scholarly journals Green ICT Adoption Survey Focused on ICT Lifecycle from the Consumer’s Perspective (SMEs)

2012 ◽  
Vol 4 (4) ◽  
pp. 109-122 ◽  
Author(s):  
Alena Buchalcevova ◽  
◽  
Libor Gala
Keyword(s):  
2019 ◽  
Vol 11 (24) ◽  
pp. 7163 ◽  
Author(s):  
Albert Hankel ◽  
Gaston Heimeriks ◽  
Patricia Lago

The field green ICT focuses on the greening of ICT and using ICT to optimise the energy footprint of the ICT-supported processes. For organisations, applying green ICT in the broadest sense presents them with challenges. In this paper we explore what factors are influencing the adoption of green ICT. We follow three organisations that used a green ICT tool, the SURF Green ICT Maturity Model, to identify such factors. Tools like the maturity model help organisations identify the what and how. We found other factors, such as strategic alignment, culture and leadership, determine the why. As ICT is a general purpose technology, it potentially affects all processes in an organisation. To have a greening impact, the main challenge for green ICT is to take a systemic approach and involve all (relevant) parties. ICT departments often position themselves as support (followers, not leaders); this proves to be a big hurdle in the adoption of green ICT.


Author(s):  
Olena Zayats ◽  

The article examines the competitive status and competitive positions of Ukraine. It proves that in the current context the competitive status of the national economy is determined by the presence of a strong global competitive force that provides dynamic growth based on innovation potential, developed institutions, infrastructure, ICT adoption, macroeconomic stability, health, skills, product market, labor market, financial system, market size, business dynamism rather than by traditional factors (natural resources, geopolitical situation). It has been identified that a wide range of factors in global competitive force establishment suggests the complexity of its assessment. It has been noted that in world economic practice the Global Competitiveness Index of the World Economic Forum is predominantly used to assess the competitive status of the national economy. It has been determined that according to this index, in the overall ranking among 141 countries in 2019, Ukraine ranked 85th (2009-2010 – 82/133; 2018 – 83/140). The article analyzes of the competitive status of Ukraine in the international arena in terms of twelve pillars of the studied index and in the context of components of the said pillars. The dynamics of Ukraine's global competitive force in recent years shows that there has not been any build up. However, if one analyzes it in terms of the criteria of the global competitive force of the domestic economy, their assessment is volatile: the main regression can be traced in the sphere of the financial system, where Ukraine dropped by 19 positions in one year (2018 – 117/140, 2019 – 136/141), and the greatest progress is observed in the product market, where Ukraine rose by 16 positions in one year (2018 – 73/140, 2019 – 57/141). Analysis of the components of Ukraine’s global competitive force criteria shows that the worst positions in terms of such components are as follows: non-performing loans (% of gross total loans) – 139/141 and soundness of banks – 131/141. The best positions are in terms of the following components: costs of starting a business – 14/141 and attitude towards entrepreneurial risk – 18/141.


GIS Business ◽  
2020 ◽  
Vol 14 (6) ◽  
pp. 1147-1155
Author(s):  
J.Nithya Jayaseeli ◽  
T. Devi

The purpose of this study is to examine how Knowledge level augmented parameters impact on the effective adoption of information and communication technology (ICT) by onion farmers in Perambalur district of Tamil Nadu. Data were gathered from a focus group made up of 60 Farmers in Perambalur district. The paper finds that a willingness of indigenous ICT users is particularly influenced by the recognition and incorporation of visible social imperatives during the adoption process. Research limitations/implications – The outcome of this study highlights important issues for ICT adoption. One particular area that must be taken into consideration is the adoption channel. Perceptions of ICT adoption will differ significantly among adopters. For this reason, the need for developing an appropriate adoption channel that ensures successful diffusion of the innovation should be recognized. The paper also demonstrates that Knowledge Management System among farmers using ICT to yield more profit in onion Production form knowledge distributed by the experts. Hence the research work carried out to acquire, represent, and distribute the knowledge Management system to the Farming community.


2018 ◽  
Vol 50 (04) ◽  
pp. 507-512
Author(s):  
S. CHANDIO ◽  
M. SADRY ◽  
A.A CHANDIO ◽  
A. H. ABRO ◽  
A. A. SHAH ◽  
...  
Keyword(s):  

2021 ◽  
pp. 108433
Author(s):  
Sakshi ◽  
Rakesh Kumar Jha ◽  
Sanjeev Jain

2008 ◽  
Vol 20 (3) ◽  
pp. 229-242 ◽  
Author(s):  
Nicoletta Corrocher ◽  
Roberto Fontana
Keyword(s):  

Author(s):  
Anass Bayaga ◽  
Emmanuel O. Adu

Abstract Building on prior research related to (1) impact of information communication technology (ICT) and (2) operational risk management (ORM) in the context of medium and small enterprises (MSEs), the focus of this study was to investigate the relationship between (1) ICT operational risk management (ORM) and (2) performances of MSEs. To achieve the focus, the research investigated evaluating models for understanding the value of ICT ORM in MSEs. Multiple regression, Repeated-Measures Analysis of Variance (RM-ANOVA) and Repeated-Measures Multivariate Analysis of Variance (RM-MANOVA) were performed. The findings of the distribution revealed that only one variable made a significant percentage contribution to the level of ICT operation in MSEs, the Payback method (β = 0.410, p < .000). It may thus be inferred that the Payback method is the prominent variable, explaining the variation in level of evaluation models affecting ICT adoption within MSEs. Conclusively, in answering the two questions (1) degree of variability explained and (2) predictors, the results revealed that the variable contributed approximately 88.4% of the variations in evaluation models affecting ICT adoption within MSEs. The analysis of variance also revealed that the regression coefficients were real and did not occur by chance


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