Uncategorized

Jesse Bockstead
Assistant Professor
Eller School of Management, University of Arizona

Friday, January 31, 2014
10:00am – 11:30am
Speakman Hall 200

Seminar Title: Heterogeneous Problem-Solving Behavior and its Implications for Success in Unblind Innovation Contests

Abstract

Innovation contests are increasingly adopting an “unblind” format where contest submissions and feedback are viewable by all contestants and the information structure changes dynamically during the contest. In such a format, contestants must weigh the cost of revealing their submissions against the benefits of learning and improvement of their submissions through emerging contest information. We seek to understand how contestants solve problems in unblind innovation contests and what the implications of their problem-solving behavior on contest outcomes are. We analyze problem-solving behavior among contestants in terms of how they make submissions to a contest—i.e., when does a contestant begin participation, how many submissions does a contestant make, what is the number of submissions over which a contestant actively participates, and how are a contestant’s submissions distributed through her active participation. The econometric analysis of a large dataset of unblind innovation contests and participating contestants indicates that, despite the potential for intellectual property loss from revealing of submissions, contestants who make their first submission earlier are more likely to succeed in the contest as their number of submissions increases. We also find that increasing the length of participation in a contest has a strong positive effect on a contestant’s likelihood of success. More importantly, our results indicate that contestants whose submission patterns in a contest exhibit greater positive skewness, mimicking the traditional innovation funnel process, have a higher likelihood of success. Departing from prior studies on “blind” formats, our study provides new evidence that the process of problem solving has significant implications for a contestant’s success, above and beyond her prior experience and success in contests characterized by visible and dynamic information structure.

click here for a copy of the paper.

Param Vir Singh
Carnegie Bosch Junior Chair and Associate Professor of Business Technologies
David A Tepper School of Business
Tepper School of Business, Carnegie Mellon University

November 15, 2013

Speakman Hall 200, 10:00am – 11:30am
Seminar Title: Crowdsourcing New Product Ideas under Consumer Learning

Abstract

Crowdsourcing initiatives are becoming a popular tool for new idea generation for firms. On crowdsourced ideation initiatives, individuals contribute new product ideas and vote on other’s ideas which they would like the firm to implement. The firm then decides which ideas to implement. Although such initiatives are widely adopted in many different industries, they face increasing criticism as the number of ideas generated often decline over time, and the implementation rates (percentage of posted ideas that are implemented by the firm) are quite low raising concerns about their success.

We propose a dynamic structural model that illuminates the economic mechanisms shaping individual behavior and outcomes on such initiatives. Through counterfactuals, we identify the impact of several potential interventions on the success of such initiatives. We estimate the model using a rich dataset obtained from IdeaStorm.com, which is a crowdsourced ideation initiative affiliated with Dell. We find that, on Ideastorm.com, individuals tend to significantly underestimate the costs to the firm for implementing their ideas but overestimate the potential of their ideas in the initial stages of the crowdsourcing process. Therefore, the “idea market” is initially overcrowded with ideas that are less likely to be implemented. However, individuals learn about both their abilities to come up with high potential ideas as well as the cost structure of the firm from peer voting on their ideas and the firm’s response to contributed ideas. We find that individuals learn rather quickly about their abilities to come up with high potential ideas, but the learning regarding the firm’s cost structure is quite slow. Contributors of low potential ideas eventually become inactive, while the high potential idea contributors remain active. As a result, over time, the average potential of generated ideas increases, while the number of ideas contributed decreases. Hence, the decrease in the number of ideas generated represents market efficiency through self-selection rather than its failure. Through counterfactuals, we show that providing more precise cost signals to individuals can accelerate the filtering process. Increasing the total number of ideas to respond to and improving the response speed will lead to more idea contributions. However, failure to distinguish between high and low potential ideas and between high and low ability idea generators lead to the overall potential of the ideas generated to drop significantly.

click here a copy of the paper.

Gediminas Adomavicius
Carolyn I. Anderson Professor in Business Education Excellence and Professor of Information and Decision Sciences
Department of Information and Decision Sciences
Carlson School of Management, University of Minnesota

November 8, 2013

Speakman Hall 200, 10:00am – 11:30am
Seminar Title: Suggest or Sway? Effects of Online Recommendations on Consumers’Willingness to Pay

Abstract

Recommender systems have become an integral part of the online retail environment. Prior research has focused on advancing computational approaches to improving recommendation accuracy. Only recently have their behavioral implications become an object of study. In particular, the potential impact of recommender systems on economic behavior of individual consumers represents an important issue yet to be comprehensively explored. We present the results of two controlled experiments in the context of purchasing digital songs, which explore this issue. In the first study, we found strong evidence that randomly assigned song recommendations affected participants’ willingness to pay, even when controlling for participants’ preferences and demographics. In the second study, participants viewed actual system-generated recommendations that were intentionally perturbed (introducing recommendation error) and observed similar effects on willingness to pay. The results have significant implications for the design and application of recommender systems as well as for online retail practices.

For a copy of the paper, please email swattal@temple.edu

Ning Nan
Assistant Professor of MIS
Saunder School of Business, University of British Columbia

October 4, 2013

Speakman Hall 200, 10:00am – 11:30am
Seminar Title: Hypercompetition within Industry: Achieving and Renewing Temporary Competitive Advantages with Information Technology

Abstract

In the U.S, almost all industries exhibit increasing levels of hypercompetition. Sustained competitive advantages have become very rare. Firms seek to achieve temporary competitive advantages and renew them as they are eroded by rivals. These developments challenge theories about IT-enabled sources of sustained competitive advantage. They call for new theories explaining IT-enabled sources of temporary competitive advantage. In this study, we develop a theory to explain: (1) how and why increasing IT intensity in an industry contributes to increasing levels of hypercompetition in the industry; and (2) how a firm can use IT-enabled data analytics capabilities to achieve temporary competitive advantages and renew them on an ongoing basis in a hypercompetitive industry. Drawing on complex adaptive systems theory and the economic theory of complementarities, we posit that increasing IT intensity within an industry speeds up digitization and modularization of products and business processes, establishes interconnections among previously autonomous product markets, and enhances complementarity or substitution types of mutual dependency relationships among the product markets. Via IT-enabled interconnections, strategic changes originating in one product market propagate to the complementary and substitute product markets and affect their strategic dynamics as well, and increase turbulence in performance rank orderings in an industry, a phenomenon known as hypercompetition. IT-enabled data analytics capabilities help firms to identify and manage mutual dependency relationships among product markets so that firms can achieve temporary competitive advantage in hypercompetitive industries. Agent-based simulations provide additional insights into the complex nature of IT-induced hypercompetition. They also reveal caveats of IT-enabled data analytics capabilities in taming uncertainties in a hypercompetitive industry.

Sang Pil Han
Assistant Professor of Information Systems
City University of Hong Kong

September 16, 2013

Speakman Hall 200, 10:00am – 11:30am
Seminar Title: Cross Channel Synergies between Web and Mobile Advertising: A Randomized Field Experiment

Abstract

As companies divert more funds from traditional media towards digital advertising, they are interested in understanding what effects the two channels of advertising—web advertising and mobile advertising—have on consumer choices. Any analysis that measures the effects of web and mobile advertising only separately remains incomplete. In this paper, we design and execute a randomized field experiment to estimate causal effects of cross-channel interdependence between web and mobile advertising. We conduct a consumer-level analysis to attribute cross-channel advertising to click-throughs and conversions at the individual consumer-level. This helps isolate the effect of complementarity or substitution across platforms (web and mobile) from the role of the quantity of advertising, confound with carry-over, and consumer heterogeneity. We find that a mix of online and mobile display ad acts as a better memory cue that triggers consumers to recall product and eventually click/purchase, as compared to either online ad only or mobile ad only. Hence, in channel planning, optimal decisions in one need to take account of the effects in the other. Further, we present results from policy simulations regarding the optimal level of web and mobile advertising using CPM (cost per thousand impressions) based pricing. These synergistic relationships run counter to the single-click methodology in use and suggest that, for a market in which advertising dollars are allocated based on their influence on purchase behavior, new methods must be developed to insure efficient market functioning.

Click here for a copy of the paper.

Karthik N Kannan
Associate Professor of Management
Krannert School of Management, Purdue University

September 13, 2013

Speakman Hall 200, 9:45am – 1115am
Seminar Title: Economic and Policy Implications of Restricted Patch Distribution

Abstract

In this paper, we study how restricting the availability of patches to legal users impacts vendor’s profits, market share, software maintenance decisions, and welfare outcomes. Prior work on this topic assumes that hacker’s effort is independent of the vendor’s decision to release the patch freely or not. Clearly, if the patch is not available to everyone, the hacker finds it easier to exploit the vulnerability in the product and, as a result, is likely to alter his effort. In order to understand the role of a strategic hacker, we build a game-theoretic model, where the hacker’s decision is endogenous. With this model, we find that the hacker’s effort may, on one hand, decrease the utility that the vendor can extract from the consumers. On the other hand, it may help differentiate the legal version of the product from the pirated version. A vendor can strategically exploit the hacker’s behavior in its pricing and software maintenance decisions. The endogeneity of hacker’s actions drives several of our findings that have interesting policy implications. For example, the vendor may increase the price and reduce market share in order to exploit the differentiation. In such a case, there may be more pirates in the restricted-patch case than when the patch is freely available, a result that runs counter to typical arguments provided for restricting patches. A government body that understands this trade-off may exert a different level of piracy prevention effort so that the vendor is incentivized to make decisions that improve social welfare.

Click here for a copy of the paper.

Pei-yu Chen
Associate Professor of MIS
Fox School of Business, Temple University

May 10, 2013

Speakman Hall 200, 10:00am – 1130am
Seminar Title: Does Multi-media Advertising Pay Off?  Quantifying the Value of Multi-media Advertising on Brand Purchase

Abstract

Among the many decisions marketing managers must make is how to spread advertising dollars across the broad swath of available media: television, the Internet, social media, for example. With increased spending comes the need for accountability and for understanding the effectiveness of these marketing actions. Marketing practitioners, however, have been unable to efficiently measure the effectiveness of their multi- media advertising strategy in monetary terms using robust methodologies that can capture the complexity and diversity of multi-media efficacy, and thus fail to comprehensively evaluate multi-media investment with an eye toward more effective distribution of advertising dollars.

We address this industry need by quantifying the value of multi-media advertising for business. Our research interest is two-fold: Does social media affect brand purchase? If yes, how is the brand purchase generated in presence of multi-media advertising? Specifically, we draw upon the daily basis data of what households have bought, what they have watched on TV, their banner ad exposures, and what have been presented to them on their Facebook news feeds for a specific retailing product category over a 12-month observation window. We first examine whether multi-media advertising drive brand purchase, in terms of purchase counts, spending per purchase, and the total purchase value. Then we explore plausible explanations of how these brand purchases are created. We apply econometric modeling approaches, including fixed effect modeling, Fama-MacBeth cross-sectional regressions, and Seemingly Unrelated Regressions (SUR), to estimate these effects at disaggregate level, yet controlling for advertising endogeniety and heterogeneity.

We find that multi-media advertising effect exist and is important, while the relative effectiveness vary across media. Much of the impact of multi-media advertising can be attributed to the focal company’s market expansion, promotion on future purchase, and advertising externalities from competing brands. This study adds to our empirical knowledge of how different media channels work in concert – yet differing in their relative effectiveness – to drive marketing effectiveness. The findings point to how managers could gauge the potential value of seeding additional advertising channel and optimize the marketing mix to generate brand purchase.