Organizing for Inbound Open Innovation: How External Consultants and a Dedicated R&D Unit Influence Product Innovation Performance

TL;DR: In this article, the authors focus on a relevant yet overlooked category of moderating factors: organization of research and development (R&D), and explore two organizational mechanisms: one informal and externaloriented (involvement of external consultants in R&D activities) and one formalized and internal-oriented (existence of a dedicated research unit), in the acquisition of technological knowledge through outsourcing, a particular contractual form for inbound open innovation.

About: This article is published in Journal of Product Innovation Management.The article was published on 2016-07-01 and is currently open access. It has received 105 citations till now. The article focuses on the topics: Open innovation & Product innovation.

Summary

INTRODUCTION

• This article examines whether and how the organization of Research and Development (R&D) influences the relationship between the acquisition of technological knowledge from external sources and innovation performance.
• By considering informal and external-oriented and formalized and internal-oriented (dedicated R&D unit) organizational mechanisms, this study offers a multifaceted (though naturally incomplete) view of R&D organization.
• 2008), R&D outsourcing, defined as “buying R&D services from other organizations, such as universities, public research organizations, commercial engineers or suppliers” (van de Vrande et al., 2009, pp. 428), has received limited attention in innovation research, compared to other forms of IOI, e.g., mergers and acquisitions, joint ventures and in-licensing (Chiesa and Manzini, 1998; Kotlar et al., 2013).
• The next section develops theory and hypotheses.

CONCEPTUAL FRAMEWORK AND RESEARCH HYPOTHESES

• Technological innovation can be conceptualized as a process that transforms a set of inputs (technological and market knowledge) into outputs (new products).
• The involvement of external consultants allows the focal firm to develop other critical capabilities for IOI, such as creating a trustworthy relationship with the external contractor and effectively negotiating the terms of the R&D outsourcing agreement.
• This effect derives from the influence played by this organizational mechanism on certain capabilities needed to productively acquire technological knowledge from R&D contractors and to transform it into new products, which are discussed below.
• Therefore, the existence of a dedicated R&D unit allows the focal firm to develop a critical capability for IOI, namely the capability to establish formalized routines for the acquisition of external technological knowledge.
• Because some firms stopped providing information during the sample period for several reasons and because only firms whose data were available for at least three consecutive years are included, the article is based on an unbalanced panel of 841 firms, consisting of 6,161 firm-year observations.

Dependent variable

• In the dataset, new products are recognized as such only if they are completely different from previous product lines or if they have undergone substantial modifications from existing products.
• Therefore the number of new products measures both the firm’s ability to introduce new products in the market and its ability to upgrade current ones, which are critical indicators of innovative performance (Schoonhoven et al., 1990).
• Other studies use closely related measures of innovative performance such as patents, invention counts and sales growth (Ahuja and Katila, 2001; Scherer, 1983).
• By using this measure, this study departs from Grimpe and Kaiser (2010) who use the share of sales due to products new to the market.
• Firms in this sample introduced, on average, 4.25 new products annually.

Independent variable

• The level of external technological knowledge acquired through R&D outsourcing ( 𝑅&𝐷_𝑂𝑢𝑡𝑠𝑜𝑢𝑟𝑐𝑖𝑛𝑔𝑖𝑡 ) is measured using the average ratio of expenditures for R&D outsourcing in Euros over total sales, spent by firm i in the last three years t, t-1 and t-2.
• This operationalization allows controlling for endogeneity concerns.
• The ratio, instead of the absolute expenditures, is used in order to remove size effects.
• Because the presence of outliers could severely bias the results, this variable is winsorized (e.g., Dixon and Yuen, 1974) with a 1% cut-off for each tail.

Moderating variables

• To investigate the moderation played by the R&D organization, two items that capture whether a firm uses the following organizational mechanisms in R&D are considered: (i) involvement of external consultants in R&D activities (𝑅&𝐷_𝐶𝑜𝑛𝑠𝑢𝑙𝑡𝑎𝑛𝑡𝑠𝑖𝑡); (ii) existence of a dedicated R&D unit (𝑅&𝐷_𝑈𝑛𝑖𝑡𝑖𝑡 ) i.
• These items, measured every year, are dummy variables that take value 1 if the firm i used the specific mechanism in at least one of the last three years.
• The moderating factors over three years are estimated in order to control for the endogeneity of these factors.
• Moreover, it should be considered that the effect on innovation performance may not occur for some timeii.
• During the years covered in the sample, 532 firms involved external consultants in R&D, whereas a dedicated R&D unit existed in 487 firms.

Control variables

• Following seminal studies on absorptive capacity (Cohen and Levinthal, 1990; Rothaermel and Alexander, 2009), internal R&D (𝑅&𝐷_𝐼𝑛𝑡𝑒𝑟𝑛𝑎𝑙𝑖𝑡) is included as a control variable.
• The same procedure is used to estimate the R&D outsourcing variable and internal R&D is measured as the average ratio between internal R&D expenditures in Euros and total sales estimated over the last three years, and winsorized at 1% level.
• A dummy variable Patentsit is also included, indicating whether firms have patents or not, because many sample firms do not have any patent.
• This variable is preferred over sales or other measures of size because it is more stable across time and less sensible to macroeconomic shocks.
• Ageit is measured with the number of years since foundation in logs.

MODEL SPECIFICATION

• 𝛽1 is expected to be positive and significant and 𝛽2 to be negative and significant, indicating an inverted U-shaped relationship between IOI through R&D outsourcing and product innovation performance.
• To test the hypotheses on the moderation caused by the R&D organizational mechanisms (H1 and H2), two different operationalizations found in prior innovation research are used.
• The first, named Moderation Effect 1, refers to the effect that the moderating variable has on the elasticity of the inverted U-shaped IOI-performance curve.
• Instead, a positive Moderation Effect 2 indicates that, by using a specific organizational mechanism, the firm starts experiencing the negative effects of IOI on product innovation performance at higher levels of R&D outsourcing.
• Two different models are estimated in which the effect of 𝑅&𝐷_𝐶𝑜𝑛𝑠𝑢𝑙𝑡𝑎𝑛𝑡𝑠𝑖𝑡 and 𝑅&𝐷_𝑈𝑛𝑖𝑡𝑖𝑡 , and their interactions with the linear and the squared terms of 𝑅&𝐷_𝑂𝑢𝑡𝑠𝑜𝑢𝑟𝑐𝑖𝑛𝑔𝑖𝑡, are inserted separately (see Model A2 and Model B2 in Tables 4 and 5).

RESULTS

• To correctly evaluate Moderation Effect 2, the results of Equation [5] are considered, where the tipping point of this moderated curve is estimated (Model A2).
• This is true because, even though the squared term of interaction is not significant, the linear term of interaction is found negative and significant.
• The coefficients of the linear and squared terms of R&D outsourcing when both external consultants and a dedicated R&D unit exist, estimated by Equation [4] and reported in Table 5 (Model B3, lower part “With R&D organizational mechanisms”), are significant, indicating that the IOIperformance curve is still U-shaped.
• Overall, the results of the empirical analysis suggest that by combining the use of external consultants with the presence of a dedicated R&D unit, their moderation effects on the IOI-performance relationship may cancel out.

DISCUSSION AND CONCLUSIONS

• To deepen the understanding of this important phenomenon, this article investigates the influence of two R&D organizational mechanisms on the relationship between external technological knowledge acquired through R&D outsourcing and product innovation performance.
• The results concerning Moderation Effect 1 indicate that the involvement of external consultants strengthens the marginal benefits of R&D outsourcing on product innovation performance (in the ascending part of the curve), whereas the existence of a dedicated R&D unit attenuates these benefits.
• The knowlege transfer process is augmented, meaning that by involving external consultants the firm can make the most out of the acquired technological knowledge and achieve the highest innovation performance at lower levels of R&D outsourcing.
• The different moderating role played by the two organizational mechanisms might suggest that they have contrasting effects on the critical capabilities for managing IOI and also explain why their combined use has no significant effect on the IOI–performance relationship.
• While these synergistic effects may occur only at companies at the forefront of open innovation practice, the diverse firms investigated in this large scale empirical study may experience inefficiencies due to the increased complexity and investments required by combining the two R&D organizational mechanisms.

Figures

Table 5: Moderating Effects

Table 1: A summary of the critical capabilities for managing IOI that are influenced by each R&D organizational mechanism.

Figure 2: Moderating Effects by the R&D organizational mechanisms.

Table 2: Sample overview

Table 6: Overview of the empirical results for the moderation effects

Table 3: Means, standard deviations and correlations

Figure 1: Moderation Effect 1 and 2.

Table 4: Negative binomial estimation model predicting Product innovation performance

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Organizing for inbound open innovation: how external consultants and a dedicated r&d unit influence product innovation performance" ?

This article focuses on a relevant yet overlooked category of moderating factors: organization of R & D. Drawing on a capabilities perspective and using a longitudinal dataset of 841 Spanish manufacturing firms observed over the period 1999-2007, this article provides a fine-grained analysis of the moderation effects of the two organizational mechanisms. The study provides guidance on how to improve the benefits of inbound open innovation using two different mechanisms: external R & D consultants or a dedicated R & D unit. 

Q2. What are the future works in "Organizing for inbound open innovation: how external consultants and a dedicated r&d unit influence product innovation performance" ?

This study has several limitations, which suggest future research efforts. Future research is encouraged to study the micro-dynamics through which R & D organizational mechanisms influence the firm ’ s capabilities for managing IOI, not only at the firm level of analysis but also at the project and individual levels. Going beyond the findings of this study, future research should adopt a contingency perspective to scrutinize under what contextual factors managers should apply each of the two organizational mechanisms. Future studies should also broaden the scope of the analysis, including service sectors, other contractual forms for acquiring external technological knowledge, as well as other managerial and organizational levers that can be used to support IOI ( e. g., types of incentives given to R & D employees ). 

Q3. What is the effect of a dedicated R&D unit on the ability to integrate external technology?

By leveraging complementarities between heterogeneous knowledge bases and generating novel combinations, a dedicated R&D unit improves the firm’s capability to combine and integrate external technology with its internal knowledge basis. 

Q4. What is the effect of the use of external consultants on the IOI-performance relationship?

the results of the empirical analysis suggest that by combining the use of external consultants with the presence of a dedicated R&D unit, their moderation effects on the IOI-performance relationship may cancel out. 

Q5. What is his role at Politecnico di Milano?

He is Director of the MBA & Executive MBA Division and of the ICT & Digital Learning Division of MIP, the Graduate School of Business of Politecnico di Milano. 

Q6. How does the involvement of external consultants affect the optimal level of R&D outsourcing?

By leveraging the thick extended social networks of the external consultants, firms can access the most suitable partners whose R&D services contribute to higher product innovation performance. 

Q7. What are some of the common opportunistic behaviors that occur when the technological knowledge?

In particular, shirking and other opportunistic behaviors typically arise when the technological knowledge is transferred from the contractor to the focal firm. 

Q8. Why is the article based on an unbalanced panel of 841 firms?

Because some firms stopped providing information during the sample period for several reasons and because only firms whose data were available for at least three consecutive years are included, the article is based on an unbalanced panel of 841 firms, consisting of 6,161 firm-year observations. 

Q9. What is the effect of external consultants on the IOI-performance relationship?

Hypothesis H1 predicts that the involvement of external consultants in R&D activitiespositively moderates the IOI-performance relationship. 

Q10. What is the significance of the coefficients in Equation 3?

Because the sign and the significance of the coefficients 𝛽4 and 𝛽5 only indicate how and whether each moderating variable influences the IOI-performance relationship, a test is conducted on a combination of parameters in Equation [3] that allow estimation of both the linear and the squared terms of R&D outsourcing in the presence of the moderating factor 𝑀𝑖𝑡, as follows:{ 𝐿𝑖𝑛𝑒𝑎𝑟 𝑡𝑒𝑟𝑚 𝑜𝑓 𝑅&𝐷_𝑂𝑢𝑡𝑠𝑜𝑢𝑟𝑐𝑖𝑛𝑔𝑖𝑡 = 𝛽1 + 𝛽4𝑆𝑞𝑢𝑎𝑟𝑒𝑑 𝑡𝑒𝑟𝑚 𝑜𝑓 𝑅&𝐷_𝑂𝑢𝑡𝑠𝑜𝑢𝑟𝑐𝑖𝑛𝑔𝑖𝑡 = 𝛽2 + 𝛽5 [4]