Paying for Privacy and the Personal Data Economy

Growing demands for privacy and increases in the quantity and variety of consumer data have engendered various business offerings to allow companies, and in some instances consumers, to capitalize on these developments. One such example is the emerging “personal data economy” (PDE) in which companies, such as Datacoup, purchase data directly from individuals. At the opposite end of the spectrum, the “pay-for-privacy” (PFP) model requires consumers to pay an additional fee to prevent their data from being collected and mined for advertising purposes. This Article conducts a simultaneous in-depth exploration of the impact of burgeoning PDE and PFP models. It identifies a typology of data-business models, and it uncovers thesimilarities and tensions between a data market controlled by established companies that have historically collected and mined consumer data for their primary benefit and one in which consumers play a central role in monetizing their own data. The Article makes three claims. First, it contends that PFP models facilitate thetransformation of privacy into a tradable product in the online setting, may worsen unequal access to privacy, and could further enable predatory and discriminatory behavior. Second, while the PDE may allow consumers to regain a semblance of control over their information by enabling them to decide when and with whom to share their data, consumers’ direct transfer or disclosure of personal data to companies for a price or personalized deals creates challenges similar to those found in the PFP context and generates additional concerns associated with innovative monetization techniques. Third, existing frameworks and proposals may not sufficiently ameliorate these concerns. The Article concludes by offering a path forward

Leveraging data to enable business growth through different market channels

Project Work presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and AnalyticsThe shift from mechanical and analog technology to digital electronics leading to the "Second Digital Revolution."With the rise of the Data Economy, companies need to redefine their role in this economy by evaluating their engagement. Data has become a valuable asset that can be monetized, and companies are leveraging it to scale their businesses. Schneider Electric, a top energy management company, uses innovative technologies and solutions to drive digital transformation. This project was created to answer challenges faced by Schneider Electric in giving visibility to partners, monetizing data, and sharing data securely. As part of the project deployment, qualitative analysis methods were used, including semi-structured interviews and use case analysis. Semi-structured interviews were conducted with service partners at different project stages to gather insights and requirements. Use case analysis was employed to define user interactions within the system. The interviews revealed service partners' need for tools to record and display inventory, access comprehensive product information, and receive proactive notifications. The use cases were developed based on these insights and aimed to address the partners' pain points while aligning with Schneider Electric's business objectives. Overall, these methods helped gather valuable input for the project and shape the solution design. The project successfully improved the customer journey for all types of customers through the mySchneider portal, providing convenient access to customer information, service maintenance contracts, service visits, and reports. The methodology employed in the project can be applied to other initiatives and future enhancements, aiming to enhance customer satisfaction and increase business revenue. The project also has theoretical implications for marketing and customer relationship management, empowering businesses to develop effective strategies and cultivate stronger customer relationships. Agile project methodology was effective in navigating budget and timeline constraints. The implementation of the project will support Schneider Electric's global offices and their services growth strategies through partnerships

Mobile search, a case for next generation information society policies

After more than a decade of development work and hopes, the usage of mobile Internet has finally taken off. Now, we are witnessing the first signs of evidence what might become the explosion of mobile content and applications that will be shaping the (mobile) Internet of the future. Similar to the wired Internet, search will become very relevant for the usage of mobile Internet. Within the mobile ecosystem framework, this paper will discuss if and how intense public action in the mobile search domain should (could) be. Potential actions refer both to ‘conventional’ and 'non-conventional' regulatory approaches. Public administrations as procurement bodies may leverage services and thus acting as early deployers of applications is an example of a ‘conventional’ case, while the use of the wealth of public data with high added value in mobile search scenarios would be one of a ‘non-conventional’ case. The paper will present a list of different policy options and analyse their feasibility. These include policies options aimed both at the demand side (user-oriented) and at the supply side (innovation-support policies, regulatory policies, industrial-type policies, …) of mobile search

The Platformed Money Ecosystem: Digital Financial Platforms, Datafication, and Reimagining Financial Well-being

Digital financial platforms have become an integral part of consumers\u27 lives–resulting in the datafication of everyday life and potential for uniquely impacting financial well-being. Extending previous transformative consumer research, we suggest financial well-being must center the ways digital financial platforms and their resulting data are increasingly enmeshed with financial decision making and consumption. Drawing on a theoretical lens of platformization, we propose the Platformed Money Ecosystem, which accounts for increased embeddedness of digital financial platforms within consumers\u27 lives and the subtlety of how everyday life is transformed into data: producing data at the micro-level, monetizing data at the meso-level, and regulating data at the macro-level. In conceptualizing the Platformed Money Ecosystem, we identify three data-informed considerations for scholars and policymakers to reimagine financial well-being: protecting consumer data, limiting data biases, and supporting data literacy

Business Intelligence And Geographic Information System Lifecycle Architecture Using Cloud Computing For Smart Community

Business Intelligence (BI) is a technique and IT tool that supports business decision making. BI is considered a unique source of competitive advantage in the market place and it can combine data, multimedia, and transactions all in one application to address people\u27s needs. Using BI applications can increase both operational efficiency and customer satisfaction. In addition, BI improves planning that provides the foundation for top successful performances in the future. Geographic Information Systems (GIS) deliver productivity tools that are highly beneficial for businesses. These benefits include: visualization, business capacity, analysis, and interpreting data to understand relationships, patterns, and trends. Another benefit is a new feature can report drivers who speed, accelerate hard, and make sudden stops. Nowadays, GIS is responsible for developing standard, strategy, and policy that emphasize coordination and cooperation among organizations and businesses in order to maximize cost effectiveness. Smart card technology is the name that describes plastic cards with an embedded computer chip. Basically, smart cards are usually the most cost-effective solution because it increases the level of processing power, memory, and flexibility. Therefore, implementing a smart card in a driver\u27s license can help to build control in a community. However, the general objective of the study is to investigate the feasibility of integrating Cloud Computing, BI, and GIS to build smart community. The research focuses on enhancing GIS tools and build control in community. The proposed system is a new approach in Information Technology that can lower business cost and build policy in organization. The research is nonexperimental study used qualitative method to answer certain research questions posed for the study. The result obtained from analysis exists GIS showed that enhance GIS can build control in the community. Furthermore, there is a feasibility integrating BI, Cloud and GIS to build smart community. On the bases of these finding, IT synergy will influence the business workflow process and performance of organization. Organizations can achieve many benefits from the integrating Cloud Computing approach, BI and GIS in decision making

Investigating the Impact of Social Interaction on Consumers' Purchasing Behavior in Social Commerce Platform

Abstract. S-commerce is a modern trend in the field of internet trading, which uses social media as the medium for transactions. To study this rising propensity, we examine how social interaction affects the consumer's s-commerce purchasing behavior. The sampling technique used purposive sampling and the 189 respondents were selected according to predetermined criteria. The data processing approach employed Structural Equation Model (SEM) - Partial Least Square (PLS) with SmartPLS 3.0 software assistant. The results showed that social interaction had a positive and significant effect on trust and intention to purchase, trust had a positive and significant impact on purchase intention and s-commerce purchasing behaviour, and purchase intention had positive and significant influence on s-commerce purchasing berhavior. In contrast, the consumer's social interaction effect toward s-commerce purchasing behavior was insignificant. The results are expected to provide a comprehensive understanding in term of consumer's behavior in social media and its consequences for the s-commerce market strategy in Indonesia.Keywords: Social interaction, trust, purchase intention, s-commerce purchasing behavior, SEM-PLSAbstrak. S-commerce merupakan evolusi baru dalam dunia perdagangan internet yang memanfaatkan media sosial sebagai platform transaksi bisnisnya. Untuk menyelidiki fenonema tersebut, penelitian menganalisis bagaimana interaksi sosial memengaruhi perilaku pembelian konsumen s-commerce di Indonesia. Teknik pengambilan sampel menggunakan purposive sampling dan 189 responden kemudian dipilih berdasarkan kriteria yang telah ditetapkan sebelumnya. Teknik analisis data menggunakan Structural Equation Model (SEM) – Partial Least Square (PLS) dengan alat bantu software SmartPLS 3.0. Hasil penelitian membuktikan bahwa konstruk interaksi sosial berpengaruh positif dan signifikan terhadap kepercayaan dan niat pembelian, kepercayaan berpengaruh positif dan signifikan terhadap niat pembelian dan perilaku pembelian s-commerce, niat pembelian berpengaruh signifikan terhadap perilaku s-commerce konsumen. Sebaliknya, pengaruh interaksi sosial terhadap perilaku pembelian s-commerce positif namun tidak signifikan. Temuan diharapkan dapat memberikan pemahaman baru mengenai perilaku konsumen di media sosial dan implikasinya pada strategi perusahaan s-commerce di Indonesia.Kata Kunci: Interaksi sosial, kepercayaan, niat pembelian, perilaku pembelian s-commerce, SEM-PL

The Platformed Money Ecosystem: Digital Financial Platforms, Datafication, And Reimagining Financial Well-Being

Digital financial platforms have become an integral part of consumers' lives–resulting in the datafication of everyday life and potential for uniquely impacting financial well-being. Extending previous transformative consumer research, we suggest financial well-being must center the ways digital financial platforms and their resulting data are increasingly enmeshed with financial decision making and consumption. Drawing on a theoretical lens of platformization, we propose the Platformed Money Ecosystem, which accounts for increased embeddedness of digital financial platforms within consumers' lives and the subtlety of how everyday life is transformed into data: producing data at the micro-level, monetizing data at the meso-level, and regulating data at the macro-level. In conceptualizing the Platformed Money Ecosystem, we identify three data-informed considerations for scholars and policymakers to reimagine financial well-being: protecting consumer data, limiting data biases, and supporting data literacy

The Benefits of Air Pollutant Emissions Reductions in Maryland: Results from the Maryland Externalities Screening and Valuation Model

This paper reports the results of policy simulations of environmental and human health externalities arising from the production of electricity. The primary purpose of this paper is to illustrate the Maryland Externalities Screening and Valuation Model, developed for the State of Maryland’s Department of Natural Resources. A secondary purpose is to estimate likely Maryland benefits from Title IV emissions reductions at electric power generation facilities. Sources and scope of benefits, and the potential of policy to achieve specific environmental and human health goals, are suggested by the results. The authors find that expected health benefits from reductions in power plant emissions dominate the estimated benefits of improved recreational visibility and residential visibility. The latter are the only environmental benefits the model is currently equipped to estimate, because of gaps in the science-to-economics literature. The model fully accounts for all significant environmental pathways, so future parameter estimates can be inserted as they are developed. The authors estimate that in 2010 Maryland health benefits will be about $0.7 billion, while recreational visibility benefits (in Shenandoah National Park) will be approximately$21 million (to residents of Virginia and Maryland), and residential visibility benefits, for inhabitants of a city of the size of Washington, DC and similarly affected by reduced urban visibility, will be about $1.2 million. This integrated-assessment model is designed to estimate and report also the tremendous uncertainties in measuring and valuing these effects.