events, such as COVID-19, that can cause unexpected disruptions in the value supply chain. Although globalized supply chains have already been criticized for lack of control over sustainability and resilience of supply chain operations, these issues have become more prevalent in the uncertain environment driven by COVID-19. The use of emerging technologies such as blockchain, Industry 4.0 analytics model and artificial intelligence driven methods are aimed at increasing the sustainability and resilience of supply chains, especially in an uncertain environment. In this context, this research aims to identify the problematic areas encountered in building a resilient and sustainable supply chain in the pre-COVID-19 era and during COVID-19, and to offer solutions to those problematic areas tackled by an appropriate emerging technology. This research has been contextualized in the automotive industry; this industry has a complex supply chain structure and is one of the sectors most affected by COVID-19. Based on the findings, the most important problematic areas encountered in SSCM pre-COVID-19 are determined as supply chain traceability, demand planning and production management as well as purchasing process planning based on cause and effect groups. The most important issues to be addressed during COVID-19 are top management support, purchasing process planning and supply chain traceability, respectively.