nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2020‒11‒09
six papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  1. ICT, Collaboration, and Science-Based Innovation: Evidence from BITNET By Kathrin Wernsdorf; Markus Nagler; Martin Watzinger
  2. Assimilation and Diffusion of Multi-Sided Platforms in Dynamic B2B Networks: Inhibiting Factors and Their Consequences By Wallbach, Sören
  3. Digital Innovation Hubs as policy instruments to boost digitalisation of SMEs: A Practical Handbook & Good Practices for regional/national policy makers and DIH Managers By KALPAKA Anna; SORVIK Jens; TASIGIORGOU Alexandra
  4. The American knowledge economy By Soskice, David
  5. Technological Complexity and Economic Growth of Regions By Lars Mewes; Tom Broekel; ; ;
  6. Technological Complexity and Economic Growth of Regions By Michael Fritsch; Michael Wyrwich; ; ;

  1. By: Kathrin Wernsdorf; Markus Nagler; Martin Watzinger
    Abstract: Does access to information and communication technologies (ICT) increase innovation? We examine this question by exploiting the staggered adoption of BITNET across U.S. universities in the 1980s. BITNET, an early version of the Internet, enabled e-mail-based knowledge exchange and collaboration among academics. After the adoption of BITNET, university-connected inventors increase patenting substantially. The effects are driven by collaborative patents by new inventor teams. The patents induced by ICT are exclusively science-related and stem from fields where knowledge can be codified easily. In contrast, we neither find an effect on patents not building on science nor on inventors unconnected to universities.
    Keywords: ICT, communication, knowledge diffusion, science-based innovation, university-patenting
    JEL: H54 L23 L86 O30 O32 O33
    Date: 2020
  2. By: Wallbach, Sören
    Abstract: Spurred on by increasing digitalization and the rise of technology companies such as Facebook, Airbnb or Uber, multi-sided platforms (MSPs) have become increasingly important in a wide range of industries in recent years. In general, MSPs represent an electronic marketplace in which two or more groups of actors interact, and the decisions of individual actors influence the decision-making behavior of the remaining actors. Due to their distributed nature and their interdependencies with institutions, markets, and technologies, MSPs depict unique, new socio-technical artifacts and therefore present researchers with an exciting and challenging research object. Previous research on MSPs have predominantly taken a pro-innovative perspective and have accumulated a vast knowledge base on factors that promote the success of MSPs. However, the triumphant growth and success of MSPs, such as Airbnb or Uber, represent the exception rather than the rule. Most multi-sided platforms are struggling hard to stay viable and often lose this battle. Failure of an MSP can result in massive financial damage for companies, which is revealed, for example, by the $4 billion collapse of General Electric's "Predix" platform. Existing technology diffusion and adoption models provide only anecdotal evidence to the failure of MSPs, which is why knowledge of factors that inhibit the diffusion of MSPs is particularly important. Scholars, therefore, call for a comprehensive and systematic investigation of factors inhibiting the diffusion of MSPs as well as for the development of new or the extension of existing technology diffusion and adoption models to increase their explanatory and predictive validity. Network effects are a key characteristic and a crucial driver for the diffusion of MSPs. The impacts of diffusion-inhibiting factors on network effects have only been superficially examined in previous research. In contrast, the beneficial influence of network effects in the case of one- or two-sided platforms in conventional market relations between businesses and consumers (e.g., game consoles or service platforms such as Airbnb) has been thoroughly investigated. However, dependencies and areas of tension, which mainly occur in the diffusion of technology within or between different organizations (company to company context, B2B), have been neglected. Furthermore, case studies have often analyzed MSPs where management and ownership are carried out by a single organization. Nowadays, however, organizations are no longer isolated. They create their values together and act in corporate networks. As a result, the highly complex management structure within these networks can also influence the diffusion of multi-sided platforms. Dynamic B2B networks are characterized by intensive cooperation between loosely connected organizations in a fast-changing environment with a high degree of uncertainty. The organizations operating in the network are dependent on the rapid exchange of information with their competitors and are therefore in a co-operative and competing business relationship with them at the same time. The management structure within a dynamic B2B network is shared, the goods or services produced are easily interchangeable and are provided by several organizations. Although MSPs have been developed specifically for the interaction of different actors and offer a fast exchange of information between multiple organizations, the diffusion of these systems in dynamic B2B networks is particularly challenging. In summary, MSPs depict new socio-technical information system artifacts that have so far been examined from a pro-innovative perspective. Their manifold interdependencies with institutions, markets, and technologies lead to a highly complex diffusion process in which, among others, internal and external organizational factors, as well as the individuals' pre- and post-adoption behavior must be taken into account. Previous research cannot provide sufficient explanation for why MSPs fail, especially in dynamic B2B networks where a large number of organizations operate dynamically in an environment with frequently changing business relationships. Motivated by the limited explanatory and predictive validity of existing technology diffusion and adoption models for the investigation of multi-sided platforms in dynamic B2B networks, this thesis will examine factors inhibiting the diffusion of MSPs as well as their impact on network effects and on individuals’ pre- and post-adoption behavior. For this purpose, five studies have been conducted to systematically illuminate various partial aspects of the diffusion of MSPs. The first study (Article 1) identified 21 factors that inhibit the diffusion of MSPs in dynamic B2B networks. The second study (Article 2) examined the influence of these 21 inhibiting factors on network effects, which depict main drivers for the diffusion of MSPs. Studies three to five (Articles 3 - 5) each consider the influence of a specific inhibitory factor on individuals' pre- and post-adoption behavior. In detail, article 3 examines the extent to which specific technological features (factor functionalities) influence trust in technology and subsequently, the adoption of the technology. Article 4 examines the extent to which causal attributions (factor blaming other actors) influence users' information system continuance intention. Finally, article 5 analyses the extent to which users' continuance intention is influenced by the personality trait resistance to change (factor spirit of innovations). Taken together, this thesis provides a deeper and more comprehensive understanding of the diffusion of MSPs in dynamic B2B networks. The systematical and comprehensive investigation of factors inhibiting the diffusion of MSPs in dynamic B2B networks contributes to answering various calls for research. By analyzing the relationships between factors inhibiting diffusion and network effects, this thesis contributes to research at the interface between platform and technology diffusion research. Alongside these contributions to research, each of the five articles contained an in-depth and comprehensive discussion on contributions to research and practice.
    Date: 2020–09–28
  3. By: KALPAKA Anna (European Commission - JRC); SORVIK Jens; TASIGIORGOU Alexandra
    Abstract: Building upon the knowledge gained during the last two years on how Digital Innovation Hubs (DIHs) operate in different regional socioeconomic contexts, this practical handbook aims to provide national/regional policy makers and/or existing DIH managers useful and structured information on how to setup a new DIH or reinforce existing ones while benefiting from available funds with a special focus to the European Regional Development Fund (ERDF) 2021-2027. Given the urgent need of SMEs and public administrations to rapidly deploy advanced digital technologies to mitigate the negative consequences of the recent COVID19 crisis to their businesses, the role of DIHs is more important than ever. The Handbook introduces a step-by-step approach to provide support to policy makers that envisage strengthening DIHs in their regions/countries with a view to accelerate digital transformation of the economy and society. This approach allows to use the Handbook as a reference tool depending on the specific needs and level of implementation of DIHs. The practical character of the Handbook is enhanced with the inclusion of many examples that highlight good practices in the different steps of the proposed methodology.
    Keywords: Digital Innovation Hubs, DIH, digital transformation, digitalisation, SMEs, public sector, regional policy, regional development
    Date: 2020–10
  4. By: Soskice, David
    JEL: J1 N0 R14 J01
    Date: 2020–10–01
  5. By: Lars Mewes; Tom Broekel; ; ;
    Abstract: One the one hand, complex technologies o↵er substantial economic benefits, and on the other, they are difficult to invent and to imitate, and they refuse a fast dissemination. This two-sidedness motivates the idea that regions’ competitive advantages and, in consequence, their economic growth, originate in their ability to produce and utilize complex technologies. However, the relationship between technological complexity and regional economic growth has rarely been empirically investigated. Here, we address this pressing issue by assessing the complexity of technological activities in 159 European NUTS 2 regions and relating it to their economic growth from 2000 to 2014. Our empirical results suggest that technological complexity is an important predictor of regional economic growth. A 10% increase in complexity is associated with a 0.45% GDP per capita growth. By showing that technological complexity is important for regional economic growth, our results fuel current policy debates about optimal regional policies such as the Smart Specialization strategy.
    Keywords: Knowledge Complexity, Technological Complexity, Regional Economic Growth, Patent Data
    JEL: O10 O33 R11
    Date: 2020–09
  6. By: Michael Fritsch; Michael Wyrwich; ; ;
    Abstract: We investigate how initial conditions that existed in East Germany at the end of the socialist regime impact regional development during the turbulent shock transition to a market economic system. Our investigation spans a period of almost 30 years. Both the self-employment rate (an indication of the existence of a pre-socialist entrepreneurial tradition) and the share of the workforce with a tertiary degree have a strong positive effect on regional development. We conclude that knowledge and a tradition of entrepreneurship have long-run positive effects on development in regions that face disruptive shocks. Entrepreneurship and knowledge play a less important role for development across West German regions, where no significant shocks occurred.
    Keywords: Entrepreneurship, knowledge, economic development, history, transformation, East Germany
    JEL: L26 R11 N93 N94
    Date: 2020–10

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