attributional complexity: a link between training, job complexity, decision latitude,...

Attributional Complexity: A Link Between Training, Job Complexity, Decision Latitude, Leader-Member

Exchange, and Performance

JOELLYN C. TOWNSEND Assessment Solutions, Inc.

New York, New York

NANCY DA SILVA, LORIN MUELLER, PAT CURTIN,

University of Houston AND Lois E. 'ETRICK~

Previous research demonstrated that individuals differ in the relative sophistication of their schemas for organizing and interpreting social stimuli (i.e., attributional complexity, or AC) and that AC has been linked to performance in social situations. In the present study, 420 employed students completed surveys for an investigation of the relationship between individual, work role, and job characteristics; AC; and job performance. Educa- tional level and major predicted AC, but leader-member exchange (LMX), decision latitude (DL), and socialhask complexity of the job did not. Contrary to expectations, social and task complexity did not interact with DL and LMX to predict AC. AC, DL, LMX, and educational level predicted job performance. Further, AC interacted with social complexity of the job to predict performance. The results suggest that AC may be both content and process based, and predictive of performance in certain jobs.

Research has indicated that individuals differ in the relative sophistication of their schemas for organizing and interpreting social stimuli (e.g., Fletcher, Danilovics, Fernandez, Peterson, & Reeder, 1986; Press, Crockett, & Delia, 1975; Weiss & Adler, 1981). Individuals also may vary with regard to domain- specific types of schemas. For example, Fletcher et al. found individual differences in attribution-oriented schemas (i.e., attributional complexity, or AC). AC has been associated with accuracy in interpersonal judgments (Fletcher, Reeder, & Bull, 1990; Fletcher, Rosanowski, Rhodes, & Lange, 1992) and social effectiveness (Funder & Harris, 1986). However, research has not identified how work-role characteristics might contribute to differences in AC. Further, no field research could be located that considered the effects of job complexity on the relationship between AC and performance. The present study examines (a) how

'Correspondence concerning this article should be addressed to Lois Tetrick, Department of Psy- chology, University of Houston, Houston, TX 77204-5341.

207

Journal of Applied Social Psychology, 2002, 32, 1, pp. 207-221. Copyright 0 2002 by V. H. Winston & Son, Inc. All rights reserved.

208 TOWNSEND ET AL.

subordinates’ educational training and perceptions of their decision latitude (DL) and leader-member exchange (LMX; Dansereau, Graen, & Haga, 1975; Graen & Cashman, 1975) relate to AC, and (b) the interaction of AC and job complexity in explaining individuals’ job performance.

Attributional complexity (AC) refers to an individual-difference variable that addresses the sophistication of attributional schemas (Fletcher et al., 1986) and is based on the construct of cognitive complexity (Vannoy, 1965). Cognitive complexity has been measured in numerous ways (Vannoy, 1965), but has been defined consistently as the degree to which individuals use discriminant dimensions when perceiving and evaluating social stimuli, and organize the connec- tions between the dimensions (i.e., integrate; Vannoy, 1965). More cognitively complex individuals use more dimensions, weigh alternatives, recognize relativ- ism, and use more complicated causal speculation during perception and evaluation (Fletcher et al., 1986; Higgins, King, & Mavin, 1982; Weiss & Adler, 1981). Cognitive complexity has been associated with academic persistence and achievement (Talbot, 1990) and effectiveness at handling job problems (Wofford, 1994). Further, Wofford found cognitive complexity to be positively associated with promotability in complex jobs and negatively associated with promotability in less complex jobs. Thus, cognitive complexity relates to performance when the task demands are facilitated by analysis.

Research has indicated that memory is category related and has shown the complexity of schemas to be domain specific (e.g., Alba & Hasher, 1983; Barsalou, 1992; Chi, Glaser, & Rees, 1982; Fletcher et al., 1986; Naus & Omstein, 1983; Ornstein & Naus, 1978; Tulving, 1984), as opposed to a general- ized personality trait. Chi et al., Naus and Ornstein, and Ornstein and Naus showed that experience and expertise with domain-specific stimuli were associated with increased schematic organization and interpretation. Consistent with this domain-specific approach, Fletcher et al. developed a measure of AC that targets the discrimination and integration of dimensions used to assign causality in social perception. Fletcher et al. suggested that AC might be highly related to the level of interest or motivation for understanding and explaining social behavior. Thus, based on experiential and motivational influences on schema complexity, one would expect that aspects of one’s education and work role, which facilitate these conditions, might contribute to AC. Educational characteristics likely associated with AC are level of education and major focus of study. Two such work-role characteristics are DL and LMX.

Educational Training

Educational training has been associated with AC (Fletcher, 1983; Fletcher et al., 1986). First, more advanced education might contribute to AC. Higher education provides training and experience in gathering, interpreting, and inte-

ATTRIBUTIONAL COMPLEXITY 209

grating information, thus practicing those processes involved in making complex attributions. Indeed, Fletcher reported that educational level was positively related to AC. Individuals with higher levels of education acknowledged more numerous, complex, abstract, and temporally distal causes for a social event (i.e., divorce) than did those with less education. Thus, the processes involved and developed in education are like those used when making complex attributions. Second, educational focus has been linked to AC as well (Fletcher et al., 1986). For example, Fletcher et al. found psychology students to be more attributionally complex than students from other disciplines. Fletcher noted that this relationship might be explained by knowledge and interest differences between students of various majors and the nature of AC. More specifically, psychology students may have a deeper understanding of interpersonal events than other students may. Also, those electing psychology as their educational focus may be more interested in interpersonal analysis than are other students. Thus, the content of education may contribute to AC because of domain-specific knowledge and interest.

Hypothesis I . Higher levels of education will be related to higher levels of attributional complexity.

Hypothesis 2. Students majoring in psychology will have higher levels of attributional complexity than will students majoring in other disciplines.

Decision Latitude

Larger amounts of DL may contribute to increased AC. Decision latitude (DL) is the degree to which incumbents are involved in the process of making nontrivial decisions (Scandura, Graen, & Novak, 1986). Degrees of DL range from none (i.e., under the direction of an autocratic supervisor) to input of ideas without making the final decision (e.g., consultation, collaboration), to enacting a decision-making role (i.e., delegation; Vroom & Yetton, 1973). Individuals who have more DL are likely to be recipients of more group-/organization-related information than those lower in DL because of role differences (Dansereau et al., 1975; Graen & Cashman, 1975; Vroom & Yetton, 1973). Because individuals with decision-making roles would need to seek, receive, categorize, prioritize, or weigh information and judgments, they would likely gain experience differentiat- ing and integrating information.

Occupation of a decision-making role might contribute to increased AC, as those individuals might generalize the decision-making strategies (i.e., differenti- ating and integrating information) to interpret interpersonal stimuli in addition to organizational stimuli. Further, those with DL in complex, social jobs (i.e.,

210 TOWNSEND ET AL.

involving social interaction) might show more AC than those in less socially complex jobs because of differences in experience. In other words, analytical skills that are used to understand and react to organizational stimuli could be used to analyze and react to interpersonal stimuli. One would expect that practice would develop these skills and that the skills might be applied in the context of varied stimuli. However, as expertise develops, one may become more proficient at understanding and reacting to certain types of information than other, less familiar types (e.g., Chi et al., 1982; Naus & Omstein, 1983; Omstein & Naus, 1978). Thus, someone practiced at organizing and interpreting social information might be more expert at these operations than are less practiced people.

Hyporhesis 3. The social and task complexity of the job will moderate the relation between decision latitude and attributional complexity.

Leader-Member Exchange

The quality of the supervisor-subordinate relationship (leader-member exchange, or LMX) might contribute to AC. Previous research (Dansereau et al., 1975; Graen & Cashman, 1975; Graen & Uhl-Bien, 1995; Wayne, Liden, & Sparrowe, 1994) has suggested that the quality of subordinates’ working relationships with their supervisors determines the degree to which subordinates have roles that allow more responsibility, autonomy, and growth opportunity. DL has been noted as a role characteristic on which subordinates differ, depending on their relationship with the supervisor (Dansereau et al., 1975; Graen & Cashman, 1975; Graen & Uhl-Bien, 1995; Scandura et al., 1986; Wakabayshi & Graen, 1984). Scandura et al. demonstrated that a subordinate’s perception of a good LMX was enough to create the impression that the subordinate had greater DL. As subordinates handle more complex work issues (a characteristic of high LMX; Graen & Uhl-Bien, 1995), they would likely become more practiced at organizing and interpreting information. To the extent that this information involves interpersonal issues (i.e., a more socially complex job), their analytical practice would be socially specific.

Hypothesis 4. The social and task complexity of the job will moderate the relation between leader-member exchange and attributional complexity.

Performance

AC might contribute to performance on jobs that require complex social interaction. AC has been associated with performance in social situations

ATTRIBUTIONAL COMPLEXITY 21 1

(Fletcher et al., 1990, 1992; Funder & Harris, 1986). Fletcher et al. (1 992) found that attributionally complex people were more accurate in assigning causes to others’ behavior. Funder and Harris reported a close relationship between AC and interpersonal effectiveness. Fletcher et al. (1990) found AC to positively affect performance in interpersonal judgments only when the task required in- depth information processing. Thus, AC is associated with performance of complex, interpersonal tasks. In the work context, one might expect that individuals with more AC would be more effective at handling interpersonal interactions because they might have a more sophisticated understanding of others’ patterns of behavior. In jobs where social interaction is not an essential or important part of the job (e.g., engineer, computer technician), one would not expect AC to facilitate effective performance. However, in jobs that involve ongoing social interaction and reciprocation (e.g., social worker, customer-service jobs), AC might facilitate effectiveness.

Further, one might expect that AC would contribute positively to performance when the tasks were complex and negatively when the tasks were simple. That is, the preference for analysis might make one more effective when solutions could be improved with more sophisticated processing. However, AC might not contribute or even detract from performance when solutions cannot be improved with increased analysis.

Hypothesis 5 . The social and task complexity of the job will moderate the relation between attributional complexity and job performance.

Method

Participants

Participants were 420 working students, who each received extra credit. The mean age was 24 years, and 65% (n = 273) were women. Of these students, 29% (n = 122) were freshmen and sophomores, 57% (n = 239) were juniors and seniors, and 14% (n = 59) were postbaccalaureate and graduate students; 30% (n = 126) indicated that they were presently working full time, and 70% (n = 294) were working part time. Average tenure with their respective employers was 2.3 years.

Measures

Attributional complexity (AC). AC was measured using Fletcher et al.’s (1986) 28-item scale. Coefficient alpha was .88. All items were rated on a 7-poht Likert-type response scale ranging from 0 (strongly disagree) to 6 (strongly agree).

212 TOWNSEND ET AL.

Decision latitude (DL). DL was measured using 1 1 items from Moch, Cammann, and Cooke (1983). Coefficient alpha was .88. A 5-point Likert-type response scale ranging from I (no say at all) to 5 (a very great deal ofsay) was used for these items.

Leader-member exchange (LMX). LMX was measured using seven items from Graen, Novak, and Sommerkamp (1 982). A 4-point Likert-type response scale was used, with varying response formats for the different items. Coefficient alpha was .87.

Job performance. Participants were asked to rate their own job performance. A 5-point Likert-type response scale ranging from 1 (consistently below expectations) to 5 (consistently exceeds expectations) was used.

Social complexity ofjob. Social complexity of the job was measured using four items from Harvey (1990). The items were introduced with “How frequently does your job require you to . . . ” and were completed with the following: (a) “depend on others to complete their work before you can complete your work?’; (b) “complete your work so that others can complete theirs?’; (c) “deal with conflicts between different work goals or projects assigned to you?’; and (d) “work with others on common tasks or projects?” A 5-point Likert-type response scale was used, ranging from 1 (practically never) to 5 (almost always). Coefficient alpha was .68.

Task complexity ofjob. Task complexity of the job was measured using five items from Harvey ( 1 990). These items were introduced with “HOW frequently does your job allow you to . . . ” and were completed with the following: (a) “learn new skills on your job?”; (b) “select the projects you work on?”; (c) “control your work pace or schedule of activities?”; (d) “use different skills?’; and (e) “produce an entirely finished product or perform a complete service?” A 5-point Likert-type response scale was used, ranging from 1 (practically never) to 5 (almost always). Coefficient alpha was .77.

Work status. Work status was measured using one item, Responses were coded 1 (fiull time) and 0 (part time).

Major Participants’ majors were measured using one item. Responses were coded 1 (psychology major) and 0 (other major).

Class standing. Class standing was measured with one item. Responses were coded 1 (freshman or sophomore), 2 (junior or senior), 3 (pastbaccalaureate and graduate student).

Results

Means, standard deviations, and zero-order correlations are presented in Table 1. AC was positively related to job performance (r = .13, p < .01) and positively related to school major and class standing ( r = .32 and .13, ps < .01, respectively). Job performance was positively related to most of the variables

Tabl

e 1

Des

crip

tive

Stat

istic

s and

Rel

iabi

litie

s of t

he S

cale

s

Inte

ritem

cor

rela

tions

Var

iabl

e M

SD

1

2 3

4 5

6 7

8 1.

Job

perf

orm

ance

4.

06

0.80

-

2. A

ttrib

utio

n co

mpl

exity

4.

06

0.81

.1

3**

.88

3. D

ecis

ion

latit

ude

2.63

0.

78

.25*

* .08

.88

4. L

eade

r-em

ber

exch

ange

1.

90

0.65

.2

8**

.06

.39*

* .8

7 5.

Soc

ial c

ompl

exity

2.

96

0.94

.1

2*

.08

.16*

* .0

3 .6

8 6.

Tas

k co

mpl

exity

3.

27

0.95

.1

8**

.07

SO**

.3

7**

.25*

* .7

7 7.

Wor

k st

atus

0.

30

0.46

.1

8**

.03

.26*

* .08

.20*

* .2

2**

-

8. M

ajor

0.

30

0.46

-.0

1 .3

2**

-.OO

.05

-.06

.03

-.09

-

.20*

* .0

4 9.

Cla

ss st

andi

ng

1.89

0.

63

.19*

* .1

3**

.13*

* .O

O .0

9 .0

2

Not

e. N

= 4

20. R

elia

bilit

y co

effic

ient

s are

repr

esen

ted

in th

e di

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als.

Wor

k st

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was d

umm

y co

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(1 =

full

time,

0 =

par

t tim

e),

ther

efor

e the

mea

n re

pres

ents

the p

ropo

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of f

ull-t

ime s

ubje

cts.

Majo

r: 1 =

psyc

holo

gy m

ajor,

0 =

othe

r. C

lass

stan

ding

: 1 =

fres

hman

, so

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2 =

juni

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enio

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stbac

cala

urea

te, g

radu

ate s

tude

nt.

*p < .0

5. *

*p <

.01.

Y u

214 TOWNSEND ET AL.

Table 2

Summary of Moderated Regression Analyses for Variabfes Predicting Attributional Complexity

Predictors Pa AR2

Step 1 Step 2

Step 3 Step 3 Step 3 Step 3 Step 4 Step 4

Work status Major Class standing Leader-member exchange (LMX) Decision latitude (DL) Social Task Social x LMX Social x DL Task x LMX Task x DL Social x Task x LMX Task x Social x DL

.oo . 00

.32** .13**

.lo*

.02

.04

.os

.O 1 .oo .oo . 00 . 00 .oo .oo

Note. N = 420. Work status: 1 = full time, 0 = part time. Major: 1 = psychology, 0 = other. Class standing: 1 = freshman, sophomore; 2 =junior, senior; 3 = postbaccalaureate, graduate student. aBeta coefficients are for the equation without the inclusion of the interaction terms. * p < .05. **p < .01.

(AC, DL, LMX, social and task complexity, work status, and class standing). As expected, DL and LMX were positively related (r = .39, p < .O 1). Complexity of the job, both on social and task dimensions, was positively related to DL (r = -16 and SO, p s < .01, respectively), but only task complexity was positively related to LMX (r = . 3 7 , p < .01).

Hypotheses 1 through 4 were tested using hierarchical moderated multiple regression in which AC was regressed on major, class standing, LMX, DL, social complexity, and task complexity while controlling for work status.2 Each of the cross-product terms reflecting the interactions of social and task complexity with DL and LMX was entered separately (Table 2). Academic major and class standing positively predicted AC (p = .32 and .lo, p s < .05, respectively) sup- porting Hypotheses 1 and 2 . However, none of the cross-product terms signifi- cantly increased squared multiple correlation. Contrary to Hypotheses 3 and 4, the complexity of the job did not moderate the relation of DL with AC, or of LMX with AC.

2Tests of the assumptions for regression analyses were conducted, and no violations were found.


Table 3

Summary of Moderated Regression Analyses for Variables Predicting Job Performance

Predictors P" AR2

Step 1 Work status .09 .03** Step 2 Major -.05 .12**

Class standing .14** Attributional complexity (AC) .lo* Social .05 Task .oo Decision latitude (DL) . l l Leader-member exchange (LMX) .22* *

Step 3 AC x Social .01* Step 3 AC x Task .oo Step 4 AC x Task x Social .oo Note. N = 420. Work status: I = full time, 0 = part time. Major: 1 = psychology, 0 = other. Class standing: 1 = freshman, sophomore; 2 =junior, senior; 3 = postbaccalaureate, graduate student. aBeta coefficients are for the equation without inclusion of the interaction terms. *p < .05. **p < .01.

To test whether social and task complexity moderated the relationship between AC and job performance, a hierarchical moderated regression analysis was conducted in which job performance was regressed on major, class standing, AC, social and task complexity, DL, and LMX while controlling for work status. The cross-product terms reflecting the interaction of social complexity and task complexity with AC were entered separately (Table 3). Social complexity of the job moderated the relationship between AC and job performance (AR2 = .O I , p < .05). However, the interaction was not in the direction hypothesized. As can be seen in Figure 1, the relationship between social complexity and job performance was stronger when AC was low than when AC was medium or high. This finding suggests that the level of AC does not seem to be as important a predictor of job performance when social complexity is high as compared to when social complexity is low.

Discussion

The present study investigated the relationship between perceived work role characteristics, educational training, AC, and job performance. More specifically,

216 TOWNSEND ET AL.

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it examined how employee education, and perceptions of complexity, DL, and LMX related to AC, and how AC interacted with job characteristics to predict performance. Contrary to our expectations, greater DL, LMX, and the task and social complexity of the job were not related to AC. However, as predicted, higher levels of education were associated with AC, and psychology majors reported higher levels of AC than did those majoring in other disciplines. Thus, consistent with Fletcher (1983; Fletcher et al., 1986), individual differences in AC appear to be associated with educational training.

Characteristics of the job do not appear to be related to AC, suggesting that the decision-making processes involved in job roles might not be salient enough to relate to AC. Further, people may pick transitional jobs with little attention to a fit with their information-processing strengths (i.e., attributional schemas). Yet, when careers are selected or when employees stay in a given position for longer periods, stronger relationships between the job and AC may emerge. Of course, we only included a few characteristics of jobs and roles at work. Future research might benefit from including other aspects of the work environment, as well as a work-identity measure Qob vs. career) and position tenure.

We did find that AC was related to self-reports of job performance. In fact, employee level of education, work status, social and task complexity of the job, DL, and LMX also were related to job performance. However, only AC, level of education, DL, and LMX predicted job performance. There was also support for an interaction between AC and social complexity of the job; however, the nature of the interaction was contrary to what was expected. People who were higher on

ATTRIBUTIONAL COMPLEXITY 21 7

AC had a weaker relationship between social complexity and job performance than did people who were low on AC. These findings are consistent with Fletcher et al. (1990, 1992) and Funder and Harris (1986), who proposed that AC seems to be a predictor of job performance under some circumstances, although the specific circumstances need further exploration. This is especially the case in light of the relatively weak effect size (the interaction accounted for 0.9% of the vari- ance) and may not be of practical significance.

The findings of this study suggest that one’s formal training is more related to AC than one’s job role experience. Perhaps with more education, one develops more complex reasoning (Fletcher, 1983). The strong relation between psychology majors and AC, replicating that found by Fletcher et al. (1986), is interesting. One interpretation might be that psychology majors’ training increases the sophistication of their causal schemas for interpersonal events. Alternatively, it may be that people with higher levels of AC are attracted to psychology because of their interest in human behavior. Clearly, this study cannot rule out either explanation. Additional research, which would allow comparisons of specific majors as well as class standing, would be helpful here, as would longitudinal studies.

It is interesting that the only two significant predictors of AC found in this study were major (psychology vs. all other majors) and class standing. This suggests that AC may be both process and content based. That is, individuals with higher levels of education had relatively more sophistication in their causal attributions for interpersonal perceptions. This may indicate that the experience of analyzing information is more crucial to AC than is the content of the information. In other words, the decision-making practice, rather than the content of the decisions, is important for some aspects of AC. This argues for process-based learning of AC, rather than content-based learning.

However, psychology majors reported higher levels of AC than did people with majors in other disciplines, and this effect was stronger than that for class standing. This finding suggests that the nature or content of the information involved in the training is important to the development of AC.

Given the relation between AC and job performance, it would appear that the development of AC may be very important, especially in certain types of jobs (e.g., those that involve working with other people or decision making concerning other people). People with higher levels of AC may bring in more sources of information in analyzing a situation. Further, they appear to be able to integrate the information and gain a more thorough understanding of the situation. This may lead them to adopt more appropriate strategies than individuals with lower levels of AC. As past research has demonstrated, higher quality strategies lead to better performance (e.g., Cervone et al., 1991; DeShon & Alexander, 1996; Mitchell & Silver, 1990).

With regard to the study’s limitations, first, our participants were a conve- nience sample of working college students. However, all of the participants had

218 TOWNSEND ET AL.

some form of job experience, and their jobs were very heterogeneous. A second limitation concerns the single-item self-report measure of performance. Research has shown that self-reported performance can be a valid and accurate measure of job performance (Farh et al., 1988; Fox & Dinur, 1988). However, it is possible that people with high self-regard (Taylor & Brown, 1988) or ego-defensive biases rated their performance higher than did those with low self-regard or who lack such biases. Future studies that include self-reported performance might overcome this ambiguity by measuring self-referent constructs (e.g., self-esteem, self-regard, ego-defensive biases) and controlling for their relationship with reported performance. Also, Sackett and Larson (1990) and Wanous, Reichers, and Hudy (1997) argued that single-item measures might be valid, given that the item is straightforward and adequately addresses the construct of interest. Because the item in the present study concerned a global, bottom-line assessment of the degree to which one meets job-performance expectations, our measure seems relatively specific and thus adequate.

In summary, the results suggest that individual, job, and work role characteristics are related to AC and job performance. Further, training that may afford experience in information processing was related to increased processes of discrimination, as reflected by reported AC. Also, training that involves interpersonal analysis was related to reports of increased causal analysis. AC may be important in explaining performance because it might predict differences in strategy formation. These differences in strategy formation might lead to differences in performance. Greater AC might lead to a better understanding of the situation, resulting in the adoption of a more appropriate strategy and thus better performance. Finally, AC was a predictor of job performance, especially for those in less socially complex jobs.

AC needs to be studied further. First, research needs to examine how decision-making experiences impact strategy formation. Second, future investiga- tions might test the possibility of a curvilinear relationship between AC and job performance. That is, too much AC might lead to perseveration and thus hinder performance. Third, an analysis that juxtaposes temporary or transitional environmental fit with long-term environmental fit would be interesting. People who have to work and study could generate data on attributional/social complexities in both work environments, A comparison of their perceptions would help to answer some questions about adapting one's attributionalhocial complexity skills to the work or finding work that meets with one's level of attributional/social complexity.

References

Alba, 1. W., & Hasher, L. (1983). Is memory schematic? Psychological Bulletin, 93,203-23 1.

ATTRIBUTIONAL COMPLEXIN 219

Barsalou, L. W. (1992). Cognitive psychology: An overview for cognitive scien- tists. Hillsdale, NJ: Lawrence Erlbaum.

Cervone, D., Jiwani, N., & Wood, R. (1991). Goal setting and the differential influence of self-regulatory processes on complex decision-making performance. Journal of Personality and Social Psychology, 61, 257-266.

Chi, M. T., Glaser, R., & Rees, E. (1982). Expertise in problem solving. In R. Sternberg (Ed.), Advances in the psychology of human intelligence (Vol. 1 , pp. 17-76). Hillsdale, NJ: Lawrence Erlbaum.

Dansereau, F., Graen, G., & Haga, W. (1975). A vertical dyad linkage approach to leadership within formal organizations: A longitudinal investigation of the role making process. organizational Behavior and Human Performance, 13,46-78.

DeShon, R. P., & Alexander, R. A. (1996). Goal setting effects on implicit and explicit learning of complex tasks. Organizational Behavior and Human Decision Processes, 65, 18-36.

Farh, J. L., Werbel, J. D., & Bedeian, A. G. (1988). An empirical investigation of self-appraisal-based performance evaluation. Personnel Psychology, 4 I , 141- 156.

Fletcher, G. J. (1983). The analysis of verbal explanations for marital separation: Implications for attribution theory. Journal of Applied Social Psychology, 13,

Fletcher, G. J., Danilovics, P., Fernandez, G., Peterson, D., & Reeder, G. D. ( 1986). Attributional complexity: An individual differences measure. Journal of Personality and Social Psychology, 51, 875-884.

Fletcher, G. J., Reeder, G. D., & Bull, V. (1990). Bias and accuracy in attitude attribution: The role of attributional complexity. Journal of Experimental Social Psychology, 26,275-288.

Fletcher, G. J., Rosanowski, J., Rhodes, G., & Lange, C. (1992). Accuracy and speed of causal processing: Experts versus novices in social judgment. Jour- nal of Experimental Social Psychology, 28,320-338.

Fox, S., & Dinur, Y. (1988). Validity of self-assessment: A field evaluation. Per- sonnel Psychology, 41,581-592.

Funder, D. C., & Harris, M. J. (1986). On the several facets of personality assessment: The case of social acuity. Journal of Personality, 54, 528-550.

Graen, G., & Cashman, J. (1 975). A role-making model of leadership in formal organizations: A developmental approach. In J. G. Hunt & L. L. Larson (Eds.), Leadership frontiers (pp. 143-165). Kent, OH: Kent State University Press.

Graen, G. B., Novak, M. A., & Sommerkamp, P. (1982). The effects of leader- member exchange and job design on productivity and satisfaction: Testing a dual attachment model. Organizational Behavior and Human Peformance,

Graen, G. B., & Uhl-Bien, M. (1995). Relationship-based approach to leadership: Development of leader-member exchange (LMX) theory of leadership over

245-258.

30, 109-131.

220 TOWNSEND ET AL.

25 years: Applying a multi-level multi-domain perspective. Leadership Quarterly, 6,219-247.

Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Decision Mak- ing Processes, 16,250-279.

Harvey, R. J. (1 990). Common metric questionnaire. San Antonio, TX: Harcourt Brace Jovanovich.

Higgins, E. T., King, G. A., & Mavin, G. H. (1982). Individual construct accessi- bility and subjective impressions and recall. Journal of Personality and Social Psychologv, 43,35-47.

Mitchell, T. R., & Silver, W. S. (1990). Individual and group goals when workers are interdependent: Effects on task strategies and performance. Journal of Applied Psychology, 75, 185- 193.

Moch, M., Cammann, C., & Cooke, R. A. (1983). Organizational structure: Mea- suring the distribution of influence. In S. E. Seashore, E. E. Lawler, P. H. Mirvis, & C. Cammann (Eds.), Assessing organizational change: A guide to metho&, measures, andpractices (pp. 177-199). New York, NY: John Wiley & Sons.

Naus, M. J., & Omstein, P. A. (1983). Development ofmemory strategies: Anal- ysis, questions, and issues. In M. T. H. Chi (Ed.), Trends in memory development (Vol. 9, pp. 1-30). New York, N Y Karger.

Omstein, P. A., & Naus, M. J. (1978). Rehearsal processes in children’s memo- ries. In P. Omstein (Ed.), Memory development in children (pp. 69-101). Hillsdale, NJ: Lawrence Erlbaum.

Press, A. N., Crockett, W. H., & Delia, J. G. (1975). Effects of cognitive complexity and of the perceiver’s set upon the organization of memory. Journal of Personality and Social Psychology, 32, 865-872.

Sackett, P. R., & Larson, J. R., Jr. (1990). Research strategies and tactics. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed., Vol. 1, pp. 419-489). Palo Alto, CA: Consulting Psychologist Press.

Scandura, T. A., Graen, G. B., & Novak, M. A. (1986). When managers decide not to decide autocratically: An investigation of leader-member exchange and decision influence. Journal of Applied Psychology, 71,579-584.

Talbot, G. L. (1990). Personality correlates and personal investment of college students who persist and achieve. Journal of Research and Development in Education, 24,53-57.

Taylor, S. E., & Brown, J. D. (1988). Illusion and well-being: A social psychological perspective on mental health. Psychological Bulletin, 103, 193-210.

Tulving, E. (1984). PrCcis of elements of episodic memory. The Behavioral and Brain Sciences, 7,223-268.

Vannoy, J. S. (1965). Generality of cognitive complexity-simplicity as a personality construct. Journal of Personality and Social Psychology, 2,385-396.


Vroom, V. H., & Yetton, P. W. (1 973). Leadership and decision making. Pitts- burgh, PA: University of Pittsburgh Press.

Wakabayashi, M., & Graen, G. (1984). The Japanese career progress study: A seven year follow up. Journal of Applied Psychology, 69,603-614.

Wanous, J. P., Reichers, A. E., & Hudy, M. J. (1997). Overall job satisfaction: How good are single-item measures? Journal of Applied Psychology, 82,247- 252.

Wayne, S. J., Liden, R. C., & Sparrowe, R. T. (1994). Developing leader- member exchanges: The influence of gender and ingratiation. American Behavioral Scientist, 37,697-7 14.

Weiss, H. M., & Adler, S. (1981). Cognitive complexity and the structure of implicit leadership theories. Journal of Applied P.yychology, 66,69-78.

Wofford, J. C. (1994). An examination of the cognitive processes used to handle employee job problems. Academy of Management Journal, 37, 180-1 92.

attributional complexity: a link between training, job complexity, decision latitude,...

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