Estimating a Simultaneous Search Model

Stern, Steven

doi:10.1086/298212

Cited by 47 publications

(33 citation statements)

References 12 publications

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“…More recently, researchers such as Wolpin (1987), Stern (1989), and Christiansen and Kiefer (1991) have pursued a more structural approach in which the estimation is derived explicitly from the theory. This approach incorporates the restrictions given by the condition of optimal search to the empirical work.…”

Section: Structural Estimation Without Heterogeneitymentioning

confidence: 99%

“…With this lack of information about fundamental elements of the theoretical model, it becomes di¢cult to construct meaningful tests of the model. Stern (1989) suggests in a model where r and c are not separately identi…ed that one can construct the set of combininations of r and c that are consistent with the search behavior equation and then determine whether any elements of the set are "reasonable" values. This provides an informal test of the theory.…”

Section: Structural Estimation Without Heterogeneitymentioning

confidence: 99%

“…Several authors have dealt with this problem by explicitly incorporating the possibility of measurement error in the estimation of the structural model. Among the papers that have followed this approach are Wolpin (1987), Stern (1989), and Christensen and Kiefer (1994). All three papers assume that the observed wages are a¤ected by random error in measurement that is normally distributed.…”

Section: Measurement Errormentioning

confidence: 99%

“…As a result, these parameters cannot be independently identi…ed. Stern (1989) presents a extensive discussion of identi…cation in a similar context.…”

Section: Measurement Errormentioning

confidence: 99%

“…In fact, workers with di¤erent characteristics may face di¤erent wage o¤er distributions and thus have di¤erent reservation wages. Also, in more complex search models in which workers can choose the search intensity, workers with di¤erent characteristics may have di¤erent costs of search and, as a result, they can optimally choose to search with di¤erent levels of intensity as is the case in Stern (1989). We divide our discussion into the e¤ect of observed heterogeneity and the e¤ect of unobserved heterogeneity on estimation.…”

Section: Sample Heterogeneitymentioning

confidence: 99%

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Empirical Search Models

Canals

Stern

2002

Search Theory and Unemployment

Self Cite

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Section: Structural Estimation Without Heterogeneitymentioning

confidence: 99%

Section: Structural Estimation Without Heterogeneitymentioning

confidence: 99%

Section: Measurement Errormentioning

confidence: 99%

“…As a result, these parameters cannot be independently identi…ed. Stern (1989) presents a extensive discussion of identi…cation in a similar context.…”

Section: Measurement Errormentioning

confidence: 99%

Section: Sample Heterogeneitymentioning

confidence: 99%

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Empirical Search Models

Canals

Stern

2002

Search Theory and Unemployment

Self Cite

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Motivation for using search engines: A two‐factor model

Chuang

Chen

2008

J. Am. Soc. Inf. Sci.

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From a user-centered perspective, an effective search engine needs to attract new users to try out its features, and retain those users so that they continue using the features. In this article, we investigate the relations between users' motivation for using (i.e., trying out and continuing to use) a search engine and the engine's functional features. Based on Herzberg's two-factor theory (F. Herzberg, 2003; F. Herzberg, M. Bernard, & B. Snyderman, 1959), the features can be categorized as hygiene factors and motivation factors. Hygiene factors support the query process and provide a basic "task context" for information seeking that allows users to access relevant information. Motivation factors, on the other hand, help users navigate (i.e., browse) and comprehend the retrieved information, related to the "task-content" aspect of information seeking. Given the consistent findings that hygiene factors induce work motivation for a shorter period of time, it is hypothesized that hygiene factors are more effective in attracting users; while motivation factors are more effective in retaining than in attracting users. A survey, with 758 valid participants, was conducted to test the hypotheses. The empirical results provide substantial support for the proposed hypotheses and suggest that the two-factor theory can account for the motivation for using a search engine. IntroductionSearch engines have become one of the most important Web services because of the rapid growth in the amount of information available on the Internet. Increasingly advanced features are being developed to improve the standard of service provided to search engine users. However, for search engine designers, choosing from the abundance of features on a design checklist presents a challenging task. Therefore, a theoretical framework should be developed as the basis Received April 21, 2007; revised April 16, 2008; accepted April 16, 2008 © 2008 ASIS&T • Published online 9 July 2008 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/asi.20889 for systematic categorization of search engine features. Such a framework also should take account of the relationships between categories of features and users' motivations for using them. By knowing what kinds of features motivate usage, search engine designers can focus on and improve the features that stimulate and strengthen a user's motivation rather than on enhancing aspects of the physical system's performance that are not as highly appreciated by users.Inspired by the two-factor theory of job motivation (Herzberg, 2003;Herzberg, Bernard, & Snyderman, 1959), we propose classifying search engine features in terms of hygiene and motivation factors. It is assumed that there exists an analogy between the motives of search engine operators in servicing people's information-seeking needs and the motives of organizations that encourage employees to work harder. In other words, both provide basic functionalities to support a task's context (i.e., hygiene factors) and motivating features that e...

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