The introduction and rapid proliferation of e-commerce in recent years have forced many companies to rethink their operations, including their supply chains, to integrate online and offline channels, inspiring the birth of the omni-channel world. Although this omni-channel environment offers new, unparalleled opportunities for accelerated growth, most companies (notably, retailers) are also facing unprecedented challenges, and the very survival of brick-and-mortar channels is in question. They must keep pace with ever-evolving technology and customer expectations, and offer a seamless experience across all channels, blurring the lines of distinction between brick-and-mortar and digital experiences.
Several companies have responded to this challenge by offering additional services, including buy online/pickup-in store (BOPS), reserve-online-pick-up-and-pay-in-store (ROPS), ship-to-store (STS), ship-from-store (SFS), or buy-inStore/ship home (BSSH). However, there are still many open operations research/management science (OR/MS) questions involving the integration of supply chain network design, product fulfillment, distribution, pricing, and returns. To address these questions most effectively, companies must turn to advanced analytical approaches within a data-rich environment.
Within this context, this special issue is expected to present a broader, more thorough insight for the successful application of analytical practices by companies participating in omni-channel supply chains on topics such as (but not limited to):
Demand prediction for online vs. offline channels concerning product level, SKU level, location, and time of consumption;
Location analytics combining geographic data, map-driven analysis, infrastructure, facility size and availability, and spatial patterns;
Analytical approaches (including novel inventory models) to address central issues from e-fulfillment to omni-channel fulfillment;
Distribution and delivery models with a variety of service offerings for last-mile delivery (e.g., same-day, next-day, bulk, inexpensive, expedited, and premium delivery), especially with membership services that offer "free" deliveries or that consider different delivery pricing models;
New shipping ideas and models supporting omni-channels, including handling the challenges of closed-loop supply chains;
Pricing, omni-channel revenue management, managing the financial impact of returns, mark-down optimization, and market segmentation;
Collaboration and coordination with supply chain teams and partners internally and externally, potentially with pricing contracts;
Integration of information systems and optimization tools;
Analytical barriers and challenges in the design and management of omni-channel supply chains;
Influence of new trends in the digital-platform economy, sharing economy, and disruptive manufacturing on omni-channel supply chain design.
Authors should review the instructions on preparing a paper for the INFORMS Journal on Applied Analytics at: pubsonline.informs.org/page/inte/submission-guidelines. Papers must be submitted online at: mc.manuscriptcentral.com/inte.
When submitting a paper, please note the following:
Under "Step 1: Type, Title, & Abstract," select "Special Issue" for "Type."
Under "Step 5: Details & Comments," answer "This paper is for which special issue?" with "Omni-channel Supply Chains."
The editors encourage potential authors to contact them with ideas for papers before a making a full submission of a paper. Please note the following dates:
November 15, 2019: Letter of intention to publish due to the editors, with an abstract including the organization at which the work was implemented.
February 15, 2020: Target deadline for the first round of submissions.
May 15, 2020: First round of reviews completed; decisions (and requests for revision, if appropriate) delivered to authors.
August 15, 2020: Second round of reviews delivered to authors.
November 15, 2020: Final versions of accepted papers must be submitted.
Publication contact information for the Special Issue Editors:
Burcu B. Keskin
University of Alabama
IBM T.J. Watson Research Center