consumer behavior Archives - Mack Institute for Innovation Management

Samsung NEXT on Connectivity Within the ‘Experience Economy’

Brandon Hoffman (WG’15) discusses the role Samsung NEXT plays in transforming the customer experience that Samsung delivers.…Read More

Privacy and Innovation: The Short-run Effects of GDPR on Consumer Engagement

In today’s connected world, individuals are no longer mere consumers of goods, information and services, but public producers of often valuable data. In fact, personal data is becoming such a core input that The Economist called it “the world’s most valuable resource” ahead of oil.…Read More

The Impact of Adopting an AI-Enabled Distribution Channel

The advance in intelligent technology is changing the way that people search for and purchase products. There is an emerging trend in which consumers are shopping through artificial intelligence (AI) enabled devices such as Amazon’s Alexa and Google Assistant, for a variety of products.…Read More

Estimating the Impact of Consumer Privacy Regulations

This study aims to measure the impact of General Data Protection Regulations on firms and consumers. Specifically, we plan to document GDPR’s impact on consumers search and discovery of products, and firm’s ability to reach out and sell to a broad set of consumers.…Read More

Innovation Through Diversity: Understanding The Ever-Changing Consumer Landscape

As firms look to innovate, attention must be paid to the role cultural diversity (e.g. racial and gender diversity) plays in consumer interest in new products. In today’s society, firms need an understanding of how diversity can be used as an asset to engage consumers with their brands.…Read More

Optimizing Service using High Dimensional Panel Data

We study how retail stores’ multi-dimensioned service levels affect consumers’ buying behavior in a spatial setting. To this end, we propose the Double Block-Lasso BLP estimator, which combines the double selection procedure introduced in Belloni, Chernozhukov, and Hansen (2014), with demand estimation methods set forth in Berry, Levinsohn and Pakes (1995).…Read More

Predictable Magic: Designing Around Customer Emotions to Reach Beyond Existing Markets

Deepa Prahalad, author of “Predictable Magic: Unleash the Power of Design Strategy to Transform Your Business,” introduces design thinking frameworks that can create strong emotional engagement between customers and firms.…Read More

Better Sales Forecasting: Why the Crowd Outperforms the “Expert with the Eye”

The ability to predict consumer preferences for new fashions by clothing manufacturer executives seems rather low. This is confirmed by secondary data on inventory markdowns and our pilot interviews with major manufacturers. …Read More

How Do Product Attributes Moderate the Impact of Recommender Systems?

We investigate the impact of several different recommender algorithms (e.g., Amazon.com’s “Consumers who bought this item also bought”), commonly used in ecommerce and online services, on sales volume and diversity, using field experiment data on movie sales from a top retailer in North America. …Read More

Can Telematics Technology Help Improve Driving Behavior?

Technological innovation is changing the landscape of many industries, and automotive telematics devices are perhaps the most disruptive technology for the auto insurance industry and most automotive manufacturers have plans to develop telematics. Moreover, a number of startup companies use telematics devices in various applications. …Read More

The Demand for One-to-One Customization: Evidence from the Personal Computer Industry

We study the demand for one-to-one customization in the computer hardware industry. Using household browsing, transaction, and demographic data from the comScore database, we uncover evidence that geographically isolated households that are technologically savvy are more likely to buy and customize computer hardware online. …Read More

The Long Tail Theory, Debunked: We Stick With What We Know

Wharton professor Serguei Netessine finds that even as consumers are deluged with a growing array of choices, they tend to remain loyal to familiar brands and products.…Read More

Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook

We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and Natural Language Processing algorithms.…Read More

Is Tom Cruise Threatened? An Empirical Study of the Impact of Product Variety on Demand Concentration

We empirically examine the impact of expanded product variety on demand concentration using large data sets from the movie rental industry as our test bed. We find that product variety is likely to increase demand concentration.…Read More

Media Multiplexing Behavior: Implications for Targeting and Media Planning

There is a growing trend among consumers to serially consume small, incomplete “chunks” of multiple media types—television, radio, Internet, and print—within a short time period. We refer to this behavior as media multiplexing and note the key challenges for integrated marketing communications media planners.…Read More

Price Effects in Online Product Reviews: An Analytical Model and Empirical Analysis

Consumer reviews may reflect not only perceived quality but also the difference between quality and price (perceived value). In markets where product prices change frequently, these price-influenced reviews may be biased as a signal of product quality when used by consumers possessing no knowledge of historical prices.…Read More

Revenue Management with Strategic Customers: Last-Minute Selling and Opaque Selling

Companies in a variety of industries (e.g., airlines, hotels, theaters) often use last-minute sales to dispose of unsold capacity. Although this may generate incremental revenues in the short term, the long-term consequences of such a strategy are not immediately obvious.…Read More