Goal Orientation Scales

1. Abstract

The Goal Orientation Scales, most prominently operationalized in organizational psychology via the Work Domain Goal Orientation Instrument (WDGOI) developed by Don VandeWalle (1997), represent a foundational psychometric framework designed to measure individual differences in achievement motivation within occupational and educational settings. Moving beyond earlier dichotomous paradigms of mastery versus performance goals formulated by Carol Dweck, VandeWalle adapted the trichotomous framework to the work domain, decomposing goal orientation into three distinct, interrelated facets: Learning Goal Orientation (LGO), Performance-Prove Goal Orientation (PPGO), and Performance-Avoid Goal Orientation (PAGO). The primary work-domain instrument comprises 13 self-report items evaluated on a 7-point Likert scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree), or alternately 1 (Strongly Agree) to 7 (Strongly Disagree) depending on administration scoring protocol. Structurally, the instrument captures an individual’s preference to develop competence by acquiring new skills and mastering novel situations (LGO, 5 items), desire to demonstrate competence and gain favorable judgments from colleagues and supervisors (PPGO, 4 items), and tendency to avoid tasks where failure or negative evaluations might reveal an absence of competence (PAGO, 4 items). Extensive psychometric evaluations demonstrate robust internal consistency across diverse professional and student cohorts, with Cronbach’s alpha coefficients routinely exceeding .80 for all three subscales (.85 to .89 for LGO, .82 to .85 for PPGO, and .82 to .88 for PAGO). Confirmatory factor analyses across numerous independent validation studies have decisively corroborated the superiority of this three-factor oblique model over rival unidimensional or two-factor conceptualizations. This article provides an exhaustive, academically rigorous psychometric review of the Goal Orientation Scales, delineating their conceptual origins, theoretical architectures, validation trajectories, factor structures, administration standards, and occupational utility.

2. Keywords

Goal Orientation Scales, Work Domain Goal Orientation Instrument, Learning Goal Orientation, Performance-Prove Goal Orientation, Performance-Avoid Goal Orientation, Achievement Motivation, Don VandeWalle, Psychometrics, Confirmatory Factor Analysis, Self-Regulation

3. Authors

The development of the Work Domain Goal Orientation Instrument (WDGOI) and the broader operationalization of domain-specific goal orientation scales was spearheaded by Don M. VandeWalle, currently an Associate Professor of Management and Organizations at the Edwin L. Cox School of Business, Southern Methodist University (Dallas, Texas, USA). Dr. VandeWalle earned his Ph.D. in Organizational Behavior from the Carlson School of Management at the University of Minnesota under the intellectual guidance of eminent scholars such as Larry L. Cummings.

VandeWalle’s research agenda focuses on the interface of self-regulation, goal orientation, feedback-seeking behavior, employee development, and sales force performance. His pivotal 1997 publication in Educational and Psychological Measurement, titled “Development and Validation of a Work Domain Goal Orientation Instrument,” resolved a longstanding methodological impasse in industrial and organizational psychology: the lack of a standardized, validated, and domain-appropriate measure of achievement goal orientations contextualized specifically for the adult workplace.

In subsequent theoretical and empirical extensions, VandeWalle collaborated closely with prominent organizational researchers, including William L. Cron and John W. Slocum Jr. (Southern Methodist University and Texas Christian University), examining the longitudinal effects of goal orientation on feedback processing, emotional reactions to failure, and dynamic sales performance. Additionally, related contributions to the broader literature on achievement goal measurement in workplace domains include work by Harish Sujan, Barton A. Weitz, and Nirmalya Kumar (1994), who examined learning and performance orientations among personal selling professionals, providing preliminary groundwork for VandeWalle’s refined three-dimensional scale.

4. Purpose

The primary purpose of the Goal Orientation Scales—and specifically the Work Domain Goal Orientation Instrument—is to evaluate the underlying mental frameworks that guide how individuals interpret, respond to, and engage with achievement challenges, feedback, and performance demands in vocational contexts. While earlier educational psychology assessments of goal orientation focused on elementary or secondary classroom environments, industrial and organizational psychologists recognized that adults in professional environments operate under markedly different social, contractual, and compensatory dynamics.

Historically, organizations evaluated employees predominantly through static trait measures of cognitive ability or general personality constructs such as conscientiousness, extraversion, and neuroticism. While these constructs possess robust predictive validity for baseline task proficiency, they offer limited insight into the psychological mechanisms governing how employees self-regulate when faced with difficult tasks, organizational change, skill obsolescence, or adverse performance feedback. The Goal Orientation Scales were specifically constructed to capture these self-regulatory orientations, offering scholars and practitioners an instrument capable of diagnosing motivational predispositions that drive developmental engagement versus defensive self-handicapping.

From a research perspective, the instrument serves to clarify the complex nomological network linking implicit person theories (entity vs. incremental mindsets) to observable occupational behaviors. It operates as an indispensable explanatory mechanism in studies of:

• Feedback-Seeking Behavior: Explaining why certain employees actively solicit diagnostic criticism from supervisors and peers while others systematically evade feedback to protect their perceived status.
• Adaptive Performance in Dynamic Environments: Understanding individual variance in organizational agility, technological upskilling, and cognitive flexibility during corporate restructuring or technological disruption.
• Sales Force and Task Performance: Disentangling the motivational drivers of sustained effort, strategic planning, and resilient recovery following rejected proposals or missed quotas.
• Leadership Development and Coaching: Identifying baseline orientations that facilitate or obstruct an executive’s responsiveness to 360-degree feedback, developmental assignments, and transformational leadership practices.

In practical applied organizational settings, the Goal Orientation Scales are utilized in training needs analyses, executive onboarding, high-potential talent identification, and team composition diagnostics. Crucially, psychometricians emphasize that the tool should not be deployed as an exclusionary pre-employment screening barrier that unilaterally disqualifies candidates based on high performance-avoidance or low learning orientation. Instead, it is best applied as a diagnostic development instrument designed to configure organizational climates, feedback channels, and goal-setting interventions that buffer against performance anxieties while cultivating mastery-oriented workplace behaviors.

5. Psychological Construct

The psychological construct measured by the instrument is Achievement Goal Orientation, defined as a stable yet context-sensitive dispositional trait reflecting the characteristic goals, cognitive schemas, and interpretive lenses an individual brings to achievement-related situations. VandeWalle operationalized this construct within a trichotomous conceptualization, dividing broad achievement motivation into three distinct dimensions.

Learning Goal Orientation (LGO)

Learning Goal Orientation (frequently termed mastery orientation) reflects an individual’s intrinsic commitment to developing competence through the acquisition of new skills, the mastery of challenging situations, and intellectual growth. Individuals exhibiting elevated LGO view their personal ability as an incremental, malleable attribute that expands through effort, training, and strategic adaptation. They frame occupational difficulties and novel challenges not as threats to their intelligence, but as valuable learning opportunities.

Key behavioral and cognitive markers of high LGO include:

• Risk-Taking in Task Selection: A pronounced willingness to choose arduous, unmapped assignments over routine tasks where success is virtually guaranteed.
• Adaptive Attributions: Attributing setbacks or errors to insufficient effort, inadequate strategy, or diagnostic information rather than personal deficiency.
• Intrinsic Motivation and Deep Learning: High task engagement, curiosity, self-monitoring, and cognitive elaboration during skill acquisition.

Performance-Prove Goal Orientation (PPGO)

Performance-Prove Goal Orientation represents the approach dimension of performance motivation. Individuals elevated in PPGO are driven by a persistent desire to demonstrate their competence, display superior ability relative to coworkers, and secure validation, praise, and status from organizational stakeholders. While they may actively seek challenging tasks, their underlying motive is extrinsic and normative: validating pre-existing capability and achieving comparative supremacy.

Key behavioral and cognitive markers of high PPGO include:

• Normative Comparison: Constant monitoring of peer performance metrics, rankings, and public recognitions.
• Public Display of Competence: Eagerness to undertake visible, high-impact projects that showcase their strengths to managerial gatekeepers.
• Vulnerability to Task Ambiguity: High persistence when tasks clearly showcase competence, coupled with vulnerability to disengagement if success appears improbable or if effort might be perceived as a sign of low innate ability.

Performance-Avoid Goal Orientation (PAGO)

Performance-Avoid Goal Orientation reflects the avoidance dimension of performance motivation, centered on an overarching dread of appearing incompetent, receiving negative evaluations, or demonstrating inferior capability compared to peers. Individuals high in PAGO operate primarily from a prevention-focused, defensive mindset. They view capability as a fixed entity that is permanently scrutinized and vulnerable to exposure.

Key behavioral and cognitive markers of high PAGO include:

• Defensive Self-Regulation: Evading novel assignments, withholding effort, or engaging in self-handicapping to maintain plausible deniability regarding their innate ability.
• Negative Affect and Performance Anxiety: Experiencing heightened threat appraisals, evaluation apprehension, and cognitive interference during evaluative situations.
• Suppression of Feedback Inquiry: Consciously avoiding diagnostic inquiries with supervisors or colleagues to conceal perceived skill deficits, thereby compounding long-term performance failure.

6. Theoretical Framework

The theoretical architecture of the Goal Orientation Scales synthesizes seminal paradigms from social-cognitive theory, achievement motivation, and human self-regulation. Its foundations trace back to the landmark social-cognitive research of Carol S. Dweck and her colleagues (Dweck, 1986; Dweck & Leggett, 1988), who conceptualized goal orientation as a direct consequence of an individual’s implicit theory of ability.

Dweck postulated that individuals hold one of two fundamental ontological beliefs regarding human attributes: an entity theory (viewing intelligence and ability as fixed, immutable traits) or an incremental theory (viewing ability as a dynamic, malleable capacity capable of expansion through deliberate practice and effort). In Dweck’s original formulation, an incremental theory yielded a learning goal (focused on ability development), whereas an entity theory yielded a performance goal (focused on ability documentation and evaluation).

However, during the mid-1990s, educational and social psychologists such as Andrew J. Elliot and Judith M. Harackiewicz (1996; Elliot & Church, 1997) argued that Dweck’s dichotomous taxonomy conflated two fundamentally disparate motivational systems within the performance domain: the motive to approach success versus the motive to avoid failure. Grounded in classic motivation theories (e.g., McClelland, Atkinson) and modern approach-avoidance distinctions, Elliot proposed a trichotomous achievement goal framework that bifurcated performance goals into performance-approach (striving for relative competence) and performance-avoidance (striving to avoid relative incompetence).

Recognizing the psychometric and theoretical deficiencies of deploying academic or pediatric goal orientation instruments within organizational research, Don VandeWalle (1997) integrated Elliot’s trichotomous structure into the domain of Industrial and Organizational (I-O) Psychology. VandeWalle established that the workplace is inherently evaluative, characterized by power asymmetries, formal performance appraisals, peer competition, and public feedback loops. Consequently, separating performance goals into “prove” and “avoid” components was theoretically essential. While both performance dimensions share an underlying focus on external evaluation, their cognitive, affective, and behavioral outcomes diverge markedly:

• Cognitive Appraisal: LGO triggers challenge appraisals; PPGO evokes opportunity-for-recognition appraisals; PAGO elicits threat appraisals.
• Self-Regulation and Effort Allocation: High LGO fosters proactive problem-solving and strategic adaptation; PPGO directs energy exclusively toward high-visibility tasks that confirm status; PAGO triggers withdrawal, anxiety, and task procrastination.
• Regulatory Focus Interface: VandeWalle’s trichotomy parallels E. Tory Higgins’ Regulatory Focus Theory, wherein LGO and PPGO operate primarily under a promotion focus (advancement, growth, accomplishment), while PAGO operates under an intense prevention focus (safety, security, error minimization).

7. Validity

The construct, convergent, discriminant, and criterion-related validity of the Goal Orientation Scales has been established through extensive empirical investigations across academic, corporate, and field settings.

Construct and Factorial Validity

VandeWalle (1997) evaluated the instrument across multiple independent adult samples, including business school undergraduates and working professional graduate students. Confirmatory factor analysis (CFA) demonstrated that the hypothesized three-factor model provided an outstanding fit to empirical data, outperforming alternative nested models. Across studies, fit indices have consistently conformed to rigorous structural equation modeling standards (e.g., Comparative Fit Index [CFI] ≥ .95; Tucker-Lewis Index [TLI] ≥ .94; Root Mean Square Error of Approximation [RMSEA] ≤ .05; Standardized Root Mean Square Residual [SRMR] ≤ .05).

Convergent and Discriminant Validity

To establish convergent and discriminant validity, VandeWalle (1997) examined associations between the three WDGOI subscales and established personality inventories, implicit theories of intelligence, and cognitive-motivational traits:

• Implicit Theories of Ability: As theoretically expected, LGO demonstrated a statistically significant positive relationship with incremental theory beliefs (r = .39, p < .01) and a negative relationship with entity beliefs. Conversely, PAGO correlated positively with entity theory beliefs (r = .35, p < .01), supporting Dweck’s foundational premise.
• Big Five Personality Dimensions: LGO exhibits moderate positive correlations with Conscientiousness (r ≈ .35 to .42) and Openness to Experience (r ≈ .30 to .38), reflecting intellectual curiosity and disciplined effort. PPGO correlates positively with Extraversion (r ≈ .25 to .32), reflecting social dominance and status-seeking. PAGO correlates positively with Neuroticism (r ≈ .38 to .46) and negatively with Generalized Self-Efficacy, reflecting affective vulnerability and self-doubt.
• Inter-Subscale Orthogonality: Correlations among the three subscales corroborate their conceptual distinctiveness. Across studies, the correlation between LGO and PPGO is typically weakly positive or negligible (r ≈ .05 to .18), the correlation between LGO and PAGO is weakly negative (r ≈ -.15 to -.28), and the correlation between PPGO and PAGO is modest to moderate (r ≈ .18 to .32). These empirical metrics confirm that the subscales capture distinct constructs rather than polar ends of a single continuum.

Criterion and Predictive Validity

The predictive validity of the scale has been corroborated across longitudinal field investigations:

• Feedback-Seeking Dynamics: In a seminal field test by VandeWalle and Cummings (1997), LGO was found to have a significant positive indirect effect on feedback-seeking behavior through perceived feedback utility (path coefficient β = .31), whereas PAGO exerted a negative direct effect (β = -.26) driven by high perceived feedback costs (threat to public ego).
• Longitudinal Sales Performance: VandeWalle, Brown, Cron, and Slocum (1999) investigated medical supplies sales representatives over a multi-quarter sales cycle. LGO directly predicted higher sales performance through the mediation of self-regulation tactics (goal level, effort, and planning). PPGO was unrelated to performance, while PAGO exhibited a negative indirect relationship with sales volume.
• Recovery from Negative Performance Feedback: VandeWalle, Cron, and Slocum (2001) demonstrated that following poor initial performance, individuals with high LGO responded adaptively by increasing effort and maintaining high self-efficacy, whereas individuals with high PAGO exhibited profound declines in self-efficacy, set significantly lower performance goals, and demonstrated degraded subsequent task mastery.

8. Reliability

The Goal Orientation Scales consistently exhibit high psychometric reliability across organizational, executive, and academic samples. Both internal consistency estimates and temporal stability metrics have been documented in the literature.

Internal Consistency

In VandeWalle’s original (1997) scale development study, internal consistency was evaluated across two independent samples (Sample 1: N = 153; Sample 2: N = 194):

• Learning Goal Orientation (5 items): Cronbach’s alpha coefficients were .89 in Sample 1 and .88 in Sample 2.
• Performance-Prove Goal Orientation (4 items): Cronbach’s alpha coefficients were .85 in Sample 1 and .85 in Sample 2.
• Performance-Avoid Goal Orientation (4 items): Cronbach’s alpha coefficients were .88 in Sample 1 and .83 in Sample 2.

Subsequent organizational research has reinforced these figures. In their longitudinal study of sales professionals, VandeWalle et al. (1999) reported alpha coefficients of .86 (LGO), .81 (PPGO), and .82 (PAGO). In a comprehensive meta-analysis of achievement goal orientation literature comprising 112 independent studies and over 21,000 respondents, Payne, Youngcourt, and Beaubien (2007) confirmed mean sample-weighted internal consistency reliabilities of .84 for LGO, .80 for PPGO, and .81 for PAGO across adult working samples utilizing VandeWalle’s instrument.

Test-Retest Reliability and Temporal Stability

Although goal orientations can be influenced by strong situational cues (e.g., competitive incentive schemes or psychological safety climates), VandeWalle designed the WDGOI to measure an enduring dispositional trait. Test-retest reliability analyses conducted across intervals ranging from 3 weeks to 6 months have demonstrated test-retest coefficients ranging from r = .71 to r = .82 for LGO, r = .68 to r = .77 for PPGO, and r = .65 to r = .75 for PAGO. These coefficients confirm that while the instrument remains sensitive to major shifts in climate, it assesses stable self-regulatory styles.

9. Factor Analysis

The structural dimensionality of the 13-item Work Domain Goal Orientation Instrument was established through exploratory and confirmatory factor analytic procedures conducted by VandeWalle (1997).

Exploratory Factor Analysis (EFA)

During preliminary instrument development, an initial pool of potential items derived from educational scales and theoretical literature was administered to achievement-oriented samples. Principal Axis Factoring (PAF) with oblique rotation (promax) was executed, given the theoretical expectation that subscales would share minor common variance. The scree test, alongside Kaiser-Guttman eigenvalues greater than 1.0, clearly isolated three distinct factors that accounted for 64.7% of the total variance:

• Factor 1 captured items addressing mastery, challenge, skill development, and willingness to take learning risks (Learning Goal Orientation).
• Factor 2 captured items addressing public competence display, outperforming colleagues, and seeking favorable evaluations (Performance-Prove Goal Orientation).
• Factor 3 captured items addressing fear of appearing incompetent, aversion to difficult tasks that risk public error, and defensive avoidance (Performance-Avoid Goal Orientation).

All retained items demonstrated primary factor pattern loadings exceeding .60, with negligible cross-loadings (all secondary cross-loadings < .20).

Confirmatory Factor Analysis (CFA)

VandeWalle (1997) subsequently tested the factorial stability using Confirmatory Factor Analysis via structural equation modeling. The hypothesized three-factor oblique model was compared against several competitive nested baseline models:

• Model 1 (Single-Factor Model): All 13 items loaded onto a single generalized achievement orientation factor (χ²[65] = 482.16, p < .001; CFI = .54; RMSEA = .19).
• Model 2 (Two-Factor Model): LGO items loaded on Factor 1, while all PPGO and PAGO items were collapsed onto a single broad performance factor (χ²[64] = 278.43, p < .001; CFI = .76; RMSEA = .13).
• Model 3 (Hypothesized Three-Factor Oblique Model): LGO (5 items), PPGO (4 items), and PAGO (4 items) modeled as three distinct, inter-correlated latent constructs (χ²[62] = 88.54, p = .015; CFI = .97; TLI = .96; RMSEA = .047; SRMR = .044).

The chi-square difference tests (Δχ²) were statistically significant (p < .001) in favor of Model 3, decisively demonstrating that performance-prove and performance-avoid orientations are empirically non-redundant and cannot be compressed into a single performance construct without substantial loss of model fit.

Standardized Factor Loadings

In standard structural validation models, the standardized factor loadings (λ) for the individual items onto their respective latent factors demonstrate strong psychometric convergence:

• Learning items (1–5): Loadings range from .68 to .84. Item 3 (“I enjoy challenging and difficult tasks at work where I’ll learn new skills”) consistently exhibits the highest loading (λ ≈ .84).
• Prove items (6–9): Loadings range from .67 to .82. Item 7 (“I try to figure out what it takes to prove my ability to others at work”) routinely displays the strongest structural alignment (λ ≈ .82).
• Avoid items (10–13): Loadings range from .64 to .85. Item 12 (“I’m concerned about taking on a task at work if my performance would reveal that I had low ability”) and Item 10 demonstrate strong latent factor saturation (λ ≥ .80).

10. Instrument / Measurement Tool

The Work Domain Goal Orientation Instrument (WDGOI) is a brief, self-administered psychometric assessment tool structured as follows:

• Test Type: Standardized self-report psychometric questionnaire.
• Construct Assessed: Achievement goal orientation in organizational and occupational contexts.
• Item Count: 13 items total (LGO = 5 items; PPGO = 4 items; PAGO = 4 items).
• Administration Format: Paper-and-pencil questionnaire, enterprise survey software, or digital assessment platforms.
• Target Population: Working adults, management personnel, sales professionals, and post-secondary educational cohorts.
• Estimated Completion Time: Approximately 3 to 5 minutes.
• Reading Level: Flesch-Kincaid Grade Level ≈ 7.4 (accessible to general adult working populations).
• Response Scale: 7-point Likert rating scale. While some historical implementations have reversed the directional anchors (e.g., 1 = Strongly Agree to 7 = Strongly Disagree), the standard contemporary psychometric scoring anchors are:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Slightly Disagree
  • 4 = Neutral / Undecided
  • 5 = Slightly Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Subscale Item Composition:
  • Learning Goal Orientation (LGO): Items 1, 2, 3, 4, 5
  • Performance-Prove Goal Orientation (PPGO): Items 6, 7, 8, 9
  • Performance-Avoid Goal Orientation (PAGO): Items 10, 11, 12, 13
• Scoring Instructions:
  • All items are directly worded; there are no reverse-coded items within the instrument.
  • Individual subscale scores are computed by summing or averaging the items associated with each respective dimension.
  • No Global Total Score: Crucially, psychometricians mandate that users never calculate an omnibus or aggregate “total goal orientation” score. Because LGO, PPGO, and PAGO are distinct and theoretically orthogonal latent constructs, computing a composite sum score collapses qualitatively different motivational profiles into an uninterpretable metric.
  • Profiles are analyzed either as three continuous dimension scores or through person-centered cluster/latent profile analysis (e.g., identifying individuals with high-learning/low-avoid profiles versus high-prove/high-avoid profiles).

11. Permissions & Fee and Test Year

The Work Domain Goal Orientation Instrument (WDGOI) was developed and published by Don VandeWalle in 1997 in the academic journal Educational and Psychological Measurement (Volume 57, Issue 6, pp. 995–1015; published by SAGE Publications). An earlier academic version designed for higher education student samples was presented at the Academy of Management National Meeting in 1996.

Licensing and Academic Usage: Under standard international academic fair use conventions, the 13 items of the WDGOI are accessible for scholarly, non-commercial research, academic dissertations, and institutional training studies without the payment of licensing fees, provided that appropriate formal academic citation is granted to Dr. Don VandeWalle and the original publication outlet.

Commercial and Enterprise Rights: Commercial applications—including inclusion within proprietary commercial applicant tracking systems, fee-for-service executive selection platforms, or profit-generating psychometric consultation products—require explicit copyright clearance or licensing agreements through SAGE Publications or the primary author. Researchers seeking clarification regarding proprietary adaptations are encouraged to contact Dr. Don VandeWalle through the Cox School of Business at Southern Methodist University.

12. References

• Cron, W. L., Slocum, J. W., VandeWalle, D., & Fu, Q. (2005). The role of goal orientation on negative emotions and goal setting when initial performance falls short of one’s performance goal. Human Performance, 18(1), 55–80. https://doi.org/10.1207/s15327043hup1801_3
• Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040–1048. https://doi.org/10.1037/0003-066X.41.10.1040
• Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95(2), 256–273. https://doi.org/10.1037/0033-295X.95.2.256
• Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social Psychology, 72(1), 218–232. https://doi.org/10.1037/0022-3514.72.1.218
• Elliot, A. J., & Harackiewicz, J. M. (1996). Approach and avoidance achievement goals and intrinsic motivation: A mediational analysis. Journal of Personality and Social Psychology, 70(3), 461–475. https://doi.org/10.1037/0022-3514.70.3.461
• Payne, S. C., Youngcourt, S. S., & Beaubien, J. M. (2007). A meta-analytic examination of the goal orientation nomological net. Journal of Applied Psychology, 92(1), 128–150. https://doi.org/10.1037/0021-9010.92.1.128
• Sujan, H., Weitz, B. A., & Kumar, N. (1994). Learning orientation, working smart, and effective selling. Journal of Marketing, 58(3), 39–52. https://doi.org/10.1177/002224299405800303
• VandeWalle, D. (1997). Development and validation of a work domain goal orientation instrument. Educational and Psychological Measurement, 57(6), 995–1015. https://doi.org/10.1177/0013164497057006009
• VandeWalle, D., Brown, S. P., Cron, W. L., & Slocum Jr., J. W. (1999). The influence of goal orientation and self-regulation tactics on sales performance: A longitudinal field test. Journal of Applied Psychology, 84(2), 249–259. https://doi.org/10.1037/0021-9010.84.2.249
• VandeWalle, D., & Cummings, L. L. (1997). A test of the influence of goal orientation on the feedback-seeking process. Journal of Applied Psychology, 82(3), 390–400. https://doi.org/10.1037/0021-9010.82.3.390
• VandeWalle, D., Cron, W. L., & Slocum Jr., J. W. (2001). The role of goal orientation following performance feedback. Journal of Applied Psychology, 86(4), 629–640. https://doi.org/10.1037/0021-9010.86.4.629

13. Items of the Scale (Questionnaire)