Measuring Performance in Freight Transport. A Structured Literature Review


Master's Thesis, 2016
270 Pages, Grade: 1

Excerpt

TABLE OF CONTENTS

ABSTRACT

ACKNOWLEDGEMENTS

LIST OF FIGURES

LIST OF TABLES

LIST OF ABBREVIATIONS

1 INTRODUCTION
1.1 Rationale behind this Thesis
1.2 Rationale behind Structured Literature Reviews
1.3 Structure of this Thesis

2 POSITIONING THE FIELD OF INQUIRY
2.1 Scope of this SLR
2.2 Performance Measurement and Metrics
2.3 Freight Transport
2.3.1 Definition
2.3.2 Modes of Transport
2.4 Performance Measurement in Transportation
2.4.1 Performance Assessment in Road Freight Transport
2.4.2 Performance Assessment in Rail Freight Transport
2.4.3 Performance Assessment in Air Freight Transport
2.4.4 Performance Assessment in Maritime Freight Transport
2.5 Research Gap
2.6 Review Questions and Objectives

3 METHODOLOGY
3.1 Systematic Literature Reviews
3.2 Summary of the Review Process
3.3 Review Panel
3.4 Systematic Search
3.4.1 Database Selection
3.4.2 Identification of Keywords
3.4.3 Search Strings
3.4.4 Results of Systematic Search
3.4.5 Selection of other Sources
3.5 Selection Criteria
3.6 Quality Assessment
3.7 Data Extraction
3.8 Data Synthesis
3.9 Summary of the Search and Selection Process of this SLR

4 DESCRIPTIVE FINDINGS
4.1 Articles by Author
4.2 Articles by Year
4.3 Articles by Type of Literature
4.4 Articles by Publication
4.5 Articles by Country
4.6 Articles by Topic
4.7 Articles by Distribution across Database
4.8 Articles by Distribution across Review Fields

5 CONCEPTUAL FINDINGS
5.1 Introduction
5.2 Performance Measures for Intermodal Freight Transport and Freight Transport Chains
5.2.1 Classification of Performance Measures for Intermodal Freight Transport and Freight Transport Chains
5.2.2 Measuring Performance Intermodal Freight Transport and Freight Transport Chains
5.2.3 Descriptive Summary of Performance Metrics for Intermodal Freight Transport and Freight Transport Chains
5.3 Road Freight Transport
5.3.1 Classification of Performance Measures in Road Freight Transport
5.3.2 Measuring Performance in Road Freight Transport
5.3.3 Descriptive Summary of Performance Metrics in Road Freight Transport
5.4 Rail Freight Transport
5.4.1 Classification of Performance Measures in Rail Freight Transport
5.4.2 Measuring Performance in Rail Freight Transport
5.4.3 Descriptive Summary of Performance Metrics in Rail Freight Transport
5.5 Air Freight Transport
5.5.1 Classification of Performance Measures in Air Freight Transport
5.5.2 Measuring Performance in Air Freight Transport
5.5.3 Descriptive Summary of Performance Metrics in Air Freight Transport
5.6 Maritime Freight Transport
5.6.1 Classification of Performance Measures in Maritime Freight Transport
5.6.2 Measuring Performance in Maritime Freight Transport
5.6.3 Descriptive Summary of Performance Metrics in Maritime Freight Transport
5.7 Descriptive Summary of Conceptual Findings
5.7.1 Classification of Performance Metrics in Freight Transport
5.7.2 Measuring Performance in Freight Transport

6 DISCUSSION
6.1 Answer to Review Question and Review Objectives
6.1.1 Review Question
6.1.2 Review Objective 1
6.1.3 Review Objective 2
6.2 Trends and Patterns in Conceptual Findings
6.2.1 Trends and Patterns across Performance Categories
6.2.2 Trends and Patterns across Performance Metrics
6.3 Knowledge of Performance Measurement in Freight Transport
6.4 Filling of Defined Research Gap
6.5 Emerging Research Gaps from this SLR

7 CONCLUSION
7.1 Practical and Academic Value of this SLR
7.2 Limitations of Practical and Academic Value of this SLR
7.3 Implications and Recommendations for Academia
7.4 Implications and Recommendations for Practice
7.5 Limitations of the Methodological Approach
7.5.1 Methodology and Article Selection
7.5.2 Databases and other Sources
7.5.3 Research Resources and Time Frame
7.6 Personal Reflection on the Research and Learning Process

REFERENCES

APPENDICES

ABSTRACT

Changing economic conditions and increasing competition forced many companies to extend their supply, production and distribution networks towards global approaches. This led to an increase in the importance of freight transport. In consequence, freight carriers are currently required to provide either cost or time efficient solutions to a wide range of industries. In order to select appropriate modes of transport or suitable carriers, enterprises must consider their performance beforehand. Moreover, carriers must be precisely aware of their own performance at any time. Consequently, performance measurement and the definition of suitable performance metrics plays an essential role in freight transport. In practice, companies have to face an extensive variety of indicators that can be used to assess performance in freight transport. Studies prove that there is lack of consistency in the usage of metrics. At the same time, researchers have to cope with wide range of available literature that discusses performance evaluation in freight transportation which is, though, often limited to specific areas of application.

In this thesis a structured literature review (SLR) is carried out which has the objective to systematically find out how companies measure performance in intermodal, road, rail, air, and maritime freight transport. The conceptual findings of this SLR provide a list of 1742 metrics from the literature that can either be applied for one or several modes of freight transport. In addition, 47 different ways how KPIs can be classified are identified. The SLR proves that operational performance indicators mainly regard time, distance and available equipment. Strategic metrics focus on costs levels, the change of costs over time, ratios, fleet characteristics, environmental performance and market developments. The findings of this thesis are beneficial to practitioners because they provide guidance on how to appropriately select, classify and assess performance metrics. Furthermore, academics benefit from a structured overview on available knowledge across the literature.

ACKNOWLEDGEMENTS

I would like to express my gratitude to my thesis supervisor Andrey Pavlov for taking the effort, patience and time to guide me through this research project and providing valuable advice, support and feedback.

I acknowledge Cranfield University, the School of Management and the LSCM faculty for having been an outstanding host university during my exchange.

I would also like to thank Heidi and Viktoryia for everything we have experienced together in the UK.

A special thank you goes to my family for all the encouragement and support during my studies.

LIST OF FIGURES

Figure 1-1 Overview on the structure of this thesis

Figure 2-1 Illustration of the narrative review (adapted from Mbiyu 2013, p. 15)

Figure 2-2 Overview on the scope of the systematic review

Figure 4-1 Reviewed literature classified by publication date

Figure 4-2 Reviewed literature classified by type of literature

Figure 4-3 Reviewed literature classified by publication

Figure 4-4 Reviewed literature classified by country

Figure 4-5 Reviewed literature classified by topic (“freight transport” indicates that the article specifically addresses freight transport, while “transport” means that both, freight and passenger transport are discussed)

Figure 4-6 Reviewed literature classified by distribution across databases

Figure 4-7 Reviewed literature classified by distribution across review fields (where A is performance measurement, B is road freight transport, C is rail freight transport, D is air freight transport and E is maritime freight transport)

Figure 5-1 Number of key performance indicators for intermodal freight transport and freight transport chains classified by author(s) and performance category

Figure 5-2 Total number of key performance indicators for intermodal freight transport and freight transport chains according to literature classified by performance category

Figure 5-3 Number of key performance indicators for road freight transport classified by author(s) and performance category

Figure 5-4 Total number of key performance indicators for road freight transport according to literature classified by performance category

Figure 5-5 Number of key performance indicators for rail freight transport classified by author(s) and performance category

Figure 5-6 Total number of key performance indicators for rail freight transport according to literature classified by performance category

Figure 5-7 Number of key performance indicators for air freight transport classified by author(s) and performance category

Figure 5-8 Total number of key performance indicators for air freight transport according to literature classified by performance category

Figure 5-9 Number of key performance indicators for maritime freight transport classified by author(s) and performance category

Figure 5-10 Total number of key performance indicators for maritime freight transport according to literature classified by performance category

Figure 5-11 Total number of key performance indicators for freight transport according to literature classified by performance category

Figure 5-12 Total number of key performance indicators for freight transport according to literature classified by mode of transport

LIST OF TABLES

Table 2-1 Overview on performance metrics that can be applied in road freight transport summarized by Cottrell 2007 and Collins & Rossetti 2004

Table 2-2 Overview on performance metrics that can be applied in rail freight transport summarized by Cottrell 2007 and the Austrian Federal Railways (Vaugoin 2016)

Table 2-3 Overview on performance metrics that can be applied in air freight transport summarized by the Worldbank 2016 and Fry et al. 2004

Table 2-4 Overview on performance metrics that can be applied in maritime freight transport summarized by Cottrell 2007 and The Committee on the Marine Transportation System 2013

Table 3-1 Summary of the differences between traditional and systematic literature reviews (Jesson et al. 2011, p. 105)

Table 3-2 Phases of a systematic literature review and corresponding chapters in this SLR (Tranfield et al. 2003, p.214)

Table 3-3 The review panel of this SLR

Table 3-4 List of keywords that were used for this SLR ordered by the field of interest

Table 3-5 Precise formulation of search strings used for this systematic review

Table 3-6 Combinations of search strings as used in ABI and EBSCO for this systematic review

Table 3-7 Number of hits in EBSCO for each defined search string combination

Table 3-8 Number of hits in ABI for each defined search string combination

Table 3-9 Summary of the selection criteria applied for the systematic literature search of this thesis

Table 3-10 Overview on quality appraisal categories and criteria (adapted from Pavlov 2006, p. 36)

Table 3-11 Data extraction form used for this thesis (adaped from Ganesh 2011)

Table 3-12 Total number of hits based on the defined search strings from all sources used in this review

Table 3-13 Total number of hits in EBSCO and ABI for each defined combination of the search strings

Table 3-14 Number of hits after assessment of the article’s content

Table 3-15 Number of hits after the removal of duplicates and quality assessment

Table 5-1 Categorization of metrics that is used in this literature review

Table 5-2 Classification of performance metrics for intermodal freight transport and freight transport chains according to reviewed literature

Table 5-3 Classification of performance metrics for road freight transport according to reviewed literature (blue indicates that more than one reference mentions the classification)

Table 5-4 Classification of performance metrics for rail freight transport according to reviewed literature

Table 5-5 Classification of performance metrics for air freight transport according to reviewed literature

Table 5-6 Classification of performance metrics for maritime freight transport according to reviewed literature (blue indicates that more than one reference mentions the classification)

LIST OF ABBREVIATIONS

illustration not visible in this excerpt

1 INTRODUCTION

1.1 Rationale behind this Thesis

Supply chain management regards the storage and flow of resources, materials and information into and through a production process to a customer or an end user. In most of the cases, the flow of a material, a semi-finished or finished product within a supply chain involves some form of transportation. In many parts of the world changing economic conditions and increasing competition forced enterprises to extend their supply, production and distribution networks towards global approaches. This change in the nature of supply chains had and has a significant impact on the relative importance of different modes of freight transport. Freight carriers must provide suitable and high-quality solutions for existing supply and distribution networks that either require cost or time efficiency. The selection process for companies to find the most appropriate mode of freight transport involves four different fields that must be considered, namely, operational factors, a mode’s characteristics, consignment factors as well as cost and service requirements. Any adequate decision regarding the mode selection can only be executed if sufficient and eligible operational and strategic information on the performance of each mode is available (Rushton et al. 2015). This is also true for the decision-making processes of freight carriers, which must be precisely aware of their performance at any time.

Considering this, it can be stated that performance measurement plays an essential role in freight transport for all stakeholders. Underlying performance measurement systems provide an efficient way of monitoring and controlling performance on a general or more specific level in various fields of application. To make appropriately use of them, decision makers need to define and constantly monitor performance indicators. Metrics are summarizing the performance of freight transportation services as a whole as well as different individual elements of their operations (Rushton et al. 2015).

By today, much research on performance measurement in supply chains has been done, including several systematic literature reviews. While the collaborative perspective on performance assessment in supply chains must not be neglected, it can also be beneficial to focus on the individual area of freight transport within the frameworks of a supply chain. Therefore, this thesis has the overall objective to systematically review how companies measure performance in freight transport.

1.2 Rationale behind Structured Literature Reviews

Generally, literature reviews have the purpose to summarize or evaluate available academic and practical knowledge in order to provide answers to a research question that will add further value to a defined field of science. With regard to management research, literature reviews are considered to be a key tool that enables scientists to organize a wide range of knowledge. The majority of studies in management science makes use of so called traditional literature reviews (Tranfield et al. 2003). Traditional literature reviews are criticised to be “singular descriptive accounts of the contributions made by writers in the field, often selected for inclusion on the implicit biases of the researcher” and are furthermore critiqued for a lack of critical assessment (Tranfield et al. 2003, p. 208).

In contrast to traditional reviews, structured or systematic literature reviews have the aim to provide “systematic, transparent means for gatherings, synthesising and appraising the findings of studies on a particular topic or question. [Their intention] is to minimise the bias associated with single studies and non-systematic reviews” (Jesson et al. 2011, p. 104). Systematic literature reviews are replicable, auditable and follow a transparent process. Bias is tried to be reduced by an in-depth literature search (Tranfield et al. 2003).

The underlying research methodology of this thesis is a structured literature review. The central review aim is to systematically and transparently identify performance metrics from the literature that are used in the major modes of freight transport.

1.3 Structure of this Thesis

As illustrated in figure 1-1, this thesis consists of seven chapters. Following this introduction, chapter 2 positions the field of inquiry of this SLR. After outlining the scope, relevant themes and definitions with a focus on performance measurement and freight transport are presented in a narrative literature review. The chapter concludes with a description of the research gap, leading to the review question of this SLR and the corresponding review objectives.

Chapter 3 provides an overview on the methodology of structured literature reviews, including a description of relevant characteristics and the underlying search process. Afterwards, the systematic literature search of this thesis is described by specifying keywords, search strings, selection criteria and the quality assessment method.

Chapter 4 summarizes the descriptive findings of the systematic search based on eight different qualitative and quantitative criteria.

Chapter 5 outlines the conceptual findings of the structured search. It is organised in accordance with the defined review questions and objectives and concludes with a descriptive summary of the conceptual findings.

Chapter 6 discusses and interprets the findings of the SLR. It provides the answers to the review questions, outlines trends and patters across the conceptual findings and also summarizes the current level of knowledge of performance measurement in freight transport.

To conclude, chapter 7 describes the value of this SLR and consistent limitations. Moreover, implications and recommendations for academia and practice are specified.

illustration not visible in this excerpt

Figure 1-1 Overview on the structure of this thesis

2 POSITIONING THE FIELD OF INQUIRY

This chapter comprises three main parts. Initially, the scope of this thesis will be defined in part 2.1. Afterwards, in sections 2.2 to 2.4, relevant key concepts, namely, performance measurement, the four major modes of freight transport and performance measurement in freight transport, will be outlined in form of a narrative literature review (see figure 2-1). Finally, the research gap that is going to be addressed by this thesis and the corresponding review question as well as two review objectives are outlined in part 2.5 and 2.6.

illustration not visible in this excerpt

Figure 2-1 Illustration of the narrative review (adapted from Mbiyu 2013, p. 15)

2.1 Scope of this SLR

This systematic literature review addresses two research disciplines, namely, performance measurement and transportation. Due to the fact that there is a wide range of literature available in both scientific areas, the scope had to be narrowed down. The research field of performance measurement is limited to performance metrics and their categorization. Journal articles that specifically discuss performance measurement systems (PMS), PMS implementation, or data collection and organization are not considered in this SLR. The broad field of transport is limited to the most important modes of freight transport, which are road, rail, air and maritime carriage, or any combination out of these (intermodal). Any literature or studies that are explicitly related to transport infrastructure, public- or passenger transport, or national transportation systems and networks are not addressed by this systematic literature review.

illustration not visible in this excerpt

Figure 2-2 Overview on the scope of the systematic review

2.2 Performance Measurement and Metrics

According to a definition from the US Department of Energy “performance measurement [informs] about products, services and the processes that produce them. It is a tool [that helps] to understand, manage and improve what organizations do. Performance [measurement answers] how well a company does, if goals are met, if customers are satisfied, if processes are in statistical control and whether improvements are necessary. [Performance assessment] provides all information necessary to make intelligent decisions“ (U.S Department of Energy 1995, p. 4).

Performance indicators can be classified into quantitative and qualitative metrics. A quantitative performance metric consists of two entities, namely a digit and a unit. The digit informs about a quantity and the unit of measure assigns the number a meaning. Performance indicators can either be represented by single dimensional unit (e.g. length of time) or a multidimensional unit of measure (e.g. kilometers per hour). Qualitative metrics are designed to capture qualitative data. Their characteristics depend on the specific field of application and may for example measure a company’s abilities or customer feedback. (U.S Department of Energy 1995).

Performance measures must always be defined in connection with a target. Metrics are then able to indicate the variation in a process or the deviation from a predefined target (U.S Department of Energy 1995). In order to reach specified targets, companies then set up strategies. While executing these, performance indicators enable corporations “to measure, control and improve” (Konsta & Plomaritou 2012, p. 142).

2.3 Freight Transport

2.3.1 Definition

The term transportation can be defined as all physical entities that aim at the mobility of persons and the movement of freight between an origin and a destination. Those entities mainly “consist of infrastructure, transport means, networks and supporting facilities”. The transport means may involve modes like rail, road, water and maritime but also “sensible combinations operating as intermodal services” (Janić 2014, p. 1).

In accordance with the scope of this thesis the definition of Janić 2014 is fully applicable, though, it must be limited to the movement of freight and corresponding means instead of including the mobility of persons or any other entities to it. The advantages and disadvantages of the transport modes road, rail, air and maritime will be further described in the next chapter.

2.3.2 Modes of Transport

This section briefly describes the advantages and disadvantages for companies that come along with the usage of a specific mode of freight transport. To be precise, road, rail, air and maritime freight transportation are discussed. Finally, a definition for the term intermodal transport is given.

Road Freight Transport

Freight transport by road has several advantages. First, road freight carriers can usually provide very quick solutions to their customers. Moreover, the mode can be considered as cost-efficient, assuming that a full truck load (FTL) is shipped from one common origin to one common destination. Besides, required handling processes are comparably fast and damages are unlikely. In addition, road freight carriers are able to reach a very wide and diverse range of destinations. In contrast, road transport proves to be unreliable for time-sensitive goods if they have to be delivered to or transported through regions with high traffic congested (Rushton et al. 2015).

Rail Freight Transport

In most cases, rail freight is the second-cheapest available mode of transport. It is especially suitable for non-time sensitive consignments that are heavy or bulky and that are required to be transported over medium or long distances. Unfortunately, the shipping of freight by rail has several disadvantages: First, there is a high risk of damage for the freight due to the fact that the wagons of a cargo train are prone to intense shocks. Second, there is a need for double-handling because train stations are almost never the initial origin or final destination of the shipped goods. Third, rail freight transport is unreliable in terms of timeliness and schedule adherence. Delays are likely because priority is given to passenger trains in most countries of the world. Finally, there is a lack of standardization in rail transport across Europe, as for example in track gauge sizes or minimum bridge heights (Rushton et al. 2015).

Air Freight Transport

The transportation of cargo by air has the advantage that consignments can be shipped over long distances in very short time. Considering this, companies are therefore able to reduce their holding costs when using air freight due to lower inventory levels along their supply chains. They can also benefit from a higher market flexibility. Moreover, air freight transport is very reliable in terms of punctuality and quality. In addition, shipped goods are usually not prone to damage. Air cargo is particularly suitable for perishables, fashion goods, emergency supplies and spare parts. The major disadvantage of air freight is that it is the most expensive mode of transport. In addition, air freight is opposed to various safety and security constraints and procedures which slows down handling processes (Rushton et al. 2015).

Maritime Freight Transport

Maritime freight transport can be defined as the provision of “physical means by which cargo may safely and efficiently transported by sea”. This mode of transport is particularly suitable for high volume freight that either is not time sensitive or has a long lead time (Rushton et al. 2015, p. 389f).

There are two major advantages of maritime freight transport. First, maritime shipping offers the lowest freight rates over longer distances in comparison to other modes. Second, there is a high availability of ocean freight services that can deal with a wide range of different types of cargo. Nevertheless, carrying cargo by sea also comes along with a few disadvantages. First of all, sea freight is a very slow transportation mode which has a negative impact on a company’s flexibility, lead time and supply chain inventory. The high amount of time required is not only caused by the low cruising speed of vessels but also by time-consuming handling processes in many harbours. Moreover, ocean cargo is prone to delays and a high risk of damage during many stages of the transport chain (Rushton et al. 2015).

Intermodal Transport

Intermodal transport can be defined as “the movement of goods in one and the same loading unit or vehicle, which uses successively several modes of transport without handling of the goods themselves in changing modes” (Rushton et al. 2015, p.417).

2.4 Performance Measurement in Transportation

According to Cottrell 2007, there are five different categories of freight performance measurement that can be distinguished, namely asset management, cost, customer service, productivity and quality. In addition, performance evaluation in freight transport can also be classified by the stakeholder. The relevant parties to consider are the infrastructure provider, the manufacturer, the shipping company, as well as the customer. Consequently, according to this classification, there a 20 different categories in which performance could further be examined. Nevertheless, as outlined in the scope of this SLR, the only stakeholders that will be reviewed are the carriers, while all different kinds of categories in performance measurement are considered.

Cottrell’s point of view was already suggested in 1998 by Fawcett & Cooper. The authors state that performance metrics for transport majorly exist in the field of asset management, cost, customer service, productivity and quality. Interestingly, Fawcett & Cooper already pointed out back in 1998 that this very traditional perspective will not be valid in the future anymore. They criticize that the “classification no longer provides the insight needed to manage logistics resources for competitive advantage in today’s dynamic and intensely competitive global marketplace”. The authors refer to (at that point of time) emerging trends like just-in-time principles, the increasing complexity of supply chains, globally increasing production networks and the greater need for recognizing customer needs. They conclude that “competitive and environmental developments […] require more aggressive and innovative performance measurement” (Fawcett & Cooper 1998, p. 342).

2.4.1 Performance Assessment in Road Freight Transport

Cottrell 2007, referring to a study carried out in the US points out that there are three performance measures in road freight that are commonly regarded as very useful. These metrics are the average length of haul, the empty miles factor and the operating margin (or operating ratio). In general, all metrics that were listed in the study, can be classified into three broad categories. They are either related to finance, to equipment, or to load and haul (Cottrell 2007).

Cottrell 2007, referring to survey conducted by the American Transport Research Institute in 2007, emphasizes that there is another field of performance measurement in road freight which can be considered as increasingly important. This field covers all performance measures that relate to question whether or not a truck operator is compliant in terms of operational safety, industrial safety and environmental impact. Regarding this, the four major performance categories are hours of service (e.g. hours of service per driver), driver availability and shortages (e.g. driver recruitment and training costs), fuel costs (e.g. average miles per gallon) and highway congestion (e.g. average speed of travel). Also environmental controls and on-board technology are categories that are interesting for operators to consider, though, according to Cottrell, there were no appropriate measures by 2007. Collins & Rossetti 2004 reviewed available literature to create a list of metrics that can be used to assess performance in road freight transport. Table 2-1 provides an overview of metrics that can be applied for performance evaluation in road freight transport according to Cottrell 2007 and Collins & Rossetti 2004.

Table 2-1 Overview on performance metrics that can be applied in road freight transport summarized by Cottrell 2007 and Collins & Rossetti 2004

illustration not visible in this excerpt

2.4.2 Performance Assessment in Rail Freight Transport

The American Association of Railroads (AAR) annually publishes industry statistics. When considering these, some figures can be interpreted as performance measures for rail freight transportation (Cottrell 2007). The mentioned metrics in the AAR statistics are mainly related to service production resources (e.g. locomotives in service), industry employment (e.g. employee compensation), traffic (e.g. ton miles), operations (e.g. freight revenue per ton-mile) and finance (e.g. freight revenue) (American Association of Railroads 2016).

The Austrian Federal Railways have defined three major aims when it comes to the usage of performance indicators, namely, the identification of trends and progress, the detection of causes and effects, as well as the assessment of measures and changes in strategy. Moreover, they outlined, that asset utilization, efficiency, safety, quality and reliability, finance, innovation and accessibility are their main field of interest when it comes to the measurement of performance (Vaugoin 2016). Table 2-2 provides an overview on available performance metrics in rail freight transportation according to Cottrell 2007 and Vaugoin 2016.

Table 2-2 Overview on performance metrics that can be applied in rail freight transport summarized by Cottrell 2007 and the Austrian Federal Railways (Vaugoin 2016)

illustration not visible in this excerpt

2.4.3 Performance Assessment in Air Freight Transport

Cottrell 2007 states that metrics in air cargo transport can be classified into four categories, namely, customer service, performance, value and information technology. The term performance addresses for example the question to what extent scheduled transit times are accomplished or whether or not contractual responsibilities are met. The field of customer service includes the question how claims and problems are handled. Moreover, information technology plays a very important role in air cargo. Metrics in this field mainly measure the availability of tracking and tracing as well as internet and e-commerce options for customers. According to Fry et al. 2004, performance measurement in air freight transport has the aim to monitor operations, safety and finance. Metrics are required “to evaluate customer response to services and to maintain management control of geographically disparate route networks” (p. 2). Table 2-3 provides an overview on available performance metrics in air freight transport according to the Worldbank 2016 and Fry et al. 2004.

Table 2-3 Overview on performance metrics that can be applied in air freight transport summarized by the Worldbank 2016 and Fry et al. 2004

illustration not visible in this excerpt

2.4.4 Performance Assessment in Maritime Freight Transport

Maritime vessel operators commonly use metrics that are measuring volume, solvency, efficiency and safety (Cottrell 2007). Table 2-4 provides an overview on available performance metrics in maritime freight transportation according to Cottrell 2007 and The Committee on the Marine Transport System 2013.

Table 2-4 Overview on performance metrics that can be applied in maritime freight transport summarized by Cottrell 2007 and The Committee on the Marine Transportation System 2013

illustration not visible in this excerpt

2.5 Research Gap

As outlined in the previous section, practitioners face a great variety of metrics that can be used to assess performance in freight transport. Therefore, even within a single mode of transport, different companies use different performance indicators. Among the companies, there is a strong disagreement on the question which performance metrics can be considered to be the best or most suitable. Another challenge is that not all freight transport metrics are applicable for all transportation modes. As a result, there is a lack of consistency in performance assessment in freight transportation in practice (Cottrell 2007). A structured literature review on available key performance indicators for freight transportation, including their similarities and differences, would therefore enable practitioners to appropriately assess, select and classify their metrics to be used.

Performance measurement is not only a topic that plays an important role in practice but it is also intensively examined and covered from a theoretical and research perspective in academia. This is also true for the broad field of transportation and the combination of both research areas. At the same time, it can be seen that, as previously outlined in chapter 2.4, there is a wide range of literature available that discusses performance measurement in freight transportation. However, due to the large number of available metrics, many articles are limited to specific areas of application. Consequently, a systematic overview on performance measures in freight transportation is beneficial in order to reach a structured overview and summary on available knowledge that is discussed in the literature. Another significant advantage for academia of carrying out a structured review is that similarities and differences between different journal articles or researches can be outlined, summarized and discussed.

2.6 Review Questions and Objectives

This systematic literature review will be led by the following review question:

What metrics are used by companies to measure performance in freight transport?

Additionally, the systematic search is guided by two objectives. For both objectives additional review questions are formulated which will be addressed by the structured review.

Objective 1

Identification of a list of metrics available in the literature that measure performance in the most common modes of freight transportation.

- What are the metrics used to measure performance in road, rail, air, and maritime freight transportation?
- What are the metrics used to measure performance in intermodal freight
transportation?

Objective 2

Reviewing of similarities and differences between performance metrics in the most common modes of freight transportation that are discussed in the literature.

- How can performance metrics in road, rail, air and maritime freight
transportation be categorized?
- What are the similarities between performance metrics in road, rail, air and maritime freight transportation?
- How do performance metrics differ in road, rail, air and maritime freight transportation?

3 METHODOLOGY

This chapter provides an overview on the systematic literature review methodology. Initially, the concept will be outlined on a general level and differentiated from traditional reviews in chapters 3.1 and 3.2. Afterwards, all steps that are required to carry out a systematic search are presented and are specifically defined for this thesis in chapters 3.3 to 3.9. To be precise, this part involves the definition of a review panel (3.3), the selection of data bases, the identification of key words, the definition of search strings (3.4.1 to 3.4.5), the definition of selection criteria (3.5), an overview on the quality assessment method (3.6) and the data extraction form (3.7) as well as the data synthesis (3.8), as well as a summary of the actual systematic database search (3.9).

3.1 Systematic Literature Reviews

Almost any type of research requires a review of relevant literature in the field of interest. There are two different types of literature reviews that must be differentiated, namely, the traditional or narrative literature review and the systematic or structured literature review.

Traditional reviews provide an overview on a topic of interest by usually referring to a few available studies. In short, they can be regarded as a summary on what is known on that specific topic. Although it is very common in research to make use of traditional reviews, it is important to reflect narrative reviews critically. This is because, first, they do not clarify the criteria used to identify the studies they refer to and second, they do not provide any details on the question why some studies are mentioned while others are not. In consequence, important journal articles may not have been considered in traditional reviews because the author was not aware of them. Therefore, the appropriateness of the study selection in traditional review cannot be assessed and moreover, the meaning of all review results cannot be interpreted (Gough et al. 2012). To summarize, narrative reviews “can be biased by the researcher and often lack rigour” (Tranfield et al. 2003, p. 207).

In contrast, the major goal of systematic literature reviews is to have an explicit, transparent, rigorous and accountable selection of studies and corresponding research results (Gough et al. 2012). To be precise, “identifying and sifting through all the relevant studies and evaluating each according to predefined criteria is what distinguishes a systemic review from a traditional one” (Jesson et al. 2011, p. 105). Therefore, “a comprehensive, unbiased search is one of the fundamental differences between a traditional narrative review and a systematic review” (Tranfield et al. 2003, p. 215). The methodology of systematic literature reviews emerged from medical science, in which the process of carrying out systematic, auditable and reproducible searches, proved to be very useful to summarize available knowledge and enhance the research process (Tranfield et al. 2003). Table 3-1 provides an overview on the most important differences between traditional and systematic literature reviews.

Table 3-1 Summary of the differences between traditional and systematic literature reviews (Jesson et al. 2011, p. 105)

illustration not visible in this excerpt

3.2 Summary of the Review Process

Systematic literature reviews follow a fixed list of three stages, in which each stage consists of several phases. Stage 1 involves the planning before the systematic search is carried out. Within this stage it is required to outline the scope of the study and to define a review panel. Stage 2 starts with the identification of appropriate key words and search strings. Moreover, the search strategy has to be explained. The goal of the search is to find a list of journal articles on which the findings of the SLR will be built on. Finally, during stage 3, two reports are required, namely, a descriptive analysis and a thematic analysis (Tranfield et al. 2003).

This SLR will precisely follow the required stages that were defined by Tranfield et al. 2003. Only phase 9 will be left out, as it is not applicable for this type of research. Table 3-2 provides an overview on which phases are addressed in which part of this thesis.

Table 3-2 Phases of a systematic literature review and corresponding chapters in this SLR (Tranfield et al. 2003, p.214)

illustration not visible in this excerpt

3.3 Review Panel

Before carrying out a systematic literature review a review panel must be formed. It comprises methodological and content experts. The review panel should support the systematic search and selection process of the review and solve any disputes over the in- or exclusion of journal articles or studies (Tranfield et al. 2003). The review panel that is responsible for this structured literature review is presented in table 3-3.

Table 3-3 The review panel of this SLR

illustration not visible in this excerpt

3.4 Systematic Search

3.4.1 Database Selection

For the systematic search of this review two databases were selected, namely Business Source Complete (EBSCO) and ABI Inform Complete via ProQuest (ABI). The databases were selected for the following two reasons: First, both of them comprise an extensive collection of academic papers in management science. Second, the databases cover a sufficient range of relevant journal articles regarding the field of supply chain management, logistics and transportation. Therefore, after having evaluated other available options beforehand, EBSCO and ABI were considered to be the most suitable databases to carry out this systematic literature review. Below, the characteristics of both databases are summarized briefly.

- Business Source Complete

EBSCO is a database that provides access to over 2800 scholarly publications in the area of business and management science. It includes more than 900 peer-reviewed journals. The publications in the database cover a time frame from 1922 to 2016 (Cranfield University 2016).

- ABI Inform Complete via ProQuest

ABI Inform Complete is a database that provides access to more than 2500 international business publications and periodicals. ABI covers publications that were published between 1971 and 2016 (Cranfield University 2016).

3.4.2 Identification of Keywords

Structured literature searches always begin with the identification of relevant and suitable keywords or search terms. Keywords must be formulated in such a way that they are in accordance with the previous scoping study and the narrative review (Tranfield et al. 2003).

Table 3-4 provides an overview on the keywords and search terms that have been used to carry out the systematic search of this thesis. Five fields of interest were defined based on the scoping of the study, namely, performance measurement (A) as well as the four major modes of transport, which are road (B), rail (C), air (D) and maritime (E). The table also points out the rationale behind each of the selected keywords and search terms.

Table 3-4 List of keywords that were used for this SLR ordered by the field of interest

illustration not visible in this excerpt

3.4.3 Search Strings

Search strings are a combination of keywords, Boolean operators and proximity operators that are entered into selected databases to actually execute the structured literature search. Depending on the scope and background of the review a string can either be entered individually or in combination with one or more other string(s). Table 3-5 shows the search strings ordered by the fields of interest that are used for this thesis. Table 3-6 illustrates which search strings were combined for the actual search. The search strings were combined in such a way that they suit to the scope described in chapter 2.

Table 3-5 Precise formulation of search strings used for this systematic review

illustration not visible in this excerpt

Table 3-6 Combinations of search strings as used in ABI and EBSCO for this systematic review

illustration not visible in this excerpt

3.4.4 Results of Systematic Search

The systematic search for this thesis was executed with the search string combinations outlined in table 3-6, using the two databases described in chapter 3.4.1. The database queries were carried out between the 9th and 16th of May 2016. Due to the fact that both databases, that were used for this review, are constantly updated, search results may differ over time although the same search strings are used. Tables 3-7 and 3-8 show the numerical output of EBSCO and ABI. The total number of articles was already reduced at this initial stage of the search by limiting the hits to journal articles and articles that are written in English. The exact journal article selection criteria are specified more precisely in chapter 3.5.

Table 3-7 Number of hits in EBSCO for each defined search string combination

illustration not visible in this excerpt

Table 3-8 Number of hits in ABI for each defined search string combination

illustration not visible in this excerpt

3.4.5 Selection of other Sources

According to Greenhalgh and Peacock 2005, systematic literature reviews that are following “protocol-driven search strategies may fail to find important literature or central ideas” (p. 1065). The authors state that “informal approaches such as browsing, asking around, and being alert to serendipitous discovery can substantially increase the yield and efficiency of search efforts” (p. 1065). Therefore, they suggest to make use of so called snowball methods (“snowballing”) in structured reviews. The idea of snowball methods is to pursue references of references in order to “identify high quality sources in obscure locations” (p. 1065). Based on their study, the authors conclude that “systematic reviews of complex evidence cannot rely solely on protocol-driven search strategies” (Greenhalgh & Peacock 2005, p. 1064).

This structured literature review made use of the snowball method by reviewing the references of 59 journal articles that had a suitable scope for the review (see chapter 3.9) and by including a recommendation.

3.5 Selection Criteria

According to Tranfield 2003, only articles that meet all specified selection criteria may be used for the descriptive and conceptual report of a SLR. The strictly defined selection criteria have the aim to base the review on the highest quality evidence being available (Tranfield et al. 2003). Table 3-9 provides an overview on all selection criteria that were applied for the systematic search of this thesis. A complete list of selected articles that were used for this review can be found in appendix A, details on the content of the academic papers are given in the data extraction forms in appendix B.

Table 3-9 Summary of the selection criteria applied for the systematic literature search of this thesis

illustration not visible in this excerpt

3.6 Quality Assessment

According to Tranfield 2003, the “quality assessment refers to the appraisal of a study’s internal validity and the degree to which its design, conduct and analysis have minimized biases or errors” (p. 215). All journal articles to be used in the report of a structured literature review must be “judged against a set of predetermined criteria and checklists” (p. 215). Whether or not an article is relevant to the review depends on the previously defined review questions (i.e. scope) and the specified quality criteria (Tranfield et al. 2003). Table 3-10 provides an overview on the quality appraisal categories and criteria that will be applied during the article selection of this thesis. Assessment details regarding the quality for each reviewed article of this thesis can be found in the data extraction forms in appendix B.

Table 3-10 Overview on quality appraisal categories and criteria (adapted from Pavlov 2006, p. 36)

illustration not visible in this excerpt

3.7 Data Extraction

According to Tranfield 2003, data-extraction forms should consider “all the information that will be needed to construct summary tables and to perform data synthesis”. To be more precise, they should comprise “details of the information source and any other features of the study such as population characteristics, context of the study and an evaluation of the study’s methodological quality”. Moreover, “links to other concepts, identification of emergent themes, key results and additional notes also need to be included” (Tranfield et al. 2003, p. 217).

The data extraction form to be used in this thesis is shown below. It was developed in accordance with the requirements specified by Tranfield 2003. It comprises three main sections, namely bibliographic information, quality assessment and conceptual information. The bibliographic information is provided as a support to the reader. The formal reference can be found in the list of references for each reviewed article. The quality assessment is carried out in accordance with the method specified in chapter 3.6 and therefore assigns a number between 1 and 3 for each of the entries. The conceptual information mentions a list of keywords quoted without change from the reviewed article, the industry the article refers to, a reference to the scope of this review by naming to what field of interest the article contributes (A to E) and what performance metrics it mentions, as well as a short summary. The complete list of data extraction forms for the reviewed articles can be found in appendix B.

Table 3-11 Data extraction form used for this thesis (adaped from Ganesh 2011)

illustration not visible in this excerpt

3.8 Data Synthesis

According to Tranfield 2003, synthesis can be defined as “the collective term for a family of methods for summarizing, integrating and cumulating the findings of different studies on a topic or research question” (p. 217). In management science data synthesis usually involves a two-stage report. The first stage provides a descriptive analysis of the field, the second stage makes a thematic analysis available to the reader. The overall aim of a structured literature reviews is “to make it easier for the [reader] to understand the research by synthesizing extensive primary research papers from which it was derived” (Tranfield et al. 2003, p. 218).

This systematic review will follow the usual process for data synthesis according to Tranfield described above. The descriptive analysis of the field will be provided in chapter 4 of this thesis. Afterwards, the conceptual findings will be presented in chapter 5.

3.9 Summary of the Search and Selection Process of this SLR

This chapter provides a short summary of the search and selection process of the structured literature search carried out for this SLR. Initially, the search process found 6118 hits from the databases by using the defined search strings, twelve articles from snowballing and one recommendation (table 3-12).

Table 3-12 Total number of hits based on the defined search strings from all sources used in this review

illustration not visible in this excerpt

In order to focus on the subject of the investigation, the selection criteria specified in chapter 3.5 were applied for each of the search string combinations. For this, the relevant filter in the databases were selected, namely “journal articles” and “articles in English”. This reduced the total number of database hits from 6118 to 654 (table 3-13).

Table 3-13 Total number of hits in EBSCO and ABI for each defined combination of the search strings

illustration not visible in this excerpt

Afterwards the 654 remaining journal articles in EBSCO and ABI were reviewed. At this stage only the name of the article, the abstract and the keywords were considered. Based on those three pieces of information it was assessed whether or not the papers were in accordance with the scope specified in chapter 2.1. To be more precise, articles were selected if one out of the words KPI, metric, or indicator occurred in combination with any synonym for a major mode of transport. At a later stage of the process, the content of the articles was skimmed and it was specifically checked whether or not the articles mention performance metrics. Journal articles that did not list performance indicators, or that discussed any other mode of transportation than specified in chapter 2.1, or that explicitly focussed on infrastructure or public transport were not included for further examination. During this process 36 journal articles from EBSCO and 23 articles from ABI were selected to be suitable (table 3-14).

Table 3-14 Number of hits after assessment of the article’s content

illustration not visible in this excerpt

During the search, hits from EBSCO were reviewed before the hits from ABI. The list of journal articles from ABI therefore comprised 8 duplicates that were removed. Next, all remaining journal articles and reports were read completely. For each source the quality assessment was then carried out, applying the method specified in chapter 3.6. The quality assessment results are listed in the data extraction forms in appendix B. After the quality assessment 61 articles and reports remained. As show in table 3-15, 33 journal articles from EBSCO, 15 articles from ABI, twelve articles and reports through snowballing and one recommendation were used to answer the review question and objectives of this SLR.

Table 3-15 Number of hits after the removal of duplicates and quality assessment

illustration not visible in this excerpt

4 DESCRIPTIVE FINDINGS

This chapter lists the descriptive findings of the structured literature review. The list of reviewed articles (see appendix A) is statistically analysed based on eight criteria, namely, author, year, type of literature, publication, country, topic, the distribution across databases and the distribution across review questions.

4.1 Articles by Author

Out of the 61 reviewed pieces of literature the same combination of authors only occurs twice. The systematic review considers two journal articles from Feng & Wang as well as McKinnon & Ge. All other authors or combinations of authors were only found once. This is interesting because it proves that the field of performance measurement in freight transport is examined by a large number of different scientists instead of a few researchers only.

4.2 Articles by Year

This structured literature review considers articles that were published between 1980 and 2015. The mean of the data is the year 2009, the average of all years that were considered is 2007,8. These two descriptives together with the histogram below indicate that the literature review majorly considers more recent articles. The histogram may also indicate that the topic of performance measurement in freight transport became more popular in literature over the last ten years.

illustration not visible in this excerpt

Figure 4-1 Reviewed literature classified by publication date

4.3 Articles by Type of Literature

This review considers three different types of literature, namely journal articles, reports and conference papers. The 56 journal articles make up the largest fraction (91,8%), followed by 3 reports (4,9%) and 2 conference papers (3,3%). The large number of journal articles can be explained by the fact that the database search was limited to that type of literature while other references were discovered by using snowballing.

illustration not visible in this excerpt

Figure 4-2 Reviewed literature classified by type of literature

4.4 Articles by Publication

This review refers to 28 different publications. The three most frequent ones are “Benchmarking: An International Journal” (11,5%), followed by “International Journal of Physical Distribution & Logistics Management” (8,2%) and “International Journal of Logistics Research and Applications” (6,5%) as well as “Transportation Research” (6,5%). In total, the literature review is based on 36 different sources. The fact that most articles emerge from “Benchmarking: An International Journal” can for example be explained by the fact that the topics of benchmarking and performance measurement (especially performance metrics) are related very closely. Furthermore, the allocation of the topic over 36 sources shows that performance measurement in freight transport is interesting for a wide range of scientific fields.

illustration not visible in this excerpt

Figure 4-3 Reviewed literature classified by publication

4.5 Articles by Country

The major fraction of underlying articles of this literature review originate from the United Kingdom (26,2%), the United States (13,1%), followed by Sweden and Taiwan (6,5%). In total, the reviewed literature comes from 20 different countries. The large number of journal articles that are from the United Kingdom and the United States can be explained by the fact that the database search was limited to literature that is written in English. The allocation of the topic over 20 countries proves that performance measurement in freight transport is an area that is under investigation world-wide and not only in specific geographic areas. Though, the list mainly comprises countries that are considered to be more economically developed.

illustration not visible in this excerpt

Figure 4-4 Reviewed literature classified by country

4.6 Articles by Topic

The literature review addresses 13 different topics. The most frequent topic among all hits is road freight transport (26,2%), followed by maritime freight transport (18,0%) and rail transport (9,8%). It strikes that only four articles in total are not directly related to the broader field of transportation. These four articles focus on the consumer goods industry and grocery retail distribution. It can also be seen that a few articles discuss passenger transport, although this is formally not in accordance with the scope. After consulting the review panel, it was decided to consider the articles because the listed metrics are applicable one-to-one for freight transport.

illustration not visible in this excerpt

Figure 4-5 Reviewed literature classified by topic (“freight transport” indicates that the article specifically addresses freight transport, while “transport” means that both, freight and passenger transport are discussed)

4.7 Articles by Distribution across Database

As already mentioned in chapter 3.9 the underlying literature of this review has four different sources: 33 pieces of literature were found in EBSCO, 15 in ABI, twelve through snowballing and one recommendation was given. The fact that most articles emerge from EBSCO can be explained by the fact that EBSCO hits were reviewed before ABI hits during the structured search. Consequently, the total number of ABI findings does not consider any duplicates.

illustration not visible in this excerpt

Figure 4-6 Reviewed literature classified by distribution across databases

4.8 Articles by Distribution across Review Fields

53 out of 61 pieces of literature found during the search directly relate to one of the search string combinations. Most of the articles regard performance measurement in road freight transport (34,4%), followed by rail and maritime freight (18,0% each) as well as air freight transport (16,4%). Eight of the literatures covered the topic of performance measurement in combination with two or more modes of freight transport. It is interesting that the topic of performance measurement in road freight transport is covered at a much larger extent than performance measurement in rail, air or maritime freight transport.

illustration not visible in this excerpt

Figure 4-7 Reviewed literature classified by distribution across review fields (where A is performance measurement, B is road freight transport, C is rail freight transport, D is air freight transport and E is maritime freight transport)

5 CONCEPTUAL FINDINGS

5.1 Introduction

Chapter 5 lists the conceptual findings of the systematic literature search. It is structured into six sub-chapters. Five of them describe the findings for each of the review fields, namely performance measurement in intermodal freight transport and freight transport chains (5.2), in road freight transport (5.3), in rail freight transport (5.4), in air freight transport (5.5) and in maritime transport (5.6). All five sub-chapters are divided into two major sections to address the review objectives that were specified in chapter 2.6. The first part of each sub-chapter regards review objective 2 and answers the question how performance metrics are categorized according to the literature. The second part of each sub-chapter is related to review objective 1 and addresses the question what metrics are used to measure performance in freight transport. Each sub-chapter concludes with a short descriptive summary of the findings. Finally, a descriptive summary on all sub-chapters is provided (5.7).

A definition for mentioned performance metrics is only given, if an entire journal article focuses on that specific metric. Formulae for the performance indicators are provided if they were defined in the underlying literature. All lists of performance metrics use exactly the wording that was used in the referred journal article. There are two exceptions from this:

- Abbreviations were converted into the expanded form of the word;
- If a metric in context of the paper meant “number of” a “no. of” was added.

The number of performance metrics mentioned in most of the reviewed articles is very large. Therefore, the presentation of the metrics requires a form of classification within the conceptual findings of this SLR. It was decided to group each KPI list into four categories, namely finance and costs, operations, customer service and quality, as well as environmental and other. This way of classifying the metrics was considered to be most suitable by the author of this review and is not based on any reference or recommendation. Some indicators could be listed in two or even more of these groups. In that case the indicator was assigned to the most suitable headline and highlighted with an asterisk (*). Within their category, the metrics will be shown in alphabetical order.

Table 5-1 Categorization of metrics that is used in this literature review

illustration not visible in this excerpt

5.2 Performance Measures for Intermodal Freight Transport and Freight Transport Chains

5.2.1 Classification of Performance Measures for Intermodal Freight Transport and Freight Transport Chains

There are significant differences on how performance indicators for intermodal freight transport and transport chains can be classified. Within the reviewed literature of this thesis, the following ways of grouping indicators were identified:

Islam et al. 2013 presented three different ways of how performance indicators can be classified, namely by quality, time, flexibility and cost; or by quantitative and qualitative metrics; or by top-layer and lower-layer indicators.

Kunadhamraks & Hanaoka 2008 order intermodal performance metrics by logistics costs, service quality, reliability and security. Besides, they also discuss to organize KPIs by end customer benefits, supply chain goals, financial goals and system improvement.

Lee & Wu 2014 suggest to differentiate strategic, tactical, operational metrics, or to distinguish financial and non-financial indicators.

The reviewed literature does not mention any identical approaches on how performance metrics for intermodal freight transport or freight transport chains can be classified.

Table 5-2 Classification of performance metrics for intermodal freight transport and freight transport chains according to reviewed literature

illustration not visible in this excerpt

5.2.2 Measuring Performance Intermodal Freight Transport and Freight Transport Chains

Islam et al. 2013 assessed a benchmarking tool for transport chains. Within their research, the authors came across the following quantitative and qualitative performance metrics:

Cost and finance:

- Cleaning cost;
- Container rent;
- Fuel/energy cost;
- Handling fee for loading and unloading;
- Infrastructure charge;
- Inspection cost;
- Inventory cost;
- Overhead cost;
- Payment terms;
- Terminal charge;
- Terminal/handling cost;
- Total transport cost;
- Vehicle/vessel cost.

Operations:

- Driving/sailing duration*;
- Flexibility*;
- Handling duration*;
- Quality systems preference;
- Size adaptability*;
- Timetable adaptability*;
- Total reliability of the chain*;
- Total transport time*;
- Transit time variation*;
- Waiting time*.

Customer service and quality:

- Confirmation of Delivery;
- Insurance;
- Invoice accuracy;
- No of complaints;
- Proof of delivery;
- Punctuality*;
- Quality*;
- Reliability of the service*;
- Tracking and tracing ability.

Environment and other:

- CO² emissions;
- Demand adaptability*;
- Nmh emissions;
- Nox emissions;
- PM10 emissions;
- Reputation*;
- Robustness;
- SO² emissions;
- Sustainability.

Kunadhamraks & Hanaoka 2008 assessed the performance of intermodal freight transport in Thailand. In comparison to Islam et al. 2013, the authors addressed the field of cost and finance with less detail but therefore emphasize how quality and customer service performance can be measured. It also strikes that environmental performance is not addressed at all. Kunadhamraks & Hanaoka 2008 refer to 30 different KPIs, namely:

Cost and finance:

- Cost;
- Economic value added;
- Gross revenue;
- Handling cost;
- Holding cost;
- Profit;
- Total logistics costs;
- Transport cost.

Operations:

- Capacity*;
- Cut-off time;
- Documentation time;
- Flexibility*;
- Inspection time;
- Loading/unloading time;
- Travel time*.

Customer service and quality:

- Change in frequency of freight damage;
- Changes in frequency of delay;
- Duration of disruptions;
- Duration of unacceptable delays;
- Frequency of disruptions;
- Frequency of freight damage;
- Frequency of unacceptable delays;
- Quality of cargo handling in terms of cost;
- Quality of cargo handling in terms of speed;
- Reliability*;
- Security;
- Service quality;
- Severity of freight damage;
- Tracking and tracing availability/quality.

Environment and other:

- No. of value-added logistics services*.

Selviaridis & Norrman 2015 executed a case study on major challenges in performance based contracting in the logistics and transport sector. With regard to the category cost and finance, it can be stated that, different than Islam et al. 2013, Selviaridis & Norrman 2015 do not focus on total cost values but prefer examination of the change in cost levels to measure financial performance. It also strikes that the authors do not mention any KPIs that regard operations. Within their case study Selviaridis & Norrman 2015 unveiled 16 different indicators that are:

Cost and finance:

- Air freight cost reduction;
- Financial stability;
- Logistics cost reduction;
- Ocean freight cost reduction;
- Supply chain cost reduction;
- Total freight cost reduction.

Customer service and quality:

- Accuracy of sailing list when using multiple carriers;
- Customer satisfaction (based on survey results);
- Deliveries accuracy;
- Perfect orders;
- Product availability*;
- Product damages;
- Transport delivery accuracy;
- Transport delivery precision.

Environment and other:

- CO² emissions reduction;
- Increase in product volumes.

Lee & Wu 2014 examined how economic and environmental performance can be measured in intermodal freight transport chains. In comparison to Islam et al. 2013 and Kunadhamraks & Hanaoka 2008 it can be seen that the authors also consider costs per transport unit besides total cost levels. Moreover, Lee & Wu 2014 contemplate performance measurement in operations and environmental performance in much more detail than the previous three papers. In contrast to Islam et al. 2013 and Kunadhamraks & Hanaoka 2008, this journal article addresses the field of customer service and quality only on a very brief level. Lee & Wu 2014 point out the following performance indicators in their study:

Cost and finance:

- Average cost per TEU;
- Consolidation and break bulk cost for a 20 TEU container;
- Cost per kilometre for a full/empty 20/40 TEU truck;
- Cost savings;
- Freight handling costs;
- Fuel costs;
- Oil price;
- Operating costs;
- Percentage of fuel costs in transport operating costs;
- Total costs;
- Transport cost;
- Unit transport costs.

Operations:

- Average distance transported;
- Distance between locations;
- Fleet*;
- Freight volume*;
- Fuel consumption*;
- Fuel efficiency*;
- Location(s) of container terminal/cross dock/inland container hub/warehouse/empty container park/retailers;
- Number of trucks available for 20 TEU containers;
- Percentage of 20 TEU containers;
- Percentage of 40 TEU containers;
- Percentage of containers transported to terminal/cross dock/inland container hub/warehouse/empty container park/retailers;
- Traffic/road congestion*;
- Transport mode and modal split*;
- Transport utilization.

Customer service and quality:

- Available transport options*;
- Lead-time*;
- Quality;
- Size/type of container*;
- Transit time*.

Environment and other:

- Average emissions per TEU;
- Carbon emissions;
- Carbon intensity of fuel;
- Eco-efficiency;
- Emission per kilometre for a full/empty one-/two-TEU truck;
- Energy consumption;
- Energy efficiency;
- Environmental performance;
- Greenhouse gas emissions;
- No. of empty/half full/full containers moved*;
- Number of containers;
- Power consumption;
- Sustainability performance.

Lai et al. 2002 developed a supply chain performance measurement tool with a focus on transport logistics. Regarding cost and finance the authors agree to Islam et al. 2013 and Kunadhamraks & Hanaoka 2008 and prefer to measure financial and cost performance based on the level of different cost types instead of directly comparing the change over time. It also strikes that Lai et al. 2002 mention a wide range of quality and customer measures. With regard to the content of them though, the list is quite similar to what is mentioned by Islam et al. 2013 and Selviaridis & Norrman 2015. The tool of Lai et al. 2002 considers 28 performance indicators which are:

Cost and finance:

- Administration costs;
- Cash to cash cycle time;
- Cost efficiency;
- Inventory costs;
- Net asset turns;
- Operating costs;
- Order management costs;
- Transportation costs;
- Warehousing costs.

Operations:

- Facility/equipment/manpower utilization;
- Operations efficiency;
- Shipping frequency*.

Customer service and quality:

- Advisory of estimated time of arrival;
- Availability of special packaging;
- B/L accuracy;
- Complaint handling;
- Invoice accuracy;
- Location/opening hours of depots/stations/similar infrastructure*;
- On-time arrival*;
- Perfect order fulfilment;
- Reliability;
- Response time;
- Service effectiveness for consignees;
- Service effectiveness for shippers;
- Supply chain reliability;
- Timeliness of responses;
- Willingness to help.

Environment and other:

- Freight rate.

5.2.3 Descriptive Summary of Performance Metrics for Intermodal Freight Transport and Freight Transport Chains

Out of the five journal articles that were reviewed with the aim to list indicators that are used to measure performance in intermodal freight transport, the journal article written by Lee & Wu 2014 provided the most indicators (44), followed by Islam et al. 2013 (41) and Kunadhamraks & Hanaoka 2008 (30).

With regard to performance indicators that concern cost and finance, the most metrics are mentioned by Islam et al. 2013 (13). The largest number of KPIs that measure performance in operations of intermodal transport chains is provided from the journal article written by Lee & Wu 2014 (14). Most metrics that measure customer service and quality were outlined by Kunadhamraks & Hanaoka 2008 (14), environmental performance and other fields are addressed by Lee & Wu 2014 (13) at the most.

illustration not visible in this excerpt

Figure 5-1 Number of key performance indicators for intermodal freight transport and freight transport chains classified by author(s) and performance category

Out of the five reviewed journal articles that discuss performance measurement in intermodal freight transport or freight transport chains, 51 of all the mentioned KPIs regard customer service and quality, followed by cost and finance (48), operations (34) and environment and other (26). In total 159 different metrics (including duplicates) were identified for this review field.

illustration not visible in this excerpt

Figure 5-2 Total number of key performance indicators for intermodal freight transport and freight transport chains according to literature classified by performance category

5.3 Road Freight Transport

5.3.1 Classification of Performance Measures in Road Freight Transport

According to the reviewed literature there are significant differences on how performance metrics in road freight transport can be classified. Within the underlying literature of this thesis, the following ways of grouping indicators were identified:

McKinnon 2009 carried out research on efficiency and performance in road freight transport with a focus on sustainability. KPIs are classified by five main fields, namely vehicle loading, empty running, fuel consumption, vehicle time utilization and deviations from schedule in the journal article.

Feng & Wang 2001 carried out research on measuring and evaluating financial performance in road passenger transport (see appendix B for reason of inclusion) and classified metrics into production, marketing and execution. In more detail, they considered performance evaluation, performance in production, performance in marketing, performance indicators in execution, information from the balance sheet as well as information from the income statement.

Rodrigues et al. 2014 suggest the introduction of a new metric that identifies disruption causes and their impact in road freight operations. In their literature review they outline various dimensions of performance, including the classifications by quality, time, efficiency and cost; or reliability, flexibility and responsiveness; or efficiency and cost.

Ruzzenenti & Basosi 2009 evaluated changes and trends of energy efficiency in European road freight transport. Within the framework of their research, they define two overall performance measurement groups. First, the energy intensity indicators that are a “measure of the energy consumed per unit of service provided” (p. 4080). Second, the fuel economy indicators, that are “a measure of the fuel consumed per distance travelled” (p. 4080).

Simons et al. 2004 propose the introduction of a new metric that evaluates road freight transport efficiency. In their literature review the authors mention customer -, supply chain - and individual function metrics; as well as company financial performance, company-based operations and segment-based operations as two suitable methods to classify KPIs.

Francia et al. 2011 examine whether the ownership of trunking companies has an impact on profitability. Their journal article classifies indicators into financial and non-financial.

McKinnon & Ge 2004 examined vehicle and route data to search for potential improvements in transport efficiency for grocery distribution. The study differentiates between operational and commercial KPIs. Moreover, the study discusses a classification of metrics by utilization, productivity and effectiveness. Moreover, as already mentioned above when referring to McKinnon 2009, the articles states that KPIs can be organized by vehicle loading, empty running, fuel consumption, vehicle time utilization and deviations from schedule.

Wilding & Juriado 2004 carried out research on customer perceptions on outsourcing decisions. Within the topic they classify cost, service, productivity, asset management, customer satisfaction, employee satisfaction as the major relevant categories to measure performance in transport.

Van Donselaar et al. 1998 identified operational and financial indicators that directly impact financial performance in road freight transport and therefore follow a classification that was also used by McKinnon & Ge 2004. Van Donselaar et al. 1998 also classify the KPIs by long-term financial metrics, operational metrics at company level and operational metrics at segment level.

Graham & Rogers 2013 compared the performance of road transport network types. They differentiate between environmental, economic and social metrics.

Pérez-Martínez 2009 evaluated a survey carried out in Spain on performance in road freight transport. The paper mentions performance indicators that either measure utilization or production or effectiveness.

The Bureau of Industry Economics 1992 classifies road freight performance metrics by customer oriented indicators, operating efficiency indicators and indicators setting out a comparative analysis of vehicle operating costs.

Wang et al. 2008 mention a classification by time, cost, quality and efficiency, contextually following what was also done by Rodrigues et al. 2014, but then replace efficiency with service later on in their journal article.

Van Amster & D’hert 1996 divide performance metrics into output, processes and input as well as internal and external indicators. In addition, they differentiate between transport, warehousing, inventory control and customer service indicators.

Table 5-3 Classification of performance metrics for road freight transport according to reviewed literature (blue indicates that more than one reference mentions the classification)

illustration not visible in this excerpt

5.3.2 Measuring Performance in Road Freight Transport

McKinnon 2009 set up a list of key performance indicators that can be used to execute benchmarking studies in road freight transport. The author mainly addresses indicators that evaluate performance in operations as well as customer service and quality, while the broader areas of cost and finance as well as environmental performance are not or almost not mentioned:

Cost and finance:

- Asset utilization (ratio of capacity used to available capacity)*;
- Output score (turnover divided by costs).

Operations:

- Annual average fuel efficiency;
- Average pallet height;
- Distance the vehicle travels empty*;
- Empty fuel efficiency*;
- Empty running*;
- Fuel consumption by tractor units*;
- Loaded fuel efficiency;
- Payload weight;
- Relative fuel efficiency;
- Space efficiency (ratio of actual number of units carried to the maximum number that could have been carried);
- Time a truck is delayed or otherwise inactive;
- Time a truck is empty and stationary;
- Time a truck is loaded or unloaded;
- Time a truck is preloaded and awaiting departure;
- Time a truck is running on the road but stationary during the daily driver rest-period;
- Time a truck is running on the road;
- Time a truck is undergoing maintenance or repair;
- Utilization;
- Vehicle load factor.

Customer service and quality:

- Customer service;
- Delivery reliability;
- Number of delays due to equipment breakdown or lack of a driver*;
- Number of delays due to own company actions*;
- Number of delays due to problem at collection point*;
- Number of delays due to problem at delivery point*;
- Number of delays due to traffic congestion*;
- Quality of a delivery (measured in adherence to schedule).

Environment and other:

- Fuel consumption*;
- Pallet numbers*;
- Productivity (ratio of outputs to inputs).

[...]

Excerpt out of 270 pages

Details

Title
Measuring Performance in Freight Transport. A Structured Literature Review
College
Vienna University of Economics and Business  (Informationsverarbeitung & Prozessmanagement)
Grade
1
Author
Year
2016
Pages
270
Catalog Number
V373123
ISBN (eBook)
9783668514041
ISBN (Book)
9783668514058
File size
1365 KB
Language
English
Tags
Transport, Performance, Logistik, Performance Management, KPI, Key Performance Indikator, Key Performance Indicator, Metrics, Road, Rail, Sea, Air, Freight, Cargo, Maritime, Formula, Literature Review, Shipping, Supply Chain, Supply Chain Management, Freight transport, Cargo transport, Road freight transport, Rail freight transport, Air freight transport, Maritime freight transport, Performance Measurement, Transportation, Logistics, Straße, Schiene, Luft, See, Fracht, Beförderung, Traffic, Controlling, Passengers, SLR, Structured Literature Review, modes of transport, means of transport, operations, strategy, cost, cost performance, performance monitoring, cost control, revenue, revenue control, services, freight services
Quote paper
Nicolas Eschenbach (Author), 2016, Measuring Performance in Freight Transport. A Structured Literature Review, Munich, GRIN Verlag, https://www.grin.com/document/373123

Comments

  • No comments yet.
Read the ebook
Title: Measuring Performance in Freight Transport. A Structured Literature Review


Upload papers

Your term paper / thesis:

- Publication as eBook and book
- High royalties for the sales
- Completely free - with ISBN
- It only takes five minutes
- Every paper finds readers

Publish now - it's free