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Bicycle sharing offers a novel way to create smart and sustainable mobility solutions for the future. The purpose of this study is to draw on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework for identifying the factors necessary to predict bike-sharing intention among users in India.

Data were collected through a questionnaire distributed across four major cities in India, and 515 responses were analyzed. A sequential approach was employed to analyze the data using Partial Least Square–Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA).

The findings from PLS analysis revealed that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation and price value are the salient variables that affect users' intentions to participate in bike sharing. In addition, based on fsQCA, six configurations of causal conditions are presented as intermediate solutions that produce the same results. Although antecedent conditions, such as habit and social influence, had an insignificant effect on individuals' BSI, they create conditions sufficient to encourage users' participation in bike sharing in combination with other variables.

A few limitations of this research and the implications of the findings in terms of theory and policy implications are also discussed.

The reported study is one of the earliest to explain bike-sharing adoption in India using the UTAUT 2 model.

The recent debate on smart cities research is challenged by the arrival of brand-new technologies and new ideas on their social impact. Beyond the hype and the expectations, the next generation smart cities research has to be grounded on the lessons learnt and the experience of the current extensive implementations of smart cities projects worldwide. Additionally, it is required to revisit the basic assumptions for the added value of smart cities research to the strategic blueprints around the world. This chapter is aiming to communicate a new agenda for future smart cities research including social, economic, technological, and community factors. The main contribution is organized around a framework that intends to integrate the technology sophistication, the human and social dynamics, and the strategy orientation of smart cities.

Digital transformation is one of the key concepts attached to the smart cities’ domain. The requirement to enhance strategically the way that business is delivered around different areas is a critical milestone for the digital transformation agenda and also for business performance management. In this short position chapter, we are focusing on the area of healthcare and we are providing key insights and lessons learned from Saudi Arabia. The main contribution of the chapter is a structured discussion on a digital healthcare strategy in the context of smart cities.

Healthcare education is a huge industry with a significant social footprint and resilient impact on well-being and on the quality of life. It integrates diverse scientific domains and needs to continuously update its value proposition to reflect the need for preparing top-quality health professionals. It also has to support professional development and to manage effectively the accreditation of programs and the certification of skills and knowledge. In this chapter, the authors expand a theoretical framework about Active and Transformative Learning (ATL) that has introduced in the volume of ATL for STEAM disciplines and also discussed how artificial intelligent (AI) tools, such as OPENAI Chat GPT, can serve as transformers and value carriers for the implementation of ATL activities and use cases in healthcare education.

Active and transformative learning is a holistic strategy for the enhancement of the unique value proposition of education and learning. In Chapter 1 of this edited volume we introduced a unique value proposition on the impact of ATL in higher education and we communicated a five-tier value framework including pillars related to ATL, higher education, industry, entrepreneurship, research& development, and innovation. In this concluding chapter we move the discussion on another context. With emphasis on the robust and resilient strategy of the Vision 2030 in the Kingdom of Saudi Arabia we comment on the capacity of the ATL to facilitate, to enable and to transform positively the added value of the Vision 2030 implementation. The chapter is organized as follows. At the beginning, we provide a short overview of the Vision 2030 mandate, and then based on the ATL metaphors we presented in Chapter 1 of this edited volume, we strategize the ATL framework towards the implementation and the resilience of the Vision 2030.

Active and transformative learning (ATL) challenges the new era of teaching and learning in higher education. In this chapter a systematic approach to ATL theories and methodologies is provided. Authors provide a unique methodological framework for the integration of active learning practices in modern higher education curricula. This chapter also provides an integrated context for the overall discussion of the phenomenon in the volume. The recent arrivals of new disruptive artificial intelligence-enabled technologies such as OpenAI, ChatGPT, DeepAI and others are only few aspects of a new challenging era for the teaching, learning, innovation and sustainability in the higher education.