Search results

E-healthcare has gained importance, particularly in emerging economies, because of its ability to provide health-care products and services while minimizing contact with the external world, which was particularly relevant during the COVID-19 pandemic. Despite its advantages, consumers seem hesitant to use mobile apps to access such services. Previous research has found that perceived usefulness, time consumption and price significantly impact consumer willingness to purchase e-healthcare products on mobile apps. This study aims to investigate the role of consumer trust in the willingness to purchase e-healthcare products on mobile apps while controlling for the effects of perceived usefulness, time consumption and price.

Data have been collected using non-probability judgmental and snowball sampling techniques from five major cities in India. After the data cleaning process, 238 questionnaires were used for data analysis in this study. The authors used confirmatory factor analysis to validate all the constructs and subsequently used the hierarchical regression technique to conduct this study.

The study’s findings show that consumer trust is the most crucial factor for predicting a willingness to purchase e-healthcare products through mobile apps, despite several other variables that also have a positive impact. These findings present important practical implications for mobile app developers, health-care professionals and lawmakers to further enhance the adoption of e-healthcare products on mobile apps.

The research was conducted by considering primarily young adults (those between the ages of 20 and 45 – above) and targeted five cities in India. This highlights a limitation in the research, as small groups of the intended audience were included (mainly young people).

This study considers perceived usefulness, time and price, in addition to trust, to predict consumer willingness to purchase. Its findings can be valuable in the fields of consumer behavior, health care and technology, especially in emerging markets.

This study aims to assess the effect of both apigenin-loaded zinc oxide nanoparticles (ZnONPs) and apigenin only against cisplatin (CP)-induced experimental cardiotoxicity.

A total of 32Wister rats (male) were randomly divided (n = 8) into four groups. Normal control group, CP group received CP (20 mg/kg); treated group I received CP and then received apigenin (0.78 mg/kg/day) orally; treated group II received CP and then received apigenin loaded ZnONPs. At the end of the experiment (10 days), samples were extracted from each rat for the assessment of complete blood picture, lipid profile, atherogenic indices, oxidative status, inflammatory and cardiotoxicity markers as well as histological examination.

The results indicated that CP produced significant alterations in the complete blood picture, lipidemic profile, atherogenic indices, antioxidation capacity and cardiac inflammatory markers as well as function enzymes as compared with the control group. Administration of apigenin only showed a non-significant change in the atherogenic indices, oxidative status and cardiotoxicity parameters, indicating incomplete cardio-protection against CP upon. Additionally, all the observed alterations in CP group were reversed when apigenin nanoparticle at lower dose was used with ZnONPs which was also confirmed by histopathological investigation.

The apigenin loaded ZnONPs exert protective effects against CP-induced experimental cardiotoxicity and improved cardiac function, suggesting a potential adjuvant role of apigenin nanoparticles against cardiotoxicity.

This paper investigates the static and dynamic directional return spillovers and dependence among green investments, carbon markets, financial markets and commodity markets from January 2013 to September 2020.

This study employed both the quantile vector autoregression (QVAR) and time-varying parameter VAR (TVP-VAR) technique to examine the magnitude of static and dynamic directional spillovers and dependence of markets.

Results show that the magnitude of connectedness is extremely higher at quantile levels (q = 0.05 and q = 0.95) compared to those in the mean of the conditional distribution. This connotes that connectedness between green bonds and other assets increases with shock size for both negative and positive shocks. This further indicates that return shocks spread at a higher magnitude during extreme market conditions relative to normal periods. Additional analyses show the behavior of return transmission between green bond and other assets is asymmetric.

The findings of this study offer significant implications for portfolio investors, policymakers, regulatory authorities and investment community in terms of carefully assessing the unique characteristics offered by each markets in terms of return spillovers and dependence and diversifying the portfolios.

The study, first, uses a relatively new statistical technique, the QVAR advanced by Ando et al. (2018), to capture upper and lower tails’ quantile price connectedness and directional spillover. Therefore, the results possess adequate power against departure from mean-based conditional connectedness. Second, using a portfolio of green investments, carbon markets, financial markets and commodity markets, the uniqueness of this study lies in the examination of the static and dynamic dependence of the markets examined.

We adopt an information risk view and argue that higher levels of pledge risk incurred by insiders incentivize opportunistic financial disclosure and impair the quality of information available to analysts to forecast firm performance.

We sample Chinese listed companies from 2010 to 2022. Following the literature, we apply established models to measure and test analysts’ forecasting accuracy/dispersion related to controlling shareholders pledging equity and the amount of margin call pressure. Analyst characteristics and nonfinancial disclosures proxied by CSR reports are also examined as factors likely to influence the relationship between pledge risk and analysts’ forecast quality.

We find that analysts’ earnings predictions are less accurate and more dispersed as the proportion of shares pledged (pledge ratio) increases and in combination with greater margin call pressure. Pledge ratios are significantly associated with several information risk proxies (i.e. earnings permanence, accruals quality, audit quality, financial restatements, related party transactions and internal control weaknesses), validating the channel through which equity pledges undermine analysts’ forecast quality. The results also demonstrate that forecast quality declines for a wide variety of analysts’ attributes, including high- and low-quality analysts and analysts from small and large brokerage firms. Importantly, nonfinancial disclosures, as proxied by CSR reporting, improve analysts’ forecasts.

We extend the literature by demonstrating that incremental pledge risk increases non-diversifiable information risk; all non-pledging shareholders pay a premium through more diverse and less accurate earnings forecasts. Our study provides important policy implications with economically significant costs to investors associated with insider equity pledges. Our results highlight the benefits of nonfinancial disclosures in China, which has implications for the current debate on the global convergence of CSR reporting.

This paper aims to examine the impact of ownership structure on the accounting-based performance of listed Nigerian deposit money banks (DMBs) on Nigerian Exchange Group (NGX) from 2011 to 2020.

The study adopts ex post facto research design, using initially “the panel fixed and random effects regression analysis and Hausman specification test and thereafter, the IV Generalised method of moments (GMM) to check for endogeneity issues and strengthen the robustness of the results.

The one lagged value result reveals that ownership structure of DMBs in Nigeria has cumulative significant impact to influence corporate financial performance of the banks in the future. Overall, CEO, board/managerial, family, government and foreign ownership structures in DMBs in Nigeria do not have significant influence on accounting-based corporate financial performance of the banks. However, the study reveals that board/managerial ownership could significantly improve market value/growth of DMBs in Nigeria.

Policy makers, investors (both local and foreign), academics, corporate governance administrators, and the government could apply the study's findings to the management of banking operations in Nigeria.

The paper highlights the impact of five ownership structures on the accounting-based performance of DMBs in Nigeria from 2011 to 2020, providing valuable insights into the influence of stockholding categories on corporate financial performance, which is a shift from extant literatures with limited insights.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

This study analyzes whether industry relatedness between a corporate borrower and its group peers significantly affects that firm's borrowing cost.

A regression analysis is run on bank-loan data of a sample of Indonesian companies for 2010–2020. The main variables of interest are the natural logarithms of the borrowing firm's number of affiliates classified within either similar 2- or 4-digit GICS industries, and the Caves weighted index of these firms' related diversification. This index measures how firms in a group are diversified in relation to the borrower. The dependent variable is the all-in credit spread, stated in basis points, over the LIBOR or similar benchmark, as of the loan issuance date.

Findings support the industry-relatedness hypothesis and contradict the risk-reduction hypothesis and show that banks charge lower loan spreads on a borrowing firm that either operates within a similar industry as its affiliate or diversifies into related sectors or industries. Consistent with the co-insurance-effect hypothesis, the results also underline the importance of the parent and first-layer firms as supporting instead of the tunneling vehicles within business groups. These conclusions hold even after segregating the sample and using the loan maturity as the dependent variable.

This study uses a unique diversification measurement based on the borrowing firm's sector or industry, relative to other group members, and offers new insights on business group diversification and bank loan costs.

Given the popularity of online health communities (OHCs) and medical question-and-answer (Q&A) services, it is increasingly important to understand what constitutes useful answers and user-adopted standards in healthcare domain. However, few studies provide insights into how health information characteristics, provider characteristics and recipient characteristics jointly influence user information adoption decisions. To fill this research gap, this study examines the combined effects of physicians' certainty tone as information characteristics, seniority as provider characteristics and disease severity as recipient characteristics on patients' health information adoption.

Drawing on dual-process theory and information adoption model, an extended information adoption model is established in this study to examine the effect of attitude certainty on patients' health information adoption, and the moderating effects of online seniority and offline seniority, as well as patient motivation level—disease severity. Utilizing logit regression models, the authors empirically tested the hypotheses based on 4,224 Q&A records from a popular Chinese OHC.

The results show that (1) attitude certainty has a significant positive impact on patients' health information adoption, (2) the relationship between attitude certainty and information adoption is negatively moderated by physicians' online seniority, but is positively moderated by offline seniority; (3) there is a negative three-way interaction effect of attitude certainty, online seniority and disease severity on patients' health information adoption.

This study extends the information adoption model to examine the two-way interaction between argument quality and source reliability, as well as the three-way interaction with user motivation level, especially for health information adoption in the healthcare field. These findings also provide direct practical applications for knowledge contributors and OHCs.

We examine the relationship between board demographic diversity, board structural diversity, board capital diversity and corporate carbon performance (CCP). Additionally, we investigate how corporate sustainable resource use mediates these relationships.

We utilize unbalanced panel data from Refinitiv Eikon covering 9,960 global firms from 2002 to 2022. We conduct a panel regression analysis to examine the relationship between board demographic diversity, board structural diversity, board capital diversity and CCP. In addition, we estimate entropy balancing estimation and two-step system GMM to address endogeneity issues.

The results indicate that board demographic diversity (including tenure, gender, and cultural diversity), structural diversity (such as board independence, board size, CEO-chairman duality, board meetings, and board compensation), and capital diversity (comprising board member affiliation and specific skills) all have a positive and significant association with corporate carbon performance. Additionally, our findings reveal that corporate sustainable resource use fully mediates the relationship between board demographic diversity and CCP and partially mediates the relationship between board structural diversity, board capital diversity, and CCP.

Our study findings are based on a diverse range of global firms, ensuring that the results address the global challenges of firm-level climate change response and governance issues.

Our group diversity constructs offer new insights into the literature and further advance research on board group diversity. Additionally, for the first time, we explore the mediating role of sustainable resource use through the resource-based view (RBV) between-group diversity attributes and corporate carbon performance.

This study aims to explore the role of international ambidexterity (IA) in improving the innovation capability of emerging market multinationals. In particular, the main purpose of this research is to study the relationship amongst digitalisation, IA and innovation performance (IP) amongst multinational enterprises in China’s healthcare industry.

The data for this investigation were collected from 134 listed companies in China’s healthcare industry during the study period. This study tested the hypotheses by constructing a two-way fixed-effects model.

The results show that both the balance dimension and the combined dimension of IA have significant positive effects on IP. Digitalisation not only has a direct positive effect on IP but also positively moderates the positive correlation between IA and IP.

Previous studies have not captured the relationship between ambidexterity, digitalisation and IP, and this study helps to fill in the gap and examine these associations in China’s healthcare industry. The results of this study provide valuable insights for healthcare industry managers to understand the role of ambidexterity and digitalisation in innovation in the context of internationalisation.