Consuming Cyberseniors: Some Personal and Situational Characteristics That Influence Their On-Line Behavior

Charles A. McMellon, Baruch College, CUNY
Leon G. Schiffman, Baruch College, CUNY
Elaine Sherman, Hofstra University
ABSTRACT - Of the many consumer groups allocating time to on-line activities, the elderly appear to be of special interest since they are breaking the stereotypical image of a group not especially receptive to new technology. Our exploratory study of these "Cyberseniors" was designed to examine their sociodemographic and personality characteristics. Interviews were conducted on-line over a six month period. What emerges suggests two different types of cyberseniors: the technology loverCindividuals’ whose life long fascination with technology has led them to readily adopt computers, and the technology userCa more pragmatic group of individuals, who accept technology and consider computers just another tool. The differences in these two types of on-line consumers are discussed.
[ to cite ]:
Charles A. McMellon, Leon G. Schiffman, and Elaine Sherman (1997) ,"Consuming Cyberseniors: Some Personal and Situational Characteristics That Influence Their On-Line Behavior", in NA - Advances in Consumer Research Volume 24, eds. Merrie Brucks and Deborah J. MacInnis, Provo, UT : Association for Consumer Research, Pages: 517-521.

Advances in Consumer Research Volume 24, 1997      Pages 517-521

CONSUMING CYBERSENIORS: SOME PERSONAL AND SITUATIONAL CHARACTERISTICS THAT INFLUENCE THEIR ON-LINE BEHAVIOR

Charles A. McMellon, Baruch College, CUNY

Leon G. Schiffman, Baruch College, CUNY

Elaine Sherman, Hofstra University

ABSTRACT -

Of the many consumer groups allocating time to on-line activities, the elderly appear to be of special interest since they are breaking the stereotypical image of a group not especially receptive to new technology. Our exploratory study of these "Cyberseniors" was designed to examine their sociodemographic and personality characteristics. Interviews were conducted on-line over a six month period. What emerges suggests two different types of cyberseniors: the technology loverCindividuals’ whose life long fascination with technology has led them to readily adopt computers, and the technology userCa more pragmatic group of individuals, who accept technology and consider computers just another tool. The differences in these two types of on-line consumers are discussed.

Computers and the internet are beginning to play an important role in the lives of millions of elderly consumers (Dickerson 1995). They send e-mail to their grandchildren, communicate with distant friends, search for information and purchase products and services on-line, and perform many other beneficial activities. They are "cyberseniors," consumers over te age of fifty-five who are active on the internet. It appears that computers and the internet are especially relevant to this segment of older consumers, since they make it easier for them to do what they want to do, when they want to do it (Wylde, 1995). The elderly’s involvement with the internet is also important to marketers, who for years thought they would not be innovative with respect to new technology, but are now beginning to recognize the importance of this behavioral change in the elderly. Firms like Apple, Intel, and Microsoft have new programs targeting older adults.

The economic importance of the elderly as a consumer subgroup and the internet as a marketing phenomena are well documented and will not be discussed here. Yet from a consumer behavior perspective, examination of these two important trends, as they interact, appears to have been largely overlooked. Although we know something about who cyberseniors are demographically (e.g., The 4th Hermes 1995 Survey reports less older women than men using the internet), we know little of the factors that influence their internet behavior.

The purpose of our study is to examine the personal differences that may influence older consumer’s use of the internet. We begin with a discussion of older consumers and their involvement with the internet. We then examine related research and various models of time allocation which may aid our understanding of this phenomena. Next, we discuss our method of data collection on the internet. Little has been written on this subject. Thus, our method of interacting with subjects was developed through past personal experience. Results of our analysis are presented along with limitations and future research direction. What emerges suggests two different types of cyberseniors: the technology loverCindividual’s whose life long fascination with technology has led them to adopt computers, and the technology user C a more pragmatic individual, who accepts technology and considers computers as just another tool. If time spent on the internet is time consumed, then knowledge of these consumer segments may aid those interested in a variety of consumer behavior issues and topics.

THE ELDERLY AND THE INTERNET

The cybersenior phenomenon is growing. Nationally, over 20 percent of all older consumers own computers (Stock 1995). The AARP reports over two million computer members among its members, and SeniorNetCa national computer training organization for the elderlyC has trained over 30 thousand individuals. These numbers should not surprise marketers. Enders (1995) points out the irony of stereotyping older consumers as afraid of technology. Older consumers have seen their world evolve to laser beam surgery and men walking on the moon. Older consumersCboth the young elderly and the older elderlyChave adopted many new technologies. Thus, it should not be too surprising that they are adopting computers and the internet as they begin to discover its benefits of increased productivity and quality of life (McMellon, Schiffman, and Sherman 1995).

In addition, the very nature of the elderly may also be changing. The new-age elderly (Schiffman and Sherman 1991) are an emerging subgroup who not only perceive themselves as younger than their chronological age, but are generally more experiential, less materialistic in their life activities, more self-confident, and more in control than the generations that have gone before them. This experiential dimension might be a motivating factor in why more and more elderly are going on-line. Sheehy (1995) sees this phenomenon as a general shift downward of all adulthood stages by about ten years. Many adults in their sixties now think and act like they are in their forties or fifties.

THE ALLOCATION AND CONSUMPTION OF TIME

Although the use of the internet by the older consumers appears in the popular press regularly (e.g., Stock, 1995), little has been written about elderly behavior on-line and any of the factors that might influence such behavior. Thus, we look to related theoretical and empirical research for possible guidance.

Previous research has examined the allocation of travel time (Barff, Mackay, and Olshavsky 1982), time spent watching mass media (Hornik and Schlinger 1981), and shopping time (e.g., Arndt and Gronmo 1980). In these studies, the value a consumer places on their time and its influence on their time allocation decisions are examined in relation to a variety of personal characteristics (e.g., demographics or personality traits) that might influence such behavior. These studies begin to demonstrate that a relationship exists between a consumer’s allocation of time and various socioeconomic, demographic, and psychological variables.

Another approach which offers guidance for our exploratory study of time consumed on the internet is the area of time allocation frameworks (e.g., Feldman and Hornik 1981). These frameworks focus on organizing various influential variables that aid in understanding the consumption aspect of products and services as measured by time.

Feldman and Hornik (1981) offer a comprehensive conceptual model for the allocation of time which includes: (1) time structure (i.e., work time and the various components of non-work time), (2) resource availability (i.e., what constraints money, time and space have on allocation), (3) activity availability (i.e., how accessibility to the activity affects allocation), and (4) and personal characteristics (i.e., what demographic and personality differences influence time allocation). Time structure and resource availability define a time domain construct while activity availability and personal characteristics influence the individual’s perceived value of the activity. Time value is operationalized as satisfaction in the activity itself and satisfaction based on interaction with others while performing the activity (Kaplan, 1972; Neulinger and Raps, 1972). The time domain and perceived value constructs influence the allocation of time to the activity. In our study, it is the amount of time spent on-line.

While some of the independent variables that are included in these models have been identified (e.g., socioeconomic and situational), personality characteristics, which may also contribute significantly to our understanding of time allocation, have not been identified. It appears identifying them will be a more difficult task since personality characteristics may be specific to each type of leisure activity (Martin and Myrick, 1976).

While researchers have yet to discuss what personality types gravitate toward the internet, some writers offer clues. Rheingold (1993), after ten years of talking with people on the internet, suggested two personality types gravitate towards on-line activities: those whose professional background seems a good fit with the internet method of communicationCwhich is the typing and reading of words or symbols (e.g., computer programmers or librarians), and those individuals who were not afraid of computers and were curious about the internet as some kind of cultural phenomenon.

Researchers studying the elderly’s attitudes toward computers also offer some clues. Jay (1989) found a relationship between attitudes toward computers and external locus of control, indirect experience (e.g., past experience with calculators), and intellectual control beliefs. Igbaria and Parasuraman (1989) found a relationship between age, education, external locus of control, and cognitive style (feeling-thinking) and computer attitudes. Specifically, external locus of control and math anxiety had an indirect effect through a measure of computer anxiety. Computer anxiety, in turn, was strongly related to negative attitudes towards computers.

In summary, a general lack of knowledge on what influences the allocaion and consumption of time on-line among the elderly suggests exploratory research as a necessary first step. Related literature offer some clues. It appears as if the satisfaction one derives from a behavior may influence the time spent in the activity. Also one’s attitude towards computers is important. Last, a number of personal and situational characteristics may be influential and should be examined. They would include personality traits (e.g., need for cognition and locus of control), socioeconomic and demographic factors (e.g, income and education), psychographic (e.g., cognitive age), and situational or lifestyle variables (e.g., money constraints).

METHOD

A semi-structured interview approach using e-mail was chosen based on the lead author’s personal on-line experience. The alternate approach of real-time interviewing on the internet was deemed too difficult since it appeared that most respondents would not want to spend the continuous time on-line necessary to complete a single depth interview. Respondents also appeared more comfortable with a more prolonged interchange with time to consider answers.

Depth interviewing can be defined as "...repeated face-to-face encounters between the researcher and informants directed toward understanding informants’ perspectives on their lives, experiences, or situations as expressed in their words" (Taylor and Bogdan, 1984, p.77). The most obvious difference with our approach is that on-line interviewing is not a face-to-face interaction but occurs in the realm of cyberspace, a reality that is created between people who communicate on the internet. The following method was developed to communicate in this "cyber-reality."

Insight Development

Potential respondents were identified by browsing special interest group libraries in commercial on-line services (e.g., Compuserve). Fifteen cyberseniors, who had written on-line autobiographies, were chosen as potential subjects since publishing one’s life story on-line suggested a willingness to talk. On-line autobiography is a technique commonly used to involve the new user in computing. We recognize that identifying potential respondents in this manner can bias our sample, but as the study was exploratory in nature and with little to guide us in method, we chose those who might facilitate our research by their willingness to communicate. An initial e-mail message was sent to each of them. It contained a favorable comment about their autobiography, a request that they participate in our research project, and a few questions to give them some practice in communicating with us.

How they responded was also of interest so that further communication could be adjusted to their style. We asked if they would like to participate in this research project because internet protocol suggests one does not send unsolicited e-mail such as a survey or an advertisement without the recipient’s agreement ahead of time. Researchers risk being flamed (i.e., your e-mail mailbox becomes stuffed with rude, ALL CAPITALIZED, messages) if "netiquette" is breached. Nine of the 15 potential respondents replied within three days. The other six never responded. They may not have been reading their mail or simply were not interested. A few more questions were sent off to the nine who responded. We added an additional question asking them if they would like to continue to participate in a dialog. Six agreed to continue the discussion. These six respondents continued the discussion over a six month period in 1995, as the on-line depth interviews were conducted via e-mail. Individual weekly correspondence was conducted with each of the respondents covering a variety of subjects suggested by our literature review. The lead author is still in weekly communication with these six respondents discussing a wide rnge of subjects. All on-line responses were captured and stored in ASCII files for later analysis.

Communication Analysis

Our data included the respondent’s original autobiographies and their responses to a wide variety of personality related, situational, satisfaction, and computer usage questions suggested by the literature and the authors personal experience on-line.

Analysis of the responses proceeded systematically using iterative processing (Spiggle 1994). At the completion of the response collection period, each respondent’s answers and comments were converted into hard copy. An analysis outline was developed which listed each of our discussion areas and the respondent’s answers along with a space for the researcher’s comments. The responses were analyzed both vertically and horizontally. Vertical analysis examines each respondent independently of the other respondents while horizontal analysis examines each response area of all respondents independently of the other response areas. The vertical and horizontal interpretation procedures were repeated until the diminishing returns of interpretation suggested further analysis was not necessary. The vertical and horizontal analyses and interpretations were then integrated into the following.

ANALYSIS

Our analysis focuses on the understanding of on-line consumer behavior through individual differences of the respondents. We began by examining the respondent’s autobiographies. Our sample appeared to be comprised of a relatively varied group of individuals with differences in family life, past careers, and retirement activities. The length of their autobiographies began to tell us something about their differences. The amount of what they wrote suggested some level of need to communicate with the outside world (i.e., the more written, the more the need to communicate). It became apparent later, as familiarity with each of the respondents grew, that a need to communicate was stronger in some individuals than in others. Four of the respondents wrote long, detailed autobiographies while two wrote very short ones. For example, one respondent wrote five pages of text while another wrote a single paragraph. The writer of the short paragraph was very dissatisfied with life, apparently influenced by the death of a spouse and the serious illness of a parent. The four long autobiographies were all written by respondents who were very satisfied with their lives. These respondents tended to be very active in their retirement, with activities that ranged from church volunteering to long distance bike riding. They were also extremely interested in computers and electronic communication. Those with a high interest in computers seemed different. Five respondents embraced, even loved, technology while one respondent was neutral towards technology and "just used it." As Igbaria and Parasuraman (1989) have shown, a continuum of attitudes toward technology exists. Therefore, given the potential for added dimensions in an individual’s relationship with technology, we suspect that attitude towards computers may be only one dimension in the segmentation of computer consumers. What emerges from our research are two possible segments of on-line consumers: the technology lover and the technology user. They appear to behave differently in terms of on-line behavior and to vary in terms of some personal characteristics.

Technology Lovers and Technology Users Emerge as Segments

We asked participants if they "loved" technology. Seven of the original nine respondents answered positively, while one was neutral, and one did not answer. As we discussed technology, it became clear how they felt:

(From the tech-user)

"It (technology) exists and we must make the best of it...I have a PC which I use mainly for word processing....I find technology somewhat less than intuitive."

(From tech-lovers)

"I’ve always been interested and involved with technology."

"I was fascinated by the concept of computers."

"(A friend)...showed me how to use a doorbell battery and a screwdriver to make a flashlight bulb burn. To my young mind, it was a remarkable feat...the process became so clear, I was astounded!"

As we began to examine the data, it became apparent that loving or using technology might define the segments of our sample. To better understand this notion, we asked the respondents to define the word "technology." Here are a few responses:

"The application of human knowledge. To accomplish practical and useful objectives through the use of physical materials and methods."

"The body of knowledge of particular skills."

"The use of science in everyday life for the improvement of the quality of life."

We also discussed satisfaction. The tech-lovers appear more satisfied with their lives although it was also apparent that certain situational variables modify life satisfaction. Indeed, the most dissatisfied subject is also a tech-lover. In this person’s case, both personal and family health problems have made him "a prisoner in his own home." Another tech-lover who did not rate life satisfaction as high as others cites problems with children and grandchildren. Thus, for these respondents, it appears that computers and on-line activities, while highly satisfying activities, are not the dominate contributors to life satisfaction.

In addition, we examined two dimensions of on-line satisfaction. That is, satisfaction with the activity and satisfaction with the people who also do the same activity (Kaplan, 1972; Neulinger and Raps, 1972). The tech-lover appeared to be more satisfied than the tech-user on both satisfaction subdimensions. In addition, we asked a variety of cognitive age questions (i.e., age self-perception with respect to looking, feeling, doing, and thinking). Tech-lovers saw themselves as generally younger than their chronological age, whereas the tech-user did not. These findings are in general agreement with earlier research reported by Sherman, Schiffman, and Dillon (1988) that the younger the cognitive age, the more likely the person is to be satisfied. As to why they felt this way, the tech-user stated, "I feel as though I am in my 60’s because I know I am." A tech-lover said, "...I still have a great intellectual curiosity and interest in so many different fields..." Tech-lovers appear to have a youthful enthusiasm and outlook that is absent in the tech-user.

Overall, tech-lovers seem to view the impact of computers and on-line services on their lives more positively. They see it as a tool to expand their horizons, to create new programs, to communicate their ideas, and to meet new people while the tech-user views the impact of computers less positively; that is, with a more inward direction where computers help make tasks easier (e.g., word processing is easier than typing).

Attitudinal and Situational Characteristics

The tech-lover’s responses suggest that they are innovators and more in control of their lives. Also they may be a little healthier and happier. There were no differences between tech-lovers and the tech-user in propensity to collect things, amount of travel, and whether or not computers were seen "as magical." Upon finishing the preliminary questioning, we began a dialog on a wide range of subjects with the six respondents who had indicated a willingness to continue. The three respondents that dropped out at this stage appeared to be of the ech-user type and seemed overly concerned over the cost of continuing communication.

We began our dialog by asking the six remaining participants how they became involved with computers. Tech-lovers stated involvement usually began with an early childhood interest in things electronic. The tech-user had little interest in technology and became involved with computers because of the influence of another (i.e., at the prompting of a grandchild). We speculate this may be one of the key differences between these segments. Tech-lovers have been involved with technology from an early age, perhaps due to an internal motivation or early learning from parents. Thus, when computers were developed these participants quickly became involved, while the tech-user needed some outside motivation to adopt computers. (One of the advantages of electronic interviewing is the ability to easily go back and ask another question during the analysis stage. Thus, we asked respondents about childhood or early interest in technology.) Their answers were relatively consistent. Here are two excerpts from tech-lovers:

"As a boy, I was particularly interested in airplanes and the principles of flight. I loved to go to the airport and watch the planes landing and taking off and to climb up into the cockpits of those in the hangers. There was little need of airport security in those days."

"...as a kid I built radios out of razor blades and rusty nails, then with Galina crystals, then graduated to one tube radios. I read Popular Mechanics, Popular Science...My wish when I was a kid was the Edmund Scientific catalog."

The responses of tech-lovers suggests to us a life long involvement and fascination with technology. As for current involvement with computers and on-line services, the tech-lovers, had more equipment and were more computer literate. This determination was made from their ability to communicate with us on-line and from how they described their hardware and software. They also spent more time with their computers, purchased more products on-line, and performed a greater variety of on-line activities (e.g., joined on-line groups, sought out more information, and met more people).

Situational constraints (i.e., amount of free time, money and space available for on-line activities) were also discussed. A variety of answers suggested no clear direction except for their general concern for money (e.g., "..if it were free, I’d do more."). Their answers supported the general assumption that these variables can act as constraints on time spent on consumer behavior (Becker 1965; Feldman and Hornik 1981). Health (either one’s own or of others in the household) also emerges from our discussions as a potential constraint on elderly consumer behavior. A comment from one of our respondents supports this notion:

"I am the sole care giver to my mother with advanced Alzheimer’s disease, which makes me a prisoner in my own home."

Personality Characteristics

It is generally accepted in marketing that personality traits influence consumer behavior in some manner (Schiffman and Kanuk 1994); while specific traits may influence specific behaviors. We suspect certain traits (e.g., need for cognition and locus of control) are influential in on-line behavior.

Need for cognition is an individual’s predisposition to enjoy thinking and do more of it than others (Cacioppo and Petty 1982). We discussed the subject in some detail with respondents. Tech-lovers appear to have a higher need for cognition than tech-users. Tech-lovers like the intellectual challenge of computers and of learning new applications. Here is what two said:

"I do like complex problems, and I enjoy the intellectual pursuit of new and better ways to solve probems."

"I usually prefer a hard thinking job with new technologies and new solutions. I’m not satisfied with only a finished work but I continue to think of improvements even after the task is done. Perhaps I am a perfectionist."

Locus of control is the level of internal (i.e., one’s own) or external (i.e., others or fate) control that an individual perceives in their life (Rotter 1966). It is potentially important for older consumers: Lumpkin (1986) has demonstrated that the elderly tend to have a more external locus of control. He hypothesizes that as aging individuals deteriorate in health and lessen in activities, they feel they are losing control of their lives. If this is true, than computer use for the elderly may be an activity that provides an opportunity to regain some of that lost control. Our findings suggest this might be true. Tech-users appeared to be "generally" in control of their lives "as far as any of us are" while tech-lovers told us in no uncertain terms that they were in control of their lives.

"I learned, in the beginning, by hit or miss but I kept on plugging away and slowly made sense out of what I was doing. Now I can usually go on- line and accomplish whatever it was I set out to do."

"Bad luck is usually because I jumped in without taking the time to think out just what it was I wanted to do."

Additional Insights Also Emerge

Some additional insights on the differences between tech-lovers and tech- users emerged from their "response style." The tech-lovers generally responded with more enthusiasm and with more detail than the tech-user. Tech-lovers also responded faster. As mentioned earlier, we felt tech-lovers had a stronger need to communicate (at least over the computer). That is, they appear to have a need to pass on information they have accumulated through their years of experience or to talk with like minded people on subjects that interest them. One respondent, when asked a simple question on how he fared during hurricane Opal, responded with two pages of detail rich text. This type of response stands out in the domain of computer mediated communication since most communication appears much shorter and to the point. Another respondent was more direct in indicating a need to communicate by saying, after a short absence from the net, "I am glad to be back to communicating." Other tech-lovers felt:

"I think we can improve our knowledge by communicating to each other our experiences."

"...all of us around the world need to have a glimpse about what other people feel and think."

This need to communicate does not seem to be driven by loneliness but appears to be related to their need for cognition and may be more a function of a sheer need to communicate with like-minded people or to pass on information to the next generation. This need to communicate may be important to marketers. For example, it may aid in better understanding word-of-mouth, which appears to be quite common among internet users.

Finally, we were interested in the changing nature of the elderly (Schiffman and Sherman 1991; Sheehy 1995). If there was a difference, did it somehow influence their use of computers? We asked respondents how they saw themselves in relation to their parents. Their answers suggest they are different than their parents including the perception of better health, more positive attitudes, and a much higher level of physical activity. We could find nothing to link computer use to these differences. From two tech-lovers:

"When my father was 64 or 65, he could not climb a tree or a ladder. I’m still able to paint a ceiling."

"I think on the whole I am a lot younger at my age than my parents were. They semed ready for the rocking chair...(while I’m) riding a bike at my age."

CONCLUSIONS

In summary, tech-lovers feel younger and appear very satisfied with their lives. They have a stronger internal locus of control, a higher need for cognition and communication, and are more impressed with computers and what can be done with them (e.g., meet new people). They also appear to be more satisfied with their on- line activities, to spend more time on-line, to search for more information, to join more on-line groups, and buy more products. The tech-user does not feel younger and appears to have a lower need for cognition and communication. They also seem less impressed with computers (e.g., "It helps me type better"). Both tech-lover and tech-user are constrained somewhat by money. The tech-lovers had been involved with computers for many years, thus when on-line services became available, they gravitated to them easily. The tech-user appeared to have had a more reluctant involvement (e.g., through the urging of children). Tech-lovers seem to be going somewhere with computers expanding their lives. Tech-users seem to be coming from somewhere with computers aiding in their current situation.

The respondents in this exploratory study offer new insights into the nature and motivations of the elderly internet user. Situational and personal characteristics, which may shape how the elderly consumer behaves on-line, were examined. Two potential types of on-line consumers emerged: the technology lover and the technology user. They emerge as distinct segments and behave differently in their consumer behavior on-line. Our findings should be considered preliminary due to the exploratory nature and limitations of our method. Two of these limitations are small sample size and method of sample recruitment which may bias our results. We justify our approach given the newness of on-line research. Limited by the difficulties of on-line recruitment, we chose a small number of respondents who appeared willing to cooperate with us. This method was also a learning process for us. As this is a first step into a new and uncharted area of investigation, we feel the method may be justified.

We have identified and examined a number of situational and personal variables that may have an influence on the older consumer’s on-line behavior. More qualitative and quantitative research is needed to better understanding of the differences between tech-lovers, tech-users, and any other segment that might exist.

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