nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2020‒02‒17
five papers chosen by
Laura Ştefănescu
Centrul European de Studii Manageriale în Administrarea Afacerilor

  2. R&D and Knowledge Expertise of French Regions By Tan Tran
  3. China’s Housing Bubble, Infrastructure Investment, and Economic Growth By Shenzhe Jiang; Jianjun Miao; Yuzhe Zhang
  4. Smart City: process of emergence. Interactions between governance and digital technologies By Yoann Queyroi; Pierre Marin
  5. Firm Growth through New Establishments By Dan Cao; Henry Hyatt; Toshihiko Mukoyama; Erick Sager

  1. By: Wioleta Kucharska
    Abstract: Change adaptability reflects intelligence and learning capacity. Mistakes are powerful in relation to teaching potency and learning efficacy, but they are not likely to be accepted by organizations. This has become a serious organizational problem. Is it possible to learn without making mistakes? This study conducts an in-depth exploration of the relation between change adaptability and acceptance of mistakes. Organizational learning is crucial for development, and technology is a major driver of growth in today’s fast-changing world. The majority of learning at work is in the form of human interactions. Hence, the question is: How do technology-driven interactions influence adaptability to change via the acceptance of mistakes in the learning process? This study analyzed 380 cases of Polish employees working in knowledge-driven organizations in various industries between November and December 2019. Analysis of moderated moderation was conducted using PROCESS software. The author found that high intensity of contacts via technology supports change adaptability through the acceptance of mistakes only for the IT industry.The main novelty from this study is that the overall “mindset†and working conditions consistency determines the employees' ability to non-formal learning from mistakes and change adaptability. Hence, the consistency of mindset and non-formal working conditions is important. Moreover, it has been noted that the industry factor matters for organizational learning studies.
    Keywords: change adaptability, organizational learning, acceptance of mistakes, organizational intelligence, IT industry, knowledge-driven organizations, non-formal learning, learning organizations
    JEL: D83 M14 M14
    Date: 2020–01
  2. By: Tan Tran
    Abstract: Within the literature of regional innovation systems, a growing stream of research emphasizes the role of differentiated knowledge bases. The employees’ occupations mainly measure the existing work on knowledge bases. Even though the conceptual theory highlights the importance of interactions across types of knowledge bases underlying innovation activities, they are separately measured and treated in most empirical studies. While few studies use the interaction term between knowledge bases, it does not reflects their actual relationships. In this study, an attempt is made to analysis and observe the regional knowledge for long periods of time. The study suggests suggesting to measure different types of expertise in science and technology of the region, as the fine-grained layers of regional knowledge bases, by using patent and publication datasets in France. Finally, we imply the new measurements to understand the relationships between regional R&D expenditure and their knowledge expertise. The results show that R&D expenditure has a positive relationship with the numbers of the scientific and technological expertise of the region; however, not to the level of expertise. The results also show that the level of technological expertise will increase if it is complementary to a specific science.
    Keywords: regions, science, technology, interdependence, R&D
    JEL: R11 O32 O34
    Date: 2020–02
  3. By: Shenzhe Jiang (Peking University); Jianjun Miao (Boston University); Yuzhe Zhang (Texas A&M University)
    Abstract: China’s housing prices have been growing rapidly over the past few decades, despite low growth in rents. We study the impact of housing bubbles on China’s economy, based on the understanding that local governments use land-sale revenue to fuel infrastructure investment. We calibrate our model to the Chinese data over the period 2003-2013 and find that our calibrated model can match the declining capital return and GDP growth, the average housing price growth, and the rising infrastructure to GDP ratio in the data. We conduct two counterfactual experiments to estimate the impact of a bubble collapse and a property tax.
    Keywords: Housing Bubble, Infrastructure, Economic Growth, Chinese Economy, Property Tax
    JEL: O11 O16 O18 P24 R21 R31
    Date: 2019–12
  4. By: Yoann Queyroi (CREG - Centre de recherche et d'études en gestion - UPPA - Université de Pau et des Pays de l'Adour); Pierre Marin (CREG - Centre de recherche et d'études en gestion - UPPA - Université de Pau et des Pays de l'Adour)
    Date: 2019–03–05
  5. By: Dan Cao (Department of Economics, Georgetown University); Henry Hyatt (Center for Economic Studies, U.S. Census Bureau); Toshihiko Mukoyama (Department of Economics, Georgetown University); Erick Sager (Division of Research and Statistics, Federal Reserve Board)
    Abstract: This paper analyzes the distribution and growth of firm-level employment along two margins: the extensive margin (the number of establishments in a firm) and the intensive margin (the number of workers per establishment in a firm). We utilize administrative datasets to document the behavior of these two margins in relation to changes in the U.S. firm-size distribution. In the cross section, we find the firm-size distribution, as well as both extensive and intensive margins, exhibits a fat tail. The increase in average firm size between 1990 and 2014 is primarily driven by an expansion along the extensive margin, particularly in very large firms. We develop a tractable general-equilibrium growth model with two types of innovations: external and internal. External innovation leads to the extensive margin of firm growth, and internal innovation leads to intensive-margin growth. The model generates fat-tailed distributions in firm size, establishment size, and the number of establishments per firm. We estimate the model to uncover the fundamental forces that caused the distributional changes from 1995 to 2014. The largest contributors to the increase in the number of establishments per firm are the external innovation cost and the decline in establishment exit rate. Classification-JEL E24, J21, L11, O31
    Keywords: firm growth, firm-size distribution, establishment, innovation
    Date: 2020–01–31

This nep-knm issue is ©2020 by Laura Ştefănescu. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.