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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.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

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.

This research examines what motivates professional truck drivers to engage in eco-driving by linking their self-reports with objective driving scores.

Theory of Planned Behavior (TPB) is illustrated in an embedded, single-case study of a Finnish carrier with 17 of its truck drivers. Data are obtained through in-depth interviews with drivers, their fuel-efficiency scores generated by fleet telematics and a focus group session with the management.

Discrepancies between drivers’ intentions and eco-driving behaviors are illustrated in a two-by-two matrix that classifies drivers into four categories: ideal eco-drivers, wildcards, wannabes and non-eco-drivers. Attitudes, subjective norms and perceived behavioral control are examined for drivers within each category, revealing that drivers’ perceptions did not always align with the reality of their driving.

This study strengthens the utility of TPB through data triangulation while also revealing the theory’s inherent limitations in elucidating the underlying causes of its three antecedents and their impact on the variance in driving behaviors.

Managerial insights are offered to fleet managers and eco-driving solution providers to stipulate the right conditions for drivers to enhance fuel-efficiency outcomes of transport fleets.

This is one of the first studies to give a voice to professional truck drivers about their daily eco-driving practice.

The purpose of this study is to quantify port efficiency assessment indicators to analyze the impact of COVID-19 on Chinese One Belt One Road (OBOR) ports.

This study utilized a grey prediction model GM(1,1) to forecast five relevant indicators for each of the 17 OBOR ports both with and without COVID-19 background conditions. Additionally, the data envelopment analysis (DEA) efficiency assessment approach was used to analyze the impact of COVID-19 on port efficiency.

The results indicate that cargo and container throughput growth rates during the COVID-19 pandemic are reduced by 1.7 and 2.1%, respectively. There was also a noticeable reduction in technological efficiency (TE) as well as pure technological efficiency (PTE), while scale efficiency (SE) remained largely unaffected. Furthermore, the dynamic efficiency MI was mainly negatively impacted by changes in overall efficiency change (EFFCH), where pure efficiency change (PECH) less than one contributed significantly towards overall regression of port efficiencies during this period.

This paper is unique in its use of a combination of the grey prediction model and DEA efficiency assessment to quantify changes in important indicators during pandemic periods. This approach not only provides a quantitative understanding of the impact on port-level efficiency through numerical quantification but also offers readers an intuitive understanding.

The noise and dust particles caused by the construction transport are by most stakeholders experienced as disturbing. The purpose of this study is to explore how sonification can support visualization in construction planning to decrease construction transport disturbances.

This paper presents an interdisciplinary research project, combining research on construction logistics, internet of things and sonification. First, a data recording device, including sound, particle, temperature and humidity sensors, was implemented and deployed in a development project. Second, the collected data were used in a sonification design, which was, third, evaluated with potential users.

The results showed that the low-cost sensors used could capture “good enough” data, and that the use of sonification for representing these data is interesting and a possible useful tool in urban and construction transport planning.

There is a need to further evolve the sonification design and better communicate the aim of the sounds used to potential users. Further testing is also needed.

This study introduces new ideas of how to support visualization with sonification planning the construction work and its impact on the vicinity of the site. Currently, urban planning and construction planning focus on visualizing the final result, with little focus on how to handle disturbances during the construction process.

Showing the potentials of using low-cost sensor data in sonification, and using sonification together with visualization, is the result of a novel interdisciplinary research area combination.

An increasing number of last mile deliveries (LMDs) pose many sustainability challenges that retailers and logistics service providers (LSPs) can address. Using cognitive frames (CFs) as a lens, this study explored how retail and LSP managers make sense of sustainable LMDs.

The methodological approach used is a multiple embedded case study. The data were obtained from interviews with retailers and LSPs, supplemented with secondary data for triangulation.

The findings present the operational aspects of LMDs that managers associate with sustainability and indicate that retail and LSP managers frame sustainability primarily as emission reduction. Managers indicate an externalization of responsibility and a compartmentalization of the supply chain, in which social sustainability is not associated with the last mile. Most managers indicate hierarchical CFs regarding sustainability, in which sustainability is an important topic but is subordinate to economic interests.

Collaboration between retailers, LSPs and other stakeholders is viewed as challenging but could alleviate some of the sustainability shortcomings and aid in the paradoxical framing and inclusion of social issues.

A conceptualization of managerial CFs for sustainable LMDs, together with empirical frame indicators and three propositions, is presented, providing novel insights into how paradoxical CFs could make LMDs more sustainable. This approach illuminates the possibilities for how to untangle the operational manifestations of managerial framing and adds to the empirical exploration of CFs in supply chain management.

This study identifies key facets leading to consumers' Internet of Things (IoT) adoption intention.

Applying four technology acceptance theories (theory of planned behavior, technology acceptance model, pleasure-arousal-dominance theory and technology readiness index), the author uses deductive quantitative research to develop a model, explaining IoT adoption intentions. Administrated questionnaires are distributed in Egypt among generation-Z and millennials in malls. A total of 400 questionnaires are used for hypotheses testing, applying structural equation modeling (SEM) path coefficient analysis.

Results of this study show that attitude, dominance, perceived usefulness, innovativeness and insecurity impact consumers' IoT adoption intentions; subjective norms, perceived behavior control, pleasure, arousal, perceived ease, optimism and discomfort hold insignificant impact on consumers' IoT adoption intentions.

Exploring IoT facets and how these facets impact consumers' adoption intentions, this study helps grasp technology acceptance in theory and practice, guiding scholar and practitioners (e.g. IoT developers, retailers, marketers and other field experts) to consider consumers' mindset when developing, improving and marketing IoT.

The contribution stems from the incorporation of various frameworks used to explain technology acceptance. By studying several theories jointly, the research extracts and identifies a significant set of facets (technical and psychological) to build a comprehensive theory of IoT acceptance, showing consumers' IoT adoption is not entirely similar to adoption of other past innovations. This understanding allows marketers to focus on content that needs to be promoted to boost consumers' IoT purchase plans. Future researchers could replicate the results to IoT categories (e.g. home appliances, cars, healthcare, education, sportswear, etc.) to improve external validity of the findings, among other future research opportunities.

Organic food processing must include organic principles to be authentic. This qualitative study aims to understand the processors' understanding of organic food processing quality.

This study is based on semi-structured expert interviews with eight employees of six purely or partly organic dairies from Germany and Switzerland. Interview themes are (1) quality of organic milk processing in general, (2) assessment of specific processing techniques, (3) product quality of organic milk and (4) flow of information between producer and consumer. The interviews have been audio-recorded, transcribed verbatim and thematically analysed.

(1) Experts prefer minimal processing; some prefer artisanal processing, whilst others stress the advantages of mechanisation. (2) High temperature short time (HTST) pasteurisation and mechanical processing techniques are accepted; ultra-high-temperature (UHT) milk processing is partly rejected. (3) Traditional taste and valuable ingredients should be present in the final product. Natural variances are judged positively. (4) Consumers' low level of food technology literacy is challenging for communication.

The results cannot be generalised due to the qualitative study design. Further studies, e.g. qualitative case analyses and studies with a quantitative design, are necessary to deepen the results.

The paper shows which processing technologies experts consider suitable or unsuitable for organic milk. The paper also identifies opportunities to bridge the perceived gap between processors' and consumers' demands.

The study shows the challenges of processors in expressing the processors' understanding of process quality.

Health risks associated with coronavirus disease 2019 (COVID-19) have severely affected the financial stability of airline companies globally. Recapturing financial stability following this crisis depends heavily on these companies’ ability to attain efficient and productive operations. This study uses several empirical approaches to examine key factors contributing to carriers sustaining high productivity prior to, during and after a major recession. Findings suggest, regardless of economic conditions, that social distancing which requires airline companies in the Asia Pacific region to fly with a significant percentage of unfilled seats weakens the performance of those companies. Furthermore, efficient operations do not guarantee the avoidance of productivity declines, especially during a recession.