Through an objective, systematic, and comprehensive review of the literature on open innovation (OI), this article identifies gaps in existing research, and provides recommendations on how hitherto unused or underused organizational, management, and marketing theories can be applied to advance the field. This study adopts a novel approach by combining two complementary bibliometric methods of co-citation analysis and text mining of 321 journal articles on OI that enables a robust empirical analysis of the intellectual streams and key concepts underpinning OI. Results reveal that researchers do not sufficiently draw on theoretical perspectives external to the field to examine multiple facets of OI. Research also seems confined to innovation-specific journals with its focus restricted to a select few OI issues, thereby exerting limited influence on the wider business community. This study reveals three distinct areas within OI research: (1) firm-centric aspects of OI, (2) management of OI networks, and (3) role of users and communities in OI. Thus far, studies have predominantly investigated the firm-centric aspects of OI, with a particular focus on the role of knowledge, technology, and R&D from the innovating firm's perspective, while the other two areas remain relatively under-researched. Further gaps in the literature emerge that present avenues for future research, namely to: (1) develop a more comprehensive understanding of OI by including diverse perspectives (users, networks, and communities), (2) direct increased attention to OI strategy formulation and implementation, and (3) enhance focus on customer co-creation and conceptualize "open service innovation." Marketing (e.g., service-dominant logic), organizational behavior (e.g., communities of practice), and management (e.g., dynamic capabilities) offer suitable theoretical lenses and/or concepts to address these gaps. Practitioner PointsFirms will benefit from holistic insights on collaborating with users, networks, and communities to guide their open innovation initiatives. By integrating marketing perspectives into their R&D efforts, firms can better understand and implement open innovation in services and co-creation with customers. In order to balance the creation and capture of value, firms need to tightly link their open innovation initiatives with overall firm strategy.

No abstract

James G. March has published his seminal work 'Exploration and Exploitation in Organizational Learning' in 1991. We revisit March's article and analyze the impact it has had on scholarly thinking, providing a comprehensive and structured review of the extensive and diverse research inspired by this publication. Unlike previous reviews on the topic, we combine bibliometric analysis and machine-based text mining to portray a picture of the evolving landscape of this article's influence. We show that although this influence has changed significantly over the years, there are still unexplored opportunities left by this seminal work. Our approach enables us to identify promising directions for future research that reinforce the themes anchored in March's (1991) article. In particular, we call for reconnecting current research to the behavioral roots of this article and uncovering the microfoundations of exploration and exploitation. Our analysis further identifies opportunities for integrating this framework with resource-based theories, and considering how exploration and exploitation can be sourced and integrated within and across organizational boundaries. Finally, our analysis reveals prospects for extending the notions of exploration and exploitation to new domains, but we caution that such domains should be clearly delineated. We conclude with a call for more research on the antecedents of exploration and exploitation and for studying their underexplored dimensions.

No abstract

Service-dominant logic (SDL) emerged over a decade ago as a potential framework and paradigmatic lens for rethinking the role of service in exchange and value creation. The growth of SDL reflects a major shift in service research. However, SDL's relationship to prior service literature and its potential for future development in this field have not been empirically examined. We explore the foundational research areas and evolution of SDL research through a systematic investigation, which combines cocitation analysis with a novel text mining tool, Leximancer. Specifically, we investigate the research streams connected with SDL and compare core themes across two time periods (2004 to 2008 vs. 2009 to 2015). The findings reveal SDL's interdisciplinary theoretical heritage and significant changes in the structure of focal themes and concepts over time. Our analyses identify current limitations and subsequent research areas and questions to further develop strategic approaches for SDL and advance a service ecosystems view. These include open innovation, dynamic capabilities, organizational microfoundations, and service systems, as well as social capital and consumer culture theories. Integration of midrange theories and strategic frameworks in these particular areas can help to guide managers in improving service innovation and enhancing value creation in service ecosystems.

No abstract

No abstract

The availability and quality of instrumental variables (IV) are frequent concerns in empirical management research when trying to overcome endogeneity problems. For endogeneity that does not arise from sample selection, management scholars have recently started to apply the Gaussian Copula (GC) approach as an alternative to IV regression. Although the GC approach has various promising features, its limitations and usefulness in a management context are still not fully understood. We discuss the GC approach as a flexible, instrument-free approach to correct for endogeneity and examine its suitability for applied management research. We use simulations to explore the limitations and practical usefulness of the GC approach relative to ordinary least squares (OLS), IV regression, and a Higher Moments (HM) estimator by simulating the impact of different degrees of violation of the key underlying assumptions of the GC approach. We show that the GC approach can recover the true parameters remarkably well if all of its assumptions are met but that its absolute and relative performance in terms of parameter recovery and estimation precision can deteriorate quickly if these assumptions are violated. This is of particular concern as some of these assumptions are not testable and violations of them are likely in many empirical management contexts. Based on our results, we provide a series of recommendations and practical guidelines for scholars who consider using the GC approach when dealing with endogeneity.