Unlocking Digital Potential: Technological Capability as a Key Moderator-Mediator in Migrant Workers' Use of JMO Mobile

Authors

  • Tarimantan Sanberto Saragih Student of Doctoral Program in Leadership and Policy Innovation, Graduate School of Gadjah Mada University, Indonesia Author
  • Ratminto Promoter of Doctoral Program in Leadership and Policy Innovation, Graduate School of Gadjah Mada University, Indonesia Author
  • Achmad Djunaedi Co-promoter of Doctoral Program in Leadership and Policy Innovation, Graduate School of Gadjah Mada University, Indonesia Author
  • Hakimul Ikhwan Co-promoter of Doctoral Program in Leadership and Policy Innovation, Graduate School of Gadjah Mada University, Indonesia Author
  • Arief Dahyan Social Security Administration Agency (BPJS) for employment. Indonesia Author
  • An Nisa Pramasanti an.nisa@bpjsketenagakerjaan.go.id Author
  • Fergie Stevi Mahaganti Social Security Administration Agency (BPJS) for employment. Indonesia Author

DOI:

https://doi.org/10.56294/dm2025727

Keywords:

Perceived Ease of Use, Technological Capability, Technology Adoption, Perceived Benefits, Organizational Support

Abstract

This study aims to examine the factors influencing technology adoption (TA) among Indonesian migrant workers, particularly in the use of the JMO Mobile application. The research integrates technological capability (TC) as both a moderating and mediating variable within the TAM to provide a more comprehensive understanding of adoption behavior. Specifically, the study investigates the impact of Perceived Ease of Use (PEOU), Perceived Benefits (PB), and organizational support on TC and TA. The research employs a quantitative approach using a survey method, collecting data from Indonesian migrant workers who use the JMO Mobile application. PLS-SEM is applied to analyze the links among the variables. The findings reveal that PEOU, PB, and organizational support significantly influence both TC and TA. Furthermore, TC serves as a moderator, strengthening the link between PEOU and TA, as well as between PB and TA. Additionally, TC functions as a mediator between PEOU and TA, and between organizational support and TA, indicating its critical role in facilitating the adoption process. These findings have practical implications for improving the technological engagement of Indonesian migrant workers. By enhancing user-friendly features, providing clear benefits, and offering organizational support through training programs, applications like JMO Mobile can better meet migrant workers' needs. The study contributes to the theoretical expansion of the TAM by incorporating TC as a key factor influencing adoption. The originality of this research lies in its focus on Indonesian migrant workers, a group that has received limited attention in TA studies, and its integration of TC as both a moderating and mediating variable.

References

1. Kraus S, Jones P, Kailer N, Weinmann A, Chaparro-Banegas N, Roig-Tierno N. Digital transformation: An overview of the current state of the art of research. Sage Open. 2021;11(3):1–15. DOI: https://doi.org/10.1177/21582440211047576

2. Saniuk S, Grabowska S, Straka M. Identification of social and economic expectations: Contextual reasons for the transformation process of Industry 4.0 into the Industry 5.0 concept. Sustainability. 2022;14(3):1391. DOI: https://doi.org/10.3390/su14031391

3. Zhang J, Li M. Digital technology access, labor market behavior, and income inequality in rural China. Heliyon. 2024;10(14). DOI: https://doi.org/10.1016/j.heliyon.2024.e33528

4. Garabiles MR, Gagni EMF, Corpus AMFL, Alonzo VB, Opiniano JM. Mapping and Evaluating the Localized Migrant Assistance Services in Ilocos Norte, Philippines: An Asset-Based and Multi-Stakeholder Approach. J Soc Serv Res. 2024;50(6):1058–74. DOI: https://doi.org/10.1080/01488376.2024.2393411

5. Moeda F. The Analysis of the Effectiveness of Jamsostek Mobile Integration in Increasing Settlement of Old Age Security Claims. Monet J Keuang dan Perbank. 2024;12(2):458–72.

6. Pratistha IGNY, Mahyuni LP. Jamsostek Mobile (JMO): Analysis of Service Quality from a Digital Application on BPJS Ketenagakerjaan Member’s Satisfaction. In: 2024 10th International Conference on Smart Computing and Communication (ICSCC). IEEE; 2024. p. 576–81. DOI: https://doi.org/10.1109/ICSCC62041.2024.10690539

7. Parsons TD, McMahan T, Kane R. Practice parameters facilitating adoption of advanced technologies for enhancing neuropsychological assessment paradigms. Clin Neuropsychol. 2018;32(1):16–41. DOI: https://doi.org/10.1080/13854046.2017.1337932

8. Kouhizadeh M, Saberi S, Sarkis J. Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers. Int J Prod Econ. 2021;231:107831. DOI: https://doi.org/10.1016/j.ijpe.2020.107831

9. Bansal A, Panchal T, Jabeen F, Mangla SK, Singh G. A study of human resource digital transformation (HRDT): A phenomenon of innovation capability led by digital and individual factors. J Bus Res. 2023;157:113611. DOI: https://doi.org/10.1016/j.jbusres.2022.113611

10. Sailer M, Stadler M, Schultz-Pernice F, Franke U, Schöffmann C, Paniotova V, et al. Technology-related teaching skills and attitudes: Validation of a scenario-based self-assessment instrument for teachers. Comput Human Behav. 2021;115:106625. DOI: https://doi.org/10.1016/j.chb.2020.106625

11. Wiesböck F, Hess T, Spanjol J. The dual role of IT capabilities in the development of digital products and services. Inf Manag. 2020;57(8):103389. DOI: https://doi.org/10.1016/j.im.2020.103389

12. Vargo D, Zhu L, Benwell B, Yan Z. Digital technology use during COVID‐19 pandemic: A rapid review. Hum Behav Emerg Technol. 2021;3(1):13–24. DOI: https://doi.org/10.1002/hbe2.242

13. Rydzik A, Kissoon CS. Decent work and tourism workers in the age of intelligent automation and digital surveillance. In: A Sustainable Tourism Workforce. Routledge; 2024. p. 244–61. DOI: https://doi.org/10.4324/9781003435457-14

14. Graham M, Hjorth I, Lehdonvirta V. Digital labour and development: impacts of global digital labour platforms and the gig economy on worker livelihoods. Transf Eur Rev labour Res. 2017;23(2):135–62. DOI: https://doi.org/10.1177/1024258916687250

15. Zeng Y, Li Y. Understanding the use of digital finance among older internet users in urban China: Evidence from an online convenience sample. Educ Gerontol. 2023;49(6):477–90. DOI: https://doi.org/10.1080/03601277.2022.2126341

16. Huda M. Towards digital access during pandemic age: better learning service or adaptation struggling? Foresight. 2023;25(1):82–107. DOI: https://doi.org/10.1108/FS-09-2021-0184

17. Martín-García A V, Redolat R, Pinazo-Hernandis S. Factors influencing intention to technological use in older adults. The TAM model aplication. Res Aging. 2022;44(7–8):573–88. DOI: https://doi.org/10.1177/01640275211063797

18. Ma J, Wang P, Li B, Wang T, Pang XS, Wang D. Exploring User Adoption of ChatGPT: A Technology Acceptance Model Perspective. Int J Human–Computer Interact. 2024;1–15.

19. Mohd Amir RI, Mohd IH, Saad S, Abu Seman SA, Tuan Besar TBH. Perceived ease of use, perceived usefulness, and behavioral intention: the acceptance of crowdsourcing platform by using technology acceptance model (TAM). In: Charting a Sustainable Future of ASEAN in Business and Social Sciences: Proceedings of the 3rd International Conference on the Future of ASEAN (ICoFA) 2019—Volume 1. Springer; 2020. p. 403–10. DOI: https://doi.org/10.1007/978-981-15-3859-9_34

20. Tubaishat A. Perceived usefulness and perceived ease of use of electronic health records among nurses: Application of Technology Acceptance Model. Informatics Heal Soc Care. 2018;43(4):379–89. DOI: https://doi.org/10.1080/17538157.2017.1363761

21. Dubey P, Sahu KK. Students’ perceived benefits, adoption intention and satisfaction to technology-enhanced learning: examining the relationships. J Res Innov Teach Learn. 2021;14(3):310–28. DOI: https://doi.org/10.1108/JRIT-01-2021-0008

22. Hasani T, Rezania D, Levallet N, O’Reilly N, Mohammadi M. Privacy enhancing technology adoption and its impact on SMEs’ performance. Int J Eng Bus Manag. 2023;15:18479790231172870. DOI: https://doi.org/10.1177/18479790231172874

23. Ray A, Bala PK, Dasgupta SA. Role of authenticity and perceived benefits of online courses on technology based career choice in India: A modified technology adoption model based on career theory. Int J Inf Manage. 2019;47:140–51. DOI: https://doi.org/10.1016/j.ijinfomgt.2019.01.015

24. Al Hadwer A, Tavana M, Gillis D, Rezania D. A systematic review of organizational factors impacting cloud-based technology adoption using technology-organization-environment framework. Internet of Things. 2021;15:100407. DOI: https://doi.org/10.1016/j.iot.2021.100407

25. Hsu H-Y, Liu F-H, Tsou H-T, Chen L-J. Openness of technology adoption, top management support and service innovation: a social innovation perspective. J Bus Ind Mark. 2019;34(3):575–90. DOI: https://doi.org/10.1108/JBIM-03-2017-0068

26. Davis FD, Bagozzi RP, Warshaw PR. Technology acceptance model. J Manag Sci. 1989;35(8):982–1003. DOI: https://doi.org/10.1287/mnsc.35.8.982

27. Venkatesh V, Davis FD. A model of the antecedents of perceived ease of use: Development and test. Decis Sci. 1996;27(3):451–81. DOI: https://doi.org/10.1111/j.1540-5915.1996.tb00860.x

28. Kumar RL, Smith MA, Bannerjee S. User interface features influencing overall ease of use and personalization. Inf Manag. 2004;41(3):289–302. DOI: https://doi.org/10.1016/S0378-7206(03)00075-2

29. Salahshour Rad M, Nilashi M, Mohamed Dahlan H. Information technology adoption: a review of the literature and classification. Univers Access Inf Soc. 2018;17:361–90. DOI: https://doi.org/10.1007/s10209-017-0534-z

30. Putro AK, Takahashi Y. Entrepreneurs’ creativity, information technology adoption, and continuance intention: Mediation effects of perceived usefulness and ease of use and the moderation effect of entrepreneurial orientation. Heliyon. 2024;10(3). DOI: https://doi.org/10.1016/j.heliyon.2024.e25479

31. Jeong S, Kim S, Lee S. Effects of Perceived Ease of Use and Perceived Usefulness of Technology Acceptance Model on Intention to Continue Using Generative AI: Focusing on the Mediating Effect of Satisfaction and Moderating Effect of Innovation Resistance. In: International Conference on Conceptual Modeling. Springer; 2024. p. 99–106. DOI: https://doi.org/10.1007/978-3-031-75599-6_7

32. Isiaku L, Adalier A. Determinants of business intelligence systems adoption in Nigerian banks: The role of perceived usefulness and ease of use. Inf Dev. 2024;02666669241307024. DOI: https://doi.org/10.1177/02666669241307024

33. Nguyen TTU, Van Nguyen P, Huynh HTN, Truong GQ, Do L. Unlocking e-government adoption: Exploring the role of perceived usefulness, ease of use, trust, and social media engagement in Vietnam. J Open Innov Technol Mark Complex. 2024;10(2):100291. DOI: https://doi.org/10.1016/j.joitmc.2024.100291

34. Cimbaljević M, Demirović Bajrami D, Kovačić S, Pavluković V, Stankov U, Vujičić M. Employees’ technology adoption in the context of smart tourism development: the role of technological acceptance and technological readiness. Eur J Innov Manag. 2024;27(8):2457–82. DOI: https://doi.org/10.1108/EJIM-09-2022-0516

35. Attié E, Meyer-Waarden L. The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy calculus theories. Technol Forecast Soc Change. 2022;176:121485. DOI: https://doi.org/10.1016/j.techfore.2022.121485

36. Indulska M, Green P, Recker J, Rosemann M. Business process modeling: Perceived benefits. In: Conceptual Modeling-ER 2009: 28th International Conference on Conceptual Modeling, Gramado, Brazil, November 9-12, 2009 Proceedings 28. Springer; 2009. p. 458–71. DOI: https://doi.org/10.1007/978-3-642-04840-1_34

37. Ianole-Călin R, Druică E. A risk integrated technology acceptance perspective on the intention to use smart grid technologies in residential electricity consumption. J Clean Prod. 2022;370:133436. DOI: https://doi.org/10.1016/j.jclepro.2022.133436

38. Jo H, Park D-H. AI in the workplace: Examining the effects of ChatGPT on information support and knowledge acquisition. Int J Human–Computer Interact. 2024;40(23):8091–106. DOI: https://doi.org/10.1080/10447318.2023.2278283

39. Dolmark T, Sohaib O, Beydoun G, Wu K. The effect of individual’s technological belief and usage on their absorptive capacity towards their learning behaviour in learning environment. Sustainability. 2021;13(2):718. DOI: https://doi.org/10.3390/su13020718

40. Stamenkov G, Zhaku-Hani R. Perceived benefits and post-adoption usage of education management information system. Libr Hi Tech. 2023;41(4):1063–83. DOI: https://doi.org/10.1108/LHT-06-2021-0185

41. Al-Okaily A, Teoh AP, Al-Okaily M. Evaluation of data analytics-oriented business intelligence technology effectiveness: an enterprise-level analysis. Bus Process Manag J. 2023;29(3):777–800. DOI: https://doi.org/10.1108/BPMJ-10-2022-0546

42. Featherman M, Jia SJ, Califf CB, Hajli N. The impact of new technologies on consumers beliefs: Reducing the perceived risks of electric vehicle adoption. Technol Forecast Soc Change. 2021;169:120847. DOI: https://doi.org/10.1016/j.techfore.2021.120847

43. Leso BH, Cortimiglia MN, Ghezzi A. The contribution of organizational culture, structure, and leadership factors in the digital transformation of SMEs: a mixed-methods approach. Cogn Technol Work. 2023;25(1):151–79. DOI: https://doi.org/10.1007/s10111-022-00714-2

44. Faqih KMS, Jaradat M-IRM. Integrating TTF and UTAUT2 theories to investigate the adoption of augmented reality technology in education: Perspective from a developing country. Technol Soc. 2021;67:101787. DOI: https://doi.org/10.1016/j.techsoc.2021.101787

45. Rhoades L, Eisenberger R. Perceived organizational support: a review of the literature. J Appl Psychol. 2002;87(4):698. DOI: https://doi.org/10.1037//0021-9010.87.4.698

46. Sharma D, Sahoo CK. Social support and self-employment intentions of professional and technical students in India: The moderating role of organizational support. J Educ Bus. 2024;99(3):155–63. DOI: https://doi.org/10.1080/08832323.2023.2293719

47. Mustapha S, Man N, Arif Shah J, Hirawaty Kamaruzzaman N, Abubakar Tafida A. Mediating Role of Motivation in the Relationships between Awareness, Accessibility, Perceived Organizational Support and Adoption of ICT among Extension Agents in North-East, Nigeria. J Agric Sci Technol. 2022;24(6):1313–29. DOI: https://doi.org/10.52547/jast.24.6.1313

48. Soomro S, Fan M, Sohu JM, Soomro S, Shaikh SN. AI adoption: a bridge or a barrier? The moderating role of organizational support in the path toward employee well-being. Kybernetes. 2024; DOI: https://doi.org/10.1108/K-07-2024-1889

49. Xie Y, Chen Z, Khan A, Ke S. Organizational support, market access, and farmers’ adoption of agricultural green production technology: evidence from the main kiwifruit production areas in Shaanxi Province. Environ Sci Pollut Res. 2024;31(8):12144–60. DOI: https://doi.org/10.1007/s11356-024-31981-3

50. Díaz-Arancibia J, Hochstetter-Diez J, Bustamante-Mora A, Sepúlveda-Cuevas S, Albayay I, Arango-López J. Navigating digital transformation and technology adoption: A literature review from small and medium-sized enterprises in developing countries. Sustainability. 2024;16(14):5946. DOI: https://doi.org/10.3390/su16145946

51. Coombs JE, Bierly III PE. Measuring technological capability and performance. R&D Manag. 2006;36(4):421–38. DOI: https://doi.org/10.1111/j.1467-9310.2006.00444.x

52. Khin S, Ho TC. Digital technology, digital capability and organizational performance a mediating role of digital innovation. Int J Innov Sci. 2019;11(2):177–95. DOI: https://doi.org/10.1108/IJIS-08-2018-0083

53. Graham K, Moore R. The role of dynamic capabilities in firm-level technology adoption processes: A qualitative investigation. J Innov Manag. 2021;9(1):25–50. DOI: https://doi.org/10.24840/2183-0606_009.001_0004

54. Jalil MF, Ali A, Kamarulzaman R. Does innovation capability improve SME performance in Malaysia? The mediating effect of technology adoption. Int J Entrep Innov. 2022;23(4):253–67. DOI: https://doi.org/10.1177/14657503211048967

55. Tallon PP, Queiroz M, Coltman T, Sharma R. Information technology and the search for organizational agility: A systematic review with future research possibilities. J Strateg Inf Syst. 2019;28(2):218–37. DOI: https://doi.org/10.1016/j.jsis.2018.12.002

56. Malik S, Chadhar M, Vatanasakdakul S, Chetty M. Factors affecting the organizational adoption of blockchain technology: Extending the technology–organization–environment (TOE) framework in the Australian context. Sustainability. 2021;13(16):9404. DOI: https://doi.org/10.3390/su13169404

57. Zhang Y, Sun J, Yang Z, Wang Y. Critical success factors of green innovation: Technology, organization and environment readiness. J Clean Prod. 2020;264:121701. DOI: https://doi.org/10.1016/j.jclepro.2020.121701

58. Polisetty A, Chakraborty D, Kar AK, Pahari S. What determines AI adoption in companies? Mixed-method evidence. J Comput Inf Syst. 2024;64(3):370–87. DOI: https://doi.org/10.1080/08874417.2023.2219668

59. Uren V, Edwards JS. Technology readiness and the organizational journey towards AI adoption: An empirical study. Int J Inf Manage. 2023;68:102588. DOI: https://doi.org/10.1016/j.ijinfomgt.2022.102588

60. Taherdoost H. A review of technology acceptance and adoption models and theories. Procedia Manuf. 2018;22:960–7. DOI: https://doi.org/10.1016/j.promfg.2018.03.137

61. de Assis Dornelles J, Ayala NF, Frank AG. Smart Working in Industry 4.0: How digital technologies enhance manufacturing workers’ activities. Comput Ind Eng. 2022;163:107804. DOI: https://doi.org/10.1016/j.cie.2021.107804

62. Warner KSR, Wager M. Building dynamic capabilities for digital transformation: an ongoing process of strategic renewal. Long Range Plann. 2019;52(3):326–34. DOI: https://doi.org/10.1016/j.lrp.2018.12.001

63. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989;13(3):319–340. DOI: https://doi.org/10.2307/249008

64. Shirazi F, Hajli N, Sims J, Lemke F. The role of social factors in purchase journey in the social commerce era. Technol Forecast Soc Change. 2022;183:121861. DOI: https://doi.org/10.1016/j.techfore.2022.121861

65. Al-Abdullatif AM. Towards Digitalization in Early Childhood Education: Pre-Service Teachers’ Acceptance of Using Digital Storytelling, Comics, and Infographics in Saudi Arabia. Vol. 12, Education Sciences. 2022. DOI: https://doi.org/10.3390/educsci12100702

66. Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q. 2003;27(3):425–478. DOI: https://doi.org/10.2307/30036540

67. Igbaria M, Tan M. The consequences of information technology acceptance on subsequent individual performance. Inf Manag. 1997;32(3):113–21. DOI: https://doi.org/10.1016/S0378-7206(97)00006-2

68. Kwon TH. Unifying the Fragmented Models of Information Systems Implementation. Crit Issues Inf Syst Res Wiley. 1987;

69. Chauhan J, Mishra G, Bhakri S. Career Success of Women: Role of Family Responsibilities, Mentoring, and Perceived Organizational Support. Vision. 2021 Jul;26(1):105–17. DOI: https://doi.org/10.1177/09722629211024887

70. Agarwal R, Prasad J. The antecedents and consequents of user perceptions in information technology adoption. Decis Support Syst. 1998;22(1):15–29. DOI: https://doi.org/10.1016/S0167-9236(97)00006-7

71. Yu W, Zhao G, Liu Q, Song Y. Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective. Technol Forecast Soc Change. 2021;163:120417. DOI: https://doi.org/10.1016/j.techfore.2020.120417

72. Smidt HJ, Jokonya O. Factors affecting digital technology adoption by small-scale farmers in agriculture value chains (AVCs) in South Africa. Inf Technol Dev. 2022 Jul;28(3):558–84. DOI: https://doi.org/10.1080/02681102.2021.1975256

73. Yu H, Jiang S, Land KC. Multicollinearity in hierarchical linear models. Soc Sci Res. 2015;53:118–36. DOI: https://doi.org/10.1016/j.ssresearch.2015.04.008

74. Henseler J, Sarstedt M. Goodness-of-fit indices for partial least squares path modeling. Comput Stat. 2013;28(2):565–80. DOI: https://doi.org/10.1007/s00180-012-0317-1

75. Hair JF, Ringle CM, Gudergan SP, Fischer A, Nitzl C, Menictas C. Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice. Bus Res. 2019;12:115–42. DOI: https://doi.org/10.1007/s40685-018-0072-4

76. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18(1):39–50. DOI: https://doi.org/10.1177/002224378101800104

77. Nunnally JC. Psychometric theory—25 years ago and now. Educ Res. 1975;4(10):7–21. DOI: https://doi.org/10.3102/0013189X004010007

78. Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci. 2015;43(1):115–35. DOI: https://doi.org/10.1007/s11747-014-0403-8

79. Preacher KJ, Curran PJ, Bauer DJ. Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. J Educ Behav Stat. 2006;31(4):437–48. DOI: https://doi.org/10.3102/10769986031004437

80. Chan XY, Rahman MK, Mamun A Al, A. Salameh A, Wan Hussain WMH, Alam SS. Predicting the intention and adoption of mobile shopping during the COVID-19 lockdown in Malaysia. Sage Open. 2022;12(2):21582440221095012. DOI: https://doi.org/10.1177/21582440221095012

81. Zhang J, Riaz M, Boamah FA, Ali S. Harnessing technological innovation capabilities by the mediating effect of willingness to share tacit knowledge: a case from Pakistani software SMEs. Kybernetes. 2023;52(12):6590–616. DOI: https://doi.org/10.1108/K-09-2021-0845

82. Kharis A, Suci W, Priatna Y. Social Sciences & Humanities Open Strategic decision-making : Linking corporate choices , social responsibility , and environmental accounting in waste management. 2025;11(March). DOI: https://doi.org/10.1016/j.ssaho.2025.101404

83. Ika Sari G, Winasis S, Pratiwi I, Wildan Nuryanto U, Basrowi. Strengthening digital literacy in Indonesia: Collaboration, innovation, and sustainability education. Soc Sci Humanit Open [Internet]. 2024;10(May):101100. Available from: https://doi.org/10.1016/j.ssaho.2024.101100 DOI: https://doi.org/10.1016/j.ssaho.2024.101100

84. Janmethakulwat A, Thanasopon B. Digital technology adoption and institutionalization in Thai maritime industry: An exploratory study of the Thai shipowners. Asian J Shipp Logist. 2024;40(3):157–66. DOI: https://doi.org/10.1016/j.ajsl.2024.08.001

85. Jaiswal D, Kant R, Mehta B. Consumer adoption of battery electric cars: analyzing techno-psychological perception-attitude-intention linkage perspective and gender effects. Int J Energy Sect Manag. 2024 Jan;ahead-of-p(ahead-of-print). DOI: https://doi.org/10.1108/IJESM-04-2024-0009

86. Uda SK, Prasetyo D, Dopo ESEB, Uda SAKA, Basrowi. Development of Mobile Learning Application System for Environmental Science Material (SARITHA-Apps). Int J Inf Educ Technol. 2024;14(3):452–63. DOI: https://doi.org/10.18178/ijiet.2024.14.3.2066

87. Berkat, Setinawati, Basrowi. The role of educational management in enhancing innovation and problem-solving competencies for students towards global competitiveness: A literature review. Soc Sci Humanit Open [Internet]. 2025;11(June 2024):101280. Available from: https://doi.org/10.1016/j.ssaho.2025.101280 DOI: https://doi.org/10.1016/j.ssaho.2025.101280

88. Himel MTA, Ashraf S, Bappy TA, Abir MT, Morshed MK, Hossain MN. Users’ attitude and intention to use mobile financial services in Bangladesh: an empirical study. South Asian J Mark. 2021 Jan;2(1):72–96. DOI: https://doi.org/10.1108/SAJM-02-2021-0015

89. Nuryanto UW, Basrowi, Quraysin I, Pratiwi I. Harmonizing eco-control and eco-friendly technologies with green investment: Pioneering business innovation for corporate sustainability in the Indonesian context. Environ Challenges [Internet]. 2024;15(March):100952. Available from: https://doi.org/10.1016/j.envc.2024.100952 DOI: https://doi.org/10.1016/j.envc.2024.100952

90. Lam L, Nguyen P, Le N, Tran K. The Relation among Organizational Culture, Knowledge Management, and Innovation Capability: Its Implication for Open Innovation. J Open Innov Technol Mark Complex. 2021;7(1):66. DOI: https://doi.org/10.3390/joitmc7010066

91. Nuryanto UW, Basrowi, Quraysin I, Pratiwi I. Magnitude of digital adaptability role: Stakeholder engagement and costless signaling in enhancing sustainable MSME performance. Heliyon [Internet]. 2024;10(13):e33484. Available from: https://doi.org/10.1016/j.heliyon.2024.e33484 DOI: https://doi.org/10.1016/j.heliyon.2024.e33484

92. Nuryanto UW, Basrowi, Quraysin I, Pratiwi I. Environmental management control system, blockchain adoption, cleaner production, and product efficiency on environmental reputation and performance: Empirical evidence from Indonesia. Sustain Futur [Internet]. 2024;7(March):100190. Available from: https://doi.org/10.1016/j.sftr.2024.100190 DOI: https://doi.org/10.1016/j.sftr.2024.100190

93. Purwaningsih E, Muslikh, Fathurahman M, Basrowi. Optimization of Branding and Value Chain Mapping Using Artificial Intelligence for the Batik Village Clusters in Indonesia to Achieve Competitive Advantage. Data Metadata. 2024;3. DOI: https://doi.org/10.56294/dm2024.620

94. Fauzi, Basrowi, Wulandari, Irviani R. Fostering sustainability through leadership and employee personality traits. Sustain Futur [Internet]. 2025;9(February):100502. Available from: https://doi.org/10.1016/j.sftr.2025.100502. DOI: https://doi.org/10.1016/j.sftr.2025.100502

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2025-03-28

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Sanberto Saragih T, Ratminto R, Djunaedi A, Ikhwan H, Dahyan A, Nisa Pramasanti A, et al. Unlocking Digital Potential: Technological Capability as a Key Moderator-Mediator in Migrant Workers’ Use of JMO Mobile. Data and Metadata [Internet]. 2025 Mar. 28 [cited 2025 Nov. 30];4:727. Available from: https://dm.ageditor.ar/index.php/dm/article/view/727