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Market-Based Solutions to Vital Economic Issues

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Market-Based Solutions to Vital Economic Issues

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Channels have traditionally been viewed as intermediaries that facilitate the transfer of products from manufacturers to consumers. Innovations in digital technologies help firms to integrate the customer experience across channels and devices. This new phenomenon is referred to as “omnichannel marketing.”

This article investigates patent citations made to published patent applications. Although citations to patent publications are conceptually indistinguishable from citations to granted patents, they are omitted from all standard measures. We find that publication citations are a large and growing portion of patent citations, and that they differ statistically from citations to granted patents on several important dimensions. We conclude that omitting publication citations is likely to generate biased measures, and that standard measures of patent citations should be corrected. We release our computer code and corrections for future use.

The selection of novel ideas is vital to the development of truly innovative products. Firms often turn to idea crowdsourcing challenges, in which both ideators and the seeker firms participate in the idea selection process. Yet prior research cautions that ideators and seeker firms may not select novel ideas. To address the links between idea novelty and selection, this study proposes a bi-faceted notion of idea novelty and probes the role of task structure.

We consider the anesthesiologist staff planning problem for operating services departments in large multi-specialty hospitals. In this problem, the planner makes monthly and daily decisions to minimize total costs.

When multinational corporations face foreign marketing crises, the psychic distance between the home and host country represents a distinct challenge. This paper examines the curvilinear relationship between psychic distance and firm performance during marketing crises, and the moderating role of marketing capabilities.

When financially distressed firms have overwhelming debts, a prominent option for survival is to file for Chapter 11 bankruptcy protection. We empirically study the effect of Chrysler’s Chapter 11 bankruptcy filing on the quantity sold by its competitors in the U.S. auto industry.

We study dynamic decision-making under uncertainty when, at each period, a decision-maker implements a solution to a combinatorial optimization problem. The objective coefficient vectors of said problem, which are unobserved prior to implementation, vary from period to period.

We examine trends in the use of predictive analytics for a sample of more than 25,000 manufacturing plants using proprietary data from the US Census. Comparing 2010 and 2015, we find that use of predictive analytics has increased markedly, with the greatest use in younger plants, professionally-managed firms, more educated workforces, and stable industries.

Marketers create social media, in the form of firm-generated content (FGC), to ignite interest in new products such as movies; in turn, there is a clear need to understand whether and how FGC influences demand. With a descriptive study, the authors investigate two potential mechanisms by which FGC may drive box office revenues.

We derive asymptotic properties of estimators and test statistics to determine - in a grouped data setting - common versus group-specific factors. Despite the fact that our test statistic for the number of common factors, under the null, involves a parameter at the boundary (related to unit canonical correlations) we derive a parameter-free asymptotic Gaussian distribution. We show how the group factor setting applies to mixed frequency data. As an empirical illustration we address the question whether Industrial Production (IP) is still the dominant factor driving the U.S. economy using a mixed-frequency data panel of IP and non-IP sectors. We find that a single common factor explains 89% of IP output growth and 61% of total GDP growth despite the diminishing role of manufacturing.

We consider an online retailer facing heterogeneous customers with initially unknown product preferences. Customers are characterized by a diverse set of demographic and transactional attributes. The retailer can personalize the customers' assortment offerings based on available profile information to maximize cumulative revenue. To that end, the retailer must estimate customer preferences by observing transaction data.

While previous research has investigated various drivers of electronic word of mouth (eWOM), the firm's offline competitive environment has not been considered. The authors explore this new horizon and examine the different effects of firms’ geographic concentration, or agglomeration, on the volume of eWOM received. They distinguish three types of agglomeration—density agglomeration (number of firms in the industry in an area), product agglomeration (overlap in product types offered by the firms in the area), and temporal agglomeration (overlap in moment of consumption).