Flexibility and Resilience in Corporate Decision Making: A New Sustainability-Based Risk Management System in Uncertain Times

The nonlinear impact of financial flexibility on corporate sustainability: Empirical evidence from the Chinese manufacturing industry

In the face of challenges ushered in by globalization and technological advancements, financial flexibility has emerged as a pivotal strategy for attaining sustainable development in China's manufacturing sector. Financial flexibility allows firms to manage internal cash flows, alleviate external financing constraints, and augment their capability to absorb risks. Using the framework of Financial Flexibility Theory and Institutional Theory, this study examines data from A-share listed manufacturing firms on the Shanghai and Shenzhen Stock Exchanges from 2011 to 2021. The research aims to investigate the nexus between financial flexibility and sustainable performance, while also probing the moderating roles of environmental uncertainty and governmental grants. The key findings of the study unveil an inverted U-shaped relationship between financial flexibility and sustainable performance. Moreover, environmental uncertainty exerts a significant negative influence on sustainable performance. When both environmental uncertainty and governmental grants are substantial, the inverted U-shaped correlation between financial flexibility and sustainable performance intensifies. The innovation of this study lies in revealing the optimal zone of financial flexibility for enterprises under the influence of environmental uncertainty and government grants. Amidst an increasingly intricate macro-environment, this research furnishes pragmatic insights for optimizing sustainable performance in manufacturing enterprises and offers a series of empirically grounded suggestions for enterprise managers, government departments, and investors, guiding them to enhance sustainable performance through judicious calibration of financial flexibility levels.

How can the Sendai framework be implemented for disaster risk reduction and sustainable development? A qualitative study in Iran

BACKGROUND

The Sendai Framework is the United Nations' most significant approach to reducing the risk of disasters from 2015 to 2030. This framework designed for all communities. However, communities should create operational and remedial strategies based on their unique circumstances. Considering the gaps in the implementation of Sendai framework strategies in Iran, as a developing country, the present study was designed.

METHOD

This study was conducted by using a qualitative direct content analysis method to find out the expert's opinions on the implementation of the Sendai framework in Iran from 2021 to 2023. 35 experts in the focus group discussion and 9 experts in the interview were the participants of the study.

RESULTS

Study findings were merged and reported as one main theme entitled Executive actions for implementing the Sendai Framework, four categories, and 37 codes. Eleven codes for the strategy of understanding disaster risk, 11 codes for the strategy of strengthening disaster risk governance to manage disaster risk, eight codes for the strategy of Investing in disaster risk reduction for resilience, and finally, seven codes for the strategy of enhancing disaster preparedness for effective response and to "Build Back Better" in recovery, rehabilitation, and reconstruction were identified as implementation solutions.

CONCLUSION

The Sendai Framework has not provided any detailed implementation solutions because the countries' economic, social, level of development, etc., are different. The study's findings can be used as a guide for other developing countries.

Selection of suppliers using crisp gradual means integral in conjunction with clustering algorithms

It is important for companies to select the right suppliers to deal with in order to avoid any disruptions. Considerable research has been conducted to find the solution for this problem. Previous attempts were made to account for uncertainties and disruptions in decision-making in order to rank suppliers based on different criteria of interest and select the desired resources as needed. This study addresses this issue by grouping suppliers in groups based on their similarities in terms of decision-making standards (criteria). Crisp Gradual Means Integral used in fuzzy analytic hierarchy process is used in conjunction with the clustering technique. By grouping suppliers into clusters, several advantages can be gained by the decisions' maker firms. For example, a firm can determine the level of similarity between different suppliers when taking into consideration all variables of interest to its decision-makers. When computing this similarity, the decision-makers can substitute any of the suppliers with other supplier from the same group in the event of the occurrence of a negative event that prevents the original selected supplier from fulfilling their obligations. •The crisp gradual means integral is a well know approach used in the fuzzy analytics hierarchy processes.•The proposed methodology adapts the crisp means integral and clustering algorithms.•The resulted outcomes group suppliers into groups to help the decision makers select the best supplier.

Knowledge risk management in banks - An area for improving organizational performance

Research on the topic of knowledge risks and their management in organizations is still very scarce, this also applies to empirical studies. However, to avoid the uncritical acceptance of empirical results, replication studies play a crucial role in science. Therefore, this study represents a replication study of the type of empirical generalization of the paper by Durst et al. (2019) which studied knowledge risk management (KRM) in private and public organizations. Considering the KRM and performance assumptions underlying the original study and the methodology used, the results at that time are reviewed using new data from 103 Italian cooperative banks. This paper contributes to the study of risks related to knowledge and its theoretical development by providing new empirical evidence from a different cultural, geographical and institutional context. Furthermore, it emphasizes the importance of replication studies for knowledge accumulation and theory development in management science.

Calculating Strategic Risk in Financial Institutions

Banks face many intangible hazards that are difficult to calculate. Strategic risk is one of the most critical factors affecting a bank's profitability, financial strength, and commercial success. The impact of risk on profit may be insignificant in the short term. Still, it may become highly significant in the medium and long term, with the potential to cause substantial financial losses and impair bank stability. Hence, strategic risk management is an important endeavor that must be carried out according to the rules set out under the Basel II framework. Analysis of strategic risk is a relatively new research enterprise. The current literature addresses the need to manage this risk and links it to the concept of economic capital, the amount of capital that a company should hold to survive such a risk. However, an action plan has yet to be produced. This paper attempts to address this gap by providing a mathematical analysis of the probability and effect of different strategic risk factors. Specifically, we develop a methodology for calculating a metric of strategic risk in terms of a bank's risk assets. Furthermore, we suggest a way of integrating this metric into the calculation of the capital adequacy ratio.

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.

IT Capabilities, Strategic Flexibility and Organizational Resilience in SMEs Post-COVID-19: A Mediating and Moderating Role of Big Data Analytics Capabilities

This research provides a novel progression to the existing research about big data analytics capabilities (BDAC) by investigating and measuring its influence on organizational resilience and strategic flexibility. Toward that end, 400 different SMEs in Saudi Arabia were approached. Data were collected via questionnaire. Results confirm that the ability to handle big data analytics totally mediates the relationship between IT capabilities and strategic flexibility. Big data infrastructure flexibility has a negative effect on strategic flexibility. Big data personal expertise not only negatively affects the relationship between IT capabilities and strategic flexibility but also stimulates and reinforces the relationship between strategic flexibility and organizational resilience. The critical pathway developed and tested the trend to make the organization as an immune system able to make the best of the worst. This implies the urgent need for policymakers and managers to adopt and comprehend the concept of BDAC instead of IT capabilities to define oriented plans specifically formulated for stimulating strategic flexibility and organizational resilience. By adopting the proposed model, SMEs can interact more effectively internally and externally.

Flexible Green Supply Chain Management in Emerging Economies: A Systematic Literature Review

The purpose of this research is to synthesize the fragmented extant knowledge on flexible and green supply chain management (FGSCM) in the context of emerging economies and to unearth research gaps to motivate future research. We adopted a novel structured systematic literature review by triangulating a systematic literature review, text mining, and network analysis. Institutional theory and contingency theory were employed to analyze the results of the review. The results show that, firstly, research on FGSCM in emerging economies, despite its importance, is immature compared to general FGSCM literature. Second, the specificities of strategies and practices that distinguish this topic in emerging economies are discussed and the drivers and barriers are identified with respect to sources of institutional pressure. Third, a research framework for FGSCM in emerging economies is developed and 12 gaps for future research are identified. This study has exclusively developed a research framework for FGSCM in an emerging economy which has received the least consideration in the literature and practice. The framework was developed to synthesize the existing literature and to identify the research gaps to inspire future research.

Towards the circular economy in the fashion industry: the second-hand market as a best practice of sustainable responsibility for businesses and consumers

The transition to a circular economy is a key concern for the fashion industry. The emerging second-hand market is a practice that could enable the circular economy in the fashion industry. As this is an emerging trend, the literature has not yet sufficiently explored how it is possible to simultaneously meet consumer and industry expectations in the management of second-hand garments within the value chain. This article aimed to fill that gap with the analytic hierarchy process, which demonstrated that garment collection and recycling are not necessarily best practices for the circular economy. For this to happen, close collaboration between manufacturers and retailers in the value chain is needed to move the industry towards responsibly sustainable production and consumption models. The results emphasise that harvesting management and internal competition on low-cost collection are critical business drivers, while responsible consumption and benefits are opportunities for consumers.

Engineering Education Understanding Expert Decision System Research and Application

Engineering education is based on technical science and aims at training engineers who can transform science and technology into productive forces. In recent years, due to the emergence of new technology revolution, engineering science and production technology have achieved new development, and higher engineering education is also facing new challenges. Engineering education is to cultivate talents in an international environment and update the traditional engineer training model from the aspects of educational philosophy, mode, goal, approach, and means. The author believes that in the process of exploring the new talent training model, we must first change the educational concept and correctly understand and deal with various relationships in engineering education. To solve various decision-making problems in engineering construction, this study introduces the concept of engineering education certification under the background of new infrastructure and engineering education certification, analyzes the current situation and existing problems of engineering education understanding in recent years, and carries out reform and exploration from different aspects. The achievements in engineering education are analyzed. The engineering education project is analyzed and researched using the engineering decision-making scheme. It can be seen from the experimental analysis that the method has a good effect.

Internet of Things Device Identification Algorithm considering User Privacy

The Internet of Things has become the third wave of the information industry and cloud computing, big data, and Internet technologies. Among the many identification technologies used in the Internet of Things, radiofrequency identification technology is undoubtedly one of the most popular methods today. It is replacing the traditional contact IC card and becoming a new trend of smart cards. At the same time, a large amount of data is generated in the IoT environment. A lot of data involve user privacy, and users do not have good control over these data. Collecting and utilizing these data on the basis of protecting user privacy have become an important problem to be solved urgently. With the implementation of the strategy of rejuvenating the country through science and education, major colleges and universities are developing rapidly through enrollment and expansion, which also brings inconvenience to campus security management. Although the traditional campus all-in-one card system can guarantee the security identity of people entering and leaving, it does not reasonably integrate and utilize this information, resulting in waste of information resources and, to a certain extent, the problem of user privacy leakage. To solve the above problems, a new system was developed to integrate resources to identify users. To protect the privacy data of Internet of Things users, a specific solution using blockchain technology is proposed; for the identity authentication problem of Internet of Things users, the identity authentication based on the public key address of the blockchain is used on the chain, and the group signature is used off the chain. The identity authentication method solves the contradiction between anonymity and traceability in blockchain application scenarios. The simulation results show that the system not only considers user privacy but also has extremely important practical significance for the promotion of Internet of Things and RF applications.

Research on the Mining of Intangible Cultural Heritage Digital Resources in the Manual Online Teaching System of Preschool Education

Our country's international status as a cultural power has been further enhanced, and the protection of intangible cultural heritage containing the essence of traditional culture is also gradually being carried out. In addition, with the rapid development of the digital environment, the public's cultural needs continue to grow, and the contradiction between the supply and demand of public digital cultural services continues to intensify. Converting intangible cultural heritage into digital form for protection and providing resource services for the public has become an important trend in the protection and inheritance of intangible cultural heritage at home and abroad, and it is also an inevitable requirement to solve the contradiction between supply and demand. Improving public cultural services is one of the key projects. At present, our country's research and practice of intangible cultural heritage digitization and services are also in progress, but there is no research on intangible cultural heritage digital resource services and system construction from the perspective of information service elements. Based on the digital resource service of intangible cultural heritage, the manual course is one of the main skill courses for preschool education majors. At this stage, the short class hours of manual courses, the lack of class hours, the low utilization rate of teaching materials, and the disconnection between the content and the needs of the kindergarten are all problems that need to be solved at present. Just relying on cross-references between schools, the manual knowledge and skills mastered by graduates are not comprehensive enough to complete the manual tasks assigned by the kindergarten. This paper implements the concept of intangible cultural heritage and hopes that by studying the manual knowledge and skills that today's kindergarten teachers need to possess, the content of existing manual courses can be adjusted in a targeted manner, so that the electronic culture dissemination of manual curriculum resources for preschool education is more reasonable, meeting the requirements of kindergarten teachers in terms of manual knowledge and skills.

A Method for Prediction the Trajectory of Table Tennis in Multirotation State Based on Binocular Vision

The research on the space trajectory of high-speed moving and flying objects has very important research significance and application value in the fields of sports, military, aerospace, and industry. Table tennis has the characteristics of small size, fast flight speed, and complex motion model. It is very suitable as an experimental object for the study of flying object trajectory. This study takes table tennis as the research object to carry out research on the trajectory prediction of flying objects and builds a trajectory prediction system based on the trajectory prediction model, combining the constraints of the simple physical motion model and the deviation correction of the double LSTM neural network. Aiming at the problem of trajectory extraction of flying table tennis balls, a high-speed industrial camera was used to build a table tennis trajectory extraction system based on binocular vision. A multicamera information fusion method based on dynamic weights is proposed for the prediction of the trajectory of flying table tennis. In order to solve the problems that some model parameters are difficult to measure and the model is too complicated in the traditional physical motion model of table tennis trajectory, a method combining simple physics is proposed. This paper proposes a trajectory prediction model with motion model constraints and dual LSTM neural network bias correction. Experiments show that the proposed method can greatly improve the accuracy of the trajectory extraction and prediction system and can achieve a certain success rate of hitting.

Social Organizational Life Cycle Assessment (SO-LCA) and Organization 4.0: an easy-to-implement method

Organizations often face difficulties when measuring their social performance. The lack of international standards, the qualitative/quantitative nature of data, and the unavailability of primary sources all hinder social impact assessments, especially in manufacturing settings. To fill these gaps, the method proposes a simple application protocol of Social Organizational Life Cycle Assessment (SO-LCA), customized for an Italian ceramic tile manufacturer. The method leverages Industry 4.0 digital technologies to collect real-time primary and site-specific social data, making the social assessment dynamic. The managerial approach adopted for the selection of social metrics and weighting of indicators and indexes, can support the transition of the manufacturing organization into Organization 4.0. The method also provides a contribution to the operational validation of the UNEP guidelines by extending their area of application. Finally, the proposed method gives substance to social responsibility through social accounting, helping the organization to measure the correct social impact starting from the detailed data, namely the decisions made in the business and in production.•

Social Organizational Life Cycle Assessment (SO-LCA) application protocol validated in Industry 4.0 environment.

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Social metrics directly linked to production and business processes for the dynamic assessment of social performance.

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Easy replicability of the method in other organizational contexts.

Research on Keyword Extraction Algorithm in English Text Based on Cluster Analysis

How to facilitate users to quickly and accurately search for the text information they need is a current research hotspot. Text clustering can improve the efficiency of information search and is an effective text retrieval method. Keyword extraction and cluster center point selection are key issues in text clustering research. Common keyword extraction algorithms can be divided into three categories: semantic-based algorithms, machine learning-based algorithms, and statistical model-based algorithms. There are three common methods for selecting cluster centers: randomly selecting the initial cluster center point, manually specifying the cluster center point, and selecting the cluster center point according to the similarity between the points to be clustered. The randomly selected initial cluster center points may contain “outliers,” and the clustering results are locally optimal. Manually specifying the cluster center points will be very subjective because each person’s understanding of the text set is different, and it is not suitable for the case of a large number of text sets. Selecting the cluster center points according to the similarity between the points to be clustered can make the selected cluster center points distributed in each class and be as close as possible to the class center points, but it takes a long time to calculate the cluster centers. Aiming at this problem, this paper proposes a keyword extraction algorithm based on cluster analysis. The results show that the algorithm does not rely on background knowledge bases, dictionaries, etc., and obtains statistical parameters and builds models through training. Experiments show that the keyword extraction algorithm has high accuracy and can quickly extract the subject content of an English translation.

Characterizing Organizational Lifecycle through Strategic and Structural Flexibility: Insights from MSMEs in Mexico

Today's lifespan of companies tends to be low in the so-called micro-, small-, and medium-sized enterprises (MSMEs). Organizational life cycle (OLC) theory indicates that organizational aging is related, but not determined, by the firm chronological age or its size. Therefore, a firm's aging should be analyzed by other factors such as flexibility. The literature considers flexibility as an essential capability, a source of competitive advantage, and an enabler of long-term growth for MSMEs. However, little attention in emerging economies has been paid to examine the nuances of this concept in relation to the OLC in this type of companies. Additionally, studies tend to analyze flexibility as a general term, ignoring that it is a polymorphic concept. That is why there is a need to research the different categories of flexibility. Drawing on a quantitative approach conducting a factor analysis, a two-step cluster, and decision tree analysis to interrogate data from 257 MSMEs in Mexico, this study provides evidence of different dimensions of strategic and structural flexibility that help to characterize and predict the growth, maturity, and declining stages of MSMEs. Our results show that mature firms present more strategic and structural flexible characteristics than those involved in growth or decline stages. The flexible factors that help classify and predict an MSME in the maturity stage include open communication, decentralized decision making, and formalization. We provide a model with these results to illuminate unaddressed issues regarding the broad term of flexibility and its relationship to OLC.

Analysis of factors impacting firm performance of MSMEs: lessons learnt from COVID-19

Purpose

The micro, small and medium scale enterprises (MSMEs) faced various challenges in the ongoing COVID-19 pandemic, making it challenging to remain competitive and survive in the market. This research develops a model for MSMEs to cope with the current pandemic's operational and supply chain disruptions and similar circumstances.

Design/methodology/approach

The exhaustive literature review helped in identifying the constructs, their items and five hypotheses are developed. The responses were collected from the experts working in MSMEs. Total 311 valid responses were received, and the structural equation modeling (SEM) approach was used for testing and validating the proposed model.

Findings

Critical constructs identified for the study are-flexibility (FLE), collaboration (COL), risk management culture (RMC) and digitalization (DIG). The statistical analysis indicated that the four latent variables, flexibility, digitalization, risk management culture and collaboration, contribute significantly to the firm performance of MSMEs. Organizational resilience (ORS) mediates the effects of all the four latent variables on firm performance (FP) of MSMEs.

Practical implications

The current study's findings will be fruitful for the manufacturing MSMEs and other firms in developing countries. It will enable them to identify the practices that significantly help in achieving the firm performance.

Originality/value

The previous researches have not considered the effect of “organizational resilience” on the “firm performance” of MSMEs. This study attempts to fill this gap.

Flexibility and Adaptation: Creating a Strategy for Resilience

Civil society actors engaged in social innovation supporting activities provide crucial services that address unmet social needs and empower communities. Yet, creating a resilient framework that not only supports their activities but helps to sustain them as an organization is often difficult. It necessitates resilience strategies that help them survive and overcome crises even without former institutionalization. The paper identifies three distinct strategies that can be followed: adaptability, diversification and ecosystem building. While all three represent different ways of resilience, the latest provides the most complex safety net, allowing bottom-up organizations and partnerships to share resources, develop complementary services and sustain social innovation. Choosing the time of the first COVID-19 pandemic and the ensuing lockdown for the analysis, the paper illustrates with eight selected case studies how these strategies enfold during a crisis. The paper analyses the activities of different civic initiatives, gauging their capacity to adapt flexibly to radically new situations. While doing so, it brings together the concept of social innovation and resilience and enriches resilience studies with a less frequently found focus on small, civic initiatives.

New Strategies to Explain Organizational Resilience on the Firms: A Cross-Countries Configurations Approach

Organizations need to develop their resilience to foster future success to survive complex environments. This research conducts a comparative analysis to understand firms’ strategies in a “black swan” event. We use the “strategy tripod” to operationalize resilience theory and explain the configurations or pathways that lead to high organizational resilience in a crisis context. The data correspond to 1936 firms drawn from the “Enterprise Survey 2020 for Innovation and Entrepreneurship in China (ESIEC)”, and to 66 Central American firms drawn from the “World Bank 2020 Enterprise Surveys” are also analyzed. The methodological approach fuzzy set qualitative comparative analysis (fsQCA) is applied. We discuss and analyze the strategies of companies in this “new normal”; our results establish that in the case of emerging economies, organizational innovation seems to be a necessary condition for becoming an organizational resilience to a black swan crisis (finding from both cases). We also found that labor flexibility and emotional intelligence for the case of firms from China, and adequate control of the turbulence environment for the cases of Central America, were also necessary conditions for each region. We further argue that digitalization depends on access to government support for its success. China reinforces its strategies in an intensification of human resources flexibility. In addition, they are better prepared for the “black swan” crisis, allowing them to adapt quickly and generate business model innovation to mitigate the effects of the pandemic in this “new normal.” In contrast, Central America needs rapid organization for organizational resilience.

Reflective backward analysis to assess the operational performance and eco-efficiency of two industrial districts

Purpose

The best strategy to apply for the future cannot disregard a careful analysis of the past and is the one capable of seizing opportunities from outside. Manufacturing sectors are characterized by sudden changes, and in this work, we analyze the ceramic tiles sector characterized by a mature technology in which innovation has played a key role.

Design/methodology/approach

This study aims to provide a sectorial analysis based on a historical data set (2004–2019) to highlight how an industry is performing both operationally and in terms of eco-efficiency. For this purpose, from a methodological point of view, the data envelopment analysis (DEA) was used.

Findings

The results of the analysis show that the Spanish ceramics industry shows a growing economic trend by taking advantage of lower industrial costs, while the Italian industry is characterized by a modest decline partially mitigated by exports. The industrial districts are an aggregation of companies that in the ceramic sector has allowed to combine innovation, sustainability and digitalization and is a model toward the maximization of sustainable efficiency because it is a place of aggregation of resources and ideas.

Originality/value

This study experiments with an innovative way of addressing traditional industry analysis, namely, integrating the reflective management approach with DEA-based backward analysis. This provides decision makers with the basis for new interpretations of variable trends.

Assessing regional performance for the Sustainable Development Goals in Italy

The monitoring report on progress towards the Sustainable Development Goals (SDGs) in a global context involves a large number of actors as it represents probably the biggest change that our society is implementing. Actions at all levels, from local, regional and national to the aggregation of multiple countries (e.g. EU 27) are needed to achieve a sustainable future. This work focuses on a national perspective (Italy) where multi-criteria decision analysis (MCDA) is used to measure current performance. A sustainability score for each region is calculated from a set of 175 indicators contained in all 17 SDGs. Additionally, sustainability scores are disaggregated along the three pillars – social (1–5, 10, 16, and 17), environmental (6, 13–15) and economic (7–9, 11, and 12). The results highlight the positive performance of northern regions and, in particular, of Trentino Alto Adige, which ranks first in the two considered scenarios. In addition, the relevance of territorial specificities emerges for which the analysis of individual SDGs shows different leading regions. It is noteworthy to highlight the performance of the environmental sub-group of SDGs in southern regions, in contrast to the social and economic sub-groups. Evidently, policy actions are needed to reduce the long-lasting North/South divide—yet the highlighted heterogeneous sustainability performance along the three dimensions calls for well targeted policy measures necessary to regain competitiveness at a European and global level, without compromising with environmental sustainability.

Design Optimization of a HAZMAT Multimodal Hub-and-Spoke Network with Detour

The growing transportation risk of hazardous materials (hazmat) is an important threat to public safety. As an efficient and reliable mode of transportation, the multimodal hub-and-spoke transport network helps to achieve economies of scale and reduce costs. Considering the dual goals of risk and cost management of hazmat transportation, a novel optimization model of a multimodal hub-and-spoke network with detour (MHSNWD) for hazmat on the strategic level is designed. It integrates the planning of hub location and route selection based on the risk quantification for different transportation modes. Additionally, a detour strategy is applied, which allows for more than two hub nodes to be selected to form an optimal path between any supply and demand nodes in a hub-and-spoke network. Then, the risk is taken as the main objective and the cost is converted into a budget constraint to solve the model by using CPLEX. Additionally, a numerical study is conducted based on a CAB dataset to find the influence of the number of hubs and budget constraints on the optimization results. In addition, a counterpart model of the multimodal hub-and-spoke network without detour (MHSNOD) is tested to validate the advantages of the proposed model of MHSNWD. The numerical experiment shows that an appropriate increase in the number of hubs and the cost budget can remarkably reduce network risk. Compared with MHSNOD, the optimal result of MHSNWD can achieve a marginal improvement in risk reduction. This work may provide an informative decision-making reference for planning a hazmat transportation network.

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

The COVID-19 pandemic has severely impacted the global social sustainability of the supply chains, pushing them towards a more flexible management approach. However, there is a paucity of literature that focuses on social sustainability issues for emerging economies. In the post-COVID-19 period, firms around the world will face several critical challenges to social sustainability, which will hinder achieving sustainable development goals (SDGs). Against this backdrop, this study identifies the pressing challenges to social sustainability in the post-COVID-19 context by a literature review and opinions from an expert panel, focusing on the footwear supply chain. In this paper, the best–worst method is applied to compute the criticality of social sustainability challenges towards the flexibility of the supply chains. The study findings reveal that among the nine identified critical challenges, “high level of lay off”, “health protocol development”, “complexity in ensuring workplace safety”, “facing trouble in mental health”, and “lack of government enforcement and regulations for social issues” are reported as the top five challenges, respectively. Furthermore, this study suggests several flexible managerial guidelines, which will help practitioners and policymakers to achieve SDGs considering the COVID-19 pandemic.

Industry 4.0 and Smart Data as Enablers of the Circular Economy in Manufacturing: Product Re-Engineering with Circular Eco-Design

The digital transformation of manufacturing firms, in addition to making operations more efficient, offers important opportunities both to promote the transition to a circular economy and to experiment with new techniques for designing smarter and greener products. This study integrates Industry 4.0 technologies, smart data, Life Cycle Assessment methodology, and material microstructural analysis techniques to develop and apply a circular eco-design model that has been implemented in the Italian ceramic tile manufacturing industry. The model has been initially adopted in a simulation environment to define five different scenarios of raw material supply, alternative to the current production one. The scenarios were then validated operationally at laboratory scale and in a pilot environment, demonstrating that a proper selection of raw material transport systems significantly improves the environmental performance of the ceramic product. Both the results of the laboratory tests and of the pre-industrial experiments have demonstrated the technological feasibility of the solutions identified with circular eco-design, enabling the re-engineering of the ceramic product as the fifth of the 6Rs of the circular economy.

Addressing the Challenges to Sustainable Initiatives in Value Chain Flexibility: Implications for Sustainable Development Goals

The value chain refers to the source of competition to facilitate organizations to maximize and sustain value for their consumers. Value chain flexibility is necessary to build sustainable initiatives in addressing ambiguity. In the literature, there is a lack of framework to highlight the challenges to sustainable initiatives in value chain flexibility. This study fills this research gap by suggesting a framework for challenges to sustainable initiatives in value chain flexibility. In this study, thirteen potential challenges to sustainable initiatives in value chain flexibility are identified and an integrated model is developed. It adopts the modified Total Interpretive Structure Model and the Cross-Impact Matrix Multiplication Applied to Classification methodology. The mixed approach is used as the modified Total Interpretive Structure Model organizes the binary interactions among the challenges, while Cross-Impact Matrix Multiplication Applied to Classification analysis organizes specific precise assessments of the driving power and dependence of the challenges. The results of the study reflect that (i) lack of supplier commitment to sustainable products and (ii) lack of knowledge toward sustainability in value chains are the challenges that achieved the highest driving power. The challenge ‘inadequate communication among the suppliers in the value chain’ is at the highest level in the analysis. The proposed framework could help government and non-government bodies to formulate policies to efficiently address challenges to sustainable initiatives in value chain flexibility.