Emotions and Performance in Virtual Worlds

Emotions and Performance in Virtual Worlds

EMOTIONSANDPERFORMANCEINVIRTUAL WORLDS An Empirical Study in the Presence of Missing Data Inauguraldissertation zur Erlangung des Doktorgrades der Wirtschafts- und Sozialwissenschaftlichen Fakultät der Universität zu Köln 2015 vorgelegt von Diplom-Informatikerin Sabrina Schiele aus Duisburg Referent: Prof. Dr. Detlef Schoder Koreferent: Prof. Dr. Claudia Loebbecke Datum der Promotion: 27.11.2015 EMOTIONSANDPERFORMANCEINVIRTUALWORLDS sabrina schiele Department of Information Systems and Information Management Faculty of Management, Economics and Social Sciences University of Cologne Sabrina Schiele: Emotions and Performance in Virtual Worlds, An Em- pirical Study in the Presence of Missing Data, 2015 To Gregor, who supported all of my decisions and always found the right words to keep me going in times of despair. ABSTRACT In this work, we first investigate characteristics of virtual worlds and de- termine important situational variables concerning virtual world usage. Moreover, we develop a model which relates individual differences of vir- tual world users, namely emotional and cognitive abilities, experiences with virtual worlds as a child, and the level of cognitive absorption per- ceived during virtual world use, to the users’ individual performance in virtual worlds. We further test our model with observed data from 4,048 study participants. Our results suggest that cognitive ability, childhood media experience, and cognitive absorption influence multiple facets of emotional capabilities, which in turn have a varyingly strong effect on virtual world performance among different groups. Notably, in the present study, the effect of emotional capabilities on performance was stronger for users which prefer virtual worlds that have more emotional content and require more social and strategic skills, particularly related to human behavior. Interestingly, while cognitive ability was positively related to various emotional capabilities, no evidence for a direct path between cognitive ability to performance could be identified. Similarly, cognitive absorption positively affected emotion perception, yet did not influence performance directly. Our findings make the case for aban- doning the traditional perspective on IS–which mainly relies on mere usage measures–and call for a more comprehensive understanding and clearer conceptualizations of human performance in psychometric stud- ies. Additionally, our study treats missing data (an inherent property of the data underlying our study), links their presence to theoretical and practical issues, and discusses implications. vii ZUSAMMENFASSUNG In der vorliegenden Arbeit untersuchen wir zunächst die charakteris- tischen Eigenschaften virtueller Welten und ergründen die besonderen Umstände ihrer Nutzung. Zudem entwickeln wir ein Modell, welches die Performanz von Nutzern virtueller Welten in Bezug setzt zu ihren emotionalen und kognitiven Fähigkeiten, ihrem Erfahrungshintergrund bezüglich virtueller Welten im Kindesalter, und dem Niveau an kogni- tiver Absorption, welches sie während der Nutzung von virtuellen Wel- ten erleben. Desweiteren testen wir unser Modell anhand von Daten, welche wir im Rahmen unserer Studie mit 4.408 Teilnehmern erhoben haben. Unsere Ergebnisse deuten darauf hin, dass kognitive Fähigkei- ten, Medienerfahrung in der Kindheit und kognitive Absorption die emotionalen Fähigkeiten von Nutzern virtueller Welten beeinflussen, und dass diese Wirkbeziehung wiederum die Performanz der Nutzer beeinflusst–jedoch je nach Nutzergruppe unterschiedlich stark. Insbeson- dere war die Wirkung von emotionalen Fähigkeiten auf Performanz in der vorliegenden Studie größer für diejenigen Nutzer, die virtuelle Wel- ten bevorzugen, welche mehr emotionale Inhalte enthalten und deren Aufgabenstellung mehr soziale Kompetenzen und strategisches Geschick erfordern, vor allem bezüglich menschlicher Verhaltensweisen. Interes- santerweise ließ sich kein direkter Zusammenhang zwischen Performanz und kognitiven Fähigkeiten nachweisen, auch wenn letztere einen wichti- gen Einfluss auf verschiedene emotionale Fähigkeiten zeigten. Ähnlich verhielt es sich mit kognitiver Absorption, welche sich zwar auf die Wahrnehmung von Emotionen auswirkte, jedoch nicht direkt auf Per- formanz. Als Fazit unserer Untersuchung schlagen wir vor, die tradi- tionelle Sicht auf Informationssysteme, welche hauptsächlich auf bloßen Nutzungsstatistiken fußt, aufzugeben, und im Hinblick auf zukünftige psychometrische Studien ein umfassenderes Verständnis und eine kla- rere Konzeptualisierung von menschlicher Performanz zu entwickeln. Zusätzlich befasst sich unsere Studie mit fehlenden Werten (welche un- seren Daten in größerem Umfang anhafteten), untersucht damit ver- bundene theoretische und praktische Problemstellungen und diskutiert Implikationen. viii LISTOFPUBLICATIONS In reverse chronological order; publications c-e appeared under my maiden name Steinfels. a. Weiss, T. & Schiele, S. (2013). Virtual worlds in competitive contexts: Analyzing eSports consumer needs. Electronic Markets, 23 (4), 307–316. doi:10.1007/s12525-013-0127-5. b. Schiele, S., Weiss, T., & Putzke, J. (2011). On inter-reality lit- eracy: Emotions as predictors of performance in virtual worlds [Research in progress]. In D. F. Galletta & T.-P. Liang (Eds.), Proceedings of the Thirty-Second International Conference on In- formation Systems (ICIS 2011). c. Floeck, F., Putzke, J., Steinfels, S., Fischbach, K., & Schoder, D. (2011). Imitation and quality of tags in social bookmarking sys- tems: Collective intelligence leading to folksonomies. In T. Basti- aens, U. Baumöl, & B. Krämer (Eds.), On collective intelligence (Vol. 76, pp. 75–91). Advances in Intelligent and Soft Computing. Berlin: Springer. doi:10.1007/978-3-642-14481-3_7. d. Oster, D., Schoder, D., Putzke, J., Fischbach, K., Gloor, P. A., & Steinfels, S. (2010). Tell your customers what they really want to hear: Improving the effectiveness of advertising campaigns in the financial sector using SNA on the Web2.0. In Proceedings of the 2010 International Sunbelt Social Network Conference (Sunbelt XXX). e. Oster, D., Steinfels, S., Putzke, J., Fischbach, K., Gloor, P. A., & Schoder, D. (2009). Measuring and enhancing advertising success using SNA on the Web. In Proceedings of the 2009 International Sunbelt Social Network Conference (Sunbelt XXIX). Some ideas and figures presented in the following have been developed and published prior to this thesis as part of the publications above; ref- erences to them will be made in the relevant text passages accordingly. ix CONTENTS 1 introduction 1 1.1 Subject Area I: Virtual Worlds 2 1.1.1 Motivation 2 1.1.2 Research Objective 5 1.2 Subject Area II: Missing Data 6 1.2.1 Motivation 6 1.2.2 Research Objective 8 1.3 Research Design and Structure of This Work 9 2 prior research, model, and study hypotheses 13 2.1 Previous Work and the Present Study 13 2.2 Virtual Worlds 15 2.2.1 Characteristic Features 17 2.2.2 Perspectives and Applications 19 2.2.3 Human Responses 27 2.3 Prior Media Theories 31 2.4 A Theory of Individual Differences 38 2.5 Research Model and Hypothesis Development 41 2.5.1 Emotions, Cognitive Ability, Cognitive Absorption, and IR Performance 45 2.5.2 Childhood Experience and IR Media Literacy 64 2.5.3 Other Effects and Differences Across Groups 68 3 context, constructs, measurements, and data 75 3.1 Context and Participants of the Study 75 3.2 Measurement Development 76 3.2.1 Relationships Between Factors and Indicators 77 3.2.2 Measurements for Constructs and Controls 78 3.2.3 Assessment of Content Validity 85 3.3 Pilot Studies and Pretests 86 3.3.1 Setup and Implementation 86 3.3.2 Purification and Refinement of Measures 86 3.4 Actual Data Collection 87 3.4.1 Means of Gathering Data 87 3.4.2 Exclusion of Suspended Participants 91 3.4.3 Merging the Data Sources 91 3.5 Outline of Analysis Activities 91 4 data screening, analysis, and results 95 4.1 Preliminary Examination and Omission of Data 95 4.2 Specifics of Participants and Data 99 4.2.1 Demographic Characteristics 99 xi xii contents 4.2.2 Univariate Outlier Inspection 101 4.2.3 Distributions and Missing Data 102 4.3 Missing Data Treatment for Exploratory Analysis 107 4.4 Exploring Factor Structures and Reliability 111 4.5 Missing Data Treatment for Hypothesis Testing 117 4.6 Verifying Factor Structures and Reliability 118 4.6.1 Choice of Estimation Method and Fit Measures 118 4.6.2 Reliability, Fit, Sample Size, and Statistical Power 121 4.7 Hypotheses Testing 129 5 discussion 143 5.1 Interpretation of Results 143 5.2 Possible Limitations 146 5.3 Missing Data, Distributions, and Other Issues Related to Conducting Empirical Studies 152 6 conclusion 189 6.1 Contribution and Implications 189 6.2 Directions for Future Research 192 appendices 197 a items and scales 197 a.1 Wordings, Item Sources, and Scale Formation 197 a.1.1 Primary Constructs 197 a.1.2 Secondary Constructs 206 a.1.3 Control Items 212 a.1.4 Preferences, Motives, Suggestions 212 a.1.5 Demographic Items 214 a.1.6 Self-Disclosure and Comment 214 a.2 Items in Order of Appearance 215 b distribution examination 219 b.1 Skewness and Kurtosis 219 b.2 Distribution Diagrams 221 c missing data treatment 231 c.1 Extent of Missings 231 c.2 Missing Patterns 233 c.3 Data Base for EM and FIML Estimation 235 d results of analyses 237 d.1 Exploratory Factor Analyses 237 d.1.1 Suitability Tests and Factor Structures 237 d.1.2 Preliminary Reliability Analyses 245 d.1.3 Simultaneous Exploratory Factor Analysis 255 contents xiii d.2 Confirmatory Factor Analyses 265

View Full Text

Details

  • File Type
    pdf
  • Upload Time
    -
  • Content Languages
    English
  • Upload User
    Anonymous/Not logged-in
  • File Pages
    360 Page
  • File Size
    -

Download

Channel Download Status
Express Download Enable

Copyright

We respect the copyrights and intellectual property rights of all users. All uploaded documents are either original works of the uploader or authorized works of the rightful owners.

  • Not to be reproduced or distributed without explicit permission.
  • Not used for commercial purposes outside of approved use cases.
  • Not used to infringe on the rights of the original creators.
  • If you believe any content infringes your copyright, please contact us immediately.

Support

For help with questions, suggestions, or problems, please contact us