JP2002352041A - System for predicting sales in game facility - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system for predicting sales in a newly constructed or the episting game facility, the system in which the number of customers and the sales are predicted on the basis of appeal, as the game facility, of game facilities existing in a market including a user's shop. SOLUTION: The number of installed game machines classified by machine types, the number of game players, the degree of appeal of game machines classified by machine types, and the degree of appeal of the game facility existing in the market including the user's shop are digitized by comparison with those of other shops and comprehensively evaluated to digitize the appeal of the game facility, and the visit rate of a game population in the market is calculated to predict the number of customers and the sales.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system for predicting customer attraction and sales of a gaming facility such as a pachinko hall in a commercial area (area).

[0002]

2. Description of the Related Art Conventionally, as a means for determining whether a commercial facility in a commercial area is appropriate, a method using a Huff model used for mobilization prediction, sales prediction, and the like is well known. The Huff Model is also effective at amusement facilities, and the theoretical calculation of the turnover rate of customers between your store and competitors using the store size allows the game population to be You can ask how easy it is to come. As a result, the number of customers can be estimated and sales can be predicted. When using the Huff model, the scale was often used as the attractiveness of each game facility.

[0003]

That is, the number of visitors obtained by using the conventional Huff model is an estimate of the number of visitors using the scale of the game facility, and the attractiveness of the installed gaming table, Due to ingenuity and appeal, the number of visitors could not be increased.

[0004] In other words, there is no scale for quantitatively evaluating the sensory part and the gambling factor, which are the major attractions of a game store. It was difficult to make quantitative evaluations and comparisons. Therefore, it has been difficult to objectively evaluate which part is inferior or superior to the competing store and to quantify it. Furthermore, there was no objective evaluation method of the installed gaming table. In addition, there was no way to evaluate the ingenuity and attractiveness of a game facility. Therefore, there is no system that uses the Huff model to predict customers by using the attractiveness of a game facility and to predict sales.

[0005] Furthermore, there is no method for estimating the number of visitors by using the evaluation of how many people actually support each type of game console.

[0006] Therefore, the purpose of the present invention is,
It is to enable accurate sales forecasting by estimating the number of visitors by evaluating the device and attractiveness as a game facility. The other purpose is to objectively evaluate which part is inferior or superior to competing stores, and to predict customers using attractiveness of amusement facilities, Making predictions. Still another object is to enable accurate sales forecasting by estimating the number of customers using an evaluation of how many people actually support each type of game console. The above-mentioned objects of the invention are objects to be achieved by each invention, and should not be construed that each invention achieves all objects at the same time.

[0007]

In order to solve the above-mentioned problems, a first game facility sales amount prediction system according to a first aspect of the present invention is a system for predicting a sales area of a customer attraction area including its own store stored in a storage device in advance. Regional game population distribution information, pachinko parlors existing in commercial areas, first gaming machine information that is an evaluation value obtained for a plurality of evaluation items for each model of installed gaming machines in gaming facilities including pachislot shops, The first game console attractiveness calculating means uses the number of game consoles installed in each game facility and the game facility information including the evaluation values for a plurality of evaluation items of the game facility, and the first game console attractiveness calculation means, and First
Enabled to calculate the game console attractiveness. Further, the first gaming facility attractiveness calculating means can be used to calculate the first gaming facility attractiveness for each gaming facility using the obtained first gaming table attractiveness, and the first gaming facility attractiveness can be calculated. By using the degree, the first customer attracting rate calculating means can calculate the first customer attracting rate to the own store of the gaming population in the commercial area. Next, based on the regional game population distribution information and the determined first customer attracting rate, the first customer attracting number predicting means makes it possible to calculate the number of customers attracted to the own store. The system is characterized in that a predicted sales amount is calculated, and the predicted sales amount can be output by an output unit.

Further, in the second invention, the first game facility sales amount prediction system calculates the first game console attractiveness in order to evaluate the attractiveness of the game console as a numerical value. Using the first gaming machine information in the calculating means, the first gaming machine attractiveness of the gaming machine of model k is calculated as E1k (1 ≦ k ≦ n
_k ), the evaluation value of the model k of the evaluation item d of the game _console is a _kd (1
≦ d ≦ n _d ), and when the weight of the evaluation item d in the evaluation of the gaming machine is α _d (1 ≦ d ≦ n _d ),

Equation 12] E1k = sigma _d is characterized in that as determined by _{(a kd × α d) /} Σ d α d ... (12).

Further, in the third invention, the first game facility sales amount prediction system includes a first game facility j (1 ≦ j ≦ n _j ) for evaluating the attractiveness of the game facility as a numerical value. gaming facility attractiveness G1j a _{(1 ≦ j ≦ n j)} , is an evaluation value which is determined that there is attractive gaming facility larger, the first game machine attractiveness, first by using the gaming facility information The first game facility attractiveness calculation means can calculate the first game machine attractiveness of the game machine of model k, E1k (1 ≦ k ≦ _nk ), and the evaluation value of the evaluation item y of the game facility j. the _{bjy (1 ≦ j ≦ n j} , 1 ≦ y ≦ n y), a weight which accounts for the evaluation of the gaming facility of the evaluation item y βy (1 ≦ y ≦
n _y ), the weight of the first game console attraction evaluation being βn
_{y + 1,} and the gaming table of the number of installed model k in the gaming facility j and _{Djk (1 ≦ j ≦ n j} , 1 ≦ k ≦ n k),

G1j = ((ΣkE1k × Djk) × βny _{+ 1} ) + Σy (bjy × βy)) / (Σyβy + βny _{+ 1} ) (13) I do.

Further, the first gaming facility sales amount prediction system according to the fourth aspect of the present invention uses the attractiveness of the first gaming facility to determine the first customer attracting rate, so that the residential area Ww constituting the commercial area W is obtained. (1 ≦ w ≦ n _w ),

W = １４w Ww (1 ≦ w ≦ n _w ); (14), the gaming facility J (1 ≦ J ≦
n _j ), the first customer attracting rate R1wJ is calculated by the first customer attracting rate calculating means:

[Number 15] ^{R1wJ = (G1J / TwJ fj)} / (Σj (G1j / Twj fj)); (1 ≦ w ≦ n w, 1 ≦ j ≦ n j), ... (15) Σj R1wj = 1; (1 ≦ j ≦ n _j ), G1j: first game facility attractiveness of game facility j Twj: time distance from residence Ww to game facility j fj: resistance coefficient to distance I do.

Further, the first game facility sales amount prediction system according to the fifth aspect of the present invention provides a local game population distribution in order to obtain the number of customers using a customer collection rate obtained using the degree of attraction of the first game facility. The game population inhabiting in the residential area WW (1 ≦ w ≦ n _w ) constituting the commercial area W of the gaming facility j in the information is PH
w (1 ≦ w ≦ n _w ), and the game facility j (1
≦ j ≦ n _j ), the first rate of attracting customers is R1wj (1 ≦ w ≦
When n _w , 1 ≦ j ≦ n _j ), the number of visitors PHj (1 ≦ j ≦ n _j ) of the gaming facility j is calculated by the first number of visitors prediction means.

(16) PHj = Σw (R1wj × PHw) (16)

Further, the second game facility sales amount prediction system according to the sixth aspect of the present invention is a game machine sales amount prediction system, comprising: a pre-stored storage device; Second, which is the number of players for each type of gaming table installed in a gaming facility including a store and a pachislot store.
The second game console attractiveness calculation is performed by using the game machine information of the game machines, the number of game machines installed in each game facility, and the game facility information including the evaluation values for a plurality of evaluation items of the game facilities. By means, the second game console attractiveness for each model can be calculated. Further, the second game facility attractiveness calculating means can be used to calculate the second game facility attractiveness for each game facility using the obtained second game console attractiveness, thereby obtaining the second game facility attractiveness. The second customer attracting rate calculating means can calculate the second customer attracting rate of the game population in the commercial area by using the degree. Next, based on the regional game population distribution information and the determined second attracting rate, the second attracting number prediction means enables the number of attracting customers to be calculated, and using the number of attracting customers,
It is characterized in that the predicted sales amount is calculated by the sales amount prediction means, and the predicted sales amount can be output by the output means.

Further, in the second game facility sales amount prediction system according to the seventh aspect of the present invention, in order to be able to grasp the preference of the gaming table, which differs according to the type of population, the distribution information of the local game population and the second game are provided. The table information is characterized by comprising population composition type information.

Further, in the second game facility sales amount prediction system according to the eighth aspect of the present invention, in order to be able to grasp the preference of the gaming table which varies depending on the age band, the population structure type is classified by age band. It is characterized by doing so.

Further, in the second game facility sales amount prediction system according to the ninth invention, the demographic composition type may be gender-specific so that it is possible to grasp the preference of the gaming table which differs according to gender. It is characterized by the following.

Further, according to the second game facility sales amount prediction system in the tenth invention, the degree of attraction of the gaming table can be obtained from the preference of the gaming table by the player, so that the second gaming table attractiveness can be obtained. The degree is obtained using the second game table information reflecting the player's selection of the game table in the second game table attractiveness calculating means, and the second game of model k (1 ≦ k ≦ _nk ) is determined. The degree of attractiveness of the vehicle is E2k (1 ≦ k ≦ _nk ), and the population type i
The second attractiveness of the model k with respect to (1 ≦ i ≦ n _i ) is E2k
when the _{i (1 ≦ k ≦ n k} , 1 ≦ i ≦ n i), E2k
= {E2ki} (1 ≦ i ≦ n _i ), and Pijk (1 ≦ i
≦ n _i , 1 ≦ j ≦ n _j , 1 ≦ k ≦ n _k ) is the number of players of the population type i at the gaming table of model k in the commercial area, which is the second gaming table information, Djk (1 ≦ j ≦ n _j , 1 ≦ k ≦
_nk ) is the model k which is the store information in the trade area
The second attraction level is E2ki
Is

[Expression 17] E2ki = (Σj Pijk) / (Σj Djk) (17)

Further, a second game of the eleventh invention is provided.
The facility sales forecasting system can be used to
Reflect the attractiveness of Mito as a game facility in the attractiveness of the game facility
In order to play, the game facility j (1 ≤ j ≤ n_j) Second game
Facility attractiveness G2j (1 ≤ j ≤ n _j) Is the population type i (
1 ≦ i ≦ n_iGame facility attraction G2ji ()
1 ≦ j ≦ n_j, 1 ≦ i ≦ n_i) And G2
k = {G2ki} (1 ≦ i ≦ n_i) And large if large
This is an evaluation value that determines that amusement facilities are very attractive.
Using the second game console attractiveness and the gaming facility information
Of the game k
The second game console attractiveness E2k of the game console is determined by the population type i
The second game console attraction level E2ki,
2k = {E2ki} (1 ≦ i ≦ n_i), Evaluation item of gaming facility j
The evaluation value of the eye y is bjy (1 ≦ y ≦ n_y), Evaluation item y
Βy (1 ≦ y ≦ n)_y),
Βn is the weight occupied in the evaluation of the gaming machine attractiveness of No. 2._{y + 2}, Games
The number of game consoles of model k installed at facility j is Djk (1 ≦
j ≦ n_j, 1 ≦ k ≦ n_k)

(18) G2ji = ((ΣkE2ki × Djk) × βny _{+ 2} ) + Σy (bjy × βy)) / (Σyβy + βny _{+ 2} ) (18) And

Furthermore, the second game facility sales amount prediction system in the twelfth aspect of the present invention uses the second game facility attractiveness to determine the second customer attracting rate, so that the residence area WW ( 1 ≦ w ≦ n _w )

(19) W = １９w Ww (1 ≦ w ≦ n _w ); (19) Population composition type i (a) in the residential area Ww by the gaming facility J
1 ≦ _i ≦ n i) second attracting rate R2wJi (1 ≦ w ≦ into
n _w , 1 ≦ j ≦ n _j ) in the second attracting rate calculation means,

[Number 20] ^{R2wJi = (G2Ji / TwJ fj)} / (Σj (G2ji / Twj fj)), ... (20) ΣjiR2wji = 1, G2ji: the second of the gaming facility attractive to the scale and population structure type i of the gaming facility j Degree, Twj: the time distance from the place of residence Ww to the game facility j, and fj: the coefficient of resistance to the distance.

Further, the second gaming facility sales amount prediction system according to the thirteenth aspect of the present invention provides the gaming facility j (1 ≦ j ≦ n _j ), a residential area Ww constituting the trade area W
(1 ≦ w ≦ n _w )
(1 ≦ i ≦ n _i ) The game population is represented by PHwi (1 ≦ w ≦ n _w , 1
≦ i ≦ n _i ) and the second rate of attracting customers to the population type i by the gaming facility j existing in the commercial area is Rwji (1 ≦ w ≦
When n _w , 1 ≦ j ≦ n _j , 1 ≦ i ≦ n _i ), the number of visitors PHj (1 ≦ j ≦ n _j ) of the gaming facility j is calculated by the second number of attendance prediction means.

(21) PHj = ji (Σw (R2wji × PHwi)) (21)

Further, the sales forecasting means in the fourteenth invention uses the number of customers attracted by the above-described method to estimate the number of customers in the gaming facility j (1 ≦ j ≦ n _j ) in order to predict the sales. _{PHj (1 ≦ j ≦ n j} ), an average number of visits to the store n, when the per vehicle average sales amount was DT, the sales amount U,

(22) U = PHj × N × DT (22)

Further, in the fifteenth invention, the regional game population distribution information is characterized by further comprising time zone-specific regional game population distribution information in order to grasp the regional game population distribution that varies depending on the time zone. I do.

Further, in the sixteenth invention, the regional game population distribution information is characterized by further comprising regional game population distribution information for each day of the week in order to grasp the regional game population distribution that varies depending on the day of the week.

Further, the regional game population distribution information in the seventeenth aspect of the present invention may further comprise a holiday or a non-holiday regional game population distribution information in order to grasp a different regional game population distribution on holidays and outside holidays. It is characterized by having done.

Further, in the eighteenth aspect, the number of players is characterized by being composed of the number of players by time zone in order to grasp the number of players different by time zone.

Further, in the nineteenth invention, the number of players is characterized by comprising the number of players by day of the week in order to grasp the number of players different by day of the week.

Further, in the twentieth aspect, the number of players is characterized by further comprising a holiday or a different number of players outside of the holiday in order to ascertain a different number of players outside the holiday. And

Further, in the twenty-first aspect of the present invention, the regional game population distribution information uses the information of the map information system in the first game facility sales amount prediction system and the second game facility sales amount prediction system described above. It is obtained from a map information system so that the information can be obtained.

Further, in the twenty-second aspect of the present invention, the first game facility sales amount prediction device used in the first game facility sales amount prediction system comprises: a local game population information; a first game table information; First information input means for inputting information, information storage means for storing the input information,
A first game console attractiveness calculating means, a first gaming facility attractiveness calculating means, a first customer attracting rate calculating means, a first customer attracting number predicting means, and a sales amount predicting means; It is characterized by comprising an arithmetic means, and an output means for outputting the input information and the estimated sales amount.

Further, in the twenty-third aspect of the present invention, the second game facility sales amount prediction device used in the second game facility sales amount prediction system comprises: a local game population information; a second game table information; Second information input means for inputting information, information storage means for storing the input information,
A second game console attractiveness calculating means, a second gaming facility attractiveness calculating means, a second customer attracting rate calculating means, a second customer attracting number predicting means, and a sales amount predicting means; It is characterized by comprising an arithmetic means, and an output means for outputting the input information and the estimated sales amount.

[0030]

According to the first game facility sales amount prediction system of the present invention having the above-described structure, information on the distribution of local game population in a commercial area, which is a customer attraction area including own shops, and pachinko parlors existing in the commercial area, In gaming facilities including pachislot stores,
Since the first game console information, which is an evaluation value obtained for a plurality of evaluation items for each model of the installed game console, is stored in the storage device in advance, the game console is evaluated for each model,
The evaluation value can be stored in the storage device. Further, the game facility information including the number of game machines installed in each game facility and the evaluation value for a plurality of evaluation items of the game facility is stored in the storage device in advance. The evaluation value for can be used. Next, the first gaming console attractiveness calculating means can calculate the first gaming console attractiveness for each model by using the first gaming console information which is the evaluation value of the gaming console stored in the storage device. I made it. Thereby, the evaluation value of the gaming table can be used as the attractiveness. Further, the first gaming facility attractiveness calculating means can be used to calculate the first gaming facility attractiveness for each gaming facility using the first gaming table attractiveness and the gaming facility. As a result, the degree of attraction of the gaming facility can be obtained using the evaluation value of the installed gaming table and the attraction of the gaming facility.

Further, the first customer attracting rate calculating means can calculate the first customer attracting rate of the game population in the commercial area to the own shop by using the first game facility attractiveness. The customer attracting rate can be obtained using the first game facility attractiveness of another competing store existing in the commercial area. Further, based on the regional game population distribution information and the first rate of attracting customers, the number of customers attracting to the own store can be calculated by the first attracting number predicting means. Further, the estimated sales amount can be calculated by the sales amount prediction means using the obtained number of customers, and the predicted sales amount can be output by the output means. Therefore, it is possible to predict customers by using the evaluation value of the gaming table installed in the gaming facility and the evaluation value of the gaming facility, and to predict the sales. You will be able to make predictions.

Further, according to the second invention, in the first game facility sales amount prediction system, the first game console attractiveness E1k (1 ≦ k ≦ _nk ) of the game console of the model k is determined by The evaluation value of the model k of the evaluation item d of the game console is obtained by using the first game console information in the first game console attractiveness calculating means.
_{Assuming that kd} (1 ≦ d ≦ n _d ) and the weight of the evaluation item d in the evaluation of the game console is α _d (1 ≦ d ≦ n _d ), the weight can be obtained by the equation (1). The first game console information, which is the evaluation value of the game console for each model stored in the means, is used to assign a weight to the overall evaluation of each evaluation item to determine the first game console attractiveness of the game console. You can ask for it.

Further, according to the third invention, in the first game facility sales amount prediction system, the game facility j (1
≦ j ≦ n _j ) the first game facility attractiveness G1j (1 ≦ j ≦ n)
_j ) is an evaluation value for determining that the larger the larger, the more attractive the gaming facility is, and the first gaming table attractiveness E1k,
The evaluation value of the evaluation item y of the gaming facility j which is the gaming facility information is bjy, and the weight of the evaluation item y in the evaluation of the gaming facility is βy
, The weight of the first game console attractiveness evaluation as βny _{+ 1} ,
The first game facility attractiveness calculating means can obtain the value by the equation (2) using the number of installed game tables Djk of the model k in the game facility j. As a result, the number of installed games can be reflected on the first gaming table attractiveness of the installed gaming tables in the gaming facility, and the first gaming facility attractiveness of the gaming facility combined with the evaluation value as the gaming facility can be obtained. become.

Further, according to the fourth invention, in the first game facility sales amount prediction system, in the residence WW (1 ≦ w ≦ n _w ) constituting the commercial area W, the commercial area W is expressed by the formula (3) ), The first customer attracting rate R1wJ by the gaming facility J (1 ≦ J ≦ n _j ) at the place of residence Ww.
Is the first gaming facility attractiveness G1j of the gaming facility j, the residence W
Using the time distance Twj to the game facility j and the resistance coefficient fj with respect to the distance from the w, the first customer attracting rate calculation means can be obtained by Expression (4). As a result, the first attracting rate of the gaming facility J at the residence Ww is
The first game facility attractiveness can be obtained using the first game facility attractiveness. The attractiveness of the gaming facility makes it possible to determine the proportion of the gaming population that can attract customers. When using the Huff model to determine the customer acquisition rate of commercial facilities, the scale of all commercial facilities existing in the commercial area, the time distance to commercial facilities,
It is obtained by using the resistance coefficient with respect to the distance. At this time, the distance resistance coefficient is, for example, in a shopping center,
2.0 for daily necessities, 1.5 for purchased goods
Degree is used. In the case of a game facility, it differs depending on the location conditions. The distance resistance coefficient is small when the road condition is good, and is large when the road condition is bad. In addition, the completeness of the parking lot has a significant effect. The actual numerical values are individually set based on experience in consideration of such conditions.

The meaning of the equation when Σj R1wj = 1 is as follows:
The gaming population from a certain area Ww is determined to be
It means to go to. That is, when the Huff model is used, it is assumed that all the game population living in the area Ww go to one of the game facilities j existing in the commercial area.

Further, according to the fifth aspect of the present invention, in the first game facility sales amount prediction system, the settlement area constituting the commercial area W of the game facility j (1 ≦ j ≦ n _j ) in the regional game population distribution information. _{ww (1 ≦ w ≦ n w} ) and game population PHw living in the Acquisition number PHj game facility j using the first attracting rate R1wj by game facility j present in commercial area the previously obtained formula (5) Can be obtained by This makes it possible to obtain the first customer attracting rate obtained using the attraction of the gaming facility.

Further, according to the sixth aspect of the present invention, in the second game facility sales amount prediction system, information on the distribution of regional game population in a commercial area, which is a customer attraction area including its own shop, and pachinko and pachislot stores existing in the commercial area Since the second game console information, which is the number of players for each model of the installed gaming table in the gaming facility including the above, is stored in the storage device in advance, the number of players on the installed gaming table for each model can be stored. Become. Further, the game facility information including the number of game machines installed in each game facility and the evaluation value for a plurality of evaluation items of the game facility is stored in the storage device in advance. The evaluation value for can be used. Next, using the second game console information, which is the actual number of players stored in the storage device, the second game console attractiveness calculating means can calculate the second game console attractiveness for each model. I made it. Further, the second game facility attractiveness calculation means can be used to calculate the second game facility attractiveness for each game facility using the second game console attractiveness. Further, the second attracting rate calculating means calculates the second attracting rate of the gaming population in the commercial area to the own shop by using the obtained second gaming facility attractiveness, thereby obtaining the regional gaming population distribution information and the second attracting rate. According to the customer attracting rate of 2, the customer attracting number to the own store can be calculated by the second customer attracting number predicting means. Further, using the number of customers attracted, the estimated sales amount is calculated by the sales amount prediction means,
The estimated sales amount can be output by the output unit.
As a result, it becomes possible to obtain the second game console attractiveness of the game console by the number of players at the installed game consoles for each actual model, and to perform the forecast of the number of customers attracted and the sales forecast reflecting the actual information. Will be able to

Further, according to the seventh aspect of the present invention, in the second game facility sales amount prediction system, the regional game population distribution information and the second game console information comprise population structure type information. It is possible to obtain the second game console attractiveness for each type, and it is possible to predict the number of customers and sales by population type. In general, it is known that preferred gaming tables are different depending on the type of population, so that more accurate customer attraction prediction and sales prediction can be performed.

Further, according to the eighth invention, in the above-mentioned second game facility sales forecast system, the demographic composition type is by age band, so that the second game console attractiveness for each age band is obtained. Is required, the second gaming facility attractiveness using the second gaming table attractiveness according to age band,
Since it will be possible to determine the second customer attraction rate,
Also in the distribution information of the game population, since the information is by age band, the number of customers by age band can be obtained. Therefore, more accurate sales prediction can be performed.

Further, according to the ninth aspect, in the second game facility sales amount prediction system, since the population structure type is further divided by gender, the second game table information
The second game console attractiveness for each gender can be obtained. Further, using the obtained second game console attractiveness, the second game facility attractiveness is obtained, the second customer attracting rate is obtained, and the number of customers attracted is predicted using the regional game population distribution information by gender. As a result, it is possible to more accurately predict customers. As a result, the sales forecast can be made accurately. Further, by using the present invention in combination with the eighth invention, it becomes possible to obtain the second game console attractiveness by gender and age band. Will be able to do. As a result, more accurate customer attraction prediction can be performed, and sales prediction can also be performed accurately.

Further, according to the tenth aspect, the second aspect is provided.
In the game facility sales amount prediction system, the second game console attractiveness E2k is obtained by setting the second attractiveness of the model k to the population type i as E2ki. E2ki is the number of players Pijk of the population type i in the gaming machine of the model k of the gaming facility j in the commercial area which is the second gaming machine information, and the number of the gaming machines of the model k which is the gaming facility information existing in the commercial area. It is obtained by equation (6) using the installed number Djk. this is,
Since it is the ratio of the actual number of players to the number of installed games, the second game console attractiveness can be obtained from the ratio of the actually used game consoles. Furthermore, the second
Can be obtained according to the demographic composition type, so that it is possible to predict the number of customers and sales for each demographic composition type depending on how the actual table is selected.

Further, according to the eleventh aspect, the second aspect
In the gaming facility sales forecasting system, the second gaming facility attractiveness G2j is composed of the second gaming facility attractiveness G2ji for the population type i, and the second gaming console attractiveness E
2ki, the evaluation value bjy of the evaluation item y of the gaming facility j, the weight βny _{+ 2 in} the evaluation of the second game console attractiveness, the evaluation item y
Using the weight βy in the evaluation of the gaming facility of the above and the number Djk of the gaming tables of the model k installed in the gaming facility j, the equation (7) is used. The second game facility attractiveness can be obtained. Thus, the second game facility attractiveness can be obtained using the second game table information that is the actual number of players at the game table.

Further, according to the twelfth aspect, the second aspect
In the gaming facility sales amount prediction system, the residential area Ww constituting the commercial area W is expressed by the following equation (8).
The second attracting rate R2wJi to the demographic type i by the gaming facility J in w is calculated by the second attracting rate calculating means, and the second game facility attractiveness level to the demographic type i and the residential area Ww
From the time distance to the gaming facility j and the resistance coefficient with respect to the distance. Thereby, the second
The second rate of attracting customers using the game facility attractiveness can be obtained.

Further, according to the thirteenth aspect, the second aspect
In the game facility sales amount prediction system of the above, in the regional game population distribution information, the game population PH of the population structure type i of the game population living in the residence Ww constituting the trade area W of the game facility j
Using wi and the second attracting rate Rwji for the population type i by the gaming facility j existing in the commercial area, the gaming facility j
Is calculated by the second method for predicting the number of customers from the formula (1).
0). As a result, the number of customers to be attracted can be obtained using the second game console attractiveness.

Further, according to the fourteenth aspect, the sales forecasting means used in the above-mentioned gaming facility sales amount prediction system uses the number of customers attracted, the average number of visits N, and the average sales amount per vehicle DT, Expression (11) allows the sales amount to be predicted. Therefore, the sales amount can be predicted using the number of customers attracted using the above-described first game console attractiveness and the second game console attractiveness.

Further, according to the fifteenth aspect, the regional game population distribution information used in the above-mentioned gaming facility sales amount prediction system further includes time zone-specific regional game population distribution information. Therefore, it is possible to perform customer attraction prediction and sales prediction for each time zone. As a result, more accurate sales prediction can be expected. In addition, it is possible to grasp a time zone in which sales are good and a time zone in which sales are bad.

Further, according to the sixteenth aspect, the regional game population distribution information used in the above-mentioned gaming facility sales amount prediction system further includes day-of-week regional game population distribution information. Therefore, it is possible to perform the customer attraction prediction and the sales prediction for each day of the week. As a result, more accurate sales prediction can be expected. In addition, the day of the week with a large amount of sales and the day of the week with a small amount of sales can be grasped. Further, when used in conjunction with the fifteenth aspect, it is possible to ascertain whether the sales amount is large or small at the time and the day of the week.

Further, according to a seventeenth aspect, the regional game population distribution information used in the above-mentioned gaming facility sales forecast system further comprises holiday or non-holiday regional game population distribution information. Therefore, it is possible to perform the customer attraction prediction and the sales prediction separately on holidays or on holidays. As a result, more accurate sales prediction can be expected. In addition, it is possible to recognize a holiday with a large sales amount or a holiday. Furthermore, the fifteenth and sixteenth
By using the present invention in conjunction with the invention, it is possible to determine whether the sales amount is large or small during the time period, the day of the week, holidays, and holidays.

Further, according to the eighteenth aspect, the number of players used in the above-mentioned second game facility sales amount prediction system further includes the number of players by time zone. The facility attractiveness can be obtained, and when used in conjunction with the fifteenth aspect, it is possible to perform customer attraction prediction and sales prediction by time zone.

Further, according to the nineteenth aspect, the number of players used in the second game facility sales amount prediction system further includes the number of players by day of the week. Therefore, the second game facility attractiveness can be obtained for each day of the week, and when used in conjunction with the sixteenth invention, it is possible to perform customer attraction prediction and sales prediction for each day of the week. Further, by using the present invention in combination with the eighteenth and fifteenth aspects, it is possible to perform customer attraction prediction and sales prediction by day of the week and by time zone.

Further, according to the twentieth aspect, the number of players used in the second game facility sales forecasting system further includes holidays or non-holiday players. Therefore, the second game facility attractiveness can be obtained for each holiday or non-holiday, and when used in conjunction with the sixteenth invention, it is possible to predict the number of customers and sales for each holiday or non-holiday. Will be able to further,
When used in combination with the eighteenth and fifteenth aspects, it is possible to perform customer forecasting and sales forecasting on holidays, outside holidays, and time zones.

Further, the fifteenth, sixteenth, seventeenth, first
By using the eighth, ninth, and twentieth aspects of the present invention together, it is possible to perform customer attraction prediction and sales prediction by day of week, holiday, by day outside of holiday, and by time zone.

Further, according to the twenty-first aspect, the regional game population distribution information used in the game facility sales amount prediction system is obtained from the map information system.
It becomes easy to obtain regional game population distribution information. Further, accurate information can be obtained.

Further, according to the twenty-second aspect, according to the first aspect,
First used in the gaming facility sales forecast system
The game facility sales amount prediction device includes information input means for inputting regional game population distribution information, first game console information, and game facility information; information storage means for storing the input information; A game console attractiveness calculating means, a first gaming facility attractiveness calculating means, a first customer attracting rate calculating means, a first customer attracting number predicting means, a calculating means having a sales amount predicting means,
Since the input device and the output unit for outputting the predicted sales amount are provided, necessary information can be input to the first game facility sales amount prediction device.
, The first gaming facility attractiveness, the first attracting rate, the first number of attracting customers, and the predicted sales amount. Further, the output means enables the input information to be output-confirmed and the calculated predicted sales amount to be output.

Further, according to the twenty-third aspect, the second aspect
Used in the game facility sales forecast system
A game facility sales amount predicting device, information input means for inputting regional game population information, second game table information, and game facility information; information storage means for storing the input information; A game console attractiveness calculating means, a second gaming facility attractiveness calculating means, a second customer attracting rate calculating means, a second customer attracting number predicting means, and a calculating means having sales amount predicting means are inputted. And the output means for outputting the predicted sales amount, it is possible to input necessary information in the second game facility sales amount prediction device, and further, the second gaming machine attractiveness level, The second game facility attractiveness, the second rate of attracting customers, the second number of attracting customers, and the estimated sales amount can be obtained.
Further, the output means enables the input information to be output-confirmed and the calculated predicted sales amount to be output.

The functions and effects of the above-described invention are the functions and effects achieved by the respective inventions, respectively, and should not be construed as meaning that each invention achieves all the functions and effects at the same time.

[0057]

DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 1 is a block diagram showing a configuration of a game facility sales amount prediction device for realizing a first game facility sales amount prediction system according to one embodiment of the present invention. The control device 10 includes a first gaming table attractiveness calculating means 21, a first gaming facility attractiveness calculating means 22, and a first customer attracting rate calculating means 2.
3, first customer attracting number predicting means 24, and sales amount predicting means 2
5, a storage unit 30 for storing a local game population distribution information storage unit 31 for each population type, a first gaming table information storage unit 32, and a game facility information storage unit 33. Be composed. The information input means 51, which is the operation input device 50, includes a keyboard 52, a mouse 53, a scanner 54, a touch panel 55, and a modem 56.
The information on the area distribution of the population for each type of population, the first game console information, and the information on the game facilities are input and stored in the storage means 30 via the information input means 51.

FIG. 4 is a block diagram showing a configuration of a game facility sales amount prediction device which realizes a second game facility sales amount prediction system according to another embodiment of the present invention. Only different points from the first game facility sales amount prediction system will be described. The control device 10 controls the second game console attractiveness calculating means 26,
CPU 20 which is a calculating means having a gaming facility attractiveness calculating means 27, a second attracting rate calculating means 28, a second attracting number predicting means 29, and a sales amount predicting means 25; Local game population distribution information storage means 31;
Game table information storage means 34 and game facility information storage means 3
3 is constituted by a storage means 30 for storing the information. The second game console attractiveness calculating means 26 calculates the second game console attractiveness using the second game console information, and uses the second game console attractiveness and the game facility information to perform a second game console attractiveness calculation. The game facility attractiveness calculating means 27 calculates a second game facility attractiveness. Further, the second attracting rate calculating means 28 calculates a second attracting rate, and the second attracting number predicting means 29 uses the gaming population stored in the gaming population area distribution information storage means 31 to calculate the attracting number. Predict.

First, information used in the present system will be described. The regional game population distribution information for each population structure type may be a game population distribution in an administrative division, or, for example, a game population distribution in a predetermined area of every 50 meters in length and width. The regional game population distribution information may use information of a map information system (GIS).

The first gaming machine information is information for each type of gaming machine, and has, for example, the contents shown in a table as shown in FIG. Basic, model name, model number, manufacturer name,
In addition to information such as series name and model classification, jackpot probability,
The evaluation values obtained as numerical values, such as the probability of probable change, the probability of reduced working hours, and the number of prize balls, and the sensory aspects such as winning, winning, and playing, which are the attractiveness of a game console, also indicate the specific evaluation criteria. In this way, it is evaluated as a numerical value, and the degree of attractiveness of the gaming table is obtained. For example, as an evaluation criterion, the starting feeling is that the player keeps starting (highest level 5 points), starts immediately (good level 4 points), starts moderately (passing level 3 points), rarely starts (lower level 2). Points), almost no start (minimum level 1 point), create specific evaluation criteria in 5 steps, actually play at the gaming table, evaluate, give points to each step Digitize. For all items,
By determining a specific evaluation criterion, comparing it with another model, and quantifying the numerical value, the first game console attractiveness calculating means 21 obtains the first game console attractiveness calculating means 21 by the equation (1). Further, in the above example, the difference is for each point, but the point to be given may be changed depending on the evaluation item.

The game facility information is obtained by collecting information on a game facility located at a place where a new game facility is newly opened or a customer attraction area centering on a game facility for predicting sales and attracting customers. For example, FIG. 3 shows an example of gaming facility information. Amusement facility information is basic information such as store name, location, telephone number, capital, number of installed gaming consoles, etc. Peripheral population, location type (suburban type, station type), percentage of main transportation,
Location factors such as the percentage of complete parking lots and the percentage of complete bicycle parking lots for the installed gaming tables. Exchange rate, availability of time service, frequency,
The gambling factor consists of the frequency of the event, the fun of the event, the fulfillment of the point system, the frequency of replacing machines, the effects of in-store production, and the effects of nail adjustment. Corporate strength points (good / bad brand image, business stability), building points (luxury, newness, superiority of design, etc.), installed gaming table points (popular model installation ratio, model installation balance), sales activities points (Service, lighting, environment, premium content, etc.). For each item, set specific evaluation criteria, surveyed and evaluated the same standards for all stores in the area, and the information of the installed gaming machines and the number of installed games at each store, The store information is constructed from information obtained by investigating the customer-attached status of each model at each store by day and time. The method of evaluating the game facility information is an application of SWOT analysis. The SWOT analysis is based on an analysis of “own store” and an analysis of “environment surrounding own store”, and a method and method. It is. For each factor, specific evaluation criteria are determined and quantified, and finally the degree of attractiveness of the own store and other stores is quantified.

An analysis is made on strength, weakness, opportunity, and threat. Specifically, as described above, basically,
We will consider two categories: “own store” and “environment”. "Own store" refers to the relative strengths and weaknesses of your store relative to its competitors; "Environment" refers to, for example, business opportunities and threats related to the environment surrounding your store . Further, the strengths and weaknesses are to evaluate whether the stores are strong or weak compared to other stores, such as product quality, low production cost, wide distribution, and services to customers. Threats will be evaluated based on external factors that threaten the business continuity of the store. For example, the counterattack of competitors, the entry of new competitors, the occurrence of price competition, the magnitude of changes in consumer preferences, and the like. As an opportunity, factors that become business opportunities for the store are specifically listed and evaluated. For example, market size, market growth rate, technological change, etc. For these factors, evaluation points are determined for each evaluation item and quantified.

Specifically, what is required as a numerical value, such as the completeness of the parking lot, is fully equipped and, when parking is easy, the highest level is provided, but there is room for improvement. , Good level, pass level to be able to park for the time being, inferior level if not able to stop,
If you do not want to stop, you may assign a minimum level. Further, items that cannot be captured as numerical values, such as gambling elements, are quantified by setting specific evaluation criteria. For example, the exchange rate is extremely high (highest level 5 points), slightly higher (good level 4 points), normal (passing level 3 points), slightly lower (bad level 2 points), and extremely low (lowest level 1 point). ), But these are determined by comparison with other stores,
Actual figures will vary depending on the region and time period studied. For other items, for example, specific evaluation criteria in five levels are determined, and compared with other stores and quantified. Using the gaming facility information, the first gaming facility attractiveness calculating means 22 obtains the first gaming facility attractiveness by equation (2).

For example, as shown in the table of FIG. 5, the second game console information is based on the date and time, the weather, and the peculiarity of the survey date as basic data as information for each store. The number of players for each type of installed gaming table in a gaming facility in a commercial area obtained by examining the number of people for each configuration type. By investigating the actual number of people playing the game, the information is set as the second game table information. As a result, it becomes clear which of the installed gaming tables is preferred and easily selected. The degree of selection is determined by equation (6) as the second game console attractiveness. When investigating, by investigating based on population composition type, the second game console attractiveness,
It is the degree of attractiveness for the population type.

Next, FIG. 6, FIG. 7, FIG. 8, FIG. 9, FIG.
The processing procedure of the first gaming facility sales amount prediction system will be described in detail with reference to the flowchart shown in FIG.

First, the process will be described with reference to the schematic flowchart of FIG. In step 100, the distribution information of the game population in the area to be traded is input to the game population area distribution information storage means 31 via the information input means 51. The first game console information shown in FIG. 2 is investigated and collected for each model for all the game consoles installed in the gaming facilities in the commercial area in advance, and the information is input to the control device 10 in step 102 and stored in the storage unit 30. In the first game console information storage means 32. Further, as for the gaming facility information shown in FIG. 3, information that has been investigated in advance for all gaming facilities existing in the commercial area is input and stored in the gaming facility information storage unit 33.

In step 104, the first game console attractiveness is determined. In step 106, the first game facility attractiveness is obtained for all the game facilities existing in the commercial area. Further, using the first game facility attractiveness level, in step 108, the first customer attracting rate is obtained for each region constituting the commercial area. In step 110, the number of customers to be attracted is obtained using the first customer attracting rate. Further, in step 112,
Predict the sales amount from the number of customers. In step 114, the output means 60 outputs the sales amount.

Step 104 in the above general description
Therefore, step 112 will be described in detail according to another flowchart.

First, according to the flowchart of FIG.
A procedure for obtaining the first game console attractiveness in the game console attractiveness calculating means 21 will be described. In step 200, a game console number is initialized to obtain the first game console attractiveness for all the game consoles. In step 202, the first game console information storage means 32 stores the model k
Evaluation item d from the gaming table information of the gaming table of (1 ≦ k ≦ _nk )
Evaluation value a _kd (1 ≦ k ≦ _nk , 1 ≦ d) of (1 ≦ d ≦ _nd )
≦ n _d ). That is, the evaluation values evaluated for the evaluation items, such as the jackpot probability, the start feeling, and the hit feeling shown in FIG. 2, are obtained as the evaluation value a _kd .

Next, in step 204, the evaluation item
α is the weight of d in the game machine evaluation _d(1 ≦ d ≦ n_d)
And set. The weight in this evaluation depends on experience
Is set. For example, the jackpot probability is
As an evaluation item for selecting a platform,
Weight, etc., when making a selection
No. In this way, by weighting the evaluation,
The first game console attractiveness of the game console is E1k (1 ≦ k ≦ n_k) Expression
It is obtained by (23) (step 206).

[Number 23] _{E1k = Σ d (a kd ×} α d) / Σ d α d ... (23)

In step 208, the next model number is set. In step 210, it is checked whether or not the first game console attractiveness level has been obtained for all the models, and from step 202 to step 210
repeat.

Next, according to the flowchart of FIG.
Game facility attraction calculating means 22 of the first game
The detailed procedure for determining the degree of attractiveness is described. Steps
At 300, the first for all gaming establishments
The store number is initialized in order to obtain the game facility attractiveness.
In step 302, the first game console attractiveness previously determined
Get degrees for all models. By step 304,
From the gaming facility information storage means 33, the corresponding gaming facility j
Get game facility information. That is, the game facility information shown in FIG.
From the number of game consoles of model k installed at the gaming facility j
jk (1 ≦ j ≦ n _j, 1 ≦ k ≦ n_k), As a game facility
Evaluation value bjy of evaluation item y (1 ≦ j ≦ n_j , 1 ≦ y ≦
n_y) Respectively. Evaluation items as a gaming facility and
Include the location, gambling, and qualitative analysis elements.
, Surrounding population, parking lot complete rate, exchange rate, in-store production, building
Items such as luxury. FIG. 3 shows an example.
Yes, parking lot complete rate, and amusement facilities with evaluation item y
Weight βy (1 ≦ y ≦ n_y) And the first game
Weight in the evaluation of the installed gaming table obtained using the degree of stand attractiveness
βn_{y + 1}Get. Next, in step 306, the first
The game facility attractiveness G1j is calculated by equation (24).

G1j = (((Σk E1k × Djk) × βny _{+ 1} ) + Σy (bjy × βy)) / (Σyβy + βny _{+ 1} ) (24)

At step 308, the number of the next store is set. In step 310, it is determined whether or not the first game facility attractiveness has been determined for all the stores, and
From step 302, until the game facility attractiveness of
Step 308 is repeated to determine the first game facility attractiveness.

Next, according to the flowchart of FIG.
The detailed procedure for finding the customer acquisition rate will be described. The first attracting rate is calculated by the first attracting rate calculating means 23, and in step 400, the distance resistance coefficient fj is set. The distance resistance coefficient fj is individually set in consideration of the location conditions of the game facility. Since the first rate of attracting customers is obtained for each residential area constituting the business area, the area Ww is initialized (step 402). In step 404, the area Ww stored in the game population area distribution information storage means 31.
, The time distance TwJ to the own store J is set. In step 406, a time distance Twj from the area Ww to the gaming facility j existing in the business area is obtained. In step 408, the first gaming facility attractiveness G1j for all gaming facilities j is obtained. In step 410, the first rate of attracting customers R1w to the local store J in the area Ww is obtained by the equation (25).
Ask for J.

[Number 25] ^{R1wJ = (G1J / TwJ fj)} / (Σj (G1j / Twj fj)); (1 ≦ w ≦ n w, 1 ≦ j ≦ n j), ... (25)

At step 412, the next area is set. In step 414, it is determined whether or not the first rate of attracting customers R1wJ has been determined for all the places of residence Ww constituting the trade area, and the steps from step 404 to step 414 are repeated until the first rate of attracting customers R1wJ has been determined for all of the places of residence Ww. .

Next, according to the flowchart of FIG.
The procedure for estimating the number of customers attracted will be described. The first number of customers attracted is predicted by the first number of customers attracting predicting means 24, and in step 500, the first rate of attracting customers R by the own store J is calculated.
1wJ is obtained for the residences Ww that make up all trade areas. In step 502, the place of residence W constituting the trade area
The game population PHw living in each w is obtained from the game population area distribution information storage means 31. In step 504, the number of people who can attract customers in the game population PHw living in the residence Ww formula is obtained by multiplying the first customer attraction rate R1wJ, and the sum of all regions Ww is obtained. J
Forecasts the first number of customers, PHJ.

(26) PHj = Σw (R1wj × PHw) (26)

Next, the procedure for estimating the sales amount will be described with reference to the flowchart of FIG. The sales amount is predicted by the sales amount prediction means 25.
In, the number of customers PHJ attracted by the own store J is set. next,
At step 552, the average visit number N is set. This average number of visits depends on the period for which the sales amount is obtained. For example, when estimating the sales amount for one month,
This is the average number of times a game population visits a store in a month.
The number of visits is a number that is statistically known. Next, in step 554, the average sales amount DT per vehicle is set. The average sales per unit is a game price used by one game population when visiting the store once. This is also a statistically known amount. Next, step 556
, The sales amount U is obtained by the equation (27).

[Mathematical formula-see original document] U = PHj * N * DT, (27)

According to the above procedure, the sales amount can be predicted using the first game console information, game facility information, and local game population distribution information. The predicted value of the sales amount obtained in this way is displayed by using the display means 62, and the printing means 61
And may be stored in the external storage device 40.

Next, FIG. 12, FIG. 13, FIG. 14, FIG.
According to the flowchart shown in FIG.
The processing procedure of the gaming facility sales amount prediction system will be described in detail. First, the processing will be described with reference to the schematic flowchart of the processing in FIG. In step 600, distribution information of the game population in the area to be traded is input to the game population area distribution information storage means 31 via the information input means 51. The information of the second game console shown in FIG. 5 is checked and collected for each model for all the game consoles installed in the game facilities in the commercial area in advance, and the information is input to the control device 10 in step 602 and stored in the storage unit 30. Is stored in the second game console information storage means 34. Further, regarding the gaming facility information shown in FIG.
Information that has been investigated in advance for all gaming facilities existing in the commercial area is input and stored in the gaming facility information storage means 33.

In step 604, a second game console attractiveness is determined. In step 606, the second game facility attractiveness is calculated for all the game facilities existing in the commercial area. Further, in step 608, a second rate of attracting customers is determined for each region constituting the business area using the second game facility attractiveness. In step 610, the number of customers to be attracted is obtained by using the second rate of attracting customers. Further, in step 612,
Predict the sales amount from the number of customers. In step 614, the output unit 60 outputs the sales amount.

Step 604 in the above brief description
Therefore, step 612 will be described in detail according to another flowchart.

First, the procedure for obtaining the second game console attractiveness will be described with reference to the flowchart of FIG. In step 700, the second type is set for all game machine types.
Initialize the model number to be obtained in order to obtain the game console attractiveness of the game. Further, the second gaming table attractiveness is obtained from the number of players for each demographic composition type and is obtained for each demographic composition type. Therefore, in step 702, the demographic composition type is initialized. In the present embodiment, for example, gender and age shown in FIG. In step 704, the number of players Pijk at the gaming facility j for the population type i of the gaming table of model k is obtained from the second gaming table information storage means. In step 706, in order to obtain the number of game consoles of the model k in the commercial area, the number Djk of game consoles of the model k in the game facility j is obtained. In step 708, the second game console attractiveness E2ki for the model k and the population type i is obtained by the equation (28).

E2ki = (】 j Pijk) / (Σj Djk) (28)

At step 710, the next population type i is set. In step 712, it is determined whether or not the second gaming table attractiveness E2ki has been obtained for all the population type i, and the steps 704 to 712 are repeated until it is obtained for all the population type i.
Next, in step 714, the next model number is set. In step 716, it is determined whether or not the second game console attractiveness has been obtained for all models, and steps 702 to 716 are repeated until the second game console attractiveness has been obtained for all models. As a result, the second game console attractiveness can be obtained for all the game console models and the population type i.

Next, a procedure for obtaining the second game facility attractiveness calculated by the second game facility attractiveness calculating means 27 will be described with reference to the flowchart of FIG. Second
As for the game facility attractiveness, the attractiveness is calculated for each population composition type. First, in step 750, the store number is initialized. In step 752, the population composition type is initialized. In step 754, the second game facility attractiveness E2ki previously obtained is obtained. In step 756, the number of installed gaming machines Djk of each type of game facility information stored in the game facility information storage means 33 is obtained for each model. In step 758, the second game facility attractiveness calculating means 2
In step 7, the second game facility attractiveness G2ji is determined for each model and for each type of population. At this time, the second game console attractiveness E2k of the game console of the model k is constituted by the second game console attractiveness E2ki for the population type i, and E2k = kE2k.
i} (1 ≦ i ≦ n i), the game evaluation values of the evaluation items y facility j bjy (1 ≦ y ≦ n y), evaluation items evaluated weights [beta] y (1 ≦ y ≦ occupied in the y game facility _ny ), the weight of the _second game console attractiveness in the overall evaluation is βny _{+ 2} , and the number of game consoles of model k installed in the game facility j is Djk (1 ≦ j ≦
Assuming that n _j , 1 ≦ k ≦ _nk , the second game facility attractiveness G2ji is obtained by equation (29).

G2ji = (((Σk E2ki × Djk) × βny _{+ 2} ) + Σy (bjy × βy)) / (Σyβy + βny _{+ 2} ) (29)

Next, at step 760, the next population type i is set. Further, in step 762, it is determined whether or not the second game facility attractiveness has been obtained for all the population type i. From step 754, the step 762 is repeated to obtain the second game facility attractiveness for all the population type i. Ask for.

Next, in step 764, the next game facility j is set. In step 766, it is determined whether or not the second game facility attractiveness has been obtained for all the game facilities j. From step 752, step 766 is repeated to obtain the second game facility attractiveness for all the game facilities j.

Next, a procedure for obtaining the second customer attracting rate in the second customer attracting rate calculating means 28 will be described with reference to the flowchart of FIG. In step 800, different distance resistance coefficients fj are set depending on the location conditions of the game facility j. In step 802, the area Ww is initialized in order to obtain the second rate of attracting customers for all areas. In step 804, the time distance TwJ from the area Ww to the own store J is obtained. In step 806, the region Ww
, A time distance Twj to the game facility j is obtained. Step 80
At 8, the population type i is initialized. Step 8
At 10, the second game facility attractiveness G2ji of the game facility j with respect to the population type i and the second game facility attractiveness G2Ji of the own store J are obtained. Further, in step 812, the own store J for each population type i is calculated by the equation (30).
A second rate of attracting customers is calculated.

[Number 30] ^{R2wJi = (G2Ji / TwJ fj)} / (Σj (G2ji / Twj fj)), ... (30)

Next, in step 814, the next population type i is set. In step 816, it is determined whether or not the second rate of attracting customers has been determined for all the population type i. From step 810, step 816 is repeated to determine the second rate of attracting all the population type i.

Next, in step 818, the area Ww
Is set. Further, in step 820, it is determined whether or not the second rate of attracting customers has been obtained for all areas Ww, and steps 804 to 820 are repeated to determine the second rate of attracting customers for all areas Ww.

Next, in accordance with the flowchart of FIG.
The following describes a procedure for predicting the number of customers. First, in step 900, the second customer attracting rate R2wJi is obtained for each population type i by the own store J and for each area Ww. Step 90
In 2, from the game population area distribution information storage means 31,
The game population PHw for each population type i living in the region Ww
get i. In step 904, the number of customers attracted at the own store J is calculated by the equation (31).

[Expression 31] PHj = Σi (Σw (R2wji × PHwi)) (3)
1)

Next, the sales amount prediction means 25 predicts the sales amount by the equation (27) using the number of customers attracted PHH. Further, the predicted sales amount is output via the output means 60.

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

In the above embodiment, for the sake of simplicity, the day of the week, the time zone, the holidays, and the days outside the holidays are not described in detail in the sales forecast. However, since it is limited to adults, in general, the composition of the game population changes greatly on weekdays, during working hours, on holidays, and outside working hours. In order to make sales forecasts suitable for these changes, actually, sales forecasts are made by subdividing by holidays, weekdays, during working hours, after closing hours, school class days, non-school days, etc. Thus, more accurate sales forecasting can be performed. For this purpose, by setting the regional game population distribution information, the second game table information, and the like in accordance with the trend of the game population, more accurate sales prediction can be performed.

The evaluation items in the first game console information and the game facility information in the above embodiment are merely examples, and are not limited to these. The evaluation items may be increased or decreased as needed. Further, as the evaluation method, an evaluation method using the SWOT analysis method was used, but the evaluation method is not limited to this as long as it can be quantified, and another method may be used.

Furthermore, the gender classification and the age zone classification of the population composition type in the above embodiment are merely examples, and are not actually limited to the above examples. It may be further subdivided, collectively,
It may be unified. For example, student, youth, middle age, old age,
It may be a category such as a man, a woman, a man and a woman couple. Furthermore, the case of unification is the case where there is only one gender and age group, and there is no classification.

Further, since the division by time zone and day of the week is not limited to the above embodiment, it may be further subdivided or unified.

Further, in the above-described embodiment, the description has been made according to the day of the week and the time of the hour. Further, holidays, school holidays, summer vacations, winter vacations, etc. may be added as special days.

Further, as a model classification, information summarizing similar models may be further output. For example,
A pachislot machine and a pachinko machine may be divided. Further, regarding the model classification, similar models may be collectively handled as one model.

[Brief description of the drawings]

FIG. 1 is a connection block diagram of a first game facility sales amount prediction device showing an example of the present embodiment.

FIG. 2 is an explanatory diagram of first game console information.

FIG. 3 is an explanatory diagram of game facility information.

FIG. 4 is a connection block diagram of a second game facility sales amount prediction device showing an example of another invention.

FIG. 5 is an explanatory diagram of second game console information.

FIG. 6 is a flowchart showing an outline processing procedure of the first gaming facility sales amount prediction system.

FIG. 7 is a flowchart showing a processing procedure for obtaining a first game console attractiveness level.

FIG. 8 is a flowchart showing a processing procedure for obtaining a first game facility attractiveness level.

FIG. 9 is a flowchart showing a processing procedure for obtaining a first customer attracting rate.

FIG. 10 is a flowchart showing a processing procedure for estimating the first number of customers.

FIG. 11 is a flowchart showing a processing procedure for estimating a sales amount.

FIG. 12 is a flowchart showing an outline processing procedure of a second game facility sales amount prediction system.

FIG. 13 is a flowchart showing a processing procedure for obtaining a second game console attractiveness level.

FIG. 14 is a flowchart showing a processing procedure for obtaining a second game facility attractiveness level.

FIG. 15 is a flowchart showing a processing procedure for obtaining a second rate of attracting customers.

FIG. 16 is a flowchart showing a processing procedure for predicting a second number of customers.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 ... Control device 20 ... CPU 21 ... First game console attractiveness calculating means 22 ... First gaming facility attractiveness calculating means 23 ... First customer attracting rate calculating means 24 ... First customer attracting number predicting means 25 ... Sales Amount prediction means 26 ... second game console attractiveness calculating means 27 ... second gaming facility attractiveness calculating means 28 ... second customer attracting rate calculating means 29 ... second customer attracting number predicting means 30 ... memory means 31 ... game Population area distribution information storage means 32 first game console information storage means 33 gaming facility information storage means 34 second game console information storage means 40 external storage device 50 operation input device 51 information input device 52 Keyboard 53 Mouse 52 Scanner 55 Touch panel 56 Modem 60 Output unit 61 Printing unit 62 Display unit

Claims (23)

[Claims] 1. A distribution table of population of gaming areas in a commercial area, which is a customer attracting area including its own store, stored in a storage device in advance, and a model of an installed gaming table in a gaming facility including pachinko and pachislot shops existing in the commercial area. First game console information that is an evaluation value obtained for each of a plurality of evaluation items, and the number of game consoles installed in each of the gaming facilities, and
Using the gaming facility information including evaluation values for a plurality of evaluation items of the gaming facility, the first gaming console attractiveness calculating means calculates a first gaming console attractiveness for each model by the first gaming console attractiveness calculating means, The first gaming facility attractiveness calculating means calculates the first gaming facility attractiveness for each gaming facility using the attractiveness, and the first customer attracting rate calculating means using the first gaming facility attractiveness. Calculates the first rate of customer attraction of the game population in the commercial area to the own store by using the regional game population distribution information and the first rate of customer attraction,
Calculating the number of customers attracted to the own store by the first number of customers attracting means, calculating the estimated sales amount by the sales amount predicting means using the number of customers, and outputting the estimated sales amount by the output means; A first game facility sales amount prediction system characterized by the following. 2. The first game console attractiveness is calculated by the first game console attractiveness calculating means using the first game console information, and the first game console of a model k game console is provided. E1k (1 ≦ k ≦
_nk ), the evaluation value of the model k of the evaluation item d of the game _console is a _kd (1 ≦ k ≦
n _k , 1 ≦ d ≦ n _d ), and the weight of the evaluation item d in the evaluation of the game console is α _d (1 ≦ d
When ≦ n _d) to, [Equation 1] _{E1k = Σ d (a kd ×} α d) / Σ d first game facility sales according to claim 1, characterized in that the alpha _d ... (1) Forecasting system. Wherein the gaming facility _{j (1 ≦ j ≦ n j} ) first game facility attractiveness _{G1j (1 ≦ j ≦ n j} ) of is determined that there is attractive gaming facility larger An evaluation value, which is obtained by the first gaming facility attractiveness calculating means using the first gaming console attractiveness and the gaming facility information, and the first gaming console attractiveness of the gaming machine of the model k To E1k (1 ≦
k ≦ n _k ), and the evaluation value of the evaluation item y of the gaming facility j is bjy (1 ≦ j).
_{≦ n j, 1 ≦ y ≦} n y), wherein a weight occupying the evaluation of the gaming facility endpoints y [beta] y (1
≦ _y ≦ n y), the weight occupied in evaluation of the first game machine attractiveness β
n _{y + 1} , the number of game consoles of model k in the gaming facility j is D
Assuming that jk (1 ≦ j ≦ n _j , 1 ≦ k ≦ n _k ), G 1j = (((Σk E1k × Djk) × βny _{+ 1} ) + Σy (bjy × βy)) / (Σyβy + Βny _{+ 1} )... (2). The first game facility sales amount prediction system according to claim 2, wherein 4. A place of residence Ww (1 ≦ w ≦ n) constituting a trade area W
_w ), W = Σw Ww; (1 ≦ w ≦ n _w ),... (3), the game facility J (1 ≦ J ≦
first attracting rate R1wJ by n _j), in the first attracting rate calculating means, Equation 4] ^{R1wJ = (G1J / TwJ fj)} / (Σj (G1j / Twj fj)); (1 ≦ w ≦ n _w , 1 ≦ j ≦ n _j ),... (4) Σj R1wj = 1; (1 ≦ j ≦ n _j ), G 1j: First game facility attractiveness Twj of the game facility j Twj: Game from the place of residence Ww The first time according to claim 3, wherein the time distance fj to the facility j is obtained by a resistance coefficient to the distance.
Game facility sales forecast system. 5. A place of residence Ww constituting a trade area W of a game facility j (1 ≦ j ≦ n _j ) in the regional game population distribution information.
(1 ≦ w ≦ n _w ) is the game population living in PHw (1 ≦ w ≦
n _w ), and the first rate of attracting customers by the gaming facility j existing in the trade area is R 1 _w j
When (1 ≦ w ≦ n _w , 1 ≦ j ≦ n _j ), the number of visitors PHj (1 ≦ j ≦ n _j ) of the gaming facility j is calculated by The first game facility sales amount prediction system according to claim 4, wherein the first game facility sales amount prediction system is obtained by the following equation. 6. A distribution of distribution of population of gaming areas in a commercial area, which is a customer attracting area including its own store, stored in a storage device in advance, and a model of a game console installed in a gaming facility including pachinko and pachislot shops existing in the commercial area. Using the second gaming table information that is the number of players, the number of gaming tables installed in each of the gaming facilities, and gaming facility information including evaluation values for a plurality of evaluation items of the gaming facility. The second game console attractiveness calculating means calculates the second game console attractiveness for each model, and the second game facility attractiveness calculating means uses the second game console attractiveness. The second game facility attractiveness of each facility is calculated, and the second customer collection rate calculation means uses the second game facility attractiveness to calculate the second customer collection rate of the game population in the commercial area to the own store. Calculating the regional game population distribution information and the second By attracting customers,
Calculating the number of customers attracted to the own store by the second number of customers attracting prediction means, calculating the predicted sales amount by the sales amount predicting means using the number of customers attracted, and outputting the predicted sales amount by the output means; A second game facility sales amount prediction system, characterized in that: 7. The second game facility sales amount prediction system according to claim 6, wherein the regional game population distribution information and the second game console information comprise population structure type information. 8. The second game facility sales forecasting system according to claim 7, wherein said population type is classified by age group. 9. The method according to claim 7, wherein the population type is further classified by gender.
Game facility sales forecast system. 10. The second game console attractiveness is obtained by the second game console attractiveness calculating means using the second game console information, and the model k (1 ≦ k ≦ _nk ) The attractiveness of the second game console is E2k
_{(1 ≦ k ≦ n k)} , the second attractiveness of E2ki (1 ≦ _k ≦ n k model k for demographic type _{i (1 ≦ i ≦ n i} ),
When a 1 ≦ _i ≦ n i), a E2k = {E2ki} (1 ≦ i ≦ n i), Pijk (1 ≦ i ≦ n i, 1 ≦ j ≦ n j, 1 ≦ k ≦ n k)
Is the model k of the gaming facility j in the commercial area, which is the second gaming table information.
The number of players of demographic composition type i in the game consoles, and the number of game consoles of model k, which is the store information at the gaming facility j in the commercial area where Djk (1 ≦ j ≦ n _j , 1 ≦ k ≦ _nk ) 10. The second game facility according to claim 7, wherein: E2ki = (Σj Pijk) / (Σj Djk) (6) Sales forecasting system. 11. The second game facility j (1 ≦ j ≦ n _j )
Game facility attractiveness _{G2j (1 ≦ j ≦ n j} ) , the second gaming facility attractiveness G for demographic type _{i (1 ≦ i ≦ n i} )
It is constituted by the _{2ji (1 ≦ j ≦ n j} , 1 ≦ i ≦ n i), it is determined that there is G2 k = {G2ki} (1 ≦ i ≦ n i) a is attractive gaming facility larger The second gaming facility attractiveness is calculated by the second gaming facility attractiveness calculating means using the second gaming facility attractiveness and the gaming facility information. degrees E2k is constituted by the second game machine attractiveness E2ki against demographic type i, E2k = {E2ki} ( 1 ≦ i ≦ n i), the evaluation value of the evaluation item y of the gaming facility j bjy (1 ≦ y
≦ _ny ), the weight of the evaluation item y in the evaluation of the gaming facility is βy (1
≤ y ≤ _ny ), and the weight of the evaluation of the second game console attractiveness is β
n _{y + 2} , the number of game consoles of model k in the game facility j is Djk
When _{(1 ≦ j ≦ n j,} 1 ≦ k ≦ n k) to, [Equation 7] G2ji = (((Σk E2ki × Djk) × βn y + 2) + Σy (bjy × βy)) / (Σy βy + βn _{y + 2} ) (7) The second game facility sales forecasting system according to claim 10, wherein: 12. A place of residence WW (1 ≦ w ≦
In n _w), [number 8] W = Σw Ww (1 ≦ w ≦ n w); ... (8) the first of the to the residence Ww demographic category by the gaming facility J in _{i (1 ≦ i ≦ n i} ) 2 customer attraction rate R2wJi (1 ≦ w ≦
_{n w, 1 ≦ j ≦ n} j) , in the second attracting rate calculating means, Equation 9] ^{R2wJi = (G2Ji / TwJ fj)} / (Σj (G2ji / Twj fj)), ... (9) ΣjiR2wji = 1, G2ji: second game facility attractiveness for the size and population type i of game facility j, Twj: time distance from residence Ww to game facility j, fj: resistance coefficient to distance The second game facility sales amount prediction system according to claim 11, wherein: 13. A place of residence Ww constituting a trade area W of a game facility j (1 ≦ j ≦ n _j ) in the regional game population distribution information.
(1 ≦ w ≦ n _w )
(1 ≦ i ≦ n _i ) The game population is represented by PHwi (1 ≦ w ≦ n _w , 1
≦ i ≦ n _i ) and the second rate of attracting customers to the demographic type i by the gaming facility j existing in the business area is Rwji (1 ≦ w ≦ n _w , 1 ≦ j ≦
When n _j , 1 ≦ i ≦ n _i ), the number of attracted customers PHj (1 ≦ j ≦ n _j ) of the game facility j is calculated by the second attracted number predicting means as follows: (R2wji × PHwi))... (10)
Game facility sales forecast system. 14. The sales forecasting means according to claim 1, wherein said number of customers of said gaming facility j (1 ≦ j ≦ n _j ) is represented by PHj (
1 ≦ j ≦ n _j ), where N is the average number of visits and DT is the average sales per unit, and the sales U is determined by the following equation: U = PHj × N × DT, (11) Characteristic sales forecasting means. 15. The regional game population distribution information according to claim 1 or 6, wherein the regional game population distribution information further comprises time zone-specific regional game population distribution information. 16. The regional game population distribution information according to claim 1, 6 or 15, wherein the regional game population distribution information further comprises day-of-week regional game population distribution information. 17. The method of claim 1, claim 6, claim 15, or
17. The regional game population distribution information according to claim 16, wherein the regional game population distribution information further comprises holiday or non-holiday regional game population distribution information. 18. The number of players according to claim 6, wherein the number of players further comprises the number of players by time zone. 19. The number of players according to claim 6 or 18, wherein the number of players further comprises a number of players by day of the week. 20. Claim 18, Claim 19, or Claim 19
, Wherein the number of players further comprises holidays or the number of players outside holidays. 21. The regional game population distribution information, wherein the regional game population distribution information according to claim 1 or 6 is obtained from a map information system. 22. A first game facility sales amount prediction device used in the first game facility sales amount prediction system according to any one of claims 1 to 5, further comprising: First information input means for inputting first game console information and the gaming facility information; information storage means for storing the input information; first game console attractiveness calculating means; First computing means having first gaming facility attractiveness computing means, the first customer attracting rate computing means, the first customer attracting number predicting means, and the sales amount predicting means; A first game facility sales amount prediction device, comprising output means for outputting information and the predicted sales amount. 23. A second game facility sales amount prediction device used in the second game facility sales amount prediction system according to any one of claims 6 to 13, comprising: A second information input unit for inputting second gaming table information and the gaming facility information; an information storage unit for storing the input information; the second gaming table attractiveness calculating unit; A second game facility attractiveness calculating means, a second attracting rate calculating means, a second attracting number predicting means, and a second calculating means including the sales amount predicting means; A second game facility sales amount prediction device, comprising output means for outputting information and the predicted sales amount.