Big Data and its potential role in regional growth: evidence from Great Britain

REFERENCES

• Acs, Z. J., Braunerhjelm, P., Audretsch, D. B., & Carlsson, B. (2009). The knowledge spillover theory of entrepreneurship. Small Business Economics, 32(1), 15–30. https://doi.org/10.1007/s11187-008-9157-3
   Web of Science ®Google Scholar
• Ansar, A., Flyvbjerg, B., Budzier, A., & Lunn, D. (2017). Big is fragile: An attempt at theorizing scale. In B. Flyvbjerg (Ed.), The Oxford Handbook of megaproject management (pp. 60–69). Oxford University Press.
   Google Scholar
• Arrow, K. J. (1972). Economic welfare and the allocation of resources for invention. In C. K. Rowley (Ed.), Readings in industrial economics (pp. 219–236). Palgrave.
   Google Scholar
• Bakhshi, H., Biosca, A. B., & Garcia, J. M. (2014). Inside the datavores: Estimating the effect of data and online analytics on firm performance. Nesta.
   Google Scholar
• Beugelsdijk, S., Klasing, M., & Milionis, P. (2018). Regional economic development in Europe: The role of total factor productivity. Regional Studies, 52(4), 461–476. https://doi.org/10.1080/00343404.2017.1334118
   Web of Science ®Google Scholar
• Bishop, P., & Shilcof, D. (2017). The spatial dynamics of new firm births during an economic crisis: The case of Great Britain, 2004–2012. Entrepreneurship & Regional Development, 29(3), 215–237. https://doi.org/10.1080/08985626.2016.1257073
   Web of Science ®Google Scholar
• Boyd, D., & Crawford, K. (2011). Six provocations for big data. In A. E. Marwick & D. Boyd (Eds.), A decade in internet time: Symposium on the dynamics of the internet and society. Oxford International Institute, Oxford University.
   Google Scholar
• Božič, K., & Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International Journal of Information Management, 46, 93–103. https://doi.org/10.1016/j.ijinfomgt.2018.11.020
   Web of Science ®Google Scholar
• Braunerhjelm, P., Acs, Z. J., Audretsch, D. B., & Carlsson, B. (2010). The missing link: Knowledge diffusion and entrepreneurship in endogenous growth. Small Business Economics, 34(2), 105–125. https://doi.org/10.1007/s11187-009-9235-1
   Web of Science ®Google Scholar
• Brynjolfsson, E., Hitt, L. M., & Kim, H. H. (2011). Strength in numbers: How does data-driven decisionmaking affect firm performance? Available at SSRN 1819486.
   Google Scholar
• Caragliu, A., & Nijkamp, P. (2012). The impact of regional absorptive capacity on spatial knowledge spillovers: The Cohen and Levinthal model revisited. Applied Economics, 44(11), 1363–1374. https://doi.org/10.1080/00036846.2010.539549
   Web of Science ®Google Scholar
• Cavanillas, M., Curry, E., & Wahlster, W. (2016). New horizons for a data-driven economy: A roadmap for usage and exploitation of big data in Europe. Springer Nature.
   Google Scholar
• CEBR. (2012). Data equity. Unlocking the value of big data. Report for SAS April 2012.
   Google Scholar
• Clark, J., & Sudharsan, S. (2019). Firm strategies and path dependencies: An emerging economic geography of industrial data. Regional Studies, 4, 1–3. https://doi.org/10.1080/00343404.2019.1619926
   Google Scholar
• Cohen, W. M., & Levinthal, D. A. (2000). Absorptive capacity: A new perspective on learning and innovation. Strategic Learning in a Knowledge Economy, 39–67. https://doi.org/10.1016/B978-0-7506-7223-8.50005-8
   Google Scholar
• Curry, E. (2016). The big data value chain: Definitions, concepts, and theoretical approaches. In J. Maria Cavanillas, E. Curry, & W. Wahlster (Eds.), New horizons for a data-driven economy (pp. 29–37). Springer.
   Google Scholar
• Denti, D. (2019). R&D spillovers and regional development/growth. In R. Capello & P. Nijkamp (Eds.), Handbook of regional growth and development theories (pp. 277–307). Edward Elgar.
   Google Scholar
• DG Connect. (2013). A European strategy on the data value chain. European Commission.
   Google Scholar
• Dijkstra, L., Poelman, H., & Rodríguez-Pose, A. (2019). The geography of EU discontent. Regional Studies, 19, 1–7. https://doi.org/10.1080/00343404.2019.1654603
   Google Scholar
• Faggian, A., Modrego, F., & McCann, P. (2019). Human capital and regional development. In R. Capello & P. Nijkamp (Eds.), Handbook of regional growth and development theories (pp. 149–171). Edward Elgar.
   Google Scholar
• Fu, X. (2008). Foreign direct investment, absorptive capacity and regional innovation capabilities: Evidence from China. Oxford Development Studies, 36(1), 89–110. https://doi.org/10.1080/13600810701848193
   Google Scholar
• Goodridge, P., & Haskel, J. (2015). How does big data affect GDP? Theory and evidence for the UK. (No. 25156).
   Google Scholar
• Hermelin, B. (2020). Knowledge economy. In A. Kobayashi (Ed.), International encyclopaedia of human geography (2nd ed., vol. 8, pp. 23–27). Elsevier.
   Google Scholar
• International Data Corporation. (2020). Worldwide Big Data and analytics spending guide. https://www.idc.com/getdoc.jsp?containerId=IDC_P33195
   Google Scholar
• Johansson, B., & Karlsson, C. (2019). Regional development and knowledge. In R. Capello & P. Nijkamp (Eds.), Handbook of regional growth and development theories (pp. 308–325). Edward Elgar.
   Google Scholar
• Jung, J., & Lopez-Bazo, E. (2017). Factor accumulation, externalities, and absorptive capacity in regional growth: Evidence from Europe. Journal of Regional Science, 57(2), 266–289. https://doi.org/10.1111/jors.12304
   Web of Science ®Google Scholar
• Martin, R., Pike, A., Tyler, P., & Gardiner, B. (2016). Spatially rebalancing the UK economy: Towards a new policy model? Regional Studies, 50(2), 342–357. https://doi.org/10.1080/00343404.2015.1118450
   Web of Science ®Google Scholar
• Maskell, P., & Malmberg, A. (1999). Localised learning and industrial competitiveness. Cambridge Journal of Economics, 23(2), 167–185. https://doi.org/10.1093/cje/23.2.167
   Web of Science ®Google Scholar
• McCann, P. (2008). Globalization and economic geography: The world is curved, not flat. Cambridge Journal of Regions, Economy and Society, 1(3), 351–370. https://orcid.org/10.1093/cjres/rsn002
   Web of Science ®Google Scholar
• McCann, P. (2018). The trade, geography and regional implications of Brexit. Papers in Regional Science, 97(1), 3–8. https://doi.org/10.1111/pirs.12352
   Web of Science ®Google Scholar
• McCann, P., & Van Oort, F. (2019). Theories of agglomeration and regional economic growth: A historical review. In R. Capello & P. Nijkamp (Eds.), Handbook of regional growth and development theories (pp. 6–23). Edward Elgar.
   Google Scholar
• Mihet, R., & Philippon, T. (2019). The economics of Big Data and artificial intelligence. International Finance Review, 20, 29–43. https://doi.org/10.1108/S1569-376720190000020006
   Google Scholar
• Moretti, E. (2012). The new geography of jobs. Houghton-Mifflin Harcourt.
   Google Scholar
• Morrissey, K. (2016). A location quotient approach to producing regional production multipliers for the Irish economy. Papers in Regional Science, 95(3), 491–506. https://doi.org/10.1111/pirs.12143
   Web of Science ®Google Scholar
• Niebel, T., Rasel, F., & Viete, S. (2019). BIG data–BIG gains? Understanding the link between big data analytics and innovation. Economics of Innovation and New Technology, 28(3), 296–316. https://doi.org/10.1080/10438599.2018.1493075
   Web of Science ®Google Scholar
• Office for National Statistics (ONS). (2017). Location quotients by industrial sector, 2015.
   Google Scholar
• Office for National Statistics (ONS). (2018). Regional and subregional productivity comparisons, UK and selected EU countries: 2014.
   Google Scholar
• Office for National Statistics (ONS). (2019). Regional economic activity by gross domestic product, UK: 1998 to 2018.
   Google Scholar
• Philip, J. (2018). An application of the dynamic knowledge creation model in big data. Technology in Society, 54, 120–127. https://doi.org/10.1016/j.techsoc.2018.04.001
   Web of Science ®Google Scholar
• Rabari, C., & Storper, M. (2015). The digital skin of cities: Urban theory and research in the age of the sensored and metered city, ubiquitous computing and big data. Cambridge Journal of Regions, Economy and Society, 8(1), 27–42. https://doi.org/10.1093/cjres/rsu021
   Web of Science ®Google Scholar
• Roberts, N., Galluch, P. S., Dinger, M., & Grover, V. (2012). Absorptive capacity and information systems research: Review, synthesis, and directions for future research. MIS Quarterly, 36(2), 625–648. https://doi.org/10.2307/41703470
   Web of Science ®Google Scholar
• Rodriguez-Pose, A. (2018). The revenge of the places that don’t matter (and what to do about it). Cambridge Journal of Regions, Economy and Society, 11(1), 189–209. https://doi.org/10.1093/cjres/rsx024
   Web of Science ®Google Scholar
• Sadowski, J. (2019). When data is capital: Datafication, accumulation, and extraction. Big Data & Society, 6(1), 1–12. https://doi.org/10.1177/2053951718820549
   Web of Science ®Google Scholar
• Schintler, L. A. (2017). The constantly shifting face of the digital divide: Implications for big data, regional science, and urban informatics. In L. A. Schintler & Z. Chen (Eds.), Big Data for regional science (pp. 336–347). Routledge.
   Google Scholar
• Schintler, L. A., & Fischer, M. M. (2018). Big data and regional science: Opportunities, challenges, and directions for future research. Working Paper in Regional Science, 2018/02.
   Google Scholar
• Storper, M., & Venables, A. J. (2004). Buzz: Face-to-face contact and the urban economy. Journal of Economic Geography, 4(4), 351–370. https://doi.org/10.1093/jnlecg/lbh027
   Web of Science ®Google Scholar
• Stough, R., & McBride, D. (2017). Big data, privacy and the policy process in the United States. In L. A. Schintler & Z. Chen (Eds.), Big Data for regional science (pp. 336–347). Routledge.
   Google Scholar
• Tambe, P. (2014). Big data investment, skills, and firm value. Management Science, 60(6), 1452–1469. https://doi.org/10.1287/mnsc.2014.1899
   Web of Science ®Google Scholar
• Thelen, K. (2019). Transitions to the knowledge economy in Germany, Sweden, and the Netherlands. Comparative Politics, 51(2), 295–315. https://doi.org/10.5129/001041519X15647434969821
   Web of Science ®Google Scholar
• Urbinati, A., Bogers, M., Chiesa, V., & Frattini, F. (2019). Creating and capturing value from Big Data: A multiple-case study analysis of provider companies. Technovation, 84–85, 21–36. https://doi.org/10.1016/j.technovation.2018.07.004
   Web of Science ®Google Scholar
• Yang, C. H., & Lin, H. L. (2012). Openness, absorptive capacity, and regional innovation in China. Environment and Planning A: Economy and Space, 44(2), 333–355. https://doi.org/10.1068/a44182
   Web of Science ®Google Scholar
• Zeng, J., Liu, Y., Wang, R., & Zhan, P. (2019a). Absorptive capacity and regional innovation in China: An analysis of patent applications, 2000–2015. Applied Spatial Analysis and Policy, 12(4), 1031–1049. https://doi.org/10.1007/s12061-019-09300-y
   Web of Science ®Google Scholar
• Zeng, J., Wu, W., Liu, Y., Huang, C., Zhao, X., & Liu, D. (2019b). The local variations in regional technological evolution: Evidence from the rise of transmission and digital information technology in China’s technology space, 1992–2016. Applied Geography, 112, 102080. https://doi.org/10.1016/j.apgeog.2019.102080
   Web of Science ®Google Scholar