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This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.

The purpose of this study was to explore how transport companies in Uganda execute strategies in a turbulent business environment.

The study adopted an exploratory qualitative methodology using the data collected through an open-ended instrument. Utilizing the qualitative data analysis software QSR NVivo9, the data were analyzed following the Gioia's methodology. Verbatim texts were used to explain the emergent themes.

The study's findings show that to successfully execute strategies, companies in Uganda communicate, coordinate and put control systems in their operations. The activities undertaken include customer care, timely settlement of complaints, comfortable seats, playing local music, partnerships with reliable fuel stations, setting up strategic offices, cost management, use of experienced drivers, sub-renting vehicles and inspections.

The study produces a pioneering result of how transport companies execute strategies in a turbulent business environment, an aspect that has not been adequately highlighted in previous studies.

Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide insights into patients' perceptions of satisfaction, experience and self-reported outcomes. However, little attention has been devoted to questions about factors fostering the use of patient-reported information to create value at the system level.

Action research design is carried out to elicit possible triggers using the case of patient-reported experience and outcome data for breast cancer women along their clinical pathway in the clinical breast network of Tuscany (Italy).

The case shows that communication and engagement of multi-stakeholder representation are needed for making information actionable in a multi-level, multispecialty care pathway organized in a clinical network; moreover, political and managerial support from higher level governance is a stimulus for legitimizing the use for quality improvement. At the organizational level, an external facilitator disclosing and discussing real-world uses of collected data is a trigger to link measures to action. Also, clinical champion(s) and clear goals are key success factors. Nonetheless, resource munificent and dedicated information support tools together with education and learning routines are enabling factors.

Current literature focuses on key factors that impact performance information use often considering unidimensional performance and internal sources of information. The use of patient/user-reported information is not yet well-studied especially in supporting quality improvement in multi-stakeholder governance. The work appears relevant for the implications it carries, especially for policymakers and public sector managers when confronting the gap in patient-reported measures for quality improvement.

With more cities aiming to achieve climate neutrality, identifying the funding to support these plans is essential. The purpose of this paper is to exploit the present of a structured green bonds framework in Sweden to investigate the typology of abatement projects Swedish municipalities invested in and understand their effectiveness.

Marginal abatement cost curves of the green bond measures are constructed by using the financial and abatement data provided by municipalities on an annual basis.

The results highlight the economic competitiveness of clean energy production, measured in abatement potential per unit of currency, even when compared to other emerging technologies that have attracted the interest of policymakers. A comparison with previous studies on the cost efficiency of carbon capture storage reveals that clean energy projects, especially wind energy production, can contribute to the reduction of emissions in a more efficient way. The Swedish carbon tax is a good incentive tool for investments in clean energy projects.

The improvement concerning previous applications is twofold: the authors expand the financial considerations to include the whole life-cycle costs, and the authors consider all the greenhouse gases. This research constitutes a prime in using financial and environmental data produced by local governments to assess the effectiveness of their environmental measures.

The purpose of this paper is to provide a guiding framework for studying the travel patterns of PT users. The combination of public transit (PT) users’ travel data and user profiling (UP) technology to draw a portrait of PT users can effectively understand users’ travel patterns, which is important to help optimize the scheduling of PT operations and planning of the network.

To achieve the purpose, the paper presents a three-level classification method to construct the labeling framework. A station area attribute mining method based on the term frequency-inverse document frequency weighting algorithm is proposed to determine the point of interest attributes of user travel stations, and the spatial correlation patterns of user travel stations are calculated by Moran’s Index. User travel feature labels are extracted from travel data containing Beijing PT data for one consecutive week.

In this paper, a universal PT user labeling system is obtained and some related methods are conducted including four categories of user-preferred travel area patterns mining and a station area attribute mining method. In the application of the Beijing case, a precise exploration of the spatiotemporal characteristics of PT users is conducted, resulting in the final Beijing PTUP system.

This paper combines UP technology with big data analysis techniques to study the travel patterns of PT users. A user profile label framework is constructed, and data visualization, statistical analysis and K-means clustering are applied to extract specific labels instructed by this system framework. Through these analytical processes, the user labeling system is improved, and its applicability is validated through the analysis of a Beijing PT case.

Many countries have a renewed focus on health inequalities since COVID-19. In England, integrated care systems (ICSs), formed in 2022 to promote integration, are required to reduce health inequalities. Integration is supported by population health management (PHM) which links data across health and care organisations to inform service delivery. It is not well-understood how PHM can help ICSs reduce health inequalities. This paper describes development of a programme theory to advance this understanding.

This study was conducted as a mixed-methods process evaluation in a local ICS using PHM. The study used Framework to analyse interviews with health and care professionals about a PHM tool, the COVID-19 vaccination uptake Dashboard. Quantitative data on staff Dashboard usage were analysed descriptively. To develop a wider programme theory, local findings were discussed with national PHM stakeholders.

ICS staff used PHM in heterogeneous ways to influence programme delivery and reduce inequalities in vaccine uptake. PHM data was most influential where it highlighted action was needed for “targetable” populations. PHM is more likely to influence decisions on reducing inequalities where data are trusted and valued, data platforms are underpinned by positive inter-organisational relationships and where the health inequality is a shared priority.

The COVID-19 pandemic accelerated a shift toward use of digital health platforms and integrated working across ICSs. This paper used an evaluation of integrated data to reduce inequalities in COVID-19 vaccine delivery to propose a novel programme theory for how integrated data can support ICS staff to tackle health inequalities.

This paper is premised upon an analysis of 26 cities within the UK regarding their smart city projects. Each city was analyzed through news articles, reports and policy documents to ascertain the level of each city's development as a smart city. Each was coded by separating the projects into five types, which were ranked on a scale from 0 (no plans for use) to 5 (project type in use). The most common types are the provision of open data and the creation of business ecosystems as the primary driver of the smart city. However, many councils and enterprises proclaim smartness before the technology is actually in use, making it difficult to separate what is utilised and what is under development. Therefore, this paper further carried out an analysis of 20 cities and their intended plans to usher in the smart city, to observe the expected emergence of smart city technology. This was achieved by interrogating various roadmaps and policy documents produced by the respective cities. It was found that the most prevalent form of emergent smart city technology is the rollout of 5G and increased educational programmes alongside a proliferation of internet of things and electric vehicle usage.

The paper aims to present a grid-connected multi-inverter for solar photovoltaic (PV) systems to enhance reliability indices after selected the placement and level of PV solar.

In this study, the associated probability is calculated based on the solar power generation capacity levels and outages conditions. Then, based on this probability, dependability indices like average energy not supplied (AENS), expected energy not supplied and loss of load expectations (LOLE) are computed, also, another indices have been computed such as (customer average interruption duration index (CAIDI), system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI)) addressing by affected customers with distribution networks reliability assessment, including PV. On the basis of their dependability indices and active power flow, several PV solar modules installed in several places are analyzed. A mechanism for assessing the performance of the grid's integration of renewable energy sources is also under investigation.

The findings of this study based on data extracted form a PV power plant connected to the power network system in Diyala, Iraq 132 kV, attempts to identify the system's weakest points in order to improve the system's overall dependability. In addition, enhanced reliability indices are given for measuring solar PV systems performance connected to the grid and reviewed for the benefit of the customers.

The main contributions of this study are two methods for determining the reliability of PV generators taking into consideration the system component failure rates and the power electronic component defect rates in a PV system which depend on the power input and the power loss using electrical transient analysis program (ETAP) program.

User acceptance is a necessary precondition to implementing self-driving buses as a solution to public transport challenges. Focusing on potential users in a real-life setting, this paper aims to analyze the factors that affect their willingness to use public autonomous shuttles (PASs) as well as their word-of-mouth (WOM) intentions.

Grounded on Unified Theory of Acceptance and Use of Technology (UTAUT2), the study was carried out on a sample of 318 potential users in a real-life setting. The hypothesized relationships were tested using partial least squares structural equation modeling (PLS-SEM).

The study reveals that performance expectancy, facilitating conditions, hedonic motivation and trust are significant predictors of PAS usage intention, which is, in turn, related to WOM communication. Additionally, the factors that impact the intention to use a PAS are found to exert an indirect effect on WOM, mediated by usage intention.

This study includes practical insights for transport decision-makers on PAS service design, marketing campaigns and WOM monitoring.

While extant research focuses on passengers who have tried autonomous shuttles in experimental settings, this article adopts the perspective of potential users who have no previous experience with these vehicles and identifies the link between usage intention and WOM communication in a real-life traffic environment.

若要引入自動駕駛巴士來解決公共交通的問題和挑戰,一個必不可少的先決條件是得到用戶的認可。本研究透過重點分析活在真實生活環境中的潛在用戶,來探討影響他們使用公共自動交通工具的意願和口碑動機的各個因素。

本研究以延伸整合型科技接受模式為基礎,對一個涵蓋處身於真實生活環境中318名潛在用戶的樣本進行分析和探討。研究人員以偏最小平方法的結構方程模型 (PLS-SEM), 去測試各個被假設的關聯。

研究結果顯示,績效期望、有利條件、享樂動機和信任均明顯能夠預測人們使用公共自動交通工具的意願,而人們使用公共自動交通工具的意願又反過來與口碑溝通有所相關。另外,研究人員發現,影響人們使用公共自動交通工具意願的各個因素,對口碑會產生間接的影響,而使用意願是會起著調節作用的。

現存的學術研究均聚焦分析那些曾於實驗設置下坐過自動交通工具的人士,而本研究卻採用從未坐過自動交通工具人士的角度來進行分析與探討,並且找出了於實際的交通環境裡、使用意願與口碑溝通之間的關聯。

本研究提供的啟示,對有關公共自動交通工具服務設計、市場營銷活動和口碑監督工作的運輸決策者來說頗具實務意義。

This paper aims to present the internalization process by which Venezuelan migrants and refugees are resettled. Using system dynamics, the authors model a Brazilian humanitarian operation (“Acolhida” – Welcome), simulate the internalization process, propose policies and provide lessons learned for future migratory operations.

Using system dynamics simulation, the authors use Acolhida Operation’s historical data to recreate the reception and resettlement process of Venezuelan migrants and refugees. The authors identify the main bottlenecks in the system and propose policies to respond to scenarios according to the number of internalization vacancies, that is, available places in Brazil where migrants and refugees can be resettled. Finally, based on interviews with former decision-makers, the model represents a first attempt to convert the pressure of public opinion on authorities into temporary shelters as a way of reducing the number of unassisted people.

The results confirm that internalization vacancies are the main constraint when resettling Venezuelan migrants and refugees. Had the internalization program been promoted since the operation’s beginning, there would have been fewer unassisted people in Roraima and fewer shelters. The pressure-converting mechanism presented in this study, although incipient, constitutes a first attempt to support decision-makers in determining when to build temporary shelters.

This study can be useful to public authorities and humanitarian organizations when developing policies to enhance resettlement in migratory crises. In Acolhida’s case, the internalization program should continue to be the operation’s priority and can be enhanced by investing more resources to create internalization vacancies while maintaining logistical capacities.

The authors suggest policies to improve the Acolhida internalization program: give more people the choice to relocate in other cities, increase turnover in shelters and provide a more efficient and effective response to Venezuelan migration in Roraima.

Although a number of studies have applied system dynamics to humanitarian operations, few models have focused on migratory emergencies, such as those occurring in northern Brazil. The model is applied to the largest humanitarian operation carried out in the Brazilian territory and provides decision-makers with valuable insights and alternatives for better implementation in the future. Furthermore, this study narrows the gap between the social sciences and modeling and simulation techniques by proposing ways of predicting migratory implications in the construction of shelters and resettlement policies.