JP2018032179A - Parking lot guide device, parking lot guidance method and parking lot guide program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To propose services reducing opportunity losses with respect to users of parking lots with due considerations to profitability of large-sized shopping facilities.SOLUTION: A parking lot guide device according to the present invention comprises: a shop profit management unit that predicts a profit of a shop; a service creation unit that creates candidates of services to be provided at the shop in accordance with a waiting time of a vehicle entering a parking lot annexed to the shop, and a predicted profit; a waiting time prediction unit that predicts a waiting time of the vehicle; and a service proposition unit that acquires the candidate of the service corresponding to the predicted waiting time of the created candidates of the services, and displays the acquired candidate of the service on a terminal device, which an occupant of the vehicle operates, together with the predicted waiting time.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a parking lot guidance device, a parking lot guidance method, and a parking lot guidance program.

  In recent years, many large shopping facilities have opened in large cities and their suburbs. Large shopping facilities not only have many stores on their premises, but also have a vast parking lot for visitors. As a matter of course, such a parking lot is provided for the purpose of attracting customers to visit, and is often managed by a large shopping center operator.

  On holidays, etc., when there are many customers (vehicles) in the vehicle, the parking space is always full, and many vehicles are parked on the roads in large shopping facilities or on public roads in contact with large shopping facilities. A queue of “wait” will be created. When a customer who has finished shopping returns to the parking lot, drives the vehicle and leaves the parking lot, the vehicle at the top of the queue finally parks in the vacant parking space. In this way, customers in the vehicle need to be prepared to continue to wait while sitting in the driver's seat, but the customers feel more stressed if they wait in an unclear situation about how long the waiting time will be.

  The parking waiting time guidance system of Patent Document 1 detects a stagnation state of a vehicle in a parking lot and a stagnation state of a vehicle waiting for entry into the parking lot with a video camera. Then, the system predicts the time until the vehicle arriving at the tail of the queue enters based on the time-series change of the detected image, and displays the prediction result on the in-vehicle device or the road guidance display board. .

  In the information processing system of Patent Document 2, a plurality of base stations that transmit radio waves are installed at equal intervals along a road lined up by vehicles waiting to enter a parking lot of a facility such as a department store. The system predicts the time until a vehicle waiting to enter in the vicinity of the base station enters based on the past performance, and transmits the prediction result from the base station to the vehicle. The system accepts a vehicle occupant waiting for entry to apply for the purchase of goods, etc. to the facility, and provides a discount for parking fees for the purpose of sales promotion to the occupant who provided personal information. I do.

Japanese Patent No. 3295024 JP 2003-281684 A

  However, the parking waiting time guidance system of Patent Document 1 is intended to “provide real-time waiting times of a plurality of parking lots to a driver of a vehicle traveling on the road” (paragraph 0001 of Patent Document 1). . The driver checks the displayed waiting time, and determines whether to wait at the target store along the line for the waiting time, or to give up to go to the store on that day. However, since the operator of the system does not have a direct stake in the store, it cannot give special consideration to a driver who plans to shop at the store.

In the information processing system of Patent Document 2, consideration is given to store visitors. However, this system lacks the viewpoint of providing services in line with securing profits of stores, taking a step further from general sales promotion. For example, there is no consideration from the viewpoint of how much the application for the purchase of goods, etc., discounts on parking fees, etc. affect profits or on the contrary. Therefore, in order to provide a truly strategic service from the viewpoint of profits to customers who have been waiting in the vehicle to use a large shopping facility, a separate measure is required.
Accordingly, an object of the present invention is to propose to a parking lot user a service that reduces opportunity loss while taking into account the profitability of a large shopping facility.

The parking lot guidance apparatus of the present invention is a store revenue management unit that predicts profits of a store, a waiting time of a vehicle that enters a parking lot attached to the store, and a service candidate provided in the store according to the predicted profits A service generation unit that generates a waiting time of the vehicle, a waiting time prediction unit that predicts the waiting time of the vehicle, and a service candidate corresponding to the predicted waiting time is acquired from the generated service candidates. And a service proposing unit that is displayed on a terminal device operated by a vehicle occupant together with the predicted waiting time.
Other means will be described in the embodiment for carrying out the invention.

  ADVANTAGE OF THE INVENTION According to this invention, the service which reduces an opportunity loss can be proposed with respect to the user of a parking lot, considering the profitability of a large shopping facility.

It is a figure explaining the environment where the structure of a parking lot guidance apparatus and a parking lot guidance apparatus are set | placed. It is a figure explaining the idea of ensuring profits. It is a figure explaining the method of determining a discount rate, ensuring a profit. It is a figure which shows an example of a service database. It is a figure which shows an example of a service utilization performance database. It is a figure which shows an example of a contribution database. It is a flowchart of a processing procedure. (A) And (b) is a figure which shows an example of a service proposal screen.

  Hereinafter, a mode for carrying out the present invention (referred to as “the present embodiment”) will be described in detail with reference to the drawings.

(Configuration and environment of parking lot guidance device)
A configuration of the parking lot guide device 1 and an environment where the parking lot guide device 1 is placed will be described with reference to FIG. The large shopping facility 2 has stores 3 a, 3 b, 3 c and 3 d and a parking lot 4. That is, the parking lot 4 is attached to the store 3a and the like. The parking lot 4 has an entrance 5a, an exit 5b, and many parking spaces 6a, 6b,. When the parking space is full as shown in FIG. 1, the vehicle 7 that has visited the large shopping facility 2 forms a queue on the road 8 that leads from the entrance 5 a to the parking lot 4. Now, four vehicles 7a, 7b, 7c and 7d have already formed a queue. In this state, when the number of vehicles that visit the large shopping facility 2 further increases, vehicles 7e, 7f,...

  Each of the vehicles 7a, 7b,... The terminal device 11 may be an in-vehicle device such as a car navigation device or a car stereo, or may be a mobile terminal device such as a so-called smartphone carried by an occupant of the vehicles 7a, 7b,. The large shopping facility 2 further includes a camera 9 and a base station 10. Among them, the camera 9 constantly monitors the road 8 and detects the positions of the vehicles 7a, 7b,. The base station 10 is connected to a terminal device 11 mounted on each of the vehicles 7a, 7b,. Hereinafter, the vehicles 7a, 7b,... Are collectively referred to as a vehicle 7.

  The large shopping facility 2 has a facility server 12. The facility server 12 is connected to the camera 9 and the base station 10 by wireless or wired technology. Each of the stores 3a, 3b, 3c and 3d has a store server (not shown), and the store server is connected to the facility server 12 by wireless or wired communication technology. The facility server 12 is usually installed in a management building (not shown) of the large shopping facility 2.

  The parking lot guidance apparatus 1 is a general computer. The parking lot guidance apparatus 1 includes a central control device 21, an input device 22, an output device 23, a main storage device 24, an auxiliary storage device 25, and a communication device 26. These are connected by a bus. The auxiliary storage device 25 stores a service database 41, a service usage record database 42, and a contribution database 43 (details will be described later). The waiting time prediction unit 31, the store revenue management unit 32, the service generation unit 33, and the service proposal unit 34 in the main storage device 24 are programs. In the following description, when the operation subject is described as “XX section”, it means that the central control device 21 reads the XX section from the auxiliary storage device 25 and loads it into the main storage device 24 and then loads the XX section. It means to realize the function (detailed later).

  The communication device 26 of the parking lot guidance device 1 is connected to the facility server 12 via the network 13. The parking lot guidance device 1 may be installed in an information processing center (not shown) or the like away from the large shopping facility 2 or may be installed in the site of the large shopping facility 2. In the latter case, the communication device 26 of the parking lot guidance device 1 may be connected to the facility server 12 without going through the network 13, and further, without going through the facility server 12, the camera 9, the base station 10, and It may be connected to a store server.

  Now, the vehicle 7 has arrived at the large shopping facility 2 while the parking lot 4 is full. The camera 9 detects that the vehicle 7 has stopped at the position of the vehicle 7d on the roadway 8 through the entrance 5a. In this situation, the occupant of the vehicle 7 becomes anxious about how long it will take to park the vehicle 7 in the parking space and be able to shop at the store 3a or the like. The occupant may return to the outside of the large-scale shopping facility 2 by turning back the roadway 8 without any waiting time. Then, an opportunity loss (loss of profit that would have been obtained) occurs for the large-scale shopping facility 2, and a passenger is wasted time. If the occupant turns back without being able to endure even though the car can be parked after waiting for a short period of time, there are significant disadvantages for both the occupant and the large shopping facility 2.

  The parking lot guidance apparatus 1 according to the present embodiment displays a predicted value of the waiting time on the terminal device 11 of the vehicle 7. Furthermore, the parking lot guidance apparatus 1 displays a candidate for a service provided by the store 3a or the like on the terminal device 11. The service here is typically an electronic discount coupon (electronic coupon). The ability to shop at discounted prices gives the occupants the motivation to endure some waiting time. However, if the service content becomes excessive, even if the sales of the store 3a and the like increase, the important profit may decrease. Therefore, the parking lot guidance device 1 proposes service candidates so that an increase in profit is guaranteed.

(Terms related to services)
First, the parking lot guidance device 1 “suggests” service candidates to the passengers via the terminal device 11. The occupant then “selects” the proposed service candidates that match his preference. Thereafter, the occupant “uses” the service he / she selects at the store. In the present embodiment, use of a service means purchasing a product or the like at a discount price. The crew may not use the selected service. To “use” a service is to “provide” the service from the standpoint of the store.

(Securing profits)
The concept of securing profit will be described with reference to FIG. The facility server 12 stores, for example, the following POS (Point of Sales) information for each store.
・ When and what products were sold at what price and in what quantity as revenue a.
- as expenditure b _1, when and which product, at any price, or bought in any quantity.
- as expenditure b _2, when and what services, at any price, or bought in any quantity.
To simplify the explanation, it is assumed that a certain store purchases and sells one type of product. Assuming fixed price sales, revenue a is directly proportional to sales volume, and spending b ₁ is also directly proportional to sales volume (assuming the inventory volume remains constant). Such expenditure b ₁ is called “variable cost”.

Usually, the store multiplies the purchase unit price by “assumed profit rate + 1” to determine the sales unit price of the product. Therefore, the profit resulting from subtracting the expenditure b ₁ from the income a is also directly proportional to the sales quantity. However, for example, the salary of the store clerk, store maintenance costs (utility costs, property costs), etc. are continuously the same amount regardless of the sales volume. Such expenditure b ₂ is referred to as a "fixed costs".

Then, the profit as a result of subtracting the sum of the expenditure b ₁ and the expenditure b ₂ from the income a becomes a negative number (red) while the sales quantity is small. In this way, the sales volume that becomes the red / black break-off point is generally called the “break-even point”. FIG. 2 illustrates the above. The parking lot guidance apparatus 1 can draw FIG. 2 based on the POS information. The horizontal axis of the coordinate plane in FIG. 2 is sales volume, and the vertical axis is income or expenditure. A straight line 51 indicates sales (income a), a straight line 52 indicates variable costs (expenditure b ₁ ), and a straight line 53 indicates fixed costs (expenditure b ₂ ). Point 54 is a breakeven point. In FIG. 2, the area of the area to the right of the breakeven point 54, above the straight line 52, and below the straight line 51 indicates the profit of the store. The profit when fixed costs are taken into account is hereinafter referred to as “net profit”.

  Naturally, the net profit increases as the sales volume increases. However, the increase in net profit is theoretical. Actually, there is an opportunity loss as described above, and the sales volume does not grow as expected in stores. Therefore, the basic idea of the present embodiment is that the store secures a part of the theoretical net profit and returns the rest to the customer (occupant of the vehicle 7).

For example, it is assumed that the sales quantity q ₁ corresponding to the breakeven point 54 is currently secured as a record. When the store provides a service of “2% discount of the regular price” to the occupant, the section of the straight line 51 whose horizontal axis is “2% discount” moves downward as a straight line 55. Naturally, the net profit is reduced compared to the case where the service is not provided. Furthermore, when the sales quantity q ₂ is achieved as an actual result, and the store then provides a service of “5% discount on the regular price” to the occupant, the horizontal axis of the straight line 51 is the section where the “5% discount on the regular price” Moves down like a straight line 56. Of course, net profit will be reduced compared to the initial “2% discount on the list price”. The discount rate determination reference line in FIG. 2 (and FIG. 3) will be described later.

(Determination of discount rate)
A method for determining the discount rate while securing profit will be described with reference to FIG. Assume that the sales volume of the store reaches the sales volume corresponding to the breakeven point 54. Future sales of products etc. are guaranteed to lead to an increase in net profit. And the predicted sales volume Q in the next one unit time in the case of selling the product or the like in the price, and predicted sales volume Q _r in the next one unit time in the case of sale by r% discount on the list price. Parking guide device 1, it is possible to analyze the POS information, seek such a Q and Q _r. Usually, Q <Q _r and ΔQ _r / Δr> 0 hold. It should be noted that, in the sense that the r is _{Q r} is determined if Kimare, can also be expressed as _Q r (r) and _{Q r} in the function model.

The profit per unit of product when the predicted sales quantity Q is realized in the next one unit time is B, and the profit per unit of product when the predicted sales quantity Q _r is realized in the next one unit time _Let it be _Br . Parking assistance apparatus 1 may analyze the POS information, obtains such a B and B _r. Usually, B> B _r and ΔB _r / Δr <0 hold. In the sense that r is _{B r} it is determined if Kimare, may represent _{B r} in the function type as _B r (r).

The parking lot guidance apparatus 1 calculates the maximum r that satisfies “Q _r × B _r −Q × B> 0”. This corresponds to obtaining the maximum r in FIG. 3 such that the area of the broken line “discount triangle” is larger than the area of the solid line “list triangle”.

The example shown in FIG. 3 is merely an example, and the parking lot guidance apparatus 1 can obtain r by other methods. In general, the parking lot guidance device 1 provides a maximum discount such that a profit when a product is sold at a discounted current price is larger than a profit when the product is sold while maintaining the current price. The rate is obtained by applying a statistical method to the past performance (POS information).
Note that r can be obtained even if the sales volume corresponding to the breakeven point 54 is not realized at the present time. The value obtained by subtracting the area of the regular triangle from the area of the discount triangle of FIG. 3 and further subtracting the cumulative loss (area of the area surrounded by the vertical axis, straight line 51, and straight line 52) in FIG. The parking lot guidance apparatus 1 can obtain such r.

(Service database)
The service database 41 will be described with reference to FIG. In the service database 41, in association with the service ID stored in the service ID column 101, the gender column 102 is the gender, the age column 103 is the age, the residence area column 104 is the residence area, and the waiting time column 105. , The provision store name in the provision store column 106, the provision product in the provision product column 107, the discount rate in the discount rate column 108, the discount rate in the time zone column 109, and the time zone in the day of week column 110 stores the day of the week.

The service ID in the service ID column 101 is an identifier that uniquely identifies the service. In the present embodiment, the service means that, in principle, a specific product or the like is sold at a discount price in a specific store. Exceptionally, for example, distribution of free prizes by lottery is not a “sale”, but the act of giving some economic benefit is also included in the service.
The gender in the gender column 102 is the gender of the target customer segment. The target customer segment is a customer segment that the store expects to use the service.
The age in the age column 103 is the age of the target customer group. “40s” means “40 years old or older and less than 50 years old”.

The residence area in the residence area column 104 is an area where the target customer group resides.
The waiting time in the waiting time column 105 is a waiting time (predicted value) until the vehicle 7 is parked in the parking space from the time when the vehicle 7 is arranged at the tail of the line of the roadway 8. Note that “0 to 5 minutes” indicates more than 0 minutes and 5 minutes or less. Others are the same.
The provided store name in the provided store name column 106 is the name of the store providing the service.
The provided product in the provided product column 107 is the name or type of the product etc. for which the service is provided.

The discount rate in the discount rate column 108 is a discount rate (%) with respect to the fixed price of the product or the like. The discount rate of this embodiment is a vector having four components. Each component corresponds to a plurality of different expected profit margins. A main profit rate flag “#” is attached to one of the four components. This will be described later.
The time zone in the time zone column 109 is a time zone in which the service is provided.
The day of the week column 110 is the day of the week on which the service is provided.

When attention is paid to the records in the first to sixth lines of the service database 41, for example, the following can be understood.
-Six services corresponding to these six records are all provided when A cosmetic store sells cosmetics between 10:00 and 14:00 on weekdays.
・ The target customers of these six services are all women in their 40s who live in A city. For example, a new town for families is built in A city, and A cosmetics store wants to increase sales to housewives who live there.
-A cosmetic store wants to apply different discount rates to customers who have a waiting time of 0 to 30 minutes (occupants of the vehicle 7) according to the length of the waiting time and the profit rate.
・ The discount rate increases as the waiting time increases and increases as the profit rate increases.

(Service usage record database)
The service usage record database 42 will be described with reference to FIG. In the service usage record database 42, in association with the occupant ID stored in the occupant ID field 121, the parking waiting position field 122 has a parking waiting position, the waiting time field 123 has a waiting time, and the actual waiting time field 124. Is the actual waiting time, the parking time column 125 is the parking time, the selection service ID column 126 is the selection service ID, the usage service ID column 127 is the usage service ID, and the usage store name column 128 is the usage store name. However, the usage time column 129 stores the usage time, and the usage amount column 130 stores the usage amount.

The occupant ID in the occupant ID column 121 is an identifier that uniquely identifies a person who has selected the service proposed by the parking lot guidance device 1 among the occupants of the vehicle 7. The occupant ID may be a license plate of the vehicle 7 captured by the camera 9, or may be a number assigned by the parking lot guide device 1.
The parking waiting position in the parking waiting position column 122 is information indicating the last position when a queue is formed on the roadway 8. For example, in FIG. 1, when the last position of the queue is the position of the vehicle 7a, the parking waiting position in FIG. 4 is “IN1”. When the last position of the queue is the position of the vehicle 7b, the parking waiting position in FIG. 4 is “IN2” (the same applies hereinafter).

The waiting time in the waiting time column 123 is the same as the waiting time (predicted value) in FIG.
The actual waiting time in the actual waiting time column 124 is a waiting time (actual value) actually required from when the vehicle 7 is arranged at the end of the line of the road 8 until the vehicle 7 is parked in the parking space. is there.
The parking time in the parking time column 125 is a time until the vehicle 7 departs toward the exit 5b after the vehicle 7 arrives at the parking space. During the parking time, the occupant is shopping at the large shopping facility 2.

The selection service ID in the selection service ID column 126 is the service ID of the service selected by the occupant. The parking lot guidance apparatus 1 proposes one or more service candidates to the occupant. The occupant selects one or more services from the candidates (details will be described later).
The use service ID in the use service ID column 127 is a service ID of a service that the occupant actually uses in the store. The selected service is not always used.
The used store name in the used store name column 128 is the name of the store where the crew actually used the service.
The use time in the use time column 129 is the year, month, day, hour, minute and second when the occupant actually uses the service at the store.
The usage amount in the usage amount column 130 is the amount (discount price × quantity) of a product or the like purchased by the passenger using the service.

The parking lot guidance device 1 determines the parking waiting position, the actual waiting time, and the parking time for each vehicle based on images captured by a plurality of cameras (not shown) installed at many positions in the parking lot 4. The obtained result is stored in the auxiliary storage device 25 as the service use record database 42.
Furthermore, the parking lot guidance apparatus 1 learns a mathematical expression indicating the relationship between the parking waiting position and the waiting time by performing statistical processing on the accumulated data. Then, the parking lot guidance apparatus 1 can predict the waiting time based on the parking waiting position (indicating the length of the queue when the vehicles 7 are arranged at the end of the queue).

If a simple example is given, the parking lot guidance apparatus 1 can predict the waiting time as follows.
(1) The number n _{in of the} vehicles 7 passing through the entrance 5a of the parking lot 4 and the number n _out of the vehicles 7 passing through the exit 5b are constantly monitored. For example, for each time zone having a width of 10 minutes, n _{Get in} and n _out .
(2) An average parking time is obtained by subtracting a time zone (start time) at which n _in is maximized from a time zone (time at which n _out is maximized). Assume that the average parking time is 60 minutes.

(3) If there are 60 parking spaces and the vehicle is currently full, all parking spaces will be vacated once after 60 minutes.
(4) It is assumed that 60 vehicles 7 currently form a queue and that new vehicles 7 will not line up at the end of the queue in the future. Since parking is performed in the empty parking space in order from the vehicles 7 arranged at the head of the queue, the queue will eventually disappear after 60 minutes.
(5) Therefore, the waiting time of the vehicles 7 arranged at the head of the queue is 60 minutes / 60 vehicles = 1 minute. The waiting time of the vehicles 7 arranged in the second row is 2 minutes (the same applies hereinafter).

  Data in the usage service ID column 127 to the usage amount column 130 of the service usage record database 42 is acquired by the parking lot guidance apparatus 1 from the POS information stored in the facility server 12. When the occupant selects one of the proposed service candidates, the parking lot guidance device 1 transmits the occupant ID together with the service ID of the service to the portable terminal device carried by the occupant. The occupant presents the mobile terminal device at the cash register of the store. Therefore, the facility server 12 can store, as the service use record database 42, a state in which the occupant performs shopping while using the service in the large-scale shopping facility 2.

If attention is paid to the service use record database 42 in FIG.
There are four occupants who have selected the service as shown in FIG. 5, and their occupant IDs are “C001”, “C002”, “C003”, and “C004”.
The occupant C001 and the occupant C003 selected one service, the occupant C002 selected two services, and the occupant C004 selected three services.
The occupant C001 and the occupant C002 used all the selected services at the store. Crew C003 did not use the selected service. Crew C004 used only one of the three selected services.

Furthermore, when attention is again paid to the service use record database 42 of FIG. 5 with reference to FIG.
-Crew C001 and C002 selected the service of the same store (C restaurant).
-The waiting time of passenger C002 is longer than the waiting time of passenger C001.
Due to these reasons, even if the service is in the same store, the discount rate (6%) of the service SS033 selected by the occupant C002 is lower than the discount rate (5%) of the service SS032 selected by the occupant C002. Bigger than.

(Contribution database)
The contribution database 43 will be described with reference to FIG. In the contribution database 43, the time zone 142, the weather zone 143 is the weather, the waiting time column 144 is the waiting time, the time zone 142 is associated with the date stored in the date field 141. In the service proposal presence / absence column 145, there is a service proposal presence / absence, in the proposed service ID column 146, the proposed service ID is used, in the usage service ID column 147, the usage service ID is in sales, in the sales column 148, the sales amount is in service usage. The sales column 149 stores service usage sales, the profit column 150 stores profits, the service usage profit column 151 stores service usage profits, and the contribution column 152 stores contributions.

The date in the date field 141 is the date on which the large-scale shopping facility 2 is operated.
The time zone in the time zone column 142 is a time zone in which the large shopping facility 2 is open.
The weather in the weather column 143 is the weather for the time period.
The waiting time in the waiting time column 144 is the same as the waiting time (predicted value) in FIG. However, the waiting time here is an average value of all waiting times transmitted to the vehicle 7 in the time period.

The presence / absence of a service proposal in the service proposal presence / absence column 145 is either “Yes” indicating that a service proposal has been made in the time slot or “No” indicating that no proposal has been made. Of course, “none” is stored in the record whose waiting time is “0”.
The proposed service ID in the proposed service ID column 146 is the service ID of the service proposed to the occupant. A plurality of services may be proposed during the time period.
The use service ID in the use service ID column 147 is a service ID of a service used in the store. A plurality of services may be used during the time period.

The sales in the sales column 148 is the sales of the product in the store.
The service use sales in the service use sales column 149 is the number of sales when the service is used.
The profit in the profit column 150 is the net profit of the store.
The service use profit in the service use profit column 151 is the number of profits when the service is used.
The contribution degree in the contribution degree column 152 is a ratio (%) of the service use profit to the profit.

  The parking lot guidance apparatus 1 can create the contribution database 43 by analyzing the POS information acquired from the facility server 12. If attention is paid to the contribution degree of the contribution degree database 43, it is possible to know the influence of the use of the service on the profit. The parking lot guidance apparatus 1 may use the ratio of service use sales to sales, the ratio of service use profits to service use sales, and the like as contributions. As shown in FIG. 6, the parking lot guidance apparatus 1 can create a contribution database 43 that aggregates data of all stores, and can also create a contribution database 43 for each store.

(Processing procedure)
A processing procedure will be described with reference to FIG.
In step S201, the store profit management unit 32 of the parking lot guidance apparatus 1 predicts the profit of the store. Specifically, first, the store profit management unit 32 acquires past data for an arbitrary period of an unprocessed arbitrary store from the facility server 12. Fixed costs (number of shop assistants, scale of sales equipment, etc.) are often determined monthly. Accordingly, the “arbitrary period” here is preferably a period from the first day to the last day of the previous month, for example.

  Second, the store profit management unit 32 draws the fixed cost, variable cost, and sales graphs described in FIG. At this time, the store revenue management unit 32 may use the previous year's graph as it is as the current year's graph, or accept that the user (store manager) modifies the previous year's graph based on the weather conditions or the like. Also good.

In step S <b> 202, the service generation unit 33 of the parking lot guidance device 1 generates the service database 41. Specifically, first, the service generation unit 33 draws a vertical straight line corresponding to the target sales quantity after the discount rate is applied in the region on the right side of the breakeven point. This vertical straight line is called a “discount rate determination reference line” (see FIG. 2). Then, a triangle surrounded by a variable cost line, a sales line, and a discount rate determination reference line is determined. The name “discount rate determination reference line” means a reference line for determining “discount rate” for each level of profit rate. The profit rate here is a value calculated by the formula of “profit rate = net profit / sales × 100 (%)”, and reflects the magnitude of accumulated profit including past losses. Incidentally, the discount rate is a value calculated by the formula “discount rate = (list price−discount price) / list price × 100 (%)”.
Second, the service generation unit 33 obtains the maximum discount rate r by the method described with reference to FIG.

In general, the larger the profit rate, the more margin is the store management, and the maximum discount rate r can be set to a large value. That is, as the profit rate increases, the maximum discount rate r increases accordingly. Therefore, for example, the service generation unit 33 can create a “longest wait time discount rate vector” as follows by accepting that the user inputs an arbitrary profit rate and obtaining r for each received profit rate. .
(R ₅ , r ₁₀ , r ₁₅ , r ₂₀ ) = (10%, 12%, 14%, 16%)

The first component r ₅ = 10% of the longest waiting time discount rate vector means that if a profit rate of 5% can be expected, the discount rate may be 10%. Similarly, the second component r ₁₀ = 12% of the longest waiting time discount rate vector means that if a profit rate of 10% can be expected, the discount rate may be 12% ( The same applies below). Note that the number of components of the longest wait time discount rate vector is not limited to “4”.

The more the discount rate determination reference line is drawn on the right side, the more the store has a bullish sales target. However, the user often assumes a profit rate having a special meaning, such as a profit rate that is likely to be realized or a profit rate (norm) that must be realized. Therefore, the service generation unit 33 determines that the user attaches the main profit rate flag “#” to the discount rate corresponding to such a profit rate among the four components of the longest wait time discount rate vector. Accept through. Then, the longest waiting time discount rate vector is as follows.
(R ₅ , r ₁₀ , r ₁₅ , r ₂₀ ) = (10%, 12% #, 14%, 16%)
“#” Is added to the second component. This means that the user expects, for example, “the profit rate that is likely to be realized is 10%”, and “the discount rate may be set to 12% in order to achieve the profit rate of 10%”. Show what you think.

  Thirdly, the service generation unit 33 accepts that the user inputs “the longest waiting time” via the input device 22. The longest waiting time is the longest time (the limit of patience) that the occupant can wait inside the vehicle 7. Here, it is assumed that the user inputs “30 minutes”. Then, the service generation unit 33 divides 30 minutes into a predetermined number of sections. Here, the service generation unit 33 sets 30 minutes to “0 to 5 minutes”, “5 to 10 minutes”, “10 to 15 minutes”, “15 to 20 minutes”, “20 to 25 minutes”, and “25”. Suppose that it is divided into six segments having the same length of “˜30 minutes”. As described above, “5 to 10 minutes” means more than 5 minutes and 10 minutes or less. Others are the same.

Fourth, the service generation unit 33 creates a “discount rate vector” for each waiting time category. For example, the service generation unit 33 assigns the longest waiting time discount rate vector to the longest segment “25 to 30 minutes”. Then, according to the following adjustment formula, the discount rate vector V _i for the other sections is created by multiplying the longest wait time discount rate vector V _max by the coefficient α _i .
V _i = α _i × V _max
Here, subscript "i" is the _{V i,} which is the upper limit of latency for the longest of the respective segments other than division, 5 minutes, 10 minutes, 15 minutes, 20 minutes and 25 minutes. Furthermore, α _i satisfies 0 ≦ α ₁ ≦ α ₂ ≦ α ₃ ≦ α ₄ ≦ α ₅ ≦ 1.

The discount rate vector created here is, for example, about a waiting time of 0 to 5 minutes.
(R ₅ , r ₁₀ , r ₁₅ , r ₂₀ ) = (1%, 1% #, 1%, 2%).
Similarly, for a waiting time of 5-10 minutes,
(R ₅ , r ₁₀ , r ₁₅ , r ₂₀ ) = (2%, 2% #, 3%, 3%).
About waiting time 10-15 minutes
(R ₅ , r ₁₀ , r ₁₅ , r ₂₀ ) = (4%, 5% #, 6%, 6%).
About 15-20 minutes waiting time
(R ₅ , r ₁₀ , r ₁₅ , r ₂₀ ) = (6%, 7% #, 8%, 10%).
About waiting time 20-25 minutes
(R ₅ , r ₁₀ , r ₁₅ , r ₂₀ ) = (8%, 10% #, 11%, 13%). The position of the main profit margin flag has not changed.

  Fifth, the service generation unit 33 allows the user to input the gender, age and residence area, name of the store to be provided, product to be provided, and the time zone and day of the week when the service is provided via the input device 22. To accept input.

  Sixth, the service generation unit 33 creates a record for the store being processed in the service database 41 for each waiting time based on the data created or received in “first to fifth” in step S202. To do. Note that the large shopping facility 2 does not allow a customer in the vehicle 7 to wait more than 30 minutes. Therefore, if a waiting time of more than 30 minutes is predicted, the records “SS991” to “S993” are applied to prompt the occupant to leave (turn back) from the queue without rudeness.

  The store revenue management unit 32 repeats the process of step S201 for all unprocessed stores, and the service generation unit 33 repeats the process of step S202 for all unprocessed stores.

  In step S203, the waiting time prediction unit 31 of the parking lot guidance apparatus 1 determines whether or not the vehicle 7 has been detected. Specifically, the waiting time prediction unit 31 constantly monitors an image captured by the camera 9. When the waiting time predicting unit 31 detects that the vehicle 7 stops on the road 8 (aligned at the end of the queue) (step S203 “Yes”), the parking waiting position of the vehicle (the end of the queue) ) Is acquired, and the process proceeds to step S204. If the waiting time prediction unit 31 does not detect that the vehicle 7 stops on the roadway 8 (step S203 “No”), it waits until it is detected.

  In step S204, the waiting time prediction unit 31 predicts a waiting time. Specifically, the waiting time prediction unit 31 predicts the waiting time based on the past accumulated data and the parking waiting position as described above.

In step S205, the service proposal unit 34 of the parking lot guidance apparatus 1 accepts that the occupant inputs the attribute and the service category (immediately described later). Specifically, first, the service proposal unit 34 displays an acceptance screen (not shown) on an input / output device (not shown) such as a touch panel of the terminal device 11. The reception screen has an age selection field, a sex selection field, a residential area selection field, and a service category selection field.
Second, the service proposing unit 34 accepts that the occupant selects and inputs his / her age, gender, residential area, and service category. The service category here is, for example, a classification such as “meal” and “fashion”, and the provided product in the service database 41 of FIG. 4 is associated with at least one of the service categories.

In step S <b> 206, the service proposal unit 34 acquires service candidates according to the waiting time and the like. Specifically, the service proposing unit 34 searches the service database 41 (FIG. 4) using the following data as a search key, and acquires all corresponding records.
-Waiting time predicted in step S204-Age, sex, residential area and service category received in "second" of step S205-Current time (may include time to walk from the parking lot 4 to the store) and Day of the week

  In step S207, the service proposing unit 34 proposes service candidates according to the waiting time or the like. Now, the description will be continued assuming that the waiting time predicted in step S204 is 30 minutes or less. Specifically, first, the service proposal unit 34 displays a service proposal screen 61 a (FIG. 8A) on the input / output device of the terminal device 11. At this time, the service proposing unit 34 displays the waiting time predicted in step S204 in the waiting time column 62 of the service proposing screen 61a.

Second, the service proposing unit 34 creates a message including the provided store name, the provided product, and the discount rate with the main profit margin flag, based on all the records of the service database 41 acquired in step S206. . The message created here is, for example, “A cosmetic store, 5% discount on cosmetics”. The message may include a time zone in which the service is applied.
Thirdly, the service proposal unit 34 displays all the created messages as service candidates in the service candidate field 63 of the service proposal screen 61a.

On the other hand, if the waiting time predicted in step S204 is more than 30 minutes, first in step S207, the service proposal unit 34 displays the service proposal screen 61b (FIG. 8B).
Second, the service proposing unit 34 creates a message that prompts the occupant to leave the queue based on all the records of the service database 41 acquired in step S206. The message created here is, for example, “network shopping, 5% discount”.
Thirdly, the service proposal unit 34 displays all the created messages as service candidates in the service candidate field 63 of the service proposal screen 61b.

  In step S208, the service proposing unit 34 accepts the selection of the occupant. Specifically, the service proposal unit 34 accepts that the occupant presses either the “Yes” button or the “No” button in the selection column 64 of the service proposal screen 61a or 61b.

  In step S209, the service proposal unit 34 determines whether a service has been selected. Specifically, when at least one “Yes” button is pressed (step S209 “Yes”), the service proposing unit 34 proceeds to step S210. In other cases (step S209 “No”), the process returns to step S205.

  The second and subsequent processing in steps S205 to S208 is referred to as “loop processing”. In step S205 during the loop process, as described above, the service proposing unit 34 first displays the acceptance screen (not shown) again, and secondly, the occupant has his / her age, sex, and residential area. And accepting the selection of the service category again. When the occupant input changes, the service candidates proposed in step S207 during the loop process also change. Even if the occupant does not perform such re-input, for example, the service proposing unit 34 automatically changes the previous input content and considers that the re-input after the change has occurred. May be. Examples of changes include removing gender restrictions on previous entries, expanding the age range of previous entries, removing residential areas for previous entries, expanding service categories to similar preset service categories, etc. Is mentioned.

  In step S210, the service proposing unit 34 transmits a service coupon. Specifically, the service proposal unit 34 transmits a service coupon to the terminal device 11 carried by the passenger. A service coupon is an electronic coupon including the service ID of the service selected by the occupant. The service coupon may include sales words related to the store or the product, contents that the occupant can spend without waiting for the waiting time, and the like.

  Here, the terminal device 11 to which the service proposing unit 34 transmits the service coupon is not a vehicle-mounted device such as a car navigation device but a portable terminal device carried by a passenger. This is because the occupant uses the service by holding the portable terminal device over a POS device such as a cash register when shopping in the store in the future. The occupant who received the service coupon spends a waiting time in a convinced mood, and eventually parks the vehicle 7 in the parking space and heads to the store.

  The store database (not shown) of each store of the large-scale shopping facility 2 can refer to the service database 41. Then, the store server, based on the service ID included in the service coupon read from the occupant's mobile terminal device, the discount rate to be applied to the occupant (the main profit rate flag “#” is attached). Can be specified.

  In step S211, the store profit management unit 32 of the parking lot guidance apparatus 1 acquires a service usage record. Specifically, the service proposing unit 34 acquires POS information from the facility server 12 on, for example, regular holidays (every day of the week) of the large-scale shopping facility 2. And the service proposal part 34 produces the service utilization track record database 42 (FIG. 5) using POS information.

In step S212, the store profit management unit 32 calculates a contribution. Specifically, first, the store revenue management unit 32 creates the contribution database 43 (FIG. 6) using the POS information.
Second, the store profit management unit 32 calculates the service use profit generated by the used service for each record of the created contribution database 43. For example, it is assumed that a service use profit of 60 thousand yen is generated as a result of using the services SS023, SS033, and SS043. At this time, 60,000 yen is equally distributed, and data such as “(SS023, 20000 yen), (SS033, 20000 yen), (SS043, 20000 yen)” is generated. Of course, the store profit management unit 32 may apportion the service use profit at a discount price.

Thirdly, the store revenue management unit 32 calculates the service use profit results for a certain period (for example, May 2016) for each service by totaling this data for all records.
Fourth, the store revenue management unit 32 rearranges the services in descending order of service use profits. Then, the store revenue management unit 32 displays the services on the output device 23 in association with the attributes (gender, age, and residential area) of the target customer group of the services in the sorted order. The store profit management unit 32 may display the service use profits in a predetermined manner for each gender, each age, and each residential area.

Then, the user who has viewed the displayed information can know, for example, the following.
-What attributes (gender, age, and place of residence) the passengers are making, how much profits they can use for the service?
• What kind of attributes (gender, age, and place of residence) can be tolerated by the occupant?

In step S213, the store profit management unit 32 updates the service database 41. Specifically, first, the store revenue management unit 32 uses the service usage record database 42 (FIG. 5) created in step S211 and the contribution database 43 (FIG. 6) created in step S212 in the output device 23. indicate. The user who visually recognizes such information can know, for example, the following.
・ How long wait time occurred at which point?
• Which services are proposed, which are selected, and which are used.
• To what extent did the services used contribute to profits, for example?

Second, the store revenue management unit 32 displays the service database 41 (FIG. 4) on the output device 23.
Third, the store profit management unit 32 accepts that the user updates any data in the service database 41. The update here includes, for example, reviewing the target customer segment, reviewing the discount rate, reviewing the correspondence relationship between the waiting time and the discount rate, reviewing the position of the main profit rate flag, and the like.
Thereafter, the processing procedure ends. In step S202 when the next processing procedure is executed, the service generation unit 33 sets the service database 41 updated in “third” in step S213 as the service database 41 to be generated.

(Effect of this embodiment)
The effect of the parking lot guidance apparatus of this embodiment is as follows.
(1) The parking lot guidance device can provide a service corresponding to the waiting time and the profit of the store to the occupant. Therefore, when no profit is generated, it is possible to avoid providing an excessive service.
(2) The parking lot guidance device can return a part of the profit to the passenger by providing the service. Therefore, a sense of satisfaction arises for the occupant who has endured the waiting time.
(3) The parking lot guidance device causes the passenger to select a service. Therefore, the passengers feel more convinced.

(4) The parking lot guidance device can use general management indexes such as sales, fixed costs and variable costs as they are.
(5) When the waiting time exceeds a predetermined threshold, the parking lot management device displays a message recommending that the user not enter. Therefore, even when shopping is not possible, waste of passenger time can be minimized.
(6) The parking lot management apparatus can predict the profit actually generated for each attribute of the target occupant. Therefore, a detailed sales promotion plan can be made.

  In addition, this invention is not limited to an above-described Example, Various modifications are included. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Further, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of each embodiment.

Each of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by the processor. Information such as programs, tables, and files that realize each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.
In addition, the control lines and information lines are those that are considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. In practice, it may be considered that almost all the components are connected to each other.

DESCRIPTION OF SYMBOLS 1 Parking lot guidance apparatus 2 Large shopping facility 11 Terminal apparatus 12 Facility server 13 Network 21 Central controller 22 Input apparatus 23 Output apparatus 24 Main storage apparatus 25 Auxiliary storage apparatus 26 Communication apparatus 31 Waiting time prediction part 32 Store profit management part 33 Service Generation unit 34 Service proposal unit 41 Service database 42 Service usage record database 43 Contribution database

Claims (8)

Store revenue management department to predict store profits,
A service generation unit that generates a candidate for a service provided in the store according to the waiting time of the vehicle entering the parking lot attached to the store and the predicted profit;
A waiting time prediction unit for predicting the waiting time of the vehicle;
A service candidate corresponding to the predicted waiting time is acquired from the generated service candidates, and the acquired service candidate is displayed together with the predicted waiting time on a terminal device operated by a vehicle occupant. A service proposal department to
A parking lot guidance device comprising: The service generation unit
Generating a candidate for the service that returns a portion of the predicted profit to a passenger of the vehicle;
The store revenue management department
Calculating a contribution indicating how much the passenger actually used the service contributed to the profit;
The parking lot guidance device according to claim 1. The service proposal unit
Receiving the occupant selecting at least one of the displayed candidate services;
The parking lot guidance apparatus according to claim 2. The store revenue management department
Predicting the current profit of the store based on the past sales, fixed costs and variable costs of the store;
The parking lot guidance apparatus according to claim 3. The service proposal unit
If the predicted waiting time exceeds a predetermined threshold, displaying a message on the terminal device recommending that the vehicle not enter the parking lot;
The parking lot guidance apparatus according to claim 4. The store revenue management department
Predicting the profit generated in the store by using the service for each attribute of the occupant to be the target of the service;
The parking lot guidance device according to claim 5. The store revenue management department of the parking lot guidance device
Predict store profits,
The service generation unit of the parking lot guidance device
According to the waiting time of the vehicle entering the parking lot attached to the store and the predicted profit, a candidate for a service provided in the store is generated,
The waiting time prediction unit of the parking lot guidance device
Predicting the waiting time of the vehicle,
The service proposal unit of the parking lot guidance device
A service candidate corresponding to the predicted waiting time is acquired from the generated service candidates, and the acquired service candidate is displayed together with the predicted waiting time on a terminal device operated by a vehicle occupant. To do,
A parking lot guidance method for a parking lot guidance device. For store revenue management department of parking lot guidance device,
Run a process to predict store profits,
For the service generation unit of the parking lot guidance device,
According to the waiting time of the vehicle entering the parking lot attached to the store and the predicted profit, a process of generating a service candidate provided in the store is executed.
For the waiting time prediction unit of the parking lot guidance device,
Executing a process for predicting the waiting time of the vehicle;
For the service proposal section of the parking lot guidance device,
A service candidate corresponding to the predicted waiting time is acquired from the generated service candidates, and the acquired service candidate is displayed together with the predicted waiting time on a terminal device operated by a vehicle occupant. To execute the process to
A parking lot guidance program for causing a parking lot guidance device to function.

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