Abstract
The study focuses on organizational alignment and procurement officials' behaviour in big data programs across Bhutanese procuring agencies. Despite a digitalized procurement system, there is little evidence of integrating big data methods into real-time procurement decisions in the country. A mixed-method study approach has been employed to investigate the use of big data. This study used stratified and purposive sampling techniques to determine 41 sample sizes. The 41 respondents (32 males and 9 females), the procurement professionals of government agencies were involved in a three-month long survey. Thematic analysis and descriptive statistics, such as the Relative Importance Index(RII), were adopted to analyze the data, with the Toulmin Argument Model used for literature reviews. The results were presented in various figures and tables. Around 70% of the respondents believe that big data analytics can be used to generate procurement reports. The highest RII score of 0.81 is with the significance of data accessibility and understanding for improving the procurement decision-making process. Likewise, most respondents believe in the importance of big data to assess new opportunities for better alignment across the agencies(0.80). Additionally, the RII score for individuals' reactions to complex data analysis was also high (0.80), indicating their belief that it could benefit procuring agencies. Procurement experts are likely to view big data as a useful instrument for improving procurement procedures and enhancing their value. The accountability and transparency of the procuring agency may increase if big data analytics is being implemented. To fully realize the potential benefits of big data in procurement, it is recommended to establish realistic and attainable initiatives to promote procurement technology in various government agencies in Bhutan.
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Data availability
The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.
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Acknowledgements
We would like to express our sincere gratitude to all the respondents who participated in this study. Their willingness to share their experiences, insights, and perspectives has been invaluable in generating meaningful and relevant findings. Their contribution has played a crucial role in shaping the conclusions and implications of this study. We would also like to extend my appreciation to the reviewers and SPRINGER editorial team who dedicated their time and expertise to providing constructive feedback and valuable suggestions for improving the quality of this study. Their insightful comments and recommendations have significantly contributed to refining the conclusions and enhancing the overall coherence of this study. Their contributions have been instrumental in the successful completion of this project, and I am truly grateful for their participation. Finally, we would like to extend our appreciation to Grammarly, an American cloud-based typing assistant for its invaluable assistance in refining the grammar and language of this study paper enhancing the overall readability of the manuscript.
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The authors declare that a grant of Nu.49,000(Forty-Nine Thousand Only) was received during the preparation of this manuscript from Jigme Namgyel Engineering College as a College Annual Study Grant 2022–2-23 award under grant No. JNEC-ADM-19/2–2022-2023. This grant was initiated as per the Jigme Namgyel Engineering College Study Policy (JNECRP2021) to encourage teaching faculty to conduct studies besides normal duty. The fund is subject to annual auditing as per the law of the country.
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The studyers do not foresee considerable ethical issues considering the nature of the study during the project. However, in the process of data collection, there will be encounters with questionnaire respondents and other interviewees. All personal credentials of the interviewees are completely protected. Regarding the information from the case studies, grey articles, and journal articles, a proper acknowledgement will be provided. In brief, the studyer will ensure respect, free plagiarism, and acknowledgement for the use of other resources as well as avoid using exclusive languages such as sexiest, racist, homophobic and so on. Regarding the nature of the survey and questionnaire, it will not include controversial and offensive questions. Further, the study will strictly follow the University’s study guidelines.
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Wangchuk, P., Jie, F. & Wangdi, K. Big data analytics in the procurement process: organizational alignment and the behavior of procurement professionals in bhutanese procuring agencies. J. of Data, Inf. and Manag. 6, 15–27 (2024). https://doi.org/10.1007/s42488-023-00109-6
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DOI: https://doi.org/10.1007/s42488-023-00109-6