References
- Ahsanullah, S.S., Kamil, M., & Muzafar, K. (2006). Understanding factors influencing user experience of interactive systems: A literature review. ARPN Journal of Engineering and Applied Sciences (JEAS), 10, 18175–18185.
- Ali, O., Shrestha, A., Soar, J., & Wamba, S.F. (2018). Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review. International Journal of Information Management, 43, 146–158.
- Aredal, M., & Cianciotta, C. (2019). Robotization as a driver of increased labour productivity and economic convergence or divergence in the European Union. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264226
- Atanasoff, L., & Venable, M.A. (2017). Technostress: Implications for adults in the workforce. The Career Development Quarterly, 65(4), 326–338.
- Berente, N., Gu, B., Recker, J., & Santhanam, R. (2019). Managing AI. MIS Quarterly, 45(3), 1433–1450. DOI: 10.25300/MISQ/2021/16274
- Bloomberg. (2021). Agtech Booms as Investors Target Climate-Friendly Technology. Retrieved from https://www.bloomberg.com/news/ar-ticles/2021-12-09/agtech-booms-as-investors-target-climate-friendly-technology
- Bondanini, G., Giorgi, G., Ariza-Montes, A., Vega-Muñoz, A., & Andreucci-Annunziata, P. (2020). Technostress dark side of technology in the workplace: A Scientometric analysis. International Journal of Environmental Research and Public Health, 17(21), 8013. https://doi.org/10.3390/ijerph17218013
- Borges, A.F., Laurindo, F.J., Spínola, M.M., Gonçalves, R.F., & Mattos, C.A. (2021). The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International Journal of Information Management, 57, 102225.
- Brod, C. (1984). Technostress: The human cost of the computer revolution. Reading, MA, USA: Addison-Wesley.
- Campbell, C., Sands, S., Ferraro, C., Tsao, H.Y.J., & Mavrommatis, A. (2020). From data to action: How marketers can leverage AI. Business Horizons, 63(2), 227–243.
- Chandra, S., Shirish, A., & Srivastava, S.C. (2019). Does technostress inhibit employee innovation? Examining the linear and curvilinear influence of technostress creators. Communications of the Association for Information Systems, 44, 299–331.
- Chandirasekaran, G., Arokiaraj, D., & Jebasingh, D. (2022). Digital transformation: Artificial intelligence based product benefits and problems of Agritech industry. In, Agri-Food 4.0: Innovations, Challenges and Strategies (pp.141–163). Emerald Group Publishing. DOI: 10.1108/S1877-636120220000027010
- Chi, M., Huang, R., & George, J.F. (2020). Collaboration in demand-driven supply chain: Based on a perspective of governance and IT-business strategic alignment. International Journal of Information Management, 52, Article 102062.
- Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383.
- Coombs, C. (2020). Will COVID-19 be the tipping point for the intelligent automation of work? A review of the debate and implications for research. International Journal of Information Management, 55, Article 102182.
- Dejoux, C., & Leon, E. (2018). Metamorphose des Managers (1st ed.). Paris: Pearson Education France.
- Dennehy, D. (2020). Ireland post-pandemic: Utilizing AI to kick-start economic recovery. Cutter Business Technology Journal, 33(11), 22–27.
- Dragano, N., & Lunau, T. (2020). Technostress at work and mental health: concepts and research results. Current Opinion in Psychiatry, 33(4), 407–413. doi: 10.1097/YCO.0000000000000613
- Duan, Y., Edwards, J.S., & Dwivedi, Y.K. (2019). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71.
- Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., … Medaglia, R. (2021). Artificial Intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, Article 101994.
- Finstad, K. (2010). The usability metric for user experience. Interacting with Computers, 22, 323–327. DOI: 10.1016/j.intcom.2010.04.004.
- Fischer, T., & Riedl, R. (2017). Technostress research: a nurturing ground for measurement pluralism? Communications of the Association for Information Systems, 40(17). https://doi.org/10.17705/1CAIS.04017
- Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
- Gruber, M., Heinemann, F., Brettel, M., & Hungeling, S. (2010). Configurations of resources and capabilities and their performance implications: An exploratory study on technology ventures. Strategic Management Journal, 31(12), 1337–1356.
- Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2010). Multivariate data analysis. Upper Saddle River, NJ: Prentice Hall.
- Hart, J., Sutcliffe, A., & De Angeli, A. (2012). Evaluating user engagement theory. Conference: CHI 2012 Workshop ‘Theories behind UX research and how they are used in practice’. https://www.researchgate.net/publication/271524138_Evaluating_User_Engagement_Theory
- Hornbaek, K., & Hertzum. M. (2017). Technology acceptance and user experience: a review of the experiential component in HCI. ACM Transactions on Computer-Human Interaction, 24(5), Article 33, 30 pages. https://doi.org/10.1145/3127358
- Hooper, D., Coughlan, J., & Mullen, M.R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53–60.
- Issa, H., & Bouchaib, B. (2018). Understanding the consequences of technostress: A non-linear perspective. ECIS Proceedings, ECIS2018, Research Papers 71. https://aisel.aisnet.org/ecis2018_rp/71
- Issa, H., Jabbouri, R., & Palmer, M. (2022). An artificial intelligence (AI)-readiness and adoption framework for AgriTech firms. Journal of Technological Forecasting & Social Change, 182, 121874, 1–17. https://doi.org/10.1016/j.techfore.2022.121874
- Kahn, W.A. (1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal, 33(4), 692–724.
- Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizon, 62, 15–25.
- Law, E., Roto, V., Hassenzahl, M., Vermeeren, A., & Kort, J. (2009). Understanding, scoping and defining user experience: A survey approach. CHI ‘09: CHI Conference on Human Factors in Computing Systems, Boston, MA. https://dl.acm.org/doi/10.1145/1518701.1518813
- Lezoche, M., Panetto, H., Kacprzyk, J., Hernandez, J.E., & Alemany Díaz, M.M.E. (2020). Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture. Computers in Industry, 89, 158–174. https://doi.org/10.1016/j.compind.2020.103187
- Longoni, C., Bonezzi, A., & Morewedge, C.K. (2019). Resistance to medical artificial intelligence. Journal of Consumer Research, 46(4), 629–650.
- Martínez-Córcoles, M., Teichmann, M., & Murdvee, M. (2017). Assessing technophobia and technophilia: development and validation of a questionnaire. Technology in Society, 51, 183–188.
- McCarthy, J., & Wright, W. (2004). Technology as Experience. Interactions, MIT Press. DOI: 10.1145/1015530.1015549
- Miranda, J., Ponce, P., Molina, A., & Wright, P. (2019). Sensing, smart and sustainable technologies for Agri-Food 4.0. Computers in Industry, 108, 21–36. https://doi.org/10.1016/j.compind.2019.02.002
- Mohammed, G. (2022). The impact of technostress on employees’ well- being: the role of work engagement and perceived supervisor support. International Journal of Science and Research (IJSR),11(1), 10. DOI: 10.21275/SR22117144703.
- Monett, D., & Lewis, C.W. (2018). Getting clarity by defining Artificial Intelligence - A Survey. In V. C. Müller (Ed.), Philosophy and theory of artificial intelligence (pp. 212–214). Berlin: Springer.
- Nishant, R., Kennedy, M., & Corbertt, J. (2020). Artificial intelligence for sustainability: challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104.
- Norman, D.A. (2004). Emotional design: Why we love (or hate) everyday things. New York, NY: Basic Books.
- Okolo, D., Kamarudin, S., & Ungku, A. (2013). An exploration of the relationship between technostress, employee engagement and job design from the Nigerian banking employee’s perspective. Management Dynamics in the Knowledge Economy, 6, 511-530. 10.25019/MDKE/6.4.01
- Ongori, H., & Agolla, J.E. (2008). Occupational stress in organizations and its effects on organizational performance. Journal of Management Research, 8(3), 123–134.
- Park, S. (2017). The fourth industrial revolution and implications for innovative cluster policies. AI & Society, 33(3), 433-445.
- Preacher, K. J., & Hayes, A.F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–731.
- Preacher, K.J., & Hayes, A.F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891.
- Ragu-Nathan, T.S., Tarafdar, M., Ragu-Nathan, B.S., & Tu, Q. (2008). The consequences of technostress for end users in organizations: Conceptual development and empirical validation. Information Systems Research, 19(4) 417-433.
- Rather, R.A., & Hollebeek, L.D. (2021). Customers’ service-related engagement, experience, and behavioral intent: Moderating role of age. Journal of Retailing and Consumer Services, 60, 102453. DOI: 10.1016/j.jretconser.2021.102453
- Sagnier, C., Loup-Escande, E., Lourdeaux, D., Thouvenin, I., & Valléry, G. (2020). User acceptance of virtual reality: An extended technology acceptance model. International Journal of Human–Computer Interaction. DOI: 10.1080/10447318.2019.1708612
- Saks, A. (2006). Antecedents and consequences of employee engagement. Journal of Managerial Psychology, 21(7), 600–619.
- Schaufeli, W.B., & Salanova, M. (2007). Efficacy or inefficacy, that’s the question: burnout and work engagement, and their relationships with efficacy beliefs. Anxiety, Stress, and Coping, 20(2), 177–196.
- Shoukat M.H., & Ramkissoon, H. (2022). Customer delight, engagement, experience, value co-creation, place identity, and revisit intention: A new conceptual framework. Journal of Hospitality Marketing & Management. DOI: 10.1080/19368623.2022.2062692
- Spanaki, K., Sivarajah, U., Fakhimi, M. et al. (2022). Disruptive technologies in agricultural operations: A systematic review of AI-driven Agri-Tech research. Annals of Operations Research, 308, 491–524. https://doi.org/10.1007/s10479-020-03922-z
- Spiros, A. (2019). Mitigating technostress in new knowledge workers through perceived self-efficacy. University of Jyväskylä.
- Srivastava, S.C., Chandra, S., & Shirish, A. (2015). Technostress creators and job outcomes: Theorising the moderating influence of personality traits. Information Systems Journal, 25, 355–401.
- Soni, N., Sharma, E.K., Singh, N., & Kapoorc, A. (2020). Artificial intelligence in business: from research and innovation to market deployment. Procedia Computer Science, 167, 2200–2210.
- Szollosy, M. (2015). Why are we afraid of robots? The role of projection in the popular conception of robots. In Beyond artificial intelligence (pp. 121–131). Berlin: Springer.
- Tarafdar, M., Tu, Q., Ragu-Nathan, B.S., & Ragu-Nathan, T.S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328.
- Tarafdar, M., Tu, Q., Ragu-Nathan, T.S., & Ragu-Nathan, B.S. (2011). Crossing to the dark side: examining creators, outcomes, and inhibitors of technostress. Communications of the ACM, 54(9), 113–120.
- Tarafdar, M., Pullins, E., Ragu-Nathan, T.S. (2014). Examining impacts of technostress on the professional salesperson’s behavioural performance. Journal of Personal Selling Sales Management, 34(1), 51–69.
- Tarafdar, M., Pullins, E.B., & Ragu-Nathan, T.S. (2015). Technostress: negative effect on performance and possible mitigations. Information Systems Journal, 25(2),103–132.
- The Business Times. (2019). Urban Singapore’s Agritech Role Lies in SE Asia’s 71m Small Farms. Retrieved from https://www.businesstimes.com.sg/garage/urban-singapore%E2%80%99s-agritech-role-lies-in-se-asia%E2%80%99s-71m-small-farms
- Tims, M., Bakker, A.B., & Derks, D. (2013). The impact of job crafting on job demands, job resources, and well-being. Journal of occupational health psychology, 18(2), 230–240.
- Truss, C., Shantz, A., Soane, E., Alfes, K., & Delbridge, R. (2013). Employee engagement, organisational performance and individual well-being: exploring the evidence, developing the theory. The International Journal of Human Resource Management, 24(14), 2657–2669.
- Turel, O., & Gaudioso, F. (2018). Techno-stressors, distress and strain: the roles of leadership and competitive climates. Cognition Technology & Work, 20(2), 309–324.
- Van Doorn, J., Lemon, K.N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P.C. (2010). Customer engagement behavior: theoretical foundations and research directions. Journal of Service Research, 13(3), 253–266.
- Vayre, E., & Vonthron, A.M. (2019). Identifying work-related internet’s uses—at work and outside usual workplaces and hours—and their relationships with work–home interface, work engagement, and problematic internet behavior. Frontiers in Psychology, 10, 2118.
- Velnampy, T., & Aravinthan, S.A. (2013). Occupational stress and organizational commitment in private banks: a Sri Lankan experience. European Journal of Business and Management, 5(7), 254–267.
- Wirth, N. (2018). Hello marketing, what can artificial intelligence help you with. International Journal of Market Research, 60(5), 435–438.
- Wolfe, A. (1991). Mind, self, society, and computer: artificial intelligence and the sociology of mind. American Journal of Sociology, 96(5), 1073–1096.
- Yahya, N. (2018). Agricultural 4.0: Its implementation toward future sustainability. In: Green urea. Green energy and technology. Singapore: Springer https://doi.org/10.1007/978-981-10-7578-0_5
- Yusoff, M.S.B., Esa, A.R., Mat Pa, M.N., Mey, S.C., & Aziz, R.A. (2013). A longitudinal study of relationships between previous academic achievement, emotional intelligence and personality traits with psychological health of medical students during stressful periods. Education for Health, 26(1), 39–47.
- Zardari, B.A., Hussain, Z., Arain, A.A., Rizvi, W.H., & Vighio, M.S. (2021). Development and validation of user experience-based e-learning acceptance model for sustainable higher education. Sustainability, 13, 6201. https://doi.org/10.3390/su13116201