The Mediating Influence of Technology Adoption on Readiness Factors and Performance Results in Forensic Laboratories in Abu Dhabi

The increasing complexity of forensic investigations and the rapid advancement of digital technologies have intensified the need for effective technology adoption within forensic laboratories. Despite substantial governmental investments in digital transformation initiatives in Abu Dhabi, inconsistent performance outcomes suggest that technology availability alone does not guarantee operational improvement. This study investigates the mediating influence of technology adoption on the relationship between organizational readiness factors and performance outcomes in forensic laboratories in Abu Dhabi. Grounded in the Technology–Organization–Environment (TOE) framework, Diffusion of Innovations (DOI) theory, and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study conceptualizes organizational readiness as a higher-order construct comprising technological infrastructure, human capital, organizational support, external collaborations, and regulatory environment. Performance outcomes are operationalized through accuracy, efficiency, speed, data management, and operational effectiveness. A quantitative research design was employed using structured survey instruments distributed to personnel across forensic laboratories in Abu Dhabi. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess measurement validity, structural relationships, and mediation effects. The findings indicate that organizational readiness factors significantly influence technology adoption. Moreover, technology adoption demonstrates a significant mediating effect in the relationship between organizational readiness and performance outcomes. While organizational readiness also exerts a direct positive effect on performance, the mediation results confirm that effective adoption and utilization of advanced technologies serve as the primary mechanism through which readiness conditions translate into measurable operational improvements. This study contributes to technology adoption literature by extending mediation-based models to the underexplored forensic laboratory context. Practically, the findings provide strategic insights for policymakers and laboratory managers in Abu Dhabi to enhance organizational preparedness and maximize returns on technological investments, thereby strengthening forensic performance and supporting the criminal justice system.

Technology Adoption, Readiness Factors, Forensic Laboratories, Performance Results, UAE,

1. Ahmed, F., Qin, Y. J., & Martínez, L. (2019). Sustainable change management through employee readiness: Decision support system adoption in technology-intensive British e-businesses. Sustainability, 11(11), 2998. [Google Scholar] [Crossref]

2. Al Mansoori, A. S. N. A., Khatibi, A., & Azam, S. F. (2018). Determinants of leadership styles on organizational culture towards organization performance in abu dhabi public sector: structural equation modelling (SEM). European Journal of Social Sciences Studies. [Google Scholar] [Crossref]

3. Al Shamsi, R. (2025). Evaluation of employees’ views on technological changes in the Abu Dhabi Police, and a framework for effective change management (Doctoral dissertation, Nottingham Trent University (United Kingdom)). [Google Scholar] [Crossref]

4. Al-Matrouk, A., Aldasem, A., Haidar, M., & Mousawi, F. (2026). Quality assurance and quality control in forensic science: from evidence collection to laboratory analysis. In Investigative and Predictive DNA Testing (pp. 391-406). Academic Press. [Google Scholar] [Crossref]

5. Almehairbi, K. M. S. S., Jano, Z., & Mosali, N. A. (2022). Structural relationship of technology adoption and performance factors in UAE manufacturing industry. International Journal of Sustainable Construction Engineering and Technology, 13(4), 320-337. [Google Scholar] [Crossref]

6. Almessabi, A. M. A., & Kamalrudin, M. (2022). Proposed framework for Improving Standardisation of Forensic Laboratory Performance Through Laboratory Information Management Systems (LIMS). NeuroQuantology, 20(10), 8047. [Google Scholar] [Crossref]

7. Almutairi, H. A. S., Almesawa, I. H., Alhazmy, T. I., Alrehaili, A. A., Alsharif, M. M., & Alharbi, A. A. (2024). The Role of Laboratory-Based Theories in Enhancing Forensic Evidence Interpretation. Journal of International Crisis and Risk Communication Research, 7(S7), 784. [Google Scholar] [Crossref]

8. Altayari, W., Kamalrudin, M., & Jaber, M. M. (2022). The role of artificial intelligence in forensic evidence presentation. International journal of health sciences, (II), 5649-5662. [Google Scholar] [Crossref]

9. Balasubramanian, S., Shukla, V., Sethi, J. S., Islam, N., & Saloum, R. (2021). A readiness assessment framework for Blockchain adoption: A healthcare case study. Technological Forecasting and Social Change, 165, 120536. [Google Scholar] [Crossref]

10. Blut, M., & Wang, C. (2020). Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage. Journal of the Academy of marketing science, 48(4), 649-669. [Google Scholar] [Crossref]

11. Duhamel, F. B., Gutiérrez-Martínez, I., Cordova-Díaz, H., & Cue-Funes, S. (2023). Determinants of adoption of IS-based service innovations in government to create public value. Transforming Government: People, Process and Policy, 17(2), 204-217. [Google Scholar] [Crossref]

12. Ghaleb, E. A., Dominic, P. D. D., Fati, S. M., Muneer, A., & Ali, R. F. (2021). The assessment of big data adoption readiness with a technology–organization–environment framework: a perspective towards healthcare employees. Sustainability, 13(15), 8379. [Google Scholar] [Crossref]

13. Haddad, A., Ameen, A., Isaac, O., Alrajawy, I., Al-Shbami, A., & Midhun Chakkaravarthy, D. (2019). The impact of technology readiness on the big data adoption among UAE organisations. In Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 2 (pp. 249-264). Singapore: Springer Singapore. [Google Scholar] [Crossref]

14. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. [Google Scholar] [Crossref]

15. Hasani, S. (2024). Innovative behavior as a mediator: self-efficacy, supportive environment and creativity in employee performance. Journal on Innovation and Sustainability RISUS, 15(4), 90-109. [Google Scholar] [Crossref]

16. Hasani, T., Rezania, D., Levallet, N., O’Reilly, N., & Mohammadi, M. (2023). Privacy enhancing technology adoption and its impact on SMEs’ performance. International Journal of Engineering Business Management, 15, 18479790231172874. [Google Scholar] [Crossref]

17. Kaewsaengon, R. (2024). Organizational Readiness, Digital Technology, and Sustainable Performance: The Moderating Role of Knowledge Acquisition. Journal of Digitovation and information system, 4(1), 98-111. [Google Scholar] [Crossref]

18. Marcon, E., Soliman, M., Gerstlberger, W., & Frank, A. G. (2022). Sociotechnical factors and Industry 4.0: an integrative perspective for the adoption of smart manufacturing technologies. Journal of Manufacturing Technology Management, 33(2), 259-286. [Google Scholar] [Crossref]

19. Mouakket, S., & Aboelmaged, M. (2022). Drivers and outcomes of green information technology adoption in service organizations: an evidence from emerging economy context. Journal of Science and Technology Policy Management, 13(4), 898-924. [Google Scholar] [Crossref]

20. Nair, J., Chellasamy, A., & Singh, B. B. (2019). Readiness factors for information technology adoption in SMEs: testing an exploratory model in an Indian context. Journal of Asia Business Studies, 13(4), 694-718. [Google Scholar] [Crossref]

21. Nasrollahi, M., & Ramezani, J. (2020). A model to evaluate the organizational readiness for big data adoption. International Journal of Computers Communications & Control, 15(3). [Google Scholar] [Crossref]

22. Niguse, T., Borji, B., Amentie, C., & Kant, S. (2025). Effect of organization readiness on competitive advantage with mediating effect of human capital: A case of SMEs, Ethiopia. In Organizational readiness and research: Security, management, and decision making (pp. 25-52). IGI Global Scientific Publishing. [Google Scholar] [Crossref]

23. Otzen, T., & Manterola, C. (2017). Sampling techniques on a population study. International journal of morphology, 35(1), 227-232. [Google Scholar] [Crossref]

24. Ruangkanjanases, A., Hariguna, T., Adiandari, A. M., & Alfawaz, K. M. (2022). Assessing blockchain adoption in supply chain management, antecedent of technology readiness, knowledge sharing and trading need. Emerging Science Journal, 6(5), 921-937. [Google Scholar] [Crossref]

25. Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill-building approach (7th ed.). Wiley. [Google Scholar] [Crossref]

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