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The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

The purpose of this study is to construct a new index to assess the impact of an energy price shock on macroeconomic indicators of India. This paper also shows a comparative analysis of the constructed index along with pre-existing World Bank and International Monetary Fund indices on energy.

This paper uses three vector autoregressions and compute the long-term impact of the indices on the considered macroeconomic variables through impulse response functions.

This paper finds that an energy price shock has a detrimental impact on the macroeconomic indicators of India in the long run. This study also finds that the constructed index acts as a relatively more sensitive index in comparison to the International Monetary Fund and World Bank indices, which is bespoke to a developing economy case. This sensitivity is ascribed to dynamic weighting for a different basket of energy components, which are more pertinent to an Indian context.

The novelty of this research lies in the construction of a new index and its comparison to the existing ones. This study justifies why a developing economy would require a different measure of energy as opposed to the existing indices.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

The purpose of this paper is to investigate the integrated role of psychological, economic and environmental determinants of entrepreneurial intention among tribal community.

This study applied the utility maximisation approach to model the determinants of entrepreneurial intention (EI) among tribal youth. Using a non-linear qualitative response model, the study examined the effects of psychological, economic and environmental determinants tribal youth entrepreneurship intention. A total of 363 tribal youths were sampled across the eastern central region of India.

The result from the use of a logit model revealed strong evidence in favour of economic and contextual factors in comparison to psychological factors as determinants of EI among tribal youth. Further, the external environmental factors along with socio-economic background of tribal community were found to be dominant in influencing their decision to be an entrepreneur.

This study provides empirical evidence for the integrated and relative role of psychological, economic and environmental factors in shaping the entrepreneurial career decision of tribal community. Hence, one of the key contributions of this research was the development of an eclectic theory of tribal entrepreneurship.

This study discovering the determinants of entrepreneurial decision of tribal community using some recent advances in non-psychological approaches to study entrepreneurship. The domain of tribal/indigenous entrepreneurship is still in a nascent stage and in this context, it enriches the literature by closing few glaring gaps.

Research on leaders’ knowledge management systems focuses exclusively on how leaders gather and disseminate knowledge in collaboration with external actors. Not much is known about how leaders address the psychological aspects of employees and strategize internal communication. In addition, while previous work has treated high uncertainty as a default feature of crisis, this study aims to propose that perceived uncertainty varies in experience/meaning and has a crucial bearing on the relative balance of cognitive/emotional load on the leader and behavioral/psychological responses.

The authors contribute by qualitatively examining the role of leader knowledge systems in designing communication strategies in the context of the COVID-19 crisis by investigating communication characteristics, style, modes and the relatively unaddressed role of compassion/persuasion. In this pursuit, the authors interviewed 21 C-suite leaders, including chief executive officers, chief marketing officers, chief financial officers, chief human resource officers and founders, and analyzed their data using open, axial and selective coding, which were later extracted for representative themes and overarching dimensions.

Drawing from grounded theory research, the authors present a framework of knowledge systems and their resultant communication with employees in high uncertain and low uncertain crises. The authors highlight interactions of a set of concepts – leaders’ preparedness, leaders’ support to employees tailored communication adapted to perceived uncertainty, leading to enhanced trust – in the achievement of outcomes related to balancing operational and relational systems with employees. The findings suggest that a structured process of communication helps employees mitigate any concern related to uncertainty and feel confident in their leadership.

The research has implications for leaders in managing their knowledge systems, for human esources practitioners in designing effective internal communication programs, as well as for scholars in knowledge management, communication and leadership.

Vaccine hesitancy is a long-standing issue among both the general population and health communicators. This study aims to ascertain the inclination and the reasons for vaccine hesitancy by conducting content analysis and sentiment analysis of the perspectives expressed in comments on videos related to vaccine hesitancy uploaded from India on YouTube.

The assessment of the sentiments of the vaccine-hesitant population is done using Valence Aware Dictionary and sEntiment Reasoner sentiment analysis module implemented with Python’s NLTK library to automatically determine the sentiments of the comments. Manual content analysis was performed on 60.09% viewer comments randomly selected from the total comments in 238 videos on vaccine hesitancy originated from India and labelled each comment with labels “Anti”, “Pro”, “Confused”, “Not Applicable” and “Unrelated” labels.

The study found “Mistrust-Government policies”, “Fear-health related consequences”, “Mistrust-Scientific research”, “Vaccine effectiveness and efficacy” and “Misinformation/myths” as the top five determinants for vaccine hesitancy, whereas “Religious beliefs”, “Fear-Economic consequences”, “Side Effects- short-term” and “Fear-mode of administration” found to be the lesser cited reasons for vaccine hesitancy. However, the study also investigates changes in the inclination of Indian commenters towards vaccine hesitancy and revolving issues over time.

Public health policymakers and health communicators may find the study useful in determining vaccine hesitancy factors in India.

The originality of this study lies in its approach. To date, no sentiment analysis has been conducted on the content released on YouTube by Indian content creators regarding pro- and anti-vaccination videos. This inquiry seeks to fill this research gap.

Luxury as a construct warrants an assessment of entities promoting themselves as luxurious offerings. Therefore, this study attempts to evaluate the experiencescapes of luxury trains operating in developed and developing countries to assess the presence of luxury values in the elements affecting tourists' experiences and immersion.

Two different types of luxury trains were selected from across developed and developing countries for a holistic assessment of the experiencescapes. Through netnography and hermeneutic interpretation, this study analyzes 218 experiential descriptions on Tripadvisor from luxury trains of Australia, UK, Peru and India.

Although luxury trains in both the regions entailed financial, functional, social and individual value, they struggled to offer these values in conjunction. While the positioning of luxury trains in developing countries under the “inaccessible luxury” segment is exaggerated, developed countries were also found to struggle with customer service and management.

By emphasizing on areas within the control of the service providers, short-haul luxury trains can be a better fit in developing countries. Better usability testing and employee training should be undertaken to improve the functional values of luxury in long-haul luxury trains of developed countries.

This article not only assesses the validity of luxury trains' positioning but also provides new insights into the nature of the tourist immersion process. Having extensively discussed experiences in the backdrop of luxury, it contributes to the progression of literature on luxury trains, experiencescapes and immersion.

A nation's economic development is adversely affected by the rising population and the lack of employment opportunities, necessitating the promotion of entrepreneurial activities. This study aims to unfurl the critical factors shaping university students' entrepreneurial intentions (EI) in an emerging economy.

The study assessed the EI of 640 university students across India's top 5 central universities through structural equation modeling by extending the entrepreneurial event model (EEM) and dark triad theory. Mediation and moderation techniques were used to examine the model's direct and indirect linkages.

The results show that propensity to act (PTA), perceived resilience (PRS) and narcissism (NAR) magnify desirability, significantly increasing students' EI. The association between the underlying constructs is partially mediated by the PTA and perceived desirability (PD). In addition, the linkage between PD and students' EI is strengthened by the pursuit of excellence (PoE) and weakened by perceived risk (PR).

The study's findings could assist educators, universities, aspiring entrepreneurs, financial institutions, policymakers, investors, venture capitalists, incubators and accelerators in reinforcing entrepreneurial culture in India by establishing a link between crucial personality traits and intentions to start entrepreneurial ventures.

Personality traits such as NAR, resilience and the PoE have not received much attention in the entrepreneurship literature and call for a rigorous inquiry. The study tries to embrace these dominant personality traits by broadening the perspectives of EEM and dark triad theory via a comprehensive conceptual model. It also explores the role of the PoE and PR as moderators to examine the possible association between the identified constructs.

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.