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This research adopts the social cognitive career theory (SCCT) and a moderated mediation model to investigate the moderating impacts of entrepreneurial fear of failure (FOF) and gender on the direct and mediation relationships between entrepreneurial education (EE), entrepreneurial self-efficacy (ESE) and entrepreneurial intention (EI).

The authors utilized a three-phase random sampling to compile a dataset from 1,890 graduate students from nine universities and higher education institutions in Vietnam. Cronbach's alpha and confirmatory factor analysis results showed that the key study variables were reliable and valid. Harman's single-factor method and other tests of analysis assumptions ruled out common method bias and other confounding factors. The authors utilized the PROCESS macro to test a hypothesized moderated mediation model that included direct, indirect and conditional indirect effects.

The findings yield that ESE partially and positively mediates the relation between EE and EI. FOF was found to negatively moderate the impacts of EE on ESE and EI, and the direct effect of ESE on EI among females is stronger than among males. More importantly, the mediation influence of FOF on the linkage between EE and EI becomes weaker when the level of FOF is high, yet this mediation relationship among females is higher than among males at all levels of FOF.

The results of this research are valuable for educators, policymakers and practitioners so that they may inspire individuals' entrepreneurial pursuits, especially those of female entrepreneurs.

This study significantly contributes to the entrepreneurship and gender literature by applying the SCCT to elucidate the moderated mediation impacts of FOF, ESE and gender on the relationship between EE and EI.

The purpose of this paper is to expand and analyze deeply customer emotions, concretize the levels of positive or negative emotions with the aim of using machine learning methods, and build a model to identify customer emotions.

The study proposed a customer emotion detection model and data mining method based on the collected dataset, including 80,593 online reviews on agoda.com and booking.com from 2009 to 2022.

By discerning specific emotions expressed in customers' comments, emotion detection, which refers to the process of identifying users' emotional states, assumes a crucial role in evaluating the brand value of a product. The research capitalizes on the vast and diverse data sources available on hotel booking websites, which, despite their richness, remain largely unexplored and unanalyzed. The outcomes of the model, pertaining to the detection and classification of customer emotions based on ratings and reviews into four distinct emotional states, offer a means to address the challenge of determining customer satisfaction regarding their actual service experiences. These findings hold substantial value for businesses operating in this domain, as the findings facilitate the evaluation and formulation of improvement strategies within their business models. The experimental study reveals that the proposed model attains an exact match ratio, precision, and recall rates of up to 81%, 90% and 90%, respectively.

The study has yet to mine real-time data. Prediction results may be influenced because the amount of data collected from the web is insufficient and preprocessing is not completely suppressed. Furthermore, the model in the study was not tested using all algorithms and multi-label classifiers. Future research should build databases to mine data in real-time and collect more data and enhance the current model.

The study's results suggest that the emotion detection models can be applied to the real world to quickly analyze customer feedback. The proposed models enable the identification of customers' emotions, the discovery of customer demand, the enhancement of service, and the general customer experience. The established models can be used by many service sectors to learn more about customer satisfaction with the offered goods and services from customer reviews.

The research paper helps businesses in the hospitality area analyze customer emotions in each specific aspect to ensure customer satisfaction. In addition, managers can come up with appropriate strategies to bring better products and services to society and people. Subsequently, fostering the growth of the hotel tourism sector within the nation, thereby facilitating sustainable economic development on a national scale.

This study developed a customer emotions detection model for detecting and classifying customer ratings and reviews as 4 specific emotions: happy, angry, depressed and hopeful based on online booking hotel websites agoda.com and booking.com that contains 80,593 reviews in Vietnamese. The research results help businesses check and evaluate the quality of their services, thereby offering appropriate improvement strategies to increase customers' satisfaction and demand more effectively.

This study investigates the optimum size for manufacturing firms and the impact of subcontracting on firms' likelihood of achieving their optimal scale in Vietnam.

Using data from the enterprise census in 2017 and 2021, the paper first estimates the production function to identify the optimum firm size for manufacturing firms and then, applies the logit model to investigate factors associated with the optimal firm size.

The study reveals that medium-sized firms exhibit the highest level of productivity. Nevertheless, a consistent trend emerges, indicating that nearly 90% of manufacturing firms in Vietnam operated below their optimal scale in both 2017 and 2021. An analysis of the impact of subcontracting on firms' likelihood to achieve their optimal scale emphasizes its crucial role, especially for foreign firms, exerting an influence nearly five times greater than that of the judiciary system.

The paper's findings offer crucial policy implications, suggesting that initiatives aimed at enhancing the overall productivity of the manufacturing sector should prioritise facilitating contract arrangements to encourage firms to reach their optimal size. These insights are also valuable for other countries with comparable firm size distributions.

This paper provides the first empirical evidence on the relationship between firm size and productivity as well as the role of subcontracting in firms' ability to reach their optimal scale in a country with a right-skewed distribution of firm sizes.

There is a need for research examining how governments and firms responded to the coronavirus disease (COVID-19) pandemic. This study investigates the interdependence between governments and innovative small and medium-sized enterprises (SMEs) during the pandemic in relation to the dynamic capabilities and resource dependence theories.

We use World Bank survey data collected immediately before and after the COVID-19 outbreak and a generalized structural equation model to examine the mediating role of government support in the relationship between firm innovation, resilience and survival.

Innovative SMEs exhibited higher resilience and a better chance of survival during the pandemic, partly due to attracting more government support.

This study offers a novel understanding of the government’s role in supporting innovative SMEs during the pandemic. The findings have implications for how government support policies can limit the deadweight effect and the substitution effect.

The study seeks to conduct an empirical investigation on the impact of entrepreneurship education (EE) through its components, i.e. entrepreneurial knowledge (EK) and business planning (BP) on entrepreneurial intentions (EI) in India.

An electronic questionnaire was used to collect data from 340 engineering students and partial least square-structural equation modeling (PLS-SEM) was used to analyze the collected data.

The findings revealed that EK and BP have no direct impact on EI, however, they have an indirect influence through attitude towards entrepreneurship (ATE) and perceived behavioral control (PBC), whereas subjective norms (SN) have no mediation impact on the relationships.

This research has been conducted on students of engineering background only, future studies can be carried out by incorporating more attitudinal and environmental determinants with larger data sizes from diverse educational streams.

This study is of immense significance to policymakers and educational establishments in designing the purposefully designed EE courses that can drive the entrepreneurial intentionality of students.

The study adds to the paucity of research on the systematic elaboration of EE construct underlining the specific impact of EK and BP as EE dimensions on students' EI. To the best of authors' awareness, this kind of investigation has not been conducted in indian higher educational institution (HEI) context.