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Prospective students and other stakeholders in the education system use global and national rankings as a measure of the quality of education offered by different higher educational institutions. The ranking of an Institution is seen as a measure of reputation and has a significant role in attracting students. But are students happy in the top-ranked institutions? Does a high rank translate into high student satisfaction? This study answers this question taking data from top educational institutions in India.

This study examines how the top-ranked higher education institutions in India fare on student satisfaction. Using the data on key performance indicators published by the National Institutional Ranking Framework (NIRF) and student satisfaction scores of these institutions reported by NAAC, the study explores a possible relationship between the ranking of an institution and its student satisfaction score.

The study finds no significant relationship between the ranking of an institution and its student satisfaction score. The only institutional performance dimension which has a positive correlation with student satisfaction is graduate outcome. The diversity dimension is seen to be negatively correlated with student satisfaction.

The importance of modifying the ranking frameworks to account for the real drivers of student satisfaction is highlighted. The items in the student satisfaction survey should be regularly updated to reflect the actual concerns of the students. This is very important given the fact that the number of Indian students going abroad for higher education recorded a six-year high in 2022 at 750,365.

With more than 50,000 institutions catering to over 40 million students, India has the largest higher education system in the world. Given the high level of competition among these institutions, ranking and accreditation have become important parameters used by students for selection of an institution. But do top-ranked higher education institutions have the most satisfied student community? The assumption is disproved using the most credible secondary data. This study is the first of its kind in the Indian context. It has huge implications for the most respected ranking frameworks.

This paper investigates the stock market reaction to three different events related to the UEFA Champions League – the announcements of draws, odds and match results. The aim of the paper is to test whether these events are informative for stock market operators, i.e. whether they produce abnormal returns.

Applying the event study methodology, the authors investigate the stock market reaction before (at two events: the draw date and on the release of betting odds) and after the matches of 11 listed soccer teams in the period 2003–2019. The authors also conduct OLS regression analyses in order to disentangle the impact of firm specific variables and match characteristics on cumulative abnormal returns.

This paper finds that match outcomes affect the stock market performance of listed teams, while the announcements of draws and odds do not. More specifically, the market does not consider match outcomes involving wins and ties as informative events, while it penalizes losing teams. Moreover, investor reactions to events related to the UCL competition depend more on match characteristics than on company specific variables.

The study enriches the ongoing debate about the impact of soccer team results on stock market performance in several ways: using the widest time span ever adopted in this area; focusing on UCL, which is the most important soccer competition played by private clubs; disentangling for the first time the effects of draws, odds release and sporting outcome on stock returns of listed soccer clubs.

Academic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.

Using data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.

Our analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.

Our results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

Using data from 36,981 respondents to the Global Drug Survey (GDS) COVID-19 Special Edition, this study aims to compare changes, following the first “lockdown,” in alcohol consumption between lesbian, gay, bisexual and other sexual minority (LGB+) and heterosexual respondents with and without lifetime mental health and neurodevelopmental (MHND) conditions.

Characteristics and drinking behavior of respondents to GDS who disclosed their sexual orientation and past 30-day alcohol use were described and compared. LGB+ participants with and without MHND conditions were compared, and logistic regression models identified correlates of increased drinking among LGB+ people. The impact of changed drinking on the lives of LGB+ participants with and without MHND conditions was assessed.

LGB+ participants who reported that they were “not coping well at all” with the pandemic had twofold greater odds of reporting increased binge drinking. LGB+ participants with MHND conditions were significantly more likely than those without to report increased drinking frequency (18.7% vs 12.4%), quantity (13.8% vs 8.8%) and that changed drinking had impacted their lives.

This study, which has a uniquely large and international sample, explores aspects of alcohol use not considered in other COVID-19 alcohol use research with LGB+ people; and to the best of the authors’ knowledge, this is the first study to explore alcohol use among LGB+ people with MHND conditions.

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with the aim of elucidating the underlying economic principles governing this dynamic interplay.

Using monthly data of China, the authors use the asymmetry nonlinear autoregressive distributed lag (NARDL) model to test for nonlinearity in the relationship between land supply price and urban housing prices.

The empirical results confirm the existence of an asymmetric relationship between land supply price and urban housing prices. The authors find that land supply price has a positive and statistically significant impact on urban housing prices when land supply is increasing. Policymakers should strive to strike a balance between safeguarding residents’ housing rights and maintaining market stability.

Although the asymmetric effect of land supply price has been identified as a significant contributor in this study, it is important to note that the research primarily relies on time series data and focuses on analysis at the national level. Although time series data offer a macroscopic perspective of overall trends within a country, they fail to adequately showcase the structural variations among different cities.

To ensure a stable housing market and meet residents’ housing needs, policymakers must reexamine current land policies. Solely relying on restricting land supply to control housing prices may yield counterproductive results. Instead, increasing land supply could be a more viable option. By rationally adjusting land supply prices, the government can not only mitigate excessive growth in housing prices but also foster the healthy development of the housing market.

First, the authors have comprehensively evaluated the impact of land supply prices in China on urban housing sales prices, examining whether they play a facilitating or mitigating role in the fluctuation of these prices. Second, departing from traditional linear analytical frameworks, the authors have explored the possibility of a nonlinear relationship existing between land supply prices and urban housing sales prices in China. Finally, using an advanced NARDL model, the authors have delved deeper into the asymmetric effects of land supply prices on urban housing sales prices in China.

Many studies have shown that from a theoretical and empirical point of view, downside risk-based measures of risk are better than the traditional ones. Despite academic appeal and practical implications, downside risk has not been thoroughly examined in markets outside developed country markets. Using downside beta as a measure of downside risk, this study examines the relationship between downside beta and stock returns in Indian equity market, an emerging market with unique investor, asset and market characteristics.

This is an empirical study done by using ranked portfolio return analysis and regression analysis methodologies.

The study results show that downside risk, as measured by downside beta, is distinctly priced in the Indian equity market. There is a direct positive relationship between downside beta and contemporaneous realized returns, indicating a premium for downside risk. Downside risk carries a higher weightage than upside potential in the aggregate return of the stock portfolios. Downside beta is a better measure of systematic risk than conventional market beta and downside coskewness.

The empirical results support the adoption of downside beta in practice and provide a case for replacing traditional beta with downside beta in asset pricing applications, trading and investment strategies, and capital allocation decision-making.

This is one of the first in-depth studies examining downside beta in Indian equity markets using a broad sample of individual stock returns covering a wide time range of 22 years. To the best of our knowledge, this study is the first one to compare downside beta and downside coskewness using individual stock data from the Indian equity market.

The fear of the pandemic, confinement at home and the need to work created a unique situation. The pandemic catalyzed work-from-anywhere practice by adopting information and communication technologies (ICT) across all industries. While ICT saved organizations, it increased technostress among the workforce. A better understanding of the adverse effects of ICT usage might enable organizations to manage the mental well-being of the workforce. While technostress is gaining increasing interest, scholarly work investigating the dimensions of technostress and its impact on creating stress across various employee demographics and industry types is missing. Contrary to the prevalent assumptions, the authors theorized and tested the adverse moderation effect of the home-work interface on the linkage between technostress dimensions and stress. This paper aims to discuss the aforementioned objective.

The study captures dimensions of technostress and the resulting stress at work using a survey-based analysis of 881 working employees in India, representing multiple industries and functions.

The study indicates that techno-overload, techno-complexity and techno-invasion significantly impact employees during the pandemic. The authors further found that the home-work-interface is a powerful factor in understanding the complex linkage between dimensions of technostress and its outcomes.

Based on the Conservation of Resources Theory and the Job-Demand-Resources model, this study highlights the adverse impact of this trend on employee well-being. However, the study suffers from a cross-sectional research design. The technostress research has focused primarily on static, at-premise environments and mostly on high ICT usage industries. Due to the pandemic, it has neglected the impact of various technostress dimensions across employee cohorts subjected to rapid technology-enabled working. Further, most studies focus on the voluntary choice of remote work. Employees struggle with the unexpected and involuntary shift to technology-enabled remote work. This study contributes to the literature by examining the consequences of technostress in the context of non-voluntary remote work. Contrary to prevailing assumptions, this study highlights the adverse effect of organizational home-work interface in influencing ICT-created stress.

The increasing use of ICT enables telecommuting across the workforce while increasing organizational productivity. Due to the pandemic, these trends will likely change the future of work permanently. To minimize employee stress, practitioners need to reconsider the dimensions of technostress. Further, the study cautions against the prevalent interventions used by practitioners. While practitioners facilitate a home-work interface, it could have adverse consequences. Practitioners may consider the adverse consequences of home-work interface while designing organizational policies.

This study during the pandemic is crucial as research forecasts the likelihood of other cataclysmic events, such as future pandemics and political or climate change events, which may sustain technology-driven remote work practices and remain a feature of the future workplace. Hence understanding the implications of the dimensions of technostress would help organizations and policymakers to implement necessary interventions to minimize employee stress.

The present study examines the dimensions of technostress across multiple industries and job functions in an emerging market marked by a high economic growth rate and an Eastern cultural context. This study presents the dark side of excessive ICT adoption and indicates how organizations and HRM practices can help mitigate some of these effects.

To remain sustainable, open source software (OSS) projects must attract new members—or newcomers—who make contributions. In this paper, the authors develop a set of hypotheses based on the knowledge barriers framework that examines how OSS communities can encourage contributions from newcomers.

Employing longitudinal data from the source code repositories of 232 OSS projects over a two-year period, the authors employ a Poisson-based mixed model to test how community characteristics, such as the main drivers of knowledge-based costs, relate to newcomers' contributions.

The results indicate that community characteristics, such as programming language choice, documentation effort and code structure instability, are the main drivers of knowledge-based contribution costs. The findings also suggest that managing these costs can result in more inclusive OSS communities, as evidenced by the number of contributing newcomers; the authors highlight the importance of maintaining documentation efforts for OSS communities.

This paper assumes that motivational factors are a necessary but insufficient condition for newcomer participation in OSS projects and that the cost to participation should be considered. Using the knowledge barriers framework, this paper identifies the main knowledge-based costs that hinder newcomer participation. To the best of the authors' knowledge, this is the first empirical study that does not limit data collection to a single hosting platform (e.g., SourceForge), which improves the generalizability of the findings.

The primary objective of the paper is to examine the asymmetric Cointegration and asymmetric causality between financial development and poverty alleviation on annual data in Indian context over the period from 1980 to 2019.

First nonlinearity test by Brooks et al. (1999) is applied to ascertain the nonlinear behavior of the variables used. Once the nonlinear behavior of variables is confirmed, asymmetric and nonlinear unit root tests by Kapetanios and Shin (2008) are applied to check for the order of integration of selected variables. Next, nonlinear autoregressive distributed lag model (NARDL) is employed to analyze the asymmetric Cointegration. Finally, Hatemi-j- asymmetric causality tests is applied to work out the direction of asymmetric causality.

The empirical findings document the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The findings of Wald's test also confirm the presence of asymmetric Cointegration. The asymmetric cumulative dynamic multipliers used to examine the behavior of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator. This result exhibits the robustness of the model. Furthermore, the result emanating from recently introduced asymmetric causality test reveals a unidirectional asymmetric causality between negative shocks in financial development and poverty. The findings of the present study necessitate the need for investigating asymmetric and nonlinear effects in finance–poverty nexus, which existent literature has completely neglected, in order to have relevant policy conclusions.

The study used “Per capita consumption expenditure” as a measure for poverty due to lack of continuous time series data on headcount ratio. In future, researchers can extend this study by incorporating headcount ratio as a measure of poverty in their respective works. There is further scope of research on this issue by finding out the impact of formal and informal sources of credit on poverty separately. A panel data study for developing countries over a period of time could further confirm/negate the findings of the present study.

To the best of the authors’ knowledge none of the studies in Indian context has scrutinized asymmetric and nonlinear impact of financial development on poverty. To dredge up asymmetric structures at work, the authors have used the highly celebrated NARDL estimator. To enrich the existent body of knowledge along the lines of asymmetric (nonlinear) linkages, the authors have also used recently introduced asymmetric causality test by Hatemi-j-(2012) to find out the direction asymmetric causality.

This study aims to investigate whether social media use (SMU) at work has a curvilinear effect on job performance and whether Cyberloafing (non-work-related use) and job complexity moderate this effect.

Online surveys were conducted in China among WeChat users from multiple organizations working in the office environment, generating 350 valid responses.

The results revealed that there is an inverted U-shaped relationship between SMU at work and job performance through mediations of communication, information sharing and entertainment; such that the relationship is initially positive but becomes weaker as SMU increases and exceeds the optimal level. Notably, it is found that Cyberloafing negatively moderates the relationship between SMU and job performance, and there is a significant joint moderating effect of job complexity and Cyberloafing.

This study improves the research of information system use. It also provides implications for organizations concerned about formulating policies related to individuals' SMU and suggests that SM users and managers should find strategies to arrive at without surpassing the optimal level to maximize productivity.

This paper enriches the job demands-resources model to extend the literature on the advantages and disadvantages of SMU at work, which indirectly affect performance through two job conditions (job resources and demands). The study finds that employees benefit from a moderate amount of SMU at work, once it surpasses the optimal level, job demands surpass job resources and counterproductivity will appear. In addition, Cyberloafing and job complexity moderate the optimal level of SMU at work, which have not yet been investigated.