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In this chapter, Professor Dean Shepherd shares his experiences of becoming a qualitative researcher, bringing us on a [often personal] journey through his research beginnings, how his career developed and how he gravitated towards qualitative research. There are many lessons for Ph.D. students and early career academics and interesting takes on thinking about your research approach and impact.

This chapter describes the redevelopment of the Open Language Chief Executive Personality Tool (OLCPT), a language-based machine learning (ML) tool for assessing executives' traits along the five factor model (FFM) of personality (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism). Whereas the initial release of the OLCPT demonstrated the viability of using supervised machine learning to unobtrusively assess executives' personality traits, recent advances in artificial intelligence (AI) related to large language models (LLMs) warranted revisiting its development. After applying LLM embeddings and performing other updates, including expanding the training sample, the redeveloped tool (available at https://zenodo.org/records/10800801) achieved substantially higher convergent validity than the initial release. The updated tool also demonstrates strong discriminant validity and reliability, and it can measure traits not included in the initial version (narcissism and humility). These improvements demonstrate the potential value of continuously updating existing, computer-aided measures in strategy and management research. Yet, such efforts may not always be feasible or even necessary. Thus, we also use this chapter to offer guidelines for determining when updating similar measures is worthwhile, urging scholars to carefully consider how existing tools perform and the relevance of advancements to the technologies underlying them. We conclude with additional suggestions for advancing measurement in our field, including keeping up with emerging technologies, encouraging complementary approaches to enable triangulation, avoiding the use of advanced techniques without carefully considering their applicability in a given context, and being realistic about what we ask for during the review process and what we consider a meaningful contribution in our field.

Consciously or unconsciously, every management researcher adopts a certain philosophical perspective. In this chapter, I discuss the connection between philosophy and management research and show how philosophical perspectives affect the perception of empirical phenomena, choice of research methods, and interpretation of research results. The discussion indicates that the connection is far more crucial than what many management researchers may have thought. I then share my experience of studying philosophy and provide suggestions to those who are interested in enhancing their knowledge of the subject.

Virtual reality (VR) presents an important technological advancement that can enable management researchers to improve their laboratory work and test theories previously considered untestable. VR places a participant in a virtual environment completely designed and controlled by the research team. These environments can range from anything as benign as a regular corporate board meeting or a job interview to as hostile as a CEO answering questions in front of Congress or witnessing sexual harassment in an office hallway. A key feature of experimental work using VR is drastic improvements in external and ecological validity – VR allows researchers to transition experiments from measuring how participants self-report they would react in the real-world to measuring how they actually behave when confronted with a scenario literally in front of their eyes. While alluring, the design, coding, and implementation of studies using VR adds technical complexity to projects and care must be taken to be intentional throughout the process. In this manuscript, we provide guidance to management scholars to understanding VR, its potential applications, and the considerations one must undertake when creating studies using VR. Overall, we advocate the use of VR by management researchers in their work and introduce both a roadmap and best practices to jump-start such endeavors.

As the field of strategic management has evolved, expectations for the empirical evidence presented in manuscripts have risen substantially. Rather than a single model testing a hypothesis with a p-value below a standard threshold being sufficient, reviewers, editors, and eventual readers now demand additional evidence including multiple tests, advanced statistical models, alternative specifications, interpretation of practical rather than just statistical significance, and more. Reviewers appear to be increasingly skeptical and often raise a seemingly endless number of questions. In this chapter, I outline the idea of a body of evidence and suggest ways authors can build their evidence by anticipating reviewer questions and structuring manuscripts accordingly. Doing so allows authors to overcome skepticism by building positive rapport and trust with reviewers and the ultimate readers of their work. I conclude by discussing the review process where I offer suggestions about how reviewers and editors might adapt to this changing landscape. I specifically argue that all studies are flawed. Rather than asking for a single study to do more to address small inconsistencies or puzzling results, I suggest gatekeepers in the review process should consider the possibility that publishing and allowing research conversations to flourish might result in greater knowledge generation over time.

Strategic management research faces increasing calls concerning our work's relevance, reliability and credibility. Management journals have addressed these concerns by elevating the expectations for scholars during the publication process, such as publishing code, scripts and data. While the authors’ believe these changes are necessary for the field's long-term success, in the short term, there is a high resource cost for researchers (many with temporal constraints) to adjust to these new expectations. In this paper, the authors aim to decrease this cost on Strategic Management researchers in two ways. First, the authors discuss the vision, strengths and step-by-step instructions for the emerging code-sharing instrument – The SMART tool (Standardized Measures that are Accurate, Replicable and Time-saving, available at http://www.smartdatatool.net/) – for Strategic Management research. Second, the authors discuss some essential conditions for the tool's benefits to be fully realized by the field. Together, this paper offers the initial steps for creating a collaborative and open-source ecosystem for code and data in Strategic Management research that can strengthen stakeholder confidence in the field.