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Collaboration networks are the main mechanisms through which regional innovation capacities are enhanced. These networks have been analyzed by using data either on research projects or patents. However, analyzing only one type of network can limit our understanding of regional innovation dynamics. In this paper, we investigate the drivers of network evolution in two inter-regional network types within the European Union: R&D project networks and co-patenting networks. Specifically, we examine data on Framework Program project collaborations and patent collaborations at the NUTS2 regional level between 2011 and 2019. Our empirical strategy is based on Stochastic Actor-Oriented Model where we analyze and compare the factors that affect the evolution of two networks. We find that path-dependent processes resulting from past networks, such as triadic closure, preferential attachment, and tie repetition, play a more important role in explaining the evolution of R&D project networks compared with patent networks. On the other hand, regional characteristics, particularly the patenting intensity of a region and similarity in patenting between regions appear to be more influential in shaping patent networks. These results have important implications for the future evolution of knowledge networks in Europe. [ABSTRACT FROM AUTHOR]

Motivated by the practical research and development (R&D) process in high-end equipment manufacturing, this study investigates a bi-level scheduling problem in a complex R&D project network, where each project contains multiple modules with a complete task network. In the bi-level scheduling problem, the upper-level problem is that the R&D project leader makes the decision on allocating all R&D project modules to limited R&D researchers and the objective is to minimise the total penalty cost of all projects, and the lower-level problem is that the researchers schedule and sort the assigned tasks to minimise their minimum makespan. The different capacity of researchers is considered, and some structural properties are derived based on the capacity analytics. To tackle this complex scheduling problem, an effective Variable Neighborhood Search algorithm based on the 'less is more' concept is proposed, where a Multi-Greedy Heuristic is incorporated. Interestingly, we observe that simpler algorithmic strategies may lead to better algorithmic performance. Computational experiments are carried out to demonstrate that the performance of the proposed algorithm is efficient and stable. [ABSTRACT FROM AUTHOR]

The paper presents the model resilience measurement based on the complex network theory and analyzes the resilience of project portfolio network considering risk propagation. The model can be used to evaluate the resilience and improve its success probability of projects in the portfolio network. Firstly, the research analyzes the dynamic changes of the portfolio network derived from the construction of the project portfolio matrix, as well as the main factors to be taken into consideration in measuring the resilience of the project portfolio. Further, the research measures the resilience of the project portfolio network according to the node attributes (project) and the relationship attributes (the relationship that one project will impact another in the portfolio network) respectively. Then, to integrate the resilience of the projects and influence relationship between projects, the research proposes the dynamic PageRank algorithm to analyze the resilience of the project portfolio based on the analysis of traditional PageRank algorithm. In addition, resilience is not only affected by the projects and its influence relationship between them, but is also affected by risk propagation. Therefore, the research presents a model for analyzing the portfolio network resilience considering multiple risk propagation. Finally, a research and development project portfolio are taken as an example to demonstrate the effectiveness of the method presented in this research. Our approach can be used by managers to identify the scores of project resilience capacity in portfolio network. Our method explicitly allows to uncover the most resilient projects considering the resilience of project (node) and their influence relationship (network structure), and the risk propagation. Utilizing the outcomes of this research can enhance the capacity of the whole project portfolio to manage risks and improve the success probability of the whole project portfolio by enhancing network resilience. [ABSTRACT FROM AUTHOR]

Preventing nicotine use among youth is a public health priority. Nicotine use emerges from complex relationships between numerous factors. This project used network analysis to model behavioral precursors of nicotine use (knowledge, attitudes, perceptions, intentions) among youth who had never used nicotine and determine which predicted future trajectories of use across multiple nicotine products. Data were from the Population Assessment of Tobacco and Health study (2013–2018; analyzed 2023–2024), youth ages 12–17, who reported never using nicotine at Wave 1. Network structure was determined for behavioral precursors at Wave 1 and central network nodes were identified (N =5,087). Central nodes were then tested as predictors of trajectories of use across multiple nicotine products during Waves 1–4 (N =3,851). Central nodes of the Wave 1 network were harm perception, expectancy that tobacco would calm anger/reduce stress, and intention to try. Those with lower intent to try at Wave 1 had lower odds of being in an Experimentation or Use class versus a Nonuse class during Waves 1–4 (p <0.0001). Those with more accurate harm perception had lower odds of being in an Experimentation versus Nonuse class (p =0.004). Those with positive expectancies had higher odds of being in an Experimentation versus Nonuse or Use class (p =0.04, 0.02). Findings suggest a network model of behavioral precursors of nicotine use that can be tested, including central nodes that predicted trajectories of use across multiple nicotine products, and therefore may be priority intervention targets. [ABSTRACT FROM AUTHOR]

Increasing impacts from wildfires are reshaping fire policies worldwide, with expanded investments in a wide range of fuel reduction strategies. In many fire prone regions, especially in the Mediterranean basin, fuel management programs have relied on fuel break networks for decades to facilitate fire suppression and reduce area burned and damage. By contrast, on the fire prone federal forests in the western United States, fuel management is guided primarily by landscape restoration goals, including improving fire resiliency such that wildfires can be managed for ecological benefit, and suppression is used more as a tool to shape burn patterns and less to extinguish fires. New policies in both fire systems are now calling for hybrid approaches that rely on both types of investments and efficient allocation of alternative spatial treatment patterns: linear networks versus patches across the landscape. However, studies that combine these strategies and examine alternative co-prioritization outcomes and potential synergies are largely non-existent. Here, we analyzed scenarios for implementing both types of treatments in concert while varying the prioritization metrics for one type or the other on a western United States national forest. We measured the response related to both treatment strategies including fire intersection rate, improvement in forest resiliency, and net revenue. We found that projects with benefits to both strategies can be identified and mapped independently of the implementation scenario and restoration objective. However, scenarios prioritized for fuel breaks preceding restoration resulted in the identification of more projects that met the criteria for providing dual benefits. The study is a rare example of optimizing hybrid fuel treatment projects that serve both restoration and fire protection goals with different spatial treatment designs. [ABSTRACT FROM AUTHOR]

In some production processes, the effort associated with a certain activity for its execution can vary over time. In this case, the amount of work per time unit devoted to each activity, so as its duration, is not univocally determined. This kind of problem can be represented by an activity project network with the so-called feeding precedence relations, and activity variable execution intensity. In this paper, we propose a forward recursion algorithm able to find the earliest start and finish times of each activity, in O (m log n) time, with n and m being the number of activities and the number of precedence relations, respectively. In particular, this requires the calculation of the (optimal) execution intensity profile, for each activity, that warrants the earliest start schedule and the minimum completion time of the project. [ABSTRACT FROM AUTHOR]

The implementation of the European Fisheries Local Action Group (FLAG) system applies a neo‐endogenous approach, which can restructure public intervention in favour of a mosaic of local territories. By resting on a Finnish case study, this article studies the local adaptation of the FLAG system and how FLAG managers are positioned as intermediaries in horizontal and vertical networks that enhance local fisheries' livelihoods. The analysis of the FLAG system's approaches and various roles of the managers is based on qualitative interviews and a stakeholder survey, set in the interactive governance framework. Our findings show how via its intermediary role, expertise, commitment and networking, the FLAG system, and especially FLAG managers, can mend the failures of the governance system. We conclude that the recruitment of the right type of FLAG managers can be a path towards the enhancement of local small‐scale fishers in a well‐functioning governance system. [ABSTRACT FROM AUTHOR]

The present study was conducted to analyze the engineering students' ability to apply project management techniques in the projects planned using the concepts given by Project Management Institute (PMBOK). Selected student projects related to civil and multi-disciplinary nature are verified from project charter preparation. The techniques used are related to scheduling, Milestones, work breakdown structure, cost estimation methods and different management plans. Feedback is taken from the student batches regarding the applicability of techniques, time taken for project plans, charter document, difficulty levels and other aspects of suitability of techniques. Out of 100 projects analysed, 66% of student groups felt easy to apply PMI project management techniques. Bottom up technique is applied by 76%teams for cost estimation and second best technique is top down with 16% applicability. 69% teams used PERT technique for scheduling with second best as CPM for 19% projects. [ABSTRACT FROM AUTHOR]

Copyright of Die Deutsche Schule is the property of Waxmann Verlag GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Based on conceptual reasoning, combined with illustrations from the air cargo industry, this article proposes a gradual broadening of the concept of what project management offices (PMOs) are responsible for to provide added value to the collaborating organizations when planning for and executing interorganizational projects. Thus far, the ability of PMOs to support interorganiza-tional projects and practices has been restricted—this goes for project management practice as well as a lack of concepts and theoretical reasoning from research in the domain of project studies. Against this background, this article distinguishes four types of PMOs and identifies promising organizational design elements pointing to functions and barriers, as well as to the interorga-nizational bridging practices of PMOs in support of their interorganizational responsibilities. [ABSTRACT FROM AUTHOR]

Purpose: Abnormal behaviors such as rework, backlog, changes and claims generated by project organizations are unavoidable in complex projects. When abnormal behaviors emerge, the previously normal state of interactions between organizations will be altered to some extent. However, previous studies have ignored the associations and interactions between organizations in the context of abnormal organizational behaviors (AOBs), making this challenging to cope with AOBs. As a result, the objective of this paper is to explore how to reduce AOBs in complex projects at the organizational level from a network perspective. Design/methodology/approach: To overcome the inherent limitations of a single case study, this research integrated two data collection methods: questionnaire survey and expert scoring method. The questionnaire survey captured the universal data on the influence possibility of AOBs between complex project organizations and the expert scoring method got the influence probability scores of AOBs between organizations in the case. Using these data, four organizational influence network models of AOBs based on a case were developed to demonstrate how to destroy AOBs networks in complex projects using network attack theory (NAT). Findings: First, the findings show that controlling AOBs generated by key organizations preferentially and improving the ability of key organizations can weaken AOBs network, enabling more effective coping strategies. Second, the owners, government, material suppliers and designers are identified as key organizations across all four influence networks of AOBs. Third, change and claim behaviors are more manageable from the organizational level. Practical implications: Project managers can target specific organizations for intervention, weaken the AOBs network by applying NAT and achieve better project outcomes through coping strategies. Additionally, by taking a network perspective, this research provides a novel approach to comprehending the associations and interactions between organizations in the context of complex projects. Originality/value: This paper proposes a new approach to investigating AOBs in complex projects by simultaneously examining rework, backlog, change and claim. Leveraging NAT as a novel tool for managing the harmful effects of influence networks, this study extends the knowledge body in the field of organizational behavior (OB) management and complex project management. [ABSTRACT FROM AUTHOR]

Community detection can help analyze the structural features and functions of complex networks, and plays important roles in many aspects such as project recommendation and network evolution analysis. Therefore, community detection has always been a hot topic in the field of complex networks. Although various community-detection methods have been proposed, how to improve their accuracy and efficiency is still an ambition pursued by researchers. In view of this, this paper proposes a community-detection method for complex networks based on node influence analysis. First, the influence of nodes is represented as a vector composed by neighborhood degree centrality, betweennes centrality and clustering coefficient. Then, Pareto dominance is used to rank the influence of nodes. After that, the community centers are selected by comprehensively considering the node influence and crowding degree. Finally, the remaining nodes are allocated to different communities using a labeling algorithm. The proposed method in this paper is applied to several actual networks. The comparison results with other methods demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study investigates the effects of project network characteristics (i.e., network density and centrality) and transactive memory systems on project performance. Based on 361 valid questionnaires from megaproject teams, a structural equation modeling (SEM) approach is used for data analysis. The findings discover that high network density is positively associated with specialization, credibility, and project performance, without a significant link with coordination. Meanwhile, a high degree of network centrality negatively affects three dimensions of transactive memory systems, as well as project performance. Regarding the mediating role of transactive memory systems dimensions, specialization and credibility serve as the dominant mediating effects. Interestingly, the interactive relationships among transactive memory systems dimensions are empirically examined. These findings provide a network perspective to integrate and utilize organizational knowledge, thus improving organizational flexibility and resilience. Keywords network characteristics, transactive memory systems, project performance, organizational resilience [ABSTRACT FROM AUTHOR]

Purpose: Project portfolio risk (PPR) management plays an important role in promoting the smooth implementation of a project portfolio (PP). Accurate PPR prediction helps managers cope with risks timely in complicated PP environments. However, studies on accurate PPR impact degree prediction, which consists of both risk occurrence probabilities and risk impact consequences considering project interactions, are limited. This study aims to model PPR prediction and expand PPR prediction tools. Design/methodology/approach: In this study, the authors build a PPR prediction model based on a genetic algorithm and back-propagation neural network (GA-BPNN) integrated with entropy-trapezoidal fuzzy numbers. Then, the authors verify the proposed model with real data and obtain PPR impact degrees. Findings: The test results indicate that the proposed method achieves an average absolute error of 0.002 and an average prediction accuracy rate of 97.8%. The former is reduced by 0.038, while the latter is improved by 32.1% when compared with the results of the original BPNN model. Finally, the authors conduct an index sensitivity analysis for identifying critical risks to effectively control them. Originality/value: This study develops a hybrid PPR prediction model that integrates a GA-BPNN with entropy-trapezoidal fuzzy numbers. The authors use this model to predict PPR impact degrees, which consist of both risk occurrence probabilities and risk impact consequences considering project interactions. The results provide insights into PPR management. [ABSTRACT FROM AUTHOR]

The article investigates the humorous reactions to two important controversies that received a great deal of attention in the Estonian public sphere during the summer of the year 2023. These are the Wagner group rebellion and the scandal involving Estonian Prime Minister Kaja Kallas. Building on theories of the public sphere and observations on how humour functions in such a context, by comparing the two cases, we tested the hypothesis that the content, form, humour mechanisms, and the comments on humour can be influenced by the nature of the controversy and by the psychological distance to the source of the initial triggering controversy. We used the data collected and coded within the CELSA1 network project "Humour and Conflict in the Public Sphere: An Interdisciplinary Analysis of Humour Controversies and Contested Freedoms in Contemporary Europe". The analysis revealed that 1) the most popular forms of humour in the online public sphere (primarily memes) are shaped by the patterns of the online communication in general and not by the particular cases or controversies; 2) humour mechanisms depend moderately on the nature of the controversy and their distance from the meme-makers; 3) content is most dependent on the nature of the controversy, and is affected by the tension between globalisation and localisation trends; and 4) the distance to the controversy influences the humorousness of the comments. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Highlight: Sound risk management implementation is well noted for helping organisations to overcome operational inefficiencies. However, the management of risk associated with construction materials vendors, and how they impact project operational performance appear to have not been extensively researched. Goal: In this study, the effect of materials vendor risk management (vendor risk identification and vendor risk prevention) on project operational performance (project quality and scheduled completion time) was investigated. We also interrogate the mediating role of risk-oriented culture in the relationship between vendor risk management and operational performance. Design/Methodology/Approach: The target population was all 1,044 registered public construction firms under the Urban Regeneration Programme in Nigeria. The cross-sectional survey design was adopted, and random sampling was used to select 173 project managers, engineers, surveyors, vendors/contractors, and store representatives. Primary data was collected through the structured questionnaire, they were analysed via the Structural Equation Modelling (SEM) technique. Results: Three main conclusions are made about managing vendor risks: First, properly identified materials vendor risks (in terms of material handling issues, price escalation, non-compliance to specification, delivery delay, and sharp procurement practices) is positively related to operational performance. Second, implementing context-specific risk prevention measures (prior assessment score, vendor financial capacity, warranty policy, continuous monitoring, technical capacity) positively enhances operational outcomes. Third, paying attention to risk culture orientation of project stakeholders positively impact their risk prevention capability and operational performance of construction projects. Limitations: Study was limited to few operational performance indicators in project management. Future study could include other performance indicators. Practical Implications: The results can help project operations managers in industry address numerous risks associated with materials vendor. Originality/Values: The numerous abandoned and failed construction projects in developing countries as a result of less attention to vendor risks management prompted this study. [ABSTRACT FROM AUTHOR]

Copyright of Public Health Forum is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Collaboration is challenging for complex project teams that have many subteams with diverse and complementary skills that are working toward shared goals. Knowledge transfer among subteams (i.e., project-level knowledge transfer) enhances integrative collaboration and results in behavioral changes within subteams (i.e., group-level knowledge transfer). However, there is a lack of quantitative evidence about how such project-level knowledge transfer influences group-level knowledge transfer behaviors. This study examined the change in knowledge transfer behaviors along with project progress, using the energy-efficiency subteam as an example. To achieve the goal, the authors collected longitudinal email exchanges and archival project data during the delivery of a complex construction project in the state of Michigan. Social network analysis and social influence models were utilized to analyze the change of knowledge-transfer networks over time. The results confirmed that exposure to project-level knowledge transfer positively predicts the subsequent group-level knowledge transfer behaviors during project delivery, measured by eigenvector centrality. The findings provide quantitative evidence explaining the importance of knowledge transfer behaviors in project communication: project-level knowledge transfers change members' attitudes and behaviors and subsequently improve individuals' influences in their respective project subteams. In addition, opinion leaders demonstrate a certain extent of resistance to the change. [ABSTRACT FROM AUTHOR]

Accurate estimation of activity durations is a critical project scheduling step. If abundant data are available for activity durations, then distribution fitting is straightforward. However, if sample sizes are small, then choosing an appropriate theoretical distribution for activity duration is challenging. In this study, we propose a methodology for experimenting with the impact of sample size on the accuracy of the estimated duration of a stochastic project network. We synthesized a total of 3,264 stochastic project networks and estimated the true project duration distribution for each network using large-sample Monte Carlo simulation. We varied the sample size per activity and investigated how the choice of theoretical distribution (normal, beta, triangular, and lognormal) for estimated activity durations impacted the accuracy of the estimated project duration distribution. We find that the best choice for a theoretical activity duration distribution highly depends on the sample size. For sample sizes below 50, we find that not much is gained from the common practice of putting extensive effort into selecting best-fit theoretical distributions compared to simply using normal distributions. [ABSTRACT FROM AUTHOR]

Continual Learning (CL) plays a crucial role in enhancing learning performance for both new and previous tasks in continuous data streams, thus contributing to the advancement of cognitive computing. However, CL faces a fundamental challenge known as the stability-plasticity quandary. In this research, we present an innovative and effective CL algorithm called Primary Null Space Projection (PNSP) to strike a balance between network plasticity and stability. PNSP consists of three main components. Firstly, it leverages the NSP-LRA algorithm to project the gradient of network parameters from previous tasks into a meticulously designed null space. NSP-LRA harnesses high-dimensional geometric information extracted from the feature covariance matrix through low-rank approximation algorithm to obtain the basis of null space dynamically. This process constructs an innovation null space and ensures the continuous updating of orthonormal bases to accommodate changes in the input data. Secondly, we propose a Consistency-guided Task-specific Feature Learning (CTFL) mechanism to tackle the issue of catastrophic forgetting and facilitate continual learning. CTFL achieves this by aligning feature vectors and maintaining consistent feature learning directions, thereby preventing the loss of previously acquired knowledge. Lastly, we introduce Label Guided Self-Distillation (LGSD), a technique that utilizes true labels to guide the distillation process and incorporates a dynamic temperature mechanism to enhance performance. To evaluate the effectiveness of our proposed method, we conduct experiments on the CIFAR100 and TinyImageNet datasets. The results demonstrate significant improvements over state-of-the-art methods. We have made the implementation code of our approach available for reference. • Proposal of PNSP method: Addresses stability-plasticity dilemma in continual learning. • NSP-LRA: Dynamically constructs null space for minimizing interference. • CTFL mechanism: Ensures consistent feature learning directions. • LGSD technique: Incorporates true labels and dynamic temperature for enhanced distillation. [ABSTRACT FROM AUTHOR]

To prevent the escalation of family problems, in 2018, Taiwan's government overhauled its multi-tiered prevention system and introduced multi-agency collaboration. The purpose of this paper is to uncover the real collaboration dynamics after policy reform. Twenty-eight frontline social workers from various tiers of the prevention system were interviewed. Qualitative analysis reveals that the status quo of collaboration was more complex than the policy document anticipated it would be. In particular, it often involved unequal power relationships between the participating agencies. The findings suggest that the government should go beyond functionalist thinking in future service reforms by considering power issues. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to further the understanding of multi-level analysis in inter-organisational relationships by investigating the interplay of governance, cooperation and coordination in inter-organisational projects (IOPs) on sub-system and project levels. Design/methodology/approach: The authors use the Viable Systems Model as a framework to analyse inter-organisational project governance, cooperation and coordination by adopting a multiple-case study. Findings: The findings illustrate how governance and coordination mechanisms exhibit a filter-down effect on lower sub-systems while cooperation influence is confined within each sub-system. While remarking the importance of specific sub-systems on the overall project performance, the interplay of governance, cooperation and coordination across sub-systems appears to be complex, with governance influencing cooperation and coordination, whereas cooperation and coordination influence each other with an incremental effect. Originality/value: This study defines two propositions that explain how multiple levels of analysis (project and sub-systems) can support the governance of large inter-organisational projects. The authors elaborate theory on the interplay of inter-organisational project governance, cooperation and coordination. [ABSTRACT FROM AUTHOR]

Considering the coevolution of interorganizational project and social networks, this study examines the evolution of research and development (R&D) cooperation by simulating the play of an appropriate game model. We assume that decision‐makers are aggressive or prudent in terms of expectations. The results show that the effects of expectation type and heterogeneity on cooperation evolution depend on the project scale. Aggressive decision‐makers are more sensitive to free‐riding behaviors than prudent decision‐makers. The effect of supervision on cooperation is contingent on decision‐makers' expectations. Finally, the study develops suggestions for the governance of interorganizational R&D cooperation. [ABSTRACT FROM AUTHOR]

Systemic risk refers to the potential for a disruption in one part of a financial system to trigger a cascade of adverse effects, impacting the functioning of the system. Despite the progress on novel systemic risk measures, research on dynamics of systemic risk network structure and its community effect is still in its initial state. In this study, we utilize price data from 107 representative Chinese stocks spanning the period from 2017 to 2022. A systemic risk network is derived from the Risk Transmission Index based on TENET and the QR–Lasso model. By utilizing DBSCAN, HITS and community detection algorithms on the network, we aim to propose a more suitable definition of systemically important companies, explore the interrelationships between companies, and discuss its plausible reasons for dynamics structural changes. The empirical findings demonstrate a substantial involvement of insurance companies in both contributing to and receiving systemic risk within the analyzed context. We identify prominent risk output and input centers, and emphasize the profound impact of the COVID-19 pandemic on the dynamics of systemic risk. [ABSTRACT FROM AUTHOR]

Problem definition: Intraproject learning in project scheduling involves the use of learning among the similar tasks in a project to improve the overall performance of the project schedule. Under intraproject learning, knowledge gained from completing some tasks in a project is used to execute similar later tasks in the same project more efficiently. We provide the first model and solution algorithms to address this intraproject learning problem. Academic/practical relevance: Intraproject learning is possible when, for example, the difficulty of the tasks becomes better understood, or the efficiency of the resources used becomes better known. Hence, it is necessary to explore the potential of intraproject learning to further improve the performance of project scheduling. Because learning consumes time, firms may underinvest in intraproject learning if they do not recognize its value. Although the project scheduling literature discusses the potential value of using obtained information from learning within the same project, we formally model and optimize the use of intraproject learning in project scheduling. Methodology/results: We model the tradeoff between investing time in learning from completed tasks and achieving reduced durations for subsequent tasks to minimize the total project cost. We show that this problem is intractable. We develop a heuristic that finds near optimal solutions and a strong relaxation that allows some learning from partially completed tasks. Our computational study identifies project characteristics where intraproject learning is most worthwhile. In doing so, it motivates project managers to understand and apply intraproject learning to improve the performance of their projects. A real case is provided by a problem of the Consumer Business Group of Huawei Corporation, for which our model and algorithm provide a greater than 20% improvement in project duration. Managerial implications: We find consistent evidence that projects in general can benefit substantially from intraproject learning, and larger projects benefit more. Our computational studies provide the following insights. First, the benefit from learning varies with the features of the project network, and projects with more complex networks possess greater potential benefit from intraproject learning and deserve more attention to learning opportunities; second, noncritical tasks at an earlier project stage should be learned more extensively; and third, tasks that are more similar (or have more similar processes) to later tasks also deserve more investment in learning. Learning should also be invested more in tasks that have more successors, where knowledge gained can be used repetitively. Funding: This work was supported by the National Natural Science Foundation of China [Grant 71732003 to N. G. Hall and Grants 72131010 and 72232001 to W. Zhao], the Shanghai Subject Chief Scientist Program [Grant 16XD1401700 to G. Wan], and the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning [Grant TP2022019 to W. Zhao]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0159. [ABSTRACT FROM AUTHOR]

The Middle Route of South-to-North Water Diversion Project (MRSNWD) is the main skeleton of China's National Water Network, its construction has changed the structure of the original water network, and analyzing the topological change of the water network in context with MRSNWD is significant for water network planning and management. In this study, the overall network characteristics of the water network in 2010 and 2020 were analyzed based on the small-world and scale-free characteristics of complex network theory. The topological changes of the water network from a node perspective were examined using three network centrality indexes: degree centrality (DC), closeness centrality (CC), and betweenness centrality (BC), while assessing the important nodes of the water network and recognizing functional areas of cold-hot spots. The results show that the water network's centrality in the study area improved after the project construction, with the average degree of the water network increasing from 2.39 to 2.42 and the average path length decreasing from 111.81 to 97.08. The propagation efficiency and network stability also increased, with a rise in important node proportion from 9.8 to 14.4%. The nodes in the DC hotspot zone along the project route have increased by 1.5%, implying an increase in the connectivity of the water network, while MRSNWD optimizes its north–south hub propagation path. "Small-worldness" indicates that most nodes of a network can be accessed and connected over shorter paths. The water network has a significant "small-worldness" and has been enhanced by the MRSNWD's construction. Approximating the water network as a scale-free network can impact its security by identifying critical nodes. The results of this research can provide the necessary technical support and reference significance for China's National Water Network. [ABSTRACT FROM AUTHOR]

The available slack-based methods for measuring the robustness of schedule networks do not pay sufficient attention to the structural characteristics of such networks nor do they provide a comparison point for measuring the sensitivity to changes. This research fills these gaps by addressing a core research question: How can an integrative measure of schedule robustness be developed? To answer this question, this paper performs a centrality analysis to capture the structural characteristics of the schedule network. Further, it draws on the concept of perfect uniformity to establish a baseline for measuring the degree of schedule sensitivity to disruptions. Finally, it uses entropy theory to develop an integrative measure of schedule robustness by combining two classes of robustness measures: quality and solution robustness. An experimental analysis is undertaken to evaluate the statistical performance of the new measure. The validation results show a high inverse correlation between the proposed measure and a cost-based indicator of schedule performance; in turn, proving the better performance of the new measure compared to the two widely discussed and quoted slack-based measures of robustness. This can be ascribed to the ability of the new measure to simultaneously capture various attributes of a schedule network. The results of this research can assist decision makers in making informed decisions in the appraisal and monitoring phases of construction projects. This research provides the opportunity for future studies to extend the proposed method by incorporating resource-constrained and cost-related attributes of project activities into the formulation of schedule robustness. [ABSTRACT FROM AUTHOR]

This study aimed (a) to understand the actual state of reference relations in RDA guidelines and instructions, expressed as RDF data, and (b) to grasp its characteristics at a global level by applying network analysis to those reference relations. The reference relations were examined and extracted from four datasets – RDA guidelines, instructions on entities, and those on Manifestation and Work elements. Furthermore, they were aggregated by source and destinations. The characteristics of the four graphs formed by the reference relations were analyzed using measures such as centrality. [ABSTRACT FROM AUTHOR]

This paper presents the results of applied research on the Adriatic linear city (Marche, Abruzzo) aimed at building an innovative cognitive framework through GIScience methods/techniques (geodata processing, remote sensing, and scientific indexes) to support the first analytical phase of the A_GreeNet Life+ project and its aims. In particular, the paper shows the different methodological steps necessary to produce a risk map and multi-thematic geodatabase in a GIS (Geographic Information Systems) environment based on open data. The research results lay the foundations for new ways and different perspectives of investigating the urban landscape in line with the process of renewing cognitive tools for urban planning. Starting with the cognitive framework developed, the project partnership network will be scaled down for the second analysis phase aimed at prefiguring a new scenario for forestation and redeveloping the landscapevegetation system with the support of the related administrations and in accordance with the current planning framework. [ABSTRACT FROM AUTHOR]

"Project Management Blunders: Lessons from the Project That Built, Launched, and Sank Titanic" by Mark Kozak-Holland is a book that explores the project management techniques used during the construction and sinking of the Titanic. The book provides a chronological account of the Titanic's story, including its design, passengers and crew, the collision, and the rescue efforts. It emphasizes the importance of risk assessment, communication and collaboration, stakeholder management, and contingency planning in project management. The book offers valuable lessons that can be applied to modern-day project management practices. [Extracted from the article]

Predicting pavement rutting is associated with significant uncertainties that often lead to inefficient maintenance planning. The predictive performance of rutting models is exacerbated in local road agencies and developing countries that rely on generic and knowledge-based models which are typically unreliable if used without adaptation, validation, or calibration. This study aims at developing a probabilistic framework that employs Ensemble Kalman Filter (EnKF) techniques to update the parameters associated with generic rutting predictive models while accounting for the prevailing uncertainties. When coupled with a continuous influx of measured data, the EnKF framework sequentially updates the generic models and minimizes prediction errors in real-time. The robustness of the presented scheme is demonstrated through a numerical example, and its sensitivity to the use of different generic curves as starting points is examined. The results indicate that the EnKF framework improves the accuracy of rutting predictions by up to 60% and that accuracy remains within tolerable limits whilst varying the range of the uncertainty in the measurements or the initial states. The paper concludes with a discussion of how practitioners can integrate the outcomes of the presented framework to enact maintenance policies that minimize the financial cost at the project and network levels. [ABSTRACT FROM AUTHOR]

The majority of the projects funded under the European Research Framework Programme (FP) require a collaborative effort in order to tackle complex societal challenges. The underlying assumption is that collaborative networks boost research productivity and the attainment of the goals set out by the European Commission's agenda. In general, the production of scientific knowledge increasingly takes place within networks and consortia with a wide diversity and interlinkages of disciplines, expertise, backgrounds and approaches. This relational dimension has become even more important in the Horizon Europe FP, which has moved from a project-focused to a mission-oriented approach whereby a portfolio of projects is managed in coordination in order to stimulate cross-learning and experimentation. Starting from key concepts and theories of evaluation research, including ten years of experience for the Italian National Research Council (CNR) team as an internal evaluator, we are proposing a new approach, namely a Relations-based Evaluation (RE) approach, that analyses, assesses and builds relationships, both internal and external, with the ultimate aim of supporting collaborative research and innovation (R&I) projects. The framework originated within the context of EU projects and deals with the specific case of consortia funded under the EU FPs. However, it could be easily applied to other types of research consortia and project networks with similar features. [ABSTRACT FROM AUTHOR]

Based on the 5G renovation project for public network coverage in tunnels of the Shandong section of Beijing-Shanghai High-speed Railway, this paper studies the scheme for such issues as leakage cable selection, link budget, power supply, and transmission. After analyzing the existing situation of the public network equipment, it proposes the integrated renovation of the existing public network equipment and its supporting power supply and transmission optical cables, which provides design experience for similar projects in the future. [ABSTRACT FROM AUTHOR]

Purpose: This study investigates the impact of network positions on inter-team conflicts and project success in megaprojects. Design/methodology/approach: Network position is measured with centrality and structural holes. Substantive conflict and affective conflict reflect inter-team conflicts. A questionnaire survey was implemented in Chinese megaprojects, and 309 valid questionnaires were collected. The data were analyzed using structural equation modeling and bootstrapping methods. Findings: The results show that centrality negatively impacts project success, while the presence of a team in a structural hole has no significant impact on project success. Centrality is negatively related to substantive conflict and is positively related to affective conflict. The team in a structural hole has a positive effect on substantive conflict and a negative effect on affective conflict. Substantive conflict and affective conflict have positive and negative effects on project success, respectively. The effect of network position on project success is mediated by inter-team conflict. Research limitations/implications: This research provides a reference for megaproject managers to better conduct network governance, manage inter-team conflict, and successfully manage projects. The study did not investigate the effects of changes in teams' network positions on project success. Future research should explore this facet of megaprojects. Originality/value: This research adds to existing research on network position, and reveals that project network governance is important for megaproject success. This provides a new direction for megaproject management. Furthermore, the results validate constructive and non-constructive roles and the mediating role of inter-team conflict. This complements the literature on conflict management, providing a reference for megaproject managers when managing inter-team conflict. [ABSTRACT FROM AUTHOR]

Construction projects are inherently distinguished by their unique durations and associated costs, factors which are pivotal in determining project efficiency and quality, and consequently impacting broader societal development. The inherent unpredictability intrinsic to these projects presents significant challenges in completing them within established schedules and budgets. This unpredictability stems largely from the distinct nature of building operations, rendering the task of construction management analysis multifaceted and complex. In addressing these challenges, the present study explores the influence of architectural building specifics on the cost and duration estimations of construction projects through the application of artificial neural networks (ANNs). Recognized for their robust capacity to generalize from complex input-output relationships within extensive datasets, ANNs were employed to analyze a database incorporating six input variables: the number of activities, the total area of the building, the type of foundation, the number of storeys, the classification of consumers and vendors, alongside two output variables, namely cost and duration. The findings reveal that construction projects entrusted to individual or small-scale contractors are more susceptible to fluctuations in cost and duration compared to those managed by larger or multi-company contractors. The selection process for contractors was significantly influenced by the factors of bidding cost and negotiation fees, with clients possessing higher financial resources more frequently opting for larger companies. The research incorporated the development of a sophisticated intelligent model in MATLAB, utilizing a feed-forward back-propagation network for analysis. The efficacy of the ANN model was rigorously evaluated against statistical benchmarks, focusing on loss-function parameters. A strong correlation was unveiled between the ANN model predictions and the empirical data, as evidenced by an exemplary average coefficient of determination (R2) of 0.99995, markedly outperforming the multiple linear regression (MLR) model, which yielded a result of 0.6986. Additional performance metrics, including the mean absolute error (MAE) of 0.2952 and the root mean square error (RMSE) of 0.5638, attested to the model's robustness. Through the implementation of this research, a significant contribution is made towards enhancing the precision of resource and time estimations for clients and contractors undertaking construction projects, while concurrently accounting for the principal constraining factors. [ABSTRACT FROM AUTHOR]

Maintenance, Refurbishment and Network Upgrading Systems occupy a prominent place among service systems, especially due to their dispersed location and large territorial extent. For the efficient opertaion of these systems, it is essential to apply Project Oriented Management (POM), which aims at optimizing logistic processes and meeting project specific requirements. [ABSTRACT FROM AUTHOR]

How do inter-organizational networks emerge? We address this question using an equilibrium framework where firms' decisions to form links with other firms are modeled as a strategic game. In this game, firms weigh the costs and benefits of establishing a relationship with other firms and form ties if their net payoffs are positive. We characterize the equilibrium networks as exponential random graphs (ERGM), and we estimate the firms' payoffs using a Bayesian approach. We apply the framework to a co-investment network of venture capital firms in the medical device industry, providing economic interpretations ERGM parameter estimates. We learn that firms rely on their joint partners (transitivity) and prefer to form ties with firms similar to themselves (homophily). These results hold after controlling for the interdependence among ties. Our structural approach allows us to simulate the effects of economic shocks or policy counterfactuals. We test two such policy shocks, namely, firm entry and regulatory change. We show that while entry of few firms does not have meaningful effects on the shape of the network, a regulatory shock of minimum capital requirements increases the co-investment network's density and clustering. [ABSTRACT FROM AUTHOR]

Widespread adoption of Building Information Modeling (BIM) is firmly on policy agenda in several countries. Despite emphasis on governments' ambitions for industry-wide BIM adoption, there is scant understanding about what construction firms need to do regarding training provision and how to do that to meet policy goals. There is, therefore, little evidence of how construction companies have tackled this challenge internally and on projects in existing studies. Through a qualitative research approach and case studies of two leading UK construction companies, this paper describes the different strategies that construction companies adopt to provide the requisite skills and training for their workforce and their project supplier network partners to successfully support and sustain the implementation of BIM. The findings show that successful main contractors employed an "in-house" training strategy at intra-organizational level and a "growing together" approach for their project supplier network partners. In providing BIM training, these firms tackled problems of heterogeneity in workforce digital literacy and competencies, a lack of attention to soft skills, and a lack of understanding of BIM benefits using tailored and role-specific training. These insights contribute to the growing literature on BIM training, complementing the existing literature that focuses mainly on BIM training through education. [ABSTRACT FROM AUTHOR]

Simultaneously acquiring broad clinical knowledge and scientific expertise is a major challenge for young clinical scientists. Female researchers may face additional hurdles in their career, for example, due to unconscious bias. We aimed to address clinical, research, and gender‐related challenges among young female clinical neuroscientists. We implemented a peer‐led networking group dedicated to increasing clinical and scientific knowledge, improve soft skills, and encourage exchange between fellow residents. In monthly meetings, two participants hold short presentations on a clinical topic or scientific method, followed by a discussion and feedback to the presenter. Afterwards, participants network and discuss challenges they face in their daily experience. Nine neurology residents at a Swiss University Hospital with ≤3 years of training participated in the Connecting Women in Neurosciences project from August 2020 to June 2021. In a qualitative evaluation, participants reported they felt empowered by these meetings and profited from their new network. We identified several challenges in combining clinical and research activities, some of which participants perceived to be gender‐related. In addition to women‐only meetings, we will promote events addressing all interested researchers. Peer‐to‐peer networking is an easy and low‐budget intervention to encourage female residents to engage in research activities, profit from each other's expertise, and promote interdisciplinary teamwork. It can provide a protected environment to discuss and overcome in particular gender‐related challenges. We encourage young colleagues to regularly engage in structured networking activities with their local peers. [ABSTRACT FROM AUTHOR]

Estimating software effort is an essential project management practice. The software effort estimation is the process of predicting the time and efforts required in the development of software projects. Estimating software cost is a critical challenge during the planning stage. Due to the lack of availability of quality data and the dynamic nature of software development, accurate estimation is difficult. This paper proposes an efficient software cost estimation method for the Genetic Elephant Herding Optimization-based Neuro-Fuzzy Network (GEHO-based NFN). In this method, a neuro-fuzzy network (NFN) is used to predict the software efforts in terms of cost. The training of this NFN is optimized using the genetic elephant herding optimization (GEHO) method, which combines the features of the genetic algorithm (GA) and the elephant herding optimization (EHO) techniques. The performance of the developed method was evaluated using five historical & benchmark datasets from the industrial projects. These are based on the four widely used performance evaluation metrics, such as Mean magnitude of relative Error (MMRE), Median magnitude of relative error (MdMRE), Root Mean Square Error (RMSE), and Prediction Accuracy (PRED). The Comparative analysis and experimental results of the proposed method conclude that the performance of the GEHO-based NFN method is better than other popular soft computing methods like Linear regression, Support Vector Regression (SVR), Wavelet ANN (WNN), and Decision Tree (DT) based Software project effort estimation (SPEE) methods. [ABSTRACT FROM AUTHOR]

Urban ecology is a rapidly growing research field that has to keep pace with the pressing need to tackle the sustainability crisis. As an inherently multi‐disciplinary field with close ties to practitioners and administrators, research synthesis and knowledge transfer between those different stakeholders is crucial. Knowledge maps can enhance knowledge transfer and provide orientation to researchers as well as practitioners. A promising option for developing such knowledge maps is to create hypothesis networks, which structure existing hypotheses and aggregate them according to topics and research aims. Combining expert knowledge with information from the literature, we here identify 62 research hypotheses used in urban ecology and link them in such a network. Our network clusters hypotheses into four distinct themes: (i) Urban species traits & evolution, (ii) Urban biotic communities, (iii) Urban habitats and (iv) Urban ecosystems. We discuss the potentials and limitations of this approach. All information is openly provided as part of an extendable Wikidata project, and we invite researchers, practitioners and others interested in urban ecology to contribute additional hypotheses, as well as comment and add to the existing ones. The hypothesis network and Wikidata project form a first step towards a knowledge base for urban ecology, which can be expanded and curated to benefit both practitioners and researchers. [ABSTRACT FROM AUTHOR]