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Wednesday, June 28, 2017

2nd CEIBS Marketing Symposium

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June 16, 2017. Shanghai – The latest research and trends in marketing were the focus of discussions today among more than 80 scholars from around the world who gathered at CEIBS Shanghai Campus for the 2nd CEIBS Marketing Symposium organized by the CEIBS Marketing Department. Under the theme, “Brave New World of Marketing: New Strategies, Methods and Decision Processes”, faculty from universities such as NYU, UBC, HKUST, Johns Hopkins University, CKGSB, and Harvard joined CEIBS professors to explore topics such as maximizing big data, building efficient marketing strategies, encouraging consumer spending, and allocating limited resources to benefit both companies and consumers. CEIBS Assistant Professor of Marketing Lin Chen hosted the symposium and the Chair of the Marketing Department, Professor of Marketing Zhou Dongsheng, gave the Welcome Address. 

“Does Big Data Solve Big Problems,” was the title of the keynote speech by Editor-in-Chief of Marketing Science Professor Ho Teck Hua of Singapore National University. Prof. Ho has studied the influence of big data in the transportation and healthcare sectors, and in his speech he gave some practical examples of the benefits of big data analysis. One study he discussed showed how a vehicle’s colour can help prevent accidents. Researchers looked at a 36-month dataset provided by the largest taxi company in Singapore, which included millions of data points on the company’s drivers and taxis, including driving behaviour, daily earnings, and accidents. Their analysis found that accident rates could not be attributed to driver demography or driving behaviour. Instead, it seemed that the taxis’ colour had some relationship to the number of accidents, as yellow taxis had the fewest accidents. Prof. Ho also discussed a healthcare study that used big data analysis to explore the benefits of screenings to catch early-stage cancers.

The presenters and discussants for this years’ symposium were:
Senior Editor, Information System Research Prof. Anindya Ghose from New York University;
Prof. Li Yang from CKGSB;
Prof. Doug Chung from Harvard University;
Prof. Chunhua Wu from UBC;
Prof. Wenbo Wang from HKUST;
Profs. Jian Ni and Meng Zhu from Johns Hopkins University;
Prof. Iris Hung from Fudan University;
Prof. Hannah Chang from SMU; and
Prof. Charlene Chen from NBS.

Below are abstracts of some of the papers presented.

Mobile Targeting Using Customer Trajectory Patterns presented by Prof. Anindya Ghose finds that trajectory-based mobile targeting can lead to higher redemption probability, faster redemption behavior, and a higher transaction amount from customers compared to other baselines. It also facilitates higher revenues for the local store as well as the overall shopping mall. Moreover, the effect of trajectory-based targeting comes not only from improvements in the efficiency of customers’ current shopping process, but also from its ability to nudge customers towards changing their future shopping patterns and generate additional revenues. The paper also finds significant heterogeneity in the impact of trajectory-based targeting. It is especially effective in influencing high-income consumers. Interestingly, it becomes less effective in boosting the revenues of the shopping mall during the weekends and among shoppers who like to explore across product categories.

Does Online Word-of-Mouth Increase Demand? (and How?) Evidence from a Natural Experiment presented by Prof. Wenbo Wang leverages a temporary block on the Chinese micro-blogging platform Sina Weibo due to political events, to estimate the causal effect of online word-of-mouth content on product demand in the context of TV show viewership. Based on this source of exogenous variation, the researchers estimated an elasticity of TV show ratings (market share in terms of viewership) with respect to the number of relevant comments (comments were disabled during the block) of 0.016. In terms of the behavioural mechanism, the paper finds more post-show microblogging activity increases demand, whereas comments posted prior to the show airing do not affect viewership. These patterns are inconsistent with informative or persuasive advertising effects and suggest a complementarity between TV consumption and anticipated post-show microblogging activity.

The Urgency Bias presented by Prof. Meng Zhu uses five experiments to provide compelling support for the notion of the “urgency bias”, a tendency to prefer urgency over importance even when normative and motivational reasons such as task difficulty, goal progress, reward immediacy, supply/demand and task interdependence are controlled for. The minimalistic and flexible paradigm introduced in this research sheds light on the psychological process through which people make tradeoffs between urgent and important tasks in daily life: the restricted time frame embedded in urgent tasks elicits greater attention, diverting focus away from the magnitudes of task outcomes, and thereby leads people to exhibit the urgency bias. This attentional focus consequently leads to the urgency bias document in the current research. Consistent with this attention-based reasoning, the paper further finds that experimentally increasing the salience of task outcomes or decreasing people’s attentional capacity moderates the magnitude of the urgency bias. These results provide a possible explanation for why the search process done under time pressure might be random with respect to value.

Writer: 
Iris Wan
Editor: 
Coughlin, JANINE M.