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on Payment Systems and Financial Technology |
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Issue of 2020‒01‒13
forty-one papers chosen by |
| By: | Boeing, Geoff (Northeastern University) |
| Abstract: | As the rental housing market moves online, the Internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings' representativeness could impact different communities' access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners' and researchers' ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the US and finds that they spatially concentrate and over-represent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities' online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real-time, it does not evenly represent all market segments. The Internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms like Craigslist construct new institutions with the power to shape spatial economies, human interactions, and planners' ability to monitor and respond to urban challenges. |
| Date: | 2019–07–13 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:pqgw7&r=all |
| By: | Laurent Busca (MRM - Montpellier Research in Management - UM1 - Université Montpellier 1 - UM3 - Université Paul-Valéry - Montpellier 3 - UM2 - Université Montpellier 2 - Sciences et Techniques - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier); Laurent Bertrandias (TBS - Toulouse Business School) |
| Abstract: | The digital marketing discipline is facing growing fragmentation; the proliferation of different subareas of research impedes the accumulation of knowledge. This fragmentation seems logically tied to the inherent complexity of the Internet, itself resulting from 50 years of evolution. Thus, our aim is to provide an integrative framework for research in digital marketing derived from the historical analysis of the Internet. Using practice theory and institutional theory, we outline a new type of institutional work: imprinting work. We apply this framework to the analysis of historical secondary sources. We find four cultural repertoires on the Internet (collaborative systems, traditional market systems, co-creation systems, and prosumption market systems) and describe the dynamics of imprinting work leading to their creation, showing how new systems are created by appropriating and assimilating existing cultural repertoires. We contribute to the digital marketing literature by providing a cultural framework and a theory explaining the dynamics of the creation of four cultural repertoires. Moreover, we outline three paths of potential evolution of the digital landscape. Our framework may help managers make sense of their digital strategy and navigate the various Internet systems. |
| Keywords: | Prospective,Cultural framework,Digital marketing,Historical method,Digital cultures,Institutional theory,Practice theory |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02391063&r=all |
| By: | Silvia Bartolucci; Fabio Caccioli; Pierpaolo Vivo |
| Abstract: | The Lightning Network is a so-called second-layer technology built on top of the Bitcoin blockchain to provide "off-chain" fast payment channels between users, which means that not all transactions are settled and stored on the main blockchain. In this paper, we model the emergence of the Lightning Network as a (bond) percolation process and we explore how the distributional properties of the volume and size of transactions per user may impact its feasibility. The agents are all able to reciprocally transfer Bitcoins using the main blockchain and also - if economically convenient - to open a channel on the Lightning Network and transact "off chain". We base our approach on fitness-dependent network models: as in real life, a Lightning channel is opened with a probability that depends on the "fitness" of the concurring nodes, which in turn depends on wealth and volume of transactions. The emergence of a connected component is studied numerically and analytically as a function of the parameters, and the phase transition separating regions in the phase space where the Lightning Network is sustainable or not is elucidated. We characterize the phase diagram determining the minimal volume of transactions that would make the Lightning Network sustainable for a given level of fees or, alternatively, the maximal cost the Lightning ecosystem may impose for a given average volume of transactions. The model includes parameters that could be in principle estimated from publicly available data once the evolution of the Lighting Network will have reached a stationary operable state, and is fairly robust against different choices of the distributions of parameters and fitness kernels. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1912.03556&r=all |
| By: | Gulcin Ipek Emeksiz (Anadolu University) |
| Abstract: | Corporate reputation is the value that brands give the most importance as it forms the perception of their stakeholders towards the brands, enables the brands to be separated from their rivals and to be respected. Therefore, brands try to shape the perception of their stakeholders in a positive way with the messages that they send through the traditional media continually. However, with the common usage of social media today, brands have to manage their corporate reputation on the online platforms, as well. Nevertheless, the usage of social media platforms possess some possible risks because social media has given the control to the consumers who can easily create user generated content in these platforms. Discontent consumers can express their negative experiences to brands directly on online communities such as Facebook brand fan pages and can prepare a basis for the outburst of a crisis with the support that they gain from other consumers. Therefore, brands should be prepared in advance for crisis scenarios and should maintain an effective complaint management on their Facebook brand fan pages. This paper aims to discuss what makes consumers powerful on social media and the possible risks that brands can come across on social media. Moreover, it examines how complaint management should be handled on Facebook to prevent the emergence of an online crisis. This paper will contribute to the literature of crisis communication from the aspect of social media. |
| Keywords: | Facebook, brands, online reputation management, risks, user-generated content, crises. |
| JEL: | Z00 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:9710999&r=all |
| By: | Aniruddha Dutta; Saket Kumar; Meheli Basu |
| Abstract: | In today's era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent neural network (RNN) and long short-term memory (LSTM) have been shown to perform better than traditional time series models in cryptocurrency price prediction. However, very few studies have applied sequence models with robust feature engineering to predict future pricing. in this study, we investigate a framework with a set of advanced machine learning methods with a fixed set of exogenous and endogenous factors to predict daily Bitcoin prices. We study and compare different approaches using the root mean squared error (RMSE). Experimental results show that gated recurring unit (GRU) model with recurrent dropout performs better better than popular existing models. We also show that simple trading strategies, when implemented with our proposed GRU model and with proper learning, can lead to financial gain. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1912.11166&r=all |
| By: | Bart van Ark; Klaas de Vries; Abdul Erumban |
| Abstract: | This paper reviews the latest evidence on productivity growth by industry and innovation competencies by occupation to observe whether, beneath the productivity slowdown of the past decade in both the European Union and the United States, signs can be detected of structural performance improvements due to digital transformation. We find that in the United States, the digital-producing sector has continued to contribute strongly to aggregate productivity in recent years. While labour productivity growth in the US was only 0.6 percent from 2013-2017, as much as 0.5 percentage point (or 86 percent) was coming from digital-producing industries representing only 8.2 percent of US GDP. Other industries, which account for the remaining 92 percent of the US economy, including some of the most digital intensive-using industries, have seen a dramatic decline in their contribution to productivity growth. In the European Union, the digital-producing sector has seen a strong decline in its contribution to productivity growth, which by 2013-2017 was only one third of the US contribution at 0.15 percentage points. However, the most digital intensive-using industries contributed 4 times as much to labor productivity as in the United States, driving overall labour productivity growth from 2013-2017 up to 0.9 percentage point – 0.3 percentage points higher than in the US. A positive factor, both in the EU and in the US, is that total factor productivity (TFP) growth in the most intensive digital-producing industries, notably trade and business services has improved. Digital intensiveusing manufacturing industries generally contribute less to productivity than digital intensive-using services, partly because of slower productivity growth and partly because of their smaller size. A novel measure of innovation competencies by occupation shows that, when applied to industries, those industries with the highest competencies, also show positive productivity contributions, and the most intensive digital-using industries are strongly represented in this category. Overall, while the evidence is still thin due to time lags in the data, there are signs of positive contributions to productivity growth related to digital transformation even though those effects are still not widespread observable across the economy. |
| JEL: | O40 O47 O30 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:euf:dispap:119&r=all |
| By: | Saha, Satabdi; Maiti, Tapabrata |
| Abstract: | Rapid advancement of the Internet and Internet of Things have led to companies generating gigantic volumes of data in every field of business. Big data research has thus become one of the most prominent topic of discussion garnering simultaneous attention from academia and industry. This paper attempts to understand the significance of big data in current scientific research and outline its unique characteristics, otherwise unavailable from traditional data sources. We focus on how big data has altered the scope and dimension of data science thus making it severely interdisciplinary. We further discuss the significance and opportunities of big data in the domain of social science research with a scrutiny of the challenges previously faced while using smaller datasets. Given the extensive utilization of big data analytics in all forms of socio-technical research, we argue the need to critically interrogate its assumptions and biases; thereby advocating the need for creating a just and ethical big data world. |
| Date: | 2019–12–29 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:ft27y&r=all |
| By: | Baranes, Edmond; Cortade, Thomas; Cosnita-Langlais, Andreea |
| Abstract: | We study the impact of cost savings on the outcome of horizontal mergers between two-sided platforms. We consider four symmetrically differentiated platforms located equidistantly on the unit circle and competing in membership fees. Users on both sides single-home, and we allow for both positive and negative cross-group externalities. We find that the impact of merger cost savings on prices is generally not monotonic, and that synergies are necessary for horizontal platform mergers to be Pareto-improving. Furthermore, the merger may benefit users on one side while harming users on the opposite side, which raises some interesting questions for the enforcement of merger control on two-sided markets. |
| Keywords: | horizontal merger, two-sided markets, cost savings, indirect network effects, merger control |
| JEL: | D43 K21 L41 |
| Date: | 2019–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:97459&r=all |
| By: | Leonardo Gambacorta; Yiping Huang; Han Qiu; Jingyi Wang |
| Abstract: | This paper compares the predictive power of credit scoring models based on machine learning techniques with that of traditional loss and default models. Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, we test the performance of different models to predict losses and defaults both in normal times and when the economy is subject to a shock. In particular, we analyse the case of an (exogenous) change in regulation policy on shadow banking in China that caused lending to decline and credit conditions to deteriorate. We find that the model based on machine learning and non-traditional data is better able to predict losses and defaults than traditional models in the presence of a negative shock to the aggregate credit supply. One possible reason for this is that machine learning can better mine the non-linear relationship between variables in a period of stress. Finally, the comparative advantage of the model that uses the fintech credit scoring technique based on machine learning and big data tends to decline for borrowers with a longer credit history. |
| Keywords: | fintech, credit scoring, non-traditional information, machine learning, credit risk |
| JEL: | G17 G18 G23 G32 |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:834&r=all |
| By: | Islam, Mazharul; Habes, Essam M.; Alam, Md. Mahmudul (Universiti Utara Malaysia) |
| Abstract: | The purpose of this study is to uncover the impacts of mobile phone use on the performance of micro-enterprises (MEs) in Bangladesh, a developing country where the total number of mobile subscriptions reached around 131.38 million by the end of June in 2016 with penetration rate of 81 percent. Data were collected from owners of MEs through face to face interview. A multivariate analysis and SPSS macro developed by Preacher and Hayes were used as statistical techniques to assess the effects of mobile phone use. Results of the study indicate that micro-enterprises which owners were using mobile phone were having significantly greater benefits and financial performance compared to counterparts. A significant direct relationship between mobile phone use, and social capital and ME‟s financial and non-financial performances was found. A further investigation revealed that financial performance is also indirectly related to social capital and quality and enterprise processes, which are significantly influenced by mobile phone usage. Therefore social capital and non-financial business performances are involved in the mediational process between the financial performance of MEs and use of mobile phone. The novelty of this research lies in the establishment of, for the first time, high level statistical relationship between the use of mobile phone, its mediating factors and financial performance of MEs. The findings will assist micro-entrepreneurs and policy makers in taking right courses of action that make the implementation of this device more effective. |
| Date: | 2019–06–15 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:vfk6y&r=all |
| By: | Lobo-Pulo, Audrey E. (The Australian Public Service); Ribas Fernandes, José J. F. (Canada Energy Regulator); Hester, Annette; Hum, Ryan J. |
| Abstract: | As new digital platforms emerge and governments look at new ways to engage with citizens, there is an increasing awareness of the role these platforms play in shaping public participation and democracy. We examine three case studies on digital engagement (vTaiwan, We the People, and social media), and discuss key considerations for effective public engagement in the digital age: Empowerment, time to deliberate, transparency, useful data, consensus, and dynamic engagement. We hope that these serve as a basis for constructing meaningful engagement. |
| Date: | 2019–08–30 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:h2vc4&r=all |
| By: | Asian Business Consortium; Hasan, Mohammad Abid |
| Abstract: | This study discusses the amalgamation of Technology Acceptance Model with the underlying 8 factors to investigate the intensity of users’ intentions towards 4G adoptions in Bangladesh. So, it has tried to list all the latest released facilities and the adoption tendency. A sample size of 119 respondents with random sampling as well as in-depth interviewing methods have used and collected primary data from different institutions across Bangladesh with a self-administered field survey questionnaire as well as having secondary sources from different webs, books, journals, annual reports, and unpublished research works. The SPSS and the 5-Point-Likert scale have used to validate the results. Also the tests include correlation, multiple regression technique, ANOVA, and co-efficient of variance have used. The study indicates that 36% respondents are positively prone to 4G (r2=.362, f=5.531, p=.000). Besides, among the 8 factors, the image has the greatest influence on it (β=.249, t=2.558, p=.012) followed by the variety of services (β=.189, t=1.608, p=.111), the perceived enjoyment (β=.148, t=1.803, p=0.109), the perceived ease of use (β=0.108, t=0.916, p=0.368), the personal Innovativeness (β=.098, t=.934, p=.352), and the network effects (β=.002, t=.025, p=.980). Conversely, the price (β=-.027, t=-.406, p=.685) and the perceived usefulness (β=-.069, t=-.629, p=.303) have a rare impact on it. However, with the outcomes, the telecommunication services providers will be able to accelerate the wining strategies at different levels in Bangladesh. As there are few studies published in this regard, future research is necessary to investigate the financial and industrial implications associated with it. |
| Date: | 2019–01–28 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:hft45&r=all |
| By: | Boeing, Geoff (Northeastern University) |
| Abstract: | Urban planning and morphology have relied on analytical cartography and visual communication tools for centuries to illustrate spatial patterns, propose designs, compare alternatives, and engage the public. Classic urban form visualizations – from Giambattista Nolli’s ichnographic maps of Rome to Allan Jacobs’s figure-ground diagrams of city streets – have compressed physical urban complexity into easily comprehensible information artifacts. Today we can enhance these traditional workflows through the Smart Cities paradigm of understanding cities via user-generated content and harvested data in an information management context. New spatial technology platforms and big data offer new lenses to understand, evaluate, monitor, and manage urban form and evolution. This paper builds on the theoretical framework of visual cultures in urban planning and morphology to introduce and situate computational data science processes for exploring urban fabric patterns and spatial order. It demonstrates these workflows with OSMnx and data from OpenStreetMap, a collaborative spatial information system and mapping platform, to examine street network patterns, orientations, and configurations in different study sites around the world, considering what these reveal about the urban fabric. The age of ubiquitous urban data and computational toolkits opens up a new era of worldwide urban form analysis from integrated quantitative and qualitative perspectives. |
| Date: | 2019–10–01 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:vhrdc&r=all |
| By: | Svatopluk Kapounek; Zuzana Kucerová |
| Abstract: | The paper employs a dynamic market-wide herding behavior measure of 117,166 lending-based campaigns in 119 online platforms in 37 countries that explores whether lenders follow each other in the whole crowdfunding market, within the groups of top platforms, within the specific category or platform, and within the specific category in the specific platform. We show that herding behavior plays an important signaling role in reducing opportunity costs if the auction does not receive enough monetary bids. Additionally, our threshold models identify significant herding behavior after funding goals are raised and highlight the controversial effects of signaling mechanisms on adverse selection in crowdfunding markets. |
| Keywords: | asymmetric information, crowdfunding, herding behavior, overfunding, peer-to-peer lending, signaling |
| JEL: | C55 G21 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7973&r=all |
| By: | Jens Suedekum; Nicole Woessner |
| Abstract: | We estimate the impact of a recent digital automation technology - industrial robotics - on the distribution of productivity and markups within industries. Our empirical analysis combines data on the industry-level stock of industrial robots with firms' balance sheet data for six European countries from 2004 to 2013. We find that robots dis-proportionally raise productivity in those firms that are already most productive to begin with. Those firms are able to increase their markups, while markups tend to decline for less profitable firms within the same industry, country and year. We also show that industrial robots contribute to the falling aggregate labour income share through a rising concentration of industry sales. In short, our paper suggests that robots boost the emergence of superstar firms within European manufacturing, and thereby shifts the functional income distribution away from wages and towards profits. |
| JEL: | D4 L11 O33 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:euf:dispap:118&r=all |
| By: | Brynjolfsson, Erik; Collis, Avinash; Diewert, W. Erwin; Eggers, Felix; Fox, Kevin J. |
| Abstract: | The welfare contributions of the digital economy, characterized by the proliferation of new and free goods, are not well-measured in our current national accounts. We derive explicit terms for the welfare contributions of these goods and introduce a new metric, GDP-B which quantifies their benefits, rather than costs. We apply this framework to several empirical examples including Facebook and smartphone cameras and estimate their valuations through incentive-compatible choice experiments. For example, including the welfare gains from Facebook would have added between 0.05 and 0.11 percentage points to GDP-B growth per year in the US. |
| Date: | 2019–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:sptfu&r=all |
| By: | CANDRA FAJRI ANANDA (Supervisory Board of Bank Indonesia); ABDUL MANAP PULUNGAN (Supervisory Board of Bank Indonesia); RAHMIA HASNIASARI (Supervisory Board of Bank Indonesia) |
| Abstract: | The financial technology (fintech) has a fundamental impact on the economy, particularly for emerging economies through improving financial inclusion and reducing the poverty level, unemployment, and income inequality (Furche et al, 2017). The rapid development of fintech should not be seen as a favourable condition alone. Several research argue that this phenomenon might impact to the existing financial industry, bank for instance (Wong, 2017; Temelkov, 2018) and at some point it will possibly run beyond the reach of regulation. Thus, regulator needs to start right to minimize the potential drawback of the fintech development including the potential disruption to the financial stability.This research employs the ?separating apples from oranges? framework from Minto et al (2017) that consists of four filters in categorizing fintech and aims to: (1) figure out the most significant part to be regulated in the fintech industry in Indonesia; (2) give an advisable input to central bank in mitigating the issue without burden the growth of fintech. It is interesing to have a further look on the fintech development in Indonesia since it gave significant contribution in the national economy. As an ecosystem of fintech, Delloitte (2016) revealed that digital economy in Indonesia led to the 2% annual GDP and 80% growth of small-medium enterprises (SME). |
| Keywords: | financial technology, central bank, financial regulator, regulation, regulating financial technology |
| JEL: | E58 O10 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:9912270&r=all |
| By: | Melissa Liborio Zapata (SYMME - Laboratoire SYstèmes et Matériaux pour la MEcatronique - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc, LISTIC - Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc); Lamia Berrah (LISTIC - Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc); Laurent Tabourot (SYMME - Laboratoire SYstèmes et Matériaux pour la MEcatronique - USMB [Université de Savoie] [Université de Chambéry] - Université Savoie Mont Blanc) |
| Abstract: | Companies, and especially manufacturers, are facing today a truly complex scenario, with technology developing at a fast speed and demanding a digital transformation to face the many challenges. The aim of this paper then is to assess the fitness of digital maturity models in their role of assisting manufacturers of smart products in their digital transformation journeys and propose a set of recommendations to improve the usability of the tool in this scenario. To achieve this, an analysis of a selection of seven maturity models is performed, applying several design principles to the specific case of manufacturers of smart products. According to the most relevant findings, the recommendations suggested for the models are related to the need for a wider scope for the tool, a prescriptive condition, and a broad business perspective in the definition of their dimensions. Validation of the applicability of the recommendations in the small and medium enterprises scenario is also presented through an illustration of the manufacturers of the Arve Valley. |
| Keywords: | digital transformation,small and medium enterprises,industry 40,maturity models,Smart products |
| Date: | 2019–11–20 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02389603&r=all |
| By: | VALERIA VANNONI (University of Perugia) |
| Abstract: | Invoice trading has recently emerged in Italy as an alternative instrument for small and medium-sized enterprises financing. It represents a form of credit transfer, with the particularity that transactions take place via online platforms. In Italy, as of 30 June 2018, six platforms are active: Cashinvoice, Credimi, CashMe, Crowdcity, Fifty, Workinvoice. They are distinguished on the basis of some operational characteristics, mainly due to the mechanism of credit transfer (marketplace, supply chian finance, direct purchase). This work aims to deepen the typical profile of firms that, in this initial phase of the phenomenon, turn to the invoice trading platforms. The verification uses the tool of the unstructured questionnaire in ten points. The survey took place via email in the period January-March 2019. We received feedback from all the platforms, even if two of them communicated the impossibility to provide informations due to confidentiality issues. Collected answers show a very high number of applications, but it still generally corresponds to a limited success rate; among the main reasons for rejection, a low creditworthiness profile of applicant is reported (followed by: default risk; fraud risk; prejudicial information on firms and shareholders; pricing; invoice amount). Firms are concentrated in the northern regions of the country; the most represented sectors are manufacturing and wholesale trade. Customers are mainly mature firms, not in the start-up phase. The average value of credit is around 74 th. Euros, with an outlier platform. Operations proceed with no criticalities: only one respondents underlines that 5.42% of invoices has had a serious delay in payment by debtor. |
| Keywords: | Small Business financing; Alternative finance; Invoice trading. |
| JEL: | G23 G30 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:9912115&r=all |
| By: | Paola Soto Herrera (Rochester Institute of Technology); Rudy Pugliese (Rochester Institute of Technology) |
| Abstract: | The present study investigated long-distance relationships and media use. It surveyed individuals involved in long distance relationships to determine which media are most often used, whether they are more likely to use rich or lean media, and whether family, friends, and romantic partners differ in their selection of media. Instant Messaging, social media (Instagram, Facebook, Twitter, Snapchat), telephone (cellular, mobile, or landline), online video chat, online audio chat, SMS, and regular mail were the most popular media. Romantic partners were more likely than either family or friends to use Instant messaging, the telephone, audio chat, and video chat. Results provide support for Rich Media Theory within the context of long-distance relationships. Additional findings are presented. |
| Keywords: | media, long-distance relationships |
| JEL: | L82 D83 J24 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:9711702&r=all |
| By: | Michael, Friedrich; Ignatov, Dmitry I. |
| Abstract: | This papers discusses the scientific and practical perspectives of using general game playing in business-to-business price negotiations as a part of Procurement 4.0 revolution. The status quo of digital price negotiations software,which emerged from intuitive solutions to business goals and refereed to as electronic auctions in industry, is summarized in scientific context. Description of such aspects as auctioneers’ interventions, asymmetry among players and time-depended features reveals the nature of nowadays electronic auctions to be rather termed as price games. This paper strongly suggests general game playing as the crucial technology for automation of human rule setting in those games. Game theory, genetic programming, experimental economics and AI human player simulation are also discussed as satellite topics. SIDL-type game descriptions languages and their formal game theoretic foundations are presented. |
| Keywords: | Procurement 4.0; Artificial Intelligence; General Game Playing; Game Theory; Mechanism Design; Experimental Economics; Behavioral Eco-nomics; z-Tree; Cognitive Modeling; e-Auctions; barter double auction; B-to-B Price Negotiations; English Auction; Dutch auction; Sealed-Bid Auction; Industry 4.0 |
| JEL: | C63 C72 C90 D04 D44 |
| Date: | 2019–09–23 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:97313&r=all |
| By: | Eva Malovics (University of Szeged); Beata Vajda (University of Szeged) |
| Abstract: | Scientific research on doctor-patient communication dates back for decades, and the current situation of its practical realization has been criticized in many studies at both nation and international level and is generally considered inefficient. Doctor-patient communication, embedded within the framework of the complex health care system is itself a complex subject. According to experts, in a networked society, the digitalization of information and communication changes the way people communicate and cooperate and predict significant changes in communication. The knowledge asymmetry between doctors and patients has decreased with the use of the Internet. Accordingly, our research question is how this phenomenon appears in doctor-patient communication in a Hungarian setting.In accordance with the complexity of the topic, we chose to use in-depth interviews and focus group interviews as a research method and analyzed them using the Grounded Theory method. Two focus groups were conducted in which both actors, doctors and patients appeared, and we conducted in-depth interviews with four doctors and ten patients. Subjects, in accordance with the Grounded Theory method, were selected by quality sampling. We had an interview guideline, but we deviated from it from time to time, which is allowed by our chosen research method.The characteristics of communication were interpreted according to the social psychological and functional model. According to our results, the traditional communication culture of healthcare is dominant in communication, doctors adhere to this, which today leads to a decrease in patient trust, which is attempted to be managed by patients with different strategies. |
| Keywords: | healthcare, communication, grounded theory |
| JEL: | I12 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:9712163&r=all |
| By: | Ilya Musabirov; Evgeniya G. Nim (National Research University Higher School of Economics) |
| Abstract: | The article analyzes how Russian students interpret and practice digital technologies of self-tracking (fitness trackers, apps and wearables), that allow to collect biometric and activity data. It is based on the results of reflective thematic analysis of students’ essays on this topic. How do students describe their experience in using self-tracking technologies? What discourses of self-tracking are represented in their essays? How do they imagine the digital future and further development of the systems of self-surveillance? The research demonstrated that many students have certain experience with quantified self-tracking, whereas some tend to limit it or refused from it for some reasons. Based on the students’ stories (former and active users), the author offers to distinguish three styles of self-tracking: ‘gamer’, ‘manager’ and ‘transformer’. A ‘gamer’ is looking for the feelings of thrill, pleasure and novelty; a ‘manager’ aims at putting one’s head and life in order; a ‘transformer’ wants to change one’s life and mind radically. In reality any self-tracker combines all three roles, though one of them might dominate. According to the students, the existing technologies of self-measuring cannot give strong enough motivation for self-optimization, but in the future their effectiveness may increase. This study also resulted in defining four types of discourse on self-tracking: ‘progressivist’, ‘pragmatic’, ‘critical’ and ‘anti-utopian’. They represent the differences in conceptualization of self-tracking as a cultural phenomenon. Some students are prone to optimistic or balanced evaluation of the potential of self-tracking technologies; others focus on risks and hazards of ‘datafication’ of people and social life. The outcomes of the study develop the previous research on styles of quantified self-tracking, providing additional analysis of the reflections of (non-)users, concerning self-tracking as a cultural phenomenon. |
| Keywords: | self-tracking, digital technologies, «Quantified self» (QS), Russian students |
| JEL: | L82 O33 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:91/soc/2019&r=all |
| By: | Benkovich, Nikita; Dedenok, Roman; Golubev, Dmitry |
| Abstract: | In this paper, we introduce DeepQuarantine (DQ), a cloudtechnology to detect and quarantine potential spam messages. Spam at-tacks are becoming more diverse and can potentially be harmful to emailusers. Despite the high quality and performance of spam filtering sys-tems, detection of a spam campaign can take some time. Unfortunately,in this case some unwanted messages get delivered to users. To solve thisproblem, we created DQ, which detects potential spam and keeps it ina special Quarantine folder for a while. The time gained allows us todouble-check the messages to improve the reliability of the anti-spam so-lution. Due to high precision of the technology, most of the quarantinedmail is spam, which allows clients to use email without delay. Our solutionis based on applying Convolutional Neural Networks on MIME headersto extract deep features from large-scale historical data. We evaluatedthe proposed method on real-world data and showed that DQ enhancesthe quality of spam detection. |
| Keywords: | spam filtering; spam detection; machine learning; deeplearning; cloud technology |
| JEL: | C45 M15 |
| Date: | 2019–09–23 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:97311&r=all |
| By: | hadi, leony |
| Abstract: | The development of digital economy in Indonesia/ Leony/130216039/kp B |
| Date: | 2019–03–11 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:2nuek&r=all |
| By: | Nicola Uras; Lodovica Marchesi; Michele Marchesi; Roberto Tonelli |
| Abstract: | This paper studies how to forecast daily closing price series of Bitcoin, using data on prices and volumes of prior days. Bitcoin price behaviour is still largely unexplored, presenting new opportunities. We compared our results with two modern works on Bitcoin prices forecasting and with a well-known recent paper that uses Intel, National Bank shares and Microsoft daily NASDAQ closing prices spanning a 3-year interval. We followed different approaches in parallel, implementing both statistical techniques and machine learning algorithms. The SLR model for univariate series forecast uses only closing prices, whereas the MLR model for multivariate series uses both price and volume data. We applied the ADF -Test to these series, which resulted to be indistinguishable from a random walk. We also used two artificial neural networks: MLP and LSTM. We then partitioned the dataset into shorter sequences, representing different price regimes, obtaining best result using more than one previous price, thus confirming our regime hypothesis. All the models were evaluated in terms of MAPE and relativeRMSE. They performed well, and were overall better than those obtained in the benchmarks. Based on the results, it was possible to demonstrate the efficacy of the proposed methodology and its contribution to the state-of-the-art. |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2001.01127&r=all |
| By: | Wijaya, Martin Besaliel |
| Abstract: | Review of The Developpment of Digital Economy In Indonesia by Ahmad Zafrullah, Lucia Endang and Radita Gora. The original writers state some fact of interesting development that will effect the development of digital economy in Indonesia and why it is important to us. |
| Date: | 2019–03–06 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:pcjz3&r=all |
| By: | March, Christoph |
| Abstract: | Artificial intelligence (AI) is starting to pervade the economic and social life rendering strategic interactions with artificial agents more and more common. At the same time, experimental economic research has increasingly employed computer players to advance our understanding of strategic interaction in general. What can this strand of research teach us about an AI-shaped future? I review 90 experimental studies using computer players. I find that, in a nutshell, humans act more selfishly and more rational in the presence of computer players, and they are often able to exploit these players. Still, many open questions prevail. |
| Keywords: | Experiment,Robots,Computer players,Survey |
| JEL: | C90 C92 O33 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bamber:154&r=all |
| By: | Kelty-Stephen, Damian (Grinnell College) |
| Abstract: | The milkshake acting like a computer is an idea that appeared on my stupid professional website ten years ago when I was first struggling to begin a straight-faced professional, academic “web presence.” This text here has no new empirical evidence and is not an attempt to develop theory in any way. It is an attempt to thank the digital community of scholars that has kept me afloat for these past 10 years by answering some of the questions and concerns that the sea of digits has thrown my way. I aim here for a format that is hopefully easier to read and more open to discussion than much of the peer-reviewed literature. I would ask that people read this document in the spirit of open review. And if you have any comments, questions, or thoughts, I’m asking right now for you to please share them to help me make the future of milkshakes acting like computers ever better than the milkshakes past. |
| Date: | 2018–08–14 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:ztgyr&r=all |
| By: | Nick James; Max Menzies; Jennifer Chan |
| Abstract: | We propose a new approach using the MJ$_1$ semi-metric, from the more general MJ$_p$ class of semi-metrics \cite{James2019}, to detect similarity and anomalies in collections of cryptocurrencies. Since change points are signals of potential risk, we apply this metric to measure distance between change point sets, with respect to returns and variance. Such change point sets can be identified using algorithms such as the Mann-Whitney test, while the distance matrix is analysed using three approaches to detect similarity and identify clusters of similar cryptocurrencies. This aims to avoid constructing portfolios with highly similar behaviours, reducing total portfolio risk. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1912.06193&r=all |
| By: | McGaughey, Ewan (King's College, London) |
| Abstract: | Will the internet, robotics and artificial intelligence mean a ‘jobless future’? A recent narrative, endorsed by prominent tech-billionaires, says we face mass unemployment, and we need a basic income. In contrast, this article shows why the law can achieve full employment with fair incomes, and holidays with pay. Universal human rights, including the right to ‘share in scientific advancement and its benefits’, set the proper guiding principles. Three distinct views of the causes of unemployment are that it is a ‘natural’ phenomenon, that technology may propel it, or that it is social and legal choice: to let capital owners restrict investment in jobs. Only the third view has any credible evidence to support it. Technology may create redundancies, but unemployment is an entirely social phenomenon. After World War Two, 42% of UK jobs were redundant but social policy maintained full employment, and it can be done again. This said, transition to new technology, when markets are left alone, can be exceedingly slow: a staggering 88% of American horses lost their jobs after the Model T Ford, but only over 45 years. Taking lessons from history, it is clear that unemployment is driven by inequality of wealth and of votes in the economy. To uphold human rights, governments should reprogramme the law, for full employment, fair incomes and reduced working time, on a living planet. Robot owners will not automate your job away, if we defend economic democracy. |
| Date: | 2019–10–15 |
| URL: | http://d.repec.org/n?u=RePEc:osf:lawarx:udbj8&r=all |
| By: | Dingli Xi; Timothy Ian O'Brien; Elnaz Irannezhad |
| Abstract: | This study investigates the socio-demographic characteristics that individual cryptocurrency investors exhibit and the factors which go into their investment decisions in different Initial Coin Offerings. A web based revealed preference survey was conducted among Australian and Chinese blockchain and cryptocurrency followers, and a Multinomial Logit model was applied to inferentially analyze the characteristics of cryptocurrency investors and the determinants of the choice of investment in cryptocurrency coins versus other types of ICO tokens. The results show a difference between the determinant of these two choices among Australian and Chinese cryptocurrency folks. The significant factors of these two choices include age, gender, education, occupation, and investment experience, and they align well with the behavioural literature. Furthermore, alongside differences in how they rank the attributes of ICOs, there is further variance between how Chinese and Australian investors rank deterrence factors and investment strategies. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1912.03311&r=all |
| By: | Siciliani, Paolo (Bank of England and UCL Laws); Giovannetti, Emanuele (Anglia Ruskin University & Hughes Hall, University of Cambridge) |
| Abstract: | The paper develops a static model to explore how, under platform competition, heterogeneous levels of switching costs can give rise to an incumbency advantage. The key condition required for the coexistence of both platforms on the market, to have effective competition, relies on the relative strength of switching costs over the network effects. Only when switching costs are stronger than cross-group network benefits is market tipping avoided. The same condition also underpins the presence of a material incumbency advantage vis-à-vis the entrant platform. Therefore, regulatory intervention aimed at facilitating switching, for example by imposing data portability, might worsen entry condition as the incumbent platform is less accommodative. Besides the standard configuration with exogenous singlehoming, we also fully characterise the model with endogenous multihoming on both sides. Partial multihoming occurs only on one side, the one with comparatively lower switching costs. However, in contrast to the seminal ‘competition bottleneck’ model, on the opposite side, where singlehoming arises endogenously, agents face higher prices than under exogenous singlehoming. Therefore, the incumbent platform would normally opt for this regime, whereas we show that the entrant is basically indifferent between the two. |
| Keywords: | two-sided markets; platform competition; switching costs; multihoming |
| JEL: | L11 L13 |
| Date: | 2019–12–20 |
| URL: | http://d.repec.org/n?u=RePEc:boe:boeewp:0839&r=all |
| By: | Van Roy, Vincent; Vertesy, Daniel; Damioli, Giacomo |
| Abstract: | Economic activities based on the invention, production and distribution of artificial intelligence (AI) technologies have recently emerged worldwide. Yet, little is known about the innovative activities, location and growth performance of AI innovators. This chapter aims to map and analyse the global innovative landscape of AI by exploring 155,000 patents identified as AI-related by means of text-mining techniques. It highlights the emergence and evolution of AI technologies and identifies AI hotspots across the world. It explores the scale and pervasiveness of AI activities across sectors, and evaluates the economic performance of AI innovators using firm accounting information. Finally, it assesses recent trends in venture capital investments towards AI as financial support to promising AI startups. Findings of this chapter reveal a tremendous increase in AI patenting activities since 2013 with a significant boom in 2015-2016. While most of AI patenting activities remain concentrated in the sectors of software programming and manufacturing of electronic equipment and machinery, there are clear signs of cross-fertilisation towards (non-tech) sectors. The market of AI patenting firms is very vibrant and characterised by a large increase of new and small players with economic performances above industry average. This trend is also reflected by the recent increase in venture capital towards AI startups. |
| Keywords: | Artificial intelligence,innovation,patents,robotics |
| JEL: | O31 O33 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:433&r=all |
| By: | Yupawan Vannavanit (Kasetsart University); Sirirat Kosakarika (Kasetsart University) |
| Abstract: | The paper aims to study the level of customer satisfaction in using Shopee application for shopping in Thailand. Shopee is the largest retail e-commerce in Southeast Asia. The study is based Electronic Service Quality Model (E-S-QUAL) and electronic recovery service quality (E-Recs-QUAL). 100 online questionnaires have been distributed to Shoppe customers who had an experience in using Shopee application. The study result reveals that most respondents are single and female with an average age of 21. The level of satisfaction is high for all dimensions. To be more specific, the highest level of satisfaction is witnessed in system availability while privacy, efficiency, responsiveness, fulfillment and contact share similar satisfactory level of high. The lowest is compensation. The study also reveals that there are differences in placing important to those dimensions, which can be divided into 3 categories. High degree of importance efficiency and fulfillment while moderate degree of significance consists of privacy system availability responsiveness. The least importance factors are contact and compensation. The study suggests that the quality of fulfillment should be improved because of there being high level of importance from customer perspective with moderate satisfactory level. |
| Keywords: | Shopee Application, Satisfaction, Thai Customer |
| JEL: | M31 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:9712140&r=all |
| By: | YANO Makoto |
| Abstract: | Abstract in English is not available. |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:eti:rpdpjp:19024&r=all |
| By: | Eric J. Bartelsman |
| Abstract: | This paper reviews briefly the scientific literature on new technologies and future trends and on how and why the technologies may affect production, labour relations, and living conditions. Recent evidence points towards a slowing of productivity growth and a growing sense of unease in EU households concerning the impact of future economic developments. The paper argues that new digital technologies not only have the potential to change economic interactions, but also change the framework needed by economists to analyse the supply side of the economy. With appropriate policies, the technological advances can continue apace and will translate into productivity growth, so that households can contribute to and benefit from the new goods and services that the future economy will produce. |
| JEL: | D40 E31 L51 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:euf:dispap:113&r=all |
| By: | Simon Amez; Suncica Vujic; Lieven De Marez; Stijn Baert (-) |
| Abstract: | To study the causal impact of smartphone use on academic performance, we collected—for the first time worldwide—longitudinal data on students’ smartphone use and educational performance. For three consecutive years we surveyed all students attending classes in eleven different study programmes at two Belgian universities on general smartphone use and other drivers of academic achievement. These survey data were merged with the exam scores of these students. We analysed the resulting data by means of panel data random effects estimation controlling for unobserved individual characteristics. A one standard deviation increase in overall smartphone use results in a decrease of 0.349 points (out of 20) and a decrease of 2.616 percentage points in the fraction of exams passed. |
| Keywords: | smartphone use, academic performance, longitudinal data, causality |
| JEL: | I23 J24 |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:rug:rugwps:19/986&r=all |
| By: | JOURNALS, INTERNATIONAL SCIENTIFIC Available online at https://int-scientific-journals.com; Mehta, Abhijit; Degi, Faisal Rafik |
| Abstract: | The main purpose of this paper is to specify the thoughts of the modern era paradigm on Total quality management "TQM" and its application in the field of education. This research starts with the background theory/ literature review and then outline the result of the study, conducted by the students to obtain the different perspective on Total quality management in education. This sector needs improvement. It means that adoption of TQM in education gives you an excellent result in the overall system. As we can say that adoption of total quality management in education can ascertain more effective institutional change with success. As a result, this research proposed a theory which is obtained from TQM like institutional change environment, sustainable success, and innovation which express the relationship between the educational institutions and the role of total quality management. Available online at https://int-scientific-journals.com |
| Date: | 2019–02–28 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:hua4k&r=all |
| By: | Ekaterina Semenova (National Research University Higher School of Economics); Ekaterina Perevoshchikova (National Research University Higher School of Economics); Alexey Ivanov (National Research University Higher School of Economics); Mikhail Erofeev (Lomonosov Moscow State University) |
| Abstract: | Machine learning (ML) affects nearly every aspect of our lives, including the weightiest ones such as criminal justice. As it becomes more widespread, however, it raises the question of how we can integrate fairness into ML algorithms to ensure that all citizens receive equal treatment and to avoid imperiling society’s democratic values. In this paper we study various formal definitions of fairness that can be embedded into ML algorithms and show that the root cause of most debates about AI fairness is society’s lack of a consistent understanding of fairness generally. We conclude that AI regulations stipulating an abstract fairness principle are ineffective societally. Capitalizing on extensive related work in computer science and the humanities, we present an approach that can help ML developers choose a formal definition of fairness suitable for a particular country and application domain. Abstract rules from the human world fail in the ML world and ML developers will never be free from criticism if the status quo remains. We argue that the law should shift from an abstract definition of fairness to a formal legal definition. Legislators and society as a whole should tackle the challenge of defining fairness, but since no definition perfectly matches the human sense of fairness, legislators must publicly acknowledge the drawbacks of the chosen definition and assert that the benefits outweigh them. Doing so creates transparent standards of fairness to ensure that technology serves the values and best interests of society |
| Keywords: | Artificial Intelligence; Bias; Fairness; Machine Learning; Regulation; Values; Antidiscrimination Law; |
| JEL: | K19 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:93/law/2019&r=all |
| By: | Yixiao ZHOU (Crawford School of Public Policy, Australian National University); Rod TYERS (Business School, University of Western Australia; Research School of Economics and Centre for Applied Macroeconomic Analysis (CAMA), Australian National University) |
| Abstract: | Relative wages and the share of total value added accruing to low-skill workers have declined during the past three decades, among both OECD countries and large developing countries. The primary beneficiary until recently has been skill, the supply of which has risen as education investment has increased. The rise in artificial intelligence (AI)-driven automation suggests that declines in value added shares accruing to low-skill workers will continue. Indeed, AI-driven automation creates an impulse for diminished labor market performance by low-skill workers throughout the world but most prominently in high-fertility, relatively youthful regions with comparatively strong growth in low-skill labor forces. The implied bias against such regions will therefore enhance emigration pressure. This paper offers a preliminary analysis of these effects. Central to the paper is a model of the global economy that includes general demography and real wage sensitive bilateral migration behavior, which is used to help quantify potential future growth in real wage disparities and the extent, direction and content of associated migration flows. Overall, global wage inequality is increased by expanded skilled migration, primarily because of large increases in skilled wage premia that arise in developing regions of origin. Inter-regional divergences in skilled wages are reduced, however, due to the additional skilled labour market arbitrage opportunities offered by more open migration policies. |
| Keywords: | Automation, demographic change, migration incentives, labor markets and economic growth |
| JEL: | C68 E22 E27 F21 F43 J11 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:uwa:wpaper:19-19&r=all |