Innovation Practice eJournal最新文献

{"title":"Self-Powered Flexible Artificial Synapse for Near-Infrared Light Detection","authors":"Hao Chen, Lei Lv, Yanan Wei, Tianhua Liu, Song Wang, Qinqin Shi, Hui Huang","doi":"10.2139/ssrn.3845004","DOIUrl":"https://doi.org/10.2139/ssrn.3845004","url":null,"abstract":"Summary In the era of artificial intelligence, photonic artificial synapses that are capable of light detection and information storage are attracting much attention, although complex device configuration and high energy consumption are two remaining challenges. Here, a flexible polymer-based optical synapse for infrared light detection in the absence of applied voltage is fabricated to emulate human synaptic photoplasticity. Investigation into the mechanism of the self-powered properties demonstrates that both the localized electric field of the polyethylene terephthalate (PET) substrate and the high dielectric constant of narrow-band conjugated polymer contribute to spontaneous exciton dissociation. Moreover, array imaging and data encryption are achieved by modulating light for the flexible devices, which exhibit excellent mechanical flexibility and long-term air stability. Thus, this work may provide a strategy to develop self-powered artificial synapses for infrared light detection.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"340 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122756014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BIG Picture: El modelo de innovacíon (Big Picture - The Graz Innovation Model)","authors":"H. Lercher","doi":"10.2139/ssrn.3850007","DOIUrl":"https://doi.org/10.2139/ssrn.3850007","url":null,"abstract":"The English version of this paper can be found at <a href=\"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2965373\">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2965373</a><br><br><b>Spanish abstract:</b> Muchas empresas han reconocido claramente la importancia de la innovación y de innovar para competir o mantener su posición. Sin embargo, los modelos de innovación existentes no anclan la gestión de la innovación tan profundamente en la empresa y con la estrategia corporativa como sería necesario para una acción empresarial eficaz y aprovechando todas las posibilidades de innovación. Además, estos modelos a menudo carecen de una orientación real y sólo cubren partes del proceso de innovación. El modelo de innovación BIG Picture es un modelo cíclico, holístico y orientado a la estrategia, que es particularmente útil en las empresas medianas. Hace que el tema complejo de la gestión de la innovación, desde la integración de la estrategia, las posibles clases de innovación de incremental a radical, y las fases operativas y los pasos de toma de decisiones, sean comprensibles y utilizables de un vistazo. El modelo BIG Picture ya se está aplicando con éxito en numerosas organizaciones de todo el mundo y se basa en años de experiencia práctica con proyectos de innovación en empresas y el análisis científico de modelos de innovación existentes.<br>BIG Picture ayuda a las empresas a organizar la gestión de la innovación de manera pragmática y eficiente, definiendo y coordinando las fases de trabajo, tareas, comunicación, los plazos, las responsabilidades, las funciones, los criterios de decisión y los puntos de decisión.<br><br><b>English abstract:</b> Innovation is an omnipresent topic nowadays. Many companies and organizations have become aware of the need to innovate in order to compete. The existing innovation models, however, do not anchor innovation management as deeply in the company strategy as would be necessary for operating entrepreneurially and for exploiting the potential of all fields of innovation. Besides, these models are often out of touch with reality and cover the innovation process only partially. The innovation model BIG Picture™ is a holistic, strategy-oriented and cyclical model, which serves as an innovation engine, particularly suitable for small and medium-sized businesses. It facilitates the understanding of innovation which is otherwise often perceived as complex and yet, does not omit essential and detailed aspects as strategy integration, innovation classes (from incremental to radical), operational processes and decision points. It was developed by the principles of design science and is based on our experiences with innovation consulting in practice as well as our scientific analysis of existing innovation models.<br><br>BIG Picture guides companies pragmatically and efficiently through all stages of their innovation work defining and coordinating workflow, documentation, timings, responsibilities, decision crit","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126244124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"International Venture Capital and Post-Policy Economic Development: Why Innovation and High-Growth Entrepreneurship have Leapfrogged the State","authors":"C. Lesueur","doi":"10.2139/ssrn.3904188","DOIUrl":"https://doi.org/10.2139/ssrn.3904188","url":null,"abstract":"The purpose of this paper is an exploration of the rapidly evolving relationships between entrepreneurship, economic growth/development, Capital and the State in developing nations, with an emphasis on Latin America. Orthodox economic study of growth and development in emerging markets leaves most academics and policy makers exasperated at the lack of progress after half a century of failed policy intervention and billions of dollars in foreign aid programs and investment. I argue that the dissemination of functional entrepreneurial knowledge specific to high-growth startups, fueled by private venture capital, offers more potential for sustainable economic growth and development over the next decade than the entirety of Western foreign aid and policy intervention over the past 60 years. This argument is supported by the deviation of international venture capital investment volume in Latin America away from countries with higher traditional policy metrics such as ease of doing business toward countries with the highest population density metros and largest market potential.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129610411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovering and Transforming Exhaust Data to Realize Managerial Value","authors":"D. O’Leary, V. Storey","doi":"10.2139/ssrn.3746010","DOIUrl":"https://doi.org/10.2139/ssrn.3746010","url":null,"abstract":"“Exhaust data” is “extra data” or “left over” data from “core data” digital transactions, collected, either intentionally or unintentionally, but for which there is no initial, specific purpose for its collection. This article differentiates core data from exhaust data, defines and describes exhaust data, and proposes how to turn it into core data to provide value for firms. We present a framework for discovering and transforming exhaust data and apply it to four case studies involving Internet search data, accounting entries and data security, social media disclosures and Edgar use logs. From the cases, we extract five managerial challenges and generate five recommendations to help managers identify exhaust data applications for realizing potential value.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122814620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Can I Enhance, and Provide Evidence of, the Impact of My Research?","authors":"Christian Nielsen","doi":"10.2139/ssrn.3719702","DOIUrl":"https://doi.org/10.2139/ssrn.3719702","url":null,"abstract":"The purpose of this conceptual paper is to assist researchers in connecting with the notion of impact. Funding bodies, governments, and taxpayers are currently seeking value for their investments in research and a value for money perspective is dominant. Impact is therefore no longer merely a question of number of scientific publications, building a community of interest or counting patents. Rather, impact now emphasizes the delivery of value to stakeholders, and innovative research must encompass this aspect. This paper surveys the literature on research impact, and presents guidelines for researchers on how to conceptualize and work towards providing evidence of the impact of their own research. The paper rests on a structuring and improvement of guidelines issued by funding bodies for creating impact. It clarifies the link between outputs, outcomes and impacts and how this can be applied to clearly communicating the evidence of overall research impact. In doing so, it aims to clarify the continuum from research exploration and output to exploitation and commercialization. Finally, it identifies policy implications of the value - for - money perspective currently emphasized by funding bodies.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129387430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Macro Celebrity and Micro Influencer Endorsements on Consumer-Brand Engagement in Instagram","authors":"Inês Rios de Castro Marques, Beatriz Casais, M. Camilleri","doi":"10.1108/978-1-80071-264-520211008","DOIUrl":"https://doi.org/10.1108/978-1-80071-264-520211008","url":null,"abstract":"Several brands are striving in their endeavors to find new ways to improve their consumer engagement through social media. They are using different tools including influencer marketing through social networking sites (SNSs). Therefore, this chapter addresses a gap in the academic literature as it distinguishes between two types of online influencers. The researchers investigate the effects of celebrity endorsers’ and of micro influencers’ posts on a brand’s page on Instagram. They examine the number of followers, clicks, comments and likes that are generated following their influencer marketing. The results suggest that both influencers have generated varying levels and types of interactions. In sum, this exploratory study revealed that the chosen celebrity’s posts attracted more followers to the brand’s Instagram page, when compared to the micro influencer’s publications. However, the latter has garnered more clicks, comments and likes, thereby increasing the consumer-brand engagement through social media. In conclusion, this contribution identifies future research avenues relating to influencer marketing.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132104433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Impact Analysis of the Coronavirus, An Alternative Data Perspective","authors":"Tony Zhang, Jiayue Wang, Yanjun Li, Xiyuan Zhang, Beibei Li, Danxia Xie","doi":"10.2139/ssrn.3617029","DOIUrl":"https://doi.org/10.2139/ssrn.3617029","url":null,"abstract":"Alternative data is transforming the investment management process for financial industry, hedge funds, mutual funds, foundations, and pension funds. This paper describes the use of alternative data on the field of finance, particularly illustrating the complex forces driving the stock markets in China and the U.S., through the exploration of the alternative data through the outbreak of COVID-19. The analytic results demonstrate that the subway traffic and commercial housing deal area are positively correlated to the Chinese market in a rather weak level, and that search trends of coronavirus is negatively correlated to the American market with high reliability. The alternative data, which are closely connected with the situation of the coronavirus outbreak, have the ability of predicting where the markets are heading.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132293238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence Platforms – A New Research Agenda for Digital Platform Economy","authors":"T. Mucha, Timo Seppala","doi":"10.2139/ssrn.3532937","DOIUrl":"https://doi.org/10.2139/ssrn.3532937","url":null,"abstract":"Abstract Three out of nine of S&P500 digital platform companies stand out as building own artificial intelligence (AI) platforms. There is overwhelming empirical evidence of AI technologies are being central to running a digital platform business. However, the current research agenda is not directing researchers to study AI technologies in the context of digital platforms. We have divided the proposed AI platforms research agenda as follows: The first set of questions we propose relates to an overall conceptualization of AI platforms. Thereafter, we recognize specific aspects of AI platforms, which need to be investigated in detail to gain understanding that is more complete. The second set of questions we propose relates to understanding the dynamics between AI platforms and the broader socio-economic context. This topic might be particularly relevant to economies of countries without indigenous AI platforms. Our paper builds on the proposition that AI is a general-purpose technology, which by itself carries properties of a digital platform.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"2 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117319171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protection for Artificial Intelligence in Personalised Medicine – The Patent/Trade Secret Trade Off","authors":"Nari Lee","doi":"10.4337/9781788973342.00019","DOIUrl":"https://doi.org/10.4337/9781788973342.00019","url":null,"abstract":"Personalised medicine is a new and developing field that carries a great potential for future healthcare applications, for prediction, diagnostic and treatment. Personalised medicine allows targeted treatment of different subgroups of patients, making it possible to tailor the treatment to the best-responding patients, while avoiding non-responders or patients that are likely to suffer adverse effects. Data is crucial in the research for personalised medicine as the interesting potential for the clinical use of personalised medicine may become hampered by absence of reliable large data sets. Conclusive evidence on relevant information of molecular mechanisms is not readily available, as most data often comes from inconclusive and relatively small studies of insufficient quality. Once collected, it is claimed that biomedical data becomes often fragmented, as there are numerous IP claims including both patents and trade secret, as well as the reluctance among the researchers in sharing data. Fragmentation in biomedical data is further exasperated by complex legal, moral and ethical questions surrounding biomedical data. While the need to share personal and private genetic information to advance research and industrial development is acknowledged, there are fundamental moral and ethical questions stemming from the general discomfort against exclusive control of an individual rights’ holder over genetic information. As rights overlap, restriction in one right affects access in other right in personalised medicine. Arguably, the recent move by the US courts to strictly regulate the patentability of diagnostic tools in biomedicine to address the problem of the individual rights holder pushed the shift in protection as trade secrets.<br><br>Moral and ethical questions become even more controversial where machine learning algorithm (AI artificial intelligence) is used in the personalised medicine. AIs and machine learning algorithms are used to discover genes and variants related to specific decisions, to handle next generation sequencing so that they can be analysed in the full context of other genomics and clinical information to drive personalised medicine research. Not only the data sets, the selection of the correct machine algorithms is crucial in their use in personalised medicines. When AIs routinely processes private medical data, to make sure such algorithm based decision making is morally unbiased and ethically correct, the disclosure of the algorithm may be necessary. However, restricting patenting of algorithms for fear of depriving basic research tools from the public, simultaneously creates incentive to protect these algorithms as trade secret.<br><br>This chapter explores this conundrum of patent and trade secret trade off in the context of AIs used in personalised medicine. Among others, the chapter discusses how these questions are addressed in the current EU law at the interface of GDPR, trade secret directive and biotechnology Directi","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125446650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Models of Innovation Diffusion","authors":"L. Spankulova","doi":"10.2139/ssrn.3481072","DOIUrl":"https://doi.org/10.2139/ssrn.3481072","url":null,"abstract":"Modeling the spread of innovation has become an important focus of a series of studies since the 1960s, which confirmed the strong impact of knowledge flows on the regional economy. The results of the works of L. Fort and J. Woodlock, E. Mansfield, A. Floyd, E. Rogers and F. Bass are widely known abroad after numerous publications. They have carried out a large cycle of research to simulate the spread of innovation.","PeriodicalId":102383,"journal":{"name":"Innovation Practice eJournal","volume":"85 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123567633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}