scholarly journals PEMETAAN VARIABEL-VARIABEL PEMBENTUK INDEKS DAYA SAING DAERAH MENGGUNAKAN METODE MICMAC

2021 ◽  
Vol 5 (1) ◽  
pp. 1-8
Author(s):  
Hari Soesanto
Keyword(s):  
Market Efficiency ◽  
Analysis Method ◽  
Regional Competitiveness ◽  
Innovation Ecosystem ◽  
Financial Access ◽  
Micmac Analysis ◽  
National Competitiveness ◽  
Initial Comparison ◽  
Key Variables ◽  
Competitiveness Index

Indeks daya saing daerah sebagai pembentuk indeks daya saing nasional sangat penting untuk diketahui oleh banyak pihak. Hal ini karena melalui indeks daya saing daerah dapat diketahui dimensi dan varibel yang memerlukan perhatian lebih. Saat ini, pemetaan indeks daya saing daerah sudah dilakukan oleh Kementerian Riset dan Teknologi pada tahun 2019 dengan 4 kategori dan 12 varibel. Dari pemetaan tersebut menghasilkan kesimpulan dimensi yang paling berpengaruh yaitu ekosistem inovasi. Penelitian ini bertujuan untuk melakukan pemetaan varibel-varibel yang mempengaruhi daya saing daerah dengan metode analisis MICMAC sebagai komparasi awal dari laporan yang sudah diterbitkan oleh Kementerian Riset dan Teknologi. Hasil penelitian mengindikasikan bahwa variabel kunci atau variabel penggerak yang menjadi pemicu daya saing daerah berkelanjutan yaitu terdiri dari dua variabel pada kategori faktor penguat, yaitu variabel kelembagaan dan infrastruktur; serta dua variabel pada kategori pasar yaitu variabel efisiensi pasar dan akses keuangan.   ABSTRACT The regional competitiveness index, which forms the national competitiveness index, is significant to be recognized by many parties because the regional competitiveness index can identify dimensions and variables that require more attention. At present, the mapping of the regional competitiveness index was carried out by the Ministry of Research and Technology in 2019, resulting in 4 categories and 12 variables. This mapping concludes that the most influential dimension is the innovation ecosystem. This study aims to map the variables that affect regional competitiveness using the MICMAC analysis method as an initial comparison of the Ministry of Research and Technology reports. The results indicated that the key variables or driving variables that trigger sustainable regional competitiveness consist of two variables: the reinforcing factor category (institutional and infrastructure variables) and two variables in the market category (market efficiency and financial access variables).

Measuring regional competitiveness through agricultural indices of productivity

2017 ◽  
Vol 13 (2) ◽  
pp. 78-95 ◽  
Author(s):  
Francisco Coronado ◽  
Vincent Charles ◽  
Rocky J. Dwyer
Keyword(s):  
Natural Resources ◽  
Agricultural Production ◽  
Social Implications ◽  
Agricultural Activity ◽  
Regional Competitiveness ◽  
Content Type ◽  
Soil Production ◽  
National Competitiveness ◽  
Productivity Indices ◽  
Competitiveness Index

Purpose The purpose of this paper is to incorporate factors that characterize the agricultural activity as productivity indices to compute the agricultural competitiveness of regions in order to rank the regions, and compare the results with those obtained by applying other commonly used social and economic indicators. Design/methodology/approach The authors identify regional factors related to the use of water, soil, production, revenues, and rural population, which conform a total of six productivity indices, that the authors then employ to calculate the regional agricultural competitiveness index. Findings The agricultural-related indices are informative in supporting the regional ranking related to resources and technology utilization. The results reveal that the coastal regions are the most competitive when compared to the regions located in the highlands and the jungle. Nevertheless, in contrast with other existing competitiveness rankings, the present study identifies the regions with the greatest potential for agriculture. Research limitations/implications The authors identify the regions which have a higher potential of development considering the natural resources and agricultural production. The authors hope that this paper can assist regional and national policymakers in their endeavor to improve regional and national competitiveness. Practical implications The authors identify the regions with a higher potential of development considering natural resources and agricultural production and the possibilities to improve their competitiveness. Social implications The study also bears social implications, given that the rural activities in Peru are carried out by approx. 7 million inhabitants, whose contribution to the gross domestic product (GDP) is as much as 7 percent, making use of about 94 percent of the available water. Originality/value The originality of the present paper resides in the attempt to compute a regional competitiveness index by taking agricultural resources as determinant factors. The authors rank the regions based on their agricultural competitiveness.

Does Enhancing of the Competitiveness Influence on Foreign Direct Investments in Western Balkan Countries?

2016 ◽  
Vol 1 (2) ◽  
pp. 164 ◽  
Author(s):  
Matea Zlatković
Keyword(s):  
Market Efficiency ◽  
Foreign Direct Investments ◽  
Global Competitiveness ◽  
Technological Readiness ◽  
Regional Market ◽  
National Competitiveness ◽  
Good Market ◽  
World Economic ◽  
Global Competitiveness Index ◽  
Per Capita

Foreign direct investments present a valuable source of national competitiveness as they have attributes of capital flows provide knowledge and technology transfer from one country to target country. In this paper are used variables defined by World Economic Forum which construct Global Competitiveness Index for assessing competitiveness of the country. The purpose of the research is to examine does the national competitiveness increase enhance the level of FDI flows in transition Western Balkan economies that are not yet full members of European Union. The findings claim that larger increase in FDI per capita stocks in majority analyzed countries would have if making infrastructure more competitiveness, accelerate their technological readiness and improve innovation while certain countries should work on health and primary education and higher education and training. According to the results, there is no correlation between FDI flows and macroeconomic environment, institutions, development of financial markets, good market efficiency, labor market efficiency and business sophistication. Applying benchmark method, it is established the most competitive WB country as benchmark value for other transition countries in its neighborhood for enhancing their competitiveness, specially in the regional market. Also, it is obtained what if analysis to detect potential rise of FDI per capita stocks as a consequence of potential changes in some competitiveness variables. It is also calculated the potential increase in FDI/capita due to similar changes in different competitiveness variables.

scholarly journals Regional Climate Change Competitiveness—Modelling Approach

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3704
Author(s):  
Agnieszka Karman ◽  
Andrzej Miszczuk ◽  
Urszula Bronisz
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Measurement Scale ◽  
Practical Application ◽  
Adaptation To Climate Change ◽  
Regional Competitiveness ◽  
The Face ◽  
Competitiveness Index ◽  
Modelling Approach

The article deals with the competitiveness of regions in the face of climate change. The aim was to present the concept of measuring the Regional Climate Change Competitiveness Index. We used a comparative and logical analysis of the concept of regional competitiveness and heuristic conceptual methods to construct the index and measurement scale. The structure of the index includes six broad sub-indexes: Basic, Natural, Efficiency, Innovation, Sectoral, Social, and 89 indicators. A practical application of the model was presented for the Mazowieckie province in Poland. This allowed the region’s performance in the context of climate change to be presented, and regional weaknesses in the process of adaptation to climate change to be identified. The conclusions of the research confirm the possibility of applying the Regional Climate Change Competitiveness Index in the economic analysis and strategic planning. The presented model constitutes one of the earliest tools for the evaluation of climate change competitiveness at a regional level.

scholarly journals Development Analysis of Global Competitiveness Index of ASEAN-7 Countries and Its Relationship on Gross Domestic Product

2019 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
Tongam Sihol Nababan
Keyword(s):  
Gross Domestic Product ◽  
Economic Performance ◽  
Domestic Product ◽  
Basic Requirement ◽  
Analysis Method ◽  
Global Competitiveness ◽  
Government Bureaucracy ◽  
Global Competitiveness Index ◽  
Competitiveness Index ◽  
Development Analysis

The objectives of the research are: (1) to investigate the development of global competitiveness index (GCI) of ASEAN-7 countries as an illustration of economic performance and potentiality, (2) to investigate which factors or pillars are drivers for the improvement of GCI ASEAN-7 countries, and (3) to analyze the effect of Gross Domestic Product (GDP) on GCI of ASEAN-7 countries. The analysis method used in calculating the weight of the contribution of each pillar to changes in the competitiveness index, and determining the effect of GDP on GCI, a Semi-Logarithmic Regression analysis is used. The result shows that during the period of year 2008/2009 to the year of 2016/2017, the rank and index of GCI of each ASEAN-7 countries continue to increase. The pillars of the basic requirement subindex still dominate the largest contribution to the improvement of the competitiveness index for Indonesia, Philippines, Thailand, Cambodia, and Vietnam. As for Malaysia and Singapore sub-indexes of efficiency enhancers and innovation-sophistication have been able to give the largest contribution to the improvement of GCI.  The GDP of ASEAN-7 countries has a positive and significant impact on the improvement of global competitiveness index, except for Thailand. The most problematic factors in improving the competitiveness index are corruption, inadequately educated labour, access to financing, tax regulations, and inefficient government bureaucracy.

A two-stage OGI approach to compute the regional competitiveness index

2019 ◽  
Vol 29 (2) ◽  
pp. 78-95 ◽  
Author(s):  
Vincent Charles ◽  
Tomonari Sei
Keyword(s):  
Resource Curse ◽  
Well Being ◽  
Academic Community ◽  
Factor Level ◽  
Regional Competitiveness ◽  
Two Stage ◽  
Content Type ◽  
Positive Correlation ◽  
Level Information ◽  
Competitiveness Index

Purpose Regional competitiveness refers to the capacity of a region to manage its resources and competencies to increase the well-being of its people. Measuring regional competitiveness is, thus, a major consideration for policymakers, businesses and the academic community in their endeavour to improve the same. This paper aims to demonstrate a novel way to calculate the regional competitiveness index under a two-stage objective general index (OGI) framework. Design/methodology/approach The authors compute the regional competitiveness index under a two-stage OGI framework. In the first stage, they aggregate the sub-factor level information into a factor level index; in the second stage, they use the factor level index to obtain a regional competitiveness index. Findings The authors discuss the properties of the proposed index in detail. They further analyse five periods of regional competitiveness of Peru spanning the period 2008-2015. Among others, the results reveal the existence of the resource curse of the mining regions of Peru. Practical implications The paper is a contribution to the practical measurement of competitiveness. Social implications The calculation of a regional competitiveness index is vital for improving the competitiveness of the countries and for reducing regional inequalities. Originality/value When compared to the existent methods available in the literature, the advantage of the proposed method resides in the fact that the derived index has a positive correlation with the factor-level indices and the factor-level indices have a positive correlation with the sub-factor-level information.

Developing a competitiveness index at sub-national level for India: an economic growth measure

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nirmalkumar Singh Moirangthem ◽  
Barnali Nag
Keyword(s):  
Economic Growth ◽  
Longitudinal Study ◽  
Panel Data ◽  
Regional Growth ◽  
Generalized Method Of Moments ◽  
Regional Competitiveness ◽  
Regional Economic ◽  
Content Type ◽  
Economic Disparity ◽  
Competitiveness Index

PurposeThe objective of this study is threefold–first, to develop a Regional Competitiveness Index (RCI) for measuring competitiveness of sub-national regions for India; second, to test this index for its ability to explain regional growth, which validates usage and applicability of this index; and third, to further investigate if the competitiveness of states is in turn caused by economic growth, i.e. it is tested if there is a bidirectional causality between competitiveness and regional growth.Design/methodology/approachThe data of indicators used in the index are from sources available freely in public domain. The competitiveness index is constructed using equal weightage supported by principal component analysis (PCA) technique. The causal relationship analysis is done using panel data of 10 years from 2008 to 2017 for 32 Indian states/union territories. The generalized method of moments (GMMs) is used for this dynamic regression estimation.FindingsBased on RCI score, states have been ranked and through rank analysis, the authors observe the performance status of these sub-national regions and are able to categorize them as improving, no change or deteriorating in regional competitiveness. Using the GMM estimation, the association between RCI and economic growth is found to be significant at 10% level. This shows that regional competitiveness as captured through the RCI score is able to explain regional economic growth and economic disparity among the sub-national units. Further, that RCI score is found to Granger-cause growth, while growth does not lead to better RCI scores. This establishes the usefulness of RCI as an important policy variable to compare states and provide direction for sectoral reforms.Research limitations/implicationsThe limitations of the study include (1) broad assumption that these sub-national regions belong to a uniform macro-economic and technology environment, and (2) data constraints as it is a longitudinal study. The study implies that the composite index could capture differences in regional competitiveness explaining regional economic disparity and that competitiveness causes higher economic growth and not vice versa.Practical implicationsThe RCI score can prove to be a useful indicator of economic performance of different states and can be used by national and state policymakers to compare and assess regional disparity among different states. The pillar-wise scores will be useful for in-depth study of weakness and strength of the sub-national territories.Originality/valueConstruction of an RCI for sub-national territories and analysis of panel data for longitudinal study of ten years is unique in the regional competitiveness literature.

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