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This study aims to investigate how companies’ understanding of the business network influences the creation of value in business-to-business relationships. The authors do this by analysing dimensions in actors’ “network pictures” and illustrating how value perception and network understanding influence actors’ mutual effort to create value. Approaching relationship value from the point of actors’ cognitive understanding of their business network has so far been largely overlooked in relationship value research.

This study applies a qualitative case study methodology whereby dyadic data from a well-established business-to-business relationship is collected from 18 company representatives through personal interviews and group interviews supplemented by participant observations and company data.

The findings contribute with new insight into how companies’ understanding of their surrounding network influence (facilitates or limits) relationship value creation. The authors find that companies continuously reflect on changes in their networks and the related changes in partners’ value perceptions. Through value articulations, companies seek to explicitly express their value perception. Value reflections and value articulations create a dynamic process formed not only by the individual actor but also through their relationship and engagement in their network environment. This requires companies to develop their networking capabilities.

This paper presents findings, insights and contributions limited to a case study of a particular business relationship within an industrial setting. Although the findings and contributions are valid and in line with the criteria for rigorous qualitative research, the authors advocate and call for additional studies that investigate relationships value creation and address the interplay between actors’ network understanding and their actions and behaviour. One way to approach this would be to test the four propositions derived and presented as part of the present study.

The findings imply that management needs to be aware not only of the value created and delivered to a specific partner but also of how the partner’s understanding of the wider network will influence the value delivering and capturing process.

This study contributes to the growing literature on relationship value creation by outlining a dynamic process where relationship partners reflect upon and articulate value. Such activities are influenced by the partners’ network understanding and form the basis of the mutual relationship value creation effort. The findings also contribute to the network pictures literature by emphasizing insights into the formation of value perceptions through actors’ understanding of their surrounding networks.

The purpose of this study is to develop a model of a starting situation for relationship initiation in turbulent business networks.

The study is designed as an extreme single case study that takes its point of departure in a company’s bankruptcy in the Swedish automotive industry.

This study illustrates how a new business relationship can start from a resource combination previously controlled by one actor (i.e. a single company) in a turbulent business network, thereby bringing nuances to the common understanding that new relationships start in stable business networks where resource combinations are developed between actors in established business relationships.

Previous studies have stated that the development of a mutual orientation between actors leads to the formation of a business relationship. The business relationship then leads to resource adaptations between the two companies. The developed model, however, illustrates that this pattern can be reversed in situations of turbulence. Hence, previously adapted resources might lead to the formations of a business relationship. Based on this observation, the authors argue that there are reasons to question if previous models of business relationship initiation and development in business networks are adequately equipped for analysis in turbulent business networks.

This study aims to contribute to the body of knowledge through focusing on the moderating effect of risk-taking propensity in the relationship between network linkage and business performance.

Exploratory factor analysis was conducted so as to verify the items. Furthermore, the direct and moderation tests were conducted through the PROCESS macro.

The findings revealed the propensity for risk-taking is a significant moderator of the relationship between network linkage and business performance.

Women entrepreneurs are urged to increase their level of involvement in the networks so as to obtain external resources. Also, women entrepreneurs are encouraged to improve their risk-taking behaviour through training.

Little is known about the moderating role of risk-taking proclivity in the relationship between network linkage and business performance, particularly for women-owned businesses.

This study aims to provide a holistic review of social media influencers (SMIs) research based on a unique approach of bibliometric analysis and content analysis between 2011 and 2020. The review examines the main influential aspects, themes and research streams to identify research directions for the future.

The sample selection and data collection were done from the Scopus database. The sample dataset was refined based on the inclusion and exclusion criteria to determine the final dataset of 183 articles. The dataset was exported in the BibTeX format and then imported into the BiblioShiny app for bibliometric analysis. The content analysis was done following the theory-context-methodology framework.

The several findings of this study include (1) Co-word analysis of most used keywords; (2) Longitudinal thematic evolution; (3) The focus of the research papers as per the theory-context-methodology review protocol are persuasion knowledge model, fashion and beauty industries, Instagram and content analysis, respectively; and (4) The network analysis of the research studies is known as the co-citation analysis and depicts the intellectual structure in the domain. This analysis resulted in four clusters of the research streams from the literature and two emergent themes (Chen et al., 2010)

In general, the previous reviews in the area are either domain, method or theory-based. Thus, this study aims to complement and extend the existing literature by presenting the overall picture of the SMI research with the help of a unique combined approach and further highlighting the trends and future research directions based on the findings of this study.

The study utilises unique survey data gathered from 12,427 party members. The dependent variable measures party members’ in-party commitment and is based on willingness to donate money, to contribute effort, the feeling of belonging in the party network and social trust in the party network.

In this article, we study how different extra-parliamentary online and offline activities are associated with in-party commitment amongst political party members from the six largest Finnish parties. We especially delve into the differences between members of the Finnish parties.

We found that extra-parliamentary political activity, including connective action through social media networks and collective action through civic organisations, is highly associated with members’ in-party commitment. Additionally, members of the newer identity parties more effectively utilised social media networks, whilst the traditional interest parties were still more linked to traditional forms of extra-parliamentary political action.

By employing the sociological network theory perspective, the study contributes to ongoing discussions surrounding the impact of social media on political participation amongst party members, both within and beyond the confines of political parties.

This study examines the role of technology as a driver of sustainable tourism perceptions among Generation Z.

The work considers the perspective of locals in Pakistan and uses a multi-method, multiphase embedded research design approach.

The research findings demonstrated that technology has a positive correlation with the environmental, socio-cultural and economic dimensions of sustainable tourism perception among Generation Z. Therefore, technology could be considered a dimension of sustainable tourism perception for locals, but perceptions differ significantly depending on the size of the city of the participant. The results of the experimental design phase that utilized picture stimuli demonstrated a linear relationship between technology and sustainability and enhanced their definition and implementation for developing countries.

This research diverges from most past research on these topics by focusing on Generation Z, for whom digital media and technology play a crucial role and for whom these technologies are positively correlated with sustainability and its overall perception. Implications for policies and practices for emerging country governments are provided.

The purpose of this study is to depict the value added by digital transformation to intellectual capital (IC) by virtue of the studies reached by the literature review on different databases are examined.

Journal of Intellectual Capital, which has the highest number of records from the resources included in the “Web of Science” content and covering the title of “intellectual capital” has been selected in this study. Research using bibliometric analysis has been conducted and it has been determined that the terms “digital transformation” and “intellectual capital” should be searched for simultaneously in each and every article published in the journal between the years 1975 and 2022.

A bibliometric analysis and citation mapping process are carried out considering all dimensions to reach the results and interpretation of findings. VOSviewer is used to visualize the bibliometric networks of results and findings in the form of scientific mapping, as well as to visualize the co-authorship analysis of keywords, co-authorship analysis and citation networks.

Bibliometric analysis is a method that can be used to evaluate the performance of a single journal. However, it is important to note that bibliometric analysis has some limitations when it comes to assessing the validity of a single journal. This circumstance is elaborately described as a limitation of this study. Bibliometric analysis is a method that can be used to evaluate the performance of a single journal. However, it is important to note that bibliometric analysis has some limitations when it comes to assessing the validity of a single journal. One limitation is that bibliometric analysis is based on quantitative metrics, such as citation counts, which do not take into account the quality of the research. Therefore, bibliometric analysis alone may not provide a complete picture of the validity of a single journal. In addition, bibliometric analysis is based on the number of times a paper is cited, which can be influenced by factors such as the prestige of the journal, the field of research and the time since the publication. In conclusion, bibliometric analysis can be used to evaluate the performance of a single journal, but it is important to consider its limitations.

This study identified contributions, gaps and limits based on the results of a bibliometric analysis. Italy is the most influential country and the issue is structured around four clusters: IC; digital transformation; human capital; and knowledge management. As previously unexplored issues are addressed in an innovative manner, it is acceptable to underline the paper’s originality.

Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for inspectors. Image-based automatic inspection of cracks can be very effective when compared to human eye inspection. With the advancement in deep learning techniques, by utilizing these methods the authors can create automation of work in a particular sector of various industries.

In this study, an upgraded convolutional neural network-based crack detection method has been proposed. The dataset consists of 3,886 images which include cracked and non-cracked images. Further, these data have been split into training and validation data. To inspect the cracks more accurately, data augmentation was performed on the dataset, and regularization techniques have been utilized to reduce the overfitting problems. In this work, VGG19, Xception and Inception V3, along with Resnet50 V2 CNN architectures to train the data.

A comparison between the trained models has been performed and from the obtained results, Xception performs better than other algorithms with 99.54% test accuracy. The results show detecting cracked regions and firm non-cracked regions is very efficient by the Xception algorithm.

The proposed method can be way better back to an automatic inspection of cracks in buildings with different design patterns such as decorated historical monuments.

Resilience has evolved as a dynamic process in the entrepreneurship field. The purpose of this paper is to outline a comprehensive structure to analyse the patterns and trends in the publications of the existing literature at the junction of entrepreneurship and resilience. With the help of bibliometric and network analysis, this study offers insights into the topic that have not been evaluated and assessed by previous reviews.

A computerised search of 104 papers was performed using the Scopus database, and graphical visualisation of the bibliographic material was developed using VOSviewer software.

This comprehensive bibliometric mapping helps in the graphical visualisation of publication evolution of the domain along with identifying present research trends and possible future directions. There is not much collaborative research in the field, as most prolific thinkers work in isolation or in pairs. Hence, there are limited publications in top-rated journals. Future researchers need to work collaboratively to produce high-quality papers. Developed nations make a sound contribution to the field. The exact significance of resilience in entrepreneurship is yet to be determined due to a wide variety of themes that reflect the multi-disciplinary nature of the domain.

Uncovering the trends and developments of the field, this study provides a global perspective and potential themes lying at the junction of resilience and entrepreneurship. Hence, this study provides a robust roadmap for future researchers interested in this area.

The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images problems such as detail loss, low contrast and color distortion, and verify the feasibility of the proposed methods through experiments.

The improved RGHS algorithm to enhance the original underwater target image is proposed, and then the YOLOv4 deep learning network for underwater small sample targets detection is improved based on the combination of traditional data expansion method and Mosaic algorithm, expanding the feature extraction capability with SPP (Spatial Pyramid Pooling) module after each feature extraction layer to extract richer feature information.

The experimental results, using the official dataset, reveal a 3.5% increase in average detection accuracy for three types of underwater biological targets compared to the traditional YOLOv4 algorithm. In underwater robot application testing, the proposed method achieves an impressive 94.73% average detection accuracy for the three types of underwater biological targets.

Underwater target detection is an important task for underwater robot application. However, most underwater targets have the characteristics of small samples, and the detection of small sample targets is a comprehensive problem because it is affected by the quality of underwater images. This paper provides a whole set of methods to solve the problems, which is of great significance to the application of underwater robot.