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Economic theory suggests that profits of firms in industries with higher competition are less persistent and more volatile than in industries with lower competition (Stigler, 1963; Mueller, 1977). Extending this reasoning, I hypothesize that accounting-based fundamentals are more effective in predicting performance in industries with lower competition. I find that a measure of fundamentals (Piotroski’s F-score) has greater ability to identify potentially mispriced securities in industries with lower competition. The results are robust to using a variety of competition measures and imply that industry competition is an important consideration in the application of fundamental analysis.

What explains patterns in stock prices is an important question. One such pattern, price momentum, is a well-known capital markets anomaly where recent stock price performance appears to continue into the future. This momentum is frequently thought to reflect delayed reaction by investors to unspecified information (i.e. underreaction). This study aims to provide a useful insight regarding momentum: potential mispricing related to accounting fundamentals appears to conceal longer-term reversals in price momentum. Controlling for these fundamentals reveals that price momentum reverses, indicating that investor overreaction is a potentially important source of stock price momentum. The evidence presented in this study emphasizes the importance of decoupling momentum and accounting fundamentals to achieve a more complete understanding of what explains stock price momentum.

This study explores this question by examining the longer-term performance of momentum stocks in the US market after decoupling it from performance related to accounting fundamentals using returns to fundamentals-based factors as controls in time series regressions.

This study finds evidence of clear reversals in the remaining price momentum. These reversals provide a new insight into the momentum effect because they imply that the component of price momentum not traceable to accounting fundamentals reflects investor overreaction rather than underreaction.

The findings indicate that the underlying nature of the information driving price movements is important to achieving a complete understanding of what explains price momentum. To the best of the author’s knowledge, no other study has examined the behavior of stock price momentum while controlling for accounting fundamentals.

Prior evidence that financial reporting quality (FRQ) of publicly listed firms improves investment efficiency in developed markets leaves unaddressed questions of whether this relationship holds in emerging and frontier markets and what channels influence this relationship. This study aims to test the role of financial constraints faced by firms and managerial risk-taking on the association of FRQ and investment efficiency in 13,231 publicly listed firms in 24 emerging and frontier markets.

Available accounting data from 1998 to 2022 are collected for all listed firms across 41 industries in 24 countries. Causal relationships are tested using fixed-effect regression analysis, several additional tests and robustness checks are applied using alternative proxies and concerns for endogeneity are addressed using two-stage least square and system generalised method of moments analysis.

Findings show that FRQ of firms in emerging and frontier markets positively affects investment efficiency, the affirmative impact of FRQ on investment efficiency is higher when firms are facing more financial constraints and when managerial risk-taking is lower and financial constraints and risk-taking have a more pronounced impact on the link between FRQ and investment efficiency in the under-investment scenario.

These findings contribute to the growing body of evidence, shedding light on the meticulous interplay between FRQ and investment efficiency in frontier and emerging markets. Specifically, the increased financial constraints encountered by firms and a more conservative approach to managerial risk-taking emerge as crucial factors complementing this relationship.

This research is designed to explore the relationship between social media addiction, student engagement and student retention. Social media addiction is dealt with as an independent variable student engagement acts as a mediating variable and student retention as a dependent variable.

This is a cross-sectional and quantitative research. Primary data are collected from 600 respondents (university students) with the help of a structured questionnaire. Multistage sampling techniques, i.e. simple random sampling and judgment sampling, are used for the selection of respondents.

Results indicate that for direct relationships, social media addiction has a significant positive impact on student engagement and student retention, respectively, while student engagement is partially mediating the relationship between social media addiction with student retention.

In the future, these kinds of research may also be conducted on students of different universities in Pakistan, which are located in other cities of Pakistan besides Lahore. This research provides a practical framework for the higher authorities of the universities of Pakistan and explains how the use of media positively fosters the levels of student retention directly and indirectly through the path of student engagement. It is commonly believed that media addiction is bad but the result of this research indicates that anything is not dangerous but depends upon its use, media addiction itself is not bad but if someone uses this for a good purpose in limitation then it has better outcomes. The result indicates that the media addiction of students has a positive impact on student retention. This means that if someone uses media for a positive purpose then he/she will use it as a supporting tool for success. Longitudinal research on these variables will also help to check the status after a specific interval of time.

The current study will help the practitioners or policymakers (Managers) of higher education institutions by providing practical insights into the positive use of media by students for increasing their knowledge and grades. This research can also help practitioners or policymakers to focus their students on the positive use of social media for fostering the levels of student retention.

To the best of the researcher’s knowledge, no previous study has been done to incorporate social media addiction and student engagement in a single model in the Pakistani cultural context. Similarly, the relationship of variables social media addiction with student engagement is rarely checked empirically because the research of Wang et al. (2011) proposed that social media addiction has a relationship with student engagement so that is why this is the rationale of the research is to check this empirically. Moreover, this study is an initial effort to check the mediating effect of student engagement in the relationship between social media addiction and student retention. This research is also proposing the framework of social media addiction, student engagement and student retention based on the social exchange theory (SET).

Are the capital markets of leading industrialized nations rational and efficient? This powerful hypothesis was badly dented by the work of De Bondt and Thaler (1985) on stock market overreaction and by subsequent research on momentum and reversals in prices and earnings.

Human psychology, at times predictably irrational, drives the markets. This paper investigates this issue.

The author reviews the origins of the idea of overreaction, how behavioral insights modify standard asset pricing theory and how they contribute to our understanding of the world of finance.

The paper reveals the origins of the idea of overreaction, how behavioral insights modify standard asset pricing theory and how they contribute to our understanding of the world of finance.

The purpose of this paper is to analyze the market response of the aerospace and defense industry and the airline industry to the ongoing conflict between Ukraine and Russia based on the sentiments from war-related news articles over the period from October 2021 to June 2022.

The study uses the news article database of Global Database of Events, Languages and Tone (GDELT) to create a new set of variables that reflect the news sentiment regarding war and conflict. By investigating the newly created sentiment variables in combination with traditional event study methodology, the authors seek to find out whether sentiment indicators can be helpful to rationalize the evolution of the different stock markets before and after the conflict.

The authors' results point out a significant negative impact of the war on the airline market and a positive impact on the defense market. The authors' study also introduces a new set of war-related news-based sentiment variables that is significant to explain the evolution of the two markets before and after the war. The relationships between this study's new set of variables and the performance of the two markets are also proven to be significantly impacted by the invasion.

To the best of the authors' knowledge, this is the first research to use the news sentiment related to the topic of war and conflict to explain the market movement of different industries during the Ukraine invasion.

The present study aims to examine the current digital information literacy (DIL) skills of female online shoppers in Lahore city of Pakistan. Data were gathered from a purposive sampling of women, aged between 20–50 years who were buying products online, not from the traditional retail stores. Out of 309 received questionnaires, 269 responses were useable and were utilized for data analysis. Descriptive and inferential statistics were used to deduce inferences.

Quantitative research approach was employed for this study, and a survey was conducted to collect the data from the study's respondents. For data analysis, descriptive and inferential statistics were used.

Results revealed that the digital information literacy skills of women were good to a moderate level. However, they were not confident in applying advanced searching options. In accordance with what was hypothesized in a directional hypothesis, DIL was found to be a strong predictor of online shopping behavior of women, consequently highlighting the importance of such competencies in modern life. Other findings illustrate that participating women rarely engaged in online shopping and felt hesitation in using credit/debit card for online transactions.

These observations highlight the important role of information professionals in creating digital literacy among different population groups, specifically women, by planning digital information instruction through courses, workshops and trainings. This could eventually be possible with the dynamic role of librarians or information professionals in the society.

The present study adopts the unique approach of measuring online shopping behavior of female shoppers in connection with their digital information literacy skills.

This study intends to unmask the antecedents of metaverse adoption intention (MAI) within the Indian hospitality industry. To achieve this objective, we extended the “unified theory of acceptance and use of technology” (UTAUT) by integrating additional constructs: “perceived cyber risk” (PCR), “trust” (TR), “personal innovativeness in IT” (PIT) and “hedonic motivation” (HM).

A quantitative research methodology was employed, utilizing data gathered through an online survey disseminated via Google Forms to evaluate the constructs of the study. Convenience and snowball sampling were used, and the proposed relationships were analyzed using “partial least squares structural equation modeling” (PLS-SEM).

The study presents a robust model explaining MAI among Indian hospitality consumers, with a high R² of 81%, indicating strong predictive relevance. Core UTAUT constructs (PE, EE, SI and FC) and additional constructs (TR, HM and PIT) positively influence MAI, while PCR negatively impacts it.

This research enhances the existing body of knowledge by providing a deeper insight into metaverse adoption among hospitality consumers in India. The proposed framework provides a more nuanced perspective on metaverse adoption, extending beyond conventional technological factors.

This study is distinctive in its integration of four additional constructs- PCR, TR, PIT and HM- into the original UTAUT model, thereby addressing a gap in the existing literature. Furthermore, it advances the understanding of the metaverse by identifying key antecedents influencing MAI among Indian hospitality consumers.

Pharmacy services start right from prescribing medicines and continue as the medication’s effect is monitored. Hospital and community pharmacy staff promote rational prescribing and medicine use. Consequentially, pharmacy is a complex and busy field. Often there are peak workload hours when patients must wait, which is associated with patient dissatisfaction that may negatively affect patient experience and the organisation’s reputation. The purpose of this paper is to enlist techniques, methods and technological advancements that have been successfully employed to reduce patient waiting time.

A database search was conducted in 2017 to locate articles addressing methods and technologies that reduce pharmacy waiting time. The literature revealed various techniques and technologies like queuing theory, tele-pharmacy, evidence-based pharmacy design, automated pharmacy systems (robotics), system modelling and simulation and the Six Sigma method for identifying potential problems associated with increased wait time.

The authors conclude that various techniques and methods, including automated queuing technology, tele-pharmacy, automated pharmacy devices/machines for quick and accurate filling and dispensing, computer simulation modelling, evidence-based pharmacy infrastructure for smooth workflow and Six Sigma can maintain customer satisfaction, reduce waiting time, attract new customers, decrease workload and improve the organisation’s reputation.

The authors conclude that various techniques and methods, including automated queuing technology, tele-pharmacy, automated pharmacy devices/machines for quick and accurate filling and dispensing, computer simulation modelling, evidence-based pharmacy infrastructure for smooth workflow and Six Sigma methodology can maintain customer satisfaction, reduce waiting time, attract new customers, decrease workload and improve the organisation’s reputation.

The authors carried out a literature search and identified the techniques that have been successfully implemented to reduce pharmacy patient waiting time and methods that can identify potential process behind medication dispensation delays.

This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice.

A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare.

The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI’s role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology.

This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.