Search results

Social entrepreneurs often make public appeals for funding to investors who are motivated by nonfinancial considerations. This emerging research context is an opportunity for researchers to expand the bounds of entrepreneurship theory. To do so, we require appropriate research tools. In this chapter, we show how computer-aided text analysis (CATA) can be applied to advance social entrepreneurship research. We demonstrate how CATA is well suited to analyze the public appeals for resources made by entrepreneurs, provide insight into the rationale of social lenders, and overcome challenges associated with traditional survey methods.

We illustrate the advantages of CATA by examining how charismatic language in 13,000 entrepreneurial narratives provided by entrepreneurs in developing countries influences funding speed from social lenders. CATA is used to assess the eight dimensions of charismatic rhetoric.

We find that four of the dimensions of charismatic rhetoric examined were important in predicting funding outcomes for entrepreneurs.

Data collection and sample size are important challenges facing social entrepreneurship research. This chapter demonstrates how CATA techniques can be used to collect valuable data and increase sample size. This chapter also examines how the rhetoric used by entrepreneurs impacts their fundraising efforts.

A growing body of research outlines how to best facilitate and ensure methodological rigor when using dictionary-based computerized text analyses (DBCTA) in organizational research. However, these best practices are currently scattered across several methodological and empirical manuscripts, making it difficult for scholars new to the technique to implement DBCTA in their own research. To better equip researchers looking to leverage this technique, this methodological report consolidates current best practices for applying DBCTA into a single, practical guide. In doing so, we provide direction regarding how to make key design decisions and identify valuable resources to help researchers from the beginning of the research process through final publication. Consequently, we advance DBCTA methods research by providing a one-stop reference for novices and experts alike concerning current best practices and available resources.

The use of artificial intelligence (AI) in management research is still nascent and has primarily focused on content analyses of text data. Some method scholars have begun to discuss the potential benefits of far broader applications; however, these discussions have not led yet to a wave of corresponding AI applications by management researchers. This chapter explores the feasibility and the potential value of using AI for a very specific methodological task: the reliable and efficient capturing of higher-level psychological constructs in management research. It introduces the capturing of basic emotions and emotional authenticity of entrepreneurs based on their macro- and microfacial expressions during pitch presentations as an illustrative example of related AI opportunities and challenges. Thus, this chapter provides both motivation and guidance to management scholars for future applications of AI to advance management research.

Organizational crises are complex events for researchers to assess. However, research in this domain remains fragmented, and advanced empirical techniques remain underutilized. In this chapter, we offer an integrated approach to assessing crises. We first specify a behavioral process model of crisis management comprised of three stages: interpretations, responses, and outcomes. Within each stage, we identify areas of opportunity and provide methodological recommendations that enhance our understanding of crises and crisis management. We also provide recommendations that could be applied across stages of the model. Taken together, we present a framework by which researchers can more effectively measure and analyze critical crisis dimensions.

Investigates the differences in protocols between arbitral tribunals and courts, with particular emphasis on US, Greek and English law. Gives examples of each country and its way of using the law in specific circumstances, and shows the variations therein. Sums up that arbitration is much the better way to gok as it avoids delays and expenses, plus the vexation/frustration of normal litigation. Concludes that the US and Greek constitutions and common law tradition in England appear to allow involved parties to choose their own judge, who can thus be an arbitrator. Discusses e‐commerce and speculates on this for the future.

This article examines the educational decision-making of hearing parents for their deaf children born during a period (1970–1990s) before the introduction of new-born hearing screening in New South Wales, where the study was conducted, and prior to the now near-universal adoption of cochlear implants in Australia.

We present findings from an oral history study in which parents were invited to recall how they planned for the education of their deaf children.

We propose that these oral histories shed light on how the concept, early intervention – a child development principle that became axiomatic from about the 1960s – significantly shaped the conduct of parents of deaf children, constituting both hope and burden, and intensifying a focus on early decision-making. They also illustrate ways in which parenting was shaped by two key structural shifts, one, being the increasing enrolment of deaf children in mainstream rather than separate classrooms and the other being the transformation of deafness itself by developments in hearing assistance technology.

The paper contributes to a sociological/historical literature of “parenting for education” that almost entirely lacks deaf perspectives and a specialist literature of parental decision-making for deaf children that is almost entirely focussed on the post cochlear implant generation. The paper is distinctive in its treatment of the concept of “early intervention” as a historical phenomenon rather than a “common sense” truth, and proposes that parents of deaf children were at the leading edge of late-20th and early-21st century parenting intensification.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

The links between substance use and offending are well evidenced in the literature, and increasingly, substance misuse recovery is being seen as a central component of the process of rehabilitation from offending, with substance use identified as a key criminogenic risk factor. In recent years, research has demonstrated the commonalities between recovery and rehabilitation, and the possible merits of providing interventions to substance-involved offenders that address both problematic sets of behaviours. The purpose of this paper is to provide an overview of the links between substance use and offending, and the burgeoning literature around the parallel processes of recovery and rehabilitation.

This is provided as a rationale for a new treatment approach for substance-involved offenders, Breaking Free Online (BFO), which has recently been provided as part of the “Gateways” throughcare pathfinder in a number of prisons in North-West England. The BFO programme contains specific behaviour change techniques that are generic enough to be applied to change a wide range of behaviours, and so is able to support substance-involved offenders to address their substance use and offending simultaneously.

This dual and multi-target intervention approach has the potential to address multiple, associated areas of need simultaneously, streamlining services and providing more holistic support for individuals, such as substance-involved offenders, who may have multiple and complex needs.

Given the links between substance use and offending, it may be beneficial to provide multi-focussed interventions that address both these behaviours simultaneously, in addition to other areas of multiple and complex needs. Specifically, digital technologies may provide an opportunity to widen access to such multi-focussed interventions, through computer-assisted therapy delivery modalities. Additionally, using digital technologies to deliver such interventions can provide opportunities for joined-up care by making interventions available across both prison and community settings, following offenders on their journey through the criminal justice system.

Recommendations are provided to other intervention developers who may wish to further contribute to widening access to such dual- and multi-focus programmes for substance-involved offenders, based on the experiences developing and evidencing the BFO programme.