18-20 March 2015
Cologne University of Applied Sciences, Germany
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B 7: Technology Acceptance
The reciprocity effect: how corporate transparency leads to voluntary sharing of personal data
University of Amsterdam
Relevance: Companies increasingly collect large amounts of personal consumer data from a multitude of sources, allowing marketers to target consumers with more precision than ever before. In the upcoming era of the “internet of things” and the “quantified self”, data-driven solutions will dominate the marketing landscape. Although effective use of personal data ensures that consumers are exposed to more relevant marketing content, consumers often react against the collection of their data. This reluctance is often attributed to a lack of understanding on when and why data is being collected, the perceived lack of control over the collection and use of the data, and privacy concerns. Leading scholars and practitioners agree that retaining consumer trust will become the key challenge for the effective use of personal data for marketing purposes. In the current study, we address this issue and investigate whether corporate transparency can trigger a process of reciprocity ultimately leading to an increased willingness to share personal data.
Method: We conduct an online experiment in which we ask 200 participants to share personal data they provided in the context of a study on shopping behavior and preferences with a leading food producer. To test the proposed reciprocity effect, we compare a condition (1) in which the firm proactively discloses information on its subpar performance with regards to sustainability to a condition (2) in which the firm explains how exactly it uses personal data and a control condition (3). To distinguish between the effect of mere information availability and the effect of corporate transparency, we added two conditions (4 and 5) in which information from condition 1 and 2 is provided by the researcher rather than the firm.
Results: Data is currently being collected.
Added Value: This study demonstrates if and how corporate transparency can trigger consumer reciprocity ultimately leading to voluntary sharing of personal data. If the results support our propositions, the study contributes to the debate on the collection and use of personal data by showing that by being transparent, firms can collect personal data and at the same time build rather than undermine consumer trust.
Evaluation of Technology Acceptance of Data glasses based on an application for Smart Ski Goggles
evolaris next level, Austria
Research question: User-experience as well as the perception of a technology are playing a decisive part in the decision to adopt a new technology. Data glasses are becoming more and more popular and increasingly catch the attention of many researchers, developers and also the general public. In our study we aimed to evaluate the technology acceptance of a prototypical data glass application in the leisure and amusement sector: an application for smart ski goggles providing information in a built-in display for skiers and snowboarders on the slope.
Method & Data: We established a User Experience (UX) Model, based on the Technology Acceptance Model (TAM) by Davis. The model consists of the factors “Personal Value”, “Social Value”, “Task Value”, “Satisfaction”, “Attitude” and “Intention to Use”. After defining the target group based on an online survey representative for Austria (n=1000), a user experience test was carried out in an Austrian skiing region in April 2014 to capture the users’ perceptions on-site. In addition to testing the smart ski goggles and giving in-situ feedback through the goggles’ control element, the 54 respondents filled in an ex-ante and ex-post questionnaire designed to collect quantitative and qualitative data. Furthermore, real-time context data was tracked via GPS-sensors and a backend system. For the analysis we used PLS (Partial Least Squares) to test the model.
Results: According to the results, the “Personal Value” is the most important factor and neither “Task” nor “Social Value” have an impact on “Satisfaction” and “Intention to Use”. The quality criteria clearly show that the model is suitable to describe the user experience which is also mirrored by a high coefficient of determination regarding the factor “satisfaction”.
Added Value: The results provide insights into the specific values that influence the satisfaction with and usage intention of the new data glass technology applied in the leisure and amusement sector. The UX model can be applied by the scientific community and expanded according to the type of technology being reviewed. Moreover, the results deliver useful information for researchers regarding general needs of the target group of data glasses applications in the above mentioned sectors.
Debunking the Diagnosis Internet Gaming Disorder: Motivational differences between high engagement and addiction in a German sample of World of Warcraft players
1Sigmund Freud University, Austria; 2Vanderbilt University, Nashville/Tennessee
Relevance & Research Question:
The DSM-5 introduced Internet Gaming Disorder (IGD) as a condition needing more research. Proposed criteria include amongst others tolerance, preoccupation, deceiving, or continued excess despite psychosocial problems. However, some studies suggest differences between addiction (criteria like conflict, withdrawal symptoms, relapse and reinstatement and behavioral salience) and engagement (criteria like cognitive salience, tolerance and euphoria). Other studies highlight additional motivational factors as especially relevant in gaming such as immersion. The research questions of the presented study were if a difference between engagement and addiction is visible looking at motivational aspects and if there are gender related differences regarding motivation.
Methods & Data:
Using an online-based questionnaire, we surveyed 676 adult (18+) volunteers (mean age 23.26 years; 84.9% male) from German speaking parts of the world (Germany, Austria, Switzerland). In addition to demographic questions an adapted version of the “Asheron’s call” questionnaire (which covers six addiction criteria including salience, euphoria, tolerance) and the Gaming Motivation Scale (Yee, 2006) were used to answer the research questions. According to existing criteria only 127 of the participants could be grouped in engaged versus addicted. Statistical analyses for hypotheses testing included MANOVA, ANOVAs between groups and t-tests for gender differences.
Significant results (F(3, 123)=57.950; p<.001) show highly relevant differences between the groups regarding all motivational aspects. ANOVAs reveal that the relevant motivational factors to differentiate between engaged and addicted gamers are achievement (F(1, 125)=165,477; p<.001) and immersion (F(1, 125)=51,332; p<.001). Achievement (t(674)=-4.027; p<.001) and immersion (t(674)=3.602; p<.001) values are in addition significantly higher in male participants and women show higher values regarding social motivation (t(674)=2.559; p=.011).
Motivational aspects obviously play a huge role to differentiate between problem behavior (addiction) and engaged gaming. In addition gender differences need to be addressed even more carefully. Women tend to be less interested in achievements from a motivational point of view and immersion as motivational factor is also not as relevant as for men, but the social aspect seems to be the typical “female” motive. Gender sensitive models have to include that aspect in the future.
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