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The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.

Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.

Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.

The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.

This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.

This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.

The study examines the presence of the pollution haven or pollution halo hypothesis in Brazil, Russia, India, China and South Africa (BRICS) and Next-11 economies. Hence, it empirically tests the direct impact of foreign direct investment (FDI) on the ecological footprint. Further, it explores the moderating role of green innovation on the nexus between FDI and ecological footprint.

The study uses the Driscoll–Kraay (DK) standard error panel regression technique to examine the long-run elasticities amongst the variables for the group of emerging countries, BRICS and Next-11, during the period of 1992 to 2018. Further, statistical robustness is demonstrated using the fully modified ordinary least squares technique.

The empirical finding shows that FDI degrades environmental quality by raising the ecological footprint. Thus, it proves that FDI is a source of pollution haven in BRICS and Next-11 countries. However, green innovation negatively moderates the relationship between FDI and ecological footprint. That means the joint impact of green innovation, and FDI proves the presence of the pollution halo hypothesis. Further, renewable energy consumption is reducing the ecological footprint, but economic growth and industrialisation are worsening the environmental quality.

This study offers policy implications for governments and policymakers to promote environmental sustainability by improving green innovation and allowing FDI that encourages clean and advanced technology.

No prior studies examine the moderating role of green innovation on the relationship between FDI and ecological footprint in the context of emerging countries.

This study aims to explore the adoption behaviour of consumers towards innovative technology products and services (ITPS).

A qualitative study using semi-structured in-depth interviews was conducted with 47 respondents. Their lived experiences across 50+ ITPS were studied. A grounded theory approach was used to develop a theory with reference to consumer adoption of ITPS.

Themes emerged across the adoption process, such as triggers for adoption (pressing need, making life more pleasurable, urge to acquire and forced initiation); hesitancies faced by consumers during evaluation (value alignment, utilization, ecosystem, risks with new technology and price); and factors that help in overcoming the hesitancies (word of mouth, de-risking schemes and self-devised strategies).

Innovators must understand customer triggers and design offerings that activate the same – addressing a pressing need or making lives more pleasurable. Users driven purely by an urge to acquire can be a source of early word of mouth for radical innovations. Innovations must be designed and communicated to minimize hesitancies. Mitigating schemes such as equated monthly installment and return policy can be offered to empower customers to overcome hesitancies. Factors such as price, risk, beliefs, traditions and nationalistic values assume importance, specifically in an emerging economy.

This study based on grounded theory keeps the user at the centre and explains the innovation adoption phenomenon for a wide variety of 50+ ITPS in the context of an emerging economy.

The purpose of this paper is to demonstrate how network theory and methods can provide insights into the forces shaping architectural learning agendas and knowledge construction in architectural schools.

The methodology involves conceptualising learning as a constructivist process and the agenda as an interconnected network of actors, concepts and relations. Network analysis techniques, including centrality and brokerage metrics, are used to identify roles and knowledge flows using the data locally collected from Turkish universities as well as from the OpenSyllabus open-source database.

The analysis reveals the enduring influence of early modernists, signalling imbalanced canon formation in the architectural learning system. However, marginal voices highlight struggles in integrating unconventional perspectives. Limited integration of local figures indicates a consolidation of Eurocentric epistemes. Identifying these hidden forces is vital for reimagining learning agendas and socio-culturally engaged forms of learning. Pioneering figures demonstrate potential for synthesis when situated as brokers, not bifurcated schools.

The outcomes are limited by the geographical and temporal boundaries of the data and the analysis method employed. Despite limitations, the diagnostic network framework reveals architectural learning as an open, contested ecosystem demanding pluralistic pedagogies concerning not only the global but the local, both canonical and marginal. Further research covering more data could enrich the understanding of qualitative complexities.

The network perspective prompts critical reflexivity about power, ideology and exclusion in knowledge construction. Strategic inclusion and diversification of voices provide pathways to bridge divides and ground learning locally.

This research offers a methodology model to examine forces and influences shaping architectural education by elucidating hidden and remote roles and knowledge gaps in learning agendas. Extending the techniques more widely can enable strategic interventions toward inclusive, impactful learning across disciplines, time and geographies.

Introduction: This chapter examines the impact of Financial Technology (Fintech) on Environmental, Social, and Governance (ESG) goals to promote a sustainable financial system. Digital payment platforms, blockchain applications, and AI-powered analytics have revolutionised the financial landscape in recent years. These advancements have made integrating ESG principles into investment decisions and business practices easier.

Purpose: The main aim of this chapter is to analyse the connections and possibilities that Fintech offers to achieve ESG goals. Understanding how Fintech can facilitate sustainable finance practices is crucial for promoting investment in Fintech.

Methodology: A series of indexes have been examined, including the Global FinTech Index (GFI) in Global and Regional Rank, the Global Sustainable Competitiveness Index, and performing the Green Growth Index, the Green Economic Opportunity Index, the Global Green Finance Index (GGFI), and the Financial Inclusion Index.

Findings: Through comparative analysis, it can be concluded that the countries with the highest rankings are Sweden, Finland, Denmark, Switzerland, and Germany. Sweden ranks highly in the GFI. These results show that these countries rank highly in achieving ESG objectives. Balkan countries, specifically Albania, Bosnia and Herzegovina, and Montenegro, have the weakest results compared to other countries. Policymakers can benefit from the study’s findings to design better regulations and frameworks that promote responsible fintech practices and foster sustainable finance.

Practical Implications: Regulators and agencies responsible for measuring fintech and ESG should strive to align the indexes associated with these two domains as closely as possible. In addition, businesses can utilise the findings of this study to increase awareness about the diverse solutions that fintech offers to achieve the objectives of ESG.

Battery electric vehicles (BEVs) are living up to their claims as consumers choose them more frequently. The increasing demand for sustainable vehicles translates into the global need for specific components, materials, and infrastructures and drives the regulatory frameworks in each country. While BEVs offer environmental benefits and global business opportunities, the technology has not yet gained mainstream acceptance. Thus, this work aims to investigate the characteristics of BEV users and their role in the diffusion of products to larger segments, as this may vary from country to country. For this purpose, a survey based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) (Venkatesh et al., 2012) framework and structural equation modeling (SmartPLS) was adopted. The results indicated that, except for the constructs of effort expectancy (EE) and social influence (SI), the predictors in the model performed well in this context. Current users are satisfied with their vehicles and are supportive of BEVs in the future. The analysis also revealed that in addition to the availability of financial resources, early adopters are attracted by new technologies in a way that leads them to make decisions outside of the traditional influence of the other members of society. It is suggested to leverage the perceived benefits of status, differentiation, or uniqueness motives, to appeal to those seeking to appear trendy and tech-savvy in society. Companies and policymakers should acknowledge the peculiarities of early customers in their communication strategies to reach a wider audience around the globe and encourage the adoption of BEV technology.

This final chapter of this book highlights and critically discusses some specific issues concerning talent management in the context of higher education raised in the chapters of this book. It recapitulates the transition higher education is going through. This transition started decades ago but was boosted by the movements of Open Science and Recognition and Rewards. It leads to a reorientation on the conceptualization of academic performance and subsequently also on the meaning of talent and talent management in academia. It points to a shift from an exclusive and performance orientation on talent, to an inclusive, developmental approach to talent management or a hybrid form. Yet, Thunnissen and Boselie state that there is a talent crisis in academia, and this crisis urges the need for more innovative ways of developing and implementing talent management practices. This chapter ends with some recommendations for further talent management research and practice.

Organizations have started using the metaverse to sell non-fungible tokens, execute engineering processes and conduct business meetings. A condition of creating value by moving business processes to the metaverse is acceptance of this technology. In business-to-business scenarios, internal employees and external partners may have different views on the topic but must agree upon new practices. Understanding common motivations and challenges associated with using the metaverse is crucial to its success.

The authors interviewed managers from a pharmaceutical company considering conducting meetings with clients in the metaverse. A series of 23 statements on reasons for (non)-use was generated. Twenty-five individuals (13 employees and 12 clients) then ranked these statements against each other, revealing what would drive or hinder their metaverse use. The authors compared these perspectives to identify common issues.

The authors identified four different views. Views 1 and 2 correspond to internal and external participants, while Views 3 and 4 correspond to external ones only. View 1 is skeptical and underlines the role of peers in acceptance. View 2 is a positive perspective centered on usefulness. View 3 is ambivalent and is centered on efforts required to use the metaverse. View 4 reveals a reversed perspective wherein using the metaverse is a low-effort activity.

This paper proposes a case study probing acceptance of a realistic business use of the metaverse. This paper identifies risks to mitigate and motivations to leverage when proposing metaverse usage in a business-to-business context.

This is the application of the Entropy and TOPSIS model to assess the eco-efficiency of European financial institutions using environmental, social, and governance (ESG) strategies. The aim is to categorize financial institutions based on key factors such as environmental training and management and to examine the alignment between ideal ESG performance and eco-efficiency.

The study uses environmental, social, and governance (ESG) strategies to identify and categorize eco-entrepreneurs in European financial institutions. The study utilizes data to examine the structure between environmental training, effective management practices, and the green performance of financial institutions.

The study shows that European financial institutions exhibit varying degrees of eco-efficiency as assessed using the Entropy and TOPSIS model applied to ESG strategies. Surprisingly, the study found that institutions with a high ESG performance do not always match those with the highest eco-efficiency.

They emphasize the need for financial institutions to align their operations with sustainable practices. This research provides insights to increase eco-efficiency and improve the ESG performance of financial institutions. It also informs policy and decision-making in these institutions in relation to environmental training and management practices, contributing to the wider dialogue on sustainable finance.

This indicates a discrepancy between ESG ratings and actual eco-efficiency, emphasizing the need to reassess the ESG framework. The study findings are crucial for aligning financial institutions with sustainable practices and improving the effectiveness of the ESG framework, especially for institutions at the lower end of the eco-efficiency spectrum.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.