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This paper aims to provide a macro perspective on diffusion structure research, and to investigate the deep structure of international technology diffusion and structural differences between technology diffusion networks. This work also provides an understanding of the nature of globalization. Globalization has highlighted changes in socioeconomics and is reshaping the world. However, when comparing endogenous factors, exogenous factors are complex and demonstrate themselves as network phenomena. These network phenomena compose themselves as neither sole nor independent units. Countries in the global network act interdependently, and heavily influence one another.

This study utilizes social network analysis to investigate the structural configuration of international technology diffusion. This investigation uses a sample of 42 countries over the period from 1997 to 2008. The data set contains two categories: bilateral trade flow and aggregate R&D expenditure. Meanwhile, this study uses block model analysis to reveal a network structure, which can precisely illustrate a global network configuration.

The findings not only illustrate the pattern change of diffusion from a cascade-like to radial-like structure, but also present the structural configuration of technologically advanced countries and their competitive positions.

In the shift to a diffusive structure, time and space are represented in new ways. Therefore, radial-like diffusion structure can provide some technological development approaches for countries interested in exogenous effects for technological growth and managing their international relation.

This study is the first to use a multilateral perspective and longitudinal data to examine a cross-country network structure, to provide an understanding of the nature of globalization, its conceptualization and how influence and effects are transmitted through the interconnectedness of international technology diffusion.

The purpose of this paper is to investigate the factors of technology diffusion in Saudi Arabia. It is a relevant study for Saudi Arabia, which has embarked on high gears of economic modernization that is supposed to be driven by technology and knowledge. Thus, an up-to-date research on the factors of technology diffusion in the country is expected to be of high-valued contribution.

It employs co-integration method to analyse the long run relations between the technology diffusion and its determinants.

The study finds that the international trade, particularly the oil sector trade, of the Saudi Arabia appears to play no relevant role in the international technology transfer for Saudi Arabia. The study confirms that technology is an endogenous variable in the presence of human capital; and that the higher levels of educational attainments are found to significantly improve factor productivity. The foreign direct investment (FDI) stock is confirmed to be a consistent and important factor in the process of technology diffusion. The capital goods imports and the domestic R&D expenditure are found to be negatively associated with the technology diffusion.

The machine and transport equipment imports are used by the study as a measure of capital goods imports, and thus a better measure is needed in a further research. Similarly, the limited data on the domestic R&D expenditure has forced the author to rely on estimates and own calculations. Thus, these data limitations could not allow us to have better understanding of the impacts of capital goods imports and domestic R&D on the technology diffusion.

Human capital and FDIs are the key drivers the Saudi authorities should consider for transferring and diffusing technology in the country and expanding non-oil sources of economic growth.

This paper is a first of its kind for the case of Saudi Arabia to analyze the determinants of technology diffusion and investigate the role of the its oil sector trade in the technology diffusion. The oil sector trade is found insignificant in the international technology diffusion process; thus the authorities should refocus the oil sector trade towards technology localization and adoption to increase integrative by-product industries in the country.

The purpose of this paper is to investigate the role of cross‐border diffusion of technology as a contributor to national economic performance at both aggregate and sectoral levels. Specifically, it aims to explore: the relationship between inflows of foreign technology and home country knowledge base; and the impact of international technology diffusion on indigenous productivity and international competitiveness.

Values of international trade in manufactured sectors as well as other data sources of economic and scientific performance are used to measure inflows of foreign technology, indigenous knowledge base, or international competitiveness at the aggregate and/or sectoral levels. This paper employs correlation and regression models for data analysis. Sectoral patterns are revealed based on various taxonomies for industrial systems.

At the aggregate level, it is found that there is a positive relationship between a nation's domestic knowledge base and inflows of foreign technology; and technology inflows, as well as home country knowledge base, significantly contribute to a nation's labor productivity (LP) and its international competitiveness. At the sectoral level, it is found that patterns of contribution from technology inflows to international competitiveness differ from industry to industry. There is a general trend of increase in the contributions from international technology inflows to a nation's international competitiveness over time and from lower to higher technology industries. However, for complex system technologies where tacit knowledge prevails, the diffusion of technology could be a significant challenge.

Empirical findings of this paper have significant public policy implications. National industrial policies should be sector‐specific to reflect the particular features of each industry. In the meantime, a proper balance must be kept between enhancing home country knowledge base and promoting inflows of foreign technology.

Patent data have been exploited to track invention and international technology diffusion. We review evidence on research activity, international patenting, and income differences across countries. Guided by that evidence, we construct a model of ideas in the world economy that includes the decision of whether and where to patent them. The model makes precise connections between international patent statistics and cross-country differences in innovation, technology diffusion, market size, and strength of patent protection. We use it to organize our discussion of existing empirical studies, which typically focus on one of five core relationships: (i) national pools of knowledge and international spillovers from basic research; (ii) aggregate productivity and international technology diffusion from applied research; (iii) international patenting and the production of ideas, international diffusion, market sizes, and intellectual property regimes; (iv) the value of ideas and diffusion, market sizes, and the intellectual property regimes; or (v) investment in research and research productivity, the cost of research, and the value of ideas. While distinguishing between these five relationships proves useful, they are, of course, logically intertwined. Taking these interconnections into account will contribute to the goal of building a quantitative model of the creation, diffusion, and adoption of ideas in the global economy.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

Sustainability is increasingly becoming an essential aspect of technological innovations. In addition, the diffusion of sustainable new technology-based products appears to be uneven across the globe. The authors examine the effect of three country-level Hofstede measures of culture and two national-level innovation characteristics on the diffusion of Sustainable New Technology-based Products (SNTP).

Regression and Necessary Conditions Analysis were used to analyze a panel dataset of electric and hybrid vehicles sales from 2008 to 2017 across 89 countries.

Results suggest Long-Term Orientation (LTO) was correlated with SNTP diffusion, Indulgence (IVR) was partially correlated with SNTP diffusion and was also a necessary condition. Surprisingly, Uncertainty Avoidance (UAI) was not correlated with SNTP diffusion. In addition, a national proclivity for developing innovations and a history of utilizing prior generic innovations were both correlated and necessary for SNTP diffusion.

This paper measures the impact of several macro-level variables (culture and other innovation related characteristics of countries) on SNTP diffusion. In addition to regression analyses to measure the average effect size, the authors conduct Necessary Conditions Analysis, which assesses the necessity of a variable for the outcome. These insights may help multinational companies better strategize entry decisions for international markets and aid governments in formulating more effective policies by recognizing and accommodating the influences of national culture and innovation attitudes.

The purpose of this paper is to investigate the factors influencing the total factor productivity (TFP) gap between the USA and eight Latin American countries for the period of 1970-2000.

The paper provides an explicit application of TFP estimation by employing a growth accounting approach (Solow Residual) in the presence of non-constant returns to scale and a non-parametric approach (DEA – Malmquist Index) while relaxing the scale-related constraint. A macro-based economic model of innovator and follower countries is employed to explore the linkage between technology gaps and innovations, labor productivity, trade openness, foreign direct investment, and adult workforce illiteracy rates. A pooled model and a fixed effects model are used to determine the factors of the technology gap between the innovator and the follower countries.

The results show that the labor productivity gap, adult work force illiteracy rates, patent filing gap, and trade openness are significant determinants of the technology gap between innovator and follower country.

Latin American countries would benefit from the technology diffusion from an innovator country; but a minimum threshold of human capital, such as adult workforce illiteracy rates and patent filing has to be met. The authors find government policies on trade openness also have large effects on technology limitations in foreign countries.

This paper is of value to researchers, policy makers, and economic development specialists trying to improve the rate of technology adoption and innovation.

Discusses the meanings of innovation and innovation diffusion, how innovations are affecting US corporations, and the developments that are emerging to improve innovation diffusion. Examines the implications of innovation for corporate culture and developments in innovation diffusion and organizational structure, such as international and national alliances. Concludes that managers must be aware of the importance of innovation diffusion, and successfully create cultures and alliances which facilitate the adoption of innovation.

The technological revolution is creating new goods and services and altering how and where they are produced. One of the principal issues for all countries is how these new technologies will affect employment and the composition of skills demand. Surveys the literature to attempt to answer three main questions: to what degree are the new technologies becoming diffused around the world? How much do they reduce, or increase employment? And do they reduce, or increase, the skills required in the labour force? Touches briefly on implications for educational policy. The survey suggests that because of new technologies, new organizations of production, changing employment conditions and the development of new sectors of production, the complementarity of general, formal schooling, in‐plant training and learning‐by‐doing to capital investment are increasing over time and that general schooling plus on‐the‐job training is more complementary to new technologies than is vocational schooling. The former combination is more likely to give workers the flexibility they need in such changing conditions.

The purpose of this paper is to present a modeling approach for aggregate and disaggregate level models for cluster‐based diffusion of a new technology. The aggregate approach refers to the diffusion modeling of a product at the overall population level, while the disaggregate approach refers to the diffusion process at the individual entity level.

The pattern of diffusion of a new technology in a representative two‐cluster situation is studied. In the aggregate level modeling, a diffusion model is developed in which potential adopters of both clusters learn about the new technology from each other. This is done by a Lotka‐Volterra type of dynamical system of equations. Then, to focus on relatively micro‐level phenomena, such as different propensities of imitation and innovation of firms within a cluster, an agent‐based disaggregate model for cluster‐based diffusion of technology is proposed. In these disaggregate models, the effects of heterogeneity and the inter‐cluster and intra‐cluster distances between the agents are captured.

The results highlight two major points: first, both aggregate and disaggregate models are in agreement with each other, and second, both of the models exhibit a form similar to the Bass model. Thus, consistent with the general theme of why the Bass model fits without decision variables, it is found that the Bass model, when extended appropriately, can be expected to work well also in the cluster‐based technology diffusion situation.

This modeling approach can be applied to the modeling of those situations in which heterogeneous industrial units are present in geographical clusters. It can also be applied in the related contexts such as diffusion of practices (e.g. quality certifications) within a multi‐divisional organization or across various networked clusters.

For a homogenous population, the Bass model has been used extensively to predict the sales of newly introduced consumer durables. In comparison, little attention has been given to the modeling of the technology adoption by the industrial units present in disparate groups, called clusters. The major contribution of this paper is to propose a framework for cluster‐based diffusion of technological products, and then to present an analysis of that framework using two different methodologies.