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on Network Economics |
| By: | Johannes Hoelzemann (Department of Economics, University of Toronto); Hongyi Li (School of Economics, UNSW Business School) |
| Abstract: | Motivated by the problem of organizational design, we study coordination in the network minimum game: a version of the minimum-effort game where players are connected by a directed network. We show experimentally that acyclic networks such as hierarchies are most conducive to successful coordination. Introducing a single link to complete a network cycle may drastically inhibit coordination. Further, acyclic networks enable resilient coordination: initial coordination failure is often overcome (exacerbated) after repeated play in acyclic (cyclic) networks. |
| Keywords: | organizational design, weak-link game, minimum-effort game, coordination failure, quantal response equilibrium |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:swe:wpaper:2021-02&r=all |
| By: | Belo, Rodrigo; Ferreira, Pedro |
| Abstract: | We study the effect of peer influence on products that exhibit positive network externalities to non-adopters, i.e., products that benefit adopters' friends even if they do not adopt. Contrary to products that exhibit positive network externalities upon adoption, this structure of incentives likely results in negative peer influence: the more friends that adopted the product, the smaller the incentives to adopt. We measure this effect empirically by using observational data from a large mobile carrier serving 5.7 million users. We estimate the effect of peer influence across five different products of this type. A naive approach to do so results in a positive estimate for peer influence due to unobserved homophily. We follow two approaches to address this issue. First, we suggest using the number of friends that end up adopting the product as a proxy for unobserved user fixed effects. Second, we control for homophily by applying a shuffle test, i.e., we compare the effect of peer influence from the original data with the effect obtained from comparable randomly generated data without peer influence. We get negative estimates from both approaches, which provides robustness to our findings. Finally, we show that even for these products, the effect of peer influence associated with the first friends that adopt the product is positive, which arises because they still convey useful information about reducing uncertainty. The negative effect of peer influence arises only for the subsequent friends that adopt the product. These friends are unlikely to convey new information about the product, but each of them decreases the economic incentive to adopt, resulting in a negative aggregate effect of peer influence. |
| Date: | 2021–02–14 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:wz4k9&r=all |
| By: | Andry Alamsyah; Maribella Syawiluna |
| Abstract: | Knowledge management is an important aspect of an organization, especially in the ICT industry. Having more control of it is essentials for the organization to stay competitive in the business. One way to assess the organization's knowledge capital is by measuring employee knowledge networks and their personal reputation in social media. Using this measurement, we see how employees build relationships around their peer networks or clients virtually. We are also able to see how knowledge networks support organizational performance. The research objective is to map knowledge network and reputation formulation in order to fully understand how knowledge flow and whether employee reputation has a higher degree of influence in the organization's knowledge network. We particularly develop formulas to measure knowledge networks and personal reputation based on their social media activities. As a case study, we pick an Indonesian ICT company that actively build their business around their employee peer knowledge outside the company. For the knowledge network, we perform data collection by conducting interviews. For reputation management, we collect data from several popular social media. We base our work on Social Network Analysis (SNA) methodology. The result shows that employees' knowledge is directly proportional to their reputation, but there are different reputations level on different social media observed in this research. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2102.12337&r=all |
| By: | Nomaler, Önder (UNU-MERIT); Verspagen, Bart (UNU-MERIT, Maastricht University) |
| Abstract: | We present a number of green technology patent landscaping exercises, based on a method that we developed earlier to identify the main technological trends in a very large (i.e., universal) patent citation network comprising all patented technologies. This method extracts a so-called network of main paths, where we interpret each path as a technological trajectory in the sense of Dosi (1982). We use co-occurrence on the technological trajectories as the main metric to build a network of technological relations, with green/non-green, the technology class (4-digit IPC classes) and geographical location (countries) as the main dimensions along which we observe green technology. The technology landscaping exercise visualises these networks. In this way, we draw a detailed map of green technologies (along with the particular non-green technologies that contribute thereto or benefit therefrom), in which we find both very broad and general areas (such as ICT or medical and health), and specific green technologies, such as batteries, wind power and electric vehicles. In the geography- based map, we find specific European and non-European areas. In all our landscaping maps, non-green technologies play a large role, indicating that sectoral and geographical progress in greentech cannot be fully understood independently of developments in particular fields of non-greentech technologies. |
| Keywords: | green technology, technological trajectories, patent citations, patent landscaping |
| JEL: | O31 O33 Q55 |
| Date: | 2021–02–08 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2021005&r=all |
| By: | Andry Alamsyah; Endang Sofyan; Tsana Hasti Nabila |
| Abstract: | In the context of modern marketing, Twitter is considered a communication platform to spread information. Many companies create and acquire several Twitter accounts to support and perform varieties of marketing mix activities. Initially, each accounts used to capture a specific market profile. Together, the accounts create a network of information that provide consumer to the information they need depends on their contextual utilization. From many accounts available, we have the fundamental question on how to measure the influence of each account in the market based not only on their relations but also on the effects of their postings. The magnitude of Influence (MOI) metric is adapted together with Influence Rank (IR) measurement of accounts in their social network neighborhood. We use social network analysis approach to analyze 65 accounts in the social network of an Indonesian mobile phone network operator, Telkomsel which involved in marketing communications mix activities through series of related tweets. Using social network provide the idea of the activity in building and maintaining relationships with the target audience. This paper shows the results of the most potential accounts based on the network structure and engagement. Based on this research, the more number of followers one account has, the more responsibility it has to generate the interaction from their followers in order to achieve the expected effectiveness. The focus of this paper is to determine the most potential accounts in the application of marketing communications mix in Twitter. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2102.12320&r=all |
| By: | Sascha O. Becker (Monash U and U Warwick); Volker Lindenthal (University of Munich); Sharun Mukand (University of Warwick); Fabian Waldinger (University of Munich) |
| Abstract: | We study the role of professional networks in facilitating the escape of persecuted academics from Nazi Germany. From 1933, the Nazi regime started to dismiss academics of Jewish origin from their positions. The timing of dismissals created individual-level exogenous variation in the timing of emigration from Nazi Germany, allowing us to estimate the causal effect of networks for emigration decisions. Academics with ties to more colleagues who had emigrated in 1933 or 1934 (early émigrés) were more likely to emigrate. The early émigrés functioned as “bridging nodes†that helped other academics cross over to their destination. Furthermore, we provide some of the rst empirical evidence of decay in social ties over time. The strength of ties also decays across space, even within cities. Finally, for high-skilled migrants, professional networks are more important than community networks. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:crm:wpaper:2105&r=all |
| By: | Arai, Natsuki; Nakazawa, Nobuhiko |
| Abstract: | We estimate long-term peer effects in the workplace by investigating whether working with a future executive in the early stages of a junior employee's career will make them more likely to be promoted in the future. Using the data for comprehensive career history at the Japanese central administration, from 1946 to 2019, we find that long-term peer effects are substantial and persistent: Junior employees who work with a future executive in the same division during the first few years of their employment are promoted significantly faster, on average, than employees who do not work with a future executive. They are also more likely to be promoted to the executive level in the future. Additional empirical analysis suggests that improved network connections between senior and junior employees are crucial for the promotion of junior employees in the future. |
| Keywords: | Peer Effect, Coworkers, Promotion, Productivity, Social Connection |
| JEL: | J01 J24 M12 M51 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:hit:econdp:2021-01&r=all |
| By: | Tao Wang; Shiying Xiao; Jun Yan; Panpan Zhang |
| Abstract: | A multi-regional input-output table (MRIOT) containing the transactions among the region-sectors in an economy defines a weighted and directed network. Using network analysis tools, we analyze the regional and sectoral structure of the Chinese economy and their temporal dynamics from 2007 to 2012 via the MRIOTs of China. Global analyses are done with network topology measures. Growth-driving province-sector clusters are identified with community detection methods. Influential province-sectors are ranked by weighted PageRank scores. The results revealed a few interesting and telling insights. The level of inter-province-sector activities increased with the rapid growth of the national economy, but not as fast as that of intra-province economic activities. Regional community structures were deeply associated with geographical factors. The community heterogeneity across the regions was high and the regional fragmentation increased during the study period. Quantified metrics assessing the relative importance of the province-sectors in the national economy echo the national and regional economic development policies to a certain extent. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2102.12454&r=all |
| By: | Daniel Felix Ahelegbey (University of Pavia); Paola Cerchiello (University of Pavia); Roberta Scaramozzino (University of Pavia) |
| Abstract: | How much the largest worldwide companies, belonging to different sectors of the economy, are suffering from the pandemic? Are economic relations among them changing? In this paper, we address such issues by analysing the top 50 S&P companies by means of market and textual data. Our work proposes a network analysis model that combines such two types of information to highlight the connections among companies with the purpose of investigating the relationships before and during the pandemic crisis. In doing so, we leverage a large amount of textual data through the employment of a sentiment score which is coupled with standard market data. Our results show that the COVID-19 pandemic has largely affected the US productive system, however differently sector by sector and with more impact during the second wave compared to the first. |
| Keywords: | COVID-19 Pandemic, Textual analysis, Financial risk, Network model |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:pav:demwpp:demwp0198&r=all |