Transport policies should aim to integrate the demands and expectations of all stakeholders, even in maritime logistics contexts where a mix of private and public interests play out, sometimes in conflicting situations. The added value of an ecosystem for transport policy largely depends on how effectively coordination amongst its stakeholders is managed. The study aims to define stakeholders’ attributes within a small maritime logistics ecosystem, using the case study of Malta, by analyzing how power, legitimacy and urgency are relationally constructed and hierarchically distributed. This is grounded in the Stakeholder Salience Theory and distinguish ecosystem participants based on the attribute positioning derived from individual traits. Data is collected through interviews with the stakeholders and analysed qualitatively using thematic analysis. The results show how legitimacy emerges as a key attribute; power is developed by inter-organizational relationships and urgency plays a more limited role. In aggregate, salience attributes are pivotal in building the ecosystem collective identity and when the ecosystem orchestrator lacks legitimacy in constrained environments, the overall ecosystem stability is affected. Policies should therefore focus on the understanding of stakeholder salience and dynamics, as well as the need for effective coordination in maritime logistics ecosystems to guarantee stability and collective value creation.
Cracks are common defects in concrete structures and could lead to structural failure. This study provides a solution to support Structural Health Monitoring of concrete bridges from 2D images to a 3D model and then to Virtual Reality (VR) visualisation. To accomplish this, two concrete bridges in the Mediterranean Sea region were inspected, and image data were collected. This data was subsequently annotated manually for cracks through the VGG tool and then analysed via the 3DF Zephyr software. From a Sparse point cloud to a Dense point cloud and then a 3D mesh, all were smoothly constructed using the mentioned software, with better visualisation of the annotated cracks in the final 3D model of the bridges. In the end, the 3D model .ply file was converted to .glb format, which is supported by the majority of the VR glasses apps, making the virtual inspection possible through mobile devices.
A copy of a graph F is called an F-copy. For any graph G, the F-isolation number of G, denoted by t(G, F), is the size of a smallest subset D of the vertex set of G such that the closed neighbourhood N[D] of D in G intersects the vertex sets of the F-copies contained by G (equivalently, G-N[D] contains no F-copy). Thus, t(G, K1) is the domination number gamma (G) of G, and t(G, K2) is the vertex-edge domination number of G. Settling a conjecture of Zhang and Wu, the present first author proved that if F is a k-edge graph, gamma (F) = 1 (that is, F has a vertex that is adjacent to all the other vertices of F), and G is a connected m-edge graph, then t(G, F) <= m+1 k+2 unless G is an F-copy or F is a 3-vertex path and G is a 6-cycle. The graphs that attain the bound were determined for 0 <= k <= 1 by Fenech, Kaemawichanurat and the present first author, and for k = 2 by Zhang and Wu. In this paper, we determine them for k >= 3. Our result was also conjectured by Zhang and Wu. (c) 2026 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Purpose-This article aims at exploring the importance of perceived benefits in scholars' decision to use generative artificial intelligence (GAI), as well as at developing and testing a theoretical multifaceted model of scholars' intention to use GAI. Design/methodology/approach-The article uses a mixed deductive-inductive approach. The theoretical multifaceted model of scholars' intention to employ GAI was tested based on structural equation modelling using partial least squares (PLS-SEM) and a survey conducted among 471 scientists. Findings-The results show that the benefits perceived by scholars in the fields of teaching and research have the strongest influence on their decision to employ GAI. On the other hand, perceived benefits in the administrative field are not of importance in scholars' intention to use GAI. Research limitations/implications-The research conducted was limited in context (universities in Poland) and did not take into account a longitudinal perspective, which could have led to the omission of changes in researchers' intentions regarding the use of GAI as a result of more intensive use of those tools in scientific work (those intentions are subject to change over time). Originality/value-The presented research constitutes a significant contribution to the literature on the use of GAI in the academic environment. Relative to previous research, our findings offer a new conceptual framework that illustrates the perceived benefits of GAI in shaping researchers' intentions to use it, taking into account the following three key areas of academic activity: research, teaching and administrative tasks. The findings respond to the need for an in-depth analysis. They also include an analysis of the impact of socio-demographic factors and personality traits on the intention to use GAI, which constitutes an innovative contribution to the existing scientific achievements in this field.
