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This research intends to investigate the impact of economic policy uncertainty (EPU) on the firm's leverage and its adjustment speed.

This study applies dynamic panel data modeling by using a partial adjustment model. The study is based on secondary data of the non-financial firms that are listed on the Pakistan stock exchange. For the analysis purpose, the study applies the generalized method of moments (GMM) estimation technique and uses a newly developed text-based measure of economic policy uncertainty.

The results show the negative impact of EPU on leverage decisions but a positive impact of EPU on leverage speed of adjustment for both, short-run and long-run economic policy shocks. Additional analysis reveals that the negative influence of long-run policy shocks on leverage decisions is moderated through profitability, and the negative influence of short-run policy shocks on leverage is moderated through firm size, tangibility and available growth prospects. However, the significant positive impact of EPU on the leverage speed of adjustment in both short and long-term policy shocks indicates that the speed of adjustment for these firms is not affected by policy shocks.

This research contributes to the existing literature on capital structure dynamics,by investigating the impact of EPU on firm financing decisions and estimating the adjustment speed of capital structure in a developing market context. The study also extends the existing literature by applying the concept of long-run and short-run economic policy uncertainty in the capital structure dynamic framework. Additionally, the new news-based measure of EPU is used. Moreover, it also looks into the COVID-19 effect on the relationship.

This study aims to explore the impact of capital structure (CS), including total debts, short-term debt, long-term debt and total shareholder equity, on environmental, social and governance (ESG) performance in the context of Jordan.

To achieve the study’s objectives, the authors used the content analysis approach and the longitudinal data generated from the annual reports of 51 industrial companies listed on the Amman Stock Exchange for the period 2012–2020.

The findings show that debt financing enhances ESG performance in all dimensions, while financing by equity did not affect ESG. Consequently, Jordanian companies’ managers are trying to reduce agency costs by investing in ESG activities. In addition, companies are focusing on debt financing instead of equity to achieve their financial as well as nonfinancial goals. This is because the opportunism of new shareholders will likely lead to a focus on maximizing their value at the expense of the broader group of stakeholders, and this will adversely affect companies’ ESG performance. Therefore, debt financing limits shareholder control.

To the best of the authors’ knowledge, this is the first examination of the impact of CS financing choices on ESG performance. Thus, this study has important implications for the decisions of executives, policymakers, shareholders and lenders, as it enables them to better understand the linkage between CS and ESG.

This paper aims to test for volatility spillovers among Islamic stock markets with the exogenous impact of geopolitical risk (GPR) to check the risk transmission among Saudi Arabia, Malaysia, Indonesia and Turkey. Researchers test for both the symmetric and asymmetric risk transmission.

For the symmetric response of volatility, the study uses simple generalized autoregressive conditional heteroscedastic (GARCH) and for the asymmetric response of volatility with the exogenous impact of GPR, the exponential GARCH models have been adopted.

The results suggest spillover effects exist from Turkey to Saudi Arabia, Indonesia to Malaysia and Saudi Arabia and Malaysia to Indonesia. The findings of volatility spillover from GPR to sample countries suggest that only Malaysia and Indonesia experience volatility spillovers from GPR.

The present study is limited to the context of four countries and Islamic equities; the study contributes to the literature on volatility spillover, Islamic finance, GPR and asset pricing.

This study contributes to individual, institutional investors’ policymakers’ knowledge in determining security prices, trading plans, investment hedging and policy regulation.

The extant literature disregards the GPR index to examine the volatility spillover effects among Islamic stock markets, which allow researchers to justify the mechanism of risk transmission due to GPR across the Islamic stock market.

To the best of the authors’ knowledge, this is the first research of its type to look at volatility spillover and GPR transmission in Islamic stock markets.

Allocation of the marketing budget has become increasingly challenging due to the diverse channel exposure to customers. This study aims to enhance global marketing knowledge by introducing an ensemble attribution model to optimize marketing budget allocation for online marketing channels. As empirical research, this study demonstrates the supremacy of the ensemble model over standalone models.

The transactional data set for car insurance from an Indian insurance aggregator is used in this empirical study. The data set contains information from more than three million platform visitors. A robust ensemble model is created by combining results from two probabilistic models, namely, the Markov chain model and the Shapley value. These results are compared and validated with heuristic models. Also, the performances of online marketing channels and attribution models are evaluated based on the devices used (i.e. desktop vs mobile).

Channel importance charts for desktop and mobile devices are analyzed to understand the top contributing online marketing channels. Customer relationship management-emailers and Google cost per click a paid advertising is identified as the top two marketing channels for desktop and mobile channels. The research reveals that ensemble model accuracy is better than the standalone model, that is, the Markov chain model and the Shapley value.

To the best of the authors’ knowledge, the current research is the first of its kind to introduce ensemble modeling for solving attribution problems in online marketing. A comparison with heuristic models using different devices (desktop and mobile) offers insights into the results with heuristic models.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

The purpose of our study is to investigate the impact of corporate culture on sales order backlog.

The authors use regression analysis to examine the relation between corporate culture and the level of sales order backlog, an important leading indicator of firm performance.

Using a large panel sample of US firms for the period of 2003–2021, the authors find a significant and positive relation, suggesting that firms with strong corporate culture have a higher level of sales order backlog.

The study findings contribute to two separate areas of research: corporate culture in management literature and sales order backlog in accounting literature. Prior study has focused on the impact of corporate culture on current firm performance. This study extends prior research by investigating the impact of corporate culture on order backlog, an important leading indicator of future performance.

This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings.

This study foremostly combined building energy efficiency ratings from several data sources and used them to create predictive models using a variety of ML methods. Secondly, to test the hypothesis of ensemble techniques, this study designed a hybrid stacking ensemble approach based on the best performing bagging and boosting ensemble methods generated from its predictive analytics.

Based on performance evaluation metrics scores, the extra trees model was shown to be the best predictive model. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method. Finally, it was discovered that stacking is a superior ensemble approach for analysing building energy efficiency than bagging and boosting.

While the proposed contemporary method of analysis is assumed to be applicable in assessing energy efficiency of buildings within the sector, the unique data transformation used in this study may not, as typical of any data driven model, be transferable to the data from other regions other than the UK.

This study aids in the initial selection of appropriate and high-performing ML algorithms for future analysis. This study also assists building managers, residents, government agencies and other stakeholders in better understanding contributing factors and making better decisions about building energy performance. Furthermore, this study will assist the general public in proactively identifying buildings with high energy demands, potentially lowering energy costs by promoting avoidance behaviour and assisting government agencies in making informed decisions about energy tariffs when this novel model is integrated into an energy monitoring system.

This study fills a gap in the lack of a reason for selecting appropriate ML algorithms for assessing building energy efficiency. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method.

This study aims to examine the association between mandatory corporate social responsibility (CSR) regulations (CSR mandate) and social disclosures (SOCDS) in India. It also investigates whether CSR committees mediate the relationship between CSR mandate and SOCDS. Furthermore, this paper explores how business group (BG) affiliation moderates CSR committee quality and SOCDS.

This study uses a data set of 5,345 observations from the Bombay stock exchange (BSE)-listed firms over 10 years (2011–2020) to examine the research questions. Baron and Kenny’s (1986) three-step model is estimated to examine the mediating role of CSR committees on the relationship between CSR mandate and SOCDS.

The study reveals that the CSR mandate positively impacts SOCDS in India due to coercive pressures. CSR committees mediate this relationship, with higher CSR committee quality leading to increased SOCDS. Furthermore, the authors report that SOCDS in India is positively related to CSR committee quality, and this relationship is stronger for BG firms. Finally, the supplementary analysis reveals that promoting CSR committee quality enhances firms’ likelihood of meeting CSR mandatory spending and actual CSR spending in India.

This research contributes to the academic literature by shedding light on the intricate dynamics of CSR mandates, CSR committees and SOCDS in emerging economies. Notably, the authors identify the previously unexplored mediation role of CSR committees in the link between CSR mandates and SOCDS. The creation of a composite index that measures complementary CSR committee attributes allows us to undertake a novel assessment of CSR committee quality. An examination of the moderating influence of BG affiliation documents the importance of CSR committee quality, particularly in governance, for enhancing SOCDS transparency within BG firms.

This study aims to investigate the consumer behavior toward telemedicine services in India during the COVID-19 pandemic onset. With lockdown restrictions and safety concerns in visiting brick-and-mortar clinics or hospitals during the pandemic, Telemedicine had emerged as a potent alternative for seeking redressal to health issues. Based on theory and focus interviews with the telemedicine users, the researchers proposed a model to understand the intent and actual usage of telemedicine in India.

The cross-sectional study undertaken used a questionnaire designed on a seven-point Likert scale and administered to respondents with the objective of identifying the determinants of intent and actual usage of telemedicine services. Simple random sampling was used to collect primary data. The data was cleaned and finally a sample of 405 responses complete in all respects was considered for analysis. The questionnaire comprised of 34 items and following the recommendation of Hair et al. (2016), which says the minimum sample size in structural equation modeling should be ten times the number of indicator variables, a sample size of 405 was deemed adequate.

The research paper finds that performance expectancy, attitude, credibility and self-efficacy positively impact the intention of consumers to use telemedicine services. As the effort expectancy or risk perception toward telemedicine increases the intent and actual usage of telemedicine decreases. The intention to use telemedicine emerged as a strong predictor of the actual usage of telemedicine. Intent to use telemedicine was explained 81.4% by its predictors of performance expectancy, effort expectancy, attitude, risk, credibility and self-efficacy, and actual usage was explained 79.9% by its predictors. This study also reports that telemedicine was found to be popular among chronic as well as episodic patients though the preference was skewed in favor of the episodic patients. One of the advantages of telemedicine is its availability round the clock, and the study found that 8 a. m. to 12 noon time slot as the most preferred slot for seeking telemedicine services.

Chang (2004) opined that telemedicine can fulfill the needs of all stakeholders: citizens, health-care consumers, medical doctors and health-care professionals, policymakers, and so on. Considering the promise telemedicine holds, this realm must be studied and leveraged to the full potential. The study found that patients were using telemedicine even for their day-to-day aliments. This indicates a growing popularity of telemedicine and as such an opportunity for telemedicine companies to leverage it. In India, pharmaceutical companies cannot give commercial advertisements for medicines, and the same can only be sold through a registered medical practitioner’s prescription. As such there is total dependency on the medical practitioner for the sale of medicines. Telemedicine companies offer services of home delivering medicines clubbed with medical consultation thus giving them forward integration in their business models. Using telemedicine the patients had control over the timings of the services offered, and as such the waiting time to get a consultation and subsequent treatment was reduced considerably. Best medical advice from across the globe is available to the patient at less cost. Medical practitioners also stand to benefit as they can treat a variety of cases, collaborate among the medical fraternity and give consultation safely in case of fatal contagious diseases.

This study points to a definite growing popularity of telemedicine services not only in episodic patients but also chronic patients. Telemedicine with its unique advantages holds the promise to grow exponentially in the future and is a compelling health-care segment to focus on for delivering health-care solution to the geographically distant consumers.

First, with real-life examples and current research, this study aims to demonstrate the existence of various forms of ostracism (linguistic, gender, social and workplace). Second, following the “need-threat model,” this research addresses the previously unaddressed topic of coping with, reducing, mitigating or curbing workplace ostracism. Moreover, the researchers also proposed a “multiplying effect model” of ostracism.

Data was gathered from 199 service sector employees. The NVivo software is used for the thematic analysis of qualitative data(suggestions) gathered using open ended question on how to mitigate/reduce/curb ostracism.

The results generated were the suggestive measures, which were further categorized under three major themes: individual, society and organizational. The measures to reduce, mitigate and stop the practices of workplace ostracism can be initiated on all these three levels.

This is the only study that addresses the subject of decreasing, alleviating or eliminating workplace ostracism and explains the compounding effect of ostracism by suggesting a multiplying effect model. The study will pique the interest of the government and legislators to propose legal measures to prevent ostracism and achieve sustainable development goals (gender equality and reduced inequalities. The study’s practical, social, theoretical and managerial utility are discussed in the implications section.