Application of Fuzzy Risk Analysis for Selecting Critical Processes in Implementation of SPC with a Case Study

Fuzzy risk analysis is widely used in risk assessment of components by linguistic terms. Fuzzy numbers are used to quantify the associated uncertainty. This study employs fuzzy risk analysis to evaluate processes for implementing statistical process control (SPC) in a specified manufacturing system. To reach this goal, fuzzy risk analysis has been applied based on both ranking and similarity of generalized trapezoidal fuzzy numbers in a stepwise procedure. Therefore, a new approach has been introduced for fuzzy risk analysis of processes to overcome the shortcomings of previous fuzzy risk analysis approaches. As a result, fuzzy risk analysis is used as a decision making technique to select critical processes under uncertainty. Also, the application of the proposed SPC implementation algorithm is illustrated in the manufacturing line of a car battery factory.     

The Coordinated Effect of a Merger with Balanced Sharing of Collusive Profits

It is hard to assess the coordinated effect of mergers in solid and convincing fashion, in part because economic theory deals mainly with the sustainability of tacit collusion and generally does not explore the conditions that foster collusion in the first place. Also the most popular schemes of collusion (Joint profit maximization and Nash Bargaining) proposed by the economic literature seem at odds with the evidence recorded on cartels and with the practical attitude of entrepreneurs. In this scenario the recent version of the Horizontal Merger Guidelines contained the interesting suggestion to pay attention to the process - parallel behaviour – which leads to collusive equilibria. Working on the same intuition we propose an approach based on the idea that firms can always find a feasible collusive agreement, for every possible value of the factor which discounts future profits. Assuming that in order to collude, firms demand the fair sharing of collusive gains, we exploit the egalitarian property of grim trigger strategies when all incentive compatibility constraints are binding. This approach suggests using three indicators to determine whether and how a merger affects the probability of collusion. An application of this approach to a real-world case (the AT&T/T-Mobile merger) is provided.     

Ownership structure and golden parachutes: Evidence of credible commitment or incentive alignment?

Using a sample of S & P 500 firms, we find that golden parachutes are associated with concentrated external ownership, less concentrated internal ownership, and non-Delaware incorporation. We find little support that concentrated external owners use golden parachutes as credible commitment devices. The general multivariate results support the incentive alignment hypothesis, and reaffirm the view that golden parachutes are a mechanism used to align managerial and shareholder interests when there is a separation between ownership and control. (JEL G32)     

Comparison of Hypothesis Testing and Bayesian Model Selection

The main goal of both Bayesian model selection and classical hypotheses testing is to make inferences with respect to the state of affairs in a population of interest. The main differences between both approaches are the explicit use of prior information by Bayesians, and the explicit use of null distributions by the classicists. Formalization of prior information in prior distributions is often difficult. In this paper two practical approaches (encompassing priors and training data) to specify prior distributions will be presented. The computation of null distributions is relatively easy. However, as will be illustrated, a straightforward interpretation of the resulting p-values is not always easy. Bayesian model selection can be used to compute posterior probabilities for each of a number of competing models. This provides an alternative for the currently prevalent testing of hypotheses using p-values. Both approaches will be compared and illustrated using case studies. Each case study fits in the framework of the normal linear model, that is, analysis of variance and multiple regression.     

Optimising a Probabilistic Model of the Development of Play in Soccer

We present a probabilistic model based on the one developed by Hernández Mendo and Anguera (Revista de Psicologíca Social, 16(1), 71–93, 2001). Here we have tried to break down the interaction contexts that the opposing teams are able to generate and transform during the game. We are aware that a given player or team does not produce consistent behaviour in similar situations. However, a degree of uncertainty is assumed to exist regarding whether the results obtained are a specific function of the analysis used. In order to carry out this research a category system which optimized that used in the previous model was developed. This system should enable the interaction between teams to be observed within the actual play of a soccer game. A lag sequential analysis was performed on the basis of a coding of the behavioural flow. After describing the behavioural patterns obtained a probabilistic model of the development of play in soccer is proposed.     

Barriers to women entrepreneurship. Different methods,different results?

Building on research by Akehurst et al. (Serv Ind J 32:2489–2505, 2012), this study analysed internal and external factors in women entrepreneurship and linked these factors to the barriers that women face when starting businesses. To do so, two contrasting statistical techniques were used: PLS and QCA. After analysing results from each of these techniques, we observed that family duties and difficulties in obtaining financing (both internal and external) were the main factors related to barriers faced by women entrepreneurs.     

Social capital and entrepreneurial process

The paper examines the relationship between social capital and entrepreneurial engagement of individuals in 35 nations from Europe and Asia. To the best of our knowledge, this is the first empirical research that attempts to investigate the influence of three-dimensional social capital concept – trust, networks and norms – on three stages of entrepreneurial process – preference, trial and success – using such large and comprehensive cross-sectional micro data. In general, we find that all three dimensions of social capital matter in the entrepreneurship context, albeit differently. They become beneficial in different ways and at different stages of entrepreneurial involvement. For example, among trust variables, institutional trust in general, and trust in business-oriented and business-supporting actors in particular, exert significant positive effect on entrepreneurial process. Individuals with formal membership in professional associations are more likely to perceive entrepreneurial opportunities, while some close or strong-tie networks might prevent them from progressing in the entrepreneurship ladder. Finally, individual level civic norms appear to be negatively associated with early-stage entrepreneurship, while the success in becoming an entrepreneur is not found to be bound by people’s civic norms.