Search results

By analysing and discussing the case study, students should be able to evaluate the factors responsible for social entrepreneurship, more specifically, Harinath Kashiganeshan as a social entrepreneur; explore the entrepreneurial intention of Kashiganeshan; understand the link between social entrepreneurship and community development; examine the role of social entrepreneurship with regard to Sustainable Development Goals; and evaluate the business model, supply chain and marketing strategies in the context of the protagonist’s.

The case study revolves around the entrepreneurial journey of Kashiganeshan, who shunned his lucrative career in the USA to revamp traditional Indian herbs for holistic health care. The protagonist returned to his roots in Pennagaram village, Tamil Nadu, India, back in 2015 and started researching the possibilities of Indian medicinal herbs which have the potential to cure complex diseases like arthritis, diabetes, anaemia and high blood pressure. While researching medicinal plants, he travelled across Tamil Nadu to identify traditional herbs with medicinal properties. He visited the local farmer’s market, interacted with them and shared the importance of organic farming. Subsequently, he became a strong advocate for organic agriculture and traditional medicine. He developed “Moringa Bullets”, made from medicinal plants to treat arthritis, diabetes, anaemia and high blood pressure. Along with preparing herbal concoction medicinal recipes, he started creating awareness towards organic farming among local communities. The motto was to help communities learn this recipe and prepare independently.

This case study is suitable for postgraduate students.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

Research indicates a significant risk of economic crime associated with post-disaster funding. The purpose of this paper is to assess the characteristics of post-disaster funding that make it susceptible to the risk of economic crime and to analyse how the statutory and regulatory disaster risk management instruments of South Africa aim to manage post-disaster events.

This paper uses secondary sources such as, but not limited to, legislation, institutional reports, textbooks and peer-reviewed academic journal articles.

Post-disaster funding is inherently susceptible to economic crime due to characteristics identified such as time pressure; substantial inflow of money, goods and services; inadequate needs assessment, large-scale reconstruction and the involvement of contractors or suppliers; power imbalance; and the responsibility of governments. The Disaster Management Act and National Disaster Management Framework provide an extensive regulatory framework for mitigating post-disaster funding risks by attempting to find a balance between quick aid distribution and financial controls. This paper finds that even though South Africa is known to have some of the best disaster risk management laws, the pervasive nature of the characteristics could still render post-disaster funding structures susceptible to the risk of economic crime.

There is limited scientific research on this topic. The expected prevalence of future disasters requires the regulatory and legislative disaster risk management instruments to evolve concomitantly. Research on this topic must continue to ensure that risks associated with post-disaster funding and its susceptibility to economic crime can be mitigated as far as possible.

Despite firms’ growing investments, process improvement (PI) programs often fail to deliver the expected benefits. In this paper, we argue that the widespread adoption in PI research of a paradigm founded in positivism plays a primary role in deriving these conclusions and limits the development of PI theory and practice.

We examine the main characteristics of the dominant paradigm in PI research and then propose an alternative perspective drawing on research in management innovation and complexity. Findings from two empirical case studies in a pharmaceutical and an automotive firm are reported to support our theoretical argument.

The proposed perspective highlights the interaction between various PI approaches – such as lean, Six Sigma and total quality management (TQM) – and the context-dependence and experiential aspects of PI. We argue that this perspective can better account for where, by whom and how PI approaches are shaped and used and, ultimately, can more effectively advance both theory and practice.

This study suggests that PI approaches should be considered as adaptable rather than static, in combination rather than as single entities and as continuously interpreted and translated by organizational actors rather than homogeneously diffused across companies and business units. In this paper, we discuss the substantial conceptual, methodological and practical implications of adopting this perspective.

The harmful content statement (HCS) has garnered interest over the past several years as a type of documentation that addresses harmful and/or problematic content within an institution’s collections and metadata. These statements can aid in implementing diverse, equitable and inclusive (DEI) related goals and a framework of cultural humility. This paper reviews current literature on the topic, proposes a definition and four core components for an HCS and argues how a statement can aid in an institution’s cultural humility work.

By examining harmful content statements from institutions across the US as well as existing literature, the authors assess current literature and discussion of HCSs and derive four suggested components of a statement that can be integrated into the existing theory of cultural humility.

This paper identifies common components that are often addressed when examining HCSs. After a theory of cultural humility is applied to these components, it is found that an HCS can aid an institution in integrating cultural humility into collection and metadata management workflows.

This paper examines the literature and discussion around HCSs and provides a concrete definition of what a statement is. The authors connect two bodies of literature – harmful content statements and cultural humility – and illustrate how these topics influence each other in a way that progresses both theory and practical applications for collection and metadata management.

The purpose of this paper is to analyse the measures that could be taken to combat the risk of economic crime in the aftermath of South African disasters.

This paper used secondary sources including, but not limited to, institutional reports, newspaper articles and peer-reviewed academic journal articles.

The COVID-19 pandemic was used as an example in this paper to discuss the susceptibility of post-disaster funding to the risk of economic crime and to assess how the South African government attempted to combat this risk during the pandemic. The Auditor-General of South Africa (AGSA) conducted a real-time audit of the government’s essential COVID-19 initiatives in collaboration with the newly established Fusion Centre. Through their collaborative efforts, they successfully identified mismanaged funds, facilitated the recovery thereof and prosecuted individuals and entities involved. This paper found that to proactively combat economic crime in future post-disaster events, the collaborative use of the AGSA and the Fusion Centre, in conjunction with existing bodies established under the Disaster Management Act, should be considered.

This paper contributes to the body of knowledge in disaster risk management and forensic accountancy. As the frequency of disasters is expected to increase in the future, so will the economic crime risk associated with post-disaster funding. This paper demonstrates that post-disaster funding is especially susceptible to the risk of economic crime and it is therefore important to research methods to combat this problem and prevent further losses.

Artificial intelligence (AI) has transformed various sectors, including automotive, finance, media, travel and retail by leveraging new-age technologies. Education, banking, health care, social policy and regulation, within the public sector have witnessed significant AI applications and substantial benefits. The importance of AI in the public sector includes enhanced efficiency, improved decision-making, cost savings, citizen-centric services, etc. Despite these advancements, a mindful discussion on the societal impact of AI in the public sector demands comprehension regarding its subjugation. Therefore, this study aims to analyze the role of AI in transforming the public sector using a bibliometric analysis of recent trends and challenges.

This study has used bibliometric analysis to trace the intellectual patterns of previous research. It comprises 231 articles from 2000 to 2024 from Scopus through the Scientific Procedures and Rationales for Systematic Literature Reviews protocol. This protocol has adopted a three-step process for identifying articles, i.e. assembling, arranging and assessing.

The publication trend shows an upward trajectory since 2017, whereas network visualization protrudes with the recent trends and thematic expressions, namely, Global AI ethics and policy challenges in public sectors, AI adoption and governance in public sector, challenges and opportunities of implementing AI in public administration and AI’s role in economic and public transformation.

The findings suggest AI adoption in the public sector enhances transparency and efficiency but demands ethical guidelines, legal frameworks and stakeholder governance to address challenges such as data privacy, algorithmic bias and public trust. Policies should promote responsible AI use, balancing innovation with accountability to improve public service delivery and uphold democratic values.

This paper enhances the limited literature on the integration of AI in the public sector, focusing on emerging themes and trending topics with future research directions to furnish a holistic perspective. It aims to guide researchers and policymakers in exploring areas for further investigation in this domain.

Effective knowledge management in large academic institutions is crucial for fostering innovation and improving educational practices. However, these institutions often face challenges, such as data fragmentation, siloed information systems and the complexity of integrating different data sources from various departments with complex hierarchical structures. To address these problems, the authors proposed a data fabric strategic framework that improves and enhances knowledge management by leveraging ontologies and knowledge graphs. This study aims to investigate the potential of knowledge graphs, ontological knowledge modelling and knowledge representation to improve knowledge management in large academic institutions. It also describes how technology can enhance knowledge accessibility and exchanges and improve decision-making processes based on insights from complex educational systems.

This study uses coordination theory as a foundational framework to analyse intricate data systems in preparation for constructing, the Wizard of Oz method to facilitate the systematic organisation and management of information and the execution of an ontology-based data fabric framework and knowledge graphs. The authors propose a data fabric strategic framework aimed at improving knowledge management by leveraging ontologies and knowledge graphs.

The final evaluation demonstrates that this approach effectively breaks down data silos, promotes research collaboration and improves decision-making processes in large academic settings, offering solution-oriented data fabric technologies applicable to universities and university federations globally.

The proposed system provides a more efficient way of managing and connecting fragmented academic resources, improving accessibility for both learners and educators. By interconnecting and streaming knowledge management process, the system can reduce not only operational costs but also expenses on doing scientific research.

Academic institutions prioritise time efficiency when acquiring vital data for improved scientific results. This emphasis extends beyond data governance to focus on how collective intelligence might improve organisational performance. The academic community has enhanced data utilisation through the implementation of data fabric technologies to improve data accessibility and data line tracking.

The main purpose of this study is to enhance knowledge regarding the early stages of planning for and adopting artificial intelligence (AI) in governmental public procurement. While there are numerous studies on AI and procurement in private companies, there is limited information on AI and public procurement.

The empirical data consists of information obtained from 18 semi-structured interviews with procurement managers and individuals involved in the development of procurement at governmental agencies. Additionally, a workshop was conducted with the respondents to discuss and validate the study’s findings.

Findings indicate a generally low level of AI maturity in previous research and within the investigated governmental agencies. The perceived benefits of AI primarily revolve around improved operational capabilities, potential for certain process efficiencies and the ability to enhance monitoring through AI. Various challenges related to organizational, process, technological and data management were highlighted. Findings also indicate that perceived benefits and value created by AI can be viewed from a short-term perspective to a long-term perspective.

The study provides insights into societal values that can be achieved using AI in public procurement.

This study provides a new perspective on AI in public procurement by focusing on governmental agencies. It explores the perceived benefits, interests and challenges associated with AI implementation in public procurement. Furthermore, this study discusses the potential outcomes of incorporating AI in public procurement and the impact it may have on the values created by the public service, both short- and long term.