том 31 издание 4 страницы 106907272311613

A Process Model of Career Decision-Making and Adaptation Under Uncertainty: Expanding the Dual-Process Theory of Career Decision-Making

Тип публикацииJournal Article
Дата публикации2023-03-05
scimago Q1
Tоп 10% SciMago
wos Q2
white level БС1
SJR1.413
CiteScore6.7
Impact factor2.8
ISSN10690727, 15524590
General Psychology
Organizational Behavior and Human Resource Management
Applied Psychology
Краткое описание

The dual-process theory of career decision-making (DTC; Xu, 2021a ; 2021b ) resulted from a synthesized and critical reflection of career decision-making and related models in the contemporary psychosocial context of career development. The DTC features persistent decision uncertainty as a salient condition of contemporary career decision-making, and its theoretical framework and predictive model establish DTC’s conceptual and empirical foundation, respectively. However, the DTC and the career decision-making literature in general still lack a process-oriented prescriptive model that foregrounds decision uncertainty. Consequently, the extant literature fails to prescribe key decision-making components and procedures under decision uncertainty. Thus, drawing on the DTC, decision-making science, and existing models of career decision-making, we propose a four-stage process model, which involves four interlinked macro stages and micro steps within each stage. The model also involves five propositions to explain and predict the effects of important personal and environmental factors on the process and outcomes of each stage. We describe the DTC process model and use a case example to illustrate how the model can be applied in practice. Together, the DTC’s theoretical framework, predictive model, and process-oriented prescriptive model constitute a comprehensive theory regarding dynamic career decision-making and adaption in an uncertain world and offer diverse research and practical implications.

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Топ-30

Журналы

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Journal of Career Assessment
5 публикаций, 31.25%
Career Development Quarterly
1 публикация, 6.25%
Personality and Individual Differences
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Psychotherapy Research
1 публикация, 6.25%
Acta Psychologica
1 публикация, 6.25%
British Journal of Guidance and Counselling
1 публикация, 6.25%
IEEE Transactions on Aerospace and Electronic Systems
1 публикация, 6.25%
Journal of Developmental Entrepreneurship
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1 публикация, 6.25%
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ГОСТ |
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Xu H., Flores L. Y. A Process Model of Career Decision-Making and Adaptation Under Uncertainty: Expanding the Dual-Process Theory of Career Decision-Making // Journal of Career Assessment. 2023. Vol. 31. No. 4. p. 106907272311613.
ГОСТ со всеми авторами (до 50) Скопировать
Xu H., Flores L. Y. A Process Model of Career Decision-Making and Adaptation Under Uncertainty: Expanding the Dual-Process Theory of Career Decision-Making // Journal of Career Assessment. 2023. Vol. 31. No. 4. p. 106907272311613.
RIS |
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TY - JOUR
DO - 10.1177/10690727231161378
UR - https://journals.sagepub.com/doi/10.1177/10690727231161378
TI - A Process Model of Career Decision-Making and Adaptation Under Uncertainty: Expanding the Dual-Process Theory of Career Decision-Making
T2 - Journal of Career Assessment
AU - Xu, Hui
AU - Flores, Lisa Y.
PY - 2023
DA - 2023/03/05
PB - SAGE
SP - 106907272311613
IS - 4
VL - 31
SN - 1069-0727
SN - 1552-4590
ER -
BibTex |
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BibTex (до 50 авторов) Скопировать
@article{2023_Xu,
author = {Hui Xu and Lisa Y. Flores},
title = {A Process Model of Career Decision-Making and Adaptation Under Uncertainty: Expanding the Dual-Process Theory of Career Decision-Making},
journal = {Journal of Career Assessment},
year = {2023},
volume = {31},
publisher = {SAGE},
month = {mar},
url = {https://journals.sagepub.com/doi/10.1177/10690727231161378},
number = {4},
pages = {106907272311613},
doi = {10.1177/10690727231161378}
}
MLA
Цитировать
Xu, Hui, and Lisa Y. Flores. “A Process Model of Career Decision-Making and Adaptation Under Uncertainty: Expanding the Dual-Process Theory of Career Decision-Making.” Journal of Career Assessment, vol. 31, no. 4, Mar. 2023, p. 106907272311613. https://journals.sagepub.com/doi/10.1177/10690727231161378.
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