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The purpose of this paper is to look at the factors driving labour creation in Russia, while paying attention to the role of innovation policy. The study considers innovation variables with indicators linked to social conditions (social filter component) and geographical spillovers for 85 regions during the period 2010-2016.

In particular, the study uses latitude and longitude coordinates to compute the distance between Russian regions according to the Haversine formula. In this manner, it measures the spillovers as the weighted sum of R&D capital stock on the basis of computed distance, according to the accessibility index procedure.

The finding is very important in terms of policy implications for supporting employment. As the results stress that own innovation produces labour creation effects, while knowledge spillovers are labour-saving, the study could conclude that regional innovation policy may have undetermined the objective of an efficient level of absorptive capacity able to benefit positively from external innovation.

The study contributes to the literature by exploring whether geographical spillovers are labour-friendly or labour-saving in Russia.

What is the effect of an increase of migration inflows on the R&D and innovative performance of developing countries? The purpose of this paper is to investigate the impact of migration inflows on the R&D and innovation activity (measured as expenditures on R&D and technological innovations) in Russian regions.

To this end, the authors use data on 85 Russian regions for the period 2010-2016 through a multi-region economic geography model. In particular, the authors test the hypothesis about the importance of migration inflows on R&D and technological innovation activity (H1) and the hypothesis about the importance of immigrants’ (incoming migrants) human capital (measured by the education level of incoming migrants) on R&D and innovation activity (H2).

Empirical findings support the evidence in favour of a positive causal link between innovation and migration inflows. Results of our investigation are important because they suggest useful insights for formulating science and innovation policies in Russia, which is a developing country where the recent policies favouring the technological innovation as the transition period have not yet achieved a satisfying outcome.

This paper increases the knowledge in the field with respect to the existing literature, shedding further light on the migration inflows effects, which is a political topic to manage very relevant in all countries.

The implications of trade on developing economies have generated substantial debates with most studies focussed on “openness in the policy”. Hence, the purpose of this study is to focus on “openness in practice”.

This study uses two models and employed the vector error correction model and structural vector autoregression, first, to examine the sectoral effects; second, to investigate the efficacy of neoclassical and new trade theories; and third, to analyse the effect of trade openness shock on Nigerian labour market performance.

The results of the first model showed that trade openness has an adverse effect on employment and wages in both the agriculture and manufacturing sectors. Likewise, the study concludes that the new trade theory explains trade's behaviour on employment and wages in Nigeria. The second model showed that the effect of error shock from trade openness affected wages more than employment.

The study ignores the distributional effects due to unavailability of data.

The study suggested, amongst others, the need for policies mix on the labour market via a coherent set of initiatives in other to increase the competitiveness of Nigeria in the international market.

Most studies focussed on openness in policy through the channels identified in the literature. However, this study investigates these channels in “openness in practice” and investigates trade theories' efficacy on manufacturing and agricultural sectors in Nigeria, which has been neglected in the literature.

The aim of this paper is to assess the effects of traditional inputs and firms' R&D capital on labour productivity growth.

The study measures the effects of the traditional inputs on firms' productivity growth, through four procedures: OLS in first differences, within group, GMM in first differences and GMM system.

Whatever the specification considered, the more efficient estimates obtained from the GMM system show a similar effect of the firm's R&D stock upon its labour productivity performance.

The results suggest that physical capital plays a more prominent role for European firms than for US ones, while employees are more productive in the USA.

By presenting some empirical evidence on the effects of R&D on labour productivity, at the firm level, the present study makes two main contributions to the existing literature. First, a unique firm‐level database for European and US firms is used. It is self evident that firms in these countries operate in different economic and institutional settings; as a consequence the results identify some robust common effects concerning the two areas considered (the USA versus Europe) at the micro level. Second, service and manufacturing sectors are merged.

Environmental sustainability orientation has emerged to drive firms into eco-friendly production. Yet, the consequence of this new strategic thinking on firms’ green innovations, especially small- and medium-scale enterprises (SMEs), remains unresolved. Recognizing that the connection between environmental sustainability orientation and green innovation may not always be direct, the study theorizes that dynamic capability and entrepreneurial orientation may form part of the boundary conditions that strengthen its effect on small enterprises’ green innovation. The study adjoins the dynamic capability theory with the entrepreneurial orientation theory to test this relationship among small businesses within a developing economy. Results from the partial least squares–structural equation modeling (PLS-SEM) suggest that environmental sustainability orientation will result in green innovation when the SME’s dynamic capability can develop a creative reconfiguration of knowledge and new distinctive resources to support this new strategic direction. Similarly, findings from the study suggest that environmental sustainability orientation will translate into better green innovation outcomes when the SME entrepreneurial orientation has a solid attraction to protect the ecosystem and does not perceive green innovation as a risky enterprise.

Due to excessive carbon dioxide emissions, the world is facing environmental devastation. Energy and environmental innovations are considered to be critical tools in combating the growing CO₂ emissions. Developing these innovations requires extremely high investments in research and development processes, where knowledge is generated as one of the important outputs. This knowledge serves as a basis for innovation development and raising awareness among all relevant stakeholders about excessive environmental degradation. One of the significant sources of knowledge is scientific publications. Therefore, the aim of this research is to examine whether increased CO₂ emissions stimulate the scientific community to publish a greater number of papers, as well as whether the knowledge contained in these publications is utilized in reducing CO₂ emissions. The sample consists of G7 member countries. The time frame of the research is 1996–2019. The dynamic properties of the vector autoregression (VAR) models were summarized using impulse response function and variance decomposition forecast error. In most G7 countries, it has been determined that an increase in scientific production in environmental science and energy leads to a reduction in CO₂ emissions. On the other hand, increased CO₂ emissions affect higher scientific productivity in environmental science and energy only in Canada.

The purpose of this paper is to analyze the correlation between the educational level and the number of children in Italy, where a very low fertility rate may be observed.

Since the number of children ever born is a count variable, Poisson regression is the suitable statistical procedure used to conduct the empirical analysis. First, the authors estimate the correlation between the female's education and her number of children, and then the authors use also partner's education to take into account the family dimension. Furthermore, in the context of fertility, zero observations might be due either to the choice not to have children, or to the impossibility of becoming a mother. For this reason, the authors adopt also a more appropriate tool, that is a zero‐inflated Poisson regression.

From the empirical results, a significant negative correlation may be observed between the level of education and the number of children.

There are other studies in the literature focusing on the correlation between female participation rate and her fertility rate in the Italian case. In those frameworks, the education variable is usually considered as a control variable. The paper's contribution to the literature is twofold: on one hand the authors develop a theoretical model giving an intuition reason of mechanism underlying the fertility behaviour of families; on the other hand, the authors implement more appropriate empirical models to test for this hypothesis, taking education as the main variable.

The Lao People's Democratic Republic (Lao PDR) has a socialist transition economy with a high growth rate of entrepreneurial families compared to other member states of the Association of Southeast Asian Nations (ASEAN) Economic Community. A significant challenge for entrepreneurial family growth includes vigorously seeking the capital assets necessary for their survival, due to ongoing competition. The purpose of this paper is to estimate the capital assets of Laotian entrepreneurial families require to be competitive in the garment industry.

The study adopted a multi-stage sampling technique, with a representative sample size of 350 Laotian entrepreneurial families. The approach was a structural schedule interview at participating families home addresses between August and December 2017. The study uses a three-stage least squares (3SLS) regression model to estimate whether capital assets have a positive association with competition and was organised with the assistance of Stata 16, a software programme.

The main findings show that, using the 3SLS regression model as the instrument, the values are almost identical and fit the data well. The model shows that capital assets (human, financial, social, physical and natural) have a positive and significant relationship with competition. The study suggests that financial capital is a major determinant of the capital assets to build competitive advantage.

To the best of the authors' knowledge, this is the first research to estimate the capital assets of Laotian entrepreneurial families in Vientiane, Lao PDR. The findings contribute to research about existing optimal capital assets that can be used to maintain long-term competitive advantage.

The purpose of this study is to examine how humanitarian organisation size affects inter-organisational coordination and further tested the mediating role of organisational innovativeness, self-organisation in the relationship between humanitarian organisation size and inter-organisational coordination among humanitarian organisations in Uganda.

The study is based on cross-sectional survey; data was collected from 101 humanitarian organisations. The analysis of the proposed hypotheses was done with the help of PLS-SEM using SmartPLS version 3.3.0 for professionals.

The results show that humanitarian organisation size significantly relates with inter-organisational coordination. In addition, self-organisation and organisational innovativeness play a complementary role between humanitarian organisation size and inter-organisational coordination.

The findings of this research provide useful insights into the role of humanitarian organisation size in boosting inter-organisational coordination in humanitarian relief delivery. High levels of self-organisation and organisational innovativeness not only improve inter-organisational coordination in humanitarian relief delivery but also enhance the transformation of humanitarian organisation size benefits into inter-organisational coordination.

This research is one of the few studies that investigated the effect of humanitarian organisation size and inter-organisational coordination. It also brings into the limelight the mediating role of self-organisation and organisational innovativeness between humanitarian organisation size and inter-organisational ordination in humanitarian relief delivery.

In the context of collaborative research and development (R&D), multi-actor participation and multi-resource integration of technological knowledge has become the mainstream paradigm for the R&D and spillover of industry generic technology (GT). As GT's core characteristics, “fundamentality” and “externality,” make differential requests on knowledge bases regarding the R&D and spillover of GT (SGT). Knowledge breadth can enhance the generality of technology. The purpose of this paper is to integrate “generic technology R&D” and “generic technology spillover” into a single study, and try to solve the theoretical problem of “whether broader mean more general?”

This paper collects and collates the patent data from the two patent databases of Derwent and SooPAT, and then makes an empirical analysis of the patent data collected by the authors with the data analysis software Stata.

Taking 352 strategic emerging firms in China as the sample, this paper examined the effects of general knowledge breadth (GKB) and specific knowledge breadth (SKB) on the R&D and SGT. The authors concluded that both general and SKB have a positive effect on the R&D of GT (RGT), and the latter has a greater effect. There is a significant inverted U-shaped relationship between SKB and SGT.

The theoretical contributions of this paper are as follows. GT can effectively link different technologies and knowledge fields (Gambardella and Giarratana, 2013; Appio et al., 2017a, b). Therefore, existing studies regard the role of knowledge breadth on the R&D and SGT as an existing hypothesis. This paper challenges such hypothesis in two ways. First, this paper divides knowledge breadth into “general knowledge breadth” and “specific knowledge breadth” in response to the insufficient division of knowledge breadth in previous research, although some existing studies have examined the antecedents of the R&D and SGT from the perspective of R&D and SGT. Thus, the authors define GKB as the scope of context-free knowledge and SKB as the scope of context-specific knowledge, both of which shows differential nature, source and application. Second, this paper decomposes the effect of knowledge breadth on RGT, as well as on SGT, basing on distinguishing the SKB from GKB. Existing research reaches a consensus of the positive role of knowledge breadth, no matter on RGT or SGT (e.g. Schmidt et al., 2016; Appio et al., 2017a, b). Yet, such hypothesis ignores the refinement and decomposition of “knowledge breadth” in the research field of R&D and SGT, which is essential in promoting the development of GT theory. In this paper, the authors find that these two types of knowledge breadths play different roles in the RGT, and especially SKB plays a double-edged sword effect on the SGT.