Learning from openness : the dynamics of breadth in external innovation linkages

We explore how openness in terms of external linkages generates learning effects, which enable firms to generate more innovation outputs from any given breadth of external linkages. Openness to external knowledge sources, whether through search activity or linkages to external partners in new product development, involves a process of interaction and information processing. Such activities are likely to be subject to a learning process, as firms learn which knowledge sources and collaborative linkages are most useful to their particular needs, and which partnerships are most effective in delivering innovation performance. Using panel data from Irish manufacturing plants, we find evidence of such learning effects: establishments with substantial experience of external collaborations in previous periods derive more innovation output from openness in the current period

Nokia on the slope: the failure of a hybrid open/closed source model

This case study explores the origins of Nokia’s decline in the mobile technology market, as an unsuccessful attempt to introduce an open-source strategy into the business. Nokia created a hybrid model, which codified conflicting principles taken from closed and open mode of collaboration. A series of implementation problems resulted in Nokia struggling to attract open-source partners, growing issues with managing in-house staff and ultimately failing to develop a new mobile operating system fast enough to stay competitive

Measuring open innovation practices through topic modelling: Revisiting their impact on firm financial performance

Despite the popularity of open innovation in recent years, studies examining the impact of open innovation upon firm performance have shown mixed results. Previous empirical work on this topic is often based on surveys or archival sources, usually done either in isolation or in aggregate through employing proxy measures. In contrast, we employ an unsupervised learning technique (i.e., topic modelling) utilizing natural language processing to extract information on companies’ open innovation practices, creating an initial keyword basket for future development. We then revisit the relationship between open innovation practices and financial performance of firms. The results show that a firm’s overall openness level is associated with improved financial performance. More granular practices developed from our approach, however, show variations. The inverted U-shaped relationships are observed in specific open innovation practices but not in all, partly supporting the existence of the openness paradox from prior literature. The complementarity between internal R&D and individual open innovation practices also varies by practice. Further, the influence of these open innovation practices also varies by sector. Our findings prompt us to conclude that open innovation’s impact on financial performance is nuanced, and that there is no uniform set of best practices to practice open innovation effectively

The interplay between open innovation and lean startup, or, why large companies are not large versions of startups

This essay considers the contribution of Lean Startup to the lack of practical advice for employing Inside-out knowledge flows in open innovation. Lean Startup offers a series of practical steps for exploring—and validating—potential new business models that might utilize otherwise neglected technologies, or potential general-purpose technologies that may be languishing. Open Innovation has some contributions to offer to Lean Startup as well, particularly in the context where Lean Startup is employed inside large established firms. We describe the basic principles of Lean Startup philosophy and discuss how Lean Startup is implemented in large companies. This is highly related to business model reconfiguration, since in many cases, incumbent companies develop a new business model as part of their innovation efforts, often with great difficulty. This line of reasoning leads us to reconsider how Lean Startup might work in established companies, and why it is so difficult due to conflicts with many roles that already exist in the established companies. We then bring forward the idea that Open Innovation can contribute to the corporate venturing process and describe both Outside-In and Inside-Out processes that may help ease the pain of a Lean Startup implementation in an incumbent firm

Competitor Collaboration Before a Crisis: What the AI Industry Can Learn

Overview: For artificial intelligence (AI) technology to impact society positively, the major AI companies must coordinate their efforts and agree on safe practices. The social legitimacy of AI development depends on building a consensus among AI companies to prevent its potentially damaging downsides. Consortia like the Partnership on AI (PAI) aim to have AI competitors collaborate to flag risks in AI development and create solutions to manage those risks. PAI can apply valuable lessons learned from other industries about how to facilitate collective action but do so proactively rather than after the fact. The Dynamic Capabilities Framework of “sensing, seizing, and transforming” provides a process map for the AI industry to create processes to reduce the risk of a major disaster or crisis

ON THE PERFORMANCE OF NONPARAMETRIC SPECIFICATION TESTS IN REGRESSION MODELS

Some recently developed nonparametric specification tests for regression models are described in a unified way. The common characteristic of these tests is that they are consistent against any alternative hypothesis. The performance of the test statistics is compared by means of Monte Carlo simulations, analysing how heteroskedasticity, number of regressors and bandwidth selection influence the results. The statistics which do not use a bandwidth perform slightly better if the regression model has only one regressor; otherwise, some of the statistics which use a bandwidth behave better if the bandwidth is chosen adequately. These statistics are applied to test the specification of three commonly used Mincer-type wage equations with Uruguayan and Spanish data; all of them are rejected.

Leveraging open innovation to improve society: past achievements and future trajectories

Open innovation (OI) is an approach which describes a purposive attempt to draw together knowledge from different contributors to develop and exploit innovation. It has become clear that OI directly benefits organisations' economic performance and resilience, but researchers, practitioners, and policy makers became also convinced that OI might be the way forward to tackle the world’s most pressing societal challenges, representing unresolved Grand Challenges, which can only be weathered by diverse sets of collaborative partners that join forces. Although anecdotal evidence points at how OI practices can be employed to achieve societal impact not only in private firms but also in public organisations, very little understanding exists -beyond anecdotal- to link OI to societal impact. This special issue has the ambition to start the discussion and establish a framework as the stepping stone to tackle this complex research gap

The Forces of Ecosystem Evolution

Ecosystems are the result of a delicate balance between centripetal forces that push economic activities toward integration, and centrifugal forces that pull economic activities out onto the market. Ecosystems evolve when these forces change. For example, technological complementarities—the main source of centripetal force—are dynamic and may be commoditized, generalized, or standardized over time. Management and coordination also change: for example, open innovation practices enable firms to move innovation activities from the in-house R&D lab out into the ecosystem. This article discusses how such dynamics in technologies and management lead to ecosystem evolution

Challenges of open innovation in the tourism sector

This study shows how the tourism sector is applying the new paradigm of open innovation (OI) supported by social media. We drew on a sample of 135 companies from the sector in the south of Portugal and Spain to perform a cluster analysis. Currently, OI is a challenge in tourism, and social media are a strategic tool. The main objective is to evaluate the impact of customer involvement in innovation performance. The results show positive impact of OI in new product development, moreover results derived in terms of turnover and competitiveness improvehowever, it all depends on the innovation management model. Anyway, even today, formal adoption is still pending to achieve the desired outcomes but this research highlights how the sector is advancing in the direction of OI.Junta de Andalucia (Andalusian Goverment) [SEJ-314

External knowledge sourcing and firm innovation efficiency

This study examines the relationship between external knowledge sourcing and firm innovation efficiency. We build on the organizational learning theory to propose that this relationship follows an inverted U‐shape: as the level of external knowledge sourcing increases from low to moderate, firm innovation efficiency increases; as the level of external knowledge sourcing increases from moderate to high, firm innovation efficiency declines. Further, we explore the moderating role of different contextual factors and contend that this inverted U‐shaped relationship is flattened in firms that operate in high‐tech sectors and in firms that face high internal constraints for innovation. Our empirical analysis is based on a sample of 3,204 Spanish firms over the period 2004–2015, and our results provide support for these contentions. We used data envelopment analysis methodology to estimate firm innovation efficiency relative to industry best performers, and truncated regression models for panel data with bootstrapped confidence intervals to test our hypotheses