Call for Papers

In recent years, we have witnessed the emergence of a wide range of business and social models based on information technology-enabled data: from online retailing and online dating to crowdsourcing and crowdfunding. The growth of information technology and its subsequent permeation into social media, the corporate arena, public policy, and countless other fields has irrevocably changed the modern world. We now have a chance to harness the power of information technology and use it to encourage and create global and local projects for social good, including programs that stimulate developing economies, work to solve public health issues, and create positive change in communities from the grassroots to the global level.

In the current era, vast amounts of data on behaviours and events are now available that have not previously been accessible both in the developed and developing world. Researchers are collecting and using this data to address a variety of topics related to the social and economic impact of information technology enabled models. The purpose of this conference is to gather an interdisciplinary group of researchers interested in using empirical methods to derive insights from information technology-enabled data in a range of areas, in particular those that tackle questions of social good and data-driven decision-making.

We invite submissions of papers that highlight statistical challenges and empirical opportunities related to Electronic Commerce research, Big Data, Internet of Things, smart nation and related areas. This year’s theme, in line with the conference venue at the Rotterdam School of Management, Erasmus University Rotterdam will be “Addressing Data Challenges toward a Positive Change in the World”

We welcome submissions in a broad range of areas, including the digitization of media industries, online content distribution, electronic marketplaces, online social interactions, search engine advertising, FinTech, and smart nation, among others. We also welcome methodological contributions on statistical, data mining or other approaches motivated by data enabled by information technology, particularly those that contribute to social good. Submissions should highlight statistical/empirical challenges that arise in collecting, modelling, and converting such data into usable, practically applicable knowledge.

See Submission Guidelines