The basics of Social Science Research Lecture 3 Dr. Jordy Gosselt Department of Communication Science

Today Research training: 3rd part Research methods and Data collection Making a questionnaire: Social Research Training Next meeting: Data analysis (making a data file in spss, calculating the reliability of your instrument, making variables, calculating Means/SD, comparing groups) Crime Science (M. Junger)  Book Chapter 5, 6, 7, 9, 10 [Bha2012] Bhattacherjee, A. (2012). Social Science Research. Principles, Methods, and Practices. Tampa, Florida: University of South Florida. PDF http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=1002&context=oa_textbooks

Now: Being a participant Third part of the study

Now: Making a questionnaire Social Science Research Training: Aim of the study?

Now: Making a questionnaire Study: The privacy paradox observed in normal behavior – the role of technical expertise and money Theory: Users claim to be highly concerned about their privacy (=attitude) Consumer’s choice to download an app is driven by (1) popularity; (2) usability; (3) price, without much hesitation (=actual behavior) Privacy paradox? For the largest part of lay people, technical processes that run in the background are not understandable: users make use of risky online services even if they have privacy or security concerns Knowledge gap? Users have the tendency not to buy an app even it costs very little money, free versions are preferred Monetary compensation?

Now: Making a questionnaire Study: The privacy paradox observed in normal behavior – the role of technical expertise and money Research showed that surfing the digital, online world and using mobile computing is characterized by a paradoxical behavior as users claim to be very concerned about their privacy, but at the same time, do download and install mobile applications and disclose private information seemingly without any hesitation. Quite often, the so-called privacy paradox was studied rather theoretical than focusing on actual behavior, leading to a well-documented measurement bias. Therefore, this study focusses on observing actual behavior in order to determine if the privacy paradox is indeed observable at users when actually interacting with their mobile phone. Furthermore, some scholars claim that the paradoxical behavior results from insufficient knowledge about technical aspects of (mobile) computing. Technical processes that run in the background are not understandable for lay users, eventually leading to a seemingly acceptance of certain risks accompanying online, disclosure behavior. In order to diminish the effect of lack of knowledge, we studied actual behavior among a technical experienced user group. As a third factor, literature on the privacy paradox discusses the phenomenon in the light of financial considerations. Quite often, users are not willing to pay for their privacy and therefore, trade personal data for services for free. Consequently, within the scope of this study, monetary compensation was provided in order to control for financial constraints.

Now: Making a questionnaire Study split into three parts Combination of survey, experiment and qualitative design Part 1: Evaluation of participants’ general smart phone knowledge and skills: survey Part 2: Measuring users’ information privacy concerns: experiment downloading app description of your downloading process short survey Part 3: Observing actual behavior/factors influencing download process: review + survey

Now: Making a questionnaire Part 1: Evaluation of participants’ general smart phone knowledge and skills: survey Participant information Informed consent Ask for demographical data: Participant information + informed consent = see CCS website Demographics: Ask as much as you need to carefully describe your sample but do not ask useless information

Now: Making a questionnaire Part 1: Evaluation of participants’ general smart phone knowledge and skills: survey Scale: General smartphone knowledge and skills (adapted from Androulidakis & Kandus, 2011, 2012) Scale smartphone knowledge and skills  no Cronbachs alpha available but quite a lare sample, more than 7000 participants Measurement of smartphones knowledge and skills  is there any influence of the level of knowledge on the decision making process to download an app? [And2011] Androulidakis, I., & Kandus, G. (2011). Mobile phone security awareness and practices of students in Budapest. Availability, Reliability and Security (ARES), The Sixth International Conference on Digital Telecommunications, Budapest, Hungary. https://www.google.nl/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwjambHKo8bSAhUGOhQKHVqxCZcQFghBMAA&url=https%3A%2F%2Fwww.thinkmind.org%2Fdownload.php%3Farticleid%3Dicdt_2011_1_40_20110&usg=AFQjCNHcKrrmozMQgJ2TQph6NlMU-mhXAQ&bvm=bv.148747831,d.d24

Now: Making a questionnaire Part 1: Evaluation of participants’ general smart phone knowledge and skills: survey Scale: Perceived usefulness (Chuah et al., 2016) Scale: Perceived ease of use (Yang, 2013) High Cronbach‘s alpha see high internal consistency reliability = items measure the constructs you aim to examine [Chu2016] Chuah, S. H-W., et al. (2016). Wearable technologies: The role of usefulness and visibility in smartwatch adoption. Computers in Human Behavior, 65, 276-284. http://www.philipprauschnabel.com/wp-content/uploads/2015/06/chuah-rauschnabel-et_al-2016-smartwatches-adoption-fashnology-CHB.pdf [Yan2013] Yang, H. C. (2013). Bon appétit for apps: Young American consumers’ acceptance of mobile applications. Journal of Computer Information Systems, 53(3), 85-96. https://www.researchgate.net/profile/Hongwei_Yang/publication/256585586_Bon_Appetit_for_Apps_Young_American_Consumers'_Acceptance_of_Mobile_Applications/links/00b7d523744cb27c2f000000.pdf

Now: Making a questionnaire Part 1: Evaluation of participants’ general smart phone knowledge and skills: survey Scale: Westin Privacy Index (see Kumaraguru & Cranor, 2005) Westin Privacy Index = General privacy sensitivity Does the general privacy sensitivity has an influence on the decision which app to download? [Kum2005] Kumaraguru, P. & Cranor L. F., 2005. Privacy indexes : a survey of Westin's studies. Technical report. Carnegie Mellon University: Pittsburgh, Pennsylvania. http://repository.cmu.edu/cgi/viewcontent.cgi?article=1857&context=isr

Now: Making a questionnaire Part 1: Evaluation of participants’ general smart phone knowledge and skills: survey Scale: Factors that play a role in the selection process of downloading an app (own scale) Verification of experiment: do you mention consistent factors that play a role in the selection process of downloading an app (comparison with review and which app you actually downloaded)

Now: Making a questionnaire Part 2: Measuring users’ information privacy concerns: experiment Evaluate different apps regarding user experience, 2 groups: Hedonic app (game) vs utilitarian app (to-do-list), choice based on a pre-test Mellow Meadows Tower Defense (0 permission but 1,55 Euro) New Eskimo Defense (2 permissions and 0,96 Euro) Astroid Defense Classic (4 permissions, for free) Safe the cave: Tower Defense (6 permissions, for free) Tower Defense: Infinite War (7 permissions, for free) And the same for group 2 (to-do-list) 10 euros to spend, use and write review Apps increasing in permissions that are not related to functionality (e.g. in-app purchases, identity, contact, photos, WIFI connection etc.)

Now: Making a questionnaire Part 2: Measuring users’ information privacy concerns: experiment Verification of experiment: do you mention consistent factors that play a role in the selection process of downloading an app (comparison with the questions from the first questionnaire) Explanation of downloading process = evaluating your decision making process: Did you followed a risk-benefit calculation or not e.g. do you mention different factors after having downloaded an app?

Now: Making a questionnaire Part 3: Observing actual behavior/factors influencing download process: review + survey Manipulation check (did they really download?) Which app did you download? Verification of app store: only include data from participants that have used Google Play Store Did you buy the app or not

Now: Making a questionnaire Part 3: Observing actual behavior/factors influencing download process: review + survey Review: What factors play a role? (do privacy related issues play a role?) Review: combination of qualitative and quantitative data: makes the reliability of your study stronger Do you mention different or additional factors in the review compared to the factors we asked for in the questionnaire?

Now: Making a questionnaire Part 3: Observing actual behavior/factors influencing download process: review + survey Scale: Factors influencing intention to install mobile applications (Harris et al., 2016) Perceived security Application characteristics Positive reputation Familiarity Desensitization Perceived risk Consumer trust Perceived benefits Intent to install This scale is more privacy related: If we ask this prior to the experiment you might be biased in terms of privacy and probably consider different factors while selecting an app [Har2016]. Harris, M. A., Brookshire, R., & Chin, A. G. (2016). Identifying factors influencing consumers’ intent to install mobile applications. International Journal of Information Management, 36, 441–450. http://s3.amazonaws.com/academia.edu.documents/43653825/Published_Paper.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1488971234&Signature=tLGViwEP%2BC1CSqe5JMzJf8qwr6k%3D&response-content-disposition=inline%3B%20filename%3DIdentifying_factors_influencing_consumer.pdf

Now: Making a questionnaire Part 3: Observing actual behavior/factors influencing download process: review + survey Scale: Mobile users’ information privacy concerns (Xu et al., 2012) Perceived surveillance Perceived intrusion Secondary use of personal information Prior Privacy Experience Behavioral Intention This scale is more privacy related: If we ask this prior to the experiment you might be biased in terms of privacy and probably consider different factors while selecting an app [Xu2012]. Xu, H., Gupta, S., Rosson, M. B., & Carroll, J. M. (2012). Measuring mobile users’ concerns for information privacy. Thirty Third International Conference on Information Systems, Orlando, 1-16. http://s3.amazonaws.com/academia.edu.documents/46247454/viewcontent.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1488971444&Signature=1nYuWzo9gnZ7nEVsR4kNMhwXk04%3D&response-content-disposition=inline%3B%20filename%3DMeasuring_Mobile_Users_Concerns_for_Info.pdf

To sum up Develop an experiment costs you time (and money) Do a pre-test if possible (validity!) Use existing scales (reliable!) Combination of research methods

Data Collection Type of data collection: qualitative vs. quantitative Expected amount of collected data Online questionnaire: Between 200 and 250 respondents Hard-copy questionnaire: Between 100 and 150 respondents Experimental designs: Depending on number of conditions (min 30 resp. per condition) Interviews: Between 15 and 20 participants Focus groups: Between 4 and 6 group sessions Content analysis: Depends on the research design Observations: Depends on the research design

Data Collection: Qualtrics Data collection procedure Online survey tool “Qualtrics” is available in cases of quantitative data collection (i.e. surveys, experiments, sorting tasks, heat maps...) Easy to use and distribute Direct export to SPSS

Your research proposal: Refine RQ(s) based on literature De/Refine your concept(s), construct(s) and variable(s) Determine how to examine your RQ(s) The research method must fit your RQ(s) Define your target group and sampling method Operationalize your chosen method Make or find scales / make experimental groups / make interview questions / etc. and think of validity and reliability Fill in the documents for the ethical committee Contact your student assistant if you have questions