JOURNALOF CONSUMER PSYCHOLOGY, 13(1&2),17-27 copyrightO 2003, Lawrence Erlbaurn Associates, Inc.
Web-Based Chatting: Consumer Communication in Cyberspace George M. Zinkhan Department of Marketing University of Georgia
Hyokjin Kwak Department of Marketing Drexel University
Michelle Morrison Department of Psychology University of Georgia
Cara Okleshen Peters Department of Marketing University of Georgia
The World Wide Web has the potential to change much about consumer behavior and consumer communication.Web-based chatting, the focus of this study, is one example. In this article, we provide an illustrative description of various consumer chatting situations, examine the motivations underlying Web-based chatting, and discuss the ways in which chatters act as "nai've marketers" in their attempt to attract chatting partners. Using information gathered through the combined use of an Internet survey and a content analysis, we explore five research questions: who chats, why individuals chat, how chatters communicate, what links exist between Web chatting and other consumer behaviors, and which factors lead to a successful chatting experience? The findings provide some insight into how consumers market themselves in cyberspace and the effectiveness of their "personal advertisements" in attracting other chatters. In recent years, Internet use has grown in popularity for both individuals and companies, and projections indicate continued growth. According to Nielsen Media Research and CommerceNet (CommerceNet, 1999), over 120 million people use the Internet worldwide, and the value of electronic commerce transactions exceeds U.S. $9 billion. Academic researchers have examined several aspects of Internet usage, including online consumer behavior (Geissler & Zinkhan, 1998), Internet advertising strategy (Leong, Huang, & Stanners, 1998), electronic marketing strategy (Quelch & Klein, 1996), and the economics of the Internet (Bakos, 1997). However, an important yet often neglected aspect of academic research Requests for reprints should be sent to George Zinkhan, University of Georgia, Marketing Department, 6258, 138 Brooks Hall, Athens, GA 30602-6258. E-mail:
[email protected]
concerns how consumers use the Internet as a means of communication. Web-based chatting is one such medium. Web-based chatting has increased in popularity in recent years (Kwak, Zinkhan, & Pitt, 2001). America Online (AOL), the biggest Internet service provider, estimates that 10 million consumers spend approximately 25% of their online time engaged in Web-based chatting in one of 18,000 chat rooms (Marsh, 1997). Internet chatting provides companies, as well as individuals, with new methods for communication. Today, chat is an important component of many commercial Web sites, as well as public sites such as the U.S. Government. Chat rooms are used for relationship marketing and can enhance the recognition of products and services. It is estimated that installations of chat programs on a Web site can increase consumers' visits by 50%, it can keep
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ZINKHAN, KWAK, MORRISON, OKLESHEN PETERS
consumers on the Internet site 30% longer, and it can increase online purchases by 41% (Business Wire, 1998). At the individual level, Web-based chatting allows people to advertise personal information on a Web chat server. In recent years, a number of individuals looking to post personal advertisements have moved away from news articles because they feel restricted by some of the regulations imposed by the print media, such as the limitation on the number of lines of text allowed and the prohibition of sexual content. Therefore, some individuals are now moving to Web-based classified ads and chatting servers to post personal advertisements. To encourage Web-based chatting, most online chat servers recommend that chatters register information such as birth date, age, gender, hobby, and comments with the service. Computer technology makes it easy to find people with the same or similar interests. For example, many online chat services offer databases of chatter-created profiles, searchable by scrolling a computer screen or clicking on key words to locate particular information. These profiles can be anonymous which, in and of itself, may be an attractive component for people interested in chatting on the Web. More than 50,000 online chatters, on hundreds of servers around the world, get together each night to discuss their interests (Smith, 1997).
CONSUMER BEHAVIOR IN VARIOUS CHATTING SITUATIONS It is difficult to explain Web-based chatting with a single definition. Consumers in cyberspace are not driven by a single motivation, and online chatting is not impeded by a single barrier. Through qualitative data collected previously (Kwak, 2001), we uncovered some general motivations behind consumers' Web chatting. These motivations include information seeking, an opportunity to experience a brush with greatness, problem solving, social bonding, needs for affiliation, and addiction. Despite recognizing the positive aspects of Web chatting, some individuals are apprehensive about this form of communication. Our research identifies three types of barriers to online chatting: lack of personal connection, social sanction, and lack of reality (Kwak, 2001). This research examines the motivations individuals give for Web-based chatting and attempts to understand the breakdown of barriers to online chatting. In this article, we view Web-based chatting as an online tool that allows for interactive consumer communications, both socially and commercially. We focus on Web-based chatting as a human behavior and a consumer behavior. Our research focuses not on purchase behaviors or consumer perceptions of marketing phenomena created by professional marketers but, instead, concentrates on the ways that consumers market themselves on the Web. We create a profile of
Web chatters and explore what makes a potential chatter's "personal a d attractive to other chatters. Thus, the purpose of this article is to focus on the consumer behavior of Web chatters and, specifically examine how they market themselves on the Web. To that end, we investigate five basic research questions: who chats, why individuals chat, how chatters communicate, what links exist between Web chatting and other consumer behaviors, and which factors lead to a successful chatting experience? Microsoft NetMeeting (MNM), one of the popular multimedia-based chatting servers with a worldwide following, is used to explore several aspects of consumer chatting behavior. An Internet survey is used to collect data from individual MNM users to address specific research questions (e.g., How often do chatters connect to MNM to chat? To what extent does chatting on the Internet impact the time an individual spends using other media sources?). In addition to the survey, a content analysis is conducted using the personal advertisements posted by chatters logged on to MNM to understand the factors that lead to successful chatting experiences (e.g., the variables most likely to attract other chatters to a personal advertisement). There are many kinds of chatting situations in cyberspace. However, two major chatting situations exist--commercial chatting and social chatting. Commercial chatting can be defined as online consumer communications for the sake of sharing and exchanging information about specific products or services. Commercial chatting includes consumer-to-consumer chatting and business-to-consumer chatting. Consumer-toconsumer chatting can take the form of company-sponsored chatting, media-sponsored chatting, or third-party-sponsored chatting. Consumers who engage in company-sponsored chatting can obtain information about specific products and services from both the marketers who sponsor the virtual community and the community members. As opposed to consumer-to-consumer commercial chatting, business-to-consumer chatting focuses mainly on customer care. Customer-care-oriented chatting attempts to strengthen the association between business employees and customers. If a customer has aproblem with a product or service, this chatting situation allows the customer to chat with a firm's customer service employee to solve the problem. Social chatting is defined as consumer communications to develop and enhance the relationship between individuals in a social context. Social chatting encompasses group chatting and individual chatting. In a group chatting situation, the conversation has predetermined topics and group identifications, organized by either a third party (e.g., chat.yahoo.com) or specific individual chatters who are providing space for chatting through a third party. In an individual chatting situation, a single individual hosts a chatting session with another individual. The host has a right to accept or reject other's chatting requests. Therefore, the topic for chatting is initially determined by the host and chatting continues only if the two chatters share common
WEB-BASED CHATTING
interests. There are two types of individual chatting: chatting used as a dating service and chatting as a means of making friends. Whereas the dating service mode of chatting provides virtual opportunities to initiate and develop interactions that further human dating rituals, the contents of the friend-making chatting situation are likely to be parasocial (e.g., to explore how other people live), entertainment (e.g., to waste time), information-driven (e.g., to gain knowledge from someone who better understands an area of mutual interest), and subject oriented (e.g., to find another individual who shares your interests, hobbies, or demographic profile). However, consumers may go back and forth between "dating" and "friend-making" even within the same chatting session. MNM is an example of a server that provides such environments. Although we have identified many chatting situations and their relationship to consumer behavior in cyberspace, two types of individual social chatting situations (i.e., dating, friend-making) are the main focus of this article.
Conceptual Overview Motivations underlying Web-based chatting. Because there is very little theory specifically related to Web chatting and the exploratory nature of this research, we examine various literatures to gauge the potential motivations that underlie Web chatting. McClelland is credited with authoring the seminal work on motivations in the field of psychology. He defined a motive as "a recurrent concern for a goal state based on a natural incentive-a concern that energizes orients and selects behavior" (McClelland, 1987, p. 590). McClelland (1953, 1955, 1961, 1987) identified four major motive systems, including (a) achievement, (b) affiliation, (c) power, and (d) uniquenesslnovelty. In the e-commerce literature, Zinkhan, Conchar, Gupta, and Geissler (1999) apply McClelland's motive systems to the creation of personal Web pages. They find evidence that these motives, combined with more postmodern motives, underlie consumers' designs of Web pages. The most relevant of McClelland's (1987) psychological motives to apply to web chatting is afiliation, which is defined as "the need to be with people" (p. 347). Affiliation encompasses maintaining interpersonal networks. Zinkhan et al. (1999) found that consumers design Web pages for purely social purposes. However, they also suggest that online communication allows consumers to interact socially and experience affiliation, albeit at a physical distance. Work in the field of communication is even more specific in that it addresses the motivations that underlie media use and the resulting gratifications. Rubin (1984) is the preeminent scholar in media uses and gratifications and identified (a) goal-directed and (b) habitual motivations for television viewing. When consumers are goal-directed, they are motivated to watch those television shows that fulfill their need for entertainment and information. When con-
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sumers have habitual motivations, they are filling time and have a need for companionship, relaxation, arousal, and escape. Also published in the communication literature, Lull (1980) investigated the social uses of television. He found two overarching uses of television: (a) structural and (b) relational. A structural motivation for the medium's use encompasses using television to fill the environment, such as for entertainment, and regulative, for punctuation of time and activity. Relational motivations for television use include communication facilitation, such as conversation, affiliation, and relationship maintenance, social learning, including decision making and information gathering, and competenceldominance, such as intellectual validation or gatekeeping. Maignan and Lukas (1997) applied Lull's theory to the nature and uses of the Internet. When they interviewed consumers, they found that most people viewed the Internet as a source of information, aplace or object of consumption, and a communication tool. Supporting Maignan and Lukas' (1997) finding linking the Internet to a consumption motive, work by Burke (1997) and Peterson, Balasubramanian, and Bronnenberg (1997) found that convenience is the primary motivation underlying Internet shopping. We anticipate that aspects of the motivations delineated previously will emerge as the motivations underlying web-based chatting. Consumers will have basic motivations that are goal-directed or structural, including entertainment, information, regulation of time or activities, consumption, and convenience. In addition, we expect to find that consumers will also have basic motivations that are habitual or relational, including companionship, relaxation, arousal, escapism, relationship maintenance, and communication. Therefore, these basic motivation systems will be tested in our application.
Thejargon of Web chatting. The marketing literature has also begun to examine the connection between vocabulary and consumer behavior. West, Brown, and Hoch (1996) suggested that consumers develop and use consumption vocabularies. Their results indicate that when consumers are provided with a consumption vocabulary, it shapes their preference formation. Their findings reveal that consumers can develop consumption vocabularies that influence the development of stable, well-defined preferences. Okleshen and Witte (1999) applied West et al.'s idea of a consumption vocabulary to the virtual community context. They suggested that virtual communities develop unique, group-specific consumption vocabularies that influence members' social norms and cognitive processes. Similarly, Web chatters may develop andor adopt a common vocabulary orjargon that they use to communicate with each other in the online context. These vocabularies serve as a way for chatters to communicate with one another.
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ZINKHAN, KWAK, MORRISON, OKLESHEN PETERS
Naive marketing. Heider's (1958) theory of 'naYve psychology" provides a foundation for understanding the ways that chatters market themselves and attract others via the Web. Naive psychology is the ways in which the average person understands and interprets human behavior and causality. Consumers also have a naYve psychology of how to market themselves, what could be called "naive marketing." They do not launch formal advertising campaigns and marketing strategies to sell others on their attributes; however, they do attempt to present themselves in a manner that best attracts desirable others. Thus, the term nai've rnarketing reflects the idea that everyday consumers have opportunities to market themselves and they have their own ideas about the best ways to do this. Moreover, chatters have an opportunity to market themselves through the use of chatting directories to attract chatting partners. Research Questions In this study, we explore several research questions pertaining to Web-based chatting behavior. Table 1 presents the organizing principles of this research article. The table illustrates the exploratory nature of the research and contains the five research questions and their components. The first question asks, "Who chats on the Internet?"is question examines typical Internet chatters by asking respondents to provide information about themselves, such as age, gender, nationality, language, marital status, education level, and current employment status. The first question also examines TABLE 1 Major Research Questions and Their Components Research Question Who chats
Motivations to chat How chatters communicate Links to consumer behaviors and attitudes
Factors associated with successful chatting: The success of naive marketing
Components Age Gender Nationality Language Marital status Education Employment status Chatting frequency Time of chat Possession of multilnedia equipment Rank order of motivations Gender differences Jargon Symbols Opinion leadership Risk taking Attitude toward Internet ads Time use Multimedia use Inclusion of sexual content Language used Inclusion of correct e-mail address
specific descriptive components of chatting behavior: a) HOWoften do chatters connect to MNM in order to chat? b) What time of the day/night do chatters typically connect to MNM to chat? and c) How often do chatters use the various chatting services (e.g., text-based communication services, microphones, video)? The information gathered to address this first research question serves to create a profile of Web chatters. The second question examines the reasons chatters give for chatting on the Internet, which in turn helps us discover the motivations behind Web-based chatting. The third question explores how chatters communicate on the Web. It is not uncommon to find symbols, abbreviations, and characters in online chat rooms that are unfamiliar to the inexperienced user. With this question, we explore whether chatters have a special language and whether this special language contributes to a successful chatting experience. The next question explores the link between Internet chatting and other consumer behaviors. This information allows us to explore the extent to which chatting on the Internet influences the time an individual spends engaged in other activities (e.g., going to the movies, watching television, exercising). It also provides insight as to whether Internet chatters are more likely or less likely to enjoy behaviors involving risk. In addition, the information gathered allows us to explore related questions such as "Is the amount of time one spends chatting online related to the extent that other individuals will seek himher out for hislher opinion on products, stores, or sales (i.e., treated as a market maven)?'and "How does the amount of time spent chatting relate to an individual's attitude toward Internet advertising?" Last, this study examines the factors that do and do not lead to successful chatting experiences (i.e., finding another person with whom to chat). For example, does the inclusion of sexual content in a personal advertisement on the Web increase or decrease a chatter's chance of finding someone with whom to chat? The full set of research questions is designed to enhance our understanding of who uses chat rooms, the reasons why individuals chat, and which variables lead to the greatest chances for a successful chatting experience. In addition, we may also learn of links to other kinds of consumer behaviors (e.g., opinion leadership).
METHOD Participants E-mail messages were sent to addresses found on a popular multimedia-based chatting server (i.e., MNM). As an incentive to participate in the survey, e-mail recipients were told that each participant would qualify to win a prize valued at approximately $100 which would be awarded to four participants whose names would be chosen randomly among all
WEB-BASED CHATTING
21
those who completed the survey. Three hundred seven chatters responded to our survey.
(e.g., e-mail address, status of having audio or video equipment, current chatting status, country).
Materials
Design and Procedure
MNM (version 2.1 1) Web server was selected to explore chatting behavior for a few reasons. First, the server allows the researchers to examine chatter's unrestricted personal ads exactly as they are posted. Unlike the MNM, for instance, AOL requires all members in its chat rooms to follow its "terms of services," which basically bans uttering obscenities and harassing or disruptive behavior. AOL users are encouraged to report a violation of its rule. In some cases, chatting environments are censored by a chatting service provider (i.e., Talk City, www.talkcity.com). MNM allows individuals the freedom to solicit chatting partners in the manner in which they believe will be most successful. Second, the MNM enables people to chat using multimedia-based tools (i.e., availability of using voice and video communications). Therefore, a variety of people utilize MNM, from those interested in traditional text chatting to those who utilize the most advanced methods (i.e., using real-time video chat). Finally, the program provides the opportunity to obtain a variety of information about its users
Two methods, an Internet survey and acontent analysis of personal advertisements, were employed in order to examine the five research questions. First, data were collected through the use of an Internet survey. Actual chatters who use the service MNM were contacted through e-mail requesting their participation in a survey on Internet usage. E-mail addresses were obtained through several directories of information on MNM, which chatters use to display their personal advertisement. Second, a content analysis was conducted using personal advertisements posted by chatters using MNM software. MNM utilizes nine servers to which chatters can log on, and these servers are available 24 hours a day. In this sample, chatters who logged on during one of two time periods (noon and midnight U.S. EST on a Saturday in May 1999) were examined. This sampling procedure resulted in a sample size of 1,348 chatters. An example of the data set appears in Table 2. As shown in the table, MNM allows its users to display their personal ads, along with other information (e.g., name, e-mail address, citylstate, andcountry). Theuser's comments column can be viewed as a kind of "personal ad" to attract fellow chat-
TABLE 2 Information Available From Potential Chatters E-maila
kzs ~ Y U
kor koh klari ki.m kaya kar kari kar kap jyan juli j tmd jros jr@ joyfi joy jorg jon JO Jill@ jeny jean Jcha JCG janit
First
Lasr
kun k korh Marc klari kame1 kay a kara Karin Kar Vj JOSE Julian mike Edith Ric Chasi Ric Jorge Jon guy Jill Jerry Jean Lover Bo Jan
kazu yuca 111133 Koh P Soft yakar Kara Lesbf 1's a kapur YAN D duke Rosas Eisn
City/State
Istanbul Istanbul Differdange De Lier Rades lady beni ara
v
Virginia London Rio Negro, Patagonia Scotland No gayzzzzz Dallas PortsmouthIOhio Freiberg Planete Nuevo Leon N Br.
with 30's D Icq2 Dream CHI Jen
Newcastle Here Lima Hong Kong T:619175609 MOVIL NJ New Jersey
Gitan Cle
Country Japan Turkey Turkey Luxemburg Netherlands Tunisia Turkey Turkey Austria United States United Kingdom Argentina United Kingdom United States United States United States Germany Canada Mexico Netherlands Singapore United Kingdom United States Peru China Spain United States
Comments
Gay/f/u/e/@IPILTn;VIDIUIW/@/Q/U/@////only No gay pls ICQ15158279 Bi Cherche asma MI39 Only female for LADY Co cam, hut my mic works
Male Engish o espanol Only family and friends
GYPSY Saludos desde monterray M2mC2C no fat Looking for big man Are there any f here for chat? Very nice man! TOD@MUJERES Clean chat only
aChatter's e-mail addresses and names are not fully displayed for purpose of anonymity. ba = voice capability; b =video camera capability.
otherh
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ZINKHAN, KWAK, MORRISON, OKLESHEN PETERS
ters. Also, the MNM reports the status of whether its users are currently chatting, and whether they have voice or video communication equipment. The contents of the MNM status report will be used to determine which factors lead to a successful chatting experience. Information gathered during the content analysis phase of this study required investigators to code many of the variables posted within the personal advertisement. Information was coded using two different procedures. Because several variables posted by chatters are objective in content, only one graduate student was needed to code the following items:(a) E-mail address: 1 (displaying correct e-mail address) and 2 (displaying incorrect e-mail address); (b) Country; (c) Status of having voice function: 1 (have) and 2 (don't have); (d) status of having video function: 1 (have) and 2 (don't have); and (e) Whether the chatters are currently chatting: 1 (chatting) or 2 (not chatting). The comments section in MNM provides a form of personal advertisement used to attract other chatters. The comments section allows Internet users to introduce themselves to other Internet users. Many different expressions are used in the comments section (see Table 2), so two coders were used to interpret and code this content. Twelve coding items were developed for the following variables: (a) whether personal comments were included, (b) language used, (c) whether comments were cryptic, (d) whether a specific gender was requested, (e) whether a specific ethnic group was requested, (f) whether a specific age group was requested, (g) whether self-identification was offered, (h) status of displaying sexual context, (i) whether camera-to-camera chatting was specified, (j) whether a gay chatting partner was specified, (k) whether "clean chat" was required, and (1) whether an "already known" personal was specified. Both coders were graduate students with expertise in web-basedchatting. One coder was trained inpsychology, and a second was trained in communication and marketing. Levels
TABLE 3 lntercoder Agreement and Reliability Intercoder Agreemen$
Intercoder Reliabilityb
Personal comments Language used Cryptic comments Gender request Ethnic group request Age group request Camera-to-camera chat Sexual content Gay chat partner Clean chat required Already known person Self-identified aHolsti's (1955) percentage of agreement. Cohen's Kappa (1960); all of indexes here significant at p < .05.
of agreement between the two coders were assessed for the content of the personal ads. Traditionally,Holsti's (1969) reliability estimate is used in consumer research to determine interrater agreement (Kang, Kara, Laskey, & Seaton, 1993). However, because Holsti's index does not adequately account for coder agreements by chance (Wimmer & Dominick, 1997), Cohen's Kappa (Cohen, 1960) was used for this study. Table 3 illustrates reliability evaluations for the twelve items that were evaluated by the two coders (based on the chatters' personal comments). Overall, the results suggest an acceptable reliability range for both indexes (Kassarjian, 1977; Wimmer & Dominick, 1997).
FINDINGS Who Chats To answer the first research question ("Who chats on the Web?')), the descriptive statistics from the sample of survey respondents were examined. The majority of respondents using MNM were between 16 and 40 years old, with 21% between 26 and 30 years of age. Seventy percent of respondents were male. Fifty-seven countries were represented in our sample with the majority of respondents from the United States (81 of 307, 26.4%). Canadian respondents were the second largest group (14%), followed by Chinese (6.2%), Australian (5.5%), Korean (4.9%), and Taiwanese (3.3%). English was the predominant language used by MNM chatters, with 79% of respondents reporting its use. Over half (52%) reported being unmarried with no children, whereas 31% were married with children. The majority of respondents (82%) reported having at least a college education, and 52% were employed full time. We found that 54% of the respondents connected to MNM less than 5 times per week, whereas 29% connected between 6 and 15 times per week. Once connected, one quarter of the respondents stay connected for 1 to 2 hr of time; twenty-two percent remain connected for only 30 min to 1 hr. Approximately half of the users who responded to the survey logged on to MNM on Monday through Friday, between 5 p.m. and midnight (local time). Multimedia-equipped chatters were found to be attracted to MNM's chat room. Of the chatters, 91.1% possessed at least a microphone, and 44.5% owned both microphones and videophones. As discussed later, the role of multimedia functions may play an important role in their chatting.
Motivations to Chat Respondents were asked to rate their agreement with a series of possible motivations for chatting on the Web using a 7-point scale ranging from 1 (strong disagreement) to 7 (strong agreement). Table 4 provides a summary of these
data. The top five reasons for Web-based chatting found in our sample include (a) it is economic/inexpensive (M = 5.21), (b) entertainment (M = 5.07), (c) convenience (M = 4.87), (d) relaxation (M = 4.86), and (e) companionship (M = 4.36). Examining the least cited reasons for Web-based chatting, we find that escapism received the lowest score (M = 2.82). In addition, although there were social reasons reported for Web-based chatting (e.g., the mean score for companionship = 4.36), respondents did not view chat rooms as a learning environment (e.g., the mean score for chatting as a way to find tips on social skills = 2.96). Surprisingly, - - the most citedreason for chatting in our study (it., "its low cost") is not one that is typically discussed in the literature on cyberspace (e.g., see our Conceptual Overview section at the outset of the article). The remaining four motivations cited by chatters taking our survey correspond well with those identified earlier. Entertainment is identified as a structural motivation of television viewing (Lull, 1980) and relaxation can be viewed as a habitual motivation for watching television (Rubin, 1984). Affiliation, in addition to being one of the four major motive systems (McClelland, 1987),is also identified as arelational (Lull, 1980) and a habitual motivation for television viewing (Rubin, 1984). Convenience has been cited as a primary motivation underlying Internet shopping (Burke, 1997), so it is not surprising that this motivation surfaces with respect to Web-based chatting as well. Although "escape" is often cited as a habitual motivation for watching television (Rubin, 1984), it was the least cited motivation in our study. Moreover, McClelland's major motive systems of achievement, power, and uniqueness/novelty did not emerge as motivations behind Web-based chatting. Therefore, this study provides evidence that consumer behavior in cyberspace, althoughdisplaying similarities to othermedia usage, has its unique aspects and should be treated accordingly.
To determine whether men and women differed in their motivations for chatting, the mean scores for each gender were compared. Men and women differed on five of the motivations listed and, in each case, women were significantly more likely to cite the motivation as a reason for chatting than were men. The five chatting motivations that resulted in gender differences were: (1) To kill time, t = -4.69, p < .05; (2) for entertainment, t = -3.72, p
