Search Results (8)

Multinational corporations (MNCs) face significant reputational and performance risks from product recalls, yet the severity of these consequences varies across national markets. While prior research suggests that corporate social responsibility (CSR) can buffer against such crises, limited attention has been paid to how country-level institutions shape this effect. This study examines whether—and under what institutional conditions—CSR reputation mitigates the negative market consequences of product recalls. We focus on how the insurance-like effect of CSR varies with the level of corruption in a country’s institutional environment. Using panel regression analysis and hand-collected data from 14 global automotive manufacturers across eight countries (2007–2015), we find that firms with stronger CSR reputations experience significantly smaller declines in market share after recall announcements. Furthermore, this buffering effect is amplified in countries with higher corruption levels, suggesting that when formal institutional trust is weak, CSR signals play a greater role in stakeholder perceptions. These findings advance CSR literature by showing that its reputational benefits are contingent on institutional context and contribute to international business scholarship by revealing how national-level corruption interacts with firm-level reputational assets during crises. Full article

This article examines the relationship between implementing sustainable development measures and financial risk in the context of global companies and the recycling economy. This study uses statistics from Forbes, TIME, and Statista on 50 global companies that actively embrace sustainable development and recycling-economy practices across various industries. As a result, we have compiled a Structural Equation Model (SEM), with the help of which we established that growth in the activity of their implementing the measures of sustainable development and the recycling economy by each 1 point leads to a reduction in the risk of a shortfall in global companies’ profit by USD 0.0741 billion and the risk of ousting global companies from the market by USD 1.8374 billion. It has also been revealed that a reduction in the risk of the shortfall in profit by each USD 1 billion is accompanied by an increase in the activity of global companies’ implementing the measures of sustainable development and the recycling economy by 0.3433 points, and a reduction in the risk of market displacement by each USD 1 billion is accompanied by a growth in this activity by 0.0073 points. The theoretical novelty of the research consists of substantiating the differences in the consequences of the development of the recycling economy for financial risks of companies from different sectors. Practical implications of the proposed recommendations for companies in different industries are that the authors’ recommendations for the development of the recycling economy will allow for systemic reduction in financial risks in the sectors “Automotive Industry & Suppliers”, “Banking, Insurance & Financial Services”, “Chemicals, Drugs & Biotechnology”, and “Retail, Wholesale & Consumer Goods”. We have also revealed the threat of growth of all financial risks in the course of the development of the recycling economy in the sphere “Transportation, Logistics & Aviation”. In “Electronics, Hardware & Equipment” and “Manufacturing & Industrial Production”, the implications are differentiated among financial risks, which require flexibility and care during the development of the recycling economy. We find that global companies’ implementation of sustainable development measures, recycling economy practices, and financial risks are mutually dependent organizational phenomena. Moreover, the risk to profits and market displacement manifest differently among global industries. Our conclusions support expediency in implementing sustainable development and recycling-economy measures to reduce the financial risks to global companies. Further, we propose practical recommendations for companies from different sectors of the world economy. Full article

The automotive supply chain is one of the top eight value chains that cause 50% of global emissions. Despite its significance, limited literature has researched the role of insurance companies in addressing automotive supply chain emissions. This research explores strategies developed by insurance companies for addressing carbon emissions in the automotive supply chain in the UK. It employs a qualitative multiple case study approach and conducts in-depth analysis of main drivers, barriers, and strategies in four insurance companies in addressing automotive supply chain emissions. It finds that cost savings and competitive advantage, changing mindset, impending regulation, market changes, and increased connectedness are the main drivers. But further progress is slowed down by five main barriers: ‘the complexity of tracking and quantifying emissions’, ‘conflicts of interest in the supply chain’, ‘skill shortage’, ‘lack of accountability’, and ‘profit prioritisation’. To overcome this, the study establishes five main strategies for insurance companies to follow: ‘circular business model with green parts and repair-over-replace methodologies’, ‘supply chain collaboration’, ‘quantifying emissions and setting key performance indicators’, ‘higher weighting for ESG in tenders and policies’, and ‘education and awareness’. If followed correctly, businesses will be able to achieve ‘emission reductions’, ‘gain competitive advantage’, and ‘reduce costs in the supply chain’. Taking into account these findings and the academic literature, this study develops a framework for insurance companies to mitigate automotive supply chain emissions. This is one of the first papers to study carbon emissions in automotive supply chains from the perspective of the insurance industry. It provides practical implications for the insurance industry in developing carbon emission strategies in automotive supply chains. Full article

This article delves into the acceptance of autonomous driving within society and its implications for the automotive insurance sector. The research encompasses two different studies conducted with meticulous analysis. The first study involves over 600 participants involved with the automotive industry who have not yet had the opportunity to experience autonomous driving technology. It primarily centers on the adaptation of insurance products to align with the imminent implementation of this technology. The second study is directed at individuals who have had the opportunity to test an autonomous driving platform first-hand. Specifically, it examines users’ experiences after conducting test drives on public roads using an autonomous research platform jointly developed by MAPFRE, Universidad Carlos III de Madrid, and Universidad Politécnica de Madrid. The study conducted demonstrates that the user acceptance of autonomous driving technology significantly increases after firsthand experience with a real autonomous car. This finding underscores the importance of bringing autonomous driving technology closer to end-users in order to improve societal perception. Furthermore, the results provide valuable insights for industry stakeholders seeking to navigate the market as autonomous driving technology slowly becomes an integral part of commercial vehicles. The findings reveal that a substantial majority (96% of the surveyed individuals) believe that autonomous vehicles will still require insurance. Additionally, 90% of respondents express the opinion that policies for autonomous vehicles should be as affordable or even cheaper than those for traditional vehicles. This suggests that people may not be fully aware of the significant costs associated with the systems enabling autonomous driving when considering their insurance needs, which puts the spotlight back on the importance of bringing this technology closer to the general public. Full article

Despite the rapid expansion in the insurance industry, many issues remain unresolved and may require immediate action. As the insurance sector continues to evolve with the development of new technologies, it faces more challenges, especially related to data security and fraud. The fraud-prevention data and tactics presently used by insurance firms are outdated and ineffective. Additionally, insurance firms have traditionally handled the settlement of all consumer claims through lengthy manual processes. These manual processes need to be changed to provide opportunities for insurance businesses to grow. In the case of vehicles, the information obtained from an automobile data recorder can be used as evidence. Data from automated vehicles are critical because they can help the police, law enforcement agencies, and insurance companies to reconstruct the events leading up to a collision. Insurance companies require the forensic analysis of accident videos, which is a time-consuming process and involves a large amount of storage. Due to hardware limitations and associated costs, the current standalone (and often dedicated) computing infrastructures used for this purpose are quite limited. Previous research focused on simple video analysis tasks within cloud computing and blockchain technology. The requirements for a large-scale auto-insurance system are quite high and need more thorough investigation. In this paper, a review of the contribution of recent approaches to storing accidental data in cloud computing using blockchain is provided. We focused on the latest cloud and blockchain studies related to auto-insurance along with the related issues and challenges. Some useful solutions and recommendations are provided to address the identified issues and challenges in the cloud-based and blockchain-based auto-insurance sector. Full article

GPS trajectories collected from automotive telematics for insurance purposes go beyond being a collection of points on the map. They are in fact a powerful data source that we can use to extract map and road network properties. While the location of road junctions is readily available, the information about the traffic control element regulating the intersection is typically unknown. However, this information would be helpful, e.g., for contextualizing a driver’s behavior. Our focus is to use a map-matched GPS OBD-dongle dataset provided by a Canadian insurance company to classify intersections into three classes according to the type of traffic control element present: traffic light, stop sign, or no sign. We design a convolutional neural network (CNN) for classifying intersections. The network takes as entries, for a defined number of trips, the speed and the acceleration profiles over each segment of one meter on a window around the intersection. Our method outperforms two other competing approaches, achieving 99% overall accuracy. Furthermore, our CNN model can infer the three classes even with as few as 25 trips. Full article

The growing trend in the number and severity of auto insurance claims creates a need for new methods to efficiently handle these claims. Machine learning (ML) is one of the methods that solves this problem. As car insurers aim to improve their customer service, these companies have started adopting and applying ML to enhance the interpretation and comprehension of their data for efficiency, thus improving their customer service through a better understanding of their needs. This study considers how automotive insurance providers incorporate machinery learning in their company, and explores how ML models can apply to insurance big data. We utilize various ML methods, such as logistic regression, XGBoost, random forest, decision trees, naïve Bayes, and K-NN, to predict claim occurrence. Furthermore, we evaluate and compare these models’ performances. The results showed that RF is better than other methods with the accuracy, kappa, and AUC values of 0.8677, 0.7117, and 0.840, respectively. Full article

Integral foam has been used in the production of polymer materials for a long time. Metal integral foam casting systems are obtained by transferring and adapting polymer injection technology. Metal integral foam produced by casting has a solid skin at the surface and a foam core. Producing near-net shape reduces production expenses. Insurance companies nowadays want the automotive industry to use metallic foam parts because of their higher impact energy absorption properties. In this paper, manufacturing processes of aluminum integral foam with casting methods will be discussed. Full article