Promoting or Preventing? The Influence of Artificial Intelligence Awareness on Employee Job Crafting

Abstract

Artificial intelligence (AI) enhances employees’ work efficiency and significantly impacts their cognitive and psychological states. However, there remains limited research on the complex relationship between AI-driven changes in the work setting and employees’ job crafting. Therefore, this study applies the job demand–resource (JD-R) theory to test how AI awareness influences employees’ promotion- and prevention-focused job crafting. It further investigates the mediating roles of job insecurity and creative process engagement and the moderating role of AI knowledge. Based on the sample of 324 participants, the empirical results show that challenge appraisal toward AI indirectly promote promotion-focused job crafting through creative process engagement and inhibit prevention-focused job crafting through job insecurity. Conversely, hindrance appraisal toward AI indirectly promotes prevention-focused job crafting through job insecurity. Additionally, the positive effect of challenge appraisal on creative process engagement is strengthened by AI knowledge. Discussions are provided on both the theoretical and practical implications.

Keywords

artificial intelligence awareness promotion-focused job crafting prevention-focused job crafting creative process engagement job insecurity artificial intelligence knowledge

Get full access to this article

View all access options for this article.

References

Aghaei

Nematbakhsh

M. A.

Farsani

H. K.

(2012). Evolution of the world wide web: From WEB 1.0 TO WEB 4.0. International Journal of Web & Semantic Technology, 3(1), 1–10. https://doi.org/10.5121/ijwest.2012.3101

Aryee

Walumbwa

F. O.

Mondejar

Chu

C. W.

(2017). Core self-evaluations and employee voice behavior: Test of a dual-motivational pathway. Journal of Management, 43(3), 946–966. https://doi.org/10.1177/0149206314546192

Bag

Pretorius

J. H. C.

Gupta

Dwivedi

Y. K.

(2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change, 163, 120420. https://doi.org/10.1016/j.techfore.2020.120420

Bakker

A. B.

Demerouti

(2017). Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology, 22(3), 273. https://doi.org/10.1037/ocp0000056

Bindl

U. K.

Unsworth

K. L.

Gibson

C. B.

Stride

C. B.

(2019). Job crafting revisited: Implications of an extended framework for active changes at work. Journal of Applied Psychology, 104(5), 605–628. https://doi.org/10.1037/apl0000362

Brockner

Higgins

E. T.

(2001). Regulatory focus theory: Implications for the study of emotions at work. Organizational Behavior and Human Decision Processes, 86(1), 35–66. https://doi.org/10.1006/obhd.2001.2972

Cao

(2021). Portrait-based academic performance evaluation of college students from the perspective of big data. International Journal of Emerging Technologies in Learning, 16(4), 95–106. https://doi.org/10.3991/ijet.v16i04.20475

Cha

S. S.

(2020). Customers’ intention to use robot-serviced restaurants in Korea: Relationship of coolness and MCI factors. International Journal of Contemporary Hospitality Management, 32(9), 2947–2968. https://doi.org/10.1108/ijchm-01-2020-0046

Chaker

N. N.

Nowlin

E. L.

Walker

Anaza

N. A.

(2021). Defending the frontier: Examining the impact of internal salesperson evasive knowledge hiding on perceptions of external customer outcomes. European Journal of Marketing, 55(3), 671–699. https://doi.org/10.1108/ejm-02-2019-0174

10.

Cheng

Lin

Kong

(2023). Challenge or hindrance? How and when organizational artificial intelligence adoption influences employee job crafting. Journal of Business Research, 164, 113987. https://doi.org/10.1016/j.jbusres.2023.113987

11.

Chiu

Y. T.

Zhu

Y. Q.

Corbett

(2021). In the hearts and minds of employees: A model of pre-adoptive appraisal toward artificial intelligence in organizations. International Journal of Information Management, 60, 102379. https://doi.org/10.1016/j.ijinfomgt.2021.102379

12.

Crawford

E. R.

LePine

J. A.

Rich

B. L.

(2010). Linking job demands and resources to employee engagement and burnout: A theoretical extension and meta-analytic test. Journal of Applied Psychology, 95(5), 834–848. https://doi.org/10.1037/a0019364

13.

Darvishmotevali

Ali

(2020). Job insecurity, subjective well-being and job performance: The moderating role of psychological capital. International Journal of Hospitality Management, 87, 102462. https://doi.org/10.1016/j.ijhm.2020.102462

14.

Demerouti

Bakker

A. B.

Bulters

A. J.

(2004). The loss spiral of work pressure, work–home interference and exhaustion: Reciprocal relations in a three-wave study. Journal of Vocational Behavior, 64(1), 131–149. https://doi.org/10.1016/s0001-8791(03)00030-7

15.

Demerouti

Bakker

A. B.

Nachreiner

Schaufeli

W. B.

(2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499. https://doi.org/10.1037//0021-9010.86.3.499

16.

Ding

(2021). Employees’ challenge-hindrance appraisals toward STARA awareness and competitive productivity: A micro-level case. International Journal of Contemporary Hospitality Management, 33(9), 2950–2969. https://doi.org/10.1108/ijchm-09-2020-1038

17.

Zhang

Chen

(2016). From creative process engagement to performance: Bidirectional support. Leadership & Organization Development Journal, 37(7), 966–982. https://doi.org/10.1108/lodj-03-2015-0046

18.

Frey

C. B.

Osborne

M. A.

(2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019

19.

Greenhalgh

Rosenblatt

(1984). Job insecurity: Toward conceptual clarity. Academy of Management Review, 9(3), 438–448. https://doi.org/10.2307/258284

20.

Guo

Polak

(2021). Artificial intelligence and financial technology FinTech: How AI is being used under the pandemic in 2020. The fourth industrial revolution: implementation of artificial intelligence for growing business success, 169-186. https://doi.org/10.1007/978-3-030-62796-6_9

21.

Teng

Song

(2023). Linking employees’ challenge-hindrance appraisals toward AI to service performance: The influences of job crafting, job insecurity and AI knowledge. International Journal of Contemporary Hospitality Management, 36(3), 975–994. https://doi.org/10.1108/ijchm-07-2022-0848

22.

Hobfoll

S. E.

(1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513. https://doi.org/10.1037//0003-066x.44.3.513

23.

Hobfoll

S. E.

(2002). Social and psychological resources and adaptation. Review of General Psychology, 6(4), 307–324. https://doi.org/10.1037//1089-2680.6.4.307

24.

Hobfoll

S. E.

(2011). Conservation of resources theory: Its implication for stress, health, and resilience. The Oxford handbook of stress, health, and coping. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780195375343.013.0007

25.

Huang

Wang

You

(2016). The job demands-resources model and job burnout: The mediating role of personal resources. Current Psychology, 35(4), 562–569. https://doi.org/10.1007/s12144-015-9321-2

26.

Ivanov

Webster

(2019). Conceptual framework of the use of robots, artificial intelligence and service automation in travel, tourism, and hospitality companies. Robots, artificial intelligence, and service automation in travel, tourism and hospitality, 7-37. https://doi.org/10.1108/978-1-78756-687-320191001

27.

Jin

Yang

(2023). Approach or avoidance? A study on the impact of overall rewards on employees’ proactive and responsive creativity. Dongyue Tribune, 44(2), 119–127. In chinese. https://doi.org/10.15981/j.cnki.dongyueluncong.2023.03.013

28.

Kang

D. Y.

Hur

W. M.

Shin

(2023). Smart technology and service employees’ job crafting: Relationship between STARA awareness, performance pressure, receiving and giving help, and job crafting. Journal of Retailing and Consumer Services, 73, 103282. https://doi.org/10.1016/j.jretconser.2023.103282

29.

Khan

A. K.

Khalid

Abbas

Khalid

(2022). COVID-19-related job insecurity and employees’ behavioral outcomes: Mediating role of emotional exhaustion and moderating role of symmetrical internal communication. International Journal of Contemporary Hospitality Management, 34(7), 2496–2515. https://doi.org/10.1108/ijchm-05-2021-0639

30.

Kong

Yuan

Baruch

Jiang

Wang

(2021). Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management, 33(2), 717–734. https://doi.org/10.1108/ijchm-07-2020-0789

31.

Koo

Curtis

Ryan

(2021). Examining the impact of artificial intelligence on hotel employees through job insecurity perspectives. International Journal of Hospitality Management, 95, 102763. https://doi.org/10.1016/j.ijhm.2020.102763

32.

Lazarus

R. S.

Folkman

(1984). Stress, appraisal, and coping. Springer publishing company. https://doi.org/10.1016/0005-7967(85)90087-7

33.

Lesener

Gusy

Wolter

(2018). The job demands-resources model: A metaanalytic review of longitudinal studies. Work & Stress, 33(1), 76–103. https://doi.org/10.1080/02678373.2018.1529065

34.

Bonn

M. A.

B. H.

(2019). Hotel employee’s artificial intelligence and robotics awareness and its impact on turnover intention: The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172–181. https://doi.org/10.1016/j.tourman.2019.02.006

35.

Liang

Guo

Shu

Gong

Luo

(2022). Investigating the double-edged sword effect of AI awareness on employee’s service innovative behavior. Tourism Management, 92, 104564. https://doi.org/10.1016/j.tourman.2022.104564

36.

Lichtenthaler

P. W.

Fischbach

(2016). The conceptualization and measurement of job crafting: Validation of a German version of the job crafting scale. Zeitschrift für Arbeits- und Organisationspsychologie, 60(4), 173–186. https://doi.org/10.1026/0932-4089/a000219

37.

Lichtenthaler

P. W.

Fischbach

(2019). A meta-analysis on promotion-and prevention-focused job crafting. European Journal of Work and Organizational Psychology, 28(1), 30–50. https://doi.org/10.1080/1359432x.2018.1527767

38.

Liu

(2023). The role of synergistic interplay among LMX, leader creativity expectations and job characteristics in stimulating creative process engagement. Management Decision, 61(3), 610–636. https://doi.org/10.1108/md-08-2021-1113

39.

(2022). Linking artificial intelligence to service sabotage. The Service Industries Journal, 42(13-14), 1054–1074. https://doi.org/10.1080/02642069.2022.2092615

40.

Makarius

E. E.

Mukherjee

Fox

J. D.

Fox

A. K.

(2020). Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization. Journal of Business Research, 120, 262–273. https://doi.org/10.1016/j.jbusres.2020.07.045

41.

Makridakis

(2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. https://doi.org/10.1016/j.futures.2017.03.006

42.

Mauno

Leskinen

Kinnunen

(2001). Multi-wave, multi-variable models of job insecurity: Applying different scales in studying the stability of job insecurity. Journal of Organizational Behavior: The International Journal of Industrial, Occupational and Organizational Psychology and Behavior, 22(8), 919–937. https://doi.org/10.1002/job.122

43.

Mawritz

M. B.

Folger

Latham

G. P.

(2014). Supervisors’ exceedingly difficult goals and abusive supervision: The mediating effects of hindrance stress, anger, and anxiety. Journal of Organizational Behavior, 35(3), 358–372. https://doi.org/10.1002/job.1879

44.

McClure

P. K.

(2018). You’re fired,” says the robot: The rise of automation in the workplace, technophobes, and fears of unemployment. Social Science Computer Review, 36(2), 139–156. https://doi.org/10.1177/0894439317698637

45.

Menguc

Auh

Yeniaras

Katsikeas

C. S.

(2017). The role of climate: Implications for service employee engagement and customer service performance. Journal of the Academy of Marketing Science, 45(3), 428–451. https://doi.org/10.1007/s11747-017-0526-9

46.

Nguyen

Sharma

Malik

(2024). Leadership styles and employee creativity: The interactive impact of online knowledge sharing and organizational innovation. Journal of Knowledge Management, 28(3), 631–650. https://doi.org/10.1108/jkm-01-2023-0014

47.

Ong

W. J.

Johnson

M. D.

(2023). Toward a configural theory of job demands and resources. Academy of Management Journal, 66(1), 195–221. https://doi.org/10.5465/amj.2020.0493

48.

Pan

Froese

Liu

(2022). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. The International Journal of Human Resource Management, 33(6), 1125–1147. https://doi.org/10.1108/jkm-01-2023-0014

49.

Petrou

Demerouti

Schaufeli

W. B.

(2018). Crafting the change: The role of employee job crafting behaviors for successful organizational change. Journal of Management, 44(5), 1766–1792. https://doi.org/10.1177/0149206315624961

50.

Podsakoff

N. P.

Lepine

J. A.

Lepine

M. A.

(2007). Differential challenge stressor-hindrance stressor relationships with job attitudes, turnover intentions, turnover, and withdrawal behavior: A meta-analysis. Journal of Applied Psychology, 92(2), 438–454. https://doi.org/10.1037/0021-9010.92.2.438

51.

Podsakoff

P. M.

Mackenzie

S. B.

Lee

J. Y.

Podsakoff

N. P.

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

52.

Preacher

K. J.

Hayes

A. F.

(2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/brm.40.3.879

53.

Shang

Zhao

Richards

(2023). Do work stressors facilitate or impede job crafting? The role of employee trait and work regulatory focus. Career Development International, 28(2), 250–274. https://doi.org/10.1108/cdi-02-2022-0028

54.

Shoss

M. K.

(2017). Job insecurity: An integrative review and agenda for future research. Journal of Management, 43(6), 1911–1939. https://doi.org/10.1177/0149206317691574

55.

Song

Zhang

Cao

(2022). Dancing with service robots: The impacts of employee-robot collaboration on hotel employees’ job crafting. International Journal of Hospitality Management, 103, 103220. https://doi.org/10.1016/j.ijhm.2022.103220

56.

Teng

Zhou

Zheng

(2024). Artificial intelligence (AI) awareness and work withdrawal: Evaluating chained mediation through negative work-related rumination and emotional exhaustion. International Journal of Contemporary Hospitality Management, 36(7), 2311–2326. https://doi.org/10.1108/ijchm-02-2023-0240

57.

Tims

Bakker

A. B.

Derks

(2013). The impact of job crafting on job demands,job resources, and well-being. Journal of Occupational Health Psychology, 18(2), 230–240. https://doi.org/10.1037/a0032141

58.

Van Dam

Oreg

Schyns

(2008). Daily work contexts and resistance to organisational change: The role of leader–member exchange, development climate, and change process characteristics. Applied Psychology, 57(2), 313–334. https://doi.org/10.1111/j.1464-0597.2007.00311.x

59.

Vatan

Dogan

(2021). What do hotel employees think about service robots? A qualitative study in Turkey. Tourism Management Perspectives, 37, 100775. https://doi.org/10.1016/j.tmp.2020.100775

60.

Webster

J. R.

Beehr

T. A.

Love

(2011). Extending the challenge-hindrance model of occupational stress: The role of appraisal. Journal of Vocational Behavior, 79(2), 505–516. https://doi.org/10.1016/j.jvb.2011.02.001

61.

Xanthopoulou

Bakker

A. B.

Demerouti

Schaufeli

W. B.

(2007). The role of personal resources in the job demands-resources model. International Journal of Stress Management, 14(2), 121–141. https://doi.org/10.1037/1072-5245.14.2.121

62.

Xanthopoulou

Bakker

A. B.

Fischbach

(2013). Work engagement among employees facing emotional demands. Journal of Personnel Psychology, 12(2), 74–84. https://doi.org/10.1027/1866-5888/a000085

63.

Stienmetz

Ashton

(2020). How will service robots redefine leadership in hotel management? A Delphi approach. International Journal of Contemporary Hospitality Management, 32(6), 2217–2237. https://doi.org/10.1108/ijchm-05-2019-0505

64.

Xue

Zhao

(2023). The association between artificial intelligence awareness and employee depression: The mediating role of emotional exhaustion and the moderating role of perceived organizational support. International Journal of Environmental Research and Public Health, 20(6), 5147. https://doi.org/10.3390/ijerph20065147

65.

Shum

Alcorn

Sun

(2022). Robots can’t take my job: Antecedents and outcomes of gen Z employees’ service robot risk awareness. International Journal of Contemporary Hospitality Management, 34(8), 2971–2988. https://doi.org/10.1108/ijchm-10-2021-1312

66.

Zehir

Karaboğa

Başar

(2020). The transformation of human resource management and its impact on overall business performance: Big data analytics and AI technologies in strategic HRM. In Hacioglu

(Ed.), Digital business strategies in blockchain ecosystems: Transformational design and future of global business (pp. 265–279). Springer. https://doi.org/10.1007/978-3-030-29739-8_12

67.

Zhang

Bartol

K. M.

(2010). Linking empowering leadership and employee creativity: The influence of psychological empowerment, intrinsic motivation, and creative process engagement. Academy of Management Journal, 53(1), 107–128. https://doi.org/10.1108/dlo.2010.08124ead.007

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB