International cargo transportation is majorly dependent on marine transport, which moves 80% of the international cargo. With the increase in vessel size and the same yard area available for container transportation, it is important to study the processes and understand the efficiency of the container operations process. This research paper aims to review the import container transportation process and understand the process cycle efficiency through lean six sigma concepts. The process is evaluated from the operations process perspective and documentation process at one of the ports of India. The research has been designed by conducting an industry expert review on the process of container transportation from vessel berthing to gate out for import containers, utilising lean six sigma principles such as value stream mapping (VSM) and process cycle efficiency. The results have contributed to the existing knowledge in identifying the waste in the container handling process and demonstrated the inefficiency in the system from the perspective of waiting time of containers due to customs examination, scanning, and inter-terminal handling and movement. The process cycle efficiency of 40% is calculated by analysing the detailed time of handling containers from vessel berthing to gate out. A new future value stream mapping is proposed considering the process cycle efficiency. Future studies will focus on studying this process for export containers and benchmarking the results with the top-performing ocean ports globally.
This research papers aims to evaluate the impact of two major institutional indexes logistics performance index (LPI) and ease of doing business (EODB) along with logistics cost (LC) on the economic development (Gross domestic product – GDP per capita). The variables selected for the research study provides the comprehensive impact and forms the core of the economy for any country. Top seven economies of the world (China, France, Germany, India, Japan, United Kingdom and USA) along with Czech Republic, Singapore and Slovenia have been selected for this analysis. Mid-sized Economies of Czech Republic, Singapore, Slovenia have been selected for the regional balance of Asia and Europe and for cooperative results. A preliminary analysis of Pearson correlation analysis and detailed fuzzy qualitative comparative analysis have been opted for the study. The results illustrate that LPI is the core component for displaying the positive results on economic development. LC and EODB have displayed mixed results and will be studied in future research for identifying their impact on economic development. Future research will incorporate indexes such as global competitive index, innovation index for the evaluation of the combined impact on economic development.
Logistics is an important sector that determines a country’s economic strategy while attaining higher impetus in terms of globalization and competitiveness. Infrastructure along with trade friendly government policies are the key important parameters for a competitive logistics sector. One such method to evaluate competency is the logistics performance index (LPI) by the World Bank. This index evaluates the logistics performance of the economies of the world and rank them on the basis of six parameters (customs, infrastructure, timeliness, tracking & tracing, logistics competence and international shipments). This research study illustrates the impact of logistics costs (LC) and logistics competency parameters (LPI) on the economic development. The fuzzy set qualitative comparative analysis (fsQCA) methodology is applied to identify the causal configuration relations for higher values of economic development (GDP per capita). Eight major economies across Asia (China, India, Japan, Singapore), Europe (Germany, France), the UK and the USA have been studied for the analysis. The Czech Republic and Slovenia are also included to the list of countries to have a perspective of mid-sized economies. These mid-size economies are landlocked countries (Czech Republic) and a smaller port sector (Slovenia) for logistics. The results indicate two configurations of LPI and LC that lead to higher values of GDP per capita. The major contribution to the existing literature is in identifying the influence of LPI index parameters along with LC on the economic development. The associated results illustrate that logistics competence, infrastructure and tracking & tracing of LPI index are identified as the core parameters, resulting in the higher values of GDP per capita. The results offer various insights into future area of research for evaluating new parameters such a LC to be inducted in LPI for evaluating logistics performance.
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