A paradoxical view of speed and quality on operational outcome: An empirical investigation of innovation in high-tech small and medium-sized enterprises

https://doi.org/10.1016/j.ijpe.2020.107780Get rights and content

Highlights

  • High-tech SMEs' R&D investment facilitates innovation speed and quality.

  • Organizational risk strengthens the positive effect of R&D investment on innovation quality.

  • Both innovation speed and quality are beneficial for firms to improve performance in operation.

  • The interaction between innovation speed and quality hinders firms in reaping performance.

Abstract

Recently, there has been increasing attention on the speed versus quality paradox in operations and innovation management literature. This study examines the innovation speed-quality paradox on operational performance in small and medium-sized enterprises (SMEs) from high-tech industries. Specifically, we seek to understand how R&D investment with organizational risk influences the innovation speed-quality paradox and how this paradox further influences a firm's operational performance. Based on a panel data of 247 firms (1782 firm-year observations), the empirical results show that R&D investment positively affects innovation speed and quality, and organizational risk positively moderates the relationship between R&D investment and innovation quality. Also, both the innovation speed and quality are positively related to firm's operational performance, while the interaction of speed and quality is negatively related to firm's operational performance. The theoretical and practical implications of our research are also discussed.

Introduction

With the development of economics and intensification of competition, innovation is recognized as a key facilitator to a firm's survival and development (Boh et al., 2020; Cadwallader et al., 2010; Santos-Vijande et al., 2016). In general, innovation speed and quality are two major dimensions in firm operation (Carbonell et al., 2009; Miner and Glomb, 2010; Wang et al., 2018). “Innovation speed” refers to the pace of innovation progress, from the conception and initial development to the ultimate commercialization (Carbonell et al., 2009; Wang et al., 2016). “Innovation quality” means the process and the results of innovation with the criteria, such as reliability creativity, standardization, and systematic procedures (Carbonell et al., 2009; Haner, 2002; Wang et al., 2018). In firm's operation, innovation speed and innovation quality are deemed as trade-off and paradoxical (Guo et al., 2019b; Kostami and Rajagopalan, 2013; Yeung et al., 2019). On the one hand, the relationship between innovation speed and innovation quality is contradictory and conflicted due to time constraints and limited resources (Guo et al., 2019b; Kostami and Rajagopalan, 2013; Santos-Vijande et al., 2016); on the other hand, innovation speed and quality are interdependent due to the fact that speed enhances focus and discipline in innovation for quality, and quality triggers effectiveness for speed (Caulkins et al., 2017; Santos-Vijande et al., 2016). In other words, innovation speed and quality are elements of persistent contradiction between interdependence, which is called a paradox in the management field (Schad et al., 2016). Innovation speed-quality paradox is a critical characteristic in firms' operation. Consequently, it is critical to better understand the role of speed and quality in order to find the balance between the two to improve operational performance (Guo et al., 2019b; Kostami and Rajagopalan, 2013; Wang et al., 2018). Thus, it is of theoretical and practical relevance to explore the innovation speed-quality paradox.

Previous studies on the innovation speed-quality paradox mainly focus on two streams (i.e., antecedents and outcomes). One stream explores the predictors of innovation speed and quality from a resource and knowledge perspective. For example, Taghizadeh et al. (2018) investigates how knowledge from the customer, for the customer, and about the customer influences innovation speed and quality. However, they ignore the role of R&D investment, which is key to a firm's innovation (Frenz and Ietto-Gillies, 2009; Wu et al., 2019). Additionally, the effect of R&D investment on firm's innovation speed and quality may be contingent on the riskiness in which an organization is embedded (e.g., organizational risk) (Boh et al., 2020; Hasan et al., 2018), which has been also ignored in previous studies. Organizational risk reflects firms' income stream uncertainty (Palmer and Wiseman, 1999) and can act as an external environmental factor affecting the efficiency in resource allocation for innovation (Godfrey et al., 2009; Hasan et al., 2018). Thus, it may have an impact on the R&D investment concerning innovation speed and quality. As a result, organizational risk deserves further investigations along with the paradoxical view of innovation speed and quality.

In terms of outcomes of the speed-quality paradox, previous studies examine how innovation speed and quality separately influence firm performance (Carbonell et al., 2009; Santos-Vijande et al., 2016; Wang et al., 2018). Nevertheless, they fail to explore a potential interaction effect between innovation speed and quality on firm performance because overlooked the trade-off between innovation speed and quality on performance outcomes have been overlooked (Guo et al., 2019b; Kostami and Rajagopalan, 2013; Miner and Glomb, 2010). Moreover, the trade-off between innovation speed and quality can be even more critical for small and medium-sized enterprises (SMEs) in high-tech industries because these SMEs are innovation-oriented while resource-constrained (Guo et al., 2020; Wang et al., 2018). They are confronted with the survival pressure and competition imposed by large firms. Accordingly, they have to effectively transform their limited R&D resources to innovation outcomes at a fast (speed) and steady (quality) pace (Mei et al., 2019; Wang et al., 2018). Therefore, we study the innovation speed-quality paradox in the context of high-tech SMEs. To this end, this study incorporates both the antecedents and outcomes associated with the innovation speed-quality paradox in high-tech SMEs. More specifically, we answer the following three research questions:

  • (1)

    How does R&D investment influence the innovation speed-quality paradox in high-tech SMEs' operation?

  • (2)

    What role does organizational risk play in the above relationship?

  • (3)

    How does the innovation speed-quality paradox influence firm performance in high-tech SMEs' operation?

We argue that R&D investment is indicative to resource commitment (Shan et al., 2016), absorptive capability (Cohen and Levinthal, 1989; Wu et al., 2019), risk tolerance (Ehie and Olibe, 2010; Lee et al., 2014), and high-quality knowledge creation and combination (Czarnitzki and Hottenrott, 2011), which can significantly accelerate innovation speed and quality in high-tech SMEs. Meanwhile, organizational risk reflects income uncertainty and uncertain expectations (Freeman et al., 2007; Hasan et al., 2018). In our research context, firms tend to slow down the pace of innovation (speed) and improve the reliability and stability of innovation (quality) by investing in R&D. Consequently, this hinders the effect of R&D investment on innovation speed and facilitates innovation quality. In addition, innovation speed enables firms to benefit from first-mover advantage (Shan et al., 2016; Wang and Wang, 2012), while innovation quality may guarantee long-term values and create barriers for preventing products and services being imitated (Santos-Vijande et al., 2016; Wang and Wang, 2012), thereby improving SMEs' operational performance. Furthermore, the scarcity of R&D resource in high-tech SMEs impedes them to simultaneously accelerate innovation speed and quality (Guo et al., 2020; Zhu et al., 2019), and therefore the interplay between innovation speed and quality may be negatively related to firm performance in high-tech SMEs’ operation.

The analysis in this study uses 247 firms (1782 firm-year observations) from high-tech SMEs. The empirical results show that within the high-tech SMEs, R&D investment is conductive to both innovation speed and quality; organizational risk amplifies the positive effect of R&D investment on innovation quality. Both innovation speed and innovation quality lead to higher operational performance; however, the interaction of innovation speed and quality inhibits operational performance.

This study contributes to the current literature in several aspects. First, this study theorizes the speed-quality paradox in operations management and empirically examines this paradox on operational performance in high-tech SMEs. Meanwhile, this study contributes to the multi-disciplinary literature, i.e., innovation and operations management by revealing a positive effect of R&D investment on innovation speed and innovation quality in high-tech SMEs’ operations. Finally, this study suggests that there is a contingent effect of organizational risk on the relationship between R&D investment and innovation quality in high-tech SMEs.

Section snippets

Innovation speed-quality paradox in firms’ operations

Innovation in operational processes has two dimensions: innovation speed and innovation quality (Carbonell et al., 2009; Wang and Wang, 2012). Innovation speed reflects the extent to which innovative products or services can be created from initial development (i.e., the conception or an idea of an innovation) to the commercial introduction of products or services to the market (Kessler and Bierly, 2002; Taghizadeh et al., 2018; Wang and Wang, 2012). Innovation quality, on the other hand,

Data collection

High-tech SMEs, as an important entity of the Chinese economy, play an increasingly important role in economic development in China (Mei et al., 2019; Wang et al., 2018). The high-tech SMEs are innovation orientated because they face survival pressure and intense competition from large firms, and they have to effectively apply their R&D resources to innovate quickly (speed) and steadily (quality); thus, high-tech SMEs are appropriate for exploring the innovation speed-quality paradox. The

Regression analysis

Given that we used panel data in the analysis, we followed the approach of Bichescu et al. (2018) for a panel data analysis. Table 1 shows the descriptive statistics and pairwise correlations of key variables in this study. Table 2 presents the results of regression analysis.

We regressed innovation speed on R&D investment (RDI) to test the main effect (see Model 1) and found that R&D investment shows a significant and positive effect on innovation speed (b = 3.384, p < 0.001). Therefore, H1 is

Discussion

This study aims to examine the antecedent and outcome of the innovation speed-quality paradox in high-tech SMEs’ operation. Based on a total number of 1782 firm-year observations of high-tech SMEs, we find that R&D investment facilitates innovation speed and quality; organizational risk strengthens the positive effect of R&D investment on innovation quality; and both innovation speed and quality are beneficial for firms to improve performance in operation. The interaction between innovation

CRediT authorship contribution statement

Feng Guo: Conceptualization, Methodology, Writing - original draft. Qingwen Bo: Data curation, Investigation, Writing - original draft. Xun Tong: Writing - review & editing, Supervision. Xiaofei Zhang: Conceptualization, Writing - review & editing.

Declaration of competing interest

The authors hereby declare that there are no other conflicts of interest.

Acknowledgements

This study is partially supported by the National Natural Science Foundation of China (71902135, 71901127, and 71672049) and Peiyang Scholar Foundation (0903061097).

References (69)

  • U.-E. Haner

    Innovation quality—a conceptual framework

    Int. J. Prod. Econ.

    (2002)
  • A. Howell

    ‘Indigenous’ innovation with heterogeneous risk and new firm survival in a transitioning Chinese economy

    Res. Pol.

    (2015)
  • J.-j. Kim et al.

    What drives the export performance of small and medium-sized subcontracting firms? A study of Korean manufacturers

    Int. Bus. Rev.

    (2016)
  • M. Koskela

    Measuring eco-efficiency in the Finnish forest industry using public data

    J. Clean. Prod.

    (2015)
  • C.-Y. Lee et al.

    How does R&D intensity influence firm explorativeness? Evidence of R&D active firms in four advanced countries

    Technovation

    (2014)
  • M. Liegl et al.

    Designing for ethical innovation: a case study on ELSI co-design in emergency

    Int. J. Hum. Comput. Stud.

    (2016)
  • B.A. Lukas et al.

    Organizing for new product development speed and the implications for organizational stress

    Ind. Market. Manag.

    (2002)
  • E. Mazzola et al.

    The curvilinear effect of manufacturing outsourcing and captive-offshoring on firms' innovation: the role of temporal endurance

    Int. J. Prod. Econ.

    (2019)
  • L. Mei et al.

    Exploring the effects of inter-firm linkages on SMEs' open innovation from an ecosystem perspective: an empirical study of Chinese manufacturing SMEs

    Technol. Forecast. Soc. Change

    (2019)
  • A.G. Miner et al.

    State mood, task performance, and behavior at work: a within-persons approach

    Organ. Behav. Hum. Decis. Process.

    (2010)
  • S. Ren et al.

    How do marketing, research and development capabilities, and degree of internationalization synergistically affect the innovation performance of small and medium-sized enterprises (SMEs)? A panel data study of Chinese SMEs

    Int. Bus. Rev.

    (2015)
  • S. Samila et al.

    Venture capital as a catalyst to commercialization ☆

    Res. Pol.

    (2010)
  • P. Shan et al.

    Entrepreneurial orientation and performance: is innovation speed a missing link?

    J. Bus. Res.

    (2016)
  • Z. Wang et al.

    From knowledge sharing to firm performance: a predictive model comparison

    J. Bus. Res.

    (2016)
  • Z. Wang et al.

    Knowledge sharing, innovation and firm performance

    Expert Syst. Appl.

    (2012)
  • Y. Yang et al.

    Improving the effectiveness of online healthcare platforms: an empirical study with multi-period patient-doctor consultation data

    Int. J. Prod. Econ.

    (2019)
  • Y. Zhu et al.

    Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach

    Int. J. Prod. Econ.

    (2019)
  • L.S. Aiken et al.

    Multiple Regression: Testing and Interpreting Interactions

    (1991)
  • K. Atuahene-Gima

    The effects of centrifugal and centripetal forces on product development speed and quality: how does problem solving matter?

    Acad. Manag. J.

    (2003)
  • C. Balducci et al.

    The individual “costs” of workaholism: an analysis based on multisource and prospective data

    J. Manag.

    (2018)
  • J. Barney

    Firm resources and sustained competitive advantage

    J. Manag.

    (1991)
  • W.F. Boh et al.

    Investor experience and innovation performance: the mediating role of external cooperation

    Strat. Manag. J.

    (2020)
  • S.W. Bradley et al.

    The importance of slack for new organizations facing ‘tough’environments

    J. Manag. Stud.

    (2011)
  • T. Brambor et al.

    Understanding interaction models: improving empirical analyses

    Polit. Anal.

    (2006)
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