Associate Professor of Marketing
Dr. Yichuan Wang
Assistant Professor (Lecturer) in Marketing at Newcastle University Business School, Newcastle University, UK
Dr. Michel Laroche
Royal Bank Distinguished Professor of Marketing at Concordia University, Canada
The massive amounts of social media data such as consumer subjective opinions, recommendations and ratings, and consumer behavioral data stored in social networking sites could be a valuable source of supporting firms’ marketing activities if it is analyzed in meaningful ways. Business intelligence and analytics (BI&A) is increasingly advocated as an important IT breakthrough to fill this growing need. However, BI&A is challenging for firms seeking to adopt a thoughtful and holistic approach to analyze and harness social media data. There are several major obstacles, including the lack of data integration, data overload issues, and barriers to the collection of high-quality consumer data, and organizational culture and change management that prevent firms from fully embracing BI&A and gaining the benefits. The value of social media data is rarely discovered, analyzed and visualized, either for creating marketing insights and knowledge to complement the insufficiency of intrinsic organizational knowledge or as a roadmap for improving service quality and firm performance. As a result, there is a need for further research to: (1) explore how to utilize social media data to capture consumer insights from the enormous variety of user-generated content in social media platforms, and (2) examine how BI&A enables firms to create business value and sustain a competitive advantage.
This special issue is seeking conceptual, empirical or technological papers offering new insights into the following topics, but is not limited to them:
- The applications of descriptive, predictive and prescriptive analytics to extract insights from social media data.
- The applications of descriptive, predictive and prescriptive analytics to understand the functioning of brand communities based in social media.
- Big data analytics for customer value creation.
- Case studies of utilizing social media analytics tools to explore business insights and support decision making.
- The development of BI&A success models for transforming consumer activities into a sustainable competitive advantage.
- How to leverage the value of social media analytics for co-creating innovation with consumers?
- Organizational learning and culture impact on BI&A applications.
- Data governance and data security in social media.
- Visualizing social media data to improve the accuracy of decision making.
- The application of sentiment analysis for brand management and new product/service development, and location based services.
Obviously other topic areas may fit with the aims of the special issue and any questions as to the suitability of the topic should be addressed to the Guest Editors.
Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals. Manuscript should be submitted to EVISE through the Elsevier system portal link https://www.evise.com/profile/#/IJIM/login Elsevier provides many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.
Editorial office and the GE will make an initial determination on the suitability and scope of all submissions. Papers that either lack originality, clarity in presentation or fall outside the scope of the special issue will not be sent for review and the authors will be promptly informed in such cases. Final acceptance will be based on their qualities and recommendations of the reviewers.
The authors must select article type “Big Data” when submitting a paper to http://ees.elsevier.com/ijim/.
Submission Deadline: December 2017
Final Decision and Notification: September 2018
Habibi, M.R., Laroche, M., & Richard, M.O. (2014). Brand communities based in social media: How unique are they? Evidence from two exemplary brand communities, International Journal of Information Management, 34, 2, 123-132.
Hajli, N., Shanmugam, M., Powell, P., & Love, P. E. (2015). A study on the continuance participation in on-line communities with social commerce perspective. Technological Forecasting and Social Change, 96, 232-241.
Hajli N, X Lin, M Featherman, Y Wang. (2014). Social word of mouth: How trust develops in the market. International Journal of Market Research, 56, 673-689.
Suo, Q., Sun, S., Hajli, N., & Love, P. E. (2015). User ratings analysis in social networks through a hypernetwork method. Expert Systems with Applications, 42(21), 7317-7325.
Wang, Y., Hsiao, S. H., Yang, Z., & Hajli, N. (2016). The impact of sellers' social influence on the co-creation of innovation with customers and brand awareness in online communities. Industrial Marketing Management, 54, 56-70.
Wang, Y., Kung, L., & Byrd, T. A. (2016). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, doi:10.1016/j.techfore.2015.12.019.
Bios of Guest Editors
Dr. Nick Hajli
Dr Nick Hajli is an Associate Professor of Management at Swansea University. Previously he was a Lecturer in Marketing and Entrepreneurship & PhD coordinator in Newcastle University. Nick received his PhD in Management from Birkbeck, University of London. He has the best PhD award from Birkbeck, University of London. Nick is in the Advisory Board of Technological Forecasting & Social Change, An International Journal (ABS 3*). He also sits on the editorial board of several academic journals as a section editor, member of the advisory board or a guest editor including, Computers in Human Behavior, International Journal of Information Management, and Journal of Strategic Marketing.
Dr. Yichuan Wang
Dr. Yichuan Wang received his Ph.D. degree in Management Information Systems from Auburn University. His research interests center on social media marketing and big data analytics, and IT-enabled innovation and business value. His articles have appeared in the Industrial Marketing Management, International Journal of Production Economics, International Journal of Information Management, Technological Forecasting and Social Change, and International Journal of Market Research, among others. He has received the Best Paper Award at the Global Marketing Conference in 2008, and was a Best Paper Award nominee at Americas Conference on Information Systems (AMCIS) in 2014.
Dr. Michel Laroche
Dr. Michel Laroche is the Royal Bank Distinguished Professor, Concordia University. He holds a Ph.D. and M.Ph. (Columbia), a D.Sc. honoris causa (Guelph), and a M.Sc.Eng. (Johns Hopkins). He is a Fellow of the Royal Society of Canada, the American Psychological Association, the Society for Marketing Advances and the Academy of Marketing Science. He was the 2000 Concordia University Research Fellow, and he received the 2000 Jacques-Rousseau Medal, the Living Legend of Marketing Award (2002), and the Sprott Leader in Business Research & Practice Award (2003). He published over 160 refereed journal articles in, among others, the Journal of Consumer Research,Journal of the Academy of Marketing Science, Journal of Retailing, Journal of Service Research, Marketing Letters, Journal of Advertising Research, and the International Journal of Information Management. His current research projects involve online consumer behaviour, digital marketing, brand communities, social media, data mining, and the sharing economy, among others.