Search results

Cargo loss has been a major issue in logistics management. However, few studies have tackled the issue of cargo loss severity via business analytics. Hence, the purpose of this paper is to provide guidance about how to retrieve valuable information from logistics data and to develop cargo loss mitigation strategies for logistics risk management.

This study proposes a research design of business analytics to scrutinize the causes of cargo loss severity.

The empirical results of the decision tree analytics reveal that transit types, product categories, and shipping destinations are key factors behind cargo loss severity. Furthermore, strategies for cargo loss prevention were developed.

The proposed framework of cargo loss analytics provides a research foundation for logistics risk management.

Companies with logistics data can utilize the proposed business analytics to identify cargo loss factors, while companies without logistics data can employ the proposed cargo loss mitigation strategies in their logistics systems.

This pioneer empirical study scrutinizes the critical cargo loss issues of cargo damage, cargo theft, and cargo liability insurance through exploiting real cargo loss data.

The purpose of this paper is to explore and analyse the risks in container shipping operations from a logistics perspective. In the paper, risks associated with the three flows in logistics − information, physical, and payment flow are identified and analysed.

The use of case study method was first explained and justified. Second, risk identification was started with supporting references, several interviews were then conducted to identify and validate the potential risks in container shipping operations. A questionnaire was deployed to collect related data; and the impacts of the risks were then assessed and ranked using the method of risk mapping.

The paper has identified a total of 35 risk factors and classified them into different categories. The paper has also revealed that the risks associated with physical flows have more serious risk impacts than the other types of risks; however, one of the risk factors associated with information flow (shippers hiding cargo information) is the most significant one among all the factors.

Although many studies have been conducted on container shipping operational risks, no studies so far have approached this issue from a perspective that inclusively examines all the possible risks and comprehensively evaluates the relative importance of each of them. This study has identified the risks in container shipping operations, and analysed and ranked the level of these risks. The research further “refines” the findings of some previous studies by placing the risk factors addressed therein in a full “risk picture” which was developed systematically.

The development of digital technology has provided technical support to various industries. Specifically, Internet-based freight platforms can ensure the high-quality development of the logistics industry. Online freight platforms can use cargo transportation insurance to improve their service capabilities, promote their differentiated development, create products with platform characteristics and increase their core competitiveness.

This study uses a generalised linear model to fit the claim probability and claim intensity data and analyses freight insurance pricing based on the freight insurance claim data of a freight platform in China.

Considering traditional pricing risk factors, this study adds two risk factors to fit the claim probability data, that is, the purchase behaviour of freight insurance customers and road density. The two variables can significantly influence the claim probability, and the model fitting outcomes obtained with the logit connection function are excellent. In addition, this study examines the model results under various distribution types for the fitting of the claim intensity data. The fitting outcomes under a gamma distribution are superior to those under the other distribution types, as measured by the Akaike information criterion.

With actual data from an online freight platform in China, this study empirically proves that a generalised linear model is superior to traditional pricing methods for freight insurance. This study constructs a generalised linear pricing model considering the unique features of the freight industry and determines that the transportation distance, cargo weight and road density have a significant influence on the claim probability and claim intensity.

Learning theory explains how organizations change as a result of experience, and can be used to predict the competitive strength of individual organizations and competitive pressures in organizational populations. We review extant learning theoretical propositions on how competitive strength is affected by experienced competition, founding conditions, and observed failures of other organizations. In addition, we propose that niche changes are an important source of learning. We test these propositions on data from the Norwegian general insurance industry. We find that historical density increases failure rates, contrary to some earlier findings, and also that the effect of founding density supports the density delay rather than trial-by-fire hypothesis. We find that failures of others before and during the lifetime of the organization reduce failure rates, and niche changes reduce failure rates for joint-stock companies but not for mutual firms. Overall the findings suggest that organizations learn more cheaply from the failures of others than from their own experiences, and that the stresses of competition can overwhelm the learning effects of competition.

The purpose of this paper is to explore cargo theft risk and security for different product types at different locations along a transport chain.

This study is based on a system-theoretical approach. The research method is deductive, as the analysis is based on secondary data and results from a questionnaire. The results are analysed based on supply chain risk management (SCRM) theories.

Due to substantial interaction effects, the type of product and transport chain location must be considered to determine the correct level of security. Specifically, the product type is more significant, since the general cargo theft risk is higher. Furthermore, the transport industry has three perspectives on security responses to cargo theft, namely, demanded, needed and actual security, which differ depending on the product type and transport chain location.

This database is structured according to the global Transported Asset Protection Association organisational structure, which implies that there are three main databases: Europe, Middle East and Africa, Americas, and Asia-Pacific.

This study has both research and practical implications, as it examines security within freight transport from three perspectives, linked to general cargo theft risk and goods owners’ requirements.

This study addresses the contemporary SCRM problem of cargo theft using actual crime statistics and the industry understanding of required generic security levels.

The purpose of this paper is to examine the patterns of reported cargo thefts at non-secure parking facilities in Europe, the Middle East, and Africa (EMEA) with respect to stolen value, frequency, incident category, and modi operandi.

This study is based on a system-theoretical approach that emphasizes on a holistic rather than an atomistic view. The research method used in this paper is deductive; the analysis is based on data obtained from the incident information service (IIS), a database of transport-related crimes from the Transported Asset Protection Association (TAPA) in the EMEA region. The results are analysed and discussed within a frame of reference based on supply chain risk management (SCRM) and criminology theories.

We found that 97 per cent of all attacks during a stop occur at non-secure parking locations. Cargo thefts at these locations are more of a volume crime than high-value thefts. Seasonal variations were seen in these thefts, and the most common type was an intrusion on weekdays during winter.

This study is limited by the content of and the classifications within the TAPA EMEA IIS database.

This paper is directly relevant to the current EU discussions regarding the creation of a large number of secure parking facilities in the region.

This is one of the first papers in the field of SCRM that utilizes actual crime statistics reported by the industry to analyse the occurrence of cargo theft by focusing on the non-secure parking aspect in the transport chain.

Identifying and managing supply chain risk is crucial for the competitiveness of a company. However, research focused on the risks of supply chain operations in Brazil is scarce. The purpose of this study is to analyze and assess the risk of cargo theft in the country. The methodology adopted is deductive and based on an analysis of historical data from January 2015 to November 2017, aiming to evaluate risk based on probability and impact. The findings unveil a scenario of criminality of transporting goods in Brazil, where the use of force, violence, and threats to steal goods is most likely to occur en route or when parked in key locations on the way to the distribution center. On the other hand, the higher impact cargo crimes are concentrated en route to the customer. This chapter provides a better understanding of the risks of transporting goods by road in Brazil and contributes to a more efficient supply chain design by identifying the risks and assessing the primary locations of the crimes along with their modi operandi and the period of the day during which the crime occurs.

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.

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.

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.

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.

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.

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.

The purpose of this study is to determine the factors that impact the trust of microenterprises in online selling platforms and cargo carriers and examine the consequences of a lack of trust.

This study adopts a qualitative exploratory approach and uses grounded theory to generate insights based on interviews with 27 microenterprise owners selling internationally on an online selling platform.

The results show that a lack of competence, an absence of an integrated claim system and a lack of transparency are the main factors affecting sellers’ trust in online selling platforms. The relationship between the sellers’ intention to continue to use the online selling platform and their trust in the platform was found to be moderated by switching costs.

This study is limited in that the results were mainly based on the sellers’ perspectives although the phenomenon of interest involves various actors. To mitigate this limitation and cross-check the data, the customer reviews and some of the sellers’ account statistics were also analyzed.

This study introduces the sellers’ perspectives on the dynamics of supply chain management in international micro trade. These dynamics provide a guideline for how to build and manage an online selling platform targeting microenterprises.

Unlike previous studies, this study examines online transaction behaviors from the standpoint of sellers, not buyers. Moreover, it is the first study examining the damaged or lost shipments within the context of online transactions in international micro trade.