JP7316562B2 - Information provision device and information provision method - Google Patents
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Description
本発明は、情報提供装置および情報提供方法に関するものであり、具体的には、宿泊施設における客室販売の機会増大、収益性の改善を図る技術に関する。 TECHNICAL FIELD The present invention relates to an information providing apparatus and an information providing method, and more particularly to a technique for increasing room sales opportunities and improving profitability in accommodation facilities.
ホテルや旅館といった宿泊施設は、自社サイトでの客室販売に加え、いわゆるOTAへの販売委託を行い、幅広く販売機会の拡大等を図っている。宿泊施設としての意図の1つには、こうして販売機会を増やすことで、ブッキングカーブをできるだけ早めに立ち上げる、すなわち満室状態を早期に達成・維持したいという願いがある。 Accommodation facilities such as hotels and Japanese inns, in addition to selling rooms on their own websites, are outsourcing sales to so-called OTAs in order to broaden sales opportunities. One of the intentions of the lodging facility is to increase sales opportunities in this way so as to raise the booking curve as early as possible, that is, to achieve and maintain full occupancy as early as possible.
このような、宿泊施設のレベニューマネジメントに関連する従来技術としては、例えば、他装置とネットワークを介して通信する通信装置と、所定宿泊施設および前記所定宿泊施設以外の他宿泊施設に関する、客室販売価格と顧客評価値とを少なくとも含む所定情報を、複数のネットエージェントそれぞれのWEBサイト、前記所定宿泊施設と契約したサイトコントローラ、および各宿泊施設自身が運営する公式WEBサイトの少なくともいずれかから、所定時間毎に取得する処理と、前記取得した情報に基づき、前記所定宿泊施設と顧客評価値が所定範囲で近しい競合施設たる他宿泊施設、または前記所定宿泊施設の近隣宿泊施設であって所定端末から指定を受けた競合施設たる他宿泊施設と、その客室販売価格を各ネットエージェントのWEBサイトごと又は前記公式WEBサイトごとに特定し、当該特定した競合施設の顧客評価値と前記所定宿泊施設の顧客評価値との乖離幅と乖離方向に応じ、該当ネットエージェントのWEBサイト又は前記公式WEBサイトにおける前記所定宿泊施設または前記競合施設の客室販売価格を所定割合で上下させた価格を、前記所定宿泊施設への提案価格として算定する処理と、前記所定宿泊施設の端末への前記提案価格の通知、または該当ネットエージェント或いは前記所定宿泊施設の公式WEBサイトの所定サーバに対する、前記提案価格を該当WEBサイトでの客室販売価格とする旨の設定指示、の少なくともいずれかを行う処理を実行する演算装置と、を備えることを特徴とするレベニューマネジメントシステム(特許文献1参照)などが提案されている。 As such conventional technology related to revenue management of accommodation facilities, for example, a communication device that communicates with other devices via a network, a room sales price related to a prescribed accommodation facility and other accommodation facilities other than the prescribed accommodation facility and a customer evaluation value from at least one of the websites of each of the plurality of net agents, the site controller contracted with the prescribed accommodation facility, and the official website operated by each accommodation facility itself for a prescribed period of time. and based on the acquired information, another accommodation facility that is a competing facility that has a customer evaluation value close to the predetermined accommodation facility within a predetermined range, or a nearby accommodation facility of the predetermined accommodation facility and is specified from a predetermined terminal Identify other accommodation facilities that are competing facilities that have received the above and their room sales prices for each net agent's website or for each official website, and the customer evaluation value of the specified competing facilities and the customer evaluation of the predetermined accommodation facility Depending on the range and direction of deviation from the value, the room sales price of the prescribed accommodation facility or the competing facility on the website of the relevant net agent or the official website is raised or lowered by a prescribed percentage, and the price is sent to the prescribed accommodation facility. and notification of the proposed price to the terminal of the prescribed accommodation facility, or the proposed price to the relevant net agent or a prescribed server of the official website of the prescribed accommodation facility at the relevant WEB site and a computing device that performs at least one of a setting instruction to set the room sales price (see Patent Literature 1).
また、インターネット上に構築されたサーバ装置に対してインターネット経由で端末装置を接続して宿泊施設の予約を受け付ける宿泊施設の予約受付方法であって、あらかじめ利用する複数の客室数と、各客室における宿泊数の総和であるトータル宿泊数の入力を受け付けて記憶するステップと、上記記憶した客室数に対応する客室毎に宿泊開始日と宿泊数の入力を受け付けるステップと、上記受け付けた宿泊開始日と宿泊数に対応する客室在庫について客室在庫データベースを参照するステップと、上記受け付けた宿泊開始日と宿泊数に対応する客室在庫がある場合に、あらかじめ記憶したトータル宿泊数に対して受け付けた宿泊数を引き当てるステップと、あらかじめ記憶したトータル宿泊数と、上記引き当てた宿泊数とが等しくなったときに予約を成立させるステップとを備えたことを特徴とする宿泊施設の予約受付方法(特許文献2参照)なども提案されている。 In addition, a reservation reception method for an accommodation facility in which a terminal device is connected via the Internet to a server device built on the Internet to accept reservations for accommodation facilities, wherein the number of rooms to be used in advance and the number of rooms in each room a step of receiving and storing the input of the total number of nights, which is the sum of the number of nights, a step of receiving an input of a start date of stay and the number of nights for each guest room corresponding to the number of rooms stored; A step of referring to a guest room inventory database for room inventory corresponding to the number of nights stayed, and if there is room inventory corresponding to the accommodation start date and the number of nights accepted, adding the number of nights received to the total number of nights stored in advance. A reservation acceptance method for an accommodation facility, comprising: a step of allocating; and a step of establishing a reservation when a pre-stored total number of nights is equal to the number of nights allocated (see Patent Document 2). are also proposed.
宿泊施設のレベニューマネージャーは、団体客に関する予約があれば、満室状態を早期に達成しやすいとの思惑もあって、収益面での確たる根拠も無く安易に当該予約を受け入れるケースが多い。 There are many cases in which revenue managers of lodging facilities easily accept such reservations without a solid basis in terms of profitability, partly because they believe that if there are reservations for group guests, it will be easier for them to reach full occupancy early.
しかしながら、当該宿泊施設における収益面を考慮すれば、団体客の予約を受け入れることには相応の注意が必要である。すなわち、そうした団体客の予約は、得てして値引き要求を含むことが多い一方、一度の客室販売数とトータルの売上額が大きく見えることで、収益性が著しく低くなる側面を無視してしまう弊害が大きい。 However, considering the profitability of the accommodation facility, it is necessary to be careful about accepting group reservations. In other words, while reservations for such group customers often include requests for discounts, the fact that the number of rooms sold at one time and the total amount of sales appear to be large can result in a significant decline in profitability. .
例えば、上限数は決まっている客室を、宿泊日の半年前、1年前の早期に、単価の低い団体客で埋めてしまえば、本来ならば獲得できていたはずの高単価の良客(やその予約要求)が該当期間に生じても、断らざるをえない事態が生じる。つまり、そうした良客を自ら失ってしまう恐れが高い。しかも、そうした状況は、予め知見を持っていないかぎり把握しにくく、該当期間における宿泊施設の収益が、団体予約の受入前よりも結局悪化している状況が見えにくくなる。 For example, if a guest room with a fixed maximum number is filled with group guests with low unit prices as early as half a year or a year before the date of stay, good customers with high unit prices that would otherwise have been acquired ( and its reservation request) occurs during the relevant period, there will be a situation where you have to refuse. In other words, there is a high risk of losing those good customers. Moreover, it is difficult to grasp such a situation unless one has knowledge in advance, and it becomes difficult to see the situation in which the profit of the accommodation facility during the relevant period is worse than before accepting group reservations.
したがって、団体客の予約受入の可否を、当該宿泊施設における収益面を踏まえつつ、的確に判断し、客室販売の機会増大とそれに伴う収益性向上を図る観点が非常に重要となってくる。そこで本発明の目的は、宿泊施設における客室販売の機会増大、収益性の改善を図る技術を提供することにある。 Therefore, it is extremely important to accurately determine whether or not to accept group reservations, while taking into consideration the profitability of the accommodation facility, and to increase opportunities for room sales and improve profitability accordingly. SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a technique for increasing room sales opportunities and improving profitability in accommodation facilities.
上記課題を解決する本発明の情報提供装置は、宿泊施設における過去の客室販売に関する情報を含む履歴DBを保持する記憶装置と、団体予約の情報を所定装置から受信し、当該団体予約の情報が示す宿泊時期と同一時期の過去に関する予約推移の情報を前記履歴DBから抽出し、当該予約推移の情報に基づき、前記団体予約の受諾の可否別の客室販売状況の推移を所定アルゴリズムにより予測する処理と、前記予測にて得た前記受諾の可否別の客室販売状況の推移に基づき、前記団体予約の受諾の可否別の前記宿泊施設での売り上げ合計額の予想値を算定する処理と、前記予想値の情報を所定の端末に出力する処理と、を実行する演算装置と、を含むことを特徴とする。 The information providing device of the present invention for solving the above problems is a storage device that holds a history DB containing information on past room sales at accommodation facilities, and receives group reservation information from a predetermined device, and receives the group reservation information. A process of extracting from the history DB information on past reservation transitions for the same period as the indicated accommodation period, and predicting, by a predetermined algorithm, the transitions in the guest room sales situation for each acceptance or rejection of the group reservation based on the information on the reservation transitions. and a process of calculating a predicted value of the total sales amount at the accommodation facility for each acceptance or non-acceptance of the group reservation based on the transition of the guest room sales situation for each of the acceptance or non-acceptance obtained in the prediction, and the prediction and an arithmetic device for executing a process of outputting value information to a predetermined terminal.
なお、上述の情報提供装置において、前記演算装置は、前記団体予約を受諾した場合の売り上げ合計額の予想値が、当該団体予約を受諾しなかった場合の売り上げ合計額の予想値より小さい場合、その旨を前記端末に出力するものである、としてもよい。 In the above-described information providing device, if the estimated value of the total sales amount when the group reservation is accepted is smaller than the estimated value of the total sales amount when the group reservation is not accepted, It may be configured such that a message to that effect is output to the terminal.
また、上述の情報提供装置において、前記演算装置は、前記団体予約を受諾する条件として、前記団体予約を受諾しなかった場合の前記客室販売状況の推移に基づく客室販売価格を推定し、前記端末に出力するものである、としてもよい。 Further, in the information providing apparatus described above, the arithmetic unit estimates, as a condition for accepting the group reservation, a room sales price based on the transition of the room sales situation when the group reservation is not accepted, and the terminal may be output to
また、上述の情報提供装置において、前記演算装置は、前記客室販売価格を前記団体予約の受諾に際しての客室販売価格下限とし、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を下回る場合、当該団体予約を拒否すべきと判定し、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を上回る場合、当該団体予約を受諾すべきと判定し、前記いずれかの判定の結果を前記端末に出力するものである、としてもよい。 Further, in the above-described information providing device, the computing device sets the room sales price as the lower limit of the room sales price when accepting the group reservation, and the requested amount of the room sales price indicated by the group reservation information is equal to the room sales price. If the price falls below the lower price limit, the group reservation should be rejected, and if the requested room sales price indicated by the group reservation information exceeds the room price lower limit, the group reservation should be accepted. and outputting the result of any of the determinations to the terminal.
また、上述の情報提供装置において、前記演算装置は、前記履歴DBで保持する所定期間分の前記情報が示す、所定の団体予約の問い合わせ時期と同一時期の過去における、前記宿泊施設の客室販売価格、他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習を予め実行しておき、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、前記客室販売価格の推定を行うものである、としてもよい。 Further, in the information providing device described above, the computing device may calculate the room sales price of the accommodation facility in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB. , Room sales prices of other accommodation facilities, and machine learning with input of the occupancy rate of the said accommodation facilities are executed in advance, and the time of inquiry of the group reservation that received the above information, the other accommodation facilities at the time of receiving the above The room selling price may be estimated according to the room selling price and the occupancy rate of the accommodation facility.
また、上述の情報提供装置において、前記演算装置は、前記機械学習に際し、過去において、所定の団体予約を前記宿泊施設が拒否し他宿泊施設が受諾した場合の、前記宿泊施設の客室販売価格、前記他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習をさらに実行し、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、当該団体予約の受諾可否に応じて異なる前記客室販売価格の推定を行うものである、としてもよい。 Further, in the above-described information providing device, the computing device, in the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and other accommodation facilities accepted, the room sales price of the accommodation facility, Machine learning is further executed with the room sales price of the other accommodation facility and the occupancy rate of the accommodation facility as input, and the timing of group reservation inquiry when the information is received and the room sales of the other accommodation facility at the time of receiving the information Depending on the price and the occupancy rate of the accommodation facility, the room sales price may be estimated differently depending on whether or not the group reservation is accepted.
また、本発明の情報提供方法は、情報処理装置が、宿泊施設における過去の客室販売に関する情報を含む履歴DBを保持する記憶装置を備え、団体予約の情報を所定装置から受信し、当該団体予約の情報が示す宿泊時期と同一時期の過去に関する予約推移の情報を前記履歴DBから抽出し、当該予約推移の情報に基づき、前記団体予約の受諾の可否別の客室販売状況の推移を所定アルゴリズムにより予測する処理と、前記予測にて得た前記受諾の可否別の客室販売状況の推移に基づき、前記団体予約の受諾の可否別の前記宿泊施設での売り上げ合計額の予想値を算定する処理と、前記予想値の情報を所定の端末に出力する処理と、を実行することを特徴とする。 Further, in the information providing method of the present invention, the information processing device has a storage device that holds a history DB containing information on past room sales at the accommodation facility, receives group reservation information from a predetermined device, and processes the group reservation. extract from the history DB the reservation transition information related to the past at the same time as the lodging period indicated by the information, and based on the reservation transition information, change the room sales status by acceptance or rejection of the group reservation by a predetermined algorithm. A process of predicting and a process of calculating an expected value of the total sales amount at the accommodation facility for each acceptance or rejection of the group reservation based on the progress of the guest room sales situation for each acceptance or rejection obtained by the prediction. , and a process of outputting the information of the predicted value to a predetermined terminal.
なお、上述の情報提供方法において、前記情報処理装置が、前記団体予約を受諾した場合の売り上げ合計額の予想値が、当該団体予約を受諾しなかった場合の売り上げ合計額の予想値より小さい場合、その旨を前記端末に出力する、としてもよい。 In the above-described information providing method, if the estimated total sales amount when the information processing device accepts the group reservation is smaller than the estimated total sales amount when the group reservation is not accepted. , a message to that effect may be output to the terminal.
また、上述の情報提供方法において、前記情報処理装置が、前記団体予約を受諾する条件として、前記団体予約を受諾しなかった場合の前記客室販売状況の推移に基づく客室販売価格を推定し、前記端末に出力する、としてもよい。 Further, in the above-described information providing method, the information processing device, as a condition for accepting the group reservation, estimates a room sales price based on the transition of the room sales situation when the group reservation is not accepted, You can also output to the terminal.
また、上述の情報提供方法において、前記情報処理装置が、前記客室販売価格を前記団体予約の受諾に際しての客室販売価格下限とし、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を下回る場合、当該団体予約を拒否すべきと判定し、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を上回る場合、当該団体予約を受諾すべきと判定し、前記いずれかの判定の結果を前記端末に出力する、としてもよい。 Further, in the above-described information providing method, the information processing device sets the room sales price as the lower limit of the room sales price when accepting the group reservation, and the requested amount of the room sales price indicated by the group reservation information is If the price falls below the minimum sales price, the group reservation should be rejected, and if the requested room sales price indicated by the group reservation information exceeds the minimum sales price, the group reservation should be accepted. It may be determined, and the result of any of the determinations may be output to the terminal.
また、上述の情報提供方法において、前記情報処理装置が、前記履歴DBで保持する所定期間分の前記情報が示す、所定の団体予約の問い合わせ時期と同一時期の過去における、前記宿泊施設の客室販売価格、他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習を予め実行しておき、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、前記客室販売価格の推定を行う、としてもよい。 Further, in the above-described information providing method, the information processing apparatus holds room sales of the accommodation facility in the past at the same time as a predetermined group reservation inquiry time indicated by the information for a predetermined period held in the history DB. Machine learning is performed in advance with price, room sales price of other accommodation facilities, and the occupancy rate of the accommodation facility as input, and the time of group reservation inquiry when the information is received, other accommodation facilities at the time of the reception and the occupancy rate of the accommodation facility, the room sales price may be estimated.
また、上述の情報提供方法において、前記情報処理装置が、前記機械学習に際し、過去において、所定の団体予約を前記宿泊施設が拒否し他宿泊施設が受諾した場合の、前記宿泊施設の客室販売価格、前記他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習をさらに実行し、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、当該団体予約の受諾可否に応じて異なる前記客室販売価格の推定を行う、としてもよい。 Further, in the above-described information providing method, when the information processing device performs the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and another accommodation facility accepted it, the room sales price of the accommodation facility , the sales price of the room of the other accommodation facility, and the occupancy rate of the accommodation facility are further executed by machine learning, and the time of inquiry of the group reservation at which the information is received, the guest room of the other accommodation facility at the time of the reception Depending on the sales price and the occupancy rate of the accommodation facility, the room sales price may be estimated differently depending on whether the group reservation is acceptable.
本発明によれば、宿泊施設における客室販売の機会増大、収益性の改善を図ることが可能となる。 According to the present invention, it is possible to increase opportunities for room sales and improve profitability in accommodation facilities.
---ネットワーク構成------ Network configuration ---
以下に本発明の実施形態について図面を用いて詳細に説明する。図1は、本実施形態の情報提供装置100を含むネットワーク構成図である。図1に示す情報提供装置100は、宿泊施設における客室販売の機会増大、収益性の改善を図るコンピュータ装置である。 Embodiments of the present invention will be described in detail below with reference to the drawings. FIG. 1 is a network configuration diagram including an information providing apparatus 100 of this embodiment. The information providing device 100 shown in FIG. 1 is a computer device that aims to increase room sales opportunities and improve profitability in accommodation facilities.
より具体的には、情報提供装置100は、例えば、種々の宿泊施設と提携する所定の事業者が運用するサーバ装置を想定できるが、これに限定しない。例えば、OTA(Online Travel Agent)が運用する装置としてもよい。 More specifically, the information providing device 100 can be assumed to be, for example, a server device operated by a predetermined operator affiliated with various accommodation facilities, but is not limited to this. For example, it may be a device operated by an OTA (Online Travel Agent).
一方、本実施形態の情報提供装置100が、処理結果である情報を出力し提示する対象は、当該情報提供装置100によるサービス提供を享受すべく契約した或る宿泊業者(の宿泊施設端末400)である。勿論、これに限定するものではなく、他の種々の事業者等の端末やシステムを情報の出力対象として想定することも可能である。 On the other hand, the information providing apparatus 100 of the present embodiment outputs and presents information as a processing result to an accommodation provider (accommodation facility terminal 400 of the accommodation facility terminal 400) contracted to receive the service provided by the information providing apparatus 100. is. Of course, it is not limited to this, and it is also possible to assume terminals and systems of other various business operators as information output targets.
よって、情報提供装置100は、インターネットなどの適宜なネットワーク10を介し、各宿泊業者の備える宿泊施設端末400(や情報収集先となりうるOTAのネットエージェントサーバ300)と通信可能に接続されている。 Therefore, the information providing device 100 is communicably connected to the accommodation terminal 400 provided by each accommodation company (and the OTA net agent server 300 from which information can be collected) via an appropriate network 10 such as the Internet.
また、上述の宿泊業者は、自宿泊施設の客室販売(宿泊プランの販売概念も含みうる)のため、上述のOTAすなわちネットエージェントと契約し、このネットエージェントに対して自宿泊施設の客室販売を委託しているものとする。 In addition, the above-mentioned lodging business makes a contract with the above-mentioned OTA, that is, a net agent, for the purpose of selling the rooms of its own lodging facility (which can also include the concept of selling accommodation plans), and sells the rooms of its own lodging facility to this net agent. shall be outsourced.
ただし、これはあくまでも説明のための一例であり、宿泊業者が自らの自社サイトで客室販売を行う形態も含むとしてよい。いずれにしても、販売サイトの種類に関して限定しない。 However, this is merely an example for explanation, and may include a form in which a lodging company sells rooms on its own website. In any case, the type of sales site is not limited.
また、本実施形態の情報提供装置100は、多くの宿泊業者が契約しているネットエージェントのWEBサイトでの、各宿泊業者の客室商品(すなわち宿泊施設)に関する情報として、販売実績(客室販売価格の値含む)、顧客からの口コミ情報、当該宿泊施設に関して各顧客による評価を集計した評価結果(例:星の数、5点満点での総合評価点数)、、といった情報を、一定時間毎にネットエージェントサーバ300から取得する。これら情報は、ネットエージェントサーバ300から取得する形態のみならず、各宿泊施設の宿泊施設端末400から取得するとしてもよい。 In addition, the information providing apparatus 100 of the present embodiment provides sales performance (room sales price (including the value of ), word-of-mouth information from customers, evaluation results that aggregate evaluations by each customer regarding the accommodation facility (e.g., number of stars, total evaluation score out of 5), etc., etc., at regular intervals Obtained from the net agent server 300 . These pieces of information may be acquired not only from the net agent server 300 but also from the accommodation terminal 400 of each accommodation facility.
また、上述のネットエージェントが運営するネットエージェントサーバ300は、各宿泊業者から委託された客室販売を行うWEBサイトを配信するサーバである。 Further, the net agent server 300 operated by the above-mentioned net agent is a server that distributes a WEB site that sells rooms entrusted by each lodging company.
このネットエージェントサーバ300は、客室販売先である顧客のユーザ端末200から、宿泊施設(やそのパッケージ商品等)の予約要求を受け付けて、当該宿泊施設に関する予約処理やそれに伴う在庫管理処理を実行する。また、当該宿泊施設に関する口コミ情報の投稿や、サービス、客室、立地、食事といった項目別の評価点数と、当該宿泊施設に関する総合点数などの評価の投稿を受け付ける。 This net agent server 300 receives a reservation request for an accommodation facility (and its package product, etc.) from the user terminal 200 of the customer who sells the guest rooms, and executes reservation processing for the accommodation facility and accompanying inventory management processing. . In addition, posts of word-of-mouth information about the accommodation facility, evaluation scores for each item such as service, guest room, location, and meals, and overall scores for the accommodation facility are accepted.
また、ネットエージェントサーバ300は、上述の評価の投稿について、その点数等を集計し、星の数や5段階評価などのシンプルな形でWEBサイトで公開する。 In addition, the net agent server 300 aggregates the scores and the like of the above-mentioned evaluation submissions and publishes them on the website in a simple form such as the number of stars or a 5-level evaluation.
なお、ユーザ端末200は、顧客の操作に応じて上述のWEBサイトにアクセスし、販売中の客室について予約要求すなわち購入処理等を行う端末である。具体的には、PC、スマートフォン、タブレット端末、などネットワーク通信可能な一般的な情報処理端末を想定する。こうしたユーザ端末200を操作する顧客としては、自身や家族の個人旅行/ビジネストリップを手配しようとする者の他、団体旅行を取り仕切る事業者などを想定できる。勿論、本実施形態では、上述のユーザ端末200を操作する顧客として、団体予約を行う者に着目し説明を行うものとする。 Note that the user terminal 200 is a terminal that accesses the above-described WEB site according to the customer's operation, and performs a reservation request, that is, a purchase process, etc. for a room that is on sale. Specifically, general information processing terminals capable of network communication, such as PCs, smartphones, and tablet terminals, are assumed. Customers who operate the user terminal 200 can be assumed to be those who want to arrange personal trips or business trips for themselves or their families, as well as business operators who manage group trips. Of course, in the present embodiment, description will be given focusing on a person who makes a group reservation as a customer who operates the user terminal 200 described above.
また、宿泊施設端末400は、宿泊業者が運用する端末で、情報提供装置100から、団体予約受諾可否に関する有用な情報提供を受け、これをディスプレイ等に出力させる端末となる。具体的には、PC、スマートフォン、タブレット端末、などネットワーク通信可能な一般的な情報処理端末を想定する。
---ハードウェア構成---Further, the accommodation facility terminal 400 is a terminal operated by an accommodation company, and serves as a terminal that receives useful information regarding acceptance or rejection of a group reservation from the information providing device 100 and outputs the information on a display or the like. Specifically, general information processing terminals capable of network communication, such as PCs, smartphones, and tablet terminals, are assumed.
--- Hardware configuration ---
また、本実施形態の情報提供装置100のハードウェア構成は、図2に示すごとくとなる。情報提供装置100は、記憶装置101、メモリ103、演算装置104、および、通信装置105、を少なくとも備える。
このうち記憶装置101は、SSD(Solid State Drive)やハードディスクドライブなど適宜な不揮発性記憶素子で構成される。
また、メモリ103は、RAMなど揮発性記憶素子で構成される。Further, the hardware configuration of the information providing apparatus 100 of this embodiment is as shown in FIG. The information providing device 100 includes at least a storage device 101 , a memory 103 , an arithmetic device 104 and a communication device 105 .
Among them, the storage device 101 is composed of an appropriate non-volatile storage element such as an SSD (Solid State Drive) or a hard disk drive.
Also, the memory 103 is composed of a volatile memory element such as a RAM.
また、演算装置104は、記憶装置101に保持されるプログラム102をメモリ103に読み出すなどして実行し装置自体の統括制御を行なうとともに各種判定、演算及び制御処理を行なうCPUである。 Arithmetic device 104 is a CPU that reads program 102 stored in storage device 101 into memory 103 and executes it, performs overall control of the device itself, and performs various determinations, calculations, and control processes.
また、通信装置105は、インターネットなどの適宜なネットワーク10と接続し、ユーザ端末200、ネットエージェントサーバ300、および宿泊施設端末400といった他装置との通信処理を担う、ネットワークインターフェイスカードを想定できる。 Also, the communication device 105 can be assumed to be a network interface card that connects to an appropriate network 10 such as the Internet and handles communication processing with other devices such as the user terminal 200 , the net agent server 300 and the accommodation facility terminal 400 .
なお、情報提供装置100は、上述の構成に加え、ユーザからのキー入力や音声入力を受け付けるキーボードやマウスなどの入力装置、演算装置104での処理データの表示を行うディスプレイ等の出力装置も備えるとしてよい。 In addition to the configuration described above, the information providing apparatus 100 also includes an input device such as a keyboard and a mouse for accepting key input and voice input from the user, and an output device such as a display for displaying data processed by the arithmetic unit 104. may be
なお、記憶装置101には、本実施形態の情報提供装置として必要な機能を実装する為のプログラム102において、機械学習エンジン110を少なくとも具備している。この機械学習エンジン110の詳細については後述する。 Note that the storage device 101 has at least a machine learning engine 110 in the program 102 for implementing the functions necessary for the information providing device of this embodiment. The details of this machine learning engine 110 will be described later.
また、記憶装置101は、上述のプログラム102に加えて、履歴DB125および評価情報DB126が少なくとも記憶されている。ただし、履歴DB125および評価情報DB126の詳細については後述する。
---データ構造例---
続いて、本実施形態の情報提供装置100が用いるデータベースについて説明する。図3に、本実施形態における履歴DB125の一例を示す。
履歴DB125は、各宿泊施設に関する所定期間ごとの販売実績を蓄積したデータベースである。In addition to the program 102 described above, the storage device 101 also stores at least a history DB 125 and an evaluation information DB 126 . Details of the history DB 125 and the evaluation information DB 126 will be described later.
--- Data structure example ---
Next, the database used by the information providing apparatus 100 of this embodiment will be described. FIG. 3 shows an example of the history DB 125 in this embodiment.
The history DB 125 is a database that accumulates sales results for each predetermined period regarding each accommodation facility.
そのデータ構造は、各案件を一意に特定する案件ID、当該案件で対象となった宿泊施設を示す施設ID、予約の受付時期、対象時期(宿泊時期)、予約受諾の可否、販売単価(=予約要求が示す客室販売価格)、販売額、宿泊者属性(団体/個人、国籍、人数、代表者、取扱エージェントなど)、といったデータを対応付けたレコードの集合体である。 The data structure includes a project ID that uniquely identifies each project, a facility ID that indicates the accommodation facility that is the target of the project, the reservation acceptance period, the target period (accommodation period), whether the reservation is accepted, the sales unit price (= It is a set of records in which data such as room sales price indicated in the reservation request), sales amount, lodger attributes (group/individual, nationality, number of people, representative, handling agent, etc.) are associated.
また、図4に、本実施形態における評価情報DB126の一例を示す。本実施形態における評価情報DB126は、各宿泊施設に関して上述のネットエージェントサーバ300のWEBサイトで各顧客から取得し集計した評価結果を蓄積したデータベースである。 Also, FIG. 4 shows an example of the evaluation information DB 126 in this embodiment. The evaluation information DB 126 in this embodiment is a database in which evaluation results acquired from each customer and aggregated on the website of the above-mentioned net agent server 300 regarding each accommodation facility are accumulated.
そのデータ構造は、各宿泊施設を一意に特定する施設IDをキーとして、評価対象期間、総合点数、項目別(例:サービス、客室、立地、食事)の評価点数、といったデータを対応付けたレコードの集合体である。
---フロー例---The data structure is a record that associates data such as the evaluation period, total score, and evaluation score for each item (e.g. service, guest room, location, meal) with the facility ID that uniquely identifies each accommodation facility as a key. is a collection of
--- Flow example ---
以下、本実施形態における情報提供方法の実際手順について図に基づき説明する。以下で説明する情報提供方法に対応する各種動作は、情報提供装置100がメモリ等に読み出して実行するプログラムによって実現される。そして、このプログラムは、以下に説明される各種の動作を行うためのコードから構成されている。 The actual procedure of the information providing method according to this embodiment will be described below with reference to the drawings. Various operations corresponding to the information providing method described below are realized by a program that the information providing apparatus 100 reads out to a memory or the like and executes. This program is composed of codes for performing various operations described below.
図5は、本実施形態における情報提供方法のフロー例を示す図である。この場合、情報提供装置100は、まず、団体予約の情報(団体予約の要求)を、ユーザ端末200またはネットエージェントサーバ300から受信するか、或いは、自身の記憶装置101の履歴DB125から取得する(s10)。 FIG. 5 is a diagram showing a flow example of an information providing method according to this embodiment. In this case, the information providing apparatus 100 first receives group reservation information (group reservation request) from the user terminal 200 or the net agent server 300, or acquires it from the history DB 125 of its own storage device 101 ( s10).
続いて、情報提供装置100は、上述のs10で得た団体予約の情報が示す宿泊時期(履歴DB125のレコードにおける“対象時期”)と同一時期の過去に関する、当該宿泊施設に関する予約推移の情報を、履歴DB125から抽出する(s11)。 Subsequently, the information providing apparatus 100 provides information on the reservation transition of the accommodation facility regarding the past at the same time as the accommodation period indicated by the group reservation information obtained in the above s10 (“target period” in the record of the history DB 125). , is extracted from the history DB 125 (s11).
この場合、情報提供装置100は、施設ID(団体予約の対象となった宿泊施設のID)と、該当団体予約の要求の受付時期および該当宿泊時期の各値である年月日のうち例えば月日とをキーに、履歴DB125にてレコードを検索する。この結果、予約受付時期から宿泊時期までの間に当該宿泊施設に関して受けた予約案件のレコードが抽出できる。 In this case, the information providing apparatus 100 selects the facility ID (the ID of the accommodation facility for which the group reservation was made), the date when the request for the group reservation was received, and the corresponding accommodation period. A record is searched for in the history DB 125 using the date as a key. As a result, it is possible to extract the records of the reservations received for the accommodation facility during the period from the reservation acceptance time to the lodging time.
そして、情報提供装置100は、上記のごとく抽出したレコードから、いわゆるブッキングカーブを生成する。こうしたブッキングカーブの生成手法自体については既存技術を適宜に用いるものとする。このブッキングカーブの生成が、予約推移の情報の抽出にあたる。 Then, the information providing apparatus 100 generates a so-called booking curve from the records extracted as described above. For the method of generating such a booking curve itself, existing technology shall be used as appropriate. The generation of this booking curve corresponds to the extraction of reservation transition information.
続いて、情報提供装置100は、上述のs11で得た予約推移の情報すなわちブッキングカーブに基づき、団体予約の受諾の可否別の客室販売状況の推移を所定アルゴリズムにより予測する(s12)。 Subsequently, the information providing apparatus 100 predicts, by a predetermined algorithm, the transition of the room sales status for each group reservation, based on the reservation transition information obtained in s11, that is, the booking curve (s12).
本実施形態における上述のアルゴリズムは、特に限定しないが、一例として機械学習エンジン110を想定する。この場合の機械学習エンジン110は、種々の時期(例:月や季節、国別の休暇シーズンなど)における、該当宿泊施設に対する予約とその予約の種別(個人/団体)、受諾可否、の各値を学習データとして、或る団体予約を受諾した場合と拒否した場合とで客室販売状況の推移パターンを学習したものである。 The algorithm described above in the present embodiment assumes the machine learning engine 110 as an example, although not particularly limited. In this case, the machine learning engine 110 generates reservations for the accommodation facility, the type of reservation (individual/group), acceptability, and acceptability at various times (e.g., months, seasons, national holiday seasons, etc.). is used as learning data to learn the transition pattern of the room sales situation when a certain group reservation is accepted or rejected.
また、情報提供装置100は、s12の予測にて得た、受諾の可否別の客室販売状況の推移に基づき、今回の処理対象となる団体予約(s10で情報を得たもの)の受諾の可否別の宿泊施設での売り上げ合計額の予想値を算定する(s13)。 In addition, the information providing apparatus 100 determines whether or not the group reservation to be processed this time (information obtained in s10) can be accepted or not, based on the transition of the room sales status by acceptance or non-acceptance obtained in the prediction in s12. An expected total sales amount at another accommodation facility is calculated (s13).
この場合、情報提供装置100は、上述のブッキングカーブに基づき、受付時期に当該団体予約を受諾すなわち当該団体予約の分の客室在庫を削除した前提と、当該団体予約を拒否して客室在庫を維持した前提の2パターンで、算定を行う。 In this case, the information providing apparatus 100 accepts the group reservation at the time of reception, that is, deletes the guest room inventory for the group reservation, and rejects the group reservation to maintain the guest room inventory. Calculation is performed with two patterns of assumptions.
団体予約を受諾した前提での算定では、情報提供装置100は、当該団体予約に伴う販売額(販売単価に宿泊者属性が示す人数を乗算)と、受付時期から対象時期までの間に(団体予約分の客室在庫減を行った状態で)新たに受け入れられる別の予約とその販売額(ブッキングカーブが示す予約の累積数に、該当期間における予約1件あたりの宿泊人数の中央値や平均値と販売単価の中央値や平均値を乗算)を集計し、上述の予想値を算定する。 In the calculation on the premise that the group reservation is accepted, the information providing device 100 calculates the sales amount accompanying the group reservation (multiplying the sales unit price by the number of people indicated by the lodger attribute) and the period from the reception time to the target time (group Another reservation newly accepted and its sales amount (with the reduction in room inventory for the reservation) multiplied by the median or average unit selling price) to calculate the above-mentioned forecast value.
また、団体予約を拒否した前提での算定では、情報提供装置100は、当該団体予約に伴う販売額は算定に入れず、受付時期から対象時期までの間に(団体予約分の客室在庫減は無かったとして)新たに受け入れられる別の予約とその販売額(ブッキングカーブが示す予約の累積数に、該当期間における予約1件あたりの宿泊人数の中央値や平均値と販売単価の中央値や平均値を乗算)を集計し、上述の予想値を算定する。
勿論、こうした算定手法やその考え方は一例であって、他の手法(既に述べた機械学習エンジン110など)を適宜に採用してもよい。In addition, in the calculation on the premise that the group reservation is rejected, the information providing device 100 does not include the sales amount associated with the group reservation in the calculation, and during the period from the reception time to the target time Another reservation newly accepted and its sales amount (the cumulative number of reservations indicated by the booking curve, the median and average number of guests per reservation and the median and average sales unit price in the relevant period) multiplied values) to calculate the expected value above.
Of course, such a calculation method and its concept are only examples, and other methods (such as the already-described machine learning engine 110) may be adopted as appropriate.
また、情報提供装置100は、s13で当該団体予約の受諾可否別に算定した、当該宿泊施設での売り上げ合計額の予想値の情報(図6の画面600参照)を、上述の宿泊施設端末400に出力し(s14)、処理を終了する。 In addition, the information providing apparatus 100 sends the information (see screen 600 in FIG. 6) of the estimated total sales amount at the accommodation facility calculated for each acceptance or rejection of the group reservation in s13 to the accommodation facility terminal 400 described above. output (s14) and terminate the process.
図6で示すように、こうした情報の出力に際し、情報提供装置100は、当該団体予約を受諾した場合の売り上げ合計額の予想値が、当該団体予約を受諾しなかった場合の売り上げ合計額の予想値より小さい場合、その旨の情報601を明示するとすれば、当該宿泊施設のレベニューマネージャーにおける判断を支援しやすい。
<更なる形態の例1>As shown in FIG. 6, when outputting such information, the information providing device 100 changes the estimated value of the total sales amount when the group reservation is accepted to the estimated total sales amount when the group reservation is not accepted. If the value is smaller than the value, if the information 601 to that effect is clearly displayed, it is easy to support the judgment of the revenue manager of the accommodation facility.
<Further Form Example 1>
また、情報提供装置100は、団体予約を受諾する条件として、前記団体予約を受諾しなかった場合の前記客室販売状況の推移に基づく客室販売価格701(図7の画面700参照)を推定し、宿泊施設端末400に出力するとすれば好適である。この客室販売価格(客室販売単価)の推定は、例えば、上述のブッキングカーブに基づく予約件数で、s13で算定した売り上げ合計額の予想値を除算することで実行する。 In addition, as a condition for accepting a group reservation, the information providing device 100 estimates a room sales price 701 (see screen 700 in FIG. 7) based on the transition of the room sales situation when the group reservation is not accepted, It is preferable to output to the accommodation facility terminal 400 . This estimation of the room sales price (room unit sales price) is performed, for example, by dividing the expected total sales amount calculated in s13 by the number of reservations based on the above-described booking curve.
客室販売価格(客室販売単価)の推定は、機械学習エンジン110で行う形態も勿論採用できる。その場合、情報提供装置100は、履歴DB125で保持する所定期間分の情報が示す、所定の団体予約の問い合わせ時期と同一時期の過去における、当該宿泊施設の客室販売価格、他宿泊施設の客室販売価格、および当該宿泊施設の稼働率を学習データとして機械学習エンジン110に付与して機械学習を予め実行しておく。そして、検討対象の団体予約の情報を受信した時期、すなわち受付時期(問い合わせ時期)、当該受信の時点での他宿泊施設の客室販売価格、および当該宿泊施設の稼働率の各値を、機械学習エンジン110に入力し、客室販売価格の推定を行うこととなる。 It goes without saying that the machine learning engine 110 can also be used to estimate the room selling price (unit room selling price). In that case, the information providing apparatus 100 displays the room sales price of the accommodation facility and the room sales of other accommodation facilities in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB 125 Machine learning is executed in advance by giving the machine learning engine 110 the price and the occupancy rate of the accommodation facility as learning data. Then, the time when the group reservation information to be considered is received, that is, the reception time (inquiry time), the room sales price of other accommodation facilities at the time of receiving the information, and the occupancy rate of the accommodation facility, are machine-learned. This information is input to the engine 110 to estimate the room sales price.
なお、情報提供装置100は、上述の客室販売価格を、該当団体予約の受諾に際しての客室販売価格下限とし、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を下回る場合、当該団体予約を拒否すべきと判定し、その旨の情報801(図8の画面800参照)を出力すると更に好適である。勿論、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を上回る場合、当該団体予約を受諾すべきと判定し、その旨の情報を出力することとなる。
<更なる形態の例2>In addition, the information providing device 100 sets the above-mentioned room selling price as the lower limit of the room selling price when accepting the group reservation, and the requested amount of the room selling price indicated by the information of the group reservation is below the lower limit of the room selling price. In this case, it is more preferable to determine that the group reservation should be rejected and output information 801 to that effect (see screen 800 in FIG. 8). Of course, if the requested room sales price indicated by the group reservation information exceeds the minimum room sales price, it is determined that the group reservation should be accepted, and information to that effect is output.
<Further Form Example 2>
また、情報提供装置100は、機械学習エンジン110における機械学習に際し、過去において、所定の団体予約を上述の当該宿泊施設が拒否し他宿泊施設が受諾した場合の、当該宿泊施設の客室販売価格、他宿泊施設の客室販売価格、および当該宿泊施設の稼働率を学習データとした機械学習をさらに実行するとしてもよい。 In addition, when the information providing device 100 performs machine learning in the machine learning engine 110, in the past, when the above-mentioned accommodation facility refuses a predetermined group reservation and another accommodation facility accepts, the room sales price of the accommodation facility, Machine learning may be further performed using the room sales prices of other accommodation facilities and the occupancy rates of the accommodation facilities as learning data.
なお、学習データとして与える情報のうち、所定の団体予約を上述の当該宿泊施設が拒否し他宿泊施設が受諾した場合の情報については、履歴DB125における各レコードの「施設ID」欄の値は異なるものの、「宿泊者属性」欄の値が同一のレコードペアで、「予約受諾の可否」欄が一方は「n」(すなわち拒否)、他方は「y」(すなわち受諾)、というレコードを特定するものとする。つまり、或る団体予約が一方の宿泊施設で拒否され、他方の宿泊施設で受諾されたレコードを特定するのである。 Among the information given as learning data, the value of the "facility ID" column of each record in the history DB 125 is different for the information when the above-mentioned accommodation facility refuses a predetermined group reservation and another accommodation facility accepts it. However, in the record pair with the same value in the ``guest attribute'' column, the ``reservation acceptance availability'' column identifies records where one is ``n'' (i.e., rejection) and the other is ``y'' (i.e., acceptance). shall be That is, it identifies records in which a group reservation was rejected at one accommodation and accepted at another.
また、その場合、情報提供装置100は、検討対象の団体予約の受付時期(問い合わせ時期)、当該受付の時点での他宿泊施設の客室販売価格、および当該宿泊施設の稼働率を、機械学習エンジン110に入力し、当該団体予約の受諾可否に応じて異なる客室販売価格の推定を行う。この場合、他宿泊施設としては、評価情報DB127における総合点数が所定範囲で近しいもの、すなわち競合となる宿泊施設を処理対象として予め特定しておくとすれば好適である。 In that case, the information providing device 100 receives the group reservation to be considered (inquiry time), the room sales price of other accommodation facilities at the time of the reception, and the occupancy rate of the accommodation facility. 110 to estimate different room sales prices depending on whether the group reservation is accepted or not. In this case, as the other accommodation facilities, it is preferable to specify in advance those accommodation facilities that have similar overall scores in the evaluation information DB 127 within a predetermined range, ie, competing accommodation facilities, as processing targets.
こうして推定した客室販売価格は、結果として宿泊施設間で拒否から受諾となった団体予約が、自宿泊施設から他の競合宿泊施設に取り込まれた場合すなわち自宿泊施設が当該団体予約を断った場合に、同日の需要が該当地域全体で高まる変化に由来した販売価格アップ(による増収予測)ないしダウンを、示唆するものとなりうる。 The room sales price estimated in this way will not be calculated if a group reservation that has changed from refusal to acceptance between lodging facilities as a result is taken from the lodging facility to another competing lodging facility, that is, if the lodging facility refuses the group reservation. In addition, it can suggest an increase (expected sales increase) or decrease in sales prices due to changes in demand on the same day that increase throughout the relevant region.
以上、本発明を実施するための最良の形態などについて具体的に説明したが、本発明はこれに限定されるものではなく、その要旨を逸脱しない範囲で種々変更可能である。 Although the best mode for carrying out the present invention has been specifically described above, the present invention is not limited to this, and can be variously modified without departing from the scope of the invention.
こうした本実施形態によれば、団体客の予約受入の可否を、当該宿泊施設における収益面を踏まえつつ、的確に判断し、客室販売の機会増大とそれに伴う収益性向上を図ることが可能となる。 According to this embodiment, it is possible to accurately determine whether or not to accept reservations from groups of guests while taking into account the profitability of the accommodation facility, thereby increasing opportunities for room sales and improving profitability accordingly. .
10 ネットワーク
100 情報提供装置
101 記憶装置
102 プログラム
103 メモリ
104 演算装置
105 通信装置
110 機械学習エンジン
125 履歴DB
126 評価情報DB
200 ユーザ端末
300 ネットエージェントサーバ
400 宿泊施設端末10 Network 100 Information Providing Device 101 Storage Device 102 Program 103 Memory 104 Arithmetic Device 105 Communication Device 110 Machine Learning Engine 125 History DB
126 Evaluation information DB
200 User terminal 300 Net agent server 400 Accommodation facility terminal
Claims (12)
団体予約の情報を所定装置から受信し、当該団体予約の情報が示す宿泊時期と同一時期の過去に関する予約推移の情報を前記履歴DBから抽出し、当該予約推移の情報に基づき、前記団体予約の受諾の可否別の客室販売状況の推移を所定アルゴリズムにより予測する処理と、前記予測にて得た前記受諾の可否別の客室販売状況の推移に基づき、前記団体予約の受諾の可否別の前記宿泊施設での売り上げ合計額の予想値を算定する処理と、前記予想値の情報を所定の端末に出力する処理と、を実行する演算装置と、
を含むことを特徴とする情報提供装置。A storage device that holds a history DB containing information on past room sales at accommodation facilities;
Receiving group reservation information from a predetermined device, extracting from the history DB information on reservation transitions in the past at the same period as the lodging period indicated by the group reservation information, and based on the reservation transition information, based on the group reservation information A process of predicting, by a predetermined algorithm, changes in room sales status by acceptance or non-acceptance, and said lodging by acceptance or non-acceptance of said group reservation based on the transition of room sales status by acceptance obtained by said prediction. A computing device that executes a process of calculating an expected value of the total sales amount at the facility and a process of outputting the information of the expected value to a predetermined terminal;
An information providing device comprising:
前記団体予約を受諾した場合の売り上げ合計額の予想値が、当該団体予約を受諾しなかった場合の売り上げ合計額の予想値より小さい場合、その旨を前記端末に出力するものである、
ことを特徴とする請求項1に記載の情報提供装置。The computing device is
If the expected total sales amount when the group reservation is accepted is smaller than the expected total sales amount when the group reservation is not accepted, that fact is output to the terminal.
2. An information providing apparatus according to claim 1, characterized by:
前記団体予約を受諾する条件として、前記団体予約を受諾しなかった場合の前記客室販売状況の推移に基づく客室販売価格を推定し、前記端末に出力するものである、
ことを特徴とする請求項2に記載の情報提供装置。The computing device is
As a condition for accepting the group reservation, a room sales price is estimated based on the transition of the room sales situation when the group reservation is not accepted, and is output to the terminal.
3. The information providing apparatus according to claim 2, characterized by:
前記客室販売価格を前記団体予約の受諾に際しての客室販売価格下限とし、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を下回る場合、当該団体予約を拒否すべきと判定し、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を上回る場合、当該団体予約を受諾すべきと判定し、前記いずれかの判定の結果を前記端末に出力するものである、
ことを特徴とする請求項3に記載の情報提供装置。The computing device is
The above-mentioned room sales price shall be the minimum room sales price when accepting the said group reservation, and if the requested amount of the room sales price indicated by the group reservation information is below the said minimum room sales price, the group reservation shall be refused. If the requested room sales price indicated by the group reservation information exceeds the minimum room sales price, it is determined that the group reservation should be accepted, and the result of any of the above judgments is output to the terminal. is to
4. The information providing device according to claim 3, characterized by:
前記履歴DBで保持する所定期間分の前記情報が示す、所定の団体予約の問い合わせ時期と同一時期の過去における、前記宿泊施設の客室販売価格、他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習を予め実行しておき、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、前記客室販売価格の推定を行うものである、
ことを特徴とする請求項3に記載の情報提供装置。The computing device is
The room sales price of the accommodation facility, the room sales price of other accommodation facilities, and the price of the accommodation facility in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB Machine learning with the occupancy rate as input is performed in advance, and the timing of the group reservation inquiry that received the information, the room sales price of other accommodation facilities at the time of the reception, and the occupancy rate of the accommodation facility , which estimates the room sales price,
4. The information providing device according to claim 3, characterized by:
前記機械学習に際し、過去において、所定の団体予約を前記宿泊施設が拒否し他宿泊施設が受諾した場合の、前記宿泊施設の客室販売価格、前記他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習をさらに実行し、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、当該団体予約の受諾可否に応じて異なる前記客室販売価格の推定を行うものである、
ことを特徴とする請求項5に記載の情報提供装置。The computing device is
In the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and another accommodation facility accepted it, the room sales price of the accommodation facility, the room sales price of the other accommodation facility, and the accommodation facility Machine learning is further performed with the occupancy rate as input, and the time of inquiry for the group reservation that received the information, the room sales price of other accommodation facilities at the time of receiving the information, and the occupancy rate of the accommodation facility. Estimates the room sales price that varies depending on whether group reservations are accepted,
6. The information providing device according to claim 5, characterized by:
宿泊施設における過去の客室販売に関する情報を含む履歴DBを保持する記憶装置を備え、
団体予約の情報を所定装置から受信し、当該団体予約の情報が示す宿泊時期と同一時期の過去に関する予約推移の情報を前記履歴DBから抽出し、当該予約推移の情報に基づき、前記団体予約の受諾の可否別の客室販売状況の推移を所定アルゴリズムにより予測する処理と、前記予測にて得た前記受諾の可否別の客室販売状況の推移に基づき、前記団体予約の受諾の可否別の前記宿泊施設での売り上げ合計額の予想値を算定する処理と、前記予想値の情報を所定の端末に出力する処理と、
を実行することを特徴とする情報提供方法。The information processing device
Equipped with a storage device that holds a history DB containing information on past room sales at the accommodation facility,
Receiving group reservation information from a predetermined device, extracting from the history DB information on reservation transitions in the past at the same period as the lodging period indicated by the group reservation information, and based on the reservation transition information, based on the group reservation information A process of predicting, by a predetermined algorithm, changes in room sales status by acceptance or non-acceptance, and said lodging by acceptance or non-acceptance of said group reservation based on the transition of room sales status by acceptance obtained by said prediction. A process of calculating an expected value of the total sales amount at the facility, and a process of outputting the information of the expected value to a predetermined terminal;
An information provision method characterized by executing
前記団体予約を受諾した場合の売り上げ合計額の予想値が、当該団体予約を受諾しなかった場合の売り上げ合計額の予想値より小さい場合、その旨を前記端末に出力する、
ことを特徴とする請求項7に記載の情報提供方法。The information processing device
If the expected total sales amount when the group reservation is accepted is smaller than the expected total sales amount when the group reservation is not accepted, outputting that fact to the terminal;
8. The information providing method according to claim 7, characterized by:
前記団体予約を受諾する条件として、前記団体予約を受諾しなかった場合の前記客室販売状況の推移に基づく客室販売価格を推定し、前記端末に出力する、
ことを特徴とする請求項8に記載の情報提供方法。The information processing device
As a condition for accepting the group reservation, estimate a room sales price based on the transition of the room sales situation when the group reservation is not accepted, and output to the terminal;
9. The information providing method according to claim 8, characterized by:
前記客室販売価格を前記団体予約の受諾に際しての客室販売価格下限とし、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を下回る場合、当該団体予約を拒否すべきと判定し、当該団体予約の情報が示す客室販売価格の要求額が、当該客室販売価格下限を上回る場合、当該団体予約を受諾すべきと判定し、前記いずれかの判定の結果を前記端末に出力する、
ことを特徴とする請求項9に記載の情報提供方法。The information processing device
The above-mentioned room sales price shall be the minimum room sales price when accepting the said group reservation, and if the requested amount of the room sales price indicated by the group reservation information is below the said minimum room sales price, the group reservation shall be refused. If the requested room sales price indicated by the group reservation information exceeds the minimum room sales price, it is determined that the group reservation should be accepted, and the result of any of the above judgments is output to the terminal. do,
10. The information providing method according to claim 9, characterized by:
前記履歴DBで保持する所定期間分の前記情報が示す、所定の団体予約の問い合わせ時期と同一時期の過去における、前記宿泊施設の客室販売価格、他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習を予め実行しておき、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、前記客室販売価格の推定を行う、
ことを特徴とする請求項9に記載の情報提供方法。The information processing device
The room sales price of the accommodation facility, the room sales price of other accommodation facilities, and the price of the accommodation facility in the past at the same time as the predetermined group reservation inquiry time indicated by the information for the predetermined period held in the history DB Machine learning with the occupancy rate as input is performed in advance, and the timing of the group reservation inquiry that received the information, the room sales price of other accommodation facilities at the time of the reception, and the occupancy rate of the accommodation facility , estimating the room sales price;
10. The information providing method according to claim 9, characterized by:
前記機械学習に際し、過去において、所定の団体予約を前記宿泊施設が拒否し他宿泊施設が受諾した場合の、前記宿泊施設の客室販売価格、前記他宿泊施設の客室販売価格、および前記宿泊施設の稼働率を入力とした機械学習をさらに実行し、前記情報を受信した団体予約の問い合わせ時期、前記受信の時点での他宿泊施設の客室販売価格、および前記宿泊施設の稼働率に応じて、当該団体予約の受諾可否に応じて異なる前記客室販売価格の推定を行う、
ことを特徴とする請求項11に記載の情報提供方法。The information processing device
In the machine learning, in the past, when the accommodation facility refused a predetermined group reservation and another accommodation facility accepted it, the room sales price of the accommodation facility, the room sales price of the other accommodation facility, and the accommodation facility Machine learning is further performed with the occupancy rate as input, and the time of inquiry for the group reservation that received the information, the room sales price of other accommodation facilities at the time of receiving the information, and the occupancy rate of the accommodation facility. estimating a different room sales price depending on the acceptance or rejection of group bookings;
12. The information providing method according to claim 11, characterized by:
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