The “Omnichannel Approach to Retailing” course aims to provide students with a comprehensive understanding of (i) the effective strategies to coordinate marketing channels and combine them into a unicum, (ii) how companies can use emerging technologies to create a seamless customer experience across various channels and (iii) how to design the omnichannel ecosystem of a company. This course will cover basic and advanced topics about channel marketing, omnichannel strategy development and new technologies that are used for implementing omnichannel strategies, such as Artificial Intelligence and Recommendation Agents, Augmented and Virtual Reality, IoT, RFID, Blockchain, Cloud Computing and others. The course will begin by discussing the concept of omnichannel retailing and how it differs from traditional retailing. Then, it examines the various channels through which retailers can reach their customers, including brick-and-mortar stores, e-commerce websites, mobile apps, social media, and more. It will then dive into the main connections (i.e., touchpoints) between consumers and channels and the strategies to optimize it as well as the emerging conflicts and sources of power in the supply chain. Subsequently, it offers an advanced depiction of the new technologies that are revolutionizing the retail industry, including Artificial Intelligence and Recommendation Agents, Augmented and Virtual Reality, IoT, RFID, Blockchain, Cloud Computing and explores how these technologies are being used by retailers to enhance customer experiences, streamline operations, and increase sales. Throughout the course, students will also discuss the challenges and opportunities of implementing an omnichannel approach to retailing by examining real case studies of successful omnichannel retailers. By the end of the course, students have a solid understanding of the omnichannel approach to retailing and the role that new technologies play in its success. Students will be able to identify the key components of an effective omnichannel strategy, evaluate the challenges and opportunities of implementing such a strategy and design an omnichannel ecosystem.

At the completion of this course, students will be able to: Knowledge and understanding Define the concept of omnichannel retailing and its benefits Identify the different channels involved in omnichannel retailing, including online, mobile, social media, physical stores, and others Develop an omnichannel retailing strategy which is aligned with the overall business goals Recognize the importance of data analytics and technology in omnichannel retailing Distinguish the latest technological advancements in omnichannel retailing, such as artificial intelligence, augmented reality, virtual reality, IoT, and others Applying knowledge and understanding Examine the effectiveness of new technology implementation in omnichannel retailing Examine how to develop omnichannel ecosystems by applying the knowledge acquired during the course and implanting Industry 4.0 technologies Examine real business cases about omnichannel retailing Making Judgements Compare the main omnichannel strategies and the business implications Examine the ethical implications of using new technologies in omnichannel retailing Communication Skills Develop skills in communication, leadership and strategic thinking to drive innovation and agility in the adoption of new technologies in omnichannel retailing Develop skills in creating personalized customer experiences through omnichannel retailing Develop skills in integrating new technologies into an omnichannel retailing strategy Learning Skills Examine the results of the relevant data analytics and technology in omnichannel retailing

The modules of the course will cover the following topics: Introduction to Channel Marketing and Omnichannel Retailing Omnichannel Strategy Development Customer Journey Mapping Pricing Decisions in Omnichannel Environments Promotions and Discounts in Omnichannel Environments Data Analytics for Omnichannel Retailing Technology in Omnichannel Retailing Artificial Intelligence for Omnichannel Retailing Recommendation Agents for Omnichannel Retailing Augmented Reality, Virtual Reality, IoT and RFID technologies for Omnichannel Retailing Customer Relationship Management Platform for Omnichannel Retailing Cloud Computing and Blockchain for Omnichannel Retailing

The key textbooks for the course are: Palmatier, R. W., Stern, L. W., & El-Ansary, A. I. (2016). Marketing channel strategy: An omni-channel approach. Routledge. (Chapter I, II and XI for attendant students; All chapters for non-attendant students) – Mandatory for both attendant and non-attendant students Course handouts - Mandatory for both attendant and non-attendant students Bell, D. R., Gallino, S., & Moreno, A. (2014). How to win in an omnichannel world. MIT Sloan Management Review. – Mandatory only for attendant students Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of marketing, 80(6), 69-96. - Mandatory for both attendant and non-attendant students Hamilton, R., Ferraro, R., Haws, K. L., & Mukhopadhyay, A. (2021). Traveling with companions: The social customer journey. Journal of Marketing, 85(1), 68-92. – Non-mandatory Reading Kumar, S., Jebarajakirthy, C., & Das, M. (2022). Building trust among channel members via power sources. Journal of Business & Industrial Marketing, 37(9), 1802-1817. - Mandatory only for non-attendant students Xu, X., & Jackson, J. E. (2019). Examining customer channel selection intention in the omni-channel retail environment. International Journal of Production Economics, 208, 434-445. - Non-mandatory Reading Webb, K. L., & Didow, N. M. (1997). Understanding hybrid channel conflict: a conceptual model and propositions for research. Journal of Business-to-Business Marketing, 4(1), 39-78. - Mandatory for both attendant and non-attendant students Priya Raghubir, J. Jeffrey Inman, Hans Grande (2004). The Three Faces of Consumer Promotions. Harvard Business Publishing - Non-mandatory Reading Alexander, B., & Kent, A. (2022). Change in technology-enabled omnichannel customer experiences in-store. Journal of Retailing and Consumer Services, 65, 102338. - Mandatory for both attendant and non-attendant students Hübner, A., Holzapfel, A., & Kuhn, H. (2016). Distribution systems in omni-channel retailing. Business Research, 9, 255-296. – Mandatory only for attendant students Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50. - Non-mandatory Reading Pournader, M., Ghaderi, H., Hassanzadegan, A., & Fahimnia, B. (2021). Artificial intelligence applications in supply chain management. International Journal of Production Economics, 241, 108250. - Mandatory only for non-attendant students Puntoni, S., Reczek, R. W., Giesler, M., & Botti, S. (2021). Consumers and artificial intelligence: An experiential perspective. Journal of Marketing, 85(1), 131-151. - Mandatory only for attendant students Xiao, B., & Benbasat, I. (2007). E-commerce product recommendation agents: Use, characteristics, and impact. MIS quarterly, 137-209. - Mandatory only for non-attendant students Aydınocak, E. U. (2021). Internet of things (IoT) in marketing logistics. In Logistics 4.0 and Future of Supply Chains (pp. 153-169). Singapore: Springer Nature Singapore. (Chapters VI and VII) - Mandatory only for attendant students Pagani, M., & Pardo, C. (2017). The impact of digital technology on relationships in a business network. Industrial Marketing Management, 67, 185-192. - Non-mandatory Reading Cole, R., Stevenson, M., & Aitken, J. (2019). Blockchain technology: implications for operations and supply chain management. Supply Chain Management: An International Journal, 24(4), 469-483. Mandatory only for attendant students

Fully synchronous TA consultations Group work Case Studies Flipped Classroom Project Work

Students will be evaluated on the following activities: Weekly quizzes (40%) – Knowledge – Individual grade In-class exercises on topics discussed during Lecture 2 (Week 2), Lecture 2 (Week 3) and Lecture 2 (Week 5) (10%) – Practice - Hybrid grade (Individual and Group grade) Project Work (20%) – Practice – Group grade – From week 7 to 12, students will develop their project work by applying the knowledge acquired through the lectures in the same weeks. See “E-tivities” of weeks 7,9,11 and 12 to understand how the grade is structured. Final project work delivery (10%) - Group grade – Students will get full 10% of their final grade (i.e., 3 points) if they deliver the full project at its deadline. In order to get that 10%, the project should be complete in all its components. In-person oral exam: (10%) - Individual grade – Students will get maximum 10% (i.e., 3 points) for presenting the final project work. The assessment will be based on the preciseness and quality of communication. Continuous In-class participation (10%) - Individual grade – Students are encouraged to actively participate during the course. Only students who are constantly engaged in the course activities and participate during lectures, will get maximum 10% (i.e., 3 points). To get all the points the students can (1) interact with the professor during the lectures, provide her/his opinion about the discussed topics and positively contribute to the learning and teaching process and (2) complete all the mandatory and non-mandatory exercises. Students can obtain an extra 1.5 points on the final grade if all the following conditions are met: The student participates in all the bonus activities (which are not mandatory). In particular, students will get the extra 1.5 points at the completion of all bonus exercises from Week 1 to Week 12. In each of the bonus activity, you have to have for each quiz 2 correct answers out of the 4 questions. For non-attending students the evaluation will be based 100% on a final written exam based on the materials of the non-attendant program.