Browsing by Author "Mishra, Arunodaya Raj"

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Citation - WoS: 10
Citation - Scopus: 18
Evaluation of Industry 4.0 Strategies for Digital Transformation in the Automotive Manufacturing Industry Using an Integrated Fuzzy Decision-Making Model
(Elsevier Sci Ltd, 2024) Gorcun, Omer Faruk; Mishra, Arunodaya Raj; Aytekin, Ahmet; Simic, Vladimir; Korucuk, Selcuk
The current paper proposes a methodological frame to identify the best Industry 4.0 (I4) strategy for the automotive manufacturing industry as a roadmap for companies to make a more straightforward digital transformation. We noticed a critical research gap when we performed an extensive literature review. Although there are many studies available that assess the readiness of companies for I4, only a few deal with decision -making in terms of sustainable development, and none have applied that to the automotive industry. Practitioners can apply the proposed model to determine the strategy based on technological developments in I4. The current paper proposes an extended version of the combined compromise solution approach with the help of the picture fuzzy sets. According to the paper 's results, by using the proposed model, developing a new business model based on technological improvements is the best strategy for the digital transformation of the automotive industry. Also, the lack of research and development implementations on I4 implementation is the most influential factor. Hence, practitioners in the automotive industry know the significance of research and development in reaching successful results for digital transformation. The acquired outcomes of the paper show that developing technology -based new business models is the best strategy for the automotive manufacturing industry concerning digital transformation instead of accommodating traditional business models and high technology utilization.
Fuel Cell Electric Long-Haul Truck Evaluation for Sustainable Transport Via a Novel Pythagorean Fuzzy Sets-Driven Tool
(Elsevier Sci Ltd, 2026) Gorcun, Omer Faruk; Rani, Pratibha; Mishra, Arunodaya Raj; Ecer, Fatih
Fossil fuel-powered trucks and vehicles used in road freight transportation play a notable role in the emission of greenhouse gases. Although the road vehicle industry's use of renewable energy is promising in terms of sustainability, the vehicle manufacturing industry's initiatives are still in their infancy. Moreover, existing studies on using electric and renewable energies in transportation have primarily focused on electric automobiles. Considering these research and practice gaps, this work investigates the selection of the most proper fuel cell electric long-haul trucks (FCETs) to restructure the Turkish fleet of long-haul trucks operating nationwide concerning sustainability. However, assessing these vehicles is challenging, as they are produced based on new and advanced technology, with severe and highly complicated uncertainties. Thus, this paper suggests a Pythagorean fuzzy distance measure-based weighted integrated sum product (WISP) with the integration of the symmetry point of criteria (SPC) and relative closeness coefficient (RCC)-based weighting methods. Surprisingly, and unlike the findings of earlier works, the acquired conclusions indicate that refueling time (0.1161) is the most influential factor for FCET selection, followed by range (0.0837) and torque (0.0785) among the 14 criteria. Besides, the first alternative (R1) outperforms the other options, followed by R5 and R7. Finally, robustness and validity checks ensured the consistency, stability, and practicality of the conclusions. The research can guide manufacturers who produce FCETs and aim to enhance the quality and desirability of their products. Furthermore, practitioners and researchers can utilize the proposed model to solve challenging decision-making problems.