B5175 - PRODUCT DEVELOPMENT AND MARKETING

Learning outcomes

By the end of the course students should be able to understand the main challenges associated with the development of new products. More specifically students will be able to: - design a new product development process; - analyze the competitive advantage of a new idea; - assess a new product idea’s value; - make decision on whether or not a new product idea should/should not be launched in the market.

Course contents

1) The new product development process. New product development as a process. The relationship between Research and Development.

2) Identification of opportunities. Ideas generation. Need analysis and classification.

3) Turn the consumer insight into a product. Preference analysis and concept development.

4) Concept testing and sales forecasting. Evaluating the market potential

5) New product Launch. Launching strategies, new product adoption and diffusion

Readings/Bibliography

Readings – Attending Students

Book Chapters:

Ely Dahan and John R. Hauser “Product Development - Managing a Dispersed Process.” Handbook of Marketing. B.Weitz and R. Wensley, Eds. http://mitsloan.mit.edu/vc/Dahan_Hauser_Product_Development_Chapter.pdf (Weeks 1&2)

Toubier Oliver. “New Product Development.” In The Handbook of Technology Management, vol., edited by Hossein Bidgoli, 953-963. Hoboken, NJ: Wiley, 2010.

Microsoft Word - New Product Development revised (columbia.edu) [https://www0.gsb.columbia.edu/mygsb/faculty/research/pubfiles/5487/New%20Product%20Development%20revised.pdf?_ga=2.146873143.1655107919.1667561169-815857227.1667561168] (week 1 &2)

Urban, Glen L. and John R. Hauser (1997), Design e Marketing dei Nuovi Prodotti, Prentice Hall,Torino. Chapter 12. (week 2)

Hair, J.F., R.E. Anderson, R.L.Tatham and W.C. Black “Conjoint Analysis” in Multivariate Data Analysis p-387-436. (week 4)

Urban, Glen L. and John R. Hauser (1997), Design e Marketing dei Nuovi Prodotti, Prentice Hall,Torino. Chapters 16 and 17. (week 5)

Moore, Geoffrey A. (1991), Crossing the Chasm, Harper Collins Publishers: New York, New York. Chapters 1, 2, 3. (Optional) (Week 5)

Articles:

a) New Product development, the Marketing and R&D interface.

1) Day, G. (2007), “Is it Real? Is it worth it? Can it Win?” Harvard Business Review..

(Settimana 1)

2) Abbie Griffin and John R. Hauser “Integrating R&D and Marketing: A Review and Analysis of the Literature” Journal of Product Innovation Management, Volume 13, Issue 3, [http://onlinelibrary.wiley.com/doi/10.1111/jpim.1996.13.issue-3/issuetoc] pages 191–215, May 1996. http://scholar.google.it/scholar?hl=it&q=Integrating+R%26D+and+Marketing%3A+A+Review+and+Analysis+of+the+Literature&btnG=&lr =

(Settimana 1) (Optional).

3) WorkLife with Adam Grant: The Daily Show’s Secret to Creativity on Apple Podcasts [https://podcasts.apple.com/us/podcast/creative-burstiness-at-the-daily-show/id1346314086?i=1000405268582&mt=2] (suggested).

b) Idea generation

4)Kim, W. Chan, and Renée Mauborgne (2004), “Blue Ocean Strategy,” Harvard Business Review.

5) Patnaik, dev and Robert Becker (1999) “Needfinding: The Why and How of Uncovering People’s Needs” Design Manangement Journal

http://www.paulos.net/teaching/2011/BID/readings/needfinding.pdf (week 2)

6) Hauser, John, Chengfeng Mao,and James Li. "Artificial Intelligence and User-generated Data are Transforming how Firms Come to Understand Customer Needs." In Review of Marketing Research, Emerald Group Publishing. Forthcoming. (Microsoft Word - Hauser_Li_Mao AI & VOC RMR Feb 14 2022.docx (mit.edu) [https://mitsloan.mit.edu/shared/ods/documents?PublicationDocumentID=8202], (Settimana 2).

7) Generating Ideas: A Process for Breakthrough Innovation - Knowledge at Wharton (upenn.edu) [https://knowledge.wharton.upenn.edu/article/generating-ideas-a-process-for-breakthrough-innovation/]

7a) Brucks, M.S., Levav, j: (2022), “Virtual communication curbs creative idea generation,” Nature 605, 108–112 (2022). https://doi.org/10.1038/s41586-022-04643-y (optional)

7b) Barry Bayus (2013) “Crowdsourcing New Product Ideas Over Time: An Analysis of the Dell IdeaStorm Community,” Management Science, 59 (January), 226-244;

http://public.kenan-flagler.unc.edu/faculty/bayusb/WebPage/Papers/Crowdsourcing.pdf

(optional);

7c) How IBM Brings Ideas Forward From Its Teams - The New York Times (nytimes.com) [https://www.nytimes.com/2014/12/07/jobs/how-ibm-brings-ideas-forward-from-its-teams.html]

(optional);

7d) What To Do When Your Boss Won't Support Your Great Ideas (forbes.com) [https://www.forbes.com/sites/elainepofeldt/2013/12/31/what-to-do-when-your-boss-wont-support-your-great-ideas/?sh=2d9a50996dae] (optional).

7e) Timoshenko A.and J.R.Hauser, (2019), “ Identifying Customer Needs from User-Generated Content, ” Marketing Science, vol. 38, no. 1, pp. 1–20 (optional)

7f) Mollick

c) Idea Screening

8) Oded Netzer, Ronen Feldman, Jacob Goldenberg, Moshe Fresko, (2012), “Mine Your Own Business: Market-Structure Surveillance Through Text Mining.” Marketing Science 31(3):521-543. https://doi.org/10.1287/mksc.1120.0713 (week 3).

9) Morwitz Vicki G., Joel H. Steckel and Alok Guptab (2007) “When do purchase intentions predict sales?” International Journal of Forecasting, 23, 3, July–September 2007, 347–364

http://www.sciencedirect.com/science/article/pii/S0169207007000799# [http://www.sciencedirect.com/science/article/pii/S0169207007000799]

(Settimana 4)

9a) Validating Product-Market Fit in the Real World (hbr.org) [https://hbr.org/2022/12/validating-product-market-fit-in-the-real-world] (optional).

9b) Can AI chatbots replace human subjects in behavioral experiments? | Science | AAAS [https://www.science.org/content/article/can-ai-chatbots-replace-human-subjects-behavioral-experiments] (optional).

Readings – Non attending students

Non-attending students (i.e., those who choose not to participate in group work) must consider all the articles and book chapters included in the program for attending students (both mandatory and optional) as an integral part of the syllabus. Additionally, they must be prepared on the following supplementary readings, which may be covered in the final written exam

BOOK Chapters:

Moore, Geoffrey A. (1991), Crossing the Chasm, Harper Collins Publishers: New York, New York. Chapters 1, 2, 3.

Urban, Glen L. and John R. Hauser (1997), Design e Marketing dei Nuovi Prodotti, Prentice Hall,Torino. Chapter, 13.

Hair, J.F., R.E. Anderson, R.L.Tatham and W.C. Black “Multidimensional Scaling” in Multivariate Data Analysis p-519-546.

Articles

a) New Product development, the Marketing and R&D interface.

1)Abbie Griffin, Brett W. Josephson, Gary Lilien, Fred Wiersema, Barry Bayus, Rajesh Chandy, Ely Dahan, Steve Gaskin, Ajay Kohli, Christopher Miller, Ralph Oliva, and Jelena Spanjol (2013), “Marketing’s Roles in Innovation in Business-To-Business Firms: Status, Issues And Research Agenda,” Marketing Letters, 24:4 (December), 323-337;

http://link.springer.com/article/10.1007/s11002-013-9240-7#page-1

2) Chang, W., & Taylor, S. A. (2016). The Effectiveness of Customer Participation in New Product Development: A Meta-Analysis. Journal of Marketing, 80(1), 47–64. https://doi.org/10.1509/jm.14.0057

b) Idea generation

4)Laura J. Kornish and Karl T. Ulrich “The Importance of the Raw Idea in Innovation: Testing the Sow's Ear Hypothesis” Journal of Marketing Research, Volume 51, Issue 1 (February 2014);

http://funginstitute.berkeley.edu/sites/default/files/Kornish-Ulrich-IdeaValue-Oct2012_0.pdf

5) Toubia O. and O. Netzer: Idea Generation, Creativity, and Prototypicality? Marketing Science 36(1), pp. 1–20

c) Idea screening

5) William J. Infosino William J. (1986) “Forecasting New Product Sales from Likelihood of Purchase Ratings [http://pubsonline.informs.org/doi/abs/10.1287/mksc.5.4.372] ” Marketing Science 5 (4) , pp. 372–384 November 1. [http://pubsonline.informs.org/action/doSearch?text1=Infosino%2C+W+J&field1=Contrib]

d) Conjoint Analysis

4) Green Paul E. and A.M.Krieger (1996) “Individualized Hybrid Models for Conjoint Analysis,” Management Science, 42 (6), 850-67.

http://www.jstor.org/stable/2634599

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Additional Reading (for your own knowledge)

Almquist, Senior, Bloch (2016), “The Elements of Value” Harvard Business Review, (December), 3-9.

Bertini, M..and O.Keonisberg (2022), The Ends Game: How Smart Companies Stop Selling Products and Start Delivering Value, MIT Press

Chang, W., & Taylor, S. A. (2016). The Effectiveness of Customer Participation in New Product Development: A Meta-Analysis. Journal of Marketing, 80(1), 47–64. https://doi.org/10.1509/jm.14.0057

Christensen, C. M. (2016). The innovator’s dilemma. Harvard Business Review Press.

Christensen,C. et al. (2005), “Marketing Malpractice: The Cause and the Cure,” Harvard Business Review, (December), 74–83.

Gourville J.T.(2006) Eager Sellers and Stony Buyers: Understanding the Psychology of New-Product Adoption, Harvard Business Review.

Hamilton, R. and L. Price (2021),“Consumer journeys: developing consumer-based strategy,” Journal of the Academy of Marketing Science, 187-191

Moore, W.L., E.A. Pessemeier (1993), Product planning and management: designing and delivering value, McGrow Hill.

Peiyao Li, Noah Castelo, Zsolt Katona, Miklos Sarvary (2022), Language Models for Automated Market Research: A New Way to Generate Perceptual Maps, SSRN Language Models for Automated Market Research: A New Way to Generate Perceptual Maps by Peiyao Li, Noah Castelo, Zsolt Katona, Miklos Sarvary :: SSRN [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4241291]

Timoshenko A.and J.R.Hauser, (2019), “ Identifying Customer Needs from User-Generated Content, ” Marketing Science, vol. 38, no. 1, pp. 1–20,

Von Hippel,E. (1994), “Sticky Information” and the Locus of Problem Solving: Implications for Innovation”, Management Science, (40), 4, 249-39.

 

Teaching methods

The course will involve lecturing, class discussion, using of statistical software

Assessment methods

This course assessment is based on a team-work and a final exam. The group work aims at measuring a student’s ability to apply both the knowledge and the tools acquired during the course. The final exam aims at testing a student’s individual understanding of the course material.

This course assessment is based on a team-work proposed by the teacher (50%) aimed at ascertaining whether students can design a new product development process and measure the expected market value of an innovation and, a final exam aimed at ascertaining the extent to which a student has acquired the knowledge shared in the course (50%)

Team-work

To complete the team-work students need:

1) to hand in: a 12 slides pptx and, a word file (appendix) encompassing both information and data that the group deems relevant, including the statistical analysis necessary to obtain the results and conclusions presented in the presentation ( the length of this document is free).

2) to present their work during the last meeting of the course.

The assessment of the group work will be based on the material handed-in (80%) and the presentation (20%).

Final exam

The final exam will be based on the subjects discussed during the meetings and on all the material included in the course reading list ( for attending and non-attending students.

The final exam will encompass two open questions and, four multiple choices and, a non-mandatory exercise.

The assessment of the final exam will be based on the following grid:

<18 failed

18-23 sufficient

24-27 good

28-30 very good

30 cum laude honors

The final exam will last no longer than an hour.

Teaching tools

See the website of Elisa Montaguti [https://www.unibo.it/sitoweb/elisa.montaguti/en]

Office hours

See the website of Elisa Montaguti