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Despite all the attempts developed so far to measure corporate social performance in the last decades, a standard metric for it is still missing. In this work, the author tries to understand why is this the case. To do so, the author has reviewed 69 relevant metrics developed in the literature since the 1970s until today, covering approaches based on social, reputational, and environmental ratings, as well as several others constructed ad hoc by reputated scholars. The author analyzes each of them through a double optics, checking if they meet the minimum requirements to be considered standard and truly social. The research reveals that the main factor that prevents such a standard is the lack of truly social orientation of the existing metrics.

Despite a legacy of research that emphasizes contradictions and their role in explaining change, less is understood about their character or the mechanisms that support them. This gap is especially problematic when making causal claims about the sources of institutional change and our overall conceptions of how institutions matter in social meanings and organizational practices. If we treat contradictions as a persistent societal feature, then a primary analytic task is to distinguish their prevalence from their effects. We address this gap in the context of US electoral discourse and education through an analysis of presidential platforms. We ask how contradictions take hold, persist, and might be observed prior to, or independently of, their strategic use. Through a novel combination of content analysis and computational linguistics, we observe contradictions in qualitative differences in form and quantitative differences in degree. Whereas much work predicts that ideologies produce contradictions between groups, our analysis demonstrates that they actually support convergence in meaning between groups while promoting contradiction within groups.

This chapter integrates research that highlights and demonstrates the importance of the marketing mix and customer attitudinal metrics in influencing the customer’s path to purchase. A key objective of this chapter is the provision of an integrative conceptual framework that links marketing actions to customer mindset metrics along the consumer’s path to purchase and the identification of the mechanisms by which customer mindset metrics contribute to consumer purchase journey. Specifically, it delineates two routes for the effects to manifest on sales: the “mindset route” where marketing actions influence customer mindset metrics, which in turn influence brand performance, or the “transactions route” where marketing actions influence market performance directly without influencing the intermediate mindset metrics. A second objective is to identify empirical patterns on incorporating marketing mix and mindset metrics along the path to purchase by reviewing key papers in this domain. Finally, the chapter concludes with the formulation of a rich, forward-looking research agenda on the customer mindset metrics – path to purchase link.

This paper aims to propose a new method to derive custom dynamic cyber risk metrics based on the well-known Goal, Question, Metric (GQM) approach. A framework that complements it and makes it much easier to use has been proposed too. Both, the method and the framework, have been validated within two challenging application domains: continuous risk assessment within a smart farm and risk-based adaptive security to reconfigure a Web application firewall.

The authors have identified a problem and provided motivation. They have developed their theory and engineered a new method and a framework to complement it. They have demonstrated the proposed method and framework work, validating them in two real use cases.

The GQM method, often applied within the software quality field, is a good basis for proposing a method to define new tailored cyber risk metrics that meet the requirements of current application domains. A comprehensive framework that formalises possible goals and questions translated to potential measurements can greatly facilitate the use of this method.

The proposed method enables the application of the GQM approach to cyber risk measurement. The proposed framework allows new cyber risk metrics to be inferred by choosing between suggested goals and questions and measuring the relevant elements of probability and impact. The authors’ approach demonstrates to be generic and flexible enough to allow very different organisations with heterogeneous requirements to derive tailored metrics useful for their particular risk management processes.