Arvind Rangaswamy

Color portrait of Arvind Rangaswamy

University Distinguished Professor of Marketing

Department Marketing
Office Address 481 Business Building
Phone Number 814-865-1907
Email Address arvindr@psu.edu

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Arvind Rangaswamy (PhD, Northwestern University) is University Distinguished Professor of Marketing at The Smeal College of Business at Penn State. From 2009 to 2012, he was the Senior Associate Dean for Research and Faculty. Before joining Penn State, he was a faculty member at the Wharton School (University of Pennsylvania) and the Kellogg School of Management (Northwestern University).

His research is focused on methods and models to improve the efficiency and effectiveness of marketing using information technologies. He has published numerous professional articles on marketing analytics and online marketing in top academic journals and is among the world’s leading scholars in these areas. He has also co-authored a widely used textbook in Marketing Analytics titled, Marketing Engineering. He is a Principal and co-founder of DecisionPro, Inc (www.decisionpro.biz, www.enginius.biz). He is also currently an editor of the Journal of Interactive Marketing. His academic honors include Government of India Scholar Award, IC2 Fellow at the University of Texas at Austin, Robert B. Clarke Outstanding Educator Award, Thinkers50 India, and IBM Faculty Partner. In addition, he is a two-time recipient of The Jan-Benedict E.M. Steenkamp Award for Long-Term Impact given by the International Journal of Research in Marketing.

Expertise

He has published numerous professional articles on marketing analytics and online marketing, and has co-authored a book titled Marketing Engineering, which is widely used as a textbook in business schools around the globe. He is currently Editor of Journal of Interactive Marketing. He has also consulted for several companies in the areas of marketing, marketing analytics, and e-Business. His consulting engagements have been at such companies as Abbott Labs, ImpactRX, J.D. Power Associates, Pfizer, Xerox, and Unisys. He was a Fellow of the IC2 Institute (1997-2019), and was an IBM Faculty Partner (2000-2001). He is a Principal and co-founder of DecisionPro, Inc., a State College, PA company that develops practical leading-edge analytical approaches to address common marketing problems.

Education

Ph D, Marketing, Northwestern University, 1985

MBA, Business Administration, Indian Institute of Management, 1979

BS, Technology, Indian Institute of Technology, 1976

Courses Taught

MKTG 474 – MKTG ANALYTICS (3)
In rapidly changing markets characterized by ever more demanding customers served by global competitors, intuitive decision making, even when honed by years of experience, is unlikely to generate superior results. Instead, successful marketers increasingly rely on Marketing Analytics, a systematic approach to applying analytical models to properly organized empirical data, with the goal of extracting true insights about the marketing environment.This course will introduce students to commonly used analytical tools in such areas as segmentation, targeting and positioning, satisfaction management, customer lifetime analysis, customer choice, product and price decisions using conjoint analysis, and text analysis and search analytics. This is a hands-on course based on the Marketing Engineering approach and Excel software, in which students will apply the tools studied to actual business situations and conduct a group project involving primary data collection and analysis.At the conclusion of this course, students will be familiar with some of the more common marketing analytics tools and be able to extract insights from marketing data using model-supported decision making.

MKTG 540 – Marketing Analytics (3)
The course objectives are to demonstrate to students the benefits of using systematic and analytical approaches to marketing decision-making, and to build their skills and confidence in undertaking such analyses and decision-making in a modern enterprise. The analytical approaches covered in the course will enable students to identify alternative marketing options and actions that enhance business performance, predict the expected market and consumer reactions associated with potential marketing actions undertaken by a business, calibrate the opportunity costs associated with each action, and choose one or more actions that have the highest likelihood of achieving established business goals. The course will help students to develop skills that will enable them to propose and justify marketing expenditures using a Return on Investment (ROI) logic that businesses are increasingly asking of their executives.This course builds on the basic business analytics concepts and methods that business students are expected to have. The topics covered include a range of analytical concepts and tools associated with various aspects of marketing, including segmentation, targeting, positioning, product design, short-term and long-term forecasting, marketing resource allocation, search engine advertising planning, social influence measurement, A/B testing, and attribution analysis.

MKTG 555 – Mktg Models (3)
Topics in the model building approach to marketing decision making, focusing on current research issues.

MKTG 597 – Special Topics (Variable)

MKTG 543 – E-Mktg (2)
Using the Internet and related technologies to enhance and transform marketing functions and processes.

BAN 540 – Predictive Analytics for Bus (3)
BAN 840 explores the use of predictive analytics tools and techniques throughout a wide range of business scenarios and problems. Initially focusing on the application of traditional predictive analytics techniques to answer the question, "What will happen in the future?", the course provides opportunities for students to apply regression and forecasting techniques to data from various business contexts to inform business leaders¿ decision. Later, students explore various software applications and techniques for acquiring, preparing, and analyzing "big data", recognizing and taking advantage of the exponential growth in the amount of structured and unstructured data generated by and available to businesses. The course next examines cutting-edge techniques gaining increased attention among analytics experts, including data mining, text analytics, and social media analytics. Finally, students will be given an overview of the future of predictive analytics, developing an awareness of artificial intelligence and machine learning concepts, such as neural networks, to help them advance their organizations¿ business analytics capabilities. Software packages, concepts, and business applications will vary and evolve to keep pace with technology, theory, and instructor interests.

EBIZ 543 – E-Mktg (2)
Using the Internet and related technologies to enhance and transform marketing functions and processes.

MKTG 521 – Sci Mktg Anlys (2)
An introduction to the tools used, rationale for, and the practice and implementation of a variety of current marketing techniques. MKTG (MS&IS) 521 Marketing Engineering (3) This course deals with concepts, methods, and applications of decision modeling to address such marketing issues as segmentation, targeting and positioning, new product design and development, advertising, sales force and promotion planning, and sales forecasting. The course is designed for MBAs as well as for students in engineering and related disciplines who have some background in or understanding of marketing principles, and exposure to spreadsheet programs such as EXCEL.Unlike conventional capstone marketing courses that focus on conceptual material, this course will attempt to provide skills to translate conceptual understanding into specific operational plans--a skill in increasing demand in organizations today. Using market simulations and related exercises tied to PC-based computer software, students will develop marketing plans in various decision contexts.Specifically, the course objectives are to: Provide students with an understanding of the role that analytical techniques and computer models can play in enhancing marketing decision making in modern enterprises. Improve students' skill in viewing marketing processes and relationships systematically and analytically. Expose students to numerous examples demonstrating the value of the analytic approach to marketing decision making. Provide students with the software tools that will enable them to apply the models and methods taught in the course to real marketing problems. The course will be of particularly valuable to students planning careers in marketing and management consulting. The course is designed for students with some background in quantitative methods as well as some exposure to basic marketing concepts.Class sessions will be devoted to probing, extending and applying the material in the readings and the cases. We will use the "Tell-Show-Do" sequence to give you hands-one experience in using the course materials for making marketing decisions. It is your responsibility to be prepared for each session as detailed in the course outline. Each one of you will benefit from belonging to a "study group" that meets and prepares for each session before coming to class.

MKTG 596 – Individual Studies (Variable)
Creative projects, including nonthesis research, which are supervised on an individual basis and which fall outside the scope of formal courses.

MKTG 597C – Marketing 2.0 (2)
This course deals with concepts, methods, and applications of decision modeling to address such marketing issues as segmentation, new product design and development, advertising, sales force and promotion planning, and sales forecasting.

MKTG 496 – Independent Studies (variable)
Creative projects, including research and design, which are supervised on an individual basis and which fall outside the scope of formal courses.

MKTG 498H – Marketing Engineering: Analysis for Strategic Consulting (3)
Formal courses given infrequently to explore, in depth, a comparatively narrow subject which may be topical or of special interest.

MS&IS 555 – Marketing Models (3)
Topics in the model building approach to marketing decision making, focusing on current research issues.

Selected Publications

Goel N., Rangaswamy A., "Blue Apron Influencer Marketing." 2022, pp. 15
Sarkar M., Rangaswamy A., "Planning Robinhood’s Response to the GameStop Debacle." 2022, pp. 33
Rangaswamy A., Moch N., Felten C., van Bruggen G., Wierenga J. E., Wirtz J., "The Role of Marketing in Digital Business Platforms." Journal of Interactive Marketing, vol. 51, no. 3, 2020, pp. 72-90
Rangaswamy A., "The Two Stars of Marketing Analytics: Automated and Directed Systems." (SAGE Publications), 2019, pp. 401-417
Lilien G. L., Rangaswamy A., De Bruyn A., "Principles of Marketing Engineering and Analytics (Third Edition)." 2017
Ebbes P., Huang Z., Rangaswamy A., "Sampling Designs for Recovering Local and Global Characteristics of Social Networks." International Journal of Research in Marketing, vol. 33, no. 3, 2016
Germann F., Lilien G. L., Rangaswamy A., "Performance Implications of Deploying Marketing Analytics." International Journal of Research in Marketing, vol. 30, no. 2, 2013, pp. 114-128
Srinivasan R., Lilien G. L., Rangaswamy A., Pingitore G. A., Seldin D., "The Total Product Concept and an Application to the Auto Market." Journal of Product Innovation Management, vol. 29, 2012, onlinelibrary.wiley.com/doi/10.1111/jpim.2012.29.issue-s1/issuetoc
Rangaswamy A., Lilien G. L., De Bruyn A., "Principles of Marketing Engineering (Second Edition)." (DecsionPro, Inc.), 2012
Clement M., Rangaswamy A., Vadali S., "Consumer Responses to Legal Music Download Services that Compete with Illiegal Alternatives." Service Science, vol. 4, no. 1, 2012
Sorescu A., Frambach R. Y., Singh J., Rangaswamy A., Bridges C., "Innovations in Retail Business Models." Journal of Retailing, vol. 87S, no. 1, 2011
Hennig-Thurau T., Malthouse E. C., Friege C., Gensler S., Lobschat L., Rangaswamy A., Skiera B., "The Impact of New Media on Customer Relationships." Journal of Service Research, vol. 13, no. 3, 2010, pp. 20
Puligadda S., Grewal R. S., Rangaswamy A., Kardes F. R., "The role of idiosyncratic attribute evaluation in mass customization." Journal of Consumer Psychology, vol. 29, no. 3, 2010, pp. 369-380, www.sciencedirect.com/science/journal/10577408
Rangaswamy A., Giles C. L., Seres S., "A Strategic Perspective on Search Engines: Thought Candies for Practitioners and Researchers." Journal of Interactive Marketing, vol. 23, no. 1, 2009, pp. 49-60
Kayande U. A., DeBruyn, Lilien G. L., Rangaswamy A., Van Bruggen G., "How Incorporating Feedback Mechanisms in a DSS Affects DSS Evaluations." Information Systems Research, vol. 20, no. 4, 2009, pp. 527-546
Huang Z., Ebbes P., Rangaswamy A., Thadakamalla H., "Sampling Large-scale Social Networks: Insights from Simulated Networks." Proceedings of 18th Annual Workshop on Information Technologies and Systems, 2008, pp. 6
Srinivasan R., Lilien G. L., Rangaswamy A., "Survival of high tech firms: The effects of diversity of product-market portfolios, patents, and trademarks." International Journal of Research in Marketing, vol. 25, no. 2, 2008, pp. 119-125
Srinivasan R., Lilien G. L., Rangaswamy A., "The Emergence of Dominant Designs." Journal of Marketing, vol. 70, no. 2, 2006, pp. 1-17
Grissom M. D., Belegundu A. D., Rangaswamy A., Koopmann G. H., "Conjoint-analysis-based multiattribute optimization: application in acoustical design." Structural and Multidisciplinary Optimization, vol. 31, no. 1, 2006, pp. 9
Steckel J., Winer R., Bucklin R. E., Dellaert B. G., Drèze X., Häubl G., Jap S., Little J. D., Meyvis T., Montgomery A., Rangaswamy A., "Choice in Interactive Environments." Marketing Letters, vol. 16, 2005, pp. 12
Srinivasan R., Rangaswamy A., Lilien G. L., "Turning Adversity into Advantage: Does Proactive Marketing During a Recession Pay Off?." International Journal of Research in Marketing, vol. 22, no. 2, 2005, pp. 17
Rangaswamy A., Van Bruggen G., "Opportunities and Challenges in MultiChannel Marketing: An Introduction to the Special Issue." Journal of Interactive Marketing, 2005, pp. 7
Lilien G. L., Rangaswamy A., Van Bruggen G. H., Starke k., "DSS Effectiveness in Marketing Resource Allocation Decisions: Reality Versus Perception." Information Systems Research, vol. 15, no. 3, 2004, pp. 20
Rangaswamy A., Srinivasan R., Lilien G. L., "First in, First out? The Effects of Network Externalities on Pioneer Survival." Journal of Marketing, vol. 68, no. 1, 2004, pp. 18, www.garylilien.info/publications/90%20-%20First%20in,%20First%20out.pdf
Rangaswamy A., "Mobile Game Apps: An Opportunity?."
Rangaswamy A., "Forecasting Adoption of Telepresence Robot Technology."

Editorships

Journal of Interactive Marketing, Editor, (www.journals.elsevier.com/journal-of-interactive-marketing), January 2020 - Present
International Journal of Research in Marketing, Subject Matter Editor, (www.journals.elsevier.com/international-journal-of-research-in-marketing/editorial-board), September 2018 - December 2019
Schmalenbach Business Review, Editorial Board, (www.sbr-online.de/editorial_advisory_board.html), January 2015 - December 2021
International Journal of Research in Marketing, Editorial Board, July 2007 - August 2018
Journal of Marketing, Editorial Board, June 2005 - May 2010
Journal of Service Research, Editorial Board, July 2000 - June 2009
The Quarterly Journal of Electronic Commerce, Editorial Board, July 1998 - June 2003
Marketing Science, Associate Editor, January 1998 - June 2011
Journal of Interactive Marketing, Editorial Board, July 1997 - December 2019
Journal of Business to Business Marketing, Editorial Board, September 1996 - Present
Marketing Science, Editorial Board, July 1994 - June 1998
International Journal of Intelligent Systems in Accounting, Finance, and Mgmt, Editorial Board, July 1993 - Present