Engagement in a Mobile Digital Plaftorm
Supervisors: Edy Portmann, Marco Pesce
Contact person: Marco Pesce
Student: Looking for a student
Project status: Open
🤳 How can system design choices influence the final deployment of your digital platform?
A very popular category of technology at the edge of the Internet are consumer-centric mobile devices. Such devices exploited as sensing units in cloud-centric and collective architecture were labeled under the buzzword of mobile crowdsensing systems (MCS) [R. K. Ganti, et al, 2011]. Mobile crowdsensing can be an urban digital platform to enable smart cities to leverage the sensing capability and ubiquity of citizens' mobile devices to capture and map phenomena of common interest. While smart city strategies are driving the adoption of Internet-of-Things (IoT) technologies and Big Data analytics by city governments around the world, urban digital platforms respond to the deep and pervasive interconnections that exist today between urban citizens, urban services, and platform ecosystems [R. I. Ogie, 2016].
Like any other innovative product, a digital platform needs to reach a critical mass in its early stages [Nedbal, Brandtner, Auinger, & Erskine, 2013]. Indeed, in the proliferation of interactive innovations, where each additional user increases the value of the innovation for all other users, it is particularly important to reach the minimum number of users to get sufficient value from the amount of data collected. But how to stabilize such an extremely brittle launching for these categories of innovation products? Fundamental to such human participation are the incentives offered to the digital platform users. Participating individuals (and their devices) may incur energy and monetary costs and other explicit and non- efforts by the device owner to collect, process, and transmit the desired data. If there are not sufficient incentives, owners may not be willing to contribute their resources, and for a digital platform to be successful, there must be appropriate engaging mechanisms to recruit, engage, and retain human participants [R. K. Ganti, 2011]. Incentives can be defined as implicit or explicit [J. Phuttharak, (2019)].
The first part of this survey will address the explicit case of incentives offered to the users of an hypothetical platform aimed to survive the first ramp of the so-called Innovation adoption curve [E. Rogers, 1962]. Furthermore, this research wants to analyze pros and cons and to create a taxonomy of those, by concreting evaluating the literature of such mechanisms.
But even with innovation, as the saying goes, the devil is in the details.
A careful study of the use and deployment of a particular technology in crowdsensing systems must be based on a mastery of the latest taxonomies and classifications of mobile crowdsensing systems. The analysis will then be based on an analysis of the most relevant and up-to-date taxonomies of such architectures, attempting to link and weigh all the factors involved in the design of an MSC with the final deployment of the product, i.e., user adoption. Accordingly, a thorough literature review will show how the engagement, participation, and download metrics of an MCS platform are related to these microcomponents.
The goal of this research is to create a publishable scientific survey on how to assess the sensitivity of the spread of an MSC product in relation to the design factors of the platform created. The Master's student involved in these studies is expected to handle scientific writing in English and will take advantage of state-of-the-art bibliometric tools to carry out this investigation.
Keywords: Mobile Crowdsensing Platform, Partecipatory Digital Platform, Incentives for Users, Innovation life-cycle, Smart Cities, IoT, Scientific survey