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This paper aims to focus on the housing situation in Indian cities and the various stakeholders involved in the housing sector. This study addresses the conflict in expectations of the supply and demand side of the housing and establishes the factors crucial to making housing successful for all the stakeholders, essential for sustainable urban development.

This paper is developed using the content analysis of preceding independent reviews on housing sustainability by authors across the globe, a review of the current housing situation in Indian cities and a Pilot study of the desired qualitative aspects of housing by the consumer group.

This paper identifies the challenges and constraints of the various stakeholders involved in the housing sector. A comprehensive list of all the parameters, both qualitative and quantitative, essential for successful housing implementation, focused on the preferences of the demand side, also referred to as the “Critical Success Factors (CSFs)” is generated. The results advocate a strict consideration and integration of these CSFs with the housing policies for all future housing projects.

Most of the studies conducted in the past have reviewed the housing situation in India from the perspective of the government authorities and the initiatives undertaken by them to improve the housing crisis. However, a gap exists in achieving a balanced understanding of the supply-side constraints, with the demand-side expectations from the housing. Focusing only on the supply without adequately understanding the consumption can only lead to further chaos in the already turbulent housing situation.

To the best of author’s knowledge, this is among the first attempts to address the housing scenario in urban centers of India, simultaneously from the perspective of both the demand side and the supply side of the housing, giving additional impetus to the expectations of the demand side which are often ignored. This study becomes more relevant in the ongoing pandemic situation to be able to provide appropriate and acceptable housing solutions to all.

This study integrates the providers' perspective as well as the patient's perspective in developing and validating a scale to measure hospital service quality in multispecialty hospitals.

An exploratory sequential mixed-method approach was used in this study. The strategies used included a thematic literature review, semi-structured interviews, modified Delphi and confirmatory factor analysis.

The reliability coefficient of 41 item scale was 0.963 with each attribute, that is, pivotal, core and peripheral, having a Cronbach's alpha of 0.907, 0.91 and 0.891, with scale content validity (S-CVI Ave) of 0.9151. The composite reliability scores of all constructs were greater than 0.7, with an Average Variance Explained (AVE) of all items greater than 0.5.

The instrument can be used to measure the difference between what service providers believe customers expect and customers’ actual needs and expectations. The scale can be used to measure the difference between what is delivered (as perceived by the provider) and what customers perceive they have received (because they are unable to accurately evaluate service quality). The dyadic approach of administering this questionnaire in measuring hospital service quality will lead to the identification of a knowledge gap and a perception gap in delivering hospital service quality.

Health care service is a widely researched area. Several established models and instruments measuring health care service quality (HCSQ) are available in the published academic literature. The objective of this article is to summarize this vast pool of available knowledge under the themes of HCSQ, its determinants and measurement strategies.

Sixty-three available published studies in peer reviewed journal combed in EBSCO and Google Scholar database have been examined and presented in exemplary literature review.

The findings have been segregated under the themes of HCSQ, its dimensions and determinants. It can be deduced from the findings that in spite of health care being a professional service, the user defined service quality takes center stage.

Rather than the seeker of care, the authors call for further research by taking a dyadic view of professional exchanges and including providers' perspectives of care in service quality evaluations as well.

Even the greatest developed countries have capitulated to the destructions imposed on the global supply systems, as the COVID-19 pandemic has revealed. The purpose of this study is to explore human resource sourcing strategies for managing supply chain performance during the COVID-19 outbreak. There are six human resource sourcing strategies such as outsourcing, near sourcing, integration, the requirement of suppliers, joint ventures and virtual enterprise that are considered to measure supply chain performance.

Based on collecting data from the potential respondents of Indian manufacturing companies, the elevation of human resource sourcing strategies to supply chain performance is measured considering the multiple regression analysis techniques.

The results of the study revealed that four of the six hypotheses have a significant and positive relationship with supply chain performance during the COVID-19 outbreak while two hypotheses are partially supported that lent good support to this study.

In this critical situation, this study will enable managers and practitioners to support the business in giving customers the best services on time.

The novelty of this study is to identify the key human resource sourcing strategies by using multiple regression analysis methods, considering the case of Indian manufacturing companies to measure their supply chain performance during the COVID-19 outbreak era.

This study aims to identify and prioritize the key practices and strategies for effective global sourcing and supply chain management (SCM).

The study uses a combination of Pareto analysis and multi-objective optimization based on ratio analysis research methodology to analyze and establish the relationships among the identified key practices and strategies. Pareto analysis enables organization to prioritize organizational efforts and resources by focusing on the most critical factors.

The study shows that the “eco-friendly sourcing strategy”, “lean manufacturing” and “tool cost analysis” are the top critical practices and strategy variables for global sourcing and SCM, whereas the “risk management”, “procurement strategy” and “leverage digital solutions” are the critical practices and strategy variables.

The findings of this research can also assist organizations in making informed decisions to optimize their global sourcing and supply chain operations.

By using these methods, this research paper gives valuable insights into the critical practices and strategies that can enhance efficiency, mitigate risks and drive success in global sourcing and SCM. The subjects and elements this study identified will serve as a framework and suggestions for further theoretical investigation and real-world implementations.

The aim of this study is to investigate and clarify how the triple helix actors can effectively implement the concepts of Kaizen to navigate and overcome the complex obstacles brought on by the global COVID-19 pandemic.

Through broad literature reviews, nine common parameters under triple helix actor have been recognized. A regression analysis has been done to study how the triple helix actors’ common parameters impact Kaizen implementation in business operations.

The results of this study revealed insightful patterns in the relationships between the common parameters of triple helix actor and the dependent variables. Notably, the results also showed that leadership commitment (LC) emerges as a very significant component, having a big impact on employee engagement as well as organizational performance.

In addition to offering valuable insights, this study has limitations including the potential for response bias in survey data and the focus on a specific set of common parameters, which may not encompass the entirety of factors influencing Kaizen implementation within the triple helix framework during the pandemic.

The originality of this study lies in its comprehensive exploration of the interplay between triple helix actors and Kaizen principles in addressing COVID-19 challenges. By identifying and analyzing nine specific common parameters, the study provides a novel framework for understanding how triple helix actors collaboratively enhance organizational performance and employee engagement during challenging times.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).

Though academic study on the subject is still in its early stages, there is growing interest in using blockchain technology for transforming the supply chain. The academic literature is divided and yet only includes studies evaluating how the supply chain has changed organizations. To comprehend the new phenomena, this study aims to investigate the factors of blockchain technology in driving supply chain transformation. To be more precise, the authors developed from the literature the most prevalent criteria for determining if supply chain transformations are ready to be scaled up.

This study followed a combination of two multi-criteria decision making methods evaluation based on distance from average solution and complex proportional assessment) methodology in this research: planning, investigating, executing out, establishing a rating of the criteria and evaluating it.

The study shows that the “organizational driver” and the “technology driver” are the factors most important to the transformation of the supply chain, whereas the “financial driver” and the “regulatory driver” are less important. This study also makes some managerial recommendations to address the factors impeding the supply chain’s transformation. Each factor’s significance was explored, and a proposed study agenda was also presented.

Although the main forces behind the transformation of the supply chain have been recognized, further research into statistical correlation is required to confirm how the various elements interact.

This research aids decision-makers in comprehending the key forces behind supply chain transformation. Managers and decision-makers might better predict and allocate the necessary resources to start the road toward digitization and make well-informed choices once these aspects have been investigated and understood.

In light of the pandemic’s effects on the world and the increase in businesses embracing the digital economy, the supply chain transformation is more important than ever. Beyond blockchain deployment and the pilot studies on digital transformation, there is a gap. The topics and factors this study uncovered will operate as a framework and recommendations for more theoretical investigation and practical applications.

With increasing pressure from the government and private sectors to be more environmentally and socially responsible, sustainable supplier selection has gained enormous currency in recent times. Particularly, in the case of the construction industry, owing to a large amount of industrial wastage generated and extreme workplace conditions, it is even more important to devise strategies to mitigate the harmful consequences. The most crucial step in this regard is the selection of sustainable suppliers that acquire a pivotal position in the supply chain ecosystem. This study aims to identify indicators for three criteria such as economic, environmental and social, and prioritize them according to their level of significance for sustainable supplier selection in the Indian construction industry.

In this study, the best-worst method (BWM) is presented for sustainable supplier selection in Indian construction organizations. Total of 27 indicators was identified for the three criteria of the triple bottom line (TBL) approach namely economic, environmental and social. Using BWM, the most important criterion was found and subsequently, all the indicators under each criterion were ranked in order of importance.

The analysis revealed that the environmental criterion was the most important criteria in the sustainable supplier selection followed by the economic criteria. The indicators that were the most influential in the effective selection process were “Usage of recyclable raw materials for production”, “Adoption of clean and green technologies”, “Waste management” and “Periodical environmental audits” under the environmental criteria; “Efficiency”, “Cost” and “Flexibility and Scalability” from the economic criteria; and “Safety programs” and “Information disclosure” in the social criteria.

The study provides a reference framework for the selection of sustainable suppliers in construction organizations. The findings can also be used for the assessment of suppliers' performance in the supply chains.

The novelty of this work lies in its attempt to model the performance of suppliers in the Indian construction supply chains.

This study aims to identify key supply chain challenges and opportunities of the case of Hong Kong toy manufacturing company during the COVID-19 outbreak and develop a comprehensive structural relationship to rank them.

In this study, a toy model company in Hong Kong is considered to discuss about what challenges and opportunities have the biggest impacts on non-necessary goods companies and how to deal with different impacts on entire supply chain flow disruption during COVID-19. A semi-structured interview with five decision-makers from the company was made to give key challenges and opportunities scores. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) technique is used to establish the model and rank them afterward to overcome the challenges.

From the data analysis and results, “salary of employee” and “inconvenient transportation” have emerged as top and bottom key challenges respectively. The sequence of organized challenges in the list needs to mitigate one by one in this order to improve the supply chain performance. The “client's orders’ frequency, customer management” and “supplier/partner relationship management” are identified as the top and bottom respectively to develop the opportunities.

These key challenges and opportunities are identified as contributing attributes and provide the way to measure to improve production, profits and sustainable growth of the toy manufacturing company during a pandemic. Moreover, it helps to improve the distribution level and good planning with appropriate decision making to manage the supply chain performance considering humanitarian aspects during a pandemic outbreak.

The novelty of this study is to identify the key supply chain challenges and opportunities measured by the TOPSIS method to rank them and consider the case of a Hong Kong toy manufacturing company as a case-based approach to measuring its performance during the COVID-19 outbreak.