Maria Jose Zapata Campos, Ester Barinaga, Richard Dimba Kiaka and Juan Ocampo
Highly deprived urban contexts, such as informal settlements in the global south, can turn into niches of extreme innovation and sparkle ingenuity out of necessity. But what are…
Abstract
Purpose
Highly deprived urban contexts, such as informal settlements in the global south, can turn into niches of extreme innovation and sparkle ingenuity out of necessity. But what are the rationales behind the participation of disadvantaged communities in social innovations? Why do they engage in grassroots innovations? What is it that makes these grassroots try novelties and continue experimenting with them, even when the perceived benefits are not clear yet? This paper aims to examine and conceptualize the rationales for engaging in grassroots financial innovations in the context of extremely deprived urban settings.
Design/methodology/approach
This paper is based on the case of grassroots organizations which have started experimenting with the development of a community currency in Kisumu, Kenya. This paper is informed by in-depth interviews with members of three grassroots organizations involved in the community currency, together with observations and meeting participation since 2019.
Findings
The rationales argued by the participants for engaging in this grassroots innovation are framed in various ways: as a means for seeking poverty alleviation (the development framing); as a challenge to conventional imaginaries of innovations (the digital framing); and as an innovation embedded in community and trust relations (the community framing). These framings have a mobilizing effect that initially draws participants into the innovation. Yet, what explains persistent participation despite the decreasing influence of these framings over time is the organizational space and strategies of incompleteness accommodating these experiments.
Originality/value
This paper contributes to the emerging body of grassroots innovations movements literature. While research has progressed in its understandings of the challenges of scaling up innovative practices, the examination of the grassroots initiatives stemming from extremely deprived settings, and the rationales and framings behind, have been under examined. This paper comes to bridge this gap.
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Devrim Murat Yazan, Guido van Capelleveen and Luca Fraccascia
The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the…
Abstract
The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?
This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.
Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.
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Agricultural systems in Mekong Delta have transformed to cope with climate change. Various researches pointed out that integrated agriculture-aquaculture (IAA) farming systems…
Abstract
Purpose
Agricultural systems in Mekong Delta have transformed to cope with climate change. Various researches pointed out that integrated agriculture-aquaculture (IAA) farming systems (i.e., rice-shrimp, rice-fish…) emerged as potential climate adaptive practices. However, limited studies are attempting to assess the sustainability of these agricultural practices. Therefore, it is essential to assess whether or not these systems will be sustainable in the context of climate change and what can be done to make it sustainable. The present study conducted the sustainability assessment of the rice-shrimp system to identify potential areas for improvement as well as policy implication to increase resilience and adaptation of coastal IAA system which could contribute to the understanding of other coastal agricultural deltas around the globe.
Design/methodology/approach
This study used a quantitative approach including the assessment protocol of van Asselt et al. (2014), the assessment framework of Vanloon et al. (2005), and the MCA methodology to flexibly and holistically assess the sustainability level of agricultural systems.
Findings
Results concluded that rice-shrimp systems have the potential to improve livelihood, food security, and adaptation of coastal farmers. Major improvements should be considered for productivity, efficiency, and equity themes, while minor improvements can be made for stability, durability, and compatibility themes.
Originality/value
This research could be used as a guideline for sustainability assessment in a context-specific case study of IAA, which showed a potential for the application of other climate-smart IAAs in similar contexts around the globe.
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Teemu Birkstedt, Matti Minkkinen, Anushree Tandon and Matti Mäntymäki
Following the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical…
Abstract
Purpose
Following the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical principles to practice through AI governance (AIG). AIG has emerged as a rapidly growing, yet fragmented, research area. This paper synthesizes the organizational AIG literature by outlining research themes and knowledge gaps as well as putting forward future agendas.
Design/methodology/approach
The authors undertake a systematic literature review on AIG, addressing the current state of its conceptualization and suggesting future directions for AIG scholarship and practice. The review protocol was developed following recommended guidelines for systematic reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).
Findings
The results of the authors’ review confirmed the assumption that AIG is an emerging research topic with few explicit definitions. Moreover, the authors’ review identified four themes in the AIG literature: technology, stakeholders and context, regulation and processes. The central knowledge gaps revealed were the limited understanding of AIG implementation, lack of attention to the AIG context, uncertain effectiveness of ethical principles and regulation, and insufficient operationalization of AIG processes. To address these gaps, the authors present four future AIG agendas: technical, stakeholder and contextual, regulatory, and process. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.
Research limitations/implications
To address the identified knowledge gaps, the authors present the following working definition of AIG: AI governance is a system of rules, practices and processes employed to ensure an organization's use of AI technologies aligns with its strategies, objectives, and values, complete with legal requirements, ethical principles and the requirements set by stakeholders. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.
Practical implications
For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.
Social implications
For society, the authors review elucidates the multitude of stakeholders involved in AI governance activities and complexities related to balancing the needs of different stakeholders.
Originality/value
By delineating the AIG concept and the associated research themes, knowledge gaps and future agendas, the authors review builds a foundation for organizational AIG research, calling for broad contextual investigations and a deep understanding of AIG mechanisms. For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.