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Small-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.

A cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.

According to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.

This is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

Entrepreneurial action under uncertainty has captured the interest of scholars and practitioners alike. However, this growing body of research has yet to connect entrepreneurial action with actual actions of entrepreneurs. We combine insights from effectuation theory and the psychology of entrepreneurship to investigate drivers of entrepreneurial actions involved in starting and running ventures, particularly optimism, self-efficacy and the use of causal and effectual logics.

The study employs a unique mixed-method approach combining a survey with experience sampling data. After measuring demographics, preference for effectual or causal logics and psychological variables, the 197 US entrepreneurs sampled entrepreneurs logged their daily actions in the form of asks during 60 consecutive days.

Results suggest that self-efficacy and causal logics are key drivers of entrepreneurial actions, while optimism serves as a deterrent. Interestingly, the impact of self-efficacy on actions is moderated by the entrepreneur’s experience level, measured both in years and past asking experience.

The potential of the ask as the basic mechanism for entrepreneurial actions is explored. Based on the findings, the authors offer new and fertile insights by linking psychological traits to entrepreneurial actions, causal and effectual logics and entrepreneurial expertise development.

This paper aims to analyse the advancement of social enterprises in Indonesia by providing comprehensive insights into crucial aspects of social enterprises such as stakeholder interests, business models, challenges and future objectives.

Using a case study approach, the study investigates four social enterprises using a narrative methodology to gain a detailed understanding of their operations. By adopting a systems perspective, the research uncovers the dynamics among stakeholders, challenges and the evolution of business models, offering a nuanced view of the social enterprise ecosystem.

The findings demonstrate that social enterprises in Indonesia emerge with a noble mission to address unmet community needs. Notably, effective collaboration among diverse stakeholders, including both the private and public sectors, plays a crucial role in achieving the missions of these social enterprises. The study highlights the significance of social enterprises in bridging gaps left by the government and contributing to positive societal impact.

By deepening the understanding of social enterprise development in Indonesia, this research provides valuable insights for policymakers, practitioners and researchers in fostering their growth and effectiveness. Ultimately, it contributes to the broader knowledge on social entrepreneurship and sustainable development.

The study aims to identify the evoked “sense of place” that the campus community attributes to a watershed area in a Malaysian higher institution, aiming to enhance their participation in watershed conservation. Central to this objective is the incorporation of the concept of a watershed as a place, serving as the conceptual framework for analysis.

This case study explores an urban lake at Universiti Malaya, Malaysia’s oldest higher institution. It uses diverse qualitative data, including document analysis, semi-structured interviews, vox-pop interviews and a co-production workshop, to generate place-based narratives reflecting the meanings and values that staff and students associate with the watershed. Thematic analysis is then applied for further examination.

The data patterns reveal shared sense of place responses on: campus as a historic place, student, staff and campus identity, in-place learning experiences and interweaving of community well-being and watershed health. Recommendations advocate translating these narratives into campus sustainability communication through empirical findings and continuous co-production of knowledge and strategies with the campus community.

The research findings play a critical role in influencing sustainable campus planning and community inclusion by integrating place-based frameworks into sustainable development and watershed management. The study recommends the process of identifying place-based narratives with implications for the development of sustainability communication in a campus environment.

This paper contributes both conceptually and empirically to the sustainable management of a campus watershed area through place-based thinking. It outlines a process for enhancing campus sustainability communication strategies.

This study aims to develop a novel theoretical model for predicting the users’ intention to use virtual tools designed for construction risk evaluation. Risk evaluation is a vital objective for construction managers. This paper intends to examine critical factors such as potential benefits, motivation, performance expectancy and rich sources of information that may affect users’ intention to use virtual technology.

A pile training module (PTM) was developed in a virtual environment to analyze the proposed virtual reality-technology acceptance model (VR-TAM) factors. Further, a questionnaire survey was conducted with the participation of 102 construction professionals in China to validate the proposed VR-TAM model and PTM tool. The retrieved data was computed to test the proposed model by using partial least squares structural equation modeling and the significance of the PTM tool in a virtual environment.

The results of this study reveal that high-significance paths represent five relationships between crucial factors affecting users’ intention to use a selected virtual reality (VR) module. Five of seven hypothesis paths were significant with acceptable t-values. By quantitative measurement of high-significance paths, this research has found that each factor under VR-TAM has received significant loadings, with many above the 0.7 threshold mark and others around 0.6. The top factors include “motivation” and “benefits” and have multiplier effects on “intention to use” as the source factors.

The finding of this study presents crucial factors for VR adoption, and the proposed VR-TAM model contributes to the body of knowledge toward managing construction risk using pre-optimization and understanding in a virtual environment. This study supports Chinese construction company managers in effectively using VR technology in their construction projects for risk assessment and management.

This study offered the development of a novel VR-TAM integrated with risk assessment techniques for piling processes. Further, the developed model was analyzed by using a survey of Chinese construction professionals to collect perceptions about the modified theoretical model of VR-TAM.

This study aims to investigate the influence of consumer value on women’s attitudes towards their intention to adopt menstrual cups. Drawing on consumer value theory, the research seeks to provide an empirical investigation of value-attitude-behaviour, an extant exploration of value concept in behaviour.

Data for this study was collected through survey questionnaires administered to 304 Indian women and analysed using partial least squares structural equation modelling.

The study’s finding indicate that emotional values (EVs) significantly predict women’s attitudes towards their intention to use menstrual cups. In addition, the desire for knowledge, price and quality considerations and awareness of the environmental impact were also found to influence women’s attitudes towards their behavioural intention to adopt menstrual cups.

This study contributes valuable empirical evidence supporting the importance of consumer values in shaping attitudes and behavioural intentions towards menstrual cups in a social marketing context. By understanding the role of EVs, social marketers can design more effective campaigns to encourage the adoption of menstrual cups. Promoting the sustainable aspects of menstrual cups, such as reduced environmental wastage, can further facilitate behaviour change among women.

This study demonstrates the value-attitude-behaviour framework, which has been a subject of very little research in the context of menstrual cup adoption in a developing country.

This paper aims to explore the accelerations and constraints libraries, archives, museums and heritage organisations (“collections-holding organisations”) face in their role as collection data providers for digital infrastructures. To date, digital infrastructures operate within the cultural heritage domain typically as data aggregation platforms, such as Europeana or Art UK.

Semi-structured interviews with 18 individuals in 8 UK collections-holding organisations and 2 international aggregators.

Discussions about digital infrastructure development often lay great emphasis on questions and problems that are technical and legal in nature. As important as technical and legal matters are, more latent, yet potent challenges exist too. Though less discussed in the literature, collections-holding organisations' capacity to participate in digital infrastructures is dependent on a complex interplay of funding allocation across the sector, divergent traditions of collection description and disciplinaries’ idiosyncrasies. Accordingly, we call for better social-cultural and trans-sectoral (collections-holding organisations, universities and technological providers) understandings of collection data infrastructure development.

The authors recommend developing more understanding of the social-cultural aspects (e.g. disciplinary conventions) and their impact on collection data dissemination. More studies on the impact and opportunities of unified collections for different audiences and collections-holding organisations themselves are required too.

Sustainable financial investment across the heritage sector is required to address the discrepancies between different organisation types in their capacity to deliver collection data. Smaller organisations play a vital role in diversifying the (digital) historical canon, but they often struggle to digitise collections and bring catalogues online in the first place. In addition, investment in existing infrastructures for collection data dissemination and unification is necessary, instead of creating new platforms, with various levels of uptake and longevity. Ongoing investments in collections curation and high-quality cataloguing are prerequisites for a sustainable heritage sector and collection data infrastructures. Investments in the sustainability of infrastructures are not a replacement for research and vice versa.

The authors recommend establishing networks where collections-holding organisations, technology providers and users can communicate their experiences and needs in an ongoing way and influence policy.

To date, the research focus on developing collection data infrastructures has tended to be on the drive to adopt specific technological solutions and copyright licensing practices. This paper offers a critical and holistic analysis of the dispersed experience of collections-holding organisations in their role as data providers for digital infrastructures. The paper contributes to the emerging understanding of the latent factors that make infrastructural endeavours in the heritage sector complex undertakings.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.

This study aims to examine whether skilled female migrants can overcome gender constraints and social stigma attached to women’s service work in host societies.

Based on interviews with 40 women who moved from mainland China and entered Hong Kong’s cross-border insurance business, the study examines how highly educated young women negotiate gender expectations and mobilize social networks in doing business.

This study finds different strategies women used in mobilizing social networks and constructing gender identities: some relied heavily on the warm market – networks of their family, relatives and friends – in doing business and developed careers by performing dutiful daughters, considerate “nieces” and caring “sisters”; some women also relied on the warm market but their jobs were regarded as nonconventional, and they had to deal with suspicions of inappropriate and instrumental womanhood and tried to prove themselves and gain support in the warm market; some women relied mainly on the cold market – connections with strangers – and performed feminine affinity to expand client networks away from judgments of families and friends; and some other women chose to expand the cold market by cultivating a professional image among strangers.

The findings speak to previous research about women’s subordinate roles in migrant networks and their devalued femininity in service work by illustrating women’s diverse forms of agency in negotiating gender identities in the stratified service sectors.