InShopnito: an advanced yet privacy-friendly mobile shopping application

Mobile Shopping Applications (MSAs) are rapidly gaining popularity. They enhance the shopping experience, by offering customized recommendations or incorporating customer loyalty programs. Although MSAs are quite effective at attracting new customers and binding existing ones to a retailer's services, existing MSAs have several shortcomings. The data collection practices involved in MSAs and the lack of transparency thereof are important concerns for many customers. This paper presents inShopnito, a privacy-preserving mobile shopping application. All transactions made in inShopnito are unlinkable and anonymous. However, the system still offers the expected features from a modern MSA. Customers can take part in loyalty programs and earn or spend loyalty points and electronic vouchers. Furthermore, the MSA can suggest personalized recommendations even though the retailer cannot construct rich customer profiles. These profiles are managed on the smartphone and can be partially disclosed in order to get better, customized recommendations. Finally, we present an implementation called inShopnito, of which the security and performance is analyzed. In doing so, we show that it is possible to have a privacy-preserving MSA without having to sacrifice practicality

Internet Giants as Quasi-Governmental Actors and the Limits of Contractual Consent

Although the government’s data-mining program relied heavily on information and technology that the government received from private companies, relatively little of the public outrage generated by Edward Snowden’s revelations was directed at those private companies. We argue that the mystique of the Internet giants and the myth of contractual consent combine to mute criticisms that otherwise might be directed at the real data-mining masterminds. As a result, consumers are deemed to have consented to the use of their private information in ways that they would not agree to had they known the purposes to which their information would be put and the entities – including the federal government – with whom their information would be shared. We also call into question the distinction between governmental actors and private actors in this realm, as the Internet giants increasingly exploit contractual mechanisms to operate with quasi-governmental powers in their relations with consumers. As regulators and policymakers focus on how to better protect consumer data, we propose that solutions that rely upon consumer permission adopt a more exacting and limited concept of the consent required before private entities may collect or make use of consumer’s information where such uses touch upon privacy interests

A Business Intelligence Framework to Provide Performance Management through a Holistic Data Mining View

Traditional views of business intelligence have mainly focused on the physical and human aspects of the organization. This paper tries to show that a new information view of business activities can make a platform for developing business intelligence and support performance management. To do that, the paper proposes a new framework that can be used to provide high level of business intelligence for performance management usage. The framework introduces a hierarchy of performance influencers and a new methodology for managing them. The new methodology introduces a holistic view towards data mining concepts. The framework can be served as a blueprint for the companies which use any of ecommerce business models

AAPOR Report on Big Data

In recent years we have seen an increase in the amount of statistics in society describing different phenomena based on so called Big Data. The term Big Data is used for a variety of data as explained in the report, many of them characterized not just by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, the way in which they are collected, and disseminated are fundamental. The change constitutes a paradigm shift for survey research.There is a great potential in Big Data but there are some fundamental challenges that have to be resolved before its full potential can be realized. In this report we give examples of different types of Big Data and their potential for survey research. We also describe the Big Data process and discuss its main challenges

Examining Personal Information Privacy-Protective Responses (IPPR) with the Use of Smart Devices

Increasingly, smart devices (such as smart phone, iPod/mp3, or tablet) have become an essential part of daily life and work of individuals. Various applications are being developed and made available to the users based on their needs. However, many applications when downloaded and installed on a phone are used as a medium for tracking users’ personal data and behavior by companies. This research in progress examines whether users are aware of the privacy issues associated with their download and use of smart devices’ apps and how that knowledge would influence their future privacy preserving behavior. The study was conducted by surveying smart device users and analyzing their responses across three categories as antecedents of users’ privacy-protective responses: whether the users are concerned about privacy and big data gathered while they are downloading an application, subjective norms, and perceived usefulness