Service Improvement Research Articles

Using an organizational change model to improve lung cancer surgery services over five years.

Lung cancer is the most common cause of cancer death in the UK resulting in 21% of all cancer deaths. In 2016, local lung cancer surgery services required improvement due to under-representation in cancer resections and resource scarcity during the pandemic, which affected critical care bed availability and extended postoperative stays. The aim of this service improvement was to increase the number of lung cancer resection; develop minimally invasive techniques and reduce the use of Critical Care Unit beds by 35% (a subsequent goal). A five-year plan, guided by Kotter's 8-step change model, was initiated to address these issues. This model promotes sustainable change by setting clear goals, effective communication, and stakeholder involvement. Initial changes included hiring a thoracic surgeon experienced in uniportal video assisted thoracoscopy and enhanced recovery protocols. The team grew to three thoracic surgeons by 2020. The service increased operating theatre days and adopted new postoperative practices to reduce complications and hospital stays. Lung Cancer Multidisciplinary Team Meetings were consistently covered by thoracic surgeons, ensuring comprehensive care. Data on surgical activity were collected from departmental databases and national audits, with internal audits conducted regularly. Statistical significance was tested using chi-square tests with P values <0.05. The number of surgical procedures more than doubled, with primary lung cancer resections increasing nearly three-fold from 12.8% to 29.8% over six years. Postoperative complications and mortality rates remained low. Critical care bed usage dropped significantly during the pandemic, with new protocols enabling safe recovery in general surgical areas. The successful expansion of thoracic surgical services was attributed to the dedicated minimally invasive surgeons, enhanced recovery measures, and skilled staff. The change model facilitated efficient and dynamic progress. With the introduction of lung cancer screening programs, the demand for surgical services is expected to rise. The effective change model will be re-applied to meet this demand. The organizational change model, focused on patients and staff, achieved sustained quality improvement in lung cancer care despite challenging conditions like the coronavirus disease 2019 pandemic.

Optimizing Postpartum Depression Prevention in Primary Health Care Services

Post-partum depression (PPD) is a post-natal disorder that not only impacts the mental health of the mother but also has long-term effects on the development and well-being of the child and family. PPD is a preventable disorder, starting from interventions at primary health care facilities. As one of the developing countries with a PPD incidence of 22% per 100,000 births, PPD is considered an urgent public health issue in Indonesia. In practice, evaluation, and improvement of services at primary health care facilities are needed. This study aims to identify and adapt international intervention strategies to reduce post-partum depression prevalence in Indonesian primary health care. A scoping review analysis method was used, involving previous studies on activities from pregnancy to post-partum that can prevent and reduce post-partum depression. The reviewed articles employed Randomized Controlled Trials or Randomized Clinical Trials (RCT) methods with specific inclusion and exclusion criteria. Data were collected from relevant sources, and a synthesis was conducted on 16 articles that met the inclusion criteria. The results show that direct psychological support activities (through health professionals or groups) and indirect support using digital platforms and applications are effective in reducing depression. Strategies such as digital technology, direct support programs, physical therapy, pharmacological therapy, community involvement, and strengthening health services, particularly post-partum psychological counseling, are recommended to enhance prevention. This research supports the expansion of evidence-based strategies that can be implemented in primary healthcare facilities to address post-partum depression.

Health professional regulation and provision of quality health services; cross sectional analysis of private health care providers in Wajir County, Kenya

Background: Health professional regulatory bodies oversee and enforce standards in healthcare to safeguard patient safety and prevent harm. However, international consistency in these regulations remains limited. The Kenya health sector relies on various bodies to enforce standards among professionals and institutions, albeit constrained by financial and human resources that hinder effective oversight. This study aimed to assess how regulatory practices- such as licensing, training oversight, inspection of practice, and quality assurance mechanisms- affect the quality of healthcare provided by private providers. Methods: The study targeted 108 healthcare providers from 36 private health facilities, primarily nurses and clinical officers. A sample of 86 participants was drawn using purposive sampling. The data were collected using a structured questionnaire. Results: The licensing of health professionals, training, inspection of practice, and quality assurance mechanisms collectively influenced 47.9% of the variation in service quality. Statistical analysis revealed significant associations between licensing (p=0.003), practice inspections (p=0.01), quality assurance (p=0.001), and service quality. Conclusions: Regulatory bodies play a crucial role in ensuring healthcare standards; however, their effectiveness hinges on tailored strategies that address local challenges and foster collaborative efforts towards sustainable quality improvement in healthcare services. Routine inspections, conducted in a supportive manner, are likely to ensure ongoing adherence to standards. Moreover, adequate resource allocation for regulatory compliance and continuous quality improvement activities, including the formation of internal quality improvement (QI) teams and the maintenance of regular QI meetings and assessments, was deemed essential.

A review on quality management system in laboratory testing

A Laboratory Quality Management System (LQMS) refers to a set of policies, procedures, and practices implemented in a laboratory to ensure consistent quality and accuracy in its operations. Continuous improvement of laboratory quality service is vital to ensure accuracy, reliability, and timeliness of laboratory results. Implementation of the quality management system is an effective way of monitoring and assuring laboratory quality service. Various standards and regulations outline specific requirements for implementing a Quality Management System (QMS) in a laboratory environment, such as ISO 15189:2022, ISO 17025:2017, and FDA 42 CFR Part 493. These standards provide guidelines and criteria for laboratory processes, including testing, calibration, documentation, personnel competency, and overall quality control. This article will discuss the applicable standards and legislation, the 12 essential elements of laboratory QMS, and the role of QMS software in a laboratory environment. The objective of this study is to assess the impact of laboratory quality management system implementation on improving quality laboratory service.

LEVERAGING INFORMATION TECHNOLOGY FOR ENHANCED GOVERNMENT SERVICE EFFICIENCY IN LINGGA REGENCY

This study investigates the impact of information technology on the effectiveness of government services in Lingga Regency, focusing on the role of technological infrastructure, information technology usage, and government policy support. A quantitative approach was employed, using total sampling with 30 employees from the North Lingga District Office as respondents. Data were analyzed using Smart PLS to test the relationships between variables. The results show that both the quality of technological infrastructure and the use of information technology have a significant positive effect on the effectiveness of government services. Furthermore, government policy support was found to moderate the relationship between infrastructure quality and service effectiveness, enhancing the impact of infrastructure investments on public service delivery. However, the moderating effect of policy support on the use of IT was weaker, indicating that IT can directly improve service effectiveness without extensive policy intervention. These findings highlight the importance of investing in both infrastructure and IT, while also developing supportive policies to sustain long-term improvements in government services. This research provides practical insights for policymakers and government officials in optimizing public administration through strategic technology integration.

Continuous Service Improvement in IT Operations through Predictive Analytics

In the evolving landscape of IT operations, continuous service improvement is essential for maintaining high performance, reliability, and customer satisfaction. Predictive analytics, leveraging advanced data analysis techniques and machine learning algorithms, offers a transformative approach to enhancing IT service management. This research paper explores the integration of predictive analytics into IT operations to drive continuous service improvement. It investigates how predictive models can forecast potential issues, optimize resource allocation, and enhance decision-making processes, ultimately leading to improved operational efficiency and service quality. The study begins with an overview of traditional IT service management practices and the limitations they face in adapting to dynamic and complex IT environments. Conventional approaches often rely on reactive problem-solving and periodic reviews, which can lead to inefficiencies and missed opportunities for proactive intervention. Predictive analytics offers a paradigm shift by utilizing historical data and real-time information to predict future outcomes, enabling organizations to address potential problems before they impact operations.

Business Models of Public Smart Services for Sustainable Development

The smart city concept has entered the public debate over the last decade as a concept for the development of urban space for the efficiency, improvement and availability of public and private services and sustainability. The Business Models Canvas is most often used in the literature for the creation of business models of smart services. On the basis of the above, we investigated whether the Business Models Canvas is the most used tool for creating business models for public smart services in Slovakia and whether cities and municipalities need to evaluate their models for the provision of public smart services. However, there is no commonly used methodology for evaluating smart city business models to help both practitioners and researchers choose the best option. The goal of the research is to create a tool for evaluating business models of public smart services in smart cities. The base method used was the Delphi method, based on the previous primary (content) analysis process of the Business Model Canvas best practices. In total, 709 towns and villages participated in the primary research. Subsequently, the obtained data were evaluated and used for further research using the Delphi method, in which 28 experts participated. The research was carried out between 2020 and 2023 in Slovakia. Primary research confirmed that the Business Models Canvas is the most used tool for creating business models for public smart services in Slovakia and cities and municipalities need to evaluate their models for the provision of public smart services. Areas and basic building blocks were also identified for the design of the evaluation methodology of business models for public smart services. The proposal of the methodology for evaluating business smodels for public smart services in Slovakia was implemented using the Delphi method with the cooperation of 28 experts. Based on the results of the Delphi method, a methodological procedure for evaluating business models for public smart services was established. The methodology proposed in the paper is a simple, organized, flexible and transparent system that facilitates the work of evaluators of business models of public smart services and marketing.

Landscape ecological risk evaluation coupled with ecosystem service improvement and its spatial heterogeneity analysis: a case study of the Yellow River Source Area

The ecological environment of the Yellow River Source Area (YRSA) is crucial to the Qinghai-Tibet Plateau, and its ecological risk management is important for the ecological protection and sustainable development of the Qinghai-Tibet Plateau. this study improves the traditional evaluation method of landscape ecological risk(LER) based on ecosystem services and detects its spatial heterogeneity by using Geodetector. The study results are as follows: (1) The temporal distribution of LER in the YRSA is similar to its landscape vulnerability. In the past 20 years, the areas of its high, medium-high, medium, and medium-low ecological risk areas have been converted to low ecological risk areas to varying degrees. (2) Overall, the spatial difference in LER in the YRSA is significant, mainly dominated by HH and HL clustering. Meanwhile, the Moran’I index of the LER Index decreases year by year, indicating that the spatial aggregation of the LER decreases and the spatial autocorrelation weakens year by year. (3) Climatic factors have the most significant influence on the ecological risk of the landscape in the YRSA, followed by topographic factors and anthropogenic factors.

Scenario-Based Analysis of High-End New Energy Vehicle User Demands

With the rise in global environmental awareness and the rapid development of new energy technologies, high-end new energy vehicles (NEV) have become an important direction for the automotive industry. Consumer demand is evolving from merely seeking a means of transportation to desiring a comprehensive experience across various scenarios, emphasizing high quality, high performance, and environmental friendliness. Understanding the characteristics and trends of high-end NEV users' demands is crucial for car manufacturers in formulating market strategies, product design, and service improvement. However, current focus is often on policies and product design, lacking analysis of actual usage scenarios. To address this gap, this article employs scenario research methods to delve into the needs of high-end NEV users, selecting typical scenarios such as urban commuting, long-distance travel, and business operations. The research indicates that high-end NEV users are primarily young, highly educated, middle-to-high income individuals who exhibit rational consumption habits. Their most common usage scenarios include commuting to work, transporting family members, and shopping. In these contexts, there is a pronounced demand for vehicle safety performance, ride comfort, and intelligent features, each showing differentiated characteristics across various user groups. For instance, female users demonstrate a particularly strong preference for comfort-related configurations, whereas married users with children have the highest demand for spacious and convenient features. Based on these insights, this paper offers targeted recommendations from the perspectives of product design and marketing.

The analysis of the stock of the Republican scientific-technical library

Nowadays, the investigation of the questions of the scientific management of library stocks has gained great urgency (increased in importance). The tasks of increasing the efficiency of the formation and usage of library stocks highlight the necessity for systematic research into their peculiarities and tendencies of development. This article analyzes the peculiarities and tendencies of the development of the stocks of the Republican Scientific-Technical Library of Lithuania's Scientific-Research Institute of Scientific-Technical Information and Technical-Economic Research. The multifaceted research of the stocks should enable the improvement of library processes and information-bibliography services. The research carried out allows for the following conclusions: The Republican Scientific-Technical Library, by volume of stocks, is the largest library among scientific libraries of the republic. Its stocks total 40.4 percent of the whole stock of the United Republican Information Stock (URIS). The library is the main library in URIS, which organizes the stocks of special documentation and literature. A peculiarity of the stock is that special technical documentation and literature have predominated in the stock since 1970, totaling approximately 90.1 percent of the entire stock. The basic stocks are in the Republican Scientific-Technical Library in Vilnius, which total 87.6 percent of the entire stock. The superextensive growth of the special technical documentation and literature during 1967-1970 is accounted for by the organization of the departments of patents and technical documentation (as per the decision of the Council of Ministers of Lithuania). At present, the growth of the stock has stabilized. Every year during 1975-1982, the library received an average of 850.2 thousand documents. The growth of the quantity of the stocks, completion on the whole, and the growth of the stocks of special kinds of scientific-technical literature and documentation may be defined by a mathematical curve, which shows that from a certain moment, the speed of the growth of the volume of the stocks slows down due to limited resources.

A Situational Overview of Prenatal Screening Services in Bhutan

ABSTRACTPrenatal genetic testing is to determine the possibility of the fetus having a genetic aberration or birth defect. Prenatal screening consists of serum analytes screening with or without nuchal translucency (NT) scanning or with cell‐free DNA (CfDNA) screening. Prenatal screening is recommended for all pregnant women regardless of the duration of pregnancy and maternal age or baseline risk. It is not advisable to screen with serum analytes and CfDNA concurrently to avoid discordant results. In developed countries, prenatal testing has been a part of routine antenatal care for a long time with adopting newer methods of screening and testing. In Bhutan, since the integration of the Safe Motherhood Program into primary healthcare in 1994, there has been an unprecedented improvement in obstetric care services. Almost all pregnant women attend antenatal and postnatal care, and 98.5% of deliveries are attended by trained health workers. The maternal mortality has reduced to 53 in 2023 from 770 per 100,000 live births in 1984 and the neonatal dealth has reduced to 15.2 per 1000 live births in 2023. However, despite improvements in the care of pregnant women, many babies are detected with congenital anomalies, syndromes, and birth defects during the postnatal period. Bhutan, being an underdeveloped country, could not initiate any form of prenatal testing program except for the anatomical scanning performed at 18–22 weeks of gestation. Early ultrasound dating scans, limited anomaly scanning, and growth scanning are offered to all pregnant women. There is a need to start centralized prenatal testing services in Bhutan to provide a comprehensive package of obstetric care to pregnant women. In addition, legal rights for parents to terminate severely deformed fetuses or severe genetic diseases before 24 weeks of pregnancy need to be established.

Development of a Utility Vehicle Express System Framework Using Design Thinking Process for the Province of Albay

Utility vehicle express or locally known as UV Express is a key mode of transportation in Albay, Philippines, offers cost-effective connectivity between urban and suburban areas. Composed of vans operating point-to-point from terminals, it serves routes connecting Legazpi with surrounding municipalities like Tabaco, Ligao, and Polangui. Its affordability and efficiency cater to students and workers, supporting both educational and economic activities. However, challenges such as overcrowding, long waits, and inconsistent scheduling persist, highlighting the need for service improvements. This study aims to address these issues through design thinking process that includes identifying the issues and tracing its root causes through 5 Why Analysis. A proposed framework is developed to modernize UV Express operations by replacing manual processes with digital solutions like a Booking System, GPS tracking, and passenger feedback integrated into a mobile app. This initiative enhances operational efficiency, aligns services with evolving transportation trends, and fosters competitiveness. Moreover, it prepares UV Express for further advancements, including usability assessments through pilot testing of the mobile application in Albay.

Analisis Kausalitas antara Kualitas Produk, Kualitas Pelayanan, dan Loyalitas Pelanggan di PT. FIFGROUP

In the digital era, FIFGROUP must meet customer expectations with fast service. This study analyzes the impact of service complaints on customer loyalty using Smart PLS and Fishbone Diagram for identifying key factors. The research employs a quantitative design with a survey approach to assess the impact of product and service quality on Spektra customer loyalty at FIFGROUP. Utilizing a sample of 100 respondents from Kranggan Cibubur, the study gathers in-depth data through questionnaires and observations. The research procedure involves a two-way model to analyze variable relationships, validity, reliability, and mediation effects, with Fishbone Diagram for identifying and prioritizing main problem causes at FIFGROUP. Improvement in product quality (coefficient 0.261; T-statistic 2.902) and service (coefficient 0.206; T-statistic 2.070) at Spektra FIFGROUP significantly enhances customer loyalty. Resource optimization and service digitalization are crucial for long-term effectiveness.

Progressive improvement in time to diagnosis in axial spondyloarthritis through an integrated referral and education system.

To assess the delay in the diagnosis of axial SpA (axSpA) in a real-world cohort over a 16-year period and to evaluate factors associated with this delay. We implemented a service improvement project and evaluated its effectiveness in improving time to diagnosis of axSpA. A cohort of axSpA patients newly diagnosed between January 2008 and December 2023 were studied. Surveys were carried out in 2013, 2017, 2019 and 2023 to assess time to diagnosis, which was divided into four periods from onset of inflammatory back pain to year of axSpA diagnosis. The time to diagnosis over the study period was analysed using a statistical process control chart. Over the study period, 988 referrals were received and 366 (37%) had axSpA. There was a progressive increase in the number of females with axSpA. The mean time to diagnosis significantly decreased from 9.8 years (s.d. 1.2) in 2008 to 1.0 years (s.d. 1.0) in 2023. The greatest delay was from the onset of back pain to first seeing their general practitioners (GPs; mean 3.2 years). There was a significant improvement in the mean time to diagnosis across the time periods through the service improvement interventions. Structural and organizational change in triage, referral and clinic pathways has led to earlier recognition of axSpA. This is further enhanced through an integrated education program and awareness campaign for the public, GPs and healthcare professionals, including physiotherapists. With continuous quality improvement cycles, we achieved our aim of reducing the mean time to diagnosis to 1 year.

Sustainable Resource Allocation and Base Station Optimization Using Hybrid Deep Learning Models in 6G Wireless Networks

Researchers are currently exploring the anticipated sixth-generation (6G) wireless communication network, poised to deliver minimal latency, reduced power consumption, extensive coverage, high-level security, cost-effectiveness, and sustainability. Quality of Service (QoS) improvements can be attained through effective resource management facilitated by Artificial Intelligence (AI) and Machine Learning (ML) techniques. This paper proposes two models for enhancing QoS through efficient and sustainable resource allocation and optimization of base stations. The first model, a Hybrid Quantum Deep Learning approach, incorporates Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs). CNNs handle resource allocation, network reconfiguration, and slice aggregation tasks, while RNNs are employed for functions like load balancing and error detection. The second model introduces a novel neural network named the Base Station Optimizer net. This network includes various parameters as input and output information about the condition of the base station within the network. Node coverage, number of users, node count and user locations, operating frequency, etc., are different parametric inputs considered for evaluation, providing a binary decision (ON or SLEEP) for each base station. A dynamic allocation strategy aims for network lifetime maximization, ensuring sustainable operations and power consumption are minimized across the network by 2 dB. The QoS performance of the Hybrid Quantum Deep Learning model is evaluated for many devices based on slice characteristics and congestion scenarios to attain an impressive overall accuracy of 98%.

Passenger Service Satisfaction Evaluation of Jakarta-Bandung High-Speed Railway

As competition in the passenger transportation industry intensifies, high-speed railway must continuously improve service quality to win passenger satisfaction and secure a place in the competitive market. The Jakarta- Bandung High-Speed Railway (JBHSR), Indonesia’s and Southeast Asia’s first high-speed rail, commenced operation in October 2023. This study aims to identify areas for service improvement by measuring and evaluating passenger satisfaction and proposing optimization suggestions. Combining domestic and international service quality evaluation schemes and customer satisfaction models, this study employs the Analytic Hierarchy Process (AHP) to construct a passenger satisfaction evaluation system for high-speed rail services from three dimensions: perceived quality, expected value, and perceived value. A passenger satisfaction survey was conducted, and the results were analyzed using AHP and Fuzzy Comprehensive Evaluation (FCE) methods to calculate satisfaction scores. The Importance-Performance Analysis (IPA) revealed that aspects such as ease of ticket purchasing, accuracy of train operation information, and punctuality scored highly in terms of satisfaction. However, items categorized under ‘Concentrate Here’ and ‘Low Priority’ quadrants require further optimization. This study benchmarks successful practices from other countries’ HSR systems and proposes specific improvement measures, including installing free Wi-Fi at stations and on trains, expanding parking capacity with an online reservation system, increasing the number of escalators and elevators at Padalarang Station, and installing electronic displays and enhancing ground signage for better visibility of carriage positions. These measures aim to improve the quality of HSR services and enhance passenger satisfaction.

The impact of Project Management Offices on organizational performance: a comprehensive review of the literature

In today's dynamic environment, information technology (IT) stands as the cornerstone for organizational success and competitive advantage, with project management playing a crucial role in efficiently deploying IT resources. Recognized across diverse sectors like telecommunications, aerospace, and construction, Project Management Offices (PMOs) facilitate task organization and supervision, whether it is for IT product development, service improvement, system design, or implementing organizational changes. Despite extensive research on the positive impact of PMOs on organizational performance, a significant research gap exists due to the absence of a direct comparison between the influence of PMOs on IT and non-IT industries, indicating the necessity for further investigation in this domain. This study delves into the contribution of PMOs to organizational performance using the Competing Values Framework and evaluates five models and 17 performance metrics within the IT industry and across sectors. When comparing PMO performance, non-IT sectors precede interpersonal relationships, competency-based training, and workplace environment, whereas IT sectors emphasize the knowledge of PMO resource teams, efficient training, technology utilization, and collaboration for project success. Additionally, IT industries underline the role of technology in averting project management failures and prioritizing the punctual delivery of client requirements. These differences highlight the variations in PMO priorities between these industries, underscoring the significance of PMOs in enhancing organizational performance.

Exploring Tourist Experience through Online Reviews Using Aspect-Based Sentiment Analysis with Zero-Shot Learning for Hospitality Service Enhancement

Hospitality services play a crucial role in shaping tourist satisfaction and revisiting intention toward destinations. Traditional feedback methods like surveys often fail to capture the nuanced and real-time experiences of tourists. Digital platforms such as TripAdvisor, Yelp, and Google Reviews provide a rich source of user-generated content, but the sheer volume of reviews makes manual analysis impractical. This study proposes integrating aspect-based sentiment analysis with zero-shot learning to analyze online tourist reviews effectively without requiring extensive annotated datasets. Using pretrained models like RoBERTa, the research framework involves keyword extraction, sentence segment detection, aspect construction, and sentiment polarity measurement. The dataset, sourced from TripAdvisor reviews of attractions, hotels, and restaurants in Central Java, Indonesia, underwent preprocessing to ensure suitability for analysis. The results highlight the importance of aspects such as food, accommodation, and cultural experiences in tourist satisfaction. The findings indicate a need for continuous service improvement to meet evolving tourist expectations, demonstrating the potential of advanced natural language processing techniques in enhancing hospitality services and customer satisfaction.

Peri-urban agriculture and household food and nutrition security around Eldoret, Kenya

Rapid urbanisation in low- and middle-income countries, which has encroached on agricultural lands but has not been consistently accompanied by corresponding improvements in water and sanitation services, has raised questions about its impact on the food and nutrition security of households living in transitional, peri-urban areas. Through an analysis of survey data collected from 518 households living around the town of Eldoret, Kenya, we investigate the existing links between peri-urban households’ engagement in agriculture, their dietary behaviour, and their children’s nutrition outcomes. We find that peri-urban households engaged in agriculture, particularly in crop growing and in the sales of their agricultural produce, have more diverse and nutritious diets than agriculturally non-engaged households, all other things being equal. However, a significant improvement in children’s health outcomes is observed in these households only when coupled with improved water, sanitation, and hygiene conditions.

Disparities in public transport accessibility in London from 2011 to 2021

Addressing urban inequalities has become a pressing concern on both the global sustainable development agenda and for local policy. Improving public transport services is seen as an important area where local governments can exert influence and potentially help reduce inequalities. Existing measures of accessibility used to inform decision-making for public transport infrastructure in London show spatial disparities, yet there is a gap in understanding how these disparities vary across demographic groups and how they evolve over time—whether they are improving or worsening. In this study, we investigate the distribution of public transport accessibility based on ethnicity and income deprivation in London over the past decade. We used data from the Census 2011 and 2021 for area-level ethnicity characteristics, English Indices of Deprivation for income deprivation in 2011 and 2019, and public transport accessibility metrics from Transport for London for 2010 and 2023, all at the small area level using lower super output areas (LSOAs) in Greater London. We found that, on average, public transport accessibility in London has increased over the past decade, with 78% of LSOAs experiencing improvements. Public transport accessibility in London showed an unequal distribution in cross-sectional analyses. Lower income neighbourhoods had poorer accessibility to public transportation in 2011 and 2023 after controlling for car-ownership and population density. These disparities were particularly pronounced for underground accessibility. Temporal analyses revealed that existing inequalities with respect to income deprivation and ethnicity are generally not improving. While wealthier groups benefited most from London Underground service improvements; lower income groups benefited more from bus service improvements. We also found that car ownership levels declined in areas with substantial increases to public transport accessibility and major housing developments, but not in those with moderate improvements.