References
Acemoglu, D., & Restrepo, P. 2020. Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188-2244. https://doi.org/10.1086/705716
Search via ReFindit
Acemoglu, D., Restrepo, P., & Robinson, J.A., 2020. Demographics, automation, and inequality. In AEA Papers and Proceedings,110, 48-53. https://doi.org/10.1257/pandp.20201063
Search via ReFindit
Agrawal, A., Gans, J.S. and Goldfarb, A., 2023. Artificial intelligence adoption and system‐wide change. Journal of Economics & Management Strategy, 33(2), 327-337. https://doi.org/10.1111/jems.12521
Search via ReFindit
Agrawal, A., Gans, J.S., & Goldfarb, A., 2019. Exploring the impact of artificial intelligence: Prediction versus judgment. Information Economics and Policy, 47, 1-6. https://doi.org/10.1016/j.infoecopol.2019.05.001
Search via ReFindit
Ahmad, S., Miskon, S., Alkanhal, T.A., & Tlili, I. 2020. Modeling of business intelligence systems using the potential determinants and theories with the lens of individual, technological, organisational, and environmental contexts-a systematic literature review. Applied Sciences, 10(9), 3208. https://doi.org/10.3390/app10093208
Search via ReFindit
Aldoseri, A., Al-Khalifa, K.N., & Hamouda, A.M. 2023. Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges. Applied Sciences, 13(12), 7082. https://doi.org/10.3390/app13127082
Search via ReFindit
Alvarez, S. A., & Barney, J. B. (2007). Discovery and creation: alternative theories of entrepreneurial action. Strategic Entrepreneurship Journal, 1(1–2), 11–26. https://doi.org/10.1002/sej.4
Search via ReFindit
Amoako, G., Omari, P., Kumi, D.K., Agbemabiase, G.C., & Asamoah, G. 2021. Conceptual framework—artificial intelligence and better entrepreneurial decision-making: the influence of customer preference, industry benchmark, and employee involvement in an emerging market. Journal of Risk and Financial Management, 14(12), 604. https://doi.org/10.3390/jrfm14120604
Search via ReFindit
Åström, J., Reim, W., & Parida, V. (2022). Value creation and value capture for AI business model innovation: a three-phase process framework. Review of Managerial Science, 16(7), 2111–2133. https://doi.org/10.1007/s11846-022-00521-z
Search via ReFindit
Baker, T., & Nelson, R.E. (2005). Creating something from nothing: Resource construction through entrepreneurial bricolage. Administrative Science Quarterly, 50(3), 329-366. https://doi.org/10.2189/asqu.2005.50.3.329
Search via ReFindit
Benk, M., Tolmeijer, S., von Wangenheim, F., & Ferrario, A., 2022. The value of measuring trust in ai-a socio-technical system perspective. arXiv preprint arXiv:2204.13480. https://doi.org/10.48550/arXiv.2204.13480
Search via ReFindit
Bouncken, R.B., Kraus, S., & Roig-Tierno, N. (2021) Knowledge-and innovation-based business models for future growth: digitalized business models and portfolio considerations. RMS, 15(1), 1-14. https://doi.org/10.1007/s11846-019-00366-z
Search via ReFindit
Box-Steffensmeier, J.M., Burgess, J., Corbetta, M., Crawford, K., Duflo, E., Fogarty, L., Gopnik, A., Hanafi, S., Herrero, M., Hong, Y.Y., & Kameyama, Y. 2022. The future of human behaviour research. Nature Human Behaviour, 6(1), 15-24. https://doi.org/10.1038/s41562-021-01275-6
Search via ReFindit
Brem, A., Giones, F., & Werle, M. 2021. The AI digital revolution in innovation: A conceptual framework of artificial intelligence technologies for the management of innovation. IEEE Transactions on Engineering Management, 70(2), 770-776. https://doi.org/10.1109/TEM.2021.3109983
Search via ReFindit
Brock, J.K.U., & Von Wangenheim, F. 2019. Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California Management Review, 61(4), 110-134. https://doi.org/10.1177/1536504219865226
Search via ReFindit
Brynjolfsson, E., & Mitchell, T., 2017. What can machine learning do? Workforce implications. Science, 358(6370): 1530-1534. https://doi.org/10.1126/science.aap8062
Search via ReFindit
Brynjolfsson, E., Rock, D., & Syverson, C., 2021. The productivity J-curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics, 13(1), 333-372. https://doi.org/10.1257/mac.20180386
Search via ReFindit
Burström, T., Parida, V., Lahti, T., & Wincent, J. 2021. AI-enabled business-model innovation and transformation in industrial ecosystems: A framework, model and outline for further research. Journal of Business Research, 127, 85-95. https://doi.org/10.1016/j.jbusres.2021.01.016
Search via ReFindit
Carbonara, E., & Santarelli, E., 2023. Artificial intelligence and robots: a threat or an opportunity for SMEs and entrepreneurship? SMEs in the Digital Era: Opportunities and Challenges of the Digital Single Market, 104. https://doi.org/10.4337/9781803921648.00013
Search via ReFindit
Chalmers, D., MacKenzie, N.G., & Carter, S., 2021. Artificial intelligence and entrepreneurship: Implications for venture creation in the fourth industrial revolution. Entrepreneurship Theory and Practice, 45(5), 1028-1053. https://doi.org/10.1177/1042258720934581
Search via ReFindit
Chesbrough, H. 2007. Business model innovation: it's not just about technology anymore. Strategy & leadership, 35(6), 12-17. https://doi.org/10.1108/10878570710833714
Search via ReFindit
Chesbrough, H., & Rosenbloom, R.S. 2002. The role of the business model in capturing value from innovation: evidence from Xerox Corporation's technology spin‐off companies. Industrial and corporate change, 11(3), 529-555. https://doi.org/10.1093/icc/11.3.529
Search via ReFindit
Cowls, J., & Floridi, L., 2018. Prolegomena to a white paper on an ethical framework for a good AI society. Available at SSRN 3198732: https://doi.org/10.2139/ssrn.3198732
Search via ReFindit
Cubric, M., 2020. Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study. Technology in Society, 62, 101257. https://doi.org/10.1016/j.techsoc.2020.101257
Search via ReFindit
DeCanio, S.J. 2016. Robots and humans–complement or substitutes? Journal of Macroeconomics, 49, 280-291. https://doi.org/10.1016/j.jmacro.2016.08.003
Search via ReFindit
Gans, J., & Leigh, A. 2020. Innovation+ Equality. Mit Press. https://doi.org/10.7551/mitpress/12407.001.0001
Search via ReFindit
Geels, F.W. 2004. From sectoral systems of innovation to socio-technical systems: Insights about dynamics and change from sociology and institutional theory. Research Policy, 33(6-7), 897-920. https://doi.org/10.1016/j.respol.2004.01.015
Search via ReFindit
Giuggioli, G., & Pellegrini, M.M. 2023. Artificial intelligence as an enabler for entrepreneurs: a systematic literature review and an agenda for future research. International Journal of Entrepreneurial Behaviour & Research, 29(4), 816-837. https://doi.org/10.1108/IJEBR-05-2021-0426
Search via ReFindit
Goldin, C., & Katz, L.F., 2018. The race between education and technology. In Inequality in the 21st Century (pp. 49-54). Routledge. https://doi.org/10.4324/9780429499821-10
Search via ReFindit
Heeks, R. 2021. From digital divide to digital justice in the global south: conceptualising adverse digital incorporation. arXiv preprint arXiv:2108.09783. https://doi.org/10.48550/arXiv.2108.09783
Search via ReFindit
Iansiti, M., & Lakhani, K.R. 2020. Competing in the age of AI: Strategy and leadership when algorithms and networks run the world. Harvard Business Press.
Search via ReFindit
Johnson, D.G., & Wetmore, J.M. eds., 2021. Technology and society: Building our socio-technical future. MIT press.
Search via ReFindit
Jorzik, P., Yigit, A., Kanbach, D.K., Kraus, S., & Dabić, M., 2023. Artificial Intelligence-Enabled Business Model Innovation: Competencies and Roles of Top Management. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2023.3275643
Search via ReFindit
Kang, X., Chaivirutnukul, K., & Zeng, Y., 2023. The Influence of Entrepreneurial Bricolage on Opportunity Recognition for New Ventures Based on Artificial Intelligence. Journal of Information Systems Engineering and Management, 8(4), 22735. https://doi.org/10.55267/iadt.07.13782
Search via ReFindit
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. 2018. Human decisions and machine predictions. The Quarterly Journal of economics, 133(1), 237-293. https://doi.org/10.1093/qje/qjx032
Search via ReFindit
Kraus, S., Palmer, C., Kailer, N., Kallinger, F.L., & Spitzer, J. 2019. Digital entrepreneurship: A research agenda on new business models for the twenty-first century. International Journal of Entrepreneurial Behavior & Research, 25(2), 353-375. https://doi.org/10.1108/IJEBR-06-2018-0425
Search via ReFindit
Lichtenthaler, U. 2018. Substitute or synthesis: the interplay between human and artificial intelligence. Research-Technology Management, 61(5), 12-14. https://doi.org/10.1080/08956308.2018.1495962
Search via ReFindit
Lin, H.C., Ho, C.F., & Yang, H. 2022. Understanding adoption of artificial intelligence-enabled language e-learning system: an empirical study of UTAUT model. International Journal of Mobile Learning and Organisation, 16(1), 74-94. https://doi.org/10.1504/IJMLO.2022.119966
Search via ReFindit
Lu, S. 2022. Data Privacy, Human Rights, and Algorithmic Opacity. Cal. L. Rev., 110: 2087. https://doi.org/10/15779/Z38804XM07
Search via ReFindit
Massa, L., Tucci, C.L., & Afuah, A. 2017. A critical assessment of business model research. Academy of Management annals, 11(1), 73-104. https://doi.org/10.5465/annals.2014.0072
Search via ReFindit
Mikalef, P., & Gupta, M., 2021. Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organisational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434
Search via ReFindit
Muhic, M., & Bengtsson, L., 2021. Dynamic capabilities triggered by cloud sourcing: a stage-based model of business model innovation. Review of Managerial Science, 15(1), 33-54. https://doi.org/10.1007/s11846-019-00372-1
Search via ReFindit
Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y., 2022. Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the Technology Acceptance Model (TAM) in combination with the Technology–Organisation–Environment (TOE) framework. Buildings, 12(2), 90. https://doi.org/10.3390/buildings12020090
Search via ReFindit
Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), 103773. https://doi.org/10.1016/j.respol.2019.03.018
Search via ReFindit
Olan, F., Arakpogun, E.O., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U., 2022. Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145, 605-615. https://doi.org/10.1016/j.jbusres.2022.03.008
Search via ReFindit
Osterwalder, A., & Pigneur, Y., 2010. Business model generation: a handbook for visionaries, game changers, and challengers (Vol. 1). John Wiley & Sons.
Search via ReFindit
Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.F., Breazeal, C., Crandall, J.W., Christakis, N.A., Couzin, I.D., Jackson, M.O., & Jennings, N.R. (2019). Machine behaviour. Nature, 568(7753), 477–486. https://doi.org/10.1038/s41586-019-1138-y
Search via ReFindit
Roundy, P.T., 2022. Artificial intelligence and entrepreneurial ecosystems: understanding the implications of algorithmic decision-making for start-up communities. Journal of Ethics in Entrepreneurship and Technology, 2(1), 23-38. https://doi.org/10.1108/JEET-07-2022-0011
Search via ReFindit
Saldaña, J., 2021. The coding manual for qualitative researchers. SAGE Publications Limited.
Search via ReFindit
Shepherd, D.A., & Majchrzak, A., 2022. Machines augmenting entrepreneurs: Opportunities (and threats) at the Nexus of artificial intelligence and entrepreneurship. Journal of Business Venturing, 37(4), 106227. https://doi.org/10.1016/j.jbusvent.2022.106227
Search via ReFindit
Tyson, L.D., & Zysman, J., 2022. Automation, AI & work. Daedalus, 151(2), 256-271. https://doi.org/10.1162/daed_a_01914
Search via ReFindit
Upadhyay, N., Upadhyay, S., & Dwivedi, Y.K. 2022. Theorizing artificial intelligence acceptance and digital entrepreneurship model. International Journal of Entrepreneurial Behavior & Research, 28(5), 1138-1166. https://doi.org/10.1108/IJEBR-01-2021-0052
Search via ReFindit
Uren, V., & Edwards, J.S. 2023. Technology readiness and the organizational journey towards AI adoption: An empirical study. International Journal of Information Management, 68, 102588. https://doi.org/10.1016/j.ijinfomgt.2022.102588
Search via ReFindit
Valter, P, Lindgren, P., & Prasad, R. (2018) The consequences of artificial intelligence and deep learning in a world of persuasive business models. IEEE Aero El Sys Mag 33(5-6), 80-88. https://doi.org/10.1109/MAES.2018.170110
Search via ReFindit
Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478. https://doi.org/10.2307/30036540
Search via ReFindit
Verganti, R., Vendraminelli, L., & Iansiti, M. 2020. Innovation and design in the age of artificial intelligence. Journal of Product Innovation Management, 37(3), 212-227. https://doi.org/10.1111/jpim.12523
Search via ReFindit
Vieira, V., Cunha, J.A., Brochado, A., & Nunes, S., 2022. Drivers and barriers to the adoption of artificial intelligence in start-ups. Journal of Business Research, 139, 1188-1200.
Search via ReFindit
Volti, R. and Croissant, J., 2024. Society and technological change. Waveland Press.
Search via ReFindit
Von Briel, F., Davidsson, P., & Recker, J. 2018. Digital technologies as external enablers of new venture creation in the IT hardware sector. Entrepreneurship Theory and Practice, 42(1), 47-69. https://doi.org/10.1177/1042258717732779
Search via ReFindit