Purpose – The purpose of this paper is to describe the seasonal patterns of reported cargo theft value and frequency in Europe, Middle East, and Africa (EMEA) countries with respect to different transport chain locations. Design/methodology/approach – This study is based on a system-theoretical approach, which emphasizes a holistic rather than an atomistic view. The research method used in this paper is deductive; the analysis is based on the data taken from Incident Information Service (IIS), a transport-related crime database of Transported Asset Protection Association (TAPA) EMEA; and the result is analyzed and discussed within a frame of reference based on supply chain risk management and criminology theories. Findings – There are seasonal variations in cargo thefts at different transport chain locations during particular months of the year as well as days of the week; however, each transport chain location has a different pattern. Indeed, hot spots, modus operandi, theft-endangered objects, and handling methods change frequently during the period under study. However, the basic theoretical frame of reference continues to be the same. Research limitations/implications – This study is based on theoretical deduction using official statistics regarding antagonistic threats. Its geographical limitation to the EMEA is owing to the limitations of the utilized database, although the frame of reference can be applied to analyze antagonistic threats against transport chains globally. Practical implications – This study is limited by the content and classification within the TAPA EMEA IIS database; nevertheless, this database is the best available one, with reports originating mainly from the industry itself, as different TAPA members anonymously report their losses. Originality/value – This paper is one of the first on supply chain risk management that uses actual crime statistics reported by the industry itself to analyze the occurrence of cargo theft by focusing on the value of the vehicle/goods stolen from transport chain locations.
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