Marco Pimpão

The automobile industry is one of the world’s largest manufacturing sectors and a key contributor to economic growth. Demand forecasting plays a critical role in supply chain management within the automotive sector. Reliable forecasts are essential for production planning, inventory control, and meeting market demands efficiently. However, accurately predicting demand remains a challenge due to the influence of external factors such as socioeconomic trends and weather conditions. This study presents a systematic literature review of the forecasting methods employed within the automotive industry, encompassing both vehicle and spare parts demand. Following PRISMA guidelines, 63 publications were identified and analyzed, covering traditional statistical models such as ARIMA and SARIMA, as well as state-of-the-art artificial intelligence approaches, including artificial neural networks. The review finds that classical statistical models remain prevalent for vehicle demand forecasting, Croston’s method dominates spare parts forecasting, and AI-based techniques increasingly outperform conventional models in recent studies. Furthermore, the review compiles a broad set of external variables influencing demand and highlights the common challenges associated with demand forecasting. It concludes by outlining potential directions for future research.

Many companies facing digitalisation lack a digital target model or transformation/implementation roadmap. Multinational companies as well as SMEs have to deal with different global market trends. Besides volatility, uncertainty, complexity and ambiguity [VUCA], companies' business models are constantly being influenced by disruptive technologies and solutions. And all this comes along with Industry 4.0 and digitalisation itself. Yet I4.0 and digitalisation are in many companies still buzzwords and lack substance. Assuming that the level of digitalisation of an enterprise has been defined, the main question is: "What does the digitalisation journey look like, and what are the transformation roadmap and the interdependencies?" This paper investigates whether, when and which of the independencies of company's functions are being neglected in the implementation of digitalisation. In a systematic literature review, gaps were identified especially in three previously defined categories that are directly related to the implementation of digitalisation, namely corporate culture, leadership and technology. After identification of these gaps, the missing link between these categories was discussed. In this way, the gaps revealed in the literature could be filled. The further scientific elaboration will primarily serve as a guide for SMEs to ensure a smooth implementation of digitalisation in the company.