Industrial Marketing Management

 

Call for Papers

Market-driven Supply Chains in a Digital World

Deadline for submission: 1 March 2019

Overview and Purpose

This special issue seeks to develop knowledge and generate insights into the opportunities and the challenges for enhancing marketing performance through the creation of digitally-enabled supply chain strategies. The special issue builds on and extends research published in Industrial Marketing Management on market-driven supply chains (IMM vol. 36, issue 3), digital innovations (IMM vol. 42, issue 5, 2013), value proposition design in digital markets (IMM vol. 41, issue 1, 2012) and linkages between servitisation and digitization (IMM, vol. 60, issue 1, 2017).

It has been apparent for some time that a powerful source of competitive advantage can be created through the way that supply/demand networks are designed and managed (Fisher 1997). This is increasingly the case as the need for agility (Christopher 2000) becomes ever more critical in today’s turbulent and uncertain market conditions. Emphasising the need for supply chains to be market-driven, responsive and agile, some authors have suggested to rename Supply Chain Management (SCM) as demand chain management (Jüttner et al. 2007). Today, the way firms in supply chains go to market and the very way supply chains compete is being transformed through digitisation. Digitisation of information causes fundamental change in supply chain management, impacting businesses in every sector (Kache and Seuring 2017). On the one hand, digitized information flows in the supply chain can increase and accelerate the opportunity for value creation (LaValle et al. 2011). Sanders (2016) suggest that analytics-driven SCM provides more opportunity for real-time inquiry, fosters new knowledge-creating inquiries and enables large scale experiments supporting an understanding of market dynamics based on an unprecedented number of social and economic variables. On the other hand, it has been argued that digital disruption can cause changes to established supply chain structures, leaving those firms behind which do not understand the shifts and are unable to adapt accordingly (Waller and Fawcett 2013). Among the key challenges for firms are how to transform their traditional supply chains with linear information flows to a dynamic, integrated digital network and how to communicate, aggregate, analyze and act upon the abundant information provided (Mussomeli and Gish 2016).

Collecting data through an IT infrastructure along the supply chain (Wu et al. 2016) and, subsequently, applying big data analytics (Richey et al. 2016) are seen as the basis for the development of digital supply chain process applications. Two Delphi studies (Kache and Seuring 2017; Brinch et al. 2018) along with a number of best practice examples (Hu and Monahan 2015) highlight the perceived opportunities of these applications for value creation. Marketing applications of digital supply chain processes enable companies to quickly adjust their customer strategies and offerings, to better forecast demand on a micro-segment basis or to rearrange individual product assortments based on predicted customer behavior. Applications in supply processes, ranging from logistics to operations, manufacturing and sourcing, can all be designed in a way to fulfill these new, data-driven value propositions more effectively and efficiently. Logistics applications can for example improve productivity by avoiding delays through preventive maintenance, tracking inventory in motion or optimizing fuel efficiency, all of which support a more sustainable, flexible and transparent flow of materials and end products throughout the chain. Automated control and virtual monitoring in operations and manufacturing applications support decisions ranging from inventory management to maintenance optimization, quality management and facility location. They enable the design of a leaner supply chain with more consistent processes and higher product quality. Finally, analytics in sourcing applications may inform negotiations with suppliers by leveraging factual evidence of customer preferences and buying behaviours. Examples such as these point to the abundant opportunities for increasing supply chain responsiveness to changing market conditions in these information-enriched ecosystems.

Although many firms in supply chains see the merits of digitalized supply and demand networks, unresolved issues prevent their full exploitation. Some of the most pressing issues have been investigated in the pre-digitalised markets but the concepts need to be readdressed in the emerging digital era. For example, Kache and Seuring (2017) find that although companies identify customer behavior analytics as the biggest corporate-level opportunity, many appear to ignore that a narrow focus on customer interaction overlooks the impact along the supply chain. Similarly, Sanders (2016) found that only leading companies are able to coordinate the often hyper-specialised process applications in a functionally linked manner and as part of a coordinated overarching business strategy. Hence, supply chain integration (Stevenson 1989) needs to be readdressed. Likewise, end-to-end supply chain visibility has been recognized as an important driver for competitive advantage for more than 20 years (Mason-Jones and Towill 1997). In digital networks, the increase of the multidirectional, real-time information flows drives new opportunities that are not restricted to more efficient demand fulfillment, but may also foster supply network-driven innovations (Schoenherr and Speier-Pero 2015) or more resilient network structures (Urciuoli 2017). Still, the abundant information among all nodes also raises important governance questions (Hu and Monahan 2015). This is likely to be exacerbated by the fact that the number of network parties may increase since transaction costs decrease through information technology (Mussomeli and Gish 2016). Linked to the IT-driven information flows is the issue of collaboration (Barratt 2004). Although agreement can be traced on the need for more structured collaboration models which enable participatory decision and co-creation (Hu and Monahan 2015), just what these models may look like remains an open question.

We want to encourage research contributions that build on established knowledge in the area of market-driven supply chains and investigate them in the new context of our increasingly data-driven world. To that end, we seek manuscripts that draw on multiple methodologies including qualitative, quantitative, case study or triangulation of methods. All manuscripts should have clear relevance to the industrial/B2B or business market domain. As well, conceptual papers that focus on digital supply chain network design and on using data and technology to optimize supply chain decisions are welcome.

Possible topics include, but are not limited to:

• Supporting digital business models through supply chains
• Supplying products and services for Big Data-driven, bespoke customer value propositions
• Increasing the market orientation, speed to market and agility of supply chains through real time, digital information flows
• Supporting the transformation from push to pull-driven supply chains through digitisation
• Designing and managing personal supply chains for customer value co-creation
• Exploring the role of digital supply chains for marketing strategies
• High tech versus high touch buyer supplier relationships in digital supply networks
• Disruption of traditional demand- and supply-side structures through digitalization
• Digital process applications in marketing, logistics, operations and sourcing
• Decision making in digital supply chains
• Sustainable operations in digital supply chains
• Big data analytics coordination between buyers and suppliers
• Digital solutions: combining physical and digital products
• Dynamic assortment adjustment strategies based on digital supply chain processes
• Digital processes and supply chain resilience
• Buyer seller relationships in remote servicing contexts
• Governance in digital networks

Other topics are also welcome as long as they relate to the digitalization of supply chains. Papers submitted to Industrial Marketing Management should be explicit about their contribution to industrial/B2B marketing or business markets.

Manuscript Preparation and Submission

To submit a paper please visit the IMM editorial site at

https://www.evise.com/profile/#/IMM/register.

Please login, register as an author, and submit the paper as the site will instruct you. Submissions are welcome no later than 1 March 2019. When you get to the step in the process that asks you for the type of paper, select SI: Market-driven Supply Chains in a Digital World. All papers will be reviewed through the standard double-blind peer review process of IMM. In preparation of their manuscripts, authors are asked to follow the Author Guidelines closely. A guide for authors, sample articles and other relevant information for submitting papers are available at:

https://www.elsevier.com/journals/industrial-marketing-management/0019-8501/guide-for-authors.

All queries about the special issue should be sent to the Guest Editors (see below).

Guest Editors

Martin Christopher, Emeritus Professor of Marketing & Logistics, Cranfield University, School of Management, M.G.Christopher@cranfield.ac.uk

Uta Jüttner, Professor of Services and Operations Management at the University of Applied Sciences Lucerne, Business School, uta.juettner@hslu.ch

References

Barratt, M. (2004), “Understanding the meaning of collaboration in the supply chain”, Supply Chain Management: An International Journal, 9(1), 30-42.

Bechtsis, D., Tsolakis, N., Vlachos, D. and Iakovou, E. (2017), “Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehiclesm,” Journal of Cleaner Production, 142, 3970-3984.

Brinch M., Kronborg, J. and Rajkumar, C. (2018), “Practitioners understanding of big data and its applications in supply chain management”, International Journal of Logistics Management, 29 (2), 555-574.

Christopher, M. (2000), “The Agile Supply Chain: Competing in Volatile Markets,” Industrial Marketing Management, 29(1), 37-44.

Fisher, M. (1997), “What is the right supply chain for your product?” Harvard Business Review, 75(2), 105-116.

Jüttner, U., Christopher, M. and Baker, S. (2007), “Demand chain management-integrating marketing and supply chain management,” Industrial Marketing Management, 36(3), 377-392.

Kache, F. and Seuring, S. (2017), “Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management,” International Journal of Operations & Production Management, 37(1), 10-36.

LaValle, S., Lesser, E., Shockley, R., Hopkins, M.S. and Kruschwitz, N. (2011), “Big Data, analytics and the path from insights to value”, MIT Sloan Management Review, 52(2), 21-31.

Li, G., Yang, H., Sun, L. and Sohal, A.S. (2009), “The impact of IT implementation on supply chain integration and performance”, International Journal of Production Economics, 120 (1), 125-138.

Mason-Jones, R. and Towill, D.R. (1997), “Information enrichment: designing the supply chain for competitive advantage”, Supply Chain Management: An International Journal, 2(4), 137-148.

Monahan, S. and Hu, M. (2015), “Sharing Supply Chain Data in the Digital Era, MIT Sloan Management Review, 57(1), 95-96.

Mussomeli, A. and Gish, D. (2016), “The rise of the digital supply network”, Research Report Deloitte University Press.

Richey, R. Morgan, T., Lindsey-Hall, K. and Adams, F. (2016), “A global exploration of Big Data in the supply chain,” International Journal of Physical Distribution & Logistics Management, 46 (8), 710-739.

Sanders, N. (2016), “How to Use Big Data to Drive Your Supply Chain,” California Management Review, 58(3), 26-48.

Schoenherr, T., and Speier-Pero, C. (2015). Data Science, Predictive Analytics, and Big Data in Supply Chain Management: Current State and Future Potential. Journal of Business Logistics, 36(1), 120-132.

Stevenson, G. (1989), “Integrating the Supply Chain,” International Journal of Physical Distribution & Logistics Management 19(8), 3-8.

Waller, M.A. and Fawcett, S.E. (2013), “Data science, predictive analytics, and Big Data: a revolution that will transform supply chain design and management”, Journal of Business Logistics, 34(2), 77-84.

Wu, L., Xiaohang Y, Jin, A. and Yen, D. (2016) "Smart supply chain management: a review and implications for future research", The International Journal of Logistics Management, 27(2), 395-417

Urciuoli, L. (2017), Automating Supply Chain Resilience should be high on your Digital Agenda, MIT Sloan Management Blog Entry, 20 Januar 2017 http://sloanreview.mit.edu/article/automating-supply-chain-resilience-should-be-high-on-your-digital-agenda/

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