Web Survey Bibliography
Relevance & research questions: The increased flexibility users experience through different devices and mobile Internet is changing the way they consume content from the Internet. In 2015, a representative study of the German population found that users do not only go online to fulfill specific goals such as finding a piece of information (76 % of the participants), but they also browse the Internet for recreational purposes such as for reading articles (59%) or watching videos (53%) (ARD/ZDF-Onlinestudie, 2015). While searching for information can be seen as a goal-directed task, Internet visits for the purpose of recreation do not require the user to undertake specific tasks. For instance, when killing time users may visit the Internet with no specific goal in mind. They explore and browse. In research this differentiation between goal-directed and exploratory online behavior has been widely recognized (e.g. Hoffmann & Novak, 1996; Hassenzahl, 2005; Wang, Wang, & Farn, 2007). Although it is often assumed that during website interaction the type of task may change users’ perception (e.g. Van Schaik & Ling, 2009), very few studies experimentally manipulate the given tasks to assess possible interactional effects. This thesis aimed to fill this gap by investigating how goal-directed (searching) or exploratory (browsing) interactions performed on a website moderate the impact of key website attributes on users’ judgements. Such key elements, namely content, perceived usability, and aesthetics have already been identified by various researchers (e.g. Thielsch, Blotenberg, & Jaron, 2014). Furthermore, the current study distinguished between three post-use judgements. Besides the overall impression of a website, the intention to revisit or recommend a website was assessed. Based on psychological models following moderating effects were expected. The influences of content and usability perception were assumed to increase in searching tasks, while aesthetics was hypothesized to be of greater importance when browsing.
Methods & data: The survey was conducted online in English and German. In total, 481 participants (21.8 % female) took part, of whom 319 were German and 163 were English speaking. Ages ranged from 14 to 69 years with a mean age of 34.84 (SD = 10.68). Two different websites of competing brands in the premium and luxury fashion segment were used as stimuli. Therefore, familiarity to the online shopping context was given. Participants were randomly assigned to one of the two conditions: free exploration (browsing) or fulfillment of specific tasks (searching). In the searching condition participants were instructed to compare prices of two products and to answer questions about product materials. Both tasks were followed by items measuring the predictor variables: Perceived website usability was measured using the English questionnaire PWU (Perceived Website Usability; Flavián et al., 2006) and its German version WWU (Moshagen, Musch, & Göritz, 2009; Thielsch, 2008). For measurement of aesthetics the VisAWI (Visual Aesthetics of Websites Inventory; Moshagen & Thielsch, 2010), was employed. The Web-CLIC served to measure the subjective perception of content facets (Thielsch & Hirschfeld, under review). Finally, participants rated their intention to revisit or recommend the website and provided their overall impression.
Results: To assess the predictive strength of content, perceived usability, and aesthetics, hierarchical and stepwise multiple linear regressions were conducted using overall impression, recommendation, and revisit intention as outcome variables. Overall, content and aesthetics contributed significantly to revisit and recommendation intention as well as overall impression. Content had the greatest impact on revisit and recommendation intention, whereas aesthetics was the most influential for overall impression. Perceived usability only contributed to overall impression. Moderation analyses further analyzed the strength of those relationships for searching and browsing tasks. Interestingly, perceived usability was not influenced by the type of task in any of the calculated models. However, contrary to the hypotheses the predictive strength of aesthetics was stronger when searching. Yet, this change did not show significance in the moderation analysis. Only the influence of content was, in some models, significantly stronger when browsing. Taken all together, browsing or searching did not consistently change the way users were influenced by content, aesthetics or usability.
In additional analyses, differences in main effects were found for English and German participants, and for a company’s registered and non-registered customers.
Added value: Three main conclusions for researchers and professionals can be drawn from this study. First, the proposed assumptions regarding the influence of browsing and searching tasks cannot be supported: The perception of neither usability nor content showed stronger influences on users’ judgements in searching tasks. Aesthetics was not of greater importance when browsing. In fact, to some degree, opposite effects were found. For professionals, this may lead to important conclusions that contrast intuition. For instance, when dealing with highly goal-directed users (e.g. searching for information, comparing different products) perception of usability does not become overly important. Contrary it might be as important to aim for high aesthetical appeal as communicating product information. In sum, results imply that the importance of each construct may not strongly depend on the type of task, but rather differs for spontaneous and more complex evaluations. Content seems to be the strongest driver for building more complex decisions such as revisit or recommendation intention whereas aesthetics is highly influential for spontaneous and overall evaluations of a website. This results in a second implication. Being valued for its simplicity a great number of companies use a measurement of customer satisfaction called the Net Promotor Score (NPS), which consists of one question asking for users' intention to recommend a website (e.g. Reichheld, 2003). However, the current survey suggests that the intention to recommend is highly influenced by content, but not as much by website facets like usability and aesthetics. The two latter constructs seem to be important rather for building an overall impression. Thus, professionals should not only focus on intention to recommend a website but also consider overall impression evaluations such as giving the website a specific grade when measuring success of websites. Third and last, the reported individual differences require further investigations. Website designers should consider adapting their content or aesthetics levels in order to enhance user experience within different cultural backgrounds or for loyal customers.
Web survey bibliography (4086)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Mind the Mode: Differences in Paper vs. Web-Based Survey Modes Among Women With Cancer; 2017; Hagan, T. L.; Belcher, S. M.; Donovan, H. S.
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Lessons from recruitment to an internet based survey for Degenerative Cervical Myelopathy: merits of...; 2017; Davies, B.; Kotter, M. R.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Examining Factors Impacting Online Survey Response Ratesin Educational Research: Perceptions of Graduate...; 2017; Saleh, A.; Bista, K.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- Push2web or less is more? Experimental evidence from a mixed-mode population survey at the community...; 2017; Neumann, R.; Haeder, M.; Brust, O.; Dittrich, E.; von Hermanni, H.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- Rates, Delays, and Completeness of General Practitioners’ Responses to a Postal Versus Web-Based...; 2017; Sebo, P.; Maisonneuve, H.; Cerutti, B.; Pascal Fournier, J.; Haller, D. M.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.