Chen, J., Xie, X., & Xia, L. The Model of Vehicle Characteristics Customer Value and Its Application. International Journal of Automotive Manufacturing and Materials. 2024, 3(2), 4. doi:


The Model of Vehicle Characteristics Customer Value and Its Application

Junxuan Chen , Xiaohu Xie, and Lu Xia

Dongfeng Commercial Vehicle Co., Ltd., Wuhan 442000, China

* Correspondence:

Received: 6 February 2024; Revised: 13 June 2024; Accepted: 14 June 2024; Published: 25 June 2024


Abstract: The customer value of vehicle characteristics is an evaluation method to evaluate the competitiveness of vehicle design from the benefits that vehicle characteristics bring to customers in actual operation. The key point of this evaluation method is to establish the calculation model of the characteristic value. Based on the customer’s actual operational analysis data, this paper establishes the value calculation model that transforms the characteristic value into the economic contribution of operating mileage; combined with the weight factor of customer-concerned characteristic, the comprehensive evaluation of customer value of vehicle characteristics is realized. Practical application demonstrates that the model can satisfy the value evaluation of the customer-concerned vehicle characteristic.


vehicle characteristics value model operational data the weights of customer-concerned characteristics

1. Introduction

With the global economic development, trucks as a means of road transport play a vital role in the logistics industry. To meet the changing market demands and customer expectations, truck manufacturers and transportation companies need to have a deep understanding of customer values and needs for truck products to meet customer expectations better in product development.

Customer value analysis is a method to analyze the extent to which vehicle characteristics indicators affect customers from the perspective of customer benefits. Through analysis of the customer value, we can evaluate the contribution degree of vehicle characteristics index to customers’ benefits, to provide a basis for the setting of characteristics targets and investment of R & D resources in the process of product development and further optimize product design and service quality.

Usually, in the development of vehicle products, only the contribution of product characteristics with high or low technical level is emphasized, but the value that technical investment and product development bring to the customer cannot be objectively assessed. Domestic manufacturers have not formed the vehicle characteristics of customer value evaluation system, and did not form a comprehensive judgment method of the customer value evaluation to technology, development cost, development cycle, balance of technology and cost. Therefore, the purpose of this study is to explore the analysis method of truck customer value and its application in product development. This study can provide an important decision-making basis for the truck industry product positioning, model definition, technology selection, technology and cost balance, promote the customer-oriented design and development of truck products, customer-oriented innovation and development, and improve the efficiency of the R & D resource and competitiveness of products and enterprise.

2. Analysis of the Truck Characteristics Importance

The purpose of truck characteristics importance analysis is to distinguish and calculate the weight proportion of truck characteristics from the perspective of customer acceptance and to analyze the impact of characteristics weight on customer value. According to the definition of a segmented market of medium and heavy trucks, each planned segmented market needs to be evaluated according to the characteristics of the segmented market, select the costomer-concerned characteristics, and determine the proportion of the weight of the concerned characteristics.

In this study, the analytic hierarchy process is selected to analyze the importance of the truck and finally get the characteristic weight [1–4].

The specific steps are as follows.

2.1. Selection of Variable

Depending on the segmented market, variables related to truck characteristics are selected as research factors, such as vehicle appearance, driving comfort, fuel economy, vehicle power performance, etc.

2.2. Determination of the Sample

To ensure that the setting of indicators weight at all levels is as objective and fair as possible, truck users, truck drivers, sales representatives, automobile designers, etc. are selected as the sample range of the study, and the appropriate sample size is determined.

2.3. Construction of the Survey Form

The questionnaire is designed to collect user evaluations of the importance of different truck features. According to the needs of the analytic hierarchy process, Table 1 “AHP User Evaluation Form” is designed as follows:

Table 1. AHP user evaluation form.

2.4. Data Processing and Analysis Methods

Sample selection was carried out according to the analytic hierarchy process questionnaire. The factors obtained by the survey questionnaire are compared in pairs to determine the judgment matrix of each evaluator, and the maximum feature root and feature vector were obtained by ANC (Asymptotic Normalization Coefficient), and the consistency test was carried out on the results. The specific method steps are as follows:

(1) Analyzing the relationship between various factors in the system and establishing a hierarchical model.

(2) Experts are asked to score indicators at each level, and A judgment matrix A is built. The judging scale of experts’ index scoring is as Table 2:

Table 2. Scoring and judging scale table.

The criteria scale represents the quantitative scale of the relative importance of factor  to . If  is more important than = 5; Conversely, when comparing the importance of  and , = 1/5.

(3) Perform a consistency test. The steps for a consistency test are as follows:

(a) The elements of the matrix are computed by column normalization:

(b) The elements that are normalized by column are added by row:

(c) In the same way, the column elements calculated by adding rows are normalized, and the weight coefficient is calculated:

(d) Calculating the maximum eigenvalue  of the matrix.

(e) Calculating the consistency index:

The larger the CI, the more serious the inconsistency.

(f) Finding the random consistency index RI from Table 3:

Table 3. Random consistency index RI.

(g) Calculating the relative consistency index:

When CR < 0.1, the degree of inconsistency of A is within the allowable range, and the eigenvector of A can be used as the weight vector.

(4) A Weighted average of each customer’s rating is made to form the final metric weight.

3. Collecting Customer’s Value Parameters

First of all, the establishment of customer value model is to conduct a detailed study of the market and customer’s operation mode, and fully understand the income, expenditure and other cost-related factors of customer operation. To define and capture valuable parameters for both individual customer vehicles and overall fleet operations, we need to establish a data collection process. This includes designing a structured table that ensures the collected data aligns with the needs of the chosen analysis model.

Based on the analysis of market vehicle operation, the cost items involved in the life cycle of vehicle operation are designed. Table 4 “Market Research Customer Value Data Collection Table” is designed as follows:

Table 4. Collection table of vehicle and customer value parameters.

4. Establishment of Vehicle Characteristics Customer Value Model

4.1. Establishment of Vehicle Characteristics Customer Value Model

Vehicle customer value is a comprehensive embodiment of the vehicle characteristics in the actual operation of the vehicle to bring benefits to users, if the use of currency value assessment, then the vehicle can bring customers to expected profit value now and in the future, the higher the monetary value income can bring, the bigger the customer value of the vehicle will be, the stronger the value competitiveness of the vehicle will be.

Next, we design the customer value model, the concept of return on investment, which is usually evaluated in economics, is introduced as an indicator to calculate and evaluate the customer value of vehicles [3].

Notably, Return On Investment (ROI) is an economic index to evaluate the effect of investment, which is equal to the net profit divided by the investment value. The formula is as follows:

here: S—sales revenue; TVE—External expenses; OE—Internal expenses of enterprises; I—Value of investment used for production

As OE (internal expenses of enterprise) is the internal control value determined by the enterprise, it depends on the management requirements and management capabilities of the enterprise, and the characteristics and quality of vehicle products are not closely related, so OE item is not considered here.

The above formula corresponds to the operation of the vehicle, and takes the year as the measuring time. The formula of the annual return on investment of the vehicle is:

here: OI—annual operating income of the vehicle; OC—annual operating expenses of the vehicle; P—The initial investment in the vehicle

The annual return on investment of the vehicle reflects the return on the investment of the customer’s vehicle. Vehicles with high return on investment naturally have higher customer value

4.2. Design of Customer Value Model of Vehicle Characteristics

According to the vehicle return on investment formula, as long as the annual total value income (OI) and annual total value expenditure brought by the products characteristics of the vehicle to the customer are calculated, the annual return on investment of the vehicle can be calculated according to the formula. In this, the calculation of the product characteristic value of vehicles is the focus of the model.

Customer value calculation of different characteristics is based on VF = V (positive benefit of the characteristics) + C (negative benefit of the characteristics). The specific characteristics include reliability, smoothness, indoor noise, handling stability, power performance, braking performance, economy, self-weight, etc. The specific calculation of the customer value model of each characteristic is shown in the subsequent sections.

4.2.1. Customer Value Model of Reliability

The model mainly considers that the improvement of reliability will bring the improvement of attendance, and the increase of vehicle operating mileage, and bring users excess returns. In addition, the maintenance cost of the per truck is reduced, the user’s expenditure will be reduced, and the cost will be saved too. The corresponding formula of customer value model is as follows:

: is the reduction in the cost of compensation for a single vehicle for each unit decrease in the 12mis value; : To improve reliability, the attendance rate of vehicles is increased, and the vehicle operating mileage is increased.

4.2.2. Customer Value Model of Smoothness

It’s a value model that considering vibration and noise.

According to the relation curve between fatigue-loss time and vibration acceleration (Figure 1), combined with the curve that shows the relationship between continuous driving market and human fatigue perception curve (Figure 2), the driver fatigue interval corresponding to a specific vibration acceleration value can be calculated, which is converted into a reduction in driver rest time and an increase in operating mileage. The corresponding customer value model formula is as follows:

Figure 1. Relation curve of fatigue-loss time and vibration acceleration.

Figure 2. Relation curve of the continuous driving market and human fatigue sensitivity.

4.2.3. Customer Value Model of Indoor Noise

According to the evaluation study of ride comfort and noise, vibration and noise have different effects on human fatigue experience, and the weight ratio of the two is about 8:2 as Table 5:

Table 5. Table of ride comfort, entropy of subjective noise index, information utility value and weight.

After considering the customer value model of vibration and noise, the customer value of noise is derived from ride comfort, that is .

4.2.4. The Customer Value Model of Handling Stability

The customer value model of handling stability considers three factors, including the improvement of tire life brought by the enhanced characteristics, the improvement of operation comfort, and the improvement of operating safety. The corresponding formula of customer value model is as follows:

4.2.5. Customer Value Model of Power Performance

Customer value model of power performance considers the increase in average vehicle speed brought by dynamic improvement, which translates into an increase in operating mileage and an increase in customer value. At the same time, we should consider the increase in fuel consumption, AdBlue, tolls, driver salary, tire wear and other expenses brought by power improvement. The corresponding formula of customer value model is:

4.2.6. Customer Value Model of Braking Safety

The customer value of braking safety considers the improvement of transportation efficiency brought about by the improvement of braking safety and the reduction of accident rate brought about by the improvement of braking safety. The formula of the customer value model is as follows:

The above calculation assumes that the insurance is complete, the insurance company bears personal injury, and the accident caused only by vehicle maintenance and loss of work is considered.

4.2.7. Economic Customer Value Model

Economic customer value mainly considers the reduction of fuel and AdBlue expenses brought about by economic improvement [5]. The corresponding customer value formula is as follows:

4.2.8. Lightweight Customer Value Model

Lightweight customer value mainly considers the increase in vehicle load caused by reduced vehicle self-weight and the rise in user benefits. The corresponding customer value formula is as follows:


: The proportion of vehicle full load is mainly considered.

5. Comprehensive Evaluation of Vehicle Customer Value

In the actual operation of the vehicle, the customer value of the characteristics is one of the factors to judge the improvement of the vehicle characteristics, but there also exists that although the customer value of the characteristics is low, the user attention is high, so that it is necessary to introduce the weight factor of customer attention characteristics.

According to the weighted analysis of market segment customer value and its weight, the comprehensive weight value of the characteristics is calculated as follows:


According to the comprehensive value of the feature, a reasonable feature enhancement item was determined.

6. Application Examples of Evaluation Model of Vehicle Customer Value

6.1. Collecting Data of Customer Operating Cost

Based on market research, collect the cost data related to customer vehicle operation as follows:

6.1.1. Vehicle Operating Division and Initial Investment

Vehicle operating division and initial investment are shown in Table 6:

Table 6. Table of vehicle operating and initial investment.

6.1.2. Cost Data of Income Category

Cost data of income category is shown in Table 7:

Table 7. Table of cost data of income category.

6.1.3. Cost Data of Expenditure Category

Cost data of expenditure category is shown in Table 8:

Table 8. Table of cost data of expenditure category.

6.2. Calculation of Customer Value Benchmark of Vehicle Characteristics

Based on the operating cost data of market customer vehicle, according to the formula of the calculation model of customer value of products characteristics, the customer value of the characteristics of the model users are calculated. This paper only considers the difference in customer value of the characteristics of the model from the perspective of benchmarking analysis, and in the actual product development, the customer value model can also be used to calculate the customer value of each characteristic, to evaluate the reasonableness of characteristic of the indicators setting.

The calculation of customer value benchmark of vehicle characteristics is shown in Table 9:

Table 9. Table of Calculation of customer value benchmark of vehicle characteristics.

By calculating characteristic customer value, mainly in the 4 aspects, including in reliability, comfort, braking safety and operating stability, the customer value competitiveness of product 2# is 2567 yuan less than that of product 1#. The largest difference between product 2# and product 1# is the reliability. So, it has been identified and determined as the key promotion item.

7. Conclusions

Vehicle characteristics customer value is the mileage operating income that vehicle characteristics can bring to users, and can assist in judging the operating income and type plan of different mileage and routes. The key point of customer value analysis is the calculation method of customer value of each characteristic. This paper tries to establish a model, variables, data, and evaluation rules for customer characteristic value calculation. Each segmented market needs to be calculated model, variables, data, and developed evaluation rules according to the specific situation of the segmented market. The above example application shows that the conclusion of customer value competitiveness obtained from the customer value analysis model is basically consistent with the characteristic conclusion, indicating that the modified model can be used to guide and evaluate the actual product development, which provides another design idea for the development and improvement of products competitiveness in addition to the structure, configuration, technology, quality and cost.

Author Contributions: Conceptualization, J.C. and X.X.; methodology, J.C. and L.X.; software, J.C.; formal analysis, J.C.; investigation, J.C.; writing—original draft preparation, J.C. and L.X.; writing—review and editing, X.X.; supervision, X.X. and L.X.; All authors have read and agreed to the published version of the manuscript.

Funding: This research received no external funding.

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Data Availability Statement: Not applicable.

Conflicts of Interest: The authors declare no conflict of interest.


  1. Wang, S. Automotive Driving—From Beginner to Expert; Chemical Industry Press: Beijing, China, 2014.
  2. Shao, C. Customer Value Evaluation Based on AHP. Value Eng. 2008, 2008, 53–56.
  3. Liu, D.R.; Shih, Y. Y. Integrating AHP and data mining for product recommendation based on customer lifetime
  4. value.Inf. Manage. 2004, 42, 387–400.
  5. Wang, L.; Xu, S.Introduction to Analytic Hierarchy Process; Chinese Renmin University Press: Beijing, China, 1990.
  6. Wang, F. Research on Strong Brand Evaluation Based on Analytic Hierarchy Process. Chin. Circ. Econ. 2007, 3.