Investigating the Personalization–Privacy Paradox in Internet of Things (IoT) Based on Dual-Factor Theory: Moderating Effects of Type of IoT Service and User Value

Despite people’s concerns over privacy leakage in the Internet of Things (IoT), the needs for personalized IoT services are increasing, creating a conflicting phenomenon viewed as the personalization–privacy (P–P) paradox. This study proposes a research model that utilizes dual-factor theory to investigate the P–P paradox in IoT. It aims to analyze the impact of the dual factor—personalization and privacy concerns related to IoT services—on the intention to use IoT. Further, the model includes four-dimensional motivated innovativeness and previous privacy-invasion experience as key antecedents of the dual factor. Particularly, this study examines the moderating effects of the type of IoT service and user value on the relationship between dual factor and usage intention. Data were collected using a web-based survey. The results showed that personalization had a significant impact on the intention to use IoT, whereas privacy concerns did not. The effects of all antecedents except social innovativeness were significant. The P–P paradox phenomenon appeared differently depending on the type of IoT service and user value. This study contributes to gaining a better understanding of the factors that influence the increase in IoT usage in terms of both protecting and appropriately using personal information for IoT services.

User Value Identification Based on Improved RFM Model and K -Means++ Algorithm for Complex Data Analysis

In recent years, with the development of machine learning and big data technology, user data has become an important element in the production process of enterprises. For today’s e-commerce platforms, the deep mining of user’s purchase behavior is helpful to understand user’s purchase preferences and accurately recommend products that meet user expectations, which can not only improve user satisfaction but also reduce platform marketing cost. To accurately identify the user value of online purchasing on an e-commerce platform, this paper uses an improved RFM model to extract user features and uses the K -means++ clustering algorithm to realize user classification. The indicators of the traditional RFM model characterize user features from three angles: recent purchase time ( R ), purchase frequency ( F ), and total consumption amount ( M ). The user group and scenarios studied in this paper are different from the previous literature: (1) the user group is relatively fixed, (2) the consumer goods are relatively single, and (3) the characteristics of repeated purchase are obvious. Therefore, based on the existing literature, this paper extracts the user characteristics studied and improves and models the traditional indicators. Based on the real purchasing data from September to December 2018, it calculates the indicators that improved RFM, empowers the weight to indicators, and finally classifies the value of users by using the K -means++ algorithm. The experimental results show that the user classification based on the improved RFM model is more accurate than the user classification based on the traditional RFM model, and the improved RFM model can identify the user value more accurately, which provides a strong support for the e-commerce platform to realize the accurate marketing strategy based on big data.

Review of the IMF Working Paper “Tec(h)tonic Shifts: Taxing the “Digital Economy”

The working paper is devoted to the issues of taxation in the digital economy. The main focus is on the concept of "user value". The authors argue that the widespread adoption of this concept has led to developing new approaches to calculating this value and the subsequent taxation of companies that profit from the use of user data. The working paper examines the steps taken at the country level to develop taxation based on user value and the difficulties of implementing the concept. Nevertheless, the authors come to the conclusion that reforming the global tax system in this direction is inevitable.

Tec(h)tonic Shifts

The ever-increasing digitalization of businesses has accelerated the need to address the many shortcomings and unresolved issues within the international corporate income tax system. In particular, the customer or “user”—through their online activities—is now considered by many as being a critical driving force behind the value of digital services. Furthermore, the rapid growth of digital service providers over the last decade has made them an increasingly popular target for special taxes—similar to wealth and solidarity taxes—which can also help mobilize much-needed revenues in the wake of a crisis. This paper argues that a plausible conceptual case can be made to tax the value generated by users under the corporate income tax. However, a number of issues need to be tackled for user-based tax measures to become a reality, which include agreement among countries on whether user value justifies a reallocation of taxing rights, establishing the legal right to tax income derived from user value, as well as an appropriate metric for valuing user-generated data if it is ever to be used as a tax base. Furthermore, attempting to tax only certain types of business is ill-advised, especially as user data is now being exploited widely enough for it to be recognized as an input for almost all businesses. Several options present themselves for consideration—from a modified permanent establishment definition combined with taxation by formulary apportionment, to user-based royalty-type taxes—each with their own merits and misdemeanors.

The Effect of Service Quality and User Value on the Satisfaction and Loyalty of Users at Library and Archives of Padang City

This study aims to determine and analyze the effect of service quality and user value on the satisfaction and loyalty of users at the Padang City Library and Archives Service. The sample used was 100 respondents. The sampling technique is purposive sampling. The data is processed using SPSS 16. The type of data used is primary data by distributing questionnaires. Data analysis method with path analysis technique. The results of the study found that the quality of service had a significant effect on the loyalty of users at the Padang City Library and Archives Service, the value of users had a significant effect on the loyalty of users at the City of Library and Archives Service, the quality of service had a significant effect on the satisfaction of visitors at the Department of Library and Archives of Padang, the value of users have a significant effect on the satisfaction of library users in the Padang City Library and Archives Office, satisfaction has a significant effect on the loyalty of users in the Library and City Archives Office in Padang, the quality of service through satisfaction has no effect on loyalty and so does the value of users through satisfaction does not affect the loyalty of users in the Padang City Library and Archives Service.