Airline competitiveness analysis method, system and equipment, medium and program product

Abstract

The invention provides an airline competitiveness analysis method, system and device, a medium and a program product. The analysis method comprises the steps of obtaining historical dimension index data of different airlines; obtaining scores of the historical dimension index data; comparing the score of the historical dimension index data of the target airline with the scores of the historical dimension index data of other airlines to obtain a comparison result; and analyzing the competitiveness of the target airline according to a comparison result. The score of the historical dimension index data of the target airline is compared with the scores of the historical dimension index data of other airlines; the competitive power of the target airline is analyzed according to the comparison result, the problems that data of other airlines in the market are difficult to acquire and user behavior data in the market are difficult to measure are solved, and the competitive level of each key operation index of the airline in the market is quantitatively given.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to an analysis method, system, device, medium and program product for airline competitiveness. Background Art

[0002] With the advancement of aviation technology and the reduction of costs, it has become easier for new airlines to emerge and for existing airlines to expand, which has led to more airlines entering the market and competition among airlines becoming increasingly fierce. With the development of the global tourism industry and the rise of emerging markets, passengers' demand for aviation services is also changing. Airlines need to constantly adapt to changes in market demand to meet passenger needs and maintain competitiveness. Whether facing increasingly fierce market competition or increasingly complex passenger needs, airlines need to continuously improve their competitiveness to adapt to market changes and attract more passengers. Therefore, the market competitiveness analysis of airlines is of great significance to airlines.

[0003] Through scientific and effective market competitiveness analysis, insights into market demand, customer preferences and competitors can be provided, thus helping airlines make smarter business decisions. For example, understanding competitors' pricing strategies can help airlines formulate competitive fares. It can help airlines understand their position in the market and the gap with competitors. This helps to formulate strategic plans, including market positioning, product and service development, and marketing strategies. At the same time, competitiveness analysis can reveal the weaknesses and opportunities of airlines in operations and management. However, it is currently difficult for an airline to obtain data from other airlines and it is difficult to measure market user behavior data. Summary of the invention

[0004] The technical problem to be solved by the present disclosure is to overcome the defects in the prior art that it is difficult for an airline to obtain data from other airlines and it is difficult to measure market user behavior data, and to provide an analysis method, system, equipment, medium and program product for airline competitiveness.

[0005] The present invention solves the above technical problems through the following technical solutions:

[0006] A first aspect of the present disclosure provides a method for analyzing the competitiveness of airline companies, the method comprising:

[0007] Obtain historical dimension indicator data of different airlines;

[0008] Obtaining the score of the historical dimension indicator data;

[0009] Compare the scores of the historical dimension indicator data of the target airline with the scores of the historical dimension indicator data of other airlines to obtain a comparison result;

[0010] Analyze the competitiveness of the target airline based on the comparison results.

[0011] Preferably, the historical dimension indicator data includes at least one of price competitiveness, passenger load factor, seat-kilometer revenue, brand loyalty, and flight selection probability;

[0012] The step of obtaining the score of the historical dimension indicator data comprises:

[0013] Obtain price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score;

[0014] The step of comparing the scores of the historical dimension index data of the target airline with the scores of the historical dimension index data of other airlines to obtain the comparison result comprises:

[0015] The price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of the target airline are compared with those of other airlines to obtain the comparison results.

[0016] Preferably, the step of obtaining the price competitiveness score comprises:

[0017] Get the difference between the ticket price of each route of each airline and the market average price;

[0018] According to the amplitude value, the total ticket volume of each route corresponding to each airline is weighted averaged to obtain the ticket price index of each airline;

[0019] Sort the air ticket price index from small to large to obtain the air ticket price index sorting result;

[0020] Obtaining a price competitiveness score according to the ranking result of the air ticket price index;

[0021] The airfare index is negatively correlated with the price competitiveness score.

[0022] Preferably, the step of obtaining the passenger load factor score includes:

[0023] Get the passenger volume and seat capacity of each airline;

[0024] Dividing the passenger volume by the number of seats to obtain the passenger load factor;

[0025] Sort the occupancy rates from large to small to obtain an occupancy rate sorting result;

[0026] Obtaining a passenger load factor score according to the passenger load factor ranking result;

[0027] The occupancy rate is positively correlated with the occupancy rate score.

[0028] Preferably, the step of obtaining the seat-kilometer revenue score includes:

[0029] Get the ticket price, actual number of passengers, seat capacity and flight kilometres for each airline;

[0030] The ticket price is multiplied by the actual number of passengers and then divided by the product of the seat capacity and the flight kilometres to obtain the seat-kilometre revenue;

[0031] Sort the seat-kilometer revenue from largest to smallest to obtain a seat-kilometer revenue sorting result;

[0032] Obtaining a seat-kilometer revenue score according to the seat-kilometer revenue ranking result;

[0033] The seat-kilometer revenue is positively correlated with the seat-kilometer revenue score.

[0034] Preferably, the step of obtaining the brand loyalty score includes:

[0035] Get the percentage of the target airline among all flights taken by the user at the preset time in history and the total number of flights taken by the user;

[0036] The brand loyalty is obtained by taking a weighted average of the proportions according to the total number of flights taken by the user;

[0037] Sorting the brand loyalty from large to small to obtain a brand loyalty ranking result;

[0038] Obtaining a brand loyalty score according to the brand loyalty ranking result;

[0039] The brand loyalty is positively correlated with the brand loyalty score;

[0040] and / or,

[0041] The steps to obtain the flight selection probability score include:

[0042] Get the ratio of the number of tickets purchased by the target airline to the total number of tickets for each route;

[0043] Taking a weighted average of the proportions according to the total number of tickets for the route, the probability of flight selection is obtained;

[0044] Sort the flight selection probabilities from large to small to obtain a flight selection probability sorting result;

[0045] Obtaining a flight selection probability score according to the flight selection probability ranking result;

[0046] The flight selection probability is positively correlated with the flight selection probability score.

[0047] A second aspect of the present disclosure provides an analysis system for airline competitiveness, the analysis system comprising:

[0048] The first acquisition module is used to obtain historical dimension indicator data of different airlines;

[0049] A second acquisition module is used to obtain the score of the historical dimension indicator data;

[0050] A comparison module, used to compare the scores of the historical dimension index data of the target airline with the scores of the historical dimension index data of other airlines to obtain a comparison result;

[0051] The analysis module is used to analyze the competitiveness of the target airline based on the comparison results.

[0052] Preferably, the historical dimension indicator data includes at least one of price competitiveness, passenger load factor, seat-kilometer revenue, brand loyalty, and flight selection probability;

[0053] The second acquisition module is used to acquire a price competitiveness score, a passenger load factor score, a seat-kilometer revenue score, a brand loyalty score, and a flight selection probability score;

[0054] The comparison module is used to compare the price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of the target airline with the price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of other airlines to obtain a comparison result.

[0055] Preferably, the second acquisition module includes:

[0056] The first acquisition unit is used to obtain the value of the difference between the ticket price of each route corresponding to each airline and the market average price;

[0057] A second acquisition unit is used to perform weighted average on the total ticket quantity of each route corresponding to each airline according to the amplitude value to obtain the ticket price index of each airline;

[0058] A first sorting unit is used to sort the air ticket price index from small to large to obtain a sorting result of the air ticket price index;

[0059] A third acquisition unit, configured to acquire a price competitiveness score according to the ranking result of the air ticket price index;

[0060] The airfare index is negatively correlated with the price competitiveness score.

[0061] Preferably, the second acquisition module includes:

[0062] The fourth acquisition unit is used to obtain the passenger volume and seat number of each airline;

[0063] a fifth obtaining unit, configured to divide the passenger volume by the number of seats to obtain a passenger load factor;

[0064] A second sorting unit is used to sort the passenger load factors from large to small to obtain a passenger load factor sorting result;

[0065] A sixth acquiring unit, configured to acquire an occupancy rate score according to the occupancy rate ranking result;

[0066] The occupancy rate is positively correlated with the occupancy rate score.

[0067] Preferably, the second acquisition module includes:

[0068] The seventh acquisition unit is used to obtain the ticket price, actual number of passengers, seat capacity and flight kilometres of each airline;

[0069] an eighth obtaining unit, configured to obtain seat-kilometer revenue by multiplying the ticket price by the actual number of passengers and then dividing the result by the multiplication of the seat capacity and the flight kilometres;

[0070] A third sorting unit is used to sort the seat-kilometer revenue from large to small to obtain a seat-kilometer revenue sorting result;

[0071] A ninth acquisition unit, configured to acquire a seat-kilometer revenue score according to the seat-kilometer revenue ranking result;

[0072] The seat-kilometer revenue is positively correlated with the seat-kilometer revenue score.

[0073] Preferably, the second acquisition module includes:

[0074] A tenth acquisition unit is used to acquire the proportion of the target airline among all flights taken by the user at the historical preset time and the total number of times the user took all flights;

[0075] an eleventh obtaining unit, configured to perform a weighted average of the proportions according to the total number of times the user takes all flights, to obtain brand loyalty;

[0076] A fourth sorting unit, used to sort the brand loyalty from large to small to obtain a brand loyalty sorting result;

[0077] a twelfth obtaining unit, configured to obtain a brand loyalty score according to the brand loyalty ranking result;

[0078] The brand loyalty is positively correlated with the brand loyalty score;

[0079] and / or,

[0080] The second acquisition module includes:

[0081] The thirteenth acquisition unit is used to obtain the ratio of the number of tickets purchased by the target airline on each route to the total number of tickets for the route;

[0082] A fourteenth obtaining unit, configured to perform a weighted average of the proportions according to the total number of tickets for the route to obtain a flight selection probability;

[0083] A fifth sorting unit, configured to sort the flight selection probabilities from large to small to obtain a flight selection probability sorting result;

[0084] A fifteenth obtaining unit, configured to obtain a flight selection probability score according to the flight selection probability ranking result;

[0085] The flight selection probability is positively correlated with the flight selection probability score.

[0086] A third aspect of the present disclosure provides an electronic device, including a memory, a processor, and a computer program stored in the memory and used to run on the processor, wherein the processor implements the airline competitiveness analysis method described in the first aspect when executing the computer program.

[0087] A fourth aspect of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the airline competitiveness analysis method described in the first aspect.

[0088] A fifth aspect of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements the airline competitiveness analysis method as described in the first aspect.

[0089] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present disclosure.

[0090] The positive and progressive effects of this disclosure are:

[0091] This disclosure compares the scores of the historical dimension indicator data of the target airline with the scores of the historical dimension indicator data of other airlines; analyzes the competitiveness of the target airline based on the comparison results, solves the problems of difficulty in obtaining data from other airlines in the market and difficulty in measuring market user behavior data, and quantitatively gives the competitive level of each key operating indicator of the airline in the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] Figure 1A flowchart of the airline competitiveness analysis method provided in Example 1 of the present disclosure.

[0093] Figure 2 A schematic diagram of the modules of the airline competitiveness analysis system provided in Example 2 of the present disclosure.

[0094] Figure 3 This is a schematic diagram of the structure of an electronic device for implementing the airline competitiveness analysis method of embodiment 3 of the present disclosure. DETAILED DESCRIPTION

[0095] The present disclosure is further described below by way of examples, but the present disclosure is not limited to the scope of the examples.

[0096] Prefixes such as "first" and "second" are used in the embodiments of the present disclosure only to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects. The use of prefixes such as ordinal numbers to distinguish description objects in the embodiments of the present disclosure does not constitute a limitation on the described objects. For the statement of the described objects, please refer to the description in the context of the claims or embodiments, and no unnecessary limitation should be constituted due to the use of such prefixes. In addition, in the description of the present embodiment, unless otherwise specified, the meaning of "plurality" is two or more.

[0097] In the embodiments of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0098] Example 1

[0099] Figure 1 A flowchart of a method for analyzing airline competitiveness provided in Example 1 of the present disclosure is shown in FIG. Figure 1 As shown, the analysis method includes:

[0100] S1. Obtain historical dimension indicator data of different airlines;

[0101] S2. Obtain the scores of historical dimension indicator data;

[0102] S3. Compare the scores of the historical dimension index data of the target airline with the scores of the historical dimension index data of other airlines to obtain a comparison result;

[0103] S4. Analyze the competitiveness of the target airline based on the comparison results.

[0104] This embodiment compares the scores of the historical dimension indicator data of the target airline with the scores of the historical dimension indicator data of other airlines; analyzes the competitiveness of the target airline based on the comparison results, solves the problems of difficulty in obtaining data from other airlines in the market and difficulty in measuring market user behavior data, and quantitatively gives the competitive level of each key operating indicator of the airline in the market.

[0105] In an optional embodiment, the historical dimension indicator data includes at least one of price competitiveness, passenger load factor, seat-kilometer revenue, brand loyalty, and flight selection probability;

[0106] Step S2 includes:

[0107] S21. Obtain price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score;

[0108] Step S3 includes:

[0109] S31. Compare the price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of the target airline with the price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of other airlines to obtain a comparison result.

[0110] This embodiment mainly measures the competitiveness score of an airline from five dimensions: price competitiveness, passenger load factor, revenue per seat kilometer, brand loyalty, and flight selection probability. The operating performance of the airline and its ranking in the market are analyzed by comparing it with other airlines in the market.

[0111] In an optional embodiment, the step of obtaining the price competitiveness score in step S21 includes:

[0112] S21-11. Obtain the value by which the airfare of each route corresponding to each airline is higher than the market average price;

[0113] S21-12. Perform a weighted average of the total ticket volume for each route corresponding to each airline according to the amplitude value to obtain the ticket price index of each airline;

[0114] S21-13, sorting the air ticket price index from small to large to obtain the air ticket price index sorting result;

[0115] S21-14. Obtain price competitiveness scores based on the ranking results of the air ticket price index;

[0116] The airfare index is negatively correlated with the price competitiveness score.

[0117] In this embodiment, price competitiveness analysis: the competitiveness of airline ticket prices compared to the market average price, for each airline, calculate the extent to which the airline's ticket price on each route is higher than the market average price (for example, the airline's average price for the route / the market average price for the route-1), and then take a weighted average according to the total ticket volume of each route to obtain the airline's ticket price index relative to the market; the ticket price index obtained by the above calculation method is sorted from small to large, and the airlines with low ticket price indexes have high price competitiveness scores (that is, airlines with lower discounts have high scores, and airlines with higher discounts have low scores). For example, the top 10% of airlines are scored 10 points, airlines ranked 10%-20% are scored 9 points, and so on, and the last 10% of airlines are scored 1 point.

[0118] In an optional embodiment, the step of obtaining the passenger load factor score in step S21 includes:

[0119] S21-21. Obtain the passenger volume and number of seats of each airline;

[0120] S21-22, divide the passenger volume by the number of seats to obtain the passenger load factor;

[0121] S21-23, sorting the passenger load factor from large to small to obtain a passenger load factor sorting result;

[0122] S21-24, obtaining a passenger load factor score according to the passenger load factor ranking result;

[0123] The load factor is positively correlated with the load factor score.

[0124] In this embodiment, the load factor of each airline = passenger volume / number of seats, and the load factor is used to measure the efficiency of capacity investment; the airlines are sorted from large to small by load factor, and the airlines with high load factors have high scores, and the airlines with low load factors have low scores. For example, the top 10% of airlines are scored 10 points, the airlines ranked 10%-20% are scored 9 points, and so on. The last 10% of airlines are scored 1 point.

[0125] In an optional embodiment, the step of obtaining the seat-kilometer revenue score in step S21 includes:

[0126] S21-31, obtain the ticket price, actual number of passengers, seat capacity and flight kilometres of each airline;

[0127] S21-32, multiply the ticket price by the actual number of seats and then divide it by the product of the seat capacity and the flight kilometers to obtain the seat-kilometer revenue;

[0128] S21-33, sorting the seat-kilometer revenue from large to small to obtain a seat-kilometer revenue sorting result;

[0129] S21-34, obtaining a seat-kilometer revenue score according to the seat-kilometer revenue ranking result;

[0130] The seat-kilometer revenue is positively correlated with the seat-kilometer revenue score.

[0131] In this embodiment, the revenue level of an airline is measured by seat-kilometer revenue = (ticket price * actual number of seats of the airline) / (seat capacity * flight kilometers). Sorted from high to low by seat-kilometer revenue, airlines with high seat-kilometer revenue score high, and airlines with low seat-kilometer revenue score low. For example, the top 10% of airlines are scored 10 points, airlines ranked 10%-20% are scored 9 points, and so on, and the bottom 10% of airlines are scored 1 point.

[0132] In an optional embodiment, the step of obtaining the brand loyalty score in step S21 includes:

[0133] S21-41, obtaining the percentage of the target airline among all flights taken by the user at the preset time in history and the total number of flights taken by the user;

[0134] S21-42. Take a weighted average of the proportions based on the total number of flights taken by the user to obtain brand loyalty;

[0135] S21-43, sorting the brand loyalty from large to small to obtain the brand loyalty ranking result;

[0136] S21-44, obtaining a brand loyalty score according to the brand loyalty ranking result;

[0137] Brand loyalty is positively correlated with brand loyalty scores;

[0138] In this embodiment, the proportion of users taking the target airline (for example, Airline X) when traveling is calculated. For each airline, the proportion of the target airline in all flights taken by the user in the historical preset time (for example, in the past year) is calculated, and then the proportion is weighted averaged according to the total number of times the user takes all flights to obtain brand loyalty; the airlines are sorted from large to small according to the above calculated proportions, and the airlines with a large proportion have a high score, and the airlines with a small proportion have a low score. For example, the top 10% of airlines are scored 10 points, the airlines ranked 10%-20% are scored 9 points, and so on. The last 10% of airlines are scored 1 point.

[0139] In an optional embodiment, the step of obtaining the flight selection probability score in step S21 includes:

[0140] S21-51, obtain the ratio of the number of tickets purchased by the target airline on each route to the total number of tickets on the route;

[0141] S21-52, taking a weighted average of the proportions according to the total number of tickets for the route, and obtaining the probability of flight selection;

[0142] S21-53, sorting the flight selection probabilities from large to small to obtain a flight selection probability sorting result;

[0143] S21-54, obtaining a flight selection probability score according to the flight selection probability ranking result;

[0144] The flight selection probability is positively correlated with the flight selection probability score.

[0145] In this embodiment, the number of passenger tickets that select the target airline (for example, Airline X) on the route accounts for the proportion of the total number of tickets on the route. For each airline, calculate the ratio of the number of tickets purchased by the target airline on each route to the total number of tickets on the route (that is, the number of tickets purchased by the target airline on each route divided by the total number of tickets on the route), and then perform a weighted average of the ratio according to the total number of tickets on the route to obtain the probability of flight selection. Sort by the ratio calculated above from large to small, with airlines with large ratios scoring high and airlines with small ratios scoring low. For example, the top 10% of airlines are given 10 points, airlines ranked 10%-20% are given 9 points, and so on, and the bottom 10% of airlines are given 1 point.

[0146] This disclosure is intended to help airlines analyze their own competitiveness level. By providing key operational information about the market, competitors and customers, it helps airlines formulate strategic plans, improve operational levels and market competitiveness, and improve management efficiency and risk management capabilities. From the perspectives of sales, prices, user behavior of various routes of different airlines in the market, and from the perspectives of historical demand and passenger preferences, it provides airlines with corresponding methods and strategic guidance in market competitiveness analysis; it helps airlines solve the problems of difficulty in obtaining data from other airlines in the market and difficulty in measuring market user behavior data, and quantitatively gives the competitive level of each key operational indicator of the airline in the market; it improves the market competitiveness analysis methodology for airlines, and provides airlines with quantitative solutions for their strategic planning, macro-advantages and disadvantages analysis, and potential opportunity identification in the context of increasingly fierce market competition.

[0147] Example 2

[0148] Corresponding to the aforementioned embodiment of an airline competitiveness analysis method, the present disclosure also provides an embodiment of an airline competitiveness analysis system.

[0149] Figure 2 A schematic diagram of a module of an airline competitiveness analysis system provided in Embodiment 2 of the present disclosure, such as Figure 2 As shown, the analysis system includes: a first acquisition module 21, a second acquisition module 22, a comparison module 23, and an analysis module 24;

[0150] The first acquisition module 21 is used to obtain historical dimension indicator data of different airlines;

[0151] The second acquisition module 22 is used to obtain the scores of historical dimension indicator data;

[0152] A comparison module 23, used to compare the scores of the historical dimension index data of the target airline with the scores of the historical dimension index data of other airlines to obtain a comparison result;

[0153] The analysis module 24 is used to analyze the competitiveness of the target airline according to the comparison results.

[0154] This embodiment compares the scores of the historical dimension indicator data of the target airline with the scores of the historical dimension indicator data of other airlines; analyzes the competitiveness of the target airline based on the comparison results, solves the problems of difficulty in obtaining data from other airlines in the market and difficulty in measuring market user behavior data, and quantitatively gives the competitive level of each key operating indicator of the airline in the market.

[0155] In an optional embodiment, the historical dimension indicator data includes at least one of price competitiveness, passenger load factor, seat-kilometer revenue, brand loyalty, and flight selection probability;

[0156] The second acquisition module is used to obtain the price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score;

[0157] The comparison module is used to compare the price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of the target airline with the price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of other airlines to obtain a comparison result.

[0158] This embodiment mainly measures the competitiveness score of an airline from five dimensions: price competitiveness, passenger load factor, revenue per seat kilometer, brand loyalty, and flight selection probability. The operating performance of the airline and its ranking in the market are analyzed by comparing it with other airlines in the market.

[0159] In an optional embodiment, the second acquisition module includes:

[0160] The first acquisition unit is used to obtain the value of the difference between the ticket price of each route corresponding to each airline and the market average price;

[0161] The second acquisition unit is used to perform weighted average on the total ticket quantity of each route corresponding to each airline according to the amplitude value to obtain the ticket price index of each airline;

[0162] The first sorting unit is used to sort the air ticket price index from small to large to obtain the air ticket price index sorting result;

[0163] A third acquisition unit is used to acquire a price competitiveness score according to the ranking result of the air ticket price index;

[0164] The airfare index is negatively correlated with the price competitiveness score.

[0165] In this embodiment, price competitiveness analysis: the competitiveness of airline ticket prices compared to the market average price, for each airline, calculate the extent to which the airline's ticket price on each route is higher than the market average price (for example, the airline's average price for the route / the market average price for the route-1), and then take a weighted average according to the total ticket volume of each route to obtain the airline's ticket price index relative to the market; the ticket price index obtained by the above calculation method is sorted from small to large, and the airlines with low ticket price indexes have high price competitiveness scores (that is, airlines with lower discounts have high scores, and airlines with higher discounts have low scores). For example, the top 10% of airlines are scored 10 points, airlines ranked 10%-20% are scored 9 points, and so on, and the last 10% of airlines are scored 1 point.

[0166] In an optional embodiment, the second acquisition module includes:

[0167] The fourth acquisition unit is used to obtain the passenger volume and seat number of each airline;

[0168] a fifth obtaining unit, configured to divide the passenger volume by the number of seats to obtain a passenger load factor;

[0169] The second sorting unit is used to sort the passenger load factors from large to small to obtain a passenger load factor sorting result;

[0170] A sixth acquisition unit, configured to acquire an occupancy rate score according to the occupancy rate ranking result;

[0171] The load factor is positively correlated with the load factor score.

[0172] In this embodiment, the load factor of each airline = passenger volume / number of seats, and the load factor is used to measure the efficiency of capacity investment; the airlines are sorted from large to small by load factor, and the airlines with high load factors have high scores, and the airlines with low load factors have low scores. For example, the top 10% of airlines are scored 10 points, the airlines ranked 10%-20% are scored 9 points, and so on. The last 10% of airlines are scored 1 point.

[0173] In an optional embodiment, the second acquisition module includes:

[0174] The seventh acquisition unit is used to obtain the ticket price, actual number of passengers, seat capacity and flight kilometres of each airline;

[0175] An eighth acquisition unit is used to multiply the ticket price by the actual number of seats and then divide the result by the multiplication of the seat capacity and the flight kilometers to obtain the seat-kilometer revenue;

[0176] The third sorting unit is used to sort the seat-kilometer revenue from large to small to obtain a seat-kilometer revenue sorting result;

[0177] A ninth acquisition unit, configured to acquire a seat-kilometer revenue score according to the seat-kilometer revenue ranking result;

[0178] The seat-kilometer revenue is positively correlated with the seat-kilometer revenue score.

[0179] In this embodiment, the revenue level of an airline is measured by seat-kilometer revenue = (ticket price * actual number of seats of the airline) / (seat capacity * flight kilometers). Sorted from high to low by seat-kilometer revenue, airlines with high seat-kilometer revenue score high, and airlines with low seat-kilometer revenue score low. For example, the top 10% of airlines are scored 10 points, airlines ranked 10%-20% are scored 9 points, and so on, and the bottom 10% of airlines are scored 1 point.

[0180] In an optional embodiment, the second acquisition module includes:

[0181] A tenth acquisition unit is used to acquire the proportion of the target airline among all flights taken by the user at the historical preset time and the total number of times the user took all flights;

[0182] The eleventh acquisition unit is used to perform a weighted average of the proportions according to the total number of times the user takes all flights to obtain brand loyalty;

[0183] The fourth sorting unit is used to sort the brand loyalty from large to small to obtain a brand loyalty sorting result;

[0184] A twelfth obtaining unit, used for obtaining a brand loyalty score according to the brand loyalty ranking result;

[0185] Brand loyalty is positively correlated with brand loyalty scores;

[0186] In this embodiment, the proportion of users taking the target airline (for example, Airline X) when traveling is calculated. For each airline, the proportion of the target airline in all flights taken by the user in the historical preset time (for example, in the past year) is calculated, and then the proportion is weighted averaged according to the total number of times the user takes all flights to obtain brand loyalty; the airlines are sorted from large to small according to the above calculated proportions, and the airlines with a large proportion have a high score, and the airlines with a small proportion have a low score. For example, the top 10% of airlines are scored 10 points, the airlines ranked 10%-20% are scored 9 points, and so on. The last 10% of airlines are scored 1 point.

[0187] In an optional embodiment, the second acquisition module includes:

[0188] The thirteenth acquisition unit is used to obtain the ratio of the number of tickets purchased by the target airline on each route to the total number of tickets for the route;

[0189] A fourteenth obtaining unit is used to perform weighted average of the proportions according to the total number of tickets for the route to obtain a flight selection probability;

[0190] A fifth sorting unit is used to sort the flight selection probabilities from large to small to obtain a flight selection probability sorting result;

[0191] A fifteenth obtaining unit, used for obtaining a flight selection probability score according to the flight selection probability ranking result;

[0192] The flight selection probability is positively correlated with the flight selection probability score.

[0193] In this embodiment, the number of passenger tickets that select the target airline (for example, Airline X) on the route accounts for the proportion of the total number of tickets on the route. For each airline, calculate the ratio of the number of tickets purchased by the target airline on each route to the total number of tickets on the route (that is, the number of tickets purchased by the target airline on each route divided by the total number of tickets on the route), and then perform a weighted average of the ratio according to the total number of tickets on the route to obtain the probability of flight selection. Sort by the ratio calculated above from large to small, with airlines with large ratios scoring high and airlines with small ratios scoring low. For example, the top 10% of airlines are given 10 points, airlines ranked 10%-20% are given 9 points, and so on, and the bottom 10% of airlines are given 1 point.

[0194] This disclosure is intended to help airlines analyze their own competitiveness level. By providing key operational information about the market, competitors and customers, it helps airlines formulate strategic plans, improve operational levels and market competitiveness, and improve management efficiency and risk management capabilities. From the perspectives of sales, prices, user behavior of various routes of different airlines in the market, and from the perspectives of historical demand and passenger preferences, it provides airlines with corresponding methods and strategic guidance in market competitiveness analysis; it helps airlines solve the problems of difficulty in obtaining data from other airlines in the market and difficulty in measuring market user behavior data, and quantitatively gives the competitive level of each key operational indicator of the airline in the market; it improves the market competitiveness analysis methodology for airlines, and provides airlines with quantitative solutions for their strategic planning, macro-advantages and disadvantages analysis, and potential opportunity identification in the context of increasingly fierce market competition.

[0195] As for the system embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The system embodiment described above is only illustrative, wherein the units described as separate components may or may not be physically separated, and the components as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the disclosed solution.

[0196] Example 3

[0197] Figure 3 This is a schematic diagram of the structure of an electronic device shown in Embodiment 3 of the present disclosure, wherein the electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor, and when the processor executes the computer program, the method for analyzing the competitiveness of an airline as described in any of the above embodiments is implemented. Figure 3 The electronic device 90 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0198] like Figure 3 As shown, the electronic device 90 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 90 may include, but are not limited to: at least one processor 91, at least one memory 92, and a bus 93 connecting different system components (including the memory 92 and the processor 91).

[0199] The bus 93 includes a data bus, an address bus, and a control bus.

[0200] The memory 92 may include a volatile memory, such as a random access memory (RAM) 921 and / or a cache memory 922 , and may further include a read-only memory (ROM) 923 .

[0201] The memory 92 may also include a program tool 925 (or utility) having a set (at least one) of program modules 924, such program modules 924 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include an implementation of a network environment.

[0202] The processor 91 executes various functional applications and data processing by running the computer program stored in the memory 92, such as the airline competitiveness analysis method provided in any of the above embodiments.

[0203] The electronic device 90 may also communicate with one or more external devices 94 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 95. Furthermore, the electronic device 90 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 96. Figure 3As shown, the network adapter 96 communicates with other modules of the electronic device 90 via the bus 93. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 90, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0204] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0205] Example 4

[0206] Embodiment 4 of the present disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the airline competitiveness analysis method provided in any of the above embodiments.

[0207] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0208] Example 5

[0209] Embodiment 5 of the present disclosure also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for analyzing the competitiveness of an airline.

[0210] Among them, the program code for executing the computer program product of the present disclosure can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0211] Although the specific embodiments of the present disclosure are described above, those skilled in the art should understand that this is only an example, and the protection scope of the present disclosure is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present disclosure, but these changes and modifications all fall within the protection scope of the present disclosure.

Claims

1. A method for analyzing airline competitiveness, characterized in that: The analysis method comprises: Obtain historical dimension indicator data of different airlines; Obtaining the score of the historical dimension indicator data; Compare the scores of the historical dimension indicator data of the target airline with the scores of the historical dimension indicator data of other airlines to obtain a comparison result; Analyze the competitiveness of the target airline based on the comparison results.

2. The method for analyzing airline competitiveness according to claim 1, characterized in that: The historical dimension indicator data includes at least one of price competitiveness, passenger load factor, seat-kilometer revenue, brand loyalty, and flight selection probability; The step of obtaining the score of the historical dimension indicator data comprises: Obtain price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score; The step of comparing the scores of the historical dimension index data of the target airline with the scores of the historical dimension index data of other airlines to obtain the comparison result comprises: The price competitiveness score, passenger load factor score, seat-kilometer revenue score, brand loyalty score, and flight selection probability score of the target airline are compared with those of other airlines to obtain the comparison results.

3. The method for analyzing airline competitiveness according to claim 2, characterized in that: The steps of obtaining the price competitiveness score include: Get the difference between the ticket price of each route of each airline and the market average price; According to the amplitude value, the total ticket volume of each route corresponding to each airline is weighted averaged to obtain the ticket price index of each airline; Sort the air ticket price index from small to large to obtain the air ticket price index sorting result; Obtaining a price competitiveness score according to the ranking result of the air ticket price index; The airfare index is negatively correlated with the price competitiveness score.

4. The method for analyzing airline competitiveness according to claim 2, characterized in that: The steps to obtain the load factor score include: Get the passenger volume and seat capacity of each airline; Dividing the passenger volume by the number of seats to obtain the passenger load factor; Sort the occupancy rates from large to small to obtain an occupancy rate sorting result; Obtaining a passenger load factor score according to the passenger load factor ranking result; The occupancy rate is positively correlated with the occupancy rate score.

5. The method for analyzing airline competitiveness according to claim 2, characterized in that: The steps to obtain seat-kilometer revenue score include: Get the ticket price, actual number of passengers, seat capacity and flight kilometres for each airline; The ticket price is multiplied by the actual number of passengers and then divided by the product of the seat capacity and the flight kilometres to obtain the seat-kilometre revenue; Sort the seat-kilometer revenue from largest to smallest to obtain a seat-kilometer revenue sorting result; Obtaining a seat-kilometer revenue score according to the seat-kilometer revenue ranking result; The seat-kilometer revenue is positively correlated with the seat-kilometer revenue score.

6. The method for analyzing airline competitiveness according to claim 2, characterized in that: The steps to derive your brand loyalty score include: Get the percentage of the target airline among all flights taken by the user at the preset time in history and the total number of flights taken by the user; The brand loyalty is obtained by taking a weighted average of the proportions according to the total number of flights taken by the user; Sorting the brand loyalty from large to small to obtain a brand loyalty ranking result; Obtaining a brand loyalty score according to the brand loyalty ranking result; The brand loyalty is positively correlated with the brand loyalty score; and / or, The steps to obtain the flight selection probability score include: Get the ratio of the number of tickets purchased by the target airline to the total number of tickets for each route; Taking a weighted average of the proportions according to the total number of tickets for the route, the probability of flight selection is obtained; Sort the flight selection probabilities from large to small to obtain a flight selection probability sorting result; Obtaining a flight selection probability score according to the flight selection probability ranking result; The flight selection probability is positively correlated with the flight selection probability score.

7. An analysis system for airline competitiveness, characterized in that: The analysis system comprises: The first acquisition module is used to obtain historical dimension indicator data of different airlines; A second acquisition module is used to obtain the score of the historical dimension indicator data; A comparison module, used to compare the scores of the historical dimension index data of the target airline with the scores of the historical dimension index data of other airlines to obtain a comparison result; The analysis module is used to analyze the competitiveness of the target airline based on the comparison results.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and used to run on the processor, characterized in that: When the processor executes the computer program, the method for analyzing the airline competitiveness according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for analyzing the airline competitiveness according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for analyzing airline competitiveness as described in any one of claims 1 to 6 is implemented.

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