Explore the vast range of titles available.

The aim of the study is the further development of theoretical principles, coverage and justification of global approaches to statistical assessment of effectiveness of green logistics under the current conditions of transformation of the global market for transport and logistics services. It is determined that green logistics, which complies with national or international environmental regulations, can enhance the competitiveness of exporters and increase exports. At the same time, environmental standards are the most important factors affecting the practical implementation of green logistics methods. The Logistics Efficiency Index is significantly related to environmental indicators. However, currently, there seems to be no ideal indicator for assessing effectiveness of green logistics. Therefore, in order to provide a comprehensive assessment of logistics performance of individual countries and environmental performance of their transport sector, for conducting a quantitative analysis, the Environmental Logistics Performance Index (ELPI), which is built using the international Logistics Index (LPI) dataset, CO2 emission from the transport sector and its oil consumption, should be used. Improvement of indicators for assessing effectiveness of green logistics contributes to enhancing factors that affect international competitiveness, in particular, upgrading infrastructure, increasing quality of logistics services, and intensifying the use of modern information technologies to improve efficiency of customs and logistics tracking capabilities.

Purpose - This paper aims to examine whether some countries achieve logistics efficiency at the cost of undermining environmental quality. In so doing, a hybrid index, the green logistics performance index (GLPI) combining both the LPI and the environmental performance index (EPI), is constructed.Design methodology approach - Being a macro analysis measuring the green supply chain efficiency of a country, this paper utilizes the secondary data compiled by the World Bank and the World Economic Forum. A series of simple regression analyses were conducted in order to find out the varying degrees of association between the LPI, the EPI, the GLPI and the national income level.Findings - As active logistics activities can have an impact on carbon footprints such as greenhouse gas emissions, it was found that some countries chose to increase their income level at the expense of the environment degradation. Consequently, the GLPI is suggested as a good indicator of a country's green logistics efficiency, showing what impact the country's logistics competitiveness has on its environment.Originality value - This paper is the first attempt to measure the efficiency of the supply chain of a country from a green perspective by proposing the GLPI combining the LPI and the EPI. It is also the first literature in the supply chain management academia to utilize both the LPI and the EPI.

PurposeThe purpose of this study is to explore the potential for the development of a country logistics performance assessment approach based upon textual big data analytics.Design/methodology/approachThe study employs design science principles. Data were collected using the Global Perspectives text corpus that describes the logistics systems of 20 countries from 2006–2014. The extracted texts were processed and analysed using text analytic techniques, and domain experts were employed for training and developing the approach.FindingsThe developed approach is able to generate results in the form of logistics performance assessments. It contributes towards the development of more informed weights of the different country logistics performance categories. That said, a larger text corpus and iterative classifier training is required to produce a more robust approach for benchmarking and ranking.Practical implicationsWhen successfully developed and implemented, the developed approach can be used by managers and government bodies, such as the World Bank and its stakeholders, to complement the Logistics Performance Index (LPI).Originality/valueA new and unconventional approach for logistics system performance assessment is explored. A new potential for textual big data analytic applications in supply chain management is demonstrated. A contribution to performance management in operations and supply chain management is made by demonstrating how domain-specific text corpora can be transformed into an important source of performance information.

In a globalized economy, effective management of international logistics chains is a key factor for maintaining competitiveness and successful trade. The present study updates the methodology for evaluating logistics chains based on the Logistics Performance Index (LPI) data developed by the World Bank, focusing on the Visegrad Four countries (Czech Republic, Poland, Slovakia and Hungary). The aim of the new methodology is to identify trends and changes in the field of modernization of transport infrastructure, efficiency of customs processes and implementation of digital technologies, including the application of Industry 4.0 solutions. In addition, the study also addresses the impact of environmental measures, such as the European Green Deal, on reducing the carbon footprint and supporting the sustainable development of supply chains. The results obtained indicate that investments in modernization technologies and digitalization of logistics services are essential for increasing efficiency and competitiveness logistics subjects in the international market. The proposed recommendations aim to strategically improve infrastructure and digital capacities, which has the potential to contribute to the sustainable development of logistics chains in a globalized economy.

PurposeThe Logistics Performance Index (LPI), published by the World Bank, is a key measure of national-level logistics performance. It comprises six indicators: customs, infrastructure, international shipments, service quality, timeliness, and tracking and tracing. The objective of this study is to explore temporal dependencies among the six LPI indicators while operationalizing the World Bank’s LPI framework in terms of mapping the input indicators (customs, infrastructure, and service quality) to the outcome indicators (international shipments representing cost, timeliness, and tracking and tracing representing reliability).Design/methodology/approachA Bayesian Belief Network (BBN)-based methodology was adopted to effectively map temporal dependencies among variables in a probabilistic network setting. Using forward and backward propagation features of BBN inferencing, critical variables were also identified. A BBN model was developed using the World Bank’s LPI datasets for 2010, 2012, 2014, 2016, 2018, and 2023, covering the six LPI indicators for 118 countries.FindingsThe prediction accuracy of the model is 88.1%. Strong dependencies are found across the six LPI indicators over time. The forward propagation analysis of the model reveals that “logistics competence and quality” is the most critical input indicator that can influence all three outcome indicators over time. The backward propagation analysis indicates that “customs” is the most critical indicator for improving the performance on the “international shipments” indicator, whereas “logistics competence and quality” can significantly improve the performance on the “timeliness” and “tracking and tracing” indicators. The sensitivity analysis of the model reveals that “logistics competence and quality” and “infrastructure” are the key indicators that can influence the results across the three outcome indicators. These findings provide useful insights to researchers regarding the importance of exploring the temporal modeling of dependencies among the LPI indicators. Moreover, policymakers can use these findings to help their countries target specific input indicators to improve country-level logistics performance.Originality/valueThis paper contributes to the literature on logistics management by exploring the temporal dependencies among the six LPI indicators for 118 countries over the last 14 years. Moreover, this paper proposes and operationalizes a data-driven BBN modeling approach in this unique context.

PurposeLogistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of intended targets by increasing the cost of doing business. Also, it is difficult to improve the efficiency of a country’s logistics operations without a metric for evaluating and understanding logistics capabilities and efficiency. Therefore, the present study has developed In-country Logistics Performance Index (ILP Index) to propose a benchmarking tool to measure the in-country logistics competitiveness, particularly in the setting of emerging economies, i.e. India.Design/methodology/approachThis study has developed a unified index using principal component analysis and quintile approach. In addition, the proposed index relies on several dimensions that are developed and illustrated using quantitative secondary panel data.FindingsThe findings of this study reveal that the quality of infrastructure, economy, and telecommunications are the three most important dimensions that may significantly support the growth of the transportation and logistics sector. The results reveal that Gujarat, Tamil Nadu, and Maharashtra are the top performers whereas, Bihar, Jharkhand, and Jammu and Kashmir scores the least due to the insufficient logistics infrastructure as compared to other Indian states.Originality/valueGiven the extensive focus on international-level logistics index (like World Bank’s LPI) in the existing literature, this study intends to develop in-country logistics index to evaluate the logistics capabilities at the regional and state level. In addition, unlike prior studies, this study utilizes quantitative secondary data to eliminate cognitive and opinion bias. Moreover, this benchmarking tool would assist decision-makers in idealizing standard practices toward sustainable logistics operations. Additionally, the ILP index could serve the international investors in crucial decision-making, as it provides valuable insights into a country’s logistics readiness, influencing their investment choices and trade preferences. Finally, the proposed approach is adaptable to measuring the overall performance of any other industry/economy.

The Logistics Performance Index (LPI) performed by the World Bank is an indicator of the logistics environment quality of a country in which logistics operators act. The LPI is an interactive tool designed to help countries identify challenges, innovative solutions, and opportunities they face in their work in the field of trade and logistics. The aim of this paper is to conduct a comparative analysis and ranking of the LPI of the countries in the Western Balkans (Bosnia and Herzegovina, North Macedonia, Albania, Serbia and Montenegro), calculated by the World Bank for 2018, using an integrated Criteria Importance Through Intercriteria Correlation (CRITIC)-Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) model and thus show the real picture of the logistics environment. In order to determine the performance of countries and show the overall logistics performance, six key dimensions are used: customs, infrastructure, international transport, logistics capability, tracking and tracing of goods and shipment delivery within scheduled or expected times. Using the CRITIC method, the weight values of the previously mentioned six criteria were calculated, whereby the criterion related to shipment delivery within scheduled times was singled out as the most significant criterion. Then, by applying the MARCOS method, the countries of the Western Balkans were ranked on the basis of the six defined criteria. Based on the results obtained, the best-ranked country is Serbia. The analysis of the sensitivity of the results to changes in the significance of the criteria does not show significant changes in the ranking.

This paper deals with a performance analysis and classification of EU member states based on their Logistics Performance Index (LPI) published by the World Bank. Our study covers 2010 to 2023 with 117 countries evaluated. The goal is to analyse, classify and compare countries based on their LPI scores using cluster analysis with parametric and non-parametric measures. Parametric measures include the mean LPI score, average growth, and linear trend slope. The focus is especially on the differences between EU member countries. For non-parametric measures, we used the Malmquist Productivity Index (MPI). This novel approach uses clustering based on the’ long-term development of LPI scores and MPI. The classification highlights three distinct clusters: “Struggling Performers,” “Improvers with Moderate Performance,” and “Rapid Advancers.” The paper confirms that older EU members have mostly stable logistics, but are less influenced by recent growth. It also shows that sustained improvement over time is a key driver of better logistics performance in the newer EU members. In addition, it was found that countries still in the catch-up phase tend to have lower current performance.

This article constructs an environmental logistics performance index (ELPI) for assessing the overall performance in green transportation and logistics practices of 112 countries. The index is measured by logistics performance index (LPI), CO2 emissions and oil consumption from the transport sector, using a range-adjusted measure (RAM) of the data envelopment analysis (DEA). ELPI effectively reflects the tradeoff between logistics efficiency and environmental protection in transportation. This article analyzes the impact of income and region on ELPI scores and discusses those countries’ reduction potential in oil consumption intensity and carbon intensity. The main finding of the research work is that ELPI is strongly correlated with LPI, and countries with high performance in LPI generally perform well in ELPI. Similar to the characteristics of LPI, ELPI is also closely related to income and region. During our study period, high income countries performed best, while Sub-Saharan Africa countries performed worst. However, some exceptions such as Venezuela, RB and Benin, indicate that the level of development of logistics performance and green transportation can outperform or lag behind their income or region group peers.

There is widespread evidence that efficiency of logistics systems is a significant determinant of bilateral trade, but the magnitude of the effect may vary according to economic and geographical characteristics. An important aspect concerning the impact of logistics performance on trade volumes is the income level. This paper presents the findings of a gravity model, which is empirically tested to assess the extent to which logistics performance constitutes a facilitator to international trade. We compare the relative impact of various logistics performance dimensions on trade, and explore the differences over country income levels. Our research differs from previous studies in adopting an income-level approach, with an analysis of the impact of various logistics performance dimensions. We observed that the regulatory or trade facilitation environment could have divergent effects depending on the level of per capita income. Particularly, low-income economies realize highest benefits of their logistics excellence. For low- and lower-middle-income economies, logistics excellence increases exports more than imports. On the contrary, imports of upper-middle- and high-income economies tend to benefit more from better logistics performance than their exports. Accordingly, collaborative acts to improve logistics performance of partner countries may have a higher impact on the exports of an upper-middle-income country than improving only the exporter’s performance.