Abstract
What is the path to smarter cities that can make data-driven decisions? In a context where data have been vastly advertised as a solution to many problems, the application of big data analytics (BDA) in government is a trending topic. As a topic and potential strategy, data is on the agenda of researchers and policy-makers worldwide, based on the hope that the use of data and technology could enable better quality of life in communities and cities. This chapter analyzes the potential of BDA for local governments, particularly in the context of smart city initiatives. The chapter also proposes an integrative framework to better understand all the components of these concepts and their interrelationships. The overall goal is to discuss what it means to cities to use data in practice, what challenges could be anticipated, and how some of those challenges could be mitigated. This will also contribute to a better explanation of the role of information sharing, integration, and collaboration in BDA and its potential to generate public value in smart city initiatives.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abbasi, A., Sarker, S., & Chiang, R. H. (2016). Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17, 3.
Abella, A., Ortiz-de-Urbina-Criado, M., & De-Pablos-Heredero, C. (2017). A model for the analysis of data-driven innovation and value generation in smart cities’ ecosystems. Cities, 64, 47–53.
Abukhousa, E., & Atif, Y. (2015). Big learning data analytics support for engineering career readiness. In 2014 International Conference on Interactive Collaborative Learning (ICL) (pp. 663–668). Piscataway, NJ: IEEE.
Acebo, A., Franks, B., Leonard, T., Manthey, K., & Burgess, M. (2012). BI experts’ perspective: Attracting analytics talent. Business Intelligence Journal, 17, 21–27.
Agranoff, R., & McGuire, M. (2003). Inside the matrix: Integrating the paradigms of intergovernmental and network management. International Journal of Public Administration, 26, 1401–1422.
Ajabi, M., Boukhris, I., & Elouedi, Z. (2016). Big data classification using belief decision trees: Application to intrusion detection. In The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28–30, 2015 (pp. 369–379). Beni Suef, Egypt: Springer.
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113–131.
Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban Technology, 22, 3–21.
Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: Why HR is set to fail the big data challenge. Human Resource Management Journal, 26, 1–11.
Anttiroiko, A.-V., Valkama, P., & Bailey, S. J. (2014). Smart cities in the new service economy: Building platforms for smart services. AI & Society, 29(3), 323–334.
Asal, V., Mauslein, J., Murdie, A., Young, J., Cousins, K., & Bronk, C. (2016). Repression, education, and politically motivated cyberattacks. Journal of Global Security Studies, 1, 235–247.
Baekgaard, M., & Serritzlew, S. (2016). Interpreting performance information: Motivated reasoning or unbiased comprehension. Public Administration Review, 76, 73–82.
Bardach, E. (1998). Getting agencies to work together: The practice and theory of managerial craftsmanship. Washington, DC: Brookings Institution Press.
Bassi, A. M., Deenapanray, P. S., & al Davidsen, P. (2013). Energy policy planning for climate-resilient low-carbon development. In Energy policy modeling in the 21st century (pp. 125–156). New York: Springer.
Bătăgan, L. (2011). Smart cities and sustainability models. Informatica Economică, 15, 80–87.
Benington, J., & Moore, M. H. (2010). Public value: Theory and practice. Basingstoke, UK: Palgrave Macmillan.
Berman, J. J. (2013). Principles of big data: Preparing, sharing, and analyzing complex information. San Francisco, CA: Morgan Kaufmann Publishers.
Bernardino, S., & Santos, J. F. (2017). Building smarter cities through social entrepreneurship. In Handbook of research on entrepreneurial development and innovation within smart cities (pp. 327–362). Hershey, PA: IGI Global.
Bharosa, N., Lee, J., & Janssen, M. (2010). Challenges and obstacles in sharing and coordinating information during multi-agency disaster response: Propositions from field exercises. Information Systems Frontiers, 12, 49–65.
Borgman, C. L. (2000). From Gutenberg to the global information infrastructure: Access to information in the networked world. Cambridge, UK: MIT Press.
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15, 662–679.
Brown, G., de Bie, K., & Weber, D. (2015). Identifying public land stakeholder perspectives for implementing place-based land management. Landscape and Urban Planning, 139, 1–15.
Brown, J. S., & Duguid, P. (2000). The social life of information. Boston, MA: Harvard Business Press.
Bryson, J., Sancino, A., Benington, J., & Sørensen, E. (2016). Towards a multi-actor theory of public value co-creation. Public Management Review, 19, 1–15.
Bryson, J. M. (2004). What to do when stakeholders matter: Stakeholder identification and analysis techniques. Public Management Review, 6, 21–53.
Bhatia, A., & Vaswani, G. (2013). Big data-a review. IEEE International Journal of Engineering Sciences & Research Technology IJESRT.
Chang, V., Ramachandran, M., Wills, G., Walters, R. J., Li, C.-S., & Watters, P. (2016). Editorial for FGCS special issue: Big data in the cloud. Future Generation Computer Systems, 65, 73–75.
Chatfield, A. T., & Reddick, C. G. (2017). Customer agility and responsiveness through big data analytics for public value creation: A case study of Houston 311 on-demand services. Government Information Quarterly, 35(2), 336–347.
Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19, 171–209.
Chen, Y.-C., & Hsieh, T.-C. (2016). Big data for digital government: Opportunities, challenges, and strategies. In Politics and social activism: Concepts, methodologies, tools, and applications (pp. 1394–1407). Hershey, PA: IGI Global.
Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J. R., Mellouli, S., Nahon, K., … Scholl, H. J. (2012). Understanding smart cities: An integrative framework. In 2012 45th Hawaii International Conference on System Science (HICSS) (pp. 2289–2297). Piscataway, NJ: IEEE.
Cocchia, A., & Dameri, R. P. (2016). Exploring smart city vision by university, industry and government. In Blurring the boundaries through digital innovation (pp. 259–270). Cham, Switzerland: Springer.
Connelly, R., Playford, C. J., Gayle, V., & Dibben, C. (2016). The role of administrative data in the big data revolution in social science research. Social Science Research, 59, 1–12.
Cordella, A., & Paletti, A. (2017). Value creation, ICT, and co-production in public sector: Bureaucracy, opensourcing and crowdsourcing. In Proceedings of the 18th Annual International Conference on Digital Government Research (pp. 185–194). New York: ACM.
Costa, G. B., Huber, M. R., & Saccoman, J. T. (2007). Understanding sabermetrics: An introduction to the science of baseball statistics. Jefferson, NC: McFarland.
Cristofoli, D., Meneguzzo, M., & Riccucci, N. (2017). Collaborative administration: The management of successful networks. Public Management Review, 19, 275–283.
Crosby, B. C., ‘t Hart, P., & Torfing, J. (2017). Public value creation through collaborative innovation. Public Management Review, 19, 655–669.
Curry, E. (2016). The big data value chain: Definitions, concepts, and theoretical approaches. In J. M. Cavanillas, E. Curry, & W. Wahlster (Eds.), New horizons for a data-driven economy (pp. 29–37). Cham, Switzerland: Springer International Publishing.
Curwell, S., Deakin, M., Cooper, I., Paskaleva-Shapira, K., Ravetz, J., & Babicki, D. (2005). Citizens’ expectations of information cities: Implications for urban planning and design. Building Research and Information, 33, 55–66.
Dahl, A., & Soss, J. (2014). Neoliberalism for the common good? Public value governance and the downsizing of democracy. Public Administration Review, 74, 496–504.
Daley, D. M. (2009). Interdisciplinary problems and agency boundaries: Exploring effective cross-agency collaboration. Journal of Public Administration Research and Theory, 19, 477–493.
Dameri, R. P., & Rosenthal-Sabroux, C. (2014). Smart city and value creation. In Smart city (pp. 1–12). Wiesbaden, Germany: Springer.
Davenport, T. H., Harris, J. G., Long, D. W. D., & Jacobson, A. L. (2001). Data to knowledge to results: Building an analytic capability. California Management Review, 43, 117–138.
Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston, MA: Harvard Business Press.
Dawes, S. S., Cresswell, A. M., & Pardo, T. A. (2009). From “need to know” to “need to share”: Tangled problems, information boundaries, and the building of public sector knowledge networks. Public Administration Review, 69, 392–402.
DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5, 121–147.
Desouza, K. C., & Jacob, B. (2017). Big data in the public sector: Lessons for practitioners and scholars. Administration and Society, 49(7), 1043–1064.
Dhar, V., & Stein, R. (1997). Seven methods for transforming corporate data into business intelligence. Cliffs, NJ: Prentice Hall Englewood.
Dremel, C., Overhage, S., Schlauderer, S., & Wulf, J. (2017). Towards a capability model for big data analytics (pp. 1141–1155). St. Gallen, Switzerland: Universität St.Gallen.
Eichbaum, C., & Lofgren, K. (2016). Big data and public service delivery - big hype? Public Sector, 39, 4.
Emerson, K., Nabatchi, T., & Balogh, S. (2012). An integrative framework for collaborative governance. Journal of Public Administration Research and Theory, 22, 1–29.
Erl, T., Khattak, W., & Buhler, P. (2016). Big data fundamentals: Concepts, drivers & techniques. Boston, MA: Prentice Hall Press.
Franks, B. (2012). Taming the big data tidal wave: Finding opportunities in huge data streams with advanced analytics. Hoboken, NJ: John Wiley & Sons.
Gagliardi, D., Schina, L., Sarcinella, M. L., Mangialardi, G., Niglia, F., & Corallo, A. (2017). Information and communication technologies and public participation: Interactive maps and value added for citizens. Government Information Quarterly, 34, 153–166.
Gamage, P. (2016). New development: Leveraging ‘big data’ analytics in the public sector. Public Money & Management, 36, 385–390.
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35, 137–144.
García, S., Ramírez-Gallego, S., Luengo, J., Benítez, J. M., & Herrera, F. (2016). Big data preprocessing: Methods and prospects. Big Data Analytics, 1, 9.
Gascó, M. (2003). New technologies and institutional change in public administration. Social Science Computer Review, 21, 6–14.
Gascó, M., Trivellato, B., & Cavenago, D. (2016). How do southern European cities foster innovation? Lessons from the experience of the smart city approaches of Barcelona and Milan. In Smarter as the new urban agenda (pp. 191–206). Cham, Switzerland: Springer.
Gasco-Hernandez, D. M. (2017). Is it more than using data and technology in local governments? Identifying opportunities and challenges for cities to become smarter. UMKC Law Review, 85, 915.
Giffinger, R., & Gudrun, H. (2010). Smart cities ranking: An effective instrument for the positioning of the cities? ACE: Architecture, City and Environment, 4, 7–26.
Gil-Garcia, J. R. (2012). Towards a smart state? Inter-agency collaboration, information integration, and beyond. Information Polity the International Journal of Government and Democracy in the Information Age, 17, 269–280.
Gil-Garcia, J. R., Chun, S., & Janssen, M. (2009). Government information sharing and integration: Combining the social and the technical. Information Polity, 14, 1–10.
Gil-Garcia, J. R., Helbig, N., & Ojo, A. (2014). Being smart: Emerging technologies and innovation in the public sector. Government Information Quarterly, 31, I1–I8.
Gil-Garcia, J. R., & Pardo, T. A. (2005). E-government success factors: Mapping practical tools to theoretical foundations. Government Information Quarterly, 22, 187–216.
Gil-Garcia, J. R., Pardo, T. A., & Luna-Reyes, L. F. (2018). Policy analytics: Definitions, components, methods, and illustrative examples. In Policy analytics, modelling, and informatics (pp. 1–16). Cham, Switzerland: Springer.
Gil-Garcia, J. R., & Sayogo, D. S. (2016). Government inter-organizational information sharing initiatives: Understanding the main determinants of success. Government Information Quarterly, 33(3), 572–582.
Gil-Garcia, J. R., Zhang, J., & Puron-Cid, G. (2016). Conceptualizing smartness in government: An integrative and multi-dimensional view. Government Information Quarterly, 33(3), 524–534.
Grabiner, D. (1994). The sabermetric manifesto. In The Baseball Archive.
Gray, B. (1989). Collaborating: Finding common ground for multiparty problems. San Francisco, CA: Jossey Bass.
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter, S. (2017). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308–317.
Gutiérrez, V., Theodoridis, E., Mylonas, G., Shi, F., Adeel, U., Diez, L., et al. (2016). Co-creating the cities of the future. Sensors, 16, 1–27.
Haarstad, H. (2016). Who is driving the ‘smart city’ agenda? Assessing smartness as a governance strategy for cities in Europe. In Services and the green economy (pp. 199–218). London: Palgrave Macmillan.
Harrison, C., Eckman, B., Hamilton, R., Hartswick, P., Kalagnanam, J., Paraszczak, J., & Williams, P. (2010). Foundations for smarter cities. IBM Journal of Research and Development, 54, 1–16.
Hashem, I. A. T., Chang, V., Anuar, N. B., Adewole, K., Yaqoob, I., Gani, A., … Chiroma, H. (2016). The role of big data in smart city. International Journal of Information Management, 36, 748–758.
Hawkins, C. V. (2011). Smart growth policy choice: A resource dependency and local governance explanation. Policy Studies Journal, 39, 679–707.
Heger, D. (2014). Big data analytics—‘Where to go from here’. International Journal of Developments in Big Data and Analytics, 1, 42–58.
Henning, F. (2016). A theoretical framework on the determinants of organisational adoption of interoperability standards in government information networks. Government Information Quarterly.
Hilbert, M. (2013). Big data for development: From information-to knowledge societies. Available SSRN 2205145.
Hollands, R. G. (2008). Will the real smart city please stand up? City, 12, 303–320.
Janssen, M., van der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decision-making quality. Journal of Business Research, 70, 338–345.
Japkowicz, N., & Stefanowski, J. (2016). A machine learning perspective on big data analysis. In Big data analysis: New algorithms for a new society (pp. 1–31). Cham, Switzerland: Springer.
Jie, S., & Chen, H. (2015). Internet finance innovation and traditional bank transformation based on big data. Finance & Economics, 1.
Ji-fan Ren, S., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2016). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55, 1–16.
Johnston, E. (2010). Governance infrastructures in 2020. Public Administration Review, 70, s122–s128.
Joseph, R. C., & Johnson, N. A. (2013). Big data and transformational government. IT Professional, 15, 43–48.
Jungstrand, A., & Ceco, P. (2017). Succeeding with smart people initiatives: Difficulties and preconditions for smart city initiatives that target citizens. Lund, Sweden: Lunds universitet/Institutionen för informatik.
Kapucu, N., & Hu, Q. (2016). Understanding multiplexity of collaborative emergency management networks. The American Review of Public Administration, 46, 399–417.
Karydis, I., Sioutas, S., Avlonitis, M., Mylonas, P., & Kanavos, A. (2016). A survey on big data and collective intelligence. In Proceedings of International Workshop on Algorithmic Aspects of Cloud Computing, ALGOCLOUD. Cham, Switzerland: Springer.
Khalifa, S., Elshater, Y., Sundaravarathan, K., Bhat, A., Martin, P., Imam, F., … Statchuk, C. (2016). The six pillars for building big data analytics ecosystems. ACM Computing Surveys (CSUR), 49, 33.
Khan, N., Yaqoob, I., Hashem, I. A. T., Inayat, Z., Mahmoud Ali, W. K., Alam, M., … Gani, A. (2014). Big data: Survey, technologies, opportunities, and challenges. Scientific World Journal, 2014, 18.
Khatoun, R., & Zeadally, S. (2016). Smart cities: Concepts, architectures, research opportunities. Communications of the ACM, 59, 46–57.
Kim, G.-H., Trimi, S., & Chung, J.-H. (2014). Big-data applications in the government sector. Communications of the ACM, 57(3), 78–85.
Klievink, B., Romijn, B.-J., Cunningham, S., & de Bruijn, H. (2016). Big data in the public sector: Uncertainties and readiness. Information Systems Frontiers, 19(2), 1–17.
Koh, J. M., Sak, M., Tan, H.-X., Liang, H., Folianto, F., & Quek, T. (2015). Efficient data retrieval for large-scale smart city applications through applied Bayesian inference. In 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) (pp. 1–6). Piscataway, NJ: IEEE.
Koliba, C., Wiltshire, S., Scheinert, S., Turner, D., Zia, A., & Campbell, E. (2017). The critical role of information sharing to the value proposition of a food systems network. Public Management Review, 19, 284–304.
Kourtit, K., Nijkamp, P., & Arribas, D. (2012). Smart cities in perspective–a comparative European study by means of self-organizing maps. Innovation: The European Journal of Social Science Research, 25, 229–246.
Kreps, D., & Richardson, H. (2007). IS success and failure—The problem of scale. The Political Quarterly, 78, 439–446.
Labrinidis, A., & Jagadish, H. V. (2012). Challenges and opportunities with big data. Proceedings of the VLDB Endowment, 5, 2032–2033.
Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, 6, 70.
Larson, S. J. (2017). A critical perspective on evidence-based policy making. Public Administration Review, 77, 787–790.
Lazer, D., Pentland, A. S., Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., et al. (2009). Life in the network: The coming age of computational social science. Science (New York, NY), 323, 721.
Lee, J. H., Hancock, M. G., & Hu, M.-C. (2014). Towards an effective framework for building smart cities: Lessons from Seoul and San Francisco. Technological Forecasting and Social Change, 89, 80–99.
Li, F., Nucciarelli, A., Roden, S., & Graham, G. (2016). How smart cities transform operations models: A new research agenda for operations management in the digital economy. Production Planning and Control, 27, 514–528.
Linoff, G. S., & Berry, M. J. (2011). Data mining techniques: For marketing, sales, and customer relationship management. Hoboken, NJ: John Wiley & Sons.
Liu, X., & Zheng, L. (2015). Cross-departmental collaboration in one-stop service center for smart governance in China: Factors, strategies and effectiveness. Government Information Quarterly.
Luna-Reyes, L. F., Gil-Garcia, J. R., & Cruz, C. B. (2007). Collaborative digital government in Mexico: Some lessons from federal web-based interorganizational information integration initiatives. Government Information Quarterly, 24, 808–826.
Luna-Reyes, L. F., Gil-Garcia, J. R., & Estrada-Marroquín, M. (2008). The impact of institutions on interorganizational IT projects in the Mexican federal government. International Journal of Electronic Government Research (IJEGR), 4, 27.
Luna-Reyes, L. F., Picazo-Vela, S., Luna, D. E., & Gil-Garcia, J. R. (2016). Creating public value through digital government: Lessons on inter-organizational collaboration and information technologies. In 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 2840–2849). Piscataway, NJ: IEEE.
Luna-Reyes, L. F., Sandoval-Almazan, R., Puron-Cid, G., Picazo-Vela, S., Luna, D. E., & Gil-Garcia, J. R. (2017). Understanding public value creation in the delivery of electronic services. In International Conference on Electronic Government (pp. 378–385). Cham, Switzerland: Springer.
Malomo, F., & Sena, V. (2017). Data intelligence for local government? Assessing the benefits and barriers to use of big data in the public sector. Policy Internet, 9, 7–27.
Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. New York: Houghton Mifflin Harcourt.
McLuhan, M. (1994). Understanding media: The extensions of man. Cambridge, UK: MIT Press.
Mergel, I., Rethemeyer, R. K., & Isett, K. (2016). Big data in public affairs. Public Administration Review, 76, 928–937.
Moore, M. H. (2014). Public value accounting: Establishing the philosophical basis. Public Administration Review, 74, 465–477.
Morandi, C., & Rolando, A. (2016). How can ICTs be drivers of spatial innovation? Urban digital nodes for the smart region between Milan and Turin. In From smart city to smart region (pp. 1–18). Cham, Switzerland: Springer.
McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: the management revolution. Harvard business review, 90(10), 60–68.
Nam, T., & Pardo, T. A. (2011). Conceptualizing smart city with dimensions of technology, people, and institutions. In Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times (p. 282). New York: ACM.
Nograšek, J., & Vintar, M. (2014). E-government and organisational transformation of government: Black box revisited? Government Information Quarterly, 31, 108–118.
O’Leary, D. E. (2013). ‘Big data’, the ‘internet of things’ and the ‘internet of signs’. Intelligent Systems in Accounting, Finance and Management, 20, 53–65.
O’Leary, R., & Vij, N. (2012). Collaborative public management: Where have we been and where are we going? The American Review of Public Administration, 42(5), 507–522.
Oomens, I. M. F., & Sadowski, B. M. (2017). The importance of value creation in smart city initiatives: An ecosystem approach. Passau, Germany: International Telecommunications Society (ITS).
Orlikowski, W. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization Science, 11, 404–428.
Orlikowski, W. J., & Iacono, C. S. (2006). Desperately seeking the ‘IT’ in IT research: A call to theorizing the IT artifact. Chichester, UK: John Wiley & Sons Ltd.
Pardo, T. A., Gil-Garcia, J. R., & Burke, G. B. (2006). Building response capacity through cross-boundary information sharing: The critical role of trust. In Exploiting the knowledge economy: Issues, applications, case studies (pp. 507–514). Dublin, Ireland: IIMC.
Pardo, T. A., Gil-Garcia, J. R., & Burke, G. B. (2008). Sustainable cross-boundary information sharing. In D. H. Chen, P. M. L. Brandt, A. D. V. Gregg, P. R. Traunmüller, D. S. Dawes, E. Hovy, P. A. Macintosh, & A. D. C. A. Larson (Eds.), Digital government (pp. 421–438). Boston, MA: Springer US.
Pardo, T. A., Nam, T., & Burke, G. B. (2011). E-government interoperability: Interaction of policy, management, and technology dimensions. Social Science Computer Review, 30(1), 7–23.
Pereira, G. V., Macadar, M. A., Luciano, E. M., & Testa, M. G. (2017). Delivering public value through open government data initiatives in a smart city context. Information Systems Frontiers, 19, 213–229.
Picazo-Vela, S., Gutiérrez-Martínez, I., Duhamel, F., Luna, D. E., & Luna-Reyes, L. F. (2017). Value of inter-organizational collaboration in digital government projects. Public Management Review, 20(5), 1–18.
Pinch, T. J., & Bijker, W. E. (1987). The social construction of facts and artifacts: Or how the sociology of science and the sociology of technology might benefit each other. The Social Constructions of Technological Systems: New Directions in the Sociology and History of Technology, 17, 1–6.
Puerzer, R. J. (2002). From scientific baseball to sabermetrics: Professional baseball as a reflection of engineering and management in society. NINE: A Journal of Baseball History and Culture, 11, 34–48.
Puron-Cid, G., Gil-Garcia, J. R., & Luna-Reyes, L. F. (2016). Opportunities and challenges of policy informatics: Tackling complex problems through the combination of open data, technology and analytics. International Journal of Public Administration in the Digital Age (IJPADA), 3, 66–85.
Pfeffer, J., & Sutton, R. I. (2006). Evidence-based management. Harvard business review, 84(1), 62.
Rasmussen, T., & Ulrich, D. (2015). Learning from practice: How HR analytics avoids being a management fad. Organizational Dynamics, 44, 236–242.
Sayogo, D. S., Zhang, J., Luna-Reyes, L., Jarman, H., Tayi, G., Andersen, D. L., … Andersen, D. F. (2015). Challenges and requirements for developing data architecture supporting integration of sustainable supply chains. Information Technology and Management, 16, 5–18.
Schaffers, H., Komninos, N., Pallot, M., Trousse, B., Nilsson, M., & Oliveira, A. (2011). Smart cities and the future internet: Towards cooperation frameworks for open innovation. In The future internet assembly (pp. 431–446). Berlin, Germany: Springer.
Scholl, H. J., & Scholl, M. C. (2014). Smart governance: A roadmap for research and practice. IConference 2014 Proceedings.
Scott, S. L., Blocker, A. W., Bonassi, F. V., Chipman, H. A., George, E. I., & McCulloch, R. E. (2016). Bayes and big data: The consensus Monte Carlo algorithm. International Journal of Management Science and Engineering Management, 11, 78–88.
Song, H., Srinivasan, R., Sookoor, T., & Jeschke, S. (2017). Smart cities: Foundations, principles, and applications. Hoboken, NJ: John Wiley & Sons.
Strawn, G. O. (2012). Scientific research: How many paradigms? Education Review, 47, 26.
Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In Collaboration Technologies and Systems (CTS), 2013 International Conference on (pp. 42–47). IEEE.
Tirunillai, S., & Tellis, G. J. (2014). Mining marketing meaning from online chatter: Strategic brand analysis of big data using latent dirichlet allocation. Journal of Marketing Research, 51, 463–479.
Toots, M., McBride, K., Kalvet, T., & Krimmer, R. (2017). Open data as enabler of public service co-creation: Exploring the drivers and barriers. In 2017 Conference for, E-Democracy and Open Government (CeDEM) (pp. 102–112). Piscataway, NJ: IEEE.
Toppeta, D. (2010). The smart city vision: How innovation and ICT can build smart, “livable”, sustainable cities. The Innovation Knowledge Foundation, 5, 1–9.
Townsend, A. M. (2013). Smart cities: Big data, civic hackers, and the quest for a new utopia. New York: WW Norton & Company.
Walravens, N., & Ballon, P. (2013). Platform business models for smart cities: From control and value to governance and public value. IEEE Communications Magazine, 51, 72–79.
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.
Watson, H. J., & Wixom, B. H. (2007). The current state of business intelligence. Computer, 40, 96–99.
Weerakkody, V., Kapoor, K., Balta, M. E., Irani, Z., & Dwivedi, Y. K. (2017). Factors influencing user acceptance of public sector big open data. Production Planning and Control, 28, 891–905.
Winner, L. (1980). Do artifacts have politics? (pp. 121–136). Cambridge, UK: Daedalus.
Winner, L. (2010). The whale and the reactor: A search for limits in an age of high technology. Chicago, IL: University of Chicago Press.
World Health Organization. (2016). Urban population growth. http://www.who.int/gho/urban_health/situation_trends/urban_population_growth_text/en/
Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77–84.
Yang, T.-M., & Maxwell, T. A. (2011). Information-sharing in public organizations: A literature review of interpersonal, intra-organizational and inter-organizational success factors. Government Information Quarterly, 28, 164–175.
Zainal, N. Z. B., Hussin, H., & Nazri, M. N. M. (2016). Big data initiatives by governments - Issues and challenges: A review. In 2016 6th International Conference on Information and Communication Technology for the Muslim World (Ict4m) (pp. 304–309). New York: IEEE.
Zygiaris, S. (2013). Smart city reference model: Assisting planners to conceptualize the building of smart city innovation ecosystems. Journal of the Knowledge Economy, 4, 217–231.
Acknowledgements
The authors would like to thank CAPES and the Office of Graduate Studies at the University at Albany, which provided partial funding for this research. The opinions expressed in this chapter are those of the authors and do not necessarily reflect the official views of CAPES or the University at Albany.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Cronemberger, F., Gil-Garcia, J.R. (2019). Big Data and Analytics as Strategies to Generate Public Value in Smart Cities: Proposing an Integrative Framework. In: Rodriguez Bolivar, M.P. (eds) Setting Foundations for the Creation of Public Value in Smart Cities. Public Administration and Information Technology, vol 35. Springer, Cham. https://doi.org/10.1007/978-3-319-98953-2_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-98953-2_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98952-5
Online ISBN: 978-3-319-98953-2
eBook Packages: Political Science and International StudiesPolitical Science and International Studies (R0)