Abstract
The urban space paper is introduced by a brief “report” on the founding of Rome by Romulus; he traced a furrow and thereby defined the urban space. The core of the paper, however, defines the urban space by the dimension of collective decision-making expressed in the form of voting games. It offers a power index analysis of the relationship between the agents of a network—applying the Public Good Index (PGI) and the Public Value (PV)—reinterprets previous work by Holler and Rupp (Power in networks: A PGI analysis of Krackhardt’s Kite Network. Transactions on computational collective intelligence. Springer, Heidelberg, 2019), and presents new numerical results and gives alternative interpretations. The results confirm our expectations: an increase of links and thereby connectedness tends to increase the power of an agent. The message for policymaking in the urban space is evident. This motivated us to discuss the question of why we should be interested in evaluating the power distribution within a network. Here, our focus is on the accountability of the agents—and the Smart City concept.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
This date is given in Fustel de Coulange (2006 [1864]: 138). The following account derives from this text.
- 2.
These intervals of carrying the plow were called portae (Fustel de Coulange 2006 [1864]: 138).
- 3.
Holler and Marciano (2010) discussed Machiavelli’s “possibility hypothesis” with reference to Arrow’s notorious “impossibility theorem” which says that, given a set of quite reasonable condition, we cannot exclude that an aggregation of individual preference fails and we cannot derive a social welfare function—unless we accept that it is dictatorial (see Arrow (1963[1951]).
- 4.
- 5.
Vertex D has the highest degree centrality, H and I rate highest with respect to betweenness centrality, and F and G have, on the average, the shortest path distance to the other vertices (closeness centrality).
- 6.
The swing players define the power for the indices of Shapley–Shubik, Penrose–Banzhaf–Coleman, Johnston, and Deegan–Packel. These measures vary in what coalitions are to be considered and how the coalition surplus is distributed among their members.
- 7.
Myerson (1977) presents a bargaining model for networks that connects the (fair) bargaining outcome and the corresponding Shapley value.
- 8.
For a recent discussion of the PGI, see Holler (2019). Note there are more than ten power indices, but there is only one measure that is serious about measuring the impact of a player in producing a public good, i.e., the PGI.
- 9.
- 10.
In general, parliaments and city councils do not change their majority rules if links between parties altered, and, in the extreme, a party became unconnected to any other like going from Γ and Γ1.
- 11.
In order to form a winning coalition, i needs to be connected to at least d − 1 vertices (such that they form a connected subgraph). The required d − 1 many nodes can be on any side of i in the network such that the winning coalitions i belong to a circle/sphere with maximal radius d − 1. Here, the notion of a radius is in terms of graph neighborhoods: if i has a high enough degree it may be the case that the coalition is formed by direct neighbors of i only, i.e., i is connected to each of the members of its coalition by minimal paths of length 1. In this sense, the worst case that can occur, maximizing the distance, is that actually a d − 1 neighbor has to be a member of the coalition. (The shortest path between i and this vertex has length d − 1).
- 12.
In his Picture of Dorian Gray, Oscar Wilde characterized a Radical member of Parliament by the by now notorious quote: “Like all people who try to exhaust a subject, he exhausted his listeners.”
- 13.
For a more intensive discussion of the relationship of power and responsibility, see Holler (2007).
References
Arrow, K. J. (1963 [1951]). Social choice and individual value (2nd ed.). New York: Wiley.
Brandes, U., & Hildenbrand, J. (2014). Smallest graphs with distinct Singleton Centers. Network Science, 2, 416–418.
Fragnelli, V. (2012). A note on communication structures. Homo Oeconomicus, 29, 163–171. Republished in Holler, M. J., & Nurmi, H. (Eds.). (2013). Power, voting, and voting power: 30 years after (pp. 467-473). Heidelberg: Springer.
Fustel de Coulange, N. D. (2006 [1864]). The ancient city: A study of religion, laws, and institutions of Greece and Rome (Orig.: La cité antique, Paris 1864), Mineola, NY: Dover Publications.
Holler, M. J. (1982). Forming coalitions and measuring voting power. Political Studies, 30, 262–271.
Holler, M. J. (2007). Freedom of choice, power, and the responsibility of decision makers. In J.-M. Josselin & A. Marciano (Eds.), Democracy, freedom and coercion: A law and economics approach (pp. 22–45). Cheltenham: Edward Elgar.
Holler, M. J. (2019). The story of the poor public good index. In N. T. Nguyen, R. Kowalzyk, J. Mercik, & A. Motylska-Kruzma (Eds), Transactions on computational collective intelligence (Vol. 34, pp. 171–179). Heidelberg: Springer.
Holler, M. J., & Li, X. (1995). From public good index to public value: An axiomatic approach and generalization. Control and Cybernetics, 24, 257–270.
Holler, M. J., & Marciano, A. (2010). Machiavelli’s possibility hypothesis. AUCO Czech Economic Review, 4, 18–31.
Holler, M. J., & Packel, E. W. (1983). Power, luck, and the right index. Journal of Economics (Zeitschrift für Nationalökonomie), 43, 21–29.
Holler, M. J. & Rupp, F. (2019). Power in networks: A PGI analysis of Krackhardt’s Kite Network. In N. T. Nguyen, R. Kowalzyk, J. Mercik & A. Motylska-Kruzma (Eds), Transactions on computational collective intelligence (Vol. 34, pp. 21–34). Heidelberg: Springer.
Krackhardt, D. (1990). Assessing the political landscape: Structure, cognition, and power in organizations. Administrative Science Quarterly, 35, 342–369.
Machiavelli, N. (1882). Discourses on the first ten books of Titus Livius. In: The Historical, Political, and Diplomatic Writings of Niccolò Machiavelli (Trans. from the Italian by Christian E. Detmold, Boston: James R. Osgood and Co.).
Myerson, R. B. (1977). Graphs and cooperation in games. Mathematics of Operations Research, 2, 225–229.
Orłowski, C., Sitek, T., Ziółkowski, A., Kapłański, P., Orłowski, A. & Pokrzywnicki, W. (2019). Introduction. In C.Orłowski, T. Sitek, A. Ziółkowski, P., Kapłański, A. Orłowski & W. Pokrzywnicki (Eds), Considerations in the design and implementation of Smart Cities systems. Gdańsk, Poland: CAS IBM Center for Advanced Studies.
Van Leewen, B., Ramalingam, A., Arjona, D. R., & Schram, A. (2019). Centrality and cooperation in networks. Experimental Economics, 16, 178–196.
Weber, M. (1948[1924]). Class, status and party. In H. H. Gerth & C. Wright Mills (Eds.), Essays from Max Weber. London: Routledge and Kegan Paul.
Acknowledgements
The authors would like to thank Barbara Klose-Ullmann for the helpful comments.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Holler, M.J., Rupp, F. (2020). Power in Networks and the Urban Space. In: Macrì, E., Morea, V., Trimarchi, M. (eds) Cultural Commons and Urban Dynamics. Springer, Cham. https://doi.org/10.1007/978-3-030-54418-8_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-54418-8_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-54417-1
Online ISBN: 978-3-030-54418-8
eBook Packages: Economics and FinanceEconomics and Finance (R0)