Waheed, Hushsham (2025) Internet-of-Things and its Impact on Inventory, Production, Lead Times, and Forecasting: Evidence from a Tier-1 Automobile Supplier in Karachi, Pakistan. Doctoral thesis, Asia e University.
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Abstract
The automobile industry of Pakistan is developing at a fast pace and, despite its relatively small size, is among the fastest-growing sectors of the national economy. This growth, coupled with its potential to stimulate other industries, makes it an important focus for technological advancement. The purpose of this study is to examine the mediating influence of the Internet of Things (IoT) on supply chain forecasting within Tier 1 suppliers of the automobile industry in Karachi, Pakistan. Traditional supply chain forecasting methods are largely based on historical data and static models. Traditional approaches to supply chain forecasting, which mainly rely on historical data and fixed models, often fall short when it comes to dealing with the rapidly changing environment of today’s supply chains. These issues cause problems with managing inventory effectively, making the most of production capacity, and keeping lead times on track. The study explores how integrating IoT technology can address these issues and improve the accuracy of forecasts. A cross-sectional study using a quantitative approach was conducted to explore the topic. The group studied consisted of supply chain experts who work with Tier 1 suppliers in the automotive industry. Using Morgan’s sample size determination table, a sample size of 384 respondents was established, ensuring a 95% confidence level with a 5% margin of error. Data was collected through a structured questionnaire distributed via convenience sampling. The data was analyzed using SPSS to evaluate the hypotheses. The findings reveal a strong consensus among respondents that IoT adoption has a positive impact on supply chain forecasting. IoT makes it possible to gather data instantly. This real-time information supports better predictions, smarter decisions, and smoother collaboration across everyone involved in the supply chain. These capabilities enhance inventory visibility, optimize production processes, and improve lead time reliability, resulting in more agile and competitive supply chains. This research addresses a notable gap in the limited literature on IoT applications in Pakistan’s manufacturing sector and offers practical implications for industry practitioners and policymakers. The results show that IoT can really help make operations smoother, make supply chains more reliable, and make customers happier. Future research could expand the scope to other sectors and explore the long-term impacts of IoT adoption.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Internet of Things (IoT), supply chain forecasting, tier 1 suppliers, automobile industry, Pakistan |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management |
| Divisions: | School of Graduate Studies |
| Depositing User: | Nor Aisyah Ghazali |
| Date Deposited: | 22 Apr 2026 06:41 |
| Last Modified: | 22 Apr 2026 06:41 |
| URI: | http://ur.aeu.edu.my/id/eprint/1482 |
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