This dissertation studies the antecedents and consequences of the flow experience in online retailing environments. Flow is the enjoyable and engrossing experience that people feel when acting with total involvement. A review of previous studies suggests that applying the notion of flow to understand the online consumer experience is a promising but underdeveloped field with several conceptual and methodological issues. This dissertation attempts to contribute to our understanding of flow in online shopping in three ways. First, a three-part validity study was carried out using different approaches to construct validity and involving two sets of two flow measures: the Flow State Scale (FSS, Jackson and Marsh 1996) and the Internet Flow Scale (IFS). The first study related flow to behavioral criteria in online shopping. The second conducted a traditional construct validity study in which we developed and tested a “nomological network” of relationships between flow measures and other logically-related constructs. This study also included a Multitrait-Multimethod validity study. The third was a factorial validity study of the flow construct. These studies provided evidence of construct validity for flow and suggested that the FSS had advantages over the IFS in terms of validity. Second, this dissertation tested a comprehensive model of flow that included the underlying dimensions of flow, the mediating effects of perceived challenge and skill on flow, and antecedents and consequences of flow. Consequences of flow include perceived usefulness, affective responses to the site, and intentions to revisit and purchase. Overall, results based on data collected by a controlled experiment supported our model, suggesting that flow is a second-order construct and positively related to outcome variables. Thirdly, we studied the effect of Web site complexity on flow. Perceived site complexity was found to effect flow negatively. Investigating the effects of it on inducing flow in online shopping may eventually lead us to guidelines for improving the shopping experience by designing more capable Web sites.

Yes / Flow experience has been widely investigated in experiential activities such as sports, the performing arts, gaming and Internet usage. Most studies focus on the positive aspects of flow experience and its effect on performance. In stark contrast, gambling research focusing on the negative side of addiction lacks an in-depth investigation of gamblers’ (positive) flow encounters. This separation of research lines seems out of place given that recent research indicates connections between flow and addiction. Joining both constructs in a causal effects model helps to gain a better understanding of their relationship and its contingencies. This paper empirically investigates whether and how it is possible to observe a “Janus face” of flow with its various sub-dimensions in online gambling. Empirical data was collected from 500 online gamblers by applying a structured questionnaire with established scales. The data was analyzed with a confirmatory factor analysis and a double-hurdle model to separate casual gamblers who are unsusceptible to any addiction issues from gamblers affected by initiatory addiction issues. The findings indicate that online gambling addiction is negatively influenced by two sub-dimensions of flow experience, namely a sense of control and concentration on the task at hand, while enhanced by a transformation of time and autotelic experience.

Title: Autotelic experiences in overcoming ropes obstacles. Resource: The purpose of this study was to determine whether and to what extent people experience flow in overcoming ropes obstacles and how their flow is affected by their previous experiences from other sports. Methods: Polling had one hundred and fifty respondents who were regular visitors to the rope sling. Polling was carried out immediately after crossing the rope obstacles using a questionnaire-Flow Kurzskala (FCS). The data obtained were divided into individual files, depending on the hypotheses posed. Using the Student's distribution, it was determined if there is a statistically significant difference in mean values of the individual files and then the related hypothesis was accepted. Results: Carried out testing showed a statistically significant difference in the flow experience in the rope obstacles park in a group of adolescents and adults. Also showed a difference between sportsmen who are engaged in everyday life competition sports and sports oriented on performance, unlike sportsmen doing collective and individual sports where a statistically significant difference in mean values did not show. The assumption of achieving different values in flow of men and women was not proved, as well as the influence of previous...

Was bringt intensive Computernutzer dazu, ihre Freizeit am Rechner zu verbringen, und gibt es hierbei Unterschiede zwischen verschiedenen Nutzertypen? N = 271 Personen nahmen an einer online Befragung zu Anreizen freizeitlicher Computernutzung teil. Durch ausgewählte Internetverteiler waren gezielt besonders engagierte Computernutzer angesprochen worden (M = 3,9 Freizeitstunden am Rechner pro Tag). Für diese Nutzer fanden sich (in der Reihenfolge ihres Gewichtes) folgende Anreizfaktoren: Zugehörigkeit/Gemeinschaft; Kompetenzerleben; Vielseitigkeit/Nutzen; Langeweilevermeidung; rebellische Illegalitätstendenz. Gruppiert nach ihren bevorzugten Nutzungsweisen fanden sich drei Nutzertypen: Zweckorientierte Nutzer (58%), Hacker (= Eindringen in fremde Systeme ohne Schädigungsabsicht, 22%) und Cracker (Eindringen mit Schädigungsabsicht, 20%). Diese Nutzertypen unterschieden sich deutlich in ihrem Anreizprofil. Hacking und Cracking, nicht aber zweckorientierte Nutzungsweisen waren korreliert mit Flow-Erleben und positiver Aktivierung am Rechner. Die Ergebnisse sind nicht repräsentativ für alle Freizeitnutzer. Sie beziehen sich auf eine gezielt rekrutierte Stichprobe besonders engagierter Computernutzer, die über spezifische Netzwerke (z. B. relevante Fachschaften, Chaos Computer Club) erreichbar sind.

Bei N = 101 Arbeitnehmern verschiedener Berufe wurden mit der Experience Sampling Method (ESM) eine Woche lang Daten zum Flow-Erleben, zu Glück/Zufriedenheit und zur Zielausrichtung laufender Aktivitäten erhoben (N = 4603 Messungen). Die Daten wurden mit GLMM-Analysen ausgewertet. Auch bei der jetzt vollständigen Erfassung aller Flow-Komponenten mit der FKS bestätigte sich das „Paradoxon der Arbeit“, wonach während der Arbeit höhere Flow-Werte, aber niedrigere Werte für Glück/Zufriedenheit auftreten als jeweils in der Freizeit. Während der Arbeit waren Aktivitäten häufiger auf die Erreichung von Zielen ausgerichtet als während der Freizeit. Die Zielausrichtung wirkte auf Flow vs. Glück/Zufriedenheit signifikant verschieden. Während der Arbeit hat die Zielausrichtung auf Flow einen stark positiven Effekt, auf Glück/Zufriedenheit jedoch nicht. Im Freizeitbereich war der Effekt von Zielausrichtung auf Glück/Zufriedenheit sogar negativ. Das „Paradoxon der Arbeit“ lässt sich partiell als Effekt der Zielausrichtung verstehen. / For a week, data of N =101 employees with different professions was collected with the Experience Sampling Method (N = 4603 measurements). These data included flow-experience, happiness/satisfaction and goal adjustment of current activities. The data were analysed with GLMM. Flow-experience was measured with all components (FKS) and they confirmed the "paradox of work" (i.e., flow-scores are higher during work but scores for happiness/satisfaction are higher during spare time). During work, participants activities were more often directed towards reaching a goal. The effects of goal adjustment on flow vs. happiness/satisfaction differed significantly. During work goal adjustment had a strong positive effect on flow, but not on happiness/satisfaction. During leisure time goal adjustment had even a negative effect on happiness/satisfaction but a positive on flow. The "paradox of work" could be partially attributed to the stronger goal adjustment during work.

Im kognitiv-motivationalen Prozessmodell des Lernens wird angenommen, dass der Lernerfolg von der Qualität und der Dauer ausgeführter Lernaktivitäten, aber auch vom Funktionszustand des Lerners während der Lernphase abhängt. Es wird vermutet, dass eine von mehreren Variablen des Funktionszustandes der Flow-Zustand während des Lernens ist. In einer Untersuchung in universitären Fremdsprachenkursen zeigte sich in der Tat, dass Flow-Erleben während des Unterrichts die späteren Lernleistungen auch dann vorhersagt, wenn der Leistungseffekt relevanter Lernkompetenzvariablen vorweg berücksichtigt wird. Gemäß dem kognitiv-motivationalen Prozessmodell wird Flow-Erleben seinerseits über die aktuelle Motivation vor der Lernphase vorhergesagt, wobei die wiederum von einer allgemeineren Motivationsvariablen zu Semesterbeginn abhängt. Diese Struktur wurde in einer zweiten Untersuchung repliziert und zwar an Studenten im Verlauf ihrer Statistikausbildung im Fach Psychologie. Beide Ergebnisse sprechen dafür, dass Flow- Erleben während des Lernens eine leistungsrelevante Variable des Funktionszustandes beim Lernen ist, die sich in ihrer Beziehungsstruktur erwartungsgemäß in das kognitivmotivationale Prozessmodell einpassen lässt. / According to the cognitive-motivational model of learning, achievement depends on the quality and quantity of learning activities as well as on the functional state during learning. We assumed that the flow-experience is one indicator of the functional state. In a study conducted in foreign language courses we demonstrated that flow-experience predicts achievement, even when controlled for ability. In accordance with the cognitive-motivational model, flow-experience was predicted by the actual motivational state, which was itself dependent on students' motivation at the beginning of the semester. This pattern of relationships was replicated in a second study conducted in a course on elementary statistics for psychology students. The results of both studies indicate that flow-experience is an indicator of the functional state relevant for learning outcome. The general pattern of the results also fits nicely with the proposed relationships of the cognitive-motivational model of learning.

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The impact of the learner flow experience (LFE) on learning outcomes has been studied for over four decades in a variety of formal and informal instructional settings, including the digital game-based learning (DGBL) environment. Since 2011, the examination of the LFE and its impact on learning outcomes has expanded to computer science-related disciplines, as well as other research communities. During this expansion, an increase in the number and definitions of terms related to the LFE has occurred. Likewise, the number of assessment tools used to capture evidence of the flow experience in learners playing DGBLs has increased. This integrative review examined 66 peer-reviewed articles published between 2011 and 2021, which reported the results of empirical studies seeking to identify and measure the learner experience of flow during DGBL gameplay. More specifically, this study sought to understand how the LFE and its dimensions were conceptualized and assessed in those articles. To do this, the relevant data was extracted from the articles, and, via iterative processes of analyses, the information related to the conceptualization and assessment of the LFE during DGBL game play was identified, analyzed, and organized. The study's findings demonstrated that the number of terms used to describe the LFE dimensions increased during the time period studied, and that there is seemingly little consensus with regard to the conceptualization of the terms or their use in the assessment instruments applied. However, this study also revealed that these terms and the methods by which they were assessed may be examined within the theoretical structure defined by Csikszentmihalyi in 1990, in which he codified nine dimensions to explain the flow experience. These dimensions are: (1) balance of skills and challenge; (2) clear goals; (3) swift, unambiguous feedback; (4) merging of action and awareness; (5) concentration on the task at hand; (6) sense of control; (7) distorted sense of time; (8) loss of ego; and (9) autotelic experience. Organizing the research question findings within this structure enabled the identification of themes of and synonyms for the nine flow dimensions with the addition of the construct flow experience. To encourage future researchers' ability to interpret, compare, and contrast studies of the experience of the LFE during gameplay in the DGBL learning environment, a set of researcher guides was developed following an iterative process of comparisons and analysis across the research questions' findings. These guides present a description of each of the flow dimensions, associated key words and/or key phrases, synonyms for the dimension, and statements or questions used to solicit information from learners regarding their experience of each of the flow dimensions, organized by theorist. The goal for these researcher guides is that they will be used as references for future studies of the impact of flow on learning outcomes for DGBL players through providing a common vocabulary and set of assessment items. They also may help encourage and enhance collaboration between instructional designers and DGBL game designers in creating effective DGBLs that increase learning or user engagement and enjoyment through the fostering of conditions that enable the LFE phenomenon. / Doctor of Philosophy / Many adults recall losing track of time during play as children. Achieving the feeling of being in "the zone" during play or competition was anticipated and relished. As adults, the desire to recapture that state of being blissfully unaware of time, focused only in the moment and free from any concerns frequently drives sales of sporting equipment, leisure activities, and electronically-based games. This experience, called the flow state, can happen when engaging in a wide variety of activities, including learning. Research has shown that if a student reaches the flow state while learning, they learn more and derive greater satisfaction throughout the learning process. This has also been found to be the case for students engaging with digital game-based learning (DGBL) applications. But how do we know if a DGBL player has entered the flow state? Researchers in the fields of instructional design and game design have asked and sought to answer this very question. This study examined the works of these researchers to understand specifically how the flow state was defined and measured in their studies. As a result of this study, researcher guides were created to explain how the learner flow experience and its component dimensions are identified and described, as well as to provide questions that could be posed to students to help evaluate if the flow state was achieved during DGBL gameplay. The goal for these guides is that they will be used as references for future studies of the impact of flow on learning outcomes for DGBL players through providing a common vocabulary and set of assessment items. They also may help encourage and enhance collaboration between instructional designers and DGBL game designers to create effective, enjoyable games for learning.

Berichtet wird über eine Möglichkeit, Flow-Erleben unter experimentell kontrollierten Bedingungen systematisch zu variieren. Dabei werden die Tätigkeit (das Computerspiel <i>Roboguard</i>) und die Situationsbedingungen konstant gehalten. Variiert wird lediglich die Schwierigkeitsstufe, auf der gespielt wird. Als abhängiges Maß wurde die Flow-Kurzskala (FKS, Rheinberg, Vollmeyer & Engeser, 2002) verwandt. Es zeigten sich die vorhergesagten kurvilinearen Beziehungen zwischen Anforderungsstufe und Flow mit Effektstärken um 1 und größer. Zusammenhänge zwischen habitueller Zielorientierung (Hayamizu & Weiner, 1991) und Flow zeigten sich nur bei den flow-auslösenden Schwierigkeitsstufen. Es gab keine negative Beziehung zwischen Zielorientierung und Flow, vielmehr korrelierten sowohl die learning- als auch die performance goal orientation positiv mit der Flowkomponente Absorbiertheit. Aus diesem Befund wird eine Arbeitshypothese zur Beziehung von Motivation und Flow hergeleitet, wonach unter optimalen Bedingungen Besonderheiten der Initialmotivation vielleicht dann keine Rolle mehr spielen, wenn die Person erst einmal im Flow-Zustand ist. / The study presents a technique how to manipulate flow-experience via the computer game <i>Roboguard</i>. Under experimentally controlled conditions all parameters of the game and the situation were kept constant except the difficulty level the participants had to play on. Flow was assessed with the Flow Short Scale (FKS, Rheinberg et al., 2002). As predicted we received the highest Flow score on the medium/optimal level in comparison with an easy and difficult level (d > 1.0). We could not confirm the predicted negative effect of approval seeking goals (AGT, Hayamizu & Weiner, 1991) on Flow experience. Instead all three AGT subscales correlated positively with the FKS-subscale absorption. Perhaps qualitative differences in initial motivation loose their influence if participants experience Flow under optimal conditions.

In the theoretical part there are approximated ballroom and latin dancing, theory of motives, achievement motivation, causal attributions, emotions and the flow-experience. In the second part are formulated hypotheses and described the methods of work. In the final part of the text there are explicated research data, discussed hypotheses and summarized the results. The full computer output is included in the annexes.