CN112070551A - Retail outlet site selection algorithm based on regional analysis - Google Patents
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Abstract
The invention discloses a retail site selection algorithm based on regional analysis, which comprises the following steps of S1, first performing retail commercial site selection element analysis, S2, then performing comprehensive space analysis based on a GIS technology, S3, finally constructing a retail site selection model algorithm, the retail business site location element analysis in the S1 extracts key analysis elements aiming at diversified site location factors influencing the retail business site, the key analysis factors comprise population factors, economic basic factors and market competition factors, the invention can timely and accurately acquire the current information influencing the site selection factors of the retail commercial network points on the basis of the site selection factor data of the existing trade lots, the GIS technology is used as a support, and the space analysis and calculation of the model are utilized to achieve quantitative analysis and calculation results, so that the best site selection and site selection score of the retail commercial site are directly obtained, and the site selection problem of the retail commercial site is scientifically and effectively solved.
Description
Technical Field
The invention relates to the technical field of intelligent analysis, in particular to a retail outlet site selection algorithm based on regional analysis.
Background
The site selection is the key of the success of the retail business, the site selection of the retail business network is in geographic distribution and relevant factors around the site are inseparable, a corresponding mathematical model is established based on the factors to be an important means of the retail site selection, the factors influencing the site selection of the retail business network are relatively complex, and the site selection not only relates to various natural environment factors and operation environment factors, but also relates to various infrastructure condition factors;
but due to the difference of the region, the operation scale, the operation mode, the operation variety, the operation condition and the operation period of the business state of the retail industry, the scale and the form of the retail business circle have great difference, thereby leading to diversification of factors influencing site selection of the retail commercial network, timely and accurately acquiring the current situation information influencing site selection factors of the retail commercial network, on the basis, comprehensive space analysis of various site selection factors is carried out, the site selection evaluation method is a key technical link for realizing scientific site selection evaluation of retail business websites, the GIS is an effective way for solving the key technical links, on one hand, acquisition, management, application and updating maintenance of space information and attribute information can be realized under the support of the GIS, and on the other hand, the special functions of Overlay analysis, buffer area analysis, network analysis and the like of the GIS effectively support the space analysis of a site selection model.
Disclosure of Invention
The invention provides a retail outlet site selection algorithm based on regional analysis, which can effectively solve the problem that the scale and the form of a retail commercial trade circle have great difference and further influence the diversification of site selection factors of retail commercial outlets due to the difference of regions, operation scales, operation modes, operation varieties, operation conditions and operation periods of commercial business states of retail businesses in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a retail outlet site selection algorithm based on regional analysis comprises the following steps:
s1, first, performing site selection factor analysis of the retail commercial network;
s2, then carrying out comprehensive space analysis based on the GIS technology;
and S3, finally constructing a retail outlet site selection model algorithm.
According to the technical scheme, the retail commercial site location element analysis in the S1 extracts key analysis elements aiming at diversified retail commercial site location factors influencing the retail commercial site location;
the key analysis elements include population factors, economic basic factors and market competition factors.
According to the technical scheme, while the site selection element of the retail commercial network is analyzed in the S1, the target candidate commercial network is searched and determined, the candidate network is divided into a cache area and a reachable area, and the target candidate network extracts corresponding population elements, economic basic factors and market competition element factors from a data warehouse.
According to the technical scheme, the population elements comprise population total amount, population density, age distribution, mobility characteristics, family characteristics, income conditions and purchasing power indexes in the radiation range area of the retail business district, and based on comprehensive statistical analysis of the elements, the purchasing power, shopping modes and types of purchased commodities of consumers can be grasped, so that merchants are helped to select proper commodity combinations, estimate sales, manage inventory and plan sales activities;
the purchasing power index calculation formula of the regional population is as follows:
purchase index = a × 50% + B × 30% + C × 20%;
in the formula: a is the sum of the disposable income in the area, B is the total retail amount in the area, and C is the number of people with purchasing power.
According to the technical scheme, the population density is a key index for carrying out site selection of the retail commercial network, is a basis for carrying out coupling degree analysis of the retail commercial network and population distribution, can obtain the population density of a site selection area by utilizing a spatial distribution model of the population density, and is specifically divided into the following steps:
step one, dividing a research area into grids with certain resolution;
step two, converting the population number in the area into population density;
step three, placing a central point in each area, and connecting the population density to the central point;
and step four, interpolating the population density on the central point into the grid surface by using an interpolation method.
According to the technical scheme, the market competition factors comprise market competition severity, distribution conditions of the same-industry network points and sales conditions of the same-industry network points, the retail saturation index IRS is an effective index reflecting the market competition environment in the region, and the calculation formula is as follows:
IRS=H*RE/RF；
in the formula, IRS is the retail saturation coefficient of certain type of commodities in a certain area, H is the number of potential customers purchasing certain type of commodities in a certain area, RE is the expense for purchasing certain type of commodities for each customer in a certain area, and RF is the total business area of the same type of commodity store operated in a certain area;
the IRS value reflects the potential demand of a unit business area of a retail store in a specific business circle in unit time, the size of a profit space of the store in the area is determined, the larger the IRS value is, the lower the market saturation degree is, the retail potential is large, and the smaller the IRS value is, the higher the market saturation degree is, the retail potential is small.
According to the technical scheme, the comprehensive space analysis based on the GIS technology in the S2 mainly comprises the steps of calculating and analyzing the evaluation factor of the radiation business district buffer area and the evaluation factor of the accessible area of the radiation business district aiming at the selected network points.
According to the technical scheme, in the calculation and analysis of the evaluation factors of the buffer area of the radiation business district, the evaluation factors and the elements of the buffer area are analyzed to obtain the evaluation factors;
and in the calculation and analysis of the radiation quotient field reachable area evaluation factor, the evaluation factor and the reachable area factor are analyzed to obtain the evaluation factor.
According to the technical scheme, the site selection model algorithm constructed in the S3 is mainly to establish a comprehensive evaluation factor system and then calculate the scores of site selection points, and the personalized site selection model algorithm constructed based on the evaluation factors is as follows:
let V1, V2, … … Vm denote the evaluation results of m alternative retail business networks in a region, the model determines n model evaluation factors, and the basic calculation formula of the j-th network site selection model calculation result value Vj is:
Vj=∑Xi*Tij（i=1，2，…n）；
in the formula, Xi is the weight of the ith evaluation factor, and Tij is the calculation result value of the jth addressing mesh point aiming at the ith evaluation factor;
the relationship between the n evaluation factor weights is: x1+ X2+ … + Xn = 1;
setting V as the best retail commercial site selection, the calculation formula is as follows: v = max { V1, V2, … Vm }.
Compared with the prior art, the invention has the beneficial effects that: the method can timely and accurately acquire the current situation information influencing the site selection factors of the retail commercial network points on the basis of the existing site selection factor data of the business circles, and can directly obtain the best network point site selection and site selection score by using the space analysis and calculation of the model and taking the GIS technology as the support so as to scientifically and effectively solve the site selection problem of the retail commercial network points.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
fig. 1 is a schematic diagram of the structure of the application process of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example (b): as shown in fig. 1, the present invention provides a technical solution, a retail outlet location algorithm based on regional analysis, comprising the following steps:
s1, first, performing site selection factor analysis of the retail commercial network;
analyzing site selection factors of the retail commercial network in S1, and extracting key analysis factors aiming at diversified site selection factors influencing the retail commercial network;
the key analysis elements include population factors, economic basic factors and market competition factors.
And S1, analyzing the site selection factors of the retail commercial network points, searching and determining target candidate commercial network points, dividing the candidate network points into a cache area and an reachable area, and extracting corresponding population factors, economic basic factors and market competition factor factors from a data warehouse by the target candidate network points.
The population elements comprise population total amount, population density, age distribution, mobility characteristics, family characteristics, income conditions and purchasing power indexes in the radiation range area of the retail business district, and based on comprehensive statistical analysis of the elements, the purchasing power, shopping mode and types of purchased commodities of consumers can be grasped, so that merchants are helped to select proper commodity combinations, estimate sales volume, manage inventory and plan sales activities;
the purchasing power index calculation formula of the regional population is as follows:
purchase index = a × 50% + B × 30% + C × 20%;
in the formula: a is the sum of the disposable income in the area, B is the total retail amount in the area, and C is the number of people with purchasing power.
The population density is a key index for site selection of the retail commercial network, is a basis for analyzing the coupling degree of the retail commercial network and population distribution, and can be obtained in a site selection area by utilizing a spatial distribution model of the population density, and the method specifically comprises the following steps:
step one, dividing a research area into grids with certain resolution;
step two, converting the population number in the area into population density;
step three, placing a central point in each area, and connecting the population density to the central point;
and step four, interpolating the population density on the central point into the grid surface by using an interpolation method.
The market competition factors comprise the market competition severity, the distribution condition of the same-industry network points and the sales condition of the same-industry network points, the retail saturation index IRS is an effective index reflecting the market competition environment in the region, and the calculation formula is as follows:
IRS=H*RE/RF；
in the formula, IRS is the retail saturation coefficient of certain type of commodities in a certain area, H is the number of potential customers purchasing certain type of commodities in a certain area, RE is the expense for purchasing certain type of commodities for each customer in a certain area, and RF is the total business area of the same type of commodity store operated in a certain area;
the IRS value reflects the potential demand of a unit business area of a retail store in a specific business circle in unit time, the size of a profit space of the store in the area is determined, the larger the IRS value is, the lower the market saturation degree is, the retail potential is large, and the smaller the IRS value is, the higher the market saturation degree is, the retail potential is small.
S2, then carrying out comprehensive space analysis based on the GIS technology;
in the step S2, comprehensive space analysis based on GIS technology is mainly to perform evaluation factor calculation analysis of the radiation business district buffer area and evaluation factor calculation analysis of the accessible area of the radiation business district for the selected network points.
In the calculation and analysis of the evaluation factors of the buffer area of the radiation business district, the evaluation factors and the elements of the buffer area are analyzed to obtain the evaluation factors;
and in the calculation and analysis of the accessible domain evaluation factor of the radiation quotient circle, the evaluation factor and the accessible domain element are analyzed to obtain the evaluation factor.
S3, finally constructing a retail outlet site selection model algorithm;
the site selection model algorithm constructed in the S3 is mainly to establish a comprehensive evaluation factor system and then calculate the scores of site selection points, and the personalized site selection model algorithm constructed based on the evaluation factors is as follows:
let V1, V2, … … Vm denote the evaluation results of m alternative retail business networks in a region, the model determines n model evaluation factors, and the basic calculation formula of the j-th network site selection model calculation result value Vj is:
Vj=∑Xi*Tij（i=1，2，…n）；
in the formula, Xi is the weight of the ith evaluation factor, and Tij is the calculation result value of the jth addressing mesh point aiming at the ith evaluation factor;
the relationship between the n evaluation factor weights is: x1+ X2+ … + Xn = 1;
setting V as the best retail commercial site selection, the calculation formula is as follows: v = max { V1, V2, … Vm }.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A retail outlet site selection algorithm based on regional analysis is characterized in that: the method comprises the following steps:
s1, first, performing site selection factor analysis of the retail commercial network;
s2, then carrying out comprehensive space analysis based on the GIS technology;
and S3, finally constructing a retail outlet site selection model algorithm.
2. The retail site selection algorithm based on regional analysis of claim 1, wherein the retail commercial site selection element analysis in S1 extracts key analysis elements for diversified factors affecting retail commercial site selection;
the key analysis elements include population factors, economic basic factors and market competition factors.
3. The retail site selection algorithm based on regional analysis as claimed in claim 1, wherein in S1, while analyzing the site selection element of the retail commercial site, the search and determination are performed on the target candidate commercial site, and the candidate site is divided into two parts, namely a cache area and a reachable area, and the target candidate site extracts the corresponding demographic element, economic basic element and market competition element factor in the data warehouse.
4. The retail site selection algorithm based on regional analysis as claimed in claim 2, wherein the population elements include total population, population density, age distribution, mobility characteristics, family characteristics, income and purchasing power index in the radiation range area of the retail commercial district, and based on the comprehensive statistical analysis of these elements, the purchasing power, shopping mode and the type of purchased goods of the consumer can be grasped, thereby helping the merchant select proper goods combination, estimate sales volume, manage inventory and plan sales activities.
5. A retail outlet location algorithm based on regional analysis according to claim 4, wherein the purchasing power index of the regional population is calculated as follows:
purchase index = a × 50% + B × 30% + C × 20%;
in the formula: a is the sum of the disposable income in the area, B is the total retail amount in the area, and C is the number of people with purchasing power.
6. The retail site selection algorithm based on regional analysis according to claim 4, wherein the population density is a key index for performing the site selection of the retail commercial site, and is a basis for performing the coupling degree analysis of the retail commercial site and the population distribution, and the population density of the site selection region can be obtained by using a spatial distribution model of the population density, which is specifically divided into the following steps:
step one, dividing a research area into grids with certain resolution;
step two, converting the population number in the area into population density;
step three, placing a central point in each area, and connecting the population density to the central point;
and step four, interpolating the population density on the central point into the grid surface by using an interpolation method.
7. The retail site selection algorithm based on regional analysis according to claim 2, wherein the market competition factors include market competition severity, distribution of the peer sites, and sales of the peer sites, and the retail saturation index IRS is an effective index reflecting the market competition environment in the region, and is calculated by the following formula:
IRS=H*RE/RF；
in the formula, IRS is the retail saturation coefficient of certain type of commodities in a certain area, H is the number of potential customers purchasing certain type of commodities in a certain area, RE is the expense for purchasing certain type of commodities for each customer in a certain area, and RF is the total business area of the same type of commodity store operated in a certain area;
the IRS value reflects the potential demand of a unit business area of a retail store in a specific business circle in unit time, the size of a profit space of the store in the area is determined, the larger the IRS value is, the lower the market saturation degree is, the retail potential is large, and the smaller the IRS value is, the higher the market saturation degree is, the retail potential is small.
8. The retail outlet siting algorithm based on regional analysis according to claim 1, wherein the comprehensive spatial analysis based on GIS technology in S2 is mainly to perform evaluation factor calculation analysis of radiated quotient circle buffer and evaluation factor calculation analysis of radiated quotient circle reachable region for a selected outlet.
9. The retail outlet site selection algorithm based on regional analysis according to claim 8, wherein the evaluation factor of the irradiated business district buffer is obtained by analyzing the evaluation factor and the buffer element in the calculation analysis;
and in the calculation and analysis of the radiation quotient field reachable area evaluation factor, the evaluation factor and the reachable area factor are analyzed to obtain the evaluation factor.
10. The retail site selection algorithm based on regional analysis according to claim 1, wherein the site selection model algorithm constructed in S3 is mainly to establish a comprehensive evaluation factor system, and then calculate scores of site selection sites, and the site selection model algorithm constructed based on these evaluation factors is as follows:
let V1, V2, … … Vm denote the evaluation results of m alternative retail business networks in a region, the model determines n model evaluation factors, and the basic calculation formula of the j-th network site selection model calculation result value Vj is:
Vj=∑Xi*Tij（i=1，2，…n）；
in the formula, Xi is the weight of the ith evaluation factor, and Tij is the calculation result value of the jth addressing mesh point aiming at the ith evaluation factor;
the relationship between the n evaluation factor weights is: x1+ X2+ … + Xn = 1;
setting V as the best retail commercial site selection, the calculation formula is as follows: v = max { V1, V2, … Vm }.
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| CN113313315A (en) * | 2021-06-11 | 2021-08-27 | 北京市富通环境工程有限公司 | Agricultural product producing area wholesale market planning method and system based on GIS |
| CN115660739A (en) * | 2022-12-27 | 2023-01-31 | 上海祺鲲信息科技有限公司 | Urban business strategy data processing method |
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| CN112669094A (en) * | 2021-01-29 | 2021-04-16 | 亿景智联(北京)科技有限公司 | Pharmacy site selection method based on space-time big data and machine learning algorithm |
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| CN115660739A (en) * | 2022-12-27 | 2023-01-31 | 上海祺鲲信息科技有限公司 | Urban business strategy data processing method |
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Application publication date: 20201211 |