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Circular economy (CE) is receiving increasing worldwide attention as a manner to overcome the challenges linked to current trends of unsustainable energy and resource consumption. This paper aims to fill this gap and analyze the adherence to sustainable, access-based and collaborative consumption practices by exploring the role of CE awareness, specifically in the context of Porto, the second-largest city of Portugal.

The methodology of choice is quantitative, based on partial least square-based structural equation modeling.

The result shows that there is an influence of CE awareness on subsequent sustainable consumption models.

Present research contributes to the theory on CE awareness and sustainable consumption. It proposes a model that could be applied in other countries. As this research is developed within the city of Porto, it may limit generalizations of obtained results.

As CE practices are embodied into national and local policies, this research contributes to understanding local contexts of CE practices dissemination, providing practical suggestions for businesses and policymakers aiming the transition to the CE.

An original approach to measuring the awareness of CE economy is proposed, that is analyzed not only from the familiarity perspective but in six dimensions of its construction: familiarity, importance, perception or interpretation, advantages, social impact and barriers in this process. Further, the conceptual model of the impact that these dimensions have on the adoption of sustainable consumption models (purchase of sustainable products, access-based and collaborative consumption) is proposed.

There are many indications that government policymakers and supporters of large-scale nuclear expansion in Poland have not seriously grappled with arguments critical of this direction of the country's power development. Instead, there is a mood of euphoric elation in these circles without even an attempt to reflect on why this kind of nuclear power is in a state of perennial crisis and lack of development prospects in Western countries.

The purpose of this chapter is to consider from an economic perspective the potential role of nuclear power in decarbonising the Polish power sector. It needs to answer two questions: why not develop large-scale nuclear power and why small modular reactors (SMRs) can be a better alternative for decarbonisation of the Polish power sector.

The primary research method used in the preparation of this chapter is a critical analysis and synthesis of the literature on the subject.

A technological revolution will offer electricity customers increasingly better alternatives. Among them there is also technology of SMRs which seems to be much less risky option in terms of its compatibility with the direction of the power sector's evolution as well as cost of sectors’ decarbonisation.

Despite a growing body of research focusing on the dark side of sharing economy development, arguments are fragmented and incomplete. This study aims to address the gap by integrating existing viewpoints based on a provider’s perspective.

This study conducted a bibliometric analysis using text mining and clustering algorithm techniques to measure the scope of scientific output on this topic and identify the main research themes.

Through the bibliometric analysis, this study developed an integrative framework based on the platform providers’ internal management issues and external conflicts with consumers, society, government regulations and traditional business. It also identified significant gaps within each research theme and proposed a future research agenda.

Sharing economy development has not yet been fully understood and regulated, leading to unprecedented challenges to existing business systems. The study addresses knowledge gaps and advances the understanding of the dark side of the sharing economy based on the provider’s internal management and interplay with external forces. It offers a roadmap for future research to advance understanding of the “hidden” dark side of the sharing economy.

This bibliometric study provides an overview of research related to digital transformation (DT) in the tourism industry from 2013 to 2022. The goals of the research are as follows: (1) to identify the development of academic papers related to DT in the tourism industry, (2) to analyze dominant research topics and the development of research interest and research impact over time and (3) to analyze the change in research topics during the pandemic.

In this study, the authors processed 3,683 papers retrieved from the Web of Science and Scopus. The authors performed different types of bibliometric analyses to identify the development of papers related to DT in the tourism industry. To reveal latent topics, the authors implemented topic modeling based on latent Dirichlet allocation with Gibbs sampling.

The authors identified eight topics related to DT in the tourism industry: City and urban planning, Social media, Data analytics, Sustainable and economic development, Technology-based experience and interaction, Cultural heritage, Digital destination marketing and Smart tourism management. The authors also identified seven topics related to DT in the tourism industry during the Covid-19 pandemic; the largest ones are smart analytics, marketing strategies and sustainability.

To identify research topics and their development over time, the authors applied a novel methodological approach – a smart literature review. This machine learning approach is able to analyze a huge amount of documents. At the same time, it can also identify topics that would remain unrevealed by a standard bibliometric analysis.

This paper aims to explore the intellectual structure shaping the circular economy (CE) discourse within the built environment in Africa.

The study adopted a bibliometric analysis approach to explore the intellectual structure of CE in the built environment in Africa. The authors collected 31 papers published between 2005 and 2021 from the Scopus database and used VOSviewer for data analysis.

The findings show that there are six clusters shaping the intellectual structure: demolition, material recovery and reuse; waste as a resource; cellulose and agro-based materials; resilience and low-carbon footprint; recycling materials; and the fourth industrial revolution. The two most cited scholars had three publications each, while the top journal was Resources, Conservation and Recycling. The dominant concepts included CE, sustainability, alternative materials, waste management, lifecycle, demolition and climate change. The study concludes that there is low CE research output in Africa, which implies that the concept is either novel or facing resistance.

The data were drawn from one database, Scopus; hence, adoption of alternative databases such as Web of Science, Google Scholar and Dimensions could potentially have yielded a higher number of articles for analysis which potentially would result in different conclusions on the subject understudy.

This study made a significant contribution by articulating the CE intellectual structure in the built environment, identified prominent scholars and academic platforms responsible for promoting circularity in Africa.

This paper aims to use text mining methods to explore the similarities and differences between countries’ national digital transformation (DT) and Industry 4.0 (I4.0) policies. The study examines the applicability of text mining as an alternative for comprehensive clustering of national I4.0 and DT strategies, encouraging policy researchers toward data science that can offer rapid policy analysis and benchmarking.

With an exploratory research approach, topic modeling, principal component analysis and unsupervised machine learning algorithms (k-means and hierarchical clustering) are used for clustering national I4.0 and DT strategies. This paper uses a corpus of policy documents and related scientific publications from several countries and integrate their science and technology performance. The paper also presents the positioning of Türkiye’s I4.0 and DT national policy as a case from a developing country context.

Text mining provides meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, aligned with their geographic, economic and political circumstances. Findings also shed light on the DT strategic landscape and the key themes spanning various policy dimensions. Drawing from the Turkish case, political options are discussed in the context of developing (follower) countries’ I4.0 and DT.

The paper reveals meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, reflecting political proximities aligned with their geographic, economic and political circumstances. This can help policymakers to comparatively understand national DT and I4.0 policies and use this knowledge to reflect collaborative and competitive measures to their policies.

This paper provides a unique combined methodology for text mining-based policy analysis in the DT context, which has not been adopted. In an era where computational social science and machine learning have gained importance and adaptability to political and social science fields, and in the technology and innovation management discipline, clustering applications showed similar and different policy patterns in a timely and unbiased manner.

This purpose of this study was to examine the impact of social and organisational capital on service innovation capability among service firms in the United Arab Emirates (UAE) during the COVID-19 pandemic.

To test the proposed research model, data were collected using a cross-sectional questionnaire. The study sample consisted of 188 private and public service sector managers in the UAE. Partial least square-based structural equation modelling (PLS-SEM) was used to examine the research model's validity and reliability and to test the research hypothesis.

The empirical evidence indicates that during this pandemic the relationship between social capital and service innovation capability was fully mediated by strategic environmental scanning, while partially mediating the relationship between organisational capital and service innovation capability.

Managers in service organisations must be proactive during crises such as the COVID-19 pandemic. Specifically, they should emphasise effective environmental scanning and the tracking of customer preferences to provide customised services that are valued and meet the emerging requirements of their customers. Prioritising investment in organisational capital to enhance innovation capacity is also recommended.

This study is the first to examine strategic environmental scanning as a mediator between social and organisational capital and service innovation capacity during a pandemic. There were significant differences between the findings of our study and previous studies: the authors found that, during crises, management priorities change, and businesses become more reliant on organisational capital to develop service innovation capability.

The effects of big data in this present age are highly significant, and big data have become more applicable to society. Big data technology has been adopted by many, and its applications are utilized at national, organizational, and industry levels. This transformation of industries due to big data is changing working practice in academia, business, the humanitarian sector, and government, as they offer insights and positive effects across all sectors, making legal, economic, political, social, and ethical impacts in our world and producing innovation, efficiency, better decision-making, and a greater return on investments. This paper reviews the social implications, risks, challenges, and present and future opportunities of big data.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

The study aims to investigate the influence of corporate governance practices on enhancing firm value in manufacturing industries in Bangladesh.

The study sample consists of 131 companies from 10 manufacturing industries listed in Dhaka stock exchange (DSE). Using the multiple regression method, the study analyzed 1,193 firm-year observations from 2012 to 2021.

The outcome reveals that managerial ownership, foreign ownership, ownership concentration, board size, board independence, board diligence and auditor quality have a significant positive influence on firm value. In contrast, audit committee size has no significant influence on firm value.

The practical implications of the current study demonstrated that good corporate governance creates value and must be invigorated for the interest of all stakeholders. Policymakers should formulate specific guidelines regarding firms' ownership structure and audit quality issues.