Application of grand techno-economic strategy based on linear programming in the textile industry
Keywords:
grand strategy, linear programming, techno-economic, textile industryAbstract
The main objective of this paper is to review of the evolution of management science, overview of grand strategy and its linkage with the techno – economic as a tactics to trigger productivity to win global competition. A review of the relevant literature was conducted and a connection between management science, grand strategy and techno – economic based on the linear programming can be applied in the textile industry. It was found that the industrial world in the midst of the Covid-19 pandemic has an impact on the market which is increasingly shrinking and is plagued by a quite severe sluggishness. Simultaneously the labor productivity is getting weaker. This is what is known as the negative impact of the global financial crisis. Will the Indonesian nation be able to maintain the momentum of economic growth amidst the tsunami waves of the global financial crisis? A grand strategy that combines the roles of technology and economy (techno-economic) strategy based on linear programming needs to be implemented immediately. The success of the techno economic strategy cannot be separated from the role of three pillars, namely mastery of technology, productivity and competitiveness.
Downloads
References
Apsari, A. E., & Purnomo, H. (2020). An Occupational safety and health (OSH) factors identified in Indonesian batik textile small/medium enterprises. International Research Journal of Engineering, IT & Scientific Research, 6(2), 55-64. https://doi.org/10.21744/irjeis.v6n2.877
Aroef, M., Djamal, J. S., & Ilwan, H. (2009). Grand techno-economic strategy: siasat memicu produktivitas untuk memenangkan persaingan global. PT Mizan Publika.
Balakrishnan, N. R., Render, B., Stair, R., & Munson, C. (2017). Managerial decision modeling. In Managerial Decision Modeling. De Gruyter.
Callon, M. (1992). The dynamics of techno-economic networks. Technological change and company strategies, 72, 102.
Chandel, M., Agrawal, G. D., Mathur, S., & Mathur, A. (2014). Techno-economic analysis of solar photovoltaic power plant for garment zone of Jaipur city. Case Studies in Thermal Engineering, 2, 1-7. https://doi.org/10.1016/j.csite.2013.10.002
Delice, E. K., & Güngör, Z. (2009). A new mixed integer linear programming model for product development using quality function deployment. Computers & Industrial Engineering, 57(3), 906-912. https://doi.org/10.1016/j.cie.2009.03.005
Ezema, B. I., & Amakom, U. (2012). Optimizing profit with the linear programming model: A focus on golden plastic industry limited, Enugu, Nigeria. Interdisciplinary Journal of Research in Business, 2(2), 37-49.
Gunasekaran, H. L., Zainali, S., & Aghapour, A. H. (2015). The Optimization Problem of Product-Mix and Linear Programing Applications; A single-Case Study in Tea Industry. Australian Journal of Basic and Applied Sciences, 9(3), 7-18.
Handoko, T. H. (2013). Operation Research (B.- UGM (ed.); October 2013).
Herdiansyah, H. (2010). Metodologi Penelitian Kuantitatif [Research Method for Qualitative]. Jakarta, Indonesia: Salemba Humanika.
Kamal, A., Vinarti, R. A., & Anggraeni, W. (2012). Optimasi Persediaan Perusahaan Manufaktur dengan Metode Mixed Interger Linear Programming. Skripsi. Program Studi Sistem Informasi. Institut Teknologi Sepuluh Nopember.
Karana, H. (2014). Pola Penyebaran Usaha Mikro Di Kota Medan.
Kotler, P., & Armstrong, G. (2013). Principles of Marketing (16th Global Edition).
Krisnadewi, N. P., & Setiawan, P. Y. (2018). Optimization Of Production On Small Business Terry Chips In The Nyanglan Kaja Village, Tembuku District, Bangli Regency. E-Jurnal Manajemen, 7(11), 6011-6040.
Küsters, D., Praß, N., & Gloy, Y. S. (2017). Textile learning factory 4.0–preparing germany's textile industry for the digital future. Procedia Manufacturing, 9, 214-221. https://doi.org/10.1016/j.promfg.2017.04.035
Marsetiani, M. (2014). Model Optimasi Penentuan Kombinasi Produk Menggunakan Metode Linear Programming pada Perusahaan Bidang Fashion. The Winners, 15(1), 1-7.
Mulyono, S. (2017). Program Linear.
Musman, A., Arini, A. B., & Kenyar, M. N. (2011). Batik: Warisan adiluhung nusantara. G-Media.
Narizny, K. (2001). The political economy of grand strategy. Princeton University.
Oliveira, C., & Antunes, C. H. (2007). Multiple objective linear programming models with interval coefficients–an illustrated overview. European journal of operational Research, 181(3), 1434-1463. https://doi.org/10.1016/j.ejor.2005.12.042
Pezzella, C., Giacobelli, V. G., Lettera, V., Olivieri, G., Cicatiello, P., Sannia, G., & Piscitelli, A. (2017). A step forward in laccase exploitation: recombinant production and evaluation of techno-economic feasibility of the process. Journal of biotechnology, 259, 175-181. https://doi.org/10.1016/j.jbiotec.2017.07.022
Rust, R. T., & Huang, M. H. (2012). Optimizing service productivity. Journal of Marketing, 76(2), 47-66.
Salami, H., Shahnooshi, N., & Thomson, K. J. (2009). The economic impacts of drought on the economy of Iran: An integration of linear programming and macroeconometric modelling approaches. Ecological Economics, 68(4), 1032-1039. https://doi.org/10.1016/j.ecolecon.2008.12.003
Satapathy, S. K., & Kanungo, S. (2016). Special reference to handicraft and cottage industry in Odisha. International Research Journal of Management, IT and Social Sciences, 3(5), 59-71. Retrieved from https://sloap.org/journals/index.php/irjmis/article/view/367
Sekaran, U., & Bougie, R. (2011). Business Research Methods: A skill-building approach. Chichester: John Wiley& Sons Ltd.
Sugiyono, D. (2010). Memahami penelitian kualitatif.
Sundary, B. (2014). Penerapan Program Linier dalam Optimasi Biaya Pakan Ikan dengan Metode Simpleks (Studi Kasus PT. Indojaya Agrinusa Medan). Informasi dan Teknologi Ilmiah.
Utomo, S. ITT B.(2018). Penerapan Linear Program pada Industri Tekstil. Arena Tekstil No 7, 7(7), 22.
Vergili, I., Kaya, Y., Sen, U., Gönder, Z. B., & Aydiner, C. (2012). Techno-economic analysis of textile dye bath wastewater treatment by integrated membrane processes under the zero liquid discharge approach. Resources, Conservation and Recycling, 58, 25-35. https://doi.org/10.1016/j.resconrec.2011.10.005
Verma, S. R., & Dwivedi, U. N. (2014). Lignin genetic engineering for improvement of wood quality: applications in paper and textile industries, fodder and bioenergy production. South African Journal of Botany, 91, 107-125. https://doi.org/10.1016/j.sajb.2014.01.002
Widowati, A. (2010). Brainstorming Sebagai Alternatif Pengembangan Berfikir Kreatif Dalam Pembelajaran Sains Biologi. Jurnal Biologi Edukasi, 2(3), 17-22.
Wisdaningrum, O. (2013). Analisis rantai nilai (value chain) dalam Lingkungan internal perusahaan. Jurnal ANALISA, 1(1).
Woubante, G. W. (2017). The optimization problem of product mix and linear programming applications: Case study in the apparel industry. Open Science Journal, 2(2).
Yaghin, R. G. (2020). Enhancing supply chain production-marketing planning with geometric multivariate demand function (a case study of textile industry). Computers & Industrial Engineering, 140, 106220. https://doi.org/10.1016/j.cie.2019.106220
Yahya, W. B., Garba, M. K., Ige, S. O., & Adeyosoye, A. E. (2012). Profit maximization in a product mix company using linear programming. European Journal of Business and management, 4(17), 126-131.
Zhou, P., & Ang, B. W. (2008). Linear programming models for measuring economy-wide energy efficiency performance. Energy Policy, 36(8), 2911-2916. https://doi.org/10.1016/j.enpol.2008.03.041
Published
How to Cite
Issue
Section
Copyright (c) 2022 Linguistics and Culture Review

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