Search Results (332)

Machine learning is increasingly used in entrepreneurship analytics to predict startup outcomes, frequently reporting accuracy above 0.90, yet whether such performance reflects a genuine ex-ante signal or methodological artifact remains unclear and consequential for investors, accelerators, and innovation-policy agencies. This study evaluates startup-outcome classification under a leakage-controlled, calibration-first protocol using two Crunchbase-derived datasets (66,368 firms; a 923-firm engineered-feature set), three success constructs, and three model families under five-fold stratified cross-validation. Removing outcome-correlated, survivorship-accumulating features lowers the area under the receiver operating characteristic curve by 0.05 to 0.09 on the large dataset, with every paired 95% confidence interval excluding zero, and by 0.19 on the engineered dataset; an independent study on the same 923-firm data without leakage control reports 88.1% accuracy. The leakage-controlled performance level is modest (0.66 to 0.77). Calibration rankings diverge from discrimination rankings: gradient boosting is well calibrated (expected calibration error of 0.006 to 0.024), whereas logistic regression shows large calibration error on imbalanced constructs (largely an artifact of class weighting rather than an intrinsic model property); post hoc isotonic recalibration then removes most of the error. The contribution is a reusable evaluation protocol for entrepreneurship analytics. Findings are associational and specific to the analyzed samples. Full article

The purpose of this study is to characterize, through an exploratory empirical diagnosis, the degree of development and preliminary association between circular economy capabilities and sustainability-oriented digital transformation capabilities in Chamber-affiliated SMEs in Lambayeque, Peru. Guided by three exploratory working hypotheses, the study expected intermediate levels of development, heterogeneous performance across dimensions, and a positive but non-confirmatory coupling between both capability families. A self-administered questionnaire with thirty Likert-type items measured four circular economy dimensions—circular design and eco-design, resource optimization, circular waste management, and circular business models—and four sustainability-oriented digital transformation dimensions—digital technology infrastructure, dynamic digital capabilities, sustainable digital strategy, and digital innovation culture. The initial database contained 111 complete Chamber-affiliated responses; however, seven large Chamber-affiliated firms were retained only as contextual comparators and were excluded from all statistical processing. Consequently, all descriptive, psychometric, and SEM results were calculated using the final analytical sample of 104 micro-, small-, and medium-sized enterprises. The findings show intermediate development in both constructs, higher perceived performance in digital innovation culture and resource optimization, and lower performance in digital technology infrastructure, reverse logistics, platforms enabling circularity, and monetization of circular models. The latent association between the two higher-order constructs was very high (β = 0.985, p < 0.001); however, because global fit indices were below conventional thresholds, this coefficient is interpreted as preliminary evidence of empirical overlap and capability co-occurrence rather than confirmatory evidence of a validated structural model or causal integration. Full article

This study investigates how family firms adjusted their tax strategies following Brazil’s 2023 alignment with the OECD transfer pricing guidelines, using nonfamily firms as a benchmark. The analysis adopts a blended socioemotional wealth (SEW) and implicit theory perspective, which explains family firms’ behavioral responses to institutional change by linking SEW intensity to owners’ cognitive orientations. The sample comprises 1239 firm-year observations from 177 nonfinancial companies listed on Brazil’s stock exchange between 2018 and 2024. Before the transfer pricing reform, family firms displayed a more aggressive approach to corporate income tax (CIT) minimization than their nonfamily counterparts. After the reform, only nonfamily firms, typically more internationalized, intensified their CIT minimization, indicating greater responsiveness to the new OECD-aligned rules. Family firms, by contrast, exhibited no significant change. Exploiting the new rules requires cross-border operations, which family firms tend to limit to preserve family control. With little such exposure, they were not positioned to benefit from the reform and their tax behavior remained unchanged. This inertia is consistent with an entity-oriented mindset, indirectly inferable from the firms’ muted tax response to the reform. The study contributes to family business and international taxation research by revealing that ownership structure conditions firms’ responses to regulatory change, extending the SEW–implicit theory framework to explain heterogeneous tax behavior, and offering policy insights that standardized enforcement may yield uneven outcomes across ownership types. Full article

Background: Malus sieversii, the wild ancestor of cultivated apples, possesses high stress tolerance and rich nutritional value but suffers from low fruit firmness. Jasmonate-ZIM (JAZ) domain proteins are key repressors of jasmonic acid (JA) signaling, yet their roles in fruit softening remain largely unexplored, especially in M. sieversii. Methods and results: In this study, we performed a genome-wide identification of the JAZ gene family in M. sieversii and characterized their structural features, phylogenetic relationships, chromosomal distribution, promoter cis-elements, expression patterns, and protein interactions. A total of 18 MsiJAZ genes were identified, which could be classified into six subfamilies. Most members are predicted to localize in the nucleus, while three are also potentially targeted to chloroplasts. The MsiJAZ genes are unevenly distributed across ten chromosomes and are enriched in light-, ABA-, and drought-responsive cis-elements. Expression analysis under storage and 1-MCP treatments revealed both shared and divergent responses among selected MsiJAZ genes. Notably, MsiJAZ1 was significantly repressed by storage but induced by 1-MCP and physically interacted with MsiPUB24 (PLANT U-BOX 24), an E3 ubiquitin ligase involved in ethylene-mediated softening. These results suggest that MsiJAZ1 may participate in a novel CORONATINE INSENSITIVE 1 (COI1)-independent degradation pathway and mediate ethylene–JA crosstalk during fruit softening. Conclusions: This study provides a comprehensive characterization of the JAZ family in M. sieversii and lays a foundation for further functional studies on JA signaling in apple fruit softening. Full article

This study investigates the determinants and predictability of stock return volatility by integrating firm-specific financial characteristics with advanced econometric and volatility modeling techniques. Using an unbalanced panel dataset comprising 1596 firms and 19,752 firm-year observations from MENA stock markets over the period 2010–2024, the analysis employs fixed-effects panel regression models, conditional volatility models, and machine learning-based forecasting approaches. Following extensive diagnostic testing, including tests for heteroskedasticity, serial correlation, cross-sectional dependence, and model specification, a two-way fixed-effects model with Driscoll–Kraay standard errors is adopted as the preferred estimation framework. The results indicate that liquidity ratio, cash ratio, sales growth, firm age, lagged volatility, and lagged returns are significant determinants of stock return volatility, whereas leverage, tangibility, board independence, firm size, Tobin’s Q, and profitability do not exhibit statistically significant effects after controlling for firm-specific and time-specific heterogeneity. The volatility analysis reveals substantial persistence in stock return volatility, with the EGARCH-t specification providing the best fit among the competing GARCH-family models according to the Akaike Information Criterion. The estimated asymmetry parameters indicate that volatility responds differently to positive and negative shocks, supporting the presence of asymmetric volatility dynamics and the suitability of asymmetric volatility models. The forecasting analysis shows that advanced machine learning and deep learning models achieve competitive predictive performance; however, differences in predictive accuracy across models are generally modest. Full article

Polygalacturonase (PG) is a key enzyme in cell wall metabolism and fruit ripening. Atemoya (Annona cherimola Mill. × A. squamosa L.) is a high-value tropical fruit that undergoes rapid postharvest softening at room temperature. However, the role of the atemoya PG gene family in this process remains unknown. This study determined that storing atemoya at 28 °C significantly reduced fruit firmness and the total pectin content but increased water-soluble pectin (WSP) and PG activity compared to storage at 15 °C. Genome-wide identification of the AaPG gene family in atemoya revealed that 40 AaPG genes were unevenly distributed across seven chromosomes. Nineteen genes were located within six tandem duplication clusters. AaPG proteins exhibited clade-specific differences: Clades B-E contained the polysaccharide lyase family 6 (PL-6) superfamily domain, while Clade A harbored the Aspergillus niger polygalacturonase 1 (Pgu1) domain and lacked several conserved motifs. Expression profiling and reverse transcription quantitative polymerase chain reaction (RT-qPCR) showed that AaPG19, AaPG21, AaPG23 and AaPG24 were specifically induced at 28 °C. Subcellular localization confirmed that these four proteins were located on the plasma membrane. These findings provide insights into the evolution and temperature-dependent regulation of the AaPG family, identifying candidate genes responsible for the rapid softening of atemoya fruit. Full article

Firms can gain a competitive advantage through a strategic patent portfolio, wherein patents elucidate technological advancements and establish legal barriers that keep competitors out. However, patents do not provide a perpetual monopoly within the prevailing open innovation paradigm, which means that firms should keep up with innovation input and patent applications to preserve their market dominance. Fostering technological breakthroughs in the patent network thus becomes a critical issue. Anchored in the theoretical views of open innovation, this study conducts an empirical analysis of patent data to examine how patent network structural features influence the technologies’ breakthrough tendency in the field of autonomous driving (AD). The findings indicate that centrality metrics such as degree centrality, harmonic centrality, and betweenness centrality within AD patent networks exert significant influence on technological breakthrough tendency, and the patent family size plays a moderating role in these relationships. Moreover, this research advances theoretical insights for patent strategy formulation in emerging firms of AD, with broader implications for other technology-intensive sectors. Full article

This paper provides a theory-informed synthesis of earnings management research through a review of the 100 most cited studies in the accounting literature. Rather than functioning as a purely bibliometric review, the study integrates theoretical, empirical, methodological, and survey-based contributions to examine how influential research has conceptualized, measured, and interpreted earnings management. Citation data were collected from Web of Science and Google Scholar as of 5 January 2025 using predefined search criteria, filtering procedures, and classification protocols. While citation counts are used to identify influential studies, they are not treated as direct indicators of research quality due to concerns regarding citation bias, publication visibility, and proxy limitations. The review organizes the literature around major themes, including corporate governance, audit quality, managerial incentives, institutional environments, market reactions, and regulatory change. The analysis highlights enduring debates concerning proxy validity, endogeneity and identification challenges, the distinction between statistical detection and economic significance, and the trade-off between accrual-based and real earnings management. The synthesis also incorporates emerging research streams involving family firms, gender diversity, ESG reporting, textual analysis, and AI-assisted analytics within broader agency and institutional theory perspectives. A central contribution of the paper is the development of an integrative analytical framework linking proxy validity, strategic substitution between reporting mechanisms, and institutional constraints within a unified interpretation of earnings management behavior. The review shows that advances in empirical design, textual analysis, machine learning, and predictive analytics extend rather than replace foundational insights, while persistent limitations in causal inference and measurement remain unresolved. Overall, the findings suggest that earnings management is best understood as a strategic response to incentives, monitoring, and institutional constraints rather than as a uniform indicator of opportunistic behavior. The paper concludes by outlining future research directions focused on theory-driven empirical design, methodological triangulation, AI-assisted detection approaches, and improved measurement frameworks across diverse reporting environments. Full article

While theory casts family firms as long-term stewards, rising global demands for sustainability create a practical conflict: unique family goals often clash with formal institutional expectations, leaving the true nature of their corporate social responsibility disputed. This tension motivates this investigation into how family ownership shapes the strategic divergence between substantive and symbolic ESG performance. Analyzing over 4000 public companies across twenty-seven countries, I identify a unique reputational caution model of governance. Empirical results reveal a consistent management lag—family firms systematically underperform in social initiatives and ESG management quality compared to non-family counterparts. Robustness checks using instrumental variable and endogenous treatment models confirm a significant measurement deficit, showing that family firms are less likely to track scope 1 and 3 emissions. These findings reveal a strategic divergence: despite higher emissions under concentrated control, family firms avoid greenwashing and non-compliance. Socioemotional wealth acts as a reputational floor, where the high affective cost of scandal deters active deception. This pattern persists across legal origins and is pronounced in weak macro-governance environments. Ultimately, family-firm ESG behavior is driven by avoidance of negative signaling rather than proactive stewardship. Full article

Family firms are central to global economic stability and employment. Generational transitions, however, involve not only the transfer of leadership but also changes in organizational structures and culture. As digitalization becomes increasingly important for competitiveness, successors are introducing digital marketing practices that may influence organizational culture during leadership transitions. While previous research has examined digital transformation in family businesses, limited attention has been given to the role of digital marketing as a mechanism of cultural change during generational succession. This article addresses the question: How do second-generation successors use digital marketing practices to shape organizational culture during generational transitions in family firms? Drawing on practice theory and Schein’s model of organizational culture, the study explores how cultural change unfolds through everyday practices within organizations. The research employs a qualitative multiple-case study approach based on semi-structured interviews with representatives from 35 family firms in Latvia. The findings identify key digital marketing practices implemented by second-generation successors and illustrate how these practices influence organizational culture during the transition process. The results suggest that digital marketing can both reinforce existing organizational values and selectively reshape organizational identity and legitimacy. The study highlights digital marketing as a culturally legitimate tool through which successors can influence decision-making processes, coordination mechanisms, and authority structures during generational succession. Full article

Global crises often force a pivotal choice between protecting human legacy and ensuring financial survival, yet the psychological drivers behind these trade-offs remain poorly understood. While family firms are traditionally viewed as inherently resilient, the unique emotional attachments of their owners may constrain their ability to adapt to unprecedented shocks. This study examines the behavioral underpinnings of crisis management across 11 European nations during the COVID-19 pandemic, challenging the traditional stewardship paradigm. Findings reveal a significant tension between preserving socioemotional wealth and economic survival. While family-managed firms prioritized personnel retention and financial autonomy, thus avoiding the psychological stigma of government aid, these non-financial priorities often proved detrimental to liquidity and business survival. This suggests that high emotional endowment can induce behavioral rigidity and an escalation of commitment, hindering strategic pivots. Furthermore, the results highlight a trend toward mimetic isomorphism, where extreme uncertainty forced a convergence of crisis responses across diverse organizational structures. Overall, the contribution of this study is to challenge the resilience myth, illustrating that acute shocks often override the distinctive behavioral archetype of family firms, forcing a shift toward institutional conformity and standardized mandates. Full article

AI/IoT initiatives are increasingly adopted in business, yet reported success varies substantially across firms. This study develops and evaluates a firm-level predictive framework for the reported AI/IoT success rate, measured on a bounded 0–100 scale. Using enterprise survey data from Slovakia and the Czech Republic (n = 1250), we compare a regularized linear baseline (Elastic Net) with nonlinear approaches (Decision Tree and Random Forest) under a consistent out-of-sample evaluation framework, and we examine the best-performing model using permutation importance and PDP/ICE tools. Random Forest achieves the strongest out-of-sample predictive performance and reduces absolute errors relative to Elastic Net for most test observations, although diagnostics also reveal a small tail of extreme errors. Across model families, ai_iot_advantage_share emerges as the most stable predictor of reported AI/IoT success. Nonlinear diagnostics indicate a threshold-like transition in predicted success around the mid-range of advantage attribution and a saturation pattern at higher values. Readiness and performance-related variables are associated with higher predicted success, whereas higher barrier levels are associated with lower predicted success. The results position value realization as the most informative predictive signal in the dataset and provide an interpretable basis for enterprise-level screening and managerial reflection rather than causal inference. Full article

Despite strong evidence that gender-diverse leadership improves organizational innovation and performance, women remain underrepresented in leadership pipelines worldwide, particularly in Asia. While prior research largely examines the outcomes of gender diversity at the firm level, far less is known about the psychological and social factors that shape women’s leadership aspirations in the first place. Addressing this gap, this study applies Social Cognitive Career Theory (SCCT) to explain how contextual support and developmental experiences influence women’s leadership aspirations in a collectivist business environment. Using survey data from 400 adult women in Indonesia and structural equation modelling, the study examines how parental involvement shapes personal mastery, how personal mastery strengthens leadership self-efficacy, and how self-efficacy, role models, and perceived leadership traits jointly predict leadership aspiration. The findings show that parental involvement indirectly contributes to leadership aspiration through personal mastery and self-efficacy, while role models and leadership traits also play significant roles. Among all predictors, self-efficacy emerges as the strongest driver of women’s leadership aspiration. This study makes three contributions. First, it extends SCCT beyond traditional STEM career research into the domain of leadership aspiration. Second, it provides rare empirical evidence from a collectivist Asian context, highlighting the role of family and social environment in shaping women’s leadership pathways. Third, it shifts the focus of gender diversity research from representation outcomes to the formation of the female leadership pipeline, offering actionable insight for educators, families, and organizations seeking to foster future women leaders. Full article

In this article, we analyze the combined impact of sustainability activities and family governance on firm-level risk, measured by earning volatility, with particular attention to the timing of ESG involvement. Using panel regression models, we distinguish between short- and long-term ESG performance and between family ownership and family management. The empirical analysis reveals a negative correlation between long-term ESG performance and corporate risk, but short-term ESG impact is insignificant. Family ownership and having a family CEO both decrease firm risk; however, family ownership moderates the link between ESG risks and firm risk. Full article

Background: Fruit texture is a major component of plum quality, affecting both consumer acceptance and postharvest behavior. Pectin methylesterases (PMEs) play important roles in cell-wall pectin modification and are therefore likely to contribute to plum fruit texture development and ripening-associated softening. However, the PME gene family has not yet been comprehensively investigated in plum (Prunus salicina L.). Methods: In the present study, a chromosome-level plum genome was used to survey this gene family at the whole-genome scale. Phylogenetic relationships, chromosomal positions, exon–intron organization, conserved motifs, domain architectures, gene duplication, and cis-elements were analyzed. Four flesh texture traits were measured in 55 plum accessions to characterize texture variation and select two representative cultivars with contrasting flesh textures for further molecular analysis. Based on the clustering results, ‘WSCL’ and ‘FR’ were selected for expression profiling during fruit development and subsequent correlation analysis with texture traits. Results: A total of 46 PsPME genes were identified. Phylogenetic analysis classified them into four major subgroups. Structural analyses indicated an overall conserved family framework, although noticeable variation was retained among individual members. Dispersed duplication made the largest contribution to family expansion, and most duplicated pairs appeared to have evolved under purifying selection. Correlation analysis showed that PsPME20, PsPME22, and PsPME25 were significantly negatively correlated with flesh firmness, while PsPME20 was additionally linked to flesh compactness and flesh fragility. Conclusions: Overall, this study clarifies the structural and evolutionary characteristics of the PsPME family and identifies candidate genes that may contribute to texture differences in plum, offering a basis for future functional studies and breeding programs. Full article