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Background: Currently, the two most common bariatric procedures are laparoscopic sleeve gastrectomy (LSG) and laparoscopic Roux-en-Y gastric bypass (LRYGB). Long-term data comparing the two interventions in terms of their effect on body composition and bone mass density (BMD) are scarce. Objective: The aim of this study was to assess body composition and BMD at least 5 years after LSG and LRYGB. Setting: Department of Endocrinology and Nutrition, St. Claraspital Basel and St. Clara Research Ltd., Basel, Switzerland. Methods:Bariatric patients at least 5 years after surgery (LSG or LRYGB) were recruited, and body composition and BMD were measured by means of dual-energy X-ray absorptiometry. Data from body composition before surgery were included in the analysis. Blood samples were taken for determination of plasma calcium, parathyroid hormone, vitamin D3, alkaline phosphatase, and C-terminal telopeptide, and the individual risk for osteoporotic fracture assessed by the Fracture Risk Assessment Tool score was calculated. After surgery, all patients received multivitamins, vitamin D3, and zinc. In addition, LRYGB patients were prescribed calcium. Results: A total of 142 patients were included, 72 LSG and 70 LRYGB, before surgery: median body mass index 43.1, median age 45.5 years, 62.7% females. Follow-up after a median of 6.7 years. For LRYGB, the percentage total weight loss at follow-up was 26.3% and for LSG 24.1% (p = 0.243). LRYGB led to a slightly lower fat percentage in body composition. At follow-up, 45% of both groups had a T score at the femoral neck below –1, indicating osteopenia. No clinically relevant difference in BMD was found between the groups. Conclusions:At 6.7 years after surgery, no difference in body composition and BMD between LRYGB and LSG was found. Deficiencies and bone loss remain an issue after both interventions and should be monitored.

Triggered by popular cases such as political election campaigns in the United States of America and the United Kingdom, research on fake news, particularly in the context of social media, has gained growing importance recently. Our chapter deals with the individual user’s perspective and places the focus on the competency to detect fake news – the so-called fake news detection literacy. One main challenge in this field is the empirical measurement of such an individual fake news detection literacy. Based on our previous research, we suggest an extended version of a general social media information literacy (SMIL) model which is enriched with respect to the context of fake news, i.e., mainly the evaluation of information. The extended model is empirically tested by applying correlation analyses based on a sample of n = 96. The updated construct provides a way to measure fake news detection literacy and offers various avenues for further research that are discussed at the end of the chapter.

Part 5: Big Data and Machine Learning; International audience; Big data has gained academic relevance over the last decade and is also of interest to other role-players such as governments, businesses and the general public. Based on our previous work on the Big Data Readiness Index (BDRI) we place the focus on one under-investigated aspect of big data: the linkage to happiness. The BDRI, applied on Africa, includes the topic of happiness within the digital wellbeing driver, but the link between the two topics requires further investigation. Thus, two underlying questions emerge: what is the relation between happiness and big data? And how does Africa perform in digital wellbeing? This paper includes a structured literature review highlighting five key clusters indicating this link. Furthermore, we present some first empirical insights using the BDRI focusing on Africa. Overall, the African continent performs best in the social inclusion cluster of happiness, with the most room for improvement in the job creation cluster.

Purpose – The purpose of this paper is to investigate the development of software pricing, following the advent of cloud-based business intelligence & analytics (BI & A) Software. A value-based conceptual software model is developed to ignite and structure further research. Design/methodology/approach – A two-step research approach is applied. In step one, the available literature is screened and evaluated, and this is followed by ten semi-structured expert interviews. With that input, a conceptual software pricing model is designed. In step two, this model is validated and refined through discussions with representatives of the five leading business intelligence suites. Findings – The paper sheds light on the value perception of customers and suggests a clear focus on the interaction between customers and vendors, and less on technical issues. The developed customer-centric, value-based pricing framework helps to improve pricing techniques and strategies. Research limitations/implications – The research ...

Electronic word-of-mouth (eWOM) has attracted a great deal of attention in both academia and practice in recent years. Our empirical study investigates the relation of negative comments and consumers’ trust in fashion presentations focusing on clothing. It is a product category characterized by a lot of online conversation and opinion sharing, but is surprisingly under-researched regarding eWOM. We calculate a multiple regression model moderated by consumers’ social media experience to identify the impact of a dichotomous eWOM stimulus. We find that negative comments referring to a fashion presentation cause a significant decrease of trust. However, the more experienced a user is in dealing with social media services such as Facebook or YouTube, the weaker this effect will get. These findings contribute to the existing academic discourse about the impact of negative eWOM.

Smartphone's and other mobile devices are omnipresent in many people's daily lives. Penetration of mobile devices has caused a significant increase in m-commerce usage, leading to both new opportunities and new challenges for providers. In this cross-cultural study, we investigate Smartphone usage of people from Russia and the UK to identify differences regarding the adoption of 14 prominent m-commerce services. We follow the empirical approach of Harris et al. (2005) and update it with new service items in four main m-commerce categories. Our theoretical foundation rests on the GLOBE study and the UTAUT2 acceptance model. We found that British m-commerce users, compared to Russians, have significantly higher performance expectations for m-commerce services, especially hedonic services. Social surroundings play a minor role in both countries during the decision-making process.

In this paper, we examine cryptocurrencies as a potentially disruptive sort of payment method. Due to its relative importance, we focus in particular on Bitcoin. Through an inductive, exploratory interview approach with 13 individuals in three distinct groups, the determinants usability, usefulness, and subjective norm that could make Bitcoin a game-changer are explored. The results reveal that most stakeholders consider perceived ease of use still rather low, with perceived usefulness varying according to the user group. The notion of Bitcoin as having much future potential as a payment method is confirmed across all interviewees. Interestingly, the underlying concept of a blockchain is also seen as a potential revolutionary way to create a more just society based on open platforms and open data. However, the reasons of why Bitcoin is actually a disruption to existing solutions varies widely.

Part 3: Big and Open Data; International audience; Facebook, Twitter, Instagram, and other players in the social media world have been on the rise during the last couple of years. In contrast to their popularity, their underlying business models are vague and often only linked to advertising. In this explorative study we identify new revenue sources for social media service providers besides advertising. Based on three use cases with Facebook, Tencent, and LinkedIn, we identify three possibly fruitful ways to extend existing social media business models. Subsequently, a survey with 301 respondents changes perspectives on the user’s willingness to pay in order to identify usage-related differences evoked by cultural and external circumstances. Four derived hypotheses lead the way to avenues of further research especially in terms of Big Data analytics with new e-commerce trends like Facebook’s Buy Button.

With a shift from the purchase of a product to the delivery of a service, cloud computing has revolutionized the software industry. Its cost structure has changed with the introduction of Software as a Service (SaaS), resulting in decreasing variable costs and necessary amendments to the software vendors’ pricing models. In order to justify the gap between the software’s price and the incremental cost of adding a new customer, it is essential for the vendor to focus on the added value for the client. This shift from cost- to value-based pricing models has so far not been thoroughly studied. Through literature review and expert interviews, a conceptual model for customer-centric SaaS pricing, especially Business Intelligence & Business Analytics tools, has been developed. The model has then been initially validated by discussions with the top five software players in this realm and builds a strong basis for further theoretical inquiry and practical application.