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This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

Nowadays, many firms are finding ways to enhance the survivability of sustainable supply chains (SUSSCs). The present study aims to develop a model for the SUSSCs of small and medium enterprises (SMEs) during the COVID-19 pandemic.

With the help of exhaustive literature review, constructs and items are identified to collect the responses from different SMEs. A total of 278 complete responses are received and 6 hypotheses are developed. Hypotheses testing have been done using structural equation modeling (SEM).

Major constructs identified for the study are supply chain (SC) performance measurement under uncertainty (SPMU), supply chain cooperation (SCCO), supply chain positioning (SCP), supply chain administration (SCA), supply chain feasibility (SCF) and the SUSSCs. From statistical analysis of the data collected, it can be concluded that the considered latent variables contribute significantly towardsthe model fit.

The present study contributes to the existing literature on disruptions and survivability. The study can be further carried out in context to different countries and sectors to generalize the findings.

The research findings will be fruitful for SMEs and other organizations in developing strategies to improve survivability during uncertain business environments.

The study has developed a model that shows that the identified latent variables and their indicators contribute significantly toward the dependent variable, i.e. survivability. It contributes significantly in bridging the research gaps existing in context to the survivability of SMEs.

The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.

The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.

The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.

This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.

The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

Reverse supply chain (RSC) is one of the ways to handle product returns efficiently. Recovery of residual value from product returns also helps in achieving sustainability. Its successful implementation requires coordination among all the channel members involved in the activities, from the acquisition to collection to the disposition of returned products. This article aims to review the literature about coordination issues in the RSC.

A systematic literature review of 151 articles published during 2004–2021 is carried out. Theory, context and methodology (TCM) framework of the literature review is used to identify the research gaps for future research directions.

This study identifies the characteristics of RSC coordination. It includes channel structures; coordination mechanisms; performance measuring parameters; the methodology applied and explored industries. The review shows that game-theoretical modeling in RSC coordination is the most commonly used method to coordinate the channels. It was found that issues like disruption, fairness and corporate social responsibility are not explored in-depth and offer much potential for future research.

There are very limited studies on coordination issues in the RSC. The proposed articles add value by considering RSC issues from different strategic, government, consumers' behavior and functionality decision-making point of view.

This paper aims to prioritize the factors for the successful implementation of total productive maintenance (TPM).

The technique used for prioritization is the analytical hierarchy process (AHP).

The commitment and involvement of the top management, i.e. the leadership team, is the most critical success factor in the successful implementation of TPM. Employee training is another vital factor. Top management should also encourage a culture favorable for information flow, equipment ownership, the involvement of people and quality management throughout the organization.

Manufacturing organizations interested in improving productivity through the implementation of TPM should first involve the leadership team and seek their full support and train all the employees in this philosophy. However, the findings cannot be generalized for global application due to the inputs taken from experts in AHP from limited geography.

Reducing production costs is a universal expectation of business leaders. TPM can be used as a long-term strategy to improve productivity by the organization.

All employees have to be trained in this philosophy, and as part of the training and the implementation of TPM, they feel empowered and committed to the organization.

This study has illustrated the use of AHP for the prioritization of success factors. Prioritization of success factors will help in strategy formulation by management for effective maintenance. It will help in improving the productivity and performance of the organization.

In the present scenario of global competition and economic recession, most of the organizations are facing tough challenge to survive in the market because of shortening product life cycle and reducing profit margin. Customers are seeking better design, production and delivery, which have made firms to concentrate on flexibility in supply chains. Therefore, the purpose of this study is to identify major factors and develop a suitable framework for flexibility in supply chains.

Based on literature review, about 14 factors have been identified. To develop relationship among these factors, a team of five experts from industry and academia was formed. Based on inputs from experts, different relationships are developed among factors to form structural self-interaction matrix (SSIM). Based on this matrix, a flexibility framework is developed by interpretive structural modelling approach.

Top management commitment, strategy development for flexible SC, application of advance technology and IT tools, information sharing in SC members, trust development among supply chain members have emerged as major driving factors. Logistics and warehouse management, suppliers flexibility, distribution flexibility and manufacturing flexibility have emerged as dependent factors.

Framework developed in this study is based on interpretive structural modelling. This framework can be further validated with some case analysis and empirical findings.

Findings of the study can be useful for industry professionals to develop strategies for flexible supply chains. It will help them in taking new initiatives for making supply chains more responsive and proactive for customers demand.

Sustainable mobility will be the key to the survival of mankind in the 21st century. Cities with debt-ridden and poorly managed transport systems have to change to the ever-growing demands of the public transport system. The low cost of transport has been a key factor in sustainable development for any city. This study is trying to propose a framework for the selection of sustainable transport in context to an Indian case of NCR Delhi, India.

The present study has identified eight criteria for the selection of a sustainable transport system. Criteria for selection of sustainable transport are CO₂ emissions, cost of fuel, energy efficiency, cost of maintenance, number of accidents, congestion, number of injuries and road noise. Three alternatives of transport considered for this study are state-run bus, pooled car and Shuttl (App-based buses). The analytic hierarchy process (AHP) is used to prioritize the criteria. The study has further illustrated a framework for the selection of sustainable transport based on these criteria.

It is observed that CO₂ emissions are the most important criterion for a sustainable transport system. It is followed by a reduction in congestion and the number of injuries. Three alternatives of transport considered for this study are state-run bus, pooled car and Shuttl (a service provider). Shuttl has been found to be the most sustainable transport system.

AHP is not able to capture the vagueness in decision-making. Therefore, fuzzy AHP can be considered for further detailed analysis as future scope of study in a different context of a sustainable transportation system. Major implications for policymakers and stakeholders are that development of public transport in cities should be done after considering different dimensions of sustainable operations.

The study has proposed a unique framework for the selection of a sustainable transport system by the public based on sustainability criteria. Findings will help policymakers in formulating strategies for developing sustainable transport system.

Manufacturing industries are facing dynamic challenges in today’s highly competitive world. In the recent past, integrating Industry 4.0 with the lean six sigma improvement methodologies has emerged as a popular approach for organizational excellence. The research aims to explore and analyze critical success factors of lean six sigma integrated Industry 4.0 (LSSI).

This research study explores and analyzes the critical success factors (CSFs) of LSSI. A three-phase study framework is employed. At first, the CSFs are identified through an extensive literature review and validated through experts’ feedback. Then, in the second phase, the initial list of CSFs is finalized using the fuzzy DELPHI technique. In the third phase, the cause-effect relationship among CFSs is established using the fuzzy DEMATEL technique.

A dyadic relationship among cause-and-effect category CSFs is established. Under the cause category, top management commitment toward integrating LSSI, systematic methodology for LSSI and organizational culture for adopting changes while adopting LSSI are found to be topmost CSFs. Also, under the effect category, organizational readiness toward LSSI and adaptability and agility are found to be the uppermost CSFs.

The study offers a framework to understand the significant CSFs for LSSI implementation. Insights from the study will help industry managers and practitioners to implement LSSI and achieve organizational excellence.

To the best of the authors’ knowledge, CSFs of LSSI are not much explored in the past by researchers. Findings will be of great value for professionals in developing long-term operations strategies.

This study has analyzed strategic issues in implementing advanced manufacturing technologies (AMTs) in manufacturing organizations in India and their relative importance.

A survey of manufacturing organizations was conducted, and the data were analyzed using statistical tools (one-sample t-tests, correlation and regression analyses).

Improvement in product quality and flexibility of operations are the motivation for AMTs implementation. Top management support and sound financial conditions are essential for implementing AMTs. Successful implementation of AMTs helps in reducing the lead time and improving overall business performance.

The findings of this study will help organizations in the implementation of AMTs for improving productivity and business performance. The study is limited to manufacturing organizations in India.

Organizations should allocate sufficient funds for AMT applications. Organizational culture should be made conducive to the adoption of new technologies. Employees should be provided adequate training for its successful implementation.

The main contribution of this paper is that it provides a detailed analysis of strategic issues for implementing AMTs in manufacturing organizations.