Page 19 - IMDR Journal 2025

Research Article
success of Industry 4.0 over a longer period. open.Juma et al. (2022) proposed a blockchain-based
mechanism named the Trusted Consortium Blockchain to
● The Full Impact of Industry 4.0 Adoption Varies
According to Industry, Size, and Digital Maturity: The speed secure IIoT data. Given that conventional encryption has its
with which companies internalize the benefits of Industry limitations, they demonstrated how blockchain can securely
4.0 depends on various factors such as industry type, scale of protect supply chain information, albeit acknowledging that
operations, current digital backbone, and the readiness of the it comes with processing intensive requirements and
workforce. Manufacturing industry companies like Tata scalability issues.Saurabh et al. (2022) established the
Motors, Hindalco, and Vedanta can look forward to faster TMAP approach for discovering vulnerabilities in IIoT
improvement in efficiency because of their reliance on systems. They demonstrated that conventional security
automation and process optimization, while IT companies audits aren't sufficient for current dynamic cyber-attacks.
like Wipro and Bosch can look for slower rises in Their approach applied case studies to demonstrate that
operational efficiency compared to immediate revenue sophisticated modeling plays a critical role in enhanced
growth. Furthermore, companies with higher digital protection.
maturity—i.e., those already having some degree of AI, IoT,
or cloud-based technology—will achieve gains quicker than RESEARCH METHODOLOGY
their beginners. Hence, comparing the financial
performance across industries needs to take into account the Research Approach
varied rates of technological adoption and integration This research utilizes a quantitative methodology, using
financial data to assess the effects of IoT implementation.
The study reviews financial statements from chosen
LITERATURE REVIEW
companies to uncover patterns in cost reductions, asset
Yang et al. (2019) considered what the Internet of Things usage, and enhancements in financial performance.
(IoT) is doing to revolutionize smart manufacturing. They Hypothesis
noted that conventional automation systems are incapable of
meeting the requirements of real-time responses and ● H0: There is no significant change in costs due to IoT
flexibility. With IoT, manufacturing plants are more efficient implementation.
and capable of predicting maintenance, among other ● H1: The implementation of IoT results in changes to costs
processes, but with challenges such as cybersecurity and and improvements in operational methods.
exorbitant setup prices. Farooq et al. (2020) polled the ways Sampling Design
in which Industrial IoT (IIoT) is transforming today's
Sampling Format: Purposive Sampling (Focusing on
manufacturing. They concluded that traditional systems companies that have adopted IoT in manufacturing and
have difficulty with real-time decisions and handling large related sectors)
volumes of data. They highlighted how cloud/edge
computing and machine-to-machine communications are Sampling Size
central to smart automation but observed that scalability and Following are Nine companies from various industries
security remain significant challenges. which are selected as a sample
Nagulan (2021) explained how IoT can transform ● Tata Motors – Automotive
manufacturing to be more environmentally friendly. ● CEAT – Tire Production
Conventional systems cannot deal with green practices
● Vedanta Ltd. – Metals and Mining
effectively, but smart factories usingIoT was meant to save
energy and reduce waste—though by embracing these ● Wipro – Information Technology and Electronics
technologies and securing them is still problematic. Mu et al. ● Bosch – Engineering and Technology
(2021) explained how IoT is applied in industrial ● Hero MotoCorp – Automotive (Two-Wheel Vehicle
management. They criticized uneven adoption among Production)
sectors and outlined high-priority use cases such as
predictive maintenance and smart inventory. They also ● Asian Paints – Paints and Coatings
pointed out how AI and machine learning are becoming ● Nestlé India – Food and Beverage
unavoidable for better decision-making.Mehrpouya et al. ● Hindalco Industries – Metals and Mining (Aluminum and
(2021) were concerned with threats in smart factories, and Copper)
more specifically in relation to cybersecurity. They believed
that conventional risk management measures just do not Reason for Company Selection
work anymore. Their research advocated for classifying The chosen companies exemplify a variety of sectors where
risks into classes and developing robust security systems to IoT and Industry 4.0 technologies significantly influence
make sure operations are safe. Belton and Olson (2022) operations. These firms were selected based on
summarized the challenges of handling large volumes of Industry Relevance: Sectors where automation, digital
data in smart factories. Conventional data systems are processes, and IoT adoption are vital for operational
unable to deal with the volume or privacy concerns optimization.
introduced by IIoT. They advocated for innovative
governance models that are responsible, secure, and ● Diverse Applications: Covering industries rich in

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