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The purpose of this paper is to identify the causal (not correlational) effect of women’s entrepreneurship on corporate social responsibility (CSR) practices in Latin America.

This study builds on a hitherto unexploited sparse data set on Latin American B Corporations to identify the causal relationship of interest and on a (synthetic) instrumental variable method.

The results confirm that women’s entrepreneurship has a positive causal effect on social responsibility. This study finds that an increase of 1% in the proportion of women entrepreneurs leads to an increase of 0.5 in the B Impact Assessment score, the CSR indicator.

This study contributes to the literature by providing robust statistical evidence of a causal relationship between women entrepreneurs and social responsibility practices in the Latin American context. This research captures the multidimensional nature of social responsibility by using a comprehensive and vast metric of CSR obtained from the data of the B Impact Assessment tool. This study illustrates how machine learning methods can be used to address the lack of structure of the Latin American B Impact Assessment data.

El propósito de esta investigación es identificar el efecto causal (no correlacional) del emprendimiento de mujeres en las prácticas de responsabilidad social empresarial (RSE) en América Latina.

Nos basamos en un conjunto de datos escasamente explorado hasta el momento sobre las Empresas B en América Latina para identificar la relación causal de interés, y utilizamos un método de Variables Instrumentales (VI) sintéticas.

Nuestros resultados verifican el efecto causal positivo del emprendimiento de las mujeres en la responsabilidad social. Descubrimos que un aumento del 1% en la proporción de mujeres emprendedoras conduce a un aumento de 0.5 en la puntuación de la Evaluación de Impacto B, nuestro indicador de RSE.

Contribuimos a la literatura proporcionando evidencia estadística sólida de una relación causal entre emprendedoras mujeres y prácticas de responsabilidad social en el contexto de América Latina. Esta investigación captura la naturaleza multidimensional de la responsabilidad social mediante el uso de una métrica amplia y vasta de RSE obtenida de los datos de la herramienta de Evaluación de Impacto B. Ilustramos cómo se pueden utilizar métodos de aprendizaje automático para abordar la falta de estructura de los datos de evaluación de impacto B en América Latina.

O propósito desta pesquisa é identificar o efeito causal (não correlacional) do empreendedorismo feminino nas práticas de responsabilidade social corporativa (RSC) na América Latina.

Baseamo-nos em um conjunto de dados escasso até então não explorado sobre as Empresas B na América Latina para identificar a relação causal de interesse, e utilizamos um método de Variáveis Instrumentais (VI) sintéticas.

Nossos resultados verificam o efeito causal positivo do empreendedorismo feminino na responsabilidade social. Descobrimos que um aumento de 1% na proporção de mulheres empreendedoras leva a um aumento de 0,5 no escore de Avaliação de Impacto B, nosso indicador de RSC.

Contribuímos para a literatura fornecendo evidências estatísticas robustas de uma relação causal entre empreendedoras mulheres e práticas de responsabilidade social na América Latina. Esta pesquisa captura a natureza multidimensional da responsabilidade social usando uma métrica abrangente e vasta de RSC obtida a partir dos dados da ferramenta de Avaliação de Impacto B. Ilustramos como métodos de aprendizado de máquina podem ser usados para lidar com a falta de estrutura dos dados de avaliação de impacto B na América Latina.

The research paper aims to analyse the scholarly literature on advancing HR analytics as an intervention for attrition, a problem that lingers on organisational performance. This study aspires to provide an in-depth literature review and critically assess the knowledge gaps in HR analytics and attritions within organisational performance.

The review analyses the corpus of 196 research articles published in ostensible journals between 2011 and 2023. To identify research gaps and provide valuable insights, this study synthesises relevant studies using School of thought (S), Context (C), Methodology (M), Triggers (T), Barriers (B), Facilitators (F) and Outcomes (O) (SCM-TBFO framework). This study employs the R programming language to conduct a systematic literature review in accordance with the “preferred reporting items for systematic reviews and meta-analysis” (PRISMA) guidelines.

The emerging discipline of HR analytics encompasses the potential to manage attrition and drive organisational performance enhancements effectively. The study of SCM-TBFO encompasses a multidimensional approach, incorporating diverse perspectives and analysing its complex aspects compared to various approaches. The School of thought includes the human capital theory, expectancy theory and resource-based view. The varied research contexts entail the USA, United Kingdom, China, France, Italy and India. Further, the methodologies adopted in the studies are artificial neural networking (ANN), regression, structure equation modelling (SEM) case studies and other theoretical studies. HR analytics and attrition triggers are data mining decision systems, forecasting for firm performance and employee satisfaction. The barriers include leadership styles, cultural adaptability and lack of analytic skills, data security and organisational orientation. The facilitators were categorised into data and technology-related facilitators, human resource policies and organisational growth and performance-related facilitators. The study's primary outcomes are technology adoption, effective HR policies, HR strategies, employee satisfaction, career and organisational expansion and growth.

The primary goal of the literature review is to provide a comprehensive overview of the current state of HR analytics and its impact on organisational performance, particularly in relation to attrition. Further, the study suggests that attrition, a critical organisational concern, can be effectively managed by strategically utilising HR analytics and empowering data-driven interventions that optimise performance and enhance overall organisational outcomes.

This study investigates the current trends in CEO compensation by applying a bibliometric technique from the Scopus database.

The bibliometric analysis examines CEO compensation trends through the Scopus database. Frequency analysis is conducted using Microsoft Excel, while data visualisation is performed using VOSviewer. Finally, citation metrics are carried out using Harzing's Publish or Perish.

The results reveal that research into CEO compensation has been consistently increasing since 1976. This study identifies the most popular publication trends, the most active institutions, the top funding institutions, annual publication growth, document and source type, publishers, subject area, author co-citations, highly cited articles, top publishing countries, and keyword co-occurrences. Notably, Arizona State University in the United States (US) is the leading institution with the most prominent publications on CEO compensation. The US is the most active country involved in CEO compensation research.

The current research only derived articles from the Scopus database. Nonetheless, the findings provide an in-depth comprehension of the meaning of “CEO compensation” and present the outline of the research trends on the concept, thus significantly facilitating further studies.

The findings can assist researchers in comprehending and classifying the drivers of CEO compensation previously identified and proven in past studies. Additionally, the findings also create opportunities for new researchers to study CEO compensation.

This study is among the pioneering research investigating CEO compensation-related publications and utilising the Scopus database from an international perspective. This study also offers a historical view of CEO remuneration, a summary of the most significant nations, journals, and writers on the topic, and an outline of how CEO remuneration studies have changed over time. These contributions will enable other researchers to focus on this subject.

The aim of this study is to examine the existing literature on service robots in order to identify prominent themes, assess the present state of service robotics research and highlight the contributions of seminal publications in the business, management and hospitality domain.

This study analysed 332 Scopus papers from 1985 to 2022 using bibliometric techniques like citation and co-citation analysis.

The study findings highlighted that there has been a consistent rise in publications related to service robots. The paper identifies three significant themes in the service robot literature: adoption of service robots in the context of customer service, anthropomorphism and integration of artificial intelligence in robotic service. Furthermore, this study highlights prominent authors, journals, institutions and countries associated with research on service robots and discusses the future research opportunities in this domain.

This study contributes to the service robots’ literature in the hospitality context by compilation of various reference materials using a comprehensive bibliometric analysis. Previous studies do not point out crucial themes in this area, nor do they provide an overview of prominent journals, institutions, authors and trends in this field. Therefore, this study attempts to fill the lacunae.