nep-ict New Economics Papers
on Information and Communication Technologies
Issue of 2018‒03‒26
six papers chosen by
Walter Frisch
Universität Wien

  1. Mapping the Radical Innovations in Food Industry: A Text Mining Study By Ilya Kuzminov; Pavel Bakhtin; Elena Khabirova; Maxim Kotsemir; Alina Lavrynenko
  3. Integrating Third Parties in Digitally Mature Companies: Determinants of Innovation Success By Daria Arkhipova; Giovanni Vaia
  4. Tax Simplicity and Heterogeneous Learning By P. Aghion; U. Akcigit; M. Lequien; S. Stantcheva
  5. Learning When to Quit: An Empirical Model of Experimentation By Ganglmair, Bernhard; Simcoe, Timothy; Tarantino, Emanuele
  6. Social Interactions, Mechanisms, and Equilibrium: Evidence from a Model of Study Time and Academic Achievement By Tim Conley; Nirav Mehta; Ralph Stinebrickner; Todd Stinebrickner

  1. By: Ilya Kuzminov (National Research University Higher School of Economics); Pavel Bakhtin (National Research University Higher School of Economics); Elena Khabirova (National Research University Higher School of Economics); Maxim Kotsemir (National Research University Higher School of Economics); Alina Lavrynenko (National Research University Higher School of Economics)
    Abstract: The article presents the results of the study of radical innovations in the global food industry which were obtained through semantic analysis of heterogeneous unstructured text data sources by applying innovative big data text mining system. The approach used allows performing rapid, yet comprehensive aggregation of the whole polyphony of existing knowledge of the technology development in any sector for traditional foresight, future oriented technology analysis, and horizon scanning studies. The sources for the analysis include research papers, patent applications with both full-text data and additional structured metadata, analytical reports by main international organizations and national key players, various media and news resources, including all the major technology innovation, disruption and venture capital news websites. Their processing with an introduced approach for trend- and technology-mapping helps to identify ongoing and emerging technology-related trends, weak signals on possible scientific breakthroughs in the global food industry, including most promising startup strategies and food innovation controversies. This kind of analysis can be performed on a regular basis owing to constant accumulation of textual data and serve as a framework for constant science and technology (S&T) monitoring for early warning on changing technology landscape and its implications on agriculture and food markets
    Keywords: radical innovations, trends, weak signals, big data, text mining, food industry
    JEL: O1 O3
    Date: 2018
    Abstract: Online education has become an important part of the landscape of higher education. Indeed, approximately 80% of colleges and universities offer online courses as part of their standard schedule of courses. As online course offerings have become commonplace, accrediting agencies have come to include examination of institutional criteria for setting standards and measuring the quality of those offerings as part of routine site evaluations. Concerns about which standards should be used and how to meet the scrutiny of accreditation agencies have prompted institutions to explore options for pre-formatted checklists of online course quality.Despite a broad range of possible products and services, many institutions are challenged to find instruments that both meet the critical need of establishing guidelines for online course design, and allow sufficient adaptability to meet unique institutional and programmatic needs and characteristics. In addition, rigid, standardized instruments have prompted faculty to question whether the instruments exert too much influence, restrain their academic freedom, and restrict their choices for methods of instruction. This presentation will report on an innovative model utilized at one institution to address the challenges of creating its own standards for online course design quality and the outcomes of that effort.
    Keywords: Innovation, Online, Education
    JEL: I23 I29
    Date: 2017–10
  3. By: Daria Arkhipova (Dept. of Management, Università Ca' Foscari Venice); Giovanni Vaia (Dept. of Management, Università Ca' Foscari Venice)
    Abstract: We develop and empirically analyse a theoretical model that examines both the antecedents of digital maturity and the involvement of external third parties in companies undergoing digital transformation. We use structural equation modelling technique to test our propositions using the survey data from IT executives on self-reported importance scores they assign to different types of IT competences. We find that digitally mature companies are more likely to establish partnerships with the third parties with a purpose of jointly carrying out digital innovation projects.
    Keywords: digital transformation, digital maturity, sourcing decisions
    JEL: M40
    Date: 2018–03
  4. By: P. Aghion; U. Akcigit; M. Lequien; S. Stantcheva
    Abstract: We study how strongly individuals respond to tax simplicity and how they learn about the complexities of the tax system. We use new French tax returns data on the self-employed from 1994 to 2012. France has three fiscal regimes for the self-employed, which differ in their monetary tax incentives and in their tax simplicity. These regimes are subject to eligibility thresholds: we find large excess masses (bunching) right below the latter. The regimes impact different agents heterogeneously and have changed extensively over time. We estimate a large value for tax simplicity of up to 650 euros per year per individual. Tax complexity has sizable costs: agents are not immediately able to understand what the right regime choice is, leave significant money on the table, and learn over time. These costs are “regressive”, impacting more the uneducated, low income, and low skill agents.
    Keywords: Taxation, personal income and business taxes, tax evasion, income elasticity.
    JEL: H21 H24 H25 H26
    Date: 2018
  5. By: Ganglmair, Bernhard; Simcoe, Timothy; Tarantino, Emanuele
    Abstract: We study a dynamic model of the decision to continue or abandon a research project. Researchers improve their ideas over time and also learn whether those ideas will be adopted by the scientific community. Projects are abandoned as researchers grow more pessimistic about their chance of success. We estimate the structural parameters of this dynamic decision problem using a novel data set that contains information on both successful and abandoned projects submitted to the Internet Engineering Task Force (IETF), an organization that creates and maintains internet standards. Using the model and parameter estimates, we simulate two counterfactual policies: a cost-subsidy and a prize-based incentive scheme. For a fixed budget, subsidies have a larger impact on research output, but prizes perform better when accounting for researchers' opportunity costs.
    Keywords: dynamic discrete choice; Experimentation; learning; Standardization
    JEL: D83 O31 O32
    Date: 2018–02
  6. By: Tim Conley; Nirav Mehta; Ralph Stinebrickner; Todd Stinebrickner
    Abstract: We develop and estimate a model of student study time on a social network. The model is designed to exploit unique data collected in the Berea Panel Study. Study time data allow us to quantify an intuitive mechanism for academic social interactions: own study time may depend on friend study time in a heterogeneous manner. Social network data allow us to embed study time and resulting academic achievement in an estimable equilibrium framework. We develop a specification test that exploits the equilibrium nature of social interactions and use it to show that novel study propensity measures mitigate econometric endogeneity concerns.
    Keywords: social networks, peer effects, homophily, time-use
    JEL: C52 C54 I20
    Date: 2018

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