Browsing by Author "Mark A. Wilson, Committee Member"

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Effects of Survey Modality and Access Controls on Perceived Anonymity and Socially Desirable Responding
(2008-04-25) Whelan, Thomas James; Lori Foster Thompson, Committee Chair; Mark A. Wilson, Committee Member; Adam W. Meade, Committee Member
The comparison of traditional and computer-based survey formats has received considerable attention in past research, along with questions about the effects of anonymity on the candor of survey respondents. As computerized survey methodologies have evolved, the Internet has presented researchers with an alternative to paper-and-pencil survey administration, although it may also pose problems of sampling (i.e., ensuring that respondents are from the target population). Access controls have been suggested as a way to deal with sampling problems, though the impact of access controls on respondents has not been fully investigated. While many survey sponsors make assurances to respondents as to the anonymity afforded to them, some have argued that access controls may undermine these assurances. In this study, the construct of anonymity perceptions are defined and subsequently examined in several survey contexts that vary in terms of survey modality (i.e., paper versus Web) as well as the style of access control implemented. Respondents (N = 264) were asked to complete an instructor evaluation and university climate survey. Respondents were randomly assigned to one of four survey conditions: Paper-and-pencil, Web-based with no access controls, Web-based with group access controls, and Web-based with individual access controls. This study did not find significant differences between survey conditions for perceptions of anonymity or impression management. In addition, perceptions of anonymity were not found to be significantly related to response distortion, contrary to research hypotheses based on previous empirical and theoretical research. The implications for examining anonymity as a subjective, rather than objective, factor in future survey research are discussed.
The Good, the Bad and the Ugly: The Mediating Role of Attributional Style in the Relationship between Personality and Performance
(2005-06-27) Baker, Becca A.; Samuel B. Pond, Committee Chair; Mark A. Wilson, Committee Member; Stephen Bartholomew Craig, Committee Member
Previous research has shown that personality traits, specifically the Five-Factor Model (FFM) and affect, are significant predictors of job performance, including organizational citizenship behavior (OCB) and counterproductive work behavior (CWB) (Barrick & Mount, 1991; Organ & Ryan, 1995). However, some debate exists regarding which individual difference variables account for the most variance. The present study tests a causal model of counterproductive behavior by Martinko, Gundlach, and Douglas (2002) which proposes that individuals' attributions about workplace events act as mediators between personality and CWB. This model is also examined regarding its generalizability to OCB. One hundred and thirty-nine employees of a national senior care organization filled out self-report questionnaires regarding their personality. Subsequently, their immediate supervisors completed performance evaluations that included items addressing CWB and OCB. Structural equation modeling revealed that attributional style did not act as mediator between personality and CWB or OCB. In addition, none of the individual differences variables predicted CWB or OCB. A post hoc cluster analysis was used to examine the appropriateness of the scoring method used for attributional style. The implications of these results and directions for future research are discussed.
How Long Should We Follow the Leader? Using Latent Growth Models of Longitudinal Leadership Performance Change to Predict Leader Outcomes.
(2007-04-06) Mullen, Torrey Rieser; Mark A. Wilson, Committee Member; Lori Foster Thompson, Committee Member; Samuel B. Pond, Committee Co-Chair; S. Bartholomew Craig, Committee Co-Chair
A paucity of research has examined longitudinal performance and the predictive ability of performance change on important outcomes. In addition, few studies have investigated the effects of rater variables on performance over time and the effect of rater group composition or rater perspective on longitudinal performance ratings. The purpose of this research was to investigate consequences related to rater characteristics including rater context, perspective and composition in the measurement and prediction of longitudinal performance. Results suggested that longitudinal self-ratings, boss ratings, and direct report ratings were equivalent. The results of this study also concur with earlier findings about the dynamic nature of performance (Thoreson, et al., 2004). Longitudinal change in performance was found for every leadership performance factor in ratings from every rater group. Latent growth curves for all rater groups were remarkably similar although boss ratings showed the most consistent longitudinal change. Adding sector and⁄or subdivision covariates to the models improved model fit for each rating source group. Using growth mixture modeling with the rater context covariates allowed the estimation of latent classes that clarified the direction of leadership performance growth. Results also indicated the importance of rater composition. Direct reports who consistently rated the same leader tended to rate those leaders more highly than the direct reports who rated different leaders. Adding the composition moderator variable to the boss rating models improved model fit for four of the five leadership performance models. The composition covariate also significantly predicted the intercept and slope for boss ratings of Ethics and Character, suggesting that obtaining leadership performance ratings from consistent bosses plays an important role in detecting linear change in leader performance, especially for ratings of Ethics and Character. Leaders with positive development on Ethics and Character had higher consensus performance scores, confirming past research showing that integrity and ethical behavior are important characteristics in successful managers (Posner & Schmidt, 1984; Mortensen, Smith, & Cavanagh, 1989).
Improving the Prediction of Commitment and Innovative Work Behavior from Climate for Innovation Perceptions: An Application of Latent Profile Analysis
(2010-04-30) Cantwell, April Renee; Mark A. Wilson, Committee Member; Lynda Aiman-Smith, Committee Member; S. Bartholomew Craig, Committee Member; Samuel B. Pond, III, Committee Chair
In this research study, I conceptualized climate for innovation perceptions as representing subjective interpretations of the environment, and also as representing a complex and dynamic interaction between people and environments. Simple variable approaches and, as demonstrated by Young and Parker (1999), simple aggregation of climate survey scores to formal organizational groups seems inadequate to represent this complexity. The use of clustering techniques to identify homogeneous groups with regard to perceptions of climate (e.g., Schneider & Reichers, 1983; Mathisen & Einarsen, 2004; Joyce & Slocum, 1984) is an approach that can represent data complex interactions of people and environments. Researchers have not yet determined which clustering techniques best account for the complex influences on perceptions of climate or best predict associated organizational outcomes. Latent profile analysis (LPA) is a clustering technique that may move the climate research forward. I used LPA to classify individuals by their climate for innovation perceptions and simultaneously to assess the relative contributions of situational and individual difference covariates, including company membership, functional membership, organizational level, and organizational tenure. Latent class membership was used to predict affective, normative, and continuance (ANC) commitment to the organization; ANC commitment to innovation, creative innovative work behavior (IWB), and implementation IWB to determine if latent class membership predicted these outcomes beyond the contribution climate for innovation perceptions. The archival dataset included 1,891 individual respondents from four high-technology firms. Only 383 cases provided commitment and IWB outcome data for the predictive study. The Innovation-Capacity Climate Survey (ICCS) measured nine dimensions of the climate for innovation, including Meaningful Work, Risk Taking, Customer Orientation, Agile Decision Making, Business Intelligence, Open Communication, Empowerment, Business Planning, and Learning Organization (Aiman-Smith, Goodrich, Roberts, & Scinta, 2005). A six-factor adaptation of Meyer and Herscovitchâ€™s (2001) ANC commitment model measured ANC commitment to the organization and ANC commitment to innovation. A two-factor adaptation of Dorenbosch, van Engen, and Verhagenâ€™s (2005) IWB scales measured Creative and Implementation IWB. The nine ICCS scales, four of six commitment scales, and both IWB scales demonstrated acceptable confirmatory factor analysis fit, maximal and internal consistency reliability, and expected factor interrelationships. After I identified three viable latent class solutions using LPA, I used multivariate analysis of variance (MANOVA) to examine the relationships among situational and individual difference covariates. I concluded that individual differences contributed more to perceptions of climate for innovation than did situational variables. I next used multivariate analysis of covariance (MANCOVA) to test whether latent class membership predicted commitment and IWB, with ICCS scores entered as covariates. For two latent class solutions, class membership predicted normative commitment to innovation; for one solution, class membership predicted IWB. Power and effect sizes for all of these analyses were low. Finally, I tested the hypotheses that climate perceptions decrease with increasing organizational tenure at the group and company level. Neither test was statistically significant but, at the company level, effect sizes were moderate and sample size was small. In sum, I sought to explore climate perceptions as a complex interaction of situation and individual differences. Although not conclusively so, I demonstrated that latent class membership was related to individual differences and situational factors, and that it predicted commitment and IWB. Future research should include person and situation variables, and models should be designed to assess the complex interactions among these variables. LPA modeling is a promising technique for understanding climate in organizations and important organizational outcomes consistent with my viewpoint.
Leaders Behaving Badly: Antecedents and Consequences of Abuse
(2010-04-30) Lindberg McGinnis, Jennifer Tricia; S. Bartholomew Craig, Committee Chair; Lori Foster Thompson, Committee Member; Samuel B. Pond, III, Committee Member; Mark A. Wilson, Committee Member
Although the leadership field has been preoccupied with identifying the leader traits and behaviors that evoke positive employee work attitudes and behaviors and maximize effectiveness (Bass, 1990; Yukl, 2002), the field has become increasingly interested in understanding the "dark side" of leader behavior. However, this research is still in its infancy. The current study increases our understanding of one class of negative leader behavior, abusive supervision, by examining supervisor personality as an antecedent of abusive supervision, along with several individual-level and organization-level consequences. An archival database was obtained from a leadership training and development consulting firm for the current study. Participants were focal managers (N = 121) who participated in a leadership development program. The managers completed a personality measure prior to the program. In addition, the managersâ€™ subordinates (N = 779) completed a customized, qualitative 360-degree assessment instrument that asked for examples of the focal managersâ€™ use of "bad leadership" behaviors and both their reactions to and the consequences (i.e., impacts) of these behaviors. A preliminary content analysis was conducted on the 360-degree data for 10 managers to develop the initial coding scheme. After this analysis, a content analysis was conducted on the 360-degree data for all 121 managers, resulting in 45 behavior categories and 59 reaction/impact categories. Next, 10 subject matter experts (SMEs) provided their ratings of abusive supervision and destructive leadership for the behavior categories. Eight behaviors were rated as abusive supervision; the same eight behaviors and an additional 16 behaviors were rated as destructive leadership, and 20 other behaviors were rated as non-destructive leadership. In total, 1,814 examples of bad leadership were provided; 501 (23.38%) were categorized as both abusive supervision and destructive leadership, 767 (35.8%) were categorized as destructive leadership only, and 875 (40.83%) were categorized as non-destructive leadership. Incivility (f = 75; 61.98% of managers) was the most common abusive supervisory behavior, followed by losing composure (f = 59; 48.76% of managers), lack of professionalism (f = 42; 34.71% of managers), and criticizing others (f = 36; 29.75% of managers). Forty-six reaction categories were associated with the eight abusive behaviors, and only two reaction categories were associated with subordinatesâ€™ responses to all eight of these behaviors: (1) damage to managerâ€™s reputation or credibility; and (2) damage to managerâ€”employee work relationships. The most common reactions across the abusive supervisory behaviors included: (1) feeling unappreciated, not valued, unworthy; marginalized (12.91%); (2) damage to managerâ€™s reputation or credibility (12.69%); (3) damage to managerâ€”employee work relationships (7.77%); (4) discomfort (6.46%); (5) apathy (6.02%); and (6) embarrassment (5.36%). Likewise, 59 impact categories were associated with the eight abusive behaviors, and only two impact categories were associated with subordinatesâ€™ responses to all eight of these behaviors: (1) decreased employee morale; and (2) decreased employee performance or results. The most common impacts across the abusive supervisory behaviors included: (1) damage to managerâ€™s reputation or credibility (12.92%); (2) decreased employee morale (7.03%); (3) damage to work relationships (6.91%); (4) damage to managerâ€”employee work relationships (6.52%); and (5) avoidance of or decreased communication with manager (5.24%). Subordinatesâ€™ reactions to and the impacts of these eight behaviors were also examined within each abusive supervisory behavior. Finally, after creating nine cluster profiles of the eight abusive supervisory behaviors, a discriminant function analysis revealed that cluster membership could not be predicted on the basis of the managersâ€™ personality characteristics (i.e., openness to experience, conscientiousness, extraversion, and agreeableness). The implications of this research for future empirical research and organizational practice were discussed.
The Relative and Incremental Validity of the Big Five and Maladaptive Personality Characteristics for Predicting Leadership Effectiveness
(2006-12-11) Lindberg McGinnis, Jennifer Tricia; S. Bartholomew Craig, Committee Chair; S. Bob Pond, Committee Member; Mark A. Wilson, Committee Member
Although previous research has examined "bright" personality characteristics that impact leadership effectiveness through their presence, there is a growing recognition of the importance of factors that promote leadership effectiveness through their absence (e.g., Hogan & Hogan, 2001; McCall & Lombardo, 1983). These "dark" or maladaptive personality characteristics have been hypothesized to interact with the length of time that an observer has been exposed to a given manager (Hogan & Hogan, 1997, 2001). In the current study, the relative and incremental validity of the Big Five and maladaptive personality characteristics in predicting leadership effectiveness was examined, as well as the moderating effect of leader-subordinate relationship length. Although previous research has examined "bright" and "dark" personality characteristics in the prediction of leadership effectiveness (e.g., Facteau & Van Landuyt, 2005; Judge, Bono, Illies, & Gerhardt, 2003), this study was the first attempt to examine both types of personality characteristics in the prediction of leadership effectiveness, in addition to the moderating role of relationship length. Personality data were collected from a sample of supervisors (N = 134), and their direct reports (N = 330) provided concurrent ratings of their supervisors' effectiveness. The multiple regression analyses revealed that the Big Five and maladaptive personality characteristics did not predict leadership effectiveness. In addition, the Big Five personality dimensions did not demonstrate incremental validity over and above the maladaptive characteristics, nor did the maladaptive characteristics demonstrate incremental validity over and above the Big Five personality dimensions in the prediction of leadership effectiveness. Finally, the relation between the maladaptive personality characteristics and leadership effectiveness did not vary as a function of leader-subordinate relationship length, contrary to the predictions of previous theoretical work (Hogan & Hogan, 2001).