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1 – 6 of 6John Fernando Macías-Prada, Yamila Silva and Ángela María Zapata
This study examines the role of universities in the social entrepreneurship ecosystems (SEEs) in Latin America from the perspective of female academic staff, administrators and…
Abstract
Purpose
This study examines the role of universities in the social entrepreneurship ecosystems (SEEs) in Latin America from the perspective of female academic staff, administrators and outreach workers of universities in the region.
Design/methodology/approach
Using a qualitative approach, the study scrutinises in-depth interviews conducted with 24 women from eight Latin American universities.
Findings
The findings underscore the pivotal role of universities in promoting social entrepreneurship through knowledge generation, entrepreneur training, network enhancement and the promotion of equity. They also highlight the importance of incorporating a gender perspective into university programmes and practices.
Research limitations/implications
The qualitative nature and small, diverse sample of this research inherently limit its scope. However, these limitations arise from the exploratory approach adopted, which was confined to eight Latin American countries. Further comparative studies in different contexts are needed to deepen the understanding of the dynamics involved.
Practical implications
Universities should offer more tangible support and training in social entrepreneurship with a gender focus. Governments can create incentives for universities to prioritise their contribution in this area.
Social implications
The study emphasises the potential of women-led social entrepreneurship initiatives to generate positive impact, underscoring the need for inclusive supportive environments.
Originality/value
By providing insights on the role of Latin American universities in SEEs from a gender perspective, this study contributes to limited literature on the intersection of social entrepreneurship, gender, higher education and geographic context in the region. The research underscores the need to further explore how gender and regional dynamics influence social entrepreneurial ecosystems.
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Amaya Erro-Garcés, Angel Belzunegui-Eraso, María Inmaculada Pastor Gosálbez and Antonio López Peláez
Rodolfo Canelón, Christian Carrasco and Felipe Rivera
It is well known in the mining industry that the increase in failures and breakdowns is due mainly to a poor maintenance policy for the equipment, in addition to the difficult…
Abstract
Purpose
It is well known in the mining industry that the increase in failures and breakdowns is due mainly to a poor maintenance policy for the equipment, in addition to the difficult access that specialized personnel have to combat the breakdown, which translates into more machine downtime. For this reason, this study aims to propose a remote assistance model for diagnosing and repairing critical breakdowns in mining industry trucks using augmented reality techniques and data analytics with a quality approach that considerably reduces response times, thus optimizing human resources.
Design/methodology/approach
In this work, the six-phase CRIPS-DM methodology is used. Initially, the problem of fault diagnosis in trucks used in the extraction of material in the mining industry is addressed. The authors then propose a model under study that seeks a real-time connection between a service technician attending the truck at the mine site and a specialist located at a remote location, considering the data transmission requirements and the machine's characterization.
Findings
It is considered that the theoretical results obtained in the development of this study are satisfactory from the business point of view since, in the first instance, it fulfills specific objectives related to the telecare process. On the other hand, from the data mining point of view, the results manage to comply with the theoretical aspects of the establishment of failure prediction models through the application of the CRISP-DM methodology. All of the above opens the possibility of developing prediction models through machine learning and establishing the best model for the objective of failure prediction.
Originality/value
The original contribution of this work is the proposal of the design of a remote assistance model for diagnosing and repairing critical failures in the mining industry, considering augmented reality and data analytics. Furthermore, the integration of remote assistance, the characterization of the CAEX, their maintenance information and the failure prediction models allow the establishment of a quality-based model since the database with which the learning machine will work is constantly updated.
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Anaile Rabelo, Marcos W. Rodrigues, Cristiane Nobre, Seiji Isotani and Luis Zárate
The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.
Abstract
Purpose
The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.
Design/methodology/approach
This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.
Findings
From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.
Originality/value
This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.
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Positive reviews can enrich the favorable impression of peer-to-peer accommodation products, and seizing this impression is vital for hosts. This study aims to focus on hosts’…
Abstract
Purpose
Positive reviews can enrich the favorable impression of peer-to-peer accommodation products, and seizing this impression is vital for hosts. This study aims to focus on hosts’ response strategies to positive reviews and their effects.
Design/methodology/approach
This study categorizes hosts’ response strategies to positive reviews into cordial and tailoring responses. This study empirically analyzes the influence of these response strategies on subsequent review volumes using 1,283 valid listings and zero-inflation negative binomial regression models.
Findings
While hosts use cordial responses more, tailoring responses are more likely to drive subsequent reviews. In addition, when the host chooses entirely shared accommodation or sets a high price, the facilitating effect of the two response strategies on subsequent reviews weakens.
Research limitations/implications
This study enriches the knowledge system on managerial responses by proposing two specific response strategies to positive reviews that can be adopted by peer-to-peer accommodation hosts and by finding the promoting impact of these strategies on subsequent review volumes.
Practical implications
This study recommends that peer-to-peer accommodation hosts adopt cordial and tailoring responses to encourage subsequent consumer reviewing behavior.
Originality/value
As an early attempt to explore hosts’ responses to positive reviews and their impacts on subsequent review volumes, this study provides valuable insights into further research on positive review response strategies in the digital space.
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Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Tadashi Nakano and Thi Hong Tran
In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality…
Abstract
Purpose
In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.
Design/methodology/approach
To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.
Findings
The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.
Originality/value
This research has not been published anywhere else.
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