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The study here examines how business actors adapt to changes in networks by analyzing their perceptions or their network pictures. The study is exploratory or iterative in the sense that revisions occur to the research question, method, theory, and context as an integral part of the research process.

Changes within networks receive less research attention, although considerable research exists on explaining business network structures in different research traditions. This study analyzes changes in networks in terms of the industrial network approach. This approach sees networks as connected relationships between actors, where interdependent companies interact based on their sensemaking of their relevant network environment. The study develops a concept of network change as well as an operationalization for comparing perceptions of change, where the study introduces a template model of dottograms to systematically analyze differences in perceptions. The study then applies the model to analyze findings from a case study of Norwegian/Japanese seafood distribution, and the chapter provides a rich description of a complex system facing considerable pressure to change. In-depth personal interviews and cognitive mapping techniques are the main research tools applied, in addition to tracer studies and personal observation.

The dottogram method represents a valuable contribution to case study research as it enables systematic within-case and across-case analyses. A further theoretical contribution of the study is the suggestion that network change is about actors seeking to change their network position to gain access to resources. Thereby, the study also implies a close relationship between the concepts network position and the network change that has not been discussed within the network approach in great detail.

Another major contribution of the study is the analysis of the role that network pictures play in actors' efforts to change their network position. The study develops seven propositions in an attempt to describe the role of network pictures in network change. So far, the relevant literature discusses network pictures mainly as a theoretical concept. Finally, the chapter concludes with important implications for management practice.

Collaborative networks (CN) are organizational forms that are especially enabled by innovations in the area of information and communication technologies. For an in‐depth understanding of CN a theoretical foundation is required. The purpose of this paper is to explain goal‐oriented and opportunity‐based CN with the help of existing and well‐known organization theories. A detailed overview about frequently mentioned concepts and theories in network studies is given and then a structured selection of theoretical approaches that are aiming to explain CN is discussed in detail. Finally, ten aspects for the existence and efficiency of CN are derived.

The approach taken in this work is based on a literature review and an impact analysis of the investigated organization theories along the life cycle of CN.

The result of the analysis shows that none of the investigated theories is able to describe the complex phenomenon of CN entirely and to clear all knowledge deficits. Therefore, multiple theories need to be considered as foundation.

This research represents a contribution to the theoretical body of knowledge in the field of CN. More specifically, it represents a first initial step towards the explanation of certain aspects of CN by means of existing organization theories.

This paper proposes a new approach source node exclusion method (SNEM) to evaluate terminal pair reliability of complex communication networks.

The proposed approach breaks a non‐series‐parallel network to obtain its sub‐networks by excluding the source node from rest of the network. The reliabilities of these sub‐networks are thereafter computed by first applying the series‐parallel‐reductions to it and if any sub‐network results into another non‐series‐parallel network then it is solved by the recursive application of SNEM.

The proposed method has been applied on a variety of network and found to be quite simple, robust, and fast for terminal pair reliability evaluation of large and complex networks.

The proposed approach is quite simple in application and applicable to any general networks, i.e. directed and undirected. The method does not require any prior information such as path (or cut) sets of the network and their pre‐processing thereafter or perform complex tests on networks to match a predefined criterion.

The proposed approach provides an easy to develop and easy to use tool to determine terminal pair reliability of a communication network. The approach is particularly useful for communication network designer and analysts.

This paper's main purpose is to provide a systematic approach for mapping the value exchange in B2B relationship marketing. This approach affords a preliminary analysis in order to distinguish business customers' different value dimensions (tangibles and intangibles) and to set sights on determining suitable metrics to evaluate and quantify the value of each customer.

The paper uses a combination of qualitative research approaches, namely an exploratory case study, in‐depth interviews, and consensus expert opinion. The empirical study took place over three months to maximize the proposed approach's expediency in the practitioners' B2B environment and to increase the validity of the research findings.

In addition to developing a new framework originating in the value network approach for mapping, modeling and analyzing business customers' value network (BCVN), the findings posit a proposed systematic approach for practitioners and marketing scholars to scrutinize the multi‐dimension values of business relationship marketing.

For companies and their business customers alike, the benefits of the systematic approach proposed in this paper are an efficient analytical system giving an opportunity to B2B marketers and managers to understand their business customers' network in detail.

The implicit concept of maximizing customer lifetime value within the business customers' network appeals for an applied approach to better understand and analyze the real value of business customers to retain them.

In this paper, the basic tenets of the European industrial networks research tradition are introduced. It is argued that the network approach offers a particularly powerful descriptive tool for analyzing contemporary interorganizational business exchange. The network approach is applied in a case study of a Finnish SME sector furniture manufacturer’s focal net. The case study should be understood as an example of how the network approach can generate meaningful analyses and provide practical implications for capability development, marketing and purchasing, and strategy development.

The purpose of this paper is to review the applications of the chemical reactor network (CRN) approach for modeling the combustion in gas turbine combustors and classify the CRN construction methods that have been frequently used by researchers.

This paper initiates with introducing the CRN approach as a practical tool for precisely predicting the species concentrations in the combustion process with lower computational costs. The structure of the CRN and its elements as the ideal reactors are reviewed in recent studies. Flow field modeling has been identified as the most important input for constructing the CRNs; thus, the flow field modeling methods have been extensively reviewed in previous studies. Network approach, component modeling approach and computational fluid dynamics (CFD), as the main flow field modeling methods, are investigated with a focus on the CRN applications. Then, the CRN construction approaches are reviewed and categorized based on extracting the flow field required data. Finally, the most used kinetics and CRN solvers are reviewed and reported in this paper.

It is concluded that the CRN approach can be a useful tool in the entire process of combustion chamber design. One-dimensional and quasi-dimensional methods of flow field modeling are used in the construction of the simple CRNs without detailed geometry data. This approach requires fewer requirements and is used in the initial combustor designing process. In recent years, using the CFD approach in the construction of CRNs has been increased. The flow field results of the CFD codes processed to create the homogeneous regions based on construction criteria. Over the past years, several practical algorithms have been proposed to automatically extract reactor networks from CFD results. These algorithms have been developed to identify homogeneous regions with a high resolution based on the splitting criteria.

This paper reviews the various flow modeling methods used in the construction of the CRNs, along with an overview of the studies carried out in this field. Also, the usual approaches for creating a CRN and the most significant achievements in this field are addressed in detail.

This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities of accomplishing tasks are highly dependent on the effective information sharing among intelligent subjects within the networks. Hence, proposing an adaptive information-sharing approach can help improve the performance of crowd networks on accomplishing tasks that are assigned to them.

This paper first introduces the factors that affect effectiveness of information-sharing pattern: the network topology, the resources owned by intelligent subjects and the degree of information demand. By analyzing the correlation between these factors and the performance of crowd networks, an Adaptive Information Sharing Approach for Crowd Networks (AISCN approach) is proposed. By referring to information needed for accomplishing the historical tasks that are assigned to a crowd network, the AISCN approach can explore the optimized information-sharing pattern based on the predefined composite objective function. The authors implement their approach on two crowd networks including bee colony and supply chain, to prove the effectiveness of the approach.

The shared information among intelligent subjects affects the efficiency of task completion in the crowd network. The factors that can be used to describe the effectiveness of information-sharing patterns include the network topology, the resources owned by intelligent subjects and the degree of information demand. The AISCN approach used heuristic algorithm to solve a composite objective function which takes all these factors into consideration, so that the optimized information-sharing pattern can be obtained.

This paper introduces a set of factors that can be used to describe the correlation between information-sharing pattern and performance of crowd network. By quantifying such correlation based on these factors, this paper proposes an adaptive information-sharing approach which can explore the optimized information-sharing pattern for a variety of crowd networks. As the approach is a data-driven approach that explores the information-sharing pattern based on the network’s performance on historical tasks and network’s characteristics, it is adaptive to the dynamic change (change of incoming tasks, change of network characteristics) of the target crowd network. To ensure the commonality of the information-sharing approach, the proposed approach is not designed for a specific optimization algorithm. In this way, during the implementation of the proposed approach, heuristic algorithms can be chosen according to the complexity of the target crowd network.

The purpose of this paper is to establish a connection between the business model (BM) and B2B marketing research by developing a new approach to the BM analysis and improvement, which is based on inter-organizational networks and value chains.

The methodology is based on mutual enrichment of methods and results of BM and business-to-business marketing studies that are relatively isolated from each other, and on integration of them to the unified structured approach that could be applied to analyze both BM and a set of interfirm relationships of networked market players. This paper is based on extensive literature review in the areas of BM and relationship/industrial marketing. The review is based on most cited and contemporary articles found in the Scopus and EBSCO databases.

This paper formulates the key BM research directions and visualizes their development over time. It is demonstrated in the paper that currently, there is little involvement of marketing researchers in the study of BM; however, there are multiple touchpoints between these areas of knowledge, which can help in further developing BM studies. On the basis of these findings, a conceptual model and new network-based approach to BM analysis is offered, which allows addressing the complex nature of networked interaction among BM participants. The approach includes stepwise algorithm for BM analysis designed for business practitioners.

The proposed approach can be applied by business practitioners to analyze and improve their BM via managing the interactions of inter-organizational network participants with a focus on customer interests. While the approach is of a universal character, the specific tools for evaluating BM on each stage may vary across different markets.

This research contributes to the current conceptual knowledge on BM studies development and their relationship with marketing. It also contributes to theory and practice by the development of a new marketing-based approach to the BM analysis focused on managing business relationships, which allows evaluation of the current state of a BM and provides directions for its improvement. This approach evaluates the alignment of interfirm relationships along the value chain and orients it toward the final consumer.

Taking stock of extant hospitality and tourism research using social network analysis approaches, this study highlights why using either quantitative or qualitative approaches to examine social networks can be misleading and generate potentially biased findings. Indeed, purely qualitative and purely quantitative studies display limitations. The purpose of this study is to provide methodological insights by suggesting that mixed methods can be suitably used, depending on the specific research questions.

The study consists of an analysis and critical discussion of the methods used in a number of papers leveraging social network approaches to study social networks in tourism and hospitality. The authors describe the benefits and limitations of each method studies considered are examined based on a number of aspects.

More than half of the studies classified as network studies adopt quantitative designs and quantitative methods including statistical analyses and observational data. Mixed methods study is a minority and they are almost never labeled as mixed methods. A relevant portion of qualitative studies increasingly embeds a number of rudimentary statistical analyses. With an example, the authors also discuss that purely quantitative or purely qualitative methods can lead to discrepant results, and thus, the authors encourage scholars to embrace mixed method research designs such as explanatory or exploratory sequential designs. Advanced researchers might attempt in the future to embrace transformative, embedded or multiphase mixed methods.

This study is based on academic papers and research published before 2019. A rich research agenda is designed.

This study contributes to explore the way social networks have been dealt with in tourism and hospitality research so far, by advancing a proposal to adopt mixed methods in the form of explanatory or exploratory sequential designs. To the best of the knowledge, it is the first study addressing methodological pitfalls in extant network-based research within the tourism and hospitality domain.