JP2005004788A - Optimum amusement facility proposal system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To solve a problem wherein diagnosis and proposal are liable not to comply with the actual situation since the current market power and the store's capacity are diagnosed by using the predicted number of expected visitors when the optimum amusement facilities are proposed. <P>SOLUTION: In this optimum amusement facility proposal system, game machine information including the number of installed game machines in amusement facilities including pachinko parlors and pachinko slot parlors present in a market of a visitor collecting area including one's own parlor actually set and player information including the number of players of the installed game machines are previously investigated; market current power of the amusement facilities in the market is evaluated by a current power index of an evaluation value obtained from game population information including the maximum estimated visitor collection number, the game machine information, and the player information; the current capacity of one's parlor is evaluated by a parlor capacity index; and thereby the optimum parlor is proposed by an optimum parlor proposal method. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a market analysis and a suggestion system for performing a current market capability of a game facility such as a pachinko hall in a trade area (region), a current store current capability diagnosis, and a proposal of an optimal game facility.

  Conventionally, a method using a Hough model used for mobilization prediction, sales prediction, etc. is well known as one means for determining whether or not a commercial facility in a trade area is appropriate. The Hough model is a theoretical calculation of the customer turnover rate between the own store and the competing store, and determines how easily the game population can come to the competing store at the own store. Based on the gap between the theoretical game population calculated from the ratio of the game population to the population, which is the theoretical number of visitors, and the number of visitors, which is a predicted value using the Hough model, determine whether the size of the store is appropriate. Was.

  In other words, the visitor population obtained using the Hough model is a predicted value of how much of the game population in the entire market actually comes, not the visitor population using the actual number of visitors, so the expected visitor schedule Depending on the number, there are cases where it is not possible to make a suggestion by diagnosing the current state of the market and the current state of the store and proposing an optimal gaming facility. Furthermore, since it is a predicted value, there is also a problem that a gaming machine selected by an actual customer cannot be accurately predicted.

  The optimum gaming facility proposal system according to the present invention includes a gaming machine information including the number of gaming machines installed in a pachinko store and a gaming facility including a pachislot store existing in a commercial area that is a customer-collecting area including a preset own store, and an installed gaming table. Investigating player information including the number of players in the game area, based on the game population information including the estimated maximum number of customers, the actually investigated game machine information, and the current power index that is the evaluation value obtained from the player information Evaluate the current market power of gaming facilities in Japan, and further evaluate the current power of the store based on the game table information and the store power index obtained from the player information. Player information, game table information, current power index, store It is characterized by proposing an optimal store using the optimal index using the power index.

  The invention of claim 2 is characterized in that the player information comprises the number of players in each gaming facility.

  According to the invention of claim 3, the gaming machine information further comprises the number of game machines installed by type at each gaming facility, and the player information further comprises the number of players by machine type of the gaming machine installed at each gaming facility. It is characterized by becoming.

  The invention of claim 4 is characterized in that the player information further comprises the number of players by age, and the game population information further comprises a game population by age.

  The invention of claim 5 is characterized in that the player information further includes the number of players by gender, and the game population information further includes a game population by gender.

  The invention of claim 6 is characterized in that the player information is further investigated by time zone, and the game population information further comprises a game population by time zone.

  The invention of claim 7 is characterized in that the player information is further investigated by day of the week, and the game population information further comprises a game population by day of the week.

  The invention according to claim 8 is characterized in that the player information is further surveyed according to holidays or outside holidays, and the game population information further includes holidays or off-days game population.

  The invention according to claim 9 is characterized in that the game population information is estimated by a game population coefficient known in advance for each component of the trade zone population existing in the trade zone.

  The invention of claim 10 is characterized in that the trade area population is obtained from a map information system.

The invention of claim 11 is an evaluation value that is evaluated as being appropriate as the current power index G is larger.
Hi (1 ≦ i ≦ n) is the maximum number of customers in the maximum number of customers component i that is the game population information,
When Pi (1 ≦ i ≦ n) is the number of players in the game population component i in all the game machine models of all the stores in the trade area as the player information,
(Equation 7)
G = Σ _i (P _i / (Σ _i Hi)); (1 ≦ i ≦ n) (7)
It is characterized by being given by.

  The invention of claim 12 is characterized in that the store power index T is an evaluation value that is evaluated as having a store power as it increases, and is given by the following.

Pijk (1 ≦ i ≦ n, 0 ≦ j ≦ m−1, 1 ≦ k ≦ l) is the number of players in the game population component i in the game table of the model k of the store j in the trade area as the player information,
Number of game machines of model k installed at store j existing in the trade area with Djk (0 ≦ j ≦ m−1, 1 ≦ k ≦ l). Therefore, (Σ _j Djk); (0 ≦ j ≦ m−1) is the sum of the number of models k installed for the stores in the trade area, and is therefore the number of models k installed in the trade area.

Pi0k (1 ≦ i ≦ n, 1 ≦ k ≦ l) is the number of players in the game population component i in the game machine of the model k of the own store,
If D0k (1 ≦ k ≦ l) is the number of game machines of model k in the store,
(Equation 8)
Sd0k = D0k / (Σ _j Djk); (0 ≦ j ≦ m−1) (8)
Is the installation ratio of the game machine of the model k of its own store in the trade area,
(Equation 9)
Sdk = (Σ _j Djk) / (Σ _jk Djk); (0 ≦ j ≦ m−1, 1 ≦ k ≦ l) (9)
Is (number of installed models k in the trade area) / (total number of game machines installed in the trade area), and is a ratio of the number of game machines installed in the trade area of model k.

(Equation 10)
_{Sp0k = Σ i ((Pi0k /} (Σ j Pijk)) × (Pi / (Σ i Pi))); (0 ≦ j ≦ m-1) ... (10)
That is, since (number of customers of model k in own store) / (number of customers of model k in the trade area), it is the actual game population ratio of the own store in model k.

At this time, the model-specific store power index Tk in the machine table of model k is
(Equation 11)
Tk = Sp0k / Sd0k (11)
The overall store power index T is obtained by multiplying and adding to the model-specific store power index Tk as a weighting factor by the game table as a weighting factor by the game machine.
(Equation 12)
T = Σ _k ((Sp0k / Sd0k) × Sdk); (1 ≦ k ≦ l) (12)
Given by.

  The invention of claim 13 is characterized in that the optimum store proposal method proposes improvement so that the model-specific store power index Tk or the store power index T becomes large.

  According to the fourteenth aspect of the present invention, there is provided an optimum gaming facility proposal device used in an optimum gaming facility proposal system, a gaming table information input means for inputting gaming table information, a player information input means for inputting player information, and a game population. Information input means having game population information input means for inputting information, game table information storage means for storing inputted information, player information storage means, and information storage means having game population information storage means; A computing means having a current power index computing means for computing a current power index, a store power index computing means for computing a store power index, and an optimal store proposal means for proposing an optimal store; input information; current power index And an information output means for outputting the store power index and the optimum store plan.

  With the above configuration, according to the optimal gaming facility proposal system according to the present invention, a gaming machine including the number of gaming machines installed in a gaming facility including a pachinko store and a pachislot store existing in a commercial area that is a customer-collecting area including the own store set in advance. Information and player information including the number of players on the installed game machine are investigated, and the game population information including the estimated maximum number of customers, the game machine information, and the current power index that is an evaluation value is obtained from the player information. As a result, the current market power of gaming facilities in the trade area was evaluated, and the current power of the store was evaluated based on the store power index. Therefore, based on the number of people who actually visited the game facility, I was able to evaluate the power. Furthermore, since the optimal store proposal was proposed by the optimal store proposal method based on the evaluation value obtained based on the number of customers who actually visited the store, it became possible to make realistic optimal proposals.

  According to the invention of claim 2, since the player information is composed of the number of players in each gaming facility, for example, by comparing the number of players in the own store with the number of players in the competitor store in the trade area, In detail, it will be possible to diagnose the current power of the store. In addition, for example, it is possible to extract a store or the like having a high rate of customers, which is a player ratio with respect to the installed game machine in the trade area.

  According to the third aspect of the present invention, the gaming machine information includes the number of game machines installed by type in each gaming facility, and the player information further includes the number of players by machine type of gaming machines installed in each gaming facility. Therefore, for example, it becomes clear which game machines are installed and how much in which stores. In addition, since it is possible to know how many players are playing on which game table, it becomes possible to obtain the rate of customers with different types of machines. Therefore, it is possible to diagnose which game table is most preferred among the installed game tables.

  According to the invention of claim 4, the player information is composed of the number of players by age, and the game population information is composed of the game population by age. Therefore, when predicting the game population, the game information is predicted by the game population. In addition, it will become clear which age population actually visits the store. This makes it possible, for example, to take measures against the age when the number of customers visiting the store is small. Further, by analyzing together with the number of players by model according to the invention of claim 3, it becomes possible to extract the types of gaming machines preferred by age. As a result, for example, it becomes possible to clarify problems such as a small number of game machines that are favored by those with fewer visitors.

  According to the invention of claim 5, since the game population generally has a gender gap, it becomes possible to reflect the gap and make a more accurate game population forecast, and the survey should be conducted separately by gender. Will be able to analyze the game population more accurately.

  According to the invention of claim 6, since it is known that the game population in the game facility varies greatly depending on the time zone, the player information is investigated by time zone, and the game population is obtained by the game population by time zone. It will be possible to obtain an accurate market status index and store power index, and to propose an optimal store.

  According to the invention of claim 7, it is known that the game population in the game facility varies greatly depending on the day of the week. Therefore, the player information is investigated for each day of the week, and the game population is obtained from the game population information for each day of the week. It becomes possible to obtain the most accurate market status index and store power index, and to propose an optimal store. For example, the day of the week where the market capacity and store power are small is clarified, and measures can be taken for that day.

  According to the invention of claim 8, it is known that the gaming population in a gaming facility varies greatly depending on holidays or outside holidays. Therefore, the player information is investigated separately on holidays or outside holidays. The game population can be obtained from the game population information separately provided, and it is possible to obtain an accurate market status index and store power index and propose an optimal store. For example, it will be clear how much the current market capacity and store power differ depending on whether it is a holiday or outside the holiday, so that measures can be taken.

  According to the invention of claim 9, since the game population can be estimated by the game population coefficient with respect to the components already known with respect to the components of the trade zone population existing in the trade zone, an accurate game population can be estimated. become able to. Furthermore, since the coefficient for each demographic component is used, it is possible to correspond by day of the week, by time of day, on holiday, or outside of holiday.

  According to the invention of claim 10, since the trade area population can be obtained from the map information system, a more accurate trade area population can be grasped. Furthermore, by linking with the data of the map information system, labor saving can be expected for population input in the trade area.

According to the invention of claim 11, the current power index G is an evaluation value that is evaluated as being appropriate as the value increases.
Hi (1 ≦ i ≦ n) is the maximum number of customers in the maximum number of customers component i that is the game population information,
When Pi (1.ltoreq.i.ltoreq.n) is the number of players in the game population component i in all the game machine types of all the stores in the trade area as the player information, it is given by the equation (1). . In other words, the equation (1) is G = (actual game population) / (theoretical game population), and is an expression that evaluates how close the actual game population is to the theoretical game population. . Here, the theoretical game population is obtained by multiplying the gender-specific trade area population by the game population coefficient, and the actual game population is obtained by research.

  Therefore, the market power is evaluated by the ratio of the game population actually visited to the game population in the trade area, making it easier to grasp the correct population ratio. In addition, since the current status of the market is accurately evaluated using a population survey by age group and the population of the trade area, the weighting is added to the demographic composition by age group, and the final evaluation is performed. Value. By quantifying in this way, it is possible to obtain a common evaluation value, and specifically to evaluate the current market power.

According to the invention of claim 12, Pijk (1.ltoreq.i.ltoreq.n, 0.ltoreq.j.ltoreq.m-1, 1.ltoreq.k.ltoreq.l) is a game in a game machine of the model k of the store j in the trade area which is the player information. Number of players in the population component i,
Djk (0 ≦ j ≦ m−1, 1 ≦ k ≦ l) is the number of game machines of model k installed in the store j existing in the trade area,
Pi0k (1 ≦ i ≦ n, 1 ≦ k ≦ l) is the number of players in the game population component i in the game machine of the model k of the own store,
D0k (1 ≦ k ≦ l) is the number of game machines of model k of the store,
Using equation (2), Sd0k is the installation ratio of the model k of the store in the trade area,
According to the equation (3), Sdk is the ratio of the game machine installed in the trade area of the model k,
Sp0k obtained by the equation (4) is the actual game population ratio (ratio with customers) of the store in model k.

In other words, the equation (4) is the actual game population ratio of the own store focusing on the game machine model k. First, pay attention to the demographic component by the first term, Pi0k / (Σ _j Pijk), and the actual game population ratio of the model k of the own store in the focused population component (number of customers of the model k of the own store) ) / (Number of customers of model k in the trade area). Next, the second term (Pi / (Σ _i Pi)) is a term for correcting the difference in population ratio due to the constituent elements of the population. By using the proportion of the population as a weighting factor and multiplying it by the ratio with customers, the difference in the number of people making up the population is correctly reflected in the proportion of actual game population by model.

  Using this, the model-specific store power index Tk in the game machine of model k is obtained by the equation (5). The store power index Tk by model is (Rate of model k at own store) / (Installation rate of model k at own store). By comparing the ratio, it is an index that evaluates how much the rate with customers is better than other stores. Based on this evaluation value, whether or not there is more customers than other stores in model k is evaluated. By obtaining this model-specific store power index Tk for all installed models, it is possible to grasp weak models compared to other stores. Theoretically, if the store power index by model Tk exceeds 1, the store power is evaluated as appropriate, but it is better to have more customers than the percentage of game machines installed. The bigger it is, the better it is.

  Next, the store power index T is an evaluation value that evaluates that the store power is greater as the model-specific store power index Tk is larger, and can be obtained by the equation (6). Specifically, the total store power index Tk is obtained by multiplying the model-specific store power index Tk by the installation ratio of the machine k of the model k in the trade area as a weighting factor of the model k, and obtaining the integrated sum of all models. In this way, it can be evaluated as a numerical value. Furthermore, since the evaluation value is the ratio of the actual game population to the ratio of game machines installed in the market, it is possible to objectively determine how many visitors are in the store in the actual market.

  According to the invention of claim 13, since the optimal store proposal method makes an improvement proposal so that the store power index T becomes large, it becomes possible to make an improvement proposal due to a factor of decreasing the store power. . For example, listing models with a small number of customers and models with a large number of customers can encourage improvements at their stores. In addition, for example, if there are members of the population with a low share in the components of the gaming population, it will be possible to take measures such as installing a gaming machine of the preferred model for that age and gender. .

  According to the invention of claim 14, the optimum gaming facility proposing device includes a gaming machine information input means for inputting gaming machine information, a player information input means for inputting player information, and gaming population information for inputting gaming population information. An information input means having an input means, a game table information storage means for storing the input information, a player information storage means, an information storage means having a game population information storage means, and a current power index are calculated. A calculation means having a current power index calculation means, a store power index calculation means for calculating a store power index, and an optimal store proposal means for proposing an optimal store; and input information, a current power index, a store power index, and Since it is configured by an output means for outputting the optimum store plan, it becomes possible to input game table information, player information, and game population information. , The player information storage means, the information storage means of the game population information storage means, it is possible to store. Furthermore, using this information, the current power index calculation means can calculate the current power index, the store power index calculation means can calculate the store power index, and the optimum store proposal means can propose the optimal store. It becomes like this. Further, the output means can output various information via, for example, a printing device, a display device, and an external storage device.

  An embodiment of the optimum gaming facility proposal system of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram showing a configuration of an optimum gaming facility proposal apparatus that realizes an optimum gaming facility proposal system according to an embodiment of the present invention. The control device 10 includes a CPU 20 comprising an optimum store proposing means 21, a current power index calculating means 22, a store power index calculating means 23, a game population information storage means 31, a game machine information storage means 32, and a player information storage means 33. It is comprised by the memory | storage means 30 which consists of. The game table information is input via the game table information input means 52 constituting the information input means 51 which is the operation input device 50, and the player information is input via the player information input means 53. As for the game table information, the installed game table survey input table shown in FIG. 2 is displayed via the display means 62, so the store name, the survey date, the installed model name, and the installed number are entered in the manner to fill in the table. . Each cell may be selected using a mouse or a touch panel. Next, using the installed game table number-of-games survey table shown in FIG. 3, the number of customers who are playing the game on the installed game table is investigated. Even in this case, the store name, survey date, weather, survey date is whether it is a special day such as a national holiday, and the survey time is entered first, and the number of players actually playing on the displayed game machines by age group Investigate and enter by gender. Further, game population information is input via the game population information input means 54. The game population information consists of the trade area population and the game population coefficient, which can be entered by gender, age, day of the week, and time zone. Each of these game population information may be input, or may be directly input from the map information system (GIS). In this case, the game population information input means 54 is a GIS data input means, and is configured to be able to set a trade area, read GIS data, and the like.

  The input information is stored in the game population information storage means 31, the game table information storage means 32, and the player information storage means 33 constituting the storage means 30, respectively. The input information is displayed by the display means 62 and can be confirmed and corrected.

  Furthermore, the input information can be stored and saved in the external storage device 40 as needed, and can be read as necessary. The external storage device 40 may be any storage medium such as MO, CD-R, CD-R / W, or memory stick.

  Regarding the player information and game table information survey input, it may be a portable terminal. In this case, the information is input to the game table information storage means 32 and the player information storage means 33 of the storage means 30 via the storage medium. Alternatively, it may be transmitted directly from the portable terminal to the storage means 30 using a communication function. In this case, the player information input means 53 and the game population information input means 54 are input means having a communication function. These devices are well known and will not be described in detail here.

  Next, the market current power index and the store power index in the present invention will be described, and information for making an optimal store proposal and the basic concept will be described. The optimal amusement facility proposal system of the present invention is a system that investigates and diagnoses the current market power of amusement facilities in a region, further diagnoses the store power of its own store in the market, and simultaneously proposes the optimal store.

  The area described here is the residential area of the customers who visit the store if it is a residential area. In the shopping district such as in front of the station, the area includes the transfer population to the station. Therefore, the game population is determined by determining the game population coefficient PFi according to the location conditions after setting the trade area in accordance with the location conditions of the store. Therefore, the game population in the trade area is obtained by multiplying the age-specific gender population living, traveling or staying in the trade area by the known game population coefficient PFi, and using this as the game population in the theoretical market. . The GIS data can be used to obtain more accurate data for the trade area population in the trade area, but it may be census data or population data obtained at city halls.

  The current market power index is calculated based on the ratio of the number of players actually visiting the store to the theoretical game population of the market. Theoretically, the market power index is 1 when the largest number of customers can be expected. Furthermore, if there are more customers than the theoretical value, it will be 1 or more, and if the number of visitors is small relative to the market size, it will be 1 or less. If it is 1 or less, it is judged that sufficient amusement facilities are not provided in the market, which indicates that it is possible to increase the number of customers by improving and expanding their own stores.

  The store power index evaluates store power by quantifying the degree of attracting customers to the store based on the ratio of the actual number of players to the ratio of the number of game machines installed in the store. Here, it is assumed that the total is calculated for each model of the game machine installed, and the evaluation value is obtained. However, if the sum is simply taken and averaged, the model with a large number of installed units and the model with a small number of installed units will have the same evaluation. Since the correct evaluation value cannot be obtained, normalization is performed according to the number of installed units and the sum is obtained to obtain the store power index.

  In addition, in order to obtain the above indices, it is necessary to conduct basic surveys of the number of game machines installed and the number of customers with game machines. When conducting a survey, for example, information such as the survey date, day of the week, time zone, gender, age, etc. is indispensable. According to Figs. 2 and 3, the game machine information and the number of customers will be investigated and collected. It will be.

  Next, the processing procedure of the optimum gaming facility proposal system will be described in detail according to the flowcharts shown in FIGS. 8, 9, 10, 11, 12, and 13. First, in step 800, a trade area is set. The trade area is often set with a radius of several kilometers. In step 802, the number of game facilities in the trade area is investigated to obtain data for creating the survey tables shown in FIGS. In step 804, the model of the installed game machine and the number of machines installed for each model are surveyed and inputted in accordance with FIG. In step 806, the number of customers at all stores is investigated by model according to FIG. This number of customers is surveyed multiple times on different days of the week, holidays, outside holidays, and time zones. In this embodiment, the age range shown in FIG. 3 is adopted, but it may be further subdivided or may be divided into large sections. Segments with a large number of players may be subdivided, and segments with a small number may be combined. Similarly, the age range may be set so that the game population is uniform. Furthermore, the time zone is the same as the time zone shown in Fig. 4 Market Status Diagnosis Table, but this may also be further subdivided or conversely. Furthermore, the time zone with a large game population is subdivided, and the time zone with a small game population may be summarized.

  In step 808, the current market power is diagnosed. In step 810, the store power is diagnosed. In step 812, an optimum store proposal is made.

A detailed procedure of the current market force diagnosis in step 808 will be described with reference to the flowchart shown in FIG. First, in Step 900 and Step 902, the survey date and time zone for obtaining the market current power index G are set. In step 904, the set game population is obtained. The game population is determined by multiplying the population by age and gender constituting the trade area population of the set survey date and time by the game population coefficient PFi to obtain Hi (1 ≦ i ≦ n) for each component (step 100, step 102). . Next, the game population (maximum number of customers) = Σ _i Hi; (1 ≦ i ≦ n) is determined to determine the game population for the set day of the week and time (step 104).

Next, in step 906, the actual game population Pi for each set demographic component for each survey date and time zone is obtained. This will be described with reference to the flowchart shown in FIG. Aggregate at all stores and all age ranges. In step 110, the store number is set, and in step 112, the population component factor number (gender-specific age zone number) is set. In step 114, the actual game population by model is totaled,
(Equation 13)
Pji = Σk Pijk (13)
Find the actual game population for each store. In step 124, the actual game population for each demographic component is obtained using the determined real game population for each demographic component for each store.
(Equation 14)
Pi = Σt Pti; (1 ≦ i ≦ n) (14)
Ask for.

In step 908,
By using the obtained maximum number of customers Hi (1 ≦ i ≦ n) and the actual game population Pi (1 ≦ i ≦ n), the market current power index is obtained by equation (1).

Next, in step 910, it is checked whether the market power index G has been obtained for all the survey dates and time periods surveyed, and by repeating step 912 from step 904, Find the market power index. In step 914, the current market power index G obtained here is output and displayed as a list in the table shown in FIG. 4 according to the diagnosis date category and the diagnosis time zone. If data cannot be collected, it is treated as a blank, and calculation and display can be performed only on a part of the data. Further, as a reference, as shown in FIG. 4, as shown in FIG. 4, the diagnosis date category for which the market power index G is obtained, the maximum number of customers in the time zone (H (time zone number, diagnosis date category) = Σ _i Hi (1 ≦ i ≦ n)) and the actual number of customers (P (time zone number, diagnosis date category) = Σ _i Pi (1 ≦ i ≦ n)) may be obtained and output and displayed.

Next, the store power index T in step 810 is obtained. This will be described in detail according to the flowchart shown in FIG. First, the survey date and time zone are set in steps 200 and 202. In step 204,
Pijk (1 ≦ i ≦ n, 0 ≦ j ≦ m−1, 1 ≦ k ≦ l) is the number of players in the game population component i in the game table of the model k of the store j in the trade area as the player information,
Djk (0 ≦ j ≦ m−1, 1 ≦ k ≦ l) is the number of game machines of model k installed in the store j existing in the trade area,
Pi0k (1 ≦ i ≦ n, 1 ≦ k ≦ l) is the number of players in the game population component i in the game machine of the model k of the own store,
Let D0k (1≤k≤l) be the number of game machines of model k of the store,
The installation ratio Sd0k for each model in the store's market is determined by equation (2).
Next, in step 206, an installation ratio Sdk for each model in the game machine trade area is obtained from equation (3).

  The actual game population ratio Sp0k of the own store in the model k for each survey date and time zone set in step 208 is obtained by equation (4).

  In step 209, the model-specific store power Tk is obtained from equation (5).

In step 210, the store power index for the set survey date and time zone is obtained by equation (6). In step 210, it is calculated for each survey date segment and time zone segment, and in step 212, as the list shown in FIG. 6 and FIG. 7, model-specific store power Tk, general store power index T, model-specific customers in own store The rate Rp0k, the model-specific installation share Sd0k, and the model-specific customer-added share Sp0k, which is an evaluation value from the entire trade area, are output. The customer-specific rate Rp0k in the own store is a value that can be obtained from equation (15).
(Equation 15)
_{Rp0k = (Σ i Pi0k) /} (D0k) ... (15)

Demographic factors breakdown _{sai0k = (Pi0k / Σ i Pi0k} ) × 100 is, for example, the proportion occupied in the case where the self-store the number of that game in the model k and 100, sbi0k = (Pi0k / ( Σ j Pijk)) X100) is the ratio of the corresponding store's age when the number of players of the same age playing in the model k in the trade area is 100. Such values may be output together. In this case, Sai0k makes it clear which age group prefers the model k. sbi0k reveals the tendency of the store's preference in the same age. Other than this, it may be set and output as necessary. In step 214, it is checked whether or not the store power index T has been obtained for all the survey dates and time zones, and the step change means 216 sets the next survey date and time zone and repeats steps 208 to 216 to repeat the store power index. T is calculated. In step 218, the general store power diagnosis table shown in FIG. 5 is output, which lists the total store power by time zone and day of the week. At the same time, the rate R0 with customers, which is the visitor rate of the store, is output by time zone and day of the week. R0 = (number with customers) / (number of game machines installed). That is, it is a store entrance rate in the own store, and can be obtained by the equation (16).
(Equation 16)
_{R0 = Σ k (Σ i (} Pi0k)) / Σ k D0k; (1 ≦ i ≦ n, 1 ≦ k ≦ l) ... (16)

  As a result, even if it is judged that the store has strength when viewed from the whole trade area, it is possible to grasp the time zone and day of the week when the rate with customers is poor.

  Next, in step 812, the optimum store is proposed and output as a list shown in FIG. This will be described with reference to the flowchart of FIG.

  In step 400, models with poor customer rate at the own store are listed in order of badness. At step 402, models with good customer rate at the own store are listed in order of goodness. This makes it possible to grasp popular and unpopular models.

  In Steps 404 and 406, models with a good customer rate in the market are listed in the order from bad to bad. Thereby, even in the models that are not installed in the own store, it is possible to grasp popular models. In addition, even if the store has a normal rate with customers, it is possible to grasp unpopular models from the market as a whole. Furthermore, in step 408, by restricting the number of installed units, a model with a good customer rate in the market, which is not installed in the store or has a small number of installed units, is listed in order of good customer rate. So that popular models can be displayed automatically. Further, in steps 410 and 412, the ages with low market share (by gender) are listed in ascending order and the high ages (by gender) are listed in descending order. As a result, the age at which the customer collection rate is bad becomes clear at the store, and measures can be taken. In step 414, listing the day of the week and the time zone with the lowest market share in the own store in ascending order makes it possible to consider holding an event or the like in the own store. Furthermore, in step 416, it is possible to obtain reference data for further increasing profits by listing the day of the week and the time zone with the highest market share in the own store in descending order. In addition to the above, it is possible to consider a measure for encouraging customers to visit the store by counting the number of visits to which store in many ages and the total market. Moreover, you may make it add a comment automatically as needed.

  In addition, since it is not restricted to this as long as the above-mentioned investigation input table and necessary information can be input, other forms may be used.

  Similarly, the list of diagnosis results may be in other formats as long as necessary information is obtained.

  Furthermore, the time zone and the day-by-day classification are not limited to this, and may be further subdivided or unified.

  Furthermore, in the above-described embodiment, the description is made for each day of the week and each hour. However, monthly information may be added as a condition for collecting information. Furthermore, holidays, school holidays, summer holidays, winter holidays, etc. may be added as special days.

  Furthermore, information on similar models may be further output as the model classification. For example, a pachislot machine and a pachinko machine may be provided.

  The above-described evaluation formula for evaluating the current market power is not limited to this, and any other evaluation formula may be used as long as it can evaluate the ability to attract customers in the market.

  Similarly, the above-described evaluation formula for obtaining the store power indexes Tk and T is not limited to this, and may be another evaluation formula as long as the store power can be compared with other stores.

  The present invention can be used to propose an optimal gaming facility. Amusement facilities can be optimized.

The connection block diagram of the optimal game facility proposal apparatus which shows an example of a present Example. Explanatory drawing of an installation game table investigation input table. Explanatory drawing of an installation game table game number investigation input table. Explanatory drawing of market current power diagnosis. Explanatory drawing of store power diagnosis. Explanatory drawing of the detail of store power diagnosis (the 1). Explanatory drawing of the detail of store power diagnosis (the 2). The flowchart which showed the process sequence of the outline | summary of the optimal game facility proposal system. The flowchart which showed the process sequence which calculates | requires the market present power index G. The flowchart which showed the process sequence which calculates | requires the maximum game population. The flowchart which showed the process sequence which calculates | requires a real game population. The flowchart which showed the process sequence which calculates | requires the store power index | exponent T. FIG. The flowchart which showed the process sequence of the optimal shop proposal means. Explanatory drawing of a store improvement proposal.

Explanation of symbols

10 ... Control device 20 ... CPU
21 ... Optimal store proposal means 22 ... Current power index calculation means 23 ... Store power index calculation means 30 ... Storage means 31 ... Game population information storage means 32 ... Game table information storage means
33 ... Player information storage means 40 ... External storage device 50 ... Operation input device 51 ... Information input means 52 ... Game table information input means 53 ... Player information input means 54 ... Game population information input means 60 ... Output means 61 ... Printing Means 62 ... Display means

Claims (14)

The game table information including the number of game machines installed in the pachinko store and the game facility including the pachislot store existing in the trade area that is the customer collection area including the store in advance, and the player information including the number of players in the game machine installed Investigate
Evaluating the current market power of gaming facilities in the trade area based on the current population power information including the estimated maximum number of customers, the game table information, and the current power index obtained from the player information,
Evaluate the current power of the store based on the store power index,
The optimal amusement facility proposal system that proposes the optimal store using the optimal store proposal method.   2. The optimal gaming facility proposal system according to claim 1, wherein the player information includes the number of players in each of the gaming facilities. The gaming machine information further comprises the number of gaming machines installed by type in each of the gaming facilities,
The optimal gaming facility proposal system according to claim 1 or 2, wherein the player information further includes the number of players according to the type of the gaming table installed in each of the gaming facilities. The player information further comprises the number of players by age,
The optimal gaming facility proposal system according to claim 2 or 3, wherein the gaming population information further includes a gaming population according to age.   The optimal game according to any one of claims 2 to 4, wherein the player information further includes a number of players by gender, and the game population information further includes a game population by gender. Facility proposal system.   The optimal game facility according to any one of claims 2 to 5, wherein the player information is further investigated by time zone, and the game population information further comprises a game population by time zone. Proposal system.   The optimal gaming facility proposal system according to any one of claims 2 to 6, wherein the player information is further investigated for each day of the week, and the game population information further includes a game population for each day of the week. .   8. The player information according to any one of claims 2 to 7, wherein the player information is further investigated according to holidays or outside holidays, and the game population information further includes holidays or non-holiday game population. The optimal amusement facility proposal system described.   9. The game population information according to claim 1, wherein the game population information is estimated by a game population coefficient known in advance for each component of a trade zone population existing in a trade zone. The optimal amusement facility proposal system described in 1.   The optimal game facility proposal system according to any one of claims 1 to 9, wherein the trade area population is obtained from a map information system. The current power index is an evaluation value that is evaluated as being appropriate as it increases,
Hi (1 ≦ i ≦ n) is the maximum number of customers in the maximum number of customers component i that is the game population information,
When Pi (1 ≦ i ≦ n) is the number of players in the game population component i in all the game machine models of all the stores in the trade area as the player information,
(Equation 1)
G = Σ _i (P _i / (Σ _i Hi)); (1 ≦ i ≦ n) (1)
The optimal amusement facility proposal system according to any one of claims 1 to 10, characterized by being given by: The store power index is an evaluation value that is evaluated as having a larger store power, and is composed of a model-specific store power index Tk and a general store power index T.
Pijk (1 ≦ i ≦ n, 0 ≦ j ≦ m−1, 1 ≦ k ≦ l) is the number of players in the game population component i in the game table of the model k of the store j in the trade area as the player information,
Djk (0 ≦ j ≦ m−1, 1 ≦ k ≦ l) is the number of game machines of model k installed in the store j existing in the trade area,
Pi0k (1 ≦ i ≦ n, 1 ≦ k ≦ l) is the number of players in the game population component i in the game machine of the model k of the own store,
D0k (1 ≦ k ≦ l) is the number of game machines of model k of the store,
(Equation 2)
Sd0k = D0k / (Σ _j Djk); (0 ≦ j ≦ m−1) (2)
The installation ratio of the store's model k in the trade area,
(Equation 3)
Sdk = (Σ _j Djk) / (Σ _jk Djk); (0 ≦ j ≦ m−1, 1 ≦ k ≦ l) (3)
Of the game machines installed in the trade area of model k,
(Equation 4)
_{Sp0k = Σ i ((Pi0k /} (Σ j Pijk)) × (Pi / (Σ i Pi))); (0 ≦ j ≦ m-1) ... (4)
Is the percentage of the actual game population of the store for model k,
The above-mentioned store-specific store power index Tk for a game machine of model k is
(Equation 5)
Tk = Sp0k / Sd0k (5)
The total store power index T is obtained by multiplying and adding the model-specific store power index Tk as a weighting factor by the game table as a weighting factor by the game table.
(Equation 6)
T = Σ _k ((Sp0k / Sd0k) × Sdk); (1 ≦ k ≦ l) (6)
The optimal amusement facility proposal system according to any one of claims 1 to 11, characterized by being given by:   The optimal game facility proposal system according to claim 12, wherein the optimal store proposal method proposes improvement so that the model-specific store power index Tk or the total store power index T is increased. The optimal gaming facility proposal device used in the optimal gaming facility proposal system according to any one of claims 1 to 13,
Information input means comprising: game table information input means for inputting the game table information; player information input means for inputting the player information; and game population information input means for inputting the game population information;
Information storage means having game machine information storage means for storing inputted information, player information storage means, and game population information storage means;
A calculation means comprising: a current power index calculating means for calculating the current power index; a store power index calculating means for calculating the store power index; and an optimal store proposing means for proposing the optimal store;
Information output means for outputting the input information, the current power index, the store power index, and the optimum store plan;
An optimal gaming facility proposing device characterized by comprising:

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