×
Home Current Archive Editorial board
Instructions for papers
For Authors Aim & Scope Contact
Original scientific article

INTEGRATED STRATEGIC FINANCIAL AND OPERATIONS MANAGEMENT FOR TECHNOLOGY INTENSIVE MANUFACTURING FIRMS

By
Megala Rajendran Orcid logo ,
Megala Rajendran

Vice Rector, Research & Innovation, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan

Yokubbaeva Umida Abduvakhob kizi Orcid logo ,
Yokubbaeva Umida Abduvakhob kizi

Associate Professor of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan

Kosimov Khusniddin Badriddinovich Orcid logo ,
Kosimov Khusniddin Badriddinovich

Senior Lecturer of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan

Ergashev Rasulbek Sokhib ugli Orcid logo ,
Ergashev Rasulbek Sokhib ugli

Senior Lecturer of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan

Iplina Antonina Aleksandrovna Orcid logo
Iplina Antonina Aleksandrovna

Associate Professor of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan

Abstract

Manufacturing systems that are technology-intensive have high interdependencies between financial decisions on investments, the change in production capacity, and operational efficiency. Traditional methods tend to look at financial and operational planning in isolation, resulting in poor performance of the system and poor use of resources. In order to overcome this shortcoming, this paper has suggested a combined techno-economic optimization framework, which models financial performance, production planning, technology-based capacity development, and energy efficiency together in a single mathematical expression. The manufacturing system is modeled in terms of a multi-period constrained optimization problem, in which the investment of technology, production output, capacity variation, and energy consumption are all optimized. A multi-objective function that combines financial and operational functions is formulated using diversity of weights, and an algorithm to find a solution is presented to achieve computational feasibility. The framework proposed is assessed by the numerical simulation in a 5-period planning horizon. Findings show that when there is a technology investment, capacity is incrementally expanded between 100 and 180 units at production levels that are viable. The integrated strategy has a total financial performance of 742.6 with a return on investment of 1.48 and average capacity utilization of 0.82. The energy efficiency is increasing to an average of 2.91, which shows that efforts are made to plan production considering energy efficiency. Sensitivity analysis also reveals that an increase in the technology gain coefficient will increase the Technical-Economic Performance Index to a maximum of 3.24, followed by a decreasing marginal gain. On the whole, the findings prove that the suggested framework offers a powerful and technologically efficient decision-support tool that can be applied to streamline financial and operational performance in technology-intensive production systems.

References

1.
Arcidiacono F, Schupp F. Investigating the impact of smart manufacturing on firms’ operational and financial performance. Journal of Manufacturing Technology Management. 2024;(3):458–79.
2.
Yiu L, Lam H, Yeung A, Cheng T. Enhancing the financial returns of R&D investments through operations management. 2020;(7):1658–78.
3.
Beusch P, Frisk JE, Rosén M, Dilla W. Management control for sustainability: Towards integrated systems. Management Accounting Research. 2022;54:100777.
4.
Chiarini A, Belvedere V, Grando A. Industry 4.0 strategies and technological developments. An exploratory research from Italian manufacturing companies. Production Planning & Control. 2020;(16):1385–98.
5.
Wang C, Lu Y, Huang C, Lee J. R&D, productivity, and market value: An empirical study from hightechnology firms. Omega. 2013;(1):143–55.
6.
Ghobakhloo M, Fathi M. Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing. Journal of Manufacturing Technology Management. 2020;(1):1–30.
7.
Ma S, Zhang Y, Liu Y, Yang H, Lv J, Ren S. Data-driven sustainable intelligent manufacturing based on demand response for energy-intensive industries. Journal of Cleaner Production. 2020;274:123155.
8.
Hutahayan B. The mediating role of human capital and management accounting information system in the relationship between innovation strategy and internal process performance and the impact on corporate financial performance. Benchmarking: An International Journal. 2020;(4):1289–318.
9.
Wen H, Zhong Q, Lee CC. Digitalization, competition strategy and corporate innovation: Evidence from Chinese manufacturing listed companies. International Review of Financial Analysis. 2022;82:102166.
10.
Chukwuma-Eke E, Ogunsola O, Isibor N. Designing a robust cost allocation framework for energy corporations using SAP for improved financial performance. International Journal of Multidisciplinary Research and Growth Evaluation. 2021;(1):809–22.
11.
Chen L, Li T, Jia F, Schoenherr T. The impact of governmental COVID-19 measures on manufacturers’ stock market valuations: The role of labor intensity and operational slack. Journal of Operations Management. 2023;(3):404–25.
12.
Bisht D, Singh R, Gehlot A, Akram SV, Singh A, Montero EC, et al. Imperative Role of Integrating Digitalization in the Firms Finance: A Technological Perspective. Electronics. 2022;11(19):3252.
13.
Ghobakhloo M. Determinants of information and digital technology implementation for smart manufacturing. International Journal of Production Research. 2019;58(8):2384–405.
14.
Shah N, Soomro B. Internal green integration and environmental performance: The predictive power of proactive environmental strategy, greening the supplier, and environmental collaboration with the supplier. Business Strategy and the Environment. 2021;(2):1333–44.
15.
Moussa T, Allam A, Elbanna S, Bani-Mustafa A. Can board environmental orientation improve US firms’ carbon performance? The mediating role of carbon strategy. Business Strategy and the Environment. 2020;(1):72–86.
16.
Dubey R, Gunasekaran A, Childe S, Papadopoulos T, Luo Z, Wamba S, et al. Can big data and predictive analytics improve social and environmental sustainability. 2019;534–45.
17.
Raisch S, Krakowski S. Artificial intelligence and management: The automation-augmentation paradox. 2021;(1):192–210.
18.
Buer S, Strandhagen J, Chan F. The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda. International journal of production research. 2018;(8):2924–40.
19.
Agostini L, Galati F, Gastaldi L. The digitalization of the innovation process: Challenges and opportunities from a management perspective. European journal of innovation management. 2020;(1):1–2.
20.
Zhou K, Gao G, Zhao H. State ownership and firm innovation in China: An integrated view of institutional and efficiency logics. Administrative Science Quarterly. 2017;(2):375–404.

Citation

This is an open access article distributed under the  Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.