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Can Governance be Intelligent?

An Interdisciplinary Approach and Evolutionary Modelling for Intelligent Governance in the Digital Age

Published online by Cambridge University Press:  14 May 2024

Eran Vigoda-Gadot
University of Haifa


Intelligence is a concept that occurs in multiple contexts and has various meanings. It refers to the ability of human beings and other entities to think and understand the world around us. It represents a set of skills directed at problem-solving and targeted at producing effective results. Thus, intelligence and governance are an odd couple. We expect governments and other governing institutions to operate in an intelligent manner, but too frequently we criticize their understanding of serious public problems, their decisions, behaviors, managerial skills, ability to solve urgent problems, and overall governability wisdom. This manuscript deals with such questions using interdisciplinary insights (i.e., psychological, social, institutional, biological, technological) on intelligence and integrating it with knowledge in governance, administration, and management in public and non-profit sectors. We propose the IntelliGov framework, that may extend both our theoretical, methodological, analytical, and applied understanding of intelligent governance in the digital age.
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Online ISBN: 9781009437783
Publisher: Cambridge University Press
Print publication: 06 June 2024

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Adams, N. B. (2004). Digital intelligence fostered by technology. Journal of Technology Studies, 30, 9397.CrossRefGoogle Scholar
Adler-Nissen, R., and Drieschova, A. (2019). Track-change diplomacy: Technology, affordances, and the practice of international negotiations. International Studies Quarterly, 63, 531545.CrossRefGoogle Scholar
Aghaei, S., Nematbakhsh, M., and Farsan, H. (2012). Evolution of the world wide web: From web 1.0 to Web 4.0. International Journal of Web and Semantic Technology, 3, 110.CrossRefGoogle Scholar
Apperly, I. A., and Butterfill, S. A. (2009). Do humans have two systems to track beliefs and belief-like states? Psychological Review, 116, 953970.CrossRefGoogle ScholarPubMed
Asgarkhani, A. (2007). Digital government and its effectiveness in public management reforms: A local government perspective. Public Management Review, 7, 465487.CrossRefGoogle Scholar
Awan, U., Sroufe, R., and Shahbaz, M. (2021). Industry 4.0 and the circular economy: A literature review and recommendations for future research. Business Strategy and the Environment, 30, 20382060.CrossRefGoogle Scholar
Baron-Cohen, S. (1991). Precursors to a theory of mind: Understanding attention in others. In Whiten, A. (ed.), Natural Theories of Mind: Evolution, Development, and Simulation of Everyday Mindreading (pp. 233251). Cambridge, MA: B. Blackwell.Google Scholar
Bastida, F., Estrada, L., and Nurunnabi, M. (2021). Empirical determinants of corruption in Honduran municipalities. Public Integrity, 24(7), 629643. Scholar
Berman, E. M., and West, J. P. (2008). Managing Emotional Intelligence In US Cities: A Study Of Social Skills Among Public Managers. Public Administration Review, 68(4), 742758.CrossRefGoogle Scholar
Binet, A. (1916a) [1905]. New methods for the diagnosis of the intellectual level of subnormals. In Kite, E. S. (trans.), The Development of Intelligence in Children: The Binet-Simon Scale (pp. 3790). Baltimore: Williams & Wilkins.Google Scholar
Binet., A., and Simon, T. (1916). The Development of Intelligence in Children. Baltimore: Williams & Wilkins. (Reprinted 1973, New York: Arno Press; 1983, Salem, NH: Ayer Company).Google Scholar
Bloom, H. 2000. Global Brain: The Evolution of Mass Mind From the Big Bang to the 21st Century. John Wiley & Sons, NeGoogle Scholar
Brunetto, Y., Teo, S. T., Shacklock, K., and Wharton, R. F. (2012). Emotional Intelligence, Job Satisfaction, Well-Being And Engagement: Explaining Organisational Commitment And Turnover Intentions In Policing. Human Resource Management Journal, 22(4), 428441.CrossRefGoogle Scholar
Bullock, J. B. (2019). Artificial Intelligence, Discretion, and Bureaucracy. The American Review of Public Administration, 49(7), 751761.CrossRefGoogle Scholar
Carrigan, C., and Coglianese, C. (2011). The politics of regulation: From new institutionalism to new governance. Annual Review of Political Science, 14, 107129.CrossRefGoogle Scholar
Cheng, Y., Yu, J., Shen, Y., and Huang, B. (2020). Coproducing responses to COVID-19 with community-based organizations: Lessons from Zhejiang province, China. Public Administration Review, 80, 866873.CrossRefGoogle ScholarPubMed
Choo, C. W. (1998). The Knowing Organization: How Organizations Use Information to Construct Meaning, Create Knowledge, and Make Decisions. Oxford: Oxford University Press.Google Scholar
Ciarrochi, J., Forgas, J. P., and Mayer, J. D. (2001). Emotional Intelligence In Everyday Life: A Scientific Inquiry. New York, NY: Psychology Press.Google Scholar
Clark, N., and Albris, K. (2020). In the Interest(s) of Many: Governing Data in Crises. Politics and Governance, 8(4), 421431.CrossRefGoogle Scholar
Coglianese, C., and Lehr, D. (2017). Regulating by robot: Administrative decision making in the machine-learning era. Georgetown Law Journal, 105, 11471223.Google Scholar
Considine, M., Mcgann, M., Ball, S., and Nguyen, P. (2022). Can robots understand welfare? Exploring machine bureaucracies in welfare-to-work. Journal of Social Policy, 51, 519534.CrossRefGoogle Scholar
Coren, S. (1995). The Intelligence of Dogs. New York: Bantam Books.Google Scholar
Criado, J. I., and Villodre, J. (2021). Delivering public services through social media in European local governments: An interpretative framework using semantic algorithms. Local Government Studies, 47, 253275.CrossRefGoogle Scholar
Crozier, M. (2008). Listening, learning, steering: New governance, communication and interactive policy formation. Policy & Politics, 36, 319.CrossRefGoogle Scholar
Cukurova, M., Luckin, R., and Kent, C. (2020). Impact of an artificial intelligence research frame on the perceived credibility of educational research evidence. International Journal of Artificial Intelligence in Education, 30, 205235.CrossRefGoogle Scholar
Detterman, D. K., and Sternberg, R. J. (eds.) (1982). How and How Much Can Intelligence Be Increased? Mahwah: Erlbaum.Google Scholar
de Sousa, W. G., de Melo, E. R. P., De Souza Bermejo, P. H., Farias, R. A. S., and Gomes, A. O. (2019). How and where is artificial intelligence in the public sector going? A literature review and research agenda. Government Information Quarterly, 36, 101392.CrossRefGoogle Scholar
Dunleavy, P., Margetts, H., Bastow, S., and Tinkler, J. (2005). New public management is dead. Long live digital-era governance. Journal of Public Administration Research and Theory, 16, 467494.CrossRefGoogle Scholar
Dunleavy, P., Margetts, H., Dunleavy, P., Bastow, S., and Tinkler, J. (2008). Digital Era Governance: IT Corporations, the State, and E-government. Oxford: Oxford University Press.Google Scholar
Eshuis, J., de Boer, N., and Klijn, E. H. (2023). Street-level bureaucrats’ emotional intelligence and its relation with their performance. Public Administration, 101(3), 804821. Scholar
Gahan, P. (2007). The politics of partnership. In Pittard, M. and Weeks, P. (eds.), Public Sector Employment in the Twenty-first Century (pp. 229254). Canberra: ANU.Google Scholar
Gardner, H. (1983). Frames of Mind: The Theory of Multiple Intelligences. New York: Basic Books.Google Scholar
Giest, S. (2017). Big data for policymaking: Fad or fast track? Policy Sciences, 50, 367382.CrossRefGoogle Scholar
Gilad, B., and Gilad, T. (1986). SMR forum: Business intelligence. The quiet revolution. Sloan Management Review, 27, 5361.Google Scholar
Gil-Garcia, J. R., Dawes, S. S., and Pardo, T. A. (2017). Digital government and public management research: Finding the crossroads. Public Management Review, 17, 633646.Google Scholar
Glikson, E., and Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Annals, 14, 627660.CrossRefGoogle Scholar
Glynn, M. A. (1996). Innovative genius: A framework for relating individual intelligences to innovation. The Academy of Management Review, 21(4), 10811111.CrossRefGoogle Scholar
Goleman, D. (2006). Social Intelligence: The New Science of Human Relationships. New York: Bantam Books.Google Scholar
Gomez, M. A., and Whyte, C. (2021). Breaking the myth of cyber doom: Securitization and normalization of novel threats. International Studies Quarterly, 65, 11371150.CrossRefGoogle Scholar
Gonçalves, A. G., Kolski, C., de Oliveira, K. M., Travassos, G. H., and Grislin-Le Strugeon, E. (2019). A systematic literature review on intelligent user interfaces: Preliminary results. In Adjunct Proceedings of the 31st Conference on l’Interaction Homme-Machine (IHM ‘19 Adjunct) (pp. 1-8). New York: Association for Computing Machinery, Article 5.Google Scholar
Gottfredson, L. S. (1997). Mainstream science on intelligence (editorial). Intelligence, 24, 1323.CrossRefGoogle Scholar
Gottfredson, L. S. (1998). The general intelligence factor. Scientific American Presents, 9, 2429.Google Scholar
Grimmelikhuijsen, S., Jilke, S., Olsen, A. L., and Tummers, L. (2017). Behavioural public administration: Combining insights from public administration and psychology. Public Administration Review, 77, 4556.CrossRefGoogle Scholar
Grossi, G., Meijer, A., and Sargiacomo, M. (2020). A public management perspective on smart cities: “Urban auditing” for management, governance and accountability. Public Management Review, 22, 633647.CrossRefGoogle Scholar
Guy, M. E., and Lee, H. J. (2015). How Emotional Intelligence Mediates Emotional Labor In Public Service Jobs. Review Of Public Personnel Administration, 35(3), 261277.CrossRefGoogle Scholar
Guy, M. E., Newman, M. A., and Mastracci, S. H. (2008). Emotional Labor: Putting The Service In Public Service. Armonk, NY: M.E. Sharpe, Inc.Google Scholar
Hancock, P.A, & Chignell, M.H. (Eds.). (1989). Intelligent Interfaces: Theory, research, and design. Amsterdam: North-HollandGoogle Scholar
Heath, S. B. (1983). Ways with words. New York: Cambridge University PressCrossRefGoogle Scholar
Hedlund, J. (2020). Practical intelligence. In Sternberg, R. (ed.), The Cambridge Handbook of Intelligence (Cambridge Handbooks in Psychology, pp. 736755). Cambridge: Cambridge University Press.Google Scholar
Henman, P. (2020) Improving public services using artificial intelligence: possibilities, pitfalls, governance. Asia Pacific Journal of Public Administration, 42(4), 209221.CrossRefGoogle Scholar
Hsieh, C. W. (2009). Emotional Labor In Public Service Roles: A Model Of Dramaturgical And Dispositional Approaches (Doctoral Dissertation). The Florida State University.Google Scholar
Herrnstein, R. J., and Murray, C. (1994). The Bell Curve: Intelligence and Class Structure in American Life. New York: Free Press.Google Scholar
Horowitz, M. C. (2020). Do emerging military technologies matter for international politics? Annual Review of Political Science, 23, 385400.CrossRefGoogle Scholar
Hudson‐Smith, A. (2022). Incoming metaverses: Digital mirrors for urban planning. Urban Planning, 7, 343354.CrossRefGoogle Scholar
Hunt, T. (1928). The measurement of social intelligence. Journal of Applied Psychology, 12, 317334.CrossRefGoogle Scholar
Hunt, J. O. S., Rosser, D. M., and Rowe, S. P. (2021). Using machine learning to predict auditor switches: How the likelihood of switching affects audit quality among non-switching clients. Journal of Accounting and Public Policy, 40, 117. Scholar
Jaquero, L., Montero, F., Molina, J. P., and Gonzalez, P. (2009). Intelligent user interfaces: Past, present and future. In Miguel, R., Crescencio, B., and Manuel, O. (eds.), Engineering the User Interface (pp. 112). London: Springer.Google Scholar
Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., and Janowski, T. (2020). Data governance: Organizing data for trustworthy Artificial Intelligence. Government Information Quarterly, 37, 18.CrossRefGoogle Scholar
Joseph, D. L., and Newman, D. A. (2010). Emotional Intelligence: An Integrative Meta-Analysis And Cascading Model. Journal Of Applied Psychology, 95(1), 5478.CrossRefGoogle ScholarPubMed
Katsonis, M., and Botros, A. (2015). Digital government: A primer and professional perspectives. Australian Journal of Public Administration, 74, 4252.CrossRefGoogle Scholar
Kaufmann, W., and Lafarre, A. (2021). Does good governance mean better corporate social performance? A comparative study of OECD countries. International Public Management Journal, 24, 762791.CrossRefGoogle Scholar
Kinn Abass, B. (2021). Culture and digital divide influence on e-government success of developing countries: A literature review. Journal of Theoretical and Applied Information Technology, 98, 13621378.Google Scholar
Kittur, A., Lee, B., and Kraut, R. E. (2009). Coordination in collective intelligence: The role of team structure and task interdependence. In CHI 2009: Proceedings of the ACM 27th International Conference on Human Factors in Computing Systems (pp. 14951504). New York: ACM Press.Google Scholar
Kohler, W. (1925). The Mentality of Apes. E. Winter (trans.), 2nd ed. London: Kegan Paul, Trench, Trubner. U.S. edition 1925 by Harcourt: Brace & World.Google Scholar
Kolski, C., and Le Strugeon, E. (1998). A review of intelligent human-machine interfaces in the light of the ARCH Model. International Journal of Human–Computer Interaction, 10, 193231.CrossRefGoogle Scholar
Kotzé, M., and Venter, I. (2011). Differences in emotional intelligence between effective and ineffective leaders in the public sector: An empirical study. International Review of Administrative Sciences, 77, 397427.CrossRefGoogle Scholar
Kristof, K., Andrew, R. A., and Conway, A. (2019). Unified cognitive/differential approach to human intelligence: Implications for IQ Testing. Journal of Applied Research in Memory and Cognition, 8, 255272.Google Scholar
Kumar, S., Raut, R. D., Queiroz, M. M., and Narkhede, B. E. (2021). Mapping the barriers of AI implementations in the public distribution system: The Indian experience. Technology in Society, 67, 19. Scholar
Lavee, E., Cohen, N., Nouman, H. (2018). Reinforcing public responsibility? Influences and practices in street-level bureaucrats’ engagement in policy design. Public Administration, 96, 333348.CrossRefGoogle Scholar
Law, K. S., Wong, C. S., and Song, L. J. (2004). The construct and criterion validity of emotional intelligence and its potential utility for management studies. Journal of Applied Psychology, 89(3), 483496.CrossRefGoogle ScholarPubMed
Legg, S., and Hutter, M. H. (2007a). A collection of definitions of intelligence. Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms, 157, 1724.Google Scholar
Legg, S., and Hutter, M. H. (2007b). Universal intelligence: A definition of machine intelligence. Minds and Machines, 17, 391444.CrossRefGoogle Scholar
Levitats, Z., and Vigoda-Gadot, E. (2017). Yours, emotionally: How emotions infuse motivation for public service and job outcomes of public personnel. Public Administration, 95, 759775.CrossRefGoogle Scholar
Levitats, Z., and Vigoda-Gadot, E. (2020). Emotionally engaged civil servants: Towards a multi-level theory and multi-source analysis in public administration. Review of Public Personnel Administration, 40, 426446.CrossRefGoogle Scholar
Levitats, Z., Vigoda-Gadot, E., and Vashdi, R. D. (2019). Engage them through emotions: Exploring the role of emotional intelligence in public-sector engagement. Public Administration Review, 79, 841852.CrossRefGoogle Scholar
Liva, G., Codagnone, C., Misuraca, G., Gineikyte, V., and Barcevicius, E. (2020). Exploring digital government transformation: A literature review. Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance (ICEGOV 2020). New York. 502509.CrossRefGoogle Scholar
Lynn, L. E. (1996). Public Management. New Jersey: Chatham House.Google Scholar
March, J. (1999). The Pursuit of Organizational Intelligence. Oxford: Blackwell.Google Scholar
March, J. G., and Olsen, J. P. (1984). The new institutionalism: Organizational factors in political life. American Political Science Review, 78, 734749.CrossRefGoogle Scholar
Mayer, J. D., and Salovey, P. (1997). What Is Emotional Intelligence? In Salovey, P. and Sluyter, D. (eds.), Emotional Development And Emotional Intelligence: Implications For Educators (pp. 331). New York: Basic Books.Google Scholar
McManus, S., Seville, E., Vargo, J., and Brunsdon, D. (2008). Facilitated process for improving organizational resilience. Natural Hazards Review, 9, 8190.CrossRefGoogle Scholar
McMaster, M. D. (1996). The Intelligence Advantage: Organizing for Complexity. Newton: Butterworth‐Heinemann.Google Scholar
McMullin, C. (2021). Challenging the necessity of new public governance: Co-production by third sector organizations under different models of public management. Public Administration, 99, 522.CrossRefGoogle Scholar
Meijer, A., and Bolívar, M. P. R. (2016). Governing the smart city: A review of the literature on smart urban governance. International Review of Administrative Sciences, 82, 392408.CrossRefGoogle Scholar
Mikalef, P., Lemmer, K., Schaefer, C., et al. (2022). Enabling AI capabilities in government agencies: A study of determinants for European municipalities. Government Information Quarterly, 39(4). Scholar
Mizrahi, S., Vigoda-Gadot, E., and Cohen, N. (2021). How well do they manage a crisis? The government’s effectiveness during the COVID-19 Pandemic. Public Administration Review, 81, 11201130.CrossRefGoogle Scholar
Moore, S. (2019). Digital government, public participation and service transformation: The impact of virtual courts. Policy & Politics, 47, 495509.CrossRefGoogle Scholar
Muniesa, F. (2007). Market technologies and the pragmatics of prices. Economy and Society, 36, 377395.CrossRefGoogle Scholar
Munoz, J. M. (2018). Global Business Intelligence. New York: Routledge.Google Scholar
Muntean, M., Cabău, L.G., and Rînciog, V. (2014). Social business intelligence: A new perspective for decision makers. Procedia – Social and Behavioral Sciences, 124, 562567.CrossRefGoogle Scholar
Neisser, U., Boodoo, G., Bouchard, T. J. et al. (1996). Intelligence: Knowns and unknowns. American Psychologist, 51, 77101.CrossRefGoogle Scholar
OECD (2003). The E-government Imperative. Paris: OECD.Google Scholar
OECD (2009). Rethinking E-government Services: User Centred Approaches. Paris: OECD.Google Scholar
OECD (2014). Recommendation of the Council on Digital Government Strategies. Paris: OECD.Google Scholar
OECD (2020). Digital Government Index: 2019 results, OECD Public Governance Policy Papers, No. 03, Paris: OECD.Google Scholar
O’Reilly, T. (2005). What is Web 2.0? (last accessed March 28, 2023).Google Scholar
Osborne, D., and Gaebler, T. (1992). Reinventing Government. New York: Plume.Google Scholar
O’Shaughnessy, M. R., Schiff, D. S., Varshney, L. R., Rozell, C. J., and Davenport, M. A. (2022). What governs attitudes toward artificial intelligence adoption and governance? Science and Public Policy, 50(2), 161176. Scholar
Ostrom, E. (1990). Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Ott, D. L., and Michailova, S. (2018). Cultural intelligence: A review and new research avenues. International Journal of Management Reviews, 20, 99119.CrossRefGoogle Scholar
Panch, T., Pearson-Stuttard, J., Greaves, F., and Atun, R. (2019). Artificial intelligence: Opportunities and risks for public health. The Lancet Digital Health, 1, e13e14.CrossRefGoogle ScholarPubMed
Park, Y. J., and Jones-Jang, S. M. (2022). Surveillance, security, and AI as technological acceptance. AI & Society, 38, 26672678. Scholar
Pereira, G.V., Parycek, P., Falco, E., and Kleinhans, R. (2018). Smart governance in the context of smart cities: A literature review. Information Polity, 23, 143162CrossRefGoogle Scholar
Piaget, J. (1972). The Psychology of Intelligence. Totowa: Littlefield Adams.Google Scholar
Raadschelders, J., and Vigoda-Gadot, E. (2015). Global Dimensions of Public Administration and Governance: A Comparative Voyage. California: Jossey-Bass.Google Scholar
Radu, R. (2021). Steering the governance of artificial intelligence: National strategies in perspective. Policy & Society, 40, 178193.CrossRefGoogle Scholar
Ramsden, S., Richardson, F. M., Josse, G. et al. (2011). Verbal and non-verbal intelligence changes in the teenage brain. Nature, 479, 113116.CrossRefGoogle ScholarPubMed
Rauhaus, B. M. (2022). Public service motivation of street-level bureaucrats amidst the COVID-19 pandemic: An analysis of experiences in implementation of an at-home vaccination program. State and Local Government Review, 54, 8291.CrossRefGoogle Scholar
Rensing, L., Koch, M., and Becker, A. (2009). A comparative approach to the principal mechanisms of different memory systems. Naturwissenschaften, 96, 13731384.CrossRefGoogle Scholar
Roberts, J. A., and David, M. E. (2020). The social media party: Fear of missing out (FoMO), social media intensity, connection, and well-being. International Journal of Human-Computer Interaction, 36(4), 386392.CrossRefGoogle Scholar
Rona-Tas, A. (2020). Predicting the future: Art and algorithms. Socio-Economic Review, 18, 893911.CrossRefGoogle Scholar
Ross, E. (2000). Intelligent User Interfaces: Survey and Research Directions. Bristol: University of Bristol.Google Scholar
Rotberg, R. I. (2014). Good governance measures. Governance, 27, 511518.CrossRefGoogle Scholar
Roth, G. (2015). Convergent evolution of complex brains and high intelligence. Philosophical Transactions of the Royal Society of London B, Biological Sciences, 370(1684), 19.Google ScholarPubMed
Saghiri, A. M., Vahidipour, S. M., Jabbarpour, M. R., Sookhak, M., and Forestiero, A. (2022). A survey of artificial intelligence challenges: Analyzing the definitions, relationships, and evolutions. Applied Sciences, 12, 4054. Scholar
Salovey, P., and Mayer, J. D. (1990). Emotional Intelligence. Imagination, Cognition and Personality, 9, 185211.CrossRefGoogle Scholar
Sanchez, C., Cedillo, P., and Bermeo, A. (2017). A systematic mapping study for intelligent user interfaces – IUI. Proceedings of the International Conference on Information Systems and Computer Science (INCISCOS), 361368.CrossRefGoogle Scholar
Schuller, B. W. (2015). Modelling user affect and sentiment in intelligent user interfaces: A tutorial overview. In Proceedings of the 20th International Conference on Intelligent User Interfaces (IUI 15), 443446. New York: Association for Computing Machinery.Google Scholar
Shen, Y., Cheng, D. Y., and Yu, J. (2023). From recovery resilience to transformative resilience: How digital platforms reshape public service provision during and post COVID-19. Public Management Review, 25(4), 710733. Scholar
Simonton, D. K. (2012). Quantifying creativity: Can measures span the spectrum? Dialogues in Clinical Neuroscience, 14, 100104.CrossRefGoogle ScholarPubMed
Singh, H. P., and Kumar, P. (2021). Developments in the human machine interface technologies and their applications: A review. Journal of Medical Engineering & Technology, 45, 552573. ScholarPubMed
Smith, G. T. (2017). Institutional Intelligence: How to Build an Effective Organization. Downers Grove, Il; IVP AcademicGoogle Scholar
Stern, W. (1914). The psychological methods of testing intelligence. Whipple, G. M. (trans.), Educational Psychology Monographs, 13. Baltimore: Warwick & York.Google Scholar
Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. Cambridge University Press.Google Scholar
Sternberg, R. J. (2020). Rethinking what we mean by intelligence. Phi Delta Kappan, 102(3), 3641.CrossRefGoogle Scholar
Sternberg, R. J., and Detterman, D. K (eds.). (1986). What is intelligence? Contemporary viewpoints on its nature and definition. Norwood, NJ: Ablex.Google Scholar
Sternberg, R. J. (1989). The Triarchic Mind: A New Theory of Human Intelligence. Westminster: Penguin Books.Google Scholar
Sternberg, R. J., and Salter, W. (1982). Handbook of Human Intelligence. Cambridge: Cambridge University Press.Google Scholar
Sorrentino, M., Sicilia, M., and Howlett, M. (2018). Understanding co-production as a new public governance tool. Policy & Society, 37, 277293.CrossRefGoogle Scholar
Taeihagh, A. (2021). Governance of artificial intelligence. Policy and Society, 40(2), 137157,CrossRefGoogle Scholar
Talaoui, Y., and Kohtamäki, M. (2021). 35 years of research on business intelligence process: A synthesis of a fragmented literature. Management Research Review, 44, 677717.CrossRefGoogle Scholar
Terman, L. M., and Merrill, M. A. (1937). Measuring Intelligence: A Guide to the Administration of the new Revised Stanford-Binet tests of Intelligence. Boston: Houghton Mifflin.Google Scholar
Torfing, J., Ferlie, E., Jukić, T., and, Ongaro, E. (2021). A theoretical framework for studying the co-creation of innovative solutions and public value. Policy & Politics, 49, 189209.CrossRefGoogle Scholar
Trewavas, A. (2005). Green plants as intelligent organisms. Trends in Plant Science, 10, 413419.CrossRefGoogle ScholarPubMed
Tsoukas, H. (2005). Complex Knowledge: Studies in Organizational Epistemology. Oxford: Oxford University Press.Google Scholar
Victorian Government (2010). Government 2.0 Action Plan. Melbourne: Department of Premier and Cabinet.Google Scholar
Vigoda-Gadot, E. (2002). From responsiveness to collaboration: Governance, citizens, and the next generation of public administration. Public Administration Review, 62, 515528.Google Scholar
Vigoda-Gadot, E. (2007). Citizens’ perceptions of organizational politics and ethics in public administration: A five-year study of their relationship to satisfaction with services, trust in governance, and voice orientations. Journal of Public Administration Research & Theory, 17, 285305.CrossRefGoogle Scholar
Vigoda-Gadot, E., (2009). Building Strong Nations: Improving Governability and Public Management. Farnham: Ashgate.Google Scholar
Vigoda-Gadot, E., and Meisler, G. (2010). Emotions in management and the management of emotions: The impact of emotional intelligence and organizational politics on public sector employees. Public Administration Review, 70, 7286.CrossRefGoogle Scholar
Vigoda-Gadot, E., and Mizrahi, S. (2014). Managing Democracies in Turbulent Times: Trust and Citizens’ Participation as a Road to Better Governance. Berlin: Springer.CrossRefGoogle Scholar
Vigoda-Gadot, E., and Vashdi, R. D. (eds.) (2020). Handbook of Research Methods in Public Administration, Management and Policy. Cheltenham: Edward Elgar.CrossRefGoogle Scholar
Vigoda-Gadot, E., Schohat, l., and Eldor, L. (2013). Engage them to public service: Conceptualization and empirical examination of employee engagement in public administration. American Review of Public Administration, 43, 516537.CrossRefGoogle Scholar
Vigoda-Gadot, E., Cohen, N., and Mizrahi, S. (2023a). Battling COVID-19: How good public management relates with resilience and trust among healthcare employees during a global crisis. Review of Public Personnel Administration, 43(3), 583613. Scholar
Vigoda-Gadot, E., Mizrahi, S., Cohen, N., and Mishor, E. (2023b). Citizens’ reactions to global crises: A longitudinal study during the COVID-19 pandemic in Israel. Springer Nature (SN) Social Sciences, 3(2), 24. ScholarPubMed
Virtanen, P., and Vakkuri, J. (2016). Searching for organizational intelligence in the evolution of public-sector performance management. Journal of Public Administration and Policy, 8, 8999.Google Scholar
Vygotsky, L. S. (1978). Mind in Society: The Development of High Psychological Processes. Cambridge, MA: Harvard University Press.Google Scholar
Wahlsten, D. (2002). The theory of biological intelligence: History and a critical appraisal. In Sternberg, R. J. and Grigorenko, E. L. (eds.), The General Factor of Intelligence: How General is it? (pp. 245277). Mahwah: Lawrence Erlbaum Associates.Google Scholar
Wang, G., Xie, S., and Li, X. (2024). Artificial intelligence, types of decisions, and street-level bureaucrats: Evidence from a survey experiment. Public Management Review, 26(1), 162184.CrossRefGoogle Scholar
Wasserman, J. D. (2018). A history of intelligence assessment: The unfinished tapestry. In Flanagan, D. P. and McDonough, E. M. (eds.), Contemporary Intellectual Assessment: Theories, Tests, and Issues (pp. 355). New York: The Guilford Press.Google Scholar
Wechsler, D. (1944). The Measurement of Adult Intelligence. Baltimore: Williams & Wilkin.Google Scholar
Wilensky, H. L. (1967). Organizational Intelligence; Knowledge and Policy in Government and Industry. New York: Basic Books.Google Scholar
Wirtz, B. W., Weyerer, J. C., and Geyer, C. (2019). Artificial intelligence and the public sector-applications and challenges. International Journal of Public Administration, 42, 596615.CrossRefGoogle Scholar
Wong, Chi-Sum, and Law, Kenneth S.. (2002). The effects of leader and follower emotional intelligence on performance and attitude: An exploratory study. The Leadership Quarterly, 13(3), 243274.CrossRefGoogle Scholar
Woolley, A. W. (2011). Responses to adversarial situations and collective intelligence. Journal of Organizational Behavior, 32, 978983.CrossRefGoogle Scholar
Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., and Malone, T. (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330, 686688.CrossRefGoogle ScholarPubMed
Wyld, D. C. (2010). A Second Life for organizations?: managing in the new, virtual world. Management Research Review, 33(6), 529562.CrossRefGoogle Scholar
Young, M. M., Bullock, J. B., and Lecy, J. D. (2019). Artificial Discretion as a Tool of Governance: A Framework for Understanding the Impact of Artificial Intelligence on Public Administration. Perspectives on Public Management and Governance, 2(4), 301313.Google Scholar
Young, S. L., Wiley, K. K., and Searing, E. A. M. (2020). Squandered in real time: How public management theory underestimated the public administration-politics dichotomy. American Review of Public Administration, 50, 480488.CrossRefGoogle Scholar

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