Using big data for customer centric marketing

This chapter deliberates on “big data” and provides a short overview of business intelligence and emerging analytics. It underlines the importance of data for customer-centricity in marketing. This contribution contends that businesses ought to engage in marketing automation tools and apply them to create relevant, targeted customer experiences. Today’s business increasingly rely on digital media and mobile technologies as on-demand, real-time marketing has become more personalised than ever. Therefore, companies and brands are striving to nurture fruitful and long lasting relationships with customers. In a nutshell, this chapter explains why companies should recognise the value of data analysis and mobile applications as tools that drive consumer insights and engagement. It suggests that a strategic approach to big data could drive consumer preferences and may also help to improve the organisational performance.peer-reviewe

Technology-enhanced Personalised Learning: Untangling the Evidence

Technology-enhanced personalised learning is not yet common in Germany, which is why we have tasked scientists with summarising the current status of international research on the matter. This study demonstrates the great potential of technology in implementing effective personalised learning. Nevertheless, it has not been assessed yet whether the practical implementation actually works: Even in countries such as the U.S., which lead the way in using techology in classroom settings, hardly any evaluation studies have been done to prove the effectiveness of technology-enhanced personalised learning. In the light of the above, the authors make recommendations for actions to be taken in Germany to make best use of the potential of technology in providing individual support and guidance to students

The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism

Computer vision and other biometrics data science applications have commenced a new project of profiling people. Rather than using 'transaction generated information', these systems measure the 'real world' and produce an assessment of the 'world state' - in this case an assessment of some individual trait. Instead of using proxies or scores to evaluate people, they increasingly deploy a logic of revealing the truth about reality and the people within it. While these profiling knowledge claims are sometimes tentative, they increasingly suggest that only through computation can these excesses of reality be captured and understood. This article explores the bases of those claims in the systems of measurement, representation, and classification deployed in computer vision. It asks if there is something new in this type of knowledge claim, sketches an account of a new form of computational empiricism being operationalised, and questions what kind of human subject is being constructed by these technological systems and practices. Finally, the article explores legal mechanisms for contesting the emergence of computational empiricism as the dominant knowledge platform for understanding the world and the people within it

Countering the Fear of Black-boxed AI in Maintenance: Towards a Smart Colleague

Digitalization forces improved maintenance in shop-floor systems. Companies have begun to upgrade their existing production lines by equipping them with new machinery or sensors. This enables intelligent tracking and control of manufacturing activities. Simultaneously, the advancement of computing power enables complex analyses including the adaptation of machine learning algorithms to gain new knowledge. However, previous research has revealed that intelligent decision support systems are only applied successfully if they are comprehensible for employees within the factory. Therefore, we have developed a prototype based on a comprehensible set of rules for automated anomaly identification in real-time. We include employee’s expert knowledge from the very beginning to establish a sense of participation. This is improved and enhanced by techniques from the fields of process mining and machine learning. Thus, the prototype presents previously unknown error correlations in an understandable and descriptive way combining intelligent anomaly detection by a linked knowledge database system

Prescriptive Analytics Data Canvas: Strategic Planning For Prescriptive Analytics In Smart Factories

Prescriptive Analytics deals with the task of prescribing actionable decisions. These decision-making processes are usually based on expert knowledge and existing Data Analytics solutions in a specific manufacturing environment. Prescriptive Analytics is seen as the next big thing for smart factories. Most Use Cases still focus on the descriptive, diagnostic, or predictive level. This is partly due to the complexity of Prescriptive Analytics algorithms. Another major challenge for practitioners is the lack of transparency when planning Use Cases as they are mostly seen as standalone initiatives. This paper presents a novel approach to developing Use Cases based on a fit-gap analysis for existing data objects for Prescriptive Production Management in the Smart Factory. First, a Prescriptive Analytics Data Canvas is developed to structure the input data for Prescriptive Analytics in the Smart Factory. Then, promising Use Cases are selected based on the Data Canvas and existing data collection methods. Synergies between different Use Cases in the same factory are derived. We demonstrate the functionality and usability of the developed artifact and method in a real-world IoT-Factory scenario

Models for online, open, flexible and technology enhanced higher education across the globe – a comparative analysis

Digital technology has become near ubiquitous in many countries today or is on a path to reach this state in the near future. Across the globe the share of internet users, for instance, has jumped in the last ten years. In Europe most countries have a share of internet users near to or above 90% in 2016 (last year available for international comparisons), in China the current share is 53%, but this has grown from just 16% in 2007, even in Ethiopia the share has grown from 0.4% to 15.4% in the same period (data from ITU). At the same time expectations of widespread adoption of digital solutions in higher education have been rising. In 2017 the New Media Consortium’s Horizon Report predicted that adaptive learning would take less than a year to be widely adopted (Adams Becker et al., 2017). And projects such as ‘Virtually Inspired’ are showcasing creative examples of how new technologies are already being harnessed to improve the quality of teaching and learning. Furthermore, discussion of the United Nations’ Sustainable Development Goals emphasise the key potentials that digital technology holds for achieving the goals for education in 2030 (UNESCO, 2017). These developments lead university and college leadership to the question of how they should position their institution. What type of digitalisation initiatives can be found practice beyond best practices and future potentials? This is the question that this study attempts to answer. It sets out to analyse how higher education providers from across the world are harnessing digitalisation to improve teaching and learning and learner support and to identify emerging types of practice. For this, it focuses on the dimensions of flexibility of provision (in terms of time, place and pace) and openness of provision (in terms of who has access to learning and support and who is involved in the design of learning provision), as both of these dimensions can significantly benefit from integration of digital solutions. The method of information collation used by the study was a global survey of higher education institutions (HEIs) covering all world continents, more than thirty countries and 69 cases. The survey found that nearly three-quarters of all HEIs have at least one strategic focus and typologies were developed based on this analysis to group HEIs with similar strategic focuses. Overall, the findings suggest that most higher education providers are just at the beginning of developing comprehensive strategies for harnessing digitalisation. For this reason, the authors of this study believe that providers can benefit from the outcomes of this study’s research, as it can be used by university and college leadership for benchmarking similarities and differences and for cooperative peer learning between institutions. The database of cases and the guidelines for reviewing current strategies, which accompany this study, aim to facilitate this learning and evaluation process

Effect of Industry 4.0 on Education Systems: An Outlook

Congreso Universitario de Innovación Educativa En las Enseñanzas Técnicas, CUIEET (26º. 2018. Gijón

Effects of spermidine supplementation on cognition and biomarkers in older adults with subjective cognitive decline (SmartAge)—study protocol for a randomized controlled trial

Background: Given the global increase in the aging population and age-related diseases, the promotion of healthy aging is one of the most crucial public health issues. This trial aims to contribute to the establishment of effective approaches to promote cognitive and brain health in older individuals with subjective cognitive decline (SCD). Presence of SCD is known to increase the risk of objective cognitive decline and progression to dementia due to Alzheimer’s disease. Therefore, it is our primary goal to determine whether spermidine supplementation has a positive impact on memory performance in this at-risk group, as compared with placebo. The secondary goal is to examine the effects of spermidine intake on other neuropsychological, behavioral, and physiological parameters. Methods: The SmartAge trial is a monocentric, randomized, double-blind, placebo-controlled phase IIb trial. The study will investigate 12 months of intervention with spermidine-based nutritional supplementation (target intervention) compared with 12months of placebo intake (control intervention). We plan to recruit 100 cognitively normal older individuals with SCD from memory clinics, neurologists and general practitioners in private practice, and the general population. Participants will be allocated to one of the two study arms using blockwise randomization stratified by age and sex with a 1:1 allocation ratio. The primary outcome is the change in memory performance between baseline and post-intervention visits (12 months after baseline). Secondary outcomes include the change in memory performance from baseline to follow-up assessment (18months after baseline), as well as changes in neurocognitive, behavioral, and physiological parameters (including blood and neuroimaging biomarkers), assessed at baseline and post-intervention. Discussion: The SmartAge trial aims to provide evidence of the impact of spermidine supplementation on memory performance in older individuals with SCD. In addition, we will identify possible neurophysiological mechanisms of action underlying the anticipated cognitive benefits. Overall, this trial will contribute to the establishment of nutrition intervention in the prevention of Alzheimer’s disease

"From Big Data to Smart Knowledge - Text and Data Mining in Science and Economy" (Köln, 23.-24. Februar 2015)

Report on a conference held at Cologne from 23 to 24 February 2015: "From Big Data to Smart Knowledge - Text and Data Mining in Science and Economy

Regulating Data as Property: A New Construct for Moving Forward

The global community urgently needs precise, clear rules that define ownership of data and express the attendant rights to license, transfer, use, modify, and destroy digital information assets. In response, this article proposes a new approach for regulating data as an entirely new class of property. Recently, European and Asian public officials and industries have called for data ownership principles to be developed, above and beyond current privacy and data protection laws. In addition, official policy guidances and legal proposals have been published that offer to accelerate realization of a property rights structure for digital information. But how can ownership of digital information be achieved? How can those rights be transferred and enforced? Those calls for data ownership emphasize the impact of ownership on the automotive industry and the vast quantities of operational data which smart automobiles and self-driving vehicles will produce. We looked at how, if at all, the issue was being considered in consumer-facing statements addressing the data being collected by their vehicles. To formulate our proposal, we also considered continued advances in scientific research, quantum mechanics, and quantum computing which confirm that information in any digital or electronic medium is, and always has been, physical, tangible matter. Yet, to date, data regulation has sought to adapt legal constructs for “intangible” intellectual property or to express a series of permissions and constraints tied to specific classifications of data (such as personally identifiable information). We examined legal reforms that were recently approved by the United Nations Commission on International Trade Law to enable transactions involving electronic transferable records, as well as prior reforms adopted in the United States Uniform Commercial Code and Federal law to enable similar transactions involving digital records that were, historically, physical assets (such as promissory notes or chattel paper). Finally, we surveyed prior academic scholarship in the U.S. and Europe to determine if the physical attributes of digital data had been previously considered in the vigorous debates on how to regulate personal information or the extent, if at all, that the solutions developed for transferable records had been considered for larger classes of digital assets. Based on the preceding, we propose that regulation of digital information assets, and clear concepts of ownership, can be built on existing legal constructs that have enabled electronic commercial practices. We propose a property rules construct that clearly defines a right to own digital information arises upon creation (whether by keystroke or machine), and suggest when and how that right attaches to specific data though the exercise of technological controls. This construct will enable faster, better adaptations of new rules for the ever-evolving portfolio of data assets being created around the world. This approach will also create more predictable, scalable, and extensible mechanisms for regulating data and is consistent with, and may improve the exercise and enforcement of, rights regarding personal information. We conclude by highlighting existing technologies and their potential to support this construct and begin an inventory of the steps necessary to further proceed with this process