A Grounded Theory of Online Shopping Flow - Taylor & Francis Online

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A Grounded Theory of Online Shopping Flow Rolf Mahnke, Alexander Benlian, and Thomas Hess ABSTRACT: With the increasing number of websites that have found their way into our daily lives, substantial resources are invested in enhancing user experience beyond mere functionality. Optimizing flow—the psychological state of deep focus while conducting a fluent activity—seems a promising approach, resulting in a win–win situation for both users and website operators. Flow has been found to result in “optimal” user experience leading to intrinsically motivated behavior, engagement, and loyalty. However, to date, there is little concrete knowledge of or advice on how to design a website for flow. This study develops a grounded theory of flow experiences in the context of online shopping, and sheds light on the theoretical relationships between concrete realizable website design options, corresponding latent constructs, and flow experience. Based on our findings we derive theoretical as well as practical implications for understanding and designing flow experience on the web. KEY WORDS AND PHRASES: Flow theory, digital service innovation, user experience, human––computer interaction, e-tail, grounded theory. The point that information systems’ use can be a source of pleasure has been increasingly emphasized for several decades by researchers in the field of information systems research and human–computer interaction (e.g., [7, 48, 81]). In this context, pleasure or enjoyment addresses “the extent to which the activity of using the computer is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated” [18, p. 1113]. Similarly, motivations to engage in information search that include both utilitarian and hedonic dimensions provide an expanded view on e-commerce that has been increasingly examined in the past decade (e.g., [5, 12, 65]). In the same vein, the theory of flow has been proposed by various authors as a useful framework to explain user behavior (e.g., [15, 22, 23, 24, 31, 37, 75, 82]). Flow describes the state of “self reflection-free immersion in a continual activity” [70, p. 380] in which time, place, and an activity’s original external aim are forgotten and the individual is totally absorbed in the activity [14, 71]. Flow experiences are related to pleasant, intrinsically motivated activities that are usually experienced as very positive [14, 54]. Examining flow experiences on the Web seems to be particularly promising, since numerous positive side effects are expected if users surf the Web or a website in a state of flow. The experience of flow is positively related to the affect toward websites [59, 60], the attitude toward websites [74], satisfaction with websites [19, 47], the evaluation of websites [57], and e-learning success [29]. Flow is associated with a website’s usefulness and ease of use [2, 30, 34, 74], as well as the intention to use a website [74]. Furthermore, the flow concept has been applied by various authors to explain loyalty to websites [30, 32, 41, 42, 47, 51, 52, 57, 76], starting with Hoffman and Novak [31, p. 51], who postulate flow as “the ‘glue’ holding the consumer in the hypermedia Computer Mediated Environment.” Assuming that these positive side effects International Journal of Electronic Commerce / Spring 2015, Vol. 19, No. 3, pp. 54–89. Copyright © 2015 Taylor & Francis Group, LLC. ISSN 1086–4415 (print) / ISSN 1557–9301 (online) DOI: 10.1080/10864415.2015.1000222

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are achieved if users surf the Web in a state of flow, resulting in a win–win situation for users and website operators, it seems to be particularly relevant to design websites in a manner that enhances users’ flow experiences. Since prior work suggests that flow on the Web is most likely to occur during informationseeking activities [11], and more specifically, likely during the product information process while shopping [53], it seems to be particularly necessary to improve online shopping experience and its outcomes by enhancing flow, developing concrete digital service innovations [3, 61]. In the literature, however, the determinants of flow experience examined to date have not be suitable to provide concrete practical advice on how to design websites for flow. On the one hand, this might be the result of the predominantly quantitative orientation of existing studies, leading to a high degree of abstraction. Examples of examined determinants include the ease of use of a website [8, 33, 77, 80], the feeling of control while using a website [10, 22, 23, 24, 36, 38, 51] or the vividness of websites [31, 50, 64]. As a result, while it can be shown that certain examined latent constructs significantly influence the experience of flow while using information systems, the link between concrete design options, these latent constructs, and flow is still missing. An approach that seeks to provide this link must account for intersubjective variance as well as the specific website context. The subjective perception of equalized demands and skills, which is one of the most widespread latent flow conditions [14, 15], may serve as an example: what constitutes challenging website attributes differs between individuals, since subjects may show different levels of familiarity regarding diverse website functions and might prefer different challenge types and levels (due to different achievement motivation levels and drivers) in different usage contexts. To shed light on a variety of these complex theoretical relationships, a holistic view of flow experience on the Web is needed. Hence, an appropriate approach to get an in-depth view of design mechanisms leading to flow seems to be a qualitative one, since it can account for specific individuals and the context of the flow activities. Whereas some existing qualitative approaches to flow on the Web have provided valuable preliminary steps, the authors have either generically explored “the Web” as a whole [10, 11, 58, 67] or focused on broad activities such as information-seeking on the Web surfing across multiple websites [62, 63], and did not focus on design issues. Therefore, as a next step to get an in-depth view of design principles for flow, it seems reasonable to focus on a specific website type on which subjects repeatedly experience flow. Moreover, a method to flow-optimize websites should go beyond the mere diagnosis of flow problems, and offer concrete techniques on how to find innovative design solutions to enhance flow. In summary, even though the flow construct and its positive effects have been widely studied in the online context, we still know little about how flow emerges on websites and what design aspects are pertinent. The objective of this study is to address these gaps guided by the following research questions: (1) What design aspects of online shopping platforms lead to flow? and (2) What theoretical mechanisms underlie these relationships?

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Since prior work suggests that flow on the Web is likely to occur during information-seeking activities while shopping [53], we focus on shopping platforms where a variety of information is provided in diverse forms. Therefore, the present research seeks (a) to find website-specific concrete design options for shopping platforms that are realizable by website operators, as well as latent perceptual, affective, and cognitive constructs related to the experience of flow, and (b) to shed light on the theoretical relationships between the explored design options, corresponding latent constructs, and the flow experience. Moreover, we derive concrete recommendations about how to redesign shopping platforms to enhance users’ experience from the perspective of flow and we propose a procedure for implementing and evaluating these changes. In doing so, this paper makes a number of substantively original theoretical and practical contributions to the information systems flow literature. First, we present an empirically developed grounded theory of online shopping flow that offers an in-depth view of flow mechanisms encompassing concrete design aspects. Second, the paper provides an empirically grounded basis for further theorizing about flow experience on the Web, providing new theoretical propositions that can be tested in future flow research. Third, our work generates concrete design recommendations for operators of online shopping platforms that are required to enhance users’ flow experiences. Fourth, the proposed approach can be applied to a variety of additional website types to derive further theoretical as well as practical implications.

Theoretical Background The flow state was first described by Csikszentmihalyi [14] on the basis of qualitative research. During a large number of interviews with people who performed activities that do not directly lead to extrinsic rewards (e.g., money, reputation), Csikszentmihalyi repeatedly found a state of mind that he called “flow experience.” The occurrence of flow is not exclusive to some unique types of activities, but is a general phenomenon. Humans can experience flow when carrying out virtually any activity. Flow can be experienced in various degrees of intensity, from micro-flow to deep flow [14]. Equally, the experience of flow is not limited only to intrinsically motivated activities. Over three decades of qualitative and quantitative flow research in psychology, the single components of flow have proved to be remarkably stable and consistent. Based on the findings of Csikszentmihalyi, Rheinberg [68] differentiates six conclusive components of the flow experience (see Table 1). According to these components, the flow state is characterized by two separate factors that can be well interpreted: (1) deep concentration on the task (absorption) (blocking out irrelevant stimuli, leading to several phenomena such as time dissociation, loss of self-reflection, and loss of self-consciousness), and (2) being in fluent action (fluency), where knowledge of what to do in each step leads to a continual activity, which as a whole seems guided by an inner logic (i.e., thoughts and movements occur automatically). Evidence of the two-factor structure of flow is provided in

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Table 1. Components of Flow. Components of flow Balance between perception of skills and task demands Clear, unambiguous demands and feedback to action Activity seems to be guided by an inner logic High degree of concentration on the activity owing to undivided attention to a limited stimulus field Change in one’s experience of time Self and the activity are not separated; loss of self-consciousness

different contexts, such as university education [72], marathon running [79], treadmill running [66], computer gaming [71], and graffiti spraying [72]. Moreover, different manifestations of both factors in different flow activities seem to be possible (e.g., highest fluency values during sport activities, highest absorption values during sexual intercourse/intimacy) [72]. Hence, a separate interpretation of both factors seems reasonable so as to examine the internal structure of the flow phenomenon. When the experience is described through its components, respondents almost invariably indicate that they know this state—for instance, 87 percent in the context of U.S. flow research [16]. In the information systems (IS) context, for instance, between 40 percent and 50 percent of surveyed Web users report that they have already had a distinct flow experience [11, 59, 67], and current research shows that flow is a general phenomenon experienced during a large variety of Internet activities [53].

Method An appropriate approach to gaining an in-depth view of design mechanisms that lead to flow is a qualitative one, since it can account for specific individuals as well as the flow activities’ context. However, common qualitative methods of user experience testing can substantially affect the phenomenon to be examined. Thinking-aloud techniques, for instance, are supposed to profoundly affect flow experience quality, since the test person must split his or her attention between the experience and the continuous verbalization of thoughts. Equally, an alternating sequence of observation and surveying—commonly applied in user testing—does not seem useful in the flow context. The mere expectation that test persons will be disturbed during their immersive experience is supposed to hinder flow. Furthermore, the examination of predefined (extrinsically motivated) tasks might hinder or at least influence the quality of the examined flow experiences, and standardized experience questionnaires (e.g., a user experience questionnaire [45]) are not applicable. To address these issues, data analysis and collection in this study are based on the grounded theory approach combined with retrospective individual problem-centered interviews. Grounded theory is an

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inductive investigative process in which theory is formulated by iteratively gathering, analyzing, and testing data. The emerging theory and data collection are incrementally refined based on previously gathered data and tested using actual data. In the study at hand, this process is used to iteratively generate a visual model of cause–effect relationships that relate concrete design options to the flow experience (if applicable via latent constructs, mediators, and moderators). Since grounded theory was first described by Glaser and Strauss [27] more than forty years ago, its popularity and acceptance has increased significantly in social research as well as in the IS discipline. However, since considerable debate has emerged that has interpreted grounded theory in different ways based on diverse epistemological perspectives, the present approach involves a stable set of key characteristics representing the methodology’s underlying tenets, which have been identified in the literature to encourage high-quality research [4, 35]: Theory development. The present study seeks to develop rather than test theory. Hence, theoretical coding is used to identify theoretical relationships between identified concepts. In our application, we seek a theory of flow regarding a specific IS. Theoretical sampling. Sampling decisions are made with respect to research efficiency (purposive sampling) and theoretical density (theoretical sampling), not to aim at representative populations. Expecting high theoretical relationship complexity, this aspect is a critical requirement for our method. Codes are generated from the data itself. The use of specific preconceptions and theories as the starting point for data collection and analysis is avoided. In line with the method, this point is limited in two cases: the phenomenon of flow is initially described, based on descriptions that stem from existing qualitative data, and in a later stage, extant theories are used to relate the emergent theory to the body of knowledge. Iterative coding. An iterative process is utilized, whereby early data collection and analysis inform subsequent data collection steps. There is thus an inextricable link between data collection and analysis (see Figure 1).

Step 1: Respondent acquisition

Step 2: Data collection

Step 4: Iteration until saturation

Figure 1. Research Process

Step 3: Data analysis

Grounded theory

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Constant comparisons lead to theory development through several data coding iterations, reducing the data, and abstracting out the individual context, if applicable. Usage of memos and visual models. The formulation of transitional memos regarding analytical and theoretical decisions and the provision of visual models of the emergent theory play a pivotal role in comparisons, the emergence of theory, sampling, and theoretical densification. The resultant iterative research process of this study is depicted in Figure 1. A detailed description of each step of the research method is provided in the following.

Respondent Acquisition The selection of respondents follows the principle of theoretical sampling [27]. The sample is continually consciously extended until the state of theoretical saturation is reached, meaning that no additional knowledge is expected based on including further respondents. In the process, ideally, a heterogeneous sample is generated to reach a variety of diverse but internally homogeneous comparison groups [27, 39, 44]. To achieve this diversity, users are spread over theoretical sampling dimensions—for instance, sociodemographic and website usage related dimensions. All sampled informants in this study are users of a large market-leading shopping platform (Amazon. de). Users are recruited via several sources: The platform’s own fan page provided by a large social network, related forums, and within the network of students of the authors’ institution. Beyond the standard grounded theory procedure, approaching potential informants, individuals are initially presented with brief, widely used (e.g., [11, 59, 67]) written descriptions of strong flow experiences (statements by a dancer, a composer, and a rock climber), as borrowed from Csikszentmihalyi’s [14] qualitative work (pages: 38–48) My mind isn’t wandering. I am not thinking of something else. I am totally involved in what I am doing. My body feels good. I don’t seem to hear anything. The world seems to be cut off from me. I am less aware of myself and my problems. My concentration is like breathing. I never think of it. I am really oblivious to my surroundings after I really get going. I think that the phone could ring, and the doorbell could ring, or the house burn down or something like that. When I start, I really do shut out the whole world. Once I stop, I can let it back in again. I am so involved in what I am doing. I don’t see myself as separate from what I am doing.

Since participants should be able to discuss flow experiences in detail, only users who have experienced flow before are invited to participate. Finally, thirty-two users were spread over the following six theoretical sampling dimensions: Age, gender, education, familiarity with the website, frequency of use, and previous flow experiences using the website. The informants’ ages range widely, from seventeen to seventy-nine (31.9 mean), 38 percent of the interviewees are female, and their educational

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attainments vary from completed apprenticeships (9), to undergraduates with university entrance qualification (17), to graduate degree levels (6), to one postdoctoral degree (habilitation). The level of experience with this website ranges from six months to fourteen years of website usage. The frequency of use varies from twice a year to everyday. Fifty-three percent of the informants stated that they already had a flow experience using the Amazon.de website.

Data Collection Flow is not a concept equally familiar to all respondents. To ensure that it is evenly apprehended between respondents and the researcher, individuals have to be intensively introduced and guided through the survey concerning the theoretically defined components [67]. This is achieved in individual face-to-face settings conducting semistructured interviews whereby both the researcher and respondent are able to pose and discuss questions in a flexible manner [56]. Gathering data for the study at hand, problem-centered semistructured interviews are used, in which the interviewer follows two strategies: On the one hand, broadly differentiated data are produced. In parallel, the respondent’s subjective view is interpreted and communication toward the research problem is increasingly sharpened. For this purpose, the researcher combines periods of listening and inquiring using a variety of discussion and narration-generating techniques [43, 83, 84, 85]. During this discursive-dialogic process [55], the respondent is regarded as an expert in his or her activities who increasingly develops self-reassurance of his or her psychological processes and behavior. The individual interview procedure starts with a further introduction to the flow phenomenon on a general level, to ensure even apprehension. After presenting the written descriptions of flow experiences, the respondent is introduced into the two factors of flow—absorption and fluency—and the respective items of the flow short scale (see Table 2), a common flow measure in psychology [68]. Furthermore, the interviewee is asked to briefly describe one past individual flow experience. In the following main part of the interview, the examined website is available to be used by the respondent as well as the interviewer to facilitate recall and for demonstration purposes. First, available prior flow experiences using the considered website are discussed at a general narrative level. Second, the respondent is asked to think about attributes of the website that enhance or inhibit flow, and to consciously connect these attributes to the holistic flow experience. Third, to further concretize the subsequently discussed relationships, the interviewer asks the informant to repeat the last step in a more differentiated way, for each of the two factors of flow and (optionally if helpful) each of the various single items of the flow short scale.

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Table 2. Flow Factors of the Flow Short Scale. F 1: Fluency My thoughts/activities ran fluidly and smoothly. I had no difficulty concentrating. My mind was completely clear. The right thoughts/movements occurred of their own accord. I knew what I had to do each step of the way. I felt that I had everything under control. F 2: Absorption I felt just the right amount of challenge. I didn’t notice time passing. I was totally absorbed in what I was doing. I was completely lost in thought.

In the course of the interviews (see our interview guideline in the Appendix), narration-generating questions support the deeper differentiation of posed concepts (e.g., What do you particularly mean by …?). Equally, comprehension-generating questions ensure precise communication between interviewee and researcher (e.g., Do I understand correctly …?, Isn’t it contradictory that …?). Furthermore, the gleaning and replaying of concrete examples from experience are used to enhance the ability to memorize previous user experiences and situational usage behavior factors (e.g., Can you show an example on the website?). Whenever applicable during the interview procedure, constant comparisons (regarding the flow model developed so far) are enhanced by relating informant statements to existing insights that emerged from past interviews and discussing their confirmatory or contradictory nature. Single interviews take approximately one hour per informant. All interviews are audio recorded with the informant’s permission and transcribed to provide accurate records for data analysis.

Data Analysis The first data analysis stage involves early concept identification, usually called initial or open coding. Here, categories and properties are identified from distinct events (incidents) in the data, and meaning labels are attached. Hence, codes are generated from the data itself, avoiding preconceptions. As concepts emerge, they are (a) constantly compared with other incidents for verification purposes and development of their properties, and (b) compared with other concepts to enhance fit with the data. As a result, coded concepts finally represent abstractions of the statements of many informants. For example, in the following, some statements that lead to the concept search for optimal product are shown. Numbers alongside user citations reveal the chronological interview order.

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I just typed in “smartphone” and checked the different devices, read all the information, read what others were saying. And then I got into it. You read on and on, because you think that there might still be a better one. Finally, I thought that I had found the optimal mobile phone for me. 12 I’ve been in flow when I caught up on the Kindle because I’m very interested in the technology. I compared the devices and read through all the information. It’s about these comparisons and the attempt to find the optimal device. I think I can totally obsess about it. 4 My camera broke and I sought information about the latest models, to find out which one is optimal for me. I spent many hours and in the end, I was sure that I had found exactly the camera I needed. 11 For example, I just wanted to get a certain TV set. But, no, I spent one hour looking at all the TV sets. First I read the product information; I am not very into this. And then I thought about getting full HD instead of just HD. I read all the specifications, and compared it with other offers. You can spend forever doing this.

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To enhance this procedure, each time a new concept is created, a memo is linked to that code, recording ideas designed to capture the present specification and stimulate the further specification of the concept. The memo that was saved in the concept’s description is: Search for optimal product, compare products, “funnel search” (collect potentially optimal products, e.g., in the shopping cart) / might be mere “opinion-forming” not necessarily leading to purchase / related to a clear goal of the activity.

In the early phases of analysis, concepts usually emerge at a low level of abstraction, but as concepts are compared to each other, it is realized that they can be grouped under more abstract concepts. In the concrete example, statements about finding the optimal product, lead to the concept existing goal, which is one of the components of the final grounded theory developed in this paper. Hence, as more concepts are identified, codes are organized in a node structure (a tree with branches). The final higher-order tree node structure thus consists of broad categories. In the concrete example, this is a category called design options, with the subcategories content, layout, design, and navigation, and distinct categories for mediators, moderators, flow experience, and flow effects. Sorting concepts in the tree structure already involves thinking about their possible positions in their conceptual network. This leads to the second stage of our analysis, called theoretical coding. Theoretical coding focuses on uncovering potential relationships between the concepts created during initial coding. Codes are reassembled with propositions about their relationships that can be derived from the data (e.g., positive, negative, mediating, or moderating effects). This enables theory development on an abstract level, without the potential to cast a technological overlay on the data (e.g., axial coding techniques), which might restrict the analytical codes constructed and jeopardize the emergent, iterative nature of grounded theory [9, 25]. In the following example, statements led to the assumption that user budget might show a moderating effect on explorative behavior.

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I normally don’t have enough money for shopping. If I don’t have money, I visit the site in a very goaldirected way and I don’t browse it. 11 Theoretically, the site is so large. I can imagine that if I had plenty of money and if I would spontaneously happen upon kitchens or whatever, I could spend weeks surfing.

Theoretical and open coding cannot be seen as distinct sequential steps because they proceed quite naturally together. Theoretical coding requires concepts found during open coding, but a sense of concept relationships is often already developed during open coding. As the resultant flow model and its complexity develops, selective coding is applied, where further coding is delimited to concepts and relationships closely connected to the core category—flow. Focusing on the core issues of the emerging theory, selective coding helps to achieve the dense development of categories and relationships, without drifting into irrelevant areas [26]. To facilitate the development of an integrated theoretical framework, we use a model-building tool to visually examine the proposed relationships. This is especially helpful to further drive abstraction of similarly aligned effects (by visually analyzing and sorting the proposed relationships) and to visually identify mediating and moderating relationships (by monitoring similarly aligned effects). Equally, visual representations support the communication of the status quo of the grounded theory with further respondents. The visual models are linked with explanatory memos, which together are used to stimulate questioning in subsequent interviews, directed at further refinement of the concepts or addressing gaps in understanding. Depending on the specific analysis or interview situation and still faced with high model structure complexity, the visual modeling of relationships can be conducted incrementally, examining theoretical relationships around central emergent categories step by step (e.g., content, curiosity, flow, etc.) using separate part models and finally reintegrating these part models stepwise toward a comprehensive model. The end of the grounded theory process is achieved by examining theoretical saturation. The transparency provided by the use of visual models is helpful to identify knowledge gaps in earlier data analysis steps, but it also provides a good indication of saturation, reviewing the evolving model versions and connected memos, realizing that no additional knowledge is gained. The complete data analysis process is facilitated by the qualitative analysis software (e.g., QSR NVivo), which is used for coding, memo writing, and dynamic visualizations of models. The software must offer coding and visualization of relationships between the concepts. To facilitate the development of an integrated theoretical framework during selective coding, an additional model-building tool (e.g., MS Visio) is used to visually examine the proposed relationships, which offers more flexibility regarding concept selection, combination, and arrangement.

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Recommender systems Proximity through hierarchy

Information filter accuracy (push)

Perceived importance (+)

(+)

(–)

Receiving of subjectively relevant information

(+)

Formulating new goal

(+)

(+) Lucidity

(+)

Information organization

Absorption

Motivation

(+)

Experience with website

User-generated content

(–) Budget

(+)

Consistency

Selfimposed time limit

(+) (+)

Existing goal

(+) (+)

Edited content

Information quality and quantity

(+) (+)

Media richness

Goal achievement expectancy

Flow

Receiving of goal relevant information

(+) (+)

(+)

Product range Information filter accuracy (pull)

Fluency

Search and filter functions

Figure 2. A Grounded Theory of Online Shopping Flow

The Grounded Theory The final result is a visual model that depicts the developed grounded theory (see Figure 2), using circles (latent concepts), rectangular boxes (design options), square boxes (moderators), arrows (directional [+ and –] relationships), and lines (associations).

Goals The terms “goal direction” and “goal orientation” are often used by the interviewees to describe that they have very specific goals when they are surfing the website. On the contrary, users with subjectively broad goals often do not consciously recognize that they have existing goals during their flow experience. 26 I definitely was in flow when I was searching for holiday offers. I was absorbed, always comparing, then I found something, and then I was searching further and further to find the optimal one, the best price– quality ratio. On Amazon, however, I have not been in flow, since I am very goal-oriented. I know what I want and that’s what I search for.

However, it turns out that goals are always present in the flow state, but that they can have different qualities. Some informants describe that even very broad goals (such as passing time) lead to the more specific (sub) goals (such as looking at recent books) that the flow experience is based on. 7 I just looked at this and that, very different things, for very long. And time passed very quickly. Normally, you don’t know exactly what you are searching for. For example, I realized that this field contains further articles, and I thought: “Aha, why not take a look at recently published books?”

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Some respondents recognized the existence of these (sub) goals, while others did not. This might be explained by deep absorption in the flow state, resulting in unconsciousness of goals. 7 First I was searching for a PlayStation, and then I discovered thousands of things that interested me, and time flew, and then my friend appeared, asking me: “What are you doing?” and I realized that I had done something completely different than I originally intended to do.

In past studies, different qualities of goals led to two distinct Web user types, who follow goals with either high or low specificity, for instance, “goaldirected” vs. “experiential” activities [58] and “directed searching” vs. “explorative browsing” [62]. There is evidence of flow regarding both types of behavior. Both types also seem to be closely interrelated, since many informants report switching back and forth between existing goals and formulating new goals. 11 Mostly, it’s like this: You start searching for something specific, but then they have such a large variety and many further offers. You find more and more things and it goes on and on like this. You look at many more things than you originally intended. You dig into it and spend much more time than you intended. 5 I searched for a certain product, and when other matching products were displayed, I looked around. Finally, I strayed further and further away from my original goal.

Hence, explorative behavior requires, on the one hand, that the website makes for the receiving of subjectively relevant information. 13 It’s fun when you find something new, if you come across it more or less by chance. For example, unknown electronic music, because it is always linked, or people write in reviews that this is similar to that, etc. Then you check it out. 22 It hinders the flow when I can’t jump from one step to another, because I first have to think about what I like.

On the other hand, explorative behavior implies openness toward the formulation of new (sub) goals, which is influenced by self-imposed time limits and user budget. 31 I know how much time I have and I am very strict with time. When I realize that the time is almost over, I simply complete the task. 10 I always try to complete the task quickly and I try to be focused, to not get distracted. 5 I normally don’t have enough money for shopping. If I don’t have money, I visit the site in a very goaldirected way and I don’t browse it. 11 Theoretically, the site is so large. I can imagine that if I had plenty of money and if I would spontaneously happen upon kitchens or whatever, I could spend weeks surfing.

Regardless of whether users visit the website with a specific goal or an illdefined goal, what seems crucial for motivated behavior is either the ability to maintain motivation toward an existing goal for a long time or the openness to formulating new goals (or broadening existing goals) during the visit.

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Motivation Goals are found to be essential to achieve sufficient motivation to engage in an activity in a way that leads to absorption. The importance of goals for motivated behavior is a commonly accepted tenet of psychology, reflected by a variety of motivational theories, for instance, expectancy value theory [21]. Motives fall into one of two types: curiosity motivation and achievement motivation. Achievement motivation is activated by perceived challenges, which means that there are sufficiently high demands compared to personal skills. In the literature, achievement motivation is seen as a primary precursor of flow [14]. 12 For me, flow happens when a product exhibits a certain complexity, when a lot of text is involved, and a higher mental effort is necessary. 3 For me, the demands could be higher, because I like complex things, even greater search and filtering functions, as offered by eBay. 4 Depending on how intensively you like to be involved, you can search on the surface or you can search for three to four hours until you make your decision.

However, an additional motivational type—curiosity motivation—is identified, which relates to an enthusiastic interest in the content offered on a website. The emergence of curiosity motivation in this study reflects recent perspectives in psychology showing that achievement motivation does not necessarily have to be present for one to experience flow [68]. 1 11 12 15 13

It was interesting. I like technology and I am always enthusiastic about new things. That’s how I got into flow. I’ve been in flow when buying a DVD, because I love films. It took forever. I’ve been in flow when catching up on the Kindle because I’m very interested in the technology. I compared the devices and read all the information. Flow arises when I am really enthusiastic, when thousands of things are really interesting to me. Regardless of the shopping site, some items are interesting to me, but too many items are not interesting. As a result, I can’t get into flow. I was interested, maybe it was an early stage of flow, but I was not concentrating fully.

Absorption Sufficient motivation leads to the first flow factor, absorption, representing a focused state of mind, blocking out irrelevant stimuli, leading to a dissociated experience of time. 18 You somehow black out the whole website and focus only on the product you want. The site serves only as a “support” and this does work so well that it puts me in flow state. 6 I am a CD collector, and there was this special offer on three CDs for 15 euro, so I put about fifty CDs in the shopping cart, and an hour later I realized that I can’t buy all these CDs. I was definitely in flow state. I was totally focused, and I took my time surfing. Many times I am so absorbed that I do not hear my wife talking to me. 13 When I shop for music, and discover more and more unknown bands or DJs whom I did not know before, I often forget about the time, and suddenly realize that I’ve been sitting in front of the PC for two to three hours.

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However, some users imply that entering the site with specific goals might hinder flow. This might be explained via the moderating effect of perceived importance on absorption. Evidence for this effect is already given in psychology [20]. 8

I only visit Amazon when I want something specific. I concentrate because I need it; it’s somehow different. I don’t consider it enjoying, like, say, reading a novel, where you are absorbed. It is more a “business” to me. 15 In my opinion, the activity is not important enough. If it’s a matter of life and death, then I concentrate totally, but not if it’s about an annoying product. 2 It depends. When I am buying entertainment products such as books, I am not 100 percent absorbed, but if it is about expensive electronic products such as a laptop, I am completely into it.

Fluency When absorption coincides with the receiving of goal-relevant information provided by a website, the second factor of flow, fluency, comes into play; it includes a sense of potential control, knowledge of what to do during each step, and attention focus that is easily maintained. 21 It is fluid, because different products are displayed that you can scroll and click through, and you have many possibilities to click further if you look at what other people were interested in or similar products. And so you go on and on … 31 I know exactly where to look when I need some information or want to do something. And as long as I know what I want to do, I feel in control of the process. 30 The site’s system is good; it leads you easily through the site. You know where you have to click and what happens next. 18 The process of using the site is fairly easy and is almost automatic.

However, if adequate information is not provided by a website, the receiving of goal-relevant information—and therefore fluency—is hindered. 1

For example, if you visit price comparison portals such as billiger.de, you have a list of all these shops but you don’t have much information about the product, so you have to visit other sites. 12 They have to invest a little bit more. You have to get aroused to immerse further into the subject matter. Why has it got this cut? Why is it lighter? What are the advantages of this shoe? What are the disadvantages? What is the material? You want to know how it can be washed, how durable it is. All sorts of things. There are so many things you want to know about the shoe, but there is nothing. You have to visit Google. 16 Usually, I am searching elsewhere for the product information, for example, on the manufacturer’s website. Here [Amazon.de] I don’t find what I need.

Fluency goes along with progress toward user goals, leading to higher expectancies of goal achievement, and higher motivation. The effect of higher expectancies on motivation is the core of expectancy value theory in psychology [21]. On the other hand, if the receiving of goal-relevant information and therefore fluency are not given, this leads to distraction and frustration.

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4 This is good usability. Because I can access what I want with a few clicks. So I don’t have problems getting disappointed or desperate. 2 It was annoying. I was searching for a netbook, and netbooks were relatively new, so the information situation was very poor, and the reviews were all contradictory. 7 And now I realize that the book is not available. And here it says that it is even unclear if it will ever be available again. This is frustrating.

The receiving of relevant information potentially provided by a website is moderated by the experience with the website. This might be explained by an expertise effect that can be applied to Web activities, which is necessary to orient oneself on a specific website. Up here I got the search field, and as an experienced Internet user, I type in “chess” after selecting the category “books.” Now I get beginners books that I am not interested in. I like to have it structured by topics. I only get that if I type in an additional space up here. I have to do everything using the input field. It is not optimal, but you are used to it. 12 If it is in the usual Amazon structure, it is easy to surf, because you already know what comes next. The headline comes first, then the price. You know the order. 7 I don’t think it’s hard to concentrate on all the unnecessary information, because I am used to blacking it out. 15 The advertisement does not disturb. You’re used to it. 7

Information Organization Information organization includes aspects of arranging elements (content elements, navigational elements, etc.) on the website. Appropriate information organization for flow includes the concept of proximity through hierarchy, which seeks to reduce eye movement distances, cursor and scrolling movement distances, and the number of clicks toward receiving the relevant elements. Proximity can be implemented through different hierarchy types. In a vertical hierarchy, the most important elements are displayed at the top of the page. 3 It is very helpful that everything is already described in the title bar. 1 All the important information is already available in the title bar: if it’s used, how much it will cost; everything that is important for a mobile phone, how large it is, the operating system, etc. 7 On Amazon you have pictures, and then product information and reviews. And that’s what’s good about it.

Using level hierarchies, important elements are provided at high levels in the website structure. Generally, it seems to be helpful to use few levels. 12 This is too confusing and too much effort for me. If I want to buy a song, for example, I get a list with all the CDs, and I want to immediately listen to each one, but I first have to click on each CD, then I can push play, and to listen to another song I have to go back again. 21 I definitely like it when I don’t have to click on “More” after five products, also because of the loading times. Everything is there; you just have to scroll. When I have to click, this is a barrier that brings me out of flow. 20 You have to click thousands of times to finally get to interesting things, if you don’t know what you want and if you don’t type in the exact search term.

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A size hierarchy highlights important elements by increased relative size. 1 This is easy. Navigation is easy. The size of the search bar, the size of the shopping cart, I like this. It is not hidden, as with many other websites.

Consistency means providing information organization consistently over time. This enhances expertise effects that lead to a better orientation on a website. Consistency implies both a consistent layout (arrangement of elements) and a consistent design (colors, fonts, etc.). 12 The Kindle site is very confusing; pictures on the left, pictures on the right, text on the left, text on the right. The style changes constantly. The fonts are changing. Colors are also changing. This is something I find disturbing. These are obstacles to flow, because you have to pay closer attention to get an overview.

Lucidity involves an intuitive—hence clear and unambiguous—structure of site elements, which helps to avoid information overload. Lucidity is achieved by a low number and clear delimitation of displayed elements, a low font variety, and a low number of modest colors.

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Here on Amazon, everything is clear, not difficult. It is clearly arranged. On eBay, it is too much for me. Too many things. Too much information. 20 It is so confusing. I don’t know where to look. Nothing catches the eye, but all at once. 7 I don’t know. My mind is obstructed. It is because of the pictures and the fonts. Everything is very close together. I don’t understand anything. 9 This shopping cart is clear to me, but yet here are other shopping carts. OK, I know what I have to do, but for the “diagram” I have in my mind, this is confusing. 9 Here for example. When I look at this bag, there is the name, four to five different colors, several font sizes, and prices. This is like a jungle. 1 The colors, blue and orange, are good. There are other sites where I would say, this is too much, too many colors, too many impressions. Here it is not like that. 14 I think the colors are good. They are not aggressive or disturbing.

Information Quality and Quantity Information quality is crucial to support the potential reception of relevant information. In addition to factual quality, users particularly report that usergenerated content shows a certain social proximity, which is important to satisfy individual interests. 10 I trust the reviews, because the reviewers control for each other, so it’s an independent user opinion written by an amateur I possibly can identify with. 12 Sometimes you can lose yourself in the reviews if you feel there is a dialogue, if they interact with each other. One of them writes total nonsense and I don’t understand what he is writing. It’s happening when I form an opinion. Particularly if it’s like a dialogue, then I shut out everything else. 7 Because you like to be further informed about a product and you like to know what other people think about it.

To enhance the factual quality of user-generated content, control mechanisms seem helpful.

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4 The evaluation of reviews is helpful. If you get evaluations like “This camera makes great pictures” and you see that one of twenty users thought that this is helpful, I am certainly not one of them.

Furthermore, factual quality might be directly enhanced by offering edited content. 2

There are information and reviews on Amazon, but I first search for product tests on other websites and when I know what I want, I come back to Amazon. 10 I think it would be cool to cooperate with test institutions, to include the top-ten list of each product type.

The affective quality of information leading to flow can be enhanced by offering media richness—providing images, audio, or video previews of the products. Prior evidence of the impact of media richness on emotional responses and flow is present in the contexts of e-commerce [1] and elearning [49]. 11 I was definitely in flow buying DVDs, but with clothing, for example, it is not attractive enough, like on other sites where you see a model wearing the clothes or see her in a video walking on the catwalk. 10 Other sites have a very emotional image, because they work with very many photos, models, etc. 7 When searching for the PlayStation, every time there were no pictures, I just did not look at that. Pictures definitely play an important role. You first check all the pictures.

Information quantity is necessary to increase absorption and explorative behavior. Concretely, information quantity is provided through product range variety. 11 You have no exact idea what you want, you visit the site, and then there are so many offers that you go on and on. 4 It is about product portfolio completeness. Even if Amazon doesn’t have it, there are offers from external suppliers on the Amazon platform. The product selection is enormous. And I would rather limit it on my own with a few clicks than go to other sites where they have only one shelf of DSLR cameras, one shelf of compact cameras, etc. 6 Great offers lead to flow. In principle, everything is available on Amazon. There’s almost nothing you can’t get.

Equally, information quantity is driven by the offering of complex products and the information depth provided by user-generated content.

12 I am very mindful, thinking about purchasing decisions, and very often I can go into such an experience. Particularly if a product is a bit more complex and I compare different types of this product. Then I also often use multiple windows. 7 For example, when I bought my mobile phone cover. I spent hours, because I came across 10 thousand things and information, and you click and click. 1 If you want to buy a mobile phone and you are not well informed, you read through all the information, what other people are saying about the product, you read further and further. 4 It’s an effect of mass. There really are a lot of reviews.

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Information Filter Accuracy The provision of potential information quantity and quality turned out to be a necessary but not a sufficient prerequisite of flow experiences.

10 Amazon is always connected with doing research in advance. I don’t go to Amazon searching for inspiration, as I do on other websites such as H&M [a fashion store]. They just have to send me a newsletter, and I go clicking. Amazon is too big for that. I think, if you don’t know what you are searching for, Amazon has too many offers. It is like a department store where you can buy everything. 2 If I buy more expensive things, such as a smart phone, I need other websites. On Amazon, I can perhaps limit the results regarding the price, but then thousands of devices are offered. That’s just too much. 10 I would not say that I feel overstrained, but I feel unsure. If I have no clue about a topic, where should I start? You first have to check out camera comparisons. Without additional information, you have almost no chance on Amazon. Its variety is too large.

The receiving of relevant information is only achieved if a broad base of potentially relevant information is individually limited via filtering mechanisms, avoiding information overload. 4 It is the completeness of the product portfolio, but also good usability, hence the different possibilities to sort and filter it.

The reported information filtering systems can be classified into pull and push types, depending on the need for action by the user. Pull filters, such as search and filtering functions where users can limit search results stepwise, support flow by providing goal-relevant as well as inspiring information, whereas push filters such as recommender systems foster flow mainly through inspiring users to pursue new goals. 6

The filters are good. You can limit via price, brands, etc. I use them extensively when I am searching just in a particular category and I don’t know exactly what I want, I go in the right direction stepwise. 13 These recommender systems definitely support flow. When you find good stuff you didn’t know about before, it is great fun. I can listen to an album, and then, at the bottom of the page, I see “customers who bought this, bought similar music.” I don’t know this music and just click on it. 11 You start with the most popular or most recent products. This is well structured. There is always something you would buy.

However, accurate results are critical for both systems. 14 Occasionally, there are obstacles to getting into flow. For example, the search function, when there are irrelevant results. 16 Recently, I was searching for a receiver. Let me see, I typed in “DVB Receiver WLAN HD Kathrein” and now it should display the Kathrein ones. But it doesn’t. And I can’t filter the other [receivers] for DVB-C. This, for example, disturbs flow. The filter categories are not good. I feel annoyed. You should be able to search for additional information. 14 However, if you don’t like the things that are offered, that others bought, that kicks you out of flow. Then you have to go back again and search for something else.

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Discussion and Implications We identified a set of open questions in the literature, related to (1) the theoretical mechanisms that let flow experience emerge during website visits, and (2) the concrete design aspects of websites that lead to users’ flow experience. Providing answers to these questions, we are able to make a number of substantively original theoretical contributions to the information systems flow literature, as well as managerial implications, which will be illustrated next.

Theoretical Implications In essence, we developed a complex grounded theory of online shopping flow, providing a theoretical in-depth view of flow mechanisms including concrete realizable design aspects as core drivers of flow. Relating our key findings to the literature we were able to integrate and extend earlier findings and models that examined flow experience on the Web. Furthermore, our results provide a grounded basis for further theorizing about flow experience on the Web, deriving promising research questions and providing theoretical propositions that can be tested in future research. Our key findings are summarized and related to the literature in Tables 3–Table 6. Since the importance of goals for motivated behavior is a commonly accepted tenet in psychology, it is hardly surprising that goals play a pivotal role during flow experience. Congruent with findings by Pace [62], we show that goals are always present in the flow state. However, goals can have different qualities (specific vs. broad goals) and informants report switching back and forth between existing goals and formulating new goals. Extending these findings, we propose (a) that broad goals lead to more specific (sub) goals on which the flow experience is based, and (b) that deep absorption in the flow state might explain that some users do not recognize the existence of these (sub) goals. The unconsciousness of (sub) goals might also explain inconsistent findings, where Novak et al. [58] and Rettie [67] found that flow experiences were more prevalent during strictly goal-directed tasks, whereas Korzaan [40], Novak et al. [59], Richard and Chandra [73], and Smith and Sivakumar [78] show evidence of flow during explorative behavior. We did not find a tendency, but evidence of flow regarding both types of behavior. In light of these arguments we ask the following question: What granularity of goals is necessary to enter the flow state? Our results propose that motives fall into one of two types: achievement motivation and curiosity motivation (see Table 4). Achievement motivation is a well-known precursor of flow in psychology (e.g., [14]) that is frequently reflected in the IS literature using the constructs skills and demands (or challenges) (e.g., [31, 77]). We were able to identify an additional motivational type that we called “curiosity motivation,” related to an enthusiastic interest in the content of a website. This integrates recent perspectives in psychology showing that achievement motivation does not necessarily have

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Table 3. Summary of Key Findings in Relation to Literature: Goals. Categories

Key findings

Relation to literature

Existing goal

Goals are always present in the flow state, Congruent with Pace [62], who differentiates but have different qualities (broad vs. directed searching and exploratory specific), where broad goals lead to more browsing, involving clearly defined goals specific (sub) goals. vs. ill-defined goals. Extending Pace’s model [62], we propose that broad goals lead to more specific (sub) goals. Existing goal Users with subjectively broad goals often do Congruent with Pace [62], who describes not consciously recognize that they have that users’ comments sometimes suggests existing (sub) goals during their flow that exploratory browsing does not experience. Deep absorption in the flow involve a goal, whereas closer state might explain why some users do not examination has revealed that this is recognize the existence of (sub) goals. wrong. To explain Pace’s findings [62], we propose considering unconsciousness of goals caused by deep absorption. Formulating new Informants report switching back and forth This switching behavior is congruent with goal between existing goals and formulating Novak et al. [58]. new goals. Formulating new Explorative behavior is influenced by Congruent with Pace [62], where some goal self-imposed time limits and user budget. disciplined informants refused to allow themselves to get sidetracked because of time constraints. Similarly to time constraints, user budget might be a limited resource, where some discipline is required to avoid its consumption. Receiving of Explorative behavior requires that the Congruent with Pace [62], who uses the subjectively website makes it possible to receive expression getting sidetracked to describe relevant subjectively relevant information. occasions when a web user decides to information pursue a different goal aroused by interesting content.

to be present to experience flow. These findings lead us to ask the following questions: How do achievement and curiosity motivation relate to each other on the Web? How do we address achievement motivation on the Web? How do we address curiosity motivation on the Web? Reviews of the conceptualization of flow show a low reliability of the flow constructs that are used in the IS literature. Novak et al. [59] list a variety of thirteen different flow constructs in their review; on average, only four of them are considered per study. Moreover, even the use of all these constructs overlaps only partially with the proposed constructs in the field of psychology [14, 69]. Choi et al. [13, p. 227] express the situation as follows: “The construct of flow is, however, too broad and ill-defined due to the numerous ways it has been operationalized, tested, and applied.” Based on the status quo of flow conceptualization in psychology, there is evidence of a two-factor structure of flow (absorption and fluency), which has been replicated in our analysis, based on informants’ statements. In turn we posit the following research question: Could we replicate the two factor-structure of flow in different website contexts, such as entertainment, e-learning, and social networks?

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Table 4. Summary of Key Findings in Relation to Literature: Motivation, Absorption, Fluency. Categories Motivation

Key findings

Relation to literature

Motives fall into one of two types: achievement motivation and curiosity motivation.

Achievement motivation is seen as a primary precursor of flow in psychology (e.g., [14]). In the IS literature this is commonly reflected when skills and demands are examined as flow antecedents (e.g., [31, 77]). We found an additional motivational type (curiosity motivation), reflecting recent perspectives in psychology showing that achievement motivation does not necessarily have to be present to experience flow (e.g., [68]). Absorption Sufficient motivation leads to absorption, Evidence of the two-factor structure of flow which is a focused state of mind, blocking (absorption and fluency) is provided in out irrelevant stimuli. different contexts in psychology, such as university education [72], marathon running [79], treadmill running [66], computer gaming [71], or graffiti spraying [72]. Perceived Perceived importance of the activity shows Evidence for this effect is already given in importance a moderating effect on absorption. psychology [20]. This effect might also be related to product involvement as an antecedent of flow (e.g., [41]). Fluency Absorption coinciding with receiving of Evidence of the two-factor structure of flow goal-relevant information leads to fluency, (absorption and fluency) is provided in including a sense of potential control, different contexts in psychology (see knowledge of what to do during each above). step, and attention focus that is easily maintained. Goal Fluency goes along with progress toward The effect of higher expectancies on achievement user goals, leading to higher expectancies motivation is the core of expectancy value expectancies toward goal achievement, and higher theory in psychology [21]. Our findings motivation. might also be related to the concept of progress toward goal leading to flow, depicted by Pace [62]. Experience The receiving of relevant information An expertise effect has been shown in a with website potentially provided by a website is variety of studies examining skills as a moderated by experience with the precursor of flow (e.g., [31, 41, 59, 62]). website.

We found that information organization, which includes aspects of arranging elements on the website, might play an important role in inducing flow experiences. We can organize our results using three dimensions: proximity through hierarchy, consistency, and lucidity (see Table 5). Furthermore, our results provide a variety of concrete examples of how to design to improve these dimensions. In a nutshell, proper information organization for flow involves fast and intuitive receiving of relevant information on the website, without distractions that might be induced by the interface. For future research it would be interesting to develop

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Table 5. Summary of Key Findings in Relation to Literature: Information Organization. Categories Proximity through hierarchy

Consistency

Lucidity

Key findings

Relation to literature

Proximity through hierarchy seeks to reduce Relates to poor interface usability and the eye movement distances, the cursor and distractions by the interface that lead to scrolling movement distances, and the number frustration (e.g., [62]). of clicks toward the receiving of relevant elements. Consistency enhances expertise effects by Relates to expertise effects that have been providing information organization (layout shown in a variety of studies examining and design) consistently over time. skills as a precursor of flow (e.g., [31, 41, 59, 62]). Lucidity helps to avoid information overload Relates to studies showing that ease of use by involving an intuitive (clear and of a website might foster flow (e.g., [33, unambiguous) structure of site elements. 74]).

Table 6. Summary of Key Findings in Relation to Literature: Information Quality and Quantity, Information Filter Accuracy. Categories Information quality

Information quantity

Information filter accuracy

Key findings

Relation to literature

User-generated content shows social Our general findings on information quality proximity, which is important to satisfy might be related to Choi et al. [13], who individual interests. Factual quality might found a positive relationship between useful be enhanced via control mechanisms and content and flow. The specific impact of providing edited content. Affective quality media richness on emotional responses and can be enhanced by offering media flow has already been shown in the context richness, leading to flow. of e-commerce [1] and e-learning [49]. Information quantity is necessary to increase The effect of information quantity on absorption and explorative behavior. absorption relates to flow antecedent Information quantity can be provided complexity (Huang [34]). Moreover through product range variety, the offering information quantity might be interpreted of complex products, and information as a challenge (i.e., an achievementdepth provided by user-generated content. motivated activity) (e.g., [31, 41, 59, 62]). The effect of information quantity on explorative behavior is congruent with Pace [62], who uses the expression getting sidetracked to describe occasions when a web user decides to pursue a different goal aroused by interesting content. Pull filters (search and filtering functions) Dailey [17] found a negative impact of support flow by providing goal-relevant restrictive navigation cues on flow, which and inspiring information. Push filters could be reproduced by our informants who (recommender systems) foster flow through complained about missing filter functions on inspiring users to pursue new goals. the examined shopping platform. Equally, our findings on information filter accuracy might be related to Choi et al. [13], who found a positive relationship between useful content and flow.

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scales to measure all three dimensions and to test different website designs in an experimental setting, examining the effects of information organization on flow. Hence, the following question emerges from our research: How do we measure information organization to compare different designs of existing websites and website prototypes? Our results show that information quality and quantity (see Table 6) are crucial prerequisites to support the reception of subjectively relevant information. In particular, the relation between user-generated content and edited content seems to be an interesting aspect that, to our knowledge, has not yet been examined in the flow context. On the one hand, user-generated content has a social proximity to the user that enhances flow, but on the other hand, the factual quality of user-generated content might be poor compared to edited content. We think that this trade-off is worth examining, and hence we pose the following research question: How can we integrate user-generated and edited content in a way that enhances website flow experience? Beyond this aspect, there is already some evidence of the positive effect of media richness on flow in the contexts of e-commerce [1] and e-learning [49], that can be reproduced, based on our informants statements. Additionally, we found that the preferred level of media richness seems to be dependent on the type of product offered on the shopping platform. Regarding the examined platform, media richness seemed to be too insufficientfor emotional products like clothing, but just right for more technical products like DVDs, books, and so on. Therefore, it seems promising to examine different levels of media richness regarding different products as well as website types (e.g., entertainment vs. information websites). Hence, we identified the following research question: Is the effect of media richness on flow dependent on the emotionality of products / websites? Regarding our data, the receiving of relevant information is only achieved if a broad base of potentially relevant information is individually limited via appropriate filtering mechanisms. Since we determined that pull filters support flow by providing both goal-relevant and inspiring information whereas push filters mainly inspire users to pursue new goals, it would be interesting to examine the trade-off between maintaining an existing goal vs. inspiring users to follow new goals. Our results allow us to assume that recommendations that diverge from providing goal-relevant information toward subjectively relevant information lead to an increased number of followed goals that might form a seamless series of shorter flow experiences. Hence, it would be even more interesting to compare the intensity of flow with and without recommendations. We thus ask the following research questions that can be quantitatively examined: Do recommendations lead to an increased number of followed goals, that is, a series of shorter flow experiences? Does a series of shorter flow experiences show a lower average intensity of flow compared to a single flow experience of the same duration?

Practical Implications On the other hand, the resulting grounded theory provides a basis to generate concrete design advice for operators of online shopping platforms aiming to enhance their users’ flow experiences. To enhance online shoppers’

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flow experiences, it seems sensible to pursue two strategies: (a) enhance the user’s ability to maintain motivation toward an existing goal, and (b) inspire the user to pursue new goals. To maintain motivation, continuous progress toward the existing goal must be ensured via providing information quantity and quality as well as optimizing search and filter mechanisms. This strategy seems particularly important to motivate users and in regard to products of high importance to users. To inspire users, the accuracy of recommender systems is decisive, particularly aiming at users who are motivated by curiosity. In both cases, appropriate information organization is useful. All proposed measures are particularly important for users with insufficiently developed expertise effects. Applied to the concrete example, information quality can be improved by offering edited content (e.g., product tests), providing a decision aid for users in the early decision stage. Filter mechanisms might be improved by providing more detailed categories. Greater accuracy of recommender systems might be achieved by including more explicit user information (e.g., via dislike statements) and implicit information (e.g., purchases that have already been made). Regarding information organization, consistency could be maintained regarding all website pages (e.g., the Kindle page), and level hierarchies could be improved by providing endlessly scrolling pages when displaying product lists. As shown above, the results of the grounded theory allowed us to derive recommendations on how to redesign online shopping platforms for flow. Moreover, the grounded theory data offer concrete examples of how to implement such advice; these examples were either directly given by users or at least validated with their help. To finally redesign a website, based on the thorough understanding of flow mechanisms that was achieved, a variety of further design ideas might be developed drawing on techniques from design thinking. The underlying methodological basis of such a design stage— design thinking—is both a set of methods and a mindset to develop innovative design solutions that are based on three core elements: inspiration, ideation, and implementation [6]. Inspiration seeks to identify concrete design questions by gaining a thorough understanding of customer needs that motivate the search for concrete solutions. Ideation offers a structured process of generating, further developing, prototyping, and user-testing ideas, whereas implementation seeks to realize concrete solutions. Since it is expected that innovative and complex human–computer interfaces that offer multimedia-based interaction are likely to induce flow experience, the possible innovativeness of the creative process enabled by design thinking seems necessary. Furthermore, the idea of early user testing in design thinking seems reasonable in accounting for the intersubjective variance of flow experiences. Hence, based on techniques borrowed from design thinking’s ideation stage, the design stage would enable a creative process of finding design solutions in a controlled setup. This is achieved by building an interdisciplinary expert team (three to seven members, ideally from interaction design, development, and management) that is initially introduced to the developed grounded theory (briefing). Team member requirements follow the concept of T-shaped skills [46]: deep functional/disciplinary skills in the individual area of expertise as well as the ability to apply knowledge

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across situations. People with these skills are able to shape their knowledge to fit the problem (instead of reshaping the problem), show curiosity as well as openness to other disciplines, and find a shared language for synergistic thinking. After briefing, an iterative application of creativity techniques, fast prototyping, and user testing might be used in order to find innovative design solutions. Based on the understanding of flow mechanisms, participants are able to derive concrete design questions and motivated to create a large number of design solutions using classical brainstorming techniques (e.g., generate 150 ideas in 20 minutes). Based on three criteria (flow, technical feasibility, and business viability), a selection of these solutions is incrementally made visible, tangible, and functional through an increasing resolution of prototypes (e.g., paper models, storyboards, mock-ups, and wireframes). In the course of this process, early informal user testing can be used to serve feedback that is considered in the further development of the prototypes [28]. During the iterative prototyping and user-testing routine, participants build in order to think, > seeking further improvement of flow, technical feasibility, and business viability. Beyond this, a final evaluation stage that seeks to test the concrete design implementation on real users in their environment seems helpful. This can be achieved measuring flow and performance indicators relevant to the supplier, such as customer loyalty and usage time. Methodologically, a controlled experiment is conducted in which users of the website are randomly assigned to the control group (the standard version) and the treatment group (the flow-optimized version), also referred to as A/B testing. To measure characteristics and intensity of the multifaceted flow experience in its components, the flow short scale can be used (see Table 2). After live-testing the potentially flow-optimized design solution, further refinement might be iteratively achieved, restarting the design stage, until no significant additional effect is generated.

Limitations and Future Research This research study is not without limitations. The main advantage of this study, which focuses on an existing website to provide a detailed view of the experience as well as the design, implies a limited extent to which the results can be generalized. However, starting with shopping platforms, this paper is seen as a first step toward general design principles and theoretical effect mechanisms that lead to flow experience on the web, which might be revealed by comparing the results of a variety of different websites and website types. We encourage researchers to examine these in the future, following the approach at hand. If applicable, we also suggest applying the proposed additional design and evaluation stages in these cases. The results obtained would enable testing the expected effects using a variety of performance indicators as well as documenting the expended efforts to estimate individual cost–benefit ratios of the method’s application in different contexts (e.g., simple vs. complex websites), which are particularly important for its further diffusion, especially in practice.

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Conclusion Since websites and devices that offer multimedia-based user interfaces are increasingly capable of inducing complex interactive user experiences, a strong interest in user experience design has encompassed both research and practice. Proposing a way to understand and optimize flow, this study shows an alternative approach of digital service innovation that includes cognitive as well as affective aspects to provide a design beyond traditional usability criteria. Since the examination of flow experience on the Web is driven toward integrating concrete and realizable website design aspects, the practical implications of the theory presented in this paper concern website operators, Web designers, and users who benefit from a design, encouraging flow. Moreover, the grounded theory that has been developed in our study offers new theoretical insights into the flow experiences of Web users engaged in shopping activities. It manages to integrate several existing findings of flow research, in the information systems discipline as well as in psychology, and provides a starting point for further research on flow mechanisms. Hence, we hope that the proposed approach will be applied to a variety of additional website types to validate the existing findings and to generate further insights regarding different objects of examination. Finally, we hope that this work will motivate further research and further integration of the flow phenomenon in information systems research and user experience design.

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Appendix: Interview Guideline General Instructions Situation and Equipment Only the researcher and the respondent are present in the interview situation. A laptop is provided to operate the website “Amazon.de.” An audio recording device is used to record the interview.

Rules of Behavior To establish a trusting relationship, you should create an open and trustful situation on an equal footing. You should be understanding and calm, avoiding the atmosphere of an examination situation.

Communication and Research Strategies 1. Narration-generating questions should be used to further differentiate posed concepts and signal the objectives of the research on a regular basis: Could you please further elaborate …? What do you particularly mean by …? Can you show an example on the website?

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2. Comprehension-generating questions should be used, to ensure precise communication by summarization, interpretation, and feedback regarding respondent’s statements. Fill gaps of understanding using questions of clarification: Reformulate a posed question or ask further, for example, How to understand …? Confirm interpretations via the use of mirroring, for example, Do I understand correctly …? Confront for further specification, for example, Isn’t it contradictory that …? 3. Constant comparisons should be used: Whenever applicable during the interview procedure, informant statements should be related to existing insights that emerged from past interviews (the flow model developed so far), discussing their confirmatory or contradictory nature.

Interview Guideline Welcoming Dear participant,

Explanation of the Research Question: Thank you for taking part in our research on flow experience in the case of online shopping. While surfing the Web, some users achieve the so-called flow state—a state of deep focus while conducting a fluent activity, which is often experienced as very positive. However, to design websites for experiencing flow we need more information about how flow happens while surfing the Web. Thus, we want to know which design options or attributes of a website support or hinder flow. In this study we focus on online shopping platforms, taking the example of Amazon.

Interview Procedure: Before we start the interview, I will give you an brief introduction to the psychological concept of flow. Then, I would like to ask you in detail about determinants of the Amazon website that might support or hinder flow. During the interview, you can use the Amazon website on this laptop as a memory aid or for demonstration purposes. Please note that there are no right answers or wrong answers. We can conduct an open conversation without a strict sequence of asking and answering. Feel free to talk about your own experiences, let yourself be guided by your thoughts, and take your time to answer. Please pose questions if something is not clear. Finally, I would like to ask you to fill out a short questionnaire. All interview data will be used in an anonymous form. Is it OK if I start an audio recording of this interview?

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Pre-Interview (Briefing) Give the Handout “Introduction to Flow” to the participant. These citations are from humans who experienced a strong flow experience. Please read them carefully. Additionally, we can have a look at the Flow Short Scale, which is a common way in psychology to measure flow experiences. It shows that flow consists of two different factors—absorption and fluency. Hence, you can say that flow is a state of deep focus while conducting a fluent activity. Do you have any questions so far?

Individual Interview Flow Experiences in General: All participants have been invited based on the statement that they already had a flow experience. Here, you should check whether the participant has already developed a proper understanding of flow, otherwise discuss it more in detail. Try to think of one past individual flow experience. Have you ever experienced flow? Can you describe this experience? What did it feel like?

Flow Experiences on Amazon: Have you ever experienced flow while surfing on Amazon? Can you describe this experience?

Flow Mechanisms (Holistic): Why did you (not) experience flow on Amazon? Which attributes, elements, contents of the website enhanced (hindered) your flow experience? Can you connect these attributes, elements, contents to the experience of flow in more detail? Can you think of intermediate steps (mediators)? Are these relations stable or can you think of reinforcing/weakening influences (moderators)? How does the context of the activity influence these relations?

Flow Mechanisms (Two Factors): In regard to the two factors of flow—absorption and fluency—did you equally experience both factors?

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Which attributes, elements, contents of the website enhanced (hindered) absorption (fluency)?

Closing Question: Is there anything that springs to mind that you like to add?

Short Questionnaire Let the respondent fill out the short questionnaire. The End: Thank you for participating!

Introduction to Flow Descriptions of Strong Flow Experiences “My mind isn’t wandering. I am not thinking of something else. I am totally involved in what I am doing. My body feels good. I don’t seem to hear anything. The world seems to be cut off from me. I am less aware of myself and my problems.” (Dancer) “My concentration is like breathing. I never think of it. I am really oblivious to my surroundings after I really get going. I think that the phone could ring, and the doorbell could ring, or the house burn down or something like that. When I start, I really do shut out the whole world. Once I stop, I can let it back in again.” (Composer) “I am so involved in what I am doing. I don’t see myself as separate from what I am doing.” (Rock climber)

The Flow Short Scale

F 1: Fluency My thoughts/activities ran fluidly and smoothly. I had no difficulty concentrating. My mind was completely clear. The right thoughts/movements occurred of their own accord. I knew what I had to do each step of the way. I felt that I had everything under control. F 2: Absorption I felt just the right amount of challenge. I didn’t notice time passing. I was totally absorbed in what I was doing. I was completely lost in thought.

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Short Questionnaire Internal Usage How long have you been using Amazon.de? _____ years, _____ months, _____ days. How frequently do you use Amazon.de? Every _____ years, _____ months, _____ days. How long have you been using the Internet? _____ years, _____ months, _____ days. Personal Details Gender □ Female □ Male Age _____ Highest educational achievement Apprenticeship Undergraduate Graduate Postdoctoral Other

□ □ □ □ □

ROLF MAHNKE ([email protected], Corresponding author) is a research associate of information systems at Ludwig-Maximilians-Universität München (LMU), Germany. His research interests include information systems post-adoptive behavior, user experience, human–computer interaction, and psychology. He holds a Ph.D. in business administration and management information systems, a master’s degree in business research, and a master equivalent in business administration and communication sciences from LMU. His work has been published in international journals and conference proceedings such as the International Journal on Media Management, International Conference on Information Systems (ICIS), European Conference on Information Systems (ECIS), and Hawaii International Conference on System Sciences (HICSS). ALEXANDER BENLIAN ([email protected]) is a chaired professor of information systems, especially electronic services, at Darmstadt University of Technology (TU Darmstadt), Germany. He holds a Ph.D. in business administration and management information systems from the Ludwig-Maximilians-Universität München (LMU). His research interests include human–computer interaction, recommender and personalization systems in electronic commerce, and software as a service. His work has been published in international journals such as Journal of Management Information Systems, International Journal of Electronic Commerce, Journal of Service Research, Journal of the Association for Information Systems, Information Systems Journal, European Journal of Information Systems, Decision Support Systems, and Business and Information Systems Engineering and the proceedings of conferences such as the International Conference on Information Systems (ICIS) and the European Conference on Information Systems (ECIS). THOMAS HESS ([email protected]) is professor of information systems and management at Ludwig-Maximilians-Universität München (LMU), Germany, where he also

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serves as director of the Institute for Information Systems and New Media and as coordinator of the Center for Internet Research and Media Integration. He holds a Ph. D. from the University of St. Gallen, Switzerland. His research focuses on the digitalization of companies and on the management of information technology and media companies. Currently he is working on the digitalization of media companies, on the digitalization of daily life, and on the management of software companies. His work has appeared in international journals such as Journal of Management Information Systems, European Journal of Information Systems, Information Systems Journal, International Journal of Electronic Commerce, Electronic Markets, Decision Support Systems, and Communication of the ACM. He has also published in the proceedings of conferences such as the International Conference on Information Systems (ICIS), European Conference on Information Systems (ECIS), and Americas Conference on Information Systems (AMCIS).