TW202319975A - System and method of analyzing employee attitude based on user behavior of enterprise messages - Google Patents

Abstract

This disclosure is related to a system and method of analyzing employee attitude based on user behavior of enterprise messages, the method includes: define an employee attitude and create a corresponding employee-attitude-analysis-model and associated one or more quantifiable-user-behavior, filter and count a plurality of message sending records of employees' by using the quantifiable-user-behavior to generate one or more matching values, bring the matching values into the employee-attitude-analysis-model for calculation to obtain a result of each employee, sort the employees according to the result, and generate an employee-attitude-analysis-report.

Description

System and method for analyzing employee attitude based on user behavior of enterprise information

The present invention relates to a user behavior analysis technology, in particular to a system and method for analyzing employee attitudes based on user behavior of enterprise information.

When a company or organization wants to implement a new project or carry out a new reform, employee attitude (Employee Attitude) is the key factor that determines its success or failure. Therefore, it is very important for leaders to understand employee attitude in a timely manner for decision-making. In order to understand employee attitudes, the most common way for companies to do is to conduct employee attitude surveys (Employee Attitude Surveys), and the methods of employee attitude surveys mainly include questionnaire method (also known as scale method), interview method and behavior observation method (also known as behavioral observation method). evaluation method or behavioral observation scale method). Questionnaire method is a survey method in which investigators use a uniformly designed questionnaire (usually using a standard scale) to solicit opinions from employees; interview method is a method in which investigators interview employees or their supervisors to understand employees' attitudes (or attitudes towards employees). The supervisor has obtained the employee data to confirm); the behavior observation method is to examine the employee's work performance and use the behavior observation scale to score. All of the employee attitude survey methods above require a lot of manpower, time and money. Usually, the internal human resources department of the company or an outsourced professional consulting company conducts employee attitude surveys. For example: If a company wants to know the centripetal force, enthusiasm and interpersonal relationship among its thousands of employees, it will take weeks at least, or months at most, and invest in a lot of investigations It takes manpower and a considerable amount of money to get the analysis results. However, some surveys need to be carried out continuously, and it is impossible to solve all the problems through one survey. Therefore, in order to conduct regular surveys, it is necessary to consider the method of sampling surveys instead of comprehensive surveys to reduce costs. However, it is very likely that the analysis results obtained by the sample survey are inaccurate, or it is easy to cause regrets (for example: the important employees who were omitted were not valued and left).

There is a prior art one, the Republic of China patent announcement number I558131, which discloses a message transmission system and method with a plurality of organizational structures. The system includes: a database, a server, a push gateway and a mobile communication device; the database, The server and the push gateway form the cloud of the invention; the database stores a plurality of member information, and each member information includes at least an organization identification code, an account number and a password, and different organization identification codes Each of the organization identification codes can define an organization as a single-level organization or multiple-level organizations; wherein, the client can access the cloud through a single App and a single interface to receive or transmit messages. The technical effect achieved by the previous technology is suitable for use within the enterprise, allowing members of the enterprise to transmit information to each other, or allowing managers to spread information from top to bottom.

There is a prior art 2, the "Line" application program and its back-end system developed by LINE Co., Ltd., a subsidiary of South Korea's NHN Corporation in Japan. This previous technology 2 is not only used for information sharing and emotional communication for private purposes, but also can be used within the enterprise to allow members of the enterprise to transmit information to each other, and it can also be used for managers to spread information from top to bottom.

Regardless of whether it is prior art 1 or prior art 2, when it is used within the enterprise for all members to transmit information to each other, or to manage the internal information of Buda, the prior art can only deal with the transmission of information, and cannot use enterprise information based on enterprise members User behavior (User Behavior) to analyze employee attitudes. That is to say, the above-mentioned prior technology does not have any analysis function, so it is impossible to analyze the historical records of user behaviors (for example: message interaction between colleagues, participation rate of each post message, response time of reply message, etc.) relevant column information) to make any connection with employee attitudes to obtain employee attitude analysis results. Therefore, it is necessary to improve the conventional method, and propose a system and method based on the user behavior of enterprise information to analyze employee attitudes based on the resources of hardware and software cooperation, and use the user behavior of enterprise information to connect with employee attitudes Obtain automated employee attitude analysis results, reduce the cost, time and manpower invested by enterprises in employee attitude surveys, and enable the analysis of all enterprise employees to avoid inaccurate problems caused by sampling surveys, so as to make up for previous technical deficiencies .

In view of this, the present invention proposes a system and method for analyzing employee attitudes based on user behavior of enterprise information, defines an employee attitude and establishes a corresponding employee attitude analysis model and associated quantifiable user behavior (screening conditions), and then based on The message sending records of corporate messages are screened and counted to obtain a matching value that can quantify user behavior, and the matching value is brought into the employee attitude analysis model for calculation to obtain the employee attitude analysis result.

The present invention proposes a system for analyzing employee attitudes based on user behavior of enterprise information, including: a database storing multiple members of an organization, corresponding multiple member information, and corresponding multiple message sending records; a server, Accessing the database includes: a first network communication module, which establishes a network connection with a client device associated with one of the members; a login verification module, which verifies that the client device is connected via the network and a first message module, which receives a new message uploaded or a reply message and generates a list of message receivers according to a receiver setting, and stores the new message or the reply message and a corresponding Read state to the database as one of the message sending records, the message receiver list includes at least one push identification code associated with the client device, the new message or the reply message includes a time stamp; a use The user behavior analysis module screens and counts the message sending records of the members of the organization according to an attitude analysis model corresponding to an employee attitude and associated one or more quantifiable user behaviors, so as to generate corresponding A matching value of quantifiable user behavior, the quantifiable user behavior is a field related to these message sending records, and the matching value of the quantifiable user behavior is brought into the attitude analysis model for calculation to obtain a Calculation results, ranking the members of the organization according to the calculation results, and generating an employee attitude analysis report according to the ranking of the members; and the client device, including: one or more processors and a screen, the processor executes a plurality of program instructions, and the program instructions include: a first program instruction to enable the client device to establish a network connection with the server for login verification; a second program instruction to enable the client device to download the new message from the server; a third program instruction to enable the client device to receive the new message or the input of the reply message and the receiving terminal settings, and the receiving terminal settings are associated with these member; a fourth program instruction, which causes the client device to upload the new message or the reply message to the server, and the new message or the reply message includes a time stamp; a fifth program instruction, when the downloaded new message After the message is read, the client device uploads the read status to the server; and a push gateway generates a push notification according to the message, and sends the push notification to the Associate the client devices corresponding to the members.

The present invention goes further. In some embodiments, the quantifiable user behavior is selected from: a number of times of sending new messages, an average number of times of sending new messages, a number of times of replying messages, an average number of times of replying messages, a number of times of going online, an Average online times, 1 online hours, 1 average online hours, 1 interaction number, 1 average interaction number, 10 interaction number, 1 average zero interaction number, 1 average reply time, 1 reply message percentage, 1 non-working hours The number of online times, the average number of online times during non-working hours, the number of reply messages during non-working hours, the average number of reply messages during non-working hours, the online hours during non-working hours, the average online hours during non-working hours, and the reply messages during non-working hours The average time, the number of unread messages, the average number of unread messages, the average time of a read, the number of read messages and the average number of read messages.

Further, in some embodiments, the quantifiable user behavior can select a time period to calculate the matching value within the time period, and the time period is selected from: one day, one week, one month, one season and one year.

Further in the present invention, in some embodiments, when the attitude analysis model includes a positive correlation of the quantifiable user behavior and a negative correlation of the quantifiable user behavior, in the calculation of the attitude analysis model It is to subtract "the matching value of the quantifiable user behavior of the negative correlation" from "the matching value of the quantifiable user behavior of the positive correlation".

The present invention goes further. In some embodiments, the server further includes: an attitude analysis model creation module, which provides a management interface of a graphical user interface for a manager with system authority to define the employee's attitude and establish the employee's attitude Corresponding to the attitude analysis model and associated one to a plurality of the quantifiable user behaviors, the quantifiable user behaviors are used as filtering or statistical conditions to filter or count the matching values.

The present invention goes further. In some embodiments, the employee attitude and the corresponding attitude analysis model are selected from: a participation degree and a corresponding participation degree analysis model, a centripetal force and a corresponding centripetal force analysis model, An positivity and a corresponding positivity analysis model, an interpersonal relationship and a corresponding interpersonal relationship analysis model, and an engagement degree and a corresponding engagement analysis model.

The present invention goes further, in some embodiments, the employee attitude and the corresponding attitude analysis model are embedded in the enterprise information system, and the corresponding employee attitude and the corresponding attitude analysis model can be used to generate a corresponding The employee attitude analysis report.

The present invention further proposes a method for analyzing employee attitudes based on user behavior of enterprise information, which is applied to an enterprise information system composed of a database and a server. The method includes: storing a plurality of organizations in the database Members, corresponding multiple member information, corresponding multiple message sending records, access the database from the server; define an employee attitude and establish a corresponding employee attitude analysis model and associated one to multiple quantifiable usage behavior; the server screens and counts the message sending records of the members of the organization based on one or more quantifiable user behaviors associated with the attitude analysis model to generate corresponding quantifiable user behaviors A matching value, the quantifiable user behavior is a field related to the message sending records; the server brings the matching value of the quantifiable user behavior into the attitude analysis model for calculation to obtain a calculation result ; The server ranks the members of the organization according to the calculation result; and, the server generates an employee attitude analysis report according to the rank of the members.

The present invention goes further. In some embodiments, the quantifiable user behavior is selected from: a number of times of sending new messages, an average number of times of sending new messages, a number of times of replying messages, an average number of times of replying messages, a number of times of going online, an Average online times, 1 online hours, 1 average online hours, 1 interaction number, 1 average interaction number, 10 interaction number, 1 average zero interaction number, 1 average reply time, 1 reply message percentage, 1 non-working hours The number of online times, the average number of online times during non-working hours, the number of reply messages during non-working hours, the average number of reply messages during non-working hours, the online hours during non-working hours, the average online hours during non-working hours, and the reply messages during non-working hours The average time, the number of unread messages, the average number of unread messages, the average time of a read, the number of read messages and the average number of read messages.

Further, in some embodiments, the quantifiable user behavior can select a time period to calculate the matching value within the time period, and the time period is selected from: one day, one week, one month, one season and one year.

Further in the present invention, in some embodiments, when the attitude analysis model includes a positive correlation of the quantifiable user behavior and a negative correlation of the quantifiable user behavior, in the calculation of the attitude analysis model It is to subtract "the matching value of the quantifiable user behavior of the negative correlation" from "the matching value of the quantifiable user behavior of the positive correlation".

The present invention goes further. In some embodiments, the server further includes: an attitude analysis model creation module, which provides a management interface of a graphical user interface for a manager with system authority to define the employee attitude and establish a corresponding The attitude analysis model is associated with one or more quantifiable user behaviors, and the quantifiable user behaviors are used as filtering or statistical conditions to filter or count the matching value.

The present invention goes further. In some embodiments, the employee attitude and the corresponding attitude analysis model are selected from: a participation degree and a corresponding participation degree analysis model, a centripetal force and a corresponding centripetal force analysis model, An positivity and a corresponding positivity analysis model, an interpersonal relationship and a corresponding interpersonal relationship analysis model, and an engagement degree and a corresponding engagement analysis model.

The present invention goes further. In some embodiments, the method further includes: the enterprise information system is embedded with the employee attitude and the corresponding attitude analysis model; and applying the ready-made employee attitude and the corresponding attitude analysis The model can generate the corresponding employee attitude analysis report.

The detailed features and advantages of the present invention are described in detail below in the implementation mode, and its content is enough to make any person familiar with the related art understand the technical content of the present invention and implement it accordingly, and according to the content disclosed in this specification, the scope of the patent application and the drawings , anyone skilled in the art can easily understand the purpose and advantages of the present invention.

The so-called "instant message" (Instant Message) of the present invention, in one embodiment, is applied to the bulletin board message of the mobile bulletin board (Bulletin Board), and can be applied to the bulletin message from top to bottom in the enterprise or organization, for example : important announcement of the company; in one embodiment, it is applied to chat messages in a mobile chat room (Chat Room), for example: all members carry out multi-person online meetings in a chat room, and send chat messages to each other; in one embodiment, they are applied to Action dynamic news (Timeline News, or News Feed) posts (Article), for example: a member sends a post to other members in the enterprise organization.

Referring to Fig. 1, a system architecture diagram of a preferred embodiment of the present invention, the system of the present invention includes: a database 20 at the server end (i.e. cloud 24), a server 10 and a push gateway 22, and a client end The client device 28. Here, the server and the client can communicate through an external push system, but this external push system is not within the scope of the system of the present invention and is only for illustration.

Database 20 pre-stores a plurality of members of an organization, corresponding plurality of member information, and corresponding plurality of message sending records, each member information includes account number and password, and the message sending record corresponding to each member includes message content, Message subject, message sender, message receiver, message attributes, message sending timestamp, read status, read timestamp, attachments... and other related information.

The server 10 includes one or more processors, and implements the following modules in a cooperative manner of hardware and software: the first network communication module 12, the login verification module 14, the user behavior analysis module 16 and the second A message module 18 .

The first network communication module 12 is used to establish a network connection with the second network communication module 32 of the client device 28. In different embodiments of the present invention, the network connection is based on the TCP protocol (including Socket and WebSocket connection), HTTP protocol, HTTPS protocol, HTTP/2 protocol or SPDY protocol.

Log in to the verification module 14, verify that the client device 28 is connected to the server 10 through the network, and receive the account number and password uploaded by a member through the client device 28, and then store the account number and password with the member stored in the database 20 The account number and password of the information are verified.

The user behavior analysis module 16 screens and counts the message sending records of the members of the organization according to the attitude analysis model corresponding to the employee attitude and the associated one or more quantifiable user behaviors, so as to generate matching quantifiable user behaviors value. The quantifiable user behavior is a column related to the message sending record. The matching value of the quantifiable user behavior is brought into the attitude analysis model for calculation to obtain the calculation result, and the members of the organization are sorted according to the calculation result, and then based on The sorting of members produces employee attitude analysis reports. The so-called attitude analysis model is a mathematical model. An attitude analysis model is used to correspond to an employee attitude (for example: participation, centripetal force, enthusiasm, interpersonal interaction, engagement, etc.), and an attitude analysis model contains an associated one to A number of quantifiable user behaviors (a time period can be specified, such as: day, week, month, quarter or year). The so-called quantifiable user behavior refers to "quantifiable field information related to the behavior of users who send corporate messages". The number of new messages sent per quarter", "the number of replies to messages per quarter", "the number of online times per quarter" and "the average online hours per quarter", these four are all information in the message sending record, and they are all "quantifiable" " information (that is, can measure specific times, time, number of people, etc.). When these four quantifiable user behaviors are used to screen and count the message sending records of all members in the enterprise organization, and then the matching value (Match Value) of these four quantifiable user behaviors is brought into the attitude analysis model for calculation ( For example: calculate the total, calculate the average or calculate the weighted average), you can get a value (that is, the calculation result). The matching value of “Sent New Messages” is “93.5 times”, the matching value of “Replies to messages per quarter” is “153.6 times”, the matching value of “Online Times per quarter” is “252.8 times” and the “Average online times per quarter The matching value of "hours" is "43.2 hours", so the system will bring the four matching values of "93.5", "153.6", "252.8" and "43.2" into the attitude analysis model of "participation" for calculation, and finally The obtained value (calculation result) is the scoring result of the member's "participation". In this embodiment, the attitude analysis model of "participation" can be the addition of positive associations, subtracting the sum of negative associations, or calculating the matching value of a certain item by weighting. For example, the aforementioned four quantifiable User behavior is positively correlated and there is no weighted item, then the score result of "participation"=93.5+153.6+252.8+43.2=543.1. As another example, a certain boss believes that the "average online hours per quarter" should be weighted by 200%, and the rest is the addition of positive correlations, then the scoring result of "participation" = 93.5+153.6+252.8+43.2* 2 = 586.3, and so on. Then, sort all the members in the enterprise organization according to the value of the participation scoring results (in ascending or descending order), and the sorting result is the "participation" employee attitude analysis report. In some embodiments, the employee attitude analysis report can choose to arrange only a specific number or a specific percentage of the head and tail, for example: arrange the participation "top 5", "lowest bottom 5", "highest Top 2%"...etc. In some embodiments, the attitude analysis model can select different time periods for screening and statistics, that is, use different periods of quantifiable user behaviors for screening and statistics to observe whether employees' attitudes in the short, medium, and long-term There are ups and downs.

In some embodiments, the quantifiable user behavior is selected from the group consisting of: number of new messages sent, average number of new messages sent, number of replies to messages, average number of replies to messages, number of online sessions, average number of online sessions, online hours, average online hours , interactive number, average interactive number, zero interactive number, average zero interactive number, average reply time, reply message percentage, non-working hours online times, non-working hours average online times, non-working hours reply messages times, non-working hours average Times of replying messages, online hours during non-working hours, average online hours during non-working hours, average time of replying messages during non-working hours, times of unread messages, average times of unread messages, read time, average time of The number of replies and the average number of messages that have been read but not returned. The above quantifiable user behaviors can choose a time period to calculate the "matching value in the latest time period" or the "average matching value in each time period" , the time period is selected from: day, week, month, quarter and year. The combination of time periods can quantify user behavior, such as: the number of new messages sent in the last day, the number of new messages sent in the last week, the number of new messages sent in the last month, the number of new messages sent in the latest quarter, the average number of new messages sent per day, and the number of new messages sent per day. The average number of new messages sent per week, the average number of new messages sent per month, the average number of new messages sent per quarter, the number of replies to messages in the last day, the number of replies to messages in the last week, the number of replies to messages in the last month, the number of replies to messages in the latest quarter, and the number of replies to messages in the latest quarter. Daily average number of reply messages, average weekly reply message count, monthly average reply message count, quarterly average reply message count, last day online count, last week online count, last month online count, latest quarter online count, daily Daily average online times, weekly average online times, monthly average online times, quarterly average online times, daily average online hours, weekly average online hours, monthly average online hours, quarterly average online hours , The number of interactions in the last day, the number of interactions in the last week, the number of interactions in the last month, the number of interactions in the latest quarter, the average number of interactions per day, the average number of interactions per week, the average number of interactions per month, the average number of interactions per quarter, the last day Zero interaction number, zero interaction number in last week, zero interaction number in last month, zero interaction number in last quarter, daily average zero interaction number, weekly average zero interaction number, monthly average zero interaction number, quarterly average zero interaction number , Daily average reply time, Weekly average reply time, Monthly average reply time, Quarterly average reply time, Daily reply percentage, Weekly reply percentage, Monthly reply percentage, Quarterly reply Percentage of messages, the number of times online during non-working hours in the last day, the number of times online during non-working hours in the last week, the number of times online during non-working hours in the last month, the number of times online during non-working hours in the latest quarter, the average number of times online during non-working hours per day, and the number of times online during non-working hours per week The average number of online times during time periods, the average number of online times during non-working hours per month, the average number of online times during non-working hours per quarter...etc. Among them, "reply message" can include: reply with text, reply with likes, or reply with stickers; and the reply time refers to the difference between "the time stamp when the other party sends the message" and "the time stamp when the user replies to the message" time; this reply time can be interpreted as the "response time of reply message" (that is, the user's reaction speed after seeing the message sent by the other party). Positivity" has a positive correlation. The average read time (that is, the response speed of reading messages) refers to the average time between the "time stamp when the other party sends the message" and the "time stamp when the user reads the message"; this average read time can be interpreted as " Response time for reading messages" (that is, the user's reaction speed after seeing the message sent by the other party), the shorter the average read time, the faster the user's response speed to read the message, and the response speed can be regarded as positively related to "positivity". associated. The matching value of some quantifiable user behaviors with negative correlations can be "operated in a subtractive manner" in the operation of the attitude analysis model (that is, "the matching values of quantifiable user behaviors with positive correlations" minus "The matching value of quantifiable user behavior with negative correlation"), for example: unread messages, read but not returned... etc. can be considered as having a negative correlation with "positivity". Quantifiable user behavior related to interactions between colleagues, such as: Engagement count (number of people who have messaged or liked each other), Zero engagement count (number of people who have never interacted with or liked each other ), unread messages, unread messages, etc., their matching values can all be used in the calculation of the attitude analysis model (interpersonal relationship analysis model). In some embodiments, the present invention further aims at quantifiable user behaviors such as zero interaction number, unread messages, read but not returned... and lists specific objects in the employee attitude analysis report (interpersonal relationship analysis report), or It is drawn on the "interpersonal relationship diagram" (not shown in the figure, it is a common technology to show the relationship between members with interaction and zero interaction with each other in a graphical way). For example: an employee always has zero interaction with a certain member, has not read the message or has not read it back, the present invention can list the specific member in the employee attitude analysis report, so that the supervisor can pay attention to the employee's troubles and then understand or enlighten, or It is to let the supervisor avoid putting two people in the same group when assigning tasks to prevent problems. Although "participation" and "centripetal force" are not synonymous, there is still a certain degree of positive correlation between the two, especially when used in small teams or groups, it is easier to observe a higher overlap between the two. For example: all members of a certain department under the enterprise organization are "highly involved" in the department's information, and it can also be considered that the member has centripetal force to the department. Therefore, in some embodiments, the centripetal force analysis model selects an appropriate After the user behavior can be quantified (that is, the quantifiable user behavior associated with the centripetal force analysis model set by the authorized manager), it can also be used to evaluate the centripetal force of the employee. In some embodiments, "participation" and "centripetal force" can share the same analysis model. Continuing to send messages, read messages, or reply to messages during non-working hours can be interpreted as having a positive relationship with "engagement".

In some embodiments, the server 10 further includes: an attitude analysis model creation module 42, which is used to provide a graphical user interface management interface (employee attitude analysis editing screen) for administrators with system authority to define employee attitudes and create The corresponding attitude analysis model is associated with one to a plurality of quantifiable user behaviors.

In some embodiments, any of the following ready-made employee attitudes and corresponding attitude analysis models are embedded in the server 10: participation degree and corresponding participation degree analysis model, centripetal force and corresponding centripetal force analysis model, enthusiasm and corresponding Corresponding positivity analysis model, interpersonal relationship and corresponding interpersonal relationship analysis model, or engagement and corresponding engagement analysis model; managers with system authority can arbitrarily choose the embedded employee attitude and corresponding attitude The analysis model can quickly generate corresponding employee attitude analysis reports.

The first message module 18 receives the new message (or reply message) uploaded by the client device 28 and generates a list of message receivers according to the setting of the receiver. The list of message receivers includes at least one push identification code associated with the client device 28 ( Push ID), a push identification code is corresponding to a member's receiving device (ie, the client device 28). When setting the Buda object of the message (that is, the setting of the receiving end), the members in the organization's address book are usually selected by checking the box. The first message module 18 needs to perform a comparison work (Mapping) to map the Buda object (that is, , "the selected members in the organization's address book") is converted into a list of message receivers (that is, the "push ID" of the selected members). In addition, the first message module 18 stores the new message (or reply message) and the corresponding read status (or unread status) in the database 20 as one of the message sending records. New or reply messages include a timestamp to record when the message was sent.

In the embodiment of the present invention, the above-mentioned modules contained in the server 10 should be understood as a kind of resource for the cooperative operation of hardware and software, and the technical characteristics of each module can be a part of a plurality of program instructions or application programs. However, the technical effect of each module must be realized in the form of one or more processors executing the program instructions or application programs (that is, resources for the cooperative operation of hardware and software), and the present invention aims to solve The biggest problem is to improve through such hardware and software cooperating resources.

The above-mentioned server 10 and database 20 are not limited to be deployed on a specific number of devices. In different embodiments of the present invention, both the server 10 and the database 20 can be deployed on the same device, or both Each of them can be deployed on a device in a cluster structure, or on a cluster device in a different place.

The push gateway 22 generates a push notification according to the setting of the message and its prompt tone, and sends the push notification to the corresponding message receiver list through the external push host 26 (for example: Microsoft Azure, MPNS, GCM, and APNS). Client device 28 . In one embodiment of the present invention, the push notification of the message includes partial or complete message content and the push identification code on the list of message receivers, and the push notification includes a non-repeated push notification sequence number (or It is not repeated at least to the extent that recent data can be queried).

In different embodiments of the present invention, the client device 28 is a smart phone, a tablet computer, a notebook computer or a desktop computer, and the client device 28 includes one or more processors and a screen, and the processor can execute multiple A program instruction or application program 30 (namely Application, also known as App). The application program 30 executed by the processor includes: a second network communication module 32 , a login module 34 , a data access module 36 , a second message module 38 and a message input module 40 . The second network communication module 32 is used to establish a network connection with the first network communication module 12 of the server 10. In different embodiments of the present invention, the network connection is based on TCP protocol, HTTP protocol , HTTPS protocol, HTTP/2 protocol or SPDY protocol. The login module 34 receives the account number and password input by the user (ie member) from the input interface of the client device 28, and uploads it to the server 10 for verification. In another embodiment of the present invention, the account number and password can be Temporarily stored in the memory of the client device 28, within a period of time (for example: one day or one week), repeated logins can automatically log in without manually inputting the account number and password. The data access module 36 is a network connection (TCP protocol, HTTP protocol, HTTPS protocol, HTTP/2 protocol) established by the second network communication module 32 and the first network communication module 12 of the server 10. or SPDY agreement), download new information from server 10. The second message module 38 generates a message view and displays it on the screen of the client device 28. The message view is a graphical user interface of the application program 30 for users to browse or operate messages. The message input module 40 receives user instructions to input message content (including new message and reply message), receiving end setting and subject, and the input message is to click on the message input box (generated by the message input module 40) to generate a message except In addition to the content of the input message, it also includes the setting of the receiving end (that is, the Buda object, and the setting interface is also generated by the message input module 40). The method of "Receiver Settings" is as follows: When entering a new message, select a specific member from the address book (such as the organization address book) by checking the box, and when replying to the message, the recipient of the original message is used as the recipient Receiver settings (that is, no need to check the address book).

The above-mentioned processor can execute a plurality of program instructions including: the first program instruction enables the client device 28 to establish a network connection with the server 10 for login verification; the second program instruction enables the client device 28 to connect to the server 10 10. Download new messages; the third program command enables the user terminal device 28 to receive new messages or reply to the input and receiving terminal settings, and the receiving terminal sets associated members; the fourth program command enables the user terminal device 28 to upload new messages or reply For the message to the server 10, the new message or reply message includes a time stamp; and, the fifth program instruction causes the client device 28 to upload the read status to the server 10 when the downloaded new message is read.

In different embodiments of the present invention, the first program instructions, the second program instructions, ... executed by the processor respectively represent a set of a plurality of program instructions, and the first, second, ..., etc. are not used to limit the sequence In the technical features or method steps expressed by the first program instruction, the second program instruction, .... Those skilled in this invention can understand that the technical features or steps expressed in the first program instruction, the second program instruction, ... can be combined or combined to be expressed by different sets of program instructions.

Referring to Fig. 2, the operation flowchart of an embodiment of the present invention illustrates the operation process of using the message sending records in the enterprise information system database to analyze the employee attitudes of all members of an organization. Please refer to Fig. 1 simultaneously, and method of the present invention comprises:

Step S101: Multiple members of an organization, corresponding multiple member information, and corresponding multiple message sending records are stored in the database 20, and the server 10 accesses the database 20.

Step S102: Define employee attitudes and establish a corresponding employee attitude analysis model and associated one to a plurality of quantifiable user behaviors. In some embodiments, the administrator with system authority can define an employee attitude and edit the employee attitude through the employee attitude analysis editing screen generated by the attitude analysis model creation module 42 on the terminal (not shown) connected to the server end 22. A corresponding attitude analysis model and one to a plurality of associated quantifiable user behaviors are established. In some other embodiments, the employee attitude analysis editing screen is generated by the attitude analysis model creation module 42, and after the administrator with system authority logs in on the client device 28 (the application program 30), he/she can use the client device 28 Displayed on the screen (not shown), the manager can execute this step on the employee attitude analysis editing screen. Quantifiable user behavior can be used as a screening or statistical condition to filter or count matching values. For example, the manager defines "participation" (one of the employee attitudes) on the employee attitude analysis editing screen and establishes the corresponding "participation Attitude analysis model" (one of the attitude analysis models), and set the associated quantifiable user behaviors as "number of new messages sent per quarter", "number of times replies to messages per quarter", "number of times online per quarter" and "per quarter The four quantifiable user behaviors of quarterly average online hours (the time period can be changed arbitrarily, and the selectable time period is: day, week, month, quarter and year, which can also be selected on the employee attitude analysis editing screen) , and positively related items, negatively related items or items that need to be weighted. The matching value of the positively related items is added, the matching value of the negatively related items is subtracted, and the items to be weighted are multiplied by the preset weight. Before any time period is selected by the manager, the attitude analysis model creation module 42 can be preset as "week", all weights are equal and all are "positively correlated". After the definition of this step is completed, the server 10 can store the setting parameters (A model=SUM(weight*matching value n)) of the aforementioned employee attitude analysis models in its memory.

Since the employee attitude analysis editing screen provides managers with permission to edit each parameter of each employee attitude analysis model (which can quantify user behavior and its corresponding weight), each employee attitude analysis model may be unique and will Results vary because of the experience of the competent managers. For example, the parameters of the centripetal force analysis model of different companies are different, which makes the personnel management policies of different companies different; and, even the same company may define different parameters of the centripetal force analysis model because of different authorized managers ; Or, authorized managers can dynamically adjust the parameters of the centripetal force analysis model by themselves, and adjust them in different periods due to changes in management experience (increase or decrease quantifiable user behaviors and their corresponding weights). In other words, the system for analyzing employee attitudes based on user behavior based on enterprise information provided by the present invention is dynamic and adjustable for the company.

In addition, in terms of another embodiment of the present invention, step S102 can provide at least two parameter setting values of the same employee attitude analysis model on the employee attitude analysis editing screen for authorized managers to compare and refer to their corresponding calculations. result. For example, the authorized administrator has set up "Participation Analysis Model 1", and set the associated quantifiable user behaviors "number of new messages sent per quarter", "number of messages replied per quarter", "number of times online per quarter" and " The four quantifiable user behaviors of "average online hours per quarter" have equal weights (all 100%) and are all positively correlated; at the same time, "participation analysis model 2" is set to set the quantifiable correlation User Behavior The four quantifiable user behaviors are "the number of new messages sent per quarter", "the number of times replies to messages per quarter", "the number of times online per quarter" and "the average number of hours online per quarter", all of which are positively correlated , and the weight of "average online hours per quarter" is 200%; and "participation analysis model 3" is set, in addition to the aforementioned four quantifiable behaviors as positively related items, another quantifiable user behavior is added "Average number of unread messages per quarter" is a negative correlation item with a weight of 200%.

Step S103: The server 10 screens and counts the message sending records of all members of the organization according to one or more quantifiable user behaviors associated with the attitude analysis model to generate matching values corresponding to quantifiable user behaviors, which can be quantified User Behavior is a field related to message sending records. Following the example of the previous step, after the "participation analysis model" is established, the user behavior analysis module 16 of the server 10 can base on the "participation analysis model" and the associated quantifiable user behavior (in this case, "every The number of new messages sent per quarter, the number of replies to messages per quarter, the number of online times per quarter, and the average online hours per quarter) to filter and count the message sending records of all members of the organization, in order to Obtain the matching value of these quantifiable user behaviors of each member (the matching value is the value corresponding to the field).

Step S104: The server 10 brings the matching value of quantifiable user behavior into the attitude analysis model for calculation to obtain a calculation result. After obtaining the matching values of these quantifiable user behaviors of each member in the previous step, each member should have 4 matching values, and then, the user behavior analysis module 16 of the server 10 will use these quantifiable user behaviors of each member The 4 matching values are brought into the "participation analysis model" in the memory for calculation to obtain the calculation result (a numerical value). Since matching values that can quantify user behaviors have been obtained and their corresponding weights have been defined (pre-defined formulas), the server 10 can dynamically and instantly calculate the calculation results of each "participation analysis model".

Step S105: The server 10 sorts all members of the organization according to the calculation result. After the previous step is executed, each member has a numerical value (the calculation result of the "participation analysis model"), and the user behavior analysis module 16 of the server 10 will upgrade all members according to the calculation result in this step sort or descending power sort.

Step S106: The server 10 generates an employee attitude analysis report according to the ranking of all members. After sorting all members in the previous step, the user behavior analysis module 16 of the server 10 generates an employee attitude analysis report of "participation". In some embodiments, the employee attitude analysis report system presents the sorted list of all members in the report; in some embodiments, the employee attitude analysis report only arranges a specific number or a specific percentage of the head and tail, for example: arranges the participation "Top 5 highest", "Bottom 5 lowest", "Top 2% highest"...etc. For example, centripetal force analysis report: 1. Wang Xiaoming 67.8; 2. Li Dayou 60.3; 3. Zhang Wuji 58.8; 4. Chen Youqing 55.5; 5. Xin Laoren 54.4; and so on. If the same employee attitude analysis model has more than two sets of parameters, the server 10 will correspondingly generate more than two sets of employee attitude analysis reports. For example: centripetal force analysis report 1: 1. Wang Xiaoming 67.8; 2. Li Dayou 60.3; 3. Zhang Wuji 58.8; 4. Chen Youqing 55.5; The quantifiable user behavior of "average times" is defined as negative correlation): 1. Old Man Xin 54.4; 2. Li Dayou 60.3; 3. Zhang Wuji 58.8; 4. Chen Youqing 55.5; 5. Wang Xiaoming 50.8. Since Wang Xiaoming often could not read back the messages from his colleagues, the results of the two groups of centripetal force analysis reports were quite different. Through the comparison of these two sets of centripetal force analysis reports, authorized managers can adjust the corresponding parameters of the optimized centripetal force analysis model accordingly.

After the employee attitude analysis report is generated, the server 10 can immediately push it to the client device 28 of each corresponding manager, so that the corresponding manager can use the screen of the client device 28 (which can be sent to the application program 30 Or in the form of a text message) to see the results of the employee attitude analysis report of its employees, so as to assist them in taking corresponding personnel management measures.

It can be understood for different embodiments of the present invention that the program instructions executed by the computer can implement each block in the flow chart, the combination of blocks in the flow chart, and the steps in each embodiment. providing the program instructions to a processor for execution to produce a machine or resources cooperating with hardware and software, whereby the instructions, when executed on the processor, will produce actions for performing the actions specified in the flowchart blocks or components of technical effects. Different sets of program instructions can also make at least some of the operation steps shown in the blocks of the flow chart be performed in parallel, and the technical content expressed by the first, second, ... program instructions of an application program may be different according to different embodiments . Furthermore, some of these steps may also be performed on more than one processor, such as may occur in a multiprocessor server computer system, or in a client device where a microprocessor and a peripheral interface processor cooperate . Furthermore, one or more blocks or combinations of blocks in the flowcharts may be performed concurrently with other blocks or combinations of blocks, or even in an order different from that shown, without departing from the scope or spirit of the present invention. .

Accordingly, the blocks of the flowchart of the present invention support combinations of means for performing specified actions or technical effects, combinations of steps for performing specified actions or technical effects, and program instruction means for performing specified actions or technical effects. It will also be understood that these specified actions or technical effects are performed by a special-purpose hardware system or special-purpose hardware and program instructions cooperating to implement each block of the flow chart of the present invention and the combination of blocks in the flow chart.

In summary, a system and method for analyzing employee attitudes based on user behavior of enterprise information disclosed in the present invention solves the problem in the prior art that "the employee attitude cannot be analyzed based on the sending records of enterprise information by enterprise members". The invention enables the enterprise organization to obtain the employee attitude analysis results automatically and quickly, reduces the cost, time and manpower invested by the enterprise in the employee attitude survey, and enables the analysis of all enterprise employees to avoid inaccurate problems caused by sampling surveys.

Although the technical content of the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any modification and modification made by those skilled in the art without departing from the spirit of the present invention should be covered by the present invention. Therefore, the scope of protection of the present invention should be defined by the scope of the appended patent application.

10:Server 12: The first network communication module 14: Login verification module 16: User Behavior Analysis Module 18: The first message module 20: Database 22: Push gateway 24: cloud 26:Push host 28: Client device 30: Apps 32: The second network communication module 34: Login module 36:Data access module 38:Second message module 40: Message input module 42: Attitude analysis model creation module

Fig. 1 is a system architecture diagram of an embodiment of the present invention; and, Fig. 2 is the operation flowchart of the embodiment of the present invention.

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10:Server

12: The first network communication module

14: Login verification module

16: User Behavior Analysis Module

18: The first message module

20: Database

22: Push gateway

24: cloud

26:Push host

28: Client device

30: Apps

32: The second network communication module

34: Login module

36:Data access module

38:Second message module

40: Message input module

42: Attitude analysis model creation module

Claims (14)

A system for analyzing employee attitudes based on user behavior of enterprise information, including: A database, storing multiple members of an organization, corresponding multiple member information, and corresponding multiple message sending records; A server accesses the database, including: A first network communication module establishes a network connection with a client device associated with one of the members; a login verification module to verify that the client device is connected to the server via the network; and A first message module, receiving and uploading a new message or a reply message and generating a list of message receivers according to a receiver setting, and storing the new message or the reply message and a corresponding read status to the data The library becomes one of the message sending records, the message receiver list includes at least one push identification code associated with the client device, and the new message or the reply message includes a time stamp; A user behavior analysis module, based on an attitude analysis model corresponding to an employee attitude and associated one or more quantifiable user behaviors, screens and counts the sending records of the messages sent by the members of the organization to generate Corresponding to a matching value of the quantifiable user behavior, the quantifiable user behavior is a field related to the message sending records, and the matching value of the quantifiable user behavior is brought into the attitude analysis model for calculation To obtain a calculation result, sort the members of the organization according to the calculation result, and then generate an employee attitude analysis report based on the ranking of the members; and The client device includes: one or more processors and a screen, the processor executes a plurality of program instructions, and the program instructions include: A first program instruction to enable the client device to establish a network connection with the server for login verification; a second program instruction to enable the client device to download the new message from the server; a third program instruction to enable the client device to receive the input of the new message or the reply message and the receiving end setting, and the receiving end setting is associated with the members; a fourth program instruction causing the client device to upload the new message or the reply message to the server, the new message or the reply message including a time stamp; and, A fifth program instruction, when the downloaded new message is read, the client device uploads the read status to the server; and A push gateway generates a push notification according to the message, and sends the push notification to the client devices corresponding to the associated members through an external push host. The system for analyzing employee attitudes based on user behavior of enterprise information as described in claim item 1, wherein the quantifiable user behavior is selected from: a number of times of sending new messages, an average number of times of sending new messages, a number of times of replying messages, a Average number of reply messages, 1 online times, 1 average online times, 1 online hours, 1 average online hours, 1 interaction number, 1 average interaction number, 10 zero interaction number, 1 average zero interaction number, 1 reply message average time , a percentage of reply messages, a number of online times during non-working hours, an average number of online times during non-working hours, a number of reply messages during non-working hours, an average number of reply messages during non-working hours, a number of online hours during non-working hours, and an average number of times during non-working hours Online hours, an average time to reply to messages during non-working hours, a number of unread messages, an average number of unread messages, an average read time, a number of read messages that were not returned, and an average number of messages that were read but not returned. The system for analyzing employee attitudes based on user behavior of enterprise information as described in Claim 1, wherein the quantifiable user behavior can select a time period to calculate the matching value within the time period, and the time period is selected from : One day, one week, one month, one season and one year. The system for analyzing employee attitudes based on user behavior of enterprise information as described in Claim 1, wherein when the attitude analysis model includes a positive correlation of the quantifiable user behavior and a negative correlation of the quantifiable user behavior In the calculation of the attitude analysis model, "the matching value of the quantifiable user behavior of the positive correlation" is subtracted from "the matching value of the quantifiable user behavior of the negative correlation". The system for analyzing employee attitudes based on user behavior of enterprise information as described in claim 1, wherein the server further includes: an attitude analysis model creation module, providing a graphical user interface and a management interface for those with system authority A manager defines the employee's attitude and establishes the corresponding attitude analysis model and associated one or more quantifiable user behaviors, and the quantifiable user behavior is used as a filtering or statistical condition to filter or count the matching value. The system for analyzing employee attitudes based on user behavior of enterprise information as described in claim item 1, wherein the employee attitude and the corresponding attitude analysis model are selected from: a degree of participation and a corresponding degree of participation analysis model, a degree of participation Centripetal force and a corresponding centripetal force analysis model, a degree of enthusiasm and a corresponding degree of enthusiasm analysis model, an interpersonal relationship and a corresponding interpersonal relationship analysis model, and an engagement degree and a corresponding engagement degree analysis model . The system for analyzing employee attitudes based on user behavior of enterprise information as described in request item 6, one of the enterprise information systems is embedded with the employee attitude and the corresponding attitude analysis model, and the ready-made employee attitude and the corresponding attitude analysis model are used The corresponding attitude analysis model can generate the corresponding employee attitude analysis report. A method for analyzing employee attitudes based on user behavior of enterprise information is applied to an enterprise information system composed of a database and a server. The method includes: Store multiple members of an organization, corresponding multiple member information, and corresponding multiple message sending records in the database, and access the database by the server; Define an employee attitude and establish a corresponding employee attitude analysis model and associated one or more quantifiable user behaviors; The server screens and counts the message sending records of the members of the organization based on one or more quantifiable user behaviors associated with the attitude analysis model to generate a match corresponding to the quantifiable user behavior Value, the quantifiable user behavior is a field related to these message sending records; The server brings the matching value of the quantifiable user behavior into the attitude analysis model for calculation to obtain a calculation result; the server performs a ranking of the members of the organization according to the calculation result; and, The server generates an employee attitude analysis report according to the ranking of the members. The method for analyzing employee attitudes based on user behavior of enterprise information as described in claim item 8, wherein the quantifiable user behavior is selected from: a number of times of sending new messages, an average number of times of sending new messages, a number of times of replying messages, a Average number of reply messages, 1 online times, 1 average online times, 1 online hours, 1 average online hours, 1 interaction number, 1 average interaction number, 10 zero interaction number, 1 average zero interaction number, 1 reply message average time , a percentage of reply messages, a number of online times during non-working hours, an average number of online times during non-working hours, a number of reply messages during non-working hours, an average number of reply messages during non-working hours, a number of online hours during non-working hours, and an average number of times during non-working hours Online hours, an average time to reply to messages during non-working hours, a number of unread messages, an average number of unread messages, an average read time, a number of read messages that were not returned, and an average number of messages that were read but not returned. The method for analyzing employee attitudes based on user behavior of enterprise information as described in Claim 8, wherein the quantifiable user behavior can select a time period to calculate the matching value within the time period, and the time period is selected from : One day, one week, one month, one season and one year. The method for analyzing employee attitudes based on user behavior of enterprise information as described in Claim 8, wherein when the attitude analysis model includes a positive correlation of the quantifiable user behavior and a negative correlation of the quantifiable user behavior In the calculation of the attitude analysis model, "the matching value of the quantifiable user behavior of the positive correlation" is subtracted from "the matching value of the quantifiable user behavior of the negative correlation". The method for analyzing employee attitudes based on user behavior of enterprise information as described in claim item 8, wherein the server further includes: an attitude analysis model creation module that provides a graphical user interface and a management interface for users with system authority A manager defines the employee's attitude and establishes a corresponding attitude analysis model and associated one or more quantifiable user behaviors. The quantifiable user behaviors are used as screening or statistical conditions to filter or count the matching values. The method for analyzing employee attitudes based on user behavior of enterprise information as described in claim item 8, wherein the employee attitude and the corresponding attitude analysis model are selected from: a degree of participation and a corresponding degree of participation analysis model, a degree of participation Centripetal force and a corresponding centripetal force analysis model, a degree of enthusiasm and a corresponding degree of enthusiasm analysis model, an interpersonal relationship and a corresponding interpersonal relationship analysis model, and an engagement degree and a corresponding engagement degree analysis model . The method for analyzing employee attitudes based on user behavior of enterprise information as described in claim 13, the method further includes: the enterprise information system is embedded with the employee attitude and the corresponding attitude analysis model; and, applying the ready-made said attitude The staff attitude and the corresponding attitude analysis model can generate the corresponding staff attitude analysis report.

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