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Jo H, Bang Y. Analyzing ChatGPT adoption drivers with the TOEK framework. Sci Rep 2023; 13:22606. [PMID: 38114544 PMCID: PMC10730566 DOI: 10.1038/s41598-023-49710-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 12/11/2023] [Indexed: 12/21/2023] Open
Abstract
With the rapid advancements in AI technology and its growing impact on various aspects of daily life, understanding the factors that influence users' adoption intention becomes essential. This study focuses on the determinants affecting the adoption intention of ChatGPT, an AI-driven language model, among university students. The research extends the Technology-Organization-Environment (TOE) framework by integrating the concept of knowledge application. A cross-sectional research design was employed, gathering data through a survey conducted to university students. Structural equation modeling was used to analyze the data, aimed at examining the relationships between key determinants influencing adoption intention. The findings of this research indicate that factors such as network quality, accessibility, and system responsiveness contribute to satisfaction. Furthermore, satisfaction, organizational culture, social influence, and knowledge application significantly affect adoption intention. These findings offer both theoretical and practical implications.
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Affiliation(s)
- Hyeon Jo
- Headquarters, HJ Institute of Technology and Management, 71 Jungdong-ro 39, Bucheon-si, Gyeonggi-do, 14721, Republic of Korea
| | - Youngsok Bang
- School of Business, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
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Uzir MUH, Bukari Z, Al Halbusi H, Lim R, Wahab SN, Rasul T, Thurasamy R, Jerin I, Chowdhury MRK, Tarofder AK, Yaakop AY, Hamid ABA, Haque A, Rauf A, Eneizan B. Applied artificial intelligence: Acceptance-intention-purchase and satisfaction on smartwatch usage in a Ghanaian context. Heliyon 2023; 9:e18666. [PMID: 37560680 PMCID: PMC10407215 DOI: 10.1016/j.heliyon.2023.e18666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 08/11/2023] Open
Abstract
Technology and its continuous advancement facilitate human beings to get rid of their criticality and limitation. Applied artificial intelligence (AAI) is one of the latest forms that delimited the limitation of human beings. Smartwatch acts as an applied artificial intelligence to assist various patients to check medical care without going to hospital and physicians. This (three) multiple-study research focused on the intention to use, purchase, and their satisfaction and spread positive word of mouth among others in the Ghanaian. To investigate these issues two renowned theories were underpinned- TAM theory and the Stimulus-Organism-Response (S-O-R). Total 550, 320, and 170 respondents were interviewed with Google forms due to COVID-19 using social media. AI-enabled smartwatch considering Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Perceived Credibility (PC), Perceived Self-Efficacy (PSE), and Perceived Financial Cost (PFC) were significant on intention to adoption and adoption intention on actual purchase. The final study showed device quality, its service level, their usage experience, perceived value, and the extent to which the satisfied customers made positive word of mouth to their friends and family, colleagues and followers. This research is significant in understanding the usage of AI-enabled smartwatches as a device doctor or electronic doctor (e-doctor).
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Affiliation(s)
- Md Uzir Hossain Uzir
- Marketing Department, Lincoln University College, Petaling Jaya, Selangor, Malaysia
- Marketing Department, Faculty of Business, Economics, and Social Development, University Malaysia Terengganu, Kuala Terengganu, Malaysia
| | - Zakari Bukari
- Department of Marketing and Customer Management, University of Professional Studies, Accra, Ghana
| | - Hussam Al Halbusi
- Department of Management at Ahmed Bin Mohammad Military College, Doha, Qatar
| | - Rodney Lim
- Marketing and E-Commerce, Swinburne University of Technology, Sarawak Campus, Hawthorn, 3122, Australia
| | - Siti Norida Wahab
- Faculty of Business and Management, Universiti Teknologi MARA, 42300, Bandar Puncak Alam, Selangor, Malaysia
| | - Tareq Rasul
- Department of Marketing, Australian Institute of Business (AIB), Adelaide, Australia
| | - Ramayah Thurasamy
- School of Management, Universiti Sains Malaysia, Minden, 11800, Penang, Malaysia
- Department of Information Technology & Management, Daffodil International University, Birulia, Bangladesh
- Department of Management, Sunway University Business School, 47500, Petaling Jaya, Selangor, Malaysia
- University Center for Research & Development (UCRD), Chandigarh University, Ludhiana, 140413, Punjab, India
- Fakulti Ekonomi Dan Pengurusan (FEP), Universiti Kebangsaan Malaysia (UKM), Hulu Langat, Malaysia
- Faculty of Economics and Business, Universitas Indonesia (UI), Depok City, West Java, 16424, Indonesia
- Azman Hashim International Business School, Universiti Teknologi Malaysia (UTM), Iskandar Puteri, Malaysia
- Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu (UMT), 21300, Kuala Terengganu, Malaysia
| | - Ishraq Jerin
- Putra Business School (PBS), Universiti Putra Malaysia (UPM), 43400, Seri Kembangan, Selangor, Malaysia
| | - M Rezaul Karim Chowdhury
- Faculty of Maritime Studies, Universiti Malaysia Terengganu, 21300, Kuala Terengganu, Terengganu, Malaysia
| | - Arun Kumar Tarofder
- Faculty of Business and Professional Studies, Management and Science University Malaysia, 40100, Shah Alam, Selangor, Malaysia
| | - Azizul Yadi Yaakop
- Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu, 21300, Kuala Terengganu, Terengganu, Malaysia
| | | | - Ahasanul Haque
- Department of Business Administration, International Islamic University Malaysia, Box No. 10, 50728, Kuala Lumpur, Malaysia
| | | | - Bilal Eneizan
- Business School, Jadara University, Irbid, Jordan
- College of Science and Humanities Studies, Prince Sattam Bin Abdulaziz University, Sulayyil, Saudi Arabia
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Lengua LJ, Stavish CM, Green LM, Shimomaeda L, Thompson SF, Calhoun R, Moini N, Smith MR. Pre-COVID-19 predictors of low-income women's COVID-19 appraisal, coping, and changes in mental health during the pandemic. JOURNAL OF COMMUNITY PSYCHOLOGY 2023; 51:2098-2116. [PMID: 36776019 DOI: 10.1002/jcop.23012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 01/24/2023] [Accepted: 01/27/2023] [Indexed: 06/14/2023]
Abstract
Study examined predictors and mental health consequences of appraisal (threat, support satisfaction) and coping (active, avoidant) in a sample of low-income women during coronavirus disease 2019 (COVID-19). Pre-COVID-19 contextual risk and individual resources and COVID-19-specific risk factors were examined as predictors of COVID-19 appraisal and coping, which, in turn, were tested as predictors of changes in depression and anxiety across the pandemic. Pre-COVID-19 resilience predicted more active coping, whereas pre-COVID-19 anxiety and depression predicted more avoidant coping and lower support satisfaction, respectively. Increases in anxiety were predicted by lower pre-COVID-19 self-compassion and higher concurrent threat appraisal and avoidant coping. Increases in depression were related to lower pre-COVID-19 self-compassion, active coping and support satisfaction, and higher COVID-19 hardships and health risk. Findings highlight contextual and individual factors and processes that contribute to mental health problems in a vulnerable population during community-level stressors, with implications for prevention and intervention.
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Affiliation(s)
- Liliana J Lengua
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | - Caitlin M Stavish
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | - Lindsey M Green
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | - Lisa Shimomaeda
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | | | - Rebecca Calhoun
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | - Natasha Moini
- Department of Psychology, University of Washington, Seattle, Washington, USA
| | - Michele R Smith
- Department of Psychology, University of Washington, Seattle, Washington, USA
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Tongtong S, Xinhang C. Research on the impact of enterprise big data analytics capability on ambidextrous innovation capability – the mediating effect of agility. TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT 2022. [DOI: 10.1080/09537325.2022.2132140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Sun Tongtong
- Beijing Inst Petrochem Technol, Sch Econ&Management, Beijing, People’s Republic of China
| | - Cheng Xinhang
- Male, graduate student at University of Jinan, Business School, Jinan, People's Republic of China
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Alshallaqi M, Al Halbusi H, Abbas M, Alhaidan H. Resistance to innovation in low-income populations: The case of university students' resistance to using digital productivity applications. Front Psychol 2022; 13:961589. [PMID: 36275207 PMCID: PMC9585972 DOI: 10.3389/fpsyg.2022.961589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 08/18/2022] [Indexed: 11/13/2022] Open
Abstract
Innovation resistance research remains in its early stages. Efforts to define and comprehend consumer resistance to innovation necessitate in-depth studies that consider the contextual factors of resistance to innovation. To address this challenge, this research explored consumer resistance to innovation in a low-income population, namely, university students on financial support. The innovation under this study is the productivity applications provided for free by the University of Hail, Saudi Arabia, to all students. This study explores variables such as value barrier, risk barrier, tradition barrier, and image barrier and how they impact consumer resistance to innovation in a low-income population. We extend the theory by investigating the moderating roles of consumer characteristics (motivation, self-efficacy, emotion, and attitude toward existing products). The current study is based on an online survey of low-income students at a Saudi Arabian University; 258 cases were gathered. We found that all the direct effects of the variables (i.e., Value Barrier, Risk Barrier, Tradition Barrier, and Image Barrier) were positively related to consumer resistance to innovation. Importantly, consumer characteristics significantly moderate this relationship, as the relationship is stronger when the measurements for consumer characteristics are high.
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Affiliation(s)
- Mohammad Alshallaqi
- Department of Management and Information Systems, College of Business Administration, University of Hail, Ha'il, Saudi Arabia
- *Correspondence: Mohammad Alshallaqi
| | | | - Mazhar Abbas
- Department of Management and Information Systems, College of Business Administration, University of Hail, Ha'il, Saudi Arabia
| | - Homoud Alhaidan
- Department of Management and Information Systems, College of Business Administration, University of Hail, Ha'il, Saudi Arabia
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Zibarzani M, Abumalloh RA, Nilashi M, Samad S, Alghamdi OA, Nayer FK, Ismail MY, Mohd S, Mohammed Akib NA. Customer satisfaction with Restaurants Service Quality during COVID-19 outbreak: A two-stage methodology. TECHNOLOGY IN SOCIETY 2022; 70:101977. [PMID: 36187884 PMCID: PMC9513347 DOI: 10.1016/j.techsoc.2022.101977] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 03/26/2022] [Accepted: 04/26/2022] [Indexed: 05/17/2023]
Abstract
Online reviews have been used effectively to understand customers' satisfaction and preferences. COVID-19 crisis has significantly impacted customers' satisfaction in several sectors such as tourism and hospitality. Although several research studies have been carried out to analyze consumers' satisfaction using survey-based methodologies, consumers' satisfaction has not been well explored in the event of the COVID-19 crisis, especially using available data in social network sites. In this research, we aim to explore consumers' satisfaction and preferences of restaurants' services during the COVID-19 crisis. Furthermore, we investigate the moderating impact of COVID-19 safety precautions on restaurants' quality dimensions and satisfaction. We applied a new approach to achieve the objectives of this research. We first developed a hybrid approach using clustering, supervised learning, and text mining techniques. Learning Vector Quantization (LVQ) was used to cluster customers' preferences. To predict travelers' preferences, decision trees were applied to each segment of LVQ. We used a text mining technique; Latent Dirichlet Allocation (LDA), for textual data analysis to discover the satisfaction criteria from online customers' reviews. After analyzing the data using machine learning techniques, a theoretical model was developed to inspect the relationships between the restaurants' quality factors and customers' satisfaction. In this stage, Partial Least Squares (PLS) technique was employed. We evaluated the proposed approach using a dataset collected from the TripAdvisor platform. The outcomes of the two-stage methodology were discussed and future research directions were suggested according to the limitations of this study.
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Affiliation(s)
- Masoumeh Zibarzani
- Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran
| | - Rabab Ali Abumalloh
- Computer Department, Community College, Imam Abdulrahman Bin Faisal University, P.O. Box. 1982, Dammam, Saudi Arabia
| | - Mehrbakhsh Nilashi
- Centre for Global Sustainability Studies (CGSS), Universiti Sains Malaysia, 11800, Penang, Malaysia
- UCSI Graduate Business School, UCSI University, No. 1 Jalan Menara Gading, UCSI Heights, 56000, Cheras, Kuala Lumpur, Malaysia
| | - Sarminah Samad
- Department of Business Administration, College of Business and Administration, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
| | - O A Alghamdi
- Business Administration Dept., Applied College, Najran University, Najran, Saudi Arabia
| | - Fatima Khan Nayer
- Artificial Intelligence and Data Analytics (AIDA) Research Lab, College of Computer and Information Sciences, Prince Sultan University, Saudi Arabia
| | | | - Saidatulakmal Mohd
- Centre for Global Sustainability Studies (CGSS), Universiti Sains Malaysia, 11800, Penang, Malaysia
- School of Social Sciences, Universiti Sains Malaysia, 11800, Penang, Malaysia
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Ashrafi DM, Easmin R. Okay Google, Good to talk to you$\ldots$Examining the determinants affecting users' behavioral intention for adopting voice assistants: Does technology self-efficacy matter? INTERNATIONAL JOURNAL OF INNOVATION AND TECHNOLOGY MANAGEMENT 2022. [DOI: 10.1142/s0219877023500049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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BOSTANCI S, YILDIRIM S, ERDOĞAN F. A review on e-Government Portal’s services within Hospital Information System during Covid-19 pandemic. KONURALP TIP DERGISI 2022. [DOI: 10.18521/ktd.1036010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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AZIKI A, FADILI MH. Highlighting artificial intelligence roles in business area Amid the COVID-19 crisis. PROCEDIA COMPUTER SCIENCE 2022; 203:450-455. [PMID: 35974967 PMCID: PMC9374311 DOI: 10.1016/j.procs.2022.07.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Purpose: The fast development of technology and data has fueled the use of artificial intelligence (AI) in the business area, but there has been no comprehensive review to guide and assess this evolution, especially in the context of Covid-19 crisis. Our objective is to highlight the nature and scale of AI research in the business area, during the COVID-19 Pandemic. Methods: We performed a scoping review and searched two literature databases (Scopus and MDPI) for terms related to AI and Covid-19 by focusing on scientific papers published in the field of business. We used multiple tools (Endnote, Covidence) for titles and abstracts selection, followed by full-text screening. The studies must include research on artificial intelligence and Covid-19, and then be published in English-language, between March 2020 and March 2022. Results: 31 studies met eligibility criteria (of 391 studies selected). Most of the published articles refer to conceptual analysis or quantitative works, the rest of the articles used a literature review except 4 articles published using a qualitative method of analysis. In addition, we observe an evolution of the total number of publications for the 31 articles included in the analysis. Conclusions: Studying AI in the business field amid the covid-19 crisis is at an early stage of maturity, especially with the use of new AI technologies.). For the field to progress, more studies are needed in the next few years.
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