The Diffusion of Innvovation: The Fortune 100 and the Internet

Jim Marchwick
Erik Tamplin
Cortney Wanca
COM 5305 - Interactive Communication Research
Florida State University
Dept. of Communication
Spring, 1997

(Brie - who does not yet have a website = a laggard)



James Marchwick
Erik Tamplin
Cortney Wanca
Research Project-5305

Fortune 100 Web Site Content Analysis

Introduction

The Internet has rapidly expanded with the promise of changing business, entertainment, and everyday life. Due to the vastness of the Internet, innovation is very complex. As the Internet develops, so have many innovations or tools. For example, e-mail and web surveys help give the Internet greater interactivity, marketing, and entertainment value. Companies that use innovations, such as email, animation, and Quick Time VR (Virtual Reality), help keep a web surfer's interest in a web site. Research of the Internet must attempt to keep pace with the growth of the Innovation, the Internet.

This study is important to the contribution of both applied and theoretical research. First, this study will have practical applications for businesses currently or planing to extend their services onto the world wide web. The web uses emerging technologies that provide new opportunities for companies. Businesses that want to have a sophisticated web presence can find which web technologies are most prevalent among the Fortune 100. Firms will be able to compare their use of web applications to those of companies within their industry. This will give them an understanding of current trends in web development. Second, this study is important to further test the Diffusion of Innovation Theory, developed by Everett Rogers. Specifically, companies that focus on new technologies should, theoretically, be adopting new technological innovations earlier than those companies that are not technologically inclined. This research will show the extent to which Rogers' Diffusion of Innovation applies to web innovations. This study will provide a means of stratification that will answer the question:

Are businesses in the telecommunication, computer, and electronic industries the earliest adopters of new web technologies?

To date, most research conducted has centered around the Internet and its adoption by individuals and organizations. Such studies have focused on the more general adoption patterns of digital technologies to facilitate business productivity and communication, such as the 1995 study by Robert LaRose, Ph.D. and Anne Hoag, of Michigan State University, on the organizational adoptions of the internet and the clustering of innovations. LaRose and Hoags study, found evidence for the innovation cluster concept in the context of organizational adoptions on the Internet (LaRose and Hoag, 1995). This content analysis is of a more specific nature, in that it shows how readily Fortune 100 companies are incorporating web innovations into their web sites.

The following hypothesis was formed by the foundation of diffusion of Internet innovations to business organizations: Fortune 100 companies specializing in telecommunications, computers, and electronics will have a higher occurrence of innovative applications on their web sites, than Fortune 100 companies whose primary focus is outside of these industries.

First and foremost, the Internet is a tool for individuals and organizations to communicate. The research of specific web applications is vital to the understanding of the diffusion of Internet innovations. Therefore, the study of web innovations use and the patterns of adoption are important in the examination and formulation of communication theory. In addition, communication researchers will be interested in this study because it provides a survey of how businesses are using the web to self promote. A more practical application of this study will allow companies the ability to compare their web sites to other on-line corporations.

This study of Fortune 100 companies on the web is quantitative in nature. The content analysis will include the coding of each companys opening web page. The sample is inclusive of all the Fortune 100 companies in 1995 (ranked by total revenues), according to Times Pathfinder Service (http://pathfinder.com). The web pages surveyed were evaluated based on a coding model developed using the following variables: access, e-mail, software downloads, animation, Shockwave, sitemaps, search/help, frames, QuickTime/QuickTime VR, and web survey.


Literature Review/Rational

Everett Rogers believes that the rapid evolution of the Internet presents a unique opportunity to revisit theories about the diffusion of innovations (Rogers, 1995). There are four basic elements in Diffusion of Innovation Theroy. Diffusion of Innovation is, the process by which an innovation is communicated through certain channels over time among the members of a social system (Rogers, 1995). In relation to this study, Diffusion of Innovation is the process by which web applications (innovations) aid communication on the Internet (channels) over time among business organizations, Fortune 100 companies (social system).
The Internet is one of the most complicated and widespread innovations to ever be introduced to humanity. Its growth and development is of great interest to social scientists throughout the world. Until recently, most studies have looked to the Internet as the innovation itself. The LaRose and Hoag study focused on the organizational adoptions of the Internet and the clustering of innovations. This research studied businesses more general adoption of the Internet and other information systems. LaRose and Hoags study suggests, future research might well be directed toward further examining complex innovations like the Internet that have multiple attributes (1996).

The Internet is in fact a combination of many internal innovations which help to facilitate a more interactive, entertaining, and useful communication channel. These internal innovations such as Shockwave, animation, and web surveys could also be studied in much the same way general Internet adoption has been studied. Recent research on Hotel Management and Marketing on the Internet looked at how hoteliers value their Internet presence and the use of e-mail, audio, and video on those web sites (Murphy, Forrest, Wotring, and Brymer, 1996). The consideration of the Internets internal innovations is important in maintaining the efficiency and intrigue of the communication between the organization and individual.

The adoption of Internet tools by organizations has spawned widespread use of the Internet. Companies and educational institutions had the money and other resources available to install the hardware and software to enable their employees, students, and faculty to gain Internet access. In 1994, only one million North American people accessed the Internet from their residence (Find/SVP, 1994), while five million others accessed the Internet through their school, employer, or other organizations (OReilly & Associates, 1995). If large institutions sparked Internet diffusion, they should also be first to adopt web technologies to help develop their web presence.

Diffusion of Innovation shows that there is a relationship between the size of an organization and its ability to adopt innovations. Rogers states that, the size of an organization has consistently been found to be positively related to its innovativeness: larger organizations are more innovative (Rogers, 1995, p. 379). Logically, the theroy can be extended to suggest that organizations that specializing in, or involved with, information processing should more readily adopt information services and web tools. The Information Economy: Definition and Measurement discusses taxonomy, adding that organizations whose primary function deals with the information sector of society should be more ready to adopt information technology than those who are in the secondary information sector (Porat, 1977). These theories indicate large companies, such as those listed in the Fortune 100, have a tendency towards higher innovativeness. The study of these firms web sites is appropriate because they should more consistently use Internet innovations. In addition, companies in telecommunication, computer, and electronic industries will be more likely to adopt a greater number of new Internet innovations.

Early adopters (Rogers, 1995) of a technology are an important key to the diffusion of any innovation. These individuals or organizations are among the first to try out an innovation. They have a high degree of innovativeness which is the degree to which an individual or other unit of adoption is faster in adopting new ideas than other members of a social system (Williams, Rice, Rogers, 1985). Early adopters also provide opinion leadership to others as to whether they should adopt a specific innovation. This is a logical conclusion because of the early adopters success or failure with the new technology. Companies in telecommunication, computer, and electronic industries by their innovative nature should tend to be early adopters of Internet communication. Therefore, these three industries should embrace more Internet innovations than companies outside of these industries.

Innovation laggards (Rogers, 1995) are those individuals or organizations who are among the last to adopt an innovation, if they adopt at all. Fortune 100 companies that do not have a URL domain yet established could be defined as innovation laggards. According to Rogers, laggards constitute the last 16% of organizations to adopt a new technology (1995). It could also be reasoned that Internet laggards should not be within the telecommunication, computer, or electronic industries because of their innovative nature.

In summary, the Internet is an innovation that has the potential to change communication between individuals and organizations. In the past, diffusion of this technology, the Internet, has mainly been studied as an innovation in and of itself. Discussions in such studies have actually suggested the further investigation of the many facets of the Internet. The study of Hotel Management and Marketing on the Internet, by Murphy, et al., identified the importance of each Internet innovation as a different variable. A study of web technology adoption by large companies, such as the Fortune 100, is appropriate because they have a tendency to be innovative. Fortune 100 companies are a prime example of the large organizations described by Rogers (1995). According to Porat, organizations can be categorized into primary and secondary information sectors (1977). Therefore, primary information companies such as the telecommunication, computer, and electronic industries will be more likely to adopt a greater number of new Internet innovations. These three industries innovative nature should make them more apt to embrace Internet innovations.


Methods

This research is a descriptive study that surveys the Fortune 100 companies, using a content analysis to determine web innovation adoption. The two coders were trained by a coding supervisor. Summative reliability was determined and compared to the initial reliability. The variables surveyed in the content analysis were the following: access, e-mail, software downloads, animation, Shockwave, sitemap, search/help, frames, QuickTime/QTVR, and web survey. Each coder was primarily responsible for fifty Fortune 100 sites. In addition, twenty-five of the sites were examined by both coders to gather the summative reliability.

The sampling method was non-random and included all of the Fortune 100 companies from 1995 . The entire Fortune 100 was selected because it gave a uniform area to survey. A content analysis was conducted of each companies web site. Through the Times Pathfinder search engine we found a listing of Fortune 100 companies URLs.

For training, the coding supervisor gave the two coders 10 URLs of music web sites. These training sites consisted of the first ten results from a search for music conducted on the AltaVista search engine. Initial reliability was established by coding twenty companies within the Fortune 500, but outside the Fortune 100. Using Scotts Pi formula (total correct - total incorrect divided by the total number measured) to measure initial reliability, the coders percentages for each variable were as follows:


Access : [100%] if the coder was able to access the page.

E-mail: [90%] if there was a link on the first page that directly led to the capability of sending an e-mail message (be it a form or browser e-mail window).

Software Downloads: [100%] if there was a link on the first page that directly linked to a software download or a page that contains such.

Animation: [100%] if the first page contained any use of animation (except blinking text).

Shockwave: [100%] if the first page contained Shockwave or had a direct link to a page that contained it.

Sitemap: [90%] if the first page contained or had a direct link to a sitemap.

Search/Help: [80%] if the first page contained a search or help function or if it contained a direct link to a page that did.

Frames: [90%] if the first page employed the use of frames or contained a direct link to a page that does (specified by Visit Our Frames version, Frames, etc.).

QT/QTVR: [100%] if the first page contained Apples QuickTime or QuickTime VR technologies or a direct link to a page that contains such.

Web Survey: [100%] if the first page contained a survey or a direct link to a page that contains a survey.

The first coder was primarily responsible for the top 50 Fortune 100 companies. The second coder was responsible for the lower 50 Fortune 100 companies. Twenty-five of the web sites were coded by both of the coders to constitute the summative reliability. The coders recorded a one if the variable was present and a zero if the variable was absent. All coding of the web sites was conducted between March 26 and March 30, 1997.

Validity for this study is mainly concerned with the external measures of our content analysis survey. In designing this survey model, researchers relied heavily on Krippendorf's book Content Analysis: An Introduction to Its Methodology (1980). Two reliability studies were carried out to ensure that the coders were in agreement. The coding supervisor observed the summative reliability test to ensure the coders were coding the same web pages. Our study also had experts in web content as coders. The coders themselves were very familiar with web page features. All three have developed web sites and are all graduate students in Interactive Communications at The Florida State University. Some of the coding categories have already been acknowledged in other research such as the Hotel Management and Marketing on the Internet (Murphy, 1996) study. Categories covered by this study that are of relevance to our study are e-mail, video (ShockWave in this study), and audio (not covered in our study).

The research design chosen for this study was a quantitative content analysis, examining the frequency of ten variables among the Fortune 100 web sites. These results will allow a comparison of Fortune 100 companies categorized in the telecommunication, electronic, and computer industries against the remaining organizations. First, the number of variables for each site were totaled to determine the organizations score, out of a possible ten. Next the scores of all Fortune 100 companies were averaged. Eighteen companies of the Fortune 100 were categorized in the telecommunication, electronic, and computer industries, by Gail Grant of Open Market, Incorporated. The scores of these eighteen were then averaged. Finally, the remaining organizations innovation scores were averaged together. These average scores provide a comparison between the two defined groups.


Results

The results of our web innovation survey fell within the acceptable parameters of reliability. The coders reliability stayed the same or improved in every variable surveyed. To determine if the hypothesis was correct, three averages for each variable were calculated. The first average tabulated was the percentage of all Fortune 100 companies that utilized a specific variable. The Fortune 100 companies were then divided into two categories: TEC (telecommunication, electronic, computer industries) and non-TEC industries. The averages for each variable were then calculated for each category. This will indicate if the TEC or non-TEC category has a higher occurrence of web innovation adoption.

The average number of innovations, out of the ten variables measured, used by all Fortune 100 companies was 2.35 per web site. The average number of innovations adopted by TEC companies was 3.33 per web site. The average number of innovations utilized by non-TEC companies was 2.13 per web site. These results indicate the TEC companies have a 50.9% higher adoption rate than non-TEC companies.

TEC Companies
(18 companies) non-TEC Companies
(82 companies) Fortune 100 Companies
(100 companies) Avg. # of web site innovations =3.33 Avg. # of web site innovations =2.13 Avg. # of web site innovations =2.35

In five out of ten surveyed variables, the TEC companies had a higher rate of adoption than non-TEC companies. TEC companies had higher results in the following variables: access, e-mail, animation, sitemap, and search/help. The non-TEC companies had a higher usage of software downloads, ShockWave, frames, and web surveys. None of the Fortune 100 companies applied QuickTime to their web sites.


TEC Companies
(18 companies) non-TEC Companies
(82 companies) Fortune 100 Companies
(100 companies) Access 94.4% 80.5% 83.0 E-mail 50.0% 30.5% 34.0% Soft. Downloads 5.6% 11.0% 10.0% Animation 55.6% 28.0% 33.0% ShockWave 0.0% 2.4% 2.0% Sitemap 44.4% 19.5% 24.0% Search/Help 83.3% 34.1% 43.0% Frames 0.0% 4.9% 4.0% QuickTime/QTVR 0.0% 0.0% 0.0% Web Survey 0.0% 2.4% 2.0%


Conclusions

The general averages of web innovation adoption, suggest that TEC companies had a higher adoption rate of web innovations than non-TEC companies. This conclusion is consistent with the hypothesis stated and with Everett Rogers' Diffusion of Innovation theory. The companies in the telecommunication, electronic, and computer industries have a higher tendency to be innovative on their web sites. These companies whose business falls into the primary information sector should be more ready to adopt Internet technologies than those in the secondary information sector.

The individual variables also provide insight into the adoption of new technologies on the Internet. Although the TEC companies had higher results in only five of the ten categories, their adoption percentages were nearly doubled that of the non-TEC companies. Non-TEC companies adoption rates were higher in four of the ten variables. Yet, the adoption rate of the non-TEC companies was no more than 6% above the TEC companies results. Neither category used QuickTime/QTVR.

Seventeen of the Fortune 100 companies had either no DNS-entry or were inaccessible. These seventeen could be constituted as innovation laggards. These results are consistent with Diffusion of Innovation paradigm. Rogers states that 16% of a social system will fall into the laggard category (Rogers, 1995). Although one would reason that TEC companies would not fall into this category, AT&T's web site was inaccessible during coding. Their site, www.att.com, requested a user name and password. This was the only TEC company that was not able to be coded during the content analysis.

The limitations of this study are embedded in the fact that the content analysis only considered the presence of web innovations. The study did not evaluate causal relationships. The identification of the web designer may give a further understanding of how and why the web sites were designed. Are the sites built in-house, or were outside contractors hired by the Fortune 100 companies? Would an automotive company hire a telecommunication firm to design and maintain their web site? Another limitation of the study is that it only surveyed ten variables, while there are many more new technological tools that could be included, such as bit maps. These newest technologies make the web sites even more interactive and entertaining.

Future research on this topic should include a follow-up survey of this study to determine what companies have adopted additional web technologies. Investigation could also be conducted to learn which web applications deemed new are being adopted. Future studies could extend this research to broaden the scope of the content analysis to Fortune 500 companies and their adoption of web innovations. Additional content analyses would be beneficial in describing web adoption trends over time. A question that may spark further investigation is, how readily do specific industries adopt web innovations?


Bibliography

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Grant G., (1997). http://www-1.openmarket.com/personal/grant/ Cited January 26, 1997.

Krippendorff, K. (1980). Content Analysis: An Introduction to Its Methodology , Newbury Park, CA: Sage Publications, Inc.

LaRose R., A. Hoag, (1996). Organizational Adoptions of the Internet and the Clustering of Innovations. http://www.tc.msu.edu/itslab/larose/ Cited February 2, 1997.

Murphy, J., E. J. Forrest, C. E. Wotring, R. A. Brymer, (1996). Hotel Management and Marketing on the Internet, Cornell Hotel and Restaurant Quarterly 37(3), p.p. 70-82.

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Porat, M.U. (1977). The Information Economy: Definition and Measurement , Washington, DC: U.S. Government Printing Office.

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Williams, F., R. E. Rice, E. M. Rogers (1988). Research Methods and the Media . New York: The Free Press.