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As the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these design teams often find it difficult to handle these design changes due to the complexity and interdependencies inherent in engineering systems. This paper aims to develop an innovative approach to clarifying system interdependencies and predicting the design change propagation at the asset level in complex engineering systems based on the digital-twin-driven design structure matrix (DSM).

The paper first defines the digital-twin-driven DSM in terms of elements and interdependencies, where the authors have defined three types of interdependency, namely, geospatial, physical and logical, at the asset level. The digital twin model was then used to generate the large-scale DSMs of complex engineering systems. The cluster analysis was further conducted based on the improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) to decompose such DSMs into modules for the convenience and efficiency of predicting design change propagation. Finally, a design change propagation prediction method based on the digital-twin-driven DSM has been developed by integrating the change prediction method (CPM), a load-capacity model and fuzzy linguistics. A section of an infrastructure mega-project in London was selected as a case study to illustrate and validate the developed approach.

The digital-twin-driven DSM has been formally defined by the spatial algebra and Industry Foundation Classes (IFC) schema. Based on the definitions, an innovative approach has been further developed to (1) automatically generate a digital-twin-driven DSM through the use of IFC files, (2) to decompose these large-scale DSMs into modules through the use of IGTA-Plus and (3) predict the design change propagation by integrating a digital-twin-driven DSM, CPM, a load-capacity model and fuzzy linguistics. From the case study, the results showed that the developed approach can help designers to predict and manage design changes quantitatively and conveniently.

This research contributes to a new perspective of the DSM and digital twin for design change management and can be beneficial to assist designers in making reasonable decisions when changing the designs of complex engineering systems.

Typically, organizations tumble with project management, and failure rates are high. Usually, one key factor in establishing a manageable and successful project portfolio is to take into account interdependencies between different projects (resources, technology and market). With an increasing amount of international cross‐border project activity, it is vital to know how different countries manage interdependencies, and how management practices differ between countries.

This research bases its empirical findings on a large‐scale questionnaire completed during 2007‐2008 in Estonia and Finland. Altogether, 288 responses were gained, and roughly two‐thirds of the answers originated from Finland and one‐thirds from Estonia. Respondents were industrial and service companies.

The results of the survey indicate similarities and some significant differences between Estonian and Finnish responses. Some country size and context‐dependent hypotheses were not supported or only weakly supported, indicating great homogeneity between managerial issues of interdependency internationally. However, existing significant differences may stem from historical and cultural reasons, such as, peculiarities of transition country compared to mature country.

The main limitation arises from the analyzed sample, which was mostly limited to information and communication technologies, engineering, machinery and construction industries and thus the findings may not be directly applicable to other industries. Because responses originate only from two Finno‐Ugrian countries, this limits the generalizability of the research results directly into other regions and countries.

Managing interdependencies between projects has a clear practical significance, and it appears in companies in both of the countries in the form of bringing additional value, saving costs and in increasing the success rate of projects. In addition, international project owners can find differences in their daily work.

This research provides empirical evidence for the less investigated, but emerging field of interdependency phenomenon of project management. To the authors' knowledge, no research to date concerns cross‐country comparison.

The purpose of this study is to analyze the connections between centrality within conflict networks, individual performance, and job satisfaction from the perspective of social networks. The intervening effects of task interdependency on these connections are also examined.

Using the social network survey approach, the empirical data from 310 engineers of a large R&D Institute affiliated with the Ministry of National Defense in Taiwan were collected.

The results show that centrality within relationship conflict networks was negatively related to individual performance and job satisfaction. However, centrality within task conflict networks was positively related to individual performance and job satisfaction Task interdependency mitigates the negative influence of relationship conflicts on individual performance and job satisfaction, and the positive influence of task conflict on job satisfaction.

As the evidence in this study came from the employees of one organization, future studies should corroborate findings by surveying more organizations.

The findings have important implications for individual social networks. Within the conflict network, people who occupy the central position of relationship conflict have a negative impact on performance and job satisfaction.

This study contributes to the literature on social networks and conflicts theory by demonstrating the concept of centrality within conflict networks. In addition, it also demonstrates that the centrality of conflict network is an important factor in influencing individual performance and job satisfaction.

The purpose of this paper is to improve decision quality, and therefore project and portfolio success, by testing the influence of different visual representations of interdependency data in a simulated decision experiment. A network mapping approach to visualize project interdependencies is introduced and compared with matrix and tabular displays.

A simulated decision task in a controlled classroom setting tested five hypotheses though a sample of 480 experiments.

The type of data representation used is associated with differing levels of decision quality, and the use of network mapping displays is aligned with the best results.

The findings are limited as this experiment-based study presented a simplified decision scenario and involved students rather than practicing managers. The findings are best interpreted in combination with organization-based research.

The findings of this study suggest that visual data displays, particularly network mapping displays, can provide benefits and improve project portfolio decision quality. Managers may draw upon this study to design ways to include visual data representations in their project portfolio management decision processes.

This study uses experimentation to complement organization-based studies to better understand the influence of different methods of visualizing data and managing interdependencies between projects. This research provides an important contribution to meet the acknowledged need for better tools to understand and manage project interdependencies.

Market leaders are constantly being forced to evaluate and modify their relationships and interactions with suppliers, buyers, and even competitors, in order to remain competitively viable in response to marketplace, technology, and competitive changes. Presents the Interdependency Cube framework which allows businesses to identify their current positions relative to their partners, and develop an understanding of what needs to be done in order to change their interdependency relationships. Real‐world examples illustrate different cells within the framework and demonstrate how a company can simultaneously, and successfully, have different types of strategic interdependencies with a number of partners, depending on the environment in each case. Managers can learn how vigilance and flexibility are vital to a company’s ability to change as its situation and circumstances change.

One of the typical issues in supply chain management (SCM) implementation is how to capture the complexities of supply chains. This paper reviews the existing supply chain modelling methods, and identifies the limitations of current methods. Based on these, a novel co‐ordinated supply chain modelling approach is proposed to capture the complexity of supply chains from the views of scenario, interdependency, process and information. The proposed method is comprehensive, inclusive and aims to capture the complexities of a supply chain, align supply chain processes, and provide the basis for supply chain integration.

The purpose of this paper is to show how interdependencies are used to make the project selection and review more effective in project portfolio management. Managers need to make appropriate pre‐evaluation of disciplines before taking them into use, therefore it is useful to know how much interdependencies can increase the success rate of projects and how big is the resource reduction from the use of interdependencies. This paper is an excerpt of a larger interdependency survey.

A large‐scale survey is carried out in two countries – Estonia and Finland. A total of 288 responses were received.

People see only positive aspects in interdependencies, but this paper proves that it is not always so. It is found that companies which take the phenomenon into account are more successful. Contrary to the respondents' perception and prior literature, a higher need for resources is noticed among the users of interdependency. The results indicate homogeneity between managerial issues of interdependencies in small‐to‐large companies.

The main limitation comes from the sample, as findings from the sample countries and industries may limit generalizability.

Practitioners can expect a higher success rate and resource consumption from interdependencies. Managers from small‐to‐large companies can find size‐related peculiarities and practices for their daily managerial actions.

This paper provides empirical evidence for a less investigated, but emerging field of interdependencies. So far, mostly components of interdependency have been investigated in isolation. The paper highlights the behavior of success rate and resource consumption among the users/non‐users of interdependency, which to the author's knowledge has not been provided so far.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

The purpose of this research is to detect, through applying a process-based view, how to manage economisation of the maintenance and modification operations in offshore petroleum logistics operations.

A single case study of engineering services, more specifically, maintenance and modification service operations, on a Norwegian Sea oil platform reveals the dynamics of building network capabilities in a consistent network structure. Two layers of coordination are studied: the engineering process and its context, represented by its network of interconnected firms. This case study empirically grounds how engineering service involves managing reciprocally interdependent exchange processes in the network structure.

Pooled interdependencies are vital in understanding the nature of service provision and use, and sequential interdependencies are vital in narrating the timing of processes to reveal the nature of process emergence to coordinate strings of production events. Furthermore, the network structure, when characterised by multiple interdependent projects, is also dynamic but at a slower pace.

Through the case study, operations management is revealed to be associated with project emergence at two levels: the core process level regarding daily continuous change, including the changing interaction of multiple different and interdependent projects, and the contextual level, where features of interdependency and integration change, affecting engineering service production. This provides guidance as to the economisation of engineering services. They change not only interactions in the flow of production but also its context.

The purpose of this paper is to present a novel approach that examines the vulnerability and interdependency of critical infrastructures using the network theory in geographic information system (GIS) setting in combination with literature and government reports. Specifically, the objectives of this study were to generate the network models of critical infrastructure systems (CISs), particularly electricity, roads and sewerage networks; to characterize the CISs’ interdependencies; and to outline the climate adaptation (CA) and flood mitigation measures of CIS.

An integrated approach was undertaken in assessing the vulnerability and interdependency of critical infrastructures. A single system model and system-of-systems model were operationalized to examine the vulnerability and interdependency of the identified critical infrastructures in GIS environment. Existing CA and flood mitigation measures from government reports were integrated in the above-mentioned findings to better understand and gain focus in the implementation of natural disaster risk reduction (DRR) policies, particularly during the 2010/2011 floods in Queensland, Australia.

Using the results from the above-mentioned approach, the spatially explicit framework was developed with four key operational dimensions: conceiving the climate risk environment; understanding the critical infrastructures’ common cause and cascade failures; modeling individual infrastructure system and system-of-systems level within GIS setting; and integrating the above-mentioned results with the government reports to increase CA and resilience measures of flood-affected critical infrastructures.

While natural DRR measures include preparation, response and recovery, this study focused on flood mitigation. Temporal analysis and application to other natural disasters were also not considered in the analysis.

By providing this information, government-owned corporations, CISs managers and other concerned stakeholders will allow to identify infrastructure assets that are highly critical, identify vulnerable infrastructures within areas of very high flood risk, examine the interdependency of critical infrastructures and the effects of cascaded failures, identify ways of reducing flood risk and extreme climate events and prioritize DRR measures and CA strategies.

The individualist or “pigeon-hole” approach has been the common method of analyzing infrastructures’ exposure to flood hazards and tends to separately examine the risk for different types of infrastructure (e.g. electricity, water, sewerage, roads and rails and stormwater). This study introduced an integrated approach of analyzing infrastructure risk to damage and cascade failure due to flooding. Aside from introducing the integrated approach, this study operationalized GIS-based vulnerability assessment and interdependency of critical infrastructures which had been unsubstantially considered in the past analytical frameworks. The authors considered this study of high significance, considering that floodplain planning schemes often lack the consideration of critical infrastructure interdependency.