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Article
Publication date: 31 December 2020

Honghong Zhang and Xiushuang Gong

This study aims to empirically investigate how susceptibility to social influence in new product adoption varies with one’s structural location in a social network.

Abstract

Purpose

This study aims to empirically investigate how susceptibility to social influence in new product adoption varies with one’s structural location in a social network.

Design/methodology/approach

The social network data were collected based on a sociometric network survey with 589 undergraduate students. Social network analysis and ordinary least squares regression analyses were used to test the hypotheses.

Findings

This study finds that consumers with high degree centrality (i.e. hubs) who have a large number of connections to others and consumers with high betweenness centrality (i.e. bridges) who connect otherwise distant groups in social networks are both less sensitive to informational influence from others. More importantly, the authors find evidence that consumers with moderate levels of degree/betweenness centrality are more susceptible to normative influence and status competition than those with low or high degree/betweenness centrality. The inverse-U patterns in the above relations are consistent with middle-status conformity and anxiety.

Research limitations/implications

This research complements social influence and new product diffusion research by documenting important contingencies (i.e. network locations) in consumer susceptibility to different types of social influence from a social network perspective.

Practical implications

The findings will assist marketers to leverage social influence by activating relevant social ties with effective messages in their network marketing strategies.

Originality/value

This research provides a better understanding of the mechanisms driving susceptibility to social influence in new product diffusion.

Details

European Journal of Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0309-0566

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Article
Publication date: 26 July 2019

Seyed Ashkan Zarghami and Indra Gunawan

In recent years, centrality measures have been extensively used to analyze real-world complex networks. Water distribution networks (WDNs), as a good example of complex…

Abstract

Purpose

In recent years, centrality measures have been extensively used to analyze real-world complex networks. Water distribution networks (WDNs), as a good example of complex networks, exhibit properties not shared by other networks. This raises concerns about the effectiveness of applying the classical centrality measures to these networks. The purpose of this paper is to generate a new centrality measure in order to stick more closely to WDNs features.

Design/methodology/approach

This work refines the traditional betweenness centrality by adding a hydraulic-based weighting factor in order to improve its fit with the WDNs features. Rather than an exclusive focus on the network topology, as does the betweenness centrality, the new centrality measure reflects the importance of each node by taking into account its topological location, its demand value and the demand distribution of other nodes in the network.

Findings

Comparative analysis proves that the new centrality measure yields information that cannot be captured by closeness, betweenness and eigenvector centrality and is more accurate at ranking the importance of the nodes in WDNs.

Practical implications

The following practical implications emerge from the centrality analysis proposed in this work. First, the maintenance strategy driven by the new centrality analysis enables practitioners to prioritize the components in the network based on the priority ranking attributed to each node. This allows for least cost decisions to be made for implementing the preventive maintenance strategies. Second, the output of the centrality analysis proposed herein assists water utilities in identifying the effects of components failure on the network performance, which in turn can support the design and deployment of an effective risk management strategy.

Originality/value

The new centrality measure, proposed herein, is distinct from the conventional centrality measures. In contrast to the classical centrality metrics in which the importance of components is assessed based on a pure topological viewpoint, the proposed centrality measure integrates both topological and hydraulic attributes of WDNs and therefore is more accurate at ranking the importance of the nodes.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 2
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 28 October 2014

Ravi S. Behara, Sunil Babbar and Philip Andrew Smart

The purpose of this paper is to examine the leadership role of authors, institutions, and countries based on research co-authorship networks in the field of operations…

Abstract

Purpose

The purpose of this paper is to examine the leadership role of authors, institutions, and countries based on research co-authorship networks in the field of operations management (OM) and ranks European authors, institutions, and countries using network centrality measures. It also identifies the primary research areas of each of the leading European authors and maps the areas that European research in general has focussed most on.

Design/methodology/approach

Based on co-authorships in publications appearing in a representative set of three leading OM journals over the 15-year period of 1998-2012, network measures of total degree centrality and betweenness centrality are used to identify influential European agents serving as leaders and bridge builders in OM research. Keyword analysis is used to identify the dominant areas of OM research in Europe as well as the primary areas of research of the leading authors.

Findings

With UK, Spain, The Netherlands, and Italy accounting for the dominant share of authorship of papers in the journal set, many authors and institutions from these countries are also found to rank high on network centrality measures. While certain authors, institutions, and countries are found ranking high on total degree centrality based on number of direct connections in the network, others are found to play uniquely important roles as gatekeepers and bridge builders in network relationships. The body of research is found to be focussed most on the area of supply chain management. It is also found to be focussed more on manufacturing than service.

Research limitations/implications

The examination of networks in this study based on co-authorships in publications in the set of three leading journals: Journal of Operations Management, International Journal of Operations & Production Management, and Production and Operations Management, is not all encompassing as there are likely other co-authorship relationships of OM researchers that go beyond publications in this set of journals.

Practical implications

Co-authorship of papers in the leading academic journals in a discipline provides a window on patterns of collaboration among key researchers within that academic community. The findings of this study inform the community of stakeholders on who the leading European agents in OM research are, what the primary areas of research of the leading European authors are, and areas that European research has focussed most on.

Originality/value

This is the first study of its kind that identifies and maps key European authors, institutions, and countries based on the analysis of co-authorship networks of researchers who have published in a set of leading OM journals that are considered to be among the most relevant outlets in the field of OM. It also maps the primary areas of research.

Details

International Journal of Operations & Production Management, vol. 34 no. 12
Type: Research Article
ISSN: 0144-3577

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Article
Publication date: 30 December 2020

Xueyan Zhang, Xiaohong Wang and Wei Zhao

Effective knowledge integration is vital for decision making in interdisciplinary research (IDR) teams. However, there is a lack of knowledge about the antecedents of…

Abstract

Purpose

Effective knowledge integration is vital for decision making in interdisciplinary research (IDR) teams. However, there is a lack of knowledge about the antecedents of knowledge integration. This study aims to examine how social capital at different levels and their interaction influences knowledge integration in IDR teams. Specifically, this study explores the moderating role of team social capital in the relationship between individual social capital and knowledge integration.

Design/methodology/approach

A survey on 346 individuals from 46 IDR teams in a research university in China is conducted. A multilevel analysis of the hierarchical linear model is used to process the sociometric data.

Findings

Results reveal that team social capital interacts with individual social capital by influencing knowledge integration. At the individual level, tie strength and structural equivalence have a positive influence on knowledge integration. There is an inverted U-shaped relationship between betweenness centrality and knowledge integration. Furthermore, team cohesion negatively moderates the positive effect of tie strength and structural equivalence on knowledge integration. No support is found for the moderating role of team cohesion on the effect of betweenness centrality.

Originality/value

First, different from previous research on social capital at single levels, this study links the individual-level and the team-level views to explore the effects of social capital on knowledge integration. Second, this study enriches research on inducing factors of knowledge integration. Third, this study extends social capital research and knowledge integration research to the IDR team context.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

Keywords

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Article
Publication date: 14 January 2014

Kamal Badar, Julie M. Hite and Yuosre F. Badir

The purpose of this paper is to investigate whether potentially disadvantaged groups of researchers derive more research performance benefits from co-authorship network…

Abstract

Purpose

The purpose of this paper is to investigate whether potentially disadvantaged groups of researchers derive more research performance benefits from co-authorship network centrality (degree, closeness and betweenness).

Design/methodology/approach

The paper builds on Badar et al. (2013), which found positive associations of network centrality on research performance with a moderating relationship of gender for female authors. Using data from ISI Web of Science (SCI), the authors study the same domestic co-authorship network of Chemistry researcher in Pakistan publishing from years 2002-2009 and investigate the moderating role of academic age and institutional sector on the relationship between co-authorship network centrality (degree, closeness, and betweenness) and the academic research performance (aggregate impact factor) of chemistry university/institute faculty members in Pakistan.

Findings

Ordinary least squares (OLS)-regression findings indicated a positive relationship between degree centrality and research performance with a positive moderating relationship for both academic age and institutional sector on the relationship between degree centrality and research performance for junior faculty members and faculty members employed in private sector universities/research institutes.

Practical implications

The findings can be heartening and motivating for junior faculty and private institute faculty in Pakistan in suggesting opportunities to surpass barriers of domination and poor resource access through co-authorship ties and structural social capital.

Originality/value

This paper adds to the limited research by strengthening the argument that potentially disadvantaged faculty with certain individual (academic age) and work-related characteristics (institutional sector) may benefit differentially from their co-authorship network centrality.

Details

Aslib Journal of Information Management, vol. 66 no. 1
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 4 November 2020

Pachayappan Murugaiyan and Venkatesakumar Ramakrishnan

Little attention has been paid to restructuring existing massive amounts of literature data such that evidence-based meaningful inferences and networks be drawn therefrom…

Abstract

Purpose

Little attention has been paid to restructuring existing massive amounts of literature data such that evidence-based meaningful inferences and networks be drawn therefrom. This paper aims to structure extant literature data into a network and demonstrate by graph visualization and manipulation tool “Gephi” how to obtain an evidence-based literature review.

Design/methodology/approach

The main objective of this paper is to propose a methodology to structure existing literature data into a network. This network is examined through certain graph theory metrics to uncover evidence-based research insights arising from existing huge amounts of literature data. From the list metrics, this study considers degree centrality, closeness centrality and betweenness centrality to comprehend the information available in the literature pool.

Findings

There is a significant amount of literature on any given research problem. Approaching this massive volume of literature data to find an appropriate research problem is a complicated process. The proposed methodology and metrics enable the extraction of appropriate and relevant information from huge quantities of literature data. The methodology is validated by three different scenarios of review questions, and results are reported.

Research limitations/implications

The proposed methodology comprises of more manual hours to structure literature data.

Practical implications

This paper enables researchers in any domain to systematically extract and visualize meaningful and evidence-based insights from existing literature.

Originality/value

The procedure for converting literature data into a network representation is not documented in the existing literature. The paper lays down the procedure to structure literature data into a network.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 14 October 2019

Pablo Galaso, Adrián Rodríguez Miranda and Santiago Picasso

This paper aims to analyze the relationship between inter-firm collaboration network and the type of innovation strategies that can be followed by firms: buy or make…

Abstract

Purpose

This paper aims to analyze the relationship between inter-firm collaboration network and the type of innovation strategies that can be followed by firms: buy or make innovation. In particular, the authors seek to analyze which are the network topologies that facilitate firms following a buy innovation strategy compared to those network properties that encourage internal R&D activities.

Design/methodology/approach

The authors use data from a fieldwork with face-to-face interviews applied to managing directors of firms in the rubber and plastic cluster of Uruguay. Subsequently, they combine social network analysis with regression techniques to determine how inter-firm networks can influence different types of innovation activities.

Findings

The authors find that degree centrality facilitates a buy innovation strategy, while betweenness centrality is positively associated with making innovation. Thus, having many direct links with other firms and organizations is relevant to buy innovation. However, indirect links that allow the firm to occupy a strategic position in the network are crucial to develop in-house innovation strategies.

Research limitations/implications

The results offer an advance in the explanation of the incidence of the cluster network structure on the firms innovation strategies; however, they should be contrasted with similar analysis in others clusters and complemented with in depth case studies on the mechanisms behind these phenomena.

Practical implications

These findings have practical implications for business innovation strategy. One factor that should be taken into account is the way in which firms interact with other actors in the cluster. On the one hand, firms can decide to establish and maintain many direct collaboration links, which may contribute to buy innovation. On the other hand, they can follow a more strategic and selective collaboration strategy to make innovation, a strategy that carefully studies not only its direct collaborations, but also what the potential indirect connections would be.

Social implications

These findings have policy implications regarding industry support organizations. The findings show that such organizations contribute significantly to the overall connectivity and cohesion of networks. This fact allows some firms to register high levels of betweenness centrality, and therefore, organizations can be an interesting instrument to support firms aiming to follow a make innovation strategy.

Originality/value

This study contributes to the literature that analyzes how inter-firm collaboration networks can influence innovation. In line with previous research, results verify that centrality is positively associated with innovation. However, the main contribution of this research is to provide evidence on different ways in which inter-firm networks are related to different innovation strategies (make or buy). In addition, the authors contribute to the understanding of collaboration dynamics and innovation activities in inter-firm interactions within a typical case of a low-tech cluster created under the so-called state-led industrialization model in Latin America.

Objetivo

Este artículo busca estudiar la relación entre las redes de colaboración entre empresas y las diferentes estrategias de innovación. En concreto, se centra en la clásica distinción entre comprar la innovación o desarrollarla en el seno de la empresa.

Diseño/metodología/aproximación

El artículo estudia el clúster del caucho y plástico de Uruguay, situado en el área metropolitana de Montevideo y Canelones. Los datos se obtuvieron de un trabajo de campo, con 118 entrevistas cara a cara a gerentes de empresas del clúster. Se combinan técnicas de análisis de redes sociales con regresiones logísticas para estimar cómo la posición en la red influye sobre las estrategias de innovación.

Resultados

Los resultados prueban que la red tiene efectos diferenciados en las estrategias de innovación: mientras que la centralidad de grado (tener muchas conexiones) facilita que las empresas compren innovación, la centralidad de intermediación (ocupar una posición estratégica en la red) está positivamente asociada con el desarrollo de innovación dentro de la empresa.

Originalidad/valor

El artículo realiza una contribución relevante a la literatura sobre redes de innovación al aclarar la relación entre diferentes formas de colaboración en red y distintas estrategias de innovación. Además, resulta de especial interés su estudio de la innovación y las interacciones entre empresas en un caso típico de industria de baja tecnología, creada bajo el llamado modelo de industrialización dirigido por el estado.

Palabras clave

Análisis de redes sociales, Innovación, Industrias de baja tecnología, Clúster industrial, Caucho y plástico, Uruguay

Objetivo

O objetivo deste artigo é estudar como as redes de colaboração entre empresas estão relacionadas a diferentes estratégias de inovação seguidas pelas empresas. Em particular, concentra-se na chamada distinção entre comprar e fazer inovação.

Design/metodologia/abordagem

O artigo estuda o cluster industrial de borracha e plásticos do Uruguai, localizado nas regiões metropolitanas de Montevidéu e Canelones. Os dados foram obtidos a partir do trabalho de campo, através de 118 entrevistas face-a-face aplicadas a diretores executivos de empresas. Ele combina análise de redes sociais com técnicas de regressão logística para determinar como a posição nas redes de colaboração influencia as estratégias de inovação.

Resultados

Os resultados provam que a rede tem efeitos diferentes pelo tipo de estratégia de inovação: a centralidade dos graus das firmas (isto é, ter muitos links diretos) facilita a compra de inovações externas, enquanto a centralidade entre as posições (estando localizada em uma posição estratégica na rede) é positivamente associado com a inovação dentro da empresa.

Originalidade/valor

O artigo fornece uma contribuição relevante para a literatura sobre redes de inovação, elucidando a relação entre diferentes formas de colaboração e diferentes estratégias de inovação. Além disso, faz uma contribuição especial, concentrando-se em inovações e interações entre firmas dentro de um caso típico de uma indústria de baixa tecnologia criada sob o chamado modelo de industrialização liderado pelo Estado.

Palavras-chave

Análise de redes sociais, Inovação, Indústrias de baixa tecnologia, Cluster industrial, Borracha e plásticos, Uruguai

Details

Management Research: Journal of the Iberoamerican Academy of Management, vol. 17 no. 4
Type: Research Article
ISSN: 1536-5433

Keywords

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Article
Publication date: 11 May 2015

Seung Ik Baek and Young Min Kim

The purpose of this paper is to explore the dynamics of an online community by examining its participants’ centrality measures: degree, closeness, and the betweenness

Abstract

Purpose

The purpose of this paper is to explore the dynamics of an online community by examining its participants’ centrality measures: degree, closeness, and the betweenness centrality. Each centrality measure shows the different roles and positions of an individual participant within an online community. To be specific, this research examines how an individual participant’s role and position affects her/his information sharing activities within an online community over time. Additionally, it investigates the differences between two different online communities (a personal interest focussed community and a social interest focussed community), in terms of the interaction patterns of participants.

Design/methodology/approach

For this research, the authors collected log files from Korean online discussion communities (café.naver.com) using a crawler program. A social network analysis was used to explore the interaction patterns of participants and calculate the centrality measures of individual participants. Time series cross-sectional analysis was used to analyze the effects of the roles and the positions on their information sharing activities in a longitudinal setting.

Findings

The results of this research showed that all three centrality measures of an individual participant in previous time periods positively influenced his/her information sharing activity in the current periods. In addition, this research found that, depending on the nature of the discussion issues, the participants showed different interaction patterns. Throughout this research, the authors explored the interaction patterns of individual participants by using a network variable, the centrality, within a large online community, and found that the interaction patterns provided strong impact on their information sharing activities in the following months.

Research limitations/implications

To investigate the changes of participant’s behaviors, this study simply relies on the numbers of comments received and posted without considering the contents of the comments. Future studies might need to analyze the contents of the comments exchanged between participants, as well as the social network among participants.

Practical implications

Online communities have developed to take a more active role in inviting public opinions and promoting discussion about various socio-economic issues. Governments and companies need to understand the dynamics which are created by the interactions among many participants. This study offers them a framework for analyzing the dynamics of large online communities. Furthermore, it helps them to respond to online communities in the right way and in the right time.

Social implications

Online communities do not merely function as a platform for the free exchange and sharing of personal information and knowledge, but also as a social network that exerts massive influence in various parts of society including politics, economy, and culture. Now online communities become playing an important role in our society. By examining communication or interaction behaviors of individual participants, this study tries to understand how the online communities are evolved over time.

Originality/value

In the area of online communities, many previous studies have relied on the subjective data, like participant’s perception data, in a particular time by using survey or interview. However, this study explores the dynamics of online communities by analyzing the vast amount of data accumulated in online communities.

Details

Industrial Management & Data Systems, vol. 115 no. 4
Type: Research Article
ISSN: 0263-5577

Keywords

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Article
Publication date: 18 June 2018

Jimmy H.T. Chan, Anthony C.K. Ko, Alan K.M. Au and Matthew C.H. Yeung

The understanding of leaders’ network centrality in social networks has been acknowledged as a major topic that can advance the social network field; most studies in this…

Abstract

Purpose

The understanding of leaders’ network centrality in social networks has been acknowledged as a major topic that can advance the social network field; most studies in this area have either taken firms as the subject by which the network centrality of firms was measured or/and have been conducted for the functional project context. Very little research has been done in the pure project context. This paper aims to revisit the centrality–performance link in the singular specialized project context.

Design/methodology/approach

The proposed relationships using panel data on 48 movie directors who lead pure projects has been studied. Freeman’s (1979) and Wasserman and Faust’s (1994) procedures have been adopted to compute our three centrality measures and their effects have been examined on box-office and artistic performance. A random effect and a mixed-effects Poisson model have been fit to examine the significance of the centrality–performance relationship.

Findings

The findings provide empirical evidence to support three out of the six hypotheses. The findings suggested that degree and closeness centrality are positively related to commercial performance and betweenness centrality is negatively related to commercial performance. However, it was found that only the degree centrality is related to artistic performance.

Originality/value

This study has two features that distinguish it from prior studies that link centrality to performance. First, the focus is on centrality attached to the leaders instead of the centrality attached to functional project teams or firms, as previously investigated. Second, this study is the first attempt of its kind to analyse the proposed relationship for an Asian market.

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Article
Publication date: 9 November 2020

Dario Cottafava and Laura Corazza

The need for stakeholder theory has been widely highlighted in the literature to develop solid strategies for a large organization. However, there is still a lack of…

Abstract

Purpose

The need for stakeholder theory has been widely highlighted in the literature to develop solid strategies for a large organization. However, there is still a lack of user-friendly visualization tools and no unique approach exists to identify and engage stakeholders. This paper aims to propose a general methodology to co-design the sustainability ecosystem at the local scale, to explore it and to assess the impact of a large organization within the identified ecosystem.

Design/methodology/approach

The methodology consists of two main processes: identifying an ontological map of the sustainability topics network and designing the local sustainability stakeholders ecosystem. Both processes are based on a nodes identification phase and a nodes prioritization phase. The identification phase was achieved by engaging 160 citizens, for the topics network and nearly 40 relevant stakeholders, for the stakeholders’ ecosystem, with a collaborative participatory mapping process. The prioritization phase was conducted because of three indicators, i.e. the closeness, the betweenness and the eigenvector centrality.

Findings

Betweenness centrality results to be the best indicator to assess the importance of a stakeholder with respect to the whole network, while eigenvector centrality highlights the quality of the already engaged stakeholders of an organization, as it mainly depends on the number of links of the first order neighbors. On the contrary, the closeness centrality, when applied to a small network, seems to be not appropriate to assess the centrality of a stakeholder.

Research limitations/implications

This approach revealed some criticalities in the mapping process, as in the weighting link procedure. Further investigations are needed to generalize the approach to a dynamic one, to allow real-time mapping and to develop a robust interconnection among centrality degrees and the power, interest and legitimacy concept of stakeholder theory.

Practical implications

Obtained results for a case study, i.e. the position of the University of Turin Green Office within the City of Turin sustainability ecosystem, are discussed showing how social network analysis centrality degrees can be used to quantitatively assess the role of an organization within a stakeholders’ ecosystem.

Social implications

Centrality analysis allows identifying emergent topics/stakeholders within a network of words/actors that, at a first sight, should not be considered by decision-makers and managers.

Originality/value

A new methodology for stakeholder identification and prioritization is proposed exploiting online data visualization tools, participatory mapping and social network analysis.

Details

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

Keywords

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