The IS-Marketing Interface
Introduction
The INFORMS journal Information Systems Research will launch an editorial initiative on the IS–Marketing interface
INTEREST CATEGORY: INNOVATION AND TECH
POSTING TYPE: Journal News
Posted by: Rajdeep Grewal
Announcement: ISR launches the IS–Marketing interface initiative
Information Systems Research (ISR), a leading INFORMS journal in information systems, is launching a new editorial initiative focused on the IS–Marketing interface.
ISR welcomes submissions that make integrated contributions to both information systems and marketing by placing the digital system at the center of the research question and explanation. Suitable papers focus on digital systems as they operate in practice, for example, tracking and logging of user actions; recognizing the same customer across devices, browsers, and sessions; data storage, access, and governance inside the firm; and algorithmic policies that determine what users see and what they receive, including search ranking, recommendations, and the allocation or pacing of ads, leads, inventory, or service capacity. This initiative also includes work on platform rules and incentives, constraints created by privacy policies and regulation, and AI-enabled workflows used by employees and customers, including settings with human review and oversight.
These system features should be linked to marketing-relevant behaviors and outcomes such as customer experience and journeys, targeting and personalization, pricing and promotion effectiveness, marketplace competition, measurement and attribution, and ultimately firm strategy and performance. For example, customer recognition across devices can change targeting accuracy, frequency control, and cross-channel attribution. Better recognition can reduce wasted impressions or repeated outreach to the same person, shift budget toward customers and channels that truly drive incremental conversions, and improve the return per marketing dollar spent.
In short, strong IS–Marketing interface submissions do not treat the platform, algorithm, or data pipeline as a black box. They identify the system mechanisms at work and connect those mechanisms to observable customer behavior and market outcomes, delivering insights that speak credibly to both IS and marketing audiences.
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