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The impact of digitalisation on smaller firms remains sparsely studied across emerging economies. The paper aims to examine the relationship between digital adoption and multiple performance parameters of micro, small and medium enterprises (MSME) in a prominent emerging economy.

The study employs data from the World Bank Enterprise Survey (WBES) 2022, capturing 9,024 Indian MSME firms spread across the country. Performance indicators are derived from growth in sales, employment and labour productivity (LPROD). Multiple regression estimates are derived that also correct for sample selection bias using Heckman’s two-step process.

Digital proliferation is found to increase as firms mature up in terms of age, size and constitution. A significant difference could also be observed in business performance across digital and non-digital businesses, with sales growth (SG) and productivity higher for digital firms. Digital financial variables are found to have a significant impact on SG but not as much in the case of employment growth and LPROD. The results are robust to correction for sample selection bias in digital adoption using inverse mills ratio (IMR).

The study highlights digital adoption gaps across various strata of MSMEs, highlighting lower adoption when firms are younger, smaller and lacking formal constitutional setup. Digital variables indicating positive association with SG highlight the need for concerted efforts at the public policy level for building appropriate skills and infrastructure for micro and small enterprises to boost their digital adoption to promote growth.

There is a lack of micro-level empirical evidence measuring the impact of advanced digital technology usage on multiple aspects of enterprise performance amongst micro and small firms. The study deploys unique digital variables including TReDS and use of online credit applications to assess the impact on business performance. The findings provide insights for practice and public policy, besides making the case for a higher focus on launching digital initiatives for smaller enterprises.

It is generally believed that business spending on capital expenditure tends to decrease as interest rates rise, and vice versa, this is not always the case. The previous literature produces inconclusive results vis-à-vis the interest rate and investment nexus. This study analyzes the responsiveness of investment to changes in high and low levels of interest rates in India through a quantile-based, non-parametric method utilizing annual data from 1980 to 2022.

This study uses Quantile-on-quantile (QQ) technique proposed by Sim and Zhou (2015) to examine the impact of interest rate quantiles on quantiles of investment. In addition, long-term association and the direction of causality are estimated through the Cho et al. (2015) test of quantile cointegration and the Jeong et al. (2012) Granger causality in quantile (GCQ) test, respectively.

The empirical evidence validates that the linkage between investments and interest rate is not consistently negative and varies from quantile to quantile. The study finds a negative impact at median quantiles and a positive impact at extreme higher quantiles. Conversely, the impact at lower quantiles is negligible, which is also observed from quantile cointegration, indicating the presence of a statistically significant association above the median quantiles. Additionally, the study finds one interesting finding that there exists unidirectional causality from investment to interest rates in India rather than other way around.

The study provides significant implications for policymakers as it suggests that during extreme economic conditions, the effectiveness of traditional monetary policy tools to boost capital formation is restricted. Policymakers may consider alternative measures to stimulate investment during these time periods. The study additionally posits that the neoclassical theory of investment may not be readily applicable in emerging economies in its unaltered state, mostly due to the lack of well-developed financial markets.

There is a limited literature available on non-linear linkage between interest rates and investment. The present study adds to the existing knowledge by investigating how investment responds differently to fluctuations in interest rates, while incorporating the complete distribution of both the variables.

Along with technology-based ecosystems, healthcare start-ups are expanding multi-fold. On the other hand, underlying uncertainties pose several challenges for these health-tech enterprises at macro-meso-micro level, influencing their business circumstances and profitability. The current study aims to comprehend the macro-, meso- and micro-level barriers that make it difficult for enterprises to set up healthcare technology start-ups. The study also observed the perceived effect of these challenges on firms' performance and cost structure over time. Using the theory of behaviour under uncertainty, the study revealed multiple systemic, sector-related, human and implementation barriers that hinder business growth and lead to uncertainties for health-tech start-ups.

Using a grounded theory approach, the study collected the views of 51 health tech start-ups in the UK using an online participants pool. The data was collected using qualitative data techniques in the form of open-ended essays, and a content analysis using thematic coding process was conducted. The questions centered around the different institutional uncertainties or barriers while setting up or running a healthcare start-up.

The study revealed several macro-, meso- and micro-level barriers these technology-based enterprises perceive in the healthcare industry. These are recognised as systemic barriers, such as lack of funding and procedural issues; sector-related barriers, such as market-related impediments; human barriers, including psychological barriers and resistance to new technology; and implementation barriers, such as operational and personnel issues.

The study used qualitative, open-ended essay techniques to collect the data. Future studies may use a mixed-methods approach to provide holistic insights. The study is conducted in a single developed country, the UK. Future work may expand these findings by comparing developed market challenges with those of emerging markets and by assessing the viewpoints of healthcare start-ups.

This research will assist the healthcare sector and government understand health tech start-up hurdles and uncertainty. Policymakers must assist start-ups and encourage entrepreneurial innovation. Regulating and enabling policies will help. The paper examines start-ups' macro, meso and micro uncertainties. Policymakers promoting sector entrepreneurship must consider these barriers while designing policy guidelines.

The study contributes to the existing literature on technology start-ups, particularly in the healthcare industry, and identifies significant barriers these start-ups face. The study synthesizes research on health-tech start-up uncertainty and bridges the gap between theory and practice by applying empirical findings.

The requirement of robust cooperative control is essential to achieve consensus between unmanned aerial vehicles (UAVs) operating in swarm formation. Often the performance of these swarm formations is affected by wind gust disturbances. This study proposes an effective robust consensus protocol, which will ensure the UAVs in swam formation to collectively meet the desired objective in real-time scenario.

In this work, the swarm of UAVs are modeled as multiagent systems by using the concepts of algebraic graph theory. To address the challenges of a complex and dynamic environment, an adaptive sliding mode control (SMC)-based consensus protocol is proposed. The closed loop stability analysis is established through Lyapunov theory.

The efficacy of the discussed robust consensus controller is analyzed through numerical simulations. Further, the quantitative analysis using Monte-Carlo simulations validates performance of the proposed robust consensus protocol. The presented consensus protocol can be easily implementable as robust flight controller for swarm of UAVs. Also, as the consensus theory is based on the algebraic graph theory, the proposed design is scalable for a large number of UAVs in swarm formation.

The proposed adaptive SMC achieves robust consensus of longitudinal dynamics states between all the UAVs by mitigating the effects of wind gust disturbances. Also, the adaptive SMC offers chattering-free control efforts.

Spiritual tourism is becoming a significant growth area of the Indian travel market, with more Indians opting to go on pilgrimage to popular religious cities. There are many spiritual destinations where some of this life's essences can be sought to enjoy harmony and peace. The study aims to prioritize motivators driving the intentions of the tourists to visit the spiritual destination.

The current study applied the analytical hierarchical process, a multi-criteria decision-making technique, on the sample of visitors from all the six spiritual destinations to rank the motivational factors that drive the intentions of the tourist to visit a spiritual destination.

The study's results postulated that spiritual fulfillment motives and destination atmosphere are the top prioritized motivations, while destination attributes and secular motives emerged as the least prioritized.

The research study provides valuable insights to the spiritual tourism industry stakeholders to target the tourists' highly prioritized motivations to augment the visits to a particular spiritual destination.

Previous research has explored the motivations and modeled their relationships with tourists' satisfaction and intentions. But, the present study has applied a multi-criteria decision-making technique to add value to the existing knowledge base.

Consumers by and large today look for economic growth and benefits without compromising on socio-environmental well-being. Having said that, it is imperative to note that consumers' consciousness may not essentially lead to sustainable purchases. This chapter aims to examine the role of both sustainable purchase intention and post-purchase dissonance in the relationship between consumers' sustainability consciousness and consumers' evangelism. With the increased role of social media pervading our lives, trusted sources' recommendations play a significant role in co-creating products. Thus, research on consumers' evangelism (especially sustainability-conscious consumers) would help marketers develop successful strategies. This study expands to the extant literature on sustainability-conscious consumers vis-a-vis consumer evangelism. We collected responses from 227 respondents to examine hypotheses, by means of structural equation modelling (SEM). The study indicates sustainable purchase intention does mediate the relationship between sustainability-conscious consumers and consumer evangelism. On the other hand, we also note that post-purchase dissonance is not a significant moderating construct between sustainability-conscious consumers and consumer evangelism.

The unique nature, complicated design, hazardous activities and complex work environment involved in the high-rise construction projects constitute significant risks worldwide. In the Indian context, construction safety management in high-rise construction projects is crucial due to the presence of significant occupational risks and hazards at the workplace. Occupational hazards lead to accidents that severely affect human health and result in substantial financial losses.

The study aims to present a hybrid risk assessment method (RAM) and the technique for order of preference by similarity to ideal solution (TOPSIS) method to detect and evaluate occupational risks in different construction activities through a questionnaire survey approach.

Aroundsix types of construction activities and corresponding ten risks are identified and evaluated during the study. Based on the calculation of risk scores, the findings imply that “roof work activities,” “finishing work,” “mechanical, electrical and plumbing work (MEP)” are hazardous construction activities, while, among the corresponding ten risks, “workers falling from height” is the most prominent risk among the majority of activities. Other risks include “risk due to fire and electric accidents” and “struck by falling objects,” which are the major risks in high-rise construction projects.

Theoriginality of the paper lies in its activity-based risk assessment and ranking of hazards in high-rise construction projects. By integrating theoretical insights with practical applications, the study attempts to enhance occupational safety and reduce accidents on construction sites, thereby significantly contributing to both academia and industry practices.

In the last 10 years, India has amended its laws dealing with sexual offences against women with the changes ranging from increasing terms of imprisonment for the offence of rape to state-funded compensation schemes for women and child victims. In this regard, challenges persist for the agencies of the criminal justice system in India especially the courts to realise the vision of restorative justice as these forums have to navigate the relevant statutory provisions and binding precedents. This chapter seeks to analyse the challenges faced by courts in proper reintegration of victims and offenders of sexual offences, the institutional responses of the courts and suggests reforms to the criminal justice system in India in consonance with the principles of restorative justice acknowledged in the restorative justice movement in the international discourse.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

The purpose of this paper is to permit the system reliability analysts/managers/engineers to model, analyze and predict the behavior of industrial systems in a more realistic and consistent manner and plan suitable maintenance strategies accordingly.

Root cause analysis (RCA), failure mode effect analysis (FMEA) and fuzzy methodology (FM) have been used by the authors to build an integrated framework, to facilitate the reliability/system analysts in maintenance planning. The factors contributing to system unreliability were analyzed using RCA and FMEA. The uncertainty related to performance of system is modeled using fuzzy synthesis of information.

The in‐depth analysis of system is carried out using RCA and FMEA. The discrepancies associated with the traditional procedure of risk ranking in FMEA are modeled using decision making system based on fuzzy methodology. Further, to cope up with imprecise, uncertain and subjective information related to system performance, the system behavior is quantified by fuzzy synthesis of information.

The complementary adoption of the techniques as discussed in the study will help the maintenance engineers/managers/practitioners to plan/adapt suitable maintenance practices to improve system reliability and maintainability aspects after understanding the failure behavior of component(s) in the system.