Information and Communications Technology (ICT) International Spillovers

Gholami, Roya; Guo, Xiaojia; Higon, M Dolores Anon; Lee, Sang-Yong Tom

doi:10.1109/tem.2009.2016044

Cited by 17 publications

(7 citation statements)

References 54 publications

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“…Supplying industries' IT capital was found to have a measurable contribution to industrial productivity [4]. Similarly, both domestic IT in a country and foreign IT spillover have an effect on national productivity [9].…”

Section: A Review Of Recent Literaturementioning

confidence: 97%

Information technology and productivity: Empirical evidence from the Chinese electronics industry

Lee

Xiang

Kim

2011

Information & Management

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Section: A Review Of Recent Literaturementioning

confidence: 97%

Information technology and productivity: Empirical evidence from the Chinese electronics industry

Lee

Xiang

Kim

2011

Information & Management

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“…Babel et al [23] propose a stochastic model to forecast the German mortality rates using panel data procedures with the consideration of common time effect and common age effect. Gholami et al [24] explore the patterns and mechanisms of international information and communication technology "spillovers" by using over 30 countries' panel data from 1996 to 2004. Kesavan et al [25] construct an analytical model using the panel data to provide joint forecasts of annual cost of goods sold, inventory, and gross margin for retailers.…”

Section: Introductionmentioning

confidence: 99%

Fashion Sales Forecasting With a Panel Data-Based Particle-Filter Model

Ren

Choi

Liu

2015

IEEE Trans. Syst. Man Cybern, Syst.

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In this paper, we propose and explore a novel panel data-based particle-filter (PDPF) model to conduct fashion sales forecasting. We evaluate the performance of proposed model by using real data collected from the fashion industry. The experimental results indicate that the proposed panel data models outperform both the traditional statistical and intelligent methods, which provide strong evidence on the importance of employing the panel-data approach. Further analysis reveals that: 1) our proposed PDPF method yields a better forecasting result in item-based sales forecasting than in color-based sales forecasting; 2) a larger degree of Granger causality relationship between sales and price will imply a better sales forecasting result of the PDPF model; 3) increasing the amount of historical data does not necessarily improve forecasting accuracy; and 4) the PDPF method is suitable for conducting fashion sales forecasting with limited data. These findings provide novel insights on the use of panel data for conducting fashion sales forecasting.Index Terms-Fashion sales forecasting, industrial problems, panel data analysis, particle filter.

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“…To assess the contribution of ICT, researchers commonly adopted methods from production economics to estimate relationships between inputs (e.g., capital and labor) and output. Studies normally assumed a standard Cobb-Douglas production function and measure variables in logarithms (Brynjolfsson and Hitt, 2003;Tom Lee et al, 2005;Gholami et al, 2009;Tambe et al, 2012).…”

Section: Methodsmentioning

confidence: 99%

Are information and communication technologies (ICTs) displacing workers? The relationship between ICT investment and employment

Jung

Lee

Kim

2019

Information Development

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This study examined how information communication technologies (ICT) investment affected sales and employment at 76 small and medium-sized Korean companies during 2009–2013. Especially, this study investigated the effects of ICT investment on sales in general and by subsets of investment in hardware, software, and ICT staff. Studies normally assumed a standard Cobb-Douglas production function, and measured variables in logarithms. In line with previous studies, we assumed that firms produced output, performance, or productivity via a Cobb–Douglas production function model with inputs capital and labor. We then suggested a new model that could be incorporated into the production function above to estimate the effect of the interaction between ICT investment and labor on sales. This study found that hardware investment complemented labor in increasing performance, whereas investments in software and ICT staff substituted labor. These results show that ICT investment might affect firm-level employment, and what business managers must consider insofar as each subset of ICT investment exerts differing effects on firm-level employment. This study also found that the effect of ICT investment on firm-level employment might be more pronounced among smaller firms and firms outside the IT industry. This study also demonstrated that ICT investment complemented labor and that the effects differed for specific types of ICT. This study can help managers respond to the challenges of ICT investment or employment, and provides a framework for analyzing the strategic significance of ICT investment and employment.

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Information and Communications Technology (ICT) International Spillovers

Cited by 17 publications

References 54 publications

Information technology and productivity: Empirical evidence from the Chinese electronics industry

Information technology and productivity: Empirical evidence from the Chinese electronics industry

Fashion Sales Forecasting With a Panel Data-Based Particle-Filter Model

Are information and communication technologies (ICTs) displacing workers? The relationship between ICT investment and employment

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