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The study aims to carry out predictive modeling based on publicly available COVID-19 data for the duration April 01, 2020 to June 20, 2020 pertaining to India and five of its most infected states: Maharashtra, Tamil Nadu, Delhi, Gujarat and Rajasthan.

The study leverages the susceptible, infected, recovered and dead (SIRD) epidemiological framework for predictive modeling. The basic reproduction number R0 is derived by an exponential growth method using RStudio package R0. The differential equations reflecting the SIRD model have been solved using Python 3.7.4 on the Jupyter Notebook platform. For visualization, Python Matplotlib 3.2.1 package is used.

The study offers insights on peak-date, peak number of COVID-19 infections and end-date pertaining to India and five of its states.

The results subtly indicate toward the amount of effort required to completely eliminate the infection. It could be leveraged by the political leadership and industry doyens for economic policy planning and execution.

The emergence of a clear picture about COVID-19 lifecycle is impossible without integrating data science algorithms and epidemiology theoretical framework. This study amalgamates these two disciplines to undertake predictive modeling based on COVID-19 data from India and five of its states. Population-specific granular and objective assessment of key parameters such as reproduction number (R0), susceptible population (S), effective contact rate (ß) and case-fatality rate (s) have been used to generate a visualization of COVID-19 lifecycle pattern for a critically affected population.

The purpose of this study is to examine the association between mall personality, hedonic and utilitarian shopping value, and shoppers' well-being. The moderating effect of compulsive shopping on the association between both hedonic and utilitarian shopping value, and shoppers' well-being is also investigated.

This study is quantitative in nature, and a purposive sampling technique is used. Data was collected through mall intercept survey. The authors collected 431 usable responses from respondents at two different malls in Lahore, Pakistan. PLS-SEM was employed to test the proposed hypotheses.

Results indicate that mall personality significantly and positively influences both hedonic and utilitarian shopping value and shoppers' well-being. Similarly, hedonic shopping value has a significant and positive impact on shoppers' well-being, while utilitarian shopping value has a non-significant relationship with shoppers' well-being. Moreover, while compulsive shopping behaviour moderates the positive relationship between hedonic shopping value and shoppers' well-being, it does not moderate the relationship between utilitarian shopping value and shoppers' well-being.

Despite the extant studies on brand and store personality on numerous retail outcomes, no study has examined the association between mall personality and shoppers' well-being. Another key contribution of this study is to examine moderation effect of compulsive shopping on the association between shopping value and shoppers' well-being. Additionally, this study enlightens mall administration to emphasise upon mall personality and hedonic shopping value so as to enhance shoppers' well-being, more so if its product assortment encourages compulsive shopping.

The paper aims to identify key human and operational focused barriers to the implementation of Total Quality Management (TQM). It develops a comprehensive structural relationship between various barriers to successfully implement TQM for sustainability in Indian organizations.

With the help of expert opinions and extant literature review, we identified the case of TQM failure companies and barriers to implement TQM effectively. Interpretive Structural Modeling (ISM) and fuzzy MICMAC techniques are employed to develop a structural model and the identified barriers are categorized based on their dependence and driving power in the various categories.

From the intensive case analysis, we identify fourteen barriers that constrain the successful implementation of TQM. The findings also provide a hierarchy of barriers in which the absence of top management involvement and ineffective leadership are the human barriers having the highest dependence.

The critical inputs show the implementation of TQM in the firms being more proactive and well prepared in the selected five companies. The study's emphasis on barriers will help organizations in implementing TQM for better sustainability in an organizational context.

In the successful implementation of TQM, barriers need to be identified because failure has often eliminated the organizations from the market. Thus, TQM is the source of strength to achieve higher productivity, profitability, and sustainable business performance. The barriers must be identified to improve organizational performance to contribute to sustainable development.

Employee engagement (EE) continues to be one of the most difficult challenges for organizations today. Numerous factors have been linked to EE, according to studies. However, the necessary human resource management (HRM) strategies and systems for enhancing EE have not yet been developed. It is questionable if all employees inside the company require the same HRM strategies, to boost engagement as one size does not fit all. Therefore, it is necessary to create employee profiles based on factors associated with EE. This study aims to develop employee profiles based on engagement dimensions and outcomes. It seeks to comprehend the relationship between engagement level and factors such as age, years of service and employment grade.

Using latent profile analysis (LPA), we identified five EE profiles (highly engaged, engaged, moderately engaged, disengaged and highly disengaged). These five profiles were characterized by five EE dimensions (Culture Dimensions, Leadership Dimensions, People Process, Business alignment Dimension and Job Dimension) and EE outcomes (Say, Stay and Strive).

The study revealed that Engaged profiles exhibited low stay outcomes. The highest percentage of disengaged employees fall under 25 years of age with less than 5 years of experience and are at the entry level.

The study highlights the significance of the people processes dimensions in enhancing engagement. Profiles with low people process dimensions showed high disengagement. Person-centered LPA adds and complements variable-centered approach to develop a better understanding of EE and help organizations devise more personalized strategies. The study would be of interest to both academics and practitioners.

The novelty of this study lies in its attempt to model the employee profiles to comprehend the relationship between engagement levels using LPA.

This study aims to identify how ICT appeared as an emergent business strategy and to investigate the impact of ICT adoption factors on the perceived benefits of micro, small and medium enterprises (MSMEs).

A total of 393 responses from Indian small and mid-size enterprises (SMEs) were collected for the final analysis. The study presents the partial least-squares structural equation modeling with the Chi-square test and descriptive analysis as a methodology based on numerous independent variables and one dependent variable.

The findings indicate that ICT adoption during and following the COVID-19 pandemic is constant in nature of the enterprise. Moreover, the results indicate that different adoption of ICT factors influence on perceived benefits of organizational performance of Indian MSMEs that lent good support except for the regulatory framework.

The implications of the current research help Indian MSMEs to take investment decisions in various technologies that help the organization. Furthermore, managers and practitioners help the organization in deciding which technology adoption factors are more critical to the betterment of the organization.

The study found certain ICT adoption factors that have a significant role in organizational performance in Indian MSMEs. Moreover, during COVID-19, investigate ICTs' role as a business strategy.

This paper aims to identify, analyze and evaluate the major enablers for the sustainable public distribution system (PDS) supply chain in India in lessening food insecurity by distributing essentials food grains at a subsidized rate.

The major enablers for the sustainable PDS supply chain were explored by conducting the literature survey and discussion with academic and warehouse experts. Then, the fuzzy-DEMATEL (decision-making trial and evaluation laboratory) technique was applied to develop a causal model that analyses the interaction among the identified enablers.

This study recognizes fifteen enablers through literature survey and experts' opinions. The present work concludes that “proper identification of the PDS beneficiaries” and “willingness and commitment of the top management and policymaker” are the two major enablers for the sustainable PDS supply chain.

This work would be helpful for profoundly understanding the major enablers, and how they are affecting the entire PDS supply chain. The study would be beneficial for the general people and the entire society straightforwardly by providing suggestions for food security.

Identifying and analyzing the major enablers for the sustainable PDS supply chain helps to visualize the problem more effectively and efficiently. Besides, the causal model explains a comprehensive perspective on the identified enablers.

This study aims to present a study on the supply chain process of a Myanmar-based pharmaceutical company (named ABC Pvt. Ltd. in this study) that produces pharmaceutical products across Myanmar and aims of bringing quality medical products and best care for Myanmar people’s health. The study aims to identify the key supply chain challenges and manage the opportunities executed by this pharmaceutical company to improve the supply chain process during the COVID-19 outbreak.

This work used a case study and conducted semistructured interviews with the manager, senior managers and senior staff of the ABC Company to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the uncertainties, real-time information and agility in a digital supply chain using grey relational analysis (GRA) method.

From the data analysis and results, “Impact of political factor,” “Delay in import process” and “Weak internet connection,” and “Weak knowledge of the use of digital platform,” “Poor information sharing in online by employees” and “Information flow from top management to operational level” have been identified as top and bottom three key challenges, respectively. “Inventory management,” “Selection of transport method” and “Operational cost”, and “Marketing and brand Innovation,” “Online delivery of products” and “E-commerce enablement (Launching applications, tracking system)” are identified as the top and bottom three managing the opportunities, respectively.

The findings of the study help to supply chain decision-makers of the company in their establishment of key challenges and opportunities during the COVID-19 era. As a leading company, it always tries to add value to its product through a supply chain system, effective management teams and working with skillful decision-making toward satisfying the demand on time and monitoring the supplier performance.

The novelty of this study is to identify the key supply chain challenges and opportunities by the GRA method to rank them, considering the case of Myanmar pharmaceutical manufacturing company as a case-based approach to measuring its performance during the COVID-19 outbreak era. This work will assist managers and practitioners help to the company to provide optimal services to its consumers on time in this critical situation.

A well-designed supply chain performance measurement system, should account for not only the capabilities and performance attributes of the focal firm but also its supply chain partners. The purpose of this paper is to help design a system that strikes a balance between the strategic objectives of the focal firm and its supply partners vis-à-vis the requirements of supply chain performance (cost, quality, speed and customer taste).

A theoretical framework on the strategic supply chain performance measurement system is developed based on existing literature and subsequently tested using a survey on 136 successful manufacturing organizations in India. The organizations were clustered into three strategy types and compared using analysis of variance on ranks to look for differences in preference for performance parameters.

The study examined the five dimensions of the supply chain practices, namely, strategic supply/distribution network, customer relationship, internal operations, information sharing and social and environmental responsiveness. The empirical results demonstrate the inclusion of business strategy orientation in designing today’s supply chain and hence its performance measurement system. Not supported hypotheses were addressed in the light of contextual factors.

The study is confined to finding preferences of non-financial aspects of supply chain performance and tier-1 suppliers. The research helps better design and benchmark supply chain performance metrics, based on the strategic choice of the firm.

This paper highlights the shortcomings in the existing performance measurement and gaps in the existing literature in the supply chain context. Further, it gives a holistic view of strategic supply chain performance measurement design.

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.

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.