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on Information and Communication Technologies |
| By: | Okeke, Clement |
| Abstract: | The impact of Information and Communication Technology (ICT) on firm performance has become the subject of active research in the last four decades. This study’s goal is to review the effect of ICT on the financial performance of firms in the consumer goods sector as measured by their Return on Capital Employed (ROCE) with firm size added as a control variable. For a period of ten (10) years, from 2013 to 2022, the study used thirteen (13) listed consumer goods companies in Nigeria. An ex-post facto research approach was used, and secondary data were gathered from the companies’ annual reports for the period under review. EViews version 12 was used to do correlation and regression analysis. The findings show that Funding for ICT Hardware (FICTH)and Funding for ICT Software (FICTS) have a negative and insignificant effect on the financial performance of listed consumer goods firms in Nigeria. The study suggests that stakeholders, especially managers in the consumer goods sector should always review all options carefully before venturing into any procurement of additional computer hardware or software bearing in mind the negative impact of their ROCE. |
| Keywords: | Information and Communication Technology (ICT), Return on Capital Employed |
| JEL: | G3 G30 L2 L8 L86 L89 O14 O30 O32 |
| Date: | 2024–04–10 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121293&r= |
| By: | Davis, Kristin; Rosenbach, Gracie; Spielman, David J.; Makhija, Simrin; Mwangi, Lucy |
| Abstract: | Effective agricultural extension and advisory services are a key component of efforts to achieve sustainable agricultural production, resilient livelihoods, and inclusive economic growth. These are all necessary elements for accelerating Rwanda’s agricultural transformation. Both extension and information and communication technologies (ICT) are important elements in Rwanda’s Strategic Plan for Agriculture Transformation. This paper examines the capacities of public and private agricultural extension agents in Rwanda and their readiness to use ICT in their work—that is, to be digitally equipped—and provides recommendations for enhancing agricultural extension capacities through expanding and effectively using ICT. To examine capacities and readiness, we use a representative survey of 500 public and private extension agents in Rwanda, augmented by qualitative data from a literature review and key informant interviews. To assess agents’ ‘digital readiness, ’ we create two indices focused on their digital experiences and attitudes toward digital modernization. |
| Keywords: | Africa; Eastern Africa; Sub-Saharan Africa; Rwanda; agricultural extension; sustainability; agricultural production; livelihoods; Information and Communication Technologies |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:rsspwp:12&r= |
| By: | Bogdan Oancea |
| Abstract: | The term of big data was used since 1990s, but it became very popular around 2012. A recent definition of this term says that big data are information assets characterized by high volume, velocity, variety and veracity that need special analytical methods and software technologies to extract value form them. While big data was used at the beginning mostly in information technology field, now it can be found in every area of activity: in governmental decision-making processes, manufacturing, education, healthcare, economics, engineering, natural sciences, sociology. The rise of Internet, mobile phones, social media networks, different types of sensors or satellites provide enormous quantities of data that can have profound effects on economic research. The data revolution that we are facing transformed the way we measure the human behavior and economic activities. Unemployment, consumer price index, population mobility, financial transactions are only few examples of economic phenomena that can be analyzed using big data sources. In this paper we will start with a taxonomy of big data sources and show how these new data sources can be used in empirical analyses and to build economic indicators very fast and with reduced costs. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.11913&r= |
| By: | Thomas Fackler; Oliver Falck; Moritz Goldbeck; Fabian Hans; Annina Hering |
| Abstract: | We investigate differences in labor demand between German automotive firms specializing in green propulsion technology and those with a focus on combustion engines. To this end, we introduce a firm-level labor demand index based on the near-universe of online job postings and firms’ patent portfolios. Workforce adjustments are a crucial dimension of technology-related structural change, and labor demand as a highly reactive decision parameter is an ideal measure to detect employment adjustments. Our index enables us to distinguish labor demand by firms’ greenness in real-time, a notable advantage over survey or administrative data. In a difference-in-differences setup, we exploit the poly-crisis triggered by unexpected escalations of trade conflicts and sustained by consequences of the pandemic and the war in Ukraine. We find green firms’ labor demand is significantly and persistently higher than before the outbreak of the poly-crisis, by 34 to 50 percentage points compared to firms with a focus on combustion technology. This gap widens over time and is not driven by unobserved firm heterogeneity. Green firms systematically adjust labor demand towards production and information technology jobs. |
| Keywords: | low carbon technology, firm employment decisions, sustainability, disruptive innovation |
| JEL: | C55 J23 M51 O14 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11160&r= |
| By: | Wanying Huang |
| Abstract: | We study whether individuals can learn the informativeness of their information technology through social learning. As in the classic sequential social learning model, rational agents arrive in order and make decisions based on the past actions of others and their private signals. There is uncertainty regarding the informativeness of the common signal-generating process. We show that learning in this setting is not guaranteed, and depends crucially on the relative tail distributions of private beliefs induced by uninformative and informative signals. We identify the phenomenon of perpetual disagreement as the cause of learning and characterize learning in the canonical Gaussian environment. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.05299&r= |