Network-based ranking in social systems: three challenges

Ranking algorithms are pervasive in our increasingly digitized societies, with important real-world applications including recommender systems, search engines, and influencer marketing practices. From a network science perspective, network-based ranking algorithms solve fundamental problems related to the identification of vital nodes for the stability and dynamics of a complex system. Despite the ubiquitous and successful applications of these algorithms, we argue that our understanding of their performance and their applications to real-world problems face three fundamental challenges: (i) Rankings might be biased by various factors; (2) their effectiveness might be limited to specific problems; and (3) agents' decisions driven by rankings might result in potentially vicious feedback mechanisms and unhealthy systemic consequences. Methods rooted in network science and agent-based modeling can help us to understand and overcome these challenges.Comment: Perspective article. 9 pages, 3 figure

Time dynamics in team entrepreneurial passion development: a case study of startups in an acceleration program

In the competitive business environment, high-growth companies, startups are the new engines of value creation. their success depends on financing which is affect by perceived entrepreneurial passion. The construct of team entrepreneurial passion is empirically observed during a startup acceleration program focusing on time dynamics occuring and on team level affective and identity processe

Exclusionary and Diffusionary Levers in Patent Law

The patent system is built on the premise that exclusion leads to innovation. But a mounting body of evidence calls into question the assumption that “innovation by exclusion” – innovation based on excluding rivals– is the only, or even primary, way innovation happens today: nearly 50% of manufacturers got the idea for their most important new product from an outside source that shared it with them, 45-60% of patentees acquire patents to access the technology of others, and over 1,300 companies, including five of the ten top holders of patents, have pledged to share their patents with others. But because of the patent system’s traditional focus on exclusion, policymakers have paid less attention to how patents can better support the diffusion of technology through mechanisms such as disclosure, transfer, waiver, and the pursuit of freedom to operate. This paper addresses this gap by exploring in depth the way that the patent system can encourage the diffusion of technology between rivals and innovators, revealing a surprising number of overlooked levers within the patent system for encouraging innovation. For example, making it easier to place inventions in the public domain through effective defensive publication, encouraging greater disclosure of patent-product relationships through the marking requirement, and changing the default for provisional applications to being open rather than closed, and for utility applications to publish upon filing, rather than after an 18-month delay, but with the right of inventors to opt-out of this default, would enhance patent disclosure by enabling technical information and permissions to use them to be available earlier to the world. Improving reporting and discovery of patent information, including ownership, availability for licensing, licensing status in the case of publicly funded inventions in accordance with existing law, patent licenses, and standards commitments, could boost markets for technology. Making it easier to waive patent rights and rely on waivers of patent rights, through the creation of a government registry of patent rights, and creating, e.g. an “open” or “defensive only” option that allows patentees to pay discounted maintenance fees in exchange for promising to use their patents only defensively, or to give up certain rights, akin to “license of right” schemes in the UK and Germany, would increase freedom to operate. As innovation increasingly takes place in open and closed modes, and often both, the patent system, by offering more ways for patentees to decide the fate of their inventions, can increase its relevance to “all of the above” types of innovation

Developing a macro-dynamic framework of start-up growth drivers supported by digital marketing

Publisher Copyright: © 2022 The AuthorsThe contemporary market positions digital marketing as a powerful mediator between efficient digital interaction, data interpretation opportunities, and business growth, while extending its impact potential to tackle different growth challenges. As start-ups usually have limited resources and struggle with customer engagement, retention, and other growth challenges, the low investment and dynamic elements of digital marketing tools can be used to support constructive digital interactions impacting start-up growth. Consequently, these links have outlined an extended digital marketing impact in the areas which build on marketing and sales and influence growth components such as product & market testing, customer engagement, and partnership development. Through a systematic literature review, we present a holistic overview encompassing start-up growth areas that use digital marketing. We also discuss how digital marketing efforts complement the start-up maturity. Furthermore, we analyze the differences in B2B and B2C digital marketing usage and discuss how emerging technologies impact digital marketing. The link between the extended digital marketing impact, start-up challenges, and growth areas result in the identification of start-up growth drivers supported by digital marketing. We propose a Macro-Dynamic framework identifying the start-up growth drivers from product, market, team, and finance areas and digital marketing tactics connected to the identified growth drivers.publishersversionpublishe

Startup dilemmas - Strategic problems of early-stage platforms on the internet

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Three Essays on the Human and Social Capital Effects and Entrepreneurial Firm Performance

This dissertation contains three articles that focus on several ways to measure human and social capital and their links to different entrepreneurial outcomes. The study begins by providing an overview of entrepreneurship policy research, highlighting the need for an interdisciplinary approach in this subfield of policy analysis. In the first article, human capital theory is used to understand variations in innovative behavior depending on the size of manufacturing companies in a developing economy. In the second article, factors associated with entrepreneurs\u27 cumulative advantages in the financial system were identified by applying a novel statistical modeling strategy for the field of entrepreneurship research. In the third research article, an estimation of entrepreneurs\u27 human capital impact on new venture performance is analyzed by applying a heterodox theory of human capital, widely used in entrepreneurship research at the regional level, but for the first time at the firm level. The dissertation concludes by providing a general discussion of the findings, policy implications, and potential further research avenues

Recommending investors for new startups by integrating network diffusion and investors’ domain preference

Over the past decade, many startups have sprung up, which create a huge demand for financial support from venture investors. However, due to the information asymmetry between investors and companies, the financing process is usually challenging and time-consuming, especially for the startups that have not yet obtained any investment. Because of this, effective data-driven techniques to automatically match startups with potentially relevant investors would be highly desirable. Here, we analyze 34,469 valid investment events collected from www.itjuzi.com and consider the cold-start problem of recommending investors for new startups. We address this problem by constructing different tripartite network representations of the data where nodes represent investors, companies, and companies’ domains. First, we find that investors have strong domain preferences when investing, which motivates us to introduce virtual links between investors and investment domains in the tripartite network construction. Our analysis of the recommendation performance of diffusion-based algorithms applied to various network representations indicates that prospective investors for new startups are effectively revealed by integrating network diffusion processes with investors’ domain preference

The Future of Service Post-COVID-19 Pandemic, Volume 1

This open access book is geared towards providing insights and stimulating new thinking about the changing nature of services, service work and workers, and service experiences during and after the COVID-19 pandemic in 2020, particularly focusing on digital service technology. This book serves as a useful resource for business practitioners and academics in the areas of service and human resource management. Each chapter deals with specific current issues within these industries due to COVID-19 and issues that will come up post-pandemic. As COVID-19 is expected introduce novel methods to the service sector, such as untact service, telecommuting, alternative work arrangements, job crafting, and new work skills, digital technology is becoming more important than ever before. This books provides a range of examples and cases to elaborate on the effective application of digital service technology in order for businesses to stay relevant in the current climate