Web Survey Bibliography
Reason analysis is a long sidelined method of data collection and analysis. I would like to draw attention to the applicability of the method today for addressing current complex social research problems. In my paper I will recount the roots and principles of the method and how it is applied. In conclusion I will present some examples of it in use and some of the problems connected with its practical application in research.
Reason analysis is an analysis of the individual reasons and motives behind the process of decision
‐making relating to various questions. It can be applied in social research generally, in public opinion research, and in market research. The method and principles of reason analysis were first expounded by Paul Felix Lazarsfeld in his article The Art of Asking “Why?” published in 1935. Over the next thirty years it was employed several times as part of the “Princeton Radio Project” and in research conducted by the Columbia Sociology School. Charles Kadushin wrote the entry on “reason analysis” in the International Encyclopedia of Social Sciences. The method then fell into obscurity for the next forty years.
The principles and approach to reason analysis: The method derives from an attempt to address the variance between a question posed generally and the individual ways in which people answer “why” questions. In the first step we ask respondents a simple question about what reason led them to make the decision they did. This decision may be a serious life decision, such as deciding to marry their chosen partner, moving into a new home, visiting a psychiatrist, or, conversely, smaller individual decisions, such as buying a new car, or a particular cosmetic product. The fact is that people usually give just one reason for their decision. Data obtained this way cannot be processed by simply categorising respondents according to what type of response they gave to this one introductory question. Every respondent naturally has all sorts of reasons for their decision. What is important is that we can hear various types of responses to the introductory question from the same mouth. The reason for buying a new Citroen C3 in light blue may be a personal preference for this brand and the person’s old car has just broken down and the cost of repairs is rising. An important motive may be that the opportunity arises to write an old car off for scrap while there is also a sale on a particular new model. The person’s partner may have heard something complimentary said about a particular model of car. The brand, model, and its accessories may be recommended by the showroom salesperson while a TV commercial aired last Sunday also encouraged a person to buy. A combination of any or all these reasons is the only correct and full answer to the original question. The “reason analysis” method looks for and proposes a concrete “tree” of questions, an “accounting scheme”. The next step is preparation of the structured interview in which variant questions are posed about the “quality of a product”, both the product replaced and the newly bought one, how the product was evaluated in advertising, by the seller, by friends and acquaintances, and the “circumstances of the situation”. In the end, it is necessary to group the responses into classes and types according to which responses are most alike and where significant differences are between them. The method did not catch on mainly owing the demands it puts on researchers. In most survey type research it was replaced by the factorial approach, which examines the effect of individual causes (influential factors) jointly for an entire sample of individuals or other units.
The question for today is whether this method has a place in current social research. The paper presents examples of research situations which directly require individualised models of data collection and whose objective is to reveal and analyse further typologies of actors making certain decisions in a given situation and under the influence of individual factors.
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Web survey bibliography - 2009 (509)
- The Coverage Bias of Mobile Web Surveys Across European Countries ; 2009; Fuchs, M., Busse, B.
- Item non-response rates: a comparison of online and paper questionnaires ; 2009; Denscombe, M.
- Using mobile phones for survey research A comparison with fixed phones ; 2009; Vicente, P., Reis, E., Santos, R.
- A Comparison of Different Survey Periods in Online Surveys of Persons with Eating Disorders and Their...; 2009; Wesemann, D., Grunwald, A., Grunwald, M.
- A Comparison of Web-Based and Paper-Based Survey Methods Testing Assumptions of Survey Mode and Response...; 2009; Greenlaw, C., Brown-Welty, S.
- Interactivity in self-administered surveys. Influence on respondents' experience; 2009; Suarez Vazquez, A., Garcia Rodriguez, N., Alvarez, M. B.
- New techniques in online research: challenges for research ethics ; 2009; Eynon, R., Schroeder, M., Fry, J.
- Web based macroseismic survey: fast information exchange and elaboration of seismic intensity effects...; 2009; De Rubeis, V., Sbarra P., Sorrentino, D., Tosi, P.
- The Effects of the Initial Mode of Contact on the Response Rate and Data Quality in an Internet-Based...; 2009; Wiseman, F.
- Doing Research in the Real World; 2009; Gray, D. E.
- Conducting Mobile Surveys: A Hands-on Introduction to an Innovative Research Mode; 2009; Pferdekämper, T., Melcher, T.
- Internet-based surveys and urban design education: A community outreach graduate project in Redding,...; 2009; del Rio, V., Levi, D.
- Exploration of secondary students’ creativity by integrating web-based technology into an innovative...; 2009; Jang, S.-J.
- An experimental mixed mode design on a general population survey ; 2009; Eva, G.
- Declining Working Phone Rates Impact Sample Efficiency; 2009; Piekarski, L.
- Using Non-Probability Samples for Confusion Surveys - Mall Intercepts and the Internet; 2009; Ericksen, E. P.
- Using Debit Cards for Incentive Payments: Experiences of a Weekly Survey Study; 2009; Gatny, H. H., Couper, M. P., Axinn, W., Barber, J. S.
- Characteristics of Cell Phone Only, Listed, and Unlisted Telephone Households; 2009; Tarnai, J., Schultz, R., Moore, D.
- Cell Phone-Only Households: A Good Target for Internet Surveys?; 2009; Bates, N.
- Nonsampling Error Research in Practice; 2009; Brick, J. M., Kalton, G.
- Total Survey Error: Past, Present, Future; 2009; Groves, R. M.
- Envisioning the Survey Interview of the Future ; 2009; Conrad, F. G., Schober, M. F.
- Metrics for panel contribution: a non probabilistic platform; 2009; Gittelmam, S. H., Trimarchi, E.
- Are telephone Surveys a dying bread. How declining response rates can be explained and resolved; 2009; Degen, M., Obermüller, A., Schielicke, A.-M.
- Relation between values and topic of a survey in internet panel research; 2009; Vis, C., Marchand, M.
- The potential of mobile research: Implications for the future and the role of industry standards; 2009; Nelson, Li.
- Factors Contributing to Participation in Web‐based Surveys among Italian University Graduates; 2009; Cimini, C., Girottu, C., Gasperoni, G.
- Integration of different data collection techniques using the propensity score; 2009; Camillo, F., Conti, V., Ghiselli, S.
- Mode effects in Switzerland: non‐response and measurement error on the European Social Survey; 2009; Roberts, C.
- The mixing of survey modes: application to Laon web and face‐to‐face household travel survey...; 2009; Bayart, C., Bonnel, P.
- Reason analysis: an ambitious alternative for mixed‐mode survey design; 2009; Jerabek, H.
- An innovative open source strategy for the development of electronic questionnaires for statistical...; 2009; Degortes, M., Landriscina, M., Murgia, M.
- Response rates in multi actor surveys; 2009; Pasteels, I., Ponnet, K., Mortelmans, D.
- Unit non‐response in panel surveys: empirical finding from an experiment; 2009; Haunberger, S.
- Do cash incentives helps with RDD studies? Examination of results from a national and a statewide survey...; 2009; Miller, Y., Barger, K., Hearn, D.
- Are people sharing their mobile phones? Selection probabilities in cellular telephone surveys; 2009; Fuchs, M., Busse, B.
- Accuracy of Estimates in Access Panel based Surveys; 2009; Enderle, T., Münnich, R., Bruch, C.
- New developments in survey methodology for official statistics; 2009; Bethlehem, J.
- Survey cooperation: response to initial and follow-up requests - Recent experiences from the recruitment...; 2009; Bartsch, S., Engel, U., Schnabel, C., Vehre, H.
- Methodological Research for Longitudinal Surveys; 2009; Lynn, P.
- Using Mobile Phones to Administer a Working Memory Updating Task in a Survey - Cognitive Performance...; 2009; Schmiedek, F., Riediger, M., Lindenberger, U., Wagner, G. G.
- Accessibility of individuals for mobile phone surveys; 2009; Gabler, S., Häder, S.
- Mixed Modes and Measurement Error: Comparing face-to-face, telephone and web modes ; 2009; Hope, S., Nicolaas, G., Jaeckle, A., Lynn, P., Nandi, A., Campanelli, P.
- The Difficult but Essential Challenge of Designing Mixed-Mode Surveys; 2009; Dillman, D. A.
- Overcoming the challenges of measuring self-reported digital media use: Using feedback to increase data...; 2009
- The Internet survey ; 2009; Getka-Wilczynska, E.
- Modelling online survey participation among Italian university graduates ; 2009; Cimini, C., Girotti, C., Gasperoni, G.
- Coverage rates of mobile telephones and the Internet in Italy ; 2009; Fabbris, L., Gorelli, S.
- Imperfect frames and new data collection techniques ; 2009; Biffignandi, S.
- Web based survey methods workshop; 2009; Weiss, M.