It is often the case, although it has not been well-documented, that local governments aiming for economic growth tend to formulate and implement very similar, or even identical, policies. This phenomenon is referred to as the `isomorphism of local development policy', or `local policy isomorphism'. Five mechanisms are theoretically elaborated in order to explain the phenomenon of local policy isomorphism. The different regions formulate similar development strategies for the following reasons: they face similar pressure from the central government (or international organisations); they are competing for investments that are highly mobile; they engage in mimetic learning attributable to the uncertainties of development; experienced personnel move from advanced regions to underdeveloped areas; and, professional organisations are involved on a consultancy basis. The case of the formation and transformation of national development zones in the Jiangsu province in post-Mao China is used to illustrate the empirical applications of these five mechanisms.
This paper proposes and evaluates the novel utilization of small world network properties for the formation of team of players with both best performances and best belongingness within the team network. To verify this concept, this methodology is applied to T-20 cricket teams. The players are treated as nodes of the network, whereas the number of interactions between team members is denoted as the edges between those nodes. All intra country networks form the cricket network for this case study. Analysis of the networks depicts that T-20 cricket network inherits all characteristics of small world network. Making a quantitative measure for an individual performance in the team sports is important with respect to the fact that for team selection of an International match, from pool of best players, only eleven players can be selected for the team. The statistical record of each player considered as a traditional way of quantifying the performance of a player. But the other criteria such as performing against a strong opponent or performance as an effective team member such as fielding, running between the wickets, good partnership deserves more credential. In this paper a revised method based on social networking is presented to quantify the quality of team belongingness and efficiency of each player. The application of Social Network Analysis (SNA) is explored to measure performances and the rank of the players. A bidirectional weighted network of players is generated using the information collected from T-20 cricket (2014–2016) and used for network analysis. Thus team was formed based on that ranking and compared with their IPL (Indian Premier League) performances of 2016.