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The purpose of this paper is to ease the methodological application of critical realist multilevel research in business marketing. Although there has been plenty of theoretical contributions in this field, it is not always clear how critical realism can be best applied in business marketing settings. Accordingly, this paper addresses this gap in literature. Also, this paper addresses the calls for a multilevel conceptualization for resilience, based on the critical realist laminated systems.

This is a conceptual paper, which uses pre-existing literature to develop a critical realist methodological approach for the purposes of multilevel business marketing research. The contribution is based on literature by combining pre-existing ideas in a new way in the context of business marketing.

This paper makes a methodological contribution by introducing the critical realist “laminated systems” to business marketing as a multilevel research approach. Furthermore, the authors conceptualize a specific laminated model, the Laminated Interactional Model (LIM), that is designed for the purpose of business marketing research. The LIM is a methodological tool that conceptualizes business marketing based on six levels of analysis, easing the methodological application of critical realism in business marketing settings. In addition, to provide an example, the authors apply the LIM to the literature on resilience, providing a multilevel conceptualization. This is a timely contribution, as resilience has emerged as a central concept addressing interorganizational survival during the COVID-19 pandemic.

This paper makes three main contributions to business marketing. First, this paper provides a methodological contribution by introducing the critical realist notion of “laminated systems” to business marketing. Second, this paper conceptualizes a specific laminated model for business marketing, namely, the LIM. Third, as a response to the COVID-19 pandemic, this paper will apply critical realism and the LIM to the notion of resilience, addressing the calls for multilevel conceptualizations.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.