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Article
Publication date: 11 April 2016

Giancarlo Lauto and Finn Valentin

The purpose of this paper is to examine the different heuristics adopted by a crowd and a management committee to evaluate new product proposals, and whether, in assessing the…

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Abstract

Purpose

The purpose of this paper is to examine the different heuristics adopted by a crowd and a management committee to evaluate new product proposals, and whether, in assessing the value of proposals, they emphasize different features.

Design/methodology/approach

The study takes a quantitative analysis approach to study an internal innovation contest held by the biotechnology company Novozymes. The contest generated 201 proposals that were evaluated by 109 research and development professionals by means of a virtual preference market, and by a management committee.

Findings

The crowd and the committees’ assessments of the value of the proposals were based on different features. The committee emphasized experience and inventors’ seniority; the crowd set more store on informative idea descriptions but penalized overly complex and lengthy proposals.

Research limitations/implications

The design of the innovation contest does not allow full comparison of the preference functions of crowd and committee. The findings from this case study cannot be generalized. The early stage of new product development seems fruitful for investigating crowdsourcing and knowledge management.

Practical implications

Firms should consider adopting preference markets for idea screening and evaluation since they appraise ideas from different angles compared to managers. However, they complement, rather than substitute managerial evaluation, especially in the case of more detailed proposals.

Originality/value

This is one of the first attempts to identify differences in the decision-making processes of crowds and committees. The paper identifies their strengths as evaluators of new product ideas and finds that the “wisdom of crowds” has some limitations in relation to the ability to process complex information.

Details

Industrial Management & Data Systems, vol. 116 no. 3
Type: Research Article
ISSN: 0263-5577

Keywords

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