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This chapter introduces evolutionary neuroscience and its organizational applications, especially its usefulness for motivation analysis in macrolevel disciplines such as strategic management. Macrolevel organizational disciplines have mostly lacked a theory of motivation beyond self-interest assumptions, which fail to explain many important macrolevel organizational phenomena. Evolutionary neuroscience provides an empirically grounded, parsimonious perspective on the human brain and brain evolution which helps clarify the profound complexities of motivation. Evolutionary neuroscience’s theory of the physiological causes of self- and other-interested motivation can support better macrolevel motivation analysis and unify disparate, potentially conflicting motivation theories. Examples are offered of how neuroscience-based motivation theory can support more comprehensive strategic management analysis of competences and competitive advantage.

Executive stock option grants are intended to remove corporate governance problems by aligning the managers’ interests with those of the outside shareholders. Conventional schemes leave several problems in place. Exotic option structures can resolve these. In this paper, such structures are proposed and tested on the Dow Jones constituents over a 10-year period. These alternative schemes increase the financial rewards to the better performing managers, at no extra cost to the company whilst offering a resolution or mitigation of the identified agency problems No one scheme dominates the others and a portfolio of option types is indicated.

In the last few decades, there has been growing interest in forecasting with computer intelligence, and both fuzzy time series (FTS) and artificial neural networks (ANNs) have gained particular popularity, among others. Rather than the conventional methods (e.g., econometrics), FTS and ANN are usually thought to be immune to fundamental concepts such as stationarity, theoretical causality, post-sample control, among others. On the other hand, a number of studies significantly indicated that these fundamental controls are required in terms of the theory of forecasting, and even application of such essential procedures substantially improves the forecasting accuracy. The aim of this paper is to fill the existing gap on modeling and forecasting in the FTS and ANN methods and figure out the fundamental concepts in a comprehensive work through merits and common failures in the literature. In addition to these merits, this paper may also be a guideline for eliminating unethical empirical settings in the forecasting studies.

This study examines the legal codification of nascent markets, specifically, the process of defining and incorporating Islamic banking and organic agriculture within the legal system in Turkey. I find that actors’ priorities differ significantly with respect to formal codification and that the existing legal order and socio-political and economic contexts shape how state and non-state actors influence legislative and regulative action. This study contributes to our understanding of how actors and their ideological commitments and relational concerns affect the legal formulation of new industries.

The paper explores the pattern of early closure risks for worker cooperatives, whether this pattern involves a “liability of newness” or a “liability of adolescence” and whether it applies identically to coops created from scratch, to rescues of failing firms and to conversions from sound conventional businesses to the cooperative form. Non-parametric hazard curves are estimated using data on the 2,740 worker cooperatives created in France in 1977–1993, 1,660 of which exited during the period. Comparisons are drawn with conventional French firms whenever data for the same cohorts are available.