This study aimed to design and validate a comprehensive model of questioning skills for higher education employees by identifying causal, contextual, and intervening conditions, strategic pathways, and individual and organizational outcomes. An exploratory mixed-methods design was employed. In the qualitative phase, 14 semi-structured interviews with academic and administrative experts were conducted and analyzed using grounded theory (open, axial, and selective coding). In the quantitative phase, a questionnaire derived from the qualitative findings was distributed to 322 higher education employees. Data were analyzed through structural equation modeling (SEM) using SmartPLS, with reliability assessed via Cronbach’s alpha and composite reliability, and convergent validity confirmed using AVE. Causal conditions such as organizational loyalty, critical thinking, social intelligence, motivation, and personal growth orientation significantly predicted the core phenomenon of questioning (β=0.562, T=14.395). Contextual (β=0.252, T=7.244) and intervening conditions (β=0.356, T=9.347) influenced strategic actions, while the core phenomenon strongly predicted strategies (β=0.424, T=11.831). Strategies had a robust effect on outcomes (β=0.586, T=15.252). Model fit was confirmed with GOF=0.425, high Q² values, and satisfactory reliability (CR>0.7) and convergent validity (AVE>0.5). The validated model offers an integrated framework for understanding and enhancing questioning skills among higher education employees. It can serve as a practical tool for fostering creativity, systemic thinking, and performance improvement while guiding leaders and policymakers to promote a culture of inquiry and professional growth in universities.
Fatemeh Roasaei, Hamid Taboli, M. Beheshtifar· Management, Education and De...· 0 citations
Objective: Social undermining represents a insidious, destructive, and covert behavioral phenomenon within organizations that erodes interpersonal trust, communication dynamics, and collaborative performance. This study develops and empirically validates a comprehensive model examining how perceived organizational justice (distributive, procedural, and interactional) influences employee social undermining, and evaluates its downstream impacts on job well-being and innovative work behavior within South Zagros Oil and Gas Production Company.Methodology: Utilizing an applied, descriptive-analytical design, this research employs Partial Least Squares Structural Equation Modeling (PLS-SEM). The target population comprised 2,400 operational and administrative employees across headquarters and five major operational extraction regions. A stratified proportional random sample of 342 valid responses was analyzed. Data were gathered using validated measurement scales for organizational justice (Folger & Cropanzano), social undermining (Duffy et al.), job well-being (Warr), and innovative work behavior (Janssen). Structural evaluation included rigorous outer model testing (indicator reliability, convergent validity, HTMT discriminant validity) and inner model structural path analysis with 5,000 bootstrap resamples.Findings: Structural path analysis reveals that perceived organizational justice exerts a profound negative direct effect on employee social undermining (β=−0.63, p<0.001). Procedural justice emerged as the strongest inhibitor (β=−0.48), followed by distributive (β=−0.41) and interactional justice (β=−0.37). Social undermining significantly degrades job well-being (β=−0.46, p<0.001) and suppresses innovative work behavior (β=−0.42, p<0.001). Furthermore, mediation analysis confirms that social undermining serves as a significant indirect mechanism translating organizational injustice into depleted employee well-being and diminished workplace innovation.Conclusion: Institutionalizing transparent, justice-driven evaluation frameworks and fostering respectful supervisory dynamics are crucial strategies for curbing covert undermining behaviors and enhancing human capital resilience in high-stress energy industries.
M. Beheshtifar, Maryam Adibzadeh, Hossein Mehdi Roknabadi et al.· Journal of Intelligent Decis...· 0 citations
