Apply GM(0,N) and Grey Relational Grade in the Relational Analysis of Business Items-An Example on the Chain Store 7-11
Notice bibliographique
Résumé
7-11 was originally started from the franchise, and it was founded in the United States. Now it is the largest chain convenience store worldwide. In November, 2005, the Japanese 7&I holding company had purchased the American 7-11. After that, 7-11 was positioned as a Japanese company. Nowadays, modern people are busy working, and they can't deal with the basic issues, like food, clothing, shelter and transportation. Hence, it enables the growth of 7-11. Currently, 7-11 has about 46,000 stores worldwide, and they distribute in the countries of Japan, the United States, Canada, Hong Kong, China, Macau, Taiwan, Singapore, Thailand, Malaysia, the Philippines and South Korea. 7-11 can not only solve the general problems, like food, clothing, shelter and transportation, it also provides collection business services in Taiwan. For example, it can deal with telephone bill, gas bill, parking bill, water bill, electricity bill, insurance bill, etc. In addition, 7-11 provides coupons, i-cash, Easy card, small-paid card and self-payment service. From the above explanations, we can understand that 7-11 is the company which makes a lot of profits, has marketing ability and vast network system. Hence, how to develop operating policies has become the first priority. In the past, there were many relevant studies and they provided good results. However, this paper started from the regional 7-11 business concept and proposed soft-calculation math method to analyze the bulk of purchasing items. Therefore, the paper used seven 7-11 convenience stores in a county in southern Taiwan as the research subject. Then the paper used globalization grey relational grade and GM(0,N) method in the grey system theory to analyze the yearly six business items, including beverages, bread, tobacco, alcohol, books and stationery. Also, the total turnover of the year was calculated as the output. The weighting of each impact factor can be reached and the main operation points can be found. Through the practical analysis and step by step math calculation, the relevant weighting of each factor in the turnover can be obtained. The clustering of the result by using two methods are quite same, which the stationary and books were ranked as the first and the tobacco is the last one, respectively. 7-11 stores’ main function is to provide convenient access to various materials and this is in line with the real situation. Hence, the results not only provide purchasing and stocking policies to operate chain enterprises, they also enhance operational efficiency and increase high income.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,005 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».