Commentary on Structural Modeling in Marketing: Review and Assessment

Chan, Tat Y.
November 2006
Marketing Science;Nov/Dec2006, Vol. 25 Issue 6, p633
Academic Journal
Chintagunta, Erdem, Rossi, and Wedel (2006) (CERW) discuss many different issues related to the use of structural models in marketing. They use examples of structural models that involve both consumer demand and supply-side competition to provide a critical assessment of the strengths and weaknesses of structural modeling and its future in marketing. While they have done a very nice job, the purpose of this commentary is to provide additional discussion of the three issues raised in their paper.


Related Articles

  • Empirical Analysis of Theory-Based Models in Marketing. Srinivasan, Kannan // Marketing Science;Nov/Dec2006, Vol. 25 Issue 6, p635 

    There has been rapidly growing interest in structural models, and the review paper by Chintagunta et al. (2006) is a timely contribution. The paper identifies the key issues and provides an excellent assessment. A contemporaneous paper by Erdem et al. (2005) also offers a critical examination on...

  • Comment on Structural Modeling in Marketing: Review and Assessment. Hartmann, Wesley R. // Marketing Science;Nov/Dec2006, Vol. 25 Issue 6, p620 

    The author offers commentary on an article about structural modeling in marketing published in this issue of "Marketing Science." Topics assessed include the strengths and weaknesses of structural modeling, validation of structural models, and incorporating multiple data sources in marketing...

  • Ask the Right Questions.  // Credit Union Magazine;Jun2007, Vol. 73 Issue 6, p82 

    The article reports on the proper way to use market research and analyze member data for credit unions. According to the author, member data can be used to create models and segments, based on the models, to sent the right offer to the right member at the right time. More importantly, knowing...

  • CONCLUSION: MANAGING THE FUTURE.  // Financial Decision Making for Entrepreneurs & Managers;Aug2011, p95 

    The article discusses the focus of financial decision making on longer term plans and particularly on strategies which involve testing alternative decisions. It highlights the need to search for information to make business models work when using financial decision making techniques. It explores...

  • Lack of role in strategic decisions, low budgets hold down research profitability. Krum, James R.; Luck, David J. // Marketing News;5/13/1983, Vol. 17 Issue 10, Special section p4 

    The article emphasizes that companies can make their marketing research efforts more profitable by directing more resources to the research department and allowing researchers participate in strategic decisions. This was included in the findings of a pilot study conducted for the Marketing...

  • Commercial Use of UPC Scanner Data: Industry and Academic Perspectives. Bucklin, Randolph F.; Gupta, Sunil // Marketing Science;1999, Vol. 18 Issue 3, p247 

    The authors report the findings from an exploratory investigation of the use of UPC scanner data in the consumer packaged goods industry in the U.S. The study examines the practitioner community's view of the use of scanner data and compares these views with academic research. Forty-one...

  • How to Deploy an Effective Data Analysis Platform. Eames, Robert // R&D Magazine;Jul2004, Vol. 46 Issue 7, p24 

    Presents tips for deploying an effective data analysis platform for research and development processes. Barriers to the incorporation of such platform into decision making; Recommendation for the selection of such platform.

  • Changing world of research: It will soon be called 'marketing information'. Bergman, Sherri // Marketing News;9/12/86, Vol. 20 Issue 19, p50 

    An interview with Barbara Knuckles, vice president of Decision Making Information, is presented. Asked what she sees as the role of the marketing researcher, Bergman says marketing research groups will eventually be known as marketing information groups. On how a large company views marketing...

  • Learn from Your Analytics Failures. Schrage, Michael // Harvard Business Review Digital Articles;9/3/2014, p2 

    The article discusses the importance of learning from failed predictive analytics in order for organizations to predict the future and make strategic plans, such as hotels using data mining and time series analysis to coordinate its yield management pricing and promotion efforts.


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics