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Resiliency is essential for achieving the necessary level of performance and ensuring the survival of a new business during difficult times. However, neither this characteristic nor its antecedents have been exhaustively studied. Using a configuration approach, this study aims to analyze the neuropsychological and business-related characteristics of entrepreneurs that may explain their resilience during the business development process.

Using the fuzzy set qualitative comparative analysis (fsQCA), the authors investigated distinct characteristics of Costa Rican agro-entrepreneurs with high levels of entrepreneurial resilience. The fsQCA methodology identifies combinations of causal measures that result in the outcome.

From the mixture of configurations, the authors found four combinations of individual’s characteristics that explain the profile of a resilient agro-entrepreneur.

This work contributes to the literature on agricultural entrepreneurship and entrepreneurial resilience. This study identifies four distinct combinations of entrepreneurs’ characteristics that produce entrepreneurial resilience in the agricultural industry. Moreover, it incorporates individuals’ business-related attributes into examining characteristics combinations that affect resilience. Also, this research offers agro-entrepreneurs’ stakeholders, valuable insights to develop more resilient entrepreneurs.

La resiliencia es esencial para lograr el nivel de rendimiento necesario y garantizar la supervivencia de un nuevo negocio en tiempos difíciles. Sin embargo, ni esta característica ni sus antecedentes han sido exhaustivamente estudiados. Empleando un enfoque de configuración, este estudio busca analizar las características neuropsicológicas y empresariales de los emprendedores que pueden explicar su resiliencia durante el proceso de desarrollo empresarial.

Utilizando el análisis cualitativo comparativo de conjuntos difusos (fsQCA, por sus siglas en inglés), investigamos distintas características de los agroemprendedores costarricenses con altos niveles de resiliencia emprendedora. La metodología fsQCA identifica combinaciones de medidas causales que originan un fenómeno o resultado.

A partir de la mezcla de configuraciones, encontramos cuatro combinaciones de características del individuo que explican el perfil de un agroemprendedor resiliente.

Nuestro trabajo contribuye a la literatura sobre emprendimiento agrícola y resiliencia emprendedora. Este estudio identifica cuatro combinaciones distintas de las características de los emprendedores que producen resiliencia emprendedora en la industria agrícola. Además, incorpora las características empresariaes de los individuos al examinar las combinaciones de características que afectan la resiliencia. También, nuestra investigación ofrece a los públicos de interés información valiosa para desarrollar emprendedores más resilientes.

A resiliência é essencial para alcançar o nível de desempenho necessário e garantir a sobrevivência de um novo negócio em tempos difíceis. Porém, nem esta característica nem seus antecedentes foram exaustivamente estudados. Empregando uma abordagem de configuração, este estudo busca analisar as características neuropsicológicas e empresariais de empreendedores que podem explicar sua resiliência no processo de desenvolvimento de negócios.

Usando a análise comparativa qualitativa do conjunto difuso (fsQCA), investigamos características distintas de agroempreendedores costarriquenhos com altos níveis de resiliência empreendedora. A metodologia fsQCA identifica combinações de medidas causais que causam um fenômeno ou resultado.

A partir da mistura de configurações, encontramos quatro combinações de características individuais que explicam o perfil de um agroempreendedor resiliente.

Nosso trabalho contribui para a literatura sobre empreendedorismo agrícola e resiliência empreendedora. Este estudo identifica quatro combinações distintas de características dos empreendedores que produzem resiliência empreendedora na indústria agrícola. Além disso, incorpora as características de negócios dos indivíduos ao examinar as combinações de características que afetam a resiliência. Adicionalmente, nossa pesquisa oferece às partes interessadas dos agroempreendedores insights valiosos para desenvolver empreendedores mais resilientes.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

This study aims to examine trends in audit committee characteristics of companies and associates characteristics subject to major change with a fee-based proxy for audit committee effectiveness.

The research adopts an empirical approach. Using descriptive and inferential statistics, observations for 253 Financial Times Stock Exchange 350 companies’ audit committee characteristics gathered from annual reports at the beginning and end of a five-year period are evaluated against averaged non-audit fees (NAF) as a proportion of total audit fees.

Audit committee composition shows an increased incidence of female membership and of members with previous audit experience. The increase in members with previous audit experience is more marked where this is gained with the incumbent auditor. An increase is also shown in chief financial officers with previous audit experience. Previous audit experience is associated with reduced NAF as a proportion of total fees. This is marked where audit experience has been gained with the incumbent auditor. These results suggest that the benefits of financial expertise gained from audit experience outweigh impairments to independence due to social ties. Nevertheless, other studies indicate concerns about independence are still well-founded.

This paper’s original contribution is to evaluate the potential effect of previous audit experience on those involved in audit committees in light of concerns raised in the literature and by regulators that external auditor independence should be maintained. The innovative fee-based proxy for audit committee effectiveness facilitates an evaluation as to which influence prevails.

Recognizing women’s potential and directing their talents to realize these potentials can be of great benefit. Accordingly, this paper aims to identify the characteristics of entrepreneurial intelligence in female entrepreneurs, drawing on a national-level study and the international literature on this topic.

The present paper conducted two studies. First, 15 female entrepreneurs in the Guilan province of Iran, who were selected using purposive sampling, were interviewed to identify the characteristics of entrepreneurial intelligence nationally. The data gathered by interviews were analyzed using inductive content analysis. Then, their validity was tested using qualitative validation and analyzed using Shannon entropy. In the second study, the characteristics of female entrepreneurial intelligence were identified through a qualitative metasynthesis. The results of the two studies were compared together.

This categorized entrepreneurial intelligence into six categories, namely, entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. Ultimately the characteristics of women’s entrepreneurial intelligence in each category were compared according to the national-level study and the international literature.

This study has the potential to discover credible and robust approaches for further examining the contextualization of women’s entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various dimensions of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women’s entrepreneurship, this paper challenges the assumption that the characteristics of women’s entrepreneurial intelligence are uniform across the world.

Innovative work behaviour (IWB) has long been advocated as a crucial resource for organisations. Evidence that work characteristics stimulate the adoption of IWB is widespread. Yet, the relationship between knowledge characteristics and IWB has often been overlooked. This study aims to address this gap by examining this relationship.

Building on an integrative vision of innovation, this study analyses the effects of combinations in work characteristics on IWB through a configurational approach. Job autonomy, complexity, problem solving, specialisation and demand for constant learning were examined as determinants of IWB using fuzzy-set qualitative comparative analysis.

Based on a sample of 214 Belgium employees, the results highlight seven configurations of work characteristics to elicit high levels of IWB. For six of them, problem solving appears as a needed condition.

Presented findings offer insights for organisations aiming at evolving in a competitive context to generate optimal conditions for promoting employee innovation.

While most studies have tested the influence of work characteristics independently, this research investigates the joint influence of work characteristics and identifies how combinations of multiple variables lead to IWB.

Situated in the Chilean context, this study investigates how Vocational Education and Training (VET) teacher profiles, based on their perceptions of prior work experience in industry, relate to their current motivation and perception of teaching in VET. By doing so, the authors seek to provide valuable evidence to inform the development of policies to attract and maintain well-qualified teachers from industry in Chile and other countries facing similar changes.

The authors used a descriptive cross-sectional design to collect data from 660 VET teachers using a two-scale instrument: Perception of Prior Occupation (PPO) and adapted FIT-Choice scales. By adopting a typological approach, the authors constructed profiles of VET teachers based on their perception of past industry experience. The authors then analyzed how these profiles vary regarding individual teacher characteristics, motivation and perception of teaching in VET.

The authors found a significant degree of heterogeneity among VET teachers' prior industry experiences, leading them to identify three distinct VET teacher profiles: “High Perception of Prior Occupation,” “Learning and Teaching-Oriented” and “Low Perception of Prior Occupation.” Notably, the most distinguishing characteristics across these profiles were age, VET teaching area, holding a job outside of teaching and years of prior industry experience. Furthermore, the authors found that motivation and perceptions of teaching varied significantly across these VET teacher profiles.

There needs to be more research on the factors that attract and retain industry workers as VET teachers in high schools. This study is among the first to address this topic in a non-European context.

When coping with uncertainties, three characteristics distinguish firms: agility, adaptability and alignment (triple-A). Based on significant field research, the triple-A highlights the significance of coordinating agility, adaptability and alignment. Start-ups are facing a lot of challenges in this turbulent environment. However, this sector is undergoing a major transformation. Agility, adaptability and alignment concepts have had a major influence on the supply chain, but their implementation in start-ups has been less visible. This paper aims to identify, analyze and categorize the enablers for agility, adaptability and alignment in start-ups using the total interpretive structural modeling (TISM) approach.

In addition to the scheduled interview, a closed-ended questionnaire was used to collect data. To identify how the factors interact, the TISM technique is used, and the Matriced’Impacts Croises-Multipication Applique’ and Classment method is used to rank and categorize the agility, adaptability and alignment enablers.

This study identified ten agility, adaptability and alignment factors for start-ups. It has been found that the key importance should be given to management involvement, conflict management, collaboration and information integration.

This study primarily focused on the agility, adaptability and alignment factors in start-ups.

This study will help academics and key stakeholders understand the aspects that lead to agility, adaptability and alignment in start-ups.

Agility, adaptability and alignment concepts have had a major influence on the supply chain, but their implementation in start-ups has been less visible. Therefore, this is a novel attempt in this industry’s agility, adaptability and alignment.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

This study aims to highlight the many distinguishing characteristics of open-access repositories that archive “Patents” in the Directory of Open-Access Repositories (OpenDOAR) provided by Asian nations.

The OpenDOAR was chosen as a data collection tool that provides a quality-assured list of repositories indexed globally. The data was extracted on 28 March 2023.

The study found that only eight Asian countries contributed to open-access repositories on OpenDOAR, with China being the highest contributor. These countries mainly focused on institutional repositories, primarily using DSpace and English as the main language interface. Web 2.0 tools, especially RSS and Atom, were commonly used, along with some presence of social media platforms on the sites, although to a lesser extent. While many repositories followed the OAI-PMH protocol, a considerable portion did not adopt open-access policies.

To the best of the authors’ knowledge, this study is the first one that brings to light the different features of repositories archiving one of the important content types, i.e. “Patents” in the OpenDOAR by Asian countries.

This study aims to use institutional and upper echelons theories to comprehensively investigate the intricate interplay between TMT legal expertise and firms' adaptive strategies in legal contexts, notably within emerging economies. It explores how upper echelons experiences shape opportunistic compliance strategies, impacting value and risk perceptions. Drawing on upper echelons theory, the research probes how TMT legal expertise molds firms’ involvement in significant lawsuits, accounting for influential roles. It scrutinizes TMT’s impact on legal strategies, positing that managerial discretion emerges from environmental factors, organizational attributes and executive traits. The study underscores TMT’s internal incentives and external factors’ interplay, molding strategic legal engagement.

To validate this framework, statistical analysis is performed on data from 2,584 Chinese-listed firms. The data set spans 2010–2015, with 5,713 material lawsuits. Chosen due to reliable institutional-level incentives data from the China Market Index Database, years 2016–2019 are excluded for methodological disparities. Moreover, 2007–2009 is omitted to mitigate the potential financial crisis impact. This study’s 11,272 observations ensure robust empirical exploration, offering insights into the interplay of TMT legal expertise, institutional factors and firms’ legal strategies.

The study reveals that firms led by executives with legal expertise are more prone to engage in significant lawsuits, indicating strategic use of legal skills. TMT age moderates this, with older teams less likely to engage. TMT tenure’s effect remains unclear due to tenure-risk preference complexity. Institutional factors matter; less legally mature regions reduce managers’ legal risk intention. Results confirm hypotheses and highlight executive human capital’s impact on firms’ legal strategies.

This study acknowledges contributions while highlighting limitations, including the need for detailed distinctions in lawsuit roles and exploration of heterogeneous TMT power dynamics. Further research is proposed for nuanced power dynamics and comprehensive TMT legal background data. The study advances upper echelons theory by introducing TMT legal expertise as a factor influencing strategic lawsuit behavior. It challenges institutional theory by showing the adaptable legal context, beyond fixed constraints. Moderating factors – group risk attitude and external knowledge – deepen understanding of upper echelons’ impact. Enhanced data collection is encouraged to address limitations and refine findings.

This study’s implications extend to managerial practices. Firms should acknowledge the dynamic legal system, using TMT legal expertise for strategic legal challenges. Executives should pragmatically approach regulations. While legal professionals enhance compliance, caution is needed in selecting TMT members with legal expertise due to the risk of misusing it for unnecessary litigation, potentially misaligned with financial performance goals.

This study combines institutional and upper echelons theories to explore TMT legal expertise’s impact on firms’ adaptive strategies in emerging economies. It challenges the idea of a universally constraining legal environment and highlights how TMT legal expertise enhances firms’ management of complex legal risks. The research introduces TMT legal expertise as an influencing factor in strategic lawsuits, revealing nuanced relationships between legal contexts and strategic decisions. The findings enrich upper echelons theory, challenge conventional institutional views and identify moderating factors that deepen the understanding of upper echelons’ influence in legal landscapes.