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The study aims to present demand chain management (DCM) modeling of Indian apparel retailers. This will result in a structured model presenting contextual interrelationship among DCM variables so that retailers can proactively manage their demand chain.

The research follows an exploratory research design. It initially involves identification and analysis of influential factors of the implementation of DCM practices through the review of literature. Then, these variables were analyzed using total interpretive structural modeling or TISM followed by a statistical verification and case-based validation of the model.

The major findings of the paper are: top-management commitment and support, information management and supply chain agility in supply chain are the most significant enablers with the highest driving power. The other apparel retail specific significant variables are assortment planning, category management and marketing orientation. The model also indicates that the firms that implement customer-centric DCM practices do well in terms of organizational performance and thereby achieve differential advantage over their competitors.

Because the literature on DCM is still in nascent stage, the study bases itself on interpretive method; that is, TISM of analysis with a limited number of experts. Future studies may consider larger sample with more advanced statistical tools such as structural equation modeling for further validation of the findings.

The novelty of the paper lies in the study of an emerging supply chain philosophy; that is, DCM and its key practices per se. It has rarely been studied from the theory building perspective hitherto. Moreover, TISM-based approach is applied for the first time to study the DCM practices and its drivers vis-à-vis dependents.

The main objectives of this study are (1) to identify the determinants of pre- and post-adoption dynamics of mobile wallets (m-wallets) usage; (2) to propose and test the linkage framework of pre-adoption and post-adoption dynamics to understand consumers' psyche of m-wallets usage and (3) to examine the moderation of select demographic variables in the path of consumers' continued usage of m-wallets.

The study considered a cross-sectional approach using a questionnaire survey method. The research model encapsulating pre- and post-adoption dynamics of the m-wallet was examined using a sample of 574 users. The analysis also comprised mediation, moderation and multi-group analysis (MGA).

The results identified key antecedents of confirmation, such as performance expectancy, effort expectancy, facilitating conditions and individual mobility. Findings also confirmed the partial mediation effects of satisfaction between confirmation and continuance intentions. Results also confirmed the moderating effects of age and education on the relationship between confirmation and satisfaction.

The key contribution of the study is in the form of research progression related to m-wallet usage to test the extended expectation-confirmation model (EECM) in the Indian context by linking the pre-adoption paradigm of extended (unified theory of acceptance and use of technology) UTAUT with individual mobility and post-adoption dynamics of the ECM. The considered framework study also draws support for the role of select demographic variables.

The purpose of this study is to explore the advantages and obstacles of implementing Lean Six Sigma in Indian MSMEs during or post-COVID-19. The following research also elaborates on the challenges of implementing Lean Six Sigma in MSMEs in India, along with the changes in the culture that are required for providing a proper climate to ensure success in a long-term manner.

The methodology used in this study is a descriptive study, which explores and looks for the factors that influence the impulse or motivation to implement Lean Six Sigma in MSMEs and factors that inhibit the implementation of Lean Six Sigma. To achieve this goal of Lean Six Sigma, a significant review of the existing literature of the subject area has been done to prepare a framework with the help of inferential statistics in view of the critical success factors. This research is a flow and arranged a type of survey of organizations that is conducted using MS-Excel and SPSS 25.0 statistical software. The number of participants selected using a purposive sampling method in this study was 127 Lean Six Sigma experts and owners or CEOs of MSMEs in India.

Lean Six Sigma be used for facilitating the improvement processes in manufacturing operations, quality improvements and productivity. As some obstacles exist in implementing the Lean Six Sigma approach, the improvement processes and outcomes of change in the culture are noteworthy and worthwhile. The implementation of Lean Six Sigma has also some constraints, including cost limitations, skill limitations, limited facilities and other such limitations. The implementation of Lean Six Sigma during COVID-19 is not yet a matter of urgency or priority, and hence, cannot yet be applied.

This paper presents opinions of only a few selected professionals of Indian MSMEs. So it was a crucial aspect of capturing the views of such practitioners of their arrival on valid and sound conclusions.

The novelty of this research is to analyze the advantages and obstacles of implementing Lean Six Sigma in MSMEs during the COVID-19 in India. The results of this research can be used as scientific references for researchers who will conduct future research. Moreover, it can be guidance for MSMEs owners to make decisions in implementing Lean Six Sigma during the COVID-19 pandemic. The organizations assess all of their aspects such as perceive objectives, required qualities and shortcomings for fruitful implementation of any practice.

Several suggestions were made for the methods and thoughts, which will constitute a Lean Six Sigma organization. Hence, the research offers an excellent framework for both working professionals and academicians to understand the view of Indian MSMEs along with their benefits and obstacles of implementing Lean Six Sigma. So this study helps in laying out a platform for understanding the uses of Lean Six Sigma for process excellence in a new era due to COVID-19.

Organizations are realizing the fact that it takes more than quality, cost, and delivery commitments to ensure survival. Organizations are recognizing the need for extra efforts in terms of ability to adjust quickly and effectively to demand fluctuations as well as product diversification according to the requirement of customer. The remedy, to face and come out as winner from this critical scenario, is the adoption of lean approach. The paper tries to trace the evolution of lean approach with an effort to re‐define the efficiency and effectiveness parameters under lean thinking. The paper also deals with the underlying principles of lean approach. The main objective of this paper lies in our proposed model, which shows the scope of SCM under lean operations. Finally, the paper exposes the benefits of lean approach at different levels of organization and customers.

The purpose of this paper is to assess the role of National Rural Health Mission (NRHM) in reducing Infant Mortality in India. The study will help the government in deciding its future course of action regarding the infant mortality rate (IMR) reduction in India.

This paper adopts the interrupted time series analysis (ITSA) approach with a control group to study the role of NRHM in reducing the IMR in India. The authors examined infant mortality in rural areas of India for the level and trend change before and after the implementation of NRHM. The authors then applied a suitable ARMA model to estimate the coefficients of the regression model. From the estimated results, the study predicts the counterfactuals for both the rural IMR and urban IMR and plots the results.

The study found the evidence supporting the hypotheses that the NRHM has led to a reduction in the difference between urban IMR and rural IMR. The research shows that the rural IMR declined at steeper rates in the post-NRHM period (2005–2015).

None of the existing studies analyses the impact of a social scheme like NRHM on the reduction of IMR in India by applying the ITSA. The study is unique as it estimates the counterfactuals and plots the results which show the impact of NRHM on reducing IMR.

This study aims to explore a paradigm for using servitization in circular supply chains, with research fields including smart, sustainable supply chains, circular economy, innovation, digital technology, product service systems and sustainability as focal areas.

A comprehensive statistical analysis of the literature on servitization, circular economy and smart supply chains reveals the history of the industry, including scholarly work, major concerns and future research prospects. The database for the analysis is provided by Scopus. Consequently, 288 research articles were reviewed, and the research trends of servitization, circular supply chains and smart supply chains from 2014 to 2022 (Q1) were covered.

The analysis reconnoitres bibliometric statistics highlighting notable authors, contemporary keywords for sifting through the literature, scientific dimensions related to smart supply chain, servitization and the circular economy, historical growth based on exploration trends and country-by-country investigation of the research field. The study also proposes a conceptual framework that illustrates how a greater emphasis on removing barriers to servitization could increase the efficiency of various circular supply chains. Given this, there is room for further research into the role servitization plays in ensuring long-term sustainability.

This paper helps to understand current scholarly publications on servitization, smart supply chains and their significance in the circular economy. It also provides a template to utilize the field’s prior accomplishments as a guide to future research opportunities.

The purpose of this study was to design a multitask learning model so that biomedical entities can be extracted without having any ambiguity from biomedical texts.

In the proposed automated bio entity extraction (ABEE) model, a multitask learning model has been introduced with the combination of single-task learning models. Our model used Bidirectional Encoder Representations from Transformers to train the single-task learning model. Then combined model's outputs so that we can find the verity of entities from biomedical text.

The proposed ABEE model targeted unique gene/protein, chemical and disease entities from the biomedical text. The finding is more important in terms of biomedical research like drug finding and clinical trials. This research aids not only to reduce the effort of the researcher but also to reduce the cost of new drug discoveries and new treatments.

As such, there are no limitations with the model, but the research team plans to test the model with gigabyte of data and establish a knowledge graph so that researchers can easily estimate the entities of similar groups.

As far as the practical implication concerned, the ABEE model will be helpful in various natural language processing task as in information extraction (IE), it plays an important role in the biomedical named entity recognition and biomedical relation extraction and also in the information retrieval task like literature-based knowledge discovery.

During the COVID-19 pandemic, the demands for this type of our work increased because of the increase in the clinical trials at that time. If this type of research has been introduced previously, then it would have reduced the time and effort for new drug discoveries in this area.

In this work we proposed a novel multitask learning model that is capable to extract biomedical entities from the biomedical text without any ambiguity. The proposed model achieved state-of-the-art performance in terms of precision, recall and F1 score.

The purpose of this paper is to investigate (1) whether the public health expenditure rises as the gross state domestic product (GSDP) increases and (2) whether the infant mortality rate (IMR) reduces as public health expenditure increases.

For this investigation, the author collected a time series of data on public health spending and IMRs for an Indian state and applied regression, stationarity, cointegration and causality tests. The author also compared the relative performance of selected Indian states.

The author found that none of the Indian states did equally well in reducing the infant mortality rate (IMR). As GSDP rises, the public expenditure on health rises, however, this increase in public health expenditures does not cause a reduction in the IMR. The cointegration and causality test results validated it.

The author recommends that policymakers must shift their focus from merely increasing government health expenditure to efficiently utilising allocated funds and removing the administrative bottlenecks. Also, an equitable health financing system that addresses existing disparities in the healthcare delivery system should be ensured.

Researchers and policymakers have debated the role of public health spending in achieving Sustainable Development Goal (SDG) 3 targets. The paper proves that there exists no long-term relationship between public health spending and IMR.

The paper aims to identify and report service quality dimensions critical to distributors’ perception of the quality of services their suppliers provide (Manufactures).

This research used unstructured interviews and focused group discussions. The authors have interviewed ten distributors and ten frontline managers of three mid-size Consumer Packaged Goods companies operating in India. Two focused group discussions were conducted involving academicians and practitioners in the service quality domain.

Seven quality dimensions critical to a distributor’s service quality evaluation have been identified. Except for tangibility, all other SERVQUAL dimensions have been found relevant. Three additional dimensions, namely “Fairness,” “Accessibility” and “Image quality,” have been identified. The authors made a theoretical contribution by not only identifying the relevant dimension but also proving their context-specific definition. The authors also present managerial implications and recommendations to improve the service experience of distributors.

This paper investigates the distributor–manufacturer dyadic relationship from a service quality perspective for the first time. This study made a theoretical contribution by explicitly identifying service quality dimensions for a manufacturer-to-distributor (M2D) service relationship.

Pearl millet (Pennisetum glaucum) is a rich source of nutrients as compared to the major cultivated cereal crops. However, major factors which limit its utilization are the presence of anti-nutritional factors (phytate, tannins and polyphenols) which lower availability of minerals and poor keeping quality because of higher lipase activity. Therefore, this paper aims to focus on the impact of different processing methods on the nutrient composition and anti-nutritional components of pearl millet.

This is a literature review study from 1983 to 2017, focusing on studies related to pearl millet processing and their effectiveness in the enrichment of nutritional value through reduction of anti-nutritional compounds.

From the literature reviewed, pearl millet processing through various methods including milling, malting, fermentation, blanching and acid as well as heat treatments were found to be effective in achieving the higher mineral digestibility, retardation of off flavor, bitterness as well as rancidity problems found during storage of flour.

Through this review paper, possible processing methods and their impact on the nutrient and anti-nutrient profile of pearl millet are discussed after detailed studied of literature from journal articles and thesis.