Transit route occupancy load factor and passenger average travel time for quality of service assessment

This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Transit route occupancy load factor and passenger average travel time for quality of service assessment

This presentation investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Stochastic analysis of transit route segments' passenger load variation for capacity and quality of service assessment

This paper investigates stochastic analysis of transit segment hourly passenger load factor variation for transit capacity and quality of service (QoS) analysis using Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia. It compares stochastic analysis to traditional peak hour factor (PHF) analysis to gain further insight into variability of transit route segments’ passenger loading during a study hour. It demonstrates that hourly design load factor is a useful method of modeling a route segment’s capacity and QoS time history across the study weekday. This analysis method is readily adaptable to different passenger load standards by adjusting design percentile, reflecting either a more relaxed or more stringent condition. This paper also considers hourly coefficient of variation of load factor as a capacity and QoS assessment measure, in particular through its relationships with hourly average and design load factors. Smaller value reflects uniform passenger loading, which is generally indicative of well dispersed passenger boarding demands and good schedule maintenance. Conversely, higher value may be indicative of pulsed or uneven passenger boarding demands, poor schedule maintenance, and/or bus bunching. An assessment table based on hourly coefficient of variation of load factor is developed and applied to this case study. Inferences are drawn for a selection of study hours across the weekday studied.

Stochastic analysis of transit route segments' passenger load variation for capacity & quality of service assessment

This study uses weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia •Stochastic analysis is compared to peak hour factor (PHF) analysis for insight into passenger loading variability •Hourly design load factor (e.g. 88th percentile) is found to be a useful method of modeling a segment’s passenger demand time-history across a study weekday, for capacity and QoS assessment •Hourly coefficient of variation of load factor is found to be a useful QoS and operational assessment measure, particularly through its relationship with hourly average load factor, and with design load factor •An assessment table based on hourly coefficient of variation of load factor is developed from the case study

Refactoring Service Interface to Support Artefact-centric Service interaction

The growth of APIs and Web services on the Internet, especially through larger enterprise systems increasingly being leveraged for Cloud and software-as-a-service opportunities, poses challenges for improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operations having multiple data entities and parameter sets, supporting varying requests, and reflecting versioning across different system releases, compared to fine-grained operations of contemporary interfaces. We propose a technique to support the refactoring of service interfaces by deriving business entities and their relationships. In this paper, we focus on the behavioural aspects of service interfaces, aiming to discover the sequential dependencies of operations (otherwise known as protocol extraction) based on the entities and relationships derived. Specifically, we propose heuristics according to these relationships, and in turn, deriving permissible orders in which operations are invoked. As a result of this, service operations can be refactored on business entity CRUD lines, with explicit behavioural protocols as part of an interface definition. This supports flexible service discovery, composition and integration. A prototypical implementation and analysis of existing Web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms proposed through the paper.

An empirical analysis of the factors and measures of Enterprise Architecture Management success

Enterprise Architecture Management (EAM) is discussed in academia and industry as a vehicle to guide IT implementations, alignment, compliance assessment, or technology management. Still, a lack of knowledge prevails about how EAM can be successfully used, and how positive impact can be realized from EAM. To determine these factors, we identify EAM success factors and measures through literature reviews and exploratory interviews and propose a theoretical model that explains key factors and measures of EAM success. We test our model with data collected from a cross-sectional survey of 133 EAM practitioners. The results confirm the existence of an impact of four distinct EAM success factors, ‘EAM product quality’, ‘EAM infrastructure quality’, ‘EAM service delivery quality’, and ‘EAM organizational anchoring’, and two important EAM success measures, ‘intentions to use EAM’ and ‘Organizational and Project Benefits’ in a confirmatory analysis of the model. We found the construct ‘EAM organizational anchoring’ to be a core focal concept that mediated the effect of success factors such as ‘EAM infrastructure quality’ and ‘EAM service quality’ on the success measures. We also found that ‘EAM satisfaction’ was irrelevant to determining or measuring success. We discuss implications for theory and EAM practice.

Introduction to the Proceedings of the Workshop on User-Focused Service Engineering, Consumption and Aggregation (USECA) 2011

The first User-Focused Service Engineering, Consumption and Aggregation workshop (USECA) in 2011 was held in conjunction with the WISE 2011 conference in Sydney, Australia. Web services and related technology are a widely accepted standard architectural paradigm for application development. The idea of reusing existing software components to build new applications has been well documented and supported for the world of enterprise computing and professional developers. However, this powerful idea has not been transferred to end-users who have limited or no computing knowledge. The current methodologies, models, languages and tools developed for Web service composition are suited to IT professionals and people with years of training in computing technologies. It is still hard to imagine any of these technologies being used by business professionals, as opposed to computing professionals. © 2013 Springer-Verlag.

A service-oriented architecture for text analytics enabled business applications

Experiences showed that developing business applications that base on text analysis normally requires a lot of time and expertise in the field of computer linguistics. Several approaches of integrating text analysis systems with business applications have been proposed, but so far there has been no coordinated approach which would enable building scalable and flexible applications of text analysis in enterprise scenarios. In this paper, a service-oriented architecture for text processing applications in the business domain is introduced. It comprises various groups of processing components and knowledge resources. The architecture, created as a result of our experiences with building natural language processing applications in business scenarios, allows for the reuse of text analysis and other components, and facilitates the development of business applications. We verify our approach by showing how the proposed architecture can be applied to create a text analytics enabled business application that addresses a concrete business scenario. © 2010 IEEE.

Leveraging of software as a service by small and medium enterprises: Information systems capabilities and organisational complementarities

This research explored how small and medium enterprises can achieve success with software as a service (SaaS) applications from cloud. Based upon an empirical investigation of six growth oriented and early technology adopting small and medium enterprises, this study proposes a SaaS for small and medium enterprise success model with two approaches: one for basic and one for advanced benefits. The basic model explains the effective use of SaaS for achieving informational and transactional benefits. The advanced model explains the enhanced use of software as a service for achieving strategic and transformational benefits. Both models explicate the information systems capabilities and organizational complementarities needed for achieving success with SaaS.

Assessment of transit quality of service with occupancy load factor and passenger travel time measures

This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Measuring route passenger load diversity for capacity and quality of service assessment

This paper develops theory that quantifies transit route passenger-relative load factor and distinguishes it from occupancy load factor. The ratio between these measures is defined as the load diversity coefficient, which as a single measure characterizes the diversity of passenger load factor between route segments according to the origin-destination profile. The relationship between load diversity coefficient and route coefficient of variation in occupancy load factor is quantified. Two tables are provided that enhance passenger capacity and quality of service (QoS) assessment regarding onboard passenger load. The first expresses the transit operator’s perspective of load diversity and the passengers’ perspective of load factor relative to the operator’s, across six service levels corresponding to ranges of coefficient of variation in occupancy load factor. The second interprets the relationships between passenger average travel time and each of passenger-relative load factor and occupancy load factor. The application of this methodology is illustrated using a case study of a premium radial bus route in Brisbane, Australia. The methodology can assist in benchmarking and decision making regarding route and schedule design. Future research will apply value of time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent aboard. This would also assist in transit service quality econometric modeling.

Measuring route passenger load diversity for capacity and quality of service assessment

This poster introduces Passenger Relative Load Factor for a route or individual bus service as a capacity and quality of service measure, distinguishing it from Occupancy Load Factor. It introduces Load Diversity Coefficient as the ratio of Passenger Relative Load Factor to Occupancy Load Factor, and relates Load Diversity Coefficient to Coefficient of Variation in Occupancy Load Factor. It qualifies the operator’s and passengers’ perspectives of load factor based on Coefficient of Variation in Occupancy Load Factor along a route. A case study using weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia illustrates the methodology. The compendium paper also qualifies the operator’s and passengers’ perspectives of these load factors along with Passengers’ Average Travel Time for capacity and quality of service assessment.

Investigating variation in bus ridership rates within localised areas of a sub-tropical city

This thesis makes a significant contribution to knowledge and understanding of 'Human Travel Behaviour' in relation to transportation research. It holds some important merits that have not been proposed before. It develops a new, comprehensive and meaningful relationship that includes bus transit ridership change due to weather variables, seasonality and transit quality of service within a single daily ridership rate estimation model. The research incorporated both temporal and spatial influences on ridership within a modelling structure, named as the Nested Model Structure. It provides a complete picture of ridership variation across the sub-tropical city of Brisbane, Australia.

Toward Self-Organising Service Communities

This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.).