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|Title:||Optimization (automation) of transportation and storage of finished product in industrial enterprises|
|Abstract:||Firms must recognize that competitive advantage can be gained through either lower product and/or service costs or commodity and/or service distinctiveness throughout terms of functionality and capabilities. A modern ecosystem necessitates not only the quality of a product, but also a timely reaction to a client request in terms of product availability and delivery. Logistics is now part of a broader concept known as supply chain management, which combines operations with intra-firm and firm-to-market communications systems, as well as a firm's technical team. Warehousing is considered an integral part of a company’s logistics system, which acts within both the production of raw materials, elements at the point of origin, as well as finished products at the point of consumption (Min, 2015). Expecting to receive (materials, quality and variety guarantees of those components), prepackaging, putaway (sending materials from point of receipt to area of storage), cross docking (receiving bulk consignments, dividing them into smaller orders, packaging and shipping), and unitizing all were traditional storage of goods or storage capabilities (merchandise packaging in shipping containers, order accumulating by outbound carriers). Transportation of finished products and raw materials are also highly important to accomplish the logistics operations’ performance. The current study aims to investigate the major factors that lead to both warehousing and transportation operations’ performance, while at the same time employs multi-criteria decision-making (MCDM) approach to optimize the decision-making in warehouse types and transport modes in the context of cement industry. In the next stage, technology acceptance model (TAM) is employed to justify firm employees’ (managerial and operational levels) desire to use new technology in regards of automation of processes of sales/marketing-to-manufacturing-to-warehousing-to-deliveries. In analytical hierarchy process (AHP) part of the analysis, 8 experts are selected from local company in Azerbaijan, while in the TAM analysis, 15 employees are involved. The measurement model is analyzed and by using the Pearson correlation analysis, the significance of relations between TAM variables are identified. Finally, based on the results, key findings are discussed and recommendations are given.|
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