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Book part
Publication date: 4 August 2014

Jordi Comas

Networks and learning matter to small- and medium-sized enterprises (SMEs). Networks and learning are also further elaborations on the exploration–exploitation (EE…

Abstract

Networks and learning matter to small- and medium-sized enterprises (SMEs). Networks and learning are also further elaborations on the exploration–exploitation (EE) dilemma. Ambidexterity, that is, managing this apparent dilemma, can be difficult as a result of many constraints. One of these constraints is that of mutually exclusive network structures. Consequently, ambidexterity is the ability to change networks, depending on need using mixed data on four small companies formed as part of an undergraduate management class, I hypothesize how specific network properties of the advice-seeking relationship, including density, cohesion, centralization, and embeddedness, affect two outcomes. Specifically, early exploratory learning is proposed to be positively affected by less-dense networks that maintain cohesion without centralization and do not have relations embedded in other relations. In contrast, later exploitative learning should be associated with denser networks that also have higher cohesion, higher centralization, and greater embeddedness. The results provide some support for these hypotheses and suggest further research in two areas that will benefit SMEs. One, how do early networks affect learning mode? Two, how does the ability to rewire networks provide the relational infrastructure to shift from exploration to exploitation – that is, to be ambidextrous in the face of the exploration–exploitation tradeoff?

Details

Exploration and Exploitation in Early Stage Ventures and SMEs
Type: Book
ISBN: 978-1-78350-655-2

Keywords

Book part
Publication date: 26 May 2020

Catherine McGregor, Judy Halbert and Linda Kaser

Professional inquiry networks are becoming essential features of effective, innovative, and responsive school systems. In this chapter, the authors draw from their work…

Abstract

Professional inquiry networks are becoming essential features of effective, innovative, and responsive school systems. In this chapter, the authors draw from their work with a team of British Columbia district leaders who use inquiry as a primary means for shifting practice and supporting innovation and change that benefit all learners. The authors argue that networking enables ways for districts to share emerging practices, engage in collective dialogue, draw from exemplary research, and deeply reflect on impacts. In doing so, leaders build strong relational ties and professional capital that accelerates innovation between and among district leaders. Two specific cases develop a deeper understanding of how change is taken up and accelerated at the local level, providing examples of how inquiry networks operate across multiple sites and simultaneously seed and nurture innovative thinking.

Details

Professional Learning Networks: Facilitating Transformation in Diverse Contexts with Equity-seeking Communities
Type: Book
ISBN: 978-1-78769-894-9

Keywords

Book part
Publication date: 20 August 2016

Paul Coughlan, David Coghlan, Denise O’Leary, Clare Rigg and Doireann Barrett

The chapter describes and reflects upon an EU-funded research initiative, TRADEIT, which has attempted to develop a learning network among European traditional food…

Abstract

Purpose

The chapter describes and reflects upon an EU-funded research initiative, TRADEIT, which has attempted to develop a learning network among European traditional food producers as one way of contributing to the economic sustainability of the ventures, the social sustainability of the food’s regional character and the environmental sustainability of food production through the use of traditional methods.

Methodology/approach

The chapter describes TRADEIT before moving on to an exploration of learning in organizations and networks. It outlines the action learning research methodology developed and implemented to explore the development of a learning network in TRADEIT. A single case history is presented to illustrate the engagement of a small food producer in the network.

Findings

The discussion reflects on the application of action learning in supporting sustainability evident in TRADEIT.

Originality/value

The chapter focuses on the application of action learning in the development of a learning network among traditional food producers across Europe.

Details

Organizing Supply Chain Processes for Sustainable Innovation in the Agri-Food Industry
Type: Book
ISBN: 978-1-78635-488-4

Keywords

Book part
Publication date: 26 October 2021

Denise Bedford and Thomas W. Sanchez

This chapter focuses on learning networks. The authors describe the six facets of knowledge networks for learning contexts. The importance of three facets is called out…

Abstract

Chapter Summary

This chapter focuses on learning networks. The authors describe the six facets of knowledge networks for learning contexts. The importance of three facets is called out, including geography, topology, and nodes. The authors provide four networks, including pedagogy networks – that is, teachers, certification and professional learning networks, school networks, and informal and collaborative learning networks.

Details

Knowledge Networks
Type: Book
ISBN: 978-1-83982-949-9

Book part
Publication date: 24 August 2011

Breda Kenny and John Fahy

The study this chapter reports focuses on how network theory contributes to the understanding of the internationalization process of SMEs and measures the effect of network

Abstract

The study this chapter reports focuses on how network theory contributes to the understanding of the internationalization process of SMEs and measures the effect of network capability on performance in international trade and has three research objectives.

The first objective of the study relates to providing new insights into the international market development activities through the application of a network perspective. The chapter reviews the international business literature to ascertain the development of thought, the research gaps, and the shortcomings. This review shows that the network perspective is a useful and popular theoretical domain that researchers can use to understand international activities, particularly of small, high technology, resource-constrained firms.

The second research objective is to gain a deeper understanding of network capability. This chapter presents a model for the impact of network capability on international performance by building on the emerging literature on the dynamic capabilities view of the firm. The model conceptualizes network capability in terms of network characteristics, network operation, and network resources. Network characteristics comprise strong and weak ties (operationalized as foreign-market entry modes), relational capability, and the level of trust between partners. Network operation focuses on network initiation, network coordination, and network learning capabilities. Network resources comprise network human-capital resources, synergy-sensitive resources (resource combinations within the network), and information sharing within the network.

The third research objective is to determine the impact of networking capability on the international performance of SMEs. The study analyzes 11 hypotheses through structural equations modeling using LISREL. The hypotheses relate to strong and weak ties, the relative strength of strong ties over weak ties, and each of the eight remaining constructs of networking capability in the study. The research conducts a cross-sectional study by using a sample of SMEs drawn from the telecommunications industry in Ireland.

The study supports the hypothesis that strong ties are more influential on international performance than weak ties. Similarly, network coordination and human-capital resources have a positive and significant association with international performance. Strong ties, weak ties, trust, network initiation, synergy-sensitive resources, relational capability, network learning, and information sharing do not have a significant association with international performance. The results of this study are strong (R2=0.63 for performance as the outcome) and provide a number of interesting insights into the relations between collaboration or networking capability and performance.

This study provides managers and policy makers with an improved understanding of the contingent effects of networks to highlight situations where networks might have limited, zero, or even negative effects on business outcomes. The study cautions against the tendency to interpret networks as universally beneficial to business development and performance outcomes.

Details

Interfirm Networks: Theory, Strategy, and Behavior
Type: Book
ISBN: 978-1-78052-024-7

Keywords

Book part
Publication date: 3 August 2017

Matt Bower

Social networking platforms such as Facebook have infiltrated the lives of many students, and as such it is natural to consider how they can be effectively used to enhance…

Abstract

Social networking platforms such as Facebook have infiltrated the lives of many students, and as such it is natural to consider how they can be effectively used to enhance learning. This chapter provides a comprehensive review of social networking in education from a design perspective. Social networking is defined based on Boyd & Ellison’s seminal definition of connected profiles, and is distinguished from social media for the purposes of investigation. Facebook, Edmodo, and other social networking platforms are briefly described, before summarizing the wide variety of social networking usage reported in the research literature. The various benefits of social networking in education are distilled from the literature, including their capacity to facilitate community building, collaboration, reflection, and expedient access to learning. Issues surrounding the educational use of social networking are also organized into themes, for instance privacy concerns, distraction, cyber-safety, and technical constraints. The implications of findings from the social networking literature are synthesized into learning design and implementation recommendations. The chapter concludes with a discussion of open questions and areas for further investigation.

Details

Design of Technology-Enhanced Learning
Type: Book
ISBN: 978-1-78714-183-4

Article
Publication date: 12 July 2021

Khalil Dirani, Jack Baldauf, Zenon Medina-Cetina, Katya Wowk, Sharon Herzka, Ricardo Bello Bolio, Victor Gutierrez Martinez and Luis Alberto Munoz Ubando

The purpose of this study was to use Watkins and Marsick model of a learning organization (1993, 1996), the dimensions of the learning organization questionnaire as a…

Abstract

Purpose

The purpose of this study was to use Watkins and Marsick model of a learning organization (1993, 1996), the dimensions of the learning organization questionnaire as a framework for interdisciplinary network collaboration and knowledge sharing.

Design/methodology/approach

The research team used a mixed-methods approach for data collection. Survey data was collected from 181 networks. In addition, data was collected from two focus groups with six participants each.

Findings

Results, in general, showed that the learning organization culture could be used as a framework for interdisciplinary network collaboration. In particular, results showed that shared vision, imbedded systems and knowledge sharing were key driving forces required for successful collaboration.

Research limitations/implications

Theoretical and practical implications were discussed, and conditions for learning organization culture for networks were established.

Originality/value

People in a network era need more than training; they need ongoing, interdisciplinary, collaborative support to solve complex problems. Organizations can only work effectively if barriers to organizational learning were removed. This originality of this paper lies in applying learning organization framework at the network level.

Details

The Learning Organization, vol. 28 no. 4
Type: Research Article
ISSN: 0969-6474

Keywords

Article
Publication date: 10 August 2021

Deepa S.N.

Limitations encountered with the models developed in the previous studies had occurrences of global minima; due to which this study developed a new intelligent ubiquitous…

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Abstract

Purpose

Limitations encountered with the models developed in the previous studies had occurrences of global minima; due to which this study developed a new intelligent ubiquitous computational model that learns with gradient descent learning rule and operates with auto-encoders and decoders to attain better energy optimization. Ubiquitous machine learning computational model process performs training in a better way than regular supervised learning or unsupervised learning computational models with deep learning techniques, resulting in better learning and optimization for the considered problem domain of cloud-based internet-of-things (IOTs). This study aims to improve the network quality and improve the data accuracy rate during the network transmission process using the developed ubiquitous deep learning computational model.

Design/methodology/approach

In this research study, a novel intelligent ubiquitous machine learning computational model is designed and modelled to maintain the optimal energy level of cloud IOTs in sensor network domains. A new intelligent ubiquitous computational model that learns with gradient descent learning rule and operates with auto-encoders and decoders to attain better energy optimization is developed. A new unified deterministic sine-cosine algorithm has been developed in this study for parameter optimization of weight factors in the ubiquitous machine learning model.

Findings

The newly developed ubiquitous model is used for finding network energy and performing its optimization in the considered sensor network model. At the time of progressive simulation, residual energy, network overhead, end-to-end delay, network lifetime and a number of live nodes are evaluated. It is elucidated from the results attained, that the ubiquitous deep learning model resulted in better metrics based on its appropriate cluster selection and minimized route selection mechanism.

Research limitations/implications

In this research study, a novel ubiquitous computing model derived from a new optimization algorithm called a unified deterministic sine-cosine algorithm and deep learning technique was derived and applied for maintaining the optimal energy level of cloud IOTs in sensor networks. The deterministic levy flight concept is applied for developing the new optimization technique and this tends to determine the parametric weight values for the deep learning model. The ubiquitous deep learning model is designed with auto-encoders and decoders and their corresponding layers weights are determined for optimal values with the optimization algorithm. The modelled ubiquitous deep learning approach was applied in this study to determine the network energy consumption rate and thereby optimize the energy level by increasing the lifetime of the sensor network model considered. For all the considered network metrics, the ubiquitous computing model has proved to be effective and versatile than previous approaches from early research studies.

Practical implications

The developed ubiquitous computing model with deep learning techniques can be applied for any type of cloud-assisted IOTs in respect of wireless sensor networks, ad hoc networks, radio access technology networks, heterogeneous networks, etc. Practically, the developed model facilitates computing the optimal energy level of the cloud IOTs for any considered network models and this helps in maintaining a better network lifetime and reducing the end-to-end delay of the networks.

Social implications

The social implication of the proposed research study is that it helps in reducing energy consumption and increases the network lifetime of the cloud IOT based sensor network models. This approach helps the people in large to have a better transmission rate with minimized energy consumption and also reduces the delay in transmission.

Originality/value

In this research study, the network optimization of cloud-assisted IOTs of sensor network models is modelled and analysed using machine learning models as a kind of ubiquitous computing system. Ubiquitous computing models with machine learning techniques develop intelligent systems and enhances the users to make better and faster decisions. In the communication domain, the use of predictive and optimization models created with machine learning accelerates new ways to determine solutions to problems. Considering the importance of learning techniques, the ubiquitous computing model is designed based on a deep learning strategy and the learning mechanism adapts itself to attain a better network optimization model.

Details

International Journal of Pervasive Computing and Communications, vol. 18 no. 1
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 3 December 2021

Henry Mutebi, Moses Muhwezi, Joseph Mpeera Ntayi, Samuel Ssekajja Mayanja and John C. Kigozi Munene

Organisations involved in relief delivery tend to have cross-boundary mandates, which cause ambiguity of roles during delivery of relief services to the targeted victims…

Abstract

Purpose

Organisations involved in relief delivery tend to have cross-boundary mandates, which cause ambiguity of roles during delivery of relief services to the targeted victims. Having no clear role, specialisation affects service timeliness and increases resource duplication among the relief organisations. The objective of this study is to understand how organisational networks and organisational learning as complex adaptive system metaphors improve both organisational adaptability and role clarity in humanitarian logistics.

Design/methodology/approach

Using ordinary partial least squares regression through SmartPLS version 3.3.3, the authors tested the study hypotheses basing on survey data collected from 315 respondents who were selected randomly to complete a self-administered questionnaire from 101 humanitarian organisations. Common method bias (CMB) associated with surveys was minimised by implementing both procedural and post statistics methods.

Findings

The results indicate that organisational networks and organisational learning have a significant influence on organisational adaptability and role clarity. The results also show that organisational adaptability partially mediates in the relationship between organisational networks, organisational learning and role clarity.

Research limitations/implications

The major limitation of the study is that the authors have used cross-sectional data to test this research hypotheses. However, this was minimised following Guide and Ketokivi's (2015) recommendation on how to address the limitations of cross-sectional data or the use of longitudinal data that can address CMB and endogeneity problems.

Practical implications

Managers in humanitarian organisations can use the authors’ framework to understand, first, how complex adaptive system competence can be used to create organisational adaptability and, second, how organisational adaptability can help organisational networks and organisational learning in improving role clarity among humanitarian organisations by collaboratively working together.

Originality/value

This research contributes to the existing body of knowledge in humanitarian logistics and supply chain management by empirically testing the anecdotal and conceptual evidence. The findings may be useful to managers who are contemplating the use of organisational networks, organisational learning and organisational adaptability to improve role clarity in disaster relief-related activities.

Article
Publication date: 9 March 2015

Katri Kallio and Inka Lappalainen

The purpose of this paper is to examine how collaborative service development in a public-private citizen innovation network can be approached as an organizational learning

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Abstract

Purpose

The purpose of this paper is to examine how collaborative service development in a public-private citizen innovation network can be approached as an organizational learning process. Although the importance of learning in networks has been highlighted in earlier studies, the actual processes and outcomes have remained less studied, especially in the public service context.

Design/methodology/approach

The approach taken is based on the theory of expansive learning. The empirical data were gathered in a qualitative case study that focused on a public service organization developing new activities for unemployed youth. The network around this focal organization consisted of citizens as end-users, private employers and a facilitating consultancy company.

Findings

The findings illustrate how and what was learned in the complex network setting and how this learning created potential for collaborative service development in the future. Importantly, the public service organization started to perceive itself as an active agent enhancing collaboration.

Research limitations/implications

The study revealed important interfaces between service development, organizational learning, and innovation activities in networks. This observation is in line with the service-dominant logic, particularly with its focus on actor-to-actor relationships in value co-creation.

Practical implications

The importance of facilitation – particularly for the emergence of the agency of the focal organization – should be taken into account in the development of networked service innovations.

Originality/value

This study illustrates how expansive learning theory may contribute on deepening understanding of the practical collaboration processes, as well as conceptual aims and outcomes of networked service innovations.

Details

Journal of Service Theory and Practice, vol. 25 no. 2
Type: Research Article
ISSN: 2055-6225

Keywords

1 – 10 of over 118000