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on Knowledge Management and Knowledge Economy |
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Issue of 2021‒08‒09
three papers chosen by Laura Ştefănescu Centrul European de Studii Manageriale în Administrarea Afacerilor |
| By: | Stefano Basilico (Friedrich Schiller University Jena, Economics Department); Uwe Cantner (Friedrich Schiller University Jena, Economics Department, and University of Southern Denmark, Odense); Holger Graf (Friedrich Schiller University Jena, Economics Department) |
| Abstract: | Cluster policies aim at improving collaboration between co-located actors to address systemic failures. As yet, cluster policy evaluations are mainly concerned with effects on firm performance. Some recent studies move to the system level by assessing how the structure of actor-based knowledge networks is affected by such policies. We continue in that direction and analyze how technology-based regional knowledge spaces structurally respond to the introduction of a cluster policy. Taking the example of the German BioRegio contest, we examine how such knowledge spaces in winning and non-winning regions evolved before, during and after the policy. Using a difference-in-differences approach, we identify treatment effects of increased knowledge space embeddedness of biotechnology only in the post-treatment period. Our findings imply that cluster policies can have long-term structural effects typically not accounted for in policy evaluations. |
| Keywords: | BioRegio contest, network analysis, knowledge space, difference in differences, patents |
| JEL: | O31 O38 R11 |
| Date: | 2021–08–02 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2021-011&r= |
| By: | Armin Falk (briq –Institute on Behavior & Inequality and University of Bonn); Thomas Neuber (University of Bonn); Philipp Strack (Yale University) |
| Abstract: | We study response behavior in surveys and show how the explanatory power of selfreports can be improved. First, we develop a choice model of survey response behavior under the assumption that the respondent has imperfect self-knowledge about her individual characteristics. In panel data, the model predicts that the variance in responses for different characteristics increases in self-knowledge and that the variance for a given characteristic over time is non-monotonic in self-knowledge. Importantly, the ratio of these variances identifies an individual’s level of self-knowledge, i.e., the latter can be inferred from observed response patterns. Second, we develop a consistent and unbiased estimator for self-knowledge based on the model. Third, we run an experiment to test the model’s main predictions in a context where the researcher knows the true underlying characteristics. The data confirm the model’s predictions as well as the estimator’s validity. Finally, we turn to a large panel data set, estimate individual levels of self-knowledge, and show that accounting for differences in self-knowledge significantly increases the explanatory power of regression models. Using a median split in self-knowledge and regressing risky behaviors on self-reported risk attitudes, we find that the R2 can be multiple times larger for above- than below-median subjects. Similarly, gender differences in risk attitudes are considerably larger when restricting samples to subjects with high self-knowledge. These examples illustrate how using the estimator may improve inference from survey data. |
| Keywords: | survey research, rational inattention, lab experiment, non-cognitive skills, preferences |
| JEL: | C83 D83 C91 D91 J24 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:ajk:ajkdps:106&r= |
| By: | Christian Bartelheimer (Paderborn University; Paderborn University; Paderborn University; Paderborn University) |
| Abstract: | Digital platforms are intermediating entities that enable interactions between distinct but interdependent groups of actors in two- or multi-sided markets. While research has investigated the management and economic effects of platforms, there is little design knowledge on digital platforms that constitute actor engagement ecosystems. We set out to design, implement, and evaluate DigiStreet—a digital actor engagement platform for local high streets, providing location-based advertising (LBA) via Bluetooth low-energy (BLE) beacons. DigiStreet is the first instantiation of a digital actor engagement platform connecting stores, service providers, and restaurants with consumers in a local high street. Based on detailed field evidence from three interventions—including 150 SMEs and over 2,300 citizens—we develop a design theory for a new class of IT artifacts: digital actor engagement platforms for local high streets. Our empirical analysis also provides unique insights on how digital actor engagement platforms impact on actors in a high street and thus assesses the prospects and limitations of providing LBA via BLE beacons, contextualizing previous insights on digital platforms. |
| Keywords: | Digital Platform, Action Design Research, Design Theory, Actor Engagement, Engagement Platform, Location-Based Advertising, Bluetooth Low-Energy |
| JEL: | C71 D85 L22 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:pdn:dispap:80&r= |