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Within the literature of global mindset there has been much discussion of antecedents. Few attempts have been made, however, to analyze the outcomes of a global mindset. Our chapter undertakes a thematic analysis of global mindset antecedents and outcomes in the 1994–2013 literature. Adopting an inductive approach and borrowing methods from international business and managerial cognition studies, we map, assess, and categorize 42 empirical and 10 theoretical studies thematically. We focus on the antecedents and outcomes at individual, group, and organizational levels. We conceptualize corporate global mindset as a multidimensional construct that incorporates global mindset at the individual level and is dependent on a robust communications infrastructure strategy for its cultivation throughout the organization. Our study categorizes antecedents and outcomes by level and identifies the gaps in global mindset outcomes and firm performance for future researchers to address.

Entrepreneurship education has been largely treated as a pedagogical “black box.” Despite the emergence of popular entrepreneurship models such as business planning, the lean startup, or business model canvas, neither theoretical nor pedagogical foundations are typically evident. This limits the accumulation of useful evidence that could inform better teaching practices. In this chapter, we develop a set of conceptual models anchored in learning theory regarding how entrepreneurship education should be taught to students. These conceptual models are built on the techniques of entrepreneurship pedagogy such as experiential education. They are developed for three groups of students: students without any entrepreneurship experience, students with previous entrepreneurship experience, and students who are currently running their start-ups. A set of potential variables that could be used for course evaluation purposes is also included. The proposed models meet the needs of students with different levels of entrepreneurship experience. Theoretically, we demonstrate that entrepreneurship students should not be treated as a homogeneous group, as they have different levels of startup experience and different educational needs. Lecturers of entrepreneurship programs could choose the suitable model proposed in this chapter in teaching based on the characteristics of their students. The chapter provides novel insights with regard to how entrepreneurship programs should be designed for students with different levels of entrepreneurship experience.

This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

Global Mindset (GM) is a multifaceted construct that has received broad interest among practitioners and academics. It is a fragmented construct at this point in time, due to definitional overlap with other constructs such as global leadership and cultural intelligence. This overlap has created complexity for research that attempts to understand GM in isolation. Lack of clear boundaries in defining and conceptualizing this construct challenges researchers who are attempting to capture fully what constitutes GM. Our work seeks to better understand and explain what underlines the individual GM construct and how does this impact the development of global competencies in individual managers.

We systematically review and analyze the individual GM literature thematically to provide an overview of the extant research from a broad array of scholarly sources dating from 1994 to 2017. Our work offers a thematic analysis that provides a visual guide to GM by tracking the corpus of individual-level GM studies. We categorize the research according to its theoretical groundings and basic concepts and proceed review how GM has been operationalized at the individual level and measured. Next, we integrate major dimensions in the GM research and propose a framework to enhance understanding of the phenomenon. Finally, we discuss the implications of our review for the development of GM for practitioners, coaches and trainers.

Purpose – This chapter examines how sentiment analysis and web-crawling technology can be used to conduct large-scale data analyses of extremist content online.

Methods/approach – The authors describe a customized web-crawler that was developed for the purpose of collecting, classifying, and interpreting extremist content online and on a large scale, followed by an overview of a relatively novel machine learning tool, sentiment analysis, which has sparked the interest of some researchers in the field of terrorism and extremism studies. The authors conclude with a discussion of what they believe is the future applicability of sentiment analysis within the online political violence research domain.

Findings – In order to gain a broader understanding of online extremism, or to improve the means by which researchers and practitioners “search for a needle in a haystack,” the authors recommend that social scientists continue to collaborate with computer scientists, combining sentiment analysis software with other classification tools and research methods, as well as validate sentiment analysis programs and adapt sentiment analysis software to new and evolving radical online spaces.

Originality/value – This chapter provides researchers and practitioners who are faced with new challenges in detecting extremist content online with insights regarding the applicability of a specific set of machine learning techniques and research methods to conduct large-scale data analyses in the field of terrorism and extremism studies.

Purpose – The purpose of this chapter is to highlight recent research addressing theories of female offending and the context of female perpetrated homicides. Women have often been omitted in research and theory development, thus gendered interventions and treatments lag behind. Additionally, female perpetrated homicides are rare, consequently research examining the context of the events and the events leading up to the homicide are inadequate.

Design/methodology/approach – The approach is to examine the historical research on female offenders, the context of female violent offenses particularly homicide offenses, and emerging theories of gendered experiences into criminal activities for women.

Findings – Findings indicate that gender matters when explaining theories of female offending and when examining the context of female perpetrated homicides.

Originality/value – Females have different life events from males, and these life events create distinct pathways into criminal offending, including the ultimate offense of homicide. Based on these differences, theory development as well as intervention and prevention strategies must be designed that are gender specific.

Worker classification continues to be a highly litigated area of taxation. That is, the status of a worker as an employee or independent contractor remains a topic closely scrutinized by the Internal Revenue Service. This study examines factors that the judiciary deems relevant in ruling whether a worker is an employee or independent contractor. A backward stepwise logistic regression model is implemented to categorize the factors that best predict the court’s decision on whether a worker is either an employee or independent contractor pursuant to the factors in Revenue Ruling 87-41 (1987-1 CB 296), judge gender, and political affiliation. The results indicate three factors (supervision/instructions, continuing relationship, and the right to discharge) are capable of accurately predicting 93 percent of the decisions made by the US Tax Court. Other findings support notable statistical differences between male and female judges rendering decisions and reaching conclusions. Also, there is a statistically significant difference based on the type of industry. Political affiliation appears to have no significant impact on judicial rulings.