Conference Agenda

This study was conducted at the University of Kassel (Germany) as part of the PRONET project (Professionalisation through Networking), funded by the BMBF. The central aim of PRONET was to foster active collaboration among the participating 34 sub-projects, bringing them together to jointly develop new outputs such as concepts, materials, seminars, and workshops. These efforts were designed to advance research, teaching, and practice in teacher education.

The evaluation of collaboration between the sub-projects was conducted through an online survey at three points in time (winter 2015, summer 2017, and winter 2018). The resulting connections between the sub-projects were analyzed using network analysis. The goal of the evaluation was to assess the impact of cooperation on the activities of the sub-projects.

This study seeks to operationalize cognitive proximity between projects in teacher education and to examine its influence on collaboration. Cognitive proximity was operationalized by analyzing the frequency of word usage (correspondence analysis) in the publications of the projects. In this context, the use of different words increases the distance between two projects, while the use of similar words brings them closer together.

The first research question addressed in this study is whether cognitive proximity directly influences network collaboration. This question was explored by testing the ego, alter, and similarity effects of cognitive proximity on collaboration between projects.

The second research question examines whether cognitive proximity influences the reciprocity of collaboration (mutuality) and the clustering within the collaboration network (triadic closure). The longitudinal analysis was conducted using a stochastic actor-oriented model (SOAM). A key finding related to the first question was that the alter effect of cognitive proximity has a negative impact on collaboration. In other words, as expected, projects that are cognitively distant are less likely to be mentioned or chosen as collaboration partners.

When concepts spread over a network of organizations, they are adapted and translated. In an organization field, organizations adopt elements of concepts that help them reflect environmental expectations they face, they leave out other elements that they do not deem to be relevant or a good fit in their context, they creatively recombine them with other concepts that are already at place in their organizations, potentially creating new conceptual ideas. As a result, there exists a variety of instances of concepts, even within one organizational field. But how can we measure and make sense of this variety of concepts’ meanings within and across fields? And how can this variety of concepts be explained by the network structure of the field?

We argue that the idea of translation is valuable for addressing this question. Concepts travel within and across organizational fields through networks and cultural linkages. In the network, the members are acting as both recipients and transmitters of concepts which, in turn, allows for an alteration or recombination of those. The greater the diversity of receiving concepts, the greater the recombinatorial possibilities. Organizational fields are characterized by network structures and a shared meaning system driven by isomorphic pressures. Field constellations can thus help making sense of the variety of concepts observable among field members.

We explore the variety of concepts in the context of three fields: The fields evolving around Blockchain technology, the issues of cooperativism and sharing economy. We argue that these three fields are promising for exploring concept variety as they all are based on conceptual ideas of decentralization and sharing: Blockchain technology allows decentralized data storage. Cooperativism involves shared ownership and decentralized decision-making in organizations. The sharing economy is based on the idea of organizing shared access to distributed products, services and resources. Based on the argument that textual embedding models are a powerful approach to representing multidimensional conceptual spaces, we apply these models to the texts we find on organizational websites using a measurement approach. Different from Acevas & Evans (2023), we will use sentence embeddings such as SBERT (Reimers & Gurevych, 2019) where sentences (or paragraphs) are already the unit of text the model was trained on. We use Wikipedia as data source to identify and describe central dimensions for the three conceptual ideas characterizing the cores of the three fields:

Blockchain technology, cooperative organizational form and sharing economy. Wikipedia reflects the social stock of knowledge as conceptualized in the theorization literature.

Our contributions are twofold. Theoretically, we contribute by emphasizing translation as an agentic process where the adoption of elements of a concept depends on both the position of an organization within the conceptual space and the social space.

Methodologically, we contribute by utilizing language models to measure the variety of the three concepts that are reflected on the websites. This allows us to trace which elements are adopted and how they are recombined with the elements of the other concepts.

This paper explores how fluctuations in the importance of brands within online news can impact retail store sales across different product categories. Using a dataset of over 250,000 news articles from The New York Times between 2019 and 2023, along with daily sales data from more than 60,000 U.S. stores, we explore the connection between brand importance and consumer behavior in physical retail environments. We analyze semantic networks and employ the Semantic Brand Score (SBS) to evaluate the prevalence, diversity, and connectivity of well-known brands across sectors such as grocery, fast food, and specialty merchandise. Our findings demonstrate that a one standard deviation increase in brand importance is associated with a sales increase of over 1%, with this effect persisting for up to five weeks. In contrast to the short-lived impact of social media, the influence of news media on sales appears to be more sustained. This paper contributes to the literature by shifting focus from social media to online news, offering detailed insights into the media’s impact across a broad range of retail sectors, and using big data in place of traditional surveys. Our results highlight the importance of maintaining a strategic presence in news media and suggest that retailers can benefit from continued media coverage, which has the potential to shape consumer behavior over an extended period.