An empirical study of perceived strategic value and adoption constructs: the Ghanaian case
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine empirically the link between the determinants of perceived strategic value (PSV) of e‐commerce and e‐commerce adoption among Ghanaian small and medium size enterprises (SMEs), defined as businesses that employ a maximum of 200 employees. Design/methodology/approach The authors randomly sampled SME owners/managers from the membership of the Ghana Club 100 (GC 100) and non‐traditional exporters (NTEs). Established databases are not the norm in Ghana, and GC 100 and NTEs had membership databases that were accessible to the local co‐author. Investigating e‐commerce adoption issues among these companies was warranted. The authors used a structured instrument developed and validated in prior studies to collect the data in a face to face interview. A pilot study was conducted to ascertain the clarity and reliability of the questionnaire. Of the SME owners/managers: 200 were contacted; 112 agreed to participate in the study; 107 responses were obtained – representing a 53.5 per cent response rate. Statistical analysis was performed using SPSS 14. Findings Factor analysis demonstrated convergent and discriminant validity and construct reliability. PSV construct resulted in four factors: Strategic Decision Support (SD), Information Management (IM), Organizational Support (OS) and Decision Aids (DA). This finding is both consistent and inconsistent with prior research. The adoption construct yielded five factors: Perceived Usefulness (PU), Ease of Use (EU), Compatibility (C), Organisational Readiness (OS) and External Pressure (EP). There was more congruence between our results and those of prior research. Research limitations/implications Limitations stem from small sample size, the population and locale from which the sample was drawn. Practical implications The study has research and practical implications, and these are discussed fully in the paper. Originality/value The paper contributes to the knowledge of perceived strategic value and adoption of e‐commerce by SMEs in an under‐researched part of the world.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".