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With the rising concerns of compulsive use of social media, it is important to understand why users develop such unplanned and irrational behaviors. Leveraging the uses and gratification theory, the authors aim to explore the determinants of compulsive use of social media from the dual perspectives of individual needs (need to belong (NTB) and need for uniqueness) and peer-related factors (referent network size and perceived peer activeness). Due to the importance of self-construal in cognitive deliberation on peer influences, the moderating effects of self-construal were taken into consideration.

The authors empirically test their model by conducting an online survey with 459 WeChat users.

The results show that compulsive use of social media is predicated by both individual needs and influence from peers. Moreover, peer influence could be attenuated when individuals develop a high degree of independent self-construal.

The authors' study contributes to the research of compulsive behavior in the context of social media use by incorporating the dual effects of individual needs and social influence. The authors also offer managerial insights on eradicating the formation of compulsive behaviors.

The authors examine the dual effects of individual needs and peer influence in predicting compulsive use of social media and the moderating role of self-construal, which have been rarely investigated in this context.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

Drawing on the stimulus-organism-response (SOR) model, this study examines how live-streaming shopping influences purchase intentions in young consumers. The multigroup analysis is applied to understand the similarities and differences of factors that trigger purchase intentions among buyers and non-buyers in live-streaming shopping.

A snowball sampling was used to collect data from 507 Chinese consumers between June and September 2022 using Wenjuanxing, i.e., an online survey platform in China. The data was analyzed using the partial least squares method of structural equation modeling.

The findings revealed that amongst the three relational bonds, social and structural bonds were positively associated with trust, whereas financial bonds had no significant relationship with trust. This implies that while price discount might not have any significant relationship with trust, the social interactions that college students have with the live-streamers and their products build trust, which in turn translates to purchasing decisions. Comparing buyers and non-buyers, the results support that buyers have a higher level of trust in live-streaming shopping than non-buyers. This is indicative of the authentic and immersive experiences enjoyed by consumers in live streaming that generate structural bonds and foster stronger connections (relational bonds), thereby establishing trust.

This study is one of the first empirical studies targeting college students as participants in live streaming. These findings are expected to provide actionable insights to streamers especially in converting non-buyers to buyers in live-streaming broadcast.

The purpose of this paper is to optimize and improve a bipolar charge transport (BCT) model used to simulate charge dynamics in insulating polymer materials, specifically low-density polyethylene (LDPE).

An optimization algorithm is applied to optimize the BCT model by comparing the model outputs with experimental data obtained using two kinds of measurements: space charge distribution using the pulsed electroacoustic (PEA) method and current measurements in nonstationary conditions.

The study provides an optimal set of parameters that offers a good correlation between model outputs and several experiments conducted under varying applied fields. The study evaluates the quantity of charges remaining inside the dielectric even after 24 h of short circuit. Moreover, the effects of increasing the electric field on charge trapping and detrapping rates are addressed.

This study only examined experiments with different applied electric fields, and thus the obtained parameters may not suit the experimental outputs if the experimental temperature varies. Further improvement may be achieved by introducing additional experiments or another source of measurements.

This work provides a unique set of optimal parameters that best match both current and charge density measurements for a BCT model in LDPE and demonstrates the use of trust region reflective algorithm for parameter optimization. The study also attempts to evaluate the equations used to describe charge trapping and detrapping phenomena, providing a deeper understanding of the physics behind the model.

This study aims to focus on how smartphone addiction impacts young consumer behavior related to mobile technology (i.e. the compulsive app downloading tendency). After a thorough literature review and following the risk and protective factors framework, this study explores factors that could mitigate its effects (resilience, family harmony, perceived social support and social capital).

The study used the covariance-based structural equation modeling approach to analyze data collected from 275 Generation Z (Gen Z) smartphone users in Spain.

Results suggest that resilience is a critical factor in preventing smartphone addiction, and smartphone addiction boosts the compulsive app downloading tendency, a relevant downside for younger Gen Z consumers.

Through the lens of the risk and protective factors framework, this study focuses on protective factors to prevent smartphone addiction and its negative side effects on app consumption. It also offers evidence of younger consumers’ vulnerability to smartphone addiction, not because of the device itself but because of app-consumption-related behaviors.

This study aims to evaluate the moderating impact of corporate governance on the relationship between internal control mechanisms and financial performance.

The study employs a structured questionnaire to collect data from 250 top managers of rural banks in the capital of Ghana. Cronbach alpha value and Fornell-Larcker tests were performed to assess the reliability and validity of the data used. The study adopted a partial least square structural equation model (PLS-SEM).

The results show that internal control and corporate governance both have a direct positive and significant impact on financial performance. Furthermore, the interaction of internal control and corporate governance also has a positive and significant impact on financial performance, thus confirming the moderating role of corporate governance in the relationship between internal control mechanisms and financial performance.

This implies that organizations need to strengthen their corporate governance procedures to increase the efficiency of their internal control systems, which would ultimately lead to an improvement in their financial performance.

The present study innovates by assessing the moderating role of corporate governance in the nexus between internal control mechanisms and financial performance. This moderating effect assessment implies that corporate governance may not only affect the technical implementation of the internal control structures but will subsequently make an impact on the overall performance of the organization.

The authors examine the role of analysts’ prior experience of forecasting for firms exposed to epidemics on analysts’ forecast accuracy during the COVID-19 pandemic.

The authors examine the impact of analysts’ prior epidemic experience on forecast accuracy by comparing the changes from the pre-COVID-19 period (calendar year 2019) to the post-COVID period extending up to March 2023 across HRE versus non-HRE analysts. The authors consider a full sample (194,980) and a sub-sample (136,836) approach to distinguish “Recent” forecasts from “All” forecasts (including revisions).

The study's findings reveal that forecast accuracy for HRE analysts is significantly higher than that for non-HRE analysts during COVID-19. Specifically, forecast errors significantly decrease by 0.6% and 0.15% for the “Recent” and “All” forecast samples, respectively. This finding suggests that analysts’ prior epidemic experience leads to an enhanced ability to assess the uncertainty around the epidemic, thereby translating to higher forecast accuracy.

The finding that the expertise developed through an experience of following high-risk firms in the past enhances analysts’ performance during the pandemic sheds light on a key differentiator that partially explains the systematic difference in performance across analysts. The authors also show that industry experience alone is not useful in improving forecast accuracy during a pandemic – prior experience of tracking firms during epidemics adds incremental accuracy to analysts’ forecasts during pandemics such as COVID-19.

The study findings should prompt macroeconomic policymakers at the national level, such as the central banks of countries, to include past epidemic experiences as a key determinant when forecasting the economic outlook and making policy-related decisions. Moreover, practitioners and advisory firms can improve the earning prediction models by placing more weight on pandemic-adjusted forecasts made by analysts with past epidemic experience.

The uncertainty induced by the COVID-19 pandemic increases uncertainty in global financial markets. Under such circumstances, the importance of analysts’ role as information intermediaries gains even more importance. This raises the question of what determines analysts’ forecast accuracy during the COVID-19 pandemic. Building upon prior literature on the role of analyst experience in shaping analysts’ forecasts, the authors examine whether experience in tracking firms exposed to prior epidemics allows analysts to forecast more accurately during COVID-19. The authors find that analysts who have experience in forecasting for firms with high exposure to epidemics (H1N1, Zika, Ebola, and SARS) exhibit higher accuracy than analysts who lack such experience. Further, this effect of experience on forecast accuracy is more pronounced while forecasting for firms with higher exposure to the risk of COVID-19 and for firms with a poor ex-ante informational environment.

This study examines the efficacy of public sector audits in providing quality healthcare in Ghana. Specifically, to ensure whether there are proper and adequate controls in place to enable providers to offer necessary health services efficiently, effectively and equitably.

A structural equation modeling (SEM) is adopted to analyze the link between public sector audit and healthcare delivery through a survey of directors, accountants, auditors and managers in selected public healthcare institutions for a calculated sample size of 123 respondents.

The study reveals that internal audit, external audit and audit committee have a positive and significant effect on the effectiveness of public sector audits. In turn, the effectiveness of public sector audit has a positive and significant effect on the quality health services. Audit committee is found to have the largest effect on the effectiveness of public sector audits.

This paper extends the literature on the value of public sector audit by providing empirical evidence from a specific context: the public health sector of a developing country in democratic transition with a common law institutional framework. It also provides insights into the financial management of public health systems in developing countries during the ongoing coronavirus disease 2019 (COVID-19) pandemic.

As one of the most influential theories in strategic management, Hambrick and Mason’s Upper Echelons Theory has yielded significant conceptual and empirical advancements linking executive characteristics and perceptions to decision-making. Specifically, work on this theory consistently shows that CEOs’ decisions are biased by personal characteristics to the benefit and detriment of firms. While this stream of research links executive decision processes to outcomes such as executive dismissals, analyst evaluations, and press coverage, surprisingly little is understood about if and whether the information CEOs convey is subject to the same filtering process by a firm’s key evaluators. Thus, in this chapter, we aim to extend Upper Echelons Theory by positing that a double filtering process occurs whereby the cognitive aids CEOs use can be informed by not only their cognitive base and values but also the characteristics and priorities of those who evaluate the nonverbal and verbal signals they send. To do so, we build on recent conceptual and empirical advancements to make a case for the decision-making biases and tendencies that influence signal interpretation by three key evaluator groups internal and external to the firm: boards of directors, financial analysts, and the media. We conclude by considering the implications of evaluators’ information filtering and how this more holistic view of Upper Echelons decision-making can enable executive teams to be strategic with the cognitive aids they use to influence evaluations.