A Framework for Enabling Synergic Interactions Between Omnichannel and Product Lifecycle Management Platform Inspired by System Dynamics Approach

  • The rapid rise of new technologies, such as mobile phones, social networks, and increased internet access, has created new opportunities for retailers to expand through omnichannel strategies, which aim to provide a seamless customer experience across different channels. While omnichannel can offer benefits and competitive advantages, it faces challenges like price inconsistencies and poor information sharing. Despite its growing recognition, its integration with Product Lifecycle Management (PLM) is underexplored. This thesis investigates the overlap and mutual effects of omnichannel and PLM, particularly emphasizing the importance of data and knowledge sharing between them. As research into data analytics in omnichannel evolves, tracking and tracing mechanisms in PLM become increasingly critical. The main objective of this study is to develop a bi-directional framework connecting omnichannel and PLM using a System Dynamics approach. This framework aims to incorporate omnichannel mechanisms into PLM and provide cause-and-effect analysis to better understand the operational role of omnichannel within PLM. Additionally, the research introduces an approach to integrate Business-to-Business (B2B) aspects from PLM with Business-to-Customer (B2C) elements through omnichannel strategies. Leveraging omnichannel's influence on touchpoints like influencers and social media, this approach helps companies align consumer behavior with strategic goals, boosting competitiveness. Ultimately, this thesis aims to bridge the gap between omnichannel and PLM, driving a shift in consumer behavior and strengthening the integration of B2B and B2C in retail.

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Publishing Institution:IRC-Library, Information Resource Center der Constructor University
Granting Institution:Constructor Univ.
Author:Noushin Mohammadian
Referee:Yilmaz Uygun, Amir Pirayesh, Alexander Schlüter
Advisor:Omid Fatahi Valilai
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1012452
Document Type:PhD Thesis
Language:English
Date of Successful Oral Defense:2024/06/04
Date of First Publication:2024/10/23
Other Countries Involved:France
Academic Department:School of Business, Social and Decision Sciences
PhD Degree:Industrial Engineering and Management
Call No:2024/11

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