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Article
Publication date: 20 March 2017

Katrien Verleye, Elina Jaakkola, Ian R. Hodgkinson, Gyuchan Thomas Jun, Gaby Odekerken-Schröder and Johan Quist

Service networks are inherently complex as they comprise of many interrelated actors, often driven by divergent interests. This can result in imbalance, which refers to a…

2523

Abstract

Purpose

Service networks are inherently complex as they comprise of many interrelated actors, often driven by divergent interests. This can result in imbalance, which refers to a situation where the interests of at least one actor in a network are not secured. Drawing on the “balanced centricity” perspective, the purpose of this paper is to explore the causes of imbalance in complex service networks.

Design/methodology/approach

Adopting a qualitative case-based approach, this paper examines a public health service network that experienced imbalance that was detrimental to the lives of its users: the Mid-Staffordshire National Health Service (NHS) Trust, UK. Drawing on service-dominant logic and stakeholder theory, case evidence provides insight into the origin and drivers of imbalance in complex public service networks.

Findings

The origin of imbalance stems from competing institutional logics of various actors (patients/public, employees, managers, regulatory bodies, etc.), but the degree to which these competing institutional logics lead to imbalance is moderated by accountability, communication, engagement, and responsiveness within the service network.

Research limitations/implications

By uncovering causes of imbalance in complex public service networks, this paper pinpoints important research avenues for developing the balanced centricity perspective.

Practical implications

The inherent existence of multiple parallel institutional arrangements makes networks imbalanced, but value creation can be achieved when the appropriate mechanisms are fostered to manage balance between divergent logics.

Originality/value

By examining imbalance as the underlying cause of network dysfunction, this research contributes to understanding of the dynamics in, and performance of, complex public service networks.

Article
Publication date: 1 December 2023

Chen Xuemeng and Ma Guangqi

The manufacturing industry and the producer service industry have a high degree of industrial correlation, and their integration will cause changes in the complex industrial…

Abstract

Purpose

The manufacturing industry and the producer service industry have a high degree of industrial correlation, and their integration will cause changes in the complex industrial network topology, which is an important reason for the synergistic effect. This paper describes the topology of industrial systems using complex network theory; further, it discusses how to identify the criticality and importance of industrial nodes, and whether node characteristics cause synergistic effects.

Design/methodology/approach

Based on the input-output data of China in 2007, 2012 and 2017, this paper constructs the industrial complex network of 30 Chinese provinces and cities, and measures the regional network characteristics of the manufacturing industry. The fixed-effect panel regression model is adopted to test the influence of agglomeration degree and centrality on synergies, and its adjustment mechanism is explored.

Findings

The degree of network agglomeration in the manufacturing industry exerts a negative impact on the synergistic effect, while the centrality of the network exerts a significant promoting effect on the synergistic effect. The results of adjustment mechanism test show that enhancing the autonomous controllable ability of the regional industrial chain in the manufacturing industry can effectively reduce the effect of network characteristics on the synergistic effect.

Research limitations/implications

Based on input-output technology, this paper constructs a complex industrial network model, however, only basic flow data are used. Considerable in-depth and detailed research on the economic and technological connections within the industry should be conducted in the future. The selection of the evaluation index of the importance of industrial nodes also needs to be further considered. For historical reasons, it is also difficult to obtain and process data when carrying out quantitative analysis; therefore, it is necessary to make further attempts from the data source and the expression form of evaluation indicators.

Practical implications

In a practical sense this has certain reference value for the formulation of manufacturing industrial policies the optimization of regional industrial layout and the improvement of the industrial development level. It is necessary to formulate targeted and specialized industrial development strategies according to the characteristics of the manufacturing industry appropriately regulate the autonomous controllable ability of the industrial chain and avoid to limit the development of industries which is in turn limited by regional resources. Industry competition and market congestion need to be reduced industry exchanges outside the region encouraged the industrial layout optimized and the construction of a modern industrial system accelerated.

Social implications

The above research results hold certain reference importance for policy formulation related to the manufacturing industry, regional industrial layout optimization and industrial development level improvement. Targeted specialized industrial development strategies need to be formulated according to the characteristics of the manufacturing industry; the autonomous controllability of the industrial chain needs to be appropriately regulated; limitation of regional resources needs to be avoided as this restricts industrial development; and industry competition and market congestion need to be reduced. Agglomeration of production factors and optimization of resource allocation is an important part of a beneficial regional economic development strategy, and it is also an inevitable choice for industrialization to develop to a certain stage under the condition of a market economy. In alignment with the research conclusions, effective suggestions can be put forward for the current major industrial policies. In the process of promoting the development of the manufacturing industry, it is necessary for regional governments to carry out unified planning and guidance on the spatial layout of each manufacturing subsector. Regional governments need to effectively allocate inter-industry resources, better share economies of scale, constantly enhance the competitive advantages and competitiveness of development zones and new districts and promote the coordinated agglomeration and development of related industries with input industries. Industrial exchanges outside the region should be encouraged, the industrial layout should be optimized and the construction of a modern industrial system should be accelerated.

Originality/value

Complex network theory is introduced to study the industrial synergy effect. A complex industrial network of China's 30 regions is built and key network nodes are measured. Based on the dimensionality of the “industrial node – industrial chain – industrial complex network”, the research path of industrial complex networks is improved.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 24 July 2023

Lin Yang, Xiaoyue Lv and Xianbo Zhao

Abnormal behaviors such as rework, backlog, changes and claims generated by project organizations are unavoidable in complex projects. When abnormal behaviors emerge, the…

Abstract

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.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 16 October 2018

Na Zhang, Yu Yang, Jiafu Su and Yujie Zheng

Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically…

Abstract

Purpose

Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically express and manage the complex products design process.

Design/methodology/approach

To solve these problems, a supernetwork model of complex products design is constructed and analyzed in this paper. First, the design elements (customer demands, design agents, product structures, design tasks and design resources) are identified and analyzed, then the sub-network of design elements are built. Based on this, a supernetwork model of complex products design is constructed with the analysis of the relationship among sub-networks. Second, some typical and physical characteristics (robustness, vulnerability, degree and betweenness) of the supernetwork were calculated to analyze the performance of supernetwork and the features of complex product design process.

Findings

The design process of a wind turbine is studied as a case to illustrate the approach in this paper. The supernetwork can provide more information about collaborative design process of wind turbine than traditional models. Moreover, it can help managers and designers to manage the collaborative design process and improve collaborative design efficiency of wind turbine.

Originality/value

The authors find a new method (complex network or supernetwork) to describe and analyze complex mechanical product design.

Details

Kybernetes, vol. 48 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 11 October 2019

Thomas E. Johnsen, Ole Stegmann Mikkelsen and Chee Yew Wong

The purpose of this paper is to explore the challenges facing companies that operate within complex supply networks and the strategies they use to manage such complex supply…

Abstract

Purpose

The purpose of this paper is to explore the challenges facing companies that operate within complex supply networks and the strategies they use to manage such complex supply networks.

Design/methodology/approach

The paper uses mixed methods by combining in-depth case studies with an executive forum with those of senior industry stakeholders. The two in-depth supply network case studies were carried out through multiple interviews with focal (or ‘developer’) firms that supply energy through offshore wind power and key suppliers such as wind turbine manufacturers.

Findings

The findings show the challenges the offshore wind power industry faces because of complex supply networks, including attempts by several actors to exert their power and control. Despite the networks facing similar complexities and challenges, two distinctly different strategies for orchestrating and governing supply networks are uncovered: one strategy resembles an interventionist strategy, while the other is based on delegation.

Research limitations/implications

Based on the findings, the authors identify and develop a classification of complex supply network divided into intervention and delegation strategies, thereby adding to existing research on ways to manage complex supply networks.

Practical implications

The authors identify strategies for focal firms for managing in complex supply networks, based on control and intervention or coordination and delegation.

Originality/value

Existing research on supply network strategies has largely focused on non-complex contexts. This paper draws from complex adaptive systems and organisational behaviour perspectives to contribute original insights into supply network strategies in complex supply networks.

Details

Supply Chain Management: An International Journal, vol. 24 no. 6
Type: Research Article
ISSN: 1359-8546

Keywords

Open Access
Article
Publication date: 7 October 2021

Jianran Liu and Wen Ji

In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network

Abstract

Purpose

In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network has become increasingly complex. Therefore, it is necessary to model and analyze this complex interactive network. This paper aims to model and demonstrate the evolution of crowd intelligence using visual complex networks.

Design/methodology/approach

This paper uses the complex network to model and observe the collaborative evolution behavior and self-organizing system of crowd intelligence.

Findings

The authors use the complex network to construct the cooperative behavior and self-organizing system in crowd intelligence. Determine the evolution mode of the node by constructing the interactive relationship between nodes and observe the global evolution state through the force layout.

Practical implications

The simulation results show that the state evolution map can effectively simulate the distribution, interaction and evolution of crowd intelligence through force layout and the intelligent agents’ link mode the authors proposed.

Originality/value

Based on the complex network, this paper constructs the interactive behavior and organization system in crowd intelligence and visualizes the evolution process.

Details

International Journal of Crowd Science, vol. 5 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

Article
Publication date: 5 May 2021

Samrat Gupta and Swanand Deodhar

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is…

Abstract

Purpose

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

Design/methodology/approach

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Findings

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

Research limitations/implications

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

Practical implications

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

Social implications

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

Originality/value

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

Details

Information Technology & People, vol. 37 no. 2
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 15 March 2013

Edward J.S. Hearnshaw and Mark M.J. Wilson

The purpose of this paper is to advance supply chain network theory by applying theoretical and empirical developments in complex network literature to the context of supply…

14061

Abstract

Purpose

The purpose of this paper is to advance supply chain network theory by applying theoretical and empirical developments in complex network literature to the context of supply chains as complex adaptive systems. The authors synthesize these advancements to gain an understanding of the network properties underlying efficient supply chains. To develop a suitable theory of supply chain networks, the authors look to mirror the properties of complex network models with real‐world supply chains.

Design/methodology/approach

The authors review complex network literature drawn from multiple disciplines in top scientific journals. From this interdisciplinary review a series of propositions are developed around supply chain complexity and adaptive phenomena.

Findings

This paper proposes that the structure of efficient supply chains follows a “scale‐free” network. This proposal emerges from arguments that the key properties of efficient supply chains are a short characteristic path length, a high clustering coefficient and a power law connectivity distribution.

Research limitations/implications

The authors' discussion centres on applying advances found in recent complex network literature. Hence, the need is noted to empirically validate the series of propositions developed in this paper in a supply chain context.

Practical implications

If efficient supply chains resemble a scale‐free network, then managers can derive a number of implications. For example, supply chain resilience is derived by the presence of hub firms. To reduce the vulnerability of supply chains to cascading failures, it is recognized that managers could build in redundancy, undertake a multi‐sourcing strategy or intermediation between hub firms.

Originality/value

This paper advances supply chain network theory. It offers a novel understanding of supply chains as complex adaptive systems and, in particular, that efficient and resilient supply chain systems resemble a scale‐free network. In addition, it provides a series of propositions that allow modelling and empirical research to proceed.

Details

International Journal of Operations & Production Management, vol. 33 no. 4
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 29 May 2009

Pavani Rangachari

The purpose of this paper is to seek to develop a theoretical framework for understanding the structure of effective knowledge sharing networks in professional organizations.

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Abstract

Purpose

The purpose of this paper is to seek to develop a theoretical framework for understanding the structure of effective knowledge sharing networks in professional organizations.

Design/methodology/approach

A literature review is performed to achieve the purpose. This article integrates two streams of literature: related to knowledge network structure and related to professional complex systems, to gain insight into the structure of effective knowledge sharing networks in professional complex systems. This preliminary theoretical framework is then used to put forth strategies for knowledge management and collective learning in professional organizations.

Findings

An analysis of knowledge networks and complex systems literatures suggests that effective knowledge sharing networks in complex systems may be richer in density compared to brokerage. However, integrating this analysis with the literature on professional organizations, including “subgoals” theory, suggests that the reverse may be true in professional complex systems, i.e. that effective knowledge sharing networks in professional complex systems may be richer in brokerage and hierarchy, rather than in density.

Research implications/limitations

The paper provides a foundation for future research avenues in the professional organizational context. For instance the framework could be used to explore effective knowledge sharing structures across professional subgroups and hierarchical levels in a hospital context; and across faculty, staff, and administrators in a college/university context.

Practical implications

A key implication is that, in order to enable collective learning in professional organizations, senior executives must make proactive and unceasing efforts to: coordinate knowledge exchange across professional subgroups; create cognitive linkages between subgroup actions and organizational outcomes; and connect professional subgroups with the changing external environment.

Originality/value

The theoretical framework lays a foundation for addressing the gap in the literature related to knowledge creation and collective learning in professional organizations.

Details

Journal of Knowledge Management, vol. 13 no. 3
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 10 September 2021

Xueping Wang and Xinqin Gao

The engineering education accreditation (EEA) is a principal quality assurance mechanism. However, at many education institutions, the most labor-intensive work of EEA process is…

1831

Abstract

Purpose

The engineering education accreditation (EEA) is a principal quality assurance mechanism. However, at many education institutions, the most labor-intensive work of EEA process is accomplished manually. Without the support of computer and information technology, the EEA process leads to high labor intensity, low work efficiency and poor management level. The purpose of this paper is to build a complex network model and realize an information management system of talent training program for supporting the EEA process.

Design/methodology/approach

Based on polychromatic graph (PG), this paper builds a network model of talent training program for engineering specialty. The related information and data are organized and processed in this network model. From the bidirections of top-down and bottom-up, the user requirements are retrieved automatically in logic layer. Together with the specialty of mechanical engineering, the proposed PG-based network modeling method is applied and the corresponding information management system is realized.

Findings

The study results show that the PG-based network modeling method takes full advantages of the strong simulation ability of PG to model the complex network system and has some unique merits in formal expression of problem, efficient processing of information and lightweight realization of system. Further, the information management system of talent training program can reduce the tedious human labor and improve the management level of EEA process dramatically.

Originality/value

This paper proposes a PG-based network modeling method, in which the nodes and the edges can be painted by some unified colors to describe the different kinds of activities and the various types of interactions. Theoretically, this modeling method does not distinguish the activities, the interactions and their properties in graphic symbol and the problem size is diminished about a half. Furthermore, this paper provides an effective experience and idea to the education institutions for implementing the engineering education accreditation, increasing the education management efficiency and promoting the talent training quality.

1 – 10 of over 108000