Research Model Research Articles

To Sustainably Ride or Not to Ride: Examining the Green Consumption Intention of Ride-Hailing Services in the Sharing Economy by University Students

An increase in ride-hailing services in the sharing economy can help to reduce the number of vehicles on the road, which will lead to a decrease in air pollution and noise pollution, an improvement in environmental conditions, a decrease in travel costs, and an increase in social benefits to travelers. Hence, there is a great need to examine the consumer’s intention toward usage of ride-hailing services in the sharing economy. The current study aims to examine the green consumption intention of eco-friendly services as an outcome of environmental responsibility and environmental knowledge. It also attempts to examine the serial mediation of green concern, value co-creation, and mediated moderation of social support as an explanatory mechanism of green consumption intention of eco-friendly services. The research design was cross-section and deductive. The respondents of the study were registered university students in Islamabad who were active consumers of major ride-hailing services in Pakistan, i.e., Uber, Careem, Uplift, InDriver, B4U Cabes, and SUVL. A total of 402 responses were gathered using purposive sampling. Partial Least Squares Structural Equation Modeling (PLS-SEM) in Smart PLS is used to evaluate the reliability of measurement instruments and the validity of the research model. The current study results showed that environmental responsibility and knowledge positively and significantly affect motivation to engage in green consumption. Furthermore, environmental concern and value co-creation partially mediate the proposed relationship. In addition, social support also moderates the association between green concern and value co-creation such that it strengthens the connection. The current research findings are an addition to the existing literature and have managerial applications with limitations preceded by future research directions.

Unpacking leader critical thinking in employee voice quality and silence frequency

AbstractPrevious research has predominantly examined either voice quantity or quality. We know little about the potential tradeoff between voice quantity and quality and the role of leaders in this tradeoff. This study focused on the dual aspects of voice, examining how and when the same leader attribute facilitates (inhibits) one aspect of voice, but does not facilitate (inhibit) or even hamper (facilitate) the other aspect. Specifically, we proposed that leader critical thinking stimulates the formation of employees' implicit voice theory of the need for solid data or solutions (IVT‐SDS) before one speaks up. This belief boosts the quality of employee voice especially when voice efficacy is high, but increases the frequency of employee silence especially when voice efficacy is low. In Study 1a, we experimentally tested the relationship between leader critical thinking and employees' IVT‐SDS. In Study 1b, we experimentally examined the interactive effect of employees' IVT‐SDS and their voice efficacy on both their voice quality and silence frequency. In Study 2, a multilevel, multi‐wave and multi‐source field study, we tested the entire research model. The results supported our hypotheses. We extend the research on leadership and voice by revealing a potential tradeoff between voice quality and quantity.

Context matters: The importance of investigating random effects in hierarchical models for early childhood education researchers

This paper highlights the importance of examining individual, classroom, and school-level variables simultaneously in early childhood education research. While it is well known that Hierarchical Linear Modeling (HLM) in school-based studies can be used to account for the clustering of students within classrooms or schools, less known is that HLM can use random effects to investigate how higher-level factors (e.g., effects that vary by school) moderate associations between lower-level factors. This possible moderation can be detected even if higher-level data are not collected. Despite this important use of HLM, a clear resource explaining how to test this type of effect is not available for early childhood researchers. This paper demonstrates this use of HLM by presenting three analytic examples using empirical early childhood education data. First, we review school-level effects literature and HLM concepts to provide the rationale for testing cross-level moderation effects in education research; next we do a short review of literature on the variables that will be used in our three examples (viz., teacher beliefs and student socioemotional behavior); next we describe the dataset that will be analyzed; and finally we guide the reader step-by-step through analyses that show the presence and absence of fixed effects of teacher beliefs on student social outcomes and the erroneous conclusions that can occur if school-level moderation (i.e., random effects) tests are excluded from analyses. This paper provides evidence for the importance of testing for how teachers and students impact each other as a function of school differences, shows how this can be accomplished, and highlights the need to examine random effects of clustering in educational models to ensure the full context is accounted for when predicting student outcomes.

The impact of ChatGPT’s competencies on users’ intention to use

ABSTRACT Driven by ChatGPT’s popularity, generative conversational artificial intelligence (GCAI) has captured global interest. Despite its widespread adoption, the competencies of GCAI and their influence on users’ intention to use it remain underexplored. This study examines the effect of GCAI competencies on users’ intention to use GCAI. Using a mixed-methods approach, we analyze social media comments and identify four key GCAI competencies. Based on media naturalness theory, trust literature, and the stimulus-organism-response model, we propose and test a research model via a survey. Our results show that accuracy of response, self-learning, and natural language interaction enhance users’ intention to use GCAI and trust in it, while human-like empathy influences trust but not intention. Trust fully mediates the relationship between human-like empathy and intention, and partially mediates the relationship between the other three competencies and intention. This study fills a gap in understanding GCAI’s appeal and offers guidance for developers and marketers.

Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes Through Service-Dominant Logic and Artificial Intelligence Device Use Acceptance Perspectives

Financial institutions are currently undergoing a significant shift from traditional robo-advisors to more advanced generative artificial intelligence (GenAI) technologies. This transformation has motivated us to investigate the factors influencing consumer responses to GenAI-driven financial advice. Despite extensive research on the adoption of robo-advisors, there is a gap in our understanding of the specific contributors to, and differences in, consumer attitudes and reactions to GenAI-based financial guidance. This study aims to address this gap by analyzing the impact of personalized investment suggestions, human-like empathy, and the continuous improvement of GenAI-provided financial advice on its authenticity as perceived by consumers, their utilitarian attitude toward the use of GenAI for financial advice, and their reactions to GenAI-generated financial suggestions. A comprehensive research model was developed based on service-dominant logic (SDL) and Artificial Intelligence Device Use Acceptance (AIDUA) frameworks. The model was subsequently employed in a structural equation modeling (SEM) analysis of survey data from 822 mobile banking users. The findings indicate that personalized investment suggestions, human-like empathy, and the continuous improvement of GenAI’s recommendations positively influence consumers’ perception of its authenticity. Moreover, we discovered a positive correlation between utilitarian attitudes and perceived authenticity, which ultimately influences consumers’ responses to GenAI’s financial advisory solutions. This is manifested as either a willingness to engage or resistance to communication. This study contributes to the research on GenAI-powered financial services and underscores the significance of integrating GenAI financial guidance into the routine operations of financial institutions. Our work builds upon previous research on robo-advisors, offering practical insights for financial institutions seeking to leverage GenAI-driven technologies to enhance their services and customer experiences.

Testing the effects of personalized recommendation service, filter bubble and big data attitude on continued use of TikTok

PurposeThis study attempts to identify the determinant factors for Chinese users’ intention of continuous use of TikTok.Design/methodology/approachDrawing on the theoretical background and previous literature, this study proposes the research model followed by research hypotheses. For the purpose of empirical analysis of this study, we conducted a questionnaire survey on current Chinese TikTok platform users. Factor analysis was conducted to verify the reliability and validity of the measurement variables; Confirmatory factor analysis was conducted to ensure that the structural dimensions of the measurement are effective; the analysis results of the structural equation model for hypothesis test.FindingsThe result of the study indicates that the core service traits (entertainment, informativeness and convenience of use) of TikTok all have a positive effect on user engagement and perceived usefulness. In addition, the study found that both personalized recommendation services and filter bubble, which are features of TikTok's service recommendation system, have a positive effect on user engagement and perceived usefulness of TikTok. In addition, it was found that both user engagement and perceived usefulness have a significant positive effect on continuous use intention. Finally, users’ attitude toward big data indicating privacy concern only had a positive moderating effect on the personalized recommendation service but not on filter bubble.Originality/valueAs consumers’ demand for services tailored to their needs and preferences fast increased, it calls for growing concern over the safety of personal data being used by the platforms. Although this paradox over increased user convenience versus privacy protection issue has been persistently recognized, no previous research empirically addressed this issue in the context of social media platforms.

Exploring Digital Mobility in China’s Tourism Metaverse

ABSTRACT This study aims to explore digital mobility in the tourism metaverse through dual factors of information entropy and media functionality moderated by structural differentiation, including China’s institutional governance of information systems. The research model was constructed through influential factors to determine the digital mobility of metaverse systems using quantitative data analysis methods. Results showed that information entropy negatively influenced digital mobility. However, media functionality could be harnessed to reduce information entropy and thus enhance digital mobility in China’s tourism metaverse systems. Structural differentiation had significant moderation and mediation effects in the research model that influenced the digital mobility of Chinese tourists.

Animal Models in COVID-19 Research: Insights and Outcomes

Animal models have been critical in understanding the pathogenesis, transmission, and therapeutic interventions for COVID-19, caused by SARS-CoV-2. The primary challenges include species-specific differences in viral receptor expression, particularly the ACE2 receptor, and immune system responses, which can affect how closely these models mimic human COVID-19 pathology. Additionally, ethical concerns around the use of animals, especially non-human primates, and logistical issues such as high costs, housing requirements, and limited availability of certain models, further complicate research efforts. Transgenic mice expressing human ACE2 (hACE2) are widely used because of their ease of handling and cost-effectiveness. Other animal models include non-human primates, hamsters, cats, and ferrets, which were used to study viral transmission and host-pathogen interactions. The rapid dynamics of the SARSCoV-2 evolution is one of the challenges and the complementary use of multiple models provides a more comprehensive understanding of the disease. Nonetheless, these models have been essential for rapid advancements in COVID19 vaccine and therapeutic development, offering insights that continue to guide public health strategies. The review discusses the various animal models used in SARS-CoV-2 research, the outcomes, and the challenges and questions to be addressed Keywords: Animal models, SARS-CoV-2, COVID-19

A pilot study examining periodontally healthy middle-aged humans and monkeys display different levels of alveolar bone resorption, gingival inflammatory infiltrate, and salivary microbiota profile.

Monkeys are an appropriate model for periodontal research owing to their similar dental anatomy and physiology unlike humans. Extensive literature exists on pathological periodontitis in monkeys and humans, although concerns regarding whether healthy middle-aged monkeys and humans display the same periodontal and oral microbial status remains unclear. The current study aimed to compare alveolar bone resorption, gingival inflammatory infiltrate, and salivary microbiota profile in periodontally healthy middle-aged humans and monkeys. CBCT examination and histological analysis were performed to compare the periodontal status in middle-aged healthy humans and monkeys. Oral saliva16S rRNA sequencing was performed to analyze the oral microbial profile. The alveolar resorption was compared between humans and monkeys, to determine the periodontal health. The percentage attachment of attachment loss was more around the posteriors teeth in humans when compared to monkeys (p<0.05). The degree of gingival inflammation was analyzed in both the groups, the expression of CD 34,45was higher in humans. 16S rRNA analysis demonstrated less diversity of salivary microorganisms in humans than in monkeys. The relative abundance of Aggregatibacter, Haemophilus, Gemella, and Porphyromonas at the genus level was significantly less in humans than in monkeys (p(<0.05). The periodontally healthy middle-aged humans and monkeys display different alveolar bone resorption and gingival inflammatory infiltrate levels. Furthermore, the salivary microbiota profile showed distinctly different oral microbiomes in these two primates. Our results suggest that the difference in alveolar bone status and gingival inflammatory infiltrate in healthy humans and monkeys might be associated with the diversity of the oral microbiome.

From microbes to mind: germ-free models in neuropsychiatric research.

The gut-microbiota-brain axis refers to the bidirectional communication system between the gut, its microbial community, and the brain. This interaction involves a complex interplay of neural pathways, chemical transmitters, and immunological mechanisms. Germ-free animal models have been extensively employed to investigate gut-microbiota-brain interactions, significantly contributing to our current understanding of the role of intestinal microbes in brain function. However, despite the many benefits, this absence of microbiota is not futile. Germ-free animals present physiological and neurodevelopmental alterations that can persist even after reconstitution with normal microbiota. Therefore, the main goal of this minireview is to discuss how some of the inherent limitations of this model can interfere with the conclusion obtained when using these animals to study the complex nature of neuropsychiatric disorders. Furthermore, we examine the inclusion and use of antibiotic-based treatments as an alternative in the research of gut-brain interactions.

Active Models in Speech Perception: A Critical Review in Phonetics

This critical review examines four prominent active models of speech perception: quantal theory, motor theory, hyper-hypo-articulation theory, and exemplar theory. Each of these models offers distinctive insights into how listeners perceive, interpret, and categorize speech sounds. Quantal theory explores the non-linear relationship between articulation and acoustic output, emphasizing stable and unstable regions in speech production. Motor theory posits that speech perception is grounded in articulatory gestures, suggesting a direct link between production and perception. The hyper-hypo-articulation theory focuses on the speaker’s adaptive articulation, which ranges from hyper- to hypo-articulation depending on the listener's needs and the communicative context. Exemplar theory, rooted in cognitive psychology, highlights the role of memory and experience, with individual speech sounds compared to stored exemplars in memory to aid perception. Despite their contributions, none of these models offers a comprehensive solution to all speech perception challenges. Each theory is suited to specific contexts, speech features, or tasks, making it crucial for researchers to understand their limitations. Furthermore, the review underscores the importance of selecting the appropriate model for particular research or practical applications, given the variability in their functionality. Finally, it calls for future research to delve deeper into passive models of speech perception and suggests that comparative studies between active and passive models could yield valuable insights.

Enhancing Employees' Social Responsibility: The Roles of Continuous Improvement, Organization Identification, and Perceived Organization Support

Social responsibility is imperative for its important function in the growth of societies and organizations. However, the research on corporate social responsibility (OSR) has predominantly focused on the actions of organizations. Not much has been discussed regarding the employee's behaviours in promoting the development of social responsibility within organizations. CI is known for its significant role in the organization's various outcomes, Although a conceptualization and some empirical support have been provided for its relationship with the behaviour of employees, However, the effect of CI on employee socially responsible behaviours has not yet been investigated. In this article, following OC and OI theories, we improve the research model which can describe mechanisms underpinning through which CI, OI and POS support actions for employees' social responsibility. Data was collected from members of service professionals in Saudi Arabia and examined using Structural Equation Modeling- Partial Least Squares. The findings indicated that CI actions and activities develop the skills that motivate employees to support social responsibility inside and outside the organization. Moreover, our research paper explained the mechanism under which CI activities reshape employees' socially responsible manners. The current study is among the first to look at how to modify the socially responsible behaviour of employees across organizations, which can be a starting point for transforming those employees into a sustainable society.

The Paris low-level jet during PANAME 2022 and its impact on the summertime urban heat island

Abstract. The low-level jet (LLJ) and the urban heat island (UHI) are common nocturnal phenomena. While the UHI has been studied extensively, interactions of the LLJ and the urban atmosphere in general (and the UHI in particular) have received less attention. In the framework of the PANAME (PAris region urbaN Atmospheric observations and models for Multidisciplinary rEsearch) initiative in the Paris region, continuous profiles of horizontal wind speed and vertical velocity were recorded with two Doppler wind lidars (DWLs) – for the first time allowing for a detailed investigation of the summertime LLJ characteristics in the region. Jets are detected for 70 % of the examined nights, often simultaneously at an urban and a suburban site, highlighting the LLJ regional spatial extent. Emerging at around sunset, the mean LLJ duration is ∼ 10 h, the mean wind speed is 9 m s−1, and the average core height is 400 m above the city. The temporal evolution of many events shows signatures that indicate that the inertial oscillation mechanism plays a role in the jet development: a clockwise veering of the wind direction and a rapid acceleration followed by a slower deceleration. The horizontal wind shear below the LLJ core induces variance in the vertical velocity (σw2) above the urban canopy layer. It is shown that σw2 is a powerful predictor for regional contrast in air temperature, as the UHI intensity decreases exponentially with increasing σw2 and strong UHI values only occur when σw2 is very weak. This study demonstrates how DWL observations in cities provide valuable insights into near-surface processes relevant to human and environmental health.

Using Digital Marketing Strategy and Perceived Value to Promote Brand Trust in Chinese Mobile Phone Brands

Over the past few years, China’s branded mobile phone industry has experienced significant growth, becoming one of the largest global markets. With fierce domestic and international competition, brand trust has emerged as a crucial factor influencing consumer purchasing decisions. Consumers trust mobile phone brands that excel in product quality, service, and value. This study explores how digital marketing strategies and perceived value enhance brand trust in Chinese mobile phone brands. The study formulates a research model and designs a survey questionnaire by reviewing relevant literature on digital marketing strategy, perceived value, brand trust, and Chinese mobile phone brands. Data is collected through an online survey using SPSS software to analyze the relationship between digital marketing strategy, perceived value, and brand trust. Finally, considering the unique characteristics of the Chinese mobile phone brand market and the research findings, the study provides practical recommendations for Chinese mobile phone brands. Keywords: digital marketing strategy, perceived value, brand trust, Chinese mobile phone brands

Drivers of digital currency adoption and their configurational impact assessment in tourism and hospitality: loss aversion under prospect theory

ABSTRACT With accelerated digitalisation in all business sectors, digital currencies (DC) are increasingly popular. This study aimed to identify the effects of central bank digital currency (CBDC) innovation characteristics and perceived risks on CBDC adoption intention in the tourism and hospitality field. This study devised a research model incorporating research hypotheses addressing CBDC customers’ perceptions of CBDC's innovative technology and risks. To test the hypotheses, data were obtained from the USA, Korea, and China. CBDC's innovation characteristics and perceived risks affected the adoption of CBDC for transactions during travel. The results have academic and practical value because they aid understanding of customers’ reactions to the new transaction system and establish proactive marketing strategies such as promotional message development to reduce perceived risks in lieu of strengthening innovative characteristics.

Strategi dalam Meningkatkan Penjualan terhadap Minat Beli Konsumen di Pedagang Eva Fashion

This research analyzes strategies for increasing sales of consumer buying interest at Eva Fashion traders, using a quantitative approach with a sample of 50 respondents selected through a purposive sampling method. Multiple linear regression analysis with a significance level of 5% shows that the three independent variables have a positive and significant influence on consumer purchasing interest, with product design as the most dominant factor (regression coefficient 0.458, p &lt; 0.05), followed by product quality (0.325, p &lt; 0.05) and product variance (0.217, p &lt; 0.05). The research model produces an R2 value of 0.734, indicating that 73.4% of the variation in purchasing interest can be explained by these three variables, with the practical implication that Fashion Parking traders need to prioritize product design aspects while maintaining the quality and diversity of dance to increase business competitiveness.

Lean logistics and corporate green practices: messianic methodologies for achieving business excellence in the logistics industry via green stakeholder satisfaction

PurposeThis study aims to explore how logistics firms exploit lean logistics and corporate green practices as significant catalysts for achieving business excellence via the mediation roles of green internal stakeholder satisfaction and green external stakeholder satisfaction.Design/methodology/approachQuestionnaire is used in garnering data from 137 Ghanaian logistics firms. Structural equation modeling, particularly partial least squares, was applied to test all hypotheses.FindingsThe results confirm the notion that although lean logistics has positive effect on business performance, the effect is insignificant; hence, it is the concurrent implementation of lean logistics and corporate green practices that leads to superior business performance. The mediation analysis further confirms that both green internal stakeholder satisfaction and green external stakeholder satisfaction are significant precursors through which logistics firms can achieve superior business performance when lean logistics and corporate green practices can influence business performance.Research limitations/implicationsData is collected from logistics firms from a single country. Hence, the results obtained cannot be imported to reflect the general occurrence in other geographical settings.Practical implicationsThis study informs managers of logistics firms that lean and green strategies are compatible when implemented together; hence, it should not be treated in isolation. Managers are further enlightened that in their pursuit of business excellence, there is a need to prioritize green internal stakeholder satisfaction and green external stakeholder satisfaction via prudent investment in lean and green practices.Originality/valueThe research model proposed in this study magnifies the literature on lean and environmental management via bridging the literature gap concerning the interrelationship between lean logistics, corporate green practices, green internal stakeholder satisfaction, green external stakeholder satisfaction and business performance.

Improved Orographic Gravity Wave Drag Parameterization Accounting for the Nonhydrostatic Effect in the Weather Research and Forecasting Model: Tests for Short-Range Forecast of Northeast China Cold Vortices

Abstract The parameterization of orographic gravity wave drag (OGWD) is essential for accurate numerical weather prediction in regions of complex terrain. Current OGWD schemes assume hydrostatic OGWs but the parameterized OGWs in fine-resolution models with narrow subgrid-scale orography can be significantly affected by the nonhydrostatic effects (NHE). In our recent work, the OGWD scheme in the Model for Prediction Across Scales (MPAS) was revised by accounting for the NHE on the surface wave momentum flux of upward-propagating OGWs. Herein, the revised OGWD scheme is implemented in the Weather Research and Forecasting (WRF) model to evaluate its performance in short-range weather forecast. Two sets of 36-hr WRF simulations are conducted for nine Northeast China cold vortices (NECVs) that occurred in the warm season of 2011 using the original and revised OGWD schemes. Results show that the WRF model tends to underestimate the intensity of the NECVs, producing too high geopotential height. When accounting for the NHE in the OGWD scheme, the NECV intensity biases are significantly reduced. Analyses reveal that the NHE act to weaken the lower-tropospheric OGWD by decreasing the surface wave momentum flux, which strengthens the NECV in the lower troposphere. Consequently, the strengthened low-level cyclonic circulation increases the post-trough cold advection to the southwest of the NECV which in turn enhances the NECV in the mid-upper troposphere with reduced geopotential height. The NHE are found to increase as the model horizontal resolution increases, suggesting greater importance of the NHE in the OGWD parameterization of high-resolution numerical models.

Research on the effectiveness and strategies of new media in promoting voluntary blood donation from a public health perspective in the post-pandemic era.

This study explores the effectiveness of new media in enhancing public enthusiasm for voluntary blood donation in the post-pandemic era and proposes effective publicity strategies to promote the sustainability and healthy development of blood donation activities. A questionnaire survey was widely used to collect public opinions and attitudes toward voluntary blood donation. The sample data underwent rigorous reliability and validity analysis to ensure authenticity and reliability. Statistical methods such as correlation analysis and regression analysis were employed to deeply investigate the underlying relationships between factors like new media publicity, emotional value, social recognition, convenience, information reliability, and willingness to donate blood voluntarily. Based on these analyses, a research model was constructed, and relevant hypotheses were verified through empirical methods. The study found that new media publicity may be associated with increasing the willingness of the public to voluntarily donate blood. Survey participants indicated that they were more likely to consider donating blood after exposure to new media publicity. Among these factors, the emotional value and content conveyed by the publicity appeared to be particularly important. Additionally, our research revealed that social recognition, the convenience of blood donation, and the reliability of promotional information seemed to have a direct impact on the public's willingness to donate blood. At the same time, these factors may indirectly promote actual blood donation behavior by enhancing the public's emotional resonance and acceptance of blood donation. This study suggests that new media may play multiple positive roles in promoting voluntary blood donation. Based on these findings, we propose a series of strategic recommendations, including further optimizing publicity content, striving to enhance the public's emotional resonance, improving the reliability of promotional information, and enhancing service convenience. These suggestions aim to potentially raise public awareness and willingness to participate in voluntary blood donation, providing a scientific basis and strong support for the promotion of voluntary blood donation in the post-epidemic era.

Application and progress of 3D tumor models in breast cancer.

Due to its high heterogeneity and significant impact on women's health globally, breast cancer necessitates robust preclinical models to understand tumor biology and guide personalized treatment strategies. Three-dimensional (3D) in vitro tumor models hold immense promise in this regard. These tumor models not only mimic the spatial structure and growth environment of tumors in vivo, but also retain the pathological and genetic characteristics of solid tumors. This fidelity makes them powerful tools for accelerating advancements in fundamental research and translational medicine. The diversity, modularity, and efficacy of 3D tumor models are driving a biotechnological revolution. As these technologies become increasingly sophisticated, 3D tumor models are poised to become powerful weapons in the fight against breast cancer. This article expounds on the progress made in utilizing 3D tumor models for breast cancer research.