Search results

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

This study investigates how human resource training and development (HRTD) shapes workplace spirituality in higher education. It delves into key factors impacting spirituality among academics, such as colleague support and e-learning initiatives. Through analytical tools like percentage analysis and Garret ranking, it divides workplace spirituality in academia, exploring the HR strategies that induce it.

(a) Type of research – Descriptive research (b) Area of research – The present study is taken up by the academicians as a respondent in selected colleges in Salem district. (c) Sampling technique – Simple random method was adopted. (d) Sources of data collection – The study comprises mixed data method that both types of data were adopted. (i) Primary data – Researcher conducted data by selecting a representative sample of the teaching faculties from various institutions employed in higher education in Salem. (ii) Secondary data – It is mostly gathered through content found on websites. (e) Method of data collection – Structured questionnaires were employed in this research to acquire the data needed for the investigation. Every item it is rated through five-point scale of with 1 denoting “Strongly Agree” to “Strongly Disagree,” this includes questions about the job, coworkers, seniors and training. (f) Research tools used – Descriptive statistics, Friedman test and Garret ranking.

Findings highlight the significance of encouraging colleagues, workplace development and online learning in fostering workplace spirituality. Faculty encouragement emerges as the most impactful HR practice, while development initiatives improve the reputation of training for new aspects. Notably, online training significantly affects workplace spirituality, increasing the influence of cultural training.

Implications for future research arise, suggesting potential models for studying workplace spirituality in academia and sparking curiosity about the connection between HR practices and spirituality.

From a practical viewpoint, the study offers actionable insights for authorities to improve workplace spirituality by supporting colleagues and emphasizing growth strategies. It outlines clear steps for organizations to create more spiritually enriching work environments.

Socially, the study advocates for healthier work cultures that impact society's perspective on work–life balance and employee well-being. It promotes positive work environments that benefit both individuals and society.

This paper's originality lies in its focus on how HRTD contributes to workplace spirituality in higher education. It emphasizes supporting colleagues, fostering growth and utilizing e-learning, offering unique insights into spirituality at work. The methodology, using structured questionnaires and statistical analysis among faculty, provides a distinct approach to studying this area.

The aim of this paper is to analyse the spillover effects of microcredit on the economy of Ecuador, with a particular focus on its potential as a poverty alleviation mechanism.

To address our research questions, we take into account the distance between cantons (Ecuador’s own administrative distribution) by adopting a spatial autoregressive (SAR) model. To this end, a database will be constructed with macroeconomic information about the country, broken down by canton (administrative division of Ecuador), and in a 2019 cross section, with a total of 1,331 microcredit operations in all 221 of Ecuador’s cantons.

We find a positive effect of microcredit on these neighbouring regions in terms of wealth generation.

We acknowledge that this study is limited to Ecuadorian cantons. Nonetheless, it is crucial to emphasize that focussing on an under-represented developing country like Ecuador adds significant value to the research.

Facilitating access to microcredit is one of the main solutions to address the goals proposed in the sustainable development goals (SDGs).

Microcredit activity contributes to the creation of value and wealth in Ecuador, exerting a spillover effect in neighbouring areas that can generate positive multiplier effects and alleviate poverty. For all of the above reasons, our proposal for the country is to support and promote microcredit as one of the main solutions to address the goals proposed in the SDGs.

The novelty of this study lies in the use of spatial econometrics to observe the indirect effects of microcredit on the regions bordering the canton in which it was issued, thus examining the spatial effects of microcredit on wealth distribution.

In order to estimate the value of semi-automated subject indexing in operative library catalogues, the study aimed to investigate five different automated implementations of an open source software package on a large set of Swedish union catalogue metadata records, with Dewey Decimal Classification (DDC) as the target classification system. It also aimed to contribute to the body of research on aboutness and related challenges in automated subject indexing and evaluation.

On a sample of over 230,000 records with close to 12,000 distinct DDC classes, an open source tool Annif, developed by the National Library of Finland, was applied in the following implementations: lexical algorithm, support vector classifier, fastText, Omikuji Bonsai and an ensemble approach combing the former four. A qualitative study involving two senior catalogue librarians and three students of library and information studies was also conducted to investigate the value and inter-rater agreement of automatically assigned classes, on a sample of 60 records.

The best results were achieved using the ensemble approach that achieved 66.82% accuracy on the three-digit DDC classification task. The qualitative study confirmed earlier studies reporting low inter-rater agreement but also pointed to the potential value of automatically assigned classes as additional access points in information retrieval.

The paper presents an extensive study of automated classification in an operative library catalogue, accompanied by a qualitative study of automated classes. It demonstrates the value of applying semi-automated indexing in operative information retrieval systems.

Students pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.

Predictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.

The results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.

The entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.

The responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.

Furthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.

Comparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.

This study aims to identify how the involvement of female university students in volunteer organisations is contributing to their self-empowerment in Bangladesh.

A cross-sectional study with a qualitative approach was conducted. A total of 20 in-depth interviews with female student volunteers, two focus group discussions with student members of the volunteer organisation and ten key informant interviews with academics, gender experts and high-level representatives of civil society organisations were conducted. The data were collected from eight purposively selected universities in Dhaka. The data were collected between 1 January 2023 and 23 March 2023.

The inter-organisational environment appears to be supportive and welcoming, despite the fact that some male colleagues belittle women with insulting comments. Female students are predominantly involved in public presentation activities and their advice is rarely considered. To reach a top position, they have to show more commitment than their male colleagues. Subjective prejudices discourage women from taking on positions of responsibility. Participation in voluntary organisations strengthens the self-confidence, critical thinking, networking and social capital of female students, making it easier for them to gain employment. These factors contribute to the empowerment of female students.

This study is an excellent empirical document that establishes a link between the empowerment of female students and their participation in voluntary activities. The recommendations of this study pave the way for future research in different countries on how volunteering helps young people, especially female students, to shape their future by taking on social responsibility alongside their academic activities.