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1 Background In recent years, many transit agencies have increased their focus on improving the state of repair of their capital assets, including their vehicles, fixed guideway, passenger facilities, administrative/ maintenance facilities, and supporting systems. Transportation asset management (TAM) is an emerging field that offers a set of tools and approaches for more efficiently and effectively manag- ing physical assets over their lifecycles and helping maintain assets in a state of good repair (SGR). Many transit agencies have put TAM concepts into practice in recent years to help detail their asset inventories, assess asset conditions, and determine investment needs for achieving SGR. Although recent research and implementation efforts have helped advance TAM practice for transit agencies, significant gaps remain with respect to current transit asset management models and approaches. One critical gap is the absence of empirical data linking asset condition and service quality. Addressing this gap is fundamental for demonstrating that implementing comprehensive asset management can help a transit agency improve service quality. In all sec- tors, asset management begins with a needâa reliable, safe, and comfortable trip in a bus, train or ferry; a sustainable and safe source of power; or a continuous supply of clean potable water. All sectors aspiring to implement best practice asset management need to begin by defining the service need that can best be satisfied through the prudent, effective, and efficient management of physical assets. The FTAâs Asset Management Guide (Parsons Brinckerhoff 2012) begins with this definition of transit asset management: A strategic and systematic process through which an organization procures, operates, maintains, rehabilitates, and replaces transit assets to manage their performance, risks and costs over their lifecycle to provide safe, cost effective and reliable service to current and future customers. This research project takes this concept of transit asset management further by explicitly link- ing the quality of service provided by the assets to their condition. Quality of service (QoS) focuses on those aspects of transit service that directly influence how passengers perceive the quality of a particular transit trip. TCRP Report 165: Transit Capacity and Quality of Service Manual (3rd Edition) defines QoS as The overall measured or perceived performance of transit service from the passengerâs point of view (Kittelson & Associates, Inc., et al. 2013). Figure 1-1, illustrating the overall interrelationship of asset condition, service quality, and customer impact, including ridership, shows the following: â¢ As asset condition declines, an asset owner tends to spend more to maintain the asset, and the likelihood of asset breakdown or failure tends to increase. â¢ For customer-facing assets, such as vehicles and passenger facilities that customers inter- act with directly, deteriorated asset conditions may increase total journey time and thereby adversely affect customer perceptions of service quality. C H A P T E R 1 Introduction
2 The Relationship Between Transit Asset Condition and Service Quality â¢ Passengers may add time to their planned journey times in anticipation of delays, thus potentially increasing perceptions of time spent in transit when passengers must contend with deteriorated assets. â¢ Reduced quality of service can be quantified through a QoS metric expressed in terms of either a generalized cost or journey time. â¢ Poor condition contributes to poor service and can result in decreased ridership and/or a modal shift from transit and, in turn, a potentially cascading revenue loss. Although not covered in the approaches presented in this report, this situation is nonetheless an important consideration. Although asset condition as depicted in Figure 1-1 relates primarily to the physical condition of an asset, this concept can be extended to address issues of technological obsolescence. For example, a transit agency may have assets such as fare collection and communications equip- ment that, although in acceptable physical condition, do not meet current functional standards or are not repairable should they fail. Their technological condition effectively results in a reduced level of service, just as in the case of an asset in poor physical condition. In considering the relationship between condition and service quality, it is important to look from the customerâs perspective. Transit offers a serviceâa tripâthat delivers value to the customer. All aspects of the service should be considered, including way-finding, moving through a station or facility, where the customer waits, embarkation, the trip itself, and finally, dis embarkation and movement back to the street. All assetsâcustomer-facing or notâare important as that experience unfolds. The lack of quantitative data linking asset condition to service quality is a barrier to improv- ing transit asset management practice, and indeed, a barrier to maximizing transit performance generally. Research efforts such as those resulting in TCRP Reports 157 and 172 (Spy Pond Partners et al. 2012, Robert et al. 2014a) have demonstrated how lifecycle costs increase when needed asset Figure 1-1. Relationship between asset condition and service quality.
Introduction 3 rehabilitation and replacement actions are deferred. However, outside of a transit agencyâs mainte- nance business unit, potential lifecycle cost impacts can seem less compelling than issues perceived to more directly affect day-to-day service and the customer experience (e.g., improving service fre- quency, fare collection, or real-time information). Thus, despite the fact that asset maintenance and operations are inextricably linked, in many transit agencies the units with responsibility for these areas seem to view themselves in opposition to each other, given the need to compete for limited funds, and so units potentially overlook opportunities to work together to maximize performance. Quantifying the relationship between asset conditions and service quality can help overcome this organizational divide by providing empirical data that agency leaders can use to relate the effects of maintenance on operations and vice versa and, ultimately, better support difficult deci- sions on how best to prioritize capital investments. Research Scope The objective of this research was to provide guidance to transit decisionmakers on the relation- ship between asset condition and transit service quality to support investment prioritization. The guidance is based on empirical evidence and â¢ Incorporates all asset classifications and the condition scale from the FTAâs Asset Management Guide (Parsons Brinckerhof 2012), â¢ Considers characteristics of transit service quality defined in TCRP Report 165, and â¢ Addresses the needs of transit agencies of different sizes and modes. The research described here yields two valuable outcomes for transit agencies: guidance describing how to relate asset condition to service quality that is of immediate value for use in supporting capital investment decisions and identification of gaps and issues in the available data and state-of-the-practice methods that should be addressed moving forward. (Revisions to condition assessment and/or data collection approaches may be required to help address the identified gaps moving forward.) Both outcomes will help transit agencies transition to an increased emphasis on better management of existing transit capital assets and more efficient and effective investment decision-making. The research addresses two different and broad domains: transit asset management and tran- sit service quality. However, given the objective of the research to develop empirical methods, the research team focused specifically on developing a quantitative method for (1) characterizing service quality and (2) showing how this quantitative measure varies with changes in asset con- dition. As a result, this report focuses on the proposed measure of service quality and effective journey time (EJT) and describes a set of spreadsheet tools that can be used to predict changes in EJT as assets deteriorate in condition, or alternatively, following an improvement in condition. This report documents the results of the research. It summarizes the results of the literature review performed at the outset of the research, details the framework for relating asset condition to transit quality of service, and documents a set of case studies performed to test the framework. This report also provides guidance on relating asset condition to service quality, describes the accompanying spreadsheet tool, and identifies gaps in the data available to a transit agency. Report Organization The remainder of this report has the following chapters: â¢ Chapter 2 â Literature Review Summary discusses the results of the review of available litera- ture related to transit quality of service and asset condition.
4 The Relationship Between Transit Asset Condition and Service Quality â¢ Chapter 3 â Framework for Relating Transit Asset Condition and Service Quality outlines the framework and the EJT model developed in this research. â¢ Chapter 4 â Case Studies describes a set of four case studies performed to test the framework presented in Chapter 3. â¢ Chapter 5 â Guidance for Calculating Effects of Changes in Asset Condition on Transit Service Quality describes the basic steps for calculating the effects of changes in asset condi- tion on transit service quality. â¢ Chapter 6 â Using the EJT Calculation Tools documents two spreadsheet tools for use in cal- culating EJT using either a comprehensive or simplified approach. This chapter also presents a set of worked examples illustrating use of the tools. â¢ Chapter 7 â Gap Assessment discusses the gaps in available data and business practices that may limit the use of the condition/service quality guidance. â¢ Chapter 8 â Conclusions summarizes the findings of the research and recommends areas for further research. Appendices provide supporting information on the research: â¢ Appendix A is a list of acronyms and abbreviations. â¢ Appendix B details the formulation of the EJT model presented in Chapter 3. â¢ Appendix C provides additional details on the case studies. â¢ Appendix D summarizes the project workshop conducted in August 2017.