A computer-implemented apparatus and method for managing over-subscribed amenities

Abstract

A computer-implemented apparatus and method embedded in, or communicably coupled to, an on-line resource reservation system for allocating resources from a defined available resource inventory to users requesting said resources, said apparatus being configured to enable allocation of a specified resource to a specified user in the event that that specified resource is not, or no longer, available in said defined resource inventory, the apparatus comprising a processor and a memory, and being configured, under control of the processor, to execute instructions stored in the memory to: - receive, at an input of said computer-implemented apparatus, reservation request data defining a reservation request received by a said on-line resource reservation system that cannot be fulfilled thereby according to the current available resource inventory; - generate, using metrics specifically associated with resources and reservations, a selected condition, weighted probability data defining data indicative of whether or not a reservation request should be attempted to be fulfilled; - if so, map said weighted probability data onto said reservation request data to generate message data to be transmitted to said resource inventory owner and, if said reservation request can be accommodated under said selected conditions; - if so, cause to be presented, via an output of said apparatus, offer data, offering said user an opportunity to have the reservation request fulfilled under certain selectable conditions; - if a user selects an acceptable one or more of said selectable conditions, direct said user to an on-line payment facility to allow them to pay at least an additional fee for said reservation request to be fulfilled under the selected conditions; - once payment has been completed, generate message data and transmit said message data to a respective establishment, via said on-line resource reservation system, informing them that said reservation request has been completed, together with any conditions attached thereto.

Description

A COMPUTER-IMPLEMENTED APPARATUS AND METHOD FOR MANAGING OVER-SUBSCRIBED AMENITIES Field of the Invention This invention relates generally to a computer-implemented apparatus and method, configured to be embedded into, or communicably coupled to, an online booking system, for managing over-subscribed amenities, such as restaurant reservations, flights, hotel stays, golf (and other sports) games, rental cars, resort / spa reservations and attractions. The present invention is not necessarily intended to be limited in relation to the amenities in question, as the training data utilized to implement the apparatus and method can be readily adapted to correspond to whichever amenity is being offered by an on-line booking system. Background of the Invention Online booking systems are well known and widely used by consumers for makingreservations / bookings in a number of amenity industries, including (but not limited to)restaurants, hotels, airlines, rental cars, golf courses, events, tourist attractions, etc. In general, providers offer a certain amount of ‘inventory’ data corresponding to availability to the online booking system and the online booking system allows users to purchase available event tickets, reserve available restaurant tables or spaces for other leisure activities, according to the current availability defined by the live inventory data. In some such systems, the facility is provided for users to join waiting or cancellationssections for their reservation request if their request cannot be met at the time of firstbooking. Additional modules or add-ons have been proposed for managing such waiting and cancellations lists, with users usually being offered any availability, arising as a result of a cancellation, that matches their request data, on a first-come-first served basis, with a time limit imposed for accepting or rejecting the offered availability before it is offered to the next consumer on the waiting list. However, there are many circumstances under which additional availability to meet a request could, in theory, be found by an establishment or organisation if the opportunityto contact them directly was available, but even then, the person who answers the call may only have access to the basic inventory data and, therefore, may not be in any better position to assist the potential customer. There are also many potential customers that would be prepared to pay a premium for reservations that might otherwise be unavailable. Consumers can, of course, utilize third party re-sellers (or purchase a ticket or reservation directly from other consumers via online social media platforms, for example), but this can lead, not just to a disproportionate financial mark-up on the original price, but also leave consumers open to the risk of fraud, theft, warranties and safety concerns. Accordingly, aspects of the invention seek to address at least one or more of these issues. Statements of Invention According to an exemplary embodiment of the invention, there is provided a computer- implemented apparatus embedded in, or communicably coupled to, an on-line resourcereservation system for allocating resources from a defined available resource inventoryto users requesting said resources, said apparatus being configured to enable allocation of a specified resource to a specified user in the event that that specified resource isnot, or no longer, available in said defined resource inventory, the apparatus comprisinga processor and a memory, and being configured, under control of the processor, to execute instructions stored in the memory to: -receive, at an input of said computer-implemented apparatus, reservationrequest data defining a reservation request received by a said on-line resource reservation system that cannot be fulfilled thereby according to the current available resource inventory; -generate, using metrics specifically associated with resources and reservations,a selected condition, weighted probability data defining data indicative of whetheror not a reservation request should be attempted to be fulfilled;- if so, map said weighted probability data onto said reservation request data togenerate message data to be transmitted to said resource inventory owner and, ifsaid reservation request can be accommodated under said selected conditions; -if so, cause to be presented, via an output of said apparatus, offer data, offeringsaid user an opportunity to have the reservation request fulfilled under certain selectable conditions; -if a user selects an acceptable one or more of said selectable conditions, directsaid user to an on-line payment facility to allow them to pay at least an additionalfee for said reservation request to be fulfilled under the selected conditions; -once payment has been completed, generate message data and transmit saidmessage data to a respective establishment, via said on-line resource reservation system, informing them that said reservation request has been completed, together with any conditions attached thereto. In an exemplary embodiment, weighted probability data is compared with apredetermined threshold to provide indicator data indicative of whether or not areservation request should be attempted to be fulfilled. In this case, the method furthermay further include mapping said indicator data to said reservation request to generatesaid offer data. Optionally, the metrics used to generate the weighted probability data may include user profile and / or other user-specific data. Advantageously, the weighted probability data may include data representative of one or more effects on other resource users if the reservation request is granted. These and other aspects of the invention will be apparent from the following detailed description. Brief Description of the Drawings Embodiments of the invention will now be described, by way of examples only, and with reference to the accompanying drawings, in which: Figure 1 is a schematic block diagram illustrating an exemplary booking / reservation server apparatus for receiving resource requests and managing resource requestsdeemed to be unavailable in accordance with inventory data held in a conventional on-line booking system;Figure 2 is a schematic flow diagram illustrating steps in a method according to anexemplary embodiment of the invention; andFigures 3 and 4 depict a process flow chart for an example online reservation platform.Detailed DescriptionReferring to Figure 1 of the drawings, an on-line booking / reservation system 100 isillustrated. Booking / reservation system 100 comprises at least a booking / reservationserver apparatus 102 and a user communications device 104. These devices areconnected in the communications network 108 (for example the Internet) throughrespective communications links 110, 112, implementing, for example, internetcommunications protocols. Communications device 104 may be able to communicatethrough other communications networks, such as public switched telephone networks (PSTN networks), including mobile cellular communications networks, but these are omitted from Figure 1 for the sake of clarity.Booking / reservation server apparatus 102 may be a single server as illustratedschematically in Figure 1, or have the functionality performed by the server apparatus 102 distributed across multiple server components. In the example of Figure 1, thebooking / reservation server apparatus 102 may comprise a number of individualcomponents including, but not limited to, one or more microprocessors 116, a memory 118 (e.g. a volatile memory such as a RAM) for the loading of executable instructions 120, the executable instructions defining the functionality the server apparatus 102carries out under control of the processor 116. Booking / reservation server apparatus102 also comprises an input / output module 122 allowing the server to communicate over the communications network 108. User interface 124 is provided for user control and may comprise, for example, computing peripheral devices such as displaymonitors, computer keyboards and the like. The booking / reservation server apparatus102 also comprises a database 126. In this embodiment, database 126 is part of thebooking / reservation server apparatus 102, however, it should be appreciated thatdatabase 126 can be separated from the booking / reservation server apparatus 102 anddatabase 126 may be connected to the booking / reservation server apparatus 102 viacommunications network 108 or via another communications link (not shown). The booking / reservation server 102 may include an admin manager module 127, the purpose of which will become readily apparent hereinafter.A user communications device 104 may comprise a number of individual componentsincluding, but not limited to, one or more microprocessors 128, a memory 130 (e.g. a volatile memory such as a RAM) for the loading of executable instructions 132, the executable instructions defining the functionality the user communications device 104 carries out under control of the processor 128. User communications device 104 also comprises an input / output module 134 allowing the user communications device 104 to communicate over the communications network 108. User interface 136 is provided for user control. If the user communications device 104 is, say, a smart phone or tablet device, the user interface 136 will have a touch panel display as is prevalent in many smart phone and other handheld devices. Alternatively, if the user communications device is, say, a desktop or laptop computer, the user interface may have, for example, computing peripheral devices such as display monitors, computer keyboards and the like.Referring now additionally to Figure 2 of the drawings, at the start of an examplemethod, a consumer utilises their user communications device 104 to access an onlinebooking application at step 300 and, at step 302, enters the required criteria for thereservation / booking being sought (e.g. size of party, time, date, etc.). The online booking application, based on predetermined inventory data representative of availability of resources across an entire availability time frame, determines a response, at step 304, which either states that the reservation request can be met in the normal manner or it cannot be met. If the reservation request can be met in the normal manner, based on the above-referenced inventory data, then the process moves through the normal booking process defined by the specific booking / reservation system being used.However, if the booking / reservation system returns a negative result at step 304,indicating that the selected reservation request cannot be met, the user has the option to CONTACT INVENTORY ADMIN MANAGER via module 127 (see Figure 1).In response to selecting the CONTACT INVENTORY ADMIN MANAGER module 127,the user is presented, via their user communications device 104, one or more selectable criteria. Such criteria may, for example, be a selectable surcharge they are prepared to pay if their specific reservation request can be met, but may also include factors such asflexibility on time (e.g. + / - 15 minutes, + / - 30 minutes), and the present invention neednot necessarily be intended to be limited in this regard. The user selects, at step 306, their selectable criteria, comprising / including the amount extra that they are willing to pay for their specified reservation request to be granted. Utilizing predefined training data, specified data from the original reservation requestdata, the criteria selected by the user at step 306, and user data including, optionally,user profile data, the CONTACT INVENTORY ADMIN MANAGER module 127generates, at step 308, probability data defining the probability that the reservationrequest can be fulfilled, even if the selected criteria are met (i.e. the offered surcharge is paid). At step 310, the module 127 is configured to map the probability data onto the originalreservation request data and determines, for example by comparing the probability datawith a predetermined threshold, if there is any likelihood that the reservation request could be accommodated under the selected criteria. The result of this determination is transmitted to the CONTACT INVENTORY ADMIN MANAGER module 127. If no, the process ends. Although in some embodiments, there may be a facility whereby the user could receive a counter-offer indicating that the reservation request could be accommodated if a greater surcharge were to be paid, for example. If the determination at step 310 is yes, at step 312, the probability data and selected criteria data is transmitted to the establishment offering the reservations, and they a) make the required reservation within their own local booking system and b) send, atstep 314, a message (e.g. SMS message, email, push message or voicemail) to theuser providing details and / or a link to an on-line payment platform where they can pay the surcharge and secure their reservation.The user utilizes the link, at step 316, to make the payment.At step 318, when the establishment offering the reservations has received confirmation of payment, the booking is confirmed (again, for example, via SMS message, voicemail, email, push message, etc).; and the process ends.Thus, the example platform captures the consumer’s interest in inventory that isunavailable online. Artificial Intelligence is used to generate probability data that willhelp the consumer to understand the probability as to whether or not their platformrequest for unavailable inventory online will be approved to declined (subject to certain criteria). As the platform is used, the original training data will be refined and alsoenable the platform to train and educate consumers on how to increase the probabilityof accessing unavailable inventory online though the CONTACT INVENTORY ADMINMANAGER module 127. The example apparatus helps operators to receive consumerrequests for unavailable inventory and leverage operator customized and AI-drivenprobability analysis to predict and suggest whether a reservation request should, irrespectively, be approved or declined. Future AI-driven features may include the ability to train the establishments offering the inventory to highlight the key parametersor drivers that are essential to increase the customer experience within the reservationand service operations process. It may also be able to suggest how much inventorycould or should be set aside to optimize the probability of platform requests coming fromconsumers being fulfilled. It may be able to predict the consumer’s compliance abilityand capability to complete platform requests. In its simplest form, the probability datamay comprise a number between 0 and 1 which will represent a likelihood of theultimate response (for example, by comparing it with a predetermined threshold).Referring to Figures 3 and 4 of the drawings, an exemplary process for using anexample apparatus is illustrated and explained. In the following, the term INVENTORY refers to the availability of a reservation / booking according to a conventional on-line booking platform, and the term PLATFORM refers toan online booking platform including an example apparatus according to the invention. The term INVENTORY MANAGER refers to a module within the example apparatus that is accessible by the establishment / organisation offering the resources available for booking / reservation, and an INVENTORY MANAGER module is included therein, with which a user at such an establishment can interact.The process starts when the CONSUMER clicks on the PLATFORM with CONSUMER’spreferences, willingness to pay extra and any description so that it prompts in the ADMINIISTRATOR dashboard (available to view at the establishment offering the INVENTORY) to the specific INVENTORY MANAGER ADMINISTRATOR page. ADMINISTRATOR can see all the requested INVENTORY REQUESTS and approve / decline what they choose, with the approved CONSUMER / S being given a time tocomplete their transaction and engage directly with the ADMINISTRATOR to receive the INVENTORY.

[0018] Mobile Application Side:

[0019] When accessing the PLATFORM feature, there may be an additional tab withinthe CONSUMER portal so the CONSUMER can click on it and check the availability ofINVENTORY within the following categories.The INVENTORY categories may be as follows:Restaurants Resorts / Spas Golf Courses Entertainment / Events Attractions / Appointments Flights Cruises CarsMedical / Specialist appointments Hospitality / catering RecreationRetail – Products & ServicesOn the screen, there are four options: Where do you want to go?: We will display a list of inventory that are available on the platform. When do you want to go?: From this option, the CONSUMER can select a single date to see the availability. What time frame do you want to go?: The CONSUMER can select start time and endtime of preferred start time from this option. Participants: Number of participantsselected, e.g., 1, 2, 3, 4.,10, etc. As a result, it will display if the specific INVENTORY is available or not. If that specific INVENTORY is available, it will redirect to the regular INVENTORY platform to book and INVENTORY slot. If the INVENTORY is available as per request, it will display similar to the following kinds of examples:

[0038] Restaurant: https: / / www.opentable.com / neighborhood / fl / tampa-restaurants

[0039] Golf: https: / / www.tpctampabay.com / book-tee-times /

[0040] Hotel: https: / / www.fourseasons.com / orlando / accommodations / CONSUMER EXPERIENCEIf the INVENTORY is NOT AVAILABLE online, whether on our platform or the INVENTORY MANAGER booking platform / s, we will add the option to “REQUEST INVENTORY” so that the CONSUMER’s INVENTORY request will be shared with the ADMINISTRATOR of that specific INVENTORY HOLDER.When CONSUMER utilizes the PLATFORM, CONSUMER can add the cost thatCONSUMER is willing to pay up to and above the typical rate, to obtain INVENTORY within their desired preferences of CONSUMER. Example 1: Where CONSUMER offers a price to REQUEST INVENTORY. CATEGORY – CONSUMER is willing to pay $XXX to secure a table atINVENTORY HOLDER for XX on DATE and before XX:XX time. Restaurants – CONSUMER is willing to pay $250 to secure a table for 6 on12 / 17 / 2023 and before 18:30.

[0047] Example 2: Where CONSUMER offers a price above the regular rate to create INVENTORY. Golf Course: CONSUMER is willing to pay extra $XXX per participant to play at INVENTORY HOLDER before XX:XX on DATE. CONSUMER is willing to pay an extra $100 per participant to play at GOLF COURSE before 09:30AM on 12 / 17 / 2023. Hotel: CONSUMER is willing to pay extra $XXXX per INVENTORY ITEM to check in at INVENTORY HOLDER before XX:XX on DATE. Hotel: CONSUMER is willing to pay an extra $1000 per night to check in at INVENTORY HOLDER before 12:00 on 12 / 17 / 2023.These amounts offered by CONSUMER in addition to than the typical rate work asincentives to the ADMINISTRATOR to create inventory for the CONSUMER. In the ADMINISTRATOR view on the INVENTORY HOLDER side, there will be a demand panel where CONSUMER requests and notifications can found, that will be displayed in the ADMINSTRATOR’s list and / or source location view. Demand Options Functionality. From the ADMINISTRATOR panel, the ADMINISTRATOR can go to the requested INVENTORY LIST. The ADMINISTATOR will have three options: Where we added three buttons Approve / Create, Compromise / Suggest Alternatives and Close / Cancel.Once ADMINISTRATOR triggers Approves CONSUMER REQUEST, a notification will be sent (via voicemail, SMS, e-mail, or push notification with details of the INVENTORYoffer to the CONSUMER only. Upon receiving the notification, CONSUMER must acceptor reject it within a certain time period. Should ADMINISTRATOR approve CONSUMER request; The CONSUMER may receive a notification similar to this: INVENTORY MANAGER can provide INVENTORY to you! After accepting the CONSUMER notification, it will redirect the CONSUMER to the payment page and pay for INVENTORY. Once INVENTORY is paid for, a notification (via voicemail, SMS, e-mail, or push notification, etc.) will be sent to ADMINISTRATOR who can create INVENTORY to support the CONSUMER’s purchase / request and automatically create any following correspondence / confirmation. END PROCESS The decision as to whether or not the CONSUMER will be offered the INVENTORY by the ADMINISTRATOR is based on a weighted probability data that is generated utilizingtraining data specific to the resource associated with the original reservation request.An example of such training data provided below, in relation to restaurant reservations (note that, in the following, the term “squeez request” is used to denote a request fromthe CONSUMER to secure their selected reservation under certain selected criteria ifthat reservation request is not able to be fulfilled in the normal manner through the PLATFORM):Training The Model – Operator – Example for restaurantsWe must use the reservations, visits, and other information from these sites to forecast future restaurant visitor totals on a given date. The training data covers the dates from 1st Jan 2023 until 31st December 2023. The admin panel highlights certain holidays and dates which are excluded from the algorithms.Example of List of Days which are excluded:• New Year’s Eve• New Years’s Day• Christmas Eve• Christmas Day• Valentine’s Day• July 4th• Veteran’s Day• Memorial Sunday• Mother’s Day• Father’s Day• EasterThe test set covers the year to draw attention to seasonality. In Florida, it highlights a greater peak in reservation demand from the week after Thanksgiving to the week after Easter Sunday. The test set is split based on time and covers a chosen subset of the full-service dining restaurants. The data will request to identify the greatest amount of bookings associated to each day. It was identified that Saturday was the day with the greatest volume of reservation bookings. Friday was the 2nd greatest day and Sunday was 3rd. Thursday was 4th. Wednesday and Tuesday were the 5thand 6th. Monday is the lowest day for reservations.The hours of 6-7pm is the hour with the greatest reservation booking volume. This is followed by 7-8, 5-6.8-9, 4-5, 9-10pm.18:00 – 19:00: 37%19:00 – 20:00: 26%17:00 – 18:00: 22%85% of all reservations are seated within a three-hour period of17:00 – 20:00Over 50% of reservations are sat within 18:00 – 20:00, almost 2 / 3rds of all reservations.Therefore, the algorithm is trained to assume there is no availability of reservations online within the restaurant, and to highlight areas of high unavailability and / or increased demand for supply based on the seasonal reservation booking experience. The algorithm also identifies how far in advance reservations are made. In this case, it seems that over 50% of reservations are made within 24 hours of the reservationbooking time. Between 11:00 – 17:00, make up of over 50% (51.55%) of all thosebookings.From 17:00 – 19:00. 10.45% plus 7.97% =Almost 20% - 18.42% booked between (24%booked including 19:00 – 20:00.Therefore: The algorithm is trained to know based on when the reservation is made, it can anticipate what reservation availability which could be accommodated, and also whether the reservation offer is at a time where the reservation may be filled with or without any additional squeez requests or demand.Training The Model – ConsumerConsumer adds request for reservation availability online. Platform sends request to a third party availability provider. When it shows unavailability, our AI platform gathers the information around the unavailable request.An example of the key data fields our AI platform collects are: Consumer Full Name, Time When Reservation Query Was Made Reservation Info: Name of Requested Operator Reservation Info: Date of Reservation Reservation Info: No. of People Reservation Info: Reservation Time Window Example: Chris Ogboke Monday 5th February at 12:30pm ET. Columbia Restaurant Friday 9th February 6 people17:45 EST – 18:45 EST (This would auto-populate four proposals requests)Four proposals would be: 17:45, 18:00, 18:15 & 18:30. This data is then sent with the amount to the back end for the operator. Probably rates of successful approval has a number of data points which are reviewed: As time of reservation is also a key indicator of the squeez request, the information on the consumer is also very beneficiary, such as, their previous history of completingsqueez requests, affinity to the restaurant or sister / affiliate restaurants, and also theimpact of the squeez amount offered to the average $ amount to operator per person. These criteria are scored with a total weighing average of 100%, which can be a toggle set by the operator. Example:• Squeez History – 20%• Consumer Affiliations – 20%• Squeez Amount – 50%• Time of Request – 10%The probability of requests approved is determined by several factors, which vary by state, including but not limited to, dining behaviors. In some states, your dining data may be used by platform for purposes of rating, through participation in platform. Whilst in some states the probably rating could decrease with poorer dining experiences, better diners will have greater probability with platform. As we review the probability of the consumer platform request being approved, the platform also reviews and assesses if there is a high probability of approving the request, it helps propose or determine HOW, or WHY the platform request is possiblefor the inventory to be created to support the platform request.An example of inputs which help the restaurants operator toggle are:• Total inventory – 20%• Target time per table size – 20%• Wait time per reservation – 10%• Consumer experience – 20%• Opportunity to Wow Consumer / $ Amount of Request – 20%• Time Window between Request & Reality – 10%If request is approved, total inventory used at time will be? Less than 100% capacity? Y or NoLess than 80% Occupancy – 1.590% - 100% Occupancy = 1.0100% - 110% Occupancy = 0.5110 – 115% Occupancy = 0.Should total inventory exceed 15%, the likelihood of request declined due to lack ofspace is high. If above 100% capacity, will the target time increase by X percent? Not to exceed 15%. If approved, what will the wait time per reservation become? Wait time RulesZero – 5 minutes = 15 mins – 10 minutes = 0.5Above 10 minutes = 0 Note: Should the request increase wait times for existing users by 10 minutes, there is a greater probability that the request will be declined. This weighted average highlights that if there is a way that the inventory can be adapted without too much risk to target time per table size or consumer experience, the platform request has a higher probability to be approved, as it exceeds 0.5 <1, which gives agreater probability of “wowing” the customer - particularly if wait time is not anticipatedto be a greater risk to other consumers.Total Consumer Experience – If any change to theThere would be a number of factors that feed into here: Restaurant: Max Capacity Restaurant: % Occupancy Restaurant: Servers to Customers Ratio Restaurant: Wait Time (To Be Seated) Restaurant: Wait Time (To Be Served Drinks)Restaurant: Wait Time (To Be Served Appetizers) Restaurant: Wait Time (To Be Served Mains) Restaurant: Wait Time (To Be Served Desserts) Restaurant: Wait Time (To Receive & {Pay for Check)Opportunity to “Wow” Customer• 1st Time Customer (if Yes, 1.0) If no, 0.5• Occasion of Visit (If annual event – 0.5) If occasion, is random, 1.0• New Customer (Y or No) If Yes, 1.0, if no, 0.75• Customer of Affiliate Restaurant (If Yes, 1, if no, 0.5)• Customer Location (Local, Out of City, Out of State,) IF Local, 1.0. If out of City,in State 0.75, If Out of State, 0.5.• Corporate Customer (If Yes, 1.0), If No, 0.• Frequent Platform User (If Yes, 1.0) –More than once per week: 1.Weekly 0.75 Bi-weekly 0.5 Monthly – 0.25 Less than Monthly – 0.• $ Amount of Request –If this is number is greater than 50% of the average $ per person, then above 1. If this is number is greater than 25% of the average $ per person, then above 0.5<1. If this is number is lower than 25% of the average $ per person, then above 0.25<0.5. If this is number is similar to the average $ per person, then 0<0.25.The example platform feeds this data to the operator platform to give a number onwhether projected customers is a customer that they would like to wow. In other words,the resultant probability data is compared with a predetermined threshold to determine whether or not to offer the additional INVENTORY to the CONSUMER. It will be apparent to a person skilled in the art as to how to apply the above training data theory to other types of reservation request, and the above example is in no way intended to limit the functionality of the admin manager module 127 described above. The same theory, considerations, weighting decisions, etc. could be applied to any number of amenities. It will also be apparent to person skilled in the art, from the foregoing description, that modifications and variations can be made to the described embodiments, without departing from the scope of the invention as defined by the appended claims.

Claims

CLAIMS1. A computer-implemented apparatus embedded in, or communicably coupled to,an on-line resource reservation system for allocating resources from a defined available resource inventory to users requesting said resources, said apparatus being configured to enable allocation of a specified resource to a specified user in the event that that specified resource is not, or no longer, available in saiddefined resource inventory, the apparatus comprising a processor and a memory, and being configured, under control of the processor, to execute instructions stored in the memory to:- receive, at an input of said computer-implemented apparatus, reservationrequest data defining a reservation request received by a said on-line resource reservation system that cannot be fulfilled thereby according to the current available resource inventory;- generate, using metrics specifically associated with resources and reservations,a selected condition, weighted probability data defining data indicative of whether or not a reservation request should be attempted to be fulfilled;- if so, map said weighted probability data onto said reservation request data togenerate message data to be transmitted to said resource inventory owner and, if said reservation request can be accommodated under said selected conditions;- if so, cause to be presented, via an output of said apparatus, offer data, offeringsaid user an opportunity to have the reservation request fulfilled under certain selectable conditions;- if a user selects an acceptable one or more of said selectable conditions, directsaid user to an on-line payment facility to allow them to pay at least an additional fee for said reservation request to be fulfilled under the selected conditions;- once payment has been completed, generate message data and transmit saidmessage data to a respective establishment, via said on-line resourcereservation system, informing them that said reservation request has been completed, together with any conditions attached thereto.

2. A computer-implemented apparatus according to claim 1, wherein weightedprobability data is compared with a predetermined threshold to provide indicator data indicative of whether or not a reservation request should be attempted to be fulfilled. In this case, the method further may further include mapping said indicator data to said reservation request to generate said offer data.

3. A computer-implemented apparatus according to claim 1 or claim 2, wherein themetrics used to generate the weighted probability data include user profile and / or other user-specific data.

4. A computer-implemented apparatus according to any of claims 1 to 3, whereinthe weighted probability data includes data representative of one or more effectson other resource users if the reservation request is granted.

5. A computer implemented method implemented by apparatus according to any ofthe preceding claims, comprising:- receiving, at an input of said computer-implemented apparatus, reservationrequest data defining a reservation request received by a said on-line resource reservation system that cannot be fulfilled thereby according to the current available resource inventory;- generating, using metrics specifically associated with resources andreservations, a selected condition, weighted probability data defining data indicative of whether or not a reservation request should be attempted to be fulfilled;- if so, mapping said weighted probability data onto said reservation request datato generate message data to be transmitted to said resource inventory owner and, if said reservation request can be accommodated under said selected conditions;- if so, causing to be presented, via an output of said apparatus, offer data, offeringsaid user an opportunity to have the reservation request fulfilled under certain selectable conditions;- if a user selects an acceptable one or more of said selectable conditions,directing said user to an on-line payment facility to allow them to pay at least anadditional fee for said reservation request to be fulfilled under the selected conditions;- once payment has been completed, generating message data and transmittingsaid message data to a respective establishment, via said on-line resource reservation system, informing them that said reservation request has been completed, together with any conditions attached thereto.

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