This study covers means, mean value theorems of the differential calculus, and mean value theorems of integral calculus.

Yes / The leading frameworks of internationalization have contributed significantly to our knowledge of how firms internationalize, but do not fully explain how firms actually create and capture value from customers when internationalizing their activities. Understanding the value creation and capture activities defining their business model(s) is critical for firms moving into less familiar markets, and is particularly relevant for service firms where variability is an inherent feature of the firm/client experience. To address this gap, we take a business model perspective to analyze 144 internationalization events of 10 professional service firms. We find that the case firms adopted four different business models when internationalizing, and that single firms may utilize portfolios of business models. Our findings contribute to both the services internationalization and business model literatures by showing how variability in the internationalization process substantiates the need for business model portfolios.

Yes / With the arrival of the service economy, businesses across different sectors have to rely increasingly on service design, with its focus on the viewpoints of customers and their experiences. Existing frameworks for evaluating customer experience tend to neglect the connection between customer experience and value co-creation, which is critical for enhancing the performance of service design. The aim of this conceptual paper is, therefore, to develop a customer experience evaluation framework that is coherently integrated with the value co-creation construct. It is achieved by intersecting the most relevant insights from prior approaches to evaluating customer experiences with a theoretical interpretation of service value as value in the experience that is always co-created and uniquely determined by the customer's personal lived and imagined experiences. The proposed framework is original in its theorizing of the evaluation process as a transformation from a customer experience evaluation to a synchronized evaluation of value in the experience and value co-creation throughout and beyond the service process. The framework proposes to utilize it in both major service redesign and on-the-spot service improvements, which are extremely relevant to businesses operating in highly competitive environments. The proposed framework is designed to guide future empirical evaluations, accommodate new theoretical extensions, and inform practical applications to design service offerings as unique and preferred experiences for customers.

Background: The rise of AI in the context of the fourth industrial revolution has captured the public’s attention. Given the potential for transformative change in business at an unprecedented scale and pace, it is imperative for stakeholders to ensure that technological advancements bring benefits to humanity and address societal challenges. With the potential to create value, as well as to destroy value, the implications of AI are substantial. Despite growing scholarly interest, there re- mains a lack of research on how AI can utilised to create shared value.  Purpose: This study explores the utilisation of AI by firms to create shared value. Specifically, it examines the underlying dynamics involved in striving to create shared value whilst utilising AI. In doing so, the study enhances the comprehension of how firms can employ this technology to create shared value, both theoretically and in practice.  Method: This study is conducted from a relativist ontology and social constructionism epistemology as philosophical standpoint. The study has adopted an inductive approach to generating theory through qualitative research. Data was collected through qualitative interviews with 12 business leaders and managers from practice. The gathered data has been analysed using thematic analysis.  Conclusion: The study indicates that companies must be driven to go beyond simply creating economic value and instead focus on creating shared value. This motivation can arise from either intrinsic- or extrinsic sources. Additionally, companies striving to create shared value must overcome barriers and exploit catalyst to extract value from utilising AI. Moreover, the potential to destroy value with AI through risks and consequences must be mitigated through a combination of self-regulation and external regulation to maximise value creation and minimise value destruction as a result of utilising AI, pointing at a shared responsibility for individuals, firms, and regulators.

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