Efficiency Measurement in International Transport Systems

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Table of Contents

Introduction
Problem Definition
Research Objectives
Research Significance and Contribution
Research Questions
Research Methods
Structure of the Project Report
Time Plan for Minor and Major Activities and a Gantt Chart
Reference List

Introduction

To a considerable extent, the level of organizational performance in international transport systems (ITS) is defined by the efficacy of the transport systems themselves (Bray, Caggiani, & Ottomanelli, 2015). The specified phenomenon is especially evident in the context of the global market, where the well-coordinated actions of the participants allow for the proper functioning of the supply chain and, therefore, the timely and successful delivery of the necessary raw materials, components, and products to the target destinations.

Improving international transport systems is a crucial step towards a gradual positive change in the state economy (e.g., the creation of premises for consistent economic growth). The use of an improved data management system that will allow for a rapid and more efficient transfer of essential information from one participant in the global supply chain management process to another will create the premise for developing an improved transportation system. The change will become possible by offering tools that are useful for addressing the emergent issues immediately, thus preventing a range of obstacles from blocking companies’ way to a successful transportation process.

Problem Definition

The emphasis on the significance of ITS development is obviously a welcome change of pace in the contemporary business and economic environment. Strategies that are currently used to manage ITS leave much to be desired, mainly because of the lack of opportunities for evaluating the efficacy of these systems. In turn, the tools that are currently used to measure the efficacy of international transport systems lack accuracy, which can lead to a significant drop in the quality of performance.

A closer look at the challenges that it has been experiencing will reveal that a significant number of these problems may result from the inappropriate use of the available data and the failure to utilize an efficient information management framework to prevent accidents and other issues from occurring (Jurjevic, Dundovic & Hess 2016).

It should be noted, however, that several approaches aiming at the improvement of the current ITS exist, with Data Envelopment Analysis (DEA) being key. The DEA framework creates an environment in which a detailed and all-embracing data analysis becomes a possibility: “DEA evaluates the efficiency of each DMU relative to an estimated production possibility frontier determined by all DMUs. The advantage of using DEA is that it does not require any assumption on the shape of the frontier surface, and it makes no assumptions concerning the internal operations of a DMU” (Bray et al., 2015, p. 187).

To enhance the data management process, DEA suggests incorporating the analysis of the fuzzy variables into the process (Mohideen, Devi, & Durga 2016). According to the existing interpretation of the subject matter, fuzzy numbers can be defined in the following way: “Any fuzzy subset where x takes its number on the real line R and ” (Xu & Zhou 2011, p. 14). Therefore, a comprehensive information management strategy based on the use of fuzzy numbers and variables would significantly improve the current situation.

The use of Intelligent Transport Systems (InTS), in turn, will allow for a notable improvement in safety levels (Janusova & Cicmancova 2016). By design, the tools help in identifying the transportation routes that will allow for the most efficient and fastest transfer to the destination point. Critical infrastructure protection strategies, which will be aimed at protecting InTS, will help prevent road accidents and will also help manage traffic congestion and similar issues that may occur during the transportation process (Janusova & Cicmancova 2016). The identified model should be viewed as an important tool for managing the needs associated with ITS improvement since it provides a comprehensive model that incorporates every possible factor affecting the transportation process (see Appendix A).

Research Objectives

Identifying the current tools for ITS efficacy measurement;
Determining the advantages and disadvantages thereof;
Suggesting a new and improved system of measuring ITS efficacy.

Research Significance and Contribution

The significance of the study can be defined as a medium in impact. While it is unlikely to reinvent the current system of global SCM processes, it may deliver results that will help create more efficient strategies for transporting goods and their components. Furthermore, the overall efficacy of the information management process may be improved significantly since, to improve the transportation process, it is necessary to considerably enhance the data management framework.

As a result, tools for improving measurement can be designed. Moreover, the foundation for a rapid positive change in the transportation domain will be built. As a result, the study will contribute to the enhancement of one of the essential business processes and, therefore, to economic growth rates (Grabara, Kolcun & Kot 2014).

Research Questions

What characteristics do contemporary ITS possess?
What are measurement tools for determining the efficacy of modern ITS currently used?
What are the advantages and disadvantages of the identified measurement frameworks?
How should the ultimate measurement tool for evaluating the performance of ITS in the context of the global economy look, based on current quality standards?
What implications for businesses do the results of the study have?

Research Methods

Seeing that both an overview of the existing methods of ITS assessment and a comparison of the models identified in the process will be required, it is reasonable to adopt a mixed study approach. The mixed design will allow obtaining qualitative data and quantifying it afterward so that a detailed assessment can be conducted.

The qualitative analysis will be conducted as phenomenology so that the nature of ITS can be explored. For this purpose, a thorough overview of the existing studies on the subject matter will be carried out. The quantitative study, in turn, will imply a statistical analysis, allowing for a comparison between the identified approaches to measuring ITS. In particular, ANOVA should be used to compare the assessment tools.

The outcomes of the study will be used to determine the best assessment framework. Afterward, the ultimate approach to evaluating the efficacy of ITS will be created, based on the combined strengths of the existing approaches to ITS assessment. It is expected that the newly designed method will allow addressing some of the limitations of the current frameworks, thus providing an opportunity for a more accurate evaluation of ITS.

Structure of the Project Report

The project report will include three main sections: the introduction, discussion, and conclusion with recommendations. The introduction will set the background for the analysis, outlining the key aspects of contemporary ITS as well as the general approaches to their management. The problem and its scope will be defined, and the research question, along with hypotheses, will be laid out. The introduction will be followed by the body of the paper, where the essential stages of the analysis will be described in detail.

Next, the interpretation of the results will be provided, including a detailed description of the implications that the strengths and weaknesses of the current measurement tools have for ITS and how the current frameworks can be improved. The final section of the report will offer a brief summary of the study, along with guidelines concerning the design of the ultimate measurement tool. Furthermore, it is expected that the suggested ITS measurement framework should be tested in follow-up studies so that it can be used in a manner that is as efficient as possible for the further promotion of the economic progress.

Time Plan for Minor and Major Activities and a Gantt Chart

It is expected that the study will be carried out within three months. The need to collect a vast amount of data and process it carefully is the primary reason for setting the specified deadline. Three major activities are planned to be carried out: collecting the needed information, analyzing it, and determining the ultimate tool for measuring ITS. As the chart below shows, the goals listed above will require meeting several minor objectives.

It should be noted, however, that minor obstacles may be faced on the way to retrieving the necessary data, analyzing it, and delivering the end results. Indeed, seeing that each assessment tool may incorporate different aspects of ITS functioning, designing a comprehensive strategy may be rather difficult. Nevertheless, a comparative analysis of the significance that the identified characteristics hold will help in determining their value. Furthermore, the process of collecting the needed data may require extra time due to the complexity of the subject matter. However, it may be assumed that by the end of the third month, the study will be completed.

Reference List

Bray, S, Caggiano, L, & Ottomanelli, M 2016, ‘Measuring transport systems efficiency under uncertainty by fuzzy sets theory-based Data Envelopment Analysis: theoretical and practical comparison with traditional DEA model,’ Transportation Research Procedia, vol. 5, pp. 186-200.

Grabara, J, Kolcun, M & Kot, S 2014, ‘The role of information systems in transport logistics,’ International Journal of Education and Research, vol. 2, no. 2, 1-8.

Janusova, L & Cicmancova, S 2016, ‘Improving the safety of transportation by using intelligent transport systems,’ Procedia Engineering, vol. 134, no. 1, pp. 14-22.

Jurjevic, M, Dundovic, C & Hess, S 2016, ‘A model for determining the competitiveness of the ports and traffic routes,’ Thenicki vjesnik, vol. 23, no. 5, pp. 1489-1496. Web.

Mohideen, SI, Devi, K & Durga, MD 2016, ‘Fuzzy transportation problem of fuzzy octagon numbers with –cut and ranking technique,’ Journal of Computer, vol. 1, no. 2, pp. 60-67.

Xu, J & Zhou, X 2011, Fuzzy-like multiple objective decision making, Springer Science & Business Media, New York, NY.

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