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The locational disadvantage of a health-care centre often restricts adequate delivery of health-care services in an area. The purpose of this study is to examine the status of primary health-care services in such a geographically disadvantageous area which is confined by forests, tea gardens and undulating topography.

Necessary secondary data of 13 primary health centres and 236 sub-centres has been collected from the Office of the Chief Medical Officer of Health. Based on obtained data, Health-care Infrastructure Index has been prepared which has been validated by an expert panel, and subsequently, the Thiessen Polygon method has been applied through Arc GIS software to show spatial variation of health-care services delivered by different health-care centres.

In the study area, there is wide variation found in the case of physical facilities, caregivers and connectivity of road networks, which altogether affect the overall status of health-care services. Among all the indicators, some health-care centres experience staff shortages for prolonged non-recruitment, inaccessibility and inconsistent patient load in different health centres.

In spite of the unfavourable geographical landscape, health-care centres have to be set up wherever possible. There is a need to make new roads and simultaneously the existing road connectivity should be improved so that patients and caregivers can move quickly whenever required. Existing physical facilities need to be renewed or redeveloped along with increasing the number of doctors and other health-care providers as per the need of people with an adequate and optimum level of services.

This paper aims to attempt to empirically investigate the impact of privatization on the performance of central public sector enterprises in India. Further attempt is made to explore whether privatization is a necessary or sufficient condition for improvement of performance of central public sector enterprises.

The scope of the study is limited to financial and operating performance analysis of 206 central public sector enterprises in India. Multiple regression analysis has been used to determine the magnitude and direction of relationship between dependent and independent variables and identify variables other than privatization which affects performance.

The study found that financial and operational performance of firms has improved significantly due to privatization. Further, firm-specific factors and other parallel reforms adopted by enterprises have significantly influenced their performance. The established regression model is highly significant with F-ratio of 31.825 at 99% significance level. The degree of explanation of the model is robust with adjusted R² at 0.956 implying that only 4.40% of explanation in the dependent variable cannot be explained by designated independent/explanatory variables.

The study would be useful to public policymakers to reach to a policy view on whether further disinvestment/privatization of central public sector enterprises need to be continued, and if so, then to what extent and direction.

The purpose of this paper is to review several influential empirical studies that examine the performance of state-owned enterprises (SOEs). The paper undertakes a citation analysis of journals, authors and titles in the area of privatization and firm performance in general, and assesses the impact of privatization on the performance of SOEs in particular.

The methodology is based on a systematic and structured review of over 100 papers published in economics, public management, business strategy and related social sciences. The systematic review is based on citation analysis of journals, authors and titles. The journal and author citation counts were tabulated by leveraging the databases of SCImago Journal Rankings and Google Scholar and filtered it to find out the most highly cited journals and authors. The structured review is based on the framing opinion with respect to major findings, variables selected, measurement techniques and statistical tools applied by different researchers. The impact is measured through coding a value “P” in case of positive effects, “N” in case of negative effects and “NT” in case the study found both positive and negative effects.

The citation analysis reveals that American Economic Review, Journal of Financial Economics, Review of Financial Studies and Journal of Finance as the top-cited journals, and Megginson and Netter (3,468), Megginson et al. (1,737), Djankov and Murrell (1,356), Boardman and Vining (1,320), Balsam et al. (1,094) and DeWenter and Malatesta (1,018) as the top-cited authors in this particular research field. While majority research studies have revealed a significant improvement in the performance of SOEs in the post-privatization period, few studies have reserved their impact as neutral or even negative in some respects.

Given that economic transitions, corporate governance, and performance of SOEs have attracted a great attention from public management and business strategy scholars in recent years, this paper aims to summarize a large number of empirical studies that examine the performance of SOEs. The paper would be useful to future researchers especially the beginners and early career researchers in terms of its current trends, selection of variables, measurement techniques and statistical tools applied.

The purpose of this study is to study the impact of relationship marketing orientation (RMO) and relationship quality on customers' commitment and pro-marketer behavior (positive word of mouth and external attribution) after negative brand publicity by using the combined lens of relationship marketing theory and the theory of cognitive dissonance.

A survey was conducted among banking customers in India using an online questionnaire. Data were analyzed using structural equation modeling and the bootstrapping procedure using the SPSS process macro.

Contrary to conventional wisdom, findings of this study suggest that RMO and relationship quality are positively correlated to commitment even after negative publicity. The path between RMO, relationship quality and pro-provider behavior is found to be mediated by commitment. This indirect path is moderated by customers' cognitive dissonance arising out of the negative publicity.

The study establishes the combined roles of RMO and relationship quality in pre-empting the detrimental effects of negative brand publicity. Further, it establishes interactions of cognitive dissonance with these relationship variables, thereby bringing together literature from relationship marketing theory and cognitive dissonance theory.

In the past three centuries in India, outsiders have dominated economic fortunes. Yet, for a brief interlude for two decades (i.e. in the 1830s and 1840s), the Bengalis from Eastern India played a dominant role in the modern business sector of the economy as partners of the British. The singular reason behind this phenomenon was the role of Dwarkanath Tagore (DT) in building multiple multiracial business partnerships in a myriad of businesses. This study aims to demonstrate how all of these activities were synthesized in an integrated marketing approach and how DT was the catalyst in forging these partnerships with the British East India Company and other enterprises.

A historical research method is used in critically examining the business practices of DT. Resources include a few biographies about him as well as several print sources, including several publications owned by him.

DT’s approach to an integrated marketing approach in the nineteenth century, involved the traditional production, distributional and promotional components, and he understood the significance of using all tools at his disposal to reach his market using these synergies, each reinforcing his main self-identify was that of an entrepreneur. He used forward integration techniques in running other operations, e.g. distribution, publishing, advertising and promotion of his products. His multiracial social networks for business and social activities are also identified.

This study synthesizes different sections of DT’s businesses and illustrates how he used integrated marketing to build an enterprising, profit-making business, which was good for both the economy of Bengal and that of the British East India Company and his other partners. The study also establishes him as a pioneering Indian entrepreneur and identifies major social networks with other business partners (both Indian and British).

In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of machine learning techniques helps in efficient management of data and draws relevant patterns from that data. The main aim of this research paper is to provide brief information about the proposed adoption of machine learning techniques in different sectors of manufacturing supply chain.

This research paper has done rigorous systematic literature review of adoption of machine learning techniques in manufacturing supply chain from year 2015 to 2023. Out of 511 papers, 74 papers are shortlisted for detailed analysis.

The papers are subcategorised into 8 sections which helps in scrutinizing the work done in manufacturing supply chain. This paper helps in finding out the contribution of application of machine learning techniques in manufacturing field mostly in automotive sector.

The research is limited to papers published from year 2015 to year 2023. The limitation of the current research that book chapters, unpublished work, white papers and conference papers are not considered for study. Only English language articles and review papers are studied in brief. This study helps in adoption of machine learning techniques in manufacturing supply chain.

This study is one of the few studies which investigate machine learning techniques in manufacturing sector and supply chain through systematic literature survey.

1. A comprehensive understanding of Machine Learning techniques is presented.

2. The state of art of adoption of Machine Learning techniques are investigated.

3. The methodology of (SLR) is proposed.

4. An innovative study of Machine Learning techniques in manufacturing supply chain.

A comprehensive understanding of Machine Learning techniques is presented.

The state of art of adoption of Machine Learning techniques are investigated.

The methodology of (SLR) is proposed.

An innovative study of Machine Learning techniques in manufacturing supply chain.

The recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic has severely disrupted the operations of global supply chains (SCs) providing an opportunity for decision-makers to rethink and tune their existing strategies. To tackle the impacts caused by such a pandemic, this study aims to examine the contextual relations among the factors influencing supply chain viability (SCV) for achieving long-term Sustainable Development Goals (SDGs).

A decision-aid approach by integrating Pareto analysis, grey theory and total interpretive structural modeling (TISM) has been propounded. The proposed approach examines contextual relations among the factors for SCV for small and medium-sized enterprises (SMEs) in an emerging economy. This study contributes to theory, methodology and practice by exploring a new research problem in the context of the SCV and COVID-19 pandemic and by developing a new decision-aid approach.

The findings reveal that the creation of SC digital twin and transformation of SCs to supply networks would help the policymakers to deal with the “new normal.” Also, SC crowdfunding and policy development for health protocols are critical driving factors influencing SCV.

This research work is perhaps one of few initial attempts to advance the theoretical and practical understanding of SCV and to achieve SDGs in industries following a pandemic risk.

The purpose of this paper is to explore the functioning of very‐large‐scale integration (VLSI) interconnects and modeling of interconnects and evaluate different approaches of testing interconnects.

In the past, on‐chip interconnect wires were not considered in circuit analysis except in high precision analysis. Wiring‐up of on‐chip devices takes place through various conductors produced during fabrication process. The shrinking size of metal‐oxide semiconductor field effect transistor devices is largely responsible for growth of VLSI circuits. With deep sub‐micron (DSM) technology, the interconnect geometry is scaled down for high wiring density. The complex geometry of interconnects and high operational frequency introduce wire parasitics and inter‐wire parasitics. These parasitics causes delay, power dissipation, and crosstalk that may affect the signal integrity in VLSI system. Accurate analysis, sophisticated design, and effective test methods are the requirement to ensure the proper functionality and reliability of VLSI circuits. The testing of interconnect is becoming important and a challenge in the current technology.

The effects of interconnect on signal integrity, power dissipation, and delay emerges significantly in DSM technology. For proper performance of the circuit, testing of interconnect is important and emerging challenge in the nanotechnology era. Although some work has been done for testing of interconnect, however, it is still an open area to test the parasitics effects of VLSI/ultra‐large‐scale integration interconnects. Efforts are required to analyze and to develop test methods for crosstalk, delay and power dissipation in current technology with solutions to minimize this effect.

This paper reviews the functioning of VLSI interconnects from micrometer to nanometer technology. The development of various interconnect models from simple short circuit to latest resistance inductance capacitance transmission line model are discussed. Furthermore, various methodologies such as built‐in self test and other techniques for testing interconnect for crosstalk and delay are discussed.