Digital transformation and corporate tax avoidance: An analysis based on multiple perspectives and mechanisms

Promoting the seamless integration of the digital economy with the real economy, mitigating the adverse impacts of widespread corporate tax avoidance, and optimizing tax governance are critical imperatives in the era of digital economy. This study examines all A-share listed companies from 2007 to 2022 as research samples. It utilizes multiple perspectives including signal theory, information asymmetry theory, and the T-O-E (Technology-Organisation-Environment) framework to investigate the primary impacts of digital transformation on corporate tax avoidance, along with the intermediate mechanisms and foundational conditions that influence its effectiveness. After conducting both theoretical and empirical analyses, this paper presents the following conclusions. (1) The implementation of digital transformation significantly reduces corporate tax avoidance, a conclusion supported by rigorous robustness tests. Moreover, digital transformation enhances corporate productivity through the suppression of tax avoidance. (2) Digital transformation diminishes corporate tax avoidance through enhanced innovation and efficiency in resource allocation (technology level), improved quality of internal controls (organization level), and decreased industry competition (environment level). (3) The impact of digital transformation in reducing tax avoidance is significantly greater for enterprises in their growth phase, experiencing lower financing constraints, particularly those situated in the central and western regions. (4) Lower business risk is essential for maximizing the effectiveness of digital transformation and reducing corporate tax avoidance. This is crucial for governments seeking to improve tax administration, guide market and regional development, and enhance the impact of corporate digital transformation on mitigating tax avoidance.

Mediation effect of knowledge management on the impact of IT capability on firm performance: exploring the moderating role of organization culture management

Introduction

With the development of the digital economy, a multitude of firms have embarked on the path of digital transformation through information technology (IT). Scholars have called for attention to the mediating or moderating mechanisms of IT capability on firm performance. This study argues that further exploration is needed regarding the relationship between IT capability and firm performance.

Methods

This study obtained questionnaire data from 152 IT senior managers of randomly selected manufacturing firms. The data was used to empirically test the proposed hypotheses using hierarchical regression analysis.

Results

The results showed that IT capability has a positive effect on firm performance directly and indirectly via knowledge stock and knowledge process. Moreover, organizational culture management moderates the relationship between knowledge stock/knowledge process, and firm performance.

Discussion

This study proposes the "resources-knowledge-performance" mechanism, which sheds light on the "black box" of how IT capability affects firm performance. This enriches the research on knowledge from different perspectives and the the research on organizational culture by discussing the moderating role of organizational culture management in the relationship between knowledge stock/process and firm performance. Our research also has important managerial implications to firm.

Factors influencing user's health information discernment abilities in online health communities: based on SEM and fsQCA

Introduction

Online health communities have become the main source for people to obtain health information. However, the existence of poor-quality health information, misinformation, and rumors in online health communities increases the challenges in governing information quality. It not only affects users' health decisions but also undermines social stability. It is of great significance to explore the factors that affect users' ability to discern information in online health communities.

Methods

This study integrated the Stimulus-Organism-Response Theory, Information Ecology Theory and the Mindsponge Theory to constructed a model of factors influencing users' health information discernment abilities in online health communities. A questionnaire was designed based on the variables in the model, and data was collected. Utilizing Structural Equation Modeling (SEM) in conjunction with fuzzy-set Qualitative Comparative Analysis (fsQCA), the study analyzed the complex causal relationships among stimulus factors, user perception, and the health information discernment abilities.

Results

The results revealed that the dimensions of information, information environment, information technology, and information people all positively influenced health information discernment abilities. Four distinct configurations were identified as triggers for users' health information discernment abilities. The core conditions included information source, informational support, technological security, technological facilitation, and perceived risk. It was also observed that information quality and emotional support can act as substitutes for one another, as can informational support and emotional support.

Discussion

This study provides a new perspective to study the influencing factors of health information discernment abilities of online health community users. It can provide experiences and references for online health community information services, information resource construction and the development of users' health information discernment abilities.

The three pillars of tomorrow: How Marketing 5.0 builds on Industry 5.0 and impacts Society 5.0?

In today's environment, the connections between Marketing 5.0, Industry 5.0, and Society 5.0 are gaining increasing attention. Governments and businesses are eager to explore how they can boost both economic competitiveness and societal well-being through strategic initiatives. It is important to ensure that technology adoption, ethical governance, and human capital development all align and are in-sync. This review dives into this challenge, aiming to create a theoretical model that provides significant insight on how Marketing 5.0 influences Society 5.0 through Industry 5.0. By analyzing a broad range of literature, the aim was to offer practical suggestions and guidelines for enhancing competitiveness and societal welfare. 48 studies were analyzed studies to discuss the complexities of the relationships between these three domains. The findings suggest actionable steps and strategies for both businesses and policymakers. Finally, the paper serves as a foundation for future research in this area, exploring the synergy between Marketing 5.0, Industry 5.0, and Society 5.0.

CEO regulatory focus on digital transformation: Evidence from China

Digital transformationsw has become crucial for business to stay competitive in today's technology-driven world. Research shows CEOs' characteristics can influence firms' digital transformation, however, this work has not considered the role of CEO regulatory focus. In this paper, we build a framework to understand the relationship between CEO regulatory focus and firm's digital transformation. Build on regulatory focus theory, we argue that CEO promotion focus is positively associated with enterprise digital transformation, whereas CEO prevention focus is negatively associated with enterprise digital transformation. We further identify two contextual factors that moderating the relationship between CEO regulatory focus and digital transformation. Specifically, we find CEO power and economic policy uncertainty strengthen the relationship between CEO regulatory focus and enterprise digital transformation. We find strong support for our hypotheses in a sample of 2696 Chinese publicly listed firms between 2008 and 2023. Our findings have significant implications for understanding the role of CEO regulatory focus on digital transformation.

Does digital-industrial technology integration reduce corporate carbon emissions?

The integration of digital technology and industrial technology emerges as a pivotal avenue for enterprises to attain Sustainable Development Goals (SDGs), promoting the transition towards a sustainable and green trajectory of development. The panel data utilized in this paper encompasses financial, operational, and carbon emission metrics of publicly listed companies in China from 2008 to 2019. This longitudinal dataset enables us to perform robust statistical analyses to evaluate the impacts of Digital-Industrial technology integration on carbon emission intensity over time. The results indicate that: (i) Digital-Industrial technology integration significantly reduces the carbon emission intensity of enterprises, the conclusion remains robust when subjected to endogeneity and sensitivity analyses. (ii) Digital-Industrial technology integration mainly reduces the marginal cost of production and enhances the accumulation of knowledge to reduce the carbon emission intensity of enterprises. (iii) Digital-Industrial Technology Integration manifests more pronounced effects in curbing carbon emissions in regions characterized by robust property rights protection and well-developed digital infrastructure. (iv) Further research finds that Digital-Industrial technology integration increases the green technology innovation and ESG (Environmental, Social, and Governance) performance of enterprises. The results of this study provide empirical evidence for the carbon emission reduction function of the Digital-Industrial technology integration, and also verify the positive externality impact of the Digital-Industrial technology integration on the enterprise green innovation and SDGs.

Which Receives More Attention, Online Review Sentiment or Online Review Rating? Spillover Effect Analysis from JD.com

Studies have found that competitive products' online review ratings (ORRs) have a spillover effect on the focal product's sales. However, the spillover effect of online review sentiment (ORS) as an essential component of online review analysis has yet to be studied. In this study, we analyze online review content from JD.com using the latent Dirichlet allocation to identify the product attribute topics that consumers are most concerned about. We then construct a baseline regression model of ORS and ORRs to explore the effects of online competitive product reviews on focal product sales. Moreover, we examine how the interaction between ORS and critical factors of online reviews affect sales. Our results indicate that the ORS of competitive products has a negative effect on focal product sales, and the effect is greater than the ORS and ORRs of focal products, respectively. In addition, the ORS of competitive products inhibits the sale of focal products as evaluations of product attributes become more positive or online review usefulness increases. We also find that the effect of ORRs of competitive products is not significant, which may be because clothing, as an experiential product, requires consumers to gain more information about specific usage scenarios before making a decision. This study provides a more accurate basis for consumer decision-making and offers retailers a novel approach to developing marketing strategies.

Understanding the rationales and information environments for early, late, and nonadopters of the COVID-19 vaccine

Anti-vaccine sentiment during the COVID-19 pandemic grew at an alarming rate, leaving much to understand about the relationship between people's vaccination status and the information they were exposed to. This study investigated the relationship between vaccine behavior, decision rationales, and information exposure on social media over time. Using a cohort study that consisted of a nationally representative survey of American adults, three subpopulations (early adopters, late adopters, and nonadopters) were analyzed through a combination of statistical analysis, network analysis, and semi-supervised topic modeling. The main reasons Americans reported choosing to get vaccinated were safety and health. However, work requirements and travel were more important for late adopters than early adopters (95% CI on OR of [0.121, 0.453]). While late adopters' and nonadopters' primary reason for not getting vaccinated was it being too early, late adopters also mentioned safety issues more often and nonadopters mentioned government distrust (95% CI on OR of [0.125, 0.763]). Among those who shared Twitter/X accounts, early adopters and nonadopters followed a larger fraction of highly partisan political accounts compared to late adopters, and late adopters were exposed to more neutral and pro-vaccine messaging than nonadopters. Together, these findings suggest that the decision-making process and the information environments of these subpopulations have notable differences, and any online vaccination campaigns need to consider these differences when attempting to provide accurate vaccine information to all three subpopulations.

Factors associated with self-management in older adults with multiple chronic conditions: a qualitative study

Background and purpose

Recognizing the importance of self-management in older adults with multiple chronic conditions (MCCs) is crucial for their quality of life. This qualitative study explored the factors linked to self-management among older adults with MCCs.

Materials and methods

The present study was conducted in three stages: an integrated review, qualitative interviews, and Delphi. The search used electronic databases including Web of Science, PubMed, Scopus, Magiran, SID, and Iranmedex. The results of 33 studies that met the inclusion criteria were analyzed using conventional content analysis. A data matrix was formed; and purposeful sampling was conducted among older adults with MCCs, family caregivers, and specialists. The data were collected through semi-structured interviews. Data analysis of 29 interviews was conducted simultaneously with data collection using oriented qualitative content analysis and the Elo and Kyngäs approach. Three rounds of Delphi were conducted via email correspondence with a group of 30 experts to develop and validate the proposed variables.

Results

The factors that influence self-management can be categorized into various categories. Biological factors, cognitive factors, co-morbidities, socio-economic factors, health-related behaviors, mental health, interactions with healthcare teams, Family relationships, medical facility resources, employee empowerment, health policy development, and cultural influences.

Conclusion

Self-management in older Iranian adults with MCCs is a complex and multidimensional phenomenon. By identifying the relevant factors, it is possible to design operational plans that promote self-management among the older adult population and are tailored to fit the specific needs of Iranian society.

Social media ostracism and creativity: moderating role of emotional intelligence

The goal of this study is to learn more about social media ostracism, a stressor associated with online social networks, defined by feelings of rejection, exclusion, or ignoring. We investigate the connection between social media ostracism and worker creativity. We suggest that psychological safety and psychological rumination serve as intermediaries in this relationship. Furthermore, we investigate emotional intelligence as a relationship regulator. To verify our hypothesis, we gathered data with the help of the HR department from 244 workers of nine Chinese organizations. Our research shows that psychological rumination and social media exclusion are significantly correlated, but only in workers with low emotional intelligence. Furthermore, for individuals with strong emotional intelligence, we did not discover a statistically negative association between psychological safety and social media exclusion. Findings suggest that psychological safety and psychological rumination serve as mediating factors in the relationship between employee creativity and social media exclusion. This study illuminates the negative aspects of social media ostracism and reveals how it might hinder creativity. It also emphasizes how emotional intelligence functions as a moderator. Organizations may learn a lot from this study on how to lessen the negative impacts of social media exclusion on employee creativity.

Mobile Patient-Provider Communication and Lifestyle Improvement: Examining the Role of Mobile Technology Identity and Health Empowerment

In the span of a decade, smartphones have gained popularity and acceptance among both patients and physicians thanks to their advantages in health care delivery. However, research investigating mobile patient-provider communication (MPPC) and its impact on patients' lifestyles is only just beginning. Drawing on the pathway model of health communication and mobile technology (MTI) theory, we developed a research model to explore the effect of MPPC on lifestyle improvement, using health empowerment as a mediator and MTI as a moderator. The findings from 432 participants (Mage = 32.5 years old, female = 212) suggested that after controlling for respondents' age, gender, education, income, and general health status, having greater communication with healthcare providers through mobile devices was positively related to lifestyle improvement and that health empowerment mediated this relationship. Moreover, MTI-emotional energy (MTIE) moderated the direct relationship between MPPC and lifestyle improvement, while MTI-dependency (MTID) moderated the indirect impact of MPPC. Individuals who hold a greater MTIE/MTID were more likely to benefit from MPPC such that they are more likely to be empowered for self-care and maintain healthy lifestyles. This study not only contributes to the growing literature on mobile health communication but also plays a reference role for interventions in patient empowerment and health promotion. Theoretical and practical implications were discussed.

The effects of right temporoparietal junction stimulation on embodiment, presence, and performance in teleoperation

Embodiment (the sensation that arises when the properties of an external instrument are processed as if they are the attributes of one's own biological body) and (tele)presence (the sensation of being fully engaged and immersed in a location other than the physical space occupied by one's body) sustain the perception of the physical self and potentially improve performance in teleoperations (a system that enables human intelligence to control robots and requires implementing an effective human-machine interface). Embodiment and presence may be interdependent and influenced by right temporo-parietal junction (rTPJ) activity. We investigated the interplay between embodiment, (tele)presence, and performance in teleoperation, focusing on the role of the rTPJ. Participants underwent a virtual reality task with transcranial direct current stimulation (tDCS) twice, receiving either active or sham stimulation. Behavioral measures (driving inaccuracy, elapsed time in the lap, time spent in attentional lapses, short-term self-similarity, and long-term self-similarity), perceived workload (mental demand, physical demand, temporal demand, own performance, effort, and frustration), embodiment's components (ownership, agency, tactile sensations, location, and external appearance), and presence's components (realism, possibility to act, quality of interface, possibility to examine, self-evaluation of performance, haptic, and sounds) were assessed. The results showed that rTPJ stimulation decreased perceived ownership but enhanced presence with changes in the complexity of visuomotor adjustments (long and short-term self-similarity indices). Structural equation modeling revealed that embodiment increased visuomotor inaccuracy (a composite variable of overall performance, including deviations from the optimal trajectory and the time taken to complete the task), presence reduced workload, and workload increased inaccuracy. These results suggested a dissociation between embodiment and presence, with embodiment hindering performance. Prioritizing virtual integration may lower human performance, while reduced workload from presence could aid engagement. These findings emphasize the intricate interplay between rTPJ, subjective experiences, and performance in teleoperation.

User Experiences of Transitioning From a Homegrown Electronic Health Record to a Vendor-Based Product in the Department of Veterans Affairs: Qualitative Findings From a Mixed Methods Evaluation

BACKGROUND

The Department of Veterans Affairs (VA), the largest nationally integrated health system in the United States, is transitioning from its homegrown electronic health record (EHR) to a new vendor-based EHR, Oracle Cerner. Experiences of the first VA site to transition have been widely discussed in the media, but in-depth accounts based on rigorous research are lacking.

OBJECTIVE

We sought to explore employee perspectives on the rationale for, and value of, transitioning from a VA-tailored EHR to a vendor-based product.

METHODS

As part of a larger mixed methods, multisite, formative evaluation of VA clinician and staff experiences with the EHR transition, we conducted semistructured interviews at the Mann-Grandstaff VA Medical Center before, during, and after going live in October 2020. In total, we completed 122 interviews with 26 participants across multiple departments.

RESULTS

Before the new vendor-based EHR went live, participants initially expressed cautious optimism about the transition. However, in subsequent interviews following the go-live, participants increasingly critiqued the vendor's understanding of VA's needs, values, and workflows, as well as what they perceived as an inadequate fit between the functionalities of the new vendor-based EHR system and VA's characteristic approach to care. As much as a year after going live, participants reiterated these concerns while also expressing a desire for substantive changes to the transition process, with some questioning the value of continuing with the transition.

CONCLUSIONS

VA's transition from a homegrown EHR to a vendor-based EHR system has presented substantial challenges, both practical and cultural in nature. Consequently, it is a valuable case study for understanding the sociotechnical dimension of EHR-to-EHR transitions. These findings have implications for both VA leadership and the broader community of policy makers, vendors, informaticists, and others involved in large-scale health information technology implementations.

You cannot spell risk without "I-S": The disclosure of information systems risks by Fortune 1000 firms

Cybersecurity events can cause business disruptions, health and safety repercussions, financial costs, and negative publicity for large firms, and executives rank cybersecurity as a top operational concern. Although cybersecurity may be the most publicized information systems (IS) risk, large firms face a range of IS risks. Over the past three decades, researchers developed frameworks to categorize and evaluate IS risks. However, there have been few updates to these frameworks despite numerous technological advances, and we are not aware of any research that uses empirical data to map actual IS risks cited by large firms to these frameworks. To address this gap, we coded and analyzed text data from Item 1A (Risk Factors) of the fiscal year 2020 Securities and Exchange Commission Forms 10-K for all Fortune 1000 firms. We build on prior research to develop a framework that places 25 IS risks into four quadrants and 10 categories, and we record the number and type of IS risks cited by each firm. The risk of cyberattack is cited by virtually all Fortune 1000 firms, and the risk of software/hardware failure is cited by 90% of Fortune 1000 firms. Risks associated with data privacy law compliance are cited by 70% of Fortune 1000 firms, and risks associated with internet/telecommunications/power outage, human error, and natural disasters/terrorism are cited by 60% of Fortune 1000 firms. We perform additional analysis to identify differences in risk citation based on industry and financial measures.

Time in hand: Temporal focus in risk discourse and audience emotions on knowledge-sharing platforms

Online knowledge-sharing platforms construct risk knowledge and provide the audience with risk-related scientific facts. We study how speakers organize narratives in past, present, and future foci to influence the audience's emotions through the audience's appraisal of motive congruency and coping potential. Empirical evidence from 210 Technology, Entertainment, Design talks about disasters from 2002 to 2018 demonstrates that emphasizing the past, present, and future in risk narrative leads to the audience's comments with more negative, less positive, and more positive emotions, respectively. Concrete (vs. abstract) portrayal of the risk narrative improves the audience's situational awareness, enhances their risk appraisal, and intensifies the impact of temporal focus on emotions, providing evidence of how temporal focus impacts. These findings demonstrate that temporal focus can effectively reduce risk overreaction or ignorance and facilitate emotion regulation in risk communication.

Can digital technology innovation contribute to firms' market value?

With the rapid development of digital technology, digital technology innovation has become a core driver of China's economic development. Thus, this study uses A-share listed companies from 2003 to 2021 as the research sample. The digital patents of firms are identified to portray the level of digital technology innovation by matching the digital economy industry classification code, national economy industry classification code, and IPC number. Considers the economic effect of digital technology innovation from the perspective of firm market value. It is found that digital technology innovation significantly contributes to the increase in firm market value, and this finding still holds when robustness tests are performed. Mechanistic tests have shown that digital technology innovation affects firm market value by driving digital transformation, promoting productivity, and enhancing market profitability. Further analysis reveals that digital technology innovation has a more significant effect on increasing firm market value for large, non-state, capital-intensive, technology-intensive and low internal control costs firms. This study verifies the enabling effect of digital technology innovation on the development of the real economy at the micro level, and provides insights for the optimization of China's digital technology innovation policies and the formulation of firms' digital development strategies.

Beyond the Screen: A Comprehensive Analysis of Emotional Skills and Social Networking in French Young Adults

(1) Background: This study investigates the influence of social networks on young adults, focusing on both positive and negative impacts. It considers problematic social networking site use (PSNSU), emotional intelligence, empathy, and the phenomenon of Fear of Missing Out (FoMO). (2) Methods: A comprehensive online survey was conducted with 442 participants aged 18 to 30 years that used various psychometric tools to assess emotional intelligence, empathy, internet and social media use, and FoMO. (3) Results: The study revealed that young adults display low competencies in emotional intelligence and empathy, with a tendency towards problematic internet and social media use. High FoMO scores were observed, correlating with negative internet use outcomes. Gender differences in these aspects were also explored. (4) Conclusions: The findings suggest a complex interaction between social network use, emotional skills, and FoMO that impacts young adults' mental health and social behaviors. This study highlights the need for a nuanced understanding of these relationships and their implications for well-being and social interaction in the digital age.

For-profit versus non-profit cybersecurity posture: breach types and locations in healthcare organisations

BACKGROUND

The implementation of emerging technologies has resulted in an increase of data breaches in healthcare organisations, especially during the COVID-19 pandemic. Health information and cybersecurity managers need to understand if, and to what extent, breach types and locations are associated with their organisation's business type.

OBJECTIVE

To investigate if breach type and breach location are associated with business type, and if so, investigate how these factors affect information systems and protected health information in for-profit versus non-profit organisations.

METHOD

The quantitative study was performed using chi-square tests for association and post-hoc comparison of column proportions analysis on an archival data set of reported healthcare data breaches from 2020 to 2022. Data from the Department of Health and Human Services website was retrieved and each organisation classified as for-profit or non-profit.

RESULTS

For-profit organisations experienced a significantly higher number of breaches due to theft, and non-profit organisations experienced a significantly higher number of breaches due to unauthorised access. Furthermore, the number of breaches that occurred on laptops and paper/films was significantly higher in for-profit organisations.

CONCLUSION

While the threat level of hacking techniques is the same in for-profit and non-profit organisations, certain breach types are more likely to occur within specific breach locations based on the organisation's business type. To protect the privacy and security of medical information, health information and cybersecurity managers need to align with industry-leading frameworks and controls to prevent specific breach types that occur in specific locations within their environments.

Therapeutic use of the humanoid robot, Telenoid, with older adults: A critical interpretive synthesis review

This review sought to critically evaluate the use of the teleoperated humanoid robotic communications device, Telenoid, for therapeutic purposes with older adults, and identify and highlight key considerations for future research and clinical practice within gerontechnology. A critical interpretive synthesis was conducted, with nine electronic databases and online sources searched using the keyword "Telenoid." Studies were included in the review if they were: written in English; reported primary research; employed a qualitative, quantitative, or mixed-method design; and described or measured effects, experiences, or perceptions of using Telenoid for therapeutic purposes with older adults. Critical engagement with the studies identified key themes, as well as opportunities to advance future research. Ten studies involving Telenoid were identified, with eight focused on older adults living with dementia. Study findings centered around two themes: effects (including positive effects and negative reactions), and challenges and considerations (including technical issues, operator training, acceptability, and dosage). Although several issues currently challenge the use of Telenoid, available studies show some therapeutic potential of using Telenoid with older adults, including those living with dementia, particularly for communication and mood. Higher-quality studies are required to advance understanding, and considerations for the field are outlined to aid development.

Antecedents and consequents of circular economy adoption: A meta-Analytic Investigation

This paper aims to integrate and empirically assess the antecedents and consequents of circular economy (CE) adoption to remove ambiguity existing in the literature and clarify divergent views. This study uses meta-analysis methodology to validate the research framework, considering 106 empirical studies with 210 effect sizes. Based on these studies, we establish twelve antecedents and three consequents related to CE. Antecedents are categorized in a technological-organizational-environmental framework and consequents in the sustainability outcomes. The result suggests that organisational factors are more prominent in driving CE practices, followed by environmental and technological factors. In the organisational category, the three most influencing factors are managing product returns, green manufacturing, and environmental strategy. In the environmental category, coercive pressure is the most influential factor, followed by mimetic and social pressures. Emerging I4.0 technologies are the most prominent factor in the technological category. Our study suggests that CE helps to achieve sustainable performance by significantly enabling economic, environmental, and social outcomes. This study further analyses how contextual factors such as national culture (masculinity) and economic regions influence the various relationships with CE using subgroup analysis. The moderation results show that low masculine culture and developing economies are more effectively using the I4.0 technologies to drive CE adoption than high masculine culture and developed economies. Additionally, different dimensions of sustainability are also influenced by the variations in masculinity and economic regions.

Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software

Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs) and neuritic plaques (NPs), without consideration of lesion heterogeneity in individual cases. We developed a deep learning workflow for automated annotation and segmentation of NPs and NFTs from AT8-immunostained whole slide images (WSIs) of AD brain sections. Fifteen WSIs of frontal cortex from 4 biobanks with varying tissue quality, staining intensity, and scanning formats were analyzed. We established an artificial intelligence (AI)-driven iterative procedure to improve the generation of expert-validated annotation datasets for NPs and NFTs thereby increasing annotation quality by >50%. This strategy yielded an expert-validated annotation database with 5013 NPs and 5143 NFTs. We next trained two U-Net convolutional neural networks for detection and segmentation of NPs or NFTs, achieving high accuracy and consistency (mean Dice similarity coefficient: NPs, 0.77; NFTs, 0.81). The workflow showed high generalization performance across different cases. This study serves as a proof-of-concept for the utilization of proprietary image analysis software (Visiopharm) in the automated deep learning segmentation of NPs and NFTs, demonstrating that AI can significantly improve the annotation quality of complex neuropathological features and enable the creation of highly precise models for identifying these markers in AD brain sections.

Assessing inclusion and representativeness on digital platforms for health education: Evidence from YouTube

BACKGROUND

Studies confirm that significant biases exist in online recommendation platforms, exacerbating pre-existing disparities and leading to less-than-optimal outcomes for underrepresented demographics. We study issues of bias in inclusion and representativeness in the context of healthcare information disseminated via videos on the YouTube social media platform, a widely used online channel for multi-media rich information. With one in three US adults using the Internet to learn about a health concern, it is critical to assess inclusivity and representativeness regarding how health information is disseminated by digital platforms such as YouTube.

METHODS

Leveraging methods from fair machine learning (ML), natural language processing and voice and facial recognition methods, we examine inclusivity and representativeness of video content presenters using a large corpus of videos and their metadata on a chronic condition (diabetes) extracted from the YouTube platform. Regression models are used to determine whether presenter demographics impact video popularity, measured by the video's average daily view count. A video that generates a higher view count is considered to be more popular.

RESULTS

The voice and facial recognition methods predicted the gender and race of the presenter with reasonable success. Gender is predicted through voice recognition (accuracy = 78%, AUC = 76%), while the gender and race predictions use facial recognition (accuracy = 93%, AUC = 92% and accuracy = 82%, AUC = 80%, respectively). The gender of the presenter is more significant for video views only when the face of the presenter is not visible while videos with male presenters with no face visibility have a positive relationship with view counts. Furthermore, videos with white and male presenters have a positive influence on view counts while videos with female and non - white group have high view counts.

CONCLUSION

Presenters' demographics do have an influence on average daily view count of videos viewed on social media platforms as shown by advanced voice and facial recognition algorithms used for assessing inclusion and representativeness of the video content. Future research can explore short videos and those at the channel level because popularity of the channel name and the number of videos associated with that channel do have an influence on view counts.

Mitigating the influence of message features on health misinformation sharing intention in social media: Experimental evidence for accuracy-nudge intervention

RATIONALE

The escalating dissemination of health misinformation on social media platforms poses a significant threat to users' well-being. It is imperative to identify the types of health misinformation that are more susceptible to widespread dissemination and to explore strategies to curb its spread.

METHOD

This study designed a 2 (emotional appeal type: positive vs. negative) × 2 (fabricated source type: pseudo-common vs. pseudo-authoritative) × 2 (accuracy-nudge label: No vs. Yes) online between-subjects experiment controlling for factors such as e-health literacy, prior sharing experience, and personal involvement. A snowball sampling approach was used to recruit 1952 participants through social media, resulting in a final sample of 1393 valid responses.

RESULTS

Compared to positive emotional appeal and pseudo-common sources, negative emotional appeal and pseudo-authoritative sources resulted in higher levels of sharing intention. Under the condition of negative emotional appeal, the promotion effect of pseudo-authoritative sources on sharing intention was intensified. The accuracy-nudge intervention could significantly mitigate this tendency. The underlying mechanisms revealed more details: both negative emotional appeals and pseudo-authoritative sources increased the perceived credibility of health misinformation, thereby increasing users' sharing intention. However, in contrast to pseudo-authoritative sources, excessive negative emotional appeal induced vigilant verification behavior among users, which reduced sharing to some extent. Adding an accuracy-nudge label to health misinformation reduced users' misguided trust in health misinformation features and stimulated information verification, ultimately reducing health misinformation sharing intention.

CONCLUSIONS

Negative emotional appeal and pseudo-authoritative sources can enhance the perceived credibility of health misinformation, thereby strengthening the sharing intention of social media users. Therefore, health misinformation with negative emotional appeal and pseudo-authoritative sources is more likely to be widely shared. The accuracy nudge intervention can trigger users' information verification behavior, suppress the persuasive effects of the misinformation features mentioned above, and help prevent the spread of health misinformation on social media.

Punishing "Privilege": Antisemitic Hate Crime in Canada

Both federal government and civil society organization data point to consistently rising incidents of antisemitic narratives and acts across Canada. In spite of this, antisemitic hate crime has not been the focus of any academic research here, some would argue because Jews are not typically thought to be an at-risk community. Rather, the Jewish community is thought to occupy a relatively privileged place in society which shields them from bias motivated attacks. Countering this narrative, our study, based in Ontario and Quebec, reveals that Jewish individuals and institutions are highly vulnerable to discursive, physical, and property violations. Many of those we spoke with felt embattled by the narrative attacks that rendered the community vulnerable to corollary physical attacks. Of particular significance are the enabling images of Jews that equate "Jewish privilege" with excessive power and control. We explore these themes, concluding with calls for strategies intended to counter hateful narratives.

Targeted communication and race: explicating perceived message relevance

Objectives: Targeting is a communication strategy in which a message is designed to address a particular group. It has been postulated that targeting increases message relevance; however, researchers are still explicating relevance and its impact on downline cognitive processes (e.g. message quality, cognitive cost). The current study addresses both gaps by evaluating the impact of targeted materials for White and African American audiences. Design: Adult women (N = 266) aged 18-74 (Mage = 47.12, SD = 1.40) were recruited to participate in a 2 (targeting: multiracial, African American) × 2 (race: White participants, African American participants) × 2 (topic: Hypertension, Environmental Breast Cancer) message experiment. Results: Across both topics, African American participants in the African American condition had reduced cognitive costs, increased message clarity, and increased message relevance. An indirect serial mediation model was supported wherein the relationship between targeting and behavioral intention was mediated by perceived relevance and perceived message quality. Conclusion: Targeting enhances perceived message relevance which, in turn, impacts behavioral intentions via perceived message quality. This model is consistent with the postulates of relevance theory and informs both intervention design and evaluation.

A Practical Guide to Manual and Semi-Automated Neurosurgical Brain Lesion Segmentation

The purpose of the article is to provide a practical guide for manual and semi-automated image segmentation of common neurosurgical cranial lesions, namely meningioma, glioblastoma multiforme (GBM) and subarachnoid haemorrhage (SAH), for neurosurgical trainees and researchers.

MATERIALS AND METHODS

The medical images used were sourced from the Medical Image Computing and Computer Assisted Interventions Society (MICCAI) Multimodal Brain Tumour Segmentation Challenge (BRATS) image database and from the local Picture Archival and Communication System (PACS) record with consent. Image pre-processing was carried out using MRIcron software (v1.0.20190902). ITK-SNAP (v3.8.0) was used in this guideline due to its availability and powerful built-in segmentation tools, although others (Seg3D, Freesurfer and 3D Slicer) are available. Quality control was achieved by employing expert segmenters to review.

RESULTS

A pipeline was developed to demonstrate the pre-processing and manual and semi-automated segmentation of patient images for each cranial lesion, accompanied by image guidance and video recordings. Three sample segmentations were generated to illustrate potential challenges. Advice and solutions were provided within both text and video.

CONCLUSIONS

Semi-automated segmentation methods enhance efficiency, increase reproducibility, and are suitable to be incorporated into future clinical practise. However, manual segmentation remains a highly effective technique in specific circumstances and provides initial training sets for the development of more advanced semi- and fully automated segmentation algorithms.

Digital health care and data work: Who are the data professionals?

BACKGROUND

This article reports on a study that investigated data professionals in health care. The topic is interesting and relevant because of the ongoing trend towards digitisation of the healthcare domain and efforts for it to become data driven, which entail a wide variety of work with data.

OBJECTIVE

Despite an interest in data science and more broadly in data work, we know surprisingly little about the people who work with data in healthcare. Therefore, we investigated data work at a large national healthcare data organisation in Denmark.

METHOD

An explorative mixed method approach combining a non-probability technique for design of an open survey with a target population of 300+ and 11 semi-structured interviews, was applied.

RESULTS

We report findings relevant to educational background, work identity, work tasks, and how staff acquired competences and knowledge, as well as what these attributes comprised. We found recurring themes of healthcare knowledge, data analytical skills, and information technology, reflected in education, competences and knowledge. However, there was considerable variation within and beyond those themes, and indeed most competences were learned "on the job" rather than as part of formal education.

CONCLUSION

Becoming a professional working with data in health care can be the result of different career paths. The most recurring work identity was that of "data analyst"; however, a wide variety of responses indicated that a stable data worker identity has not yet developed.

IMPLICATIONS

The findings present implications for educational policy makers and healthcare managers.

A comparative analysis of risk factors in taxi-related crashes using XGBoost and SHAP

Taxis play a crucial role in urban public transportation, but the traffic safety situation of taxi drivers is far from optimistic, especially considering the introduction of ride-hailing services into the taxi industry. This study conducted a comparative analysis of risk factors in crashes between traditional taxi drivers and ride-hailing taxi drivers in China, including their demographic characteristics, working conditions, and risky driving behaviors. The data was collected from 2,039 traditional taxi drivers and 2,182 ride-hailing taxi drivers via self-reported questionnaires. Four XGBoost models were established, taking into account different types of taxi drivers and crash types. All models showed acceptable performance, and SHAP explainer was used to analyze the model results. The results showed that for both taxi drivers, risk factors related to risky driving behaviors are more important in predicting property damage (PD) crashes, while risk factors related to working conditions are more important in predicting person injury (PI) crashes. However, the relative importance of each risk factor varied depending on the type of crashes and the type of taxi drivers involved. Furthermore, the results also validated certain interactions among the risk factors, indicating that the combination of certain factors generated a greater impact on crashes compared to individual factors alone. These findings can provide valuable insights for formulating appropriate measures to enhance road safety for taxi driver.

Risk factors for technology addiction in young children ages 2-5 years

PURPOSE

This study was conducted to determine the factors predictive of technology addiction in young children (aged 2-5 years). The study examined the effects of digital parenting awareness, parental stress, family demographic characteristics and parents' technology use habits on technology addiction in young children.

DESIGN AND METHODS

This cross-sectional study was conducted between October 2023 and February 2024 with 401 volunteer parents of children aged 2-5 years in a province in the Western Mediterranean region of Turkey. Data were collected using the Technology Addiction Scale for Ages 2-5, the Digital Parental Awareness Scale, and the Parental Stress Scale.

RESULTS

Digital parenting awareness, negative modeling and digital neglect, and parental stress positively and directly affect technology addiction in young children (β1 = 0.166, β2 = 0.443, β3 = 0.087, all p < 0.05). Additionally, parental gender (β = 0.095), parental marital status (β = 0.092), and household income (β = 0.088) were significant predictors of technology addiction in young children (p < 0.05). The level of technology addiction is significantly higher in children who use devices without parental controls (Z = -6.187, p < 0.001).

CONCLUSIONS

Low digital parenting awareness, high parental stress, male caregivers, low household income and single-parent families in digital tools increase the risk of technology addiction in young children (2-5 years). Multidisciplinary, family-oriented intervention programs, incorporating consideration of parental risk factors, should be developed to prevent and reduce technology addiction in this group.

Large language models and generative AI in telehealth: a responsible use lens

OBJECTIVE

This scoping review aims to assess the current research landscape of the application and use of large language models (LLMs) and generative Artificial Intelligence (AI), through tools such as ChatGPT in telehealth. Additionally, the review seeks to identify key areas for future research, with a particular focus on AI ethics considerations for responsible use and ensuring trustworthy AI.

MATERIALS AND METHODS

Following the scoping review methodological framework, a search strategy was conducted across 6 databases. To structure our review, we employed AI ethics guidelines and principles, constructing a concept matrix for investigating the responsible use of AI in telehealth. Using the concept matrix in our review enabled the identification of gaps in the literature and informed future research directions.

RESULTS

Twenty studies were included in the review. Among the included studies, 5 were empirical, and 15 were reviews and perspectives focusing on different telehealth applications and healthcare contexts. Benefit and reliability concepts were frequently discussed in these studies. Privacy, security, and accountability were peripheral themes, with transparency, explainability, human agency, and contestability lacking conceptual or empirical exploration.

CONCLUSION

The findings emphasized the potential of LLMs, especially ChatGPT, in telehealth. They provide insights into understanding the use of LLMs, enhancing telehealth services, and taking ethical considerations into account. By proposing three future research directions with a focus on responsible use, this review further contributes to the advancement of this emerging phenomenon of healthcare AI.

An optimised and validated surrogate analyte A-TEEM-PARAFAC-PLS technique for detecting and quantifying the biological oxygen demand in surface water

A 5-day test duration makes BOD5 measurement unsatisfactory and hinders the development of a quick technique. Protein-like fluorescence peaks show a strong correlation between the BOD characteristics and the fluorescence intensities. For identifying and measuring BOD in surface water, a simultaneous absorbance-transmittance and fluorescence excitation-emission matrices (A-TEEM) method combined with PARAFAC (parallel factor) and PLS (partial least squares) analyses was developed using a tyrosine and tryptophan (tyr-trpt) mix as a surrogate analyte for BOD. The use of a surrogate analyte was decided upon due to lack of fluorescent BOD standards. Tyr-trpt mix standard solutions were added to surface water samples to prepare calibration and validation samples. PARAFAC analysis of excitation-emission matrices detected the tyr-trpt mix in surface water. PLS modelling demonstrated significant linearity (R2 = 0.991) between the predicted and measured tyr-trypt mix concentrations, and accuracy and robustness were all acceptable per the ICH Q2 (R2) and ASTM multivariate calibration/validation procedures guidelines. Based on a suitable and workable surrogate analyte method, these results imply that BOD can be detected and quantified using the A-TEEM-PARAFAC-PLS method. Very positive comparability between tyr-trypt mix concentrations was found, suggesting that tyr-trypt mix might eventually take the place of a BOD-based sampling protocol. Overall, this approach offers a novel tool that can be quickly applied in water treatment plant settings and is a step in supporting the trend toward rapid BOD determination in waters. Further studies should demonstrate the wide application of the method using real wastewater samples from various water treatment facilities.

Celebrity Identification and Reasoned Action: An Integrative Model of the Relationship Between Media Use and Breast Cancer Screening Intention

This study investigates the relationship between media use and breast cancer screening intentions by integrating the celebrity identification model and the theory of reasoned action. It tests an integrative model with survey data from 315 U.S. adult women. The study found that media use for breast cancer information was positively associated with parasocial interaction (PSI) and identification with celebrities who have or have had breast cancer; PSI was positively associated with attitudes, descriptive and injunctive norms in breast cancer screening, while identification with celebrities was positively associated with descriptive norms; attitudes, injunctive norms and descriptive norms were positively associated with breast cancer screening intentions. The study supports the mediating effect of PSI, identification, attitudes, and descriptive and injunctive norms on the association between media use and breast cancer prevention intentions.

The impact of AI-enabled CRM systems on organizational competitive advantage: A mixed-method approach using BERTopic and PLS-SEM

The recent advances in machine learning and deep learning algorithms, along with the advent of generative AI, have led AI to become the "new normal" in organizations. This trend has extended to CRM, resulting in the development of AI-enabled CRM systems, or AI-CRM. Despite the growing adoption of AI as part of competitive strategies, many firms report minimal or no positive effect of AI on performance. This study addresses the research questions: "What are the critical features of AI-CRM systems?" and "How do these features impact organizational competitive advantage?" To explore this, we aim to identify key characteristics of AI-CRM and assess their impact on organizational performance. In Study 1, we utilize BERTopic topic modeling to extract critical features of AI-CRM from user reviews. Study 2 employs PLS-SEM to examine how these features influence organizational competitive advantage. Study 1 reveals four main characteristics of AI-CRM (general, marketing, sales, and service/support), each comprising distinct features. Study 2 shows that these characteristics differentially impact CRM capability, significantly affecting performance and competitive advantage. The findings offer valuable insights for both theory and practice regarding the effective use of AI in organizations.

Government support, employee structure and organisational digital innovation: Evidence from China

Digital innovation activities are data-driven, and the process of organizational digital innovation is inevitably influenced by their key participants, employees, as well as changes in the social institutional environment. How government support and employee structure impact organisational digital innovation was examined in this study. Since digital innovation activities are data-driven, the mediating role of data flows within digital innovation ecosystems was explored. A quantitative research design was employed, and data were collected by a survey from 299 firms in China. Results of structural equation modelling using SPSS and AMOS reveal that government support for enterprises in terms of policies and services, as well as the employee structure within enterprises, have a direct impact on organisational digital innovation. Data flows within digital innovation ecosystems mediate the relationship between government support and organisational digital innovation activities. Our findings provided evidence for theories of digital innovation ecosystems and employee-driven digital innovation. The results and conclusions in this study can provide reference for enterprises to achieve digital innovation breakthroughs, and for policymakers to formulate digital-related policies and regulations.

Detecting jingle and jangle fallacies by identifying consistencies and variabilities in study specifications - a call for research

Over the past few years, more attention has been paid to jingle and jangle fallacies in psychological science. Jingle fallacies arise when two or more distinct psychological phenomena are erroneously labeled with the same term, while jangle fallacies occur when different terms are used to describe the same phenomenon. Jingle and jangle fallacies emerge due to the vague linkage between psychological theories and their practical implementation in empirical studies, compounded by variations in study designs, methodologies, and applying different statistical procedures' algorithms. Despite progress in organizing scientific findings via systematic reviews and meta-analyses, effective strategies to prevent these fallacies are still lacking. This paper explores the integration of several approaches with the potential to identify and mitigate jingle and jangle fallacies within psychological science. Essentially, organizing studies according to their specifications, which include theoretical background, methods, study designs, and results, alongside a combinatorial algorithm and flexible inclusion criteria, may indeed represent a feasible approach. A jingle-fallacy detector arises when identical specifications lead to disparate outcomes, whereas jangle-fallacy indicators could operate on the premise that varying specifications consistently yield overrandomly similar results. We discuss the role of advanced computational technologies, such as Natural Language Processing (NLP), in identifying these fallacies. In conclusion, addressing jingle and jangle fallacies requires a comprehensive approach that considers all levels and phases of psychological science.

The impact of policy and technology infrastructure on telehealth utilization

The COVID-19 outbreak resulted in an unprecedented surge in telehealth utilization. However, the effects of policy enactment on utilization remain understudied in the literature. Our research examines the impact of policy mandates relating to federal incentive programs on telehealth utilization across states during the pandemic by considering technology infrastructure, such as broadband penetration and equipment possession. This study also considers the impact of political orientation and control factors, including income attributes, on telehealth utilization. Considering telehealth utilization in the Medicare program as a test case, this study employed the partial least square and structural equation model to analyze data from the Centers for Medicare & Medicaid Services, the American Community Survey, and the Microsoft Airband Project to draw inferences. Our study finds that telehealth legislation, broadband penetration, political orientation, and control factors have a direct significant impact on telehealth utilization, whereas incentive programs and equipment possession have an indirect impact through broadband penetration.

How users make online privacy decisions in work and personal contexts of use

With the rising usage of contactless work options since COVID-19, users increasingly share their personal data in digital tools at work. Using an experimental online vignette study (N = 93), we examined users' willingness to use a video conferencing tool, while systematically varying the context of use (personal vs. low trustworthiness work vs. high trustworthiness work) and the type of information shared (low vs. medium vs. high sensitivity). We also assessed users' perceived responsibility in work and personal contexts of use and their self-assessed digital competence. Our results highlight employer trustworthiness as an important factor in the willingness to use a third-party video conferencing tool, with increased willingness to use these tools in work contexts of use with high trustworthiness compared to those with low trustworthiness. This effect seems to be reduced when the data to be shared is of high sensitivity, compared to medium and low sensitivity data. Furthermore, despite reduced responsibility for data protection in work compared to personal contexts of use, the willingness to use a video conferencing tool did not decrease between trustworthy work and personal contexts of use. We discuss our findings and their methodological implications for future research and derive implications for privacy decisions at work.

Equity and efficiency of health resource allocation in the Chengdu-Chongqing Economic Circle of China

Objective

This study aimed to evaluate the fairness and efficiency of health resource allocation (HRAE) in Chengdu-Chongqing Economic Circle after the new healthcare reform. This study also aimed to identify existing problems, providing empirical evidence for the government to formulate regional health plans scientifically and reasonably.

Methods

The fairness of health resource allocation was analyzed using the Gini coefficient, Theil index, and agglomeration degree from population and geographical area perspectives. The three-stage data envelopment analysis and the Malmquist productivity index were used to analyze HRAE from static and dynamic perspectives.

Results

The Gini coefficient for population allocation in Chengdu-Chongqing Economic Circle was 0.066-0.283, and the Gini coefficient for geographical area allocation was 0.297-0.469. The contribution rate within a region was greater than that between regions, and health resources were mainly concentrated in economically developed core areas. The overall fairness of Chengdu Economic Circle was relatively better than that of Chongqing Economic Circle. Moreover, the adjusted mean technical efficiency was 0.806, indicating room for HRAE improvement in Chengdu-Chongqing Economic Circle. Stochastic Frontier Analysis found that different environmental variables have varying degrees of impact on HRAE. The adjusted mean total factor productivity change (Tfpch) was 1.027, indicating an overall upward trend in HRAE since the new healthcare reform. However, scale efficiency change (Sech) (0.997) limited the improvement of Tfpch.

Conclusion

The fairness of health resources allocated by population was better than that allocated by geographical area. The unfairness of health resources mainly stemmed from intra-regional differences, with considerable health resources concentrated in core areas. Over the past 13 years, HRAE has improved but exhibited spatial heterogeneity and Sech-hindered productivity improvement. The study recommends strengthening regional cooperation and sharing to promote the integrated and high-quality development of the health and well-being in Chengdu-Chongqing Economic Circle.

A local community on a global collective intelligence platform: A case study of individual preferences and collective bias in ecological citizen science

The collective intelligence of crowds could potentially be harnessed to address global challenges, such as biodiversity loss and species' extinction. For wisdom to emerge from the crowd, certain conditions are required. Importantly, the crowd should be diverse and people's contributions should be independent of one another. Here we investigate a global citizen-science platform-iNaturalist-on which citizens report on wildlife observations, collectively producing maps of species' spatiotemporal distribution. The organization of global platforms such as iNaturalist around local projects compromises the assumption of diversity and independence, and thus raises concerns regarding the quality of such collectively-generated data. We spent four years closely immersing ourselves in a local community of citizen scientists who reported their wildlife sightings on iNaturalist. Our ethnographic study involved the use of questionnaires, interviews, and analysis of archival materials. Our analysis revealed observers' nuanced considerations as they chose where, when, and what type of species to monitor, and which observations to report. Following a thematic analysis of the data, we organized observers' preferences and constraints into four main categories: recordability, community value, personal preferences, and convenience. We show that while some individual partialities can "cancel each other out", others are commonly shared among members of the community, potentially biasing the aggregate database of observations. Our discussion draws attention to the way in which widely-shared individual preferences might manifest as spatial, temporal, and crucially, taxonomic biases in the collectively-created database. We offer avenues for continued research that will help better understand-and tackle-individual preferences, with the goal of attenuating collective bias in data, and facilitating the generation of reliable state-of-nature reports. Finally, we offer insights into the broader literature on biases in collective intelligence systems.

A Systematic Review of Online Medical Consultation Research

Online medical consultation is a form of medical service that facilitates interactions between patients and doctors online, offering significant utility and value. This review aims to retrieve, screen, and analyze articles related to online medical consultations, formulating a theoretical framework and proposing future research directions. According to PRISMA guidelines, a systematic search was conducted in Web of Science, EBSCO, ScienceDirect, PubMed, and Scopus, retrieving a total of 4072 English records on 16 December 2023. After rigorous screening, 75 articles were included in this review. Among these, 8 articles focused on patients utilizing online medical consultation platforms, 5 on doctors participating in online medical platforms, 18 on patients' choice of doctors, 12 on doctors providing services, 7 on online reviews of patients, 14 on service quality for patients, 8 on rewards to doctors, and 11 on the spillover effect between online and offline services. These themes comprise the theoretical framework of the starting point, process, and outcomes of the online medical consultation system, providing a comprehensive understanding of the field and a foundation for future research.

NK model simulation study of intelligent manufacturing transformation path selection in pharmaceutical manufacturing enterprises

Under the wave of Industry 4.0, traditional pharmaceutical manufacturing enterprises are in urgent need of intelligent manufacturing transformation and upgrading, and exploring the optimal realization path of intelligent manufacturing transformation can help accelerate the transformation process of pharmaceutical manufacturing enterprises. This paper uses grounded theory research methods to conduct a multi-case study to summarize six influencing factors of the intelligent manufacturing transformation of Chinese pharmaceutical manufacturing enterprises; and then analyzes the correlation between the intelligent manufacturing influencing factors based on the DEMATEL method and the NK model, and identifies the key influencing factors according to this, and then draws the fitness landscape map of the intelligent manufacturing transformation, and finally arrives at the optimal path selection of the intelligent manufacturing transformation of pharmaceutical manufacturing enterprises. The study enriches and extends the research paradigm of intelligent manufacturing transformation, and provides lessons for pharmaceutical manufacturing enterprises to realize intelligent manufacturing transformation and upgrading.

The formation pattern, causes, and governance of network public opinion on university emergencies

Background

University emergencies, garnering significant public attention and shaping network opinions, pose a crucial challenge to universities' management and societal stability. Hence, network public opinion on university emergencies is a vital issue. Nevertheless, the underlying mechanism has not been fully explored and cannot be efficiently controlled. This study aimed to explore the formation pattern of network public opinion on university emergencies, analyze its causes, and provide scientific governance strategies for coping with this issue.

Methods

Based on a sample set of 204 cases from the Zhiwei Data Sharing Platform, this study classifies network public opinion on university emergencies into six types and visually analyzes their characteristics: time distribution, subject, duration, and emotion. By integrating the theory of the network public opinion field, this study develops a network public opinion field model of university emergencies to reveal its formation pattern. Furthermore, it analyzes the causes of network public opinion on university emergencies from the perspective of the public opinion lifecycle and proposes corresponding governance strategies.

Results

The sample consisted of 304 cases of real-life public opinion, and the visualization results show that public opinion on mental health and teacher-student safety constitutes the predominant types, accounting for 83.3%. High-occurrence subjects are public universities (88.24%) and students (48%). The most frequent months are July and December. 90.20% of the public opinions have a lifespan of less than 19 days, with an impact index ranging from 40 to 80. The public's emotional response to different types of public opinion varies, with negative emotions dominating.

Conclusion

This study provides novel insights for understanding their formation and dissemination. It also provides practical implications for relevant departments to govern network public opinion on university emergencies.

A Meta-Analytic Reliability Generalization Study of the Pediatric Voice Handicap Index

OBJECTIVES

The pediatric voice handicap index (pVHI) is a widely used proxy-reported outcome measure. However, its reliability values are subject to variability across studies. Accordingly, the objective of this study is to analyze the mean reliability estimation and stratified alpha coefficient of the pVHI. Another aim of the study is to determine if differences in reliability values can be linked to the specific research characteristics.

STUDY DESIGN

This is a meta-analytic reliability generalization study.

METHODS

Two researchers used Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria to review five databases (Scopus, Web of Science, YÖKTEZ, Ulakbim, and PUBMED) for publications published between 2007 and 2022 that used pVHI. A meta-analysis was then conducted on 12 papers that fit the predetermined inclusion criteria to ascertain the total effect size of the Cronbach's alpha coefficient of pVHI scores. The reliability coefficients of pVHI were computed utilizing Cochran Q, I2, and the lower and upper bounds of mean reliability. Additionally, moderator analyses were employed to examine the heterogeneity among studies.

RESULTS

The computed mean reliability value was approximately 0.916 [0.8840, 0.9401] which is within the acceptable range (>0.70). Furthermore, the mean stratified Cronbach's alpha coefficient was found to be roughly 0.95. The heterogeneity statistics indicated that the reliability estimations for each study varied significantly (Q ∼ (df = 11) ∼ = 163.6172, P < 0.0001; I2 = 93.90%).

CONCLUSIONS

Results indicate that pVHI yields sufficiently reliable outcomes. Furthermore, the reliability of the pVHI remained consistent regardless of index language, participant group (healthy, dysphonic, or both), or continent of origin. These results improve the clinical value and utility of pVHI by providing further evidence of its reliability.

Digital transformation in college libraries: The effect of digital reading on reader service satisfaction

In the pursuit of digital transformation, college libraries have increasingly embraced the promotion of digital reading as a critical initiative. While numerous studies have delved into the strategies employed by college libraries in their digital transformation endeavors, there remains a lack of research elucidating the direct influence of digital reading on reader service satisfaction within these institutions. Drawing upon the service quality model, this paper aims to address this gap by examining the multifaceted influence of digital reading on reader service satisfaction in college libraries. By examining the various dimensions of digital reading services, this study employs the fsQCA approach to uncover specific combinations that contribute to heightened levels of reader service satisfaction. The results reveal three distinct configurations that can explain the high level of reader service satisfaction. By elucidating these critical relationships, this research not only provides a contribution to the research regarding the evolving role of college libraries but also provides practical insights for college libraries aspiring to realize digital transformation by promoting digital reading.

Technology in farming: Unleashing farmers' behavioral intention for the adoption of agriculture 5.0

The agriculture sector has undergone a remarkable revolution known as Agriculture 5.0 (Ag 5.0), emphasizing digital technology to boost efficiency and profitability of farm business. However, little is known about farmers' behavioral intension to adopt Ag 5.0. In this study we examine factors influencing farmer's behavioral intension for Agriculture 5.0, identify implementation obstacles and provide managerial solutions to promote Ag 5.0 in Madhesh Province, Nepal, using the Technology Acceptance Model (TAM) and Structural Equation Model (SEM). We tested total of 20 different hypotheses. Primary data were collected from 271 farmers across 9 municipalities in Saptari District, Nepal. The study reveals that technology anxiety [(β = 0.101, p<0.01); (β = 0.188, p<0.01)], self-efficacy [(β = 0.312, p<0.01, (β = 0.170, p<0.05)] and social influence [(β = 0.411, p<0.01), (β = 0.170, p<0.05)] significantly impact the perceived usefulness as well as perceived ease of use, respectively. Individual innovativeness also affects the perceived usefulness (β = 0.004, p<0.05) and perceived ease of use (β = 0.281, p<0.01). Moreover, the study found that attitude towards using Ag 5.0 is significantly influenced by perceived usefulness (β = 0.083, p<0.10) and ease of use (β = 0.189, p<0.01), which, in turn, affects the intention to use Ag 5.0 (β = 0.858, p<0.01). Farmers perceive training programs, government assistance, and subsidies as helpful in overcoming challenges associated with adopting Ag 5.0. This study provides valuable insights for policymakers, development partners, and farmers' organizations, enabling them to understand the factors influencing the readiness for Ag 5.0 adoption in Nepal.

After Online Innovators Receive Performance-Contingent Material Rewards: A Study Based on an Open Innovation Platform

In recent years, enterprises have increasingly recognized the pivotal role of external users in driving product innovation. Open innovation platforms (OIPs), which facilitate interactions between companies and external innovators, have emerged as critical conduits in this regard. However, OIP managers face the challenge of motivating innovators to sustain their contributions. While some OIPs have implemented material incentives, the impact of such rewards on users' ongoing innovation efforts remains uncertain. This study utilized a large-scale dataset from an OIP to examine how performance-contingent material rewards influence the subsequent behaviors of online innovators. Employing a quasi-experimental design involving propensity score matching (PSM) and difference-in-differences (DID) analysis, we found that receiving performance-contingent material rewards led to a decrease in the quantity of subsequent ideas generated by innovators. However, these rewarded innovators produced ideas of higher quality. Interestingly, the novelty of ideas submitted by innovators declined following their receiving of rewards. Moreover, newly enlisted innovators exhibited a more positive response to these incentives. Our findings provide valuable insights for platform managers seeking to optimize incentive mechanisms. We suggest adopting diversified incentive approaches and refining incentive strategies to effectively motivate continuous innovation among users on OIPs.

The contingent effects of strategic orientations and strategic capabilities on competitive performance: Evidence from Ethiopian manufacturing enterprises

While there are several studies that examine the performance implications of different strategic orientations, little is known regarding the complex interplay between the two prominent strategic orientations and strategic capabilities in impacting firm performance. Notably, it is ambiguous how a firm's strategic orientations are aligned with different strategic capabilities to maintain competitive performance. To address this gap, the study employs a moderated mediation analysis to investigate the mediating role of strategic capabilities in the relationship between market, technology orientations, and firm performance. It also examines the moderating effect of environmental dynamism in shaping the mediated association between strategic orientations and performance. Based on the survey results of 205 large Ethiopian manufacturing firms, our findings confirm that market orientation exerts a positive and significant influence on both marketing and market-linking capabilities, while only marketing capabilities mediate the relationship between market orientation and firm performance. Likewise, there is a strong association between technology orientation and strategic capabilities (i.e., technology and information technology capabilities), mediating the relationship with firm performance. Meanwhile, environmental dynamism influences the indirect relationship that exists between market, technology, and firm performance through their corresponding strategic capabilities. Our study sheds light on strategic management literature by showing the unique relationship and interdependency between strategic orientations and capabilities in attaining superior performance. This study also forwarded some practical implications of the findings.

What are the key factors influencing scientific data sharing? A combined application of grounded theory and fuzzy-DEMATEL approach

Scientific data sharing (SDS) has become essential for scientific progress, technological innovation and socioeconomic development. Identifying the key influencing factors of SDS can effectively promote SDS programmes and give full play to the critical role of scientific data. This study used grounded theory and information ecology theory to construct an SDS influencing factor model that encompassed five dimensions and 28 influencing factors and followed the fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) approach to measure and analyse the degree of influence of each influencing factor and identify the key factors. The results show that (1) there are interactions and mutual interactions between the various influencing factors of SDS, which can form a complex network system. (2) 16 influencing factors, such as data-sharing policies, data-sharing regulations and data-sharing standards, comprise the key influencing factors in SDS. (3) The optimisation path of SDS is 'Scientific Researchers' → 'Scientific Data' → 'Policy Environment' → 'Research Organisations → 'Information Technologies'. In this regard, we proposed the following management suggestions to promote the development of SDS programmes in China: focusing on researchers' subjective willingness to share, enhancing the integrated governance of scientific data, fulfilling the role of policy support and guidance, strengthening the support of research organisations and improving SDS platforms with information technology.

Perspective of smokers and healthcare professionals toward real-time video counseling smoking cessation program in general out-patient clinics in Hong Kong: a qualitative study

OBJECTIVE

This study aimed to explore the perceptions and experiences of individuals that currently smoke and healthcare professionals on using real-time video counseling in the Smoking Cessation and Counselling Program in General Out-patient Clinics in Hong Kong.

DESIGN

This was a qualitative study using face-to-face semi-structured interviews based on the extended technology acceptance model. All interviews were audiotaped and transcribed verbatim. Two investigators coded the transcripts independently. Thematic analysis was adopted.

PARTICIPANTS

Individuals that currently smoke and healthcare professionals who had experience using real-time video counseling in the Smoking Cessation and Counselling Program in General Out-patient Clinics in Hong Kong were recruited. Purposive sampling was adopted. 18 participants were interviewed to reach data saturation.

MAIN OUTCOME MEASURES

Themes that emerged from thematic analysis of data were the main outcome measures. The emerged themes were refined and verified via inductive and then deductive processes until data saturation was reached.

RESULTS

Two core themes, which were in coherence with the extended technology acceptance model, namely (i) perceived ease of use and (ii) perceived usefulness, were identified. Under perceived ease of use, we identified 2 subthemes: (i) convenience and (ii) measures to facilitate the use of real-time video counseling. Three subthemes were identified under perceived usefulness: (i) empathy and rapport, (ii) measures for pandemics, and (iii) service outcome.

CONCLUSION

Our study provided a culture-specific perspective of users towards real-time video counseling. It identified users' opinions on the easiness and usefulness of the service. Those could provide clues for future improvement and development of using real-time video counseling in healthcare services.