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Abstract the Case Studies Carried out in This Paper Investigates the Innovative Heuristics of the Two Leading EU Firms in the Robotics Sector (KUKA and COMAU)

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Abstract the Case Studies Carried out in This Paper Investigates the Innovative Heuristics of the Two Leading EU Firms in the Robotics Sector (KUKA and COMAU) Paper to be presented at DRUID19 Copenhagen Business School, Copenhagen, Denmark June 19-21, 2019 Looking forward through the past - an investigation of the evolution of robotics firms' innovation strategies Eric Christian David Estolatan University of Turin Department of Economics and Statistics Cognetti De Martiis [email protected] Aldo Geuna University of Turin Economics and Statistics "Cognetti de Martiis" [email protected] Abstract The case studies carried out in this paper investigates the innovative heuristics of the two leading EU firms in the robotics sector (KUKA and COMAU). The investigation employs an evolutionary perspective and a systems approach to examine a set of derived patent-based measures that explores firm behavior in technological knowledge search and accumulation. These examinations are supplemented by analyses of the firms' various historical archives on firm strategies and prevailing economic contexts at select periods in time. Our investigation indicates that while these enterprises maintain outward-looking innovative propensities and maintain a diversified knowledge base, they tend to have a higher preference for the continuity and stability of their existing technical knowledge sets. The two company studies exhibited partially different responses to the common and on-going broader change in the robotics industry (i.e. emergence of artificial intelligence and ICT technologies in robotics applications), with KUKA being more outward-looking than COMAU. Furthermore, internal restructuring, economic shocks, and firm specificities were stronger catalysts of changes than external technology-based stimuli. Looking forward through the past: An investigation of the evolution of robotics firms’ innovation strategies Preliminary Draft – February 2019 I. Introduction Robotics has significantly advanced since the first mechanical systems were conceived. Several but related technological breakthroughs in engineering, computer science, information technology, and related sciences have expanded the robots’ value proposition. In most recent years, the continued development of more advanced technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), are providing new possibilities that may revolutionize current industry (Estolatan, et al. 2018). However, defining a robot remains a difficult challenge. As Joe Engelberger, the visionary of the industrial robot, once put, “I can’t define a robot, but I know one when I see one.” Various technical factors confound the task (Wilson, 2015) and different informants may provide their own definition (Pearson, 2015). Nonetheless, it is a challenge of paramount importance in the contemporary landscape because of the increasing role that such machines play in the future of production. Robotics is envisioned to be one of the main drivers of digital manufacturing, an environment that promises to deliver not only automated but also intelligent modes of production (Schwab, 2017); they are regarded as the exemplar ‘physical’ component in the factory of the future. Unsurprisingly, robots are now at the center of the conversation regarding next-generation manufacturing. Much of this excitement in the public revolves around either the fascination on newer-generation robots’ capabilities (such as, interactivity, autonomy, and intelligence) or the disapproval on its likeliness to replace existing jobs. However, there is a notable absence of inquiry regarding the true capabilities of those expected to deliver these machines, which are the robot companies themselves. The ‘black boxes’ themselves are often presumed to continuously remain innovative and competitive (Violino, 2016). This paper intends to fill the gap by studying the innovative behavior of the two top European robotics firms (KUKA and COMAU) and the developments within the broader sector. Our objective is to gain insights regarding these organizations’ probable responses to their contemporary environment. Is there historical antecedence to validate the expectation that robotics companies at large can easily deliver radical innovations? Can they be expected to truly revolutionize manufacturing? Answers to such questions may help explain why development and innovation in digital manufacturing-related disciplines remain captive within select institutions and regions. We rely on a theoretical framework based on both the evolutionary and ‘systems’ approaches towards innovation to understand how firms’ knowledge accumulation and innovation strategy changed over time. This is operationalized through the construct of two case studies based on firms’ patents, historical records, and broader industrial context. Our analysis is centered around industrial robots – generally regarded as intermediate products against the broader framework of user-producer interaction. While service robots are increasingly important (as later sections would demonstrate), the paper is more concerned with industrial robots that still comprises much of the industry. As such, the core of the discussion is devoted to this sub-sector. The study adds to the growing literature that uses patent data in understanding firm’s innovative behavior (among others, Stuart & Podolny, 1996; Rosenkopf & Nerkar, 2001; Katila & Ahuja, 2002; Ahuja & Katila, 2004). Our novel contribution is the development of an integrated framework, that combines a variety of objective patent-based analytical measures with rich case studies based on historical archives, that provides the reader with a holistic and detailed study of the evolution of the firms’ innovative strategies over time. The remainder of the paper is structured as follows. Section 2 provides a brief theoretical review of firms’ accumulation of technological knowledge. Section 3 depicts the contemporary robotics landscape. Section 4 discusses the hypothesis and the methodology that the analysis follows. Section 5 delves into the case studies of the selected firms. Section 6 provides a brief discussion and concludes. II. Literature review: accumulation of technological knowledge and innovation strategies In adopting an evolutionary approach, we view the enterprise as a behaviorally-constrained entity that routinely seeks competitive advantage. It relies on established routines to reduce its internal tensions and to allow it to navigate its unfolding and uncertain market environment (Nelson & Winter, 1982). firms root these routines in their existing technical knowledge base and are likely to select new combinations that approximate that base, allowing organization to accumulate a particular set of related capabilities (Dosi, 1988; Dosi, Nelson & Winter, 2001) towards a particular irreversible direction (Nishimura & Ozaki, 2017). This means that the firm’s operating environment is populated with other organizations that feature their own behavioral specificities. However, in time, a technological paradigm likely emerges that limits the amount of existing variety and sets the best practices for organizations to conduct their business (Dosi, 1988). The paradigm defines the particular direction by which the industry grows (and which firms survive and exit) and discovers innovative opportunities (Nelson & Winter, 1973; Nelson & Winter, 1982; Dosi & Orsenigo, 1988). Sectoral system approaches have highlighted latent feedback mechanisms and learning processes among the stakeholders in carrying out innovative work. Internal-based learning dynamics ‘learning-by-doing’ (Arrow, 1962), ‘learning-by-using’ dynamic (Rosenberg, 1982) and Lundvall’s (1985) ‘learning-by-interacting’ process is grounded by costs for the firm, particularly with regard to the ‘stickiness’ of the available information in the environment (von Hippel, 1994). Compatible with the broader evolutionary thought, these mechanisms serve to reinforce (or weaken) the existing structures for the realization of the system’s overall stability (or dissolution) (Fagerberg, 2003). Both the established routines and underlying learning processes determine how the firm responds to the various emergent innovations, which may either arrive as continuous improvements to existing goods (or ‘incremental’ innovations) or as revolutionary changes that overhauls existing productions processes (or ‘radical’ innovations) (Fagerberg, 2003). Early Schumpeterian thought was particularly predisposed towards radical innovations, but more recent discourses have progressively placed importance to incremental innovations and invention (Rosenberg, 1976; Lundvall, 2016). Regardless of the innovation being introduced, the broad literature has increasingly recognized the value of maintaining diverse technological capabilities for firms to respond to such stimuli properly. Investigations in the evolutionary tradition have long held the view that innovating organizations maintain position in a diverse set of technologies (Dosi, 1982; Nelson & Winter, 1982). Successful firms build their comparative advantage through their organizational competence in combining large sets of technological competencies (Pavitt, 1991) or incorporating new technologies into existing processes (Quintana-Garcia & Benavides-Velasco, 2008). Through these various dimensions, the overall body of literature to better delineate sectors on the basis of technological and industrial characteristics (Fagerberg, 2003). Prominent examples of such attempts include Pavitt’s (1984) external sources-focused taxonomy. The availability of these classifications allowed for a more nuanced differentiation of various ‘high-technology’
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