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This paper seeks to develop an approach to problem localization and an algorithm to address the issue of determining the dependencies among system metrics for automated system management in ubiquitous computing systems.

This paper proposes an approach to problem localization for learning the knowledge of dynamic environment using probabilistic dependency analysis to automatically determine problems. This approach is based on Bayesian learning to describe a system as a hierarchical dependency network, determining root causes of problems via inductive and deductive inferences on the network. An algorithm of preprocessing is performed to create ordering parameters that have close relationships with problems.

The findings show that using ordering parameters as input of network learning, it reduces learning time and maintains accuracy in diverse domains especially in the case of including large number of parameters, hence improving efficiency and accuracy of problem localization.

An evaluation of the work is presented through performance measurements. Various comparisons and evaluations prove that the proposed approach is effective on problem localization and it can achieve significant cost savings.

This study contributes to research into the application of probabilistic dependency analysis in localizing the root cause of problems and predicting potential problems at run time after probabilities propagation throughout a network, particularly in relation to fault management in self‐managing systems.

This paper explains why some firms manage to capture disproportionate value from their network of relationships, leading to superior performance. The paper examines how a firm's dependencies affect its value appropriation potential (VAP) in economic networks.

The paper follows the axiomatic method and the embeddedness perspective of firms to develop an index called nodal power, which captures the power that accrues to a firm in exchange-based economic networks. Thereafter, using the formal method and simulation, it shows nodal power reflects a firm's VAP in economic networks.

The study analysis and findings prove that a firm's dyadic level exchange relations and the embedded network structure determine its VAP by affecting the nodal power. A firm with lesser nodal power is likely to appropriate less value from its relations even if it equally contributes to the value creation. This finding explains how the structural and relational characteristics of a firm's network enable disproportionate value appropriation.

Nodal power furthers the scope of analyzing firms' economic relationships and changing power equations in dynamic networks. It can help firms build optimal strategic networks and manage the portfolio of relationships by predicting the impact of changing relations on firms' VAP.

The paper's original contribution is to explain, through formal analysis, why and how the structure and nature of relations of firms affect their VAP. The paper also formalizes the power-dependence principle through a dependency-based index called nodal power and uses it to show how interfirm dependencies are key to value appropriation.

To better understand the success of an open source software (OSS) project, this study aims to examine the role of social dependency networks (i.e. social and technical dependencies) in online communities.

This study focuses on dependencies using three network metrics – degree centrality, betweenness centrality and closeness centrality – in developer and module networks. A longitudinal analysis from the projects hosted at Sourceforge.net is conducted to examine the effects of social and technical networks on the success of OSS projects. To address our research questions, we have constructed research models to investigate the social network effects in developer networks, the technical network effects in module networks, and the social-technical network effects in both types of networks.

The results reveal nonlinear relationships between degree centrality in both social and technical networks and OSS success, highlighting the importance of a moderate level of degree centrality in team structure and software architecture. Meanwhile, a moderate level of betweenness centrality and a lower level of closeness centrality between developers lead to a higher chance of OSS project success.

This study is the first attempt to consider the network metrics in both module networks of the technical sub-system and developer networks of the social sub-system to better understand their influences on project success.

Building on the transaction cost theory and power structure literature, this paper aims to investigate the extent to which firms use two safeguarding mechanisms (supply chain relational investments and electronic collaboration) in different network dependency contexts in order to protect their portfolios of business relationships.

Empirical evidence is gathered though a survey data conducted with 159 firms in the wireless communication sector. The paper tests the assumption that the two safeguarding mechanisms are used to a greater extent in interdependency‐intensive networks than in other supply chain contexts.

This empirical study suggests that: in a network‐dependent context, relational investments allow firms to safeguard their portfolios of relationships; electronic collaboration seems to be a safeguarding mechanism for firms in downstream‐dependent network contexts; in general, firms appear to use both relational investments and electronic collaboration to manage their relationships in a supply chain network; and the knowledge‐based theory may explain the strong relationship between upstream and downstream use of electronic collaboration.

Overall, the present study complements the extant literature on supply chain management and inter‐firm electronic collaboration by showing how an important structural characteristic of supply chain networks (i.e. dependency) operates on the choice of using two key safeguarding mechanisms.

Results stress the importance of these safeguarding mechanisms in joint actions such as collaborative planning, forecasting and replenishment.

The paper addresses interdependencies from a network perspective which encompasses the firms' complete portfolio of relationships.

Most research on greening of industry using a network approach has the firm as smallest unit of analysis. In addition, few have focused on technological regimes. The purpose of this paper is to address these issues through research on the firm‐internal network of two automotive firms, the actors, resources and activities of their networks, and how change initiatives in the firm forge and dissolve external networks of alternative regimes.

The case study is based on an insider/outsider research methodology. The specific issues of contextual and temporal boundaries in case research with a network approach were addressed through a relatively open‐ended process of inquiry during which these boundaries emerge and unfold. In terms of data collection, interviews with project team members in the two focal companies were conducted.

Failure or success is not only a matter of how the alternative regime fits into its cultural ambience in society and how successful that mutual adaptation is, but also equally of how it fits into the firm and the firm‐internal mutual adaptation. Particularly established companies may experience alternative regimes as threats to the established business, even when these regimes are developed inside the firm. In addition, the actors‐resources‐activities model reveals important resource dependencies between established technologies and the alternatives to them. Most likely, such dependencies constitute important complementary causes as to why eco‐ordering endeavors often fail.

The network approach having a mesh that goes into the firm reveals important factors to the outcome of eco‐ordering efforts. The actors‐resources‐activities analyzing tool helped find important non‐human resource dependencies.

Large supply and computer networks contain heterogeneous information and correlation among their components, and are distributed across a large geographical region. This paper aims to investigate and develop a generic knowledge integration framework that can handle the challenges posed in complex network management. It also seeks to examine this framework in various applications of essential management tasks in different infrastructures.

Efficient information and knowledge integration technologies are key to capably handling complex networks. An adaptive fusion framework is proposed that takes advantage of dependency modelling, active configuration planning and scheduling, and quality assurance of knowledge integration. The paper uses cases of supply network risk management and computer network attack correlation (NAC) to elaborate the problem and describe various applications of this generic framework.

Information and knowledge integration becomes increasingly important, enabled by technologies to collect and process data dynamically, and faces enormous challenges in handling escalating complexity. Representing these systems into an appropriate network model and integrating the knowledge in the model for decision making, directed by information and complexity measures, provide a promising approach. The preliminary results based on a Bayesian network model support the proposed framework.

First, the paper discussed and defined the challenges and requirements faced by knowledge integration in complex networks. Second, it proposed a knowledge integration framework that systematically models various network structures and adaptively integrates knowledge, based on dependency modelling and information theory. Finally, it used a conceptual Bayesian model to elaborate the application to supply chain risk management and computer NAC of this promising framework.

Contends that path‐dependency provides an accurate, but under‐theorised description of organisational behaviour. By incorporating insights from actor‐network theory, we can better understand the processes by which organisations become “locked‐in” to behaviour patterns, but also how we might begin to break free from them. It seems that we must pay greater attention to the role of durable materials in networks, and to the strategies of simplification employed within organisations to deal with the complexity that surrounds them. In order to understand path‐dependency we must also look wider than traditional management theory towards a more semiotic understanding of organisational communication. All of these findings point to managers having to reconsider their role, especially with regard to the power that they may or may not hold, and to move towards an approach based more on the governance of their organisations than attempting to control every aspect under their jurisdiction. Concludes by providing some appropriate strategies through which this might be achieved.

The building design processes today are complex, involving many disciplines and issues like collaboration, concurrency and collocation. Several studies have focused on understanding and modeling formal information exchange in these processes. Few past studies have also identified the importance of informal information exchanges in the design process and proposed passive solutions for facilitating this exchange. The purpose of this paper is to term the informal information as ad hoc information and explores if components of ad hoc information exchanges can be actively managed.

An MDM-based framework integrating product, process and people dependencies is proposed and a prototype platform to implement this framework is developed. The demonstration on the usage of this platform to identify information paths during collaboration and hence manage ad hoc information exchanges is presented through an example problem.

Based on the effectiveness of the prototype platform in identifying information paths for design queries, it is concluded that the proposed framework is useful for actively managing some components of ad hoc information exchange.

This research enables the design manager/participants to make a more informed decision on requesting and releasing design information.

The purpose of this paper is to develop a conceptual framework for the analysis of supply network disruptions and present a number of propositions to define a future research agenda. In doing so, it draws on a review of the literature regarding supply chain disruptions; relationship formation and evolution; and network formation and evolution.

The literature review combined traditional contextual analysis with citation analysis and co‐citation, assuming a multi‐level, multi‐theoretical perspective.

The findings highlight a paucity of empirical research regarding supply chain disruptions assuming a network perspective, highlighting the dynamic nature of networks and emphasising the difference between supply chain disturbance and disruption.

The paper stops short of testing specific hypotheses, providing a conceptual framework and a series of propositions from which testable hypotheses can be developed. The necessity of assuming a dynamic, multi‐level, multi‐theoretical perspective highlights the difficulties of empirical research in this area. However, the significance of understanding the network context of disruption and its connection to the securing of appropriate responses and ultimately reasonable mitigation is unavoidable.

The ability to understand the implications of network structure and network relational dynamics in the context of disruption will enable managers to respond appropriately to disruptive supply chain events. This capability will assume increasing importance in the vulnerable and sensitive global economy.

The paper's specific consideration of disruption (as opposed to disturbance), and the necessitated speed of response leads to the development of several disruption‐specific propositions and the development of a new research agenda.

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.