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Open Access
Article
Publication date: 20 February 2024

Li Chen, Dirk Ifenthaler, Jane Yin-Kim Yau and Wenting Sun

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption…

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Abstract

Purpose

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

Design/methodology/approach

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Findings

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

Originality/value

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.

Details

Education + Training, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0040-0912

Keywords

Open Access
Article
Publication date: 12 September 2023

Michael Price, Nicholas Wong, Charles Harvey and Mairi Maclean

This study explores how a small minority of social entrepreneurs break free from third sector constraints to conceive, create and grow non-profit organisations that generate…

Abstract

Purpose

This study explores how a small minority of social entrepreneurs break free from third sector constraints to conceive, create and grow non-profit organisations that generate social value at scale in new and innovative ways.

Design/methodology/approach

Six narrative case histories of innovative social enterprises were developed based on documents and semi-structured interviews with founders and long serving executives. Data were coded “chrono-processually”, which involves locating thoughts, events and actions in distinct time periods (temporal bracketing) and identifying the processes at work in establishing new social ventures.

Findings

This study presents two core findings. First, the paper demonstrates how successful social entrepreneurs draw on their lived experiences, private and professional, in driving the development and implementation of social innovations, which are realised through application of their capabilities as analysts, strategists and resources mobilisers. These capabilities are bolstered by personal legitimacy and by their abilities as storytellers and rhetoricians. Second, the study unravels the complex processes of social entrepreneurship by revealing how sensemaking, theorising, strategizing and sensegiving underpin the core processes of problem specification, the formulation of theories of change, development of new business models and the implementation of social innovations.

Originality/value

The study demonstrates how social entrepreneurs use sensemaking and sensegiving strategies to understand and address complex social problems, revealing how successful social entrepreneurs devise and disseminate social innovations that substantially add value to society and bring about beneficial social change. A novel process-outcome model of social innovation is presented illustrating the interconnections between entrepreneurial cognition and strategic action.

Details

International Journal of Entrepreneurial Behavior & Research, vol. 29 no. 11
Type: Research Article
ISSN: 1355-2554

Keywords

Open Access
Article
Publication date: 1 June 2023

Julia Solnier, Roland Gahler and Simon Wood

Background/Objectives: Protein-based meal replacements (MR) with viscous soluble fibre are known aids for weight loss. This study aims to compare the effects of new whey and vegan…

Abstract

Purpose

Background/Objectives: Protein-based meal replacements (MR) with viscous soluble fibre are known aids for weight loss. This study aims to compare the effects of new whey and vegan MR containing different amounts of PGX (PolyGlycopleX) on weight loss over 12 weeks, along with a calorie-restricted diet.

Design/methodology/approach

Subjects/Methods: Sixty-eight healthy adults of both sexes (53 women; 15 men; average age 47.1 years; BMI 31 ± 7.1 kg/m2 and weight 85.05 ± 23.3 kg) were recruited. Participants consumed a whey or vegan MR twice/d (5–10 g/day PGX) with a low-energy diet (1,200 kcal/day), over 12 weeks. Weight, height, waist and hip circumference were recorded (four time periods).

Findings

Results: Forty-four participants completed the study. Results showed significant reductions in average body weight and at week 12, whey group was [−7.7 kg ± 0.9 (8.3%), p < 0.001] and vegan group was [−4.5 kg ± 0.8 (6.2%), p < 0.001)]. All participants (n = 44; BMI 27 to 33 kg/m2) achieved significant reductions in body measurements from baseline to week 12; p < 0.001. Conclusions: Supplementation of protein-based MR with PGX and a balanced, low-energy diet, appears to be an effective approach for short-term weight loss.

Research limitations/implications

As the authors were evaluating if the MR as a whole (i.e. with PGX) caused weight loss from baseline over the 12 weeks, no comparators, i.e. just the MR without PGX, were used. Formulation of these new MRs resulted in a whey product with 5 g PGX and a vegan product with 2.5 g PGX. Only 2.5 g PGX could be formulated with the vegan protein due to taste and viscosity limitations. Study participants were not randomized and no control groups (e.g. no MR or MR without PGX but with energy restricted diet) were used. Furthermore, it is not clear whether the sort of protein alone or the combination with a higher amount of PGX (whey with 5 g PGX/serving vs vegan with 2.5 g PGX/serving) has contributed to these significant greater weight-loss effects. This was something the authors were testing, i.e. could only 2.5 g PGX/serving have an effect on weight loss for a vegan MR. These limitations would be somethings to evaluate in a subsequent randomized controlled study. Hence, the results of this study may serve as a good starting point for further sophisticated randomized controlled trials that can demonstrate causality – which the authors acknowledge as one of the fundamental limitations of an observational study design. Participants tracked their calories but adherence and compliance were self-assessed and they were encouraged to keep their exercise routine consistent throughout the study. Hence, these are further limitations. No control group was used in this study to observe the effect of the dietary intervention and/or physical activity on weight loss alone. However, a goal of the authors was to keep this study as close to a real-life situation as possible, where people would not be doing any of these measurements, to see if with minimal supervision or intervention, people can still lose weight and alter their body composition. Furthermore, differences in gender and the corresponding weight loss effects in response to MR-protein-based treatments could be evaluated in follow-up studies.

Practical implications

This study indicates that the consumption of protein-based (animal, whey or plant, pea protein) MR incorporating the highly soluble viscous PGX is beneficial for weight loss when combined with a healthy-balanced, calorie-restricted diet. MRs at either 2.5 g or 5 g per serving (RealEasyTM with PGX) proved to be a highly effective as a short-term solution for weight loss. The observed results are encouraging, however, further long-term studies (i.e. randomized clinical trials RCT) are needed to confirm the clinical relevance. RCTs should focus on the individual effects of PGX and/or the different protein sources used in MRs, on weight loss and the maintenance of the reduced body weight, and should measure detailed blood parameters (lipid profiles, glucose etc.) as well as collect detailed exercise and food consumption diaries.

Originality/value

To the authors’ knowledge, this is the first study comparing a whey versus vegan, (as pea) protein-based MR that is supplemented with fibre PGX; thus, this work adds information to the already existing literature on fibre (such as PGX) and MRs regarding their combined weight loss effects. The purpose of this study was to observe if the novel protein-based (either whey or vegan versions) MR RealEasyTM with PGX at 2.5 or 5 g in addition to a calorie-restricted diet (total of 1,200 kcal/day) would aid in weight loss in individuals over a 12-weeks period. Adding increasing amounts of whey protein and soluble fibre can help reduce subsequent ad libitum energy intake which could help adherence to energy restricted diets, but whether similar effects are seen with vegan protein is unclear – this study does aim to address this.

Details

Nutrition & Food Science , vol. 54 no. 1
Type: Research Article
ISSN: 0034-6659

Keywords

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