Search

With the rise of mobile surveys comes the need for shorter questionnaires. We investigate the modularization of an existing questionnaire in the Longitudinal Internet Study for the Social Sciences (LISS) Panel in the Netherlands. We randomly divided respondents into a normal length survey condition, a condition where the same survey was split into 3 parts, and a condition where the survey was split into 10 parts. Respondents received the parts consecutively at regular intervals over a 1-month period. We discuss response rates, data quality measures, and respondents' evaluation of the questionnaire. Our results indicate higher start rates when the survey is cut into smaller parts but also higher dropout rates. However, the fraction of missing information is lower in the 3- and 10-part conditions. More respondents use their mobile phone for survey completion when the survey is shorter. We find fewer item missings and satisficing in shorter surveys. We find no effect on neutral and extreme responding nor on estimates of the validity of answers. People with low and high education and young and old evaluate shorter surveys better than the normal length survey. [ABSTRACT FROM AUTHOR]

This study explores some features of slider bars in the context of a multi-device web survey. Using data collected among the students of the University of Trento in 2015 and 2016 by means of two web surveys (N = 6,343 and 4,124) including two experiments, we investigated the effect of the initial position of the handle and the presence of numeric labels on answers provided using slider bars. It emerged that the initial position of the handle affected answers and that the number of rounded scores increased with numeric feedback. Smartphone respondents appeared more sensitive to the initial position of the handle but also less affected by the presence of numeric labels resulting in a lower tendency to rounding. Yet, outcomes on anchoring were inconclusive. Overall, no relevant differences have been detected between tablet and PC respondents. Understanding to what extent interactive and engaging tools such as slider bars can be successfully employed in multi-device surveys without affecting data quality is a key challenge for those who want to exploit the potential of web-based and multi-device data collection without undermining the quality of measurement. [ABSTRACT FROM AUTHOR]

In an experiment dealing with the use of personal computer, tablet, or mobile, scale points (up to 5, 7, or 11) and response formats (bars or buttons) are varied to examine differences in mean scores and nonresponse. The total number of “not applicable” answers does not vary significantly. Personal computer has the lowest item nonresponse, followed by mobile and tablet, and a lower mean score than for mobile. Slider bars showed lower mean scores and more nonresponses than buttons, indicating that they are more prone to bias and difficult in use. Sider bars, which work with a drag-and-drop principle, perform worse than visual analogue scales working with a point-and-click principle and buttons. Five-point scales have more nonresponses than eleven-point scales. Respondents evaluate 11-point scales more positively than shorter scales. [ABSTRACT FROM AUTHOR]

The number of satellites visible to a Global Navigation Satellite System (GNSS) receiver is important for high accuracy surveys. To aid with this, there are software packages capable of predicting GNSS visibility at any location of the globe at any time of day. These prediction packages operate by using regularly updated almanacs containing positional data for all navigation satellites; however, one issue that restricts their use is that most packages assume that there are no obstructions on the horizon. In an attempt to improve this, certain planning packages are now capable of modelling simple obstructions whereby portions of the horizon visible from one location can be blocked out, thereby simulating buildings or other vertical structures. While this is useful for static surveys, it is not applicable for dynamic surveys when the GNSS receiver is in motion. This problem has been tackled in the past by using detailed, high-accuracy building models and designing novel methods for modelling satellite positions using GNSS almanacs, which is a time-consuming and costly approach. The solution proposed in this paper is to use a GIS to combine existing, freely available GNSS prediction software to predict pseudo satellite locations, incorporate a 2.5D model of the buildings in an area created with national mapping agency 2D vector mapping and low density elevation data to minimise the need for a full survey, thereby providing savings in terms of cost and time. Following this, the ESRI ArcMap viewshed tool was used to ascertain what areas exhibit poor GNSS visibility due to obstructions over a wide area, and an accuracy assessment of the procedure was made. [ABSTRACT FROM AUTHOR]

The dramatic rise of smartphones has profound implications for survey research. Namely, can smartphones become a viable and comparable device for self-administered surveys? The current study is based on approximately 1,500 online U.S. panelists who were smartphone users and who were randomly assigned to the mobile app or online computer mode of a survey. Within the survey, we embedded several experiments that had been previously tested in other modes (mail, PC web, mobile web). First, we test whether responses in the mobile app survey are sensitive to particular experimental manipulations as they are in other modes. Second, we test whether responses collected in the mobile app survey are similar to those collected in the online computer survey. Our mobile survey experiments show that mobile survey responses are sensitive to the presentation of frequency scales and the size of open-ended text boxes, as are responses in other survey modes. Examining responses across modes, we find very limited evidence for mode effects between mobile app and PC web survey administrations. This may open the possibility for multimode (mobile and online computer) surveys, assuming that certain survey design recommendations for mobile surveys are used consistently in both modes. [ABSTRACT FROM PUBLISHER]

Mobile technology offers a promising means to collect survey data, though the factors that influence people's willingness to participate in mobile surveys and their actual participation remain unknown. To identify these factors, this study considers six conceptually distinct influences that may relate to the propensity to participate in mobile surveys. Some of them affect technology acceptance and usage of (mobile) technology in general; another set comes from studies of participation in computer-assisted surveys. The proposed unified framework encompasses utilitarian, affective, hedonic, social, self-expressive, and trust-related factors. An empirical study suggests that this framework explains the intention to participate and actual participation well, though of the six factors, hedonic, affective, self-expressive, and trust-related ones are most influential. Utilitarian aspects and beliefs about perceived social pressure to participate do not play significant roles. The authors discuss the practical implications of these results and outline some further research avenues. [ABSTRACT FROM AUTHOR]