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Purpose: The purpose of the paper is twofold: first, to examine whether the progress of strategic management research has been damaged by an excessive focus on statistical significance to the exclusion of substantive significance and second, to provide recommendations for improving research practice toward establishing the substantive significance of empirical findings.

Methodology/Approach: We conduct the same survey described in McCloskey and Ziliak (1996) on a sample of all 41 papers published in Strategic Management Journal during 2007 that use regression methodology. We use the criteria for good science represented by these survey questions as the foundation for our discussion. We present our arguments for the relevance of each of these criteria in strategy research with examples of best practice and provide a detailed analysis of areas of research practice that can be improved with associated recommendations.

Findings: Our survey suggests that there is indeed cause for concern, since 90% of our surveyed papers make no distinction between statistical and economic/substantive significance of their results. At the same time, many of the surveyed papers make some attempt to interpret their results in a substantively meaningful fashion.

Originality/Value of Paper: Our paper addresses a critical set of issues that influence progress in strategic management research. We provide a roadmap for how we can address these issues for progress in our field.

It has been discovered that some results published in studies may not be correct because different researchers using the same dataset and analytical methods were unable to create the same results. This dilemma is called the reproducibility crisis. Currently, there has not been a comprehensive examination of the possible existence of this crisis in the field of autism spectrum research. This chapter does not answer the question, ‘Is there a reproducibility crisis occurring in the field of autism spectrum research?’ Rather, it contains an outline of this crisis, explains some of the most influential factors that have contributed to its development and how scholars who study the autism spectrum can change their research practices so that this crisis does not develop.

The original contribution that this chapter makes to autism spectrum research is to explain how some solutions to the reproducibility crisis can be implemented into the field of autism spectrum research.

The objective of this chapter is to provide strategy researchers with a general resource for applying structural equation modeling (SEM) in their research. This objective is important for strategy researchers because of their increased use of SEM, the availability of advanced SEM approaches relevant for their substantive interests, and the fact that important technical work on SEM techniques often appear in outlets that may not be not readily accessible. This chapter begins with a presentation of the basics of SEM techniques, followed by a review of recent applications of SEM in strategic management research. We next provide an overview of five types of advanced applications of structural equation modeling and describe how they can be applied to strategic management topics. In a fourth section we discuss technical developments related to model evaluation, mediation, and data requirements. Finally, a summary of recommendations for strategic management researchers using SEM is also provided.

This chapter examines Massachusetts (USA) public primary and secondary educators' use of evidence-informed practices (EIPs). We pay special attention to the role of the Massachusetts Department of Elementary and Secondary Education (DESE) in this regard while employing the dual analytical frame laid out in this handbook's introduction. The first section provides relevant background/context and tentatively classifies the system according to the matrix. The next sections describe educators' use of evidence, and provide context, insights, and analyses in relation to the patterns presented. We note how certain forms of data are routinely being used (and describe DESE's role in facilitating and shaping such use), and we describe some bottom-up (and DESE-supported) research that is occurring within districts. Applying institutional analysis to this case, EIP in Massachusetts is skewed top-down in important ways, but there is also recognition of, and some earnest efforts also/instead to promote, more bottom-up EIP in and across Massachusetts schools and educational organizations. Overall, we advance this case as providing an example of a robust infrastructure at the macrolevel (DESE) that can facilitate and shape EIP, and especially in relation to providing relevant and timely data and supporting its use by educators. Accordingly, our final section focuses on how/why DESE has been successful in these endeavors, as a way of drawing out key lessons. This chapter also includes an appendix containing links to a variety of tools, reports, and resources, which may be of interest to readers interested in further exploring or applying similar approaches.

Our approach is largely historical, argument by example. We leave it to the theoreticians and empiricists to take the argument in a more technical direction.¹ Throughout, we suppose that germs are self-interested and they have a research question, for example, how might our species improve the chances of survival, the answer to which might potentially benefit germs (or, harm them by less).

This chapter is about education in four Central Asian states which were part of the former USSR until 1991. These countries have common legacy, yet, have been evolving with their own trajectories. The chapter provides the demographic information, politics, economy, social system, religion and worldview, followed by the presentation of education system of each country. The chapter presents both accomplishments and setbacks of the four counties in the education sector, highlighting key trends and strategic growth areas.