This chapter presents the literature review about the logistics performance index, identification to the factors which influencing to logistics performance, the spatial correlation, and the research hypothesis and design.
2.1 The Logistics Performance Index
The Logistics Performance Index and its indicators have been constructed from information gathered in a worldwide survey of the companies responsible for moving goods and facilitating trade around the world, the multinational freight forwarders and the main express carriers. It relies on the experience and knowledge of professionals. Their views matter: they have a direct impact on the choice of shipping routes and gateways and can influence the firms’ decisions about the location of production, choice of suppliers, and selection of target markets.
The indicators summarize the performance of countries in seven areas that capture the current logistics environment. They range from traditional areas such as customs procedures, logistics costs (such as freight rates), and infrastructure quality to new areas such as the ability to track and trace shipments, timeliness in reaching a destination, and the competence of the domestic logistics industry. None of these areas alone can ensure good logistics performance. The selection of these areas is based on the latest theoretical and empirical research, and on extensive interviews with logistics professionals involved in inter-national freight logistics. The LPI synthesizes this information in a composite index to allow for comparisons.
The LPI and its indicators are given on a numerical scale, from 1 (worst) to 5 (best).
This scale can also be used to interpret performance outcomes measures. For example, the analysis based on the additional country information gathered in the survey indicates that, on average, having an LPI lower by one point (say, 2.5 rather than 3.5) implies six additional days for getting imports from the port to a firm’s warehouse and three additional days for exports. It also implies that a shipment is five times more likely to be subject to a physical inspection at entry.
To provide a more complete picture of the key factors determining logistics performance, the Logistics Performance Survey asked logistics professionals about the institutions and processes supporting logistics operations in the countries in which they
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are based. It asked them to assess critical attributes of the supply chain, including timeliness of deliveries, quality of transport and IT infrastructure, efficiency of border clearance processes, competence of the local logistics industry, and domestic costs of services as well as provide time and cost data.
Based on the world bank report on LPI survey (2012) the indcator questions in the logistics performance survey delved into the quality of infrastructure, the competence of private and public logistics service providers, the roles of customs and other border agencies, such governance issues as corruption and transparency, and the reliability of the trading system and supply chains. Reliability (measured by the predictability of the clearance process and the timely delivery of shipments) emerged as a key concern, with the difference in satisfaction between the high-and low-performing countries much larger than for any other question in the survey.
Quality of infrastructure
The Quality of Port Infrastructure measures business executives' perception of their country's port facilities.
Competence of private and public logistics service providers
This indicator measures the performance of the supply chain depends on the quality of services delivered by the private sector through customs brokers and road transport operators and on the competence and diligence of public agencies in charge of border procedures.
Customs and other border agencies
Customs performance tends to be better than that of other border agencies; on average, customs clearance accounts for a third of import time. This underscores the importance of addressing the coordination of border agencies, especially in countries that already have attained good customs clearance.
Corruption and transparency
The transparency of government procurement, the security of property from theft and looting, macroeconomic conditions, and the underlying strength of institutions are critical factors in determining logistics performance.
Reliability of the trading system and supply chain
The reliability of the trading system and supply chain is the most important aspect of logistics performance. A high degree of uncertainty means that operators have
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to adopt costly hedging strategies, such as maintaining relatively high inventory levels.
The detail information about the indicator questions in the logistics performance survey can be seen in Appendix 1.
2.2 Factors Identification
The previous studies have been conducted to analyze the factors that have relation to the logistics performance. Some factors such as the economic, social and government regulation, and infrastructure factors are evidently have relation to logistics performance.
The customs, cost and time to export are some factors that influencing to the logistics performance in regard to economic. Meanwhile, in terms of social and government regulation, political issues and quality of human resources have the relation to logistics performance. In terms of infrastructure, the quality of transportation infrastructure has the relation to the logistics performance. All factors and their reference in details are shown in Table 1.
Table 1. The factors affect to LPI from literature study
Factors Possible set of Indicators Reference Economic - GDP per capita
Infrastructure - Road density - Road fatality
- Fixed broadband internet subscriber
Goh and Ang (2000),
2.3 Spatial Correlation
There are some studies analyzed the factors affecting logistics performance by considering spatial effect. The gravity model is the most commonly model which used in analyzing the factors that relating to the logistics performance by considering spatial effect. In addition, some studies utilized the geographically weighted regression. Table 2 presents the resume of previous studies which analyze the factor affecting to logistics performance by considering spatial effect:
Table 2. The studies analyze the factor affecting to LPI by considering spatial effect
Reference Objective Parameter Methodology
Limao and
Based on literature review that gravity model analysis and geographically weighted regression (GWR) were utilized to analyze the factor which affecting logistics performance by considering spatial effect. Both models are use distance in defining spatial terms. This research propose to use spatial regression analysis instead the gravity model and geographically weighted regression.
Unlike the gravity model and geographically weighted regression (GWR), which is spatial term (the neighborhood design) defined based on distance, the spatial regression analysis allow to define the neighborhood design based on other criteria instead of distance. The neighborhood design in this research defined based on total trading value, therefore the spatial regression analysis is utilized. The motivation of using trading value instead of geographical distance in defining neighborhood design is due to the fact that logistics performance have strong correlation with trading activity. The trading activity can become a stimulus for a country to improve their logistics performance. In fact, trading activity is not have linear correlation to the geographical distance, a country might have gretaer trading value with country that have further distance.
2.4 Research Hypothesis and Design
This research hypothesizes that the logistics performances of a country’s trading partners may plays a large role in affecting the country’s logistics performance from a global supply chain perspective. The research was conducted by collecting the LPI data and factors that influence it and an Indonesia’s trading value data with 41 trading partner countries. All the data were analyzed using spatial regression model to test the LPI spatial correlation. The LPI was selected as dependent variable because it provides snapshots of the supply chain performance of a country and widely accepted by almost all countries around the world.
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