This study analyses how firms act with regard to social responsibility from the perspective of Stakeholder Theory. The objective is to empirically analyse the importance of communication with stakeholders for social responsibility. This involves the establishment of a structural equation model that enables analysis of the empirical relationship between firms' degree of communication with stakeholders and the effectiveness of their corporate social responsibility, measured by corporate social performance (CSP). We adopt a Bayesian approach that enables exact inferences concerning the model's parameters and handles missing data by random imputations, thus increasing the study's reliability. The results obtained from a sample of 416 Spanish organisations show the importance of interacting and establishing channels of communication with different stakeholders in order to identify their specific demands and expectations. Indeed, communication with stakeholders helps firms to improve their CSP programmes and activities. We can thus conclude that failure to establish good communication channels could have a negative effect on social responsibility.

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Corporate Social Responsibility (CSR) is becoming a dominant issue in both research and practice of management. However, the underlying processes in the relationship between the degree of development of CSR in companies and the drivers/barriers that determine this development are still at the center of an intense debate. The purpose of this empirical study is to examine these relationships. We investigate a sample of 416 Spanish firms; based on a multifactorial framework, our study considers both the subjective and objective drivers/barriers, analyzing their joint effect on the final degree of sustainability. A structural equation model is established and a Bayesian approach is used, enabling exact inferences about the model's parameters and handling missing data with random imputation, thus increasing the study's reliability. The results show that this degree is related to what managers believe CSR to be (subjective drivers/barriers) and what managers expect it to accomplish or outcomes (objective drivers/barriers).

The two procedures traditionally followed for group decision making with the Analytical Hierarchical Process (AHP) are the Aggregation of Individual Judgments (AIJ) and the Aggregation of Individual Priorities (AIP). In both cases, the geometric mean is used to synthesise judgments and individual priorities into a collective position. Unfortunately, positional measures (means) are only representative if dispersion is reduced. It is therefore necessary to develop decision tools that allow: (i) the identification of groups of actors that present homogeneous and differentiated behaviours; and, (ii) the aggregation of the priorities of the near groups to reach collective positions with the greatest possible consensus. Following a Bayesian approach to AHP in a local context (a single criterion), this work proposes a methodology to solve these problems when the number of actors is not high. The method is based on Bayesian comparison and selection of model tools which identify the number and composition of the groups as well as their priorities. This information can be very useful to identify agreement paths among the decision makers that can culminate in a more representative decision-making process. The proposal is illustrated by a real-life case study.