Derecho Comparado 1 Régimen de la propiedad intelectual en el Perú

The Bicycle-Parking department, the Water Management department and the Asset Management department vary in terms of smart policy development. Indeed, the departments are rather different regarding the involvement of sensor technology in their activities. The Water Management department is the only department in which sensor technology is used. Within Bicycle-Parking and Asset Management sensor technology has never been used so far, which implies the absence of smart policies. However, the Bicycle-Parking department has

considered various technological innovations for the registration of bicycles, whereas Asset Management focusses solely on traditional policy instruments.

The Asset Management department seems to be obstructed by both path dependent behaviour of civil servants and the incompatibility of established policies and smart policies. The development of smart policies does not seem to obstructed by established agreements, which makes sense because all contracts can be phased out within three years, according to the Asset Manager. Within the Bicycle-Parking department, the development of smart policies is also obstructed by path-dependency and the incompatibility of old and new policies. However, Bicycle-Parking seems to be influenced by established collaborative agreements with private parties as well. At the Water Management department, the implementation of smart policies is not likely to be affected by the incompatibility of policies, as they already incorporate sensor technology in their activities. Moreover, there do not seem to be constraining agreements with the industry. However, civil servants seem to act upon existing norms and routines, which creates a bureaucratic organisation. Decisions therefore seem to be rather viscous. This indicates a certain level of path dependency.

To conclude, the plausibility of the hypotheses within each case varied quite a lot. In all cases, path dependent behaviour seemed to influence the development of smart policies. Both in the Water Management case and the Bicycle-Parking case, there was a strong indication that the incompatibility between established policies and goals and technologically more advanced policies affected the implementation of smart policies. Only in the Bicycle-Parking case contracts and established collaborations were likely to have a stemming effect on the development of smart public policies.

6 Conclusion & recommendations

In this final chapter of the thesis, an overall conclusion, the contributions of the study and the research limitations are presented. The conclusion summarizes the main findings and answers the research question. Thereafter, the section on contributions provides an overview of what this study has added to the current literature. Finally, the limitations of this research are elaborated upon.

Concluding remarks

This thesis has analysed the impeding effect of various institutional characteristics of the municipality of Amsterdam on the development of smart public policies. An attempt was made to uncover the obstructions the municipality encounters when implementing a LoRa network to enable technologically advanced policies. A causal mechanism representing the hypothesized obstructing factors on smart policy development, was derived from the literature. Multiple academic angles were taken into account, including smart city literature (Domingue et al., 2011; Caragliu et al., 2009), evidence-based governance literature (Kitchin, 2014a,b; Meijer et al., 2015), network governance (Giest, 2014; Head, 2008), path dependency literature (Peter et al., 2005; Howlett, 2009), and policy layering literature (Howlett & Rayner, 2007; Kay, 2007). Although smart governance is still considered an underexposed academic field, prior literature reveals various tensions regarding policy innovations in the public sphere that are relevant for this research. That is, path dependent behaviour, the incompatibility of established policies and desired smart policies, and public-private collaborative agreements are likely to obstruct policy innovation in a public environment. Path dependency refers to the presence of behavioural loops inclined by established norms and routines, risk-aversion and incrementalism (Howlett, 2009). The incompatibility of policies encompasses the situation in which new policies will inevitably have to cope with prior policy layers, which may cause new policies to be less effective. Stemming public- private collaborations entail the influence of fixed agreements between the municipality and its private partners that limit the possibilities of policy innovations. The initial research question of this thesis was:

“Which factors potentially obstruct the development of smart public services in the City of Amsterdam?”

In order to answer this research question, a qualitative research was conducted, focusing on the geographical area of Amsterdam. A within-case analysis was accomplished among three departments of the municipality of Amsterdam: the Water Management department, the Bicycle-Parking department, and the Asset Management department. Within each of the departments, three to four interviews were conducted in an attempt to uncover the obstructing factors of smart policy development. When linking the research question to the empirical data, results were diverging among the three cases. The results imply that the impeding effect of path-dependent behaviour (H1) on smart policy developments is prevalent in all cases. Furthermore, the interviews imply that the incompatibility of established policies and technologically advanced policies (H2) is likely to stem smart public policy development in both the Bicycle-Parking department and the Asset Management department. Finally, only in the Bicycle-Parking department, established agreements with private parties (H3) tend to slow down the development of smart public policies. Hence, the answer to the research question is not linear, but diverges among the cases.

Practical and theoretical contributions

This study provides both a practical and a theoretical contribution. Practically, this thesis may provide municipalities with some support to guard institutional flexibility in order to fan policy innovation. That is, several institutional mechanisms are prevalent in governmental organisations that tend to block development of smart policies. This research uncovers what these elements are in the context of the municipality of Amsterdam, which may help other governmental institutions to recognize these aspects when they become prevalent. The recognition of the elements may help to avoid such elements to become obstructs in the development of smart public policies. This thesis contributes to the academic field by exposing which tendencies typically influence smart governance. Although smart governance is not a nascent topic, it remains rather underexposed. Furthermore, this study combines

Recommendations and limitations

Prior academic work reveals which mechanisms are likely to impede policy innovation in general, but do not uncover which mechanisms affect smart policy innovations specifically. In this thesis, path dependency literature, policy layering literature and public-private collaboration literature are related to policy innovation literature. However, despite the fact that the relation between the independent variables and policy innovation is implied by previous scholars, there is no direct indication for the applicability to smart policy development. Thus, it is not assumed per se that path dependency, policy layering and public- private collaboration form the most profound explanations for slow or lagging smart policy development. Hence, which factors affect the development of smart policies in a municipality, is still rather debatable. Since the hypotheses are based on the assumption that the development of policy innovation and the development of smart, technologically advanced, IoT incorporated policies are influenced by the same mechanisms, the causal mechanism still requires thorough examination. Therefore, in order to form a more profound perspective on the obstructing factors of smart public policy development, further research must be conducted in this area.

Research results solely rely on the geographical area of Amsterdam. Regardless of the accuracy of the research, the research results are not directly applicable to other cities, since there may be other factors that influence smart public policy development that were not taken into account in this research. For instance, this research investigates the technological developments of the aforementioned departments but does not include the effect of the technological maturity of the geographical region. Differences in urban areas are likely to affect the research outcome when conducting the research elsewhere. Additionally, well- organised governmental institutions in developed countries are perhaps more capable of developing smart policies than poorly-organised governments in underdeveloped countries. The maturity of governments may be of paramount importance when studying different geographical areas. That is, underdeveloped institutions may not be capable of incorporating smart policies and sensor technology, even in the absence of path dependency, the incompatibility of policy instruments and constraining public-private agreements. Moreover, norms, culture and political policy may play a role in the incorporation of smart public policies as well. Hence, the causal model presented in this thesis should be tested in a broader

context in order to assess the generalisability and the robustness of the model. Thus, further research is required in a variety of departments, various municipalities, and in diverging geographical areas.

References

Aggarwal, R. (1999). Technology and globalization as mutual reinforcers in business: Reorienting strategic thinking for the new millennium. MIR: Management International Review, 83-104.

Amsterdam Economic Board (2014). Amsterdam tweede Smart City in Europa. 20th January. URL: https://www.amsterdameconomicboard.com/nieuws/amsterdam-tweede-smart-

city-in-europa/Retrieved at: 25th May 2016.

Béland. 2007. Ideas and Institutional change in social security: Conversion, layering, and policy drift. Wiley Online Library

Bell, S. (2004). ‘Appropriate’policy knowledge, and institutional and governance implications. Australian Journal of Public Administration, 63(1), 22-28.

Bryman, Alan. 2012. Social Research Methods. Oxford: Oxford University Press, Chapter 3.

Brutus, S., Gill, H., & Duniewicz, K. (2010). Self-reported limitations in industrial and organizational psychology. Personnel Psychology, 63: 907-936.

Caragliu, A., Del Bo, C., Nijkamp, P. (2009). Smart cities in Europe. Series Research Memoranda 0048. VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

Chesbrough, H.W. (2003). Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business School Press, Boston.

Coe, A., Paquet, G., & Roy, J. (2001). E-governance and smart communities a social learning challenge. Social Science Computer Review, 19(1), 80-93.

Coleman J.S. (1988). Social capital in the creation of human capital. American journal of sociology, S95-S120.

Domingue, J. et al. (Eds.). Future Internet Assembly, LNCS 6656, pp. 431–446, 2011. (Schaffers, H., Komninos, N., Pallot, M., Trousse, B. (2011). Smart Cities and the Future Internet: Towards Cooperation Frameworks for Open Innovation)

European Commission (2015). Digital Agenda for Europe: Smart cities URL:

https://ec.europa.eu/digital-agenda/en/smart-cities

Retrieved at: 4 April 2016

Giest, S. (2015). Network Capacity-building in High-tech Sectors: Opening the Black Box of Cluster Facilitation Policy. Public Administration.

Goldsmith, S., & Crawford, S. (2014). The responsive city: Engaging communities through data-smart governance. John Wiley & Sons.

Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. Handbook of qualitative research, 2(163-194).

Hammersley, M. (2006). Ethnography: problems and prospects. Ethnography and education, 1(1), 3-14.

He, Y., Stojmenovic, I., Liu, Y., & Gu, Y. (2014). Smart city. International Journal of Distributed Sensor Networks.

Head, B. W. (2008). Assessing network-based collaborations, Public Management Review, 10:6, 733-749.

Head, B. W. (2008). Three lenses of Evidence Based policy. Australian Journal of Public Administration, 67(1), 1-11.

Howlett & Rayner. (2007). Design principles for policy mixes: cohesion and coherence in ‘new arrangements’. Elsevier.

Howlett, M. (2009). Policy analytical capacity and evidence based policy making: Lessons from Canada. Canadian public administration, 52(2), 153-175.

Juhola, S. and L. Westerhoff. 2011. Challenges of adaptation to climate change across multiple scales: a case study of network governance in two European countries. Environmental Science and Policy 14 (3), 239-247.

Kay, A. 2007. Tense layering and synthetic policy paradigms: The politics of health insurance in Australia. Taylor & Francis.

Keller, W. (2004). International technology diffusion. Journal of economic literature, 42(3), 752-782.

Kim, G. H., Trimi, S., & Chung, J. H. (2014). Big-data applications in the government sector. Communications of the ACM, 57(3), 78-85.

King, G., Keohane, R. O., & Verba, S. (1994). Scientific inference in qualitative research. Princeton, NJ.

Kitchin, R. (2014). The real-time city? Big data and smart urbanism.GeoJournal, 79(1), 1-14.

Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), 2053951714528481.

Komninos, N. (2002). Intelligent Cities: Innovation, knowledge systems and digital spaces. Taylor & Francis, London and New York.

Komninos, N. (2008). Intelligent Cities and Globalisation of Innovation Networks. Routledge, London and New York.

Komninos, N. (2009) ‘Intelligent cities: towards interactive and global innovation environments’, Int. J. Innovation and Regional Development, Vol. 1, No. 4, pp.337–355.

Mahoney, J. (2000). Path dependence in historical sociology. Theory and society, 29(4), 507-548.

March, J. G. (1991). Exploration and exploitation in organizational learning.Organization science, 2(1), 71-87.

Meijer, A.J., Gil-Garcia, J. R., & Rodríguez Bolívar, M. P. (2015). Smart City Research: Contextual Conditions, Governance Models, and Public Value Assessment. Social Science Computer Review, 0894439315618890.

Miles, R. E., & Snow, C. C. (1986). Organizations: New concepts for new forms. California management review, 28(3), 62-73.

Mills, A. J., Durepos, G., Wiebe, E., Boje, D. M., Carr, A., David, M., ... & Jacques, R. S. (2010). SAGE encyclopedia of case study research.

Nam, T., & Pardo, T. A. (2011, June). 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 (pp. 282-291). ACM.

Narula, R., & Hagedoorn, J. (1999). Innovating through strategic alliances: moving towards international partnerships and contractual agreements.Technovation, 19(5), 283-294.

Pawson, R. (2002). Evidence-based policy: The promise of realist synthesis'. Evaluation, 8(3), 340-358.

Peters, B. G., Pierre, J., & King, D. S. (2005). The politics of path dependency: Political conflict in historical institutionalism. Journal of Politics, 67(4), 1275-1300.

Plewis, I. (2000). Educational Inequalities and Education Action Zones, in C. Pantazis and D. Gordon (eds.) Tackling Inequalities: Where Are We Now and What Can Be Done. Bristol: Policy Press.

Porter, M. E. (1990). The Competitive Advantage of Nations. Free Press, New York.

Porter, M. E. (1998). Cluster and the new economics of competition.

Provan, K., Kenis., P. (2007). Modes of Network Governance: Structure, management, and effectiveness. J-PART 18, 229-252.

Sanderson, I. (2006). Complexity, 'practical rationality' and evidence-based policy making. Policy & politics, 34(1), 115-132.

Solesbury, W. (2001). Evidence based policy: Whence it came and where it's going.

Sydow, J., & Windeler, A. (1998). Organizing and evaluating interfirm networks: A structurationist perspective on network processes and effectiveness. Organization science, 9(3), 265-284.

Toshkov, D. (2015). Research Design in Political Science. Leiden University: chapter 1-4.

Torfing, J. (2005). Governance network theory: Towards a second generation. European Political Science 4, 305-315.

Uprichard, E. (2013). Focus: big data, little questions?. Discover Society, (1).

Vlacheas, P., Giaffreda, R., Stavroulaki, V., Kelaidonis, D., Foteinos, V., Poulios, G., Moessner, K. (2013). Enabling smart cities through a cognitive management framework for the internet of things. Communications Magazine, IEEE, 51(6), 102-111.

Wallace, H., Pollack, M. A., & Young, A. R. (Eds.). (2015). Policy-making in the European Union. Oxford university press.

Wolcott, H.F. (1990). Making a study ‘more ethnographic. Journal of Contemporary Ethnography 19, 44-72.

Zhu, Y. (2013). Policy entrepreneurship, institutional constraints, and local policy innovation in China. China Review, 13(2), 97-122.