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Enregistrement W4407969916 · doi:10.1002/hrdq.21559

Shaping the Future of <scp>HRDQ</scp>: Embracing Growth, Innovation, and Scholarly Rigor

2025· article· en· W4407969916 sur OpenAlexaboutno aff
Sewon Kim, Rajashi Ghosh, Toby Egan

Notice bibliographique

RevueHuman Resource Development Quarterly · 2025
Typearticle
Langueen
DomainePsychology
ThématiqueHuman Resource Development and Performance Evaluation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPublic relationsMarketingBusinessPolitical science

Résumé

récupéré en direct d'OpenAlex

We are truly honored and excited to step into the role of incoming Co-Editors-in-Chief of Human Resource Development Quarterly (HRDQ). Rajashi brings extensive knowledge and experience to the journal, having successfully completed her tenure as the immediate past editor of Human Resource Development International. Toby and Sewon continue their editorial duties and cultivate scholarly networks, strategically positioning the journal within dynamic and interconnected academic communities across disciplines. Our collective commitment to the journal began more than two decades ago—as reviewers, authors, contributors, and editorial team members—and today, it grows even stronger and more passionate. We are privileged to follow in the footsteps of the devoted, humanistic, and visionary past Editors, including Richard Swanson, Gary McLean, Ronald Jacobs, Darlene Russ-Eft, Timothy Hatcher, Baiyin Yang, Andrea Ellinger, Valerie Anderson, Kim Nimon, Jon Werner, Thomas Reio Jr., Mesut Akdere, Toby Egan, and Sewon Kim. They have faithfully nurtured and guided HRDQ over the years. Now in its 36th year since its first publication, HRDQ is ranked as a Social Sciences Citation Index (SSCI) journal in the categories of Industrial Relations & Labor, Management, and Applied Psychology. Our goal is to honor and build on this remarkable legacy, addressing contemporary and emerging issues to advance the field and its scholarship. HRDQ has become a leading venue for disseminating new knowledge in social science and related disciplines, with submission volume increasing significantly in recent years. In response to this trend, we have maintained a multi-associate editor platform with two expanded research approach tracks for our new editorial team. During the recruitment process, we issued an open call for applicants via multidisciplinary channels, such as the Academy of Human Resource Development, Academy of Management, Society for Industrial and Organizational Psychology, and Public Administration-related associations, among others. We also sought collegial recommendations for content and methodological expertise from journal editors and editorial board members. Our selected new editorial team includes: Meera Alagaraja, Bhagyashree Barhate, Kate Black, Taha Hameduddin, Sunghoon Kim, Taehee Kim, Yi-Ling Lai, Jonas Lang, Philseok Lee, Henriette Lundgren, Yoshie Nakamura, Sunyoung Park, Jian-Min (James) Sun, Pattanee Susomrith, Zhen Wang, Bin Wang, Sangok Yoo, and Connie Zheng as associate editors; and Christine Fandrich as managing editor. The journal is housed in the Department of Organization and Leadership at Columbia University, USA. We are thrilled to work with this brilliant editorial team! Additionally, we will continue to enhance and broaden our editorial board to include scholars from human resource development and related disciplines, acknowledging the field's interdisciplinary nature. HRDQ is “the first scholarly journal focused directly on the field of human resource development” (HRDQ n.d.; Swanson 1990). Our journal prioritizes the publication of rigorous, influential, and timely studies with a strong emphasis on empirical research designs. These studies employ five key approaches: quantitative, qualitative, mixed-methods, theoretical, and methodological research, each playing a crucial role in advancing scholarship in human resource and organizational development and relevant contexts (Ellinger 2013; Kim et al. 2022; Reio Jr. 2019; Russ-Eft et al. 2014; Werner et al. 2019; Yang 2010). HRDQ also includes non-refereed sections, such as media reviews and opinion forum papers, fostering open discourse and scholarly interactions among a broad range of professional and academic stakeholders. Our readership includes researchers, professors, academicians, consultants, trainers, managers, human resource professionals, and organizational practitioners. We actively welcome research that explores topics such as training and development, talent management, management and leadership, teams, organizational learning, change management, organizational development and effectiveness, strategy, performance management, knowledge transfer, data analytics, motivation, career development, the global and virtual workplace, critical perspectives, and advanced methodological issues. As HRDQ continues to advance rigorous and impactful research, this issue features four empirical studies that addresses contemporary workplace challenges. The first article, by Cort Rudolph and Hannes Zacher, examines how flexible work arrangements affect employee work-related outcomes, such as professional isolation, work-from-home self-efficacy, and job performance. Using data from 32 monthly measurement waves collected from German employees (n = 994), this study finds that the percentage of time employees work from home generally has nonlinear associations with key work-related outcomes; in some cases, these associations form inverted U-shaped patterns, indicating that “too much of a good thing” can be detrimental. The second article addresses the learning capacity of work teams. Utilizing data from engineering teams (n = 60) in Taiwan's high-tech sector, Kuang-Jung Chen and colleagues examine the role of collective learning efficacy in relation to negative learning emotions, learning goal orientation, and team performance, thereby strengthening collective motivation for team success. The third article investigates the effects of organizational socialization strategies on the identity formation process of newcomers. Nadeem Ahmed Awan and Muhammad Abbas employ a three-wave time-lagged field survey with Pakistani employees (n = 350) and find that organizational socialization positively influences newcomers' perceived social validation (after 2 months), which subsequently enhances their team identity and organizational identity (after 4 months). The study also explores the boundary effects of person-group fit in promoting an effective organizational socialization culture. The fourth article, by Bishakha Mazumdar and colleagues, takes a qualitative approach to understanding the evolving meaning of retirement for bridge employees—retirees who re-enter the workforce. Drawing on interviews with Canadian employees (n = 26), the authors explore how bridge employees reconstruct the meaning of retirement and prioritize self-directed goals during their bridge employment. Collectively, these articles exemplify the high-quality research and scholarly dialogue that characterize HRDQ. We hope this inaugural issue serves as a catalyst for thought, inspires new insights, and encourages further exploration. Finally, we sincerely appreciate the invaluable contributions of our authors, reviewers, and editorial team members who supported this issue, as well as the broader academic and professional communities for their ongoing support in advancing HRDQ and its social impact. Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,071
score de la tête « metaresearch » (Gemma)0,163
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,071
Score d'incertitude au seuil0,375

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0710,163
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0060,005
Études des sciences et des technologies0,0090,018
Communication savante0,0710,024
Science ouverte0,0030,011
Intégrité de la recherche0,0090,015
Charge utile insuffisante (le modèle a refusé de juger)0,0090,006

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,304
Écart entre enseignants0,273 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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