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on Information and Communication Technologies |
| By: | Francesca Checchinato (Dept. of Management, Università Ca' Foscari Venice); Lala Hu (Dept. of Management, Università Ca' Foscari Venice) |
| Abstract: | Since Internet has been seen as global, few studies have examined the influence of the context in the digital marketing strategies. This paper wants to contribute on the debate about standardization-adaptation, focusing on the digital strategies, defining how companies adapt them to the Chinese market identifying the drivers that call for this adaptation. China is selected because it is a contradictory market: more advanced than the Western one but also with many restrictions. We carry out a qualitative research based on interviews with nine key informants operating in the digital Chinese market with different roles. Our findings suggest that there are drivers that force companies to create an online presence and drivers that impact the digital localization. The main adaptations concern international distribution strategy and communication related to contents and media as well as organization. |
| Keywords: | China, digital marketing, e-commerce, internationalization, Internet. |
| JEL: | M31 |
| Date: | 2018–09 |
| URL: | http://d.repec.org/n?u=RePEc:vnm:wpdman:160&r=ict |
| By: | Julie Hooft Graafland (OECD) |
| Abstract: | This paper provides a synthesis of the literature on and recent trends in new technologies and its effect on 21st century children (0-18 years old). It begins by providing an overview of recent trends in the access and use of new technologies as well as a summary of online opportunities and risks. It then explores a variety of factors, including economic, social and cultural status which underlie these trends and lead to online and offline inequalities. Building digital resilience is an important skill for 21st century children. Effective strategies to accomplish this include encouragement of active rather than passive Internet use, e-safety in the school curriculum, and teacher and parental Information and Communication Technology (ICT) support. A focus on younger children (primary school or younger) and the effects of new emerging technologies would be helpful for future research. |
| Date: | 2018–09–17 |
| URL: | http://d.repec.org/n?u=RePEc:oec:eduaab:179-en&r=ict |
| By: | Twomey, Paul |
| Abstract: | Building on the 2017 Hamburg Statement and the G20 Roadmap for Digitalization, this paper recommends a G20 framework for artificial intelligence in the workplace. It proposes high level principles for such a framework for G-20 governments to enable the smoother, internationally broader and more socially acceptable introduction of big data and AI. The principles are dedicated to the work space. It summarises the main issues behind the framework principles. It also suggests two paths towards adoption of a G-20 framework for artificial intelligence in the workplace. |
| Keywords: | artifical intelligence,privacy,wealth distribution,workplace,regulation,political principles,workers,transparency,G20,heads of government,big data,Hamburg Statement |
| JEL: | K2 O3 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifwedp:201863&r=ict |
| By: | Quan-Hoang Vuong |
| Abstract: | It is widely believed that the social contract, credited to Magna Carta of Englandin the 13th century and subsequent thinkers such as Thomas Hobbes, JohnLocke, is the major factor that has empowered the concept of civil society in theworld, starting from the West. This perspective paper suggests that althoughthat still holds to a large extent, the case of Indochina shows a diametrical, andunnatural, difference as civic engagement in social matters of deep influence wasborn out of the state’s necessity to tolerate diverging voices, either bycontrolling, empowering or engaging, in order to cope with social conflicts. Thisobservation gives rise to the need for further studies on the nature of theinformation-power nexus in the age of big data and social networks. |
| Keywords: | Political economy; the Internet; civil society; social networks |
| JEL: | F54 F59 L86 P26 |
| Date: | 2018–09–04 |
| URL: | http://d.repec.org/n?u=RePEc:sol:wpaper:2013/276633&r=ict |
| By: | Conrad, Alexander; Neuberger, Doris; Peters, Florian; Rösch, Fabian |
| Abstract: | Bisherige Studien haben den digitalen Zugang zu Finanzdienstleistungen untersucht und gut versorgte sowie unterversorgte Regionen in Deutschland identifiziert. Das Vorhandensein eines hinreichend guten digitalen Zugangs sagt aber nichts darüber aus, ob dieser auch genutzt wird, um damit Finanzdienstleistungen nachzufragen. Dieses Papier stellt die Kunden in den Mittelpunkt und untersucht, welche sozioökonomischen Faktoren Einfluss auf die Nutzung des digitalen Zugangs für die Nachfrage nach Finanzdienstleistungen haben. Als Ergebnis können auch jene Attribute benannt werden, die eine sogenannte informationelle Kluft befördern. Ein regionaler Vergleich ermöglicht schließlich eine Aussage dazu, in welchen Gebieten (hier Geschäftsgebiete der Sparkassen) Deutschlands die Gefahr einer informationellen Kluft besonders groß ist. Es zeigt sich, dass dieses Risiko in ländlichen, dünn besiedelten Gebieten, mit einem hohen Durchschnittsalter der Bevölkerung und in Regionen mit einem relativ geringen durchschnittlichen Ausbildungsgrad vergleichsweise hoch ist. Hier droht insofern ein besonders hohes Risiko, dass Menschen infolge der voranschreitenden Digitalisierung von Bankdienstleistungen abgehängt werden und den Zugang zu grundlegenden Finanzdienstleistungen als Basis gesellschaftlicher Teilhabe verlieren. |
| Keywords: | Finanzdienstleistungen,Digitalisierung,digitale Kluft,informationelle Kluft,Sparkassen,Regionalvergleich |
| JEL: | G21 L32 L38 L86 O33 R12 R20 R51 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:roswps:157&r=ict |
| By: | Boxell, Levi |
| Abstract: | I build a dataset of over one million images used on the front page of websites around the 2016 election period. I then use machine-learning tools to detect the faces of politicians across the images and measure the nonverbal emotional content expressed by each politician. Combining this with data on the partisan composition of each website’s users, I show that websites portray politicians that align with the partisan preferences of their users with more positive emotions. I also find that nonverbal coverage by Republican-leaning websites was not consistent over the 2016 election, but became more favorable towards Donald Trump after he clinched the Republican nomination. |
| Keywords: | media bias, images, emotions, nonverbal, polarization |
| JEL: | C0 H0 L82 L86 |
| Date: | 2018–09–17 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:89047&r=ict |
| By: | Bharati Wukkadada (K.J. Somaiya Institute of Management studies & Research); Davendranath Jha (K.J. Somaiya Institute of Management studies & Research); Chaitanya Patel (K.J. Somaiya Institute of Management studies & Research) |
| Abstract: | The digital statics of Indian economy has impressive trends since last few years. With 62 million internet users and the penetration of 34.8%, there has been lot of development in computer hardware and internet space. This development has helped India to resolve the problems like unavailability of reasonable and faster internet access. As the customer base of smart phones is increasing rapidly, the manufacturers have been able to manufacture high quality smart phones in lesser price. With the growing growth shown by the mobile operators and Service providers ? Digital Marketing is fast coming up as an impressive way for direct marketing to the potential customer.This paper targets to catch the most preferred element to be inserted onto the On-page SEO elements, which impact the User behavior. The paper also aims to uncover the demographic profile, related facts and preferences of the customer and the on-page elements they prefer so as the search engine optimization (SEO) strategy can be formulated on the results. Beside with these objectives the study attempts to apprehend the impact of digital on-page HTML elements on the search engine optimization (SEO). Primary data has been collected with the help of Google Analytics and the User behavior before and after the implementation has been observed and then its impact on the SEO has been studied. For analysis data, Regression statistics has been used. Finally the findings are presented in a summarized manner for understanding the impact of the HTML element tags. |
| Keywords: | on-page SEO, off-page SEO, HTML, Google analytics, Hypothesis, Social Media Marketing |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:7209205&r=ict |
| By: | Bob Martens |
| Abstract: | The number of published entities has been rapidly growing in the past years. In the framework of this contribution a demonstration will be delivered on how to structure a search string in order to retrieve an adequate number of hits when investigating the wider area of "energy" within the context of real estate. The ERES Digital Library will be highlighted in this regard, but also a large repository will be examined in detail. Finally, the results of data mining efforts within ERES submissions for the Annual Conference in the period 2012-2017 will be presented along with the concept of word pairs. |
| JEL: | R3 |
| Date: | 2017–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2017_edu_103&r=ict |
| By: | Bergemann, Dirk; Bonatti, Alessandro |
| Abstract: | We survey a recent and growing literature on markets for information. We offer a comprehensive view of information markets through an integrated model of consumers, information intermediaries, and firms. The model embeds a large set of applications ranging from sponsored search advertising to credit scores to information sharing among competitors. We then review a mechanism design approach to selling information in greater detail. We distinguish between ex ante sales of information (the buyer acquires an information structure) and ex post sales (the buyer pays for specific realizations). We relate this distinction to the different products that brokers, advertisers, and publishers use to trade consumer information online. We discuss the endogenous limits to the trade of information that derive from its potential adverse use for consumers. Finally we revisit the role of recommender systems and artificial intelligence systems as markets for indirect information. |
| Keywords: | information design; information markets; intermediaries; mechanism design; predictions; ratings |
| JEL: | D42 D82 D83 |
| Date: | 2018–08 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13148&r=ict |
| By: | Nadhakan Shinnaranantana (Faculty of Business Administration, KASETSART UNIVERSITY) |
| Abstract: | Nowadays retailers have using multichannel of distribution, especially they are more focus on Internet shopping. Because of today consumers are more using internet for several activities such as entertainment, searching for information, social media and also shopping. This conceptual paper focus on internet shopping of Baby Boomers and their buying behavior. Adult consumers are specifically targeted because of their buying power and they are high potential customers for Internet retailer. The study specially address the issues how often and why Internet purchase is made. The 6 Ws and 1 H of buying behavior are asked; who are in the target market, what do they buy, why do they buy, who participate in the buying, when and where do they buy and how do they buy. Regarding the design, methodology, and approach of this paper, a thorough literature investigation will conduct through major databases of leading academic journals and research papers related to the scope of this paper in both Thai and English. An analysis of literature reviews of relevant articles will carry out and present in the paper. The study will provide a vital information for marketers and retailers to develop effective online marketing strategy. |
| Keywords: | Internet Shopping, Buying Behavior, Baby Boomers, Bangkok Thailand |
| JEL: | M31 |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:7208950&r=ict |
| By: | Ikudo, Akina (University of California, Los Angeles); Lane, Julia (New York University); Staudt, Joseph (U.S. Census Bureau); Weinberg, Bruce A. (Ohio State University) |
| Abstract: | Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations. |
| Keywords: | UMETRICS, occupational classifications, machine learning, administrative data, transaction data |
| JEL: | J0 J21 J24 |
| Date: | 2018–08 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp11738&r=ict |
| By: | Akina Ikudo; Julia Lane; Joseph Staudt; Bruce Weinberg |
| Abstract: | Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations. |
| JEL: | C8 J01 J24 |
| Date: | 2018–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24951&r=ict |
| By: | Hunold, Matthias; Kesler, Reinhold; Laitenberger, Ulrich |
| Abstract: | We investigate whether online travel agents (OTAs) assign hotels worse positions in their search results if these set lower hotel prices at other OTAs or on their own websites. We formally characterize how an OTA can use such a strategy to reduce price differentiation across distribution channels. Our empirical analysis shows that the position of a hotel in the search results of OTAs is better when the prices charged by the hotel on other channels are higher. This is consistent with the hypothesis that OTAs alter their search results to discipline hotels for aggressive prices on competing channels, and by this reduce search quality for consumers. |
| Keywords: | consumer protection,free-riding,hotel booking,online travel agents,ranking,search bias |
| JEL: | D40 L42 L81 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:dicedp:300&r=ict |
| By: | Farah Zawaideh (Irbid National University); Raed Sahawneh (Irbid National University) |
| Abstract: | Automatic text categorization (TC) has become one of the most interesting fields for researchers in data mining, information retrieval, web text mining, as well as natural language processing paradigms due to the vast number of new documents being retrieved for various information retrieval systems. This paper proposes a new TC technique, which classifies Arabic language text documents using the naïve Bayesian classifier attached to a genetic algorithm, model; this algorithm classifies documents by generating a random sample of chromosomes that represent documents in the corpus. The developed model aims to enhance the work of naïve Bayesian classifier through applying the genetic algorithm model. Experiment results show that the precision and recall are increased when testing higher number of documents; the precision was ranged from 0.8 to 0.97 for different testing environment; the number of genes that is placed in every chromosome is also tested and experiments show that the best value for the number of genes is 50 genes |
| Keywords: | Data mining, Text classification, Genetic algorithm, Naïve Bayesian Classifier, N-gram processing |
| JEL: | C80 |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:6409186&r=ict |