25 years of factorial surveys in sociology: A review

Wallander, Lisa

doi:10.1016/j.ssresearch.2009.03.004

Cited by 563 publications

(517 citation statements)

References 127 publications

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“…To investigate whether and how privacy expectations vary across mobile activity contexts, a survey was conducted using factorial vignette methodology (Wallander 2009). The factorial vignette survey methodology was developed to investigate human judgments (Rossi and Nock 1982;Jasso 2006;Wallander 2009) and asks respondents to rate a series of hypothetical vignettes.…”

Section: Methodsmentioning

confidence: 99%

“…The factorial vignette survey methodology was developed to investigate human judgments (Rossi and Nock 1982;Jasso 2006;Wallander 2009) and asks respondents to rate a series of hypothetical vignettes. A set of vignettes is generated for each respondent, where the vignette factors are independent variables controlled by the researcher and randomly selected.…”

Section: Methodsmentioning

confidence: 99%

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Putting mobile application privacy in context: An empirical study of user privacy expectations for mobile devices

Martin

Shilton

2016

The Information Society

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Putting mobile application privacy in context: An empirical study of user privacy expectations for mobile devices

Martin

Shilton

2016

The Information Society

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“…Here, too, conjoint analysis has the potential to reduce bias as compared to traditional survey experiments (Wallander 2009), because conjoint respondents are presented with various attributes and thus can often find multiple justifications for a given choice. Indeed, some researchers have applied it to socially sensitive topics precisely for this reason, including victim blame following sexual assault (Alexander and Becker 1978), and stigmas associated with HIV (Schulte 2002).…”

Section: Potential Limitationsmentioning

confidence: 99%

Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices Via Stated Preference Experiments

2013

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Edited by R. Michael AlvarezSurvey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. The analysis enables us to propose diagnostic checks for the identification assumptions. We then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants.

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“…As each manager judged five vignettes, our factorial survey data have a hierarchical structure by design, therefore observations are not independent (Wallander, 2009). Multilevel analysis is used to deal with the hierarchical structure of the data (Hox, 2010).…”

Section: Analysesmentioning

confidence: 99%

Why demotion of older workers is a no-go area for managers

Dalen

Henkens²

2016

The International Journal of Human Resource Management

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Abstract:Demotion -a reduction of an employee's rank and salary -is often mentioned by managers and policy makers as a measure to increase the employability of older workers, but in practice demotion is rarely applied. This paper takes a fresh look at the question of demotion by first employing a survey among European employers and second the use of a survey and a vignette study among managers in the Netherlands (N = 355). The European survey shows that although demotion is not often applied a considerable percentage contemplates the application in the near future, especially those employers who encounter work staff aging. The vignette study offers insight in their stated preferences with respect to demotion for a particular employee, described by a number of possible causes of underperformance. The key question is whether these causes refer to internal or external causes and causes which the employee can or cannot control. By using background characteristics on the manager, obtained through survey questions, we can assess whether the decision to demote is also affected the expectations of managers on the wider consequences of making demotion standard practice. Internal causes such as not willing to participate in training, and not being motivated to work increase the likelihood of demotion, whereas external causes (financial situation of the firm) are of little importance. However, even when an employee scores low points on all possible causes, demotion still is hesitantly considered. Much of this hesitation is connected to the perceived negative externalities which managers expect to materialize once demotion becomes standard practice.3

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25 years of factorial surveys in sociology: A review

Cited by 563 publications

References 127 publications

Putting mobile application privacy in context: An empirical study of user privacy expectations for mobile devices

Putting mobile application privacy in context: An empirical study of user privacy expectations for mobile devices

Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices Via Stated Preference Experiments

Why demotion of older workers is a no-go area for managers

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