Rationalization of network retail management with a shift trading function based on the mathematical description of processes in the mass service area
Bibliographic record
Abstract
The authors highlight the high priority of rationalization in the management of the totality of transactions carried out in the sphere of network retail, in close contact with the service consumer. For network retail objects with a shift trading function, it is important to implement a direct and permanent impact, both on the system structure and on the basic processes in the area of mass trade services. This impact focuses on studying the flow of requests, service inputs and outputs of the system, as well as the length of waiting times, and the length of queues. The success of development in such retail networks depends on the flexibility of the operations performed by the contractor in close contact with the service consumer. It is envisaged to consider peculiarities in the rationalization of network retail management with trade turnover (flexibility) functions. The latter define the structure of the service delivery system for service consumers with processes running, in which client demands for services, as defined in the income chain, even though the intensity of the customer service flow is not constant. The purpose of the research is to present the informative field for rationalization in network retail management with the function of shifting trade, based on the mathematical description and repeated «playing» of all processes within the area of mass service. To represent the informative area for rationalization in network retail management with a shift trading function based on a mathematical description and repeated play of all processes within the public service area, Methods of probability theory and mathematical statistics have been used, as well as cloud computing in AnyLogic Claud environment, AnyLogic service. The results of the study was the presentation of new possibilities for rationalizing network retail management by groups of network objects based on the concept of a mass service area, and in view of the fact that there is an n-channel system of mass service with an unlimited queue, where the request flow has the intensity λ, and the service flow is the intensity μ. The study was implemented with the example of one of the hubs Walmart-Salvador, uniting 90 supermarkets of the company. All Walmart hubs combine only the same supermarket type, supporting the trade changeover function within a single graph (half-yearly). Similar Walmart hubs are developed in Mexico, Great Britain, Brazil, China, Canada, South Africa, Chile, Japan, Costa Rica, Guatemala, Argentina, Honduras, Nicaragua, El Salvador, and Ukraine. At the same time, all network nodes contain objects that apply multi-channel service systems, most common in the network retail with an unlimited queue and an option to add a new service node. It is the Walmart-Salvador hub that has a fairly high percentage of customers’ refusals due to the busy service devices (this estimate ranging from 19% to 25%). As a result, Walmart’s lost annual profit reaches up to USD 25.5 million approximately. The rationalization in the management of the network retail for the Walmart-Salvador hub objects is implemented with a breakdown into 8 groups, united according to common input parameters, the latter providing a solution for the optimal number of service devices, and their required reserve and runoff are calculated, as well as efficient productivity resulting from the consistency of the input and output flows in the service channel and the stability in the mass service system. At the same time, programming for solving the problem of the management rationalization is realized using rate fixing for the basic processes in the area of mass service. In this way, mass service system sustainability is ensured, with the average timing for the application staying in the mass service system being crucial. In particular, implementing such a standard could allow avoiding losses caused by waiting for servicing and unproductive ones. Among other relevant factors are: associated timing, probability or other values (necessary for transformation operations in the characteristics of the mass service area, performed for generating target values of this indicator). Perspectives of implementing the mathematical description of the processes in a mass-service area are in the fact that it will provide for significantly simplification in the processes of rationalizing the retail management in shift-trading facilities, regardless of the frequency of quantity and quality product range changes.
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".