A Hybrid Approach to Investigating Major Management Factors for Effective Highway Preventive Maintenance

A Hybrid Approach to Investigating Major Management Factors for Effective Highway Preventive Maintenance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Hybrid Approach to Investigating Major Management Factors for Effective Highway Preventive Maintenance Na Zhao, Yijuan Liu, Jianchang Li, Huihua Chen, Baoquan Cheng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4076043/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Highway preventive maintenance (HPM) can help reduce the negative environmental impacts of transportation infrastructure by prolonging the life of existing infrastructure, reducing the need for costly and resource-intensive repairs and reconstruction, and improving the energy efficiency of pavement infrastructure. However, many transportation agencies struggle with low HPM management capacity. This paper aims to enhance HPM management effectiveness by identifying and evaluating the major management factors that impact HPM. The study conducted a literature review and exploratory factor analysis (EFA) to identify the key HPM management factors. Social network analysis (SNA) was used to assess the importance of these factors, and a system dynamics (SD) model was developed to explore their influence laws. The research identified six dimensions of HPM management, including management system, management resource, management cognition, management decision, management technology, and external condition, along with 26 major management factors. The study found that key factors had a positive impact on HPM management, while hub factors were also critical. The study provides a comprehensive framework for identifying and evaluating the management factors that impact HPM, which can guide managers to develop effective HPM plans, improve the overall quality of highway maintenance, and form a sustainable transportation system. HPM EFA-SNA-SD method management factors influence mechanism sustainable transportation system Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Highways play a critical role as modern transportation infrastructure, providing an essential capacity and quality level that fosters sustainable development across the economy, society, humanities, and environment (Wang 2022 , Jiang et al. 2012 ). As one of the most crucial infrastructure types, enhancing their sustainability is a top priority to achieve better transportation functions, reduce environmental impacts, ensure passengers’ safety and comfort, extend highways’ service life, thus creating a better People-Environment-Infrastructure relationship in the urban transportation system (Kothari et al. 2022 , Naseri et al. 2022 ). However, due to the extensive use of expressways and their prolonged operational time, road damage and deterioration are often unavoidable, leading to a decline in traffic service quality and even jeopardizing personal safety in severe cases (Zhu 2022 , Shi 2017 ). Moreover, heavy traffic loads, rising user expectations, and insufficient maintenance funds pose enormous maintenance pressure on highway management (Zhang 2018 , Wang 2018 ). Therefore, the highway maintenance specification recommends implementing a prevention-based maintenance policy (Li et al. 2022 ). Highway preventive maintenance (HPM) involves the implementation of maintenance measures when there are no diseases present or at the initial stage of disease occurrence to prevent the aggravation of problems. This process includes conducting regular inspections and assessments of the highway to detect signs of wear and tear, such as cracks or potholes. Upon identification of such issues, maintenance measures such as sealing cracks or patching potholes can be promptly implemented to prevent further damage (Yan 2020 , Jiang et al. 2012 ). Effective HPM is a reasonable approach towards sustainable highways as it prioritizes preventative maintenance over corrective maintenance through early treatment, proactive maintenance, and advanced maintenance (Shi 2017 , Zou et al. 2022 ). By conducting regular maintenance and repairs, HPM can address minor issues before they become major problems, preventing the need for more extensive and environmentally damaging repairs or reconstruction which may have significant environmental impacts (Kothari et al. 2022 , Liu et al. 2022 ), including increased carbon emissions from heavy equipment, generated construction waste from construction activities, and disruption to ecosystems (Amarasiri and Muhunthan 2022 ). Moreover, HPM can also improve the energy efficiency of pavement infrastructure by improving the smoothness and ride quality of roadways, which can lead to lower fuel consumption and greenhouse gas emissions from vehicles. Additionally, some HPM techniques, such as pavement preservation, can use ecofriendly materials and processes that are less harmful to the environment. HPM also identifies and resolves safety hazards through regular maintenance, which improves the safety and accessibility of highways (Wang 2018 , Liu et al. 2019 ). In conclusion, the implementation of effective HPM can contribute to the cleaner production of highway infrastructures and sustainability of urban transportation systems. However, despite the potential benefits, the widespread adoption of HPM management has faced numerous challenges. These challenges include limited funding, lack of expertise, weak awareness of maintenance management, deteriorating road conditions, lack of political support, and other related management factors (Zhang 2018 , Wang 2018 , Kothari et al. 2022 , Liu et al. 2019 ). Effective HPM management requires a combination of technical expertise, financial resources, political support, and effective stakeholder engagement (Yang et al. 2023 , Ruiz Rodríguez et al. 2022 , El Said and Stammer 2023 , Humayun et al. 2022 ). Since these factors are reported in the literature in a piecemeal fashion, a comprehensive understanding of such factors and their dynamic impact from a systems perspective is highly desired. Therefore, this paper aims to explore the major HPM management factors, their important degree, and their influence laws through a hybrid research method combining exploratory factor analysis (EFA), social network analysis (SNA) and system dynamics (SD). Three key questions about HPM management are expected to be answered in this study: (1) What management factors affect the efficiency of HPM? (2) How to distinguish the importance degree of these identified factors? (3) How these factors influence the efficiency of HPM dynamically? The key innovation of this paper lies in its comprehensive and systematic approach to identifying and evaluating the major management factors for effective HPM in the context of the PEI relationship. By identifying the most critical management factors and modeling their dynamic interplay, transportation agencies can develop more effective HPM plans, allocate resources more efficiently, and ultimately improve the overall quality of highway maintenance. Overall, this study advances knowledge and understanding of sustainable infrastructure management, which is critical to the long-term health and sustainability of the transport system. This paper is organized as follows: Section 2 describes the research methodology, followed by Section 3 which screens the HPM management factors. Section 4 distinguishes the important degree of HPM management factors. Section 5 explores the influence law of HPM management factors using SD. Section 6 presents the implications, limitations and recommendations. Finally, the concluding section summarizes the main contributions of this study. 2. Methodology A hybrid EFA-SNA-SD method is adopted to screen the major management factors, distinguish their important degree and systematically analyze their influence laws. EFA is a method used to process multivariate observed variables and perform dimensionality reduction, which allows combining a set of interrelated observed variables into more significant latent variables (Gunduz and Abdi 2020 ). It is usually used to determine the number of hypothetical potential variables, structures, dimensions or factors (Watkins 2018 ). Thus, EFA can integrate the intricate HPM management factors in this study. SNA is a methodology that uses mathematical and statistical techniques to analyze social networks and relationships between individuals, groups, or organizations. It helps to identify patterns and structures within a network and to understand how relationships shape and influence these factors (Pryke et al. 2017 ). Therefore, it can reasonably distinguish the important degree of HPM management factors into key factors, hub factors and non-key factors (Sun et al. 2015 ). SD is a theory that studies the overall behavior of a socio-economic system by analyzing the feedback structure relationships between the variables within the system. The SD method systematically analyzes the influence law of factors, which is one of the most common procedures to determine complex systems (Gu et al. 2017 ). Consequently, SD is suitable for dynamically exploring the influence law of HPM management factors. As shown in Fig. 1 , this research is divided into the following three steps. Step 1: Related literature about HPM management is reviewed to preliminary sort out the major management factors in HPM. Expert review, questionnaire survey and EFA are applied to further determine major management factors in HPM. Step 2: The SNA method is adopted to distinguish the importance degree of identified management factors. The relationship matrix of factors is developed based on expert scoring and imported into the UCINET 6 software to calculate the relative degree of centrality. The relationship diagram is also drawn with Netdraw software. Step 3: The SD model is used to explore the dynamic influence laws among HPM management factors. Construct a causal-loop diagram for qualitative analysis and a stock-flow diagram for quantitative analysis. And the state transition equation is constructed. Based on the above steps, simulation analysis is carried out. 3. HPM management factors 3.1 Literature review 3.1.1 Management system Establishing an intelligent highway maintenance system is the way to achieve high-quality development of HPM in the new era. It efficiently integrates resources, enhances maintenance efficiency, and ensures highway transportation safety (Defu Che and Zhao 2021, Jie lin and Jing 2020, Mohamed et al. 2022 ). After thorough research, we have identified four critical aspects of this system: system establishment, system perfection, system implementation, and system feedback. Firstly, establishing an intelligent highway maintenance system is essential to improve the efficiency of maintenance management, which can help the highway management to obtain the status information of road, bridge, tunnel and other facilities in time (Defu Che and Zhao 2021, Xu Qiao et al. 2019, Yun Hou et al. 2019 , Shaojin Zhang et al. 2016 ). Secondly, for the characteristics of highway maintenance work with high frequency and long period, the management system needs to be improved to better serve the actual needs (Yun Hou et al. 2019 , Defu Che and Zhao 2021, Shaojin Zhang et al. 2016 ). Thirdly, implement the management system and closely integrate it with work practices to ensure smooth implementation (Shaojin Zhang et al. 2016 , Mingming Zhou and Zhou 2015, Xu Qiao et al. 2019). Finally, the implementation effect of the management system is continuously optimized according to the feedback until the system can better adapt to the actual work needs (Mingming Zhou and Zhou 2015, Shaojin Zhang et al. 2016 ). This enables precise maintenance and promotes sustainable development. 3.1.2 Management resource The construction and maintenance of large-scale transportation infrastructure require significant resources, emphasizing the reasonable and efficient resource allocation (Liu et al. 2021 ). This includes the integrated planning and allocation of machinery, materials, and capital. Among them, machinery is an important tool for highway preventive maintenance. The configuration of machinery should be considered to ensure the performance and quality of machinery to adapt to the maintenance needs and ensure the efficiency of machinery, thus improving the effectiveness and economic efficiency of maintenance management (Lv et al. 2022 , Zhu 2022 , Mirheli et al. 2020 , Ruiz Rodríguez et al. 2022 , Wheat 2017 ). In terms of materials, adequate and reliable material supply and standard material quality can reduce maintenance cost, improve maintenance effect and ensure the safety, smoothness and sustainability of highways (Ying Liu et al. 2021 , JingHai He et al. 2019 , Mohamed and Tran 2022 ). In terms of capital, capital investments and highway revenues are the source of HPM funding. If there is a shortage of funds, the needs of HPM cannot be met and maintenance cannot be successfully promoted. Therefore, securing a source of maintenance funding is critical to HPM (El Said and Stammer 2023 , Wang 2022 , Wang et al. 2020 , Shi et al. 2016 ). 3.1.3 Management cognition In recent years, the growth in traffic trips and the popularization of transportation have led to increased importance in the construction and maintenance of highways. However, the current problems in HPM management are becoming more and more noticeable. Among them, public cognition of highway maintenance management directly affects the difficulty of HPM management (Wheat 2017 , Love et al. 2022 , Harvey 2022 ). Therefore, it is essential to adopt the “build and maintain” policy from an ideological level and enhance public awareness and participation in maintenance management. Additionally, the degree of personal cognition directly affects the ability of individuals to drive safely and civilly on highways. Raising maintenance awareness and cognitive degree of personal can help reduce the burden of HPM management (Al-Shabbani et al. 2018 , Zuluaga et al. 2018 ). The department, as the management and implementation unit, can only accurately grasp and implement the conservation measures and improve the effectiveness of HPM management if it has an in-depth understanding of the purpose and significance of HPM (Fei Guo and Zhang 2020, Zhao 2020 , Sun 2018 ). And it is necessary to improve the ability of maintenance managers and the sense of responsibility of maintenance staff to improve the quality and efficiency of maintenance work (Wang 2020c , Ying Liu et al. 2021 , Huo 2021 , Greven et al. 2022 , Menges 2023 ). Only in this way can we guarantee the smooth implementation of HPM management and provide a more convenient and safe highway travel environment for the society and the public to achieve sustainable development. 3.1.4 Management decision The heavy workload of HPM tasks and the inadequate maintenance management decision-making system urgently require the development of a scientific and efficient management mode that can meet the demand for quick, efficient, and high-quality decision-making under high-load maintenance tasks (Mohamed et al. 2022 , Wang et al. 2020 ). The core issue of HPM is “the right maintenance measures at the right time on the right section of road to achieve the best maintenance benefits” (Xiangfeng Wang and Yong 2017). Considering traffic flow, vehicle type, road conditions and other factors, maintenance managers scientifically and reasonably select routes and develop optimal maintenance time nodes to minimize safety risks during highway operation (Yin et al. 2023 , Yu et al. 2023 , Rodoplu et al. 2023 , Wang et al. 2020 ). Also, when maintenance measures are carried out, their effectiveness needs to be measured to predict the benefits of the maintenance work (Amarasiri and Muhunthan 2022 , Zou et al. 2022 , Wang et al. 2020 ). This allows adjustments to be made to the maintenance measures to achieve optimal maintenance results. In addition, the costs of maintenance work are a factor that should not be overlooked (Lei et al. 2024 , Liu et al. 2022 , Li et al. 2022 ). Maintenance costs are directly related to the development, implementation and effectiveness of management decisions. Reasonable control of maintenance costs is conducive to realizing the economic benefits of maintenance work. Overall, management decision improves the scientific maintenance methods for the HPM management department to ensure the scientific construction maintenance and efficient operation management of highways (Li et al. 2022 , You et al. 2023 ). 3.1.5 Management technology With modern maintenance technology and efficient management, highways can operate normally and continuously improve their service level. To tackle heavy maintenance tasks, new technologies, materials, and techniques can be utilized to enhance pavement durability and extend the highway's service life (Humayun et al. 2022 , Kruachottikul et al. 2021 , Dellenbaugh et al. 2020 , Jalinoos et al. 2020 ). However, the technical level of existing maintenance personnel is inadequate (Xue 2020 ). Therefore, it is especially important to improve the personal technical level, which will help to improve the effectiveness of maintenance management (Tang 2021 , Wang 2020a , Ruiz Rodríguez et al. 2022 ). Moreover, highway maintenance information is critical. Information acquisition and utilization can help HPM managers to have a comprehensive understanding of the condition and problems of highways so that effective maintenance programs can be developed (Sameen and Pradhan 2016 , Jiang et al. 2023 , Hijji et al. 2023 , Tezel and Aziz 2017 ). This helps maintenance managers to control maintenance costs and improve resource utilization. And advanced data analysis techniques can be employed to analyze and extract relevant information from highway maintenance data, guiding the development of maintenance work. 3.1.6 External condition The success of HPM is not solely dependent on internal management mechanisms, but also on external factors. Government attention can increase the investment and support of HPM management, promote the innovation and development of HPM management technology, and provide support to ensure the safety and smooth flow of highways (Yang et al. 2023 , Liu 2019 , Hong Zhang et al. 2016 ). Market competition helps the development of highway maintenance industry, improves service quality and reduces maintenance cost (Yarmukhamedov et al. 2020 , Wu et al. 2015 ). At the same time, the risks of maintenance work should be given sufficient attention and appropriate precautions should be taken to minimize potential impacts (Yao et al. 2023 , Sabatino et al. 2015 ). In addition, maintenance work is often carried out in fields, open air and other environments that are vulnerable to climatic factors (Hernandez et al. 2023 , Liu et al. 2022 , Liu et al. 2019 , Sentic et al. 2022 ). Therefore, it is important to consider the external factors of HPM management comprehensively to enhance management efficiency and improve the quality of maintenance work. This is critical to ensure the safety and smoothness of highways. Based on the literature review, we found it necessary to collect and study the major management factors of HPM and initially screened the HPM management factors, as shown in Table 1 . Table 1 Summary of HPM factors and relevant literature references Dimension Factor Literature source Point Management system System establishment Defu Che and Zhao (2021), Xu Qiao et al. (2019), Yun Hou et al. ( 2019 ), Shaojin Zhang et al. ( 2016 ) The establishment of the management system can help the highway management to obtain timely information on the status of the road, bridges, tunnels and other facilities. System perfection Yun Hou et al. ( 2019 ), Defu Che and Zhao (2021), Shaojin Zhang et al. ( 2016 ) According to the characteristics of HPM, it is essential to perfect the management system to make it better serve the actual needs. System execution Mingming Zhou and Zhou (2015), Xu Qiao et al. (2019), Shaojin Zhang et al. ( 2016 ) To closely integrate work practices and ensure the successful implementation of maintenance work, the management system needs to be executed. System feedback Mingming Zhou and Zhou (2015), Shaojin Zhang et al. ( 2016 ) To ensure the effectiveness of the implementation of the management system, it is essential to continuously optimize the management system based on feedback. Management resource Machinery allocation Zhu ( 2022 ), Lv et al. ( 2022 ), Mirheli et al. ( 2020 ) Properly allocated machinery can ensure mechanical quality and performance. Material supply Liu et al. ( 2021 ), Mohamed and Tran ( 2022 ) Ensure adequate material supply to prepare for maintenance work. Material quality JingHai He et al. ( 2019 ), Mohamed and Tran ( 2022 ) Material quality directly affects HPM's effectiveness and ability to continue stable operation. Capital investment El Said and Stammer ( 2023 ), Wang ( 2022 ), Wang et al. ( 2020 ) Capital investment is an important safeguard for HPM. Income situation El Said and Stammer ( 2023 ), Feng Li et al. (2015), Shi et al. ( 2016 ) The income situation of highways affects the rational allocation of HPM resources. Mechanical efficiency Wheat ( 2017 ), Ruiz Rodríguez et al. ( 2022 ) Mechanical efficiency affects the effectiveness and economic efficiency of HPM. Management cognition Public cognition Harvey ( 2022 ), Wheat ( 2017 ), Love et al. ( 2022 ) The degree of public cognition directly affects the difficulty of HPM management. Personnel cognition Al-Shabbani et al. ( 2018 ), Zuluaga et al. ( 2018 ) The degree of personal cognition directly affects their ability to drive safely and civilly on highways. Department cognition Fei Guo and Zhang (2020), Zhao ( 2020 ), Sun ( 2018 ) The maintenance department has an in-depth understanding of the purpose and significance of HPM to accurately grasp and implement the maintenance measures. Manager capability Wang ( 2020c ), Ying Liu et al. ( 2021 ), Huo ( 2021 ), Greven et al. ( 2022 ) Having excellent managerial capabilities is the way to better promote HPM management. Sense of responsibility Menges ( 2023 ), Huo ( 2021 ) The sense of responsibility of the maintenance staff guarantees that maintenance work is carried out properly. Management decision Management mode Wei ( 2017 ), Hou ( 2017 ), Wang et al. ( 2020 ), Mohamed et al. ( 2022 ) To meet the need for fast, efficient and high-quality decision-making under high-load maintenance operations, there is an urgent need to develop scientific and efficient management modes. Route selection Yu et al. ( 2023 ), Ji ( 2015 ), Wang et al. ( 2020 ) Scientific and reasonable route selection reduces the safety risk of highway operation. Timing determination Yin et al. ( 2023 ), Rodoplu et al. ( 2023 ), You et al. ( 2023 ), Guan et al. ( 2023 ) Determine the optimal maintenance time point reduces the safety risk of highway operation. Measure effect Zou et al. ( 2022 ), Wang et al. ( 2020 ), Amarasiri and Muhunthan ( 2022 ) To predict the benefits of maintenance efforts, implementation effects need to be measured. Maintenance cost Lei et al. ( 2024 ), You et al. ( 2023 ), Li et al. ( 2022 ), Liu et al. ( 2022 ) Maintenance costs are directly related to the development, implementation and effectiveness of management decisions. Management technology New technology application Kruachottikul et al. ( 2021 ), Dellenbaugh et al. ( 2020 ), Jalinoos et al. ( 2020 ), Humayun et al. ( 2022 ) To address the current situation of heavy maintenance tasks, new technologies can be applied to improve the durability of pavements and extend the service life of highways. Personnel technology Tang ( 2021 ), Wang ( 2020a ), Ruiz Rodríguez et al. ( 2022 ) Improving personal technical skills helps to improve the effectiveness of maintenance management. Information utilization Hijji et al. ( 2023 ), Sameen and Pradhan ( 2016 ), Tezel and Aziz ( 2017 ) To develop effective maintenance programs, information needs to be fully explored and utilized. Information acquisition Jiang et al. ( 2023 ), Hijji et al. ( 2023 ), Sameen and Pradhan ( 2016 ) To fully understand the condition and problems of highways, adequate acquisition is required. External condition Government attention Yang et al. ( 2023 ), Hong Zhang et al. ( 2016 ), Liu ( 2019 ) Government attention can increase investment and support for HPM management. Market competition Wu et al. ( 2015 ), Yarmukhamedov et al. ( 2020 ) Competition in the market helps the development of the highway maintenance industry. Work risk Yao et al. ( 2023 ), Sabatino et al. ( 2015 ) The risky nature of maintenance work exacerbates the difficulty of maintenance work to some extent. Climate impact Hernandez et al. ( 2023 ), Sentic et al. ( 2022 ), Liu et al. ( 2022 ), Liu et al. ( 2019 ) Maintenance work is often in the field, open air and other environments, vulnerable to climatic factors. 3.2 Questionnaire survey This paper built on the literature review, drew on existing well-established scales based on the identified factors in Section 3.1 , thus setting the measurement items. And the questionnaire items were amended to form a questionnaire on the HPM management factors through expert interviews, small sample testing. This study distributed the questionnaire through a combination of online and offline methods to collect survey data. Specifically, this was done by sending questionnaire links to respondents through social media platforms such as WeChat and QQ, and adopting a combination of self-administered questionnaires and face-to-face interviews for comprehensive data collection. The questionnaire was distributed to 300 respondents. 260 valid responses were collected, resulting in a response rate of 86.7%. Invalid questionnaires were excluded based on the following criteria: (1) questionnaires that left too many questions unanswered, (2) contradictory choices, and (3) almost identical to others. The sample characteristics are shown in Table 2 . Among them, 59.62% were male and 40.38% were female. The majority of the survey respondents were under 45 years old (90.38%), had a bachelor’s degree (61.54%), and had been working for 6–15 years (53.85%). The main issuing units are the maintenance unit, detection unit, construction unit, advisory unit, supervision unit. This indicates that respondents’ source composition is consistent with reality and can reflect the actual situation to a certain extent. Table 2 Characteristics of the sample. Indicators Item Number Percentage Cumulative percentage Gender male 155 59.62 59.62 female 105 40.38 100 Education background specialty and below 100 38.46 38.46 undergraduate 117 45.00 83.46 master 30 11.54 95.00 doctor 13 5.00 100.00 Age =45 25 9.62 100.00 Working life =15 45 17.30 100.00 Working unit maintenance unit 78 30.00 30.00 detection unit 36 13.85 43.85 construction unit 84 32.31 76.16 advisory unit 42 16.15 92.31 supervision unit 20 7.69 100.00 3.3 Exploratory factor analysis To analyze the factors that influence HPM obtained from the questionnaire survey, the KMO (Kaiser-Meyer-Olkin) statistic method and the Bartlett’s spherical test were used. As the data in Table 3 shows, the KMO value was 0.778 and the Bartlett’s spherical test chi-square value was 2426.642, with a significance less than 0.01. This indicates that the HPM scale is suitable for factor analysis. Table 3 KMO and Bartlett’s test. Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.778 Bartlett’s test of sphericity Approx Chi-Square 2426.642 Df 325 Sig 0.000 To identify the most representative variables, variables with eigenvalues equal to or greater than 1.0 were selected as major factors. As presented in Table 4 , a total of six major factors were chosen with a cumulative variance contribution of 94.522%. The factor names were assigned after rotating the component matrix, which yielded the following six factors: management system, management resource, management cognition, management decision, management technology, and external condition. Only observed variables with factor loadings greater than 0.5 were included in the analysis, while those with loadings less than 0.5 were excluded. The final selection of 26 factors for HPM was based on group discussion and expert opinion, which excluded system feedback and the sense of responsibility. The validity of the factor analysis was strong, as confirmed by the high cumulative variance contribution of the six factors. The summarized 26 factors for HPM are presented in Table 5 . Table 4 Total variance explained. Component Initial Eigenvalues Rotation Sums of Squared Loadings Total Variance Cumulative Total Variance Cumulative 1 19.536 61.049 61.049 6.375 19.923 19.923 2 3.117 9.740 70.789 5.777 18.054 37.977 3 2.534 7.920 78.709 5.136 16.050 54.027 4 2.109 6.590 85.299 5.095 15.921 69.947 5 1.796 5.612 90.911 4.932 15.414 85.361 6 1.155 3.611 94.522 2.932 9.161 94.522 7 0.735 2.297 96.819 Table 5 HPM management factor scale. Dimension Factor Factor loading Management system System establishment 0.930 System perfection 0.851 System execution 0.834 Management resource Machinery allocation ` 0.945 Material supply 0.835 Material quality 0.780 Capital investment 0.784 Income situation 0.764 Mechanical efficiency 0.796 Management cognition Personnel cognition 0.788 Public cognition 0.917 Department cognition 0.813 Manager capability 0.818 Management decision Management mode 0.946 Route selection 0.797 Timing determination 0.750 Measure effect 0.788 Maintenance cost 0.806 Management technology New technology application 0.878 Personnel technology 0.813 Information utilization 0.813 Information acquisition 0.525 External condition Government attention 0.944 Market competition 0.792 Work risk 0.801 Climate impact 0.802 4. Important degree of HPM management factors To distinguish the important degree of management factors, this paper uses the SNA method to explore these factors in depth to select key, hub and non-key factors. The research invited ten experts to score the relationship between factors, with a score of 1 indicating influential and 0 indicating non-influential. The resulting relationship matrix of factors was then constructed, and imported into UCINET 6 software to calculate the relative degree of centrality, as shown in Table 6 . It can be observed that information acquisition, system perfection, system establishment, government attention, new technology application, capital investment, and management mode are also in an important position and are defined as key factors that are the top considerations to enhance management effectiveness. System execution, manager capability, personnel technology, maintenance cost, information utilization, income situation, measure effect, public cognition, department competition, and personnel cognition connect key factors and non-key factors, which are defined as hub factors. Route selection, machinery allocation, timing determination, market competition, material supply, work risk, mechanical efficiency, material quality, and climate impact are at the edge, which are defined as non-key factors. Table 6 Measurement analysis result. Factor Out-degree In-degree C IRD (X) Rank information acquisition 14.00 25.00 0.78 1 system perfection 13.00 20.00 0.66 2 system establishment 12.00 21.00 0.63 3 government attention 17.00 14.00 0.62 4 new technology application 15.00 15.00 0.60 5 capital investment 14.00 16.00 0.60 6 management mode 15.00 14.00 0.58 7 system execution 14.00 14.00 0.56 8 manager capability 18.00 10.00 0.56 9 personnel technology 14.00 14.00 0.56 10 maintenance cost 15.00 13.00 0.56 11 information utilization 13.00 11.00 0.48 12 income situation 14.00 10.00 0.48 13 measure effect 11.00 13.00 0.48 14 public cognition 10.00 13.00 0.46 15 department competition 14.00 9.00 0.46 16 personnel cognition 10.00 11.00 0.42 17 route selection 12.00 7.00 0.38 18 machinery allocation 4.00 13.00 0.34 19 timing determination 11.00 6.00 0.34 20 market competition 10.00 5.00 0.32 21 material supply 7.00 8.00 0.30 22 work risk 8.00 6.00 0.28 23 mechanical efficiency 4.00 9.00 0.26 24 material quality 6.00 7.00 0.26 25 climate impact 9.00 0.00 0.18 26 Netdraw is used to draw the relationship graph of HPM management factors, as shown in Fig. 2 . The graph highlights the critical role of information acquisition in HPM management, as evidenced by its highest relative centrality and its ability to radiate to other areas. To ensure effective preventive maintenance management, managers must possess comprehensive knowledge of systems, technologies, funds, materials, and external dynamics, enabling them to make informed decisions (Yuefeng 2021 ). Highways have the attributes of high traffic volume, perfect equipment, and high technological content. However, the existing maintenance management system has defects such as insufficient theoretical innovation and vague objectives, which cannot achieve the expected effect of preventive maintenance management (Ahmed et al. 2017 ). Additionally, the continuous evolution of maintenance technology, the emergence of new materials, and the steady progress of equipment, coupled with substantial capital investment, are the primary drivers of enhanced technology, materials, and equipment (Wang 2020b ). From the above discussion, it is clear that the relative degree of centrality of key factors such as information acquisition and system perfection is greater. System execution, managerial capability, etc., as the “link” between key and non-key factors, have a greater impact on both but less on the effectiveness of HPM management. Therefore, hub factors are relatively less centralized. With the cooperation of the government and the units, non-key factors such as route selection and machinery allocation have little impact on management efficiency, which means the lowest level of centralization. 5. Influence law of HPM management factors 5.1 Causal-loop diagram Based on the relationship among the HPM management factors, a causal-loop diagram between management factors and the effectiveness of HPM management can be built shown to describe the interaction relationships, as shown in Fig. 3 . There are 5 relationship loops, which consist of 4 positive relationship loops and 1 negative relationship loop. The dynamic interaction behavior of variables in each relationship loop is interpreted below. Loop 1: management cognition → +effectiveness of HPM management → +driving comfortableness → +management cognition Loop 1 is a positive feedback loop. Improving the management cognition will enhance managers’ positive seriousness about highway management and simulate the implementation of preventive maintenance, promoting the effectiveness of HPM management. In this situation, the conditions and quality of highways can be well maintained, which enables drivers to feel more comfortable when driving. Thus, the management perception will be enhanced. Loop 2: management cognition → +effectiveness of HPM management → +highway revenue → +management cognition Loop 2 is a positive feedback loop. The state vigorously promotes the HPM concept and increases conservation implementation. It will prolong the service of the road and further improve the effectiveness of HPM management. Therefore, highway revenue will increase since more drivers may choose highways. In this way, the improved revenue will stimulate the managers to further improve their management cognition. Loop 3: management resource → +effectiveness of HPM management → +highway revenue → +management resource Loop 3 is a positive feedback loop. The effectiveness of HPM management will be significantly improved by vigorously developing management resources and making rational allocations of resources. In turn, the revenue of the highway is on an upward trend, thus improving the supply of management resources and mechanical efficiency. Loop 4: management system → +effectiveness of HPM management → +service life → +management system Loop 4 is a positive feedback loop. The state improved the management system and realized the transformation of information, automation and intelligence of maintenance management, which contribute to promoting the effectiveness of HPM management. This will significantly extend the service life of highways. In this situation, the managers will be motivated to further improve the management system. Loop 5: external condition → +effectiveness of HPM management → +service life → -external condition Loop 5 is a negative feedback loop. The quality of preventive maintenance can be affected by the external condition, including advanced technology, advanced equipment, quality materials, strict management, and especially the appropriate season. Therefore, the less fluctuation of external condition, the better the effectiveness of HPM management, and the longer the service life of the highway. However, as the service life grows, the external condition will get worse. 5.2 Stock-flow diagram After identifying the main factors and their interactions involved in the whole system, a stock-flow diagram using the Vensim software is developed so that the SD model can be run to simulate the internal dynamic relationships between the factors, as shown in Fig. 4 . 5.3 State transition equation As an essential part of the SD model, the state transition equation describes the dynamic change patterns of the factors in the model which provides the theoretical support for simulation. The SD model for HPM management factors involves the following state transition equations which are shown in Table 7 . Table 7 State transition equations table. Variable Category Name Equation Horizontal variables management system INTEG (management system change volume,0) management resource INTEG (management resource change volume,0) management cognition INTEG (management cognition change volume,0) management decision INTEG (management decision change volume,0) management technology INTEG (management technology change volume,0) external condition INTEG (external condition change volume,0) Rate variables management system change volume system execution rate-system perfection rate management resource change volume resources growth rate-resources reduction rate management cognition change volume cognition accumulation rate-cognition elimination rate management decision change volume decisions efficient rate-decisions error rate management technology change volume technological advancement growth rate-technological advancement reduction rate external condition change volume conditions vary greatly-conditions vary small Auxiliary variables effectiveness of HPM management w 1 ×management system + w 2 ×management resource + w 3 ×management cognition + w 4 ×management decision + w 5 ×management technology + w 6 ×external condition system perfection rate a 1 ×system establishment + a 2 ×system perfection+ a 3 ×external condition system execution rate b 1 ×system execution + b 2 ×management cognition resources reduction rate c 1 ×insufficient funds + c 2 ×poor earnings+ c 3 ×inefficient machinery resources growth rate d 1 ×material quality qualified + d 2 ×timely supply of materials + d 3 ×mechanical enough + d 4 ×management technology cognition elimination rate e 1 ×personnel cognition + e 2 ×public cognition+ e 3 ×management system cognition accumulation rate f 1 ×department competition + f 2 ×manager capability+ f 3 ×management technology decisions error rate g 1 ×high maintenance cost + g 2 ×uncertain timing+ g 3 ×inaccurate route selection + g 4 ×external condition decisions efficient rate h 1 ×effective measures + h 2 ×reasonable management mode + h 3 ×management resource Technological advancement reduction rate k 1 ×unprofessional personnel + k 2 ×underutilization of information + k 3 ×management cognition technological advancement growth rate m 1 ×new technology application + m 2 ×information acquisition + m 3 ×management resource conditions vary small o 1 ×climate change + o 2 ×low government attention conditions vary great p 1 ×high risk of work + p 2 ×fierce market competition+ p 3 ×management decision Note: w 1 , w 2 , w 3 , w 4 , w 5 , w 6 , a 1 , a 2 , a 3 , b 1 , b 2 , c 1 , c 2 , c 3 , d 1 , d 2 , d 3 , e 1 , e 2 , e 3 , f 1 , f 2 , f 3 , g 1 , g 2 , g 3 , h 1 , h 2 , h 3 , h 4 , k 1 , k 1 , k 1 , k 1 , m 1 , m 1 , m 1 , o 1 , o 1 , p 1 , p 1 , p 1 are parameters, and satisfy ∑a,∑b,∑c,∑d,∑e,∑f,∑g,∑h,∑k,∑m,∑o,∑p are 1. Firstly, by setting the initial value of major factors as the mean of secondary factors, it can be ensured to a certain extent that the initial state of major factors can better synthesize the impact of these secondary factors. Secondly, the initial values of the secondary factors are set as the mean of out-degree and in-degree, which are determined by ten HPM related experts combining professional knowledge and practical experience. Finally, the parameters of secondary factors can be modified and determined by standardized relative centrality, which can eliminate the barriers to comparison between networks of different sizes. Overall, this means that the modification and determination of parameters is more impartial and reasonable, making the model more accurate and closer to reality. According to Table 6 and Fig. 2 , the sum of the relative degree of centrality in the management system, management resource, management cognition, management decision, management technology and external condition are 1.85, 2.24, 1.9, 2.34, 2.42, 1.4. And the sum of relative degree centers of all secondary factors is 12.15, so w 1 = 0.15, w 2 = 0.19, w 3 = 0.16, w 4 = 0.19, w 5 = 0.2, w 6 = 0.11. Following the above principles, the parameter results are shown in Table 8 . Table 8 Equation parameters. Parameter Value Parameter Value management system 3.1 public cognition 2.3 management resource 1.87 department competition 2.3 management cognition 2.37 manager capability 2.8 management decision 2.34 high maintenance cost 2.8 management technology 3.03 uncertain timing 1.7 external condition 1.72 inaccurate route selection 1.9 system establishment 3.1 effective measures 2.4 system perfection 3.3 reasonable management mode 2.9 system execution 2.8 unprofessional personnel 2.8 insufficient funds 3 underutilization of information 2.4 poor earnings 2.4 new technology application 3 inefficient machinery 1.3 information acquisition 3.9 material quality qualified 1.3 climate change 0.9 timely supply of materials 1.5 low government attention 3.1 mechanical enough 1.7 high risk of work 1.4 personnel cognition 2.1 fierce market competition 1.5 w 1 = 0.15,w 2 = 0.19,w 3 = 0.16,w 4 = 0.19,w 5 = 0.2,w 6 = 0.11,a 1 = 0.34,a 2 = 0.36,a 3 = 0.3,b 1 = 0.3,b 2 = 0.7,c 1 = 0.45,c 2 = 0.35,c 3 = 0.2,d 1 = 0.12,d 2 = 0.13,d 3 = 0.15,d 4 = 0.60,e 1 = 0.22,e 2 = 0.24,e 3 = 0.54,f 1 = 0.24,f 2 = 0.3,f 3 = 0.46,g 1 = 0.24,g 2 = 0.15,g 3 = 0.17,g 4 = 0.44,h 1 = 0.19,h 2 = 0.25,h 3 = 0.56,k 1 = 0.23,k 2 = 0.2,k 3 = 0.57,m 1 = 0.25,m 2 = 0.32,m 3 = 0.43,o 1 = 0.23,o 2 = 0.77,p 1 = 0,2,p 2 = 0.23,p 3 = 0.54. 5.4 Simulation results and analysis This research uses Vensim software to simulate the influence law of management effectiveness, setting INITIAL TIME = 0, FINAL TIME = 12, TIME STEPT = 1, and UNTIS for TIME as the Quarter. The simulation results are shown in Fig. 5 and Fig. 6 . In recent years, paying equal attention to construction and maintenance has become the industry orientation for the development of technology in the field of highway maintenance. With the active cooperation and participation of the state, government, and various units, management effectiveness has continued to improve. Thus, the changes in the effectiveness of HPM management show a gradual upward trend, which is consistent with the actual situation. The change rule of management system on management effectiveness There is a slight decrease in the initial stage, a gradual rise in the middle stage, a marked decline in the middle and later stages and a rapid rise in the later stage. This can be explained by the inadequate management system and weak execution in the early stage. At the same time, it is not sufficient to mine the data of the management system and apply it to the maintenance decision. In the middle stage, management system gradually becomes applicable through continuous learning and innovation, which can improve effectiveness of HPM management. Over time, management system meets the criteria and reaches a state of saturation. Hence, the effect rule is significantly reduced compared with the middle stage. In the later stage, management effectiveness is strengthened by improving management system and formulating a reasonable HPM post-evaluation mechanism. The change rule of management resource and management technology on management effectiveness It shows a slowly increasing trend. As the state actively organizes various preventive maintenance seminars, it promotes the relevant personnel to learn the advanced technology about preventive maintenance and provides funds for special preventive maintenance and standardized research of maintenance materials. Thus, it gradually forms maintenance materials and technologies with independent intellectual property rights. Advanced technology, new materials, and sufficient capital can provide infinite possibilities to improve the management effect. The change rule of management cognition on management effectiveness There is no noticeable change in the early stage, but it declines in the middle stage and increases in the later stage. This can be explained that there are still some maintenance personnel with conservative ideas even though the state actively promotes HPM management. In addition, their professional qualities are mixed. For example, they are relatively old and do not understand the economic benefits of preventive maintenance. Therefore, the impact of management cognition is relatively small in the early stage and decreases in the middle stage. With the increasingly prominent benefits of preventive maintenance, its concept and mode have been widely recognized. Besides, the concept of HPM management is popularized by summarizing the experience of pilot cities across the country. Meanwhile, the development of integrated equipment, on-site condition control and appropriate contract management has promoted the healthy development of preventive maintenance. Furthermore, the maintenance management department has gradually formed a relatively intelligent HPM management system, thus improving management effectiveness. The change rule of management decision on management effectiveness The management effectiveness increases in the early stage, decline slowly in the middle stage, and increases in the later stage. This is because the rapid development of information, data, and intelligence determines the scientific nature of maintenance time. Moreover, carrying out preventive maintenance in time can promote management effectiveness. In the middle stage, the adverse effects appear due to high maintenance costs, shortage of funds, and backward management modes. In the later stage, with the development of high-speed detection technology for pavement performance and the establishment of a digital management platform, the scientific and intelligent level of maintenance management has been improved. Thus, effectiveness of HPM management is promoted. The change rule of external condition on management effectiveness There is a decline initially and a slow rise after the middle stage. This is due to the relatively weak maintenance technology investment mechanism and market operation mechanism in the early stage, which constrains the improvement of management effectiveness. In the middle stage, the concept of preventive maintenance is widely accepted, leading to market competition and the rationality of pavement structure design. The interaction of great attention and information ensures the safety of maintenance personnel, increases the frequency of pavement inspections, and promotes management effectiveness. 6. Discussions 6.1 Implications In this paper, a hybrid EFA-SNA-SD approach is used to systematically integrate the major management factors of HPM, distinguish their important degree, and analyze their influence laws. The findings enriched and broadened the development of preventive maintenance concepts, contributing to the formation of a sustainable transportation system. The study identified 26 key HPM management factors, which were categorized into six areas. This has improved our ability to interpret maintenance problems and enables effective action to be taken in response to HPM management issues. By integrating these factors into preventive maintenance management, we can improve the overall quality of highway maintenance, create a safe and efficient traffic system, and meet the future high-demand, high-efficiency, and high-quality highway services for sustainable development. The study found that HPM management factors were hierarchical and mutually constraining. Therefore, this paper distinguished them into key, hub, and non-key factors. This facilitated preventive maintenance work and provided a direction for efficient improvement of preventive maintenance management effectiveness. Key management factors in daily HPM management include a suitable management mode, adequate preparation, and reasonable financial support. However, limitations in maintenance technology, equipment, information, and changing social industry environments can limit the choice of the best management model, the speed of obtaining the best maintenance information, and the reasonable allocation of funds. Therefore, appropriate maintenance plans need to be developed to achieve sustainable development of highways. Multi-level implementation measures are key to improving the effectiveness of HPM management. By constructing the SD model, this paper found that the influence law of different management factors on the effectiveness of HPM management varied and generally showed an upward trend. Based on the findings, we propose the following suggestions. First, we should follow the principle of adapting measures to local conditions and ensuring consistency between power and responsibility to gradually improve the HPM management system, especially the strengthening of the operation mechanism. Second, the government should increase the investment in preventive maintenance funds and allocate them reasonably, while also providing regular technical guidance to maintenance personnel to improve their professional ability. Third, we should actively promote the concept and long-term benefits of preventive maintenance management and establish the correct awareness of preventive maintenance management. Finally, we recommend collecting and integrating highway data and using GIS to improve the information and intelligence of HPM. These measures will provide strong theoretical support and technical guarantee for the implementation of preventive maintenance management. 6.2 Limitations and recommendations In this paper, we have presented a hybrid approach of EFA-SNA-SD to integrate and analyze the major management factors of HPM. However, there are some limitations in our research process that need to be addressed. Firstly, as the development of HPM management continues, the major management factors may change over time. Therefore, future research can focus on the development trend of preventive maintenance and adjust the management factors accordingly. Secondly, our data is limited and the sample size is not comprehensive enough to represent all regions. Future research could benefit from expanding the sample size and collecting data from different regions. We suggest establishing long-term performance observation stations for pavement performance across the country to provide a more comprehensive and accurate scientific basis for preventive maintenance decisions. Finally, we acknowledge that our methodology can be further improved. We recommend considering programming software such as R language and Matlab for clustering and visual analysis of management factors, which can achieve a combination of computer technology and integration of HPM management concepts. Overall, despite these limitations, this study has contributed to the understanding of HPM management and provided theoretical and practical references for enhancing the benefits of preventive maintenance management to form a sustainable transport system. We believe that further research in this area can lead to significant improvements in the effectiveness of HPM management. 7. Conclusions In conclusion, this research aimed to identify the major HPM management factors and their dynamic effects on the effectiveness of HPM management with a hybrid EFA-SNA-SD approach. The research identified 26 major HPM management factors that are categorized into six dimensions: management system, management resources, management cognition, management decision, management technology, and external conditions. Information acquisition, system perfection, system planning, etc. are identified as key factors that are critical to the effectiveness of HPM management. System execution, manager capability, organizational support, etc. are identified as hub factors that significantly influence HPM management effectiveness. Route selection, machinery allocation, pavement structure, etc. are identified as non-key factors that have less impact on the effectiveness of HPM management. The SD model developed in this study demonstrates that different management factors have varying effects on the effectiveness of HPM management. The results indicate that effective management strategies require a holistic approach that considers all dimensions of HPM management. Furthermore, the model shows that the effectiveness of HPM management can be improved through continuous monitoring and adjustment of management factors. The findings of this research have significant implications for the sustainable development of highways. The results can guide policymakers and highway managers in developing effective HPM management strategies that enhance the durability, safety, and cleaner production of highway infrastructure, thus contributing to a more sustainable transportation system. Declarations Declaration of Competing Interest The authors declare that they have no financial or personal relationships that could have appeared to influence the work reported in this paper. 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Supplementary Files SurveyofHPMmanagementfactors.xlsx Cite Share Download PDF Status: Published Journal Publication published 26 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 30 Aug, 2024 Reviews received at journal 22 Aug, 2024 Reviewers agreed at journal 12 Aug, 2024 Reviews received at journal 24 Jun, 2024 Reviewers agreed at journal 17 Jun, 2024 Reviewers agreed at journal 11 Jun, 2024 Reviewers invited by journal 31 Mar, 2024 Editor assigned by journal 26 Mar, 2024 Editor invited by journal 22 Mar, 2024 Submission checks completed at journal 22 Mar, 2024 First submitted to journal 11 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4076043","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":283668782,"identity":"fcdff5e7-10d0-442c-9ce3-267c3d31efa2","order_by":0,"name":"Na Zhao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYDACCTBpA+MyE60lDUQwNpCi5TAJWuRnNz98XFBzXl5+RvrzBwwV1okN7GcP4NXCOOeYsfGMY7cNN9zIMWxgOJOe2MCTl4BXC7NEgpk0D9vtBAOJHMYGxrbDiQ0SPAZ4tbBJpH+T5vl3LgHosIcNjP+I0MIjkWMmzdt2IIHhRoJhA2MDEVokJHKKjXn7kg03nHljOCPhWLpxG08Ofi1A92x8zPPNTl6+Pf3Bhw811rL97Gfwa0EFCSDfkaB+FIyCUTAKRgEOAAARLkCoE0qbsAAAAABJRU5ErkJggg==","orcid":"","institution":"Changsha University of Science \u0026Technology","correspondingAuthor":true,"prefix":"","firstName":"Na","middleName":"","lastName":"Zhao","suffix":""},{"id":283668783,"identity":"b6be1849-6159-41d7-b1a6-ede2feb14a26","order_by":1,"name":"Yijuan Liu","email":"","orcid":"","institution":"Changsha University of Science \u0026Technology","correspondingAuthor":false,"prefix":"","firstName":"Yijuan","middleName":"","lastName":"Liu","suffix":""},{"id":283668784,"identity":"b5b41221-9477-4113-b306-8c3d57b12834","order_by":2,"name":"Jianchang Li","email":"","orcid":"","institution":"Imperial College Business School, Imperial College London","correspondingAuthor":false,"prefix":"","firstName":"Jianchang","middleName":"","lastName":"Li","suffix":""},{"id":283668785,"identity":"3b02a97c-a29f-422b-a77f-d391c6d5fdb4","order_by":3,"name":"Huihua Chen","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Huihua","middleName":"","lastName":"Chen","suffix":""},{"id":283668786,"identity":"8a42bf01-0d72-4e47-8969-045f1897e803","order_by":4,"name":"Baoquan Cheng","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Baoquan","middleName":"","lastName":"Cheng","suffix":""}],"badges":[],"createdAt":"2024-03-11 15:19:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4076043/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4076043/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-76692-4","type":"published","date":"2024-10-26T15:58:23+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53562138,"identity":"e414049f-9fe7-410e-adac-06eeed71876c","added_by":"auto","created_at":"2024-03-27 13:46:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":354032,"visible":true,"origin":"","legend":"\u003cp\u003eResearch route.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/0eb26984f32e082134c8ea01.png"},{"id":53562139,"identity":"80d467dc-1773-4801-8fd6-e03d2fc95e40","added_by":"auto","created_at":"2024-03-27 13:46:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1252119,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork relation graph.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/2a5635b4315234e961b36db9.png"},{"id":53562148,"identity":"6a83688c-acb4-43ee-909d-f0352329f3f8","added_by":"auto","created_at":"2024-03-27 13:46:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":286035,"visible":true,"origin":"","legend":"\u003cp\u003eCausal-loop diagram.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/52074d5e131386019f9d9be4.png"},{"id":53562142,"identity":"212948ef-b247-4e77-a97f-18aca4ba4ef3","added_by":"auto","created_at":"2024-03-27 13:46:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":252004,"visible":true,"origin":"","legend":"\u003cp\u003eStock-flow diagram.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/0e3387ed92b6b9235e44152c.png"},{"id":53562147,"identity":"36952ba8-f9ab-4cc4-8222-4780ecd81174","added_by":"auto","created_at":"2024-03-27 13:46:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":18312,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution simulation effectiveness of HPM management.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/e11babc9ed7c84d5928ac0ff.png"},{"id":53562141,"identity":"d25e8668-e1da-47c5-b607-21904e2082f6","added_by":"auto","created_at":"2024-03-27 13:46:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":64019,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution simulation of HPM management factors.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/a5b6653d19d0891cbaaab997.png"},{"id":67682027,"identity":"7b7f9df0-5984-4d11-a262-649249c06b87","added_by":"auto","created_at":"2024-10-28 16:12:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3618262,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/6566723e-e3b3-4a63-a64e-987c98fe8e88.pdf"},{"id":53562146,"identity":"621ac0d7-9eeb-4aa7-b358-54f59de430d7","added_by":"auto","created_at":"2024-03-27 13:46:13","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":43307,"visible":true,"origin":"","legend":"","description":"","filename":"SurveyofHPMmanagementfactors.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4076043/v1/cb29b5e7c37d79a6c03159dd.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Hybrid Approach to Investigating Major Management Factors for Effective Highway Preventive Maintenance","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHighways play a critical role as modern transportation infrastructure, providing an essential capacity and quality level that fosters sustainable development across the economy, society, humanities, and environment (Wang \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Jiang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). As one of the most crucial infrastructure types, enhancing their sustainability is a top priority to achieve better transportation functions, reduce environmental impacts, ensure passengers\u0026rsquo; safety and comfort, extend highways\u0026rsquo; service life, thus creating a better People-Environment-Infrastructure relationship in the urban transportation system (Kothari et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Naseri et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, due to the extensive use of expressways and their prolonged operational time, road damage and deterioration are often unavoidable, leading to a decline in traffic service quality and even jeopardizing personal safety in severe cases (Zhu \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Shi \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Moreover, heavy traffic loads, rising user expectations, and insufficient maintenance funds pose enormous maintenance pressure on highway management (Zhang \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Wang \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, the highway maintenance specification recommends implementing a prevention-based maintenance policy (Li et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHighway preventive maintenance (HPM) involves the implementation of maintenance measures when there are no diseases present or at the initial stage of disease occurrence to prevent the aggravation of problems. This process includes conducting regular inspections and assessments of the highway to detect signs of wear and tear, such as cracks or potholes. Upon identification of such issues, maintenance measures such as sealing cracks or patching potholes can be promptly implemented to prevent further damage (Yan \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Jiang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Effective HPM is a reasonable approach towards sustainable highways as it prioritizes preventative maintenance over corrective maintenance through early treatment, proactive maintenance, and advanced maintenance (Shi \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Zou et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). By conducting regular maintenance and repairs, HPM can address minor issues before they become major problems, preventing the need for more extensive and environmentally damaging repairs or reconstruction which may have significant environmental impacts (Kothari et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Liu et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), including increased carbon emissions from heavy equipment, generated construction waste from construction activities, and disruption to ecosystems (Amarasiri and Muhunthan \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, HPM can also improve the energy efficiency of pavement infrastructure by improving the smoothness and ride quality of roadways, which can lead to lower fuel consumption and greenhouse gas emissions from vehicles. Additionally, some HPM techniques, such as pavement preservation, can use ecofriendly materials and processes that are less harmful to the environment. HPM also identifies and resolves safety hazards through regular maintenance, which improves the safety and accessibility of highways (Wang \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Liu et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In conclusion, the implementation of effective HPM can contribute to the cleaner production of highway infrastructures and sustainability of urban transportation systems. However, despite the potential benefits, the widespread adoption of HPM management has faced numerous challenges. These challenges include limited funding, lack of expertise, weak awareness of maintenance management, deteriorating road conditions, lack of political support, and other related management factors (Zhang \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Wang \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Kothari et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Liu et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEffective HPM management requires a combination of technical expertise, financial resources, political support, and effective stakeholder engagement (Yang et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Ruiz Rodr\u0026iacute;guez et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, El Said and Stammer \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Humayun et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Since these factors are reported in the literature in a piecemeal fashion, a comprehensive understanding of such factors and their dynamic impact from a systems perspective is highly desired. Therefore, this paper aims to explore the major HPM management factors, their important degree, and their influence laws through a hybrid research method combining exploratory factor analysis (EFA), social network analysis (SNA) and system dynamics (SD). Three key questions about HPM management are expected to be answered in this study:\u003c/p\u003e \u003cp\u003e(1) What management factors affect the efficiency of HPM?\u003c/p\u003e \u003cp\u003e(2) How to distinguish the importance degree of these identified factors?\u003c/p\u003e \u003cp\u003e(3) How these factors influence the efficiency of HPM dynamically?\u003c/p\u003e \u003cp\u003eThe key innovation of this paper lies in its comprehensive and systematic approach to identifying and evaluating the major management factors for effective HPM in the context of the PEI relationship. By identifying the most critical management factors and modeling their dynamic interplay, transportation agencies can develop more effective HPM plans, allocate resources more efficiently, and ultimately improve the overall quality of highway maintenance. Overall, this study advances knowledge and understanding of sustainable infrastructure management, which is critical to the long-term health and sustainability of the transport system.\u003c/p\u003e \u003cp\u003eThis paper is organized as follows: Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e describes the research methodology, followed by Section \u003cspan refid=\"Sec3\" class=\"InternalRef\"\u003e3\u003c/span\u003e which screens the HPM management factors. Section \u003cspan refid=\"Sec13\" class=\"InternalRef\"\u003e4\u003c/span\u003e distinguishes the important degree of HPM management factors. Section \u003cspan refid=\"Sec14\" class=\"InternalRef\"\u003e5\u003c/span\u003e explores the influence law of HPM management factors using SD. Section \u003cspan refid=\"Sec19\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the implications, limitations and recommendations. Finally, the concluding section summarizes the main contributions of this study.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cp\u003eA hybrid EFA-SNA-SD method is adopted to screen the major management factors, distinguish their important degree and systematically analyze their influence laws. EFA is a method used to process multivariate observed variables and perform dimensionality reduction, which allows combining a set of interrelated observed variables into more significant latent variables (Gunduz and Abdi \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It is usually used to determine the number of hypothetical potential variables, structures, dimensions or factors (Watkins \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Thus, EFA can integrate the intricate HPM management factors in this study. SNA is a methodology that uses mathematical and statistical techniques to analyze social networks and relationships between individuals, groups, or organizations. It helps to identify patterns and structures within a network and to understand how relationships shape and influence these factors (Pryke et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, it can reasonably distinguish the important degree of HPM management factors into key factors, hub factors and non-key factors (Sun et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). SD is a theory that studies the overall behavior of a socio-economic system by analyzing the feedback structure relationships between the variables within the system. The SD method systematically analyzes the influence law of factors, which is one of the most common procedures to determine complex systems (Gu et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Consequently, SD is suitable for dynamically exploring the influence law of HPM management factors.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, this research is divided into the following three steps.\u003c/p\u003e \u003cp\u003eStep 1: Related literature about HPM management is reviewed to preliminary sort out the major management factors in HPM. Expert review, questionnaire survey and EFA are applied to further determine major management factors in HPM.\u003c/p\u003e \u003cp\u003eStep 2: The SNA method is adopted to distinguish the importance degree of identified management factors. The relationship matrix of factors is developed based on expert scoring and imported into the UCINET 6 software to calculate the relative degree of centrality. The relationship diagram is also drawn with Netdraw software.\u003c/p\u003e \u003cp\u003eStep 3: The SD model is used to explore the dynamic influence laws among HPM management factors. Construct a causal-loop diagram for qualitative analysis and a stock-flow diagram for quantitative analysis. And the state transition equation is constructed. Based on the above steps, simulation analysis is carried out.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. HPM management factors","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Literature review\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Management system\u003c/h2\u003e \u003cp\u003eEstablishing an intelligent highway maintenance system is the way to achieve high-quality development of HPM in the new era. It efficiently integrates resources, enhances maintenance efficiency, and ensures highway transportation safety (Defu Che and Zhao 2021, Jie lin and Jing 2020, Mohamed et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). After thorough research, we have identified four critical aspects of this system: system establishment, system perfection, system implementation, and system feedback. Firstly, establishing an intelligent highway maintenance system is essential to improve the efficiency of maintenance management, which can help the highway management to obtain the status information of road, bridge, tunnel and other facilities in time (Defu Che and Zhao 2021, Xu Qiao et al. 2019, Yun Hou et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Shaojin Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Secondly, for the characteristics of highway maintenance work with high frequency and long period, the management system needs to be improved to better serve the actual needs (Yun Hou et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Defu Che and Zhao 2021, Shaojin Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Thirdly, implement the management system and closely integrate it with work practices to ensure smooth implementation (Shaojin Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Mingming Zhou and Zhou 2015, Xu Qiao et al. 2019). Finally, the implementation effect of the management system is continuously optimized according to the feedback until the system can better adapt to the actual work needs (Mingming Zhou and Zhou 2015, Shaojin Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This enables precise maintenance and promotes sustainable development.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Management resource\u003c/h2\u003e \u003cp\u003eThe construction and maintenance of large-scale transportation infrastructure require significant resources, emphasizing the reasonable and efficient resource allocation (Liu et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This includes the integrated planning and allocation of machinery, materials, and capital. Among them, machinery is an important tool for highway preventive maintenance. The configuration of machinery should be considered to ensure the performance and quality of machinery to adapt to the maintenance needs and ensure the efficiency of machinery, thus improving the effectiveness and economic efficiency of maintenance management (Lv et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Zhu \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Mirheli et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Ruiz Rodr\u0026iacute;guez et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Wheat \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In terms of materials, adequate and reliable material supply and standard material quality can reduce maintenance cost, improve maintenance effect and ensure the safety, smoothness and sustainability of highways (Ying Liu et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, JingHai He et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Mohamed and Tran \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In terms of capital, capital investments and highway revenues are the source of HPM funding. If there is a shortage of funds, the needs of HPM cannot be met and maintenance cannot be successfully promoted. Therefore, securing a source of maintenance funding is critical to HPM (El Said and Stammer \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Wang \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Shi et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Management cognition\u003c/h2\u003e \u003cp\u003eIn recent years, the growth in traffic trips and the popularization of transportation have led to increased importance in the construction and maintenance of highways. However, the current problems in HPM management are becoming more and more noticeable. Among them, public cognition of highway maintenance management directly affects the difficulty of HPM management (Wheat \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Love et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Harvey \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, it is essential to adopt the \u0026ldquo;build and maintain\u0026rdquo; policy from an ideological level and enhance public awareness and participation in maintenance management. Additionally, the degree of personal cognition directly affects the ability of individuals to drive safely and civilly on highways. Raising maintenance awareness and cognitive degree of personal can help reduce the burden of HPM management (Al-Shabbani et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Zuluaga et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The department, as the management and implementation unit, can only accurately grasp and implement the conservation measures and improve the effectiveness of HPM management if it has an in-depth understanding of the purpose and significance of HPM (Fei Guo and Zhang 2020, Zhao \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Sun \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). And it is necessary to improve the ability of maintenance managers and the sense of responsibility of maintenance staff to improve the quality and efficiency of maintenance work (Wang \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020c\u003c/span\u003e, Ying Liu et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Huo \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Greven et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Menges \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Only in this way can we guarantee the smooth implementation of HPM management and provide a more convenient and safe highway travel environment for the society and the public to achieve sustainable development.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.1.4 Management decision\u003c/h2\u003e \u003cp\u003eThe heavy workload of HPM tasks and the inadequate maintenance management decision-making system urgently require the development of a scientific and efficient management mode that can meet the demand for quick, efficient, and high-quality decision-making under high-load maintenance tasks (Mohamed et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The core issue of HPM is \u0026ldquo;the right maintenance measures at the right time on the right section of road to achieve the best maintenance benefits\u0026rdquo; (Xiangfeng Wang and Yong 2017). Considering traffic flow, vehicle type, road conditions and other factors, maintenance managers scientifically and reasonably select routes and develop optimal maintenance time nodes to minimize safety risks during highway operation (Yin et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Yu et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Rodoplu et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Also, when maintenance measures are carried out, their effectiveness needs to be measured to predict the benefits of the maintenance work (Amarasiri and Muhunthan \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Zou et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This allows adjustments to be made to the maintenance measures to achieve optimal maintenance results. In addition, the costs of maintenance work are a factor that should not be overlooked (Lei et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Liu et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Li et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Maintenance costs are directly related to the development, implementation and effectiveness of management decisions. Reasonable control of maintenance costs is conducive to realizing the economic benefits of maintenance work. Overall, management decision improves the scientific maintenance methods for the HPM management department to ensure the scientific construction maintenance and efficient operation management of highways (Li et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, You et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.1.5 Management technology\u003c/h2\u003e \u003cp\u003eWith modern maintenance technology and efficient management, highways can operate normally and continuously improve their service level. To tackle heavy maintenance tasks, new technologies, materials, and techniques can be utilized to enhance pavement durability and extend the highway's service life (Humayun et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Kruachottikul et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Dellenbaugh et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Jalinoos et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the technical level of existing maintenance personnel is inadequate (Xue \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, it is especially important to improve the personal technical level, which will help to improve the effectiveness of maintenance management (Tang \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Wang \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e, Ruiz Rodr\u0026iacute;guez et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, highway maintenance information is critical. Information acquisition and utilization can help HPM managers to have a comprehensive understanding of the condition and problems of highways so that effective maintenance programs can be developed (Sameen and Pradhan \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Jiang et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Hijji et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Tezel and Aziz \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This helps maintenance managers to control maintenance costs and improve resource utilization. And advanced data analysis techniques can be employed to analyze and extract relevant information from highway maintenance data, guiding the development of maintenance work.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.6 External condition\u003c/h2\u003e \u003cp\u003eThe success of HPM is not solely dependent on internal management mechanisms, but also on external factors. Government attention can increase the investment and support of HPM management, promote the innovation and development of HPM management technology, and provide support to ensure the safety and smooth flow of highways (Yang et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Liu \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Hong Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Market competition helps the development of highway maintenance industry, improves service quality and reduces maintenance cost (Yarmukhamedov et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Wu et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). At the same time, the risks of maintenance work should be given sufficient attention and appropriate precautions should be taken to minimize potential impacts (Yao et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Sabatino et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In addition, maintenance work is often carried out in fields, open air and other environments that are vulnerable to climatic factors (Hernandez et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Liu et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Liu et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Sentic et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, it is important to consider the external factors of HPM management comprehensively to enhance management efficiency and improve the quality of maintenance work. This is critical to ensure the safety and smoothness of highways.\u003c/p\u003e \u003cp\u003eBased on the literature review, we found it necessary to collect and study the major management factors of HPM and initially screened the HPM management factors, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of HPM factors and relevant literature references\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiterature source\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoint\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eManagement system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem establishment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDefu Che and Zhao (2021), Xu Qiao et al. (2019), Yun Hou et al. (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Shaojin Zhang et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe establishment of the management system can help the highway management to obtain timely information on the status of the road, bridges, tunnels and other facilities.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem perfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYun Hou et al. (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Defu Che and Zhao (2021), Shaojin Zhang et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccording to the characteristics of HPM, it is essential to perfect the management system to make it better serve the actual needs.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem execution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMingming Zhou and Zhou (2015), Xu Qiao et al. (2019), Shaojin Zhang et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTo closely integrate work practices and ensure the successful implementation of maintenance work, the management system needs to be executed.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem feedback\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMingming Zhou and Zhou (2015), Shaojin Zhang et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTo ensure the effectiveness of the implementation of the management system, it is essential to continuously optimize the management system based on feedback.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eManagement resource\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMachinery allocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZhu (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Lv et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Mirheli et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProperly allocated machinery can ensure mechanical quality and performance.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaterial supply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLiu et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Mohamed and Tran (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnsure adequate material supply to prepare for maintenance work.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaterial quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJingHai He et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Mohamed and Tran (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaterial quality directly affects HPM's effectiveness and ability to continue stable operation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCapital investment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEl Said and Stammer (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Wang (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Wang et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCapital investment is an important safeguard for HPM.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncome situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEl Said and Stammer (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Feng Li et al. (2015), Shi et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe income situation of highways affects the rational allocation of HPM resources.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMechanical efficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWheat (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Ruiz Rodr\u0026iacute;guez et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMechanical efficiency affects the effectiveness and economic efficiency of HPM.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eManagement cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHarvey (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Wheat (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Love et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe degree of public cognition directly affects the difficulty of HPM management.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePersonnel cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAl-Shabbani et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Zuluaga et al. (\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe degree of personal cognition directly affects their ability to drive safely and civilly on highways.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDepartment cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFei Guo and Zhang (2020), Zhao (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Sun (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe maintenance department has an in-depth understanding of the purpose and significance of HPM to accurately grasp and implement the maintenance measures.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManager capability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWang (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020c\u003c/span\u003e), Ying Liu et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Huo (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Greven et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHaving excellent managerial capabilities is the way to better promote HPM management.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSense of responsibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMenges (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Huo (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe sense of responsibility of the maintenance staff guarantees that maintenance work is carried out properly.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eManagement decision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManagement mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWei (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Hou (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), Wang et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Mohamed et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTo meet the need for fast, efficient and high-quality decision-making under high-load maintenance operations, there is an urgent need to develop scientific and efficient management modes.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoute selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYu et al. (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Ji (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Wang et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScientific and reasonable route selection reduces the safety risk of highway operation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTiming determination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYin et al. (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Rodoplu et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), You et al. (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Guan et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDetermine the optimal maintenance time point reduces the safety risk of highway operation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMeasure effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZou et al. (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Wang et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Amarasiri and Muhunthan (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTo predict the benefits of maintenance efforts, implementation effects need to be measured.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaintenance cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLei et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), You et al. (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Li et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Liu et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaintenance costs are directly related to the development, implementation and effectiveness of management decisions.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eManagement technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNew technology application\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKruachottikul et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Dellenbaugh et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Jalinoos et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Humayun et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTo address the current situation of heavy maintenance tasks, new technologies can be applied to improve the durability of pavements and extend the service life of highways.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePersonnel technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTang (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Wang (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e), Ruiz Rodr\u0026iacute;guez et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eImproving personal technical skills helps to improve the effectiveness of maintenance management.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformation utilization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHijji et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Sameen and Pradhan (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Tezel and Aziz (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTo develop effective maintenance programs, information needs to be fully explored and utilized.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformation acquisition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJiang et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Hijji et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Sameen and Pradhan (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTo fully understand the condition and problems of highways, adequate acquisition is required.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eExternal condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernment attention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYang et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Hong Zhang et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Liu (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGovernment attention can increase investment and support for HPM management.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarket competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWu et al. (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Yarmukhamedov et al. (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCompetition in the market helps the development of the highway maintenance industry.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWork risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYao et al. (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Sabatino et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe risky nature of maintenance work exacerbates the difficulty of maintenance work to some extent.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClimate impact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHernandez et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Sentic et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Liu et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Liu et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaintenance work is often in the field, open air and other environments, vulnerable to climatic factors.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Questionnaire survey\u003c/h2\u003e \u003cp\u003eThis paper built on the literature review, drew on existing well-established scales based on the identified factors in Section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e, thus setting the measurement items. And the questionnaire items were amended to form a questionnaire on the HPM management factors through expert interviews, small sample testing. This study distributed the questionnaire through a combination of online and offline methods to collect survey data. Specifically, this was done by sending questionnaire links to respondents through social media platforms such as WeChat and QQ, and adopting a combination of self-administered questionnaires and face-to-face interviews for comprehensive data collection. The questionnaire was distributed to 300 respondents. 260 valid responses were collected, resulting in a response rate of 86.7%. Invalid questionnaires were excluded based on the following criteria: (1) questionnaires that left too many questions unanswered, (2) contradictory choices, and (3) almost identical to others.\u003c/p\u003e \u003cp\u003eThe sample characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Among them, 59.62% were male and 40.38% were female. The majority of the survey respondents were under 45 years old (90.38%), had a bachelor\u0026rsquo;s degree (61.54%), and had been working for 6\u0026ndash;15 years (53.85%). The main issuing units are the maintenance unit, detection unit, construction unit, advisory unit, supervision unit. This indicates that respondents\u0026rsquo; source composition is consistent with reality and can reflect the actual situation to a certain extent.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the sample.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCumulative percentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation background\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003especialty and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eundergraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edoctor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;=25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;=45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eWorking life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;=2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;=15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eWorking unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emaintenance unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edetection unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003econstruction unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eadvisory unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esupervision unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Exploratory factor analysis\u003c/h2\u003e \u003cp\u003eTo analyze the factors that influence HPM obtained from the questionnaire survey, the KMO (Kaiser-Meyer-Olkin) statistic method and the Bartlett\u0026rsquo;s spherical test were used. As the data in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows, the KMO value was 0.778 and the Bartlett\u0026rsquo;s spherical test chi-square value was 2426.642, with a significance less than 0.01. This indicates that the HPM scale is suitable for factor analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKMO and Bartlett\u0026rsquo;s test.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eKaiser-Meyer-Olkin Measure of Sampling Adequacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBartlett\u0026rsquo;s test of sphericity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApprox Chi-Square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2426.642\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo identify the most representative variables, variables with eigenvalues equal to or greater than 1.0 were selected as major factors. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, a total of six major factors were chosen with a cumulative variance contribution of 94.522%. The factor names were assigned after rotating the component matrix, which yielded the following six factors: management system, management resource, management cognition, management decision, management technology, and external condition. Only observed variables with factor loadings greater than 0.5 were included in the analysis, while those with loadings less than 0.5 were excluded. The final selection of 26 factors for HPM was based on group discussion and expert opinion, which excluded system feedback and the sense of responsibility. The validity of the factor analysis was strong, as confirmed by the high cumulative variance contribution of the six factors. The summarized 26 factors for HPM are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal variance explained.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eComponent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eInitial Eigenvalues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eRotation Sums of Squared Loadings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVariance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCumulative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVariance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCumulative\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e37.977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e54.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e85.361\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e94.522\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHPM management factor scale.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFactor loading\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eManagement system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem establishment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem perfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem execution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eManagement resource\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMachinery allocation `\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaterial supply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaterial quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCapital investment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncome situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMechanical efficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eManagement cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePersonnel cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDepartment cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManager capability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.818\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eManagement decision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManagement mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRoute selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTiming determination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMeasure effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaintenance cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eManagement technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNew technology application\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePersonnel technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformation utilization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformation acquisition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eExternal condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernment attention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.944\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarket competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWork risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClimate impact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Important degree of HPM management factors","content":"\u003cp\u003eTo distinguish the important degree of management factors, this paper uses the SNA method to explore these factors in depth to select key, hub and non-key factors. The research invited ten experts to score the relationship between factors, with a score of 1 indicating influential and 0 indicating non-influential. The resulting relationship matrix of factors was then constructed, and imported into UCINET 6 software to calculate the relative degree of centrality, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. It can be observed that information acquisition, system perfection, system establishment, government attention, new technology application, capital investment, and management mode are also in an important position and are defined as key factors that are the top considerations to enhance management effectiveness. System execution, manager capability, personnel technology, maintenance cost, information utilization, income situation, measure effect, public cognition, department competition, and personnel cognition connect key factors and non-key factors, which are defined as hub factors. Route selection, machinery allocation, timing determination, market competition, material supply, work risk, mechanical efficiency, material quality, and climate impact are at the edge, which are defined as non-key factors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeasurement analysis result.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOut-degree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIn-degree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC\u003csub\u003eIRD\u003c/sub\u003e(X)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRank\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einformation acquisition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esystem perfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esystem establishment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egovernment attention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enew technology application\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecapital investment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emanagement mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esystem execution\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emanager capability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epersonnel technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emaintenance cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einformation utilization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eincome situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emeasure effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epublic cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edepartment competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epersonnel cognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eroute selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emachinery allocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etiming determination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emarket competition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ematerial supply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ework risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emechanical efficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ematerial quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eclimate impact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNetdraw is used to draw the relationship graph of HPM management factors, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The graph highlights the critical role of information acquisition in HPM management, as evidenced by its highest relative centrality and its ability to radiate to other areas. To ensure effective preventive maintenance management, managers must possess comprehensive knowledge of systems, technologies, funds, materials, and external dynamics, enabling them to make informed decisions (Yuefeng \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Highways have the attributes of high traffic volume, perfect equipment, and high technological content. However, the existing maintenance management system has defects such as insufficient theoretical innovation and vague objectives, which cannot achieve the expected effect of preventive maintenance management (Ahmed et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, the continuous evolution of maintenance technology, the emergence of new materials, and the steady progress of equipment, coupled with substantial capital investment, are the primary drivers of enhanced technology, materials, and equipment (Wang \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). From the above discussion, it is clear that the relative degree of centrality of key factors such as information acquisition and system perfection is greater. System execution, managerial capability, etc., as the \u0026ldquo;link\u0026rdquo; between key and non-key factors, have a greater impact on both but less on the effectiveness of HPM management. Therefore, hub factors are relatively less centralized. With the cooperation of the government and the units, non-key factors such as route selection and machinery allocation have little impact on management efficiency, which means the lowest level of centralization.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"5. Influence law of HPM management factors","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e5.1 Causal-loop diagram\u003c/h2\u003e\n \u003cp\u003eBased on the relationship among the HPM management factors, a causal-loop diagram between management factors and the effectiveness of HPM management can be built shown to describe the interaction relationships, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. There are 5 relationship loops, which consist of 4 positive relationship loops and 1 negative relationship loop. The dynamic interaction behavior of variables in each relationship loop is interpreted below.\u003c/p\u003e\n \u003cp\u003eLoop 1: management cognition \u0026rarr; +effectiveness of HPM management \u0026rarr; +driving comfortableness \u0026rarr; +management cognition\u003c/p\u003eLoop 1 is a positive feedback loop. Improving the management cognition will enhance managers\u0026rsquo; positive seriousness about highway management and simulate the implementation of preventive maintenance, promoting the effectiveness of HPM management. In this situation, the conditions and quality of highways can be well maintained, which enables drivers to feel more comfortable when driving. Thus, the management perception will be enhanced.\u003cbr\u003e\n \u003cp\u003eLoop 2: management cognition \u0026rarr; +effectiveness of HPM management \u0026rarr; +highway revenue \u0026rarr; +management cognition\u003c/p\u003eLoop 2 is a positive feedback loop. The state vigorously promotes the HPM concept and increases conservation implementation. It will prolong the service of the road and further improve the effectiveness of HPM management. Therefore, highway revenue will increase since more drivers may choose highways. In this way, the improved revenue will stimulate the managers to further improve their management cognition.\u003cbr\u003e\n \u003cp\u003eLoop 3: management resource \u0026rarr; +effectiveness of HPM management \u0026rarr; +highway revenue \u0026rarr; +management resource\u003c/p\u003eLoop 3 is a positive feedback loop. The effectiveness of HPM management will be significantly improved by vigorously developing management resources and making rational allocations of resources. In turn, the revenue of the highway is on an upward trend, thus improving the supply of management resources and mechanical efficiency.\u003cbr\u003e\n \u003cp\u003eLoop 4: management system \u0026rarr; +effectiveness of HPM management \u0026rarr; +service life \u0026rarr; +management system\u003c/p\u003eLoop 4 is a positive feedback loop. The state improved the management system and realized the transformation of information, automation and intelligence of maintenance management, which contribute to promoting the effectiveness of HPM management. This will significantly extend the service life of highways. In this situation, the managers will be motivated to further improve the management system.\u003cbr\u003e\n \u003cp\u003eLoop 5: external condition \u0026rarr; +effectiveness of HPM management \u0026rarr; +service life \u0026rarr; -external condition\u003c/p\u003eLoop 5 is a negative feedback loop. The quality of preventive maintenance can be affected by the external condition, including advanced technology, advanced equipment, quality materials, strict management, and especially the appropriate season. Therefore, the less fluctuation of external condition, the better the effectiveness of HPM management, and the longer the service life of the highway. However, as the service life grows, the external condition will get worse.\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e5.2 Stock-flow diagram\u003c/h2\u003e\n \u003cp\u003eAfter identifying the main factors and their interactions involved in the whole system, a stock-flow diagram using the Vensim software is developed so that the SD model can be run to simulate the internal dynamic relationships between the factors, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e5.3 State transition equation\u003c/h2\u003e\n \u003cp\u003eAs an essential part of the SD model, the state transition equation describes the dynamic change patterns of the factors in the model which provides the theoretical support for simulation. The SD model for HPM management factors involves the following state transition equations which are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\u003cbr\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eState transition equations table.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eVariable Category\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eName\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eEquation\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003eHorizontal variables\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003emanagement system\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eINTEG (management system change volume,0)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement resource\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eINTEG (management resource change volume,0)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement cognition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eINTEG (management cognition change volume,0)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement decision\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eINTEG (management decision change volume,0)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement technology\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eINTEG (management technology change volume,0)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eexternal condition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eINTEG (external condition change volume,0)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003eRate variables\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003emanagement system change volume\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003esystem execution rate-system perfection rate\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement resource change volume\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eresources growth rate-resources reduction rate\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement cognition change volume\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ecognition accumulation rate-cognition elimination rate\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement decision change volume\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003edecisions efficient rate-decisions error rate\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement technology change volume\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003etechnological advancement growth rate-technological advancement reduction rate\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eexternal condition change volume\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003econditions vary greatly-conditions vary small\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"13\"\u003eAuxiliary variables\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eeffectiveness of HPM management\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ew\u003csub\u003e1\u003c/sub\u003e\u0026times;management system\u0026thinsp;+\u0026thinsp;w\u003csub\u003e2\u003c/sub\u003e\u0026times;management resource\u0026thinsp;+\u0026thinsp;w\u003csub\u003e3\u003c/sub\u003e\u0026times;management cognition\u0026thinsp;+\u0026thinsp;w\u003csub\u003e4\u003c/sub\u003e\u0026times;management decision\u0026thinsp;+\u0026thinsp;w\u003csub\u003e5\u003c/sub\u003e\u0026times;management technology\u0026thinsp;+\u0026thinsp;w\u003csub\u003e6\u003c/sub\u003e\u0026times;external condition\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003esystem perfection rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ea\u003csub\u003e1\u003c/sub\u003e\u0026times;system establishment\u0026thinsp;+\u0026thinsp;a\u003csub\u003e2\u003c/sub\u003e\u0026times;system perfection+\u003cbr\u003ea\u003csub\u003e3\u003c/sub\u003e\u0026times;external condition\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003esystem execution rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eb\u003csub\u003e1\u003c/sub\u003e\u0026times;system execution\u0026thinsp;+\u0026thinsp;b\u003csub\u003e2\u003c/sub\u003e\u0026times;management cognition\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eresources reduction rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ec\u003csub\u003e1\u003c/sub\u003e\u0026times;insufficient funds\u0026thinsp;+\u0026thinsp;c\u003csub\u003e2\u003c/sub\u003e\u0026times;poor earnings+\u003cbr\u003ec\u003csub\u003e3\u003c/sub\u003e\u0026times;inefficient machinery\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eresources growth rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ed\u003csub\u003e1\u003c/sub\u003e\u0026times;material quality qualified\u0026thinsp;+\u0026thinsp;d\u003csub\u003e2\u003c/sub\u003e\u0026times;timely supply of materials\u0026thinsp;+\u0026thinsp;d\u003csub\u003e3\u003c/sub\u003e\u0026times;mechanical enough\u0026thinsp;+\u0026thinsp;d\u003csub\u003e4\u003c/sub\u003e\u0026times;management technology\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ecognition elimination rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ee\u003csub\u003e1\u003c/sub\u003e\u0026times;personnel cognition\u0026thinsp;+\u0026thinsp;e\u003csub\u003e2\u003c/sub\u003e\u0026times;public cognition+\u003cbr\u003ee\u003csub\u003e3\u003c/sub\u003e\u0026times;management system\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ecognition accumulation rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ef\u003csub\u003e1\u003c/sub\u003e\u0026times;department competition\u0026thinsp;+\u0026thinsp;f\u003csub\u003e2\u003c/sub\u003e\u0026times;manager capability+\u003cbr\u003ef\u003csub\u003e3\u003c/sub\u003e\u0026times;management technology\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003edecisions error rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eg\u003csub\u003e1\u003c/sub\u003e\u0026times;high maintenance cost\u0026thinsp;+\u0026thinsp;g\u003csub\u003e2\u003c/sub\u003e\u0026times;uncertain timing+\u003cbr\u003eg\u003csub\u003e3\u003c/sub\u003e\u0026times;inaccurate route selection\u0026thinsp;+\u0026thinsp;g\u003csub\u003e4\u003c/sub\u003e\u0026times;external condition\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003edecisions efficient rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eh\u003csub\u003e1\u003c/sub\u003e\u0026times;effective measures\u0026thinsp;+\u0026thinsp;h\u003csub\u003e2\u003c/sub\u003e\u0026times;reasonable management mode\u0026thinsp;+\u0026thinsp;h\u003csub\u003e3\u003c/sub\u003e\u0026times;management resource\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eTechnological advancement reduction rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ek\u003csub\u003e1\u003c/sub\u003e\u0026times;unprofessional personnel\u0026thinsp;+\u0026thinsp;k\u003csub\u003e2\u003c/sub\u003e\u0026times;underutilization of information\u0026thinsp;+\u0026thinsp;k\u003csub\u003e3\u003c/sub\u003e\u0026times;management cognition\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003etechnological advancement growth rate\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003em\u003csub\u003e1\u003c/sub\u003e\u0026times;new technology application\u0026thinsp;+\u0026thinsp;m\u003csub\u003e2\u003c/sub\u003e\u0026times;information acquisition\u0026thinsp;+\u0026thinsp;m\u003csub\u003e3\u003c/sub\u003e\u0026times;management resource\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003econditions vary small\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eo\u003csub\u003e1\u003c/sub\u003e\u0026times;climate change\u0026thinsp;+\u0026thinsp;o\u003csub\u003e2\u003c/sub\u003e\u0026times;low government attention\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003econditions vary great\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ep\u003csub\u003e1\u003c/sub\u003e\u0026times;high risk of work\u0026thinsp;+\u0026thinsp;p\u003csub\u003e2\u003c/sub\u003e\u0026times;fierce market competition+\u003cbr\u003ep\u003csub\u003e3\u003c/sub\u003e\u0026times;management decision\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eNote: w\u003csub\u003e1\u003c/sub\u003e, w\u003csub\u003e2\u003c/sub\u003e, w\u003csub\u003e3\u003c/sub\u003e, w\u003csub\u003e4\u003c/sub\u003e, w\u003csub\u003e5\u003c/sub\u003e, w\u003csub\u003e6\u003c/sub\u003e, a\u003csub\u003e1\u003c/sub\u003e, a\u003csub\u003e2\u003c/sub\u003e, a\u003csub\u003e3\u003c/sub\u003e, b\u003csub\u003e1\u003c/sub\u003e, b\u003csub\u003e2\u003c/sub\u003e, c\u003csub\u003e1\u003c/sub\u003e, c\u003csub\u003e2\u003c/sub\u003e, c\u003csub\u003e3\u003c/sub\u003e, d\u003csub\u003e1\u003c/sub\u003e, d\u003csub\u003e2\u003c/sub\u003e, d\u003csub\u003e3\u003c/sub\u003e, e\u003csub\u003e1\u003c/sub\u003e, e\u003csub\u003e2\u003c/sub\u003e, e\u003csub\u003e3\u003c/sub\u003e, f\u003csub\u003e1\u003c/sub\u003e, f\u003csub\u003e2\u003c/sub\u003e, f\u003csub\u003e3\u003c/sub\u003e, g\u003csub\u003e1\u003c/sub\u003e, g\u003csub\u003e2\u003c/sub\u003e, g\u003csub\u003e3\u003c/sub\u003e, h\u003csub\u003e1\u003c/sub\u003e, h\u003csub\u003e2\u003c/sub\u003e, h\u003csub\u003e3\u003c/sub\u003e, h\u003csub\u003e4\u003c/sub\u003e, k\u003csub\u003e1\u003c/sub\u003e, k\u003csub\u003e1\u003c/sub\u003e, k\u003csub\u003e1\u003c/sub\u003e, k\u003csub\u003e1\u003c/sub\u003e, m\u003csub\u003e1\u003c/sub\u003e, m\u003csub\u003e1\u003c/sub\u003e, m\u003csub\u003e1\u003c/sub\u003e, o\u003csub\u003e1\u003c/sub\u003e, o\u003csub\u003e1\u003c/sub\u003e, p\u003csub\u003e1\u003c/sub\u003e, p\u003csub\u003e1\u003c/sub\u003e, p\u003csub\u003e1\u003c/sub\u003e are parameters, and satisfy \u0026sum;a,\u0026sum;b,\u0026sum;c,\u0026sum;d,\u0026sum;e,\u0026sum;f,\u0026sum;g,\u0026sum;h,\u0026sum;k,\u0026sum;m,\u0026sum;o,\u0026sum;p are 1.\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\u003cbr\u003e\n \u003cp\u003eFirstly, by setting the initial value of major factors as the mean of secondary factors, it can be ensured to a certain extent that the initial state of major factors can better synthesize the impact of these secondary factors. Secondly, the initial values of the secondary factors are set as the mean of out-degree and in-degree, which are determined by ten HPM related experts combining professional knowledge and practical experience. Finally, the parameters of secondary factors can be modified and determined by standardized relative centrality, which can eliminate the barriers to comparison between networks of different sizes. Overall, this means that the modification and determination of parameters is more impartial and reasonable, making the model more accurate and closer to reality.\u003c/p\u003e\n \u003cp\u003eAccording to Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, the sum of the relative degree of centrality in the management system, management resource, management cognition, management decision, management technology and external condition are 1.85, 2.24, 1.9, 2.34, 2.42, 1.4. And the sum of relative degree centers of all secondary factors is 12.15, so w\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.15, w\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.19, w\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.16, w\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.19, w\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.2, w\u003csub\u003e6\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.11. Following the above principles, the parameter results are shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e\u003cbr\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEquation parameters.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003eParameter\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eValue\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eParameter\u003cbr\u003e\u003c/th\u003e\n \u003cth align=\"left\"\u003eValue\u003cbr\u003e\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement system\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003epublic cognition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement resource\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.87\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003edepartment competition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement cognition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.37\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003emanager capability\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.8\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement decision\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ehigh maintenance cost\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.8\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emanagement technology\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.03\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003euncertain timing\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.7\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003eexternal condition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.72\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003einaccurate route selection\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003esystem establishment\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eeffective measures\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003esystem perfection\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ereasonable management mode\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003esystem execution\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.8\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eunprofessional personnel\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.8\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003einsufficient funds\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eunderutilization of information\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003epoor earnings\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.4\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003enew technology application\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003einefficient machinery\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003einformation acquisition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003ematerial quality qualified\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003eclimate change\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e0.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003etimely supply of materials\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003elow government attention\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e3.1\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003emechanical enough\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003ehigh risk of work\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003epersonnel cognition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e2.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003efierce market competition\u003cbr\u003e\u003c/td\u003e\n \u003ctd align=\"left\"\u003e1.5\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003ew\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.15,w\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.19,w\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.16,w\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.19,w\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.2,w\u003csub\u003e6\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.11,a\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.34,a\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.36,a\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3,b\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3,b\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.7,c\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.45,c\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.35,c\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.2,d\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.12,d\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.13,d\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.15,d\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.60,e\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.22,e\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.24,e\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.54,f\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.24,f\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3,f\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.46,g\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.24,g\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.15,g\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.17,g\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.44,h\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.19,h\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.25,h\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.56,k\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.23,k\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.2,k\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.57,m\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.25,m\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.32,m\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.43,o\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.23,o\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.77,p\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0,2,p\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.23,p\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.54.\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\u003cbr\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e5.4 Simulation results and analysis\u003c/h2\u003e\n \u003cp\u003eThis research uses Vensim software to simulate the influence law of management effectiveness, setting INITIAL TIME\u0026thinsp;=\u0026thinsp;0, FINAL TIME\u0026thinsp;=\u0026thinsp;12, TIME STEPT\u0026thinsp;=\u0026thinsp;1, and UNTIS for TIME as the Quarter. The simulation results are shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e. In recent years, paying equal attention to construction and maintenance has become the industry orientation for the development of technology in the field of highway maintenance. With the active cooperation and participation of the state, government, and various units, management effectiveness has continued to improve. Thus, the changes in the effectiveness of HPM management show a gradual upward trend, which is consistent with the actual situation.\u003c/p\u003e\n \u003cp\u003eThe change rule of management system on management effectiveness\u003c/p\u003e\n \u003cp\u003eThere is a slight decrease in the initial stage, a gradual rise in the middle stage, a marked decline in the middle and later stages and a rapid rise in the later stage. This can be explained by the inadequate management system and weak execution in the early stage. At the same time, it is not sufficient to mine the data of the management system and apply it to the maintenance decision. In the middle stage, management system gradually becomes applicable through continuous learning and innovation, which can improve effectiveness of HPM management. Over time, management system meets the criteria and reaches a state of saturation. Hence, the effect rule is significantly reduced compared with the middle stage. In the later stage, management effectiveness is strengthened by improving management system and formulating a reasonable HPM post-evaluation mechanism.\u003c/p\u003e\n \u003cp\u003eThe change rule of management resource and management technology on management effectiveness\u003c/p\u003e\n \u003cp\u003eIt shows a slowly increasing trend. As the state actively organizes various preventive maintenance seminars, it promotes the relevant personnel to learn the advanced technology about preventive maintenance and provides funds for special preventive maintenance and standardized research of maintenance materials. Thus, it gradually forms maintenance materials and technologies with independent intellectual property rights. Advanced technology, new materials, and sufficient capital can provide infinite possibilities to improve the management effect.\u003c/p\u003e\n \u003cp\u003eThe change rule of management cognition on management effectiveness\u003c/p\u003e\n \u003cp\u003eThere is no noticeable change in the early stage, but it declines in the middle stage and increases in the later stage. This can be explained that there are still some maintenance personnel with conservative ideas even though the state actively promotes HPM management. In addition, their professional qualities are mixed. For example, they are relatively old and do not understand the economic benefits of preventive maintenance. Therefore, the impact of management cognition is relatively small in the early stage and decreases in the middle stage. With the increasingly prominent benefits of preventive maintenance, its concept and mode have been widely recognized. Besides, the concept of HPM management is popularized by summarizing the experience of pilot cities across the country. Meanwhile, the development of integrated equipment, on-site condition control and appropriate contract management has promoted the healthy development of preventive maintenance. Furthermore, the maintenance management department has gradually formed a relatively intelligent HPM management system, thus improving management effectiveness.\u003c/p\u003e\n \u003cp\u003eThe change rule of management decision on management effectiveness\u003c/p\u003e\n \u003cp\u003eThe management effectiveness increases in the early stage, decline slowly in the middle stage, and increases in the later stage. This is because the rapid development of information, data, and intelligence determines the scientific nature of maintenance time. Moreover, carrying out preventive maintenance in time can promote management effectiveness. In the middle stage, the adverse effects appear due to high maintenance costs, shortage of funds, and backward management modes. In the later stage, with the development of high-speed detection technology for pavement performance and the establishment of a digital management platform, the scientific and intelligent level of maintenance management has been improved. Thus, effectiveness of HPM management is promoted.\u003c/p\u003e\n \u003cp\u003eThe change rule of external condition on management effectiveness\u003c/p\u003e\n \u003cp\u003eThere is a decline initially and a slow rise after the middle stage. This is due to the relatively weak maintenance technology investment mechanism and market operation mechanism in the early stage, which constrains the improvement of management effectiveness. In the middle stage, the concept of preventive maintenance is widely accepted, leading to market competition and the rationality of pavement structure design. The interaction of great attention and information ensures the safety of maintenance personnel, increases the frequency of pavement inspections, and promotes management effectiveness.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"6. Discussions","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Implications\u003c/h2\u003e \u003cp\u003eIn this paper, a hybrid EFA-SNA-SD approach is used to systematically integrate the major management factors of HPM, distinguish their important degree, and analyze their influence laws. The findings enriched and broadened the development of preventive maintenance concepts, contributing to the formation of a sustainable transportation system.\u003c/p\u003e \u003cp\u003eThe study identified 26 key HPM management factors, which were categorized into six areas. This has improved our ability to interpret maintenance problems and enables effective action to be taken in response to HPM management issues. By integrating these factors into preventive maintenance management, we can improve the overall quality of highway maintenance, create a safe and efficient traffic system, and meet the future high-demand, high-efficiency, and high-quality highway services for sustainable development.\u003c/p\u003e \u003cp\u003eThe study found that HPM management factors were hierarchical and mutually constraining. Therefore, this paper distinguished them into key, hub, and non-key factors. This facilitated preventive maintenance work and provided a direction for efficient improvement of preventive maintenance management effectiveness. Key management factors in daily HPM management include a suitable management mode, adequate preparation, and reasonable financial support. However, limitations in maintenance technology, equipment, information, and changing social industry environments can limit the choice of the best management model, the speed of obtaining the best maintenance information, and the reasonable allocation of funds. Therefore, appropriate maintenance plans need to be developed to achieve sustainable development of highways. Multi-level implementation measures are key to improving the effectiveness of HPM management. By constructing the SD model, this paper found that the influence law of different management factors on the effectiveness of HPM management varied and generally showed an upward trend. Based on the findings, we propose the following suggestions. First, we should follow the principle of adapting measures to local conditions and ensuring consistency between power and responsibility to gradually improve the HPM management system, especially the strengthening of the operation mechanism. Second, the government should increase the investment in preventive maintenance funds and allocate them reasonably, while also providing regular technical guidance to maintenance personnel to improve their professional ability. Third, we should actively promote the concept and long-term benefits of preventive maintenance management and establish the correct awareness of preventive maintenance management. Finally, we recommend collecting and integrating highway data and using GIS to improve the information and intelligence of HPM. These measures will provide strong theoretical support and technical guarantee for the implementation of preventive maintenance management.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Limitations and recommendations\u003c/h2\u003e \u003cp\u003eIn this paper, we have presented a hybrid approach of EFA-SNA-SD to integrate and analyze the major management factors of HPM. However, there are some limitations in our research process that need to be addressed.\u003c/p\u003e \u003cp\u003eFirstly, as the development of HPM management continues, the major management factors may change over time. Therefore, future research can focus on the development trend of preventive maintenance and adjust the management factors accordingly. Secondly, our data is limited and the sample size is not comprehensive enough to represent all regions. Future research could benefit from expanding the sample size and collecting data from different regions. We suggest establishing long-term performance observation stations for pavement performance across the country to provide a more comprehensive and accurate scientific basis for preventive maintenance decisions. Finally, we acknowledge that our methodology can be further improved. We recommend considering programming software such as R language and Matlab for clustering and visual analysis of management factors, which can achieve a combination of computer technology and integration of HPM management concepts.\u003c/p\u003e \u003cp\u003eOverall, despite these limitations, this study has contributed to the understanding of HPM management and provided theoretical and practical references for enhancing the benefits of preventive maintenance management to form a sustainable transport system. We believe that further research in this area can lead to significant improvements in the effectiveness of HPM management.\u003c/p\u003e \u003c/div\u003e"},{"header":"7. Conclusions","content":"\u003cp\u003eIn conclusion, this research aimed to identify the major HPM management factors and their dynamic effects on the effectiveness of HPM management with a hybrid EFA-SNA-SD approach. The research identified 26 major HPM management factors that are categorized into six dimensions: management system, management resources, management cognition, management decision, management technology, and external conditions. Information acquisition, system perfection, system planning, etc. are identified as key factors that are critical to the effectiveness of HPM management. System execution, manager capability, organizational support, etc. are identified as hub factors that significantly influence HPM management effectiveness. Route selection, machinery allocation, pavement structure, etc. are identified as non-key factors that have less impact on the effectiveness of HPM management. The SD model developed in this study demonstrates that different management factors have varying effects on the effectiveness of HPM management. The results indicate that effective management strategies require a holistic approach that considers all dimensions of HPM management. Furthermore, the model shows that the effectiveness of HPM management can be improved through continuous monitoring and adjustment of management factors.\u003c/p\u003e \u003cp\u003eThe findings of this research have significant implications for the sustainable development of highways. The results can guide policymakers and highway managers in developing effective HPM management strategies that enhance the durability, safety, and cleaner production of highway infrastructure, thus contributing to a more sustainable transportation system.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no financial or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Key Laboratory of Highway Engineering of Ministry of Education (Changsha University of Science \u0026amp; Technology) (kfj220201); Ministry of Education in the Humanities and Social Sciences of China (No. 23YJC630249).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data is provided within the manuscript or supplementary information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmed, S., P. 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Baldo (2022) Benefit evaluation of preventive maintenance of highway bridges based on fuzzy neural network. \u003cem\u003eAdvances in Civil Engineering,\u003c/em\u003e 2022\u003cstrong\u003e,\u003c/strong\u003e 1-11.\u003c/li\u003e\n\u003cli\u003eZuluaga, C. M., A. Albert \u0026amp; P. Arroyo (2018) Protecting bridge maintenance workers from falls: evaluation and selection of compatible fall protection supplementary devices. \u003cem\u003eJournal of Construction Engineering and Management,\u003c/em\u003e 144.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HPM, EFA-SNA-SD method, management factors, influence mechanism, sustainable transportation system","lastPublishedDoi":"10.21203/rs.3.rs-4076043/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4076043/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHighway preventive maintenance (HPM) can help reduce the negative environmental impacts of transportation infrastructure by prolonging the life of existing infrastructure, reducing the need for costly and resource-intensive repairs and reconstruction, and improving the energy efficiency of pavement infrastructure. However, many transportation agencies struggle with low HPM management capacity. This paper aims to enhance HPM management effectiveness by identifying and evaluating the major management factors that impact HPM. The study conducted a literature review and exploratory factor analysis (EFA) to identify the key HPM management factors. Social network analysis (SNA) was used to assess the importance of these factors, and a system dynamics (SD) model was developed to explore their influence laws. The research identified six dimensions of HPM management, including management system, management resource, management cognition, management decision, management technology, and external condition, along with 26 major management factors. The study found that key factors had a positive impact on HPM management, while hub factors were also critical. The study provides a comprehensive framework for identifying and evaluating the management factors that impact HPM, which can guide managers to develop effective HPM plans, improve the overall quality of highway maintenance, and form a sustainable transportation system.\u003c/p\u003e","manuscriptTitle":"A Hybrid Approach to Investigating Major Management Factors for Effective Highway Preventive Maintenance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-27 13:46:07","doi":"10.21203/rs.3.rs-4076043/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-30T05:09:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-22T15:09:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197680418075054427680865361642395381985","date":"2024-08-12T13:06:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-24T07:40:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89269805652119111662096964281473309033","date":"2024-06-17T04:36:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229420307230490949436612656567085471028","date":"2024-06-11T16:16:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-31T14:08:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-26T10:24:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-22T14:49:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-22T14:46:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-03-11T14:51:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6b2f94e1-557e-4674-b701-c37629b6392f","owner":[],"postedDate":"March 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-28T16:05:59+00:00","versionOfRecord":{"articleIdentity":"rs-4076043","link":"https://doi.org/10.1038/s41598-024-76692-4","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-26 15:58:23","publishedOnDateReadable":"October 26th, 2024"},"versionCreatedAt":"2024-03-27 13:46:07","video":"","vorDoi":"10.1038/s41598-024-76692-4","vorDoiUrl":"https://doi.org/10.1038/s41598-024-76692-4","workflowStages":[]},"version":"v1","identity":"rs-4076043","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4076043","identity":"rs-4076043","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}