Determinants of computer vision system’s technology acceptance to improve incoming cargo receiving at Eastern European and Central Asian transportation companies’ warehouses. Mixed methods pilot study

Askar Aituov, Ramesh Kini

Abstract


Transportation companies' warehouses are an integral component of the global supply chain. However, SMBs have limited technology awareness to assess the impact of digitization on certain processes. In particular, the incoming cargo receiving process at transportation companies worldwide has a substantial fraction of manual labor.  In this study, we focus on the cargo dimensioning process of LTL and retail companies’ warehouses in Poland, Estonia, Belarus Republic, and Kazakhstan and identify whether computer vision dimensioning system usage has a positive effect on warehouse performance and its adoption determinants. Combining data from 20 expert interviews, literature review, and quantitative process mining experiments with computer vision dimensioning system performing daily dimensions within 6 months, we conclude that system reliability might be an additional acceptance determinant, which has an influence on Perceived Usefulness. Next, based on the process mining experiments we conclude that the computer vision system is capable to increase information flow in control conditions forty times and four times in the experiment condition. Finally, we find that increase in dimensioning speed as a result of IT system implementation could not be used to assess the impact on the material flow at LTL transportation company but could be a valuable source of data for the capacity monitoring process.


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