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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.

Part 11: Modelling and Managing the Digital Enterprise; International audience; German enterprises are often characterised by low levels of digital maturity. One reason for this is a lack of required structural changes on the path towards digital transformation. We consider a prescriptive framework, the digital transformation framework (DTF), which contains four structural requirements for digital transformation. Based on 16 interviews with German digitalisation experts, we aim at an evaluation of the DTF. The outcome is an enriched version of it containing seven structural requirements including the newly identified factors culture of change, agility of organizational structure, and integration of cloud computing and platforms. The extended DTF sheds light on additional facets of the digital transformation and thus supports managers in navigating their undertaking in this dynamic environment. Corresponding implications for research and practice are discussed.

Part 2: Big Data Analytics; International audience; Big data promises to drive economic growth and development, but if not applied across borders it can lead to a greater digital divide. There are, however, no indexes measuring big data readiness on country level. Most existing indexes cover topics such as digitalization and focus on developed economies with a clear underrepresentation of Africa. Thus, the underlying question to answer is: what are the required components for an index measuring big data readiness in Africa? The design science approach is used to design the Big Data Readiness Index (BDRI). The BDRI is developed in line with the academic definition of big data under the five V’s: volume, variety, velocity, veracity and value, and consists of 75 indicators, grouped into drivers that build up the five components. We apply this index to all African countries which yields, amongst others, country rankings that show relatively high BDRI levels for coastal countries such as South Africa, Kenya and Namibia as well as for islands such as Mauritius. Limitations and further development of the BDRI are discussed.

Summarization: Finance is a popular field for applied and methodological research involving multiple criteria decision aiding (MCDA) techniques. In this study we present an up-to-date bibliographic survey of the contributions of MCDA in financial decision making, focusing on the developments during the past decade. The survey covers all main areas of financial modeling as well as the different methodological approaches in MCDA and its connections with other analytical fields. On the basis of the survey results, we discuss the contributions of MCDA in different areas of financial decision making and identify established and emerging research topics, as well as future opportunities and challenges. Presented on: European Journal of Operational Research