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1 – 10 of over 1000Due to the cross-network effect, two-sided users communicate with each other, producing a coupling network. To study the spread of platform self-operation in two-sided users'…
Abstract
Purpose
Due to the cross-network effect, two-sided users communicate with each other, producing a coupling network. To study the spread of platform self-operation in two-sided users' marketing and purchasing tactics, this paper considers the differences in reputation acquired by platform-owned and third-party operating channels.
Design/methodology/approach
This study proposes a two-layer network with cross-network links: one layer represents the social network of consumers, while the other layer represents the competitive network of buyers. A closed system of differential equations, based on the binary dynamics of the stochastic network, is developed to study the trend and stability points of the platform self-operation dissemination. Then the overall benefits of platform are analyzed to unify the platform diffusion and pricing strategies.
Findings
The degree of difference in social influence and cross-network effects affect diffusion synergistically. Cross-network effects hinder diffusion when there is a significant difference of social influence between consumers and sellers but promote diffusion when there is little difference of social influence between consumers and sellers. Additionally, the network weights and reputation gap exhibit a nonlinear correlation with diffusion. For pricing strategy of the platform, it can achieve maximum profit when the pricing of self-operated goods and third-party-operated goods is equal.
Originality/value
This study considers the complex network architecture created by bilateral markets and the dynamic influence of group interactions on product. Additionally, this study takes reputation into account when considering the price and dissemination tactics of various operating channels, offering guidelines for platforms to control merchants and mediate disputes between various operating channels.
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Yuanwen Han, Jiang Shen, Xuwei Zhu, Bang An and Xueying Bao
This study aims to develop an interface management risk interaction modeling and analysis methodology applicable to complex systems in high-speed rail construction projects…
Abstract
Purpose
This study aims to develop an interface management risk interaction modeling and analysis methodology applicable to complex systems in high-speed rail construction projects, reveal the interaction mechanism of interface management risk and provide theoretical support for project managers to develop appropriate interface management risk response strategies.
Design/methodology/approach
This paper introduces the association rule mining technique to improve the complex network modeling method. Taking China as an example, based on the stakeholder perspective, the risk factors and significant accident types of interface management of high-speed rail construction projects are systematically identified, and a database is established. Then, the Apriori algorithm is used to mine and analyze the strong association rules among the factors in the database, construct the complex network, and analyze its topological characteristics to reveal the interaction mechanism of the interface management risk of high-speed rail construction projects.
Findings
The results show that the network is both scale-free and small-world, implying that construction accidents are not random events but rather the result of strong interactions between numerous interface management risks. Contractors, technical interfaces, mechanical equipment, and environmental factors are the primary direct causal factors of accidents, while owners and designers are essential indirect causal factors. The global importance of stakeholders such as owners, designers, and supervisors rises significantly after considering the indirect correlations between factors. This theoretically explains the need to consider the interactions between interface management risks.
Originality/value
The interaction mechanism between interface management risks is unclear, which is an essential factor influencing the decision of risk response measures. This study proposes a new methodology for analyzing interface management risk response strategies that incorporate quantitative analysis methods and considers the interaction of interface management risks.
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Jonan Phillip Donaldson, Ahreum Han, Shulong Yan, Seiyon Lee and Sean Kao
Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways…
Abstract
Purpose
Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.
Design/methodology/approach
This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.
Findings
The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.
Research limitations/implications
LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.
Practical implications
LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.
Originality/value
To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.
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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.
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Aziz Wakibi, Joseph Ntayi, Isaac Nkote, Sulait Tumwine, Isa Nsereko and Muhammad Ngoma
The purpose of this study is to explore the interplay among self-organization, networks and sustainable innovations within microfinance institutions (MFIs) and to examine the…
Abstract
Purpose
The purpose of this study is to explore the interplay among self-organization, networks and sustainable innovations within microfinance institutions (MFIs) and to examine the extent to which organizational resilience plays a significant role in shaping these dynamics as a mediator.
Design/methodology/approach
This paper adopted a cross-sectional research design combined with analytical and descriptive approach to collect the data. Smart partial least squares structural equation modeling (PLS-SEM) was used to construct the measurement model and structural equation model to test the mediating effect under this study.
Findings
The results revealed that organizational resilience is a significant mediator in the relationship between self-organization, networks and sustainable innovations among microfinance institutions in Uganda.
Research limitations/implications
The data for this study were collected only from microfinance institutions in Uganda. Future studies may collect data from other formal financial institutions like commercial banks and credit institutions to test the mediating effect of organizational resilience. More still, the study adopted only a single approach of using a questionnaire. However, future research through interviews may be desirable. Likewise this study was cross-sectional in nature. Therefore, a longitudinal study may be useful in future while investigating the mediating role of organizational resilience traversing over a long time frame.
Practical implications
A possible implication is that microfinance institutions which desire to have sustainable innovative solutions for their business operations in disruptive circumstances may need to scrutinize their capacity to be resilient and self-organize.
Social implications
Microfinance institutions play a great role to the underserved clients. Thus, for each to re-organize to be able to provide services that meet users’ needs, without physical products so as to ensure long-term financial and social welfare combined with the ability to bounce back and adapt in times of economic downturn to avoid mission adrift.
Originality/value
While most studies have been carried out on organizational resilience, this paper takes center stage and is the first to test the mediating role of organizational resilience in the relationship between self-organization, networks and sustainable innovations, especially in microfinance institutions in Uganda. This paper generates strong evidence and contributes to the powerful influence of organizational resilience in enhancing the level of sustainable innovations based on self-organization and networks.
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Chao Zhang, Fang Wang, Yi Huang and Le Chang
This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.
Abstract
Purpose
This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.
Design/methodology/approach
Select eight representative IS journals as data sources, extract the theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by conducting theory co-occurrence network analysis, diversity measure and evolution analysis.
Findings
As a young and vibrant discipline, IS has been continuously absorbing and internalizing external theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of some kernel theories, the interdisciplinarity of IS appears to be decreasing and gradually converging into a few neighboring disciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting from a theory centered one to a technology centered one.
Research limitations/implications
This study helps to understand the evolution of the interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.
Originality/value
This study identifies the kernel theories in IS research, measures the interdisciplinarity of IS based on the evolution of the co-occurrence network of theory source disciplines and reveals the paradigm shift being happening in IS.
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Molly R. Burchett, Rhett T. Epler, Alec Pappas, Timothy D. Butler, Maria Rouziou, Willy Bolander and Bruno Lussier
The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable…
Abstract
Purpose
The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable salespeople to foster mutually valuable resource exchange (i.e. to thin crossing points) across a selling ecosystem.
Design/methodology/approach
The authors integrate extant theoretical perspectives to advance a conceptual framework of sales-related networking across three key actors in a selling ecosystem: intraorganizational selling actors and actors in customers and external partner organizations.
Findings
Thin crossing points are defined as figurative transaction points at the boundary between organizations or organizational subunits at which actors engage in mutually valuable resource exchange in the process of value cocreation. To thin crossing points with key ecosystem actors, salespeople must adapt networking strategies considering the time and trust constraints inherent in a network relationship. Such constraints inform the most advantageous network centralities (degree, eigenvector and betweenness) and actions to impact key network properties (tie strength, contact diversity) that enable salespeople to efficiently develop social capital and thus to optimally thin crossing points across a selling ecosystem.
Originality/value
To the best of the authors’ knowledge, this study is the first social network-based exploration of salespeople’s role in thinning crossing points with key ecosystem actors. It advances a novel conceptual framework of sales-related networking strategies that foster social capital development and optimally thin crossing points across a selling ecosystem.
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Ayobami Adetoyinbo, Jacob Asravor, Sunday Adewale Olaleye and Victor Owusu
Research efforts aiming to improve understanding of how various organisational relationships contribute to better food quality (FQ) in a constantly changing business environment…
Abstract
Purpose
Research efforts aiming to improve understanding of how various organisational relationships contribute to better food quality (FQ) in a constantly changing business environment are limited. This study examines the effects of supply chain (SC) organisations on the quality of food products across multi-tiered segments with dynamic business situations.
Design/methodology/approach
Guided by a conceptual research framework based on contingency theory and netchain analysis, moderation-based partial least squares structural equation modelling (PLS-SEM) was used to analyse multi-tiered data from 405 shrimpers and 238 women processors in Akwa-Ibom, Lagos and Ondo states in Nigeria.
Findings
The authors' findings show that unpredictable business environments such as market turbulence (MT), power asymmetry (PA) and distrust (DT) not only directly influence SC organisations but also moderate how organisational networks contribute to improved FQ. Further results reveal that closer vertical ties such as relational contracts are prerequisites for small-scale actors to guarantee improved FQ along multiple nodes of the food system.
Originality/value
This is the first study to examine, from a contingency and multi-tiered perspective, how small-scale actors can maintain FQ across interdependent nodes of a food chain in a developing country context and to explore the complex interplay between SC networks and the quality of highly perishable food products in unpredictable business environments. Relevant theoretical and policy implications are discussed.
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Yang S. Yang, Xiaojin Sun, Mengge Li and Tingting Yan
This study investigates the extent to which a firm’s centrality and autonomy in its supply network are associated with the intensity and complexity of its competitive actions.
Abstract
Purpose
This study investigates the extent to which a firm’s centrality and autonomy in its supply network are associated with the intensity and complexity of its competitive actions.
Design/methodology/approach
Utilizing social network analysis and dynamic panel data models, this study analyzes a comprehensive panel dataset with 10,802 firm-year observations across various industries between 2011 and 2018 to test the hypotheses.
Findings
Our findings show that a firm’s level of centrality in its supply network has an inverted U-shaped relationship with both competitive intensity and competitive complexity. In addition, the turning points of these two inverted U-shaped relationships differ in that firms with a lower level of centrality tend to compete aggressively by launching more actions within fewer categories, while firms with a higher level of centrality tend to compete aggressively by launching fewer actions that cover a larger range of categories. Finally, we find that a firm’s structural autonomy has a positive relationship with competitive complexity.
Originality/value
This study bridges the gap between the supply chain management literature and strategic management literature and investigates how supply networks shape competitive aggressiveness. In particular, this research investigates how a firm’s structural position in its supply network affects its competitive actions, an important intermediate mechanism for competitive advantage that has been overlooked in the supply chain management literature.
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