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Effect of Personality on VirtualCommunications In Warfare
HARRY I. NIMON AND GEORGE J. GRAHAM
Individuals and corporations worldwide are increasing utilization of computer-
mediated-communications (CMC) systems and processes. Such endeavors are shortening lines
of communications, yet simultaneously distancing understanding. Winston Churchill once
opined that the British and American peoples are two great peoples separated by a common
language. Some relate aspects of culture as the source ofChurchills quote. Separating factors
may be more engrained than previously believed or theorized.
The authors examined a high-stress setting determined to be one where the trappings
of culture disappear leaving only the basic emotional and cognitive survival aspects of
personality; the environment of military combat. Observing the results of the studys individual-
environment relations raises the question of whether personality is a factor in virtual team
efficiency. The study examined the relationship of an individuals ability to function efficientlyutilizing virtual communications and processes while under extreme stress. This article is a
summarization of the findings from that study.
The world is experiencing a revolution in the availability and use of information,
specifically concerning the utilization of internet and computer-mediated
communications (CMC) (Wagner, 2002). Researchers such as Kerr and Tindale (2004)
and Wagner (2002) discussed the growing tendency within organizations to utilize CMC
and virtual communications in the creation and processes of work teams, which they
called virtual teams. Organizations link individuals of varied cultures and nationalities in
virtual teams to perform tasks once limited to collocated groups (Gupta & Govindarajan,
2004; Kring, 2004).
Kerr and Tindale (2004) reviewed studies conducted since 1992, examining the
question of whether electronic groupswhere inter-member communication is managed
electronically rather than in face-to-face interactionmight have certain performance
advantages (p. 626). Kerr and Tindales research, supported by the work by Wagner
(2002), concluded that, while a viable and growing process with many positive
tendencies, the structure of virtual groups is so complex as to render the reviewed studies
overly simplistic. Most research, according to the researchers, was limited to examining
only the relationships of group size, task type, available choices, stress conditions, or
decision scheme rather than the deeper cognitive structures of intelligence, personality,
social structure, and other non-face-to-face issues (Aldridge, 2001; Gibson et al., 2003;
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Goh, 2004; Kerr & Tindale, 2004; Wagner, 2002). Maxwell (2006) cited numerous
psychological studies linking cognition and interpersonal aspects to adaptive behavior, or
personality. Maxwell (2006) further stated that a primary faculty of emotion, or
personality, is to reflect and motivate the modification of individual-environment
relations in an advantageous manner.
The linkage of personality to individual-environment relations raises the question
of whether personality is a factor in virtual team efficiency. This study examined the
potential of such a linkage, exacerbated by the introduction of a high-stress environment,
considered and examined by J. Burgoon and others as a critical aspect of autonomic
cognitive response (Burgoon, Blair, & Moyer, 2003, J. K. Burgoon et al., 2005; J. K.
Burgoon, Blair, & Moyer, 2003; Buller & J.K. Burgoon, 1996).
In situations of high stress, the communications receiver expects a particular
message based upon the cues, verbal and nonverbal, presented by the sender. Thus, when
the cues are not present, the receiver misses or ignores the actual message as the brain is
engaged in replacing this missing information to complete the picture. Bermudez et al.
(2004), Goh (2004), Halone and Pecchioni (2001), Hawkins (2002), and Higgins (2003)
established that a situation of missing cues is particularly prevalent in virtual teams due to
the use of electronic communications media.
CMC expansion throughout government, industry, and academia is a result of the
fact that virtual teams are viable solutions to the issues of distance, cost, and globalization
of resources (Jang, 2003; Jarvenpaa & Leidner, 1998; Scholtz, 2003). Government
utilizes virtual/CMC systems in intelligence, military, and operational roles. Industry is
increasing the use of virtual meeting technology as travel costs continue to increase.
Academia utilizes virtual classrooms to expand their breadth of student coverage. In each
of these situations, information passes in pictorial and/or text format without the benefit
of non-verbal support inputs.
Background and Supporting Theories
Three major theories were considered. They are the expectations violations model
and theory (Burgoon, et al, 1998), collaborative decision making theory (Bridgland &
Watro, 1987; Buchanan & Kock, 2000; Higgins, 2003; Pidd et al., 2003; Ryan, 2002;
Thomas, 2003; Warner & Wroblewski, 2004), and fault-tolerant decision making theory
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(Brown, 2004). Each theory held, in different ways, that in a CMC environment, the
receivers of electronic communications are free to interpret the communications while
not providing non-verbal feedback to the sender. Such a situation potentially negates
participation of the sender to the idioms of individual personality. Thus, unification of
information and processes effects can occur resulting in receiver decision anomalies. The
theories do not examine the source of these anomalies, concluding the need for additional
study.
Decision support systems include options for making human collective choices;
decision support systems require optimal rules such as laws, ethical standards, and others
that make human interaction mandatory. The interaction establishes the basis for
cognitive process misunderstandings (Brown, 2004). A misunderstanding within the
cognitive process creates additional areas of uncertainty in the CMC environment,
leaving the individual more reliant upon individual expectations and personal preferences
of action.
People are social animals reared and developed within the confines of society
(Darwin, 1965; Dickson et al., 2004; Kincaid, 1987). People establish themselves as an
element of society and conform to social and normative strictures. The necessary
communications of a societal organization result from a lifetime of learning acceptable
and unacceptable standards of interaction. As cited by Allot (2001), researchers such as
Levins (1570), Butler (1634), Flint (1740), and De Saussure (1916) studied the innate
character of language or communications as the basis for the creation of society.
In a study published in 2002 at the 130th Annual Meeting of the American Public
Health Association, Campo et al. (2002) reported the link between social norms and
expectancy violation. Their work demonstrated that socially developed expectations
create inaccurate perceptions when required information is not present. The violations
cause misconceptions of correct attitude or behavior, leading to incorrect attitude changes
in the participants.
The information from Campo et al.s 2002 study pointed to the powerful effects
social norms have on behavior. Behavioral change effects link to and derive from the
societal need of humans for acceptance and social membership.
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The structure of the human mind, in particular mental processes for all human
beings, is indicative of the extent to which external, nonverbal communications stimulate
mental activity and decision making (Zaltman, 2005). Zaltman noted that language is
limited and should not be confused with the process of thinking or thought. People think
not simply in words, but in pictures, feelings, and other factors(Mahoney, 2003;
Yoogalingam, 2003).
The research cited abovedemonstrated a significant relationship between
expectation and the foundations of communications structure in all forms. The research
led to the conclusion that the basis for expectation develop within each human being from
birth as the means to develop the ability to communicate, interact, and survive within
society (Lee, 1999). The research also demonstrated an increasing reliance upon
expectation norms as stress and external uncertainty increase (Henderson, 1999; Hoch,
Kunreuther, & Gunther, Eds., 2001; Lussier, 2002). It is, therefore, logical to infer that
violation of these expectations will have an effect on the mental activities of humans in
an uncertain environment. Additionally, it is logical to infer that, as cognitive processes
rely heavily on the aspects identified by Mahoney (2003) and Yoogalingam (2003) as
well as the basics of culture and language, that the individuals personality is the foci of
cognitive behavior and determination.
Method
Due to the qualitative nature of the information gathered and the position on
psychological research methodologies espoused by Jung (1968), a mixed method process
was utilized to study the relationship of personality to CMC efficacy. Jung stated that the
construct of individual personalities defies detailed analysis in a quantitative structure
due to the variation in environments within which one finds the subject and that exhibited
personality adjusts to fit the environment (Laszlo, 1990). However, Jung did not have the
specific tools available today for the assessment and quantification of behavioral
personalities.
This study utilized a bidirectional approach similar to that utilized by Wagner
(2002). The subject pool derived from a set of U.S. Army personnel with appropriate
virtual communications experience. The experience was set within a combat
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environment, being the highest stress environment considered available and supportable
as such.
A questionnaire, the Military CMC Effectiveness Survey (M-CMCE), established
what information, data, and knowledge existed within the unique environment of the
individuals involved in high-stress combat situations. Participants were interviewed for
data on experiences, concerns, problems with systems where understanding were
involved, and overall impressions of communications accuracy using on-line systems.
The personality element was determined utilizing the Insights-Discovery
Personality Determination Questionnaire resulting in a quantifiable personality matrix.
The Insights-Discovery process relates the matrix to an internationally validated
psychological profile (Insights Learning and Discovery, 2006). The profile derives from
the work of Jung in The archetypes and collective unconscious (Collected Works of C.J.
Jung, Vol. 9, Part 1) (Jung, Adler, & Hull, 1968) and has been validated through
repetitive and detailed study by Westminster University, London, England (Lothian,
2002). Figures 1 and 2 are depictions of the output of the methodology.
Figure 1: Insights-Discovery learning
dynamics structure matrix. Note. From
Insights Learning and Discovery, Ltd.
(2006). The Insights-Discovery System.
Retrieved January 1, 2006, from
http://www.insights.com/core/English/
TheDiscoverySystem/default.shtm.
Reprinted with permission.
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Figure 2: Insights-Discovery personality
matrix compilation wheel. Note. From
Insights Learning and Discovery, Ltd.
(2006). The Insights-Discovery System.
Retrieved January 1, 2006, from
http://www.insights.com/core/English/
TheDiscoverySystem/default.shtm.
Reprinted with permission.
The specific analysis methodology is depicted in Figure 3 below.
Data Development
M-CMC
Survey
Analysis
Mind-Stretch
Database
SoldierSubject
Insight-Discovery
PersonalitySurvey
Combat CMC ExperiencePersonality Type Data
Soldiers with CMC/Combat experience are surveyed via internet Personality Data Independent Variable
Education/Demographic Data Independent VariableExperiential Information with CMC Dependent Variable
Data obtained using single survey combining Insight-Discovery and Military-Computer MediatedCommunications (M-CMC) surveys into one interface
M-CMC gathers demographic and experiential data as to the subject s CMC activities/experiences incombat
Personality/Likert data stored in Mind-Stretch, Inc. (Insight-Discovery Company) servers and fed to theIDTA Tool for base analysis and display as Insights Wheel
Textual information fed to Analysis Software for Word-based Records (AnSWR) and codified based oncommonalities such as recurring themes, etc.
Codified information compared to personality and demographic ele ments
AnSWR
AnalysisTool
Insight-DiscoveryTeam Analysis
Tool
Text Data
Personality-LikertInformation
Likert
Data
Structured CommonAttribut es
Study Data Development and Analysis Process
PersonalityData
Figure 3: Study Methodology
RESULTS
The study data provided information indicating that there were specific
differences associated with the respondents perceptions of their ability to work within a
virtual environment. The survey investigated specific domains ranging from normal face-
to-face and purely virtual communications methodologies. The resulting information
included perceptions of the clarity of the information being passed; perception of the
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message being communicated vice the intended message; and perception of error in
understanding leading to abandonment of the CMC system process. The data depicted a
nearly bi-modal structure between normal human communications and the virtual (CMC)
domains. The issue then became one of whether there existed any specific similarities
between the CMC-successful and CMC-unsuccessful groups.
Personality Results
The results from the Insights-Discovery survey consisted of four identifying
colors or labelsred, green, yellow, and bluewhich correlate to specific Jungian
personality typology functions or attributes described in Table 1. The functions or
attributes shown relate to personality characteristics, how individual participants display
the typology characteristics during personal interactions.
Table 1
Insight-Discovery Color Dynamics
A combination of Table 1 and Figure 4 indicates participants expressing a
perception of full CMC efficacy have primary personality functionality of thinking and
introverted, or what Insights-Discovery labels the Blue factor. Blue emerged as 31% of
the respondent structure. Blue individuals have primary personality traits of being highly
analytical and precise; however, others see Blue individuals as indecisive and prone to
focus on minutiae.
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Focused Respondents Personality Structure
31%
23%
20%
26%
Blue
Green
Yellow
Red
Figure 4. Focused respondents personality structure summary.
Twenty-three percent of the respondents had thinking and extroverted, or Red,
tendencies. Individuals with a Red tendency have as their personality traits a value of
taking action, making decisions, and mental challenges. However, Red individuals
generally do not tolerate indecision in others or themselves (Jung et al., 1968). Red
individuals also have a high degree of confidence in their own abilities, but communicate
to others a degree of lack of trust that may not truly be a part of their personality
construct. Individuals having a score of Blue are analytical, precise, cautious, deliberate,
and others perceive this as indecisive (Jung et al.). Figure 4 depicts the results of the color
dynamics in a related scoring value for comparative analysis.
Of specific interest are the positions of the various result points in Figure 5. The
Insights Wheel segregates into the various typology color zones and further subdivided
into degrees of strength in three concentric circles. The closer the respondent scores are
toward the center of the graph, the lower the strength of the typology. Additionally, the
closer the respondent scores are toward one of the dividers, the greater is the focus of the
respondent to that typology subcategory. For example, the respondent scoring 35 on the
wheel is a primary Blue with strong observer tendencies, yet edges toward a reformer
attitude. The participant with a score of 36 is a strong Blue reformer. Each has specific
traits not part of the current study.
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Figure 5: The Insights Wheel asterisk
group. Note. Figure created expressly
for the current study and reprinted with
the permission of Insights Learning and
Discovery, Ltd. via MindStretch, Inc.
Copyright 2008 by MindStretch, Inc.
Discussions with Insights-Discovery analysts revealed that what appear to be
outliers on this graph are, in fact, not (personal discussions with Amerman, 2008). The
coordinator/supporter structures reflect similar aspects to the other structures with the
primary differentiation being the coordinator/ supporter group represents introversion
rather than extraversion, which reflects a greater selection to attention on the preference
of sensing rather than thinking. Jung discussed that these preferences are focused
typologies or human differences (Jung et al., 1968). The Jungian typologies, when
combined, describe specific differences among people (Amerman, 2008). The
introversion typology focuses energy and attention inward (Jung et al., 1968). The inner
world is the real world, which determines the persons behavior. The outer world is less
real, exerting less influence on behavior (Jung et al.).
The individual in the supporter, or Green, position focuses on introverted feeling
and shows more attention to others. A Green person has a need to observe others level of
honesty, available in face-to-face communications and not CMC. Confirmation of this
evaluation comes from the respondents textual survey responses. Participants scoring in
the Green typology revealed the need to observe which responses exist in the nonverbal
communication of others and a concern for ensuring the others complete understanding
of the message sent by the respondents. However, the respondents also discussed a
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comfort with CMC systems not mentioned by participants scoring virtual systems lower.
The respondents comments may come from a high degree of experience and training in
the CMC systems not indicated in the limited Likert range of the M-CMCE survey.
Figure 6 contains the personality rankings for the respondents who registered their
perception of CMC efficacy as lower than face-to-face communications. Although the
rankings appear similar, the scorings show a typology strength difference. Figure 7
diagrams a reversal of strength in both the Blue (observer/reformer) scales as well as the
Red (reformer/director) scales in side-by-side depictions. The comparison demonstrates
the relationship between the two sets and the change in typology strengths. The lines
between the two charts are not depicting a change in scorings that are from the same
individuals, but are rather of different individuals from the two separated groups.
Figure 6. The Insights Wheel nonasterisk group.Note. Figure created expressly
for the current study and reprinted with the permission of Insights Learning and
Discovery, Ltd. via MindStretch, Inc. Copyright 2008 by MindStretch, Inc.
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Figure 7. The Insights Wheel nonasterisk group.Note. Figure created expressly for the
current study and reprinted with the permission of Insights Learning and Discovery, Ltd.
via MindStretch, Inc. Copyright 2008 by MindStretch, Inc.
The rankings in Figure 7 reflect the respondent personality types where each respondent
is in a leadership or leadership staff position. Claxton (2004) focused on participants in
leadership or leadership staff positions within the U.S. DOD. Thus, the relationship of the Blue
and Red rankings indicate similar findings to the findings discussed by Claxton (2004) in his
dissertation involving personality types and leadership roles in the U.S. Department of Defense.
The importance of the developed data of the current study, and an issue not considered byClaxton (2004), is the strength of the rankings. There are four zones or circles within the Insights
Wheel. The further toward the outer circle, the more embedded in the category the respondent
lies, and the less the secondary personality preference influences behavior. Conversely, the
nearer the center, the stronger the relationship between the types the personality becomes
(Amerman, 2008). Thus, while the current study both supports and is supported by Claxtons
work, the aspect of the general nature of personality types of individuals in leadership positions
becomes non sequitur as it is a constant.
CONCLUSIONS
The study conclusion is that personality typology may influence decision-making
efficacy of individuals utilizing CMC systems in combat environments. From the conclusion, the
identification of three specific elements as likely influencing factors was possible: strength of
individual personality typology, trust, and cognitive expectation.
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Strength of Individual Personality Typology
When the use of fully capable CMC systems, identified as CMC with full graphics, was
under consideration, one set of the respondents recorded increased perceptions of efficacy while
the other set did not. The divergence in perception did not derive from differences in the
respondents education, virtual system experience, knowledge of information technology
systems, or level of authority while in combat environments. Rather, the respondents data
revealed nearly identical demographics. The most likely remaining element of influence, as
derived from the data, is individual typology.
More accurately, the data indicate the possibility that the strength of the personality
typology may be the primary influence. The M-CMCE survey participant textual responses,
which included verbiage indicative of experiences directly tied to the respondents perception
scores, such as a need for visual cues for those scoring CMC system efficacy low and the
disassociation of these cue requirements for those scoring CMC system efficacy high, provided
further support for this conclusion. Therefore, given the similar results of the Claxton (2004)
study and the current study, the conclusion may be drawn that a relationship exists between
personality typology strength and decision-making.
Moreover, as the Claxton (2004) study methodology and personality tool base and the
current studys methodology and tool base are sufficiently similar for close comparison, the
similarities of the study results further support the concept that specific leadership personality
relationships are a possible constant. The theory possibility is that a relationship exists between
personality strength and communications clarity within a CMC structure in a combat
environment. Given the researched relationship between both personality and communications
clarity and decision-making, there exists a potential relationship between personality and
decision making efficacy when utilizing CMC systems within a combat environment.
Trust
Although the current studys methodology was limited to typologies, some of the
developed data addressed the issue of trust. The trust issue developed from the M-CMCE survey
data focuses on two primary domains: trust of the information arriving through the CMC systems
and the participants trust of their own ability to communicate effectively via CMC systems. The
M-CMCE survey was constructed to develop data on decision-making efficacy, not individual
trust issues such as addressed in the Wagner (2002) and Walters (2004) studies. However,
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comparisons with the Wagner and Walters studies resulted in information similar to the two trust
domains identified in the current studys data.
Wagner (2002) identified correlations in the importance or risk associated with a specific
communication message and the communications technology utilized. The nature of the issue
open for discussion by the virtual team members, according to Wagner, is a key to the
technology the teams chose to use. Walters (2004) concluded that the less confidence or trust in
the team, the sensitive or personal nature of the message, or its possible negative reception, the
more likely an individual is to select a lower technology such as e-mail. If the message is of high
importance or requires verification of understanding, is volatile, or is of high criticality, the team
member is more likely to select a face-to-face meeting or visual technology. When trust
relationships are high, advanced technology receives primary selection (Walters).
The developed data and conclusions contained in the Walters (2004) study are similar to
the data developed in the current study. Specifically, M-CMCE survey text and Likert-like score
data indicated an enhanced trust in the CMC systems by participants scoring CMC system use
high. Simultaneously, the M-CMCE survey participants scoring CMC system perceived efficacy
low likewise expressed low trust in both the systems and team members. Thus, a comparison
with the Walters study also supported acceptance of the current studys primary hypothesis.
Cognitive Expectation
A key factor in the current studys conclusion had a basis in the individuals nature to
rely upon experiences and cultural dynamics to establish expectations of which verbal and
nonverbal inputs are cognitively necessary to formulate decisions. The expectations, when
violated through their absence, result in the brain substituting potentially inappropriate memories
for missing data points. A similar occurrence exists in the psychology rubric in which a
participant reads a paragraph from which all vowels are removed. Because the cognitive
expectation has the vowels present, the brain inserts the absent vowels, enabling the reader to
understand the paragraph.
The M-CMCE survey data supported the premise of the individuals need to revert to
familiar mental processes due to the emotional comfort the processes provide. The support
derives from the participant statements expressing the desire for face-to-face communications in
sensitive situations and the participants simultaneous low scoring of CMC system perceived
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efficacy. Reversion to familiar mental processes is the basis for the expectation violation theory
(Burgoon & Hale, 1988).
Comparison with the Wagner (2002), Claxton (2004), and Walters (2004) studies again
supported the conclusion that expectation violation may constitute a primary factor in the
observed participants perception differences. As stated in the Trust section, Wagner (2002)
found that participants perception of cognitive efficacy on the part of team members was a key
to the participants selection of virtual team involvement. Lewis and Weigert (1975), as quoted
in Wagner (2002, p. 47), noted We cognitively choose whom we will trust in what respects and
under what circumstances, and we base the choice on what we take to be good reasons
constituting evidence of trustworthiness (p. 969). A cognitive choice creates an expectation as
the choice derives from what we take to be good reasons (Lewis & Weigert, as cited in
Wagner, p. 47). The reasons derive from experience, a key elemen t in Burgoons theory of
expectation violation (Burgoon & Hale, 1998). Violation of what the individual considers a good
reason results in stress and cognitive dissonance.
The conclusion of the current study, based on available survey data and the exegetic
information, is that personality typology may directly influence perceived CMC and decision
making efficacy, particularly in the highly stressful environment of combat conditions.
Additionally, there is sufficient information present to hypothesize a direct relationship in
typology strength and degree of individual reliance upon previous experiences and decision-
making efficacy based upon expectation violation in virtual CMC environments.
George J. Graham is a faculty member for the University of Phoenixs School of Advanced Studies. He isa PhD in political science/public policy from Northern Arizona University. He holds a bachelors degreefrom the University of Southern California and a masters degree from California State University LongBeach. He may be reached [email protected].
Harry I. Nimon is a Sr. Analyst for The Boeing Corporation, Defense Systems Division. He is a PhD fromthe University of Phoenix, in Phoenix, Arizona. He holds a bachelors degree in Education from AkronUniversity, Akron, Ohio and masters degrees from Central Michigan University(MBA), Mt. Pleasant, MIand the US Army Command and General Staff College (MS in Operations Management Science). Hemay be reached [email protected].
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REFERENCES
Alberts, D. S. (1996). The unintended consequences of information age technologies. Washington, DC: National DefenseUniversity.
Aldridge, J. W. (2001).A multidimensional model for building knowledge assets: Applying socio-technical systems to online
action research. Santa Barbara, CA: Fielding Graduate Institute. Retrieved November 20, 2004, from the EBSCO database.
Allot, R. (2001). The physical foundation of language. Hebworth, UK: Able. Retrieved on June 10, 2005 fromhttp://www.percepp.demon.co.uk/hypothesis.htm.
American Neurological Association. (2006). Retrieved on January 2, 2006 from http://www.aneuroa.org/
Amerman, L. (2008). The structure of Jungian psychology. Houston, TX: MindStretch.
Bermudez, J., Westenskow, D., Foresti, D., Strayer, D., Agutter, J., Syroid, N., et al. (2004). Visual representation of integratedphysiological data. Retrieved March 12, 2005, from http://faculty.arch.utah.edu/people/faculty/julio/res.htm
Bissoonauth, B. (2002). Virtual project work: Investigating critical success factors of virtual project performance. Unpublished
masters thesis, Concordia University. (UMI No. 0-612-77952-1)
Boudreau, M., Loch, K. D., Robey, D., & Straud, D. (1998). Going global: Using information technology to advance thecompetitiveness of the virtual transnational organization. Academy of Management Executive, 12(4), 120-128. Retrieved
November 28, 2005, from EBSCOhost.
Bridgland, M. F., & Watro, R. J. (1987). Fault-tolerant decision making in totally asynchronous distributed systems. Bedford,MA: MITRE. Retrieved December 10, 2004, from http://portal.acm.org/citation.cfm?id=41845
Brown, M. (2004, June 15-17). Rapid knowledge formation in an information rich environment. Paper presented at theDODCRTS Symposium, San Diego, CA. Retrieved September 12, 2004, from http://www.dodccrp.org/events/2004/
CCRTS_San_Diego/CD/foreword.htm
Buchanan, J., & Kock, N. (2000).Information overload: A decision making perspective (MCDM2000).Retrieved February 18,2005, from http://www.mngt.waikato.ac.nz/depts/mnss/john/iomcdm2000_1.pdf
Buller, D., & Burgoon, J. K. (1996). Interpersonal deception theory. Communication Theory,6, 203-242.
Burgoon, J. K. (2000). Mindfulness and interpersonal communication.Journal of Social Issues, 105-128. Retrieved October 1,2004, from www.findarticles.com/p/articles/mi_m0342/is_1_56/ai_63716504
Burgoon, J. K., Adkins, M., Kruse, J., Jensen, M. L., Meservy, T., Twitchell, D. P., et al. (2005). An approach for intentidentification by building on deception detection. Retrieved December 18, 2005, from
http://cbim.rutgers.edu/papers/Hawaii2_2005.pdf#search=%22Effects%20of%20Communications%20Modality%20on%20Arousal%2C%20Cognitive%20Complexity%2C%20Behavioral%20Control%20and%20Deception%20Detection%20During%20Deceptive%20Episodes%22
Burgoon, J. K., Blair, J. P., & Moyer, F. (2003, November 19-23) Effects of communications modality on arousal, cognitivecomplexity, behavioral control and deception detection during deceptive episodes. Proceedings of the Annual Meeting of the
National Communication Association, Miami, FL.
Burgoon, J. K., & Hale, J. L. (1988). Nonverbal expectancy violations: Model elaboration and application to immediacybehavior. Communication Monographs, 55, 58-79.
Burgoon, J. K., & Saine, T. (1978). The unspoken dialogue: An introduction to nonverbal communication. Boston: Houghton
Mifflin.
Burgoon, M., Hunsaker, F. G., & Dawson, E. J. (1994). Human communication. Thousand Oaks, CA: Sage.
Burgoon, M., & Ruffner, M. (1978).Human communication. New York: Holt Rinehart and Winston.
Caldwell, B. S., & Everhart, N. C. (1998). Information flow and development of coordination in distributed supervisory control
teams.International Journal of Human-Computer Interaction, 10, 51-70.
Campo, S., Cameron, K. A., Broussard, D., & Frazier, M. S. (2002, November 11). Social norms and expectancy violationtheories: Assessing the effectiveness of health communication campaigns. Poster session presented at the annual meeting of theAmerican Public Health Association, Ithaca, NY.
Claxton, J. D. (2004).An Examination of Personality Type Dominating Leadership Positions in Department of Defense ProgramManagement. Doctoral Dissertation, University of Southern California (UMI No. 3140458).
8/3/2019 Leadership Journal Submission 9-30-10
16/17
16
Comadena, M. A. (1990). Book reviews. [Review of the books Nonverbal communications: The unspoken dialogue; Nonverbalcommunications: Studies and applications (2nd ed.); and The nonverbal communication reader]. Communication Education, 38,161.
Cooper, J. (2004, October 7). Vicarious cognitive dissonance: Attitude change based on someone elses behavior[Lecture].Princeton, NJ: Princeton University.
De Saussure, F. (1993). Third course of lectures on general linguistics (1910-1911). London: Pergamon PressDickson, M. W., BeShears, R. S., & Gupta, B. (2004). The impact of societal culture and industry on organizational culture. In R.J. House, P. J. Hanges, M. Javidan, P. W. Dorfman, & V. Gupta (Eds.), Culture, leadership, and organizations: The GLOBEstudy of 62 societies. Thousand Oaks, CA: Sage.
Festinger, L., & Carlsmith, J. M. (1957).A theory of cognitive dissonance. Stanford, CA: Stanford University Press.
Gadanho, S. C., & Custodio, L. (2002). Asynchronous learning by emotions and cognition. Lisbon, Portugal: Institute of Systems
and Robotics. Retrieved November 28, 2004, from http://omni.isr.ist.utl.pt/~sandra/papers/ Gadanho_sab02.pdf
Gibson, C. B., & Cohen, S. G., Alcordo, T. C., Ahanassiou, N. A., Baba, M. L., Blackburn, R., et al. (2003). Virtual teams thatwork. Jossey-Bass Business and Management Series. San Francisco, CA: Wiley.
Goh, K. (2004). The role of cognition and emotion regulation in conflict: A study of the impact on organizational and virtual
teams. Unpublished doctoral dissertation, University of Southern California. (UMI No. 3145203)
Griffin, E., McClish, G., & Bacon, J. (2003).A first look at communication theory. Washington, DC: McGraw-Hill
Hale, J. L., Burgoon, J. K., & Householder, B. (2005). The relational communication scale. Unpublished manuscript.Halone, K. K., & Pecchioni, L. L. (2001). Relational listening: A grounded theoretical model. Communications Reports, 14, 1-4.
Hawkins, D. R. (2002). Power vs. force: The hidden determinants of human behavior. Carlsbad, CA: Hay House.
Henderson, E. D. (1999).Model for adaptive decision making behavior of distributed hierarchical teams under high temporalworkload. Unpublished doctoral dissertation, George Mason University, Fairfax, VA. (UMI No. 733980671)
Heylighen F., Joslyn, C., & Turchin V. (Eds.). (1995). The quantum of evolution. World Futures: The Journal of General
Evolution,45, 1-4.
Higgins, M. A. (2003). Persuasion, pitch and presentation: The effects of information style on individual decision making.Unpublished doctoral dissertation, University of Arizona, Tucson. (UMI No. 765028771)
Hoch, S. J., Kunreuther, H., & Gunther, R. (Eds.). (2001). Wharton on making decisions. New York: Wiley
Insights Learning and Discovery, Ltd. (2006). The Insights-Discovery System. Retrieved January 1, 2006, from
http://www.insights.com/core/English/ TheDiscoverySystem/default.shtm
Jang, C. Y. (2003).Awareness in global virtual teams: Its antecedents and implications. Lansing: Michigan State University.(UMI No. 3115982)
Jarvenpaa, S. L., & Leidner, D. E. (1998). Communication and trust in global virtual teams. Journal of Computer-MediatedCommunication, 13(4). Retrieved July 25, 2004, from www.ascusc.org/jcmc/vol3/issue4/jarvenpaa.html
Jung, C. J., Adler, G., & Hull, R. F. C. (1968). The archetypes and collective unconscious (Collected Works of C.J. Jung, Vol. 9,Part 1). Princeton, NJ: Princeton University Press.
Kanawattanachai, P. and Yoo, Y. (2005).Dynamic Nature of Trust in Virtual Teams. Retrieved on March 12, 2006 from
http://sprouts.case.edu/2002/020204.pdf
Kerr, N. L., & Tindale, R. S. (2004). Group performance and decision making. Annual Reviews in Psychology,55, 623-655.
Kring, J. P. (2004). Communication modality and after action review performance in a distributed immersive virtual
environment. Unpublished doctoral dissertation, University of Central Florida, Orlando. (UMI No. 862908891)
Lane, D. R. (n.d.). Function and impact of nonverbal communication in a computer mediated communication context: Aninvestigation of defining issues. Retrieved February 18, 2005, from http://www.uky.edu/~drlane/techno/nvcmc.htm
Lewis, J. D., & Weigert, A. (1985). Trust as a social reality. Social Forces, 63, 967-985. Retrieved April 6, 2008, fromhttp://www.questia.com/PM.qst?a=o&d=95735570
Lussier, C. M. (2002).Does dynamic assessment reduce the influence of stress on memory and reasoning. Unpublisheddocument, University of California-Riverside. Retrieved September 3, 2004, fromhttp://www.dynamicassessment.com/_wsn/page8.html
http://www.questia.com/PM.qst?a=o&d=95735570http://www.questia.com/PM.qst?a=o&d=95735570http://www.dynamicassessment.com/_wsn/page8.htmlhttp://www.dynamicassessment.com/_wsn/page8.htmlhttp://www.dynamicassessment.com/_wsn/page8.htmlhttp://www.questia.com/PM.qst?a=o&d=957355708/3/2019 Leadership Journal Submission 9-30-10
17/17
17
Mahoney, M. (2003, January 13). The subconscious mind of the consumer (and how to reach it). Harvard Business SchoolWeekly Publication. Retrieved March 14, 2005, from http://www.olsonzaltman.com/oza/NEWS/WorkingKnowledge.htm
Maxwell, J.S. (2006).Emotion-Related Asymmetries and Individual Differences in Cognition and Behavior. Doctoral
dissertation, University of Wisconsin (UMI No. 3234721)
McPhee, R., & Cushman, D. P. (1980). Message-attitude-behavior relationship: Theory, methodology and application. HumanCommunication Research Series. New York: Academic Press. Retrieved November 28, 2004, from the ProQuest database.
Nimon, H. I. (2004).Issues and requirements for information processing modeling within the scenarios and wargaming group(White paper). Huntington Beach, CA: Boeing.
Reynolds, R. A., Koper, R. J., & Burgoon, M. (1982). The effects of communication context, source credibility and messagevalence as predictors of perceived compliance-gaining message appropriateness and social influence. Communication: The
Journal of the Communication Association of the Pacific, 11, 58-77. Retrieved November 18, 2004, from the ProQuest database.
U.S. Department of Health and Human Services. (2006).Analysis Software for Word-based Records (AnSWR). Retrieved May10, 2006, from http://www.cdc.gov/Hiv/ SOFTWARE/answr.htm
Wagner, K. H. (2002).An investigation of conflict management in global virtual teams. Unpublished doctoral dissertation,University of California, Los Angeles. (UMI No. 3076600)
Walters, K.K.G. (2004).A Study of the Relationship Between Trust and Perceived Effectiveness in Virtual Teams. Doctoraldissertation, Capella University, Minneapolis, Mn. (UMI No. 3138510.
Warner, N., & Wroblewski, E. (2004, June 15-17). The cognitive processes used in team collaboration during asynchronous,distributed decision making. Naval Air Systems Command. Paper presented at the DODCRTS Symposium, San Diego, CA.
Retrieved September 12, 2004, from http://www.dodccrp.org/events/2004/ CCRTS_San_Diego/CD/foreword.htm
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