Fostering proactivity in the age of AI: exploring the interplay of job reflection and coaching leadership DOI
Jeeyoon Jeong, Insik Jeong

Baltic Journal of Management, Год журнала: 2025, Номер unknown

Опубликована: Апрель 18, 2025

Purpose This study examines the impact of artificial intelligence (AI) adoption on employee proactive behavior in South Korean organizations. Drawing social cognitive theory, we investigate mediating role job reflection and moderating effect coaching leadership this relationship. Our research aims to address critical gap understanding how AI influences proactivity, a crucial dynamic, technology-driven environments. By exploring processes factors involved, seek provide insights into organizations can leverage foster while emphasizing importance reflective practices supportive leadership. Design/methodology/approach We employed time-lagged survey with 405 employees across three waves. adoption, control variables were measured at Time 1, 2 3. Hierarchical regression bootstrapping analyses test hypotheses. Findings results reveal that positively relates behavior, While moderates relationship between reflection, hypothesized moderated mediation was not supported, suggesting reflection’s remains consistent regardless level. finding highlights robustness as mechanism context. Originality/value advances mechanisms linking by identifying key process. It provides enhance proactivity during implementation revealing complexity leadership’s

Язык: Английский

Examining the influence of AI event strength on employee performance outcomes: Roles of AI rumination, AI-supported autonomy, and felt obligation for constructive change DOI
Jing Bai,

Tzung Cheng TC Huan,

Wai Yie Leong

и другие.

International Journal of Hospitality Management, Год журнала: 2025, Номер 126, С. 104111 - 104111

Опубликована: Янв. 16, 2025

Язык: Английский

Процитировано

1

Harnessing machine learning models and explainable AI to understand MOOC continuance intention DOI
Vinod Sharma, Yogesh Mahajan, Manohar Kapse

и другие.

Information Discovery and Delivery, Год журнала: 2025, Номер unknown

Опубликована: Март 6, 2025

Purpose This study aims to investigate factors that influence individuals’ continuance intention use massive open online courses (MOOCs) by using machine learning models. Design/methodology/approach Data was collected from 702 MOOC users major metropolitan cities in India through a network-based sampling and recruitment via various social media outlets (e.g. LinkedIn Facebook). Various algorithms along with explainable artificial intelligence (XAI) were employed Python PyCaret. Findings Results confirm pedagogy value, content interface ubiquity teacher presence satisfaction have positive effects on the continuous of MOOCs. Furthermore, value is chief driving force CI XAI helps clarify intricate patterns learner data, thus allowing more appropriate interventions. Practical implications The findings would be useful for developers formulate better propositions ensuring sustainable business higher growth rate market. Originality/value bridges gap existing literature providing novel approach. To best authors’ knowledge, this first earlier identifying leading intentions MOOCs, so research adds method exploring enhancing retention rates among learners.

Язык: Английский

Процитировано

0

Service robots, artificial intelligence awareness, self-efficacy and work engagement DOI
Xiang‐Peng Kong, Wei Yuan, Chunhao Ma

и другие.

Management Decision, Год журнала: 2025, Номер unknown

Опубликована: Апрель 9, 2025

Purpose The rise of artificial intelligence (AI) technology has sparked concerns across various industries, especially within frontline service sectors, as it fosters a sense insecurity among practitioners. However, prior research on how and when AI impacts employees’ psychological work states remains insufficient. This study aims to explore the relationships awareness with job engagement, particular focus self-efficacy affects these dynamics. Design/methodology/approach A questionnaire survey was employed collect 302 responses from employees in hotel industry China. Data analysis conducted using SPSS 21.0 AMOS, employing hierarchical regression Johnson-Neyman tests validate main, mediating, moderating effects. Findings findings indicate that negatively influences engagement by triggering insecurity. Self-efficacy serves mitigating factor, alleviating adverse impact engagement. Notably, test reveals positive shift relationship between exceeds certain threshold. Originality/value present is first contributing growing body this area. It contributes not only enriching existing literature employee but also introducing new perspectives, thereby providing valuable insights for both scholars

Язык: Английский

Процитировано

0

Fostering proactivity in the age of AI: exploring the interplay of job reflection and coaching leadership DOI
Jeeyoon Jeong, Insik Jeong

Baltic Journal of Management, Год журнала: 2025, Номер unknown

Опубликована: Апрель 18, 2025

Purpose This study examines the impact of artificial intelligence (AI) adoption on employee proactive behavior in South Korean organizations. Drawing social cognitive theory, we investigate mediating role job reflection and moderating effect coaching leadership this relationship. Our research aims to address critical gap understanding how AI influences proactivity, a crucial dynamic, technology-driven environments. By exploring processes factors involved, seek provide insights into organizations can leverage foster while emphasizing importance reflective practices supportive leadership. Design/methodology/approach We employed time-lagged survey with 405 employees across three waves. adoption, control variables were measured at Time 1, 2 3. Hierarchical regression bootstrapping analyses test hypotheses. Findings results reveal that positively relates behavior, While moderates relationship between reflection, hypothesized moderated mediation was not supported, suggesting reflection’s remains consistent regardless level. finding highlights robustness as mechanism context. Originality/value advances mechanisms linking by identifying key process. It provides enhance proactivity during implementation revealing complexity leadership’s

Язык: Английский

Процитировано

0