Search results

In this chapter, we explicate two related techniques that help quantify the sensitivity of a given causal inference to potential omitted variables and/or other sources of unexplained heterogeneity. In particular, we describe the Impact Threshold of a Confounding Variable (ITCV) and the Robustness of Inference to Replacement (RIR). The ITCV describes the minimum correlation necessary between an omitted variable and the focal parameters of a study to have created a spurious or invalid statistical inference. The RIR is a technique that quantifies the percentage of observations with nonzero effects in a sample that would need to be replaced with zero effects in order to overturn a given causal inference at any desired threshold. The RIR also measures the percentage of a given parameter estimate that would need to be biased in order to overturn an inference. Each of these procedures is critical to help establish causal inference, perhaps especially for research urgently studying the COVID-19 pandemic when scholars are not afforded the luxury of extended time periods to determine precise magnitudes of relationships between variables. Over the course of this chapter, we define each technique, illustrate how they are applied in the context of seminal strategic management research, offer guidelines for interpreting corresponding results, and delineate further considerations.

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.

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.

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.

The purpose of this paper is to investigate the impact of Jewish holidays on US stock market returns.

The authors use event study and regression methodology to determine abnormal returns on Jewish holidays and windowed periods surrounding the day. In order to seclude the results to Jewish holidays, the authors control for several other known events that impact stock market returns. To substantiate claims of abnormal returns, the authors also use the Fama‐French four‐factor model to seek alpha and evidence returns on Jewish holidays.

This study shows, during the 1990‐2009 period, an increase in average daily returns 32 times greater on nine Jewish holidays than on the other trading days of the year. The demeanor of the specific Jewish holidays also influences stock market returns, as the market returns increase (decrease) on the joyous (solemn) Jewish holidays. Also, individual investors, rather than institutional investors, are a greater catalyst for the increased returns.

Previous research details increased stock market returns on US holidays and several other events. However, no definable research exists on stock market returns on Jewish holidays. The findings in this paper are valuable to investors who event‐trade, and are also valuable to investors and behavioral‐finance researchers who seek to understand how demeanor and moods may impact buying/selling decisions.

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.

The purpose of this paper is to examine the effect of shared leadership on the gap between male and female leadership influence in groups.

The leadership influence of 231 members from 28 committees was studied using a social networks methodology. Gender differences in committee members’ directive and supportive leadership influence were analyzed through two ANCOVA tests.

Results confirm significant differences between men and women’s leadership influence, as rated by their peers, using directive and supportive leader behaviors. Surprisingly, shared leadership has no significant effect on reducing this gender gap.

Results cannot be extrapolated to all other types of groups, since the committees studied have very unique characteristics due to their low typical mutual interaction.

Organizations may need to consider complementary strategies in their group leadership design to prevent the emergence of strong gender gaps when leadership is shared. These strategies could involve training members to recognize gender inequalities in leadership status and assigning leadership roles formally to ensure more equal participation in leadership.

This paper examines the promise of gender equality in shared leadership and provides empirical data that shows that this promise is not being realized.

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.