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The purpose of this paper is to examine the determinants of innovation outputs proxied by number of patent applications, trademarks and industrial designs in developing countries.

The paper employs a panel data and Negative Binomial method to analyse the main determinants affecting the innovation outputs.

The results implicitly suggest that providing a fertile ground to attract more foreign direct investment (FDI) can lead to much better innovation outputs. The study also strongly supports the role of institutions and governance for increasing innovation activities in developing economies as indicated by positive impacts of governance factors in the model. However, the impact of economic freedom indicators on improving innovation outputs is mixed.

This paper contributes to the existing literature in two ways: it examines the effect of FDI and research and development on innovation of selected developing countries; and the study uses a panel data approach to increase the accuracy of the results through exploiting the significant variations of innovation outputs across countries, while controlling for a larger number of innovation outputs and product determinants. To the authors knowledge, this is the first empirical study on the behaviour of innovation outputs for developing countries.

This paper aims to investigate the relationship between structural change and economic growth for a panel of four developing countries, namely, Malaysia, Nigeria, Turkey and Indonesia over 1960-2010.

The study extent the growth equation by incorporating degree of openness, labour and investment and construct structural change indices – modified Lilien index and the norm of absolute values. It utilizes the recently developed panel cointegration techniques to test and estimate the long-run equilibrium of the growth equation.

The results confirm that structural change and economic growth are cointegrated at the panel level, indicating the presence of long-run equilibrium relationship. However, the impact of structural change on economic growth seems to be small and evolve slowly.

The findings indicate the need for policymakers to identify the binding constraints that impede growth and the importance of institutionalize policy to encourage investment in productive sectors.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.