Skip to content


General Contact Information

 

Phone: 646-660-6500

Fax: 646-660-6501

 

Email:

provost.office@baruch.cuny.edu

 

Mailing Address:

Office of the Provost & Senior Vice President for Academic Affairs

Baruch College/CUNY

One Bernard Baruch Way
Box D-701

New York, NY 10010-5585

 

Walk-In Address:

Administrative Center

135 East 22nd Street, 7th Floor

Office of the Provost and Senior Vice President for Academic Affairs

Message Archive



Friday, September 30, 2016

 

This email is being sent to all members of the Baruch College faculty.

For an archive of announcements sent from the Associate Provost beginning June 2011, click here.

 

The Information Systems and Statistics Research Seminar Series

(Three Events – see RSVP information below)

 

 

From:  Prof. Kannan Mohan

Paul H. Chook Department of Information Systems and Statistics, Coordinator, Ph.D. program in Information Systems 

October 14, 2016, 12:30 to 1:45, NVC 11-217 (IS-STA Conference Room)

(Friday on a Tuesday schedule)

Exploring the Role of Learning in Crowdsourcing Creativity: The Value of Idea-Building in the Crowd

Jie Ren

Assistant Professor

Information Systems

Fordham University          

Abstract: Crowdsourcing is increasingly popular because of its inherent diversity and because of its positive impact on creativity. This paper investigates the creativity of the crowd. Based on creativity theories, we proposed that (1) knowledge is the precondition for the widely-accepted positive impact of diversity on creativity in crowdsourcing, and (2) exposure to others’ ideas (idea-building) allows members to learn and to gain knowledge required for a creative response to an open call. A series of online experiments was conducted to compare three performance settings: crowd idea-generation, crowd idea-building, and expert idea-generation. We controlled for the crowd’s knowledge level by asking them to complete creativity tasks on a familiar topic and on an unfamiliar topic. To measure the performance of the collected ideas we used human raters and also a method of semantic analysis. The findings show that when crowd members have the relevant knowledge, they can outperform experts in creativity. Otherwise, experts can be more creative. However, when crowd members build on each other’s ideas, their performance is comparable to the experts’ - or better. This paper contributes to our understanding of the diversity aspects of crowdsourcing research and to the learning effects of idea-building in crowds. It also provides insights for practitioners regarding which tasks could successfully be outsourced to the crowd and which should be addressed internally within the firm.

Presented by the Paul H. Chook Department of Information Systems and Statistics          

 

October 18, 2016, 12:30 to 1:45, NVC 11-217 (IS-STA Conference Room)       

The Impact of Asymmetric Multi-Market Competition on the Performance Impact of Negative Online Word of Mouth

Gaurav Sabnis

Assistant Professor

Information Systems

Stevens Institute of Technology

    

Abstract: Although the impact of online word of mouth about a firm on its performance has been extensively studied, there is little attention played to competitive interactions in this relationship. We examine how a continuous measure of competition between two firms moderates the competitive interactions in the online word of mouth-performance relationship. Specifically, we use the airline industry to examine how asymmetric multi-market competition (the number of focal airline routes that the competitor flies on) between dyads of airlines moderates the impact of negative online word of mouth (NOWOM) about competitors on one another’s abnormal stock returns. We collected data on nine biggest airlines in the United States for a period of 60 months spanning December 2003 to November 2008. Using investor utlity function theories, we develop a spatio-temporal model to measure the moderating effect of asymmetric multi-market competition on the role that competitors’ NOWOM plays in influencing the focal airline’s stock returns. We find that an airline accrues the maximum stock returns benefits from a competitor’s NOWOM if the focal airline flies on a higher percentage of the competitor’s routes than the competitor flies on the focal firm’s routes. We also find that airlines engaged in symmetric multi-market competition flying on approximately half of one another’s routes will both benefit from one another’s NOWOM. We further find that stock return benefits of competitor’s NOWOM are the lowest or negative when the multi-market competition among firms is mutually symmetric but high or mutually symmetric but low. These findings provide evidence of competitive interactions in the impact of online word of mouth on financial performance, demonstrate the nature of the relationship as moderated by a continuous measure of competition, and provide insights to academics and practitioners for shaping online marketing strategies with the competition in mind to maximize the return on marketing investment.

 

Presented by the Paul H. Chook Department of Information Systems and Statistics          

 

November 8, 2016, 12:30 to 1:45, NVC 11-217 (IS-STA Conference Room)

How can we detect fraudulent raters?

Yuanfeng Cai

Assistant Professor

Information Systems

Baruch College

 

Abstract: Reputation systems are designed to protect consumers from transactional risks by providing feedback from previous consumers. However, the trustworthiness of these systems is vulnerable to unfair ratings posted by fraudulent raters. Though many detection approaches have been proposed, this problem is far from being solved. In this study, I use rating datasets from Tripadvisor.com, Expedia.com and Amazon.com to empirically explore the features for fraudulent rater detection. Based on the features, I first identify entities under attack and retrieve a list of users who have rated those entities. Then clustering-based methods are proposed to discriminate fraudulent raters. Finally, I evaluate the performance of the method by using another independent cyber competition dataset. Experimental studies show that the proposed method consistently outperforms the benchmark methods in fraudulent rater detection under various attack conditions.

 

Presented by the Paul H. Chook Department of Information Systems and Statistics          

 

To RSVP for any of the above events, please visit: https://goo.gl/ETUwfG. If you have any questions, please contact Kannan Mohan at Kannan.mohan@baruch.cuny.edu.

           

____________________________________
Kannan Mohan
Professor of CIS

Coordinator, Ph.D. program in Information Systems
Baruch College, The City University of New York
Phone: (646) 312 3372

http://blogs.baruch.cuny.edu/kannanmohan

Ph.D. Program: http://cis.baruch.cuny.edu/doctoral/