JP2003114969A - Commercial facility proposing system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To carry out evaluation of factors for expanding a trade area, selection of the trade area expanded by those factors, and sales prediction, customer collection prediction, and store proposal in the expanded trade area since sales are limited in the trade area being a customer collecting region where there is only a commercial facility in proposing a commercial facility. SOLUTION: A plurality of regions whose recognition ratio is high are selected according to the recognition ratio of customer collecting factors so that trade area candidates can be selected, and the region whose sales are the most highly expected is selected as a trade area from among those regions. Then, sales prediction is carried out, and the optimal commercial facility is proposed for each scale of a commercial facility to be set in the trade area. Moreover, the customer collecting power can be compared with that of another store by using an objective numeric so as to be evaluated, and the customer collecting power can be correctly evaluated in order to accurately carry out the sales prediction.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a commercial facility model proposal, a scale selection, and a sales forecast when a new commercial facility is newly opened and when an existing store is improved or improved. For new commercial facilities, propose entertainment plans, expand commercial areas by installing them in commercial facilities, and perform customer forecasts in expanded commercial areas in addition to the conventional commercial areas where customers are expected. Then, the sales of new commercial facilities are predicted, and the scale is selected and proposed.

[0002]

2. Description of the Related Art Conventionally, when planning a new store opening or a plan to improve existing stores,
From the point where you plan to open a store or the target store, for example, set a trading area with a radius of about 5 km, and about the competitors within the trading area, store size, visitor ratio, population living in the trading area, population passing by etc. We used the Hough model to predict the number of customers, and made a plan to improve store openings. Here, the radius is set to 5 km, but it may be wider or narrower depending on the location conditions. The range expected to attract customers is determined as the commercial area based on the parking lot, road conditions in the vicinity, etc. . Therefore, the commercial area of the conventional store model seeks the number of customers attracted by the attraction of only the commercial facility, and it is not possible to expect more customers than the potential store population within the commercial area within a certain range centered on the commercial facility, Also, the sales per visitor are statistically determined by the type of commercial facility, and we could not expect an increase in sales unless the visitor population increased.

Further, regarding the distribution of customers with competing stores located within the business area, the suction rate is evaluated only by those which can be quantitatively grasped such as location conditions, product lineup, sales floor area, and completeness of parking lots. Was calculated, distributed, and sales forecasted.

[0004]

As described above, in the conventional store opening plan, the area of the customer population that naturally attracts customers is limited due to parking lots, road conditions, location conditions of competing stores, etc. Met. As long as the area attracting customers did not expand, we could not expect an increase in the number of people visiting the store, and we could not expect an increase in sales beyond the population visiting the store. Furthermore, in the conventional store opening plan,
It was not possible to expand the commercial area that can be expected to increase the population visiting stores.

That is, there is no system that proposes a plan that can expand the commercial area, and there is no system that predicts the number of visitors and sales when the commercial area can be expanded.

[0006] On the other hand, in commercial facilities, there is no scale for quantitatively evaluating sensory parts such as cleanliness, good equipment, and customer service attitude, which are major factors for customers to select a commercial facility, and It is often evaluated by customers due to the relative positioning when evaluated in commercial facilities existing in the commercial area, and it was difficult to reflect it in the difference in attraction with competitors. Therefore, it is to obtain a means to objectively evaluate which part is inferior to the competitive store and whether it is winning, and to reflect it in the difference in suction power.

Therefore, a plan which is a factor for attracting customers to newly expand the commercial area is evaluated, how much the commercial area can be expanded by the plan is predicted, the number of customers in the expanded commercial area is predicted, and the number of customers in the new store that matches is estimated. To obtain a system for forecasting and forecasting sales.

[0008]

In order to solve the above-mentioned problems, the commercial facility proposing system according to the invention of claim 1 has a regional distribution information of the population for each population structure type stored in the storage means and a plurality of customers. Using the area recognition rate information for each factor and the store information of other commercial facilities of the same type existing in the commercial area, first, a plurality of first commercial area candidate areas are selected by the commercial area candidate selecting means for each customer attraction factor. Next, a plurality of second commercial area candidate areas are selected in descending order of the area recognition rate from the first commercial area candidate areas. The number of customers attracted by the factor of attracting customers is calculated by the number-of-customers attracting means for each of the plurality of second commercial area candidate areas. By using the number of customers obtained for each second commercial area candidate, a plurality of store-scale commercial facilities proposed for each second commercial area candidate area are predicted for each second commercial area candidate area for each store size. The new visitor number is calculated by the new visitor number prediction means.

Further, the number of visitors for each commercial facility for each store size is calculated by the visitor number predicting means using the store information of other commercial facilities of the same type, and the number of new visitors and the number of visitors for each store size are used. A new sales amount predicted for each commercial facility is calculated by the sales prediction means. Among the second commercial area candidate areas for each store size, the area with the highest new sales amount is determined in order from the area with the highest new sales amount as the commercial area candidate area by the commercial area candidate determining means, and the factor of attracting customers and the expected new sales amount for each store size The determined commercial area candidate area is output from the output means.

Further, in the commercial facility proposing system according to the second aspect of the present invention, the store information is, for example, a sales floor area, the number of products handled, etc. in order to accurately evaluate the customer attraction rate with the competing stores existing in the commercial area. It is characterized in that it has evaluation values for a plurality of evaluation items of the store that represent the store attracting power.

Furthermore, in the commercial facility proposing system according to the third aspect of the present invention, the evaluation value for the evaluation item of the store can be made clear, for example, so that the relative evaluation in the area can be made clear.
It is characterized by having an evaluation value obtained by comparison with other stores.

Further, in the commercial facility proposing system according to the invention of claim 4, the area recognition rate information is a factor of attracting customers for each population composition type so that it becomes clear which population composition category has a high recognition rate. It is characterized by the regional distribution information of the population recognizing.

Further, in the commercial facility proposing system according to the invention of claim 5, it is established as a trade area that the population density of the people who recognize the factor of attracting customers is equal to or more than a certain ratio and more than a certain area. As a condition for this, the trade area candidate selection means sets the area where the population distribution of the area recognition rate information is equal to or more than a predetermined number of people in a predetermined area to the first trade area candidate area. It is characterized by doing.

Further, in the commercial facility proposing system according to the invention of claim 6, in order to obtain the number of customers from the areas constituting the commercial area, the customer number predicting means Vv (1
≤v≤nv), where Xi is the number of customers of the population structure type i, and X is the number of customers.

[Equation 12] X = Σi Xi (1 ≦ i ≦ ni), ... (12) Residence Ww (1 ≦ w ≦ which constitutes the second commercial area candidate area W
nw)

[Equation 13] W = Σw Ww (1 ≦ w ≦ nw); (13) Residence W recognizing the customer attraction factor Vv of the area recognition rate information
Let Pwvi be the population of population composition type i of w, and place of residence Ww
The attendance rate Rwvi of the population composition type i for the customer attraction factor Vv in

[Expression 14] Rwvi = (Svi / Twv ^fv ) / (Σv (Svi / Twv ^fv )), ... (14) Σvi Rwvi = 1 and Svi: Scale of attracting customers Vv and attractiveness to population composition type i Twv: Residence Time distance fv from Ww to the customer attraction factor Vv: When the resistance coefficient to the distance in the customer attraction factor Vv is defined,

(15) Xi = Σw (Rwvi × Pwvi) (15) It is characterized by obtaining the number of customers by

Further, in the commercial facility proposing system according to the invention of claim 7, in order to obtain the number of new visitors due to the factor of attracting customers, the means for predicting the number of new visitors is the number of new visitors of the population composition type i, PHXi, and the population composition type. i is the number of customers attracted by the factor of i, and PFi is the visitor coefficient to the commercial facility for each population composition type i.
Then, the number of new visitors of population composition type i is

[Formula 16] PHXi = Xi × PFi (16) To obtain the number of new visitors,

[Equation 17] PHX = Σi PHXi (1 ≦ i ≦ ni), ... (17) Is obtained by

Further, in the commercial facility proposing system according to the invention of claim 8, in order to obtain the number of visitors of the commercial facility j, the visitor number predicting means is the residence Zz (1 ≦ z which constitutes the commercial zone Z of the commercial facility j. Rzj is the proportion of the population residing in ≤ nz) to commercial facilities j (1 ≤ j ≤ nj) in the commercial area.

[Equation 18] Rzj = (Gj / Tzj ^fj ) / (Σj (Gj / Tzj ^fj )) (18) Σj Rzj = 1 and Gj: Ability to attract customers from the commercial facility j, Tzj: From the residential area Zz to the commercial facility j Time distance to fj: The resistance coefficient according to the distance to the commercial facility, and the population of population composition type i existing in the residence Zz is P
Let iz be the visitor coefficient for population composition type i, PFi,
Population PHz for visiting Zz is:

[Equation 19] PHz = Σi (Piz × PFi) (19) The number of visitors PHj of the commercial facility j is calculated by

[Formula 20] PHj = Σz (Rzj × PHz) (20) It is characterized by being obtained by.

Further, in the commercial facility proposing system according to the invention of claim 9, the sales forecasting means calculates the number of new visitors by PHX and the number of visitors to the commercial facility j by PHj in order to obtain the sales including the number of customers due to the factor of attracting customers. , Where U is the sales amount and T is the average sales amount per person,

(21) U = (PHj + PHX) × T, (21) It is characterized by being obtained by.

Further, the commercial facility proposing system according to the invention of claim 10 has an evaluation value for the evaluation item of the store, and the store attracting power can be obtained using the evaluation value. The evaluation value of the evaluation item y of the store in each commercial facility j is ayj (1≤y≤ny)
And the weight occupying the evaluation of the store of the evaluation item y is αy (1 ≦ y ≦ ny), the store attracting power Gj is

[Equation 22] Gj = Σy (ayj × αy) / Σy αy (22) It is characterized by being obtained by.

Further, the commercial facility proposing apparatus according to the invention of claim 11 is used in the commercial facility proposing system, and the regional distribution information of the population for each population composition type, the area recognition rate information for each factor of attracting customers, and the store information. Information input means for inputting ,, information storage means for storing the input information, commercial area candidate selection means, customer attendance forecasting means, new visitor forecasting means, sales forecasting means, store scale confirming means, , A calculation means having a visitor number prediction means and a trade area candidate location determination means,
It is characterized by having input information, a customer attraction factor, a predicted new sales amount, and an output means for outputting a confirmed commercial area candidate site.

Further, the commercial facility proposing device according to the invention of claim 12 is arranged so that the output means can output the map in combination with the map information system capable of visually judging the commercial area candidate areas. It is characterized by further comprising an information system output means.

One invention should not be construed as achieving all of the above objects at the same time, but each individual invention should be construed as achieving each object.

[0022]

According to the first aspect of the present invention, the area distribution information of the population for each population structure type stored in the storage means, the area recognition rate information for each of a plurality of factors for attracting customers, and the existence of the area within the commercial area. Using the store information of other commercial facilities of the same type, a plurality of first commercial area candidate areas are selected by the commercial area candidate selecting means for each factor of attracting customers. As a result, an area having a certain recognition rate for the customer attraction factor is selected as the first commercial area candidate area as a plurality of candidate sites. Furthermore, a plurality of second commercial area candidate areas are selected in descending order of area recognition rate, and the number of customers attracted by a factor of attracting customers is calculated for each of the plurality of second commercial area candidate areas by the number-of-customers-prediction predicting means, and the second commercial area candidates For the commercial facilities of multiple store scales proposed for each second commercial area candidate area, the number of new customers is estimated for each second commercial area candidate area, and the number of new customers is predicted for each second commercial area candidate area. Each is calculated by the number predicting means. This makes it possible to obtain a new number of visitors due to the factor of attracting customers. Next, the number of visitors for each commercial facility for each store size is calculated by the visitor number prediction unit using the store information, and the number of new visitors for each store size and the new sales forecast for each commercial facility using the number of visitors are calculated. The amount of money is calculated by the sales forecasting means, and the area with the highest new sales amount is determined as the commercial area candidate area by the commercial area candidate determining means in order from the second commercial area candidate area for each store size. Then, the predicted new sales amount and the confirmed commercial area candidate area can be output from the output means.

Further, the commercial facility proposing system according to the second aspect of the invention is characterized in that the store information has evaluation values for a plurality of evaluation items of the store that express the power of attracting customers to the store. About, it will be possible to accurately evaluate the ability to attract customers.

Further, according to the commercial facility proposing system according to the third aspect of the invention, the evaluation value for the evaluation item of the store has an evaluation value obtained by comparison with other stores. It becomes possible to perform relative positioning. Generally, even if the store is absolutely highly evaluated, if there is a better store in the business area, it will not be possible to attract customers. On the contrary, in absolute terms, even if a high evaluation is not obtained,
If you get a high evaluation, you will be able to attract customers. It becomes possible to reflect such positioning within the commercial area.

Further, according to the commercial facility proposal system according to the fourth aspect of the present invention, since the area recognition rate information is the area distribution information of the population recognizing the factor of attracting customers for each population composition type, depending on the factor of attracting customers, Although there is a marked difference between the age group and the gender, even if there is a difference in the number of customers depending on the population composition type, it can be accurately reflected in the population of customers.

Furthermore, according to the commercial facility proposal system according to the fifth aspect of the present invention, the first commercial area candidate area is selected by the commercial area candidate selecting means by a predetermined number of people for a predetermined area in the population distribution of the area recognition rate information. The above-mentioned continuous area having a predetermined area or more is selected as the first commercial area candidate area.

Further, according to the commercial facility proposing system according to the sixth aspect of the present invention, the number-of-customers-attracting predicting means is the factor for attracting customers Vv (1
≤v≤nv), where Xi is the number of customers of the population composition type i, the number of customers X is obtained by the equation (1), and the second commercial area candidate area W is the residential area Ww (1≤w≤ nw)
Can be expressed by equation (2). Furthermore, the residence Ww that recognizes the customer attraction factor Vv of the area recognition rate information
Let Pwvi be the population of the population composition type i, and the dispatch rate Rwvi of the population composition type i with respect to the customer attraction factor Vv in the place of residence Ww is to be calculated by the equation (3) using the Hough model. ΣviRwvi = 1 , Svi is the degree of attraction of the attracting factor Vv, which is known in advance, to the population structure type i, Twv is the time distance from the place of residence Ww to the attracting factor Vv, and the resistance coefficient to the distance in the attracting factor Vv is fv. Then, the number of customers Xi for the population composition type i can be calculated by the equation (4). As a result, the number of customers attracting means can be used to obtain the number of customers by the factor Vv.

At this time, Svi is the scale of the customer attraction factor Vv, and is a numerical value showing the degree of attractiveness to the population composition type i. Since this number varies depending on the factor of attracting customers, it is individually determined by referring to the existing facility for attracting customers due to the similar factor of attracting customers. Further, Twv is the time distance from the residence Ww to the customer attraction factor Vv, and for example, the time required from the residence to the customer attraction factor is used. In addition, fv is a resistance coefficient with respect to distance. For example, at shopping centers, 2.0 is used to buy daily necessities, and around 1.5 is used for purchased goods. In this case as well, it is determined individually because it depends on the individual attraction factor. Customer attraction factor V
Regarding v, not only the customer attraction factor proposed in the present invention, but also the existing similar customer attraction facilities existing in the trade area are reflected in Equation (3) as the customer attraction factor. In this way, it is possible to obtain the visit ratio by residence area of the population composition type i based on the obtained factor of attracting customers, and by the formula (4), the Around the number of people will be able to predict whether to attract customers.

Further, according to the commercial facility proposing system according to the seventh aspect of the invention, the new visitor number predicting means is the population composition type i.
The number of new visitors of the population composition type i is XH, the number of customers of the population composition type i is Xi, and the visitor coefficient to the commercial facility of each population composition type i is PFi.
Can be obtained by the equation (5), and the new customer number PHX can be obtained by the equation (6).

Further, according to the commercial facility proposal system according to the eighth aspect of the present invention, the visitor number predicting means has a customer attraction power of Gj, and a time distance from the residence Zz to the commercial facility j of T.
Let zj be the resistance coefficient depending on the distance to the commercial facility, fj, the residential area Zz (1 ≦ z ≦ nz that composes the commercial zone Z of the commercial facility j).
) Of the population living in
The dispatch rate Rzj to (1 ≤ j ≤ nj) can be obtained by the equation (7) using the Hough model, so that the population of the population composition type i existing in the residence Zz is Pi
z, and the visitor coefficient for population composition type i is PFi,
The store visit population PHz of the residence Zz can be calculated by the equation (8). Therefore, the number of visitors PHj of the commercial facility j can be calculated by the equation (9).

Further, according to the commercial facility proposing system according to the ninth aspect of the present invention, the sales forecasting means is used to predict the number of new customers.
X, PHj is the number of visitors to the commercial facility j, U is the desired sales amount,
When the statistically-known average sales amount per person is T, the sales amount U can be obtained by the equation (10).

Further, according to the commercial facility proposal system according to the tenth aspect of the present invention, the store information further indicates the evaluation value of the evaluation item y of the store in each commercial facility j as ayj (1≤
y ≦ ny), the weight occupying the evaluation of the store of the evaluation item y is α
If y (1 ≤ y ≤ ny), the store attracting power Gj is calculated by the formula (1
It becomes possible to obtain by 1), and it becomes possible to reflect the evaluation value of the evaluation items of the store collected as the store information in the store attraction power Gj which is an index showing the attraction power of the store.

Further, according to the commercial facility proposing apparatus according to the eleventh aspect of the invention, the commercial facility proposing apparatus used in the commercial facility proposing system has the regional distribution information of the population for each population structure type and the regional recognition for each factor of attracting customers. Information input means for inputting rate information and store information, information storage means for storing the input information, commercial area candidate selection means, customer attendance forecasting means, new visitor forecasting means, and sales forecasting means , A store scale determining means, a visitor number predicting means, a computing means having a commercial area candidate location determining means, input information, a customer attraction factor, a predicted new sales amount, and a confirmed commercial area candidate location. Since it comprises an output means for outputting, it becomes possible to obtain an apparatus for implementing the above-mentioned system for suggesting commercial facilities.

Furthermore, in the commercial facility proposing apparatus according to the twelfth aspect of the present invention, the output means further includes the map information system output means, so that the area as the commercial area can be displayed and output on the map. .

[0035]

1 is a block diagram showing the configuration of a commercial facility proposing apparatus for realizing a commercial facility proposing system according to an embodiment of the present invention. The control device 10 includes a commercial area candidate selection unit 21, a customer attendance forecast unit 22, a new visitor forecast unit 23, a sales forecast unit 24, and a visitor forecast unit 25.
CP which is a calculation means having a trade area candidate location determination means 27
U20, area distribution information storage means 31 of population for each population structure type, and area recognition rate information storage means 32 for each factor of attracting customers
And a storage unit 30 that stores the store information storage unit 33. Information input means 5 which is the operation input device 50
Reference numeral 1 denotes a keyboard 52, a mouse 53, a scanner 54, a touch panel 55, a modem 56, and an information input means 5
The area distribution information of the population for each population structure type, the area recognition rate information for each factor of attracting customers, and the store information are input and stored in the storage means 30 via 1.

The regional distribution information of the population for each population composition type is as follows:
The population distribution in the administrative divisions may be used, or for example, the population distribution in a predetermined area of every 50 meters vertically and horizontally is used. The area recognition rate information for each factor of attracting customers is subjected to a 100% survey or a sampling survey at each point, the recognition rate information for each population composition type is collected for each area, and stored in the area recognition rate information storage means 32. Let Area distribution information and area recognition rate information can be obtained from the map information system (G
Information of (IS) may be used.

The store information stored in the store information storage means 33 is displayed through the display means 62 and, as shown in FIG. 2, basic data such as store name, store location, and telephone number,
It consists of evaluation values for evaluation items. This information is
The store name, store location, telephone number, etc. are input in the same manner as they are displayed on the display means 62 and filled in the list. A mouse or a touch panel may be used for selection and input in each input field regardless of the input method. Next, regarding the input of the evaluation value regarding the evaluation of the store, the input table is displayed through the display means 62 as shown in the detailed store information explanatory view shown in FIG. Enter with survey.

Regarding the evaluation items, when the evaluation items shown in FIG. 3 are selected, specific evaluation criteria are displayed, and the evaluation can be input by selecting them. The surveyed information is shared with the data entered in the store information in FIG. Further, in the detailed store information explanatory diagram, the input and corrected information is reflected in the store information. Further, any of the input information is displayed by the display means 62 and can be confirmed and corrected.

The output means 60 comprises a printing means 61, a display means 62 and a GIS output means 63. Other than this, audio output means may be provided. Furthermore, the input information is input by the operation input device 50,
The information stored and stored in the external storage device 40 is
It can be read into the storage means 30. External storage device 4
0 may be any storage medium such as MO, CD-R, CD-R / W, and memory stick.

The survey information of the store information may be input by a mobile terminal. In this case, the store information storage unit 33 of the storage unit 30 is stored via the external storage device 40 which is a storage medium.
To enter. Furthermore, the storage means 30 can be directly accessed from the mobile terminal using a communication function such as the Internet, LAN, or WAN.
You may send it to. In this case, the information input means 51 is a modem 56 or the like which is an input means having a communication function.
These devices are well known and will not be described in detail here.

Next, the factors for attracting customers in the present invention and the information on the regional distribution of the population by the type of population composition, which is a database,
The basic concept of the area recognition rate information of the factor of attracting customers and the store information will be described. The regional distribution information of the population according to the population composition type is, for example, the population distribution information by age and by gender obtained by a national census or the like. It may be information by administrative division or information per unit area,
You may use what was provided as GIS data. This makes it possible to understand in which region and in what age the population is distributed.

Next, the area recognition rate information on the factor of attracting customers will be described. For example, with a commercial facility alone, the population who visits the store is limited to only those who are for the purpose of the commercial facility. Further, in the case of a person for the purpose of a commercial facility, generally, a store coming from a radius of several kilometers centering on the commercial facility and its commercial area differ depending on the type of commercial facility, but are statistically determined. Therefore, the commercial population cannot be expected to exceed a certain number if only considering coming from a certain commercial area. Therefore, it is possible to increase the number of visitors to the commercial facility by increasing the number of visitors from outside the commercial area of the commercial facility. Therefore, by increasing the population that visits a place with a commercial facility for purposes other than the commercial facility, it is possible to expect the store to come from within the population that has visited for a purpose other than the purpose.
In other words, the purpose other than commercial facilities is the factor of attracting customers. In other words, a commercial facility is a commercial facility that can attract customers from different industries. For example, any factor that can attract customers for purposes other than planned commercial facilities, such as shopping centers, theaters, movie theaters, sports centers, museums, and the like, may be used. The most desirable factor for attracting customers is one that attracts as many people as possible and wants to visit many times. Therefore, the area recognition rate information is obtained by collecting the distribution status of the population of each type of population that recognizes this factor of attracting customers. It is desirable to be able to conduct a 100% survey, but in reality, a 100% survey will be enormous in both time and cost.
The recognition rate is converted to population and used as distribution information. It is known that a certain proportion of the population recognizing this factor of attracting customers can expect visitors. The greater the expansion of the trade area, the more visitors can be expected, and as a result, the number of visitors to commercial facilities can be expected to increase.

Next, the store information is information on a target point or a commercial facility within the range of attracting customers only to the commercial facility centering on the store. For example,
Basic information such as the store name, location, telephone number, and capital shown in the store information shown in FIG. Location factors such as peripheral population, location type (suburb type, station front type), proportion of main transportation means, parking lot completion rate, bicycle parking lot completion rate, etc. Qualitative analysis element consisting of corporate strength points (good or bad brand image, management stability), building points (luxury, newness, design superiority,), sales activity points (holiday settings, services, lighting, environment) . For each item, a specific evaluation standard is set, and all stores existing in the area are surveyed by the same standard, and the shop information is composed of the evaluated information. How to evaluate these store information is S
The WOT analysis is applied, and the SWOT analysis is
Analysis of "own store" and "environment surrounding own store"
It is a way of thinking and a method for analyzing. We set concrete evaluation criteria for each factor and quantify it, and finally quantify the attractiveness of our own store and other stores.

The strength, the weakness, the opportunity, and the threat are analyzed. Specifically, it is as described above, and basically,
Consider the two categories of "own store" and "environment". "Own store" refers to the relative strengths and weaknesses of its own store compared to its competitors, and "environment" refers to business opportunities and threats related to the environment surrounding the own store. . Further, the strengths and weaknesses are to evaluate whether they are stronger or weaker than other stores, for example, product quality, low production cost, wide distribution, customer service, and the like. External threats that threaten the business continuity of own stores are cited and evaluated as threats. For example, counterattacks of competitors, entry of new competitors, occurrence of price competition, and magnitude of changes in consumer preferences. As an opportunity, we will specifically list the factors that will become a business opportunity for our own store,
evaluate. For example, market size, market growth rate, technological change, etc. With respect to these factors, evaluation points are set for each evaluation item and digitized.

The above-mentioned population distribution information is taken as an example of a residential area such as a residential area, but in a shopping district such as in front of a station, the population distribution information also includes the population to be transferred to a station. Therefore, the regional distribution information of the population is surveyed and provided according to the regional conditions. In other words, the population in the area is the population by age and sex who live, come, or stay in the area. Furthermore, since the regional distribution of the population differs depending on the day of the week and the time of day, the regional distribution information of the population may be configured by the day of the week and the time of the day. Further, as described above, by using the GIS data, it becomes possible to visually handle the population distribution data on the map, and thus it becomes easy to grasp the trade area, the situation of the population distribution, and the like. It may be census data or population data obtained from city halls.

Next, according to the flowcharts shown in FIGS. 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 and 15, the processing procedure of the present commercial facility proposal system. Will be described in detail.

First, the outline of the processing will be described with reference to the flowchart of the processing outline in FIG. In step 100, the first commercial area candidate area is selected. As the first commercial area candidate area, the area where the population distribution that recognizes the factor of attracting customers is a predetermined number or more and has an area as an expanded commercial area with respect to the commercial area of the commercial facility is selected. In step 102, among the first commercial area candidate areas, one having a high area recognition rate of a factor of attracting customers is set as a second commercial area candidate area.
Further, in step 104, the expected number of customers is calculated for each of the areas that have become the second commercial area candidate areas. In step 106, the number of new customers that can be expected from the second commercial area candidate area is calculated using the number of customers that has been acquired in step 104. Next, in step 108, the number of visitors is calculated. Further, in step 110, the new sales amount is obtained using the number of new visitors and the number of visitors. In step 112, the commercial area candidate areas are determined in descending order of new sales amount. In step 114, the commercial area candidate area, the customer attraction factor, and the new sales amount are output.

From step 100 described above to step 1
With respect to 14, each step will be described in detail according to a flowchart.

First, the process of selecting the first commercial area candidate area by the commercial area candidate selecting means will be described with reference to FIGS.
The first commercial area candidate area is selected by investigating the area where the area recognition rate information is provided for all the factors of attracting customers, and in the area where the recognition rate is equal to or higher than a predetermined value, there is an area enough for the commercial area. This is a process of setting an area as a first commercial area candidate area. First, in step 200, there are a plurality of customer attraction factors Vv (1≤v
Set v = 1 to set the first attraction factor for ≤nv). In step 202, when the survey area is set to Ee in order to check the recognition rate for the area Ee (1 ≦ e ≦ en) to which the area recognition rate information is provided, e 1 is set as the initial value of the area. Further, the initial value of the first commercial area candidate area is also set to f = 1. In step 204, the candidates for the first commercial area candidate area are initialized. In step 206, the customer attraction factor Vv is set. Step two
In 08, it is checked whether the population density recognizing the customer attraction factor Vv for the area Ee is a predetermined value or more. The population density here is closely related to the area of the first commercial area candidate area, and a predetermined area is required to be the first commercial area candidate area. The population is obtained from the population density and area of the area recognition rate information. For example, as in the case of Tokyo Disneyland, there are cases where the entire Asian region is a commercial area, but generally, a certain extent of customer attraction is recognized in advance due to the customer attraction factor. Therefore, the required recognition rate, which is derived from the predetermined area and is determined for each factor of attracting customers, is the population density here. If the population density is greater than or equal to the predetermined value, then in step 210, the first commercial area candidate area is added to the candidate W1t. In step 212, the next area adjacent to the candidate W1t of the first commercial area candidate area
Get Ee. In step 214, it is checked whether or not the recognition rate of the customer attraction factor Vv is equal to or higher than a predetermined population density in step 214, and if it is equal to or higher than the predetermined value, in step 210, it is added to the candidate W1t of the first commercial area candidate area. In the case of No, it is checked in step 216 whether there is an area adjacent to the candidate W1t of the first commercial area candidate area. By repeating the same operation in the adjacent area, the area having a predetermined population density or more is expanded as the commercial area candidate area. When there is no continuous area, it is checked whether W1t, which is a candidate for the first commercial area candidate area, is equal to or larger than a predetermined area (step 218). When the area is equal to or larger than the predetermined area, the first trade area candidate area W1vf (f:
The first commercial area candidate area number).

In step 224, it is checked whether or not all the areas provided with the area recognition rate information have been investigated.
If there is an area Ee that has not been investigated, it is examined as a candidate for the next first commercial area candidate area, and all areas for which information is available are investigated, and all candidate areas are the first commercial area candidate areas.

When the area Ee to be surveyed ends, the next number is set to the customer attraction factor number v so that the next customer attraction factor Vv is set (step 226). By repeating the same process for the next customer attraction factor Vv, the first commercial area candidate area W1vf is selected. In step 228, it is checked whether the customer attraction factor Vv has ended. If not, the next customer attraction factor Vv is checked, and the first commercial area candidate area is repeatedly selected. When the processing is completed, all W1vf are output as the first commercial area candidate area. This output may be a list of area names or may be displayed as GIS data. Further, the data file may be stored in the storage unit 30 and may be stored in the external storage device 40.

Next, a method for selecting a plurality of second commercial area candidate areas by the commercial area candidate selecting means will be described with reference to FIG. In step 300, the average of the recognition rates is calculated for all the first commercial area candidate areas W1vf. Step 3
In 02, M areas are selected in descending order of average recognition rate. In step 304, W1v
Output as f, W2vf, ..., Wmvf.

Next, according to the flowcharts of FIGS. 9 and 10, the second commercial area candidate area W1vf,
A process for obtaining the number of customers X when one of the W2vf, ..., Wmvf is the second commercial area candidate area is W will be described.

First, in step 400, the distance resistance coefficient fv due to the customer attraction factor is set. This distance resistance coefficient becomes a large value because the more you use it on a daily basis, the more you feel that you will be closer to it. It becomes a value. It is almost decided by the factor of attracting customers, and since it is different, that value is set. The second commercial area candidate area W is the residence Ww (1 ≦ w ≦ nw) according to the equation (2).
It is composed by. Therefore, in step 402, the residential area constituting the second commercial area candidate area is set as Ww and an initial value is set to w.

Next, at step 404, the time distance from the place of residence Ww to the customer attraction factor Vv is set to Twv. The position of the customer attraction factor Vv here is, for convenience, the time-distance center of the second commercial area candidate area. In reality, there are restrictions such as the place where the facility that attracts customers can be constructed, so it may be a biased point in the second trade area candidate area, but when obtaining a value as a predicted value From the viewpoint of obtaining an average value, the center of the time-distance is set as the position of the customer attraction factor Vv. The time distance is the time required to reach that position. In order to obtain the number of customers for each population composition type i, an initial value is set to i (step 406). At step 408, the attractiveness S of the attracting factor Vv for the population composition type i
Set vi. This is because the attractiveness Svi may or may not be attractive depending on the type of population structure depending on the attraction factor Vv. In addition, if there are facilities and events that are in the same business area and compete with each other and cause similar customer attraction, set them as well. The attendance rate for this customer attraction factor Vv is calculated by the equation (3) (step 4).
10). Steps 408 to 414 are repeated to obtain the visit ratio Rwvi from the residence Ww for all population composition types i. Further, from step 404,
By repeating step 418, the outbound rate Rwvi (1 ≦ w ≦ nw, 1 from all the settlements Ww forming the commercial area W)
≤v≤nv, 1≤i≤ni).

Next, in step 420, when the population of the population composition type i of the residence Ww recognizing the customer attraction factor Vv of the area recognition rate information is Pwvi, the population composition type i is calculated by the equation (4). Xi is the number of customers. further,
The total number of customers X, which is caused by the customer attraction factor Vv in the trade area W, is calculated by the equation (1) (step 421). Step 40
The processing from 0 to step 421 is repeated to obtain the number of customers Xi and the total number of customers X for each second commercial area candidate area W1vf, W2vf, ..., Wmvf according to the population composition type i. When distinguishing the number of customers Xi and the total number of customers X for each of the second commercial area candidate regions W1vf, W2vf, ..., Wmvf, the number of customers Xfi and the total number of customers Xf are described. In the case of simply describing, only the number of customers Xi and the total number of customers X are described.

Next, with reference to the flow chart of FIG. 11, a process of obtaining the new customer number PHX by the new customer number predicting means 23 will be described. In this description, one area representing the second commercial area candidate area will be described. The number of customers in other areas is calculated by performing the same process. Although the second trade area candidate area is not distinguished for simplicity of the symbol,
In reality, since there are a plurality of each, they are processed separately. First, in step 500, i is initialized in order to obtain the number of new visitors for the population structure type. Step 5
In 01, the corresponding number of customers Xi obtained by the number-of-customers forecasting means is set. In step 502, the commercial population coefficient PFi corresponding to the population composition type i is set.
In step 504, the number of new visitors PHXi of the population composition type i is calculated by the equation (5). By repeating Step 501 to Step 508 (1 ≦ i ≦ ni), all the new visitors PHXi for each population composition type i are obtained. Next, in step 501, the sum is calculated for the population composition type i, and the total number of new visitors PHX is obtained by the equation (6).

Next, the process of obtaining the number of visitors by the visitor number predicting means 25, which is a detailed description of step 108, will be described with reference to the flowchart of FIG. With respect to the own store Jk, the store information is obtained for each store scale in order to obtain the number of visitors for each of the plurality of store scales. Furthermore, the store scale is represented by k, and k = {1,
2, 3, ..., N}.

Here, the commercial zone Z indicates a range in which a person who visits the store for the purpose of the commercial facility j can attract customers. The trade area Z is composed of the place of residence Zz, and Z = Σz Zz (1 ≦ z
≤nz). Letting Rzj be the outbound rate to the commercial facility j (1 ≤ j ≤ nj), which is a plurality of commercial facilities existing in the commercial zone Z, the outbound rate is calculated by the equation (7).
Expression (7) is an expression using the Hough model, and the dispatch rate Rzj is the customer attraction force Gj of the commercial facility j existing in the commercial zone Z,
It can be obtained by the time distance from the residence Zz to the commercial facility j. The attracting power Gj of the commercial facility j is
Demanded by the charm of the store. Next, step 60
By repeating Step 606 from step 2, the ability to attract customers Gj of all commercial facilities j and the store scale of own store J + k
Find the customer attraction Gj + k for each k. Next, step 610
At the commercial facility j, the customer attraction power Gj, the own store J + k's customer attraction power Gj + k, and the time distance T from the residence Zz to the commercial facility j
Using zj, the visit ratio Rzj + k to the own store J + k of the store scale k is obtained from all the regions Zz forming the trade area Z by the formula (7). Next, in step 61 2, the commercial population of all areas Zz is the potential commercial population PHz existing in the residential area Zz, the population of the population composition type i is Piz, and the population composition type i is
PFi is the commercial population coefficient in, and it is calculated by equation (8). Further, in Step 614, the number of visitors PHj + k to the own store J + k is calculated by using the formula (9) by using the visit ratio Rzj + k to the own store J + k of the store scale k and the commercial population PHz. Ask. By repeating steps 610 to 618, the visitor number PHj + k is obtained for all the proposed store sizes.

Next, an explanation will be given of the processing for obtaining the new sales amount by the sales forecasting means 24 in accordance with the flowchart of FIG. First, f is initialized in order to obtain the sales amount Uf for all the second commercial area candidate regions Wf (step 700). Next, at step 702, the second commercial area candidate area Wf is set. In step 704, the number of new visitors PHXf for each second commercial area candidate area Wf is set.
Further, in step 706, in order to predict the sales amount for all the store scales, the store scale k is initialized. Next, at step 708, the number of visitors PHj + kf to the own store J + k of the store scale k is set. Using the average sales amount per person T (step 710) which is statistically known in advance, the sales amount is calculated by the equation (10) (step 71).
2). By repeating steps 702 to 716, the new sales amount Ufk is obtained for all the second commercial area candidate regions Wf.

Next, a method of deciding a commercial area candidate site by the commercial area candidate site deciding means 27 will be described with reference to the flowchart of FIG. In step 800, the store scale is initialized. Sales forecast means 24 for the corresponding store scale k
The second commercial area candidate areas Wf are rearranged in the descending order of the new sales amount Ufk for each of the second commercial area candidate areas Wf (step 802). Further, in step 804, commercial area candidate areas are set in descending order of sales amount. Step 8
At 06, the next store scale is set. In step 810, it is determined whether the commercial area candidate areas have been confirmed for all store sizes. Steps 802 to 810 are repeated to rearrange the second commercial area candidate areas Wf in descending order of the new sales amount Ufk for all store scales, and determine the commercial area candidate areas.

Finally, the commercial area candidate area and the prediction result are output via the output means 60. A description will be given according to the flowchart of FIG. In step 900, the commercial area candidate areas are output via the GIS output means 63 using the Nth highest attraction factor and the map. For example, by using a list for each store size as shown in FIG. 4, the locations of the commercial area candidate areas, factors for attracting customers, new sales amount, and predicted number of customers are displayed and printed out in order of increasing sales. At the same time, it may be stored in the external storage device 40 (step 900, step 902). Also, G
By using the IS output means 63, the commercial area candidate areas may be superimposed and output on a map, and the commercial area candidate areas may be displayed as a map on the display means 62 and printed by the printing means 61.

Further, as the trade area candidate area details shown in FIG. 16, the trade area candidate area location name, the details of the area constituting the trade area candidate area, the expected number of customers in each detailed area, the new sales amount, and the age of the main population composition type Alternatively, the detailed form such as the ratio in the trade area and the distance from the central area may be displayed and output. (Step 904).

The above-described output example is an example, and other output methods may be used.

The above-described embodiment is an example of the present invention, and the present invention is not limited to this. Various modifications can be considered in light of the essence of the invention.

[Brief description of drawings]

FIG. 1 is a connection block diagram of a commercial facility proposing apparatus showing an example of an embodiment of the present invention.

FIG. 2 is an explanatory diagram of store information.

FIG. 3 is a detailed explanatory view of store information.

FIG. 4 is an explanatory diagram of an output example of a commercial area candidate area.

FIG. 5 is a flowchart showing a processing procedure of an outline of a commercial facility proposal system.

FIG. 6 is a flowchart (part 1) showing a processing procedure for selecting a first commercial area candidate area.

FIG. 7 is a flowchart (part 2) showing a processing procedure for selecting a first commercial area candidate area.

FIG. 8 is a flowchart showing a processing procedure for selecting a second commercial area candidate area.

FIG. 9 is a flowchart (No. 1) showing a processing procedure of predicting the number of customers in a second commercial area candidate area.

FIG. 10 is a flowchart (No. 2) showing a processing procedure of predicting the number of customers in the second commercial area candidate area.

FIG. 11 is a flowchart showing a processing procedure for predicting the number of new visitors.

FIG. 12 is a flowchart showing a processing procedure for predicting the number of visitors.

FIG. 13 is a flowchart showing a processing procedure for predicting a new sales amount.

FIG. 14 is a flowchart showing a processing procedure for determining a trade area candidate area.

FIG. 15 is a flowchart showing a processing procedure of outputting a commercial area candidate area, a customer attraction factor, and a new sales amount.

FIG. 16 is an explanatory diagram of an output example of details of a trade area candidate area.

[Explanation of symbols] 10 ... Control device 20 ... CPU 21 ... Trade area candidate selection means 22 ... Means to predict the number of customers 23 ... New Customer Number Prediction Means 24 ... Sales forecasting means 25 ... Measures for predicting the number of visitors 27 ... Means for determining a candidate area for a commercial area 30 ... Storage means 31 ... Regional distribution information storage means 32 ... Area recognition rate information storage means 33 ... Store information storage means 40 ... External storage device 50 ... Operation input device 51 ... Information input means 52 ... Keyboard 53 ... Mouse 54 ... Scanner 55 ... Touch panel 56 ... Modem 60 ... Output means 61 ... Printing means 62 ... Display means 63 ... GIS output means

Claims (12)

[Claims] Claims: 1. Area distribution information of the population for each population composition type stored in the storage means, area recognition rate information for each of a plurality of factors attracting customers, and store information of other commercial facilities of the same type existing in the commercial area. A plurality of first commercial area candidate areas are selected by the commercial area candidate selecting means for each of the factors for attracting customers, and a plurality of first commercial area candidate areas are selected as the second commercial area candidate areas in order of higher area recognition rate. , For each of the plurality of second commercial area candidate areas, the number of customers attracted by the factor of attracting customers is calculated by the number-of-customers-attracting prediction means, and the number of customers obtained for each of the second commercial area candidates is used to obtain the second For commercial facilities of a plurality of store scales proposed for each trade area candidate area, the number of new visitors predicted for each of the second trade area candidate areas is calculated by the new visitor number prediction means for each store size, and each store size is calculated. The number of visitors for each commercial facility is the store Calculated by the number of visitors forecasting means using the information, the number of new visitors for each store size and the new sales amount predicted for each commercial facility using the number of visitors are calculated by the sales forecasting means, and for each store size In the second commercial area candidate area, the area with the highest new sales amount is determined in order from the area with the highest new sales amount by the commercial area candidate determining means, and the factor of attracting customers and the expected new sales amount for each store size are ,
A commercial facility proposal system, wherein the confirmed commercial area candidate area is output from an output means. 2. The commercial facility proposing system according to claim 1, wherein the store information has evaluation values for a plurality of evaluation items of the store that represent the ability to attract customers. 3. The commercial facility proposing system according to claim 2, wherein the evaluation value for the evaluation item of the store has an evaluation value obtained by comparison with other stores. 4. The area recognition rate information is area distribution information of a population recognizing the attraction factor for each population structure type, according to any one of claims 1 to 3. The commercial facility proposal system described. 5. The commercial area candidate selecting means defines, as a first commercial area candidate area, a continuous area having a predetermined area or more in which the population distribution of the area recognition rate information is a predetermined number or more with respect to a predetermined area. The commercial facility proposal system according to any one of claims 1 to 4, wherein: 6. The attracting number predicting means sets the attracting number of the population composition type i by the attracting factor Vv (1 ≦ v ≦ nv) to Xi, and the attracting number is X, where X = Σi Xi (1 ≦ i ≦ ni), ... (1) Residence Ww (1 ≦ w ≦, which constitutes the second commercial area candidate area W
nw), W = Σw Ww (1 ≦ w ≦ nw); (2) Population of population composition type i of the residential area Ww that recognizes the attracting factor Vv of the area recognition rate information Let Pwvi be the outbound rate Rwvi of the population composition type i with respect to the customer attraction factor Vv in the residential area Ww, and Rwvi = (Svi / Twv ^fv ) / (Σv (Svi / Twv ^fv )), (3) ΣviRwvi = 1, Svi: The attractiveness of the attracting factor Vv to the scale of the attracting factor Vv and the population composition type i Twv: The time distance fv from the place of residence Ww to the attracting factor Vv: The resistance coefficient to the distance at the attracting factor Vv The commercial facility proposing system according to claim 5, wherein the number of customers is calculated by: Xi = Σw (Rwvi × Pwvi) (4) 7. The new visitor number predicting means is: PHXi, the number of new guests of the population structure type i, Xi, the number of customers due to the factor of attracting customers of the population structure type i, and the number of visitors to the commercial facility for each population structure type i. Assuming that the coefficient is PFi, the number of new visitors of the population composition type i is calculated by [Formula 5] PHXi = Xi × PFi (5), and the number of new visitors is calculated as [Formula 6] PHX = Σi PHXi (1 ≦ i ≦ ni), ...
(6) The commercial facility proposal system according to claim 6, wherein: 8. The visitor number predicting means is a commercial facility j (1 ≦ j ≦) existing in a commercial area out of the population residing in a residential area Zz (1 ≦ z ≦ nz) constituting the commercial area Z of the commercial facility j. when the visits rate to nj) and Rzj, [number 7 ^{Rzj = (Gj / Tzj fj)} / (Σj (Gj / Tzj fj)) ... (7) Σj Rzj = 1, Gj: commercial facility j attract customers Force, Tzj: time distance from the residential area Zz to the commercial facility j, fj: resistance coefficient depending on the distance to the commercial facility, and the population of the population composition type i existing in the residential area Zz is P
Let iz be the visitor coefficient for population composition type i, PFi,
The store visit population PHz of the residence Zz is obtained by [Equation 8] PHz = Σi (Piz × PFi) (8), and the number of visitors PHj of the commercial facility j is [Equation 9] PHj = Σz (Rzj × PHz) The commercial facility proposing system according to claim 7, wherein the commercial facility proposing system is obtained by (9). 9. The sales forecasting means, where PHX is the number of new visitors, PHj is the number of visitors to a commercial facility j, U is the amount of sales, and T is the average amount of sales per person. = (PHj + PHX) * T, ... (10) The commercial facility proposal system according to claim 8, wherein: 10. The store information further includes evaluation items y of stores in each of the commercial facilities j.
Evaluation value ayj (1 ≦ y ≦ ny) of the evaluation item y, and the weight occupying the evaluation of the store of the evaluation item y is α y (1 ≦ y ≦
ny), the store attraction power Gj is obtained by the following formula: Gj = Σy (ayj × αy) / Σyαy (11). . 11. The commercial facility proposing apparatus used in the commercial facility proposing system according to any one of claims 1 to 10, wherein the commercial facility proposing device has the regional distribution information of the population for each population composition type and each of the factors for attracting customers. Information input means for inputting area recognition rate information and the store information, information storage means for storing the input information, the trade area candidate selection means, the customer attendance forecasting means, and the new visitor forecast Means, the sales forecasting means, the store scale deciding means, the visitor number forecasting means, and the trade area candidate location deciding means, the input information, the customer attraction factor, and the forecast A commercial facility proposing apparatus comprising: the new sales amount to be output; and an output unit that outputs the confirmed candidate commercial area. 12. The commercial facility proposing apparatus according to claim 11, wherein the output means further comprises map information system output means.