Optimal Search

Morgan, Peter; Manning, Richard

doi:10.2307/1912661

Cited by 209 publications

(135 citation statements)

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“…1961, Kohn and Shavell 1974, Rothschild 1974, Lippman and McCall 1976, Weitzman 1979, Morgan and Manning, 1985. Two other recent papers use the statistical view.…”

Section: Process Models Of Innovationmentioning

confidence: 99%

Opportunity Spaces in Innovation: Empirical Analysis of Large Samples of Ideas

2011

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A common approach to innovation, parallel search, is to identify a large number of opportunities and then to select a subset for further development, with just a few coming to fruition. One potential weakness with parallel search is that it permits repetition. The same, or a similar, idea might be generated multiple times, because parallel exploration processes typically operate without information about the ideas that have already been identified. In this paper we analyze repetition in five data sets comprising 1,368 opportunities and use that analysis to address three questions: (1) When a large number of efforts to generate ideas are conducted in parallel, how likely are the resulting ideas to be redundant? (2) How large are the opportunity spaces? (3) Are the unique ideas more valuable than those similar to many others? The answer to the first question is that although there is clearly some redundancy in the ideas generated by aggregating parallel efforts, this redundancy is quite small in absolute terms in our data, even for a narrowly defined domain. For the second question, we propose a method to extrapolate how many unique ideas would result from an unbounded effort by an unlimited number of comparable idea generators. Applying that method, and for the settings we study, the estimated total number of unique ideas is about one thousand for the most narrowly defined domain and greater than two thousand for the more broadly defined domains. On the third question, we find a positive relationship between the number of similar ideas and idea value: the ideas that are least similar to others are not generally the most valuable ones.Keywords search, opportunity, opportunities, idea, ideation, idea generation, innovation, creativity, innovation process, opportunity identification, concept development, product development, product design, entrepreneurship AbstractA common approach to innovation, parallel search, is to identify a large number of opportunities and then to select a subset for further development, with just a few coming to fruition. One potential weakness with parallel search is that it permits repetition. The same, or a similar, idea might be generated multiple times, as parallel exploration processes typically operate without information about the ideas that have already been identified. In this paper we analyze repetition in five data sets comprising 1,368 opportunities and use that analysis to address three questions:(1) When a large number of efforts to generate ideas are conducted in parallel, how likely are the resulting ideas to be redundant? (2) How large are the opportunity spaces? (3) Are the unique ideas more valuable than those similar to many others? The answer to the first question is that while there is clearly some redundancy in the ideas generated by aggregating parallel efforts, this redundancy is quite small in absolute terms in our data, even for a narrowly defined domain. For the second question, we propose a method to extrapolate how many unique ideas would result from ...

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“…1961, Kohn and Shavell 1974, Rothschild 1974, Lippman and McCall 1976, Weitzman 1979, Morgan and Manning, 1985. Two other recent papers use the statistical view.…”

Section: Process Models Of Innovationmentioning

confidence: 99%

Opportunity Spaces in Innovation: Empirical Analysis of Large Samples of Ideas

2011

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“…Workers observe all posted contracts and base their search decision on this information. Since there is a delay between sending the application letters and learning their result, workers typically have an incentive to send multiple applications simultaneously (see Morgan & Manning, 1985). Sending multiple applications is more costly than applying only once, since each application takes time and effort, but has two positive effects.…”

Section: Modelmentioning

confidence: 99%

Applications and Interviews: A Structural Analysis of Two-Sided Simultaneous Search

Wolthoff

2012

SSRN Journal

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Most of the literature analyzing equilibrium effects of labor market policies assumes bilateral meetings between workers and firms. This ignores the frictions that arise when workers and firms meet in a multilateral way and cannot coordinate their application and hiring decisions. I analyze the magnitude of these frictions. For this purpose, I present an equilibrium search model of the labor market with an endogenous number of contacts between workers and firms. Firms post a wage and a recruitment technology that determines how many applicants they will interview. After observing these contracts, workers decide to which firms to apply. Sending more applications and interviewing more applicants are both costly activities but increase the probability to match. In equilibrium, contract dispersion arises endogenously and workers spread their applications over the different types of contracts. Estimation of the model on the Employment Opportunities Pilot Projects data set provides values for the cost of an application and the cost of an interview. These estimates are used to determine the output loss compared to a Walrasian world. Frictions on the worker and the firm side reduce output by approximately 1% each. There is a potential role for activating labor market policies, because I show that for the estimated parameter values welfare can be improved if unemployed workers increase their search intensity.

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“…Many consumers (bargain hunters) typically proceed by first visiting a shopbot (for instance shopper.com or pricegrabber.com) followed by sequentially visiting the firms listed in the shopbot. This procedure resembles the optimal search protocol described in Morgan and Manning (1985), which is hybrid in nature. In addition, it has been pointed out (see for example Whelan, 2001) that some consumers are somewhat loyal (convenience shoppers).…”

Section: Applicationmentioning

confidence: 99%

Semi‐nonparametric Estimation of Consumer Search Costs

González

Sándor

Wildenbeest

2012

J of Applied Econometrics

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This paper studies the estimation of the cost of non-sequential search. We provide a new method based on semi-nonparametric (SNP) estimation that allows us to pool price data from different consumer markets with the same underlying search cost distribution but different valuations or selling costs. We show that pooling data from different markets increases the number of estimated critical search cost cutoffs at all quantiles of the search cost distribution, which increases the precision of the estimates. A Monte Carlo study shows that the method works well in small samples. We apply our method to a data set of online prices for memory chips and find that the search cost density is essentially bimodal such that a large fraction of consumers searches very little, while a smaller fraction of consumers samples a relatively large number of stores.

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Optimal Search

Cited by 209 publications

References 0 publications

Opportunity Spaces in Innovation: Empirical Analysis of Large Samples of Ideas

Opportunity Spaces in Innovation: Empirical Analysis of Large Samples of Ideas

Applications and Interviews: A Structural Analysis of Two-Sided Simultaneous Search

Semi‐nonparametric Estimation of Consumer Search Costs

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