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on Network Economics |
| By: | Helmut Dietl (Institute for Strategy and Business Economics, University of Zurich); Christian WeingŠrtner (Institute for Strategy and Business Economics, University of Zurich) |
| Abstract: | Professional football clubs earn most of their revenues from four sources: sale of broadcasting rights, matchday revenues, merchandising, and sponsorship. The relative importance of these sources differs among clubs and leagues. Economists often argue that the ability of professional football clubs to generate revenues depends to a large extent on their legal structure. In this paper we analyze the effect of different legal structures, such as private company, public company, membersÕ association, on sponsorship. Based on the platform theory we introduce a model of value creation in professional football. After elaborating the property rights situation for each of the legal structures we show the direct and indirect effects on the generation of sponsorship revenues. We theoretically proof the membersÕ association to be the favorable legal structure with regard to sponsorship. The lack of hold-up risks for the stakeholders and the strong position of the fans are the major reasons for the superiority of this non-profit legal structure. |
| Keywords: | Organization, Sponsorship, Network Effects, Platform, Property Rights |
| Date: | 2011–01 |
| URL: | https://d.repec.org/n?u=RePEc:iso:wpaper:0141&r=net |
| By: | Subhash C. Ray (University of Connecticut) |
| Abstract: | In the present study we evaluate the overall cost efficiency of a network of branches of a single large public sector bank in India within the city of Calcutta using the data for the year 2002. Our objective is to determine the optimal number of branches within a postal district that could provide the observed amounts of banking services to the customers in that area at the minimum operating cost. Our DEA results show that while in many cases, consolidating multiple branches would be more cost efficient, there are numerous instances, where increasing the number of branches would be optimal. |
| Keywords: | Network Efficiency; DEA; Banking. |
| JEL: | C61 G21 L25 |
| Date: | 2011–01 |
| URL: | https://d.repec.org/n?u=RePEc:uct:uconnp:2011-03&r=net |
| By: | Xavier Fageda (Department of Economic Policy, Universitat de Barcelona, Avinguda Diagonal 690, 08034 Barcelona, Spain.); Ricardo Flores-Fillol (Department of Economics, Universitat Rovira i Virgili, Avinguda de la Universitat 1, 43204 Reus, Spain.) |
| Abstract: | Network airlines have been increasingly focusing their operations on hub airports through the exploitation of connecting traffic, allowing them to take advantage of economies of traffic density, which are unequivocal in the airline industry. Less attention has been devoted to airlines? decisions on point-to-point thin routes, which could be served using different aircraft technologies and different business models. This paper examines, both theoretically and empirically, the impact on airlines ?networks of the two major innovations in the airline industry in the last two decades: the regional jet technology and the low-cost business model. We show that, under certain circumstances, direct services on point-to-point thin routes can be viable and thus airlines may be interested in deviating passengers out of the hub. |
| Keywords: | regional jet technology, low-cost business model, point-to-point network, hub-and-spoke network |
| JEL: | L13 L2 L93 |
| Date: | 2010–12 |
| URL: | https://d.repec.org/n?u=RePEc:xrp:wpaper:xreap2010-14&r=net |
| By: | Aloysius Gunadi, Brata |
| Abstract: | This research found most of the handicraft producers have conducted various innovations during last five years. The newest innovations are managerial innovation, marketing innovation and product innovation. Meanwhile, product innovation and managerial innovation are the most important innovations in enhancing the business performance. Based on the actors, innovation in this case could be classified as producer driven innovation. The main information source of product innovation, process innovation, and service innovation is the producer’s experiences itself. The study found that the role of social networks in the process of innovation activities is rather limited. This finding is also supported by a fact that the strongest social network of the producers is only the relation with family and close friend in term of their closeness, trust, and willingness to share information. Regression analysis also indicates the aggregate of social network elements does not influence the number of innovations. Components of social network that still show positive impact on the innovation are only the closeness with business partners and with members of other association. The study also suggest that research on the role of social network or social capital on innovations is need to consider more appropriate indicators of social networks. At the empirical level, differences in location or industry may require different indicators of social networks. |
| Keywords: | social network; innovation; handicraft industry |
| JEL: | O17 Z13 |
| Date: | 2011–01 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:28032&r=net |
| By: | Ramón Jesús Flores Díaz; Maurice Koster; Ines Lindner; Elisenda Molina |
| Abstract: | Given a social network, we are interested in the problem of measuring the influence of a group of agents to lead the society to adopt their behavior. Motivated by the description of terrorist movements, we provide a markovian dynamical model for non-symmetric societies, which takes into account two special features: the hard core terrorist group cannot be influenced, and the remaining agents may change from active to non-active and vice versa during the process. In this setting, we interpret the absorption time of the model, which measures how quickly the terrorist movement achieve the support of all society, as a group measure of power. In some sense, our model generalizes the classical approach of DeGroot to consensus formation |
| Keywords: | Collective action, Social networks, Influence and Diffusion models |
| Date: | 2010–12 |
| URL: | https://d.repec.org/n?u=RePEc:cte:wsrepe:ws104830&r=net |