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Nuclear energy is a contested topic, requiring trade-offs in energy independence, ethicality and uncertainty. Anthropogenic climate change complicates these decisions further, with nuclear energy competing with other low-carbon and sustainable energy sources. Decisions about nuclear energy’s role, as part of a sustainable energy system, must be made in cooperation with all stakeholders. However, it is unclear how the public is involved in these decisions in the UK. This study aims to address this gap, exploring the degree to which public participation has occurred in the UK.

This paper conducted a scoping review of public participation in UK nuclear energy decision-making in the context of sustainable energy transitions, where the government retains and promotes nuclear energy as part of a sustainable energy system. Following a systematic literary search, this paper reviewed 28 academic and grey literature documents.

Public participation has primarily been conducted as consultations rather than active participation. There is limited evidence that consultations have meaningfully contributed to politically and socially responsible (i.e. individuals and groups working together for community benefit) decision-making, with public opinion on nuclear energy’s role being divided and is influenced by how it is framed.

Social aspects of nuclear energy development have historically received less attention than environmental and economic elements; the role of engagement and participation is relatively rare. Modern literature reviews in this context are largely absent, a gap this paper originally contribute to. This paper suggest ways in which how effective, inclusive engagement process could contribute to a fairer, responsible decision-making process and energy system in the UK.

The chapter provides an overview of the book and addresses the rationale for the selection of cases reflecting teaching and research in major areas of SDG14. For example, the impact of increasing global sea temperature, ocean acidification, and pollution on aquatic life and biosciences. Fisheries and aquaculture for seafood and marine ingredients and marine protected areas (MPAs) that favour the assemblage of fish, crustaceans, alga, coral, and mussels to enhance and stimulate biodiversity. New products derived from marine biotechnology are viewed to conserve and sustainably use the seas and oceans whilst promoting wealth creation and employment. Marine parks allow scientists to better study the marine environment and explore sustainable balances between tourism, work, and recreation in harmony with the Life Below Water – SDG14 mandate. Finally, the aspects of governance and roles of stakeholders and societal involvement are advocated in achieving the safe and effective use of marine resources. Throughout, the role of higher education in providing educated scientists and multidisciplinary specialists for future generations to come is highlighted.

This paper aims to comprehensively analyze renewable energy alternatives in Brazil, focusing on identifying the most suitable option for investment in the country’s sustainable development.

The study adopts the step-wise weight assessment ratio analysis-multiobjective optimization by ratio analysis −3NAG (a combination of three normalization methods) methodology, a multicriteria decision-making approach, to evaluate and rank renewable energy sources based on key criteria such as resource availability, cost-effectiveness, job creation potential and environmental impact.

The analysis reveals that solar energy emerges as the preferred choice for Brazil, offering significant advantages over other alternatives such as hydroelectric, wind and biomass energy. Solar energy’s distributed generation capability, cost reduction trends and positive environmental impact contribute to its favorable position in meeting Brazil’s energy needs.

While the study provides valuable insights into renewable energy selection, there are limitations regarding the criteria’ scope and the exclusion of specific renewable energy options. Future research could explore sensitivity analyses and incorporate additional criteria to enhance the study’s comprehensiveness.

This research contributes to the existing literature by thoroughly analyzing renewable energy alternatives in Brazil using a robust multicriteria decision-making methodology. The study’s findings provide actionable guidance for policymakers, businesses and stakeholders seeking to promote sustainable energy development in the country.

Traditional grey models are integer order whitening differential models; these models are relatively effective for the prediction of regular raw data, but the prediction error of irregular series or shock series is large, and the prediction effect is not ideal.

The new model realizes the dynamic expansion and optimization of the grey Bernoulli model. Meanwhile, it also enhances the variability and self-adaptability of the model structure. And nonlinear parameters are computed by the particle swarm optimization (PSO) algorithm.

Establishing a prediction model based on the raw data from the last six years, it is verified that the prediction performance of the new model is far superior to other mainstream grey prediction models, especially for irregular sequences and oscillating sequences. Ultimately, forecasting models are constructed to calculate various energy consumption aspects in Chongqing. The findings of this study offer a valuable reference for the government in shaping energy consumption policies and optimizing the energy structure.

It is imperative to recognize its inherent limitations. Firstly, the fractional differential order of the model is restricted to 0 < a < 2, encompassing only a three-parameter model. Future investigations could delve into the development of a multi-parameter model applicable when a = 2. Secondly, this paper exclusively focuses on the model itself, neglecting the consideration of raw data preprocessing, such as smoothing operators, buffer operators and background values. Incorporating these factors could significantly enhance the model’s effectiveness, particularly in the context of medium-term or long-term predictions.

This contribution plays a constructive role in expanding the model repertoire of the grey prediction model. The utilization of the developed model for predicting total energy consumption, coal consumption, natural gas consumption, oil consumption and other energy sources from 2021 to 2022 validates the efficacy and feasibility of the innovative model.

These findings, in turn, provide valuable guidance and decision-making support for both the Chinese Government and the Chongqing Government in optimizing energy structure and formulating effective energy policies.

This research holds significant importance in enriching the theoretical framework of the grey prediction model.

The highlights of the paper are as follows:

1. A novel grey Bernoulli prediction model is proposed to improve the model’s structure.

2. Fractional derivative, fractional accumulating generation operator and Bernoulli equation are added to the new model.

3. The proposed model can achieve full compatibility with the traditional mainstream grey prediction models.

4. Energy consumption in Chongqing verifies that the performance of the new model is much better than that of the traditional grey models.

5. The research provides a reference basis for the government to formulate energy consumption policies and optimize energy structure.

A novel grey Bernoulli prediction model is proposed to improve the model’s structure.

Fractional derivative, fractional accumulating generation operator and Bernoulli equation are added to the new model.

The proposed model can achieve full compatibility with the traditional mainstream grey prediction models.

Energy consumption in Chongqing verifies that the performance of the new model is much better than that of the traditional grey models.

The research provides a reference basis for the government to formulate energy consumption policies and optimize energy structure.

The case study aims to help students/learners to analyse the role of perception and its linkage to an entrepreneur’s decision-making process in setting up a social entrepreneurship venture during the COVID-19 pandemic without any prior entrepreneurial experience; understand the definition and meaning of social enterprises based on concepts/theories of social entrepreneurship; identify if AgriVijay fits the outline of a social enterprise based on its vision, challenges faced and journey as an agriculture-based technology-oriented social venture (AgTech SE); and outline the future path of AgriVijay as an independent business (post its incubation support period) using suitable strategy and funding models related to for-profit social enterprises.

This case study details the fascinating journey of a social AgTech venture – AgriVijay – through the perspectives of the protagonist Vimal Panjwani, a budding agri-business entrepreneur. Fuelled by a desire to empower the farming communities, Panjwani with the support of his dynamic mother, Shobha Chanchlani, embarked on the challenging task of crafting a business model that sought to merge community welfare with profitable enterprise. The case study illuminates the protagonist's background, revealing Panjwani’s motivations, risk-taking tendencies and the pivotal role played by his co-partner and mother, Chanchlani. It also highlights the challenges encountered by the protagonist in setting up a technology-based social entrepreneurship venture along with its success in making a social impact across marginalised farming communities. Through all this, the case study also highlights the major dilemma of the protagonist – that of continuing to balance AgriVijay’s core mission of “empowering the farmers” with profitability and long-term growth beyond its limited incubation support period, and his own dilemma of venturing into a social enterprise as a start-up venture without any prior entrepreneurial experience. The case study through its narrative encourages the readers/learners to understand the evolving dynamics of a nascent social entrepreneurial venture in a developing economy and how such a balanced model can actually be the harbinger of social impact and change in similar economies with large rural farming and marginalised communities.

The case study is most suitable for postgraduate management, weekend executive learning or distance learning students in agri business, sustainable business, social entrepreneurship and allied management domains. It can be used for teaching and learning topics related to entrepreneurship, new venture strategy, leadership and motivation, with a specific focus on agriculture business, agricultural entrepreneurship, social entrepreneurship and sustainable ventures.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

Sustainable Development Goal 14 of the United Nations aims to ‘conserve and sustainably use the oceans, seas and marine resources for sustainable development’. To achieve this goal, we must rebuild the marine life-support systems that provide society with the many advantages of a healthy ocean. Therefore, countries worldwide have been using Marine Protected Areas (MPAs) to restore, create, or protect habitats and ecosystems. Palau was one of the first countries to use MPAs as a tool to develop biodiversity within its exclusive economic zone. On 22 October 2015, Palau placed approximately 80% of its maritime territory in a network of locally monitored MPAs, which has now shown a population increase in stationary and migratory fish species. This movement towards a MPA was intentional and because of increased pressure from tourism and the increasing incursion of foreign fishing vessels in Palauan territorial waters. Since countries worldwide are using and looking towards MPAs, secondary protection projects are becoming more and more popular. This chapter highlights the practical implementations and results in Palau, how to theoretically apply this within the Greater North Sea in combination with Windmill Farms, and how the Marine Strategy Framework Directive stimulates these practices.

The study aims to determine the impact of sustainable manufacturing on environmental performance through government regulation and eco-innovation in Indonesian small and medium-sized enterprises (SMEs).

The results indicate sustainable manufacturing plays a significant role in SMEs' environmental performance and regulations, and eco-innovation can moderate it. It also reveals that government regulation has a positive and significant effect on environmental performance. Moreover, eco-innovation has a positive and significant effect on environmental performance.

The findings of this study indicate that SMEs can embrace sustainable manufacturing practices and achieve their long-term sustainability goals by adhering to regulations, collaborating with stakeholders and implementing eco-friendly innovations.

This research uncovers ground-breaking perspectives on the evolution of scientific knowledge about the impact of eco-innovation, regulatory measures and sustainable manufacturing practices on the environmental performance of SMEs.

There is a knowledge gap regarding the determinants of open innovation processes and outcomes in a joint value creation context, as well as what role artificial intelligence (AI) and data management play in facilitating open innovation processes. One strategy to better understand joint value creation through open innovation, supported by AI and data management, is to conduct studies on the digital business ecosystem (DBE). The purpose of this paper is to improve our current knowledge of this urgent issue in contemporary management through the lens of an ecosystem-based theory by conducting an empirical study on two DBEs (called ecosystem micro-communities (EMCs)), developed by Haier, as well as multiple literature reviews on the key concepts “Haier EMC” and “digital business ecosystem”.

By building on multiple literature reviews and empirical data from a multi-year and ongoing research program driven by Haier, this study examines Haier’s EMC model for AI-driven DBEs. Secondary data were collected through iterative literature reviews on DBEs, the EMC concept and the two selected EMC cases. The empirical data were collected through a qualitative study of two Haier EMCs in China.

Haier's ecosystem micro-community concept represents a radical shift towards a more flexible, responsive and innovative cross-industry organizational structure, offering valuable lessons for business leaders and scholars. Haier’s ecosystem micro-community model, part of their RenDanHeYi philosophy and here viewed as a DBE, is a pioneering management concept that not only redefines the management of the firm and the traditional corporate structure, but also the traditional view on innovation management, business strategy, human resource management and marketing (customer centricity). The concept has therefore an important and big impact on traditional management. For scholars, the gap in understanding innovation processes in open business ecosystems is addressed by the concept. However, the concept also opens new areas for academic research, particularly in innovation management, business strategy, human resource management and marketing. The concepts further encourage more interdisciplinary research.

The DBE is a relatively new research area that will need more research. While the EMC model is promising as an effective version of a DBE, its effectiveness across different industries and organizational cultures needs to be explored further. Future research should investigate its applicability and impact in diverse business environments. To understand the EMC’s long-term impact, longitudinal studies are needed. These should focus on the sustained competitive advantages, potential market disruptions and the evolution of customer value propositions over time. Finally, considering increasing concerns about data privacy and security, future research should also explore how DBEs solve the issue of data protection and IP while promoting open innovation and value sharing.

For managers and practitioners, the EMC concept could inspire leaders to learn how to foster innovation by creating smaller, autonomous teams that can respond quickly to market changes in the form of a DBE. The concepts exemplify how value creation and capture could be enhanced for any company and even could be a new strategy in the company’s digital transformation and repositioning into a more competitive, high-end player on the market. The concept also emphasizes employee empowerment and ownership, which can lead to higher job satisfaction and retention rates. The concept can further improve companies’ adaptability and resilience by decentralizing decision-making. Finally, the micro-communities allow businesses to be more customer-centric, developing products and services that better meet specific customer needs.

The social implications could be positive, as complex social problems commonly need an ecosystem approach to develop and deliver impactful solutions. In addition, Haier’s ecosystem micro-community model seems inherently scalable and culturally adaptable.

Haier’s EMC model is well-known in the research literature and is a novel approach to DBEs, which has been proven successful and replicable in different countries and industries. Providing insights from multiple literature reviews and two unique Haier EMC cases will contribute to a better understanding of highly effective data- and AI-driven business ecosystems, as well as of determinants of open innovation processes and outcomes in a joint value creation context, as well as what role AI and data management play in facilitating open innovation processes.