Consumer Transactions with Smes: Implications for Consumer Scholars
Bibliographic record
Abstract
Much consumer research focuses on the relationship of the consumer with large businesses.This literature review examines the transactions that occur between consumers and small- to medium-sized enterprises (SMEs) in Canada.Four significant players in the consumer movement are identified -- consumers, government, consumer organizations, and sellers (i.e.,large corporations, manufacturers, trade/industry associations).The conflicts experienced both by small businesses and by consumers are compared. Previous research on job satisfaction, training, and customer service for SME employees is presented.The characteristics of SMEs in Canada are described, as drawn from a number of governmental and private data sources, as are their interactions with consumers.Job security, job creation, and consumer interest are explored in terms of how they are impacted by consumer patronage and by consumer employment at an SME.Earning and spending power are also affected by working at an SME.The link between the consumer and the SME is investigated further regarding business success or failure, firm distance from the consumer, firm financial support from foreign investors, firm support of environmental and social causes, and firm knowledge of e-commerce. In summarizing the research, several limitations and risks to both SMEs and consumers are presented.Future research and recommended areas of study are provided. (AKP)
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 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".