Search results

The promotion of low tariffs and free trade has been the underlying driver of global economic growth. The recent political developments in the United States and Great Britain calls into question, whether free trade will be supported by the governments of the industrialized world in the future. Shortly after being inaugurated in 2017, the President of the United States has repeatedly announced his plans to impose punitive tariffs on the import of foreign products in order to protect the country’s domestic economy. Besides a controversial border adjustment tax, he has frequently brought up the possibility of imposing a 35% tariff on automobile imports. The chapter aims to analyze the effects of such a tariff on trade in the automotive sector between the United States and Germany as well as on German automobile manufacturers. It takes a quantitative approach to draw a conclusion about the relationship between import tariffs on automobiles and passenger vehicle imports from Germany to the United States utilizing a fixed effects regression model based on panel data. The model finds a significant negative correlation between the examined variables, but even in a worst case scenario, German manufacturers are resilient to the predicted revenue losses caused by a tariff increase.

Case studies of four important automobile firms are used to understand how the performance of both diversifying and new entrants into the automobile industry was conditioned by their pre-entry experience. Various conjectures based on the four firms are then tested using a unique data source on the pre-entry backgrounds of all entrants into the automobile industry from the commercial inception of the industry in 1895 through 1966. In addition to analyzing the types of pre-entry experiences that affected the longevity of entrants, the analysis also focuses on the conduits by which pre-entry experience influenced the performance of entrants and the extent to which pre-entry experience had enduring effects.

While prior research has investigated factors that predict consumers’ information search behaviors as they relate to automobiles, such studies were conducted prior to the COVID-19 pandemic. Given that the pandemic has necessitated lockdowns, social distancing, business closures and other disruptions to normal shopping activities, consumer information search behaviors have also been substantially altered as the psychological distance between consumers and marketers has increased. Thus, this study aims to examine these changes and identify patterns of search behavior for a major durable product: automobiles.

Using survey data from before and during the pandemic, the study implements Finite Mixture Modeling to unveil latent segments of U.S. consumers’ search behaviors and choices for Japanese automobiles. This analytic method enables capturing consumer unobserved heterogeneity through mixing probabilities guided by individual characteristics. These segments are determined based on consumers’ information search for online and offline marketer-controlled and nonmarketer-controlled sources.

The study identifies that two segments of consumers emerge both prior to the pandemic and during the pandemic. These empirically validated findings indicate that the pandemic has led to shifts in consumers’ information search behaviors for Japanese automobiles by relying more on nonmarketer-controlled sources of information.

This work is among the first comprehensive empirical analyses of consumer search for a major durable product by comparing pre- and during pandemic patterns. Using analytics and econometrics, the first-hand analysis findings offer meaningful implications for marketers and product managers in the automotive industry.

In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.

The purpose of this paper is to analyze the historical development and characteristics of the globalizing Chinese automobile industry.

This study is positioned as an exploratory case study, using data triangulation techniques based on archival research and published reports of statistical agencies both at central government and single industry level.

China's automobile industry represents an extraordinary case of a development path toward globalization in a transitional economy. One of the obvious characteristics of the auto industry is that it necessitates technology transfer and innovative learning, which can be regarded as an important aspect of maintaining competitiveness in industrialization and global competition. The automobile industry in China is also characterized by state intervention and industrial regulations. The state initiated open-door reform has led to a mixed regulatory mechanism including both market-based competition and the legacy of a command economy. Other major features are demonstrated as follows: state-owned auto enterprises have been gradually given more freedom in the decision-making processes; the Chinese auto industry has shown phenomenal growth in the country's economic development with an average annual rate of about 9 percent. This achievement combined with the increasing impacts of globalization of production and market expansion has undoubtedly led to the increasing inflows of foreign direct investment in the form of international partnerships between the auto-producing MNCs and major local Chinese firms as per the industrial policies in the Chinese automobile industry.

This paper addresses an important topic, the historical development path of the Chinese automobile industry, but to date, it has received very little research attention. It advances the institution-based perspective and therefore develops a better understanding of changes in China's automobile industry over the past decades since 1949 and concludes that the combination of the influences of foreign technology, China's industrial policies and institutional dynamic processes has resulted in a unique dynamic development path for the globalizing Chinese automobile industry.

China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is supporting the development of industrial clusters. Building an industrial cluster is done by using a single factor but requires many additional factors like regional characteristics, competitiveness factors are also diversified. To evaluate the competitiveness of the Chinese automobile industry cluster, a competitiveness element index should be developed and a competitiveness evaluation method is needed to evaluate the importance of each element. To accomplish this objective, this research applied the analytic hierarchy process (AHP) and focused on the importance of the competitiveness elements.

This research investigated the character is tics regarding cases of clusters and also analyzed the competitiveness of the Changchun automobile cluster located in northeastern China. The purpose of this research is to help Korean enterprises who enter China in the hopes that Korea will emerge as a top automobile production country.

Global value changes continued to expand until the late 2000s. On the other hand, regional value chains have formed around major regional hubs due to the expansion of domestic demand in emerging economies, such as China, and strengthened trade protectionism since the global financial crisis. Such changes lead to the reorganisation of value chains, focusing on domestic markets (reshoring) or neighbouring countries (nearshoring). In particular, the importance of supply chain risk management has been highlighted following disruptions to the supply network due to the COVID-19 outbreak in December 2019. In this regard, major countries such as the USA and the EU are rapidly shifting to regional value chains for stable and sustainable production, rather than primarily aiming for production efficiency targeted at reducing costs. Industries in particular are more exposed to such supply chain risks under the existing structure and it now has become extremely important for businesses to take reaction to such risks. This is especially important for major industries in a country such as automobile or semiconductor manufacturing industries in South Korea. The aim of this study, therefore, is to establish the basis for the simultaneous growth of ports and linked industries by examining the existing structure of the global value chain for the automotive industry, which has a strong presence in South Korea’s domestic economy. In this regard, this research carries out a supply chain analysis focusing on the imports and exports of automotive parts. It also analyses the current structural risks and suggests risk management measures to secure a stable supply chain.

The increase in automobile usage across the world has fortified the opportunities of maintenance service garages. However, there are significant numbers of challenges in front of maintenance service providers at all stages of the business. This paper identifies, analyzes and prioritizes various challenges associated with the establishment and survival of garages specific to Indian context.

In this paper, challenges for automotive service garage are identified through expert opinion, garage survey and literature. A structural hierarchical framework of the identified challenges is established through structural models, including interpretive structural modeling and analytic hierarchy process.

This paper has identified nine challenges, namely proliferation of new models and variants; technological advancements in automobile systems; demand of better service quality; space and ambience requirements; labor requirements; requirement of modern support equipments, tools and spares; safety requirements and prevention of occupational hazards; environmental norms and concerns; proper documentation requirements. The drivers and dependent variables have been identified. A hierarchical framework of challenges has been established.

This paper provides a comprehensive list of challenges and their priority in establishing an automobile maintenance garage business in Indian context. This will help the budding entrepreneurs and existing maintenance organizations to focus on the challenges that necessitate immediate attention and corrective actions.

This paper provides a significant contribution in the literature of garage maintenance services, which is established on the viewpoint of different collaborators associated with this business. This study will be a foundation to investigate further in this domain.

The car-sharing market has entered the mature stage, and consumers' demand shows a diversified increasing trend. This paper considers two modes of operation and two pricing strategies, which are business-to-consumer and consumer-to-consumer modes, market pricing and platform pricing. Under these conditions, the platform's revenue-sharing ratio will be different. The purpose of this paper is to explore this research question, and seeks an optimal pricing mechanism that can achieve a win–win situation between platform and automobile manufacturer in the two market modes.

The authors design different profit functions for platform under the two contexts. Of course, the platform's function is constrained to the manufacturer's function. By introducing a revenue-sharing contract a Stackelberg game model dominated by the platform is established and the equilibrium solutions under the two pricing models are derived.

The study found that even if only market pricing is executed, the scale of the car-sharing market will continue to expand. As the car-sharing market becomes more saturated, platform pricing is better for the automobile manufacturer; in most cases, the platform prefers platform pricing, but when the number of private cars is relatively small, if the cost of car operation and maintenance for the automobile manufacturer is lower or the revenue-sharing ratio of private cars is high, then market pricing will be more favorable to the platform.

With the cross-border integration of car service platforms and the automobile manufacturing industry, the key to achieving win–win cooperation and sustainable development in the car-sharing market will converge on the question of how to design a suitable pricing mechanism and revenue-sharing method.

Authors have determined how a car-sharing platform achieves a win–win order pricing strategy with the manufacturer and private car owners, respectively. And authors combined the supply chain revenue-sharing contract with the car-sharing market to explore the application of the revenue-sharing contract in the sharing economy.