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FINAL CALL FOR PAPERS

Special Issue: Journal of Product Innovation Management: “Innovation in Data-Rich Environments”

Just Announced: Marketing Science Institute (MSI) Research Awards for Research Workshop Invitees and Best Paper Awards

Guest Editors

• Neeraj Bharadwaj, The University of Tennessee (nbharadwaj@utk.edu)
• Charles H. Noble, The University of Tennessee (cnoble@utk.edu)

Motivation and Overview

Proclamations abound that we have entered the era of data-rich environments. This is supported in reports suggesting that 90 percent of the data that exists in the world today was created in the last two years and that the amount of data present in the “digital universe” will double every year to reach 40,000 exabytes by 2020. As we hope to explore with this special issue, this shift towards a data-rich environment has significant implications for successful new product development and innovation efforts.

Scope and Focus of the Special Issue

We expect that this special issue will result in seminal contributions to our understanding of the broad connections between data-rich environments, innovation, and new product development (NPD). Potential research topics for this special issue include the following, many of which connect directly to the recently published (2014) JPIM research priorities. These topics are only intended to be thought-starters, and other perspectives are highly encouraged:

• Innovating in a Data-Rich Environment
  • How can companies improve their analytical capabilities to make better NPD decisions and implement them within NPD teams?
  • How can new product ideas emerge in data-rich environments? What is the appropriate role of experimentation?
  • What is the role of social media in generating new product and service ideas? How can it be used as a complement to traditional idea generation methods?
  • How can firms leverage the use of digital/social/mobile data in NPD?
  • What new analytical methods can be developed to generate better new product ideas from unstructured data (e.g., social media)?
  • What methods can be used to make real-time NPD decisions in a data-rich environment?
• Corporate Innovation
  • How can the large amount of data now available help improve technology forecasting?
  • How can companies balance the apparent contradiction between increasingly massive data challenges and constantly decreasing corporate attention spans?
• Service Innovation
  • What are the key characteristics of a systematic process for service innovation in data-rich environments?
  • How can goods-based companies use data to be more strategic in their service infusion strategies?
• Collaboration
  • What can large amounts of data add to small scale (internal) and broader external innovation collaborations?
  • How is an effective balance achieved between externally-generated large-scale data and more internally-focused “collaboratories” and innovation centers?
• Success & Failure
  • As a learning tool, how can the availability of large datasets (e.g., A.C. Nielsen Consumer Panel Data and Retail Scanner Data) improve the chances of innovation success and minimize the chances of failure?
• Globalization
  • What are the challenges encountered in incorporating large amounts of globally-generated data into the innovation process?
• Open Innovation
  • In an Open Innovation environment, are unstructured and structured data equally useful?
  • Are ideas such as “crowdsourcing” still too narrowly-bounded to take advantage of the potential of Big Data?
  • What is the effect of crowdsourcing on the organization and management of NPD? Are the traditional tasks, roles, and responsibilities challenged and how?
  • What is the “dark side” (e.g., information overload, loss of control, winner takes all, intellectual property issues) of crowdsourcing?
  • How can firms ‘qualify’ crowdsourcers? How can/should they evaluate and assess what crowdsourcers do?
• Talent
  • How does the nature of the ideal innovation-driving senior management team change in a world where large amounts of data must be understood and acted upon?
  • How does the composition of the NPD team need to change in a data-rich environment?
• Process
  • How can large-scale data best be incorporated as just one element of a successful new product development and innovation process?
  • Are different types of data (e.g., unstructured vs. structured; or text vs. images) more suitable for different types of innovation?

Review Process and Timeline

• Submission due date: February 1, 2016
• First round decisions: May 1, 2016
• Research workshop (at The University of Tennessee)* June, 2016
  *For authors who are invited to submit a revision
• Revision due date: November 1, 2016
• Second round decisions: February 1, 2017
• Final editorial decision March 31, 2017

Submission Process

Submissions to the special issue should be sent electronically through the JPIM ScholarOne system (). Authors need to clearly indicate in their submission information and letter that their manuscript is for the Special Issue on “Innovation in Data-Rich Environments.” All submissions will be subject to the standard double blind review process followed by JPIM. All manuscripts must be original, unpublished works that are not concurrently under review for publication elsewhere. All submissions should conform to the JPIM manuscript submission guidelines available at: . Questions about this special issue may be directed to either of the guest editors at their email addresses provided above. Marketing Science Institute (MSI) Research Awards for Research Workshop Invitees and Best Paper Awards The Marketing Science Institute (MSI) has graciously agreed to grant "accelerator" research awards to authors of papers selected to attend the Research Workshop.

Additionally, of the papers accepted for publication in this Journal of Product Innovation Management Special Issue ("Innovation in Data-Rich Environments"), a winner of the MSI/JPIM Best Paper Award will be selected. A prize and recognition will also be given to the paper selected as Runner-up paper.

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