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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.

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.

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.

The purpose of this study is that on the basis of the competitive edge theory, source mechanism and evaluation approaches of industrial cluster competitiveness, combined with international trends in the automobile industry and the features of Chinese automobile industrial cluster development, an evaluation index system about cluster competitiveness of auto industry is built with comprehensive consideration of factors such as cluster development environment, external scale effect and internal competitiveness from the perspective of value chain of automobile industry.

An evaluation index system for automobile industrial cluster competitiveness was realized by integrating current strengths and future growth capacities with multidimensional, dynamic and comprehensive characteristics, which included 3 second-level, 10 third-level and 16 fourth-level indices. In the light of evaluation methods, a group intelligence optimization algorithm – (cuckoo search) – and traditional methods of complex decision-making system – analytic hierarchy process (AHP) – were combined to propose the cuckoo-AHP evaluation method. It was applied for the calculation and optimization of weight values in an automobile industrial cluster competitiveness evaluation index for the purpose of obtaining better scientific and more reliable results.

The research might further enrich the evaluation theory of automobile industrial cluster competitiveness and also can be useful for showing how traditional evaluation methods can be combined with intelligent algorithms to carry out better automobile industrial cluster competitiveness evaluations. In addition, studies of channels for kick-starting Chinese auto industrial cluster competitiveness are expected to provide references for how to enhance the cluster competitiveness of the Chinese automobile industry.

Changsha and Liuzhou, the Guangxi automobile industrial clusters as the two empirical analysis objects selected for this paper, are geographically adjacent to each other. The automobile industries of the two cities are local pillar industries with the strong support of the local government. Both clusters have their own advantages and weak points with different characteristics of cluster development, and they enjoy a representative significance amongst China’s numerous auto industrial clusters that are taking shape. Comparative analysis of both clusters serves as a good reference for the objective evaluation of the competitiveness of Chinese automobile clusters in terms of their real and practical developments and in respect of the success of reasonable scientific and industrial cluster policies.

Multidimensional, dynamic, integrated evaluation index systems are constructed around automobile industrial cluster competitiveness, which has taken into account developments in current strengths and future growth capacity. The cuckoo-AHP evaluation method has been formed by combining the traditional decision-making method known as AHP with a new meta-heuristic optimization algorithm called “cuckoo search”. Both have been used in evaluations of automobile industrial cluster competitiveness in Liuzhou and Changsha, which will be beneficial for enriching automobile industrial cluster competitiveness evaluation theory and new evaluation methods that will enable better evaluations of automobile industrial cluster competitiveness.

This paper aims to make a systematic study on the factors that hinder the development of China’s intelligent automobile manufacturing industry; based on comprehensive understanding of these obstacles and by optimization means, ultimately, the healthy and sustainable development of intelligent automobile manufacturing industry in China can be promoted.

Based on a questionnaire survey of intelligent automobile manufacturing listed companies in China, first, fuzzy semantic scale was adopted to collect respondents’ choices, the fuzzy score function is used to calculate the fuzzy score value and these data are used as the basis for subsequent model analysis. Then, structural equation modeling (SEM) was adopted to analyze the causal relationship between influencing factors to explore the main hinder factors.

It is found that, in the short term, the backwardness of technological industrialization is the main reason leading to low permeability of intelligent automobile; in the medium term, the imperfect industrial R&D ability and the insufficiency of infrastructure are major causes for high manufacturing cost and low competitiveness of intelligent automobile manufacturing industry; in the long term, the lack of national policy and industrial strategic planning is the main factors affect intelligent automobile manufacturing cost and the industry competitiveness.

The research conclusion has important policy implications for promoting intelligent automobile manufacturing sustainable development. In recent years, China’s intelligent automobile manufacturing industry has gradually stepped out of breeding period; therefore, the role of government should be gradually transformed from participants to managers and regulators. Considering the fact that intelligent automobile cost is very high, and still higher than the cost of fuel vehicle, government should focus on the issues such as improving R&D capabilities, infrastructure construction, policy framework system, legal system and technological industrialization. Specifically, in short-term planning, improving technological industrialization level is the key to development; in medium-term planning, policymakers should focus on the improvement of R&D capabilities and infrastructure; considering the long-term development, establishing appropriate national policies and dealing with the adverse impact of imperfect strategic planning are the most sensible choice.

This paper analyzes the factors that hinder the development of China’s intelligent automobile manufacturing industry for the first time, and provides the basic logic of integration factors at different levels with the development of intelligent automobile to reveal the uniqueness and facts of China’s economic development.

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.

The purpose of this paper is to exhibit the influencing factors on and the process of internationalization with regard to Chinese automobile companies.

The author adopts an explorative approach to investigate the 12 major Chinese automobile manufacturers in terms of sales for the year 2010. Concentrating on the automobile industry in China, the author provides context and comparability.

The findings show that the internationalization of Chinese automobile companies cannot be explained by one theoretical model only and challenge previous internationalization research. Nevertheless, in retrospect, some patterns can be seen. Until the year 2000, technology was absorbed through domestic joint ventures with Western manufacturers. Up to 2010, internationalization involving exports may be viewed as having been a “test” phase, becoming a strategic goal defined by the Chinese government. Different internationalization attributes are aggregated into a comprehensive ranking of the case‐study companies. The ranking is analyzed with regard to managerial and company influences, as well as to incentivizing factors that potentially generate internationalization. As an incentivizing factor, the governmental environment plays a crucial role, having designated the automobile industry as one of China's pillar industries.

The paper gives new insights into internationalization processes on an industry level. In particular the Chinese strategic approach to internationalization is exhibited and discussed for the automobile industry.

This study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.

Based on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.

The results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.

The hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.

This study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.

Circular economy (CE) has gained considerable attention from researchers and practitioners over the past few years because of its potential social and environmental benefits. However, limited attention has been given in the literature to explore the drivers and barriers in CE implementation in emerging and developing countries besides China. Therefore, the purpose of this paper is to identify the drivers and barriers to implementing a CE in Pakistan’s automobile manufacturing industry.

This study adopts an explorative approach to understand the drivers and barriers at the micro-level CE implementation in Pakistan’s automobile industry. The research design includes both qualitative and quantitative methods using a survey instrument and interviews to gather data. The use of the two main sources of data provides the opportunity for triangulation of the data to improve the validity of the findings, and enables greater inferences from the results.

This study shows that “profitability/market share/benefit” (30 percent), “cost reduction” (22 percent) and “business principle/concern for environment/appreciation” (19 percent) are the top three drivers. Similarly, “unawareness” (22 percent), “cost and financial constraint” (20 percent) and “lack of expertise” (17 percent) are the top three barriers in implementing CE principles in Pakistan automobiles industry.

This study considers only Pakistan automobiles industry, and the practical implications potentially limit to emerging Asian economies.

This study is the first of its kind that has investigated the drivers and barriers of CE at the organizational level in the automobile industry of Pakistan. Thus, it helps to advance the understanding of the subject matter and enables the formulation of effective policies and business strategies by practitioners for upscaling CE and sustainability.

This paper aims to quest the strategies and paths of Chinese automobile firms for being world class. It analyzes their strengths and potentials in comparison with the development experience of the global examples and provides policy recommendations for cultivating world-class automobile firms.

The authors apply the analytic hierarchy process method to evaluate the competitiveness of automobile firms with multiple indicators.

The evaluation results suggest that Chinese automobile firms still lagged behind their world-class peers. Especially, Chinese domestic firms developed unevenly so that they could not make progress in the core parametric dimensions. Nevertheless, Chinese firms could achieve world class, at least in some niche segments, supported by its accumulated technological capacity and tremendous market size.

This research is the first scholarly work to evaluate the competitiveness of Chinese automobile firms and provides insightful comments on its industrial policies in the automobile industry. This may be valuable for policymaking in the automobile sector of China and other developing economies.