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This chapter explores the interplay between organizational conservatism (OC) and corporate social responsibility (CSR) practices within family firms, specifically in Morocco. By exploring the familial dimensions of CSR, the study aims to uncover the impact of OC on CSR strategies, outcomes, and implications. Employing an exploratory qualitative design with multiple case studies, the research examines three Moroccan family firms. Thematic content analysis (TCA) was used to synthesize interview data and extract primary themes. The findings illustrate that OC fosters stable, values-driven, and sustainable CSR initiatives. This is achieved through the alignment of shared values, cautious change management, prudent financial strategies, commitment to legacy, and integration with family values. Moreover, the study underscores the informal nature of CSR practices in the Moroccan context, which are deeply intertwined with cultural, social, and religious norms. The implications of this research shed light on the effectiveness of OC in promoting enduring and meaningful CSR efforts within family firms. This study contributes to a nuanced understanding of the relationship between conservatism, CSR, and familial dimensions, enriching the discourse on responsible business practices.

This article provides an overview of the panel vector autoregressive models (VAR) used in macroeconomics and finance to study the dynamic relationships between heterogeneous assets, households, firms, sectors, and countries. We discuss what their distinctive features are, what they are used for, and how they can be derived from economic theory. We also describe how they are estimated and how shock identification is performed. We compare panel VAR models to other approaches used in the literature to estimate dynamic models involving heterogeneous units. Finally, we show how structural time variation can be dealt with.

The purpose of this study is to propose an analytical framework for generating main path analysis (MPA) and demonstrate the process involved in identifying, analyzing the MPA on a citation network and empirically testing in the research field chromosome anomalies (CA).

The proposed methodological structure involves five phases of the process. Search path method is used to measure the weights of each citation link from a source vertex to a sink vertex. The key route local main path and global main path are generated to identify the knowledge diffusion trajectories and validated by cross-referencing with existing literature, co-citation analysis and centrality measures of social network analysis.

The empirical validation of this framework within CA research demonstrates its potential for tracing knowledge diffusion and technological development trajectories over three decades. This approach elucidates two major intellectual knowledge flows. The first key-route main path identified the primary diagnostic protocols. The second key-route main path revealed that cancer or carcinogenesis is identified as one of the mainstream of CA.

The limitations of the data and coverage period restrict the scope of this study. MPA was applied exclusively to the most influential sub network and disregarded other sub networks. MPA identified the seminal papers that provided a historical development in diagnostic protocol and their interconnectedness of disorders and diseases. This helps the researchers to develop targeted therapies and interventions, especially in cancer treatment.

Exploiting MPA on CA research provides valuable insights to stakeholders in developing evidence-based public health policies. This is crucial for preventing the birth of children with birth defects or genetic diseases, promoting public health and reducing the socioeconomic burden on a country through enhanced surveillance and prevention efforts.

The study suggests that in addition to traditional scientometrics measures, MPA can be used to trace the evolution of knowledge and technological advancements. It also highlights the role of social network analysis measures in extracting main paths.

This chapter follows two previous chapters on the nature of entrepreneurship and entrepreneurship scholarship that have been presented in this book series (Davidsson, 2003; Venkataraman, 1997). Both of these chapters are key works in the field, and they both provide critical contributions to our understanding of what entrepreneurship is, as a focus of scholarship, and how entrepreneurship should be studied. My intention for this chapter, therefore, is to offer some thoughts that, I believe, are complementary to the insights offered by my colleagues. My approach to considering the questions of “What is entrepreneurship?” and “How might entrepreneurship be studied?” is to offer some thoughts about the “community of practice” (Latour, 1987, 1999; Sargent, 1997; Wenger, 1998) that currently exists in the academic field of entrepreneurship, and to propose some suggestions for how academics might practice different ways of entrepreneurship scholarship. (This will beg the question of whether a “community of practice” can remain a community, if the practice, itself, changes).

Purpose: This study explored technology-mediated abuse (TMA) by looking at the influence of topic exposure via education (in/formal), media (non/fictional), and personal experiences (self/close others) in shaping public knowledge, understandings, and perceptions of TMA.

Methodology: Community-sampled respondents (N = 551; n = 235 men, 263 women; aged 18–81 years, M = 27.42, SD = 12.31) reported their TMA awareness and topic exposure (n = 110; 20% of the total sample indicated prior exposure).

Findings: Results indicated TMA knowledge, understanding, and perceptions varied by prior sources of topic exposure. This suggests that TMA is a crime varying in public awareness and perceived repercussions.

Research limitations: Open-ended responses, although ideal for exploratory studies such as this one, limit the scope and power of quantitative analyses. Future work should test the current study’s conclusions in a generalizable, random sample via closed-item surveys.

Originality/value: Present findings elucidate which societal forces and education types are best suited for helping people understand TMA in all its complexity. Such understanding allows for practical considerations of the comparative in/effectiveness of formal curriculum and media in shaping cognitions regarding TMA victimization.

Acute and chronic pain affects more Americans than heart disease, diabetes, and cancer combined. Conservative estimates suggest the total economic cost of pain in the United States is $600 billion, and more than half of this cost is due to lost productivity, such as absenteeism, presenteeism, and turnover. In addition, an escalating opioid epidemic in the United States and abroad spurred by a lack of safe and effective pain management has magnified challenges to address pain in the workforce, particularly the military. Thus, it is imperative to investigate the organizational antecedents and consequences of pain and prescription opioid misuse (POM). This chapter provides a brief introduction to pain processing and the biopsychosocial model of pain, emphasizing the relationship between stress, emotional well-being, and pain in the military workforce. We review personal and organizational risk and protective factors for pain, such as post-traumatic stress disorder, optimism, perceived organizational support, and job strain. Further, we discuss the potential adverse impact of pain on organizational outcomes, the rise of POM in military personnel, and risk factors for POM in civilian and military populations. Lastly, we propose potential organizational interventions to mitigate pain and provide the future directions for work, stress, and pain research.

We investigate the Bayesian approach to model comparison within a two-country framework with nominal rigidities using the workhorse New Keynesian open-economy model of Martínez-García and Wynne (2010). We discuss the trade-offs that monetary policy – characterized by a Taylor-type rule – faces in an interconnected world, with perfectly flexible exchange rates. We then use posterior model probabilities to evaluate the weight of evidence in support of such a model when estimated against more parsimonious specifications that either abstract from monetary frictions or assume autarky by means of controlled experiments that employ simulated data. We argue that Bayesian model comparison with posterior odds is sensitive to sample size and the choice of observable variables for estimation. We show that posterior model probabilities strongly penalize overfitting, which can lead us to favor a less parameterized model against the true data-generating process when the two become arbitrarily close to each other. We also illustrate that the spillovers from monetary policy across countries have an added confounding effect.