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The purpose of this paper is to study public project governance frameworks in various ministries and agencies in Norway, following the introduction of such a framework on the topmost level (i.e. the cabinet) which applies to the very largest projects.

The study is methodologically designed as a qualitative assessment of project governance frameworks that apply to state-funded investment projects in selected sectors, based on data gathered through document reviews and interviews.

The study finds that all of the agencies have introduced their own project governance frameworks, which are basically consistent with the recommendations from the project management literature and with the cabinet’s overall requirements in Norway. By contrast, only one ministry has taken a formalized role as a project owner. Governance tasks thus seem to be extensively delegated to the subordinate agencies. This even includes strategic tasks such as project selection and portfolio management, and implies there is a risk that public project governance has a narrow and internal focus.

The paper is a first step toward a better understanding of public project governance as a hierarchical system and the relationship between project owners on three levels, the cabinet, the sectoral ministry, and the government agency.

By adopting the “hard” and “soft” project management (PM) approaches from the PM-literature, this paper aims to problematize the expected role of client organizations in driving innovation in the transport infrastructure sector.

Addressing a large public client in Sweden, a case study design was initially applied to provide in-depth insights and perspectives of client project managers’ views and experiences of managing projects expected to drive innovation. In this paper, the concepts of “hard” and “soft” are used to discuss empirical findings on challenges associated with adopting a PM-approach for driving innovation in projects. The empirical material consists of interview data, complemented with observations and archival data.

Findings reveal challenges associated with combining hard and soft approaches, frequently demonstrating difficulties in balancing short-term project expectations with the promotion of innovation. In line with the literature, project managers note that there is a need for soft approaches to promote development and drive innovation. Yet, findings reflect a situation in which operational success criteria predominate, whereas soft approaches are not sufficiently used to create the grounds required for fostering innovation.

Insights are provided into how PM-approaches may impact construction innovation in the infrastructure sector, demonstrating a need for further research on the challenges and implications of applying and combining hard and soft PM-approaches.

The initial policy of the countries that developed vaccines has been to lock the vaccine by patent. This has been due to the fact that domestic demand for vaccine was mounting. Since only a few countries could invest in it, manufacturing and export remained at the behest of those few resulting in deep inequity in the global rollout. Pandemics are global health crises. Hence, calls for the patent waiver for the COVID-19 vaccine are growing to access the vaccine. The vaccine and its production, marketing and distribution have been politicized driven by the hegemonic aspiration. Both manufacturing and import-dependent countries are racing to win the diplomatic battle: the former has to win to gain hegemony and the latter to get the vaccine. Hence, the vaccine distribution has been marked with deep discrimination, and as a result, the migrant community is less likely to get their vaccine on time. This article engages in the decades-long debate over intellectual property rights and patenting life-saving vaccines. We argue that exemption of COVID-19 vaccines from intellectual property rights would improve global access and equity.

This study aims to create a better understanding of how practitioners implement and work Agile while balancing the tensions arising between stability and change.

A grounded theory approach was used to explore what happens in practice when software development teams implement and work Agile. The empirical data consists of twenty semi-structured interviews with practitioners working in fourteen different organizations and in six different Agile roles.

As a result, a substantive theory was presented of continuously balancing between stability and change in Agile teams. In addition, the study also proposes three guidelines that can help organizations about to change their way of working to Agile.

The inherent limitation of a grounded theory study is that a substantial theory can only explain the specific contexts explored in that study. Thus, this study's contribution is a substantial theory that needs to be further developed and improved.

The proposed guidelines can help organizations about to change their way of working to Agile. They can also assist organizations in switching from “doing Agile” to “being Agile”, thus becoming more successful.

The new perspective that this study contributes is the fact that our discovered categories show that several inherent processes are ongoing at the same time in order to balance the need to have both stability and change.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Left atrial appendage occlusion (LAAO) is a structural interventional cardiology procedure that offers several possibilities for the application of additive manufacturing technologies. The literature shows a growing interest in the use of 3D-printed models for LAAO procedure planning and occlusion device choice. This study aims to describe a full workflow to create a 3D-printed LAA model for LAAO procedure planning.

The workflow starts with the patient’s computed tomography diagnostic image selection. Segmentation in a commercial software provides initial geometrical models in standard tessellation language (STL) format that are then preprocessed for print in dedicated software. Models are printed using a commercial stereolithography machine and postprocessing is performed.

Models produced with the described workflow have been used at the Careggi Hospital of Florence as LAAO auxiliary planning tool in 10 cases of interest, demonstrating a good correlation with state-of-the-art software for device selection and improving the surgeon’s understanding of patient anatomy and device positioning.

3D-printed models for the LAAO planning are already described in the literature. The novelty of the article lies in the detailed description of a robust workflow for the creation of these models. The robustness of the method is demonstrated by the coherent results obtained for the 10 different cases studied.

Authorization and access control have been a topic of research for several decades. However, existing definitions are inconsistent and even contradicting each other. Furthermore, there are numerous access control models and even more have recently evolved to conform with the challenging requirements of resource protection. That makes it hard to classify the models and decide for an appropriate one satisfying security needs. Therefore, this study aims to guide through the plenty of access control models in the current state of the art besides this opaque accumulation of terms meaning and how they are related.

This study follows the systematic literature review approach to investigate current research regarding access control models and illustrate the findings of the conducted review. To provide a detailed understanding of the topic, this study identified the need for an additional study on the terms related to the domain of authorization and access control.

The authors’ research results in this paper are the distinction between authorization and access control with respect to definition, strategies, and models in addition to the classification schema. This study provides a comprehensive overview of existing models and an analysis according to the proposed five classes of access control models.

Based on the authors’ definitions of authorization and access control along with their related terms, i.e. authorization strategy, model and policy as well as access control model and mechanism, this study gives an overview of authorization strategies and propose a classification of access control models providing examples for each category. In contrast to other comparative studies, this study discusses more access control models, including the conventional state-of-the-art models and novel ones. This study also summarizes each of the literature works after selecting the relevant ones focusing on the database system domain or providing a survey, a classification or evaluation criteria of access control models. Additionally, the introduced categories of models are analyzed with respect to various criteria that are partly selected from the standard access control system evaluation metrics by the National Institute of Standards and Technology.

A number of literature contributions have underlined the importance of developing value-added logistics activities or VALS in order to help improve customers’ satisfaction. However, there is usually very little attention given regarding where to perform these VALS. This study aims to: (1) identify a comprehensive set of factors which may influence the location of VALS, (2) to analyze to what extent those factors influence location decisions, and (3) to distinguish the determinants behind the location choices for distribution centers and for the kind of VALS that will be developed in these distribution centers.

In this paper, we will present a conceptual framework on the locations of VALS in view of the identifying determinants for assigning VALS to logistical centers. We argue that the optimal location of VALS is determined by complex interactions between the determinants at the level of the choice of a distribution system, distribution center location factors, and different logistical characteristics regarding products.

The tourism and hospitality sectors are experiencing radical innovation boosted by the advancements in Information and Communication Technologies. Increasingly sophisticated chatbots are introducing novel approaches, re-shaping the dynamics among tourists and service providers, and fostering a remarkable behavioral change in the overall sector. Therefore, the objective of this paper is two-folded: (1) to highlight the academic and industrial standing points with respect to the current chatbots designed/deployed in the tourism sector and (2) to develop a proof-of-concept embodying the most prominent opportunities in the tourism sector.

This work elaborates on the outcomes of a Systematic Literature Review (SLR) and a Focus Group (FG) composed of experts from the tourism industry. Moreover, it presents a proof-of-concept relying on the outcomes obtained from both SLR and FG. Eventually, the proof-of-concept has been tested with experts and practitioners of the tourism sector.

Among the findings elicited by this paper, we can mention the quick evolution of chatbot-based solutions, the need for continuous investments, upskilling, system innovation to tackle the eTourism challenges and the shift toward new dimensions (i.e. tourist-to-tourist-to-chatbot and personalized multi-stakeholder systems). In particular, we focus on the need for chatbot-based activity and thematic aggregation for next-generation tourists and service providers.

Both academic- and industrial-centered findings have been structured and discussed to foster the practitioners' future research. Moreover, the proof-of-concept presented in the paper is the first of its kind, which raised considerable interest from both technical and business-planning perspectives.