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Serious games (SGs) are virtual systems that allow the reconstruction of the laws governing the behavior of complex adaptive systems such as urban transportation and social interaction. Unlike stated preference-based studies, improved visualization, feedback, and scores mediate players’ learning through experience. SG’s potential to understand users’ preferences regarding shared automated vehicles (SAVs) is developed. The investigation focused on three innovative, entirely automated commuting options: shared rides, shared cars, and automated transit. The research involved 10 participants actively involved in a competitive mode selection exercise, which emulated 50 workdays and was conducted in 10 separate sessions. The players aimed to maximize their overall score influenced by their mode choice, punctuality, and the other players’ choices. SG-obtained data was used to estimate a game-based discrete choice model. The sustainability policy implications of game-based methods on the future adoption of SAVs and impacts on other modes are further discussed.

Apart from the challenges related to vehicle technology, the wide-scale deployment of autonomous vehicles (AVs) in cities is linked to unprecedented opportunities and unforeseen impacts. These refer to mobility conditions, infrastructure, land use, wider socio-economic factors, energy use and environmental and climate effects. AVs may affect all these in positive or negative ways, promoting or obstructing the promotion of specific aspects of sustainable urban development. An integrated planning framework is needed to maximise the positive impacts and mitigate the negative ones. The main obstacle in the process of developing such a framework is the absence of empirical data and experience from the implementation of this emerging technology. This chapter outlines the possible impacts of AVs and discusses their uncertainty and trade-offs in relation to sustainable urban development. The categorisation of impacts derives from the priorities of the UN Sustainable Development Goal (SDG) 11: Make cities and human settlements inclusive, safe, resilient, and sustainable. The chapter also highlights the lack of data for the development of an evidence-based planning approach and suggests relevant recommendations to planners. In contrast to the current lack of data, the future abundance of Big Data collected by autonomous road transport systems is discussed in the context of future urban planning purposes. Based on the above, the chapter concludes by stressing the importance of an integrated urban transport planning approach that ensures a positive contribution of AVs to sustainable urban development. Hence, it offers valuable recommendations for policymakers in a range of fields.

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.

The supply chain is undergoing a significant digital transformation to adapt to the increasingly digitalized and globalized business environment. To remain competitive in this evolving market, businesses must seamlessly integrate digital technologies throughout the supply chain, spanning all stages from procurement to distribution. This chapter delves into models and methodologies critical to digital supply chain (DSC) transformation, with a focus on advanced techniques such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and data analytics to boost the resilience and agility of supply chain operations. By leveraging practical examples and case studies, the chapter highlights the myriad enhancements digital transformation can introduce across diverse supply chain stages, including sourcing and after-sales service. Additionally, the chapter examines the complexities of cybersecurity, data integrity, and change management within the digital transformation framework, proposing strategies to address these challenges. The insights offered in this chapter will serve as a thorough guide for both practitioners and scholars in the supply chain field, equipping them to adeptly navigate the multifaceted arena of digital transformation.

Purpose: Innovation is a multi-dimensional phenomenon influenced at the organisational level by internal and external factors that can determine how innovative an organisation can be, determining a firm’s business performance. This chapter measures and predicts how innovative a company can be, considering key internal factors using modern data analytics/science.

Need for Study: The increasing challenge of modern business operations is affected by how quickly, sustainably, effectively, and efficiently companies can innovate to mitigate the dynamic challenges of current business environments and evolving customer needs. The ability to predict, measure, and manage innovation becomes necessary to ensure that businesses are fit for purpose.

Methodology: A model was designed following the study hypotheses and statistically tested. A historical data sample from the OECD global industry dataset for eight years was used for the analysis. The ordinary least square method was used to test for model fit. Also, in machine learning engineering, predictive analysis using the multivariate linear regression analysis method was carried out.

Findings: The results support the hypotheses that an organisation’s capacity to be innovative can be measured and predicted, and it is influenced by a good number of internal factors or independent variables at various degrees.

Practical Implications: Managers must understand how to measure and predict innovation metrics to manage innovation better, ultimately leading to better business outcomes and performance. Also proposed are new measurement matrices for innovation management: innovation capacity (I_C), business innovation value (BIV), innovation creation factor (ICF), and a practical data-driven innovation management and prediction system.

Purpose: The prominence of quality education for building sustainable development is undeniable and is distinctly pointed out in 1 of the 14 sustainable development goals (SDGs). In the same context, this study intends to investigate the role of university commitment, perceived organisational prestige, student satisfaction, and perceived employability in enhancing sustainability in higher education.

Need of the Study: To evaluate how student satisfaction mediates the relationship between university commitment, perceived organisational prestige, and perceived employability with sustainable university institutes.

Methodology: An adapted questionnaire was used in this study to capture the perception of 458 management graduates selected through the purposive sampling method. Partial least squares structural equation modelling (PLS-SEM) technique was used to analyse the data with the help of Smart PLS software.

Findings: The results of this study show that student satisfaction is the strongest predictor of sustainable university institutes. University commitment was found to lead to student satisfaction significantly. Furthermore, student satisfaction wasn’t found to play the role of mediator in the proposed model.

Practical Implications: This study aims to fulfil theoretical, research, and management implications for students, higher education institutes (HEIs), and policymakers. HEIs are recommended to instil university commitment, perceived organisational prestige and student satisfaction via various practices and amendments in their curriculum. Students are recommended to enhance their perceived employability to achieve career sustainability.

The objective of this research conducted in the city of Cuenca is to elaborate on the management platform model of the smart tourist destination (STD). The chapter provides the components to develop such a system as a pilot plan. To maximize the impact of the proposed approach and enhance the decision-making capacities of local actors, the metrics that the Inter-American Development Bank (IDB) developed for the so-called intermediate cities in the study “Cuenca Sustainable City” are used. The platform (www.smarturcuenca.com) considers the transcendence of the current reality of the tourism sector, which is open to multidisciplinary work with other sectors to promote the rational use of cultural and natural resources through the Internet of Things (IoT).

Rapid technological change in the transport sector is leading to a growing range of potential and actual ‘business models’ deployable for the movement of goods and people. Two key uncertainties arise from this proliferation: first, concerning which ones can be economically viable, and, second, whether they can be both simultaneously economically viable and contribute to the imperatives of more sustainable mobility. The present chapter reviews and appraises the emergence of these new business models, drawing on both literature review and empirical research with entrepreneurs involved in the new mobility sector. Specifically, the potential of the UN Sustainable Development Goals (SDGs) (UN, n.d.) as a device to structure and frame the debate about what constitutes a valuable contribution to sustainable mobility is considered. A framework is developed which captures how mobility and transport have dependencies with the SDGs. From this analysis, key sustainability concepts are derived which have either a subsistence function (maintaining the basics of human life) or an enhancement function (enabling citizens to realise their potential whilst reducing impacts on the planet). Five different innovations involving mobility sector business entrepreneurship are then characterised using this framework to exemplify its ability to deconstruct and test claims that ‘smart mobility’ is also good for sustainability as well as good for business. It is concluded that the framework could contribute to a wider architecture of sustainability interrogation. It could promote discourse around a wide range of actors, posing questions and surfacing tensions and contingencies effectively, whilst providing a holistic, strategic assessment to inform more targeted, scientific evaluations of sustainability metrics.