Dominance intensity measure within fuzzy weight oriented MAUT: An application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers' preferences, and imprecise weights are represented by trapezoidal fuzzy weights. The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights.     

Multiple Criteria Hierarchy Process with ELECTRE and PROMETHEE

Robust Ordinal Regression (ROR) supports Multiple Criteria Decision Process by considering all sets of parameters of an assumed preference model, that are compatible with preference information elicited by a Decision Maker (DM). As a result of ROR, one gets necessary and possible preference relations in the set of alternatives, which hold for all compatible sets of parameters, or for at least one compatible set of parameters, respectively. In this paper, we propose an extension of ELECTRE and PROMETHEE methods to the case of the hierarchy of criteria, which was never considered before. Then, we adapt ROR to the hierarchical versions of ELECTRE and PROMETHEE methods.     

Objective career success among paramedics: interaction effects of location and race

The purpose of the present study is to examine objective career success for paramedics. Specifically, it examined the effects of race (Minority versus White) and location of work (rural versus non-rural) on the objective career success of paramedics, as measured by salary. Multiple regression analyses were conducted on 10 years of data from nationally representative samples of paramedics. Results showed that the human capital variables of hours worked, experience, and education predicted objective career success. In addition, rural paramedics earned significantly less than do their counterparts in non-rural areas. Although far fewer in number than White paramedics, Minority paramedics appeared to earn more than White paramedics. The study concludes with suggestions for human resource development (HRD) practitioners and for further research.     

New MNE subsidiaries in old clusters: when,why, and how

Despite the rise of globalization, industrial clusters remain vibrant spaces for the generation of knowledge and innovation. Aware of this reality, multinational enterprises (MNEs) seek to reconcile the advantages of international operations with the specific endowments of individual territories. By studying the case of the Inditex subsidiary in the Vinalopó footwear cluster, this research shows how the creation and activity of a specialized subsidiary and the evolution of the industrial system interweave. The study shows that, rather than agglomeration per se, access to specific resources guides location as the cluster matures. Furthermore, local embeddedness shapes post-entry dynamics at the micro and meso levels. Autonomous decisions boost the subsidiary’s access to local networks and the exploitation of cluster advantages, aiding the resilience of the cluster by contributing extra-cluster knowledge.