JP2011034240A - Survey system and survey method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To appropriately select survey respondents. <P>SOLUTION: An survey system 10 determines initial survey respondents based on recovery rate prediction model information showing a correspondence relationship between an elapsed time from the start of survey and a predicted recovery rate showing the rate of the number of recovery with respect to the number of survey respondents. Furthermore, on the basis of the actual number of recovery after the lapse of a predetermined time from the start of survey and the predicted number of recovery corresponding to the predetermined time in the recovery rate prediction model information, the survey system 10 subtracts the actual number of recovery from the predicted number of recovery to calculate the insufficient number of recovery, and determines the additional survey respondents corresponding to the insufficient number of recovery. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a survey system that selects a survey target person and performs a survey using the Internet or the like, and a survey method in the survey system.

  In recent years, many surveys using the Internet (net surveys) have been conducted. The survey using the Internet requires less manpower and costs compared to the so-called visit survey, in which the investigator visits the survey subjects randomly selected from the Basic Resident Register, the electoral list, etc. In addition to being inexpensive, it has the advantage that the survey results can be acquired quickly (see, for example, Patent Document 1).

  When a net survey is conducted on a survey target person, the following two types of methods are often adopted. The first method is called a period setting method. In the period setting method, a survey period is set, and the survey subject can reliably answer within the survey period. The second method is called a collection number setting method. In the collection number setting method, a target number of collections is set, and the survey is terminated when the actual number of collections reaches the target number of collections.

JP 2006-285691 A

  In the period setting method described above, the disparity between the respondent's group and the surveyed person's group is small, and even though it is within the survey period, it is not impossible to respond. small. However, if the number of survey subjects is not set appropriately, the number of responses exceeding the target may be received within the survey period, and conversely, only the number of responses that do not reach the target may be received. In particular, if the respondent is paid a reward, etc., an unexpected cost will be incurred if the number of responses exceeding the target is received within the survey period.

  On the other hand, in the collection number setting method described above, when an answer is paid to the respondent, an unexpected cost does not occur. However, even if the survey subject has a willingness to participate, if the number of collections has already reached the target number, the survey subject cannot answer and tends to be frustrated or stressed. In addition, for example, when the daytime period of weekdays is long, there are cases where there is a discrepancy between the group of respondents and the group of survey subjects, depending on the survey period, such as fewer responses from company employees.

  For this reason, it is required to appropriately select the survey target person so that the target number of collections can be obtained when the survey period expires.

  In view of the above problems, an object of the present invention is to provide a survey system and a survey method that can appropriately select a survey target person.

  In order to solve the above-described problems, the present invention has the following features. First, the first feature of the present invention is a survey system (survey system 10) that selects and surveys survey subjects, and calculates the elapsed time from the start of the survey and the ratio of the number of collections to the number of survey subjects. A storage unit (storage unit 103) that stores recovery rate prediction model information indicating a correspondence relationship with the indicated recovery rate, and an initial survey target person is determined based on the recovery rate prediction model information stored in the storage unit And an initial survey subject determination section (initial survey subject determination section 152).

  Such a survey system determines an initial survey target person based on the recovery rate prediction model information. Therefore, when the survey period and the target number of collections are determined, the survey subject is appropriately selected based on the recovery rate prediction model information so that the target number of collections can be obtained at the end of the survey period. It becomes possible to do.

  According to a second feature of the present invention, in the first feature of the present invention, the first number of collections when a predetermined time has elapsed from the start of the investigation and the collection corresponding to the predetermined time in the collection rate prediction model information. Based on the second collection number obtained from the rate, a calculation unit (deficiency number calculation unit 154) that calculates the shortage number of the first collection number with respect to the second collection number, and the calculation unit calculates The gist of the present invention is to include an additional survey subject determination unit (additional survey subject determination unit 156) that determines an additional survey subject corresponding to the shortage number.

  Such a survey system is based on the first recovery number when a predetermined time has elapsed from the start of the survey and the second recovery number obtained from the recovery rate corresponding to the predetermined time in the recovery rate prediction model information. The shortage number of the first collection number with respect to the number of collections of 2 is calculated, and an additional survey subject corresponding to the shortage number is determined.

  In this way, if the actual number of collections is less than the number of collections indicated by the collection rate prediction model information, the survey subject is added, so the actual number of collections corresponds to the collection rate prediction model information. It becomes possible to approach the number. In other words, if the survey period and the target number of collections are set, based on the recovery rate prediction model information, the survey subject is selected so that the target number of collections can be obtained at the end of the survey period. It becomes possible to select appropriately.

  According to a third aspect of the present invention, in the first or second aspect of the present invention, the initial survey target person determination unit includes a number determined based on the recovery rate prediction model information, and the recovery rate prediction model information. The gist is to determine any number of the initial survey subjects that is smaller than the number determined based on the above.

  A fourth feature of the present invention is summarized in any one of the first to third features of the present invention, wherein the recovery rate prediction model information is provided for each investigation condition.

  A fifth feature of the present invention is summarized in that, in the fourth feature of the present invention, the survey condition is at least one of an attribute of a survey target person and a survey start time.

  According to a sixth feature of the present invention, in any one of the first to fifth features of the present invention, a correction unit that corrects the recovery rate in the recovery rate prediction model information based on the first recovery number (recovery rate) The gist is to include a rate prediction model information correction unit 158).

  A seventh feature of the present invention is a survey method in a survey system that selects and surveys survey subjects, and an elapsed time from the start of the survey and a recovery rate indicating the ratio of the number of recoveries to the number of survey subjects The present invention includes a step of storing recovery rate prediction model information indicating the correspondence relationship between and a step of determining an initial survey subject based on the stored recovery rate prediction model information.

  The eighth feature of the present invention is that, in the seventh feature of the present invention, the first number of collections when a predetermined time has elapsed from the start of the investigation and the collection corresponding to the predetermined time in the collection rate prediction model information. A step of calculating a shortage of the first recovery number relative to the second recovery number based on the second recovery number determined from the rate, and an additional survey subject corresponding to the calculated shortage number And a step of determining.

  According to a ninth feature of the present invention, in the seventh or eighth feature of the present invention, the step of determining the initial survey subject includes a number determined based on the recovery rate prediction model information, and the recovery rate. The gist is to determine any one of the initial survey subjects that is smaller than the number determined based on the prediction model information.

  A tenth feature of the present invention is summarized as any one of the seventh to ninth features of the present invention, wherein the recovery rate prediction model information is provided for each investigation condition.

  The eleventh feature of the present invention is summarized in that, in the tenth feature of the present invention, the survey condition is at least one of an attribute of the survey subject and a survey start time.

  A twelfth feature of the present invention is the method according to any one of the seventh to eleventh features of the present invention, comprising the step of correcting the recovery rate in the recovery rate prediction model information based on the first recovery number. Is the gist.

  According to the present invention, it is possible to appropriately select a survey subject.

It is a block diagram of the investigation system which concerns on embodiment of this invention. It is a figure which shows the process outline | summary of the investigation system which concerns on embodiment of this invention. It is a figure which shows the classification of recovery rate prediction model information based on embodiment of this invention. It is a figure which shows an example of the determination process of a survey subject based on embodiment of this invention. It is a figure which shows the time transition of the recovery rate corresponding to recovery rate prediction model information based on embodiment of this invention, and the time transition of an actual collection rate. It is a flowchart which shows the 1st operation | movement of the investigation system which concerns on embodiment of this invention. It is a flowchart which shows the 2nd operation | movement of the investigation system which concerns on embodiment of this invention.

  Next, an embodiment of the present invention will be described with reference to the drawings. Specifically, (1) Configuration of the survey system, (2) Operation of the survey system, (3) Action and effect, (4) Other embodiments will be described. In the description of the drawings in the following embodiments, the same or similar parts are denoted by the same or similar reference numerals.

(1) Configuration of Survey System FIG. 1 is a configuration diagram of a survey system according to an embodiment of the present invention.

  A survey system 10 shown in FIG. 1 performs surveys using the Internet by selecting survey subjects. The survey system 10 is a personal computer, for example. The investigation system 10 includes a control unit 102, a storage unit 103, a communication unit 106, a monitor 110, and an operation unit 116.

  The control part 102 is comprised by CPU, for example, and controls the various functions with which the investigation system 10 is provided. The storage unit 103 is configured by a memory, for example, and stores various types of information used for control and the like in the survey system 10.

  The communication unit 106 communicates with another communication device (not shown) via the Internet.

  The monitor 110 displays an image received via the control unit 102 and displays operation details. The operation unit 116 is configured by a numeric keypad, function keys, and the like, and is an interface used for inputting user operation details.

  The control unit 102 includes an initial survey target person determination unit 152, a shortage number calculation unit 154, an additional survey target person determination unit 156, and a recovery rate prediction model information correction unit 158.

  FIG. 2 is a diagram showing an outline of processing by the control unit 102 of the investigation system 10 according to the embodiment of the present invention.

  The control unit 102 inputs a survey subject condition according to the operation of the operation unit 116 by the worker. The survey subject condition includes, for example, information such as the region and occupation of the person to be selected as the survey subject. The storage unit 103 stores information (survey monitor information) of all survey monitors that may be set as survey subjects. The survey monitor information includes, for example, attribute information such as the ID, address, name, age, sex, and occupation of the corresponding survey monitor.

  The control unit 102 reads information on a person who meets the survey target person condition (survey target person condition corresponding person information) from the survey monitor information stored in the storage unit 103. For example, when the survey subject condition is a region, the control unit 102 sets the survey monitor information that is the region where the address is the survey subject condition among the survey monitor information stored in the storage unit 103 to the survey subject condition. Read as applicable person information.

  The initial survey target person determination unit 152 in the control unit 102 inputs survey conditions according to the operation of the operation unit 116 by the worker. The survey condition includes, for example, information on attributes such as the address, age, sex, and occupation of the person to be selected as the survey target, and information at the start of the survey.

  The storage unit 103 stores recovery rate prediction model information prepared for each attribute of a person to be selected as a survey target and for each survey start. The recovery rate prediction model information is information indicating a correspondence relationship between the elapsed time from the start of the survey and the predicted recovery rate indicating the ratio of the recovery number to the number of survey subjects.

  FIG. 3 is a diagram illustrating an example of the classification of the recovery rate prediction model information. The recovery rate prediction model information shown in FIG. 3 indicates that the attributes of persons to be selected as survey subjects are two genders and ages classified into six age groups from teens to over 60s. This is an example in which the start time is 8 times from 15:00, 18:00, 21:00, and 24:00 from Monday to Thursday and 15:00, 18:00, 21:00, and 24:00 from Friday to Sunday. A total of 96 collection rate prediction model information items P1 to P96 of x8 are included. Note that the survey start time is not limited to the time every three hours shown in FIG. 3, but various surveys such as a time every 30 minutes, a time every 1 hour, a time every 5 hours, etc. The start time can be set.

  The initial survey target person determination unit 152 uses the attributes of the person to be selected as the survey target included in the survey conditions and the recovery rate prediction model information corresponding to the start time of the survey, as a recovery rate prediction for the initial survey target person. Read out from the storage unit 103 as model information. For example, if the attribute of the person to be selected as the survey subject included in the survey condition is male, 20s, and the survey start time is 18:00 on Monday, the initial survey subject determination unit 152 The recovery rate prediction model information P14 is read out from the recovery rate prediction model information P1 to P96 shown in FIG.

  Again, referring back to FIG. 1 and FIG. Next, the initial survey target person determination unit 152 selects, as survey target person information, information corresponding to the attribute of the person to be selected as the survey target person included in the survey conditions from among the survey target person condition applicable person information. Extract. For example, when the attribute of the person to be selected as the survey subject included in the survey conditions is male and in his twenties, the initial survey target person determination unit 152 selects the male, Information including attribute information of the 20's is extracted as survey target person information.

  Next, the initial survey target person determination unit 152 determines an initial survey target person (initial survey target person) from those who should be selected as the survey target person corresponding to the survey target person information (the initial survey target person in FIG. 2). Extraction).

  Specifically, the initial survey target person determination unit 152 inputs a survey period (for example, 72 hours) and a target collection number (for example, 1000) according to the operation of the operation unit 116 by the worker. Next, the initial survey target person determination unit 152 corresponds to the elapsed time when the input survey period is the elapsed time out of the recovery rates included in the read initial survey target person recovery rate prediction model information. Get the predicted recovery rate (initial target recovery rate). The initial survey target predicted recovery rate acquired here is a predicted recovery rate at the end of the survey period. Furthermore, the initial survey target person determination unit 152 calculates the initial survey target number by multiplying the input target recovery number by the reciprocal of the acquired initial survey target person predicted recovery rate. For example, when the input survey period is 72 hours, the target number of recovery is 1000, and the predicted recovery rate corresponding to the elapsed time of 72 hours included in the recovery rate prediction model information for the initial survey target person is 59.1%, The initial survey target person determination unit 152 calculates 1693 as the number of initial survey target persons by 1000 × 100 / 59.1. Note that the initial survey target person determination unit 152 may set a value smaller than a value obtained by multiplying the target number of collections by the reciprocal of the initial survey target person predicted recovery rate as the initial survey target number.

  Next, the initial survey subject determination unit 152 extracts survey subject information corresponding to the calculated number of initial survey subjects from the survey subject information, and selects a person corresponding to the extracted survey subject information as an initial survey target. As a person.

  The control unit 102 makes a survey request by e-mail or the like to the initial survey subject at the timing when the survey start time arrives.

  After the start of the survey, the control unit 102 receives information on the response to the survey (response information) transmitted from a personal computer or the like that is a communication device owned by the initial survey target person via the communication unit 106.

  Further, the control unit 102 derives the actual value of the number of collections from the initial survey subject (the number of initial survey subject performance collections) at a predetermined time interval (for example, every 6 hours). The response information includes the ID of the survey subject who is the respondent. Based on this ID, the control unit 102 can prevent the number of collections from being duplicated when the same initial survey target person answers a plurality of times.

  Next, the shortage number calculation unit 154 calculates the predicted number of collections (initial survey target person predicted collection number) based on the initial survey target person recovery rate prediction model information. Specifically, the shortage number calculation unit 154 specifies the elapsed time from the start of the survey to the timing at which the initial survey subject performance collection number is derived. Next, the deficiency number calculation unit 154 specifies a predicted collection rate (initial survey target person predicted recovery rate) corresponding to the specified elapsed time in the recovery rate prediction model information for the initial survey target person. Further, the deficiency number calculation unit 154 calculates the initial survey target person predicted collection number by multiplying the initial survey target person number by the reciprocal of the identified initial survey target person predicted collection rate. Next, the shortage number calculation unit 154 subtracts the initial survey target person actual recovery number from the initial survey target person predicted recovery number.

  When the value obtained by the subtraction is a positive value, in other words, when the initial survey target person actual recovery number is smaller than the initial survey target person predicted recovery number and there is a shortage, the additional survey target person determining unit 156 In order to make up for the shortage, an additional survey subject (additional survey subject) is determined.

  Specifically, the additional survey target person determination unit 156 displays the recovery rate prediction model information corresponding to the attribute of the person to be selected as the survey target person included in the survey condition and the current survey start time. Then, it reads out from the storage unit 103 as the recovery rate prediction model information for the additional survey target person. For example, if the attribute of the person to be selected as the survey subject included in the survey conditions is male, 20s, and the current time is 12:00 on Saturday, the additional survey subject determination unit 156 displays The recovery rate prediction model information P50 corresponding to 18:00 on Saturday, which is the start of the survey immediately after 12:00 on Saturday, is read out from the recovery rate prediction model information P1 to P96 shown in FIG.

  Next, the additional survey target person determination unit 156 determines an additional survey target person from those who should be selected as the survey target person corresponding to the survey target person information (secondary extraction in FIG. 2).

  Specifically, the additional survey target person determination unit 156 subtracts the time from the present time until the expiry of the survey period (remaining survey period) and the initial survey target person actual recovery number from the initial survey target person predicted recovery number. Specify (the number of shortages). Next, the additional survey target person determination unit 156 corresponds to the elapsed time when the remaining survey period is the elapsed time among the recovery rates included in the read recovery rate prediction model information for the additional survey target person. Get the predicted recovery rate (predicted recovery rate for additional survey subjects). The additional survey subject predicted recovery rate acquired here is the predicted recovery rate at the end of the survey period. Further, the additional survey target person determination unit 156 calculates the number of additional survey target persons by multiplying the identified shortage number by the reciprocal of the acquired additional survey target person predicted collection rate. For example, when the remaining survey period is 51 hours, the number of shortages is 26, and the predicted recovery rate corresponding to 51 hours, which is the elapsed time included in the recovery rate prediction model information for additional survey subjects, is 50.1% The initial survey subject determination section 152 calculates 26 as the number of additional survey subjects by 26 × 100 / 50.1.

  Next, the additional survey target person determination unit 156 extracts survey target person information corresponding to the calculated number of additional survey target persons from the survey target person information. Here, the additional survey subject person determination unit 156 extracts survey subject information other than the survey subject information corresponding to the initial survey subject. Further, the additional survey subject person determination unit 156 determines a person corresponding to the extracted survey subject information as an additional survey subject person.

  Thereafter, the control unit 102 receives response information transmitted from a personal computer or the like, which is a communication device owned by the initial survey subject and the additional survey subject, via the communication unit 106.

  Furthermore, the shortage number calculation unit 154 derives the actual value of the number of collections from the additional survey target person (the number of additional survey target person results collected) along with the derivation of the initial survey target person result collection number. Next, the shortage number calculation unit 154 calculates the initial survey target person predicted answer number based on the initial survey target person recovery rate prediction model information, and also calculates the predicted recovery number based on the additional survey target person recovery rate prediction model information ( Calculate the predicted number of additional survey subjects. Specifically, the shortage calculation unit 154 specifies the elapsed time from the start of the survey for the additional survey subject to the timing when the additional survey subject performance collection number is derived. Next, the deficiency number calculation unit 154 specifies a predicted recovery rate (additional survey target person predicted recovery rate) corresponding to the specified elapsed time in the additional survey target person recovery rate prediction model information. Furthermore, the shortage number calculation unit 154 calculates the additional survey target person predicted collection number by multiplying the additional survey target person number by the reciprocal of the specified additional survey target person predicted collection rate. Next, the deficient number calculation unit 154 adds the initial survey target person actual collection number and the additional survey target person actual collection number from the addition value of the initial survey target person predicted recovery number and the additional survey target person predicted recovery number. Is subtracted.

  In other words, if the value obtained by subtraction is a positive value, in other words, the sum of the initial survey subject actual recovery number and the additional survey target actual recovery number is the initial survey target predicted recovery number and the additional survey target. If there is a shortage that is less than the value added to the estimated number of persons recovered, the additional survey target person determination unit 156 determines an additional survey target person (additional survey target person) to compensate for the shortage (FIG. 2). 3rd extraction). The specific process is the same as the process for determining the additional survey subject described above.

  FIG. 4 is a diagram illustrating an example of determination processing for the initial survey target person and the additional survey target person. FIG. 4 shows an example in which the attribute of the person to be selected as the survey target is male, in his 20s, the survey starts at 18:00 on Friday, the survey period is 72 hours, and the target collection number is 1000 people. is there.

  Corresponding to the fact that the attribute of the person to be selected as the survey subject is male, twenties, and the survey start time is Friday 18:00, recovery rate prediction model information P14 from the recovery rate prediction model information shown in FIG. Is selected as the initial recovery rate prediction model information. Further, based on the predicted recovery rate of 59.1% corresponding to the elapsed time of 72 hours in the initial recovery rate prediction model information P14 and the target recovery number of 1000, the initial survey target number is determined to be 1,693. Investigation for the subject is started.

  In FIG. 4, the value obtained by subtracting the initial survey target person actual recovery number from the initial survey target person actual recovery number at 12:00 on Saturday, 18 hours after the start of the survey, is 26. In this case, corresponding to the fact that the attribute of the person to be selected as the survey subject is male, twenties, and the current time is 12:00 on Saturday, 12% of Saturday is selected from the recovery rate prediction model information shown in FIG. Recovery rate prediction model information P50 corresponding to 18:00 on Saturday, which is the start of the survey immediately after the hour, is selected as additional recovery rate prediction model information. Furthermore, the number of additional survey subjects is determined to be 52 based on the predicted recovery rate of 50.1% corresponding to the elapsed time of 51 hours in the additional recovery rate prediction model information P50 and the shortage number 26, and the additional survey is performed. Investigation for the subject is started.

  As shown in FIG. 4, by determining the initial survey subject and the additional survey subject, as shown in FIG. 5, the actual recovery rate (dotted line) can be made closer to the predicted recovery rate (solid line). .

  Again, referring back to FIG. 1 and FIG. The recovery rate prediction model information correction unit 158 in the control unit 102 corrects the predicted recovery rate in the recovery rate prediction model information based on the actual recovery rate after the expiry of the survey period (recovery result management in FIG. 2). For example, when the predicted recovery rate in the recovery rate prediction model information is an average value of a plurality of past actual recovery rates, the recovery rate prediction model information correction unit 158 calculates a weighted average value of the actual recovery rate and the predicted recovery rate. The weighted average value is calculated as a new predicted collection rate.

  The recovery rate prediction model information correction unit 158 determines the initial survey target person and the additional survey target person and calculates the actual recovery rate based on the recovery from the initial survey target person and the additional survey target person. At any time, the predicted recovery rate in the recovery rate prediction model information may be corrected based on the actual recovery rate.

(2) Operation of Survey System Next, the operation of the survey system 10 will be described. 6 and 7 are flowcharts showing the operation of the investigation system 10. In the following, an example will be described in which the attributes of a person to be selected as a survey subject are gender and age.

  In step S101, the control unit 102 inputs a survey subject condition. In step S <b> 102, the control unit 102 reads out information on a person who meets the survey target person condition (survey target person condition corresponding person information) from the survey monitor information stored in the storage unit 103. In step S103, the control unit 102 inputs an investigation condition.

  In step S <b> 104, the control unit 102 sets the recovery rate prediction model information corresponding to the sex and age included in the survey condition and the survey start time as the recovery rate prediction model information for the initial survey target person from the storage unit 103. read out.

  In step S <b> 105, the control unit 102 extracts information corresponding to the sex and age included in the survey condition from the survey subject condition applicable person information as the survey target person information.

  In step S <b> 106, the control unit 102 determines an initial survey target person based on the input survey period and target number of collections and the initial survey target person recovery rate prediction model information.

  Thereafter, when the survey is started, the process proceeds to the operation shown in FIG. 7, and in step S201, the control unit 102 derives the actual value of the number of collections from the initial survey target person (the number of initial survey target person results collected). .

  In step S <b> 202, the control unit 102 calculates a predicted collection number (initial survey target person predicted collection number) based on the initial survey target person recovery rate prediction model information. In step S203, the control unit 102 subtracts the initial survey target person actual recovery number from the initial survey target person predicted recovery number. In step S <b> 204, the control unit 102 determines whether or not there is a shortage since the initial survey target person actual recovery number is smaller than the initial survey target person predicted recovery number. If there is no shortage, the operation after the number of results collected in step S201 is repeated.

  On the other hand, when there is a shortage, in step S205, the control unit 102 adds the recovery rate prediction model information corresponding to the sex and age included in the survey condition and the survey start time that is the current time to the additional survey subject. Read out from the storage unit 103 as the recovery rate prediction model information.

  In step S206, the control unit 102 determines an additional survey subject based on the remaining survey period, the number of shortages, and the additional survey subject recovery rate prediction model information. Thereafter, the operation after the number of results collected in step S201 is repeated.

(3) Action / Effect The survey system 10 according to the embodiment of the present invention determines an initial survey subject based on the recovery rate prediction model information. Therefore, when the survey period and the target number of collections are determined, it is possible to appropriately select the survey subjects so that the target number of collections can be obtained at the end of the survey period based on the recovery rate prediction model information It becomes.

  In addition, the survey system 10 according to the present embodiment is based on the actual number of recoveries when a predetermined time has elapsed from the start of the survey and the actual number of recoveries based on the predicted number of recoveries corresponding to the predetermined time in the recovery rate prediction model information. By subtracting the number of collections, the shortage number is calculated, and an additional survey subject corresponding to the shortage number is determined. Therefore, if the actual collection number is lower than the predicted collection number indicated by the recovery rate prediction model information, the survey target person is added, and the subsequent actual collection number can be brought close to the predicted collection number. . In other words, when the survey period and the target number of collections are set, based on the recovery rate prediction model information, the survey subject is appropriately selected so that the target number of collections can be obtained at the end of the survey period. It becomes possible.

  Further, in the survey system 10 according to the present embodiment, the recovery rate prediction model information is prepared for each attribute of the person to be selected as the survey target and for each survey start. Since the time course of recovery generally varies depending on the attributes of the surveyed subject (eg gender, age) and the start of the survey (weekdays, holidays, time zones), By providing the recovery prediction model information, a more appropriate predicted recovery rate can be obtained.

  Moreover, the investigation system 10 according to the present embodiment corrects the predicted recovery rate in the recovery rate prediction model information based on the actual recovery rate. Therefore, it is possible to obtain more appropriate recovery rate prediction model information that incorporates the results.

(4) Other Embodiments As described above, the present invention has been described according to the embodiment. However, it should not be understood that the description and drawings constituting a part of this disclosure limit the present invention. From this disclosure, various alternative embodiments, examples and operational techniques will be apparent to those skilled in the art.

  In the above-described embodiment, the Internet survey has been described as an example. However, the present invention can be similarly applied to other surveys in which the survey period and the target collection number are set.

  Thus, it should be understood that the present invention includes various embodiments and the like not described herein. Therefore, the present invention is limited only by the invention specifying matters in the scope of claims reasonable from this disclosure.

  INDUSTRIAL APPLICABILITY The survey system and the survey method of the present invention can appropriately select a survey target person and are useful as a survey system and a survey method.

  DESCRIPTION OF SYMBOLS 10 ... Investigation system, 102 ... Control part, 103 ... Memory | storage part, 106 ... Communication part, 110 ... Monitor, 116 ... Operation part, 152 ... Initial investigation object person determination part, 154 ... Shortage number calculation part, 156 ... Additional investigation object Person determination unit, 158... Recovery rate prediction model information correction unit

Claims (12)

A survey system that selects survey subjects and conducts surveys.
A storage unit for storing recovery rate prediction model information indicating a correspondence relationship between an elapsed time from the start of the survey and a recovery rate indicating a ratio of the recovery number to the number of survey subjects;
A survey system comprising: an initial survey subject determination unit that determines an initial survey subject based on the recovery rate prediction model information stored in the storage unit. Based on the first collection number when a predetermined time has elapsed from the start of the investigation and the second collection number obtained from the collection rate corresponding to the predetermined time in the collection rate prediction model information, the second collection number A calculation unit for calculating a shortage of the first collection number with respect to the collection number;
The survey system according to claim 1, further comprising: an additional survey target person determination unit that determines an additional survey target person corresponding to the shortage number calculated by the calculation unit.   The initial survey target person determining unit determines either the number determined based on the recovery rate prediction model information and the number smaller than the number determined based on the recovery rate prediction model information. The investigation system according to claim 1 or 2.   The survey system according to claim 1, wherein the recovery rate prediction model information is provided for each survey condition.   The survey system according to claim 4, wherein the survey condition is at least one of an attribute of a survey target person and a survey start time.   The survey system according to claim 1, further comprising a correction unit that corrects the recovery rate in the recovery rate prediction model information based on the first recovery number. A survey method in a survey system that selects and surveys survey subjects,
Storing recovery rate prediction model information indicating a correspondence relationship between an elapsed time from the start of the survey and a recovery rate indicating a ratio of the recovery number to the number of survey subjects;
And a step of determining an initial survey subject based on the stored recovery rate prediction model information. Based on the first collection number when a predetermined time has elapsed from the start of the investigation and the second collection number obtained from the collection rate corresponding to the predetermined time in the collection rate prediction model information, the second collection number Calculating a deficiency of the first collection number relative to the collection number;
The survey method according to claim 7, further comprising: determining an additional survey target person corresponding to the calculated shortage number.   The step of determining the initial survey subject includes either the number determined based on the recovery rate prediction model information and the number less than the number determined based on the recovery rate prediction model information. The investigation method according to claim 7 or 8, wherein the method is determined.   The survey method according to claim 7, wherein the recovery rate prediction model information is provided for each survey condition.   The survey method according to claim 10, wherein the survey condition is at least one of an attribute of a survey target person and a survey start time.   The survey method according to claim 7, further comprising a step of correcting a recovery rate in the recovery rate prediction model information based on the first recovery number.

Images