Auto accessories such as car covers provide an added extra in automotive styling both in the look and construction. Any fault in these components will reduce customer satisfaction and result in higher warranty expenses among manufacturers. Automotive sector as per IATF 16949 requirements requires a very effective and strong control of its processes to reduce the defects and enhance productivity. Thus, improved methods for defect identification and higher levels of quality assurance during production are critical issues of current concern. This research focuses on the use of Artificial intelligence (AI) in the automotive industry with an emphasis of using computer vision for superior improvement of quality KPIs. The purpose is to provide an efficient system and organizational approach to the further optimization of the end-of-line inspection of covers for vehicles, and to improve the efficiency of the identification of defects under IATF 16949 regulations. This study is unique in adopting a case based on smart splicing technology implemented in the cutting area of the automobile manufacturing lines. This paper simultaneously applies AI and IoT in order to understand its degree of influence in the definitive performance KPIs. Insignificance may be identified through the application of linear regression used to analyze the correlation between the applied technology and subsequent performance gains. Experimental outcome shows a significant decline on the number of defects that are identified at the last inspection process as well as an improvement on the rate of production. AI particularly contributed to enhancement of inspection processes thereby minimizing non-value adding activities and hence improving overall quality of the products. The current study also encourages manufacturers to adopt intelligent technologies since the AI technologies implemented within the IATF 16949 standards can boost the automotive production quality and decrease the costs and customer dissatisfaction. The automotive industry has changed today due to the implementation of IoT and AI in manufacturing, as this work has shown, with an exciting horizon of the constant automation process and increasing quality indications to deliver on the promise of the redefined definition of success in this industry.

This study uses the Resource-Based View (RBV) and technology, organization, and environment (TOE) theories to examine how smart supply chain (SSC) practices affect financial performance (FP) in enterprises of various sizes. Our results show that SSC benefits larger enterprises more financially than smaller firms. SSC has a statistically significant effect on green supply chain management (GSCM) and sustainable supply chain performance (SSCP), and the strength of the relationship declines with a decline in firm size. Smaller enterprises are more receptive to competitive pressure and implement GSCM alongside SSC. Our findings show that SSCP improves financial performance, while GSCM does not, even in large enterprises. Further, mediation effects show that GSCM mediates the relationship between SSC and SSCP, whereas it does not mediate between SSC and FP across all sizes. The impact of SSC on FP is sequentially mediated via GSCM and SSCP. Using a non-linear approach (ANN), we also rank independent variables for small, medium, and large firms. Our research provides important implications.

Due to the deep integration of modern information technology, supply chain management has moved into a new stage of a smart supply chain. Considering the dual smart innovation of the manufacturer's production and retailer’s service, the manufacturer-led Stackelberg game model is constructed in the smart supply chain. Under the single and coordinated government subsidy strategies, the optimal decisions of the smart supply chain are researched, and the impacts of manufacturers' risk aversion on the government subsidy strategies and supply chain decisions are analysed. In addition, the efficiencies of different government subsidy strategies are compared and analysed by numerical simulation. Finally, the results show that: (i) The moderate risk aversion by the manufacturer can improve social welfare and help provide consumers with more affordable products. (ii) The government expenditure and product prices are highest under the coordinated subsidy strategy. (iii) Subsidising manufacturers is more beneficial than subsidising retailers among the two single government subsidy strategies. (iv) In general, the coordinated government subsidy strategy is more effective than the single subsidy strategy for the innovative development of a smart supply chain. In conclusion, the research provides a significant practical reference for jointly building the smart supply chain.

This study aims to investigate the impact of information technology and supply chain practices on supply chain excellence in the retail sector, with a particular focus on understanding the mediating and moderating effects amidst the challenges posed by COVID-19. This study offers novel insights into the complex interplay between information technology, supply chain practices, and organizational culture in the context of the automotive retail sector. It underscores the pivotal role of this triad in navigating the unprecedented challenges and uncertainties of the modern business environment, providing a blueprint for attaining supply chain resilience and excellence. A survey was conducted involving 203 questionnaires distributed to 12 automotive retail companies in Dubai. The responses were analyzed using Smart PLS software and structural equation modelling to explore the intricate relationships between information technology, supply chain practices, organizational culture, and supply chain excellence. The results confirm that information technology and supply chain practices significantly influence supply chain excellence. Organizational culture was found to have a notable moderating effect, indicating that the alignment of culture with technological and procedural advancements is crucial in achieving superior supply chain performance. The study is confined to the automotive retail sector in Dubai, limiting the generalizability of the findings. Future research can expand to other sectors and geographical areas to provide a more comprehensive insight into the studied relationships. For businesses, especially amidst challenges like COVID-19, aligning information technology and supply chain practices with organizational culture is paramount. The findings suggest that a harmonious integration can lead to enhanced supply chain excellence, offering a competitive edge in the rapidly evolving digital landscape.

Implementing sustainable and smart supply chain practices have a great impact on the performance of an organization. In today’s globalized and highly industrialized world, sustainability is recognized as one of the highest priorities of all organizations. Evolution of internet-based technologies, digital platforms and big data analytics have paved the way for redesigning supply chains to be smart, agile, and resilient. Therefore, the implementation of practices related to these two concepts is found to improve the supply chain related organizational performance. This research aims to investigate empirically the impact of these two practices on improving the supply chain organizational performance in the Small and Medium Enterprises (SMEs) of India. This research considered the dimensions and the variables related to sustainable supply chain and smart supply chain practices in SMEs in India which were not considered in research contributions prior to this. Therefore, this research becomes a unique contribution to the existing body of knowledge. Empirical analysis was carried out on data from 92 SMEs from Telangana State in India, collected using a questionnaire. The directory of SMEs of Government of Telanagana, India was used to select the cluster sample of SMEs as respondents, based on a criterion using exploratory research methodology. SPSS software was used to test the model. Regression and ANOVA were used for this purpose. Findings of this research reveal significant influence of sustainable and smart supply chain (SC) practices on improving SC organizational performance. Additionally, individually each of these practices also have a direct influence on the performance of SMEs. Obtaining responses from the representatives of SMEs was a challenge and limitation of this research while expanding the scope of this research to different geographical regions and clusters will be a topic for further research. The outcomes and results of this research provide significant contribution to the existing body of knowledge by filling the gaps and value-adding to the researchers, academicians, students, policy makers and industry practitioners.