ความเครียดจากเทคโนโลยีและภาวะหมดไฟในการทำงานแบบวิถีใหม่: การขยายมุมมองด้านการขาดความเหนียวแน่นในกลุ่ม และความสำคัญของการปรับงาน

Shifting to technology-driven work became standard after the COVID-19 pandemic subsided. Technostress has undergone a shifted pattern in the new normal. Therefore, this study aimed for: 1) investigate the new pattern of technostress components and 2) examine the causal relationships of online worklo...

全面介紹

Saved in:
書目詳細資料
主要作者: รัตนาวลี บุญยฤทธิ์
其他作者: ประพิมพา จรัลรัตนกุล
格式: Theses and Dissertations
語言:Thai
出版: จุฬาลงกรณ์มหาวิทยาลัย 2024
在線閱讀:https://digiverse.chula.ac.th/Info/item/dc:95760
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Chulalongkorn University
語言: Thai
實物特徵
總結:Shifting to technology-driven work became standard after the COVID-19 pandemic subsided. Technostress has undergone a shifted pattern in the new normal. Therefore, this study aimed for: 1) investigate the new pattern of technostress components and 2) examine the causal relationships of online workload, group-incohesion, job crafting, technostress, and burnout. Study 1 involved the reconceptualization and development of the technostress scale. Semi-structured interview was used for qualitative analysis, followed by an online survey for factor analysis. Results revealed 4 factors: techno-overload, techno-insecurity, techno-induced incohesion, and techno-instability. The Technostress Scale demonstrated high reliability in both full form (M = 3.2, SD = 0.8, 95% CI [3.09, 3.26], α = .963, CITC = .448–.707), and short form (M = 3.2, SD = 0.8, 95% CI [3.13, 3.30], α = .915, CITC = .463–.687). Study 2 examined the causal relationships using panel study with 3 times-weekly online survey. Results in the path analysis revealed that online workload had positive direct effect on technostress in both cross-sectional (β = .501, p < .001) and longitudinal analyses (β = .294, p < .001). Technostress, in turn, had positive direct effect on burnout in both cross-sectional (β = .458, p < .001) and longitudinal analyses (β = .497, p < .001). Additionally, technostress fully mediated indirect effect of online workload on burnout in both cross-sectional (β = .229, p < .001) and longitudinal analyses (β = .142, p < .001). While group incohesion had both a direct effect on burnout (β = .106, p = .013) and an indirect effect (β = .087, p < .001), but only in cross-sectional analysis. Job crafting had negative direct effect on burnout in both cross-sectional (β = -.315, p < .001) and longitudinal analyses (β = -.308, p < .001) but it had a moderation effect only in the cross-sectional analysis, with the direction differing depending on the stressor: online workload (β = -.090, p = .035) and group incohesion (β = .093, p = .031)