Assisting Disabled Persons in Online Shopping: A Knowledge-Based Process Model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Knowledge management is gaining more and more attention from business management with a consideration of knowledge as a critical intellectual resource for organization in getting successful competitive advantage. The aim of integrating of KM processes with business processes is to add value, provide supports and increase productivity. The role of technology for knowledge management processes, i.e., capture, codification, dissemination, is very important. Organization are readily adapting e-commerce and shifting business activities over web to maintain competitive advantage and building strong relationship with suppliers, employees, and customers.E-retailing emerged as a new way of shopping; people search/browse products online, compare and purchase with great convenience. It also eliminates barriers that disabled persons encounter when they visit shopping stores such as inaccessible entrance for wheelchair shoppers. However, still there is a significant part of disabled population is neglected from getting benefits of online shopping because of lack of accessibility features in websites. Understanding the knowledge about them can lead business managers to better facilitate in online shopping. This paper proposed a model based on the Nonaka Knowledge Spiral model to support business managers to capture knowledge about disabled person’s online shopping behaviors; supplement this knowledge into their website to support disabled persons. This also helps business managers to capture the un-attended population in their business net.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it