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The purpose of this paper is to look at the contemporaneous movement of the stock market indices of the five most COVID-infected countries, namely, the USA, Brazil, Russia, India and UK after the first wave along with market indices of the three least affected countries, namely, Hong Kong, South Korea and New Zealand during the first wave.

Data have been collected from the website of Yahoo finance on daily closing values of five indices. Augmented Dickey–Fuller test with its three forms has been applied to check the stationarity of the select five indices at the level and at the first difference before the pandemic, during the pandemic and post-first wave of the pandemic. Johansen cointegration test is applied to find out that there is no cointegration among the select five indices.

The five countries do neither fall in the same economic and political zone nor do they have the same economic status. But during the period of pandemic and the new-normal period, the cointegration is very distinct. The developing and developed nations thus stood at an indifferentiable stage of the economic crisis which is well reflected in their stock markets. However, the least three COVID-affected countries do not show any cointegration during the pandemic time.

The comovement even seen during the normal time in the other studies is not compared to a similar period in earlier years. But, in this study to look into the exclusive effect of COVID pandemic, the period most affected with it is compared with the period after it and that in the immediate past year had no effect.

This study aims to attempt to evaluate and establish the relationship between gender diversity (GD) on the board and corporate sustainability performance.

A sample of 212 non-financial companies listed on the National Stock Exchange has been considered for a period of 2013–2014 to 2018–2019. For the purpose of the analysis, this study has conducted the static panel data model analysis and also some diagnostics tests to arrive at robust results.

This study, from its analysis, interprets that GD or the proportion of women directors in the company plays a significant role in the decisions related to the sustainability performance of the company. Alongside GD, the profitability of the company, measured in terms of Tobin’s Q, and firm size are also seen to have a positive impact on the sustainability performance of the company.

This study from its findings contributes to the existing works of literature by highlighting the impact of GD on the sustainability performance of the firm. This study thus recommends the recruitment of an ample number of females in the top-notch positions of the board to create a gender-diverse management team to reap the benefits of leadership styles of both genders.

Very few studies have been conducted on the dynamics of women’s directorship, especially in an emerging economy like India. This study thus tries to fill this important gap in the literature by examining the relationship between board GD and sustainability performance of Indian firms.

The defective coin problem involves the identification of a defective coin, if any, and ascertaining the nature of the defect (heavier/lighter) from a set of coins containing at the most one defective coin, using an equal‐arm‐pan‐balance. An algorithmic analysis of the problem is considered. The solution strategy to minimise the number of weighings required to detect the defective coin is based on a problem reduction approach involving successive decomposition of the problem into subproblems until it is trivially solved. The algorithm is capable of generating all possible optimal solutions.

The purpose of this paper is to develop a theoretical model to explore the economic consequences of an exogenous skill‐biased technological change.

The paper develops a theoretical model based on assumptions and conditions that replicate those of a government‐sponsored poverty reduction programme in India.

The paper finds that, under certain stated conditions, wage inequality between artisans with improved toolkits and those without is likely to increase, while, under a different set of conditions, this is likely to decrease.

Actual wage inequality implications of specific exogenous skill‐biased technological changes need to be studied to take the theoretical model further.

One major implication is that, when government help is provided by way of an exogenous skill‐biased technological change to a fraction of workers, it may have the unintended consequence of increasing wage inequality between the beneficiary and the non‐beneficiary workers. In extreme cases, it may even lower the equilibrium wages of the non‐beneficiary workers.

The paper brings out the critical role of efficiency units of workers with skill‐biased technology (artisans with improved toolkits) and those without these in determining the wage inequality between these categories of workers (artisans) based on a theoretical model of the trajectory along which the rural economy moves.

Novel and emerging technologies such as cognitive analytics attract a lot of hype among academic researchers and practitioners. However, returns on investments in these technologies are often poor. So, identifying mechanisms through which cognitive analytics can add value to firms is a critical research gap. The purpose of this paper is to theorize how cognitive analytics technologies can enable the dynamic capabilities of sensing, seizing and reconfiguring for an organization.

This conceptual paper draws on the extant academic literature on cognitive analytics and related technologies, the business value of analytics and artificial intelligence and the dynamic capabilities perspective, to establish the role of cognitive analytics technologies in enabling the sensing, seizing and reconfiguring capabilities of an organization.

Through arguments grounded in existing conceptual and empirical academic literature, this paper develops propositions and a theoretical framework linking cognitive analytics technologies with organizations’ dynamic capabilities (sensing, seizing and reconfiguring).

This paper has critical implications for both academic research and managerial practice. First, the authors develop a framework using the dynamic capabilities theoretical perspective to establish a novel pathway for the business value of cognitive analytics technology. Second, cognitive analytics is proposed as a novel antecedent of the dynamic organizational capabilities of sensing, seizing and reconfiguring.

To the best of the authors’ knowledge, this is the first paper to theorize how cognitive analytics technologies can enable dynamic organizational capabilities, and thus add business value to an organization.

The purpose of this study is to understand and interpret the fundamental meanings attached to consumer behavior through m-Government (m-Gov) experience and to derive insights. The study explores the extent to which the emergence of m-Gov is able to change citizens established behavior of accessing government services primarily focusing on experience as an important driver.

The study used qualitative methods, and data were collected using semi-structured interviews of m-Gov users. Participants were identified through purposive sampling. Themes are identified from the collected data using thematic analysis.

The study reveals that m-Gov experience is highly satisfying since it meets citizens' expectations. The findings highlight that in many aspects, m-Gov services provide improved experiences compared to the traditional government and conventional e-Government (e-Gov) services (accessing public services from computers and laptop). The study also reveals a few negative experiences with m-Gov services, like limitations in the use of mobile devices due to their small screen size and high memory consumption, etc.

The qualitative method used in this study focuses clearly on unearthing depth and richness of understanding rather than the breadth of generalization. The sample size is apt for drawing reasonable conclusions. Scholars and information systems researchers may use some insights for future research.

m-Gov services in a developing economy like India is a new and emerging area for managers. The findings about the elements of m-Gov experience and how the experience influences citizens' acceptance decisions will benefit managers and policymakers in implementing m-Gov services or projects.

This study is one of the early attempts to explore the m-Gov experience. The research is important as experience affects users' attitude, a precursor to behavioral intention, which in turn, influences their behavior.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2020-0482

Different pollutants emission due to the conventional energy consumption process is of major concern owed to its significant effect on human health vis-à-vis regional climate. The purpose of this paper is to develop mitigation strategies to reduce the pollutant concentrations in the rural households conducted in a pristine rural village of Indian Sunderban area.

During winter, 2014, 20 households which were using traditional biomass cookstove for cooking and kerosene-lamp for lighting (KIT-TRD) were randomly selected. Specific type of improved forced draft biomass cookstove and solar lantern were used in ten of the selected households (KIT-IMP). Real time concentrations of particulate matter (PM) (PM_2.5, PM₁₀) and carbon monoxide (CO) during day and evening time cooking period were measured in KIT-IMP and KIT-TRD. A simulation model was established to evaluate most potential factor to control the level of pollutants inside the kitchen.

Conventional processes of energy consumption in the households, along with the outdoor concentration of pollutants influence the indoor concentration of measured pollutants. The concentration of PM and CO was significantly lower in the KIT-IMP than the other. In the KIT-TRD households, the daytime concentration of PM and CO was significantly higher compared to the evening. The simulated output overestimated the concentration of PM10 and CO in the KIT-TRD.

The concentration of PM_2.5, PM₁₀ and CO significantly reduces in the indoor environment with the introduction of improved cookstove and solar lantern; however, further research is required to develop optimum sizes of window and door in the rural households to reduce the concentrations of different pollutants inside the kitchen.

The purpose of this paper is to ascertain the impact of family ownership on the entrepreneurial orientation (EO) of firms in an emerging market and the contingencies under which it is likely to be affected.

The paper adopted a panel data multiple regression using ordinary least square methodology on a sample of 51,972 observations belonging to 12,250 firms from India.

The study finds that family businesses have higher EO than non-family firms. However, it is likely to be affected during institutional transition due to environmental uncertainty. Furthermore, during institutional transition, there will be differences in the EO of family business groups and stand-alone family firms due to the former’s ubiquitous network-level resource advantages.

This paper contributes to the literature on family business by reconciling the positive and negative views on the effect of family ownership on EO by arguing that the risk-taking behavior of family firms is contingent on the environmental conditions and the resource position of the firm.

This study will enable managers and other stakeholders to predict the entrepreneurial attitude of family-owned firms during environmentally stable as well as turbulent times.

This study highlights the implication of institutional transition through reforms on a vital part of the economy. Policy makers have to be sensitive to repercussions on family business due to environmental turbulence.

This is one of the first papers that investigate the influence of institutional transition and the resource position of Indian family firms on their EO.

The aim of this research is to re-examine the dynamic linkages between macroeconomic variables and the stock market indices in Malaysia following some transformational changes in the policies and the exchange rate regime.

Using monthly data points for all the economic variables and the stock market index (KLCI Index), the authors applied vector autoregression (VAR) model to examine the relationship. The authors also used impulse response function (IRF) in order to explore the effect of one-unit shock in “X” on “Y” under the VAR environment.

The authors' study finds a significant relationship between all the macroeconomic variables and the stock market index of Malaysia. The cointegration results indicate a long-term relationship, whereas the vector autoregressive-based impulse response analysis suggests that the Malaysian stock index (KLCI) responds negatively to the money supply, inflation and producer price index (PPI). However, the authors' results indicate a positive response from the stock index to the exchange rate.

The authors' study's results are based on selected macroeconomic variables and the VAR model. Researchers may find other variables and methods more useful and may provide findings accordingly.

Since the results are quite asymmetric, it would be interesting for the market players, policymakers and regulators to consider the findings and explore appropriate opportunities.

While the relationship between macroeconomic variables and stock market indices has been widely examined, a significant gap in the literature remains concerning the role of exchange rate variable on the stock market in an emerging economy context.

We describe the application of a nested logit function for modelling consumer brand choice using household transaction data from the Indian market. This is unique since it is one of the first attempts to integrate disparate consumer information sources available at various levels of aggregation towards developing a prediction model for brand market share in India. We test the usefulness of the model for forecasting brand market share in the premium detergents market in Mumbai, India. The results of the model building exercise reveal the importance of advertising, specifically the role of ad message in influencing brand choice. It is concluded that such modelling initiatives show significant returns for market planning exercises in developing markets. However, the need for streamlining the collection of market data and its subsequent organization in a form that can help develop more portent prediction models is apparent.