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This study enriches the theory of effectuation by discussing the four independent dimensions of effectuation and their relationships with causation. Additionally, we fill the gap in prior literature by showing how entrepreneurial experience moderates the relationship between effectuation and innovativeness of the venture. Our study of 171 practising entrepreneurs regarding their entrepreneurial decision-making logic yielded multiple findings. The authors find that entrepreneurs rely on causation as well as effectuation in their decision-making; the more experienced entrepreneurs are, the more they actually use causation; and entrepreneurial experience moderates the relationship between effectuation and innovativeness of the venture firm.

The purpose of this chapter is to offer reflections on conventional theories concerning causes and determinants of diseases. It also intends to examine both theoretical and empirical bases for adopting an Integrated Social-Ecological Systems (ISES) lens as a tool for understanding complexities related to drivers, determinants and causes of diseases.

We assessed the theoretical underpinnings of a range of historical and contemporary lenses for viewing infectious disease drivers and the implications of their use when used to explain both personal (i.e. individual) and population health. We examined these issues within the empirical context of the City of Dhaka (Bangladesh) by adopting an ISES lens. Within this study an emphasis has been placed on illustrating how feedback loops and non-linearity functions in systems have a direct bearing upon various aspects of infectious disease occurrences.

A brief triumph over microbes during the last century stemmed in part from our improved understanding of disease causation which was built using disciplinary-specific, monocausal approaches to the study of disease emergence. Subsequently, empirical inquiries into the multi-factorial aetiology and the ‘web of causation’ of disease emergence have extended frameworks beyond simplistic, individualistic descriptions of disease causation. Nonetheless, much work is yet to be done to understand the roles of complex, intertwined, multi-level, social-ecological factors in affecting disease occurrence. We argue, a transdisciplinary-oriented, ISES lens is needed to explain the complexities of disease occurrence at various and interacting levels. More theoretical and empirical formulations, with evidence derived from various parts of the world, is also required to further the debate.

Our study advances the theoretical as well as empirical basis for considering an integrated human-nature systems approach to explaining disease occurrence at all levels so that factors at the individual, household/neighbourhood, local, regional and global levels are not treated in isolation.

Potentially major shifts in privacy norms are taking place as a result of advances in genetic technologies. This chapter identifies a spillover effect in the form of the inadvertent emergence of new norms and introduces an original typology developed in response to these new norms regarding privacy. It focuses on the emerging practice of compelling access to genetic information of biologically related persons to gain information about a particular individual. This chapter highlights the recent practice in child lead paint poisoning cases in which defendants seek to discover medical and I.Q. records of biologically related non-parties to establish alternate genetic causation of low I.Q. It concludes that greater attention should be given to the spillover effect and the emergence of shadow norms.

This chapter is an appreciation of and a critical reflection on Sarasvathy's work on the causation and effectuation models of entrepreneurship. While Sarasvathy has made significant contributions to the field, it is suggested that more fruitful results can be achieved if two modifications are made. First, it is argued that the six dimensions on which the two models differ are independent and therefore it is more fruitful to focus on the dimensions rather than on the two models. Second, it is argued that a pragmatic view of entrepreneurship is most fruitful when it is not applied at the level of the entrepreneurial process, but at the level of underlying human actions.

Large-scale data analytics have raised a number of ethical concerns. Many of these were introduced in a seminal paper by boyd and Crawford and have been developed since by others (boyd & Crawford, 2012; Lagoze, 2014; Martin, 2015; Mittelstadt, Allo, Taddeo, Wachter, & Floridi, 2016). One such concern which is frequently recognised but under-analysed is the focus on correlation of data rather than on the causative relationship between data and results. Advocates of this approach dismiss the need for an understanding of causation, holding instead that the correlation of data is sufficient to meet our needs. In crude terms, this position holds that we no longer need to know why X+Y=Z. Merely acknowledging that the pattern exists is enough.

In this chapter, the author explores the ethical implications and challenges surrounding a focus on correlation over causation. In particular, the author focusses on questions of legitimacy of data collection, the embedding of persistent bias, and the implications of future predictions. Such concerns are vital for understanding the ethical implications of, for example, the collection and use of ‘big data’ or the covert access to ‘secondary’ information ostensibly ‘publicly available’. The author’s conclusion is that by failing to consider causation, the short-term benefits of speed and cost may be countered by ethically problematic scenarios in both the short and long term.

As the developing nations grow and experience rapid institutional transformation, research has begun to investigate the roles of culture, cognition and institutional context on entrepreneurship and innovation. This chapter aims to advance the entrepreneurial cognition literature by juxtaposing entrepreneurial effectuation, domain-specific expertise and ambiguity. By conducting a qualitative study of Chinese high-tech domestic and returnee entrepreneurs, the authors propose a spectrum between causation and effectuation and argue that the entrepreneur’s perceived level of ambiguity may better explain differing logic orientations among entrepreneurs, contributing to our understanding of entrepreneurial cognition. The authors theorize that (1) individual actors and the level of institutional development jointly comprise the entrepreneur’s logic orientation; (2) the level of perceived ambiguity mediates the strategy adopted by high-tech entrepreneurs; (3) the entrepreneur’s logic orientation can be regarded as a continual spectrum from effectuation to causation. Finally, the logic orientation concept is applied to the context of cross-border mergers and acquisitions (M&A) from a process perspective and the implications and fit of logic orientation with the stages of cross-border M&A are discussed.

Since its resurrection during the 1980s, comparative-historical sociology has been repeatedly critiqued on two fronts. Quantitative methodologists have argued that its “causal inferences” are unreliable due to its “small n.” And methodological individualists have argued its explanatory accounts are unacceptable because they do not specify “microfoundations.” But these critiques are built on faulty foundations, namely, a regularity theory of causation and a reductionist social ontology. In this article, I propose an alternative foundation derived from Critical Realism: a production theory of causation and an emergentist account of social structure.