Connexor (Finland)

Arranging products in stores according to planograms, optimized product arrangement maps, is an important sales enabler and necessary for keeping up with the highly competitive modern retail market. Key benefits of planograms include increased efficiency, maximized retail store space, increased customer satisfaction, visual appeal, and increased revenue. The planograms are realized into product arrangements by humans, a process that is prone to mistakes. Therefore, for optimal merchandising performance, the planogram compliance of the arrangements needs to be evaluated from time to time. We investigate utilizing a computer vision problem setting—retail product detection—to automate planogram compliance evaluation. Retail product detection comprises product detection and classification. The detected and classified products can be compared to the planogram in order to evaluate compliance. In this paper, we propose a novel retail product detection pipeline combining a Gaussian layer network product proposal generator and domain invariant hierarchical embedding (DIHE) classifier. We utilize the detection pipeline with RANSAC pose estimation for planogram compliance evaluation. As the existing metrics for evaluating the planogram compliance evaluation performance assume unrealistically that the test image matches the planogram, we propose a novel metric, called normalized planogram compliance error (EPC), for benchmarking real-world setups. We evaluate the performance of our method with two datasets: the only open-source dataset with planogram evaluation data, GP-180, and our own dataset collected from a large Nordic retailer. Based on the evaluation, our method provides an improved planogram compliance evaluation pipeline, with accurate product location estimation when using real-life images that include entire shelves, unlike previous research that has only used images with few products. Our analysis also demonstrates that our method requires less processing time than the state-of-the-art compliance evaluation methods.

Purpose– The purpose of this paper is to increase understanding on the essential managerial and technical decisions in the design of IOIS for supply chain integration (SCI). Toward this end, the authors elaborate on IOIS constructs in the SCI context, and propose a framework on the design of IOIS for SCI based on the current literature.Design/methodology/approach– The paper draws from prior literature on interorganizational information systems (IOISs) and supply chain management (SCM), and builds a conceptual framework that is illustrated by empirical examples from three case studies of a ten-year research program that focussed on e-business in SCM.Findings– Based on prior literature from several domains, the authors propose a framework, which combines the managerial viewpoints and the technical viewpoints for designing IOIS for SCI. The authors argue that these decisions form the basis for constructing three main elements of the IOIS for SCI design theory, namely, purpose and scope, design principles, and technical framework. Furthermore, the authors suggest that the real thread binding the decisions on all levels – purpose and scope; design principles; technical framework – is the flexible differentiation over use contexts, primarily over partners and focal interorganizational processes.Research limitations/implications– The key limitation of this work is the propositional nature of the advanced framework. However, the framework is strongly grounded in prior literature and is illustrated by examples from three empirical studies.Practical implications– The proposed framework provides a systematic tool for both the design and evaluation of the practical implementation of IOISs in SCI context. Furthermore, the results point explicitly to the implications of the benefits received from unilateral and bilateral modes of IOIS design.Originality/value– The synthesized framework and the observation of the requisite differentiation over use context complement prior work from multiple domains by discussing both managerial and technical questions of IOIS deployment within a single conceptualization.