Prior studies have put much emphasis on using the uses and gratification (U&G) theory to find out why people use games, social media, the Internet, e-shopping, etc. Despite past research efforts, the root causes underlying this phenomenon still need to be discovered as to why people use interactive virtual rides (vrides) entertainment services, especially when incorporating the hedonic consumption perspective (i.e. playful-consumption experiences). Considering the knowledge gap in the vrides’ context, this study aims to use the UGT to find out why people use the vrides entertainment service from a hedonic consumption point of view.
With 217 usable responses, the research model was tested using partial least squares-based structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA).
Findings reveal that only perceived enjoyment, arousal and sensory experience derive continuous intention behavior to consume vride entertainment service. Findings using the fsQCA revealed multiple causal configurations for the proposed outcome.
This study contributes to extending the assumption of UGT via incorporating the hedonic consumption perspective to explore the potential motives and intention to consume vrides entertainment services. Our study also discusses the important theoretical/practical implications of our findings. Besides, this study is unique because it shows both symmetrical and asymmetrical connections that help us understand why people keep using vrides entertainment service.
This research examines the transformative impact of the “Great Reset” on organisational theory through the thematic network analysis of managerial responses from Germany, France, and Spain, emphasising the importance of technological integration, remote working, and resilience.
Questionnaire responses from managers in Germany, France, and Spain were examined using thematic network analysis to understand remote working, digital transformation, and organisational resilience.
Managers highlighted the pivotal role of technology in reshaping future work systems, especially in telecommuting and digitising business procedures. This transformation requires upskilling, shifts in management approaches, and a modernised employee assessment structure.
This study offers practical insights into implementing the Great Reset framework and explains its impact on technological progress, managerial strategies, and organisational resilience.
This study aims to investigate the impact of brain drain on government AI readiness in EU member countries, considering the distinctive governance characteristics, macroeconomic conditions and varying levels of ICT specialists.
The research employs a dynamic panel data model using the System Generalized Method of Moments (GMM) to analyze the relationship between brain drain and government AI readiness from 2018 to 2022. The study incorporates various control variables such as GDP per capita growth, government expenditure growth, employed ICT specialists and several governance indicators.
The results indicate that brain drain negatively affects government AI readiness. Additionally, the presence of ICT specialists, robust governance structures and positive macroeconomic indicators such as GDP per capita growth and government expenditure growth positively influence AI readiness.
Major limitations include the focus on a specific region of countries and the relatively short period analyzed. Future research could extend the analysis with more comprehensive datasets and consider additional variables that might influence AI readiness, such as the integration of AI with emerging quantum computing technologies and the impact of governance reforms and international collaborations on AI readiness.
The theoretical value of this study lies in providing a nuanced understanding of how brain drain impacts government AI readiness, emphasizing the critical roles of skilled human capital, effective governance and macroeconomic factors in enhancing AI capabilities, thereby filling a significant gap in the existing literature.
This research fills a significant gap in the existing literature by providing a comprehensive analysis of the interaction between brain drain and government AI readiness. It uses control variables such as ICT specialists, governance structures and macroeconomic factors within the context of the European Union. It offers novel insights for policymakers to enhance AI readiness through targeted interventions addressing brain drain and fostering a supportive environment for AI innovation.
Generative conversational artificial intelligence (AI) demonstrates powerful conversational skills for general tasks but requires customization for specific tasks. The quality of a custom generative conversational AI highly depends on users’ guidance, which has not been studied by previous research. This study uses social exchange theory to examine how generative conversational AI’s cognitive and emotional conversational skills affect users’ guidance through different types of user engagement, and how these effects are moderated by users’ relationship norm orientation.
Based on data collected from 589 actual users using a two-wave survey, this study employed partial least squares structural equation modeling to analyze the proposed hypotheses. Additional analyses were performed to test the robustness of our research model and results.
The results reveal that cognitive conversational skills (i.e. tailored and creative responses) positively affected cognitive and emotional engagement. However, understanding emotion influenced cognitive engagement but not emotional engagement, and empathic concern influenced emotional engagement but not cognitive engagement. In addition, cognitive and emotional engagement positively affected users’ guidance. Further, relationship norm orientation moderated some of these effects such that the impact of user engagement on user guidance was stronger for communal-oriented users than for exchange-oriented users.
First, drawing on social exchange theory, this study empirically examined the drivers of users’ guidance in the context of generative conversational AI, which may enrich the user guidance literature. Second, this study revealed the moderating role of relationship norm orientation in influencing the effect of user engagement on users’ guidance. The findings will deepen our understanding of users’ guidance. Third, the findings provide practical guidelines for designing generative conversational AI from a general AI to a custom AI.
To investigate the potential of raising the retirement age and reforming pension insurance in mitigating intra- and inter-generational income inequality, thereby offering empirical support for governmental policy formulation.
A dynamic general equilibrium model with intertemporal iteration is developed to comprehensively assess the impact of policies raising the retirement age on income inequality, taking into account delayed retirement, survival probability, and pension insurance. The theoretical hypotheses are validated through simulation using MATLAB.
Through theoretical analysis, it is determined that, given certain assumptions are satisfied, raising the retirement age can effectively mitigate intra-generational income inequality, inter-generational income inequality under both the pay-as-you-go and fund accumulation systems. Simulation results indicate that, under current parameter settings, raising the retirement age can reduce the Gini coefficient. Furthermore, this study reveals that regardless of the pay-as-you-go or fund accumulation system, pension insurance serves as a mechanism for income redistribution and alleviating income inequality.
It offers a theoretical foundation for the government's policy on delayed retirement and endowment insurance.
Researchers from different disciplines have advocated for the incorporation of Systems Thinking in higher education in various fields such as environmental studies, engineering, economics and management. Nevertheless, educational experiences that seek to integrate the systems approach and citizenship education are not numerous and have not been sufficiently documented. This research paper presents classroom research aimed at understanding how Systems Thinking and citizenship education are articulated within a general education course.
The research was designed using Grounded Theory within an exploratory-descriptive approach. To collect data, the following techniques were used: participant observation, focus group and documentary analysis. The data analysis was carried out through the constant comparative method in its open, axial, selective and theoretical contrast coding phases.
The data analysis highlights the potential of Systems Thinking within the context of Citizenship Education as a comprehensive set of cognitive, affective and methodological tools. Moreover, it sheds light on the pedagogical practices, the teaching strategies and the type of socioemotional interactions in the classroom that are key elements in promoting citizenship attitudes, ideas and behaviors.
The research underscores the importance of a systemic vision of education that explicitly incorporates social-emotional learning and experiences of citizen participation beyond the classroom where students can build new knowledge from first-hand interactions with processes of social transformation.
This paper expects to analyze the connection between occupational stigma and job meaningfulness among Chinese takeaway riders, the mediating role of occupational identity and relative deprivation, and the moderating effect of job stress based on resource conservation theory.
The sample was derived from 371 takeaway riders across China. PLS-SEM was mainly utilized for the data analysis.
The findings of the study indicated a significant negative correlation between occupational stigma and job meaningfulness. Furthermore, it is worth noting that relative deprivation and occupational identity served as mediators and masks, respectively, in the relationship between occupational stigma and job meaningfulness. Furthermore, job stress amplifies the association between occupational stigma and occupational identity. Additionally, job stress diminishes the connection between occupational stigma and relative deprivation.
This study proposes a positive correlation between occupational stigma and occupational identity in the Chinese context. It also enriches the empirical research based on resource conservation theory. Furthermore, it holds practical implications for takeaway riders in China, offering insights to bolster their job meaningfulness.
The purpose of this paper is to identify the dimensions and formation mechanisms of brand value on social media platforms within the prosumption logic based on the theory of value co-creation. By adopting a process-oriented mindset, this study deconstructs and applies the prosumption theory and the theory of value co-creation in the field of social media, thereby addressing the insufficiencies of previous research that focused primarily on the subject mindset. It offers reference ideas for social media brand managers to attract prosumers to engage in value co-creation.
The crawler technology and grounded theoretical method were adopted in this research paper.
Based on the logic of prosumption and the theory of value co-creation, the research finds that the brand value of social media platforms is composed of seven dimensions. The dimensions include brand recognition, brand perception quality, brand experience, brand value-in-use, brand relationship quality, brand loyalty and brand co-creation behavior. From the perspective of prosumption logic, the formation of brand value on social media platforms is a gradual accumulation process. This process involves prosumers participating in prosumption activities, progressing through several stages. Initially, it starts with “prosumption conditions”, which include brand recognition, brand perception quality and brand experience. It then moves to “prosumption processes,” characterized by brand value-in-use and brand relationship quality. Finally, it culminates in “prosumption outcomes,” represented by brand loyalty and brand co-creation behavior. From the perspective of value creation, the formation of brand value on social media platforms is a closed-loop process that includes “brand value identification and empowerment—brand value acquisition and transformation—brand value co-creation and relationship upgradation—brand value co-creation and stability—brand value feedback and iteration.”
The findings contribute to expanding prosumption and co-creation theory and enriching the prosumption logic frame. Meanwhile, it is conducive to encouraging prosumers to participate in the platform’s prosumption activities and jointly creating the brand value of the social media platform. This paper interprets prosumption through the lens of the value co-creation process.
Many studies have examined pre-diploma students' backgrounds and academic performance with results showing that some did not achieve the expected level of competence. This study aims to examine the relationship between students’ demographic characteristics and their academic achievement at the pre-diploma level using machine learning.
Secondary data analysis was used in this study, which involved collecting information about 1,052 pre-diploma students enrolled at Universiti Teknologi MARA (UiTM) Pahang Branch between 2017 and 2021. The research procedure was divided into two parts: data collecting and pre-processing, and building the machine learning algorithm, pre-training and testing.
Gender, family income, region and achievement in the national secondary school examination (Sijil Pelajaran Malaysia [SPM]) predict academic performance. Female students were 1.2 times more likely to succeed academically. Central region students performed better with a value of 1.26. M40-income students were more likely to excel with an odds ratio of 2.809. Students who excelled in SPM English and Mathematics had a better likelihood of succeeding in higher education.
This research was limited to pre-diploma students from UiTM Pahang Branch. For better generalizability of the results, future research should include pre-diploma students from other UiTM branches that offer this programme.
This study is expected to offer insights for policymakers, particularly, the Ministry of Higher Education, in developing a comprehensive policy to improve the tertiary education system by focusing on the fourth Sustainable Development Goal.
These pre-diploma students were found to originate mainly from low- or middle-income families; hence, the programme may help them acquire better jobs and improve their standard of living. Most students enrolling on the pre-diploma performed below excellent at the secondary school level and were therefore given the opportunity to continue studying at a higher level.
This predictive model contributes to guidelines on the minimum requirements for pre-diploma students to gain admission into higher education institutions by ensuring the efficient distribution of resources and equal access to higher education among all communities.
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