Impact of Gold-Standard Label Errors on Evaluating Performance of Deep Learning Models in Diabetic Retinopathy Screening: Nationwide Real-World Validation Study

BACKGROUND

For medical artificial intelligence (AI) training and validation, human expert labels are considered the gold standard that represents the correct answers or desired outputs for a given data set. These labels serve as a reference or benchmark against which the model's predictions are compared.

OBJECTIVE

This study aimed to assess the accuracy of a custom deep learning (DL) algorithm on classifying diabetic retinopathy (DR) and further demonstrate how label errors may contribute to this assessment in a nationwide DR-screening program.

METHODS

Fundus photographs from the Lifeline Express, a nationwide DR-screening program, were analyzed to identify the presence of referable DR using both (1) manual grading by National Health Service England-certificated graders and (2) a DL-based DR-screening algorithm with validated good lab performance. To assess the accuracy of labels, a random sample of images with disagreement between the DL algorithm and the labels was adjudicated by ophthalmologists who were masked to the previous grading results. The error rates of labels in this sample were then used to correct the number of negative and positive cases in the entire data set, serving as postcorrection labels. The DL algorithm's performance was evaluated against both pre- and postcorrection labels.

RESULTS

The analysis included 736,083 images from 237,824 participants. The DL algorithm exhibited a gap between the real-world performance and the lab-reported performance in this nationwide data set, with a sensitivity increase of 12.5% (from 79.6% to 92.5%, P<.001) and a specificity increase of 6.9% (from 91.6% to 98.5%, P<.001). In the random sample, 63.6% (560/880) of negative images and 5.2% (140/2710) of positive images were misclassified in the precorrection human labels. High myopia was the primary reason for misclassifying non-DR images as referable DR images, while laser spots were predominantly responsible for misclassified referable cases. The estimated label error rate for the entire data set was 1.2%. The label correction was estimated to bring about a 12.5% enhancement in the estimated sensitivity of the DL algorithm (P<.001).

CONCLUSIONS

Label errors based on human image grading, although in a small percentage, can significantly affect the performance evaluation of DL algorithms in real-world DR screening.

Do Psychological Ownership and Communicative Presence Matter? Examining How User-Generated Content in E-Commerce Live Streaming Influences Consumers' Purchase Intention

E-commerce live streaming has become a lucrative global industry. As the main carrier to convey information in live broadcasting, user-generated content (UGC)-and especially bullet screens-are crucial in influencing users' purchase intentions. However, the influence of bullet screens' multidimensional information characteristics on consumers' decision-making processes requires further exploration. Additionally, most existing studies start with the short-term effects of live product realization, and must address how to enhance customers' psychological ownership using new means of live streaming marketing to obtain long-term sustainable brand-building effects. This study introduces psychological ownership and the communicative presence as mediating variables based on the theory of elaboration likelihood modeling to explore the mechanism of the influence of UGC's multidimensional features on viewers' purchase intentions in live e-commerce broadcasting rooms. We collected 404 valid online questionnaires and tested our hypotheses using structural equation modeling. These findings indicate that UGC emotions, quality, and their interaction significantly and positively affect purchase intentions. Moreover, psychological ownership and the communicative presence mediate UGC's effect on purchase intentions. These results provide a new perspective for understanding consumer behavior in live e-commerce to improve marketing effectiveness of e-commerce live streaming platforms.

How to Stimulate Continuous Innovative Knowledge Contribution? Mediation by Self-Efficacy and Moderation by Knowledge Level

Taking the perspective of innovative knowledge management, this study aimed to investigate the stimulation mechanism of continuous innovative knowledge contribution (CIKC). Through a quantitative study conducted in an open innovation community, we modeled a stimulus-organism-response framework to conduct a path analysis from the external environment to internal cognition, and then to knowledge contribution, and filled in the gaps in the mediating and moderating mechanisms. We focused on the stimuli of knowledge contribution, in view of both quantity and quality. Panel data from six periods in one year was collected for dynamic analysis, and we used the fixed effect model to test our hypotheses of mediation effect, moderation effect, and mediated-moderation effect. There were some interesting findings, showing that user's self-efficacy plays a partial mediating role in the quantity, rather than the quality, of CIKC; meanwhile, the users' knowledge level plays a moderating role, and there is a negative moderating mechanism of knowledge level in the process from participation value to the quality of CIKC.

The dynamic interdependencies among the negativity and the positivity in news and user-generated content about safety in a firm's products and the firm's product recalls

This article examines the dynamic interdependencies among the negativity and the positivity in news and user-generated content about safety in a firm's products (or the lack thereof) and the firm's product recalls. The authors use a panel vector autoregression (PVAR) to unearth theoretically novel and managerially relevant asymmetric associations. Specifically, they find that the negativity in the news negatively correlates with recalls, whereas the negativity in UGC positively correlates with recalls. Whereas the positivity in the news positively correlates with recalls, the positivity in UGC does not matter. Further, the negativity in the news and the negativity in UGC substitute for each other, whereas their positive counterparts complement each other's associations with recalls. Lastly, the negativity and positivity in the news have significant, though differently patterned, long-term associations with recalls. The findings contribute to research on the associations between earned media and managerial decisions in the product market.

Study examining the significant role of intellectual property protection in driving radical technological innovation among national research project teams, employing PLS-SEM and ANN modeling

This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspective. This study utilizes a sample of 336 national research project team members from various Chinese universities, research institutes, and corporations to analyze the theoretical model. Additionally, a two-stage hybrid partial least squares structural equation modeling (PLS-SEM) approach, combined with artificial neural network techniques (ANN), is employed to evaluate the hypotheses. The empirical findings of this study reveal a positive association between the intensity of IPP and RTI within national research project teams. Research and development investment intensity (R&DII) is identified as the primary predictor, while integrated leadership (IL) and group potential (GP) play crucial moderating roles. These groundbreaking findings extend the scope of innovation-driven and AMO theories, providing a proactive model for national research project teams to propose improvements to the IPP system, ultimately enhancing the realization of RTI.

How enterprise social media usage links to counterproductive work behavior: the mediating role of workplace loneliness and the moderating role of ICT hassle

Work context transformed. Employees increasingly interact with enterprise social media, wherein employees may feel disconnected from workplace. Drawing on social affiliation theory, we develop and examine a moderated mediation model to explore the indirect effect of enterprise social media usage on counterproductive work behavior (CWB) via workplace loneliness and the moderating role of information and communication technology hassle (ICT hassle). We test hypotheses by conducting a three-wave survey of 345 knowledge workers. Results indicate that enterprise social media usage has a positive effect on workplace loneliness, and workplace loneliness mediated the indirect effect of enterprise social media usage on CWB. The moderated mediation analysis indicated that ICT hassle positively moderates the above mediation effect. We discuss the theoretical and practical implications of our findings.

Assessing Patient Trust in Automation in Health Care Systems: Within-Subjects Experimental Study

BACKGROUND

Health care technology has the ability to change patient outcomes for the betterment when designed appropriately. Automation is becoming smarter and is increasingly being integrated into health care work systems.

OBJECTIVE

This study focuses on investigating trust between patients and an automated cardiac risk assessment tool (CRAT) in a simulated emergency department setting.

METHODS

A within-subjects experimental study was performed to investigate differences in automation modes for the CRAT: (1) no automation, (2) automation only, and (3) semiautomation. Participants were asked to enter their simulated symptoms for each scenario into the CRAT as instructed by the experimenter, and they would automatically be classified as high, medium, or low risk depending on the symptoms entered. Participants were asked to provide their trust ratings for each combination of risk classification and automation mode on a scale of 1 to 10 (1=absolutely no trust and 10=complete trust).

RESULTS

Results from this study indicate that the participants significantly trusted the semiautomation condition more compared to the automation-only condition (P=.002), and they trusted the no automation condition significantly more than the automation-only condition (P=.03). Additionally, participants significantly trusted the CRAT more in the high-severity scenario compared to the medium-severity scenario (P=.004).

CONCLUSIONS

The findings from this study emphasize the importance of the human component of automation when designing automated technology in health care systems. Automation and artificially intelligent systems are becoming more prevalent in health care systems, and this work emphasizes the need to consider the human element when designing automation into care delivery.

The impact of teachers' perceived competence in information and communication technology usage, and workplace anxiety on well-being, as mediated by emotional exhaustion

Introduction

The 2030 Sustainable Development Goals (SDGs) were adopted by the United Nations in 2015, emphasizing the importance of achieving peace, prosperity, and well-being for all people. With the outbreak of the COVID-19 pandemic, sustainable health has become an important issue. Teachers were forced to adopt distance teaching, necessitating rapid upgrading of their ICT skills and integration into e-learning, which caused tangible and intangible pressures on teachers and impacted their well-being. This study examined the effects of ICT competence on teachers' workplace anxiety, emotional exhaustion, and well-being during the pandemic from the perspective of Social Cognitive Theory (SCT).

Methods

A quantitative research methodology and a questionnaire survey with a total of 21 questions were used as the primary research design. The snowball method was employed as a sampling method for online questionnaires from September to October 2021. A total of 216 questionnaires were collected, of which four incomplete questionnaires were excluded, leaving 212 valid questionnaires, with a valid questionnaire recovery rate of 98.1%. The valid questionnaires were analyzed using Smart Pls 4.0 Partial Least Square Method Structural Equation Modeling (PLS-SEM).

Results

The study found that teachers' ICT competence could significantly reduce emotional exhaustion and enhance teachers' well-being. However, there was no significant effect on workplace anxiety. Additionally, well-being was not directly affected by workplace anxiety, and teachers' well-being needs to be mediated by emotional exhaustion to be indirectly affected. Emotional exhaustion plays an important mediating role between teachers' ICT competence and workplace stress, both of which are important mediators of well-being.

Discussion

From a practical point of view, to achieve the Sustainable Development Goals (SDGs) 2030, it is ideal to have good health and well-being for the whole person. This study facilitates the development of strategies to improve the well-being of teachers, which provides an empirical basis for the enhancement of mental health and well-being of educators.

Acceptance of e-learning and associated factors among postgraduate medical and health science students at first generation universities in Amhara region, 2023: using modified technology acceptance model

BACKGROUND

Electronic learning is the process of remote teaching and learning through the use of electronic media. There is a dearth of research on the factors influencing e-learning acceptance in Ethiopia using the modified technology acceptance model (TAM). Previous research appears to have overlooked the mediating impact of factors on e-learning acceptability Therefore, the present study aimed to assess the acceptance of e-learning and its associated factors among postgraduate medical and health science students by applying TAM at first-generation universities in the Amhara region.

METHODS

This institutional-based cross-sectional study was conducted from March 15 to April 20, 2023, at Amhara First Generation University, Ethiopia. A total of 659 students participated in the study. A self-administered questionnaire in the Amharic language was used to collect the data. SEM analysis was employed to test the proposed model and the relationships among factors using SPSS version 25 and AMOS version 26.

RESULTS

The proportion of postgraduate students who agreed to use e-learning was 60.7%, 95% CI (56.9-64.4). SEM analysis revealed that perceived ease of use (β = 0.210, p < 0.001), attitude (β = 0.377, p < 0.001) and perceived usefulness (β = 0.330, p < 0.001) had positive direct relationships with acceptance of e-learning. Perceived usefulness (β = 0.131, p < 0.001), and perceived ease of use (β = 0.029, p < 0.01) significantly mediate the relationship between self-efficacy, and acceptance of e-learning. Accessibility had a positive indirect effect on acceptance of e-learning through perceived ease of use (β = 0.040, p < 0.01). Facilitating condition had a positive indirect on acceptance of e-learning through perceived ease of use (β = 0.070, p < 0.01), and perceived usefulness (β = 0.084, p < 0.001).

CONCLUSION AND RECOMMENDATION

Overall, the proportion of postgraduate students who accepted e-learning is promising. Perceived ease of use perceived usefulness, and attitude had positive direct effects on the acceptance of e-learning. Facilitating conditions and self-efficacy had positive indirect effects on the acceptance of e-learning. Thus, implementers need to prioritize enhancing the provision of devices, students' skills, and knowledge of e-learning by providing continuous support to improve students' acceptance of the use of e-learning.

Effectiveness of digital health interventions for perinatal depression: a systematic review and meta-analysis

Pregnant women and new mothers within 1 year after delivery are at a high risk of depression, yet many do not get the help they need due to wide reasons heralding stigma, access, cost, time, and shortage of human resources. Hence, compelling the exploration of alternate and potentially cost-effective means of delivering care, including the leverage of digital tools. This review aimed to evaluate the effectiveness of digital health interventions in reducing depressive symptoms among perinatal women. Literatures were sought from seven academic databases alongside the references of previous reviews. Included studies were all quantitative study types involving the use of digital health interventions for perinatal women not more than 1-year post-delivery. Standardized mean difference and standard error were used to perform random-effect model meta-analysis. Sensitivity and subgroup analyses were performed to determine certainty and modifiers of the findings, respectively. Forty-eight studies were included in this review with 28 studies used for meta-analyses. Numerous digital channels were identified; however, none specified the use of a digital health theory in its development. The digital health interventions showed a small positive significant effect over the controls (standardized mean difference = 0.29, P = 0.003, I 2 = 34%), and this was significantly influenced by intervention delivery and facilitation modes, time of initiation of the intervention, and period covered by the intervention. Although digital health interventions may hold some potential for perinatal depression, scaling the interventions may be challenging sequel to overlooked influences from the interactions within the human-computer-society complex.

mRNA Vaccine Hesitancy: Spreading Misinformation Through Online Narratives

This research examined the themes that emerge from online discussions of the COVID-19 vaccines to assist health communicators and officials in combating misinformation in health-related discussions. Using framing theory and the diffusion of innovation framework, this study presents findings from a semantic network analysis of 3842 tweets collected during the first week of February 2022. The authors calculated betweenness and page rank centrality scores for Twitter users participating in the online dialogue and identified 36 semantic themes. Findings revealed that the most influential dialogue participants were retired health and medical professionals, data analysts, journalists, online advocates, and politicians. The frames identified in the study contained several misinformation narratives about the COVID-19 vaccines. The authors discuss the implications of these findings for health officials and communicators as well as the theoretical implications of the diffusion of misinformation and framing as a tool to reiterate untruths.

Understanding Users' Acceptance of Artificial Intelligence Applications: A Literature Review

In recent years, with the continuous expansion of artificial intelligence (AI) application forms and fields, users' acceptance of AI applications has attracted increasing attention from scholars and business practitioners. Although extant studies have extensively explored user acceptance of different AI applications, there is still a lack of understanding of the roles played by different AI applications in human-AI interaction, which may limit the understanding of inconsistent findings about user acceptance of AI. This study addresses this issue by conducting a systematic literature review on AI acceptance research in leading journals of Information Systems and Marketing disciplines from 2020 to 2023. Based on a review of 80 papers, this study made contributions by (i) providing an overview of methodologies and theoretical frameworks utilized in AI acceptance research; (ii) summarizing the key factors, potential mechanisms, and theorization of users' acceptance response to AI service providers and AI task substitutes, respectively; and (iii) proposing opinions on the limitations of extant research and providing guidance for future research.

Automatic uncovering of patient primary concerns in portal messages using a fusion framework of pretrained language models

OBJECTIVES

The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care.

MATERIALS AND METHODS

We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural Network for precise identification of patient primary concerns via multi-class classification. We examined 3 traditional machine learning models, 9 BERT-based language models, 6 fusion models, and 2 ensemble models.

RESULTS

The outcomes of our experimentation underscore the superior performance achieved by BERT-based models in comparison to traditional machine learning models. Remarkably, our fusion model emerges as the top-performing solution, delivering a notably improved accuracy score of 77.67 ± 2.74% and an F1 score of 74.37 ± 3.70% in macro-average.

DISCUSSION

This study highlights the feasibility and effectiveness of multi-class classification for patient primary concern detection and the proposed fusion framework for enhancing primary concern detection.

CONCLUSIONS

The use of multi-class classification enhanced by a fusion of multiple pretrained LMs not only improves the accuracy and efficiency of patient primary concern identification in PPMs but also aids in managing the rising volume of PPMs in healthcare, ensuring critical patient communications are addressed promptly and accurately.

Countering technostress in virtual work environments: The role of work-based learning and digital leadership in enhancing employee well-being

Virtual work has been highlighted as an important business trend nowadays. Technostress caused by information and communication technology threatens employee well-being in a virtual context. We integrate insights from the Job Demands-Resources theory to explore the impact of technostress on employee well-being and examine work-based learning and digital leadership capability as buffers of this negative impact via the attenuating effect of work exhaustion. We collected multi-wave survey data from 300 virtual employees to test the theoretical model. Results revealed a significant negative impact of technostress on employee well-being. However, work-based learning and digital leadership capability buffered employees' well-being from this negative effect by reducing their work exhaustion. Our findings extend our understanding of work design and shed light on how to cope with virtual work demands.

A lightweight xAI approach to cervical cancer classification

Cervical cancer is caused in the vast majority of cases by the human papilloma virus (HPV) through sexual contact and requires a specific molecular-based analysis to be detected. As an HPV vaccine is available, the incidence of cervical cancer is up to ten times higher in areas without adequate healthcare resources. In recent years, liquid cytology has been used to overcome these shortcomings and perform mass screening. In addition, classifiers based on convolutional neural networks can be developed to help pathologists diagnose the disease. However, these systems always require the final verification of a pathologist to make a final diagnosis. For this reason, explainable AI techniques are required to highlight the most significant data to the healthcare professional, as it can be used to determine the confidence in the results and the areas of the image used for classification (allowing the professional to point out the areas he/she thinks are most important and cross-check them against those detected by the system in order to create incremental learning systems). In this work, a 4-phase optimization process is used to obtain a custom deep-learning classifier for distinguishing between 4 severity classes of cervical cancer with liquid-cytology images. The final classifier obtains an accuracy over 97% for 4 classes and 100% for 2 classes with execution times under 1 s (including the final report generation). Compared to previous works, the proposed classifier obtains better accuracy results with a lower computational cost.

Healthcare information management and operational cost performance: empirical evidence

Healthcare knowledge management systems can mitigate hospitals' operational inefficiency. As a healthcare information technology, the electronic health record (EHR) receives much attention from medical institutions due to its considerable impact on operational cost performance. This paper focuses on EHR systems to address operational inefficiency by which patients pay more for health care services, and many U.S. hospitals are filing for bankruptcy. From the theoretical perspective of the practice-based view, this paper introduces a path to implement EHR systems for improving cost performance. The empirical investigation is archival data of 200 hospitals collected from the U.S. healthcare agencies. Findings contribute to prior work by hypothesizing moderating and mediating roles in EHR systems implementation. This paper introduces absorptive capacity and monitoring mechanisms as enablers of implementing EHR systems. The results showed that hospital monitoring strengthens the relationship between absorptive capacity and electronic health record systems implementation, which results in better operational cost performance. Theoretically, this study supports the long-term potential benefits of EHR adoption, and its findings are consistent with optimizing efficiency through data standardization and interoperability. From a practical perspective, this study supports hospitals' investments in evolving healthcare information technology systems through the development of a knowledge-based system employing EHR, particularly when hospitals are merging or need a financial strategic plan to control expenses.

Health welfare in the digital era: Exploring the impact of digital trade on residents' health

As a product combining information and communication technology, digital technology, and traditional trade, digital trade represents a new form of international trade development in the context of economic globalization. As its scale continues to expand, digital trade not only profoundly impacts consumer health behaviors and environmental pollution control but also enhances opportunities for residents to access healthcare products and services. This could potentially have a significant promoting effect on residents' health levels. However, the extent and mechanisms through which digital trade affects residents' health remain unclear. Accordingly, this study fills in a gap in the research by calculating the provincial-level digital trade index for China from 2012-2020 and matching it with data from the China Family Panel Studies. The goal is to find the micro-causal mechanisms of digital trade on residents' health from green consumption and environmental improvement perspectives. The results show that digital trade reduces residents' medical expenses and improves their health. We use a quasi-natural experiment by treating the cross-border e-commerce comprehensive pilot zone as a digital trade treatment group and conducting a difference-in-differences estimation, finding that the health effects of digital trade remain significant. Heterogeneity indicates that the health effects of digital trade are powerful for middle- and high-income households and rural residents. In the east and center, in regions with well-developed transportation infrastructure and digital financial inclusion, the development of digital trade is more conducive to residents' health. Additionally, we demonstrate that digital trade can affect residents' health by promoting green consumption, eliminating energy poverty (i.e., improving indoor air pollution), and enhancing environmental quality (i.e., improving outdoor environmental pollution). This study provides solid scientific empirical evidence for enhancing human sustainable development through global digital trade.

Determinants of users' unverified information sharing on social media platforms: A herding behavior perspective

The proliferation of unverified or false information by irresponsible users can significantly amplify the spread of misinformation or fake news. Despite growing research on unverified information sharing, a comprehensive understanding of the varying influences of different factors and strategies to mitigate this issue remains under investigation. To address this research gap, this study, rooted in the theory of herd behavior, develops, and tests a model theorizing the reasons behind social media users' unverified information sharing. Data was collected from 510 respondents across six regions of China using a convenience sampling method. The collected data was analyzed using Mplus. The results from this study indicated that perceived severity, state uncertainty, and herding have a significant positive influence on unverified information sharing. These results enrich the understanding of unverified information-sharing behavior among Chinese social media users. Drawing from these results, we suggest platform administrators and policymakers mitigate herd behavior tendencies and stem the spread of misinformation by disseminating timely, accurate, and authoritative information. Since this action will reduce users' perceptions of severity and uncertainty. Social media users are also advised to stay vigilant over the implications of herd behavior and foster a more critical attitude towards information sharing.

A national evaluation of Project Cautioning And Relationship Abuse ('CARA') awareness raising workshops for first time offenders of domestic violence and abuse: protocol for a concurrent mixed-methods evaluation design

Introduction

Interventions related to the perpetration of Domestic Violence and Abuse (DVA) have gained traction over the past several years, in response to dissatisfaction by victims, an inadequate response from the criminal justice system, increased demand on police time and a lack of rehabilitative responses to the perpetration of domestic abuse. The CARA model is a conditional diversionary caution, offered by police for first time offenders of 'standard' or 'medium risk' domestic abuse, that engages perpetrators in awareness raising workshops and signposts them onto further services. Although quasi-experimental studies have indicated that CARA showed promise at reducing reoffending, the CARA model has yet to be evaluated nationally and there is no qualitative evidence related to understanding or learning about the lived experience of perpetrators and victims as they engage with the intervention.

Methods

Using a concurrent pragmatic mixed methods design model we will undertake a national evaluation of CARA by triangulating quantitative data from up to nine police forces, and routine data from service providers, with qualitative data from workshop participants, victims and professional stakeholders to: (1) understand the long-term impact of CARA implementation on DVA reoffending and engagement with services and (2) explore perceptions and experiences of both delivery and receipt of CARA. We will use qualitative methodologies that draw on interpretivist and phenomenological perspectives, as well as quantitative methodologies using interrupted time series models, Poisson regression models, Geo mapping and a cost benefits analysis.

Ethics and dissemination

Where currently the CARA model is being introduced as a national option for standard risk first-time offending, we will engage with policymakers and academics nationally in the live debate on its effectiveness and suitability during its roll-out. Ethical approval was approved by the University of Southampton on the 1 st June 2022 (Ref: ERGO ID: 71818.A1).

Extending the job demands-resources model to understand the effect of the interactions between home and work domains on work engagement

Scholars have extensively used the job demands-resources model to explain the dynamics underlying work engagement and proposed several versions of the model. However, in theoretical terms, nonwork elements have not been incorporated into the model. This study investigated the roles of home demands and resources in the model by testing the boost/buffer hypotheses for work engagement from the perspective of the work-home interface. We demonstrated that (1) the demands of a domain boost the positive impact of resources drawn from another domain on work engagement, (2) the resources of a domain buffer the negative impact of demands derived from another domain on work engagement; and (3) the buffering and boosting effects of home demands and resources impact work engagement. We conducted a diary study on a group of coffee shop employees in Ireland. The results partially supported the proposed hypotheses but nevertheless indicated support for the cross-domain boost/buffer hypotheses with regard to work engagement. The proposed model may serve as a theoretical foundation for research on issues related to the impact of work and nonwork domains on work engagement.

Digital economy's role in shaping carbon emissions in the construction field: Insights from Chinese cities

Achieving net-zero greenhouse gas emissions in the construction sector is essential to sustainable development policy. Previous studies have ignored the impact of the digital economy on carbon emissions in the construction industry. Using relevant city-level data from China from 2011 to 2021 and employing ArcGIS and Stata software, this study examines the current status of carbon emissions from the construction industry and investigates the impact of the digital economy on these emissions. The findings reveal that (1) from 2011 to 2021, carbon emissions of the construction industry have a pattern of decreasing-increasing-decreasing-increasing across the country. There is an increasing concentration of areas with high and relatively high carbon discharges in Heilongjiang, Jilin, Ningxia, Inner Mongolia, Shanxi, Guangxi, and Guizhou. (2) The standard deviation ellipse indicates the core area of carbon emissions in China's construction industry is moving northeast and becoming more decentralized. (3) Through a series of robustness tests, the digital economy has been proven to effectively reduce carbon emissions from the construction sector in municipal areas. (4) In severely cold regions, mild regions, and high-population-density cities, the digital economy reduces building sector's carbon output. However, it stimulates carbon emissions in the hot summer and cold winter regions. (5) Mechanism tests show that the digital economy reduces China's urban construction carbon emissions by fostering technological progress and green innovation. Urban resilience further strengthens the contribution of the digital economy to reducing carbon discharges in the urban construction sector of China. This article presents empirical evidence demonstrating how the digital economy empowers the construction industry to curtail emissions.

Beyond diagnostic connectivity: Leveraging digital health technology for the real-time collection and provision of high-quality actionable data on infectious diseases in Uganda

Automated data transmission from diagnostic instrument networks to a central database at the Ministries of Health has the potential of providing real-time quality data not only on diagnostic instrument performance, but also continuous disease surveillance and patient care. We aimed at sharing how a locally developed novel diagnostic connectivity solution channels actionable data from diagnostic instruments to the national dashboards for disease control in Uganda between May 2022 and May 2023. The diagnostic connectivity solution was successfully configured on a selected network of multiplexing diagnostic instruments at 260 sites in Uganda, providing a layered access of data. Of these, 909,674 test results were automatically collected from 269 "GeneXpert" machines, 5597 test results from 28 "Truenat" and >12,000 were from 3 digital x-ray devices to different stakeholder levels to ensure optimal use of data for their intended purpose. The government and relevant stakeholders are empowered with usable and actionable data from the diagnostic instruments. The successful implementation of the diagnostic connectivity solution depended on some key operational strategies namely; sustained internet connectivity and short message services, stakeholder engagement, a strong in-country laboratory coordination network, human resource capacity building, establishing a network for the diagnostic instruments, and integration with existing health data collection tools. Poor bandwidth at some locations was a major hindrance for the successful implementation of the connectivity solution. Maintaining stakeholder engagement at the clinical level is key for sustaining diagnostic data connectivity. The locally developed diagnostic connectivity solution as a digital health technology offers the chance to collect high-quality data on a number of parameters for disease control, including error analysis, thereby strengthening the quality of data from the networked diagnostic sites to relevant stakeholders.

Authentic Leadership Behaviors and Thriving at Work: Empirical Evidence From The Information Technology Industry in Australia

Authentic leaders display an exceptional level of integrity and honesty, a high level of awareness and responsibility as well as a commitment to achieving their goals; as a result, they develop more trusting relationships with their employees, which could be translated into many positive outcomes, such as enhancing the ability to thrive at work. The present study aims to determine the role of authentic leadership´s (AL's) four dimensions (self-awareness, relational transparency, balanced processing, and internalized moral perspective) in fostering an environment that offers workers the opportunity to do well, including in terms of two related elements (vitality and learning). An online questionnaire was conducted to collect data from a sample of 402 participants from the information technology (IT) industry in Australia. The study used WarpPLS software to analyze the collected data by the structural equation model. According to the results, balanced processing of AL has a positive and significant effect on two aspects of thriving at work, namely vitality and learning, Moreover, the internalized moral perspective inherent in the aforementioned phenomenon affects learning. The current study is novel as it is among examples of pioneering research that employ the path model, and it uses multi-dimensional structures to examine authentic leadership and thriving at work in the workplace. The research also discusses theoretical contributions, managerial implications, and limitations along with future study directions.

Understanding Engagement With Forensic Smartphone Apps: The Service Design Engagement Model

Justice services have begun to integrate the use of mobile applications into treatment, support, and rehabilitative programs for forensic clients. One such application that been adopted to support forensic clients is "eRecovery": a smartphone application that provides clients recovering from a substance addiction with support for managing relapse. In this article, we report on evaluation findings from a trial of eRecovery in an Australian Community Justice Centre, and reflect on several issues relating to fostering and sustaining client engagement with similar applications within forensic and justice settings. We propose the Service Design Engagement Model to organize, visualize, and describe the stages and factors important to adoption, appropriation, and on-going routine use of the software by forensic clients. The model recognizes the role of contextual and environmental factors in supporting users through the early stages of engagement, and the importance of user agency in longer-term engagement with therapeutic apps.

Empirical evidence on digitization enabling the transition to a green economy in China

In the context of the new normal, enhancing digitalization to empower the transition to a green economy is a critical instrument to promote China's economic transition from virtual to real sectors. It is also a necessary approach to realize the high-quality economic development in China. Based on panel data of 282 prefecture-level and above cities in China from 2011 to 2020, the study employs panel regression, spatial metrics, and other methods to explore the impact of urban digitization on the transition to a green economy from the dimensions of direct and indirect transmission mechanism, as well as heterogeneous effects. The findings reveal that digitalization not only exerts a positive effect on the green transition but also generates significant spatial spillover effects. The influence of digitization level on green economic transition exhibits notable regional heterogeneity. Advancement in digitization can foster green economic transition by catalyzing green technological innovation. While digitalization contributes to the green transition by optimizing the structure of energy consumption, its mediating effect is relatively modest. Therefore, it is essential to fortify the supply of digital innovative technology and strengthen digitalization and green technology innovation to jointly facilitate the transition to a green economy. This necessitates the implementation of differentiated development paths for digitization-enabled green economic transition in various regions.

Blessing or curse? The role of digital technology innovation in carbon emission efficiency

Digital technology advancement provides a significant impetus to achieve China's "dual-carbon" goals, yet it also gives rise to a series of challenges. Therefore, studying the relationship between digital technology innovation and carbon emission efficiency is of paramount importance. This study theoretically analyzes and empirically tests the influence of digital technology innovation (DTI) on total factor carbon emission efficiency (TFCE) using panel data from 268 Chinese cities between 2006 and 2021. The results indicate that: (1) DTI exhibits a "U-shaped" pattern on urban TFCE, with a decrease followed by an increase. (2) Conventional technological innovation (TI) also displays a "U-shaped" relationship with TFCE, with the turning point occurring earlier than that of DTI. DTI surpasses TI in bringing about later-stage improvements in carbon emission efficiency. (3) Mechanism tests reveal that digital technology innovation indirectly affects TFCE through energy effects, technological effects, structural effects, and regulatory effects. (4) The impact of DTI on urban TFCE varies significantly due to differences in geographical location and resource endowments. (5) The development of urban polycentricity advances the turning point at which DTI enhances TFCE while amplifying both the initial "pro-carbon" effect and the subsequent "carbon reduction" effect of DTI. (6) DTI has a spatial spillover effect on urban TFCE. This study provides empirical evidence and policy recommendations for policymakers to advance the digitalization, greening, and decarbonization transformation of cities.

Catalysts of digital excellence: Unraveling the threads of connectivity, embedment, and visibility in enterprise social media for enhanced task and innovative performances

In an era characterized by rapid digital transformation, this research delves into the intricate dynamics of enterprise social media (ESM) ubiquitous connectivity, drawing on the influential framework of social cognitive theory (SCT), we unravel the complex relationships among compatibility, presenteeism, ESM-enabled embeddedness, and the visibility of digital interactions, shedding light on how these factors collectively shape task performance and innovative contributions in the contemporary hybrid work landscape. By incorporating SCT into our research model, we not only enhance the theoretical underpinning but also respond to the imperative of understanding how individual cognition and observational learning impact behaviors in digital work environments. Data is collected from 467 participants from China. Results indicated that ESM-enabled embeddedness mediates the connection between presenteeism and both digital-enabled task performance, digital-enabled innovative performance. Findings conformed that ESM-enabled embeddedness mediates the connection between compatibility and both digital-enabled task performance, digital-enabled innovative performance. ESM visibility strengthens the connection between ubiquitous connectivity (presenteeism, compatibility) and ESM-enabled embeddedness. In addition, results also indicated that ESM visibility moderates the mediation effect of ESM-enabled embeddedness between the dimensions of ESM ubiquitous connectivity (presenteeism) and both digital-enabled task performance, digital-enabled innovative performance. In contrast, ESM visibility did not moderates the mediation effect of ESM-enabled embeddedness between the dimensions of ESM ubiquitous connectivity (compatibility) and both digital-enabled task performance, digital-enabled innovative performance. This study not only contributes depth to ESM literature but also lays the groundwork for future research endeavors, encouraging exploration of diverse contexts and additional moderating factors to comprehensively grasp the intricate dynamics within modern digital workspaces.

Digital transformation and enterprise low-carbon innovation: A new perspective from innovation motivation

From the perspective of innovation motivation, low-carbon innovation is divided into substantive low-carbon innovation and strategic low-carbon innovation. On this basis, this study empirically investigates the impact and mechanism of digital transformation on enterprise low-carbon innovation using data from China's A-share listed enterprises from 2005 to 2019. The results show that digital transformation promotes the overall level of enterprise low-carbon innovation, substantial low-carbon innovation, and strategic low-carbon innovation, with a more significant impact on strategic low-carbon innovation. For enterprises with large-scale, belonging to high-monopoly industries and located in high-marketization regions, the promotion of digital transformation is more significant and facilitates strategic low-carbon innovation more than substantive low-carbon innovation. Based on the internal capability perspective, enhancing management capability, R&D capability, and environmental information disclosure capability are three important channels of digital transformation affecting low-carbon innovation.

Social media use for work during non-work hours and turnover intention: the mediating role of burnout and the moderating role of resilience

Introduction

This study uses survey data from 504 Chinese teachers to investigate the relationship between social media use for work during non-work hours (SMUNW) and turnover intention, focusing on the mediating role of burnout and the moderating role of resilience in this relationship.

Methods

In November 2023, online survey links were sent to 529 teachers from Shandong Province, China, asking them to report their perceptions of SMUNW, burnout, resilience, and turnover intention. A sample of 504 valid responses was obtained. The analysis was performed using SPSS 26.0 and Hayes' PROCESS MACRO for SPSS for testing the hypotheses.

Results

The results revealed that burnout acts as a mediator in the relationship between SMUNW and turnover intention. In addition, resilience moderated the relationship between SMUNW and burnout such that when resilience was higher, the relationship between SMUNW and burnout was alleviated. Moreover, resilience moderated the indirect relationship between SMUNW and turnover intention through burnout such that when resilience was higher, the indirect relationship was alleviated.

Discussion

The results of this study indicate that SMUNW is related to turnover intention through the mediating role of burnout. Furthermore, resilience moderates the influence of SMUNW on burnout and thus weakens the influence of SMUNW on turnover intention through burnout. This study expands our knowledge of the nuanced influence mechanisms of social media use in the context of increasing technostress among public employees. Practically, it suggests that managers should pay due attention to the impairments brought about by social media use, especially from the perspectives of preventing burnout and fostering resilience.

When does digital merger and acquisition create shareholder value? An empirical investigation in the Chinese context

In China, acquiring firms are increasingly focused on the immediate financial returns that digital mergers and acquisitions (DM&A) can help them achieve in the stock market, but there is little literature that examines which acquiring firms achieve greater returns. Based on signaling theory, this study conceptualizes DM&A announcements as signals released by the acquiring firms to the stock market and explores the factors influencing the Chinese stock market's reaction to such signals. This research empirically investigates potential influencing factors using a short-term event methodology together with regression analysis based on the data collected in China's Shanghai and Shenzhen stock markets during 2012-2021. The research finds that the Chinese stock market reacts more positively to DM&A announcements for acquiring firms with high executive shareholdings, high executive openness, strong digital innovation capabilities, and in regions with higher levels of investor protection. This study is the first attempt to explore the factors influencing the stock market's response to DM&A in the Chinese context.

How digital transformation enhances corporate innovation performance: The mediating roles of big data capabilities and organizational agility

Digital transformation has emerged as a key driver of high-quality enterprise development and an essential tool in forging an innovation-driven paradigm.Existing studies fail to delve into the specific mechanisms of their impact on firms' innovation performance, and views on their impact are divergent. Some studies suggest that digital transformation can enhance innovation performance, while others point out that it may have negative impacts, and cannot clearly answer how big data capabilities and organisational agility play a role in the digital transformation process. Therefore, based on dynamic capability theory and systems engineering theory, this study adopts the logical framework of "strategy-behaviour-performance" to systematically explore the process of digital transformation that enhances firms' innovation performance through the enhancement of big data capability and organisational agility. By empirically analysing the survey data of 476 manufacturing enterprises in China, the study reveals the chain-mediated effects of big data capability and organisational agility, and confirms the key roles of both in the transformation process. The findings suggest that digital transformation significantly improves firms' innovation performance, and that the dual mediating effects of big data capability and organisational agility are important links in its influencing mechanism. These findings not only provide empirical support for the theoretical model of digital transformation, but also provide practical guidance for enterprises to formulate strategies and optimise resource allocation in the digital era. We suggest that enterprises should strengthen the cultivation of big data capabilities and organisational agility while promoting digital transformation to better adapt to and lead market changes.

Online Medical Consultation Service-Oriented Recommendations: Systematic Review

BACKGROUND

Online health communities have given rise to a new e-service known as online medical consultations (OMCs), enabling remote interactions between physicians and patients. To address challenges, such as patient information overload and uneven distribution of physician visits, online health communities should develop OMC-oriented recommenders.

OBJECTIVE

We aimed to comprehensively investigate what paradigms lead to the success of OMC-oriented recommendations.

METHODS

A literature search was conducted through e-databases, including PubMed, ACM Digital Library, Springer, and ScienceDirect, from January 2011 to December 2023. This review included all papers directly and indirectly related to the topic of health care-related recommendations for online services.

RESULTS

The search identified 611 articles, of which 26 (4.3%) met the inclusion criteria. Despite the growing academic interest in OMC recommendations, there remains a lack of consensus among researchers on the definition of e-service-oriented recommenders. The discussion highlighted 3 key factors influencing recommender success: features, algorithms, and metrics. It advocated for moving beyond traditional e-commerce-oriented recommenders to establish an innovative theoretical framework for e-service-oriented recommenders and addresses critical technical issues regarding 2-sided personalized recommendations.

CONCLUSIONS

This review underscores the essence of e-services, particularly in knowledge- and labor-intensive domains such as OMCs, where patients seek interpretable recommendations due to their lack of domain knowledge and physicians must balance their energy levels to avoid overworking. Our study's findings shed light on the importance of customizing e-service-oriented personalized recommendations to meet the distinct expectations of 2-sided users considering their cognitive abilities, decision-making perspectives, and preferences. To achieve this, a paradigm shift is essential to develop unique attributes and explore distinct content tailored for both parties involved.

Sharing or Hiding? Exploring the Influence of Social Cognition and Emotion on Employee Knowledge Behaviors within Enterprise Social Media

As emerging knowledge management platforms, enterprise social media (ESM) provide an important way for employees to engage in knowledge sharing and information communication within their organization. However, the question of how to encourage employees to engage in continuous knowledge sharing rather than knowledge hiding on ESM has not received sufficient attention from scholars. In contrast to previous studies that focused on a single theory perspective and a single knowledge behavior, in this study, we took a user cognition and emotion perspective and constructed a mechanism model for the impact of knowledge sharing and knowledge hiding among employees on ESM based on social cognition theory and emotion as social information theory. A total of 240 valid questionnaires were collected and used to empirically test the model. The results indicate that reciprocity and outcome expectancy have a significant positive effect on employees' knowledge-sharing behavior, while reciprocity and trust have a significant negative effect on employees' knowledge-hiding behavior. Positive emotions play a positive (enhancing) moderating role on the path between outcome expectancy and knowledge-sharing behavior, while negative emotions play a negative (weakening) moderating role on the path between reciprocity and knowledge-hiding behavior, as well as between trust and knowledge-hiding behavior. By incorporating employee emotions into the framework of social cognition's impact on employee knowledge behavior, this study enriches theories related to enterprise social media, knowledge management, and user behaviors. Our research findings have practical implications for guiding employees to engage in positive knowledge sharing and reducing knowledge hiding on enterprise social media.

Socio-ecological predictors of dengue in high incidence area of Delhi, India

Despite the amplified vector-control measures, sporadic-epidemic outbreaks of dengue incidence occurred in Delhi, intermittently. This study aimed to identify the major individual, household, and community level predictors of dengue cases in the hot-spots of Delhi. Primary survey data was collected from the selected sample of 347 households, at the South- West district of Delhi. This survey has interviewed the head of the household to collect the information of dengue incidences within last one year and household information related to socio-economic, demographic, environmental factors, such as housing pattern, density, water storage containers, drainage and garbage collection site and method, mosquito protection measures and awareness. Among 347 households, 54 households had reported dengue cases, and 69 individuals had reported dengue cases in last one year. Garbage and water collection site and methods, drainage and household type, household monthly income, indoor bamboo plants, construction site (within 500 m), presence of tertiary care hospital, were the significant predictors of dengue incidences in Delhi. In conclusion, strategic control measures and intense social interventions such as household and community awareness, promotion of healthy practices should be promoted to control the dengue incidences.

Impact of stakeholder pressure on digital process innovation: An empirical analysis

Digital technologies can bring about fundamental changes in corporate processes, which may result in a shift from process innovation to digital process innovation. However, owing to resource constraints and various stakeholders, digital process implementation is extremely challenging for firms. Based on stakeholder theory, this study explores whether and how stakeholder pressure for digitalization can facilitate corporate digital process innovation and unravels the mediating effect of routine reconfiguration and the moderating effect of strategic flexibility. The findings from a survey of 351 firms prove that stakeholder pressure for digitalization can facilitate corporate digital process innovation via routine reconfiguration. Moreover, this study finds that increased strategic flexibility can strengthen the positive mediating effect of routine reconfiguration. The findings contribute to the deep understanding of digital process innovation and offer a boundary condition for the effectiveness of stakeholder pressure.

Probing the Role of Digital Payment Solutions in Gambling Behavior: Preliminary Results From an Exploratory Focus Group Session With Problem Gamblers

BACKGROUND

Technology has significantly reshaped the landscape and accessibility of gambling, creating uncharted territory for researchers and policy makers involved in the responsible gambling (RG) agenda. Digital payment solutions (DPS) are the latest addition of technology-based services in gambling and are now prominently used for deposit and win withdrawal. The seamless collaboration between online gambling operators and DPS, however, has raised concerns regarding the potential role of DPS platforms in facilitating harmful behavior.

OBJECTIVE

Using a focus group session with problem gamblers, this study describes a preliminary investigation of the role of DPS in the online gambling context and its influence on players' gambling habits, financial behavior, choices of gambling environment, and the overall outcome of gambling subjective experiences.

METHODS

A total of 6 problem gamblers participated in a one-and-half-hour focus group session to discuss how DPSs are integrated into their everyday gambling habits, what motivates them to use DPS, and what shifts they observe in their gambling behavior. Thematic analysis was used to analyze the empirical evidence with a mix of inductive and deductive research approaches as a knowledge claim strategy.

RESULTS

Our initial findings revealed that the influence of DPSs in online gambling is multifaced where, on the one hand, their ability to integrate with players' existing habits seamlessly underscores the facilitating role they play in potentially maximizing harm. On the other hand, we find preliminary evidence that DPSs can have a direct influence on gambling outcomes in both subtle and pervasive ways-nudging, institutionalizing, constraining, or triggering players' gambling activities. This study also highlights the increasingly interdisciplinary nature of online gambling, and it proposes a preliminary conceptual framework to illustrate the sociotechnical interplay between DPS and gambling habits that ultimately capture the outcome of gambling's subjective experience.

CONCLUSIONS

Disguised as a passive payment enabler, the role of DPS has so far received scant attention; however, this exploratory qualitative study demonstrates that given the technological advantage and access to customer financial data, DPS can become a potent platform to enable and at times trigger harmful gambling. In addition, DPS's bird's-eye view of cross-operator gambling behavior can open up an opportunity for researchers and policy makers to explore harm reduction measures that can be implemented at the digital payment level for gambling customers. Finally, more interdisciplinary studies are needed to formulate the sociotechnical nature of online gambling and holistic harm minimization strategy.

Role of social media to improve job performance with mediating role of transactive memory capability and employee creativity

The increased usage of social media in organizational settings has raised questions about its effect on job performance. This study explains the interplay between social media usage, transactive memory capability, employee creativity, and job performance within the Chinese organizational context. The rationale for this study stems from the need to understand how social media usage can enhance job performance through cognitive and creative processes within teams. On the basis of earlier literature, the survey questionnaire was designed to collect data and the survey included validated scales to measure these constructs. The data is collected from 816 employees in China via online resources like social media and emails and then Structural Equation Modeling is used for empirical analysis through AMOS software. The findings show the positive impact of social media on job performance while transactive memory capability and employee creativity mediates this relationship. These findings contribute to a better understanding of how social media can be leveraged to improve job performance. Practical implications highlight the importance of fostering transactive memory capability through social media platforms, facilitating employee creativity, and ultimately, bolstering job performance. Additionally, this study underscores the need for organizations to strategically harness the potential of social media as a catalyst for innovation and knowledge sharing, thus optimizing workforce performance in the digital era.

Decentralisation of the Health System Derailed by Organisational Inertia in Machinga, Malawi

BACKGROUND

Managing the transition of a health system (HS) from a centralised to a decentralised model has been touted as a panacea to the complex challenges in developing countries like Malawi. However, recent studies have demonstrated that decentralisation of the HS has had mixed effects in service provision with more dominant negative outcomes than positive results. The aim of this study was to develop a substantive grounded theory (GT) that elaborates on how activities of central decision-makers and local healthcare mangers shape the process of shifting the HS to a decentralised model in Machinga, Malawi.

METHODS

The study was qualitative in nature and employed the Straussian version of GT. Some participants were interviewed twice, and a total of 36 semi-structured interviews were conducted with 25 purposively selected participants using an interview guide. The interviews were conducted at the headquarters of the Ministry of Health (MoH) and other ministries and agencies, and in Machinga District. Data were analysed using open, axial, and selective coding processes of the GT methodology; and the conditional matrix and paradigm model were used as data analysis tools.

RESULTS

The findings of this study revealed seven different activities, forming two opposing and interactional sub-processes of enabling and impeding patterns that derailed the decentralisation drive. The study generated a GT labelled "decentralisation of the HS derailed by organisational inertia," which elaborates that decentralisation of the HS produced mixed results with more predominant negative outcomes than positive effects due to resistance at the upper organisational echelons and members of the District Health Management Team (DHMT).

CONCLUSION

This article concludes that organisational inertia at the personal and strategic levels of leadership entrusted with decentralising the HS in Malawi, contributed immensely to the derailment of shifting the HS from the centralised to the decentralised model of health service provision.

Research on the evolution mechanism of intelligent manufacturing transformation of Chinese pharmaceutical manufacturing enterprises based on system dynamics

Under the impetus of the new industrial revolution, how to realize intelligent manufacturing transformation of traditional pharmaceutical manufacturing enterprises has realistic urgency. The study starts from the perspective of complex adaptive system, constructs a system dynamics model of the evolution mechanism of intelligent manufacturing transformation of pharmaceutical manufacturing enterprises based on technological adaptation and evolutionary adaptation, and analyzes it by simulation using Vensim PLE software. The results of the study show that pharmaceutical manufacturing enterprises utilize technological affordances to provide support to realize network product-based manufacturing capability and smart product-based manufacturing capability through technological innovation capability and institutional optimization capability; the technological affordances environment promotes the realization of intelligent manufacturing transformation of pharmaceutical manufacturing enterprises to present a stage transformation law. The study enriches and extends the research paradigm of intelligent manufacturing transformation, and provides a reference for pharmaceutical manufacturing enterprises to realize intelligent manufacturing transformation.

How does environmental regulations affect digital green innovation of high-pollution enterprises? Empirical evidence from China

Digital green innovation (DGI) is crucial for high-pollution enterprises to improve green performance. However, there is a paradox regarding the impact of environmental regulations on DGI, primarily due to the varied effects of diverse regulatory tools. To resolve this paradox, based on Neoclassical Economics and the Porter Hypothesis, we empirically examine the influence of heterogeneous environmental regulations on DGI using a sample of high-pollution enterprises in China. The conclusions indicate that environmental protection tax has a pushing-forward effect on DGI, while environmental protection subsidy has a crowding-out effect. Moreover, enterprises' resource base and technological innovation capability positively moderate the impact of environmental protection tax. External pressure, internal incentives, pandering to governments, and managerial opportunism have mediating effects. Our research offers a new perspective to resolve the paradox of the effect of environmental regulations on DGI, explores potential mechanism as well as boundary condition, and proposes a new way of measuring DGI of enterprises with patents. Accordingly, we offer valuable policy recommendations about the formulation of environmental regulations, the facilitation of DGI, and the advancement of China's ecological civilization.

Indicators of technostress, their association with burnout and the moderating role of support offers among nurses in German hospitals: a cross-sectional study

OBJECTIVES

To examine the level of indicators of technostress among nurses with and without a leadership position, the relationship between indicators of technostress and burnout and the moderating role of support offered by employers. The availability of support offers and further needs of nurses were also explored.

DESIGN

Cross-sectional online survey.

SETTING

Acute care hospitals in Germany.

PARTICIPANTS

303 nurses (73.3% female) who have worked at the hospital for at least 1 year and a minimum of 10 hours per week.

PRIMARY AND SECONDARY OUTCOME MEASURES

Indicators of technostress (complexity, overload, usefulness, lack of technical support and unreliability) served as predictors in multiple linear regression analyses to examine their association with the primary outcome burnout. Support of employers was included as a moderator variable. Validated subscales from the Digital Stressors Scale and Copenhagen Burnout Inventory as well as open-ended questions were applied.

RESULTS

There were no differences in the level of indicators of technostress found between nurses with and without a leadership position. Techno-overload (β=0.259, p=0.004) and techno-complexity (β=0.161, p=0.043) were significantly associated with burnout. Support by the employer moderated the relationship between lack of technical support and burnout significantly (R² change=0.026, F(1,292)=7.41, p=0.007). Support offers such as training, IT service and contact persons on the ward helped nurses to be more confident in the use of information and communication technologies. However, they expressed further needs with regard to these and new offers.

CONCLUSIONS

There was an association between two indicators of technostress and burnout. Therefore, particular attention should be paid to supporting nurses in terms of techno-overload and techno-complexity. Furthermore, there is still a need for customised support and further offers from employers in the use of digital technologies.

Functional diversity in human song

Functional diversity-i.e., the diversity of morphophysiological characteristics of species in a biological community-revolutionized ecology in recent decades, shifting the focus of the field from species to ecosystems. While its ecological applications are known, its adaptability to other disciplines, specifically music, is explored here. We retrieved fourteen characteristics of 12,944 songs by the top 100 artists of the 2010s decade on four streaming platforms. Then, we calculated the three main components of functional diversity-richness, evenness, and divergence-to each artist using probabilistic hypervolumes. Furthermore, we investigated to what extent functional diversity and the traits of an artist, its albums and songs has an effect on their popularity across streaming platforms such as Spotify. High functional richness, where an artist's songs differ greatly sonically, correlated with increased listens of up to 244,300,000. This would lead to estimated profit earnings exceeding $1,000,000 per richness gain. Danceable, highly-energetic, melodic, pop, and, notably, melancholic songs, albums, and artists are more listened to than their counterparts in streaming services. We captured how patterns in human song might reflects the social state of human societies in recent years and demonstrate the potential of applying functional diversity concepts and tools across scientific and economic domains, extending its relevance beyond ecology. By demonstrating applications of state-of-the-art functional diversity metrics using music as a case study, we intent to communicate the often-complex concepts of functional diversity using the familiar realm of music, which is an intrinsic trait of human cultures across the globe.

Evaluating the drivers of B2B performance: An empirical analysis based on Alibaba

The rapid development of B2B has brought about fierce competition among suppliers, and how to gain customer attention and improve performance has become a common concern in academia and industry. This study examined the drivers and mechanisms of B2B performance from an enterprise capability perspective. We collected transaction and enterprise data from 325 suppliers on Alibaba 1688 platform and constructed a structural equation model (SEM). Results showed that supplier service capability, logistics capability, and production capacity all positively impacted B2B performance through the mediating role of customer attention. In addition, we found that service and logistics capabilities are more critical for attracting customer attention for Original Equipment Manufacturer (OEM) suppliers than for non-OEM suppliers. The findings contribute to understanding B2B commerce and provide constructive directions for B2B suppliers to improve their performance.

Self-perceptions of aging, physical activity, and depressive symptoms in older community residents with varied neighborhood walkability in Taiwan

BACKGROUND

Prior research has identified the mediating effect of physical activity in the relationship between self-perceptions of aging and physical health. However, this impact on mental health is unknown, and the influence of environmental contexts proposed by ecological models in this regard remains largely unexplored. Therefore, this study aimed to investigate the role of physical activity in the relationship between self-perceptions of aging and depressive symptoms in older adults, and compare the impact across four levels of neighborhood walkability.

METHODS

A sample of 1,055 community-dwelling older adults aged 65 or above was obtained through random-digit-dialing computer-assisted telephone interviewing. The individual's neighborhood walkability was calculated using Walk Score®, and categorized into four levels: car-dependent, somewhat walkable, very walkable, and walker's paradise. Partial least squares structural equation modelling was employed.

RESULTS

We found that more positive self-perceptions of aging were associated with fewer depressive symptoms and a mediation effect of physical activity in this relationship. Among the four levels of neighborhood walkability, the mediation effect of physical activity was only statistically significant in the lowest level (car-dependent). The findings supported our hypotheses regarding the mediating effect of self-perceptions of aging on depressive symptoms via physical activity. Neighborhood walkability might potentially influence the mediating role of physical activity.

CONCLUSIONS

This study emphasizes key areas on intervention programs and policy formulation to promote mental health in older adults.

Gender effects in crowdfunded business loan campaigns

Crowdfunding is a growing source of finance for entrepreneurs. In this paper, we investigate the existence of a gender effect in the time needed to obtain a business loan through crowdfunding. Using data from three Dutch crowdfunding platforms, survival analysis of the time to completion for 934 business loan campaigns shows that female entrepreneurs have a 20% shorter campaign completion time compared to male entrepreneurs, whereas couples do not differ from males. This effect persists across the different platforms. Subsequent analysis shows that female entrepreneurs do not have the disadvantage they face in traditional lending channels when requesting funds through crowdfunding, and that herding behavior by investors benefits female entrepreneurs most.

Breaking down barriers: rationalisations and motivation to stop among Chinese male smokers under cigarette dependence

BACKGROUND

Smoking rationalisation beliefs are a huge barrier to quitting smoking. What types of rationalisations should be emphasised in smoking cessation interventions? Although past literature has confirmed the negative relationship between those beliefs and motivation to stop smoking, little is known regarding the importance and performance of those beliefs on motivation with varying cigarette dependence. The study aimed to ascertain rationalisations that are highly important for motivation yet perform poorly in different cigarette dependence groups.

METHODS

The cross-sectional study was conducted from November 19 to December 9, 2023 in Guiyang City, China. Adult male current smokers were enrolled. Partial least squares structural equation modelling was used to test the hypothesis. The multi-group analysis was used to determine the moderating effect of cigarette dependence, and the importance-performance map analysis was utilised to assess the importance and performance of rationalisations.

RESULTS

A total of 616 adult male current smokers were analysed, and they were divided into the low cigarette dependence group (n = 297) and the high cigarette dependence group (n = 319). Except for risk generalisation beliefs, smoking functional beliefs (H1: -β = 0.131, P < 0.01), social acceptability beliefs (H3: β = -0.258, P < 0.001), safe smoking beliefs (H4: β = -0.078, P < 0.05), self-exempting beliefs (H5: β = -0.244, P < 0.001), and quitting is harmful beliefs (H6: β = -0.148, P < 0.01) all had a significant positive influence on motivation. Cigarette dependence moderated the correlation between rationalisations and motivation. In the high-dependence group, the social acceptability beliefs and smoking functional beliefs were located in the "Concentrate Here" area. In the low-dependence group, the social acceptability beliefs were also situated in there.

CONCLUSIONS

Social acceptability beliefs and smoking functional beliefs showed great potential and value for improvement among high-dependence smokers, while only social acceptability beliefs had great potential and value for improvement among low-dependence smokers. Addressing these beliefs will be helpful for smoking cessation. The multi-group analysis and the importance-performance map analysis technique have practical implications and can be expanded to other domains of health education and intervention practice.

Dynamic risk prediction of survival in liver cirrhosis: A comparison of landmarking approaches

Electronic health records (EHR) data provides the researcher and physician with the opportunity to improve risk prediction by employing newer, more sophisticated modeling techniques. Rather than treating the impact of predictor variables on health trajectories as static, we explore the use of time-dependent variables in dynamically modeling time-to-event data through the use of landmarking (LM) data sets. We compare several different dynamic models presented in the literature that utilize LM data sets as the basis of their approach. These techniques include using pseudo-means, pseudo-survival probabilities, and the traditional Cox model. The models are primarily compared with their static counterparts using appropriate measures of model discrimination and calibration based on what summary measure is employed for the response variable.

How epidemic information and policy information impact anti-infection behaviors: a cross-cultural study under social influence framing

Three preregistered experiments examined to what extent information about an epidemic situation provided by experts and information about anti-infection policies promoted by governments/media influenced anti-infection behaviors. The above effects were examined among populations from different countries (in Experiments 2 and 3) and across self-construals (in Experiment 3). In three experiments, participants (N =706) were presented with a scenario where experts provided (or did not provide) information about an epidemic situation and governments/media promoted (or did not promote) information about anti-infection policies. After that, participants indicated their willingness to adopt anti-infection behaviors. Results across three experiments showed that both types of information independently increased participants' anti-infection behaviors. In Experiments 2 and 3, we further found that the epidemic information had a larger impact on inducing anti-infection behaviors than the policy information, which was robust and consistent across countries and self-construals. Findings were discussed under the framework of social influence and in terms of practical implications for pandemic situations like the COVID-19.

Safety-Seeking Behaviors and Anxiety Maintenance in People With Aphasia: A Viewpoint

PURPOSE

People with aphasia (PWA) often experience higher levels of anxiety and social isolation than people without aphasia. Although the presence of anxiety is appreciated in PWA, literature examining the etiology and persistent nature of anxiety in PWA is underdeveloped. Safety-seeking behaviors, or maladaptive acts used by individuals to decrease anxiety from a feared outcome, have been reported as key facilitators of long-term anxiety toward feared situations across a variety of clinical populations. The purpose of this viewpoint is to explore the concept of safety-seeking behaviors and discuss their potential relevance to the maintenance of anxiety in PWA. We further discuss the distinction between maladaptive (i.e., safety seeking) and adaptive (i.e., coping) behaviors and how this knowledge may improve the quality of clinical services for PWA.

CONCLUSIONS

The present review advocates for further exploration of the safety-seeking behaviors that are used by PWA. Until critical attention is given to this subject, clinicians may remain ill-equipped to identify and depict whether a self-management strategy is facilitative or inhibitive to PWA's communicative participation goals. Critically, a behavior that may be "maladaptive" for one individual may be "adaptive" for another. Future research should seek to identify common behavioral and cognitive strategies that PWA implement to reduce acute perceptions of anxiety. This knowledge may help facilitate holistic aphasia rehabilitation by allowing clinicians to foster conversations around behaviors that inhibit or promote successful communicative participation.