Towards A More Complete Understanding of Consumers’ Experiences at E-Commerce Web Sites: A Post-Humanist Perspective
Working Paper Prepared for the Experiential E-Commerce Conference, Michigan State University, East Lansing, MI Please do not cite or quote this paper without permission.
Susan M. Lloyd Doctoral Candidate University of Illinois, Urbana-Champaign 1206 South Sixth Street 339 Wohlers Hall Champaign, IL 61820
[email protected] September 2001
Towards a More Complete Understanding of Consumers’ Experiences at E-Commerce Web Sites: A Post-Humanist Perspective1 Susan M. Lloyd, University of Illinois at Urbana-Champaign Working Paper Prepared for the Experiential E-Commerce Conference, Michigan State University, East Lansing, MI September 2001 Please do not quote or cite this paper without permission The E-Commerce Experience In marketing, the term “experience” has been used in many ways. In one common use, experiences refer to memorable hedonic consumption events that are centered primarily on services and processed consciously (based on Pine II and Gilmore 1998). Examples of such experiences include a trip to Disneyland or a Bob Dylan concert. But experiences can be conceptualized more broadly in two ways. First, they can focus on products. Second, they can be composed of perceptions and actions that are non-conscious; i.e., initiated by external factors and processed outside consumer awareness. Such “automatic” behaviors are unintended and effortless; they tend to occur quickly and are estimated to drive human behavior up to ninety-five percent of the time (Bargh and Chartrand 1999). Consider a woman visiting the e-commerce web sites of classy Beverly Hills boutiques. The computer, a product, provides the gateway for this virtual retail experience. Moreover, although part of the woman’s experience may stem from the color and placement of objects on the screen, he or she may be unaware of their impact. As this example illustrates, the consumer’s browsing and shopping experience at ecommerce web sites involves interactions with both products and services; the online e-
1
A more general version of this article that explores consumer interactions with a broader range of high-technology household products, is currently being prepared for publication.
commerce experience also involves perceptions and actions that are both conscious and nonconscious. Thus, on an external (or observable) basis, a consumer who shops online interacts with two intertwined and inter-related information technology products, namely, a computer and an Internet browser. Moreover, the consumer uses these products to gain access to virtual retail services available on e-commerce web sites. As a result of the juxtaposition of information technology products and virtual services in the e-commerce environment, the consumer’s online shopping experience can be conceptualized as one that is technology-mediated (Hoffman and Novak 1996). In addition, online shopping involves conscious processes (such as typing in the URL of a hip clothing company you saw advertised in Vogue magazine or checking the site’s privacy statement to see if the company will give your name and email address to other vendors) as well as non-conscious processes. One type of non-conscious process is goal-dependent automaticity; a learned repetitive behavior that is “self-propelled” (Bargh and Chartrand 2000). For example, on a given day, a consumer who enjoys monitoring the stock market “suddenly” finds himself shopping options on a brokerage firm web site even though he got online with the intention of shopping for airline tickets for an upcoming trip. This web-based example is analogous to the scenario wherein a consumer who drives to work each morning gets in the car on Saturday intending to do the weekly grocery shopping, but inadvertently ends up heading to work because the car took her there. A second type of non-conscious process is pre-conscious processing, in which people react to stimuli before they become aware of its existence, or indeed, without ever becoming aware of it at all (Bargh and Chartrand 1999). For example, mere exposure to a brand name (in which the exposure can not later be recalled) may result in a more favorable attitude toward that brand (Janiszewski 1993).
As illustrated in the above discussion, experiences are multi-dimensional: they can be centered around product or around services; they can be composed of perceptions and actions that are conscious and non-conscious. Also inherent in the above discussion is an operational definition of experience that is somewhat different than that used in previous literature. This definition of experiences as a series of interactions between consumers and information technology products that facilitate movement toward some end-state, will be used as a springboard to introducing post-humanism, a new perspective for understanding the e-commerce experience. The objectives of this paper are (1) to review existing and critique approaches and frameworks for studying e-commerce experiences, (2) to present a new perspective, posthumanism, which provides an alternative conceptual basis for thinking about consumers’ online e-commerce experience; and based on this perspective (3) to discuss methodological implications and research questions that can effectively uncover new insights about the online experiences. This paper is organized as follows. First, I will discuss and critique existing perspectives for understanding the e-commerce experience that have been introduced to or are relevant to marketing: the experiential value associated with shopping as a consumption activity, the technology acceptance model, and “flow” in the hypermedia online environment. Next, I will briefly introduce post-humanism, a perspective from sociology that was developed to explain the activities and processes underlying scientific practices and technological devices. I will then demonstrate how post-humanism can help us to understand consumers’ e-commerce experiences, and, finally, explore some methodological implications for using a post-humanist perspective.
Existing Approaches to Understanding Consumers’ E-Commerce Experiences Increasingly, more and more research articles are being written and published on what may be broadly referred to as the e-commerce experience (e.g., Hoffman and Novak 1996; Mathwick, Malhotra, Rigdon 2001; Morris and Turner 2001; Wolfinbarger and Gilly 2001). While some of this research applies ideas developed originally for the offline shopping context to the Internet environment, other research on the e-commerce experience draws from literature outside the discipline of marketing. In this section, three literatures will be briefly reviewed: the experiential value associated with shopping as a consumption activity, the technology acceptance model, and “flow” in the hypermedia computer-mediated environment. Experiential Value Associated with Shopping In terms of the length of its “history” in marketing, the experiential value literature is, perhaps, the oldest. The impetus for much of this research is rooted in a seminal article on the “experiential view,” which was introduced as an alternative to the traditional cognitive ® affective ® behavioral (or C-A-B) information processing model of consumer behavior (Holbrook and Hirschman 1982). Importantly, the experiential view focuses on highly sensitive or personal experiences, which are characterized as purchase and consumption processes that emphasize emotions, feelings, and sub-conscious thoughts (in which fantasies, daydreams, etc. exist as outward manifestations of the experience). Refinements to this approach, including the TEAV model (an acronym that stands for thoughts, emotions, activity, and value) and “hedonic consumption”, focus more centrally on emotions (particularly positive emotions) and consumption (Hirschman and Holbrook 1986; Hirschman and Holbrook 1992).
A natural extension of the experiential view was the development of the personal shopping values scale (PSV), which measures consumer perceptions of the utilitarian (goaldirected) and hedonic (entertainment or emotional) outcomes of in-store shopping (Babin, Darden, and Griffin 1994). Building upon previous research that describes utilitarian and hedonic shopping values, this study attempts to explicate the strength and direction of the relationship between the two types of values. Although the study focuses on value, the authors explicitly state that they draw upon an experiential perspective, defining value as “’an interactive relativistic preference experience … characterizing a subject’s experience of interacting with some object … [which] may be any thing or event’” (Holbrook and Corfman 1985 as appeared in Babin, Darden, and Griffin 1994). As introduced, the PSV scale had many potential applications, including an ability to help inform research related to various shopping contexts. In this vein, the concept behind the scale – of the two types of shopping values – rather than the scale itself has been used as framework for understanding the attributes of “high-quality, online shopping experiences” in the e-commerce context (Wolfinbarger and Gilly 2001, p. 36). Based on 9 focus groups (including 5 traditional focus groups in Southern California and 4 “online” focus groups with participants from throughout the U.S. and Canada), this study found that while most online shoppers have utilitarian motives (i.e., their shopping is goal-directed and efficient), some have hedonic motives (i.e., they shop “for fun”). Furthermore, utilitarian shoppers – the majority – revel in the freedom and control inherent in accomplishing tasks through e-commerce and point to the convenience (shop anywhere, anytime), merchandise selection, information-rich environment, and lack of social interaction as contributing to a highquality online e-commerce experience. On the other hand, hedonic shoppers – the minority – revel in the overall experience (as well as the goal) inherent in engaging in e-commerce. The
hedonic shoppers point to the bargains they find, their extensive involvement with the products they seek, the positive relationships they form online (with vendors or other enthusiasts), and an overall sense of excitement and surprise as the key factors contributing to a high-quality ecommerce experience. This research on utilitarian and hedonic online shopping experiences provides support in a shopping context for the findings of an earlier study that explores the longitudinal relationship between utilitarian and hedonic online activities (which may or may not include shopping per se) and the amount of previous background users have with the world wide web (Hammond, McWilliam, and Diaz 1998). The results of this study indicate that all users, regardless of the extent of their previous Internet background, perceive the web more in utilitarian terms (i.e., as a source of information) than in hedonic terms (i.e., as a source of fun or entertainment). While this perception is most pronounced among the advanced users (both at the initial period of data collection and four months later), change in perception is most rapid for novices who, at time two, report more trust of web sites’ informational content and less interest in its entertainment value. These findings suggest, and later studies support the idea that consumers will seek more utilitarian, goal-directed online experiences as they gain more knowledge of and practice with Internet media (e.g., Wolfinbarger and Gilly 2001; Novak, Hoffman, and Yung 2000). Some studies in the e-commerce experiential value stream are beginning to move beyond the simple utilitarian-hedonic dichotomy. For example, one recent study uses Holbrook’s extended typology of experiential value, a 2 x 2 framework that incorporates an activity dimension (passive or active) as well as the traditional outcomes dimension (utilitarian or hedonic), as a base for creating an experiential value scale (EVS) that can be applied to multichannel retail contexts (Mathwick, Malhotra, and Rigdon 2001). The four quadrants of this
typology are labeled (consumer return on investment, playfulness, aesthetics, and service excellence) and statistically identified as separate factors. Furthermore, a test of EVS indicates that it can predict differences in consumer preference and patronage intent for catalog shopping, e-commerce, and normal “brick and mortar” retail formats. Interestingly, while this study uses the same term – “experiential value” – as did earlier studies, it is defined somewhat differently as the benefit(s) derived from “interactions involving either direct usage or distanced appreciation of goods and services” (Mathwick, Malhotra, and Rigdon 2001, p. 41; italics added). Thus, in contrast to the PSV scale (cf. Babin, Darden and Griffin 1994), the EVS is somewhat more abstract in that it emphasizes benefits rather than preferences, and is clearly oriented to less traditional retailing formats in that it encompasses vicarious and computer/print-mediated shopping environments. Critique of the Experiential Value Literature The literature reviewed in the previous section can be classified as humanist in nature. By “humanist” I mean that this literature is based on the belief that human activities and intentions are responsible for shaping the world within which we live and the nature of the experiences in which we are engaged (Marshall 1998). Since it focuses exclusively on the motivations and emotions underlying shopping behaviors and e-commerce activities, the experiential value literature is clearly humanist. In fact, this literature is so strongly oriented to the human aspects of online shopping that almost no emphasis is placed on the unique qualities of the information technologies (i.e., the computer and the Internet) involved in the e-commerce experience. That is, the technologies are implicitly included in the research as entities that are acted upon by humans, rather than explicitly as entities that pro-actively shape and influence the e-commerce milieu.
In addition to the humanist orientation of the experiential value literature, two other points can be made. First, this literature emphasizes conscious aspects of the online shopping experience. That is, it emphasizes what consumers say they do, and what consumers say they feel: basically, the actions and emotions of which they are consciously aware. Moreover, these actions and emotions are characterized not only by awareness, but also by salience. They are the ones that people remember after-the-fact, be it minutes, hours, days or weeks after the actual online shopping experience. Second, the experiential value literature is outcome-oriented. The studies focus on marketing or behavioral outcomes of the online experience (such as its benefits or value) rather than the process or actions that occur as the experience unfolds. One possible explanation for this outcome orientation is that it follows naturally from the definitions of experience provided in the studies, which highlight benefits and value. In addition, two of the studies focus specifically on the development of a scale to measure the outcome condition. The Technology Acceptance Model The technology acceptance model (TAM) is the premier of several models developed in information systems to explain and predict end-user acceptance/rejection of computer hardware/software and other office technologies in organizational settings (Davis, Bagozzi, and Warshaw 1989). TAM is an important literature for understanding human-computer interactions for two reasons. First, while it incorporates issues associated with the adoption of computing technologies, it stretches beyond this to include consumption (or use) as a key outcome (or dependent variable). Second, TAM has gained widespread acceptance in the information systems field because it is parsimonious, it has high explanatory power (predicts, on average, 40 percent of the variance in the intention to use an information system and/or actual use), and its
results have been replicated for many office technologies (Venkatesh and Morris 2000; Agarwal and Prasad 1999). Although TAM was originally designed for the organizational setting, rather than the consumer setting, it is applicable to the latter because it explores the dynamics surrounding voluntary use of computer-based systems. The technology acceptance model is rooted in psychology in that it is a specific variant of the theory of reasoned action. The key tenet of the “classic” TAM is that attitudes toward office technologies determine intentions to use those technologies, which in turn, determine whether and to what extent they will be actually used. Importantly, attitudes in TAM are based on two specific, independent beliefs about information technology systems: their “usefulness” and their “ease of use”. Usefulness is defined as “the prospective user’s subjective probability that using a specific application system will increase his or her job performance” (Davis, Bagozzi, and Warshaw 1989, p. 985). And ease of use is defined as “the degree to which the prospective user expects the target system to be free of effort” (p. 985). With regard to the belief variables, usefulness is a strong direct determinant of intention for many information systems with a regression coefficient ranging from .40 to .60 (e.g., Venkatesh and Davis 2000; Karahanna and Straub 1999). Ease of use has a smaller effect and is less consistent across studies; its influence is sometimes direct and sometimes indirect (i.e., mediated through usefulness). That is, as people gain experience with a system, it becomes easier to use and is considered more useful. Greater perceived usefulness, in turn, leads to a stronger intention to use the system. During the past decade-plus since the technology acceptance model was introduced, many extensions to the model have been developed and studied. One extension particularly relevant to the discussion at hand involves the “experience” construct. In most of these cases,
however, experience has been incorporated as an objective construct that refers to one’s amount of prior computer use, the opportunity to use specific hardware or software, or the diversity of software applications previously used (e.g., Agarwal and Prasad 1999; Jackson, Chow, and Leitch 1997). More recently, the role of subjective aspects of experience is beginning to be explored, specifically with regard to use of computer media. In one study (where usage intention was recast in loyalty-like terms as “intention to re-use a website”) a set of external variables representing web site quality was included as an antecedent to the belief variables (Lin and Lu 1999). Web site quality, which can be construed as a proxy for one’s subjective experience with the web, was comprised of three variables: perceived information quality, response time (the time needed for web pages to download), and site accessibility. The pattern of results generally corresponded to the classic TAM; i.e., 64 percent of intention to re-use a website was explained by the belief variables, with usefulness having a stronger influence than ease of use. Moreover, of the antecedent variables, response time was found to predict both belief variables, suggesting that it is more important than either information quality or site accessibility in website design. In contrast to Lin and Lu (1999) who incorporate factors of web quality that were identified in an earlier study on information technology product success, Morris and Turner (2001) more specifically identify the factors associated with the quality of one’s Internet experience, defined in utility terms as “those factors or circumstances which influence how successfully [the Internet] does what is needed functionally” (p. 880). In asking consumers about their Internet experiences and then conducting follow-up statistical tests, ten critical elements of high-quality Internet experiences are identified. These elements are information relevance, information quantity, information availability at remote servers, organization of
information within web sites, clarity of navigation instructions at web sites, currency of web links, search engine options, how easy the browser is to use, security/privacy, and connection reliability. Furthermore, it is hypothesized that the factors associated with high-quality (or lowquality) Internet experiences may mediate between the belief variables that predict use and actual usage behaviors. In this way, subjective experience may help explain temporal changes in technology acceptance. Critique of the Technology Acceptance Model According to the technology acceptance model, decisions to adopt and use a specific hardware system or software application are determined primarily by beliefs that reflect end-user perceptions of a given information technology product (specifically its usefulness and ease of use). This emphasis on human control suggests that TAM is, like the experiential value literature, largely humanist in nature. The choice of whether or not to use a computer and which software package to select are not always left up to the end-user, however. In practice, oftentimes, particularly in organizations, these choices are involuntary. Such “captive use” suggests that it is not the end-users, but rather, the information systems professionals who, ultimately, are the humans in control of these computing systems. In fact, in many ways, the roles of both the end-user and the technology itself pale in comparison to the very dominant role of the information systems professional. Although both the belief variables and the quality of experience variables suggest, by their nature, that the success of an online experience involves a matching of user needs with technological capabilities, both the end-user and the computing systems are, essentially inert. Only the information systems professionals truly have an active role to play. And the technology
acceptance model helps to identify variables within the computing environment that these professionals can most readily address, such as usefulness and ease of use. In addition to its humanist cast, TAM, like the experiential value literature, considers only the conscious aspects of the computer experience. The belief variables (usefulness and ease of use) were originally identified as part of a focus group exercise and the ten critical elements of a high-quality online experience were gleaned through general, open-ended questions that did not relate to a specific online episode. “Flow” in the Hypermedia Computer-Mediated Environment Flow is a concept from the field of human-computer interactions (cf. Czikszentmihalyi 1990) that has been used to describe a “compelling online experience” (Novak, Hoffman, and Yung 2000). Flow within the Internet and world wide web environments has been defined as “the state occurring during network navigation, which is (1) characterized by a seamless sequence of responses facilitated by machine interactivity, (2) intrinsically enjoyable, (3) accompanied by a loss of self-consciousness, and (4) self-reinforcing” (Hoffman and Novak 1996, p. 57). More broadly, it has been defined as an optimal experience that arises when a high level of challenge is balanced by an equally high level of skill (Chen, Wigand, and Nilan 1999). Czikszentmihalyi’s nine dimensions of flow have been incorporated with several other constructs to form a process model of network navigation in online environments (Hoffman and Novak 1996), which has been modified and empirically tested using structural equation models (Novak, Hoffman, and Yung 2000). Not surprisingly, several of the model constructs – including telepresence/time distortion, exploratory behavior, challenge/arousal, focused attention, and flow – are more strongly associated with experiential (i.e., hedonic) online
activities, while one construct – skill/control – is more strongly associated with task-oriented (i.e., utilitarian) online activities. With regard to e-commerce, a supplemental online survey indicates that website features that simplify and facilitate online shopping (such as easy ordering, easy payment, quick delivery, and particularly, customer support) are important for creating a compelling experience. Other factors, specifically reliability, security, and low price are equally important for all experiences. Critique of the Flow Literature In contrast to the experiential value literature and the technology acceptance model, the flow literature begins to consider the unique qualities of Internet technologies and their role in establishing a compelling online experience. However, in many ways, this literature is still primarily humanist. For instance, consider interactivity, a key conceptual underpinning of the process model. Online environments are characterized by two types of interactivity: person interactivity and machine interactivity. The former refers to the fact that online technologies serve as a media through which persons can communicate. The latter refers to the ability of users to “’participate in modifying the form and content of a mediated environment in real time’” (Steuer 1992, as appeared in Hoffman and Novak 1996, p. 53). Clearly, both types of interactivity are humanist in nature: the action is centered around the humans (that is, the users) not the information technologies, per se. Thus, it appears that while characteristics of the ecommerce environment are addressed in the flow literature, they are cast largely in humanist terms. In addition to its humanist slant, the flow literature, like the experiential value literature and the technology acceptance model, focuses on the conscious elements of the online experience. The basic premise underlying the research is that the factors that comprise a
compelling online experience are also the ones that users are able to consciously remember and identify with What Existing Approaches Tell Us about Consumers’ Online Experiences: Summary and Shortfalls The three literature streams reviewed in this section – experiential value of shopping, technology acceptance model, and flow in the hypermedia environment – can all be classified as humanist in nature. This means that in these approaches to understanding consumer interactions with information technologies such as e-commerce, the humans (including consumers, other endusers, and information systems professionals) are responsible for weighing all the options, making all the decisions and implementing all the resulting changes. “Things” (i.e., computers and web site content) are largely inert; they exist, they may be modified to better meet human needs, but they do not actively do anything. In other words, these technologies do not act; rather, they are acted upon. All three literature streams also emphasize conscious aspects of the experience. Typically, these aspects represent the most salient memories research subjects have their previous online shopping activities and they are often elicited in a general way, rather than being tied to a specific recent experience. Thus, they may reflect “after-the-fact” rationalizations that may not correspond precisely with what actually happened. Despite the fact that the influence of technology products and non-conscious processes have been overlooked in understanding e-commerce experiences, they remain important. Fundamentally, as the reviewed literature suggests, e-commerce experiences involve consumers and technology products. Moreover, some psychologists estimate that non-conscious processes drive human behavior up to 95 percent of the time (Bargh and Chartrand 1999). Thus, the role
and influence of technology products and non-conscious processes deserve to be better understood. To better explore these aspects of the e-commerce experience, I now turn to posthumanism. Brief Introduction to Post-Humanism Post-humanism is a perspective originally developed in sociology to explain the activities and processes underlying scientific inventions as well as technological devices and practices. As such, it provides a way of thinking about and understanding the complex relationship between “humans” (e.g., consumers) and “things” (e.g., inanimate, material objects, such as personal computers, and e-commerce web sites) in everyday life. In this section, I will sketch out the broad outlines of post-humanism. First, I will describe the three key tenets of post-humanism, and in so doing, contrast post-humanism with the humanist perspective exemplified by the three literature streams I reviewed in the previous section. This will be followed by a very brief discussion of one specific approach to post-humanism, the mangle of practice. And then in the next section, I will begin to explore how post-humanism can help us to better understand consumers’ online experiences. Key Tenets of Post-Humanism Post-humanism is based on the premise that humans and things are jointly responsible for shaping the series of interactions that comprise an experience. That is, both humans and inanimate material objects play an active role in shaping their interactions with one another – they both do something (Latour 1988; Callon and Law 1989). On this basis, post-humanism can be distinguished from humanism, a “… wide-ranging set of philosophies [characteristic of the social sciences] that have at their core the belief that human interests and dignity should be of primary importance” (Marshall 1988).
Post-humanism can be broadly described by three tenets: temporality, de-centering, and unpredictability. Let me briefly describe each of these in turn. First, experiences with information technology experiences are temporal; that is, they occur over time (Pickering 1993). And, in fact, the actual series of interactions between humans and non-humans that occur “in the moment” may be remembered differently “after-the-fact” when humans have had a chance to rationalize (or re-construct) the events that have occurred. Second, experiences with information technology products are de-centered in that they are not totally under human control. Rather, such experiences arise from interactions between two sets of actors – human and non-human material objects – in which they become entangled and thus, act upon and change each other. Moveover, after they entangle, the actors are irreducible; that is, it becomes difficult (or impossible) for them to revert back to their original state (Callon and Law 1989; Pickering 1995). Fundamentally, interactions among the actors are two-way, allowing both entities to exhibit “agency,” such that their actions and behaviors influence (or shape) the use experience. Finally, the actions of non-human actors – as well as the consequences of these actions – are often unexpected and thus, difficult to predict in advance. Consider three examples. One – in 1968, an engineer in the Advanced Computing Systems Division of IBM gazed down at a computer chip and asked, “but what is it good for?”2 Today, products that contain computer chips can be found in every room of our homes and touch virtually every aspect of our lives. Two – fifteen years ago when personal computers were beginning to flood the home and workplace, the idea that keyboards could incite the onset of a medical malady (now known as carpal tunnel syndrome) was not foreseen. Three – even today,
2
Quote taken from Newell Frederick (2000), Loyalty.com: Customer Relationship Management in the New Era of Internet Marketing, New York, NY: McGraw-Hill, p. 91.
as we sit here now, can anyone state with absolute certainty that the electro-magnetic radiation emitted by computers is, as we are currently told, truly safe?3 The “Mangle of Practice” One approach to post-humanism is known as the mangle of practice (Pickering 1993; 1995). Simply put, the “mangle” refers to the entanglement between people and things that occurs in “practice” (e.g., during the span of time when consumers use computers/Internet to engage in an online shopping experience). On the most basic level, the mangle of practice consists of five principles. The first principle is intentionality. An experience begins when humans intentionally develop a goal. This goal typically involves the construction of some “thing” (e.g., the creation of a web page) or the realization of some event (e.g., the successful online purchase of some type of merchandise). In goal development, the human actor is in control. At this stage, there is no de-centering (Pickering 1993). The second principle is tuning. Tuning represents the process of reciprocal turn-taking between the human and non-human, material actors that begins after the goal has been established and that allows progress toward the goal to occur. Let’s consider the goal of purchasing accounting software online. At time 1, the consumer acts on the (currently passive) non-human, material object. He or she does something to the object, altering or using it in some way. (For example, the consumer turns on the PC, goes to a search engine to locate vendors who sell accounting software products and types in the term “small business accounting software”.) At time 2, the material object responds to the consumer’s actions. That is, the object acts on the (now passive) consumer. (For example, the search returns 20 hits, almost all of which provide 3
As is readily apparent, these three examples of unpredictability are all decidedly negative in nature. Unpredictable consequences can, of course, also be positive. However, negative consequences tend to be more salient to people
links to web sites that sell electronic counting toys for young children). The outcome of this action will modify or change the consumer’s expectations about the object in some way, and at time 3, the consumer will take her “turn,” acting on the (now passive) material object. (For example, the consumer decides to go to the URL address box and type what she guesses is the correct address for Lotus 1-2-3 because she remembers that several years ago, they offered an easy-to-use accounting software that was highly recommended by a professor at the local community college.) This process of turn-taking between the consumer and the material object continues through time 4, 5, 6, etc. In this manner, the online experience unfolds through a series of interactions. The third principle is interactive stabilization, a type of equilibrium that represents the achievement of the goal. In actuality, this goal may be the one that was originally developed, or it may be a modification of that original goal. For example, the consumer may decide to purchase a personal finance software suite that includes several basic accounting programs. At the point of interactive stabilization, the non-human actor is said to be “fully captured.” This means that an intimate connection has been established between the human and the non-human actors (in this example, between the consumer and the website at which the software was located). The two “emergently define and sustain one another,” resulting in a productive and stable relationship (Pickering 1995, p. 17). The last two principles are modeling and temporal emergence. The former refers to the actions of humans and the latter, to the actions of non-humans. In determining how to act at time 1 or how to react at later time periods, humans consider approaches and options – such as, in the example we have been following, search techniques and web browsing tactics – that already exist in their culture. Typically, human decisions and actions are based – at least loosely – on and thus, more powerful to communicate.
one (or more) of these existing options, rather than on something that is completely new. This process is called modeling (Pickering 1995). While the actions of humans tend to be fairly logical and well-grounded, the actions of non-human objects are not necessarily so. That is, the activities of non-humans (such as computers and web sites) can not always be determined in advance. Rather, from the perspective of humans, non-human material objects can transform themselves in unpredictable ways. These transformations are temporally emergent, meaning that consumers perceive that they “just happen” (Pickering 1995). Why Post-Humanism? Now that I have provided a thumbnail sketch of post-humanism, I would like to begin discussing how this perspective can provide useful insights for market and consumer behavior researchers. This will be, by necessity, a fairly short discussion, given the nature and scope of this paper.4 Lessons for Marketing and Consumer Behavior5 At first glance, post-humanism certainly enables us to tell a more complete story about consumers’ online shopping experiences. More importantly, it allows us to view these experiences from a new angle, a new vantage point. In marketing and consumer behavior, as in many of the social sciences, we typically view the world from the perspective of humans. In many ways, this emphasis on the human is one of the legacies of the Enlightenment that has been embodied in the philosophy of modernism. Modernism holds that there are two spheres of understanding: one dominated by the human (or social) element, and the other dominated by the 4
A more extensive treatment of these issues in relation to computers and other high-technology household products is currently being prepared for publication.
material, non-human element. Academic disciplines tend to fall into one of these two “camps”. For example, physics and chemistry tend to focus exclusively on the material, the non-human; on objects and “things”. Psychology, sociology, and marketing, however, tend to focus on people, on consumers, on what is going on in our minds and how we interact with one another. The key point is that, as researchers, we become indoctrinated into one of these two traditional academic camps. The risk is that we maintain the blinders we don and that we actively resist using an alternative perspective to look at the world and the phenomena that interests us. Of course, admitting that online experiences represent an intertwining of consumers and information technology, and that the role and influence of the technology are as important to study as are the role and influence of the consumer (or the sales clerk, or any other human) can be somewhat unsettling. But this openness to alternative perspectives is one of the lessons that post-humanism teaches us. A second lesson that post-humanism teaches us – and one that is, undoubtedly, equally unsettling – is the idea that the world around us is in constant flux. Essentially, post-humanism depicts the world as somewhat less stable place than what we currently assume. Post-humanism depicts an Information Age in which neither humans nor computers are fully “in charge”. It is a world in which we not only don’t know how to program our VCRs, but also is one in which we struggle with a host of computer-based “glitches” – that are both positive and negative. Thus, our online experiences (and, indeed, our experiences with computer-based products as a whole) are not only paradoxical (cf., Mick and Fournier 1998), but are also fraught with uncertainty and constant change.
5
This section incorporates ideas that arose in a discussion with Professor Andrew Pickering, University of Illinois, Urbana-Champaign.
Implications and Further Research By forcing us to look across the boundaries between people and things, post-humanism helps us to look at experiences in a new light. Coupled with this, post-humanism embodies a rather different definition of experience than has been used previously in marketing. As discussed earlier in this paper, the experiential literature is based on definitions of experience that emphasize either the benefits/value or the utility/success derived by consumers in their interactions with online vendors. Importantly, these definitions focus on outcomes. In contrast, a post-humanist definition of experience emphasizes the series of interactions that occur between consumers and information technologies that facilitate movement toward some end-state. This definition focuses on process. Such a definitional shift, coupled with the three tenets of posthumanism discussed earlier – temporality, de-centering, and unpredictability – provide the basis for methodological implications and research questions, as discussed in this section. Methodological Implications. “You can’t see the forest for the trees.” This saying highlights the fact that sometimes people become so focused on the details of a situation that they ignore (or can no longer see) the “big picture”. Post-humanism suggests that in an online experience the details (i.e., the individual interactions between consumers and online technologies) and the big picture (i.e., the outcomes or goals consumers pursue by using online technologies) are equally important. Moreover, post-humanism suggests that the details of interest are the ones people remember (i.e., conscious behaviors) as well as the ones of which they are not explicitly aware (i.e., non-conscious behaviors). Importantly, these details unfold over time, they represent reciprocal actions of people and technologies, and they may be difficult to predict in advance.
In keeping with the above discussion, “classic” post-humanist studies in sociology have used either ethnographic or case study methods. The case studies used in post-humanism have typically relied on secondary source data (cf. Pickering 1995), while the ethnographic studies have relied heavily on fieldwork that includes both participant-observation and interviewing. These techniques were used, for example, as a means of understanding how laboratory scientists at the Salk Institute construct scientific facts about neuroendocrinology (Latour and Woolgar 1979) and how scientists delineate the border between forest and savanna in the Amazon (Latour 1999). Indeed, ethnographic techniques dovetail nicely with post-humanism since they provide a way of studying processes, practices, or usage behavior in a step-by-step fashion as it unfolds over time in a natural environment, rather than in a laboratory setting. Although the ethnographic approach is consistent with post-humanism, this method does not necessarily translate easily to the online e-commerce environment (Hine 2000). First, since online shopping is often done spontaneously (in odd free moments rather than as part of a preplanned session) and is usually engaged in in the privacy of one’s own home, it can be difficult for the researcher to immerse himself in his informants’ online shopping milieu. Moreover, since online shopping is typically a personal activity, it can be difficult for researcher to truly participate in the action at the time it occurs. Nonetheless, ethnographic techniques (rather than the formal ethnographic method per se) can be profitably employed under the rubric of posthumanism, as discussed below.6 First, in order to understand the processes inherent in the e-commerce experience and how they unfold to produce planned (or un-planned) outcomes, interviews and non-participant observation should both be used. Essentially, the two methods yield different, but complementary data. Interviews, of course, provide retrospective data about behaviors, attitudes,
and feelings that are conscious as well as salient. In effect, interviews reflect people’s understandings and after-the-fact rationalizations. Observations, however, provide real-time data that depict the behaviors that actually occur. Importantly, observation offers a window to conscious and non-conscious behaviors, allowing the researcher to “… see things that may routinely escape conscious awareness among [informants] … discover things no one else has ever really paid attention to … [and] move beyond the selective perceptions of others” (Patton 1990, p. 204). Second, research on the online experience should be longitudinal. The de-centering and the unpredictability that are characteristic of e-commerce experiences emerge in real-time. To see how they emerge and the impact/consequences they have, a longitudinal perspective is required. Moreover, in this way, the story of the e-commerce experience is developed from the ground-up. Research Questions. By using a post-humanist perspective, e-commerce researchers can begin to identify new lines of inquiry. Let me provide a brief example, using the concept of control in the e-commerce environment. A post-humanist perspective suggests that, over time, control in the Internet environment rotates (or “circulates”) between the consumer and the online technology. This suggests a range of research questions: Who is in control at what points in the e-commerce experience? What factors influence how and when control is ceded between the consumers and the online technologies? What impact(s) does control have on trust? On purchase intention? On loyalty? On alternate retail channels given multi-channel choices? Conclusion This paper reviews three existing approaches from the marketing and information systems literature – experiential value, the technology acceptance model, and flow in the 6
See Wolcott (1999) for a full discussion of ethnographic technqiues vs. formal ethnographic method.
hypermedia online environment – that speak to consumers’ online shopping experience. The argument is made that these approaches, while useful, can not tell the whole story because they emphasize the role of human actors and conscious processing. In so doing, they tend to assume that the technologies associated with the online experience are largely inert, in that their influence is exerted almost wholly through human manipulation rather than computer/Internet autonomy. Post-humanism, a perspective from sociology, is introduced to help round out the story of consumers’ online shopping experience. Post-humanism focuses on the interplay – or dialectic – that occurs between consumers and complex, high-technology products (such as computers and the Internet) in the online environment. In forcing us to consider online technologies as active co-creators of the e-commerce experience, post-humanism can help us transcend more traditional ways of researching and thinking about this phenomenon. REFERENCES Agarwal, Ritu and Jayesh Prasad (1999), “Are Individual Differences Germane to the Acceptance of New Technologies?” Decision Sciences, 30 (Spring), 361-391. Babin, Barry J., William R. Darden, and Mitch Griffin (1994), “Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value,” Journal of Consumer Research, 20 (March), 644-656. Bargh, John A. and Tanya L. Chartrand (1999), “The Unbearable Automaticity of Being,” American Psychologist, 54 (7), 462-479. ----- and ----- (2000), “Mind in the Middle: A Practical Guide to Priming and Automaticity Research,” in Handbook of Methods in Social and Personality Psychology, (eds.) Harry T. Reis and Charles M. Judd, Cambridge, UK: Cambridge University Press. Chen, Hsiang, R.T. Wigand, and M.S. Nilan (1999), “Optimal Experience of Web Activities,” Computers in Human Behavior, 15 ( ), 585-608.
Davis, Fred D., Richard P. Bagozzi, and Paul R. Warshaw (1989), “User Acceptance of Computer Technology: A Comparison of Two Theoretical Models,” Management Science, 35 (August), 982-1001. Hammond, Kathy, Gil McWilliam, and Andrea Narholz Diaz (1998), “Fun and Work on the Web: Differences in Attitudes between Novices and Experienced Users,” in Advances in Consumer Research, (eds.) Joseph W. Alba and J. Wesley Hutchinson, Provo, UT: Association for Consumer Research. Hine, Christine (2000), Virtual Ethnography, Thousand Oaks, CA: Sage Publications. Hirschman, Elizabeth C. and Morris B. Holbrook (1986), “Expanding the Ontology and Methodology of Research on the Consumption Experience,” in Perspectives on Methodology in Consumer Research, David Brinberg and Richard J. Lutz (eds.), New York, NY: Springer-Verlag, 213-251. ----- and ----- (1992), “Hedonic Consumption: Emerging Concepts and Propositions,” Journal of Marketing, 46 (Summer), 92-101. Holbrook, Morris B. and Elizabeth C. Hirschman (1982), “The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun,” Journal of Consumer Research, 9 (September), 132-140. Hoffman, Donna L. and Thomas P. Novak (1996), “Marketing in Hypermedia ComputerMediated Environments: Conceptual Foundations,” Journal of Marketing, 60 (July), 6068. Jackson, Cynthia M., Simeon Chow, and Robert A. Leitch (1997), “Toward an Understanding of the Behavioral Intention to Use an Information System,” Decision Sciences, 28 (Spring), 357-389. Janiszewski, Chris (1993), “Preattentive Mere Exposure Effects,” Journal of Consumer Research, 20 (December), 376-392. Karahanna, Elena, and Detmar W. Straub (1999), “The Psychological Origins of Perceived Usefulness and Ease of Use,” Information & Management, 35 (April), 237-250. Latour, Bruno and Steve Woolgar (1979), Laboratory Life: The Construction of Scientific Facts, Princeton, NJ: Princeton University Press. ----- (1988), The Pasteurization of France, London, England: Harvard University Press. ----- (1999), Pandora’s Hope: Essays on the Reality of Science Studies, Cambridge, MA: Harvard University Press.
Lin, July Chuan-Chuan and Hsipeng Lu (1999), “Towards an Understanding of the Behavioral Intention to Use a Web Site,” International Journal of Information Management, 20 ( ), 197-208. Marshall, Gordon (1988), A Dictionary of Sociology (2nd edition), Oxford, UK: Oxford University Press. Mathwick, Charla, Naresh Malhotra, and Edward Rigdon (2001), “Experiential Value: Conceptualization, Measurement, and Application in the Catalog and Internet Shopping Environment,” Journal of Retailing, 77 (Spring), 39-56. Mick, David Glen and Susan Fournier (1998), “Paradoxes of Technology: Consumer Cognizance, Emotions, and Coping Strategies,” Journal of Consumer Research, 25 (September), 123-143. Morris, Michael G. and Jason M. Turner (2001), “Assessing Users’ Subjective Quality of Experience with the World Wide Web: An Exploratory Examination of Temporal Changes in Technology Acceptance,” 54 (June), 877-901. Novak, Thomas P., Donna L. Hoffman, and Yiu-Fai Yung (2000), “Measuring the Consumer Experience in Online Environments: A Structural Modeling Approach,” Marketing Science, 19 (Winter), 22-42. Patton, Michael Quinn (1990), Qualitative Evaluation and Research Methods (2nd edition), Newbury Park, CA: Sage Publications. Pickering, Andrew (1993), “The Mangle of Practice: Agency and Emergence in the Sociology of Science,” American Journal of Sociology, 99 (November), 559-589. ----- (1995), The Mangle of Practice: Time, Agency, and Science, Chicago: The University of Chicago Press. Pine II, B. Joseph and James H. Gilmore (1998), “Welcome to the Experience Economy,” Harvard Business Review, 77 (July/August), 97-105. Venkatesh Viswanath and Fred D. Davis (2000), “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Management Science, 46 (February), 186-204. Wolfinbarger, Mary and Mary C. Gilly (2001), “Shopping Online for Freedom, Control, and Fun,” California Management Review, 43 (Winter), 34-55. Wolcott, Harry F. (1999), Ethnography: A Way of Seeing, Walnut Creek, CA: Altamira Press.
