An established yearly survey aimed at monitoring the employment opportunities of Italian graduates, traditionally carried out with Cati methods, has been integrated during the last few years with Cawi. Cawi has become increasingly crucial due to the high number of graduates involved in the survey, which has mandated a reduction in fieldwork duration and unit costs. Although the seven Cawi surveys used here have different substantive and methodological characteristics, preliminary analysis reveals a common trend: the utmost participation is observed during the first few days immediately following initiation of fieldwork and, to a lesser degree, the delivery of follow-up reminders. Web respondents comprise a self-selected subgroup of the target population, having better academic performance and greater computer skills. A Cox regression model estimating response probability (or response time) shows, besides the obvious effects of certain personal and survey design characteristics, that faster response times are expressed by graduates in science or engineering and reporting good computer skills, whereas the fields of medicine/health and defence/security and no computer skills give rise to lower response probability. Ways to use these findings for fine-tuning data collection are discussed.

Factors Contributing to Participation in Web-based Surveys among Italian University Graduates

GASPERONI, Giancarlo;
2011

Abstract

An established yearly survey aimed at monitoring the employment opportunities of Italian graduates, traditionally carried out with Cati methods, has been integrated during the last few years with Cawi. Cawi has become increasingly crucial due to the high number of graduates involved in the survey, which has mandated a reduction in fieldwork duration and unit costs. Although the seven Cawi surveys used here have different substantive and methodological characteristics, preliminary analysis reveals a common trend: the utmost participation is observed during the first few days immediately following initiation of fieldwork and, to a lesser degree, the delivery of follow-up reminders. Web respondents comprise a self-selected subgroup of the target population, having better academic performance and greater computer skills. A Cox regression model estimating response probability (or response time) shows, besides the obvious effects of certain personal and survey design characteristics, that faster response times are expressed by graduates in science or engineering and reporting good computer skills, whereas the fields of medicine/health and defence/security and no computer skills give rise to lower response probability. Ways to use these findings for fine-tuning data collection are discussed.
AlmaLaurea Working Paper no. 35
1
14
C. Cimini; G. Gasperoni; C. Girotti
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/105710
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