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The persuasive effect of graphics in computer-mediated communication
Computers in Human Behavior, Vol.7, pp. 269-279, 1991
0747-5632/91 $3.00 + .O0 Copyright © 1991 PergamotaPress pie
Printed in the U.S.A. All rights reserved.
The Persuasive Effect of Graphics in Computer-Mediated Communication Wesley C. King, Jr. Miami University
M. Marie Dent The University of Georgia
Edward W. Miles Georgia State University
Abstract - - This study, an investigation of the persuasive effect of presentation graphics, provides a conceptual and empirical link between persuasive effect and computer-generated graphics as a form of computer-mediated communication. Testing of four hypotheses that examine differences in persuasive effect among three treatments (written text, static graphics, and dynamic graphics) provides the empirical link between graphics as a decision support tool and persuasive effect. Implications of these differences are discussed.
REVIEW OF LITERATURE
"(M)uch of the literature on using computers for communication, including both analytical articles written for professional computer users and reports of empirical research on computing, does not address the issues of how using a computer might influence the way groups communicate or the way people respond to the communiRequests for reprints should be addressed t o Prof. W. C. King, Jr., School of Business Administration, Laws Hall, Miami University, Oxford, OH 45056. 269
270
King, Dent, and Miles
cation of others . . . . The underlying assumption is that people do not respond differently to information transmitted using a computer" (Siegel, Dubrovsky, Kiesler, & McGuire, 1986, p. 184). Despite this underlying assumption, the current level of investigation about the effects of the computer in the workplace has shown that computer usage does have a significant effect upon the way individuals and groups interact in the organizational setting (Greist, Klein, & Erdman, 1976; Greist, Klein, & Van Cura, 1973; Hiltz, Johnson, Aronovitch, & Turoff, 1980; Kiesler, Zubrow, Moses, & Geller, 1983). This understanding, coupled with an expanded organizational emphasis on information technology (Weill & Olson, 1989), has led investigators from such diverse disciplines as ergonomics, sociology, psychology, education, management, and communication to attempt to identify the effects of computer-based technology on the organization, its employees, and its future. Their work has covered topics ranging from furniture design, lighting, and screen factors to user satisfaction, productivity, motivation, job stress, and decision support. Decision support researchers have focused their attention on a number of areas including cognitive style, type of task, perception, and a range of associated variables (e.g., Bostrom, Olfman, & Sein, 1990; Joshi, 1989). However, they have limited their investigation of graphics to studies examining whether the use of graphics increases decision effectiveness. What is remarkable about these studies is the lack of consistency in their results (DeSanctis, 1984; Dickson, DeSanctis, & McBride, 1986; Ives, 1982; Jarvenpaa, Dickson, & DeSanctis, 1985). Researchers (DeSanctis, 1984; Jarvenpaa et al., 1985) have reviewed this body of work and have concluded that the inconsistent findings are the result of numerous variables including viewer preference, complexity of the task, individual recognition and recall, environment, cognitive style of the decision maker, problem understanding, attitude, quality of the presentation, the lack of internal validity and reliability, and the failure to control for screen design issues such as screen resolution and illumination, use of color, height of letters, spaces between lines, line justification, color preferences for different activities, differences between working from hard copy or video terminals, and the lack of standardization for the design of graphics used in different studies. Most prior studies of the effects of graphics have dealt with graphical presentations using bar graphs, pie charts, graphs, and other simple graphics that were most often used as analytical aids. However, new software packages now offer graphical options that far exceed the capabilities of earlier softwares, and as a result, previous research with simpler graphics fails to capture today's environment. The ability to create animation on the screen, to produce three-dimensional effects (see Lee, MacLachian, & Wallace, 1986), to transform static (still) graphics into dynamic (moving or animated) graphics, and to combine a variety of audiovisual effects into a presentation provides managers with more options and researchers with new research questions. Such advanced graphics capabilities require today's researchers to distinguish between different types of graphical images. Hart (1986) has distinguished between "analytical graphics" and "presentation graphics," the former being pictorial devices such as pie charts or bar graphs that assist in presenting data, charting trends and relationships, and conveying concepts while the latter utilizes the computer's ability to manipulate such images and a smorgasbord of other visuals to create the desired visual effect. According to Hart (1986), presentation graphics are to be used "when the need is to impress" (p. 38). A similar classification is
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271
Lehman's (1986) "management graphics" that includes graphical images used as tools for decision making and graphics used for communication, either for presentation of information or for persuasion. The prior work concerning graphics in decision support has largely focused on computer based graphics as a support tool to assist decision makers by spotting trends and by summarizing, analyzing, and manipulating data. MIS researchers have typically measured effectiveness by using several dependent variables ranging from the time required to make the decision to the quality of the decision, degree of recall of the information, and satisfaction with the decision. While useful in measuring the effectiveness of graphics in a decision support environment, these variables do not adequately capture an important behavioral variable associated with graphics: persuasive appeal. If the making of a decision is viewed as the result of some persuasive effect upon the decision maker, then any graphics used to reach a decision are an integral part of a persuasive process. Hence, a broader view of decision making would be that a decision occurs as a result of some persuasive effect upon the decision maker. (For a discussion of four theoretical approaches that serve as foundations for contemporary persuasion theory, see Petty, Ostrom, & Brock, 1981.) In that regard, graphics are a part of a persuasive process, not merely support tools in decision making. One of the problems in studying the effectiveness of the persuasive appeal of graphics is that researchers studying persuasion and those studying the persuasive effect of presentation graphics have been working separately and publishing in the journals of different disciplines. Articles about the effectiveness of graphics in decision support were published in the management science and management information systems journals (e.g., Desanctis, 1984; Dickson et al., 1986; Ives, 1982; Jarvenpaa et al., 1985) while researchers studying the phenomenon of persuasion have, for the most part, published in psychological, psychiatric, and human factors journals. This absence of research concerning graphics' persuasive effect has not gone unnoticed. Dickson et al. (1986) postulated that the use of graphics may be more effective in persuasion than in decision support. Lehman (1986) as well as Vogel, Dickson, and Lehman (1986) cited evidence that presentations whose purpose was to persuade were more effective when visual aids were used. Accordingly, an area worthy of research attention is the difference in persuasive effect of computer-generated graphics - - both static and dynamic graphics - - as compared to the more conventional mode of persuasion, the written text. The purpose of this study was to investigate how presentation graphics can persuade or influence a group or an individual to accept an action or point of view. To test the persuasive effect of presentation graphics, this study tested four hypotheses. These hypotheses focused upon three treatment conditions: written text, static (still) graphics, and dynamic (moving) graphics. H1A. Subjects exposed to the static graphics treatment will report more attitude change than will subjects exposed only to the written text treatment. H1B. Subjects exposed to the dynamic graphics treatment will report more attitude change than will subjects exposed only to the static graphics treatment or to the written text treatment. H2A. Subjects exposed to the static graphics treatment will report more intention to change behavior than will subjects exposed only to the written text treatment.
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H2B.
Subjects exposed to the dynamic graphics treatment will report more intention to change behavior than will subjects exposed only to the static graphics treatment or to the written text treatment.
METHOD
Subjects The sample consisted of 179 students (48% female, 52% male) enrolled in 3 sections of two upper division management courses at a major state university in the Southeast. The average age was 22.05; the age range, 19 to 37.
Stimulus Materials Subjects in this study received a message designed to persuade them to agree to take action. All the subjects were undergraduate business students, and a message was selected that all would find relevant. The goal of the presentation was to persuade subjects to agree to pledge a future donation to the university's business school. A persuasive message - - "Fifty for the Future" - - explained why alumni should make financial contributions to their alma mater. The thrust of the message was to convey that a contribution to the business school was an investment in the reputation of the school and therefore an investment to enhance the quality of the school's degree. Because students are often without discretionary funds, any appeal for immediate donations could prejudice the results. Consequently, the message focused upon financial rewards that their degree would offer them once they obtained their first job and encouraged them to "enhance the quality of your degree by investing $50 in the Business School now and make that investment within six months after starting your first job." See Appendix A for the complete text of the stimulus message. The independent variable in this study was the communication mode in which the persuasive appeal was presented. Subjects in the first treatment received the explanation of why they should make a donation in text form only, that is, the persuasive appeal was presented to the subjects in print form on standard plain white paper. Individuals in the second treatment level viewed a presentation in which the identical text received by the first group was projected on a screen via static (still) graphics. This presentation was created on a personal computer using IBM's Storyboard, a color graphics software package. Subjects in the third treatment level viewed a presentation of the same text seen by the other two groups. The order and content of the graphics in this treatment were the same as those viewed by the second group. However, this text was presented using dynamic (moving) graphics, the chief difference being that only this third treatment level fully used the capabilities of computer generated graphics. This presentation was designed to represent a prototype of presentations commonly created with current graphics softwares and included such effects as screen implosion and explosion; screen fade-in and fade-out; wipe left and wipe right; scroll-up and scroll-down; scroll-left and scroll-right; as well as the manipulation and change of color and font size and the moving of graphs, other figures, and information around the screen to create visual appeal to the message. Presentations in both
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273
the second and third treatment levels were projected onto a 60-inch × 60-inch screen using rear-screen projection. Measurement Instrument
Subjects in all treatment conditions received the same instntment to measure two dependent variables and two covariate variables. All four variables were measured using seven-point Likert-type scales. See Table 1 for means and standard deviations for these variables. The first dependent variable (Inclined) was the degree of change in the subjects' inclination to make a donation: "As a result of this information, I am more inclined to donate to the business school." The second dependent variable (Pledge) was a more specific agreement to make a pledge to be fulfilled within a specific time limit: "I would be willing to pledge financial support to the business school within six months after starting my first job." The two covariates were included to control for the subjects' predispositions to make contributions to the business school as an alumni. The first covariate (Should) measured how strongly a subject believed that alumni should donate ("I believe that alumni should make donations to the business school"). The second covariate (Reputation) tapped the degree to which subjects believed that improvement in the business school's reputation influences the value of the degrees of alumni ("I believe that even after I graduate, maintaining a strong business school with a good reputation will increase the value of my degree"). Procedure
Although subjects responded to the stimulus independently, they received the stimulus materials in groups whose size ranged from 18 to 48. The text-only treatment was administered to 37 subjects; the static graphic presentation to 73 subjects; and the dynamic graphic presentation to 69 subjects. All subjects in the same section were assigned to the same treatment group. Sections were randomly assigned to the treatments. The composition of subjects in the three treatment groups were not significantly different in terms of age, gender, or major.
Table 1. Cell Means and Standard Deviations
Presentation Method
Variable
Mean
SD
Text-Only
Inclined Pledge Should Reputation
3.97 3.86 4.83 5.28
1.52 1.57 1.21 1.11
Static Graphics
Inclined Pledge Should Reputation
4.27 4.43 5.10 5.49
1.15 1.34 0.90 1.09
Dynamic Graphics
inclined Pledge Should Reputation
4.51 4.26 5.17 5.49
1.21 1.16 1.01 1.01
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All subjects were told that the research in which they were participating concerned how individuals make choices and that the experimenters had no vested interest in the chosen topic. After this introduction, the text-only group was given the pages on which the persuasive message was printed and the questionnaire that measured the dependent variables and covariates. After the same introduction described above, the two graphics groups were shown their respective presentations. The same questionnaire was distributed immediately following the presentation. The persuasive messages were self-explanatory and instructions for completing the questionnaire were included in the questionnaire. Consequently, no further instructions were provided to any treatlnent group.
RESULTS
A one-way analysis of covariance (ANACOVA) was used to test H1A and H1B. Belief that alumni should donate ("should") and belief that a strong reputation will affect the value of degrees of alumni ("reputation") were used as covariates. Table 2 shows the results of this test. As Table 2 indicates, both covariates have a significant effect. As a result, their inclusion helps to clarify the source of the variance. The test of the dependent variable "inclined" that measured a subject's inclination to make a donation to the business school showed that the choice of presentation method was significant at the .05 level. A Duncan's Multiple Range Test was performed as a follow-up analysis to locate the differences among group means Table 2. Results of Analysis of Covarlance (ANACOVA) and Duncan's Test for =Inclined" and "Pledge" Source
clf
MS
F
p
Inclined Presentation Method Should Reputation Model Error
2 1 1 4 172
3.43 60.71 7.78 18.84 1.20
2.86 50.65 6.49 15.72
.05 .0001 .01 .0001
Pledge Presentation Method Should Reputation Model Error
2 1 1 4 172
2.71 110.05 18.45 33.48 1.02
2.66 108.30 18.16 32.95
.07 .0001 .0001 .0001
Presentation Method
Mean
Duncan's Testa
Inclined Dynamic Graphics Static Graphics Text-Only
4.51 4.27 3.97
A A
Pledge Static Graphics Dynamic Graphics Text-Only
4.43 4.26 3.86
A A
B B
B
aMeans having the same letter are not significantly different at the .05 level.
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275
(Table 2). The mean for the dynamic graphics treatment was significantly different from the mean for the text-only treatment. This result partially confirms H1B. However, the mean for the static graphics group was not significantly different from either of the other cell means. Therefore, H 1A was not confLrmed. H2A and H2B were tested using identical analyses for the dependent variable "pledge" (Table 2). The overall results of the analysis of covariance were only marginally significant. However, the follow-up Duncan's test did identify the text treatment mean as significantly lower than the means for the static graphics and dynamic graphics treatments. This result supports H2A. As with H1B, H2B was only partially supported. The data indicate that subjects exposed to the dynamic graphics treatment were more likely to pledge to donate than were those exposed to the text-only treatment; however, the analysis revealed no significant differences between the willingness to pledge for those subjects exposed to the dynamic graphics treatment versus those exposed to the static graphics treatment.
DISCUSSION
Earlier research (Chaiken & Eagly, 1976; Shelby, 1986) has noted that oral and visual channels are generally more persuasive for simple messages while written channels are more persuasive for more complex messages. These findings may have been adequate to describe an environment in which only written, oral, or videotaped messages were available as channels for persuasive messages. Today, however, the widespread use of computer-generated graphics in organizational settings offers an additional communication mode for the transmission of persuasive messages. As the results of this study indicate, graphics can be effective both in creating what the persuasion literature calls persuasive effect and in influencing people to change their attitudes and their behavioral intentions as a result of this persuasive effect. Subjects who viewed the dynamics graphics presentation were more inclined to donate money as a result of viewing the presentation than were those who received the text-only treatment. Furthermore, subjects in both the static and dynamic treatment groups indicated a greater willingness to commit themselves to pledging money to the business school than did subjects in the textonly treatment. Several conclusions can be drawn from these results. First, text-only and graphics treatments differ in that the former involves a single mode of communication (written) while the latter involves the coupling of several modes: a traditional written message is coupled with graphs, charts, figures, and animation, i.e., the addition of visual appeal to the message. One explanation for the greater persuasive appeal of graphical presentations versus written text alone is that the graphical presentations were better able to gain and maintain the subject's attention. As Shelby (1986) pointed out, the first steps associated with implementing persuasive strategies involve getting subjects' attention and stimulating interest. Similarly, Modey and Walker (1987) found that a message's importance, novelty, and plausibility are all necessary conditions for belief change. The stimulus message (alumni donations) in the experimental setting was designed to be both important and plausible to all subjects; however, the familiar format of textual material was certainly less novel than either of the graphics treatments. Arguably, the enhanced persuasive effect may have been generated by increased interest and attention because of the
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uniqueness of the graphical communication mode, i.e., the coupling of the message with color, pictures, diagrams, animation (with the dynamic graphics treatment), and the novelty of viewing a persuasive appeal rather than just reading it. In this setting, the more traditional means of persuading individuals via the written word created less of a persuasive effect than did coupling the written word with capabilities of the newer technologies. In an organizational setting, using computer-generated graphics in persuasive appeals may be more effective in swaying decision makers to a point of view than would the same message transmitted via another communication mode. Because computer presentation graphics is a new and rapidly changing phenomenon, current research into the persuasive effect of this phenomenon is limited and has produced what appears to be contradictory results (DeSanctis, 1984; Jarvenpaa et al., 1985). Further research must identify the conditions under which a greater persuasive effect can be achieved by using computergenerated graphics versus using other more traditional formats. While the present study provides evidence of the persuasive effect of presentation graphics, it leaves unexplored a theoretical explanation for such an effect. At least two interrelated issues arise: theoretically accounting for these results from a persuasion theory perspective and assessing the persuasive effect's permanence upon attitude change. One explanation (Buller, 1986) suggests that presentation graphics, if viewed as irrelevant to the message itself, may well serve as a distracter that can reduce attitude change, not enhance it. As Buller (1986) has noted, "communication irrelevant distraction generally reduces the efficacy of a persuasive message" (p. 109). Thus, though the graphics may be novel and though they may hold the viewer's attention, they may be ineffective in producing the desired persuasive effect if viewed by the subjects as irrelevant to the message. In such a case, the communication mode itself becomes the message; the persuasive effect that is intended by the communication is not achieved; the validity of any measure of persuasive effect is called into question; and any reported attitude change will most likely be short-lived. On the other hand, presentation graphics classified as a relevant distraction can enhance the efficacy of a persuasive appeal (Buller, 1986). Focusing on presentation graphics either as a communication relevant or as a communication irrelevant distraction is an important line of inquiry to assess the true persuasive effect of presentation graphics and to be able to offer practical guidelines concerning how to ensure the communication relevance of a graphicsbased communication. A different perspective to explain graphics' persuasive effect suggests that graphics may well serve as a form of persuasive evidence, thus enhancing persuasive effect and effecting true attitude change (Reinard, 1988). If left to draw their own conclusions from the graphics, viewers become cognitively involved in the process and therefore more committed to the attitude change (see Perloff & Brock, 1980.) In this case, involving the viewer is a critical variable affecting the creation of persuasive effect. Which of these two (or other) explanations adequately explains the persuasive effect of presentation graphics remains unexplored and points to the need for both behavioral and communication researchers skilled in studying persuasion and attitude change to enter this research arena. Because of the persuasive potential available to users of graphics, this communication mode should no longer be viewed merely as a support tool in a decision support environment but as an important tool for the organization to communicate to its diverse constituency. The associated research agenda will be demanding. Unraveling the intricacies of human information processing is difficult enough
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277
when researchers are studying only the effectiveness of decision support tools; adding human behavior and choice variables, typically associated with the persuasion process, increases the complexity of the research. However, as Huseman and Miles (1988) have noted, the transformation of the computer age into the information age ensures that "organizations that effectively gather, monitor, and filter information will increasingly have a competitive edge" (p. 181). Further investigation of the persuasive effect of computer graphics is necessary to tap graphics' potential in this information age.
REFERENCES Bostrom, R. P., Olfman, L., & Sein, M. K. (1990). The importance of learning style in end-user training. MIS Quarterly, 14, 100-119. Buller, D. B. (1986). Distraction during persuasive communication: A meta-analytic review. Communication Monographs, 53, 91-114. Chaiken, S. & Eagly, A. H. (1976). Communication modality as a determinant of message persuasiveness and message comprehensibility. Journal of Personality and Social Psychology, 34, 605-614. DeSanctis, G. (1984). Computer graphics as decision aids: Directions for research. Decision Sciences, 15, 463---487. Dickson, G. W., DeSanctis,G,. & McBride, D. J. (1986). Understanding the effectivenessof computer graphics for decision support: A cumulative experimental approach. Communications of the ACM, 29, 40--47. Greist,J. H., Klein, M. H., & Erdman, H. P. (1976). Routine on-linepsychiatricdiagnosisby computer.American Journal of Psychiatry, 12, 1405-1408. Greist, J. H., Klein, M. H., & Van Cura,. L. J. (1973). A computer interview by psychiatric patient target symptoms. Archives of General Psychiatry, 29, 247-253. Hart, R. (1986). Add impact with graphics. Administrative Management, 47(7), 38-43. Hiltz, S. R., Johnson, K., Aronovitch, C., & Turoff, M. (1980). Face-w-face vs. computerized conferences: A controlled experiment: Vol. 1. Findings (Research Report No. 12). Newark: New Jersey Institute of Technology. Huseman, R. C., & Miles, E. W. (1988). Organizational communication in the information age: Implications of computer-based systems. Journal of Management, 14, 181-204. Ires, B. (1982). Graphical user interfaces for business information systems. MIS Quarterly, 6, 15-47. Jarvenpaa, S. L., Dickson, G. W. & DeSanctis, G. (1985). Methodological issues in experimental IS research: Experiences and recommendations. MIS Quarterly, 9, 141-156. Joshi, K. (1989). The measurement of fairness or equity perceptions of management information systems users. MIS Quarterly, 13, 342-358. Kiesler, S., Zubrow, D., Moses, A. M., & Geller, V. (1983). Affect in computer-mediated communication. Unpublished manuscript, Carnegie-Mellon University, Pittsburgh, PA. Lee, J. M., MacLachian, J., & Wallace, W. A. (1986). The effects of 3D imagery on managerial data interpretation. MIS Quarterly, 10, 257-269. Lehman, J. A. (1986). Business graphics: A taxonomy for information systems managers. Data Base, 18, 24-31. Morley, D. D., & Walker, K. B. (1987). The role of importance, novelty, and plausibility in producing belief change. Communication Monographs, 54, 436-442. Pedoff, R. M., & Brock, T. C. (1980)...."And thinking makes it so": Cognitive responses and persuasion. In M. E. Roloff & G. R. Miller (F_xts.), Persuasion: New directions in theory and research (pp. 67-100). Beverly Hills, CA: Sage. Petty, R. E., Ostrom, T. M., & Brock, T. C. (1981). Historical foundations of the cognitive response approach to attitudes and persuasion. In R. E. Petty, T. M. Ostrom, & T. C. Brock (Eds.), Cognitive Responses to Persuasion, (pp. 9-14). Hillsdale, NJ: Lawrence Erlbaum Associates. Reinard, J. C. (1988). The empirical study of the persuasive effects of evidence: The status after fifty years of research. Human Communication Research, 15, 3-59. Shelby, A. N. (1986). The theoretical bases of persuasion: A critical introduction. The Journal of Business Communication, 23, 5-29.
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Siegel, J., Dubrovsky, V., Kiesler, S., & McGuire, T. W. (1986). Group processes in computer-mediated communication. Organizational Behavior and Human Decision Processes, 37, 157-187. Vogel, D. R., Dickson, G. W., & Lehman, J. A. (1986). Persuasion and the role of visual presentation support: The UM/3M study (Working Paper No. MISRC-WP-86-11). Minneapolis: University of Minnesota, Management Information Systems Research Center. Weill, P., & Olson, M. H. (1989). Managing investment in information technology: Mini case exampies and implications. MIS Quarterly, 13, 2-17.
APPENDIX A. FIFTY FOR THE FUTURE
One of the principles you learn in the Business School is that the quality of your investment substantially affects your future financial health. When looking for that first job, you put this principle to work: --You spend $50 plus for a good looking resume; --You spend more than $50 for an expensive pair of shoes; and --You spend $50 or more on long distance phone calls to set up interviews and to talk with important people in the organization. You make these investments because you are convinced they make a difference, because they are wise investments in your future, and because you believe that the degree you have earned from the College of Business is a high quality degree that warrants these investments. Just as you know that you must make quality investments in resumes, shoes, and phone calls to promote your search for a job, you know that someone must invest in the College of Business to maintain the quality of the degree you are presently earning. Consider these statistics. The College of Business graduates about 900 students each year. If each of these 900 alumni invested just $50 to improve the quality of their degrees, the Business School would receive an additional $45,000 annually. How can this money enhance the quality of your degree? - - B y recruiting renowned professors as faculty members; - - B y attracting brighter and brighter students with increased scholarship funds; - - B y recruiting distinguished practitioners and lecturers to bring the everyday world of business into the classroom; - - B y rewarding professors who go that extra mile in classroom teaching. The 1986 average starting salary for a University of Georgia business major exceeded $20,000. An investment of $50 is less than 1/4% of that salary. That's about four large pizzas, not including soft drinks or extra toppings. For your $50 investment, you give the Business School the resources to provide you with higher quality teaching. For your $50 investment, you help yourself now and in the future by enhancing the reputation of the Business School... your Business School. For your $50 investment, you increase the worth of your degree even after you have graduated by ensuring that employers will continue to take note of a business degree from the University of Georgia's College of Business.
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Don't go to that first interview or any interview in the future with only a good looking resume, expensive shoes, and a large phone bill. Pay for your resume, pay for your shoes, and pay your phone bill. But pay for your future too. Enhance the quality of your degree by investing $50 in the Business School now and make that investment within six months after starting your first job.
0747-5632/91 $3.00 + .O0 Copyright © 1991 PergamotaPress pie
Printed in the U.S.A. All rights reserved.
The Persuasive Effect of Graphics in Computer-Mediated Communication Wesley C. King, Jr. Miami University
M. Marie Dent The University of Georgia
Edward W. Miles Georgia State University
Abstract - - This study, an investigation of the persuasive effect of presentation graphics, provides a conceptual and empirical link between persuasive effect and computer-generated graphics as a form of computer-mediated communication. Testing of four hypotheses that examine differences in persuasive effect among three treatments (written text, static graphics, and dynamic graphics) provides the empirical link between graphics as a decision support tool and persuasive effect. Implications of these differences are discussed.
REVIEW OF LITERATURE
"(M)uch of the literature on using computers for communication, including both analytical articles written for professional computer users and reports of empirical research on computing, does not address the issues of how using a computer might influence the way groups communicate or the way people respond to the communiRequests for reprints should be addressed t o Prof. W. C. King, Jr., School of Business Administration, Laws Hall, Miami University, Oxford, OH 45056. 269
270
King, Dent, and Miles
cation of others . . . . The underlying assumption is that people do not respond differently to information transmitted using a computer" (Siegel, Dubrovsky, Kiesler, & McGuire, 1986, p. 184). Despite this underlying assumption, the current level of investigation about the effects of the computer in the workplace has shown that computer usage does have a significant effect upon the way individuals and groups interact in the organizational setting (Greist, Klein, & Erdman, 1976; Greist, Klein, & Van Cura, 1973; Hiltz, Johnson, Aronovitch, & Turoff, 1980; Kiesler, Zubrow, Moses, & Geller, 1983). This understanding, coupled with an expanded organizational emphasis on information technology (Weill & Olson, 1989), has led investigators from such diverse disciplines as ergonomics, sociology, psychology, education, management, and communication to attempt to identify the effects of computer-based technology on the organization, its employees, and its future. Their work has covered topics ranging from furniture design, lighting, and screen factors to user satisfaction, productivity, motivation, job stress, and decision support. Decision support researchers have focused their attention on a number of areas including cognitive style, type of task, perception, and a range of associated variables (e.g., Bostrom, Olfman, & Sein, 1990; Joshi, 1989). However, they have limited their investigation of graphics to studies examining whether the use of graphics increases decision effectiveness. What is remarkable about these studies is the lack of consistency in their results (DeSanctis, 1984; Dickson, DeSanctis, & McBride, 1986; Ives, 1982; Jarvenpaa, Dickson, & DeSanctis, 1985). Researchers (DeSanctis, 1984; Jarvenpaa et al., 1985) have reviewed this body of work and have concluded that the inconsistent findings are the result of numerous variables including viewer preference, complexity of the task, individual recognition and recall, environment, cognitive style of the decision maker, problem understanding, attitude, quality of the presentation, the lack of internal validity and reliability, and the failure to control for screen design issues such as screen resolution and illumination, use of color, height of letters, spaces between lines, line justification, color preferences for different activities, differences between working from hard copy or video terminals, and the lack of standardization for the design of graphics used in different studies. Most prior studies of the effects of graphics have dealt with graphical presentations using bar graphs, pie charts, graphs, and other simple graphics that were most often used as analytical aids. However, new software packages now offer graphical options that far exceed the capabilities of earlier softwares, and as a result, previous research with simpler graphics fails to capture today's environment. The ability to create animation on the screen, to produce three-dimensional effects (see Lee, MacLachian, & Wallace, 1986), to transform static (still) graphics into dynamic (moving or animated) graphics, and to combine a variety of audiovisual effects into a presentation provides managers with more options and researchers with new research questions. Such advanced graphics capabilities require today's researchers to distinguish between different types of graphical images. Hart (1986) has distinguished between "analytical graphics" and "presentation graphics," the former being pictorial devices such as pie charts or bar graphs that assist in presenting data, charting trends and relationships, and conveying concepts while the latter utilizes the computer's ability to manipulate such images and a smorgasbord of other visuals to create the desired visual effect. According to Hart (1986), presentation graphics are to be used "when the need is to impress" (p. 38). A similar classification is
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Lehman's (1986) "management graphics" that includes graphical images used as tools for decision making and graphics used for communication, either for presentation of information or for persuasion. The prior work concerning graphics in decision support has largely focused on computer based graphics as a support tool to assist decision makers by spotting trends and by summarizing, analyzing, and manipulating data. MIS researchers have typically measured effectiveness by using several dependent variables ranging from the time required to make the decision to the quality of the decision, degree of recall of the information, and satisfaction with the decision. While useful in measuring the effectiveness of graphics in a decision support environment, these variables do not adequately capture an important behavioral variable associated with graphics: persuasive appeal. If the making of a decision is viewed as the result of some persuasive effect upon the decision maker, then any graphics used to reach a decision are an integral part of a persuasive process. Hence, a broader view of decision making would be that a decision occurs as a result of some persuasive effect upon the decision maker. (For a discussion of four theoretical approaches that serve as foundations for contemporary persuasion theory, see Petty, Ostrom, & Brock, 1981.) In that regard, graphics are a part of a persuasive process, not merely support tools in decision making. One of the problems in studying the effectiveness of the persuasive appeal of graphics is that researchers studying persuasion and those studying the persuasive effect of presentation graphics have been working separately and publishing in the journals of different disciplines. Articles about the effectiveness of graphics in decision support were published in the management science and management information systems journals (e.g., Desanctis, 1984; Dickson et al., 1986; Ives, 1982; Jarvenpaa et al., 1985) while researchers studying the phenomenon of persuasion have, for the most part, published in psychological, psychiatric, and human factors journals. This absence of research concerning graphics' persuasive effect has not gone unnoticed. Dickson et al. (1986) postulated that the use of graphics may be more effective in persuasion than in decision support. Lehman (1986) as well as Vogel, Dickson, and Lehman (1986) cited evidence that presentations whose purpose was to persuade were more effective when visual aids were used. Accordingly, an area worthy of research attention is the difference in persuasive effect of computer-generated graphics - - both static and dynamic graphics - - as compared to the more conventional mode of persuasion, the written text. The purpose of this study was to investigate how presentation graphics can persuade or influence a group or an individual to accept an action or point of view. To test the persuasive effect of presentation graphics, this study tested four hypotheses. These hypotheses focused upon three treatment conditions: written text, static (still) graphics, and dynamic (moving) graphics. H1A. Subjects exposed to the static graphics treatment will report more attitude change than will subjects exposed only to the written text treatment. H1B. Subjects exposed to the dynamic graphics treatment will report more attitude change than will subjects exposed only to the static graphics treatment or to the written text treatment. H2A. Subjects exposed to the static graphics treatment will report more intention to change behavior than will subjects exposed only to the written text treatment.
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H2B.
Subjects exposed to the dynamic graphics treatment will report more intention to change behavior than will subjects exposed only to the static graphics treatment or to the written text treatment.
METHOD
Subjects The sample consisted of 179 students (48% female, 52% male) enrolled in 3 sections of two upper division management courses at a major state university in the Southeast. The average age was 22.05; the age range, 19 to 37.
Stimulus Materials Subjects in this study received a message designed to persuade them to agree to take action. All the subjects were undergraduate business students, and a message was selected that all would find relevant. The goal of the presentation was to persuade subjects to agree to pledge a future donation to the university's business school. A persuasive message - - "Fifty for the Future" - - explained why alumni should make financial contributions to their alma mater. The thrust of the message was to convey that a contribution to the business school was an investment in the reputation of the school and therefore an investment to enhance the quality of the school's degree. Because students are often without discretionary funds, any appeal for immediate donations could prejudice the results. Consequently, the message focused upon financial rewards that their degree would offer them once they obtained their first job and encouraged them to "enhance the quality of your degree by investing $50 in the Business School now and make that investment within six months after starting your first job." See Appendix A for the complete text of the stimulus message. The independent variable in this study was the communication mode in which the persuasive appeal was presented. Subjects in the first treatment received the explanation of why they should make a donation in text form only, that is, the persuasive appeal was presented to the subjects in print form on standard plain white paper. Individuals in the second treatment level viewed a presentation in which the identical text received by the first group was projected on a screen via static (still) graphics. This presentation was created on a personal computer using IBM's Storyboard, a color graphics software package. Subjects in the third treatment level viewed a presentation of the same text seen by the other two groups. The order and content of the graphics in this treatment were the same as those viewed by the second group. However, this text was presented using dynamic (moving) graphics, the chief difference being that only this third treatment level fully used the capabilities of computer generated graphics. This presentation was designed to represent a prototype of presentations commonly created with current graphics softwares and included such effects as screen implosion and explosion; screen fade-in and fade-out; wipe left and wipe right; scroll-up and scroll-down; scroll-left and scroll-right; as well as the manipulation and change of color and font size and the moving of graphs, other figures, and information around the screen to create visual appeal to the message. Presentations in both
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the second and third treatment levels were projected onto a 60-inch × 60-inch screen using rear-screen projection. Measurement Instrument
Subjects in all treatment conditions received the same instntment to measure two dependent variables and two covariate variables. All four variables were measured using seven-point Likert-type scales. See Table 1 for means and standard deviations for these variables. The first dependent variable (Inclined) was the degree of change in the subjects' inclination to make a donation: "As a result of this information, I am more inclined to donate to the business school." The second dependent variable (Pledge) was a more specific agreement to make a pledge to be fulfilled within a specific time limit: "I would be willing to pledge financial support to the business school within six months after starting my first job." The two covariates were included to control for the subjects' predispositions to make contributions to the business school as an alumni. The first covariate (Should) measured how strongly a subject believed that alumni should donate ("I believe that alumni should make donations to the business school"). The second covariate (Reputation) tapped the degree to which subjects believed that improvement in the business school's reputation influences the value of the degrees of alumni ("I believe that even after I graduate, maintaining a strong business school with a good reputation will increase the value of my degree"). Procedure
Although subjects responded to the stimulus independently, they received the stimulus materials in groups whose size ranged from 18 to 48. The text-only treatment was administered to 37 subjects; the static graphic presentation to 73 subjects; and the dynamic graphic presentation to 69 subjects. All subjects in the same section were assigned to the same treatment group. Sections were randomly assigned to the treatments. The composition of subjects in the three treatment groups were not significantly different in terms of age, gender, or major.
Table 1. Cell Means and Standard Deviations
Presentation Method
Variable
Mean
SD
Text-Only
Inclined Pledge Should Reputation
3.97 3.86 4.83 5.28
1.52 1.57 1.21 1.11
Static Graphics
Inclined Pledge Should Reputation
4.27 4.43 5.10 5.49
1.15 1.34 0.90 1.09
Dynamic Graphics
inclined Pledge Should Reputation
4.51 4.26 5.17 5.49
1.21 1.16 1.01 1.01
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All subjects were told that the research in which they were participating concerned how individuals make choices and that the experimenters had no vested interest in the chosen topic. After this introduction, the text-only group was given the pages on which the persuasive message was printed and the questionnaire that measured the dependent variables and covariates. After the same introduction described above, the two graphics groups were shown their respective presentations. The same questionnaire was distributed immediately following the presentation. The persuasive messages were self-explanatory and instructions for completing the questionnaire were included in the questionnaire. Consequently, no further instructions were provided to any treatlnent group.
RESULTS
A one-way analysis of covariance (ANACOVA) was used to test H1A and H1B. Belief that alumni should donate ("should") and belief that a strong reputation will affect the value of degrees of alumni ("reputation") were used as covariates. Table 2 shows the results of this test. As Table 2 indicates, both covariates have a significant effect. As a result, their inclusion helps to clarify the source of the variance. The test of the dependent variable "inclined" that measured a subject's inclination to make a donation to the business school showed that the choice of presentation method was significant at the .05 level. A Duncan's Multiple Range Test was performed as a follow-up analysis to locate the differences among group means Table 2. Results of Analysis of Covarlance (ANACOVA) and Duncan's Test for =Inclined" and "Pledge" Source
clf
MS
F
p
Inclined Presentation Method Should Reputation Model Error
2 1 1 4 172
3.43 60.71 7.78 18.84 1.20
2.86 50.65 6.49 15.72
.05 .0001 .01 .0001
Pledge Presentation Method Should Reputation Model Error
2 1 1 4 172
2.71 110.05 18.45 33.48 1.02
2.66 108.30 18.16 32.95
.07 .0001 .0001 .0001
Presentation Method
Mean
Duncan's Testa
Inclined Dynamic Graphics Static Graphics Text-Only
4.51 4.27 3.97
A A
Pledge Static Graphics Dynamic Graphics Text-Only
4.43 4.26 3.86
A A
B B
B
aMeans having the same letter are not significantly different at the .05 level.
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(Table 2). The mean for the dynamic graphics treatment was significantly different from the mean for the text-only treatment. This result partially confirms H1B. However, the mean for the static graphics group was not significantly different from either of the other cell means. Therefore, H 1A was not confLrmed. H2A and H2B were tested using identical analyses for the dependent variable "pledge" (Table 2). The overall results of the analysis of covariance were only marginally significant. However, the follow-up Duncan's test did identify the text treatment mean as significantly lower than the means for the static graphics and dynamic graphics treatments. This result supports H2A. As with H1B, H2B was only partially supported. The data indicate that subjects exposed to the dynamic graphics treatment were more likely to pledge to donate than were those exposed to the text-only treatment; however, the analysis revealed no significant differences between the willingness to pledge for those subjects exposed to the dynamic graphics treatment versus those exposed to the static graphics treatment.
DISCUSSION
Earlier research (Chaiken & Eagly, 1976; Shelby, 1986) has noted that oral and visual channels are generally more persuasive for simple messages while written channels are more persuasive for more complex messages. These findings may have been adequate to describe an environment in which only written, oral, or videotaped messages were available as channels for persuasive messages. Today, however, the widespread use of computer-generated graphics in organizational settings offers an additional communication mode for the transmission of persuasive messages. As the results of this study indicate, graphics can be effective both in creating what the persuasion literature calls persuasive effect and in influencing people to change their attitudes and their behavioral intentions as a result of this persuasive effect. Subjects who viewed the dynamics graphics presentation were more inclined to donate money as a result of viewing the presentation than were those who received the text-only treatment. Furthermore, subjects in both the static and dynamic treatment groups indicated a greater willingness to commit themselves to pledging money to the business school than did subjects in the textonly treatment. Several conclusions can be drawn from these results. First, text-only and graphics treatments differ in that the former involves a single mode of communication (written) while the latter involves the coupling of several modes: a traditional written message is coupled with graphs, charts, figures, and animation, i.e., the addition of visual appeal to the message. One explanation for the greater persuasive appeal of graphical presentations versus written text alone is that the graphical presentations were better able to gain and maintain the subject's attention. As Shelby (1986) pointed out, the first steps associated with implementing persuasive strategies involve getting subjects' attention and stimulating interest. Similarly, Modey and Walker (1987) found that a message's importance, novelty, and plausibility are all necessary conditions for belief change. The stimulus message (alumni donations) in the experimental setting was designed to be both important and plausible to all subjects; however, the familiar format of textual material was certainly less novel than either of the graphics treatments. Arguably, the enhanced persuasive effect may have been generated by increased interest and attention because of the
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uniqueness of the graphical communication mode, i.e., the coupling of the message with color, pictures, diagrams, animation (with the dynamic graphics treatment), and the novelty of viewing a persuasive appeal rather than just reading it. In this setting, the more traditional means of persuading individuals via the written word created less of a persuasive effect than did coupling the written word with capabilities of the newer technologies. In an organizational setting, using computer-generated graphics in persuasive appeals may be more effective in swaying decision makers to a point of view than would the same message transmitted via another communication mode. Because computer presentation graphics is a new and rapidly changing phenomenon, current research into the persuasive effect of this phenomenon is limited and has produced what appears to be contradictory results (DeSanctis, 1984; Jarvenpaa et al., 1985). Further research must identify the conditions under which a greater persuasive effect can be achieved by using computergenerated graphics versus using other more traditional formats. While the present study provides evidence of the persuasive effect of presentation graphics, it leaves unexplored a theoretical explanation for such an effect. At least two interrelated issues arise: theoretically accounting for these results from a persuasion theory perspective and assessing the persuasive effect's permanence upon attitude change. One explanation (Buller, 1986) suggests that presentation graphics, if viewed as irrelevant to the message itself, may well serve as a distracter that can reduce attitude change, not enhance it. As Buller (1986) has noted, "communication irrelevant distraction generally reduces the efficacy of a persuasive message" (p. 109). Thus, though the graphics may be novel and though they may hold the viewer's attention, they may be ineffective in producing the desired persuasive effect if viewed by the subjects as irrelevant to the message. In such a case, the communication mode itself becomes the message; the persuasive effect that is intended by the communication is not achieved; the validity of any measure of persuasive effect is called into question; and any reported attitude change will most likely be short-lived. On the other hand, presentation graphics classified as a relevant distraction can enhance the efficacy of a persuasive appeal (Buller, 1986). Focusing on presentation graphics either as a communication relevant or as a communication irrelevant distraction is an important line of inquiry to assess the true persuasive effect of presentation graphics and to be able to offer practical guidelines concerning how to ensure the communication relevance of a graphicsbased communication. A different perspective to explain graphics' persuasive effect suggests that graphics may well serve as a form of persuasive evidence, thus enhancing persuasive effect and effecting true attitude change (Reinard, 1988). If left to draw their own conclusions from the graphics, viewers become cognitively involved in the process and therefore more committed to the attitude change (see Perloff & Brock, 1980.) In this case, involving the viewer is a critical variable affecting the creation of persuasive effect. Which of these two (or other) explanations adequately explains the persuasive effect of presentation graphics remains unexplored and points to the need for both behavioral and communication researchers skilled in studying persuasion and attitude change to enter this research arena. Because of the persuasive potential available to users of graphics, this communication mode should no longer be viewed merely as a support tool in a decision support environment but as an important tool for the organization to communicate to its diverse constituency. The associated research agenda will be demanding. Unraveling the intricacies of human information processing is difficult enough
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when researchers are studying only the effectiveness of decision support tools; adding human behavior and choice variables, typically associated with the persuasion process, increases the complexity of the research. However, as Huseman and Miles (1988) have noted, the transformation of the computer age into the information age ensures that "organizations that effectively gather, monitor, and filter information will increasingly have a competitive edge" (p. 181). Further investigation of the persuasive effect of computer graphics is necessary to tap graphics' potential in this information age.
REFERENCES Bostrom, R. P., Olfman, L., & Sein, M. K. (1990). The importance of learning style in end-user training. MIS Quarterly, 14, 100-119. Buller, D. B. (1986). Distraction during persuasive communication: A meta-analytic review. Communication Monographs, 53, 91-114. Chaiken, S. & Eagly, A. H. (1976). Communication modality as a determinant of message persuasiveness and message comprehensibility. Journal of Personality and Social Psychology, 34, 605-614. DeSanctis, G. (1984). Computer graphics as decision aids: Directions for research. Decision Sciences, 15, 463---487. Dickson, G. W., DeSanctis,G,. & McBride, D. J. (1986). Understanding the effectivenessof computer graphics for decision support: A cumulative experimental approach. Communications of the ACM, 29, 40--47. Greist,J. H., Klein, M. H., & Erdman, H. P. (1976). Routine on-linepsychiatricdiagnosisby computer.American Journal of Psychiatry, 12, 1405-1408. Greist, J. H., Klein, M. H., & Van Cura,. L. J. (1973). A computer interview by psychiatric patient target symptoms. Archives of General Psychiatry, 29, 247-253. Hart, R. (1986). Add impact with graphics. Administrative Management, 47(7), 38-43. Hiltz, S. R., Johnson, K., Aronovitch, C., & Turoff, M. (1980). Face-w-face vs. computerized conferences: A controlled experiment: Vol. 1. Findings (Research Report No. 12). Newark: New Jersey Institute of Technology. Huseman, R. C., & Miles, E. W. (1988). Organizational communication in the information age: Implications of computer-based systems. Journal of Management, 14, 181-204. Ires, B. (1982). Graphical user interfaces for business information systems. MIS Quarterly, 6, 15-47. Jarvenpaa, S. L., Dickson, G. W. & DeSanctis, G. (1985). Methodological issues in experimental IS research: Experiences and recommendations. MIS Quarterly, 9, 141-156. Joshi, K. (1989). The measurement of fairness or equity perceptions of management information systems users. MIS Quarterly, 13, 342-358. Kiesler, S., Zubrow, D., Moses, A. M., & Geller, V. (1983). Affect in computer-mediated communication. Unpublished manuscript, Carnegie-Mellon University, Pittsburgh, PA. Lee, J. M., MacLachian, J., & Wallace, W. A. (1986). The effects of 3D imagery on managerial data interpretation. MIS Quarterly, 10, 257-269. Lehman, J. A. (1986). Business graphics: A taxonomy for information systems managers. Data Base, 18, 24-31. Morley, D. D., & Walker, K. B. (1987). The role of importance, novelty, and plausibility in producing belief change. Communication Monographs, 54, 436-442. Pedoff, R. M., & Brock, T. C. (1980)...."And thinking makes it so": Cognitive responses and persuasion. In M. E. Roloff & G. R. Miller (F_xts.), Persuasion: New directions in theory and research (pp. 67-100). Beverly Hills, CA: Sage. Petty, R. E., Ostrom, T. M., & Brock, T. C. (1981). Historical foundations of the cognitive response approach to attitudes and persuasion. In R. E. Petty, T. M. Ostrom, & T. C. Brock (Eds.), Cognitive Responses to Persuasion, (pp. 9-14). Hillsdale, NJ: Lawrence Erlbaum Associates. Reinard, J. C. (1988). The empirical study of the persuasive effects of evidence: The status after fifty years of research. Human Communication Research, 15, 3-59. Shelby, A. N. (1986). The theoretical bases of persuasion: A critical introduction. The Journal of Business Communication, 23, 5-29.
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Siegel, J., Dubrovsky, V., Kiesler, S., & McGuire, T. W. (1986). Group processes in computer-mediated communication. Organizational Behavior and Human Decision Processes, 37, 157-187. Vogel, D. R., Dickson, G. W., & Lehman, J. A. (1986). Persuasion and the role of visual presentation support: The UM/3M study (Working Paper No. MISRC-WP-86-11). Minneapolis: University of Minnesota, Management Information Systems Research Center. Weill, P., & Olson, M. H. (1989). Managing investment in information technology: Mini case exampies and implications. MIS Quarterly, 13, 2-17.
APPENDIX A. FIFTY FOR THE FUTURE
One of the principles you learn in the Business School is that the quality of your investment substantially affects your future financial health. When looking for that first job, you put this principle to work: --You spend $50 plus for a good looking resume; --You spend more than $50 for an expensive pair of shoes; and --You spend $50 or more on long distance phone calls to set up interviews and to talk with important people in the organization. You make these investments because you are convinced they make a difference, because they are wise investments in your future, and because you believe that the degree you have earned from the College of Business is a high quality degree that warrants these investments. Just as you know that you must make quality investments in resumes, shoes, and phone calls to promote your search for a job, you know that someone must invest in the College of Business to maintain the quality of the degree you are presently earning. Consider these statistics. The College of Business graduates about 900 students each year. If each of these 900 alumni invested just $50 to improve the quality of their degrees, the Business School would receive an additional $45,000 annually. How can this money enhance the quality of your degree? - - B y recruiting renowned professors as faculty members; - - B y attracting brighter and brighter students with increased scholarship funds; - - B y recruiting distinguished practitioners and lecturers to bring the everyday world of business into the classroom; - - B y rewarding professors who go that extra mile in classroom teaching. The 1986 average starting salary for a University of Georgia business major exceeded $20,000. An investment of $50 is less than 1/4% of that salary. That's about four large pizzas, not including soft drinks or extra toppings. For your $50 investment, you give the Business School the resources to provide you with higher quality teaching. For your $50 investment, you help yourself now and in the future by enhancing the reputation of the Business School... your Business School. For your $50 investment, you increase the worth of your degree even after you have graduated by ensuring that employers will continue to take note of a business degree from the University of Georgia's College of Business.
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Don't go to that first interview or any interview in the future with only a good looking resume, expensive shoes, and a large phone bill. Pay for your resume, pay for your shoes, and pay your phone bill. But pay for your future too. Enhance the quality of your degree by investing $50 in the Business School now and make that investment within six months after starting your first job.