Week 8 Reading Summary (HK)

Saldanha, T. J. V., Mithas, S., & Krishnan, M. S. (2017). Leveraging customer involvement for fueling innovation: The role of relational and analytical information processing capabilities. MIS Quarterly, 41(1), 267-286.

By drawing on three streams of literature, customer involvement, innovation, and IS, Saldanha, Mithas, and Krishnan (2017) were able to respond to calls for insight of how IT enables customer-focused innovation. Previous literature had contradictory findings consider in the impact of customers on the innovation process. On one hand, industry leaders, such as Lego and Sony, and researchers have found that customer involvement in the innovation process can be beneficial. On the other hand, some researchers (e.g., Ittner & Larcker, 1997) have found that it can negatively impact innovation by causing the firm to be reactive instead of proactive. Using a combination of data from several sources including InformationWeek and Compustat, Saldanha et al. (2017) were able to empirically demonstrate that congruent IS can complement the relationship between specific types of customer involvement and innovation.

With respect to customer involvement, the extent to which a firm interacts with customers while developing a product (Carbonell et al., 2009), Saldanha et al. (2017) considered two types: information-intensive (ICI) and product-focused customer involvement (PCI). First, ICI considers the information collected on customers via customer opinion and feedback as well as structure mechanisms such as focus groups. To help manage and analyze such large datasets, Analytical Information Processing Capability (APIC) software such as business analytic technologies can be employed by the organization. Second, PCI captures involvement when the customers are engaged by the firm to actively participate in codeveloping products resulting in customers driving product development or custom configurations of products. CRM software can be employed to help manage relationships with customers as captured under Relational Information Processing Capability (RIPC) software. Effectively, results, including those from the original negative binomial models as well as various robustness checks, indicated that RIPC and AIPC complement the link between PCI and ICI respectively and firm innovation.