Gabriela Beirão

Abstract
This chapter aims to contribute to the understanding of how artificial intelligence (AI) technologies can promote increased business revenues, cost reductions, and enhanced customer experience, as well as society's well-being in a sustainable way. However, these AI benefits also come with risks and challenges concerning organizations, the environment, customers, and society, which need further investigation. This chapter also examines and discusses how AI can either enable or inhibit the delivery of the goals recognized in the UN 2030 Agenda for Sustainable Business Models Development. In this chapter, the authors conduct a bibliometric review of the emerging literature on artificial intelligence (AI) technolo¬gies implications on sustainable business models (SBM), in the perspective of Sustainable Development Goals (SDGs) and investigate research spanning the areas of AI, and SDGs within the economic group. The authors examine an effective sample of 69 publications from 49 different journals, 225 different institutions, and 47 different countries. On the basis of the bibliometric analysis, this study selected the most significant published sources and examined the changes that have occurred in the conceptual framework of AI and SBM in light of SDGs research. This chapter makes some significant contributions to the literature by presenting a detailed bibliometric analysis of the research on the impacts of AI on SBM, enhancing the understanding of the knowledge structure of this research topic and helping to identify key knowledge gaps and future challenges. © 2024, IGI Global. All rights reserved.

Abstract
The recent pandemic crisis has greatly impacted startups, and some changes are expected to be long-lasting. Small businesses usually have fewer resources and are more vulnerable to losing customers and investors, especially during crises. This study investigates how startups’ business processes were affected and how entrepreneurs managed this sudden change brought by the COVID-19 outbreak. Data were analyzed using qualitative research methods through in-depth interviews with the co-founders of eighteen startups. Results show that the three core business processes affected by the COVID-19 crisis were marketing and sales, logistics and operations, and organizational support. The way to succeed is to be flexible, agile, and adaptable, with technological knowledge focusing on digital channels to find novel opportunities and innovate. Additionally, resilience, self-improvement, education, technology readiness and adoption, close relationship with customers and other stakeholders, and incubation experience seem to shield startups against pandemic crisis outbreaks.

Abstract
Artificial intelligence (AI) has altered our world in numerous ways. Although its application has benefits, the underlying issues surrounding privacy and security in AI need to be understood, not only by the organizations that use it but also by the users that are susceptible to its vulnerabilities. To better understand the impact of privacy and security in AI, this chapter reviews the current literature on artificial intelligence, trustworthiness, and privacy and security concepts and uses bibliometric techniques to understand and identify current trends in the field. Finally, the authors highlight the challenges facing AI and machine learning and discuss the results obtained from the bibliometric analysis, which provides insight into the several implications for managers and contributions to future research and policy. © 2023, IGI Global. All rights reserved.

Abstract
Background: Over the past few years, various new types of technologies have been introduced, which have been tailored to meet the specific needs of older adults by incorporating gerontological design principles (i.e., "gerontechnologies"). However, it has been difficult to motivate older adults to adopt and use these new technologies. Therefore, it is crucial to better understand not only the role of personal drivers but also the family influences on older adults. Objective: This research goes beyond traditional technology acceptance theories by investigating the role of personal (e.g., inherent novelty seeking) and interpersonal drivers (e.g., influence of family) in stimulating older adults to use gerontechnologies. Nine hypotheses, building on traditional and new technology acceptance theories, were developed and tested. Methods: This research applies a cross-sectional study design. Therefore, a face-to-face survey instrument was developed building on a qualitative pilot study and validated scales. Three hundred and four older adults (minimum age = 70 years) were willing to participate as well as one of their family members. Structural equation modeling was applied to analyze the hypothesized conceptual model. Results: Our results extend the seminal technology acceptance theories by adding personal (i.e., inherent novelty seeking p = 0.017) and interpersonal drivers. More specifically, it was found that the attitude toward gerontechnologies was influenced by family tech savviness (i.e., people who often use technology), as this relationship is fully mediated through the social norms of older adults (p = 0.014). The same was found for older adults' trust in the family member's technology knowledge (p <= 0.001). Here, the relationship with older adults' attitude toward gerontechnologies was partially mediated by the older adults' trust in technology. Conclusion: This study identified important personal and interpersonal drivers that influence attitudes toward and intentions to use gerontechnologies. To foster technology acceptance among older adults, it was found that it is important to strengthen the trust in and the attitude toward gerontechnologies. Furthermore, family members' knowledge and beliefs in technology were the keys to promoting the actual use of gerontechnologies among older adults. Furthermore, the families' trust in gerontechnologies and the provision of access to technology can improve their attitudes toward technology and usage intentions for the older relative.

Abstract
Service organizations increasingly understand the importance of managing the customer experience to enhance customer satisfaction and loyalty. This study aims to develop a better understanding of the customer experience by investigating how the customer’s internal mechanisms influence it. That is, how it is perceived and processed at three different levels (visceral, behavioral and reflective), which determines a person’s cognitive and emotional state. To this purpose an exploratory multi-method ethnographic study was undertaken in a healthcare service. The results showed the emotions provoked by the service experience at each level. These levels are interconnected and impact each other working together to influence a person’s cognitive and emotional state, and thus playing a critical role in the overall evaluation of a service. Results show that elements such as servicescape aesthetics, face-to-face and non-human interactions influence emotions and service evaluations. The service should be designed in a way that induces positive emotions, and a feeling of being in control. Especially in healthcare services there is a need to balance the conflicting responses of the emotional stages that may be triggered at the visceral and behavioral levels, while providing reassurance and calm at the reflective level that the health problem is going to be taken care. Using service design approaches this understanding of the customers’ brain can be translated into improving the customer experience. © 2018, Springer Nature Switzerland AG.