Lincoln_Center_Entrance_TaxisThe 5th Let’s Talk About Service (LTAS), December 8-9, 2016, Fordham University/New York City, is a two-day event with the aim to introduce young scholars to the wonderful world of service research and to guide them through their academic journey: from fresh PhD Students to junior faculty. Don’t miss this unique opportunity!!  Application deadline is September 1, 2016.
(more information can be found at the conference website:

This year’s theme is “Contemporary Methodologies for Service Research.”

LawSchool_PeterIn recent years, two research methodologies have become quite popular in various fields of study, including marketing and service management: agent based modeling and sentiment analysis. We are delighted to announce that two true expert methodologists — Barak Libai and Bing Liu — will offer workshops on how these methodologies can be used in service research. Below we provide more information about these 2 methodologies, and our 2 keynote speakers for the methodology workshops.

Agent Based Modeling (ABM) is considered as one of the most exciting and practical developments in business simulation and modeling. It is argued that in the future virtually all computer simulations will be in the form of agent-based simulations (North and Macal 2007). ABM combines the principles of complex adaptive systems with the advanced discrete event simulation techniques to offer a new methodology for exploring the cutting-edge challenges in business. It enables researchers to capture the behavior of a system at the aggregate level that cannot be easily captured by calculating the sum of the behavior of the entities that build the system.  Therefore, the basic concept of ABM is that by describing simple rules of behavior for individual agents and then aggregating these rules, researchers can model complex systems, such as the procurement of services in a marketplace, the purchase of tickets for events, or the adoption of innovations. Marketing researchers have used this methodology to provide insights in areas such as the adverse effects of negative word-of-mouth on firm profits, network externalities, seeding programs, and optimal pricing decisions just to name a few. The strongest benefit of using an ABM approach within marketing is that the actions of firms and consumers within the model can be constructed based upon strong theories of behavior, but at the same time, the results can be validated against empirical data and the model can then be used to make predictions. We believe that Agent Based Modeling provides ample opportunities for future services researchers.

Barak photoBarak Libai, a world renowned scholar, will deliver a workshop on the details of the agent based modeling and how it can be used in the services research. Dr. Libai is a professor on the marketing group of the Arison School of Business at the Interdisciplinary Center (IDC), Herzliya, Israel. His research deals much with customer social effects such as word of mouth, and their effect on the profitability of new products and brands, factors that affect profitability in the growth of markets for new products and brands, and customer relationship management. He has published in journals such as Marketing Science, Journal of Marketing, Journal of Marketing Research, Journal of Service Research and the International Journal of Research in Marketing, among others.

Sentiment Analysis is the second method that will be highlighted at the LTAS workshop this year. This analysis, also known as opinion mining, refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. It aims to overcome the challenges created by recent explosions of user generated content on social sites in terms of harnessing, analyzing and interpreting textual content since data are dispersed, disorganize, and fragmented (Kaplan and Haenlein, 2010).  This analysis is used to decide whether a piece of writing is positive, negative or neutral. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. The attitude may be his or her judgment or evaluation, affective state (that is to say, the emotional state of the author when writing), or the intended emotional communication (that is to say, the emotional effect the author wishes to have on the reader). This analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing to customer service.

BingLiuBing Liu, a highly respected expert on sentiment analysis, will deliver a workshop on how this methodology can be used by service researchers.  Dr. Liu is a professor of Computer Science at the University of Illinois at Chicago (UIC). He received his PhD in Artificial Intelligence from the University of Edinburgh. He is best known for his work on sentiment analysis and opinion mining, fake/deceptive opinion detection, using association rules for classification, and PU Learning (learning from positive and unlabeled examples). He also made important contributions to Web data extraction and interestingness in data mining. Recently, he started to work on lifelong machine learning. He is also the author of the book called “Sentiment Analysis: Mining Opinions, Sentiments and Emotions”.

For details and updates please check the website at For further questions please contact Dr. Sertan Kabadayi, the organizer of this year’s workshop at