The Effects of Crude Oil Prices, Exchange Rates, and Inflation on the Level of Investment in Indonesia
DOI:
https://doi.org/10.47654/v28y2024i3p106-126Keywords:
Crude oil price, exchange rate, inflation, investment, ARDL modelAbstract
Purpose: The level of investment in a country can be influenced positively or negatively by factors such as crude oil prices, exchange rates, and inflation, all of which are closely tied to its economic conditions. Therefore, this study aims to examine the long-term and short-term effects and determine the contribution of crude oil prices, exchange rate, and inflation on investment in Indonesia.
Design/methodology/approach: Annual time series data from 1990 to 2023 were utilized to assess the effects. Accordingly, the data were analyzed using an autoregressive distributed lag model, which revealed both the long-term and short-term effects.
Findings: The results obtained from the statistical analysis, carried out using ARDL and ECM-ARDL models, showed that exchange rates had a significant influence on investment in the long term. However, crude oil prices and inflation did not affect investment. The depreciation of the IDR/USD exchange rate also decreased investments. Crude oil prices and exchange rates affected investment in the short term, and were not influenced by inflation. The most significant independent variable impacting investment was the exchange rate, followed by crude oil prices and inflation. The study result is significant because it can be used as a consideration or material for policy decisions by the government. The result provides a quantitative framework that can significantly improve governmental and corporate decision-making processes under macroeconomic uncertainty. This offers a valuable tool for strategic investment planning as a core concern of Decision Sciences.
Practical implications: All the findings in this investigation hold significant policy implications for the government as decision-makers. Accordingly, government decisions related to these policy implications include taking actions such as establishing domestic crude oil price policies and implementing government monetary and fiscal measures to stabilize exchange rates and control inflation, which were considered crucial steps for promoting investment.
Originality/value: This study represents the initial empirical investigation examining the long and short-term influences of the above factors on investment in Indonesia because, based on observation, a similar investigation has not been carried out in Indonesia. Furthermore, it presents a ranking of the contributions of each independent variable (crude oil price, exchange rate, and inflation) to investment, addressing a gap that has not been covered in previous explorations.
References
Abate, Y. (2016). Determinants of domestic private investment in Ethiopia from 1971 to 2014: An empirical analysis. The International Journal of Research Publication, 5(9), 86–95.
Adam, P., Rostin, R., & Saenong, Z. (2018a). The influence of fuel prices and unemployment rate towards the poverty level in Indonesia. International Journal of Energy Economics and Policy, 8(3), 37-42.
Adam, P., Saidi, L. O., Tondi, L., & Sani, L. O. A. (2018b). The causal relationship between crude oil price, exchange rate and rice price. International Journal of Energy Economics and Policy, 8(1), 90-94.
Aharon, D. J., Aziz, M. I. A., & Kalli, I. (2023). Oil price shocks and inflation: A cross-national examination in the ASEAN5+3 countries. Resources Policy, 82, May 2023, 103573. https://doi.org/10.1016/j.resourpol.2023.103573.
Alekhina, V., & Yoshino, N. (2018). Impact of world oil prices on an energy exporting economy including monetary policy. ADBI Working Paper, No. 828. Tokyo: Asian Development Bank Institute. Extracted from https://www.adb.org/publications/impact-world-oil-prices-energy-exporting-economy-including-monetary-policy.
Archer, C., Junior, P. O., Adam, A. M., Asafo-Adjei, E., & Baffoe, S. (2022). Asymmetric dependence between exchange rate and commodity prices in Ghana. Annals of Financial Economics, 17(02), 2250012. https://doi.org/10.1142/S2010495222500129.
Asteriou, D., & Hall, S. G. (2011). Applied econometrics. London : Palgrave Macmillan.
Ayeni, R. K. (2020). Determinants of private sector investment in a less developed country: a case of the Gambia. Cogent Economics & Finance, 8(1), 1794279. https://doi.org/10.1080/23322039.2020.1794279.
Bambe, B. W. W. (2023). Inflation targeting and private domestic investment in developing countries. Economic Modelling, 125, 106353.
Banerjee, R., Hofmann, B., & Mehrotra, A. (2022). Corporate investment and the exchange rate: The financial channel. International Finance, 25(3), 296-312.
Bhatta, S. R., Adhikari, P., & Byanjankar, R. (2020). Choice of regression models in time series data. Economic Journal of Development, 29, 1-2.
Binz, O., Ferracuti, E., & Joobs, P. (2023). Investment, inflation, and the role of internal information systems as a transmission channel. Journal of Accounting and Economics, 28 Juli 2023, 101632. https://doi.org/10.1016/j.jacceco.2023.101632.
Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society Series B: Statistical Methodology, 37(2), 149-163. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x.
Brown, S., & Yucel, M. (2002). Energy prices and aggregate economic activity: an interpretative survey. Quarterly Review of Economics and Finance, 42(2), 193–208. https://doi.org/10.1016/S1062-9769(02)00138-2.
Budescu, D. V. (1993). Dominance analysis: A new approach to the problem of relative importance of predictors in multiple regression. Psychological Bulletin, 114(3), 542-551. https://doi.org/10.1037/0033-2909.114.3.542.
Chen, L., Yuan, Y., & Zhao, N. (2022). The effect of oil price uncertainty on corporate investment in the presence of growth options: Evidence from listed companies in China (1998–2019). The North American Journal of Economics and Finance, 62, 101779. https://doi.org/10.1016/j.najef.2022.101779.
Chen, X., Li, Y., Xiao, J., & Wen, Y. (2020). Oil shocks, competition, and corporate investment: Evidence from China. Energy Economics, 89, June 2020, 104819. https://doi.org/10.1016/j.eneco.2020.104819.
Cheng, Y., Hui, Y., Liu, S., & Wong, W. K. (2022). Could significant regression be treated as insignificant: An anomaly in statistics. Communications in statistics: Case Studies, Data Analysis and Applications, 8(1), 133-151. https://doi.org/10.1080/23737484.2021.1986171.
Cheng, Y., Hui, Y., McAleer, M., & Wong, W. K. (2021). Spurious relationships for nearly non-stationary series. Journal of Risk and Financial Management, 14(8), 366. https://doi.org/10.3390/jrfm14080366.
Čipčić, M. L. (2021). The impact of oil prices on investment in croatia. Dubrovnik International Economic Meeting, 6(1), 108-117. https://doi.org/10.17818/DIEM/2021/1.11.
DATAtab-Team. (2025). DATAtab: Online Statistics Calculator. DATAtab e.U. Graz, Austria. Extracted from https://datatab.net.
Davidson, R., & Mackinnon, J. G. (1993). Estimation and inference in econometrics. New York: Oxford University Press.
Diabate, N. (2016). An Analysis of Long Run Determinants on Domestic Private Investment in Côte d'Ivoire. European Scientific Journal, 12(28), 240-251. http://dx.doi.org/10.19044/esj.2016.v12n28p240.
Dogrul, H. G., & Soytas, U. (2010). Relationship between oil prices, ınterest rate, and unemployment: Evidence from emerging market. Energy Economic, 32(6), 1523-1528. https://doi.org/10.1016/j.eneco.2010.09.005.
Drakos, K., & Konstantinous, P. T. (2012). Investment decisions in manufacturing: Assessing th effect of real oil price and their uncertainty. Journal of Applied Econometrics, 2012. https://doi.org/10.1002/jae.2297.
Elneel, F. A., & Almulhim, A. F. (2022). The Effect of Oil Price shock on Saudi Arabia’s economic growth in the light of vision 2030 “A combination of VECM and ARDL models”. Journal of the Knowledge Economy, 13, 3401-3423. https://doi.org/10.007/s13132-021-00841-7.
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica. 50, 987–1007. https://doi.org/10.2307/1912773.
Evans, O. (2023). The investment dynamics in renewable energy transition in Africa: the asymmetric role of oil prices, economic growth and ICT. International Journal of Energy Sector Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJESM-03-2022-0002.
Farooq, U., Tabash, M. I., Hamouri, B., Daniel, L. N., & Safi, S. K. (2023). 2023. Nexus between Macroeconomic factors and Corporate Investment: Empirical Evidence from GCC Markets. International Journal of Financial Studies, 11(35). https://doi.org/10.3390/ijfs11010035.
Fuller, W. A. (1976). Introduction to statistical time series. New York: John Wiley & Son Ltd.
Ghouse, G., Khan, S. A., & Rehman, A. U. (2018). ARDL model as a remedy for spurious regression: problems, performance and prospectus. MPRA Paper No. 83973, Pakistan Institute of Development Economics. Extracted from https://mpra.ub.uni-muenchen.de/83973/1/MPRA_paper_83973.pdf.
Ghouse, G., Khan, S. A., Rehman, A. U., & Bhatti, M. I. (2021). ARDL as an elixir approach to cure for spurious regression in nonstationary time series. Mathematics, 9, 2839. https://doi.org/10.3390/math9222839.
Ghouse, G., Rehman, A. U., & Bhatti, M. I. (2024). Understanding of causes of spurious associations: Problems and Prospects. Journal of Statistical Theory and Applications, 23(1), 44-66. https://doi.org/10.1007/s44199-024-00072-0.
Gohar, R., Bhatty, K., Osman, M., Wong, W. K., & Chang, B. H. (2022). Oil prices and sectorial stock indices of Pakistan: Empirical evidence using bootstrap ARDL model. Advances in Decision Sciences, (4), 1-27. https://doi.org/10.47654/v26y2022i4p50-77.
Golberg, L. S. (1993). Exchange Rates and Investment in United States Industry. The Review of Economics and Statistics, 75(4), 575-588. https://doi.org/10.2307/2110011
Granger, C. W. J., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111–20. https://doi.org/10.1016/0304-4076(74)90034-7
Greene, J., & Villanueva, D. (1990). Determinants of private investment in LDCs. Finance & Development, International Monetary Fund, December 1990, 40-42. Extracted from https://www.elibrary.imf.org/downloadpdf/journals/022/0027/004/article-A013-en.pdf
Gujarati, D. N. (2004). Basic Econometrics. New York: McGraw− Hill.
Gujarati, D. N., & Porter, D. C. (2010). Essentials of Econometrics, fourth edition. New York: McGraw-Hill Companies Inc.
Hamilton, J. D. (1983). Oil and the macroeconomy since World War II. The Journal of Political Economy, 91(2), 228–248. https://doi.org/10.1086/261140.
Harchaoui, T., Tarkhani, F., & Yuen, T. (2005). The Effects of the Exchange Rate on Investment: Evidence from Canadian Manufacturing Industries. Staff Working Papers 05-22, Bank of Canada. https://www.bankofcanada.ca/2005/08/working-paper-2005-22/.
Hassler, U. W., & Wolters, J. (2006). Autoregressive distributed lag models Cointegration. Allgemeines Statistisches Archiv, 90, 59-74. Https://doi.org/10.1007/s10182-006-0221-5.
He, Z., Zhou, F., Xia, X., Wen, F., & Huang, Y. (2019). Interaction between Oil Price and Investor Sentiment: Nonlinear Causality, Time- Varying Influence, and Asymmetric Effect.
Emerging Markets Finance and Trade, 55(12), 2756-2773. https://doi.org/10.1080/1540496X.2019.1635450.
Heij, C., De Boer, P., Franses, P. H., Kloek, T., & Van Dijk, H. K. (2004). Econometric methods with applications in business and economics. New York : Oxford University Prss.
Hui, Y., Wong, W. K., Bai, Z., & Zhu, Z. Z. (2017). A new nonlinearity test to circumvent the limitation of Volterra expansion with application. Journal of the Korean Statistical Society, 46, 365-374.
IHS Markit. (2022). EViews 13 user’s guide II. Englewood, USA: IHS Global Inc.
Imane, E., Chang, B. H., Elsherazy, T. A., Wong, W. K., & Uddin, M. A. (2023). The external exchange rate volatility influence on the trade flows: Evidence from nonlinear ARDL model. Advances in Decision Sciences, 27(2), 75-98. https://doi.org/10.47654/v27y2023i2p75-98.
Jaiswal, R. (2023). From humble beginnings to a global economic powerhouse: A comprehensive study of India’s economic development through the lens of selected macroeconomic indicators (1990–2020). Annals of Financial Economics, 18(03), 2350003. https://doi.org/10.1142/S2010495223500033.
Kandemir Kocaaslan, O. (2021). Are the responses of output and investment to oil price shocks asymmetric?: The case of an oil-importing small open economy. Empirical Economics, 61(5), 2501-2516. https://doi.org/10.1007/s00181-020-01983-4.
Kilian, L., & Vigfusson, R. J. (2011). Are the responses of the US economy asymmetric in energy price increases and decreases? Quantitative Economics, 2(3), 419–453. https://doi.org/10.3982/QE99.
Koop, G. (2006). Analysis of financial data. Chichester : John Wiley & Son Ltd.
Kripfganz, S., & Schneider, D. C. (2023). Ardl: Estimating autoregressive distributed lag and equilibrium correction models. The Stata Journal, 23(4), 983–1019. Https://doi.org/10.1177/1536867X231212434.
Lean, H. H., McAleer, M., & Wong, W. K. (2010). Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach. Energy Economics, 32(5), 979-986. https://doi.org/10.1016/j.eneco.2010.05.001.
Lean, H. H., McAleer, M., & Wong, W. K. (2015). Preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the Global Financial Crisis. International Review of Economics & Finance, 40, 204-216. https://doi.org/10.1016/j.iref.2015.02.019
Maddala, G. S. (2001). Introduction to econometrics, third edition. Chichester : Wiley & Son Inc.
Mallick, H., Mahalik, M. K., & Sahoo, M. (2017). Is Crude Oil Price Detrimental to Domestic Private Investment for an Emerging Economy? The Role of Public Sector Investment and Financial Sector Development in an Era of Globalization. Energy Economic, 69(C), 307-324. https://doi.org/10.1016/j.eneco.2017.12.008.
Mamun, T. G. M. A. (2025). Replacing ARDL? Introducing the NSB-ARDL Model for Structural and Asymmetric Forecasting. Working Paper. Cornell University. Extracted from
https://doi.org/10.48550/arXiv.2504.09646
Maydybura, A., Gohar, R., Salman, A., Wong, W. K., & Chang, B. H. (2023). The asymmetric effect of the extreme changes in the economic policy uncertainty on the exchange rates: evidence from emerging seven countries. Annals of Financial Economics, 18(02), 2250031. https://doi.org/10.1142/S2010495222500312.
Mizutani, F., & Tanaka, T. (2010). Productivity effects and determinants of public infrastructure investment. The Annals of Regional Science, 44, 493-521. https://doi.org/10.1007/s00168-008-0279-y
Moore, D. S., McCabe, G. P., Alwan, L. C., Craig, B. A., & Duckworth, W. M. (2011). The practice of statistics for business and economics (third edition). New York: W. H. Freeman and Company.
Mukhamediyev, B., Zhamanbayev, S., & Mukhamediyeva, A. (2024). Central bank independence and oil prices impact on macroeconomic indicators. International Journal of Energy Economics and Policy, 14(3), 9–17. https://doi.org/10.32479/ijeep.15621.
Muthalib, D. A., Adam, P., Azis, M. I., Nur, M., Makkulau, A. R., Tambunan, R., ... & Putera, A. (2026). The effect of crude oil prices and inflation on the profitability of government banks in Indonesia. Multidisciplinary Science Journal, 8(1), 2026047-2026047. https://doi.org/10.31893/multiscience.2026047
Narayan, P. K. (2005). The saving and investment nexus for China: evidence from cointegration tests. Applied Economics, 37, 1979–1990. http://dx.doi.org/10.1080/00036840500278103.
Naufal, M. J., Ompusunggu, D. P., Sinaga, R. K., Sitohang, M. D. A., Gunawan, T. N., Simatupang, M., Salsabila, N. S., Simanullang, T., & Hutasoit, B. T. (2025). A Theoretical Study of Multicollinearity and Linearity in Econometric Models for Economic Research. Balance Jurnal Ekonomi, 21(1), 43-52.
Noman, M., Maydybura, A., Channa, K. A., Wong, W. K., & Chang, B. H. (2023). Impact of cashless bank payments on economic growth: Evidence from G7 countries. Advances in Decision Sciences, 27(1), 1-20. https://doi.org/10.47654/v27y2023i1p1-22.
Pesaran, M. H. (2015). Time series and panel data econometrics. New York: Oxford University Press.
Pesaran, M. H., & Shin, Y. (1999). An autoregressive distributed lag modelling approach to cointegration analysis (Vol. 9514, pp. 371-413). Cambridge, UK: Department of Applied Economics, University of Cambridge. https://doi.org/10.1017/CCOL521633230.011
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Economics, 16, 289–326. https://doi.org/10.1002/jae.616
Philips, A. Q. (2022). How to avoid incorrect inferences (while gaining correct ones) in dynamic models. Political Science Research and Methods, 10(4), 879-889. https://doi.org/10.1017/psrm.2021.31
Pilbeam, K. (2023). International finance (Fifth Edition). London : Bloomsbury Academic.
Ramachandran, K. M., & Sokos, C. P. (2021). Mathematical statistics with applications in R, third edition. London: Elsevier Inc.
Reifman, A., & Keyton, K. (2010). Winsorize. In N. J. Salkind (Ed.), Encyclopedia of Research Design (pp. 1636-1638). Thousand Oaks, CA: Sage
Rosnawintang, R., Tajuddin, T., Adam, P., Pasrun, Y. P., & Saidi, L. O. (2021). Effects of crude oil prices volatility, the internet and inflation on economic growth in ASEAN-5 countries: A panel autoregressive distributed lag approach. International Journal of Energy Economics and Policy, 11(1), 15-21. https://doi.org/10.32479/ijeep.10395
Rumbia, W. A., Jabani, A., Adam, P., Abbas, B., Nur, M., & Pasrun, Y. P. (2023). Effect of exchange rates and information and communication technology on Indonesia’s economic growth: A nonlinear autoregressive distributed lag approach. Journal of Telecommunications and the Digital Economy, 11(4), 1-20. https://doi.org/10.18080/jtde.v11n4.743
Sadath, A. C., & Acharya, R. H. (2022). Effects of exchange rate fluctuation on investment: Firm level evidence from India. In: Yoshino, N; Paramik, R. N., Kumar, A. S. (eds), Studies on international economics and finance. India Studies in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-16-7062-6_26
Saidi, L. O., Adam, P., Rahim, P., & Rosnawintang, R. (2019). The effect of crude oil prices on economic growth in South East Sulawesi, Indonesia: An application of autoregressive distributed lag model. International Journal of Energy Economics and Policy, 9(2), 194-198. https://doi.org/10.32479/ijeep.7322
Sam, C. Y., McNown, R., & Goh, S. K. (2019). An augmented autoregressive distributed lag bounds test for cointegration. Economic Modelling, 80, 130–141. https://doi.org/10.1016/j.econmod.2018.11.001
Sethi, D., Wong, W. K., & Acharya, D. (2018). Can a disinflationary policy have a differential impact on sectoral output. A look at sacrifice ratios in OECD and non-OECD countries. Margin: The Journal of Applied Economic Research, 12(2), 138-170.
Shin, Y., Yu, B. C., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In: Sickels, R., Horrace, W., editors. Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (281-314). New York: Springer.
Shintani, A. (2014). Primer of statistics in dental research: Part I. Journal of Prosthodontic Research, 58(1), 11-16. https://doi.org/10.1016/j.jpor.2013.12.006
Swift, R. (2006). Measring the effects of exchange rate changes on investment in Australia manufacturing industry. Economics Record, 82(S1), S19-S25.
Tang, J., Sriboonchitta, S., Ramos, V., & Wong, W. K. (2016). Modelling dependence between tourism demand and exchange rate using the copula-based GARCH model. Current Issues in Tourism, 19(9), 876-894.
Thadewald, T., & Buning, H. (2007). Jarque-Bera test and its competitors for testing normality- A power comparison. Journal of Applied Statistics, 34(1), 87-105. https://doi.org/10.1080/02664760600994539.
Wale, Y. (2015). Determinants of Private Investment in Ethiopia: Time Series Analysis. Proceedings of the 9th Annual National Student Research Forum. London: St. Mary’s University. http://repository.smuc.edu.et/bitstream/123456789/2494/1/Yechale%20Wale.pdf
Wang, K. H., Liu, L., Li, X., & Oana-Ramona, L. (2022). Do oil price shocks drive unemployment? Evidence from Russia and Canada. Energy, 253, 124107. https://doi.org/10.1016/j.energy.2022.124107
Wang, L., & Wissel, J. (2013). Mean-variance hedging with oil futures. Finance & Stochastics, 17(4), 1-43. Https://doi.org/10.1007/s00780-013-0203-x.
Wang, Y., Wu, C., & Yang, L. (2013a). Oil price shocks and stock market activities: evidence from oil-importing and oil-exporting countries. Journal of Comparative Economics, 41, 1220-1238. https://doi.org/10.1016/j.jce.2012.12.004
Wong, W. K., Cheng, Y., & Yue, M. (2024). Could regression of stationary series be spurious?. Asia-Pacific Journal of Operational Research, 2440017. https://doi.org/10.1142/S0217595924400177
Wong, W.-K., & Pham, M. T. (2022a). Could the test from the standard regression model could make significant regression with autoregressive noise become insignificant?. The International Journal of Finance, 34, 1–18.
Wong, W.-K., & Pham, M. T. (2022b). Could the test from the standard regression model could make significant regression with autoregressive noise become insignificant – a note. The International Journal of Finance, 34, 19-39.
Wong, W.-K., & Pham, M. T. (2023a). Could the test from the standard regression model could make significant regression with autoregressive Yt and Xt become insignificant?. The International Journal of Finance, 35, 1–19.
Wong, W.-K., & Pham, M. T. (2023b). Could the test from the standard regression model could make significant regression with autoregressive Yt and Xt become insignificant – a note. The International Journal of Finance, 35, 20-41.
Wong, W. K., & Pham, M. T. (2025a). Could the correlation of a stationary series with a non-stationary series obtain meaningful outcomes?. Annals of Financial Economics, forthcoming.
Wong, W.-K., & Pham, M. T. (2025b). How to model a simple stationary series with a non-stationary series?. The International Journal of Finance, 37, 1–19.
Wong, W.-K., Pham, M. T., & Yue, M. (2024). Could regressing a stationary series on a non-stationary series obtain meaningful outcomes – a remedy. The International Journal of Finance, 36, 1–20.
Wong, W. K., & Yue, M. (2024). Could regressing a stationary series on a non-stationary series obtain meaningful outcomes?. Annals of Financial Economics, 19(03), 2450011.
Wu, X., & Wang, Y. (2021). How does corporate investment react to oil prices changes? Evidence from China. Energy Economics, 97, May 2021, 105215. https://doi.org/10.1016/j.eneco.2021.105215.
Wuhan, L. S., & Adnan, K. (2015). The effect of interest rate on investment: Empirical evidence of Jiangsu Province, China. Journal of International Studies, 8(1), 81-90. https:/doi.org/10.14254/2071-8330.2015/8-1/7
Yaro, A. S., Maly, F., & Prazak, P. (2023). Outlier detection in time-series receive signal strength observation using Z-Score method with Sn scale estimator for indoor localization. Applied Sciences, 2023, 13, 3900. https://doi.org/10.3390/app13063900
Yıldız, B. F., Hesami, S., Rjoub, H., & Wong, W. K. (2021). Interpretation of oil price shocks on macroeconomic aggregates of South Africa: Evidence from SVAR. The journal of contemporary issues in business and government, 27(1), 279-287.
Yin, L., & Yang, S. (2023). Oil price returns and firm's fixed investment: A production pattern. Energy Economics, 125, 106896. https://doi.org/10.1016/j.eneco.2023.106896
Published
Issue
Section
License
Copyright (c) 2024 Advances in Decision Sciences

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Scientific and Business World