Configurational analysis of access to basic infrastructure services: evidence from Turkish provinces

In many developing countries, access to basic infrastructure services, such as sewerage and waste disposal, varies considerably across different areas. In this study, fuzzy-set qualitative comparative analysis identifies configurations of economic and political conditions (population density, population size, income and political participation) associated with good and poor access to sewerage and waste disposal in Turkish provinces. The findings suggest that there is a core configuration of conditions associated with good access to both types of infrastructure service—high income and high political participation. A single core configuration is associated with poor access to both types of service—low population density, small population size and low political participation. Other configurations are observed relating specifically to good and poor access to sewerage and waste disposal services, respectively. We theorise the different pathways that we identify, emphasising that economic measures to support development may offer the best prospect of improving infrastructure access

Managerial networking and stakeholder support in public service organizations

Resource dependence theory suggests that to function successfully, organizations must obtain certain resources controlled by actors in their environment. To do this effectively, managers often develop networking relationships with key stakeholder groups in order to make critical resources available. Managers in public service organizations, in particular, are frequently under great pressure to network with relevant actors from stakeholder groups in order to build support for service (co)production and legitimacy for strategic and operational decisions. To identify networking strategies which are conducive to stakeholder support, we explore the networking behaviour of over 1,000 English local government managers. Fuzzy cluster analysis identifies four distinctive, though inter-related types of managerial networking: technical, reputational, political, and tokenistic. The cluster membership functions from this analysis are used to examine the relationship between types of networking and stakeholder support in depth. The results of hierarchical regression analysis suggest that technically-orientated networking is the most conducive to stakeholder support, with tokenistic networking the least conducive

Country-level investigation of innovation investment in manufacturing: Paired fsQCA of two models

Innovation plays a critical role in economic growth. This study analyzes the association between actually implementing innovation and its antecedents, considering a country-level dataset covering innovation-active manufacturing firms in 47 countries. The relationship this article considers is between different drivers of innovation and market preparation for innovation. The study investigates this relationship through fuzzy-set Qualitative Comparative Analysis (fsQCA). The study examines the consideration of different sets of condition variables, identifies the importance of individual variables across causal recipes, and provides understanding of variations in the drivers towards market introduction of innovation between sets of countries. This study also provides an example of the effect on causal recipes in fsQCA when including/excluding a condition variable

Measuring and understanding the differences between urban and rural areas

Understanding the factors that make a location more rural or urban is an important task for planners and policymakers. Traditional individual characteristics of rurality sometimes hide the more complex social as well as physical dynamics of a locality. This paper builds on early work which applied factor analysis to construct a single index of rurality. An approach is developed with a combined metric encompassing multiple measures. These are capable individually of defining rurality but together they deliver greater insight on more complex patterns and help to redefine the simple notion of rurality. The paper then utilises a novel graphical method, the constellation graph, providing a diagnostic and visual framework to aid planners when assessing the spatial dimensions of a locality

Evaluating the performance of airports using an integrated AHP/DEA-AR technique

Airport efficiency is an area of increasing interest to academics, policy makers and practitioners. This has resulted in a body of literature applying various econometric techniques to compare efficiency between different samples of airports. This paper uses the multi-criteria decision making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables into Data Envelopment Analysis (DEA) and Assurance Region DEA (DEA-AR) models, with 24 major international airports in the empirical analysis. The paper concludes the discriminatory power in the proposed AHP/DEA-AR model is greater than in the basic DEA model when measuring the efficiency of airports. By applying this approach, policy makers and practitioners can effectively compare operational efficiency between airports, and therefore generate more informed decisions

Classification and Ranking Belief Simplex

The classification and ranking belief simplex (CaRBS), introduced in Beynon (2005a), is a nascent technique for the decision problems of object classification and ranking. With its rudiments based on the Dempster- Shafer theory of evidence—DST (Dempster, 1967; Shafer, 1976), the operation of CaRBS is closely associated with the notion of uncertain reasoning. This relates to the analysis of imperfect data, whether that is data quality or uncertainty of the relationship of the data to the study in question (Chen, 2001). Previous applications which have employed the CaRBS technique include: the temporal identification of e-learning efficacy (Jones & Beynon, 2007) expositing osteoarthritic knee function (Jones, Beynon, Holt, & Roy, 2006), credit rating classification (Beynon, 2005b), and ranking regional long-term care systems (Beynon & Kitchener, 2005). These applications respectively demonstrate its use as a decision support system for academics, medical experts, credit companies, and governmental institutions

A novel technique of object ranking and classification under ignorance: An application to the corporate failure risk problem

This paper exposits a novel technique for the ranking and classification of objects to a particular state. Each object is described by measurements from a number of variables which may offer different levels of support for the individual objects to be associated with the two states, a given hypothesis and not the hypothesis. The Dempster–Shafer theory of evidence is a central component of this technique. This allows for a measure of concomitant ignorance, which may encompass the precision of the individual measurements as well as the possible ambiguity of their influence in the subsequent classification of objects. The level of ignorance present influences the utilisation of the technique as a tool for the ranking or classification of objects. A simplex plot method of representing data allows a clear visual representation (interpretation) to the degree of interaction of the support from the variables to the ranking or classification of the objects. To illustrate the proposed technique, the application considered here is the elucidation of the risk of corporate failure of a number of companies. Subsequently, each variable (financial and non-financial) may offer support for the ranking and classification of companies to between the extreme states of being a failed or non-failed company. A comparison on the ranking and classification of companies is made with a traditional multivariate discriminant analysis