Search results

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

This paper investigates if investors consider legal insider trading data while making investment decisions. If any investment decision is based on insider transactions, then it will result in abnormal stock characteristics. The purpose of this paper is to investigate if insider trading affects stock characteristics like price, return and volume. The paper further investigates the effect on stock characteristics after the trade of different types of insiders and the relationship between abnormal return and abnormal volume.

The study uses the event study method to measure the abnormal price, return and volume. Two-stage least square regression is used to investigate the relationship between abnormal return and abnormal volume.

The insider trades affect price, return and volume. The results are identical for both buy and sell transactions. The trades of different types of insiders have diverse effects on stock characteristics. The trades of substantial shareholders give rise to the highest abnormal price and return, whereas the promoters' trades result in the highest abnormal volume. No relationship is detected between abnormal return and volume.

A novel method to calculate the abnormal price is proposed. The effect of trading of all types of insiders on stock characteristics is analyzed. The relationship between abnormal return and abnormal volume, after an insider trade, is investigated.

Stakeholders' uncertainty about firms' value drives their urge to get information, as well as managerial disclosure choices. In this study, the authors examine whether and how an important source of uncertainty – the recent COVID-19 pandemic's effect on corporate social responsibility (CSR) disclosure – is beyond managerial and stakeholders' control.

The authors develop a novel construct for daily CSR disclosure by employing computer-aided text analysis (CATA) on the press releases issued by 125 New Zealand Stock Exchange (NZX) listed from 28 February 2020 to 31 December 2020. To capture COVID-19 intensity, the authors use the growth rate of the population-adjusted cumulative sum of confirmed cases in New Zealand on a specific day. To examine the association between the COVID-19 outbreak and companies' CSR disclosure, the authors employed ordinary least squares (OLS) regression by clustering standard error at the firm level.

The authors find a one standard deviation increase in the COVID-19 outbreak leads to a 28% increase in such disclosures. These results remained robust to a series of sensitivity tests and continue to hold after accounting for potential endogeneity concerns. In the channel analysis, the study demonstrates that the positive relationship between COVID-19 and CSR disclosure is more pronounced in the presence of a well-structured board (i.e. a large, more independent board and with a higher proportion of women on it). In further analysis, the authors find the documented relationship varies over the pandemic's life cycle and is moderated by government stringency response, peer CSR pressure and media coverage.

This paper is the first study that contributes to the scant literature examining the impact of the COVID-19 outbreak on CSR disclosure. Prior research either investigates the relationship of the CSR-stock return during the COVID-19 market crisis or examines the relationship between corporate characteristics including the quality of financial information and the reactions of stock returns during COVID-19. The authors extend such studies by providing empirical evidence that managers respond to COVID-19 by increasing CSR disclosure.

The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ value (local density) and δ value (the distance between a point and another point with a higher ρ value). According to the center-identifying principle of the DP, the potential cluster centers should have a higher ρ value and a higher δ value than other points. However, this principle may limit the DP from identifying some categories with multi-centers or the centers in lower-density regions. In addition, the improper assignment strategy of the DP could cause a wrong assignment result for the non-center points. This paper aims to address the aforementioned issues and improve the clustering performance of the DP.

First, to identify as many potential cluster centers as possible, the authors construct a point-domain by introducing the pinhole imaging strategy to extend the searching range of the potential cluster centers. Second, they design different novel calculation methods for calculating the domain distance, point-domain density and domain similarity. Third, they adopt domain similarity to achieve the domain merging process and optimize the final clustering results.

The experimental results on analyzing 12 synthetic data sets and 12 real-world data sets show that two-stage density peak clustering based on multi-strategy optimization (TMsDP) outperforms the DP and other state-of-the-art algorithms.

The authors propose a novel DP-based clustering method, i.e. TMsDP, and transform the relationship between points into that between domains to ultimately further optimize the clustering performance of the DP.

This study aims to examine brand personality and its application to political branding. This study focuses on the brand personality of a political leader from the BJP Party brand (Bharatiya Janta Party). The development of a strong political brand personality is crucial for success at the polls. Little research has been dedicated to this phenomenon particularly beyond Western political and post-election contexts.

The scope and development of the study required a qualitative approach. The theoretical frameworks of the study acted as the deductive base of the study. The insights of the respondents were the inductive base of the study. Semi-structured interviews were conducted with external stakeholders [voters]. In addition, semi-structured interviews were also adopted to capture the branding activities used by internal stakeholders [BJP].

The brand personality dimensions such as sincerity; agreeableness, competence, energy, openness, conscientiousness and emotional stability were clearly associated with a political leader. Negative qualities such as dictatorial attitudes and arrogance affected the political leader’s brand personality. Religious partisanship was another strong negative trait affecting the brand personality of the political leader.

The study has an actionable framework for political brand personality in the post-election context. It offers negative qualities to be avoided in the development of the political brand personality of the leader. It offers insights about the political brand personality of the leader in terms of young digitally savvy voters.

Este trabajo examina la aplicación de la personalidad de marca al ámbito del marketing político y de la marca personal política. Concretamente se centra en la personalidad de marca de un líder político del partido Bharantiya Janta Party (BJP). El desarrollo de una fuerte marca personal política es crucial para el éxito en las elecciones. Pocos trabajos se han centrado hasta el momento en este fenómeno más allá del contexto político occidental.

El alcance y desarrollo del estudio requirió la adopción de un enfoque cualitativo. El marco teórico sirvió de base deductiva al tiempo que las entrevistas realizadas sirvieron de base inductiva. Estas entrevistas fueron semi-estructuradas y dirigidas a grupos de interés externos del BJP (los votantes). Además, se realizaron entrevistas también semi-estructuradas para capturar las actividades de marca desarrolladas por los grupos de interés internos (candidatos, políticos, trabajadores y gerentes del partido).

Las dimensiones de personalidad de marca sinceridad, competencia, energía, estabilidad emocional, franqueza y escrupulosidad están claramente asociadas con un líder político. Por el contrario, rasgos negativos como las actitudes arrogantes y dictatoriales dañan la personalidad de marca de dicho líder, pero sobretodo el partidismo religioso.

El trabajo proporciona un marco de acción para la marca personal política en un contexto post-electoral. Proporciona indicaciones de los rasgos y cualidades negativas que deben de evitarse en el desarrollo de una marca personal para un líder político. Ofrece también evidencias sobre la personalidad de marca que tiene que desarrollar un líder de cara a los votantes más dinámicos y digitales.

Asset pricing revolves around the core aspects of risk and expected return. The main objective of the study is to test different asset pricing models for the Indian securities market. This paper aims to analyse whether leverage and liquidity augmented five-factor model performs better than Capital Asset Pricing Model (CAPM), Fama and French three-factor model, leverage augmented four-factor model and liquidity augmented four-factor model.

The data for the current study comprises records on prices of securities that are part of the Nifty 500 index for a time frame of 14 years, that is, from October 2004 to September 2017 consisting of 183 companies using time series regression.

The results indicate that the five-factor model performs better than CAPM and the three-factor model. The model outperforms leverage augmented and liquidity augmented four-factor models. The empirical evidence shows that the five-factor model has the highest explanatory power among the entire asset pricing models considered.

The present study bears certain useful implications for various stakeholders including fund managers, investors and academicians.

This study presents a five-factor model containing two additional factors, that is, leverage and liquidity risk along with the Fama-French three-factor model. These factors are expected to give more value to the model in comparison to the Fama-French three-factor model.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

This study aims to investigate the key determinants predicting users’ behavioural intention (BI) in adopting mobile payment (m-payment) in the new normal era.

The mobile technology acceptance model (MTAM) was extended through attitudes, perceived trust, perceived risk and personal innovativeness (PI) with government support (GS) functioning as a moderator. A total of 245 valid responses were gathered from Malaysian m-payment users with purposive sampling and subsequently evaluated through partial least square-structural equation modelling.

Mobile usefulness and PI significantly predicted user BI to use m-payment. Based on the moderation analysis, GS strengthened attitude-based impacts on BI towards m-payment adoption.

The empirical outcomes provide stakeholders with pivotal implications to develop holistic policies and strategies that potentially catalyse m-payment usage in the new normal era.

This research expands the current body of knowledge by assessing the factors impacting m-payment usage intention in the new normal era. The four aforementioned MTAM elements and GS (moderator) were recommended to boost model workability and offer novel evidence from a distinct viewpoint.

El objetivo de este estudio es investigar los determinantes clave que predicen la intención de comportamiento de los usuarios a la hora de adoptar el pago por móvil (m-payment) en la nueva era normal.

El modelo de aceptación de la tecnología móvil (MTAM) se amplió a través de las actitudes, la confianza percibida, el riesgo percibido y la capacidad de innovación personal, con el apoyo gubernamental como moderador. Se recogió un total de 245 respuestas válidas de usuarios malasios de pago por móvil mediante muestreo intencionado y se evaluó posteriormente mediante modelización de ecuaciones estructurales por mínimos cuadrados parciales (PLS-SEM).

La utilidad del móvil y la capacidad de innovación personal predijeron significativamente la intención de los usuarios de utilizar el pago por móvil. Según el análisis de moderación, el apoyo gubernamental reforzó los efectos basados en la actitud sobre la intención conductual de adoptar el pago por móvil.

Los resultados empíricos proporcionan a las partes interesadas implicaciones fundamentales para desarrollar políticas y estrategias holísticas que catalicen potencialmente el uso del pago móvil en la nueva era de la normalidad.

Esta investigación amplía el corpus actual de conocimientos al evaluar los factores que influyen en la intención de uso del pago por móvil en la nueva era normal. Se recomiendan los cuatro elementos MTAM mencionados y el apoyo gubernamental (moderador) para impulsar la viabilidad del modelo y ofrecer pruebas novedosas desde un punto de vista distinto.

本研究旨在探讨新常态时代用户使用移动支付（m-payment）行为意向的主要决定因素。

通过态度、感知信任、感知风险和个人创新能力, 并以政府支持作为调节因素, 对移动技术接受模型（MTAM）进行了扩展。通过有目的的抽样, 从马来西亚移动支付用户中收集了 245 份有效回复, 随后通过偏最小二乘法结构方程模型（PLS-SEM）进行了评估。

移动实用性和个人创新性可显著预测用户使用移动支付的行为意向。根据调节分析, 政府支持加强了态度对采用移动支付的行为意向的影响。

实证研究的结果为利益相关者提供了重要的启示, 有助于他们制定全面的政策和战略, 在新常态时代促进移动支付的使用。

本研究通过评估新常态时代影响移动支付使用意向的因素, 拓展了现有的知识体系。研究推荐了上述四个 MTAM 要素和政府支持（调节器）, 以提高模型的可操作性, 并从一个独特的视角提供了新的证据。

The purpose of this study is to extend the research on fashion renting (FR) by investigating how personal and social motives (i.e. “subjective norms”, “perceived behavioural control”, “sustainable orientation” and “FR benefits”) affect consumers’ attitudes and intentions towards it. In addition, personality traits are investigated as potential antecedents of FR, resulting in the proposal of an overall framework that combines the theory of planned behaviour with the trait theory approach.

Data were collected in Italy from a sample of 694 consumers, mainly females (88%), with an average age of 28.8 years and coming from all over the country. The collected data were then processed via structural equation modelling.

The results indicated that intention towards FR is influenced by attitude, which, in turn, is affected by social norms, perceived behavioural control, sustainable orientation and FR benefits. Furthermore, only fashion leadership acts as a direct antecedent of FR attitude, while the need for uniqueness and materialism plays critical roles as predictors of personal and social motives. Subjective norms and perceived behavioural control also serve as mediators of the significant relationships between personality traits and attitudes towards FR.

The study provides useful implications for fashion rental companies in attracting consumers and offers a foundation for further research on transforming traditional consumption into a more sustainable one.

The study presents new knowledge on the rental phenomenon in the fashion sector by responding to the call to deepen the analysis of factors that influence consumers’ adoption of FR from the perspectives of personal and social motives and personality traits.

This paper aims to improve our understanding of performance measurement systems in the health and care sector, by focussing on employee reactions to core performance measurement practices. Targets and monitoring are hypothesised to be associated with employee perceptions of job control, supportive management and job demands, which in turn, are expected to be linked to employee-wellbeing and organisational commitment.

Matched employee workplace data are extracted from a nationally representative and publicly available survey. Structural equation models are estimated.

Performance measurement systems are neither perceived as resources nor additional demands. Setting many targets and a focus on productivity can lead to negative employee outcomes, since these positively correlate with perceptions of job demands, which negatively correlate with employee wellbeing. However, monitoring financial performance and monitoring employee performance may be helpful to managers, as these are positively associated with employee perceptions of job control and supportive management, which positively correlate with job satisfaction and organisational commitment and, negatively, with anxiety. Overall, common criticisms of performance measurement systems in healthcare are questioned.

Given the lack of consensus on how performance measurement systems can influence employee experiences and outcomes, this study combines theories that argue for performance measurement systems in managing operations with models developed by psychologists to describe how perceptions of the work conditions can affect employee attitude and wellbeing. A conceptual model is therefore developed and tested, and potential direct and indirect effects of performance measurement systems in the health sector are inferred.