I found this article very interesting in regards to our privacy and how we deal with privacy issues. It is interesting how personality traits tie into the discussion. Here is the url to the original article.

The Influence of Personality Traits and Information Privacy Concerns on Behavioral Intentions

Posted on: Tuesday, 9 September 2008, 03:00 CDT

By Korzaan, Melinda L Boswell, Katherine T

ABSTRACT This study incorporates the Big Five personality traits into a theoretical model that explains and predicts individuals concerns for information privacy, computer anxiety, and individual behavioral intentions. Data was gathered via a survey, which was completed by 230 undergraduate college students, and analysis was conducted utilizing structural equation modeling. Agreeableness was found to have a significant influence on individual concerns for information privacy while neuroticism was found to have a significant influence on computer anxiety. In addition, intellect exerted a significant influence on both computer anxiety and behavioral intentions. Key insights for theory and practice are presented.

Keywords: information privacy, ethical issues, behavioral intentions, personality traits\

INTRODUCTION

Businesses are increasingly dependent upon technology to enhance their on-going operations as well as to recognize and capitalize on potential opportunities. However, concerns have arisen regarding some of the applications for which this technology is being utilized. For the last couple of decades, especially in the aftermath of 9/11, privacy issues have been in the forefront of individuals' concerns. Various privacy acts have been passed to help protect individual's personal information and privacy policies have become an accepted practice in most industries. The shift toward e- commerce has acerbated the concern over information privacy and has spawned a greater awareness by the public of the potential risks that are associated with unsafe information practices. Awareness is increasing regarding the risk associated with providing personal data using technology. These risks range from phishing scams to identity theft. All in all, society is becoming more hesitant about providing complete and accurate personal data.

A CBS news report [22] , states that 2/3 of Americans dunk the US government should be doing more to regulate the collection of personal information. This report goes on to say that 52% of the respondents believe their privacy rights are in serious jeopardy and 30% believe privacy rights are already non-existent. In addition, the report states that even after explaining why businesses collect personal information (both positive and negative), 83% of individuals surveyed still had an overall negative reaction to such business practices. Other reports have stated that consumers are becoming more diligent about protecting their own privacy by using privacy tools available and withholding more sensitive information [23], [I]. According to Hoffman et al [15], 95% of their sample stated that they withheld information requested by websites at least once. The growing concern society has on privacy invasion could severely hinder the advantageous uses of data collection.

Because of the attention privacy issues are getting in today's society, privacy concerns are increasingly a major focal point for both researchers and practitioners. According to a recent study revisiting Mason's framework of the four ethical issues in the information age, privacy was found to be the most important ethical factor facing individuals today [21]. The alleviation or at least the reduction of these privacy concerns is of primary importance. Much of the research to date on privacy concerns focuses on attempting to identify different types of concerns that arise, in order to take steps to address these concerns.

One of the most influential studies on privacy was by Smith et al. [26]. Their research verified that concern for information privacy (CFIP) was a complex construct, with four underlying factors. Stewart and Segars [28] built upon Smith et al.'s research by incorporating the information privacy concern construct into a nomological network and empirically modeled the construct as a mediator between computer anxiety and behavioral intentions. Their study provided insight into the complex nature of privacy issues in society today, and further explained how individuals interpret current business practices. This study attempts to expand upon Stewart and Segars' [28] work by investigating the impact of personality traits on privacy concerns, computer anxiety and behavior intensions. The five factor model of individual personality traits, also referred to as The Big Five, theorized by McCrae and Costa [20] will be incorporated into a theoretical model which will ultimately help explain individuals' behavioral intentions to retaliate against organizational practices of collecting personal information.

The research question under investigation in this study is: what is the role of personality traits in influencing information privacy concerns, computer anxiety, and subsequently behavioral intentions. The contributions of this study include expanding Stewart and Segars' model, improving the predictability of behavioral intentions, and providing a deeper understanding of why individuals may be concerned about privacy, be prone to anxiety, and choose to engage in behaviors related to withholding personal information.

LITERATURE REVIEW AND HYPOTHESES

Concern for Information Privacy

The construct for concern for information privacy (CFTP) was empirically introduced by Smith et al. [26]. Four major categories were identified regarding individuals' concerns in response to organizations' information privacy practices. These categories include: collection, unauthorized secondary use (internal), unauthorized secondary use (external) and errors. Collection encompasses the perception of the quantity of data being captured through organizational practices. Internal unauthorized secondary use describes utilizing collected data for secondary or alternative uses without the proper consent of the individual from whom the data was collected. External unauthorized secondary use is the unauthorized use of the data by a third party, e.g. not the organization that collected the information. Finally, errors focus on the perception that the data will be captured incorrectly or modified to the extent that the data is no longer accurate.

Stewart and Segars [28] empirically examined the CFlP framework and validated the measurement model as a multidimensional construct. In addition, CFIP was found to mediate the relationship between computer anxiety and behavioral intentions in an empirically tested nomilogical network. The current study will extend this model to encompass the big five personality traits in an attempt to explain and predict CFIP and consequently improve the predictability and theoretical understanding of behavioral intentions. This will contribute both to theory and practice by providing a deeper understanding of how individual traits are related to concerns for information privacy, and thereby enabling organizations to better adapt their business decisions to assuage these concerns.

Computer Anxiety

Davis et al. [8] stated that one of the greatest challenges in IS research has been attempting to understand individual's reactions to computers. Discovering the underlying factors that affect resistance to computers has lead to exploring the area of computer anxiety. Computer anxiety is a construct that has been studied extensively in the information systems literature. This construct is defined as the fear about the contemplation of interacting with or the actual interaction with computers. With society becoming so dependent on computer usage, understanding and coping techniques dealing with resistance on interaction with computers has become a driving need. Computer anxiety research focuses on both the physiological responses caused by computer use, such as increased heart rate, as well as the cognitive responses, such as negative feelings or fear.

Studies on this construct have focused on the differences in gender [27] to age and familiarity with computers [14] to whether computer anxiety is a technical or existential issue [29]. This construct has even been utilized as a mediator in models, such as the Social Cognitive Theory, to increase the model's explanatory capabilities [7]. Computer anxiety was utilized in Stewart and Segar's [28] study to help predict behavioral intensions.

The Five-Factor Model of Personality (The Big Five)

Trait Theory is argued to be a successful way to help explain individual differences and has garnered a great deal of attention over the last few decades. Trait Theory contends that by studying traits, you can build an entire personality system. Traits are defined as "dimensions of individual differences in tendencies to show consistent patterns of thoughts, feelings and actions" [18, ? 25]. The more an individual has of a particular trait, the more they exhibit certain types of behavior that are associated with that trait. McCrae et al. [19] theorized and evaluated the Five-Factor Model, which is based in Trait Theory.

The Five-Factor Model (FFM) was a breakthrough in the personality psychology field. This model gave some congruence to the vast number of incongruent theories that had been peppering the discipline up to that point. This model has also been referred to in other research as the Big Five. Although the Five-Factor Personality Trait theory has been researched heavily in behavioral fields, there has been little research on the impact of personality traits with regards to technology issues such as computer anxiety, computer self-efficacy, privacy concerns, acceptance, behavioral intentions or usage.

Extraversion. Extraversion is a personality trait that measures an individual's approach to dealing with their environment. McCrae and Costa [20] used terms such as assured, dominant, gregarious and warm to help describe this construct. Exhibiting leadership characteristics also falls under this trait. Extroversion focuses on any feelings of joy associating with others. Gregarious individuals enjoy large groups and the social aspects of any situation. This trait also describes the inclination to take charge of a given situation, naturally adopting a leadership role, as well as being an independent thinker. Leadership also incorporates a sense of responsibility and guidance of those being led. Given this social outlook, with an inclination toward leadership superimposed, it is hypothesized that an individual that shows high levels of extraversion would be more concerned with information privacy because s/he would wish to protect those around him/her.

H1: Extraversion will have a positive influence on CFIP.

Agreeableness. Agreeableness is defined by McCrae and Costa [20] as being trusting, sympathetic, straightforward and selfless. Agreeableness is categorized by a high degree of trust in others and by others. It also can be described as a high degree of altruism, a strong desire to commiserate and aid others. Finally, a high degree of compliance, or a willingness to defer to others, is observed with this trait.

Information privacy has become an ever-increasing concern globally and its impact is prevalent throughout our laws, our media, our working environment and even our personal environment. Individuals who measure high on agreeableness would not only demonstrate concern for their own information privacy, but be sensitive to and sympathetic with the privacy concerns of others. The unease associated with the possibility of identity theft or other misuse of other's information would be as paramount an issue to someone with high agreeableness as would the risk to his/her own information misuse.

H2: Agreeableness will have a positive influence on CFIP.

Conscientiousness. Conscientiousness is defined using terms such as rational, ordered, and informed. Conscientious individuals tend to deliberate issues, analyzing and eventually determining a course of action or adopting an opinion. They gather whatever information is needed to make these informed decisions.

Given the extensive amount of information on information privacy issues that is available, a conscientious individual would investigate this issue and be very aware of the risks associated with the primary and secondary use of the data collected. Therefore, it is expected that individuals who tend to rank high on conscientiousness will have a greater concern for information privacy because they are cognizant of the potential dangers.

H3: Conscientiousness will have a positive influence on CFIP.

Given that conscientious individuals have a tendency to rely heavily on analyzing the available information in order to draw a conclusion or base a decision, it is expected that they would be aware not only of the potential risks associated with the use of personal data, but the magnitude of the consequences of the misuse of that data. This in turn could cause an increase in the anxiety associated with the use of computers, given their knowledge of viruses and worms, data mining programs and other Spyware, and the loss of control of data once it has been gathered. Therefore, it is predicted that those individuals who have high levels of conscientiousness will display higher levels of computer anxiety.

H4: Conscientiousness will have a positive influence on computer anxiety.

Neuroticism. Neuroticism, by definition [20], encompasses both anger and anxiety. A highly neurotic individual is prone to being anxious, nervous, high strung and tense. Neurotic individuals have a tendency to worry; concerned with everything that could go wrong. Harris and Dollinger [13] studied the relationship between neuroticism and the anxiety about aging and found that there was a positive relationship between them. While there is a difference between anxiety of aging and computer anxiety, it could be argued that anxiety, regardless of what it is over, is based on concern, worry, or fear and causes anxiousness and stress to the individual.

Therefore, it is hypothesized that a high level of neuroticism in an individual would heighten the level of computer anxiety, producing a stronger negative reaction toward computer interaction.

H5: Neuroticism will have a positive influence on computer anxiety.

Intellect. McCrae and Costa [20] defines intellect, also referred to as openness of experiences, as the willingness to experience new things or to consider new or different ideas, as well as to the receptiveness of new ideas. This trait is the antithesis of rigidity of thought or action. Individuals who measure high on this trait tend to be more accepting, less judgmental, have a higher tolerance for, and in many cases embracing, new things. McCrae and Costa go on to describe individuals who rate high on openness as curious and as placing a high value on knowledge.

These individuals would be more prone to view technology as a provider of great advancements, and less likely to be mired in the detrimental outcomes of any misuse. They would tend to be more accepting of technology. Therefore, it is expected that the higher an individual measures on this trait, the less computer anxiety the individual would experience.

H6: Intellect will have a negative influence on computer anxiety.

The concern for information privacy construct focuses on the fear of misuse or incorrect collection of data. Computer anxiety focuses on the fear of interaction with computers. Due to the inherent distrust of the technology by those who have a high computer anxiety, it is expected that this would impact the concern for any privacy infringement. This relationship was tested by Stewart and Segars [28] and was supported strongly.

H7: Computer anxiety will have a positive influence on CFIP.

Behavioral Intentions

The theory that concern for information privacy would have a mediating effect between computer anxiety and behavioral intentions was introduced by Smith et al [26] and was supported by Stewart and Segars [28]. This study proposes that this relationship will hold true, given a different sampling group.

H8: The relationship between computer anxiety and behavioral intentions will be fully mediated by concerns for information privacy .

Individuals who rate high on the intellect personality trait are curious by nature and place a strong emphasis on knowledge. One would expect that these individuals would be more likely to be aware of the risks involved with the improper handling or use of personal information, and accordingly, take active steps, such as removing themselves from mailing lists or refusing to disclose personal information in order to protect their privacy. Therefore it is hypothesized that there is a positive relationship between intellect and behavioral intentions.

H9: Intellect will have a positive influence on behavioral intentions.

As noted by Stewart and Segars [28], concerns for information privacy influences behavioral intentions. They argued that an individual who exhibited high levels of CFIP would take proactive steps to reduce the likelihood of having their privacy invaded, such as removing themselves from mailing lists, not providing personal information online, etc. This study intends to test that assumption using a different test group to determine the robustness of their findings.

H10: CFIP will have a positive influence on behavioral intentions.

METHOD

Consistent with prior research in the domain of information privacy [26]. [28], a survey instrument was utilized to collect data from participants. The measurement items for the survey were developed by adapting existing measures from prior research. Both computer anxiety and behavioral intentions were adapted from Stewart and Segars [28], and concern for information privacy was adapted from Smith et al. [26]. Measures for the big five personality traits were based on the International Personality Item Pool [11], [12], [16] which is a collaborative endeavor undertaken by researchers to provide personality measures for the public domain. The survey instrument is provided in Appendix A. The survey was administered online to undergraduate college students enrolled in an introductory level computer course. Participants were granted extra-credit points for completing the survey. Students were assured diat tiieir responses would be kept confidential and were told that survey results would only be reported in die aggregate. The number of usable surveys completed was 230, widi 61% male and 39% female respondents. The majority of the students 99% were between 18 and 24 years of age.

Figure 1: Personality and Privacy, Proposed Model

The two-step modeling approach [2] was utilized in diis study. The first stage of diis two-step process is to conduct a confirmatory factor analysis in order to determine if the factor model is valid. This step establishes the measurement model and confirms both convergent and discriminant validity. The second step is a test of die hypothesized causal relationships, which establishes die structural model. The structural model was assessed by conducting a patii analysis using the Amos version 5 structural equation modeling software package [17]. The following section details die validity and reliability of the construct measures as well as die analysis of die structural model. RESULTS

Evidence of construct validity and reliability are detailed in Appendices B and C. The average variance extracted for each construct meets or exceeds die .50 threshold value for convergent validity [10]. In addition, composite reliabilities for each construct demonstrate excellent internal consistency with all measures exceeding die .70 tiireshold [4] (see Appendix B). The square root of die average variance extracted for each construct is greater dian the correlations between each pair of corresponding constructs, which indicates good discriminate validity [10], [4] (see Appendix C). According to Stewart and Segare [28], CFIP is more accurately modeled as a second-order factor rather than four correlated first-order factors. Therefore, this study modeled CFIP as a second-order construct. All path values for CFIP were significant (p<.001), consistent with theory, and comparable to values found by Stewart and Segars [28] (ranging from .67 to .87). Therefore, empirical validity for modeling CFIP as a second-order factor was verified and consistent with prior research [28].

Results of the hypothesis testing are summarized in Table 1. Hypotheses Hl, H3, H4, H7, and H8 were not supported. Neither extraversion (beta=.04, p=.595) nor conscientiousness (beta=. 13, p=.086) was found to have a significant influence on CFIP. Furthermore, the relationship between conscientiousness and computer anxiety was not significant (beta=.05, p=.447). Contrary to Stewart and Segars' [28] findings, the relationship between computer anxiety and CFBP was not significant (beta=-.07, p=.315) in this study. Therefore, the influence of computer anxiety on behavioral intentions was not mediated through CFIP [3]. Hypotheses H2, H5, H6, H9, and H10 were supported. Agreeableness was found to have a significant influence on CFTP (beta=.17, p=.027). The amount of variance explained in CFIP was seven percent. Both neuroticism and intellect exerted a significant influence on computer anxiety. Neuroticism had a very strong positive affect on computer anxiety (beta=.35, p < .001) while intellect had a significant negative affect on computer anxiety (beta=-.16, p = .012). The amount of variance explained in computer anxiety was fifteen percent. Intellect (beta= .16, p = .013), computer anxiety (beta=.15, p = .019), and concern for information privacy (beta=.34, p < .001) all had significant, positive affects on behavioral intentions. The total amount of variance explained in behavioral intentions was sixteen percent.

Table 1: Hypothesis Testing Results

DISCUSSION

This study extends the Stewart and Segars' [28] research to try to explain more deeply concern for information privacy by looking at personality traits that might impact these concerns. The results show that some of the hypothesized relationships were exhibited while others were not.

Hypothesis 1 stated that extroversion would have a negative influence on concerns for information privacy. This hypothesis was not supported. One reason could be due to the fact that the extraversion domain is made up of many facets and due to the focus of this study, some facets of the extraversion trait were emphasized more heavily than others. One facet of extraversion that was not studied as fully is a driving desire for excitement. This introduces a possible risk-seeking attitude that would be in opposition to a traditional leadership role as defined earlier. This risk-seeking factor could be a predominant reason why a lack of conclusions can be drawn with this personality trait. The impact of this personality trait on CFIP should be studied in more depth in future research to garner a better understanding of any potential impact on CFIP.

Hypotheses 3 and 4 dealt with the personality trait of conscientious. It was hypothesized that conscientious would have a positive influence on both CFIP and computer anxiety. Neither of these hypotheses was supported. For Hypothesis 3, this is an interesting finding and suggests that perhaps in their information gathering process, the individuals' concerns were reduced by the preventative measures being taken by many companies to protect individuals' privacy.

The finding for Hypothesis 4 was not unexpected, however, as Harris and Dollinger [13] found that conscientiousness had a negative relationship with the anxiety of aging. Therefore, given that all types of anxieties stem from the same underlying emotions, a strong opposite relationship would have been surprising. This result indicates that the conscientiousness trait might have a negative relationship with anxiety in general, regardless of the trigger of the anxiety.

Figure 2: Personality and Privacy, Final Model

Hypotheses 7 and 8 dealt with the impact of computer anxiety on CFIP and the mediation of CFIP between computer anxiety and behavioral intensions. Both of these hypotheses were supported in Stewart and Segars' [28] research. However, neither was supported in this study. A reason behind this could be the different samples used in the studies. Stewart and Segars [28] used a sample of customers from several geographical areas in the United States. This study used college students from one geographical location in the US. The limited sample diversity in this study could account for the difference in the findings. Using a homogenous, more educated group of participants could skew the results compared to a more diverse sample that is more representative of society in general.

The other hypotheses were supported and reaffirm the belief that personality traits have explanatory value for computer anxiety and CFIP and should be looked at in more depth.

The current study is beneficial from both theoretical and practical standpoints. The dieoretical contributions of this study have been to extend Stewart and Segars' [28] nomological network to incorporate personality theory, as well as to improve the predictability of both CFIP and behavioral intensions. It extends theoretical knowledge of factors affecting computer anxiety and concern for information privacy, as well as provides new avenues for future research in this area.

The business environment also can apply the findings of this study in several ways. In general, this study provides some linkages between personality types of individuals and their behavioral intentions, which can be viewed as predominant societal traits or more specifically as personality traits of target groups. Either way, this would give some information that could be used to help utilize methods to shift behavioral intentions by reducing anxiety or concerns for information privacy.

For instance, understanding the behavior traits of their customers would help a company in building a relationship between itself and its customers by demonstrating their awareness of these concerns. One of the greatest opportunities organizations have in reaching individuals is providing a formal privacy policy. It has been found that a clear privacy statement exerts a positive influence on online sales [24]; therefore, companies could make tiieir privacy policy more effective by restructuring it to address the issues of each personality type. For example, they may want to appeal to the intellectual aspect of individuals when choosing the wording and details of dieir privacy policy. Individuals may be more sensitive to deficient policy statements that do not fully address the fair information practice principles as set forth by the federal government. Unfortunately, it has been determined that a significant number of websites do not provide privacy policies that adequately address all of these fair information practice principles [25], [18]. Organizations that conduct business online should see this gap in privacy policy practice as a great opportunity to alleviate concerns by developing or enhancing their privacy policy statement to address all major areas of privacy concerns. In addition, companies may want to build trust through public relations and clearly communicate dieir adherence to fair information practice principles.

A company may want to also train support staff to deal with certain behavioral traits, understanding that the majority of their interaction with customers would probably be from individuals that measure high on neuroticism.

An organization could reduce fear, anxiety, and frustration by increasing the ease of use of any interface to enhance readability, by prominently displaying contact information or including a real- time chat tool. Enhanced web support is also an option to reduce frustration of their customers. Companies could incorporate a short online tutorial on how to navigate their site. Finally, the organization might maintain a consistent interface design to reduce the necessity of the customers to have to adapt continuously to major changes. There are many ways to incorporate behavioral trait information and its impact on privacy concerns and behavior intensions into organizational practices.

LIMITATIONS AND FUTURE RESEARCH

One of the limitations of this study is the selected sample of undergraduate college students. The results cannot be generalized beyond the college student population. However, college students do comprise a significant market segment of interest to many organizations that sell products targeting the college student population. Future studies should utilize samples from other populations to examine how well the model will generalize. Another limitation of the study is the focus on behavioral intentions. It would be of interest for future studies to investigate longitudinally the actual behaviors taken by individuals. Identifying additional antecedents to CFIP, computer anxiety, and behavioral intentions is also recommended for future research in order to expand the existing model and increase the amount of variance explained in these dependent variables. In addition, it would be beneficial to investigate the role of personality traits and concerns for information privacy in the context of electronic commerce. Prior research has established that privacy concerns play a significant role in influencing individuals' intentions to complete online transactions [9]. Incorporating personality traits into Dine and Hart's [9] model is recommended for extending knowledge in the domain of electronic commerce and aid in predicting online shopping behaviors. Furthermore, it would be beneficial for future research to not only shift to the context of electronic commerce, but it would also be of interest to include other constructs in the model. Trust would be one such construct to consider. Trust has already been established as an important factor in electronic shopping and prior studies have shown e-merchant ability and integrity to influence trust in an online shopping environment [6]. It would be interesting to see if trust possibly moderates or mediates the relationships between the Big Five personality traits and concerns for information privacy, computer anxiety, and/or behavioral intentions. CONCLUSION

As a growing concern for information privacy is a focal area in today's business environment, a better understanding of issues relating to this concern can only aid in good preventative measures being utilized to protect information privacy. This study looked at behavioral traits of individuals to aid in this deeper understanding of individuals and the choices they make as they relate to information privacy. The more accurate and complete the data being collected, the better decision making mat can be made, which will enhance the effectiveness of the businesses utilizing that information. Therefore, appropriate measures should be taken to protect information privacy, thereby alleviating as much of the concern individuals have on this issue so this more reliable data can be gathered and utilized.

REFERENCES

[1] "An Intimate Invasion," USA Weekend Magazine, 2000, http:// www.usaweekend.com/00_issues/000702/000702privacy. html

[2] Anderson, J. C, and Gerbing, D. W., "Structural Equation Modeling in Practice: A Review and Recommended TwoStep Approach," Psychological Bulletin (103:3), 1988, 411423

[3] Baron, R. M., and Kenny, D. A. "The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations," Journal of Personality and Social Psychology, (51:6), 1986, 1173-1182

[4] Bock, G., Zmud, R. W., Kim, Y., and Lee, J. "Behavioral Intention Formation in Knowledge Sharing: Examining the Roles of Extrinsic Motivators, Social-Psychological Forces, and Organizational Climate," MIS Quarterly, (29:1), 2005, 87-111

[5] Chin, W. W. "The Partial Least Squares Approach to Structural Equation Modeling," in Modern Methods for Business Research, G. A. Marcoulides (Ed.), Lawrence Erlbaum Associates, Mahway, NJ, 1998, 295-336.

[6] Chow, Wing S. and O, Angie N.K. "A study of trust in eshopping before and after first-hand experience is gained," Journal of Computer Information Systems. (46:4), 2006, 125-130.

[7] Compeau, Deborah R.; Higgins, Christopher A.; and Huff, Sid. ,"Social cognitive theory and individual reactions to computing technology: A longitudinal study," MIS Quarterly (23:2), 1999, 145- 158.

[8] Davis, Fred D.; Bagozzi, Richard P. and Warshaw, Paul R. "User acceptance of computer technology: A comparison of two theoretical models," Management Science (35:8), 1989, 982-1003.

[9] Dinev, T. and Hart, P. "Internet Privacy Concerns and Their Antecedents - Measurement Validity anda Regression Model". Behaviour & Information Technology. (23:6), 2004, 413-422.

[10] Fornell, C. and Larcker, D. F., "Evaluating Structural Equation Models with Unobservable Variables and Measurement Error" Journal of Marketing Research (18: 1), 1981, 39-50

[11] Goldberg, L.R. "A Broad-Bandwidth, Public Domain, Personality Inventory Measuring the Lower-Level Facets of Several Five-Factor Models," In I. Mervielde, I. Deary, F. DeFruyt, and F. Ostendorf (Eds.), Personality Psychology In Europe, Vol 7, Tilberg University Press, Tilberg, The Netherlands, 1999, 7-28

[12] Goldberg, L.R., Johnson, J.A., Eber, H.W., Hogan, R., Ashton, M.C., Cloninger, CR., and Gough, HC, "The International Personality Item Pool and the Future of Public Domain Personality Measures," Journal of Research in Personality (40), 2006, 84-96

[13] Harris, L. A and Dollinger, S.M. C. "Individual Differences in Personality Traits and Anxiety About Aging". Personality and Individual Differences. (34:2), 2003, 187-194.

[14] Harrison, Allison W. and Rainer, Kelly Jr. "The influence of individual differences on skill in end-user computing," Journal of Management Information Systems (9:1), 1992, 93-111.

[15] Hoffman, D. L., Novak, T. P., & Peralta, M. "Building consumer trust online," Communications of the ACM, (42:4), 1999,80- 85.

[16] International Personality Item Pool: A Scientific Collaboratory for the Development of Advanced Measures of Personality Traits and Other Individual Differences (http:// ipip.ori.org/) Internet Web Site.

[17] Kline, R. B. Principles and Practice of Structural Equation Modeling, The Guilford press, New York, 1998

[18] Liu, C. and Amett, K.P. "Raising a red flag on global www privacy policies," Journal of Computer Information Systems. (43:1), 2002, 117-127.

[19] McCrae, R. R.; Costa, P. T. and Busch, C. M. "Evaluating Comprehensiveness in Personality Systems: The California Q-Set and the Five-Factor Model," Journal of Personality (54:2) ,1986, 430- 446.

[20] McCrae, R. R. and Costa, P. T. Personality in Adulthood 2nd ed.. The Guilford Press, New York, NY, 2003.

[21] Peslak, Alan R. "PAPA revisited: A current empirical study of the Mason framework," Journal of Computer Information Systems. (46:3), 2006, 117-123.

[22] "Poll: Privacy Rights under attack." CBS News, 2005, http:// www.cbsnews.com/stories/2005/09/30/opinion/polls/ main894733.shtml

[23] Privacy and American Business (P&AB). Quarterly Public Opinion Surveys Report. July 2001. Quarterly Report for P&AB' s CPO 2001 Program. Commissioned by the Markle Foundation., 2001, www.markle.org/news/_news_ pressreport_index.stm

[24] Ranganathan, C and Grandon, E. "An exploratory examination of factors affecting online sales," Journal of Computer Information Systems. (42:3), 2002, 87-93.

[25] Ryker, R., Lafleur, E., McManis, B., Cox, K. C. "Online privacy policies: An assessment of the fortune E-50," Journal of Computer Information Systems. (42:4), 2002, 15-20.

[26] Smith, H. J.; Milberg, S. J.; Burke, S. J. "Information Privacy: Measuring Individuals' Concerns About Organizational Practices," MIS Quarterly (20:2), 1996, 167-196.

[27] Stemberger, Carol Sue "An examination of state anxiety and computer attitudes related to achievement on paper-andpencil and computer-based mathematics testing of nursing students," An unpublished doctoral dissertation. Purdue University, 1999.

[28] Stewart, K.A. and Segars, A.H. "An Empirical Examination of the Concern for Information Privacy Instrument." Information Systems Research (12:1), 2002, 36-49.

[29] Worthington, Valerie and Zhao, Yong (1999). "Existential computer anxiety and changes in computer technology: What past research on computer anxiety has missed. Journal of Educational Computing Research (20:4), 1999, 299315.

MELINDA L. KORZAAN

Middle Tennessee State University

Murfreesboro, TN 37132

KATHERINE T. BOSWELL

Middle Tennessee State University

Murfreesboro, TN 37132

Appendix A: Measurement Scales

Appendix A: Measurement Scales

Appendix B: Composite Reliabilities and Variance Extracted

Appendix C: Discriminant Validity

Copyright International Association for Computer Information Systems Summer 2008

(c) 2008 Journal of Computer Information Systems, The. Provided by ProQuest LLC. All rights Reserved.

Source: Journal of Computer Information Systems, The

If you found this article interesting you may want to check back for more articles regarding your privacy rights.