nep-pay New Economics Papers
on Payment Systems and Financial Technology
Issue of 2020‒04‒20
35 papers chosen by

  1. Zero Pricing Platform Competition By Shekhar, Shiva
  2. Digitalisation and its impact on SME finance in Sub-Saharan Africa: Reviewing the hype and actual developments By Disse, Sabrina; Sommer, Christoph
  4. Is Bitcoin Money? An Economic-Historical Analysis of Money, Its Functions and Its Prerequisites By Umlauft, Thomas
  5. From code to market: Network of developers and correlated returns of cryptocurrencies By Lorenzo Lucchini; Laura Alessandretti; Bruno Lepri; Angela Gallo; Andrea Baronchelli
  6. The cost of Bitcoin mining has never really increased By Yo-Der Song; Tomaso Aste
  7. Information Token Driven Machine Learning for Electronic Markets: Performance Effects in Behavioral Financial Big Data Analytics By Jim Samuel
  8. The battle of YouTube, TV and Netflix: An empirical analysis of competition in audio-visual media markets By Budzinski, Oliver; Gänßle, Sophia; Lindstädt-Dreusicke, Nadine
  9. The Gravity Model of Forced Displacement Using Mobile Phone Data By Michel Beine; Luisito Bertinelli; Rana Comertpay; Anastasia Litina; Jean-Francois Maystadt
  10. An extensive study of stylized facts displayed by Bitcoin returns By F. N. M. de Sousa Filho; J. N. Silva; M. A. Bertella; E. Brigatti
  11. Les monnaies locales en France : un bilan de l’enquête nationale 2019-20 By Jérôme Blanc; Marie Fare; Oriane Lafuente-Sampietro
  12. Digitalisation challenges and opportunities for subnational governments By Luiz de Mello; Teresa Ter-Minassian
  13. Theorization of Institutional Change in the Rise of Artificial Intelligence By Masashi Goto
  14. The Economic Consequences of Data Privacy Regulation: Empirical Evidence from GDPR By Guy Aridor; Yeon-Koo Che; Tobias Salz
  15. Choice Between IEO and ICO: Speed vs. Liquidity vs. Risk By Miglo, Anton
  16. Identifying Leadership Skills Required in the Digital Age By Milan Frederik Klus; Julia Müller
  17. Extending Deep Reinforcement Learning Frameworks in Cryptocurrency Market Making By Jonathan Sadighian
  18. Deep Recurrent Modelling of Stationary Bitcoin Price Formation Using the Order Flow By Ye-Sheen Lim; Denise Gorse
  19. E-Service Quality and Price to Build Online Transportation Loyalty in Indonesia By Heny Hendrayati
  20. Regional air traffic in Germany: Germany is a regional air traffic diaspora By Brützel, Christoph
  21. The Middle-Income Trap 2.0: The Increasing Role of Human Capital in the Age of Automation and Implications for Developing Asia By Wagner, Helmut; Glawe, Linda
  22. Bridging the divide- new evidence about firms and digitalisation By Reinhilde Veugelers
  23. How to conceptualize an alternative to platform capitalism according to the re-embedding process of K. Polanyi ? By Laura Aufrère; Philippe Eynaud; Lionel Maurel; Corinne Vercher-Chaptal
  24. Remittance Investment Climate Analysis: Framework and Methods to Ascertain the Local Development Potential of Overseas Remittances By Jeremaiah M. Opiniano; Alvin P. Ang
  25. ICO vs. Equity Financing Under Imperfect, Complex and Asymmetric Information By Miglo, Anton
  26. Where Has All the Data Gone? By Maryam Farboodi; Adrien Matray; Laura Veldkamp; Venky Venkateswaran
  27. The Economics of Social Data By Dirk Bergemann; Alessandro Bonatti; Tan Gan
  28. Defence Against Dark Artefacts: An Analysis of the Assumptions Underpinning Smart Home Cybersecurity Standards By Piasecki, Stanislaw; Urquhart, Lachlan; McAuley, Derek
  29. Deep learning for Stock Market Prediction By Mojtaba Nabipour; Pooyan Nayyeri; Hamed Jabani; Amir Mosavi
  30. The next generation of digital currencies- in search of stability By Grégory Claeys; Maria Demertzis
  31. Reselling Information By S. Nageeb Ali; Ayal Chen-Zion; Erik Lillethun
  32. Company classification using machine learning By Sven Husmann; Antoniya Shivarova; Rick Steinert
  33. To buy or not to buy? Price salience in an online shopping field experiment By Dertwinkel-Kalt, Markus; Köster, Mats; Sutter, Matthias
  34. Ground work vs. social media: how to best reach voters in French municipal elections? By Vincent Pons; Vestal Mcintyre
  35. What do online listings tell us about the housing market? By Michele Loberto; Andrea Luciani; Marco Pangallo

  1. By: Shekhar, Shiva
    Abstract: This article studies competition between different types of ad-funded platforms attracting consumers with free services. Consumers often find advertisements a nuisance on such platforms. We study how under a competitive setting platforms balance the tension between attracting consumers and rent extraction from the advertising side. We propose a flexible yet simple model that studies competition between standard platforms and social media platforms (with same-side network effects). We find that an increase in either positive same-side network effects or an increase in consumer disutility from advertisements leads to a reduction in the number of ads on that platform. When competing platforms merge, consumer side network effects do not impact prices and the number of ads is higher. In a setting where consumers present a negative (congestion) externality on each other, competition fails to protect consumer welfare and behaves erratically. Finally, we present a few extensions and discuss some policy implications.
    Keywords: Social media platforms, platforms, two-sided markets, same side network effects, cross side network effects, advertising.
    JEL: K21 L13 L82 L86
    Date: 2020–03
  2. By: Disse, Sabrina; Sommer, Christoph
    Abstract: Small and medium-sized enterprises (SMEs) are pivotal for inclusive economic development, but suffer disproportionally from institutional and market failures, especially from constrained access to external finance. Digitalisation of the financial industry is often seen as a game changer. This paper aims to answer the question what the role is of digital financial instruments in SME finance in Sub-Saharan Africa (SSA). It discusses the opportunities and challenges of digital advances for SME finance in general and of three specific financing instruments in Sub-Saharan Africa, namely mobile money (including digital credits), crowdfunding (including peer-to-peer lending) and public equity, in order to contrast the hype around digital finance with actual market developments and trends. Over 90 per cent of firms are small and medium-sized enterprises employing more than half of the formal workforce worldwide and more than 60 per cent in low- and middle-income countries (LMICs). SMEs also account for most of the new jobs created (or at least as much as larger firms). They create economic opportunities such as employment, skill development and upward mobility in diverse geographic areas and economic sectors, and provide a livelihood and income for diverse segments of the labour force, including low-skilled workers as well as disadvantaged and marginalised groups such as young people, women and minorities. Hence, SMEs can foster inclusive economic development and subsequently contribute to social cohesion. A substantial share of national value added is attributed to SMEs and the SME segment is strongly and positively associated with economic growth (even though no causality can be claimed in this respect) and economic diversification. SMEs are also vital for advances in productivity and innovation, as small and young firms may introduce new, efficient technologies or - especially important for LMICs -make small modifications in order to adapt innovations to the local or national contexts or benefit from knowledge spillover. In short, SMEs play a crucial role for economic development. (...)
    Date: 2020
  3. By: issalillah, fayola
    Abstract: The existence of the internet is followed by the development of various advanced technologies such as smartphones. A smartphone is a smart phone that is equipped with various convenience features for its users. Many aspects of life are affected by the development of the internet, one of which is consumer behavior. Consumer behavior is dynamic, meaning that consumer behavior is always changing and moving all the time, therefore when the Internet and technology continue to develop, consumer behavior also changes, including in terms of shopping. Customer satisfaction and loyalty depends on the quality of service provided by the company, in the online market we are more familiar with e-service quality is a new version of service quality that was developed to evaluate a service provided on the internet network. This study will examine the effect of e-service quality on customer satisfaction and loyalty by involving 276 respondents who frequently shop online. The analytical tool used is path analysis. From the findings of the study mentioned that e-service quality has a significant influence on customer satisfaction but e-service quality does not have a significant effect on customer loyalty. Keywords: e-service quality, customer satisfaction, loyalty
    Date: 2020–04–10
  4. By: Umlauft, Thomas
    Abstract: Bitcoin and other cryptocurrencies’ spectacular rise over the past years has attracted considerable public and academic interest. The important question arising in this context is whether cryptocurrencies can legitimately be regarded as money. This paper contributes to the current discourse by evaluating cryptocurrencies’ monetary merits based on (1) the orthodox, or Metallist, school of money and (2) the heterodox, or Chartalist, approach. The theoretical as well as empirical findings advanced in this paper serve to illustrate that cryptocurrencies cannot legitimately be regarded as money owing to their lack of essential characteristics universally shared by other monetary systems. By cryptocurrencies’ lack of intrinsic value as well as government support, virtual currencies fail according to the orthodox as well as the heterodox school of money, respectively. In addition, the inelasticity of the bitcoin stock due to the fixed maximum amount of 21 million units stands in sharp contrast to that of other monetary systems – including gold and other depletable resources –, further reducing bitcoin’s suitability as a medium of exchange, and thus as money. In an attempt to explain the apparent discrepancy between the current value the market attaches to cryptocurrencies and their monetary deficiencies, we advance that market participants are misled by what we term the input fallacy of value (IFV). Similar to the labour theory of value, which posits that value is a function of the labour required to produce a good or service, market participants appear to be misled into believing that the value of cryptocurrencies is the product of the input costs required in the “mining” process. In this context, it is overlooked that value, far from merely being a function of labour and capital deployed, is solely determined by the resultant utility. Since, however – as detailed in this paper –, bitcoin lacks the essential characteristics associated with money, cryptocurrencies’ utility, and hence price, should tend towards zero over time.
    Keywords: Bitcoin, Cryptocurrencies, Economic Bubbles, Nature of Money, Origin of Money, Theories of Money, Money, Medium of Exchange, Orthodox School of Money, Heterodox School of Money, Chartalist School, Metallist School, Labour Theory of Value, Input Fallacy of Value, Stone Currency of Yap
    JEL: B12 B13 B15 B25 B59 E31 E41 E42 E51 E58 N10 N20
    Date: 2018–06
  5. By: Lorenzo Lucchini; Laura Alessandretti; Bruno Lepri; Angela Gallo; Andrea Baronchelli
    Abstract: "Code is law" is the funding principle of cryptocurrencies. The security, transferability, availability and other properties of a crypto-asset are determined by the code through which it is created. If code is open source, as it happens for most cryptocurrencies, this principle would prevent manipulations and grant transparency to users and traders. However, this approach considers cryptocurrencies as isolated entities thus neglecting possible connections between them. Here, we show that 4% of developers contribute to the code of more than one cryptocurrency and that the market reflects these cross-asset dependencies. In particular, we reveal that the first coding event linking two cryptocurrencies through a common developer leads to the synchronisation of their returns in the following months. Our results identify a clear link between the collaborative development of cryptocurrencies and their market behaviour. More broadly, our work reveals a so-far overlooked systemic dimension for the transparency of code-based ecosystems and we anticipate it will be of interest to researchers, investors and regulators.
    Date: 2020–04
  6. By: Yo-Der Song (University College London); Tomaso Aste (University College London)
    Abstract: The Bitcoin network is burning a large amount of energy for mining. In this paper we estimate the lower bound for the global energy cost for a period of ten years from 2010 to 2020, taking into account changing oil costs, improvements in hashing technologies and hashing activity. Despite a ten-billion-fold increase in hashing activity and a ten-million-fold increase in total energy consumption, we find the mining cost relative to the volume of transactions has not increased nor decreased since 2010. This is consistent with the perspective that the proof of work must cost a sizable fraction of the value that can be transferred through the network in order to keep the Blockchain system secure from double spending attacks. We estimate that in the Bitcoin network this fraction is of the order of 1%.
    Date: 2020–04
  7. By: Jim Samuel
    Abstract: Conjunct with the universal acceleration in information growth, financial services have been immersed in an evolution of information dynamics. It is not just the dramatic increase in volumes of data, but the speed, the complexity and the unpredictability of big-data phenomena that have compounded the challenges faced by researchers and practitioners in financial services. Math, statistics and technology have been leveraged creatively to create analytical solutions. Given the many unique characteristics of financial bid data (FBD) it is necessary to gain insights into strategies and models that can be used to create FBD specific solutions. Behavioral finance data, a subset of FBD, is seeing exponential growth and this presents an unprecedented opportunity to study behavioral finance employing big data analytics methodologies. The present study maps machine learning (ML) techniques and behavioral finance categories to explore the potential for using ML techniques to address behavioral aspects in FBD. The ontological feasibility of such an approach is presented and the primary purpose of this study is propositioned- ML based behavioral models can effectively estimate performance in FBD. A simple machine learning algorithm is successfully employed to study behavioral performance in an artificial stock market to validate the propositions. Keywords: Information; Big Data; Electronic Markets; Analytics; Behavior
    Date: 2020–03
  8. By: Budzinski, Oliver; Gänßle, Sophia; Lindstädt-Dreusicke, Nadine
    Abstract: The world of audiovisual online markets is rapidly changing. Not long ago, it was dominated by linear television, transmitted terrestrially, through cable networks or via satel-lite. Recently, streaming services like Netflix, YouTube, Amazon Prime and others have emerged as new suppliers of audiovisual content. In this quickly changing industry, compe-tition interrelations between such different formats like traditional TV, videos on YouTube, and streaming via Netflix are subject to controversy. In particular, doubt is cast on services like YouTube exerting competitive pressure on services like Netflix and traditional TV. Based upon a survey with almost 3,000 participants, we provide an empirical analysis of consump-tion behavior of audiovisual contents. Using descriptive and analytical statistics, including multiple equation models, we show that there are specific areas within audiovisual content markets where YouTube exerts considerable competitive pressure on both Netflix and classic TV, for instance, through prime time video entertainment. However, our analysis yields dif-ferentiated results as we also identify areas where competition intensity between different service types appear to be low, for instance, through daytime and regarding the intention to shorten waiting time.
    Keywords: video-on-demand,streaming markets,media economics,cultural economics,commercial television,multiple equation models,competition,consumption behavior
    JEL: L82 L86 Z10 M21 L13 L40 L51 C39
    Date: 2020
  9. By: Michel Beine; Luisito Bertinelli; Rana Comertpay; Anastasia Litina; Jean-Francois Maystadt
    Abstract: Based on geolocalized mobile phone calls data, we study the mobility of refugees in Turkey. We employ a gravity model to estimate the determinants of refugee movements across 26 regions in 2017. To benchmark our findings, we estimate the same model for the mobility of individuals with a non-refugee status. Beyond the standard determinants such as the levels of income at origin, at destination and distances across regions, we find that networks, provision of humanitarian aid and asylum grants are important determinants of refugee mobility. Our paper deepens our understanding on how forcibly displaced people may respond to economic, social and political factors in their location decision.
    Keywords: Refugee Mobility, Gravity Model of Migration, Forced Displacement, Mobile Phone Data, News Media, Poisson Pseudo-Maximum Likelihood
    JEL: J6
    Date: 2020
  10. By: F. N. M. de Sousa Filho; J. N. Silva; M. A. Bertella; E. Brigatti
    Abstract: In this paper, we explore some stylized facts in the Bitcoin market using the BTC-USD exchange rate time series of historical intraday data from 2013 to 2018. Despite Bitcoin presents some very peculiar idiosyncrasies, like the absence of macroeconomic fundamentals or connections with underlying asset or benchmark, a clear asymmetry between demand and supply and the presence of inefficiency in the form of very strong arbitrage opportunity, all these elements seem to be marginal in the definition of the structural statistical properties of this virtual financial asset, which result to be analogous to general individual stocks or indices. In contrast, we find some clear differences, compared to fiat money exchange rates time series, in the values of the linear autocorrelation and, more surprisingly, in the presence of the leverage effect. We also explore the dynamics of correlations, monitoring the shifts in the evolution of the Bitcoin market. This analysis is able to distinguish between two different regimes: a stochastic process with weaker memory signatures and closer to Gaussianity between the Mt. Gox incident and the late 2015, and a dynamics with relevant correlations and strong deviations from Gaussianity before and after this interval.
    Date: 2020–04
  11. By: Jérôme Blanc (TRIANGLE - Triangle : action, discours, pensée politique et économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet [Saint-Étienne] - IEP Lyon - Sciences Po Lyon - Institut d'études politiques de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique); Marie Fare (TRIANGLE - Triangle : action, discours, pensée politique et économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet [Saint-Étienne] - IEP Lyon - Sciences Po Lyon - Institut d'études politiques de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique); Oriane Lafuente-Sampietro (TRIANGLE - Triangle : action, discours, pensée politique et économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet [Saint-Étienne] - IEP Lyon - Sciences Po Lyon - Institut d'études politiques de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This national survey on local currencies in France was conducted online between November, 2019 and January, 2020. 63 associations that already circulated their local currency filled the questionnaire, on an estimated number of 82 circulating local currencies as of end 2019. This report analyses the data from this survey. After some methodological considerations, it studies the characteristics of the issuing associations, the characteristics of the issued currencies, the monetary activity of the associations and the links between them and the socio-economic actors of the territory.
    Abstract: Cette enquête nationale sur les monnaies locales en France a été administrée en ligne de novembre 2019 à janvier 2020. 63 associations ayant mis en circulation une monnaie locale ont répondu à l'enquête, sur un nombre estimé de 82 monnaies locales en circulation à la fin 2019. Ce rapport traite les données issues de cette enquête : après quelques repères méthodologiques, il étudie les caractéristiques des associations émettrices, les caractéristiques des monnaies émises, l'activité monétaire des associations et les liens des associations avec les acteurs socio-économiques du territoire.
    Keywords: France,survey,Local currencies,enquête,Monnaies locales
    Date: 2020–04–07
  12. By: Luiz de Mello; Teresa Ter-Minassian
    Abstract: The world economy and societies are going through a digital transformation that goes well beyond computerisation and use of information and telecommunications technologies. This transformation is creating opportunities and challenges for all levels of government in the areas of tax and expenditure policy and administration, service delivery and fiscal-financial management, and regulatory practices and policies. However, governments (especially sub-national ones, SNGs) often also face shortages of skills, equipment and physical infrastructure, while having to address emerging challenges in cyber security risk management and data protection. The digital transformation calls for cooperation among the different layers of administration in support of effective and efficient digitalisation of SNGs. This paper reviews and discusses these opportunities and challenges.
    Keywords: decentralisation, digitalisation, subnational governments
    JEL: H11 O38 H70
    Date: 2020–04–20
  13. By: Masashi Goto (Research Institute for Economics and Business Administration, Kobe University, Japan)
    Abstract: This study explores how professional institutional change is theorized in the context of the emergence of disruptive technology as a precipitating jolt. I conducted a case study of two Big four accounting firms in Japan on their initiatives to apply artificial intelligence (AI) to their core audit services between 2015 and 2017. The data shows the process for incumbent dominant organizations to collaborate and develop social perceptions about the changing but continuing relevance of their profession. The analysis suggests that the retheorization can advance even without concrete alternative templates when disruptive technology is perceived to have overwhelming influences, following multi-level steps progressing from internal to external theorization. This article proposes a grounded theory model of the process of professional institutional change: (1) Theorizing change internally at the field, (2) Developing solutions by experimentations in organizations, (3) Exploring solutions driven by individuals in organizations and (4) Theorizing change externally by organizations. It contributes to the profession and institutional scholarship by expanding our knowledge about the diversity of professional institutional field change process in this age of increasing technology influences on organizations.
    Keywords: Institutional change; Professions; Artificial intelligence; Qualitative research; Grounded theory
    Date: 2020–03
  14. By: Guy Aridor; Yeon-Koo Che; Tobias Salz
    Abstract: This paper studies the effects of the EU’s General Data Protection Regulation (GDPR) on the ability of firms to collect consumer data, identify consumers over time, accrue revenue via online advertising, and predict their behavior. Utilizing a novel dataset by an intermediary that spans much of the online travel industry, we perform a difference-in-differences analysis that exploits the geographic reach of GDPR. We find a 12.5% drop in the intermediary-observed consumers as a result of the new opt-in requirement of GDPR. At the same time, the remaining consumers are observable for a longer period of time. We provide evidence that this pattern is consistent with the hypothesis that privacy-conscious consumers substitute away from less efficient privacy protection (e.g, cookie deletion) to explicit opt out, a process that would reduce the number of artificially short consumer histories. Further in keeping with this hypothesis, we observe that the average value of the remaining consumers to advertisers has increased, offsetting most of the losses from consumers that opt out. Finally, we find that the ability to predict consumer behavior by the intermediary’s proprietary machine learning algorithm does not significantly worsen as a result of the changes induced by GDPR. Our results highlight the externalities that consumer privacy decisions have both on other consumers and for firms.
    JEL: L0 L5 L81
    Date: 2020–03
  15. By: Miglo, Anton
    Abstract: This paper analyzes a financing problem for an innovative firm that is considering launching a web-based platform. Our model is the first one that analyzes an entrepreneur's choice between initial exchange offering (IEO) and initial coin offering (ICO). Compared to ICO, under IEO the firm is subject to screening by an exchange that reduces the risk of investment in tokens; also the firm gets access to a larger set of potential investors; finally tokens become listed on an exchange faster. We argue that IEO is a better option for the firm if: 1) the investment size is relatively large; 2) the extent of moral hazard problems faced by the firm is relatively large; 3) the degree of investors' impatience is relatively small. We aslo find a non-linear relationship between firm quality and its financing choice. Most of these predictions are new and have not been tested sofar.
    Keywords: FinTech; Entrepreneurial Finance; Initial Coin Offering; Initial Exchange Offering; Moral Hazard; Utility Tokens; Listing
    JEL: D82 D84 G32 L11 L26 M13 O32
    Date: 2020–04
  16. By: Milan Frederik Klus; Julia Müller
    Abstract: How should executives lead organisations and their employees in an increasingly digitalized business environment and what skills are needed to succeed? Although the evolution of digital technologies considerably changes working environments in organisations and creates new challenges for executives, only little research has been conducted on how these challenges and technology-driven changes are associated with requirements for the skill set needed by executives. In this paper, we bridge that gap by applying a three-stage research design. First, we develop a conceptual framework in which we categorise leadership skills included in the existing literature and associate them with tasks, management level, and leadership experience. To identify skills that are particularly relevant in the context of digitalisation, we conduct semi-structured interviews with executives and systematically investigate job advertisements for management positions. By triangulating the findings, we contribute new insights to the leadership literature and derive practical implications.
    Keywords: conceptual framework, digitalization, explorative study, leadership skills
    JEL: M12 M15 M51 M54 O32 O33
    Date: 2020
  17. By: Jonathan Sadighian
    Abstract: There has been a recent surge in interest in the application of artificial intelligence to automated trading. Reinforcement learning has been applied to single- and multi-instrument use cases, such as market making or portfolio management. This paper proposes a new approach to framing cryptocurrency market making as a reinforcement learning challenge by introducing an event-based environment wherein an event is defined as a change in price greater or less than a given threshold, as opposed to by tick or time-based events (e.g., every minute, hour, day, etc.). Two policy-based agents are trained to learn a market making trading strategy using eight days of training data and evaluate their performance using 30 days of testing data. Limit order book data recorded from Bitmex exchange is used to validate this approach, which demonstrates improved profit and stability compared to a time-based approach for both agents when using a simple multi-layer perceptron neural network for function approximation and seven different reward functions.
    Date: 2020–04
  18. By: Ye-Sheen Lim; Denise Gorse
    Abstract: In this paper we propose a deep recurrent model based on the order flow for the stationary modelling of the high-frequency directional prices movements. The order flow is the microsecond stream of orders arriving at the exchange, driving the formation of prices seen on the price chart of a stock or currency. To test the stationarity of our proposed model we train our model on data before the 2017 Bitcoin bubble period and test our model during and after the bubble. We show that without any retraining, the proposed model is temporally stable even as Bitcoin trading shifts into an extremely volatile "bubble trouble" period. The significance of the result is shown by benchmarking against existing state-of-the-art models in the literature for modelling price formation using deep learning.
    Date: 2020–03
  19. By: Heny Hendrayati (Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi No. 229, 40154, Bandung, Indonesia Author-2-Name: Askolani Author-2-Workplace-Name: Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi No. 229, 40154, Bandung, Indonesia Author-3-Name: Mochamad Achyarsyah Author-3-Workplace-Name: Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi No. 229, 40154, Bandung, Indonesia Author-4-Name: Ceppy Trian Sudrajat Author-4-Workplace-Name: Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi No. 229, 40154, Bandung, Indonesia Author-5-Name: Rahmy Karimah Syahidah Author-5-Workplace-Name: Northwestern Polytechnical University, 127 Youyi W Rd, Beilin, Xi'an, Shaanxi, China Author-6-Name: Author-6-Workplace-Name: Author-7-Name: Author-7-Workplace-Name: Author-8-Name: Author-8-Workplace-Name:)
    Abstract: Objective - The development of the online transportation industry has led to increasing competition. In Indonesia, Gojek and Grab are competitors in their industry. Each company strives to maintain the loyalty and satisfaction of its customers by setting up procedures such as e-service quality programs and pricing policies. Under these programs, consumers have different levels of satisfaction and loyalty for each type of online vehicle. This study aims to measure the influence of e-service quality and price to build loyalty through customer satisfaction Gojek and Grab. Methodology/Technique - The type of the study is verification. An explanatory survey with simple random sampling technique is used. The sample includes 200 respondents from both online transportation operator's customers. The data of this study employs a path analysis with SPSS 25.0 and AMOS. Findings - The results show that there is a positive influence between e-service quality and price to build loyalty through each Gojek and Grab customers' satisfaction. Thus, we can say that Gojek and Grab consumers are quite satisfied with the quality and price so they pay with loyalty. Novelty – Good management in service companies will serve customers with great satisfaction, thus affirming the rightness of consumer loyalty to the company. Therefore, prices will be appropriate in addition to quality electronic services. This is because the relationship between the two can produce positive impacts such as consumer loyalty with mediation through satisfaction. Our study has several contributions, including adding insight into e-service studies, price, customers' satisfaction, and loyalty, especially in the online transportation industry.
    Keywords: E-Service Quality, Price, Loyalty, Customer Satisfaction, Online Transportation.
    JEL: M20 M21
    Date: 2020–03–30
  20. By: Brützel, Christoph
    Abstract: The article compares regional airport infrastructures in Germany to those of other European countries and analyzes recent developments and situation of traffic at German regional airports. Type of services are segregated into hub feeder services, connections to European cities relevant for business travel and private travel destinations. It shows that, compared to other large European countries the landscape of regional airports in Germany is less dense and that traffic there is mostly restricted to hub feeders, major leisure destinations and other destinations for private air travel.
    Keywords: Aviation,Airlines,Regional Airports,Regional Air Traffic Market,Point-to-Point Air Traffic,German Air Traffic Market
    Date: 2020
  21. By: Wagner, Helmut; Glawe, Linda
    Abstract: We modify the concept of the middle-income trap (MIT) against the background of the Fourth Industrial Revolution and the (future) challenges of automation (creating the concept of the "MIT 2.0") and discuss the implications for developing Asia. In particular, we analyze the impacts of automation, artificial intelligence, and digitalization on the growth drivers of emerging market economies and the MIT mechanism. Our findings suggest that improving human capital accumulation, particularly the upgrading of skills needed with the rapid advance of automation, will be key success factors for overcoming the MIT 2.0.
    Keywords: automation,AI,human capital,middle-income trap,developing Asia,economic development,economic growth,employment
    JEL: J24 O10 O11 O15 O33 O47 O53
    Date: 2020
  22. By: Reinhilde Veugelers
    Abstract: Using new evidence on the digitalisation activities of firms in the European Union and the United States, we document a trend towards digital polarisation based on firms’ use of the latest digital technologies and their plans for future investment in digitalisation. A substantial share of firms are not implementing any state-of-the-art digital technologies and do not have plans to invest in digitalisation. However, there is also a substantial share of...
    Date: 2019–12
  23. By: Laura Aufrère (Centre d’Economie de l’Université de Paris Nord (CEPN)); Philippe Eynaud (GREGOR); Lionel Maurel (InSHS CNRS); Corinne Vercher-Chaptal (Centre d’Economie de l’Université de Paris Nord (CEPN) Title : Comment penser l'alternative au capitalisme de plateforme dans une logique de réencastrement polanyien ?)
    Abstract: L’article envisage les alternatives au capitalisme de plateforme dans une logique de réencastrement polanyien. Issus d’études de cas dans les secteurs du co-voiturage, de la livraison et de l’hébergement, les résultats mettent au jour des modèles d’activité hybrides au sein desquels le principe marchand est mis au service de la logique réciprocitaire. Rejetant la rationalité algorithmique formelle des plateformes capitalistes, les alternatives cherchent à aligner les comportements individuels et collectifs sur les valeurs de solidarité et les finalités d’intérêt général. Elles expérimentent des modalités originales de passage à l’échelle, basées sur la fédération de communautés, respectueuses de leur ancrage dans l’économie substantive. Les résultats permettent de penser des complémentarités entre différentes formes d'encastrement susceptibles de se jouer à plusieurs échelles, et ouvrent des perspectives pour repenser les politiques publiques vis-à-vis des expérimentations de l’économie solidaire et des communs.
    Abstract: The article considers alternatives to platform capitalism in a logic of Polanyian re-embedding. Stemming from case studies in the car-pooling, delivery and hosting sectors, the results uncover hybrid business models in which the market principle is used in the service of reciprocal logic. Rejecting the formal algorithmic rationality of capitalist platforms, the alternatives seek to align individual and collective behavior with values of solidarity and goals of general interest. They are experimenting with original methods of scaling up, based on the federation of communities, respectful of their anchoring in the substantive economy. The results make it possible to think of complementarities between different forms of embedding likely to be played out on several scales, and open perspectives for rethinking public policies vis-à-vis the experiments of the solidarity economy and the commons.
    Keywords: Plateformes numériques, coopérativisme de plateforme, ré-encastrement, démarchandisation, réciprocité, économie substantive.; Digital platforms, platform cooperativism, re-embedding, decommodification, reciprocity, substantive economy.
    Date: 2020–04
  24. By: Jeremaiah M. Opiniano; Alvin P. Ang
    Abstract: ABSTRACT This paper presents the integrated mixed methods results and findings of four community-based studies on the local development potential of overseas remittances. We developed a Remittance Investment Climate (ReIC) analytical framework that outlines what the rural origins of overseas migrants need to see for their remittances to make productive contributions locally. This ReIC framework was piloted through a mixed methods tool called the Remittance Investment Climate Analysis in Rural Hometowns (RICART) and was conducted over a four-year period in four rural municipalities in the Philippines. The interactions between remittance owners (remitters abroad and their families) and their rural hometowns’ investment climate conditions were analyzed. The results and findings on remittances being saved, invested and parked as operational enterprises locally are contextualized per municipality. We find that the interventions by local authorities to improve investment conditions are important actions, but so are improving rural residents’ financial literacy levels, and their practices surrounding financial inclusion and financial functioning. The local development potential of remittances thus rests on conjoint actions to improve local investment climate conditions and regulations, and the financial capabilities of rural residents.
    Keywords: Overseas remittances, migration and development, hometown investing, Remittance Investment Climate Analysis in Rural Hometowns, mixed methods
    Date: 2020–04
  25. By: Miglo, Anton
    Abstract: This paper offers a model of a firm that raises funds for financing an innovative business project and chooses between ICO (initial coin offering) and equity financing. The model is based on information problems associated with both ICO and equity financing well documented in literature. The model provides several implications that have not yet been tested. For example we find that the message complexity can be benefitial for firms conducting ICOs. Also high-quality projects can use ICO as a signal of quality. Thirdly the average size of projects undertaking equity financing is larger than that of firms conducting ICO.
    Keywords: asymmetric information, complex information, initial coin offering (ICO), equity financing, signalling
    JEL: D82 G32 L11 L26 M13 M15 O32
    Date: 2020–04
  26. By: Maryam Farboodi; Adrien Matray; Laura Veldkamp; Venky Venkateswaran
    Abstract: As financial technology improves and data becomes more abundant, do market prices reflect this data growth? While recent studies documented rises in the information content of prices, we show that, across asset types, there is data divergence. Large, growth stock prices increasingly reflect information about future firm earnings. This is the rise reflected in the previous studies. But over the same time period, the information content of small and value firm prices was flat or declining. Our structural estimation allows us to disentangle these informational trends from changing asset characteristics. These facts pose a new puzzle: Amidst the explosion of data processing, why has this data informed only the prices of a subset of firms, instead of benefiting the market as a whole? Our structural model offers a potential answer: Large growth firms' data grew in value, as big firms got bigger and growth magnified the effect of these changes in size.
    JEL: G14
    Date: 2020–04
  27. By: Dirk Bergemann; Alessandro Bonatti; Tan Gan
    Abstract: A data intermediary pays consumers for information about their preferences and sells the information so acquired to firms that use it to tailor their products and prices. The social dimension of the individual data---whereby an individual's data are predictive of the behavior of others---generates a data externality that reduces the intermediary's cost of acquiring information. We derive the intermediary's optimal data policy and show that it preserves the privacy of the consumers' identities while providing precise information about market demand to the firms. This enables the intermediary to capture the entire value of information as the number of consumers grows large.
    Date: 2020–04
  28. By: Piasecki, Stanislaw; Urquhart, Lachlan; McAuley, Derek
    Abstract: As part of the EPSRC Defence Against Dark Artefacts (DADA) project, this paper analyses the assumptions underpinning a range of smart home cybersecurity standards. We use case studies (such as the Mirai Botnet affair) and the criminological concept of ‘routine activity theory’ to situate our analysis. Our study shows that current cybersecurity standards mainly assume smart home environments are underpinned by cloud architectures, which is a shortcoming. This paper argues that edge computing approaches, such as those typified by the Databox system, are emerging and challenge the cloud focused assumptions of these standards. In edge computing, data is stored at the edge of the network, locally on the device, which can have advantages for security, privacy and legal compliance, over cloud-based approaches. As a consequence, standards should start to reflect the increased interest in this trend to make them more aspirational and show other data architectures are possible that can benefit designers and citizens. We hope that our paper may influence researchers, policy makers and IoT stakeholders to work towards the adoption of edge computing models, to better manage external cyber-criminality threats in smart homes. We also briefly discuss that standards currently do not account for the complex nature of everyday life in the home. In addition to technical aspects, the social and interactional complexities of the home mean internal threats can emerge too.
    Date: 2020–04–13
  29. By: Mojtaba Nabipour; Pooyan Nayyeri; Hamed Jabani; Amir Mosavi
    Abstract: Prediction of stock groups' values has always been attractive and challenging for shareholders. This paper concentrates on the future prediction of stock market groups. Four groups named diversified financials, petroleum, non-metallic minerals and basic metals from Tehran stock exchange are chosen for experimental evaluations. Data are collected for the groups based on ten years of historical records. The values predictions are created for 1, 2, 5, 10, 15, 20 and 30 days in advance. The machine learning algorithms utilized for prediction of future values of stock market groups. We employed Decision Tree, Bagging, Random Forest, Adaptive Boosting (Adaboost), Gradient Boosting and eXtreme Gradient Boosting (XGBoost), and Artificial neural network (ANN), Recurrent Neural Network (RNN) and Long short-term memory (LSTM). Ten technical indicators are selected as the inputs into each of the prediction models. Finally, the result of predictions is presented for each technique based on three metrics. Among all the algorithms used in this paper, LSTM shows more accurate results with the highest model fitting ability. Also, for tree-based models, there is often an intense competition between Adaboost, Gradient Boosting, and XGBoost.
    Date: 2020–03
  30. By: Grégory Claeys; Maria Demertzis
    Abstract: This Policy Contribution was prepared for the European Parliament’s Committee on Economic and Monetary Affairs (ECON) as an input to the Monetary Dialogue of 2 December 2019 between ECON and the President of the European Central Bank. The original paper is available on the European Parliament’s webpage (here). Copyright remains with the European Parliament at all times. Four major developments have challenged the status quo and reopened the debate on...
    Date: 2019–12
  31. By: S. Nageeb Ali; Ayal Chen-Zion; Erik Lillethun
    Abstract: Information is replicable in that it can be simultaneously consumed and sold to others. We study how resale affects a decentralized market for information. We show that even if the initial seller is an informational monopolist, she captures non-trivial rents from at most a single buyer: her payoffs converge to 0 as soon as a single buyer has bought information. By contrast, if the seller can also sell valueless tokens, there exists a ``prepay equilibrium'' where payment is extracted from all buyers before the information good is released. By exploiting resale possibilities, this prepay equilibrium gives the seller as high a payoff as she would achieve if resale were prohibited.
    Date: 2020–04
  32. By: Sven Husmann; Antoniya Shivarova; Rick Steinert
    Abstract: The recent advancements in computational power and machine learning algorithms have led to vast improvements in manifold areas of research. Especially in finance, the application of machine learning enables researchers to gain new insights into well-studied areas. In our paper, we demonstrate that unsupervised machine learning algorithms can be used to visualize and classify company data in an economically meaningful and effective way. In particular, we implement the t-distributed stochastic neighbor embedding (t-SNE) algorithm due to its beneficial properties as a data-driven dimension reduction and visualization tool in combination with spectral clustering to perform company classification. The resulting groups can then be implemented by experts in the field for empirical analysis and optimal decision making. By providing an exemplary out-of-sample study within a portfolio optimization framework, we show that meaningful grouping of stock data improves the overall portfolio performance. We, therefore, introduce the t-SNE algorithm to the financial community as a valuable technique both for researchers and practitioners.
    Date: 2020–03
  33. By: Dertwinkel-Kalt, Markus; Köster, Mats; Sutter, Matthias
    Abstract: We examine whether shrouding or partitioning of a surcharge raises demand in online shopping. In a field experiment with more than 34,000 consumers, we find that consumers in the online shop of a cinema initiate a purchase process for a 3D movie more often when the 3D surcharge is shrouded, but they also drop out more often when the overall price is shown at the check-out. In sum, the demand distribution is independent of the price presentation. This result qualifies previous findings on the effectiveness of shrouding surcharges and can be rationalized through low cancellation costs.
    Keywords: Salience,Inattention,Shrouding,Price partitioning,Field experiment
    JEL: D81 C93
    Date: 2020
  34. By: Vincent Pons (Harvard Business School - Harvard University [Cambridge], National Bureau of Economic Research - National Bureau of Economic Research); Vestal Mcintyre (Harvard Kennedy School - Harvard Kennedy School)
    Abstract: Platforms such as Twitter and Facebook are widely considered important, if controversial, channels for candidates and parties around the world to communicate with citizens and win votes. While political parties in France make less use of social media than in the U.S. and other Western democracies, there is disagreement of how it will affect French democracy. But discussions of the promise and peril of social media's role in elections may miss a higher-order issue: what limited evidence exists suggests that outreach via social media has little effect on voting behavior. By contrast, a series of studies show that face-to-face canvassing has a strong potential to mobilize and persuade voters. These findings give grounds for parties to increase their canvassing efforts, and for the government to enact policies that ease the way for citizens to participate in elections.
    Date: 2020–02
  35. By: Michele Loberto; Andrea Luciani; Marco Pangallo
    Abstract: Traditional data sources for the analysis of housing markets show several limitations, that recently started to be overcome using data coming from housing sales advertisements (ads) websites. In this paper, using a large dataset of ads in Italy, we provide the first comprehensive analysis of the problems and potential of these data. The main problem is that multiple ads ("duplicates") can correspond to the same housing unit. We show that this issue is mainly caused by sellers' attempt to increase visibility of their listings. Duplicates lead to misrepresentation of the volume and composition of housing supply, but this bias can be corrected by identifying duplicates with machine learning tools. We then focus on the potential of these data. We show that the timeliness, granularity, and online nature of these data allow monitoring of housing demand, supply and liquidity, and that the (asking) prices posted on the website can be more informative than transaction prices.
    Date: 2020–04

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.