SME B2B E-Commerce and Customer Loyalty Revisited
Bibliographic record
Abstract
B2B electronic commerce is an important opportunity for small and medium-sized enterprises’ (SMEs), providing increased competition on a global scale and allowing them to access wider markets. SMEs’ B2B electronic commerce success is tied to the ability to foster inter-organizational relationships and customer loyalty. However, this is not always true because many SMEs have difficulty achieving B2B benefits as suggested by media and early research. This study is an empirical examination of the effect of web tools on the inter-organizational relationships (IOR) between SMEs and their loyal customers. Data collected from 386 SMEs in North America (United States and Canada) and processed with Partial Least Square (PLS) show that the use of web tools (which include the level of web content and the level of security on the Internet) has a positive effect on the relationship between cooperation and interdependence, and customer loyalty. However, the effect of web tools on the relationship between trust and customer loyalty is different, because the use of non-secure web tools reduces the effect of trust on customer loyalty, and surprisingly, the use of secure web tools doesn’t increase or decrease the effect of trust on customer loyalty. This research also suggests that one of the factors of the failure or the success of SMEs’ B2B e-commerce is the technical skills of the managers in the use of secure web tools—high skill levels increase the positive effect of trust on customer loyalty. The implications of the results for the study are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.020 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".