MIS 9003 – Prof. Min-Seok Pang

Week 08 – Innovation

Week 8 – Kim et al. 2016 – Joe

Keongtae Kim, Anandasivam Gopal, Gerard Hoberg (2016) Does Product Market Competition Drive CVC Investment? Evidence from the U.S. IT Industry. Information Systems Research 27(2):259-281.
Companies need ideas to keep competency advantage on innovation. Besides the traditional internal R&D investment to gain innovative knowledge, Firms have several avenues available to access such investment from outside thereby complementing traditional R&D. Corporate venture capital (CVC) is one of the outside resources, classified as open innovation. Whether to use CVC to gain innovative knowledge is heterogeneous among companies in different industries. The importance of knowledge and learning is likely to be most relevant in technology-intensive industries where persistent innovation is a key determinant of success. For companies in technology-intensive industries, such as IT industry, a critical factor that might also have a strong incremental influence on the observed intensity of CVC spending is product market competition. This study explores the relationship between product market competition and IT companies CVC investment by answering the following two questions: 1) Does product market competition faced by IT-producing firms lead to higher investments in CVC spending, all else equal? 2)Do CVC investments lead to higher innovation output? If so, is the relationship moderated by the technology leadership of the investing firm?

The authors proposed to measure product market competition using metrics derived from 10-K textual similarity. Clearly, just using OLS to regress CVC spending on product market competition with covariates or fixed effects cannot uncover the causality. The baseline model suffers from omitted variable bias and reverse causality concern. The authors then tried to use GMM for the dynamic panel data to relief the concerns. The results are consistent with the hypothesis even with several robustness checks using other instruments and panel data Heckman analysis, etc. The paper may still suffer sample selection bias due to the sample filtration. The observations remained in the sample are companies are industry leaders and operate at least 10 years from 1997 to 2007, during when the IT industry leaders turned over significantly, the CVC was hot and somewhat abused, and the market competence was becoming more fierce.

This work contributes to the IS literature by 1) examine product market competition, a systemic feature of the IT industry, as one such driver of this shift from internal to external innovation spending; 2) broadening the focus of IS research on competition to include its effects on the use of external innovation; 3) showing that R&D plays a more important contingent role in IT firms than previously acknowledged.

Forman, C. and van Zeebroeck, N. (2012)-Siddharth Bhattacharya

The paper tries to investigate how the diffusion of the internet influences research collaboration within firms.Previous literature has suggested that research collaboration is hampered by the existence of significant coordination costs that increase with team size and that adoption of information technology such as internet lower coordination costs and thus increase returns of collaborative work.However although some works exist as to whether IT adoption helps academic collaboration no such work exists for industrial collaboration.This is the first work to do so.Motivating the hypothesis using prior models of Becker and Murphy(1992) the authors hypothesize that increase in IT investment(here internet adoption) will be  associated with an increase in the likelihood of geographically dispersed, multi inventor collaboration relative to collaboration within the same region/single inventor outputs.The data comes from multiple sources including:patenting data from USPTO,R&D data from Compuestat,regional controls from US census county business patterns.The analysis used is a difference in difference framework, comparing the incidence of a collaborative patent in firm-location pair prior to the treatment of basic Internet adoption to the incidence after the treatment .The model is a fixed effects linear probability model The model controls for observable changes in firm-pair conditions,fir-location employment etc which could affect collaboration volume.It also controls for location fixed effects.The diff-in-diff results show that there is a statistically significant increase in the incidence of collaborative patenting for cross-location pairs adopting Internet over the period, relative to non adopters.This however is not the case for same location teams or single inventors.To test the robustness of the findings the paper uses falsification tests and instruments to rule out endogeniety. The results remain robust and consistent.The research tries to answer a debate in previous literature of whether adoption of IT can lead to increase in collaboration due to reduction of coordination costs and managerially has implications for integration of geographically dispersed organizations/long run design of research organizations within firms.

Paper Summary- Week8 Jack Tong

Paper: Kim, Keongtae, Anandasivam Gopal, and Gerard Hoberg. “Does product market competition drive CVC investment? Evidence from the US IT industry.” Information Systems Research 27, no. 2 (2016): 259-281.

The motivation of this paper is to explore how product market competition will affect the propensity for firms to use corporate venture capital (CVC) as a venue for innovations. CVC is defined as minority equity investments by established firms in start-ups, typically alongside traditional venture capitalists (VC). The primary drivers for CVC are knowledge and learning for persistent innovation and product market competition rather than financial returns. The authors collect CVC funding information from the VentureExpert data set, augmented with data from CompuStat and the National Bureau of Economic Research (NBER) patent database. The authors use a novel measure of competition based on 10-K product descriptions-The textual network industry classification (TNIC). TNIC classifications are based on the product market vocabulary in each firm’s 10-K and are updated every year. Firms using similar product market vocabularies are classified as being in the same industry, allowing for a more accurate measure of competition that captures the dynamic nature of the IT industry. The empirical results suggest that firms in competitive markets make higher research and development (R&D) and CVC investments. In addition, the results indicate that increasing product market competition leads to a shift away from internal R&D spending and into CVC. These movements are significantly stronger for technology leaders, i.e., firms with deep patent stocks, in the IT industry. The authors also find that CVC appears to be an effective way of exploiting external knowledge for technology leaders in the IT-producing industry, but not for technology slow starters. CVC investments lead to significantly more patent applications for technology leaders but no appreciable difference for slow starters.

Week8 – Reading Summary -Leting Zhang

Tiwana, A., Kim, S. K., & Kim, S. K. (2015). Discriminating IT Governance. Information Systems Research, 143(December 2015). 

Based on the idea that different types of IT assets must be governed different, the paper examines an interesting research question: how does the interplay between firms’ IT governance choices and departmental peripheral knowledge influence IT strategic agility?

The theoretical foundation is Jensen and Meckling’s theory, the central idea is that decision rights must be colocated with the knowledge needed to make those decisions when the two are not colocated, there are delegation solution and transmission solution.  In the IT context, both the delegation and transmission solution should be used,  increasing the peripheral knowledge is also important in tandem with IT governance. Then they propose, For the IT apps, which are often uniquely tailored to different functions, JM’s delegation solution could minimize problems like agility-imperiling delays. Then, with more business knowledge, IT unit could better help line functions, which could increase the strategic agility. However, for IT infrastructure decision which requires deep technical expertise and holistic understanding, JM’s delegation solution implies the centralization of IT infrastructure governance is an optimal strategy. In the meantime, with the increase in line function’s technical knowledge, the strategic agility could be promoted.

In order to test these hypotheses, the authors design a survey and collected matched-pair data from senior IT managers and line function managers in 105 U.S firms. Data on IT strategic agility were collected from line function managers, other variables come from IT managers. Constructs in surveys are based on prior literature. After testing their validity, they use  Garen’s two-stage econometric techniques to analyze the data. In the first stage, they evaluated the endogeneity concern by Hausman test. In the second stage, they use a three-step hierarchical weighted least squares (WLS) model to test hypotheses.They also solve some main endogeneity concerns.  The paper’s main contributions are showing 1. IT governance enhances IT strategic agility only when it is discriminatingly aligned with departments’ peripheral knowledge; 2. governance-contingent nature of which department needs peripheral knowledge.

Week 8 Reading Summary – Tiwana and Kim (2015) – Xi Wu

Tiwana, A., & Kim, S. K. (2015). Discriminating IT Governance. Information Systems Research, 26(4), 656–674.

Strategic IT agility is one important weapon for firms that using IT to consistently create a series of temporary advantages, introducing a new one before rivals could even finish copying the last one. This study asks the question: why are some firms more adept at using IT in their pursuit of strategic opportunities? The belief is that the secret for exploiting IT for strategic agility is how it is governed, i.e., which department makes what IT decisions. This study addresses the research question: How does the interplay between firm’s IT governance choices and departmental peripheral knowledge influence IT strategic agility.

The theoretic foundation is the JM theory that decision rights must be collocated with the knowledge needed to make those decisions. This study develops the idea that firms’ IT governance choices foster IT strategic agility only when their alignment with departments’ peripheral knowledge is discriminating—discriminating in that only a specific department’s peripheral knowledge induces agility for a specific class (apps or infrastructure) of IT decisions; which department has peripheral knowledge must be aligned with which department makes what IT decisions.

Matched-pair data from 105 U.S. firms are collected. All principal constructs using reflective multi-item Likert scales are measured using the firm’s IT function as the unit of analysis. To account for the endogeneity in firms’ IT governance choices, several instrumental variables are used. The two hypotheses about IT app governance and IT infrastructure governance are theoretically support by a three-step hierarchical weighted least squares (WLS) model. This study contributes theoretically to discriminating alignment and governance-contingent value of peripheral knowledge in IT governance literature.

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.

Amrit Tiwana’s paper

Amrit Tiwana from University of Georgia will be visiting Fox School as a visiting scholar for a week on March 12-16. The department is scheduling his visit, and I invited him to join us in our seminar for 30 minutes on March 14.

If his visit is confirmed, I will add this paper to the reading list for Week 8.

Tiwana, A. and Kim, S.K. (2015) “Discriminating IT Governance,” Information Systems Research (26:4) pp. 656-674.