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on Information and Communication Technologies |
| By: | Efobi, Uchenna; Tanankem, Belmondo; Asongu, Simplice |
| Abstract: | This study complements existing literature by investigating how the advancement in information and communication technology affects the formal economic participation of women. The focus is on 48 African countries for the period 1990-2014. The empirical evidence is based on Ordinary Least Squares, Fixed Effects and the Generalized Method of Moments regressions. The results show that improving communication technology increases female economic participation with the following consistent order of increasing magnitude: mobile phone penetration; internet penetration, and fixed broadband subscriptions. The findings are robust to the control for heterogeneities across countries. Policy implications are discussed. |
| Keywords: | Africa; Gender; ICT; Inclusive development; Technology |
| JEL: | G20 I10 I32 O40 O55 |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:87864&r=ict |
| By: | Mbise, Theo; Taal, Sainabou; Roberts, Michael; Lammersen, Frans |
| Abstract: | Digital networks are an increasingly critical component of global trade. In 2017, the Global Review of Aid for Trade highlighted the importance of accessible and affordable connections for trade connectivity. Drawing extensively on information harvested in the Monitoring and Evaluation exercise in preparation for the Review, this paper analyses aid for trade for digital connectivity and e-commerce. Also presented in this paper are the types of issues and challenges faced in cross-border electronic transactions - an area in which demand for support is set to grow. The paper also surveys flows reported to the Organisation for Economic Cooperation and Development Creditor Reporting System. Funds disbursed to digital connectivity amounted to US$6.6 billion in concessional financing and US$8.3 billion in non-concessional financing in the period 2006-2016. The top providers of financing were the European Union, Japan, Korea, the United Kingdom and the World Bank Group. The paper also highlights the various methodological difficulties encountered, and explains the need to further refine reporting definitions so as to better capture financing flows to digital connectivity and to understand how aid for trade is being used to leverage private sector financing for ICT. The analysis concludes by reviewing the catalytic role that aid for trade is playing in mobilizing private sector financing. Research for the 2017 Global Review suggests that both developing countries and donors view ICT connectivity as an area where demand for financing will grow in future. |
| Keywords: | aid for trade,digital connectivity,ICT connectivity,e-commerce |
| JEL: | F35 P33 P45 L81 O33 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:wtowps:ersd201808&r=ict |
| By: | Hal Varian |
| Abstract: | Machine learning (ML) and artificial intelligence (AI) have been around for many years. However, in the last 5 years, remarkable progress has been made using multilayered neural networks in diverse areas such as image recognition, speech recognition, and machine translation. AI is a general purpose technology that is likely to impact many industries. In this chapter I consider how machine learning availability might affect the industrial organization of both firms that provide AI services and industries that adopt AI technology. My intent is not to provide an extensive overview of this rapidly-evolving area, but instead to provide a short summary of some of the forces at work and to describe some possible areas for future research. |
| JEL: | L0 |
| Date: | 2018–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24839&r=ict |
| By: | Schulze Schwering, Dorothee; Spiller, Achim |
| Abstract: | Heute ist die Digitalisierung unter dem Begriff Industrie 4.0 in allen Wirtschaftsbranchen allgegenwärtig. Auch die digitale Ausstattung der landwirtschaftlichen Vorleistungsunternehmen und ihrer Kunden steigt daher stetig an. Deshalb müssen Unternehmen der landwirtschaftlichen Vorleistungsindustrie die Digitalisierung ihrer Vertriebs-, Informations- und Servicefunktionen optimieren und setzen vermehrt auf electronic Commerce (E-Commerce). Ziel der Studie war es daher, das Online-Einkaufsverhalten deutscher Landwirte in Bezug auf Betriebsmittel zu untersuchen. Anhand einer Online-Umfrage der Georg-August-Universität Göttingen unter 371 deutschen Landwirten wurde festgestellt, dass knapp 90% der Landwirte das Internet häufig bis sehr häufig für betriebliche Zwecke nutzen, aber nur 18,3% von ihnen dieses regelmäßig für betriebliche Einkäufe nutzen. Das Online-Einkaufsverhalten der Landwirte hängt, ähnlich wie das allgemeine Einkaufsverhalten, von Produkt- und Marktmerkmalen, individuellen und betrieblichen Eigenschaften sowie von der Beziehung und Loyalität zum Handel vor Ort ab. So beeinflussen wahrgenommene Vorteile, Freude am Online-Einkauf und die persönliche Erfahrung mit dem Online-Handel die E-Commerce-Nutzung positiv. Im Internet werden vorzugsweise hoch standardisierte und bekannte Betriebsmittel erworben. Die Analyse der Nutzerstruktur der online-einkaufenden Landwirte ergab eine sowohl weitestgehend soziodemografische Unabhängigkeit als auch eine Unabhängigkeit hinsichtlich betriebsbezogener Eigenschaften. Misstrauen und die Beziehung/Loyalität zum Landhandel korrelieren hingegen negativ mit dem Nutzungsverhalten von betrieblichem E-Commerce. Die Studie zeigt in Ansätzen, dass die Mehrheit der Landwirte dem Online-Einkauf positiv gegenüber eingestellt ist. Es wird außerdem deutlich, dass eine enge Beziehung zum Landhandel heute noch von tragender Bedeutung ist und der strategische Vertrieb daher die Optimierung von "Multi-Channel-Systemen" zentralisieren sollte. |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:daredp:1805&r=ict |
| By: | Christian Catalini; Xiang Hui |
| Abstract: | Early crowdfunding platforms were based on a premise of complete disintermediation from traditional experts. This approach becomes problematic when equity is involved because of asymmetric information between entrepreneurs and investors. Moreover, it favors regions that already attract a disproportionate share of capital offline. We find that the introduction of intermediaries through online syndicates reverses this trend, leading to a large 33% increase in capital flows to new regions. At the same time, this "democratization effect" relies on the presence of intermediaries with professional networks that can bridge these new regions with California. Evidence from a large-scale field experiment with over 26,000 investors corroborates the idea that social networks constitute a key friction to additional democratization, since they shape how online investors screen and evaluate intermediaries. Intermediaries use their reputation to vouch for high potential startups that would otherwise be misclassified because of information asymmetry. This allows them to arbitrage opportunities across regions and shift capital flows to startups from new regions that are 36.9% more likely to generate above median returns. We discuss implications for the design of equity crowdfunding platforms. |
| JEL: | G24 L26 O31 O33 |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24777&r=ict |
| By: | George Deltas; Dakshina Garfield De Silva; Robert McComb |
| Abstract: | We estimate the effects of industrial localization on the spatial persistence of employment in the software industry, using micro-data from Texas for the 2000-2006 period. Locations with an initial concentration of software employment retain an excess number of employees, beyond that expected from job turnover and job persistence at the establishment level. This is not driven by differential establishment growth or survival, but it is due to (a) the retention by establishments in a location of jobs lost by other establishments in that location, and (b) the propensity of software establishments to enter in locations with prior software establishment presence. These findings are more consistent with labor channel effects than with human capital spillovers. |
| Keywords: | Agglomeration economies, labor pools, knowledge spillovers, firm growth, spatial effects |
| JEL: | R32 L86 R12 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:lan:wpaper:242312727&r=ict |
| By: | Naomitsu Yashiro; Stephanie Lehmann |
| Abstract: | This paper reviews policies to strengthen Germany’s productivity growth and prepare for changes in labour markets brought about by new technologies. This paper also discusses how social protection and the bargaining framework should be reformed for the future of work. Germany enjoys a relatively high labour productivity level but productivity growth has been modest in recent years. There is room to boost productivity growth by accelerating the diffusion of new technologies throughout the economy. Vigorous entrepreneurship and innovation by small and medium enterprises are key for such technology diffusion while strong broadband and mobile networks widen the scope of data-intensive technologies that can be exploited to increase productivity. Widespread use of new technologies will bring about significant changes in skill demand and work arrangements. As in many countries, Germany saw a decline in the share of middle-skilled jobs in employment. A relatively high share of jobs is expected to be automated or undergo significant changes in task contents as a result of technological change. New technologies are also likely to increase individuals engaging in new forms of work, such as gig work intermediated by digital platforms. Such workers are less covered by public social safety nets such as unemployment insurance than regular employment. |
| Keywords: | automation, digital platform, entrepreneurship, Productivity, self-employment, technology diffusion |
| JEL: | J23 J24 J29 O33 O38 O43 O52 |
| Date: | 2018–08–17 |
| URL: | http://d.repec.org/n?u=RePEc:oec:ecoaaa:1502-en&r=ict |
| By: | Tsvetkova, Milena; Wagner, Claudia; Mao, Andrew |
| Abstract: | From small communities to entire nations and society at large, inequality in wealth, social status, and power is one of the most pervasive and tenacious features of the social world. What causes inequality to emerge and persist? In this study, we investigate how the structure and rules of our interactions can increase inequality in social groups. Specifically, we look into the effects of four structural conditions—network structure, network fluidity, reputation tracking, and punishment institutions—on the distribution of earnings in network cooperation games. We analyze 33 experiments comprising 96 experimental conditions altogether. We find that there is more inequality in clustered networks compared to random networks, in fixed networks compared to randomly rewired and strategically updated networks, and in groups with punishment institutions compared to groups without. Secondary analyses suggest that the reasons inequality emerges under these conditions may have to do with the fact that fixed networks allow exploitation of the poor by the wealthy and clustered networks foster segregation between the poor and the wealthy, while the burden of costly punishment falls onto the poor, leaving them poorer. Surprisingly, we do not find evidence that inequality is affected by reputation in a systematic way but this could be because reputation needs to play out in a particular network environment in order to have an effect. Overall, our findings suggest possible strategies and interventions to decrease inequality and mitigate its negative impact, particularly in the context of mid- and large-sized organizations and online communities. |
| JEL: | J1 |
| Date: | 2018–07–20 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:89716&r=ict |
| By: | Ebbes, Peter; Netzer, Oded |
| Abstract: | An important challenge for many firms is to identify the life transitions of its customers, such as job searching, being pregnant, or purchasing a home. Inferring such transitions, which are generally unobserved to the firm, can offer the firm opportunities to be more relevant to its customers. In this paper, we demonstrate how a social network platform can leverage its longitudinal user data to identify which of its users are likely job seekers. Identifying job seekers is at the heart of the business model of professional social network platforms. Our proposed approach builds on the hidden Markov model (HMM) framework to recover the latent state of job search from noisy signals obtained from social network activity data. Specifically, our modeling approach combines cross-sectional survey responses to a job seeking status question with longitudinal user activity data. Thus, in some time periods, and for some users, we observe the “true” job seeking status. We fuse the observed state information into the HMM likelihood, resulting in a partially HMM. We demonstrate that the proposed model can not only predict which users are likely to be job seeking at any point in time, but also what activities on the platform are associated with job search, and how long the users have been job seeking. Furthermore, we find that targeting job seekers based on our proposed approach can lead to a 42% increase in profits of a targeting campaign relative to the approach that was used at the time of the data collection. |
| Keywords: | Hidden Markov Models; Data Fusion; Targeting; Customer Analytics |
| JEL: | C10 J20 J40 M30 |
| Date: | 2018–06–01 |
| URL: | http://d.repec.org/n?u=RePEc:ebg:heccah:1284&r=ict |
| By: | Alemanno, Alberto |
| Abstract: | It is almost a truism to argue that data holds a great promise of transformative resources for social good, by helping to address a complex range of societal issues, ranging from saving lives in the aftermath of a natural disaster to predicting teen suicides. Yet it is not public authorities who hold this real-time data, but private entities, such as mobile network operators and business card companies, and - with even greater detail - tech firms such as Google through its globally-dominant search engine, and, in particular, social media platforms, such as Facebook and Twitter. Besides a few isolated and self-proclaimed ‘data philanthropy’ initiatives and other corporate data-sharing collaborations, data-rich companies have historically shown resistance to not only share this data for the public good, but also to identify its inherent social, non-commercial benefit. How to explain to citizens across the world that their own data - which has been aggressively harvested over time - can’t be used, and not even in emergency situations? Responding to this unsettling question entails a fascinating research journey for anyone interested in how the promises of big data could deliver for society as a whole. In the absence of a plausible solution, the number of societal problems that won’t be solved unless firms like Facebook, Google and Apple start coughing up more data-based evidence will increase exponentially, as well as societal rejection of their underlying business models. This article identifies the major challenges of unlocking private-held data to the benefit of society and sketches a research agenda for scholars interested in collaborative and regulatory solutions aimed at unlocking privately-held data for good. |
| Keywords: | Big data; data; data governance; data sharing; data risk; data invisible; risk governance; philanthropy; |
| JEL: | I18 K23 K32 K40 |
| Date: | 2018–06–11 |
| URL: | http://d.repec.org/n?u=RePEc:ebg:heccah:1280&r=ict |