Open innovation (OI) application has gradually expanded to traditional and institutionalised industries, which have their own institutional logic. Organisations in such industries are subject to strict regulations designed to mitigate risk and build organisational legitimacy. Despite its various advantages, OI adoption and implementation is challenging. Yet, institutional effects could play a critical role in facilitating organisations' change, especially when uncertainty exists. This study focuses on the analytical investigation of the three main institutional effects, i.e. coercive, mimetic and normative forces, on the implementation of OI. A case study approach was used to analyse the issue concerned. A total of four case studies were conducted. The research outcome highlights the role of institutional effects in the implementation of OI. It suggests that institutional effects are an effective means of stimulating the adoption of OI and can guide the organisational innovation process. Moreover, the results highlight the relationship between organisational characteristics and institutional effects. Coercive forces are more important for organisations that are government owned and controlled, while mimetic forces are more crucial for organisations with limited resources. Normative forces have a particular impact on the actions of organisations having direct or indirect ties with the professional networks.

Complexities in external knowledge evaluation present significant “limits” to open innovation (OI), challenging decision making in the processes of searching, accessing, and using external knowledge for recombination, which are central to the OI paradigm. Grounded in the theory of attitudes, this study investigates the role of standardization in preventing the negative behavioral influence of “not invented here” (NIH) and “not-shared-here” (NSH) attitudes on knowledge search and sourcing decisions by debiasing decisional paths associated with reluctance to adopt OI. Using hurdle model estimations on 600 small-and medium-sized enterprises, the results of the study reveal that NIH and NSH attitudes are the origin of decision-making biases at different stages of OI implementation, where external knowledge is the focus of evaluation. Proactive standardization efforts are shown to be effective in countering the impact of NIH and NSH attitudes on knowledge sourcing decisions and on the intensity of knowledge sourcing, typically leading to bounded search, inward decisions, and anticipated termination of projects. This study provides insights into the influence of standardization efforts specifically addressing challenges related to the evaluation of external knowledge, where the likelihood of failure is higher and associated costs are significant.

Although the novelty of scientific publications has been the subject of previous studies, most have examined the distribution of references in the bibliography, which may not be effective in capturing implied scientific knowledge. We propose an analytical framework for measuring the novelty of scientific publications using a paper's title. At the heart of the framework, fastText is used to construct a vector space model in which papers with similar scientific knowledge are located close to each other, and the local outlier factor is used to measure the novelty of scientific knowledge implied in the papers on a numerical scale. The feasibility and validity of the analytical framework were assessed by comparing the average novelty scores of papers recommended with novelty-related tags in Faculty Opinions to those of papers without such tags. This case study of 15,653 papers published in a biomedical journal confirms that our framework is a useful complementary tool for the continuous assessment of the novelty of scientific publications and can serve as a starting point for developing more general models.

The government has supported the innovation of private firms by intervening the market for various purposes, such as preventing market failure, alleviating information asymmetry, and allocating resources efficiently. Although the government's R&D budget increased rapidly in the 2000s, it is not clear whether the government intervention has made desirable impact on the market. To address this, the current study attempts to explore this issue by doing a systematic literature review on foreign and domestic papers in an integrated way. In total, 168 studies are analyzed using contents analysis approach and various lens, such as policy additionality, policy tools, firm size, unit of analysis, data and method, are adopted for analysis. Overlapping policy target, time lag between government intervention and policy effects, non-linearity of financial supports, interference between different polices, and out-dated R&D tax incentive system are reported as factors hampering the effect of the government intervention. Many policy prescriptions, such as program evaluation indices reflecting behavioral additionality, an introduction of policy mix and evidence-based policy using machine learning, are suggested to improve these hurdles.

Technology advancements are underpinning firms in shaping their products and services into digital platforms to foster value co-creation in their platform-based ecosystems. While existing research has mainly focused on business-to-consumer (B2C) platforms, relatively little research has been conducted on business-to-business (B2B) platforms. To address this research gap, this study employs a case study approach to collect and examine three out-bound open innovation (OI) application cases in the context of B2B platforms, namely, TSMC, IBM and CNT Tech. The case analysis results show that the coverage of B2B markets can be expanded and diversified by OI. To improve the quality of platform offerings (not only platform services but also complementary innovations), the case firms implemented OI applications comprising two phases that manage knowledge outflows (with boundary resources) and inflows (with input/output controls) across their organisational boundaries. Knowledge sharing provided B2B platform owners new market creation opportunities, combined complementors, and pivoted some of the platform owners' core technologies, consequently diversifying the platforms' applications and making platform ecosystem more dynamic and vibrant.

Drawing on the theoretical foundations of attitudes and their role in the decision process underlying open innovation (OI) adoption, this study conveys a new perspective of examining firm-level openness as a construct. Based on Item Response Theory, a family of latent trait models rooted in psychology, and using data from the German section of the Community Innovation Survey, we advance a nuanced measure of openness capturing the firm-level attitudes toward external knowledge reception, going beyond current measures focusing on its attributed effects. This approach, based on an implicit attitude measure, allows us to assess the types of OI practices characterizing firms with different value structures (i.e., higher/lower attitudes toward external knowledge), thus offering a more reliable comparison of firms along the openness continuum. A systematic comparison with the widely used measures of external search breadth and depth shows that higher openness is not merely reflected by a higher number (or a more intensive use) of external knowledge sources but by a higher attitude toward complex search patterns, typically implying more challenging OI activities. The proposed construct has strong external validity, as it reflects the key theoretical features of openness and its paradoxes - an inverted U-shaped relationship with innovation performance. The results of this study provide both theoretical and practical implications.

Patent analysis using text mining techniques is an effective way to identify novel technologies. However, the results of previous studies have been of limited use in practice because they require domain-specific knowledge and reflect the limited technological features of patents. As a remedy, this study proposes a machine learning approach to measuring the novelty of patents. At the heart of this approach are doc2vec to represent patents as vectors using textual information of patents and the local outlier factor to measure the novelty of patents on a numerical scale. A case study of 1,877 medical imaging technology patents confirms that our novelty scores are significantly correlated with the relevant patent indicators in the literature and that the novel patents identified have a higher technological impact on average. It is expected that the proposed approach could be useful as a complementary tool to support expert decision-making in identifying new technology opportunities, especially for small and medium-sized companies with limited technological knowledge and resources.

Despite its increasing popularity and wide application of the open innovation model, less attention has been paid to its dynamic traits. By viewing open innovation as a process of transition entailing progressively higher degrees of openness to external knowledge, this study investigates the tensions between openness and organisational resistance towards external knowledge emerging in different stages of open innovation adoption and examines the role of standardisation in mitigating such concerns. Hurdle model estimations on a sample of 600 Korean small and medium-sized enterprises suggest that tensions between openness and knowledge-related biases, such as the not invented here and the not-shared-here syndromes act as thresholds in the transition between different phases of firms’ knowledge search paths, but different types of standardisation activities may act as “de-biasing” mechanisms facilitating knowledge access and transfer at each stage.

To cope with such tide, various strategies have been developed and suggested, and open innovation can be one of such strategic approaches, in that it helps firms to develop dynamic capability and establish sustainable innovation implementation. Firm A's top management promoted the Idea Suggestion Program to provide employees with opportunities to innovate voluntarily in the workplace so that they could reach consensus on such a sustainable innovation. Open innovation is innovating innovation, so it breaks static equilibrium and brings in new changes. Open innovation pushes firms to deviate from their current routines and find better ways for doing innovation, which helps firms to find a new solution and enhance their dynamic capability. One of the important hurdles for organisational routine change is the ability of organisational members to a embrace new changes, and this is promoted by a strong leadership.

Importance The COVID-19 pandemic is the greatest global test of health leadership of our generation. There is an urgent need to provide guidance for leaders at all levels during the unprecedented preresolution recovery stage. Objective To create an evidence- and expertise-informed framework of leadership imperatives to serve as a resource to guide health and public health leaders during the postemergency stage of the pandemic. Evidence Review A literature search in PubMed, MEDLINE, and Embase revealed 10 910 articles published between 2000 and 2021 that included the terms leadership and variations of emergency, crisis, disaster, pandemic, COVID-19, or public health. Using the Standards for Quality Improvement Reporting Excellence reporting guideline for consensus statement development, this assessment adopted a 6-round modified Delphi approach involving 32 expert coauthors from 17 countries who participated in creating and validating a framework outlining essential leadership imperatives. Findings The 10 imperatives in the framework are: (1) acknowledge staff and celebrate successes; (2) provide support for staff well-being; (3) develop a clear understanding of the current local and global context, along with informed projections; (4) prepare for future emergencies (personnel, resources, protocols, contingency plans, coalitions, and training); (5) reassess priorities explicitly and regularly and provide purpose, meaning, and direction; (6) maximize team, organizational, and system performance and discuss enhancements; (7) manage the backlog of paused services and consider improvements while avoiding burnout and moral distress; (8) sustain learning, innovations, and collaborations, and imagine future possibilities; (9) provide regular communication and engender trust; and (10) in consultation with public health and fellow leaders, provide safety information and recommendations to government, other organizations, staff, and the community to improve equitable and integrated care and emergency preparedness systemwide. Conclusions and Relevance Leaders who most effectively implement these imperatives are ideally positioned to address urgent needs and inequalities in health systems and to cocreate with their organizations a future that best serves stakeholders and communities.

Innovation systems have seen diverse actors attempting to tame the Covid‐19 crisis, under varying degrees of government direction. Largely neglected in scholarly and public attention, however, are ‘bottom‐up’ solutions arising from the periphery of innovation systems. Drawing on inductive case research on a fringe doctor who invented the idea of the drive‐through testing system, and two university student teams that developed coronavirus applications, this study examines how peripheral actors generate innovative, bottom‐up solutions at speed in a time of crisis. Our findings reveal that, in a crisis situation, bottom‐up solutions transpire on the basis of three innovation drivers: (a) peripheral status, expediting the commence of innovation activities; (b) interdisciplinary collaboration, enabling access to a greater spectrum of knowledge and perspectives; and (c) prior knowledge, prescribing the direction of solution generation. We also identify that system intermediaries support the innovation activities of peripheral actors, thereby helping bottom‐up solutions to become more customer facing. Such functions of intermediaries include demand articulation, technical assistance, and promulgation of generated solutions. Our findings offer theoretical implications for the literature on innovation in a time of crisis and practical implications for governments and organizations preparing themselves for the potential second wave of coronavirus emergencies, or even a completely new form of future crisis.

This study explores the complex relationships between open innovation (OI) climate and OI activities by investigating the changing moderating effects of organisational facilitators in small innovative firms. Our partial least squares structural equation modelling analysis suggests (1) OI-friendly climate promotes OI activities, (2) this process is further facilitated by various organisational efforts, but (3) the efforts firms must put in are proportional to the level of openness intensity. The findings also suggest that systematic knowledge management is the most basic facilitator, while entrepreneurial orientation is generally under-performed despite its high importance. This study provides implications for managers and policy makers who lead OI adoption and implementation.

As nanoscale photonic devices are densely integrated, multiple near-field optical eigenmodes take part in their functionalization. Inevitably, these eigenmodes are highly multiplexed in their spectra and superposed in their spatial distributions, making it extremely difficult for conventional near-field scanning optical microscopy (NSOM) to address individual eigenmodes. Here, we develop a near-field transmission matrix microscopy for mapping the high-order eigenmodes of nanostructures, which are invisible with conventional NSOM. At an excitation wavelength where multiple modes are superposed, we measure the near-field amplitude and phase maps for various far-field illumination angles, from which we construct a fully phase-referenced far- to near-field transmission matrix. By performing the singular value decomposition, we extract orthogonal near-field eigenmodes such as anti-symmetric mode and quadruple mode of multiple nano-slits whose gap size (50 nm) is smaller than the probe aperture (150 nm). Analytic model and numerical mode analysis validated the experimentally observed modes.

Open innovation (OI) has become an important business norm of successful firms; however, its strategic aspects and the role of a key individual, such as a chief executive officer (CEO) in its adoption, have been under-researched. This paper aims to investigate whether OI is relevant to SMEs and how CEO characteristics influence firm performance through OI. The hierarchical relationships between a firm and CEO characteristics are analysed with structural equation modelling (SEM) using data from 401 innovation-oriented SMEs in Korea. The results indicate that: 1) openness can make a greater contribution to firm performance; 2) CEO characteristics are positively associated with openness; 3) government support positively influences both openness and internal R&D. The research suggests that the human elements in SMEs should place a greater emphasis on OI to enhance firm performance and that policy makers should consider developing various programs for key decision makers in SMEs to increase their awareness of OI.

Input-driven policy is typically designed to support R&D and contribute to the enhancement of innovation competences in individual firms. However, it is not clear whether this ‘more is better’ approach has contributed to the establishment of a vibrant innovation ecosystem by stimulating firms’ inclination to collaborate. The current study investigates this question by analysing the data from 489 Korean innovative manufacturing firms using a propensity score matching analysis. As expected, the link to increased innovation collaborations was statistically significant between the recipients and R&D subsidies. The results show that R&D subsidies stimulate firms to choose partners more adventurously, by going outside the traditional value chains and regional boundaries. However, the impact of subsidies on innovation collaboration followed an inverted U-shaped curve: the impact in highly funded firms was smaller than that in firms that received a more modest amount. This finding suggests that government support encourages firms to work with a heterogeneous range of partners and to develop more diversified ecosystems. Our study suggests that different policy impacts, such as input and behavioural additionality, can occur simultaneously and even influence each other. Thus, there is a strong need for policy makers to develop more sophisticated policy tools for open innovation promotion.

Technology opportunity analysis has been the subject of many prior studies, although most of them have focused on discovering new technology ideas in a single narrow domain. This study proposes a product landscape analysis to identify product areas (i.e., potential technology opportunities) across multiple domains that firms can enter based on the technological capabilities embodied in their existing products. First, text mining is used to construct an integrated patent-product database from the United States patent and trademark database. Second, word2vec is employed to construct a product landscape as a vector space model where products with similar technological bases are located close to each other while maintaining the technological relationships. Third, given a product of interest, potential technology opportunities are identified via (1) automatic opportunity analysis that identifies product areas with technological bases similar to those of the product; and (2) interactive opportunity analysis that finds product areas based on experts' queries modifying the technological bases of the product (i.e., addition and subtraction). Finally, ten quantitative indexes are developed to explore the implications of the potential technology opportunities identified. The case study covering 3,016,315 patents and 160,832 products confirms that the proposed approach is valuable as a creativity support tool for technology opportunity analysis in the era of convergence.

Near-field scanning optical microscopy has been an indispensable tool for designing, characterizing and understanding the functionalities of diverse nanoscale photonic devices. As the advances in fabrication technology have driven the devices smaller and smaller, the demand has grown steadily for improving its resolving power, which is determined mainly by the size of the probe attached to the scanner. The use of a smaller probe has been a straightforward approach to increase the resolving power, but it cannot be made arbitrarily small in practice due to the steep reduction of the collection efficiency. Here, we develop a method to enhance the resolving power of near-field imaging beyond the limit set by the physical size of the probe aperture. The main working principle is to unveil high-order near-field eigenmodes invisible with conventional near-field microscopy. The destructive interference of near-field waves is induced in these high-order eigenmodes by the locally varying phases, which can reveal subaperture-scale fine structural details. To extract these eigenmodes, we construct a self-interference near-field microscopy system and measure a fully phase-referenced far- to near-field transmission matrix (FNTM) composed of near-field amplitude and phase maps recorded for various angles of far-field illumination. By the singular value decomposition of the measured FNTM, we could extract the antisymmetric mode, quadrupole mode, and other higher-order modes hidden under the lowest-order symmetric mode. This enables us to resolve double and triple nano-slots whose gap size (50 nm) is three times smaller than the diameter of the probe aperture (150 nm). The subaperture near-field mode mapping by the FTNM can be potentially combined with various existing near-field imaging modalities and promote their ability to interrogate local near-field optical waves of nanoscale devices.