Case Article—The RealPro Customer Benefits Program: Rekindling Shopper Loyalty Through a Subscription Service

In this case study, students combine data-based insights with strategic considerations to make fundamental business decisions at the German grocery retail chain Real. In response to dwindling numbers of customers and reduced revenues, Real developed the RealPro customer benefits program to achieve a quick turnaround. For a fixed annual fee, RealPro members receive substantial and permanent discounts of 20% on nonpromoted items from a broad range of food categories. Students employ data analytics methods to extract insights from the provided data set, which contains point-of-sale information from the actual market test of RealPro. Based on these insights, decisions concerning the rollout and design of the RealPro program must be made. We provide data analysis solutions in both Excel and R to analyze 75 thousand customer transactions. In the case extension, students can apply the difference-in-differences method and two covariate balancing algorithms for in-depth statistical analyses. For this purpose, we provide an additional unbalanced data set with 83 thousand transactions, on which the students can test and analyze propensity score matching and entropy balancing models.

Temporal clustering of Kawasaki disease cases around the world

In a single-site study (San Diego, CA, USA), we previously showed that Kawasaki Disease (KD) cases cluster temporally in bursts of approximately 7 days. These clusters occurred more often than would be expected at random even after accounting for long-term trends and seasonality. This finding raised the question of whether other locations around the world experience similar temporal clusters of KD that might offer clues to disease etiology. Here we combine data from San Diego and nine additional sites around the world with hospitals that care for large numbers of KD patients, as well as two multi-hospital catchment regions. We found that across these sites, KD cases clustered at short time scales and there were anomalously long quiet periods with no cases. Both of these phenomena occurred more often than would be expected given local trends and seasonality. Additionally, we found unusually frequent temporal overlaps of KD clusters and quiet periods between pairs of sites. These findings suggest that regional and planetary range environmental influences create periods of higher or lower exposure to KD triggers that may offer clues to the etiology of KD.

Online Social Integration and Depressive Symptoms in Adolescents

Social integration is known to be beneficial for mental health. However, it is not clear whether this applies to online as well as offline relationships. In this paper, we explore the association between online friendship and symptoms of depression among adolescents. We combine data from the popular social networking site with survey data on high school students (N = 144) and find that integration into the online network is a protective factor against depression. We also find that not all online connections are equally important: friendship ties with students from the same schools are stronger associated with depression than outside ties. In addition to friendship ties, we explore the effect of online interaction (“likes”). Overall, our results suggest that online relationships are associated with depression as well as offline friendship. However, the effect of more distant online connections is limited, while immediate social environment and peer relationships at school are more important.

Computing the Meridional Overturning Circulation from NEMO Output

With this script, the Meridional Overturning Circulation (MOC) can be computed from NEMO ocean-model output for the whole globe or the Atlantic (AMOC), Indic (IMOC) and Pacific (PMOC) subbasins. The MOC is computable in z- and sigma coordinates. Moreover, for nested configurations, it is possible to combine data from both host and nest grids. Finally, it is possible to take into account of that the ORCA model grid is curvilinear north of 20°N: it is possible to compute the northward velocity component from the velocity field in x- and y- directions and to sum up the meridional flux over latitudional bands instead of in x-direction. When both steps are applied, the resulting MOC shows however strong variability in meridional direction. It needs to be clarified, whether this is realistic or not. The software is provided in the form of the jupyter notebook "MOC.ipynb" which includes more informations on the possibilites of the computations and an extensive appendix section with comparisons to computations with cdftools, as well as with details on the computation of the MOC including nest data and taking the curvilinearity of the grid into account. Necessary python modules are listed at the beginning of the document.

How many online workers are there in the world? A data-driven assessment

An unknown number of people around the world are earning income by working through online labour platforms such as Upwork and Amazon Mechanical Turk. We combine data collected from various sources to build a data-driven assessment of the number of such online workers (also known as online freelancers) globally. Our headline estimate is that there are 163 million freelancer profiles registered on online labour platforms globally. Approximately 19 million of them have obtained work through the platform at least once, and 5 million have completed at least 10 projects or earned at least $1000. These numbers suggest a substantial growth from 2015 in registered worker accounts, but much less growth in amount of work completed by workers. Our results indicate that online freelancing represents a non-trivial segment of labour today, but one that is spread thinly across countries and sectors.

Communicating consent in sport: A typological model of athletes’ consent practices within combat sports

This paper provides a systematic attempt to empirically describe the ways in which athletes’ consent to take part in sport is socially constructed, communicated and understood by others. Due to a notable lack of prior research on this topic, we draw on insights from sex research to theorise consent as a communicative social practice, specifically applying this notion to interpreting the world of competitive combat sports. To do so, we combine data from across numerous studies using the method of concatenated exploration, producing a post hoc, longitudinal, cross-contextual qualitative analysis of the ways in which consent is practiced in such settings. We then outline a four-point typology of how consent is performed, including the following categories: overt communication; subtle communication; assumed consent and deferred consent. We conclude by arguing that the apparent predominance of subtle, assumed and deferred consent presents some worrying implications for athletes’ freedom, potentially undermining the morally transformative potential of consent within these ostensibly ‘violent’, often injurious sports contexts.

What Bots Can (and Can’t) Do? (Model of Protest and Counter-Protest Political Mobilization)

Despite the increasing interest among scholars in the effect of Internet bots, or automated social media accounts, on the processes of political communication and mobilization in the online sphere, the extent of bots’ effectiveness and the specific mechanisms of their use remain largely understudied. The deficit of the overarching conceptual understanding and concrete results is arguably due to researchers’ aspiration to solve a problem in the empirical way, without attempting to combine data analysis with mathematical and computational modeling. Having analyzed the existing models on the topic, the authors offer their own model that is based on the spiral-of-silence theory. The key features of the model that set it apart from the existing ones are the following: a) taking into account differences in the types of motivation and costs associated with expressing protest and loyalist sentiments; b) including “partner effect” into the spiral-ofsilence mechanism; c) employing a neurological decision-ma king scheme according to which the same stimulus can prompt action and be a deterrent. On the basis of a series of computational experiments with the model, the authors demonstrate that bots are more effective in mobilizing opposition members when an individual motivated for political participation refrains from it because his local social community does not share his views. In this case, the emergence of a like-minded partner bot can destroy the spiral of silence created by this community and encourage this individual to openly express his position. On the contrary, when mobilizing loyalists, bots are most effective in relation to poorly motivated individuals. The model elaborated by the authors not only allows us to evaluate bots’ effects in a new way, but it also sheds light on how people make decisions in the framework of political communication and mobilization in social networks.

Should Gatekeepers Be Allowed to Combine Data? Ideas for Art. 5(a) of the Draft Digital Markets Act

Should digital gatekeepers be allowed to gather data from users and combine data from different sources? That is one of the key substantive questions of the Digital Markets Act (DMA). It is currently addressed in Art. 5(a) of the draft DMA. There are two problems with the current wording: first, it is not specific enough to work as a self-executable provision; secondly, it could happen that users are nudged into giving consent easily so that the gatekeepers can continue to expand their sets of personal data, without users having a ‘real’ say and with third parties losing out in competition. In this contribution, I analyse this problem. My suggestion is to resort to a ‘rating solution’: qualified entities, e.g. trusted data intermediaries, should rate, certify or label the data options offered by the gatekeepers and serve as ‘data guides’ for consumers. I also look at other policy options.

Implicit Motor Imagery of the Foot and Hand in People with Achilles Tendinopathy: A Left Right Judgement Study

Objective To determine if impairment in motor imagery processes is present in Achilles tendinopathy (AT), as demonstrated by a reduced ability to quickly and accurately identify the laterality (left-right judgement) of a pictured limb. Additionally, this study aimed to use a novel data pooling approach to combine data collected at 3 different sites via meta-analytical techniques that allow exploration of heterogeneity. Design Multi-site case-control study. Methods Three independent studies with similar protocols were conducted by separate research groups. Each study-site evaluated left/right judgement performance for images of feet and hands using Recognise© software and compared performance between people with AT and healthy controls. Results from each study-site were independently collated, then combined in a meta-analysis. Results In total, 126 participants (40 unilateral, 22 bilateral AT cases, 61 controls) were included. There were no differences between AT cases and controls for hand image accuracy and reaction time. Contrary to the hypothesis, there were no differences in performance between those with AT and controls for foot image reaction time, however there were conflicting findings for foot accuracy, based on four separate analyses. There were no differences between the affected and unaffected sides in people with unilateral AT. Conclusions Impairments in motor imagery performance for hands were not found in this study, and we found inconsistent results for foot accuracy. This contrasts to studies in persistent pain of limbs, face and knee osteoarthritis, and suggests that differences in pathoetiology or patient demographics may uniquely influence proprioceptive representation.

A Collaborative Approach to Sharing Learner Event Data

This paper describes a collaboration organized around exchanging data between two technological systems to support teachers’ instructional decision-making. The goals of the collaboration among researchers, technology developers, and practitioners were not only to support teachers’ instructional decision-making but also to document the challenges and opportunities associated with bringing together data from instruction- and assessment-focused technologies. The approach described in this paper illustrates the potential importance of anchoring data products that combine data between two systems in the needs of teachers as well as aligning the content that students learn and are assessed on between systems. The increasing presence of data standards has made sharing complex data increasingly more feasible. The example collaboration described in this paper demonstrates the role that non-technical activities can play in supporting the exchange and use of learner event data.