Competitive tendering, ownership and cost efficiency in road maintenance services in Sweden: A panel data analysis

Yarmukhamedov, Sherzod; Smith, Andrew; Thiebaud, Jean-Christophe

doi:10.1016/j.tra.2020.03.004

Cited by 13 publications

(7 citation statements)

References 27 publications

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“…The transportation distance (b & c) of the overburden material starting from the loading point to the disposal also affects the age of the tire [28]. The operator's habits (f -k) in driving when the conveyance is loaded and the means of transport are empty as well as the condition of the mine road and front-loading area also affect the TKPH value [6], [8], [29] [30]. The study's results in Table 4 that the smallest error value is in the Multiple regression Model 3 statistic with a MAD value of 69.16 and a MAPE value of 66.07 with an R-square (R²) value of 52.41%.…”

Section: Resultsmentioning

confidence: 99%

Tonne Kilometre Per Hour (TKPH) Prediction for Lifetime Tire Estimate Using Statistical Analysis: A Case Study at Coal Mine

Sari¹,

Seto²

2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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To expedite mining production activities, the condition of the transportation equipment of fuel and spare parts must be ready because the loss of time due to refueling and waiting for spare parts can reduce the Physical Availability value of the dump truck. In this study, the type of tire used as the research object is a tire measuring 33.00-51. The initial identification of tire conditions showed that the Hours meter average was smaller than the Key Performance Indicator (KPI) Hours meter, which was 2719 HM. The type of tire damage that dominates is Sidewall Separation, with a damage percentage of 54%. This study aims to predict the value of TKPH with ten independent variables that exist in the activity of the transportation cycle. The method used to predict is the Multiple Regression and ARIMA statistical methods. From the results of Multiple Regression using the SPSS application, three models are produced, each with different independent variables. As for ARIMA seen from the choleogram of the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF), the number of lags = 1, so ARIMA models that can be applied may be (1,0,1) and (1,1,0). The results of the study prove that the prediction model that is close to this is the Multiple Regression Model 3 where the Mean Absolute Deviation (MAD) value is 69.16, the Mean Absolute Prediction Error (MAPE) is 66.07, and the R-square value is 52.41%.

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Section: Resultsmentioning

confidence: 99%

Tonne Kilometre Per Hour (TKPH) Prediction for Lifetime Tire Estimate Using Statistical Analysis: A Case Study at Coal Mine

Sari¹,

Seto²

2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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“…So that if there is damage to the construction that is faster than the planned life, it will be the responsibility of the service user. The above occurs because the form of a work contract between service users and service providers is a binding work contract in a short period [10]. Some types of contracts in Indonesia can be divided into four parts.…”

Section: Literature Reviewmentioning

confidence: 99%

Stakeholder Satisfaction in Long Segment Maintenance Contract: Application to a Hills-Road Network

Rifai,

Isradi,

Prasetijo

et al. 2023

ijmst

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Hills-road network has an essential role in maintaining the flow of transportation and logistics in mountainous areas. Implementing the Long Segment Maintenance Contract (LSMC) is one step in producing better road services and performance. The success rate of PMS implementation can be seen from the road performance and the level of satisfaction of stakeholders consisting of owners, implementers, supervision consultants, and users. This research was conducted to determine stakeholders' level of interest and satisfaction in the implementation of LSMC in the mountain road network. The methods used are Importance Performance Analysis and Customer Satisfaction Index. As a case study, the hills road network in Cirebon-Kuningan-Ciamis, West Java, Indonesia, was chosen along 103.08 km. Questionnaires were distributed to all stakeholders in the implementation of LSCM in these sections. Data analysis was carried out on questionnaires obtained from the owner as many as three respondents, contractors four respondents, supervised seven respondents, and road users as many as 100 respondents. The results showed that, in general, the level of stakeholder importance was relatively high, with an average of 4.22, an average performance level of 3.70, and a CSI value of 86.9.% or very satisfactory. In comparison, road users' on-road performance is relatively high, with an average of 4.44 with, an average level of performance of 4.41, and a CSI value of 86.83%, or very satisfactory. Furthermore, the importance of road users' on-road response time is relatively high, with an average of 4.42, an average performance level of 4.41, and a CSI value of 86.09%, or very satisfactory. Attributes that greatly influence the opinion of road users and stakeholders on LSCM in the Hill Road Network are related to the control of runoff water and routine road maintenance.

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“…The significance of transportation, particularly in the context of road maintenance and construction, cannot be overstated [1]. Despite the evident advantages of automation, this industry has been slow to adopt modernized tools and procedures [2].…”

Section: Introductionmentioning

confidence: 99%

Reinforcement Learning to Calculate Routes for Simulated Robot Safety Cones

Murio,

Balado,

Arias

2023

The 4th International Electronic Conference on Applied Sciences

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Competitive tendering, ownership and cost efficiency in road maintenance services in Sweden: A panel data analysis

Abstract: This is a repository copy of Competitive tendering, ownership and cost efficiency in road maintenance services in Sweden: A panel data analysis.

Cited by 13 publications

References 27 publications

Tonne Kilometre Per Hour (TKPH) Prediction for Lifetime Tire Estimate Using Statistical Analysis: A Case Study at Coal Mine

Tonne Kilometre Per Hour (TKPH) Prediction for Lifetime Tire Estimate Using Statistical Analysis: A Case Study at Coal Mine

Stakeholder Satisfaction in Long Segment Maintenance Contract: Application to a Hills-Road Network

Reinforcement Learning to Calculate Routes for Simulated Robot Safety Cones

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