Journal of Electronic Science and Technology, Volume. 22, Issue 1, 100229(2024)
Evaluation of a software positioning tool to support SMEs in adoption of big data analytics
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Fig. 2. Screenshot of the score entry sheet with the scores for the third stage of the positioning study.
Fig. 5. Comparison between the analytical, IT, and SME practitioner groups.
Fig. 6. Comparison between the participants from SMEs and large businesses.
Table 1. Evaluation criteria.
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Evaluation criteria Definition Reference Easy to learn The extent to which the participant believes that SMEs in the UK can learn how to use HBDAF-UKSMEs and the scoring tool. [ 30 ,46 ]Easy to use The extent to which the user believes that the HBDAF-UKSMEs scoring tool is easy to use. [ 30 ,46 ,47 ]Usefulness The extent to which the participant believes that HBDAF-UKSMEs would be beneficial for SMEs in the UK. [ 30 ,47 ,48 ]Comprehensiveness The extent to which the participant believes that HBDAF-UKSMEs incorporate all of the barriers encountered by SMEs in the UK to adopting big data analytics. [ 49 ]Adaptability SMEs can operate in different sectors such as manufacturing or retail, and the size of the business can vary. Therefore, adaptability represents the degree to which the participant believes that the scoring tool can be adapted by different SMEs. [ 30 ,46 ]Intention to use The extent to which the participant believes SMEs in the UK will utilise the HBDAF-UKSMEs scoring tool. [ 47 ,48 ]
Table 2. Five-point evaluation template.
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Question 1 2 3 4 5 Participant score How easy is it to learn? Very difficult Difficult Neither difficult nor easy Easy Very easy How easy is it to use? Very difficult Difficult Neither difficult nor easy Easy Very easy How useful is it to SMEs in the UK? Not at all useful Not useful but could be with substantial modification Useful but would require some modification Useful Very useful How comprehensive is the scoring tool and framework? Not at all Not sufficiently comprehensive as important elements are missing Fairly comprehensive Comprehensive Very comprehensive How easy is the framework and scoring tool to adapt to your business? Very difficult Difficult Neither difficult nor easy Easy Very easy How likely would you be to use the framework and scoring tool if you were in a position to? Very unlikely Unlikely Neither unlikely nor likely Likely Very likely
Table 3. Participants.
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No. Participant’s position Work for SME Category Domain 1 Business owner Yes SME practitioner Recruitment 2 Head transport planner Yes SME practitioner Logistics 3 Office manager Yes SME practitioner Automotive 4 Project manager Yes SME practitioner Higher manufacturing 5 Statistician No Analytical Healthcare 6 Accountant Yes Analytical Finance 7 IT manager Yes IT management Education 8 IT manager No IT management Education 9 Senior IT support officer No IT specialist Parcels 10 Geographic mapping information system’s officer No IT specialist Local government
Table 4. Evaluation scores.
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Criteria 1 2 3 4 5 Easy to learn 0 0 0 7 3 Easy to sse 0 0 0 6 4 Usefulness 0 0 0 7 3 Comprehensiveness 0 0 0 7 3 Adaptability 0 0 1 6 3 Intention to use 0 0 1 5 4
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Matthew Willetts, Anthony S. Atkins. Evaluation of a software positioning tool to support SMEs in adoption of big data analytics[J]. Journal of Electronic Science and Technology, 2024, 22(1): 100229
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Received: Sep. 30, 2023
Accepted: Nov. 24, 2023
Published Online: Jul. 5, 2024
The Author Email: Willetts Matthew (matthew.willetts@research.staffs.ac.uk)
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