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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.

Supplier selection (SS) is one of the prime competencies in a sourcing decision. Taking into account the key role played by suppliers in facilitating the implementation of green supply chain management (GSCM), it is somewhat surprising that very little research attention has been imparted to the development of a strategic sourcing model for GSCM. This research aims to develop a strategic sourcing framework in which supplier organizations are prioritized and ranked based on their GSCM performance. Accordingly, the benchmark organization is identified and its strategy is explored for GSCM performance improvement.

The research develops an innovative GSCM performance evaluation framework using six parameters, namely, investment in corporate social responsibility, investment in research and development, utilization of renewable energy, total energy consumption, total carbon-di-oxide emissions and total waste generation. An integrated multicriteria decision-making (MCDM) approach is proposed in which the entropy method calculates criteria weights. The Complex Proportional Assessment (COPRAS) and the Grey relational analysis (GRA) methods are used to rank supplier organizations based on their performance scores. A real-world case of green supplier selection (GSS) is considered in which five leading India-based automobile manufacturing organizations (Supplier 1, Supplier 2, Supplier 3, Supplier 4 and Supplier 5) are selected. Surveys with industry experts at the strategic, tactical, and operational levels are carried out to collect relevant data.

The results reveal that total carbon dioxide emission is the most influential parameter, as it gains the highest weight. On the contrary, investment in research and development, and total waste generation have no significant impact on GSCM performance. Results show that Supplier 5 secures the top rank. Hence, it is the benchmark organization.

The proposed methodology offers an easy and comprehensive approach to sourcing decisions in the field of GSCM. The entropy weight-based COPRAS and GRA methods offer an error-free channel of decision-making and can be proficiently used to outrank various industrial sectors based on their GSCM performances. This research is specific to the automobile manufacturing supply chain. Therefore, research outcomes may vary across supply chains with distinct characteristics.

The basic propositions of this research are based on a real-world case. Hence, the research findings are practically feasible. The less significant parameters identified in this study would enable managers to impart more attention to vulnerable areas for improvement. This research may help policymakers identify the influential parameters for effective GSCM implementation. As this research considers all aspects of sustainability, the strategies of the benchmark supplier have a direct impact on organizations' overall sustainability. The study would enable practitioners to make various strategies for GSCM performance improvement and to develop a cleaner production system.

The originality of this research lies in the consideration of both economic, social, environmental and operational aspects of sustainability for assessing the GSCM performance of supplier organizations. Quantitative criteria are considered so that vagueness can be removed from the decision. The use of an integrated grey-based approach for developing a strategic sourcing model is another unique feature of this study.

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.

This paper aims to present strategic performance management modeling of the Indian automobile manufacturing enterprises. This will help to understand the hierarchical structure and linkages of different strategic factors related to enterprise performance in a better way. Automobile manufacturing industry is one of the top industries in India. It is of paramount importance to identify the strategic factors and their linkages to understand the strategic performance management issues better.

Flexible strategy game-card, an evolving performance management framework, has been taken as the basis for the development of a strategic performance management model. Thematic content analysis is used to analyze semi-structured interviews and for identifying strategic factors related to performance. Total interpretive structural modeling (TISM) is used to develop the hierarchical structure of these performance strategic factors. Case-lets and statistical analysis are used to further validate these models.

The study proposes a strategic performance management model for Indian automobile enterprises that can be considered as a conceptual framework which helps to identify the leading and lagging factors of performance. This can be considered as an exploratory study for conceptualization and can be further validated through empirical testing.

The research methodology adopted here gives a guideline to researchers for conducting an exploratory study where they can identify the factors/variables of interest through semi-structured interviews and thematic content analysis. The TISM helps to develop the poorly articulated mental model in a well-structured hierarchical form, which would help to get more insights in relation to performance.

The study fills the gaps by addressing the issue of performance in the Indian context by identifying strategic performance factors for automobile enterprises. There is an attempt to demonstrate the application of an evolving performance management framework, i.e. flexible strategy game-card. The methodological rigor and application of mixed methods adds value to the knowledge base by providing a mechanism to conduct an exploratory study for the area of interest.

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 study aims to utilize DMAIC methodology along with value stream mapping and other Lean Six Sigma tools in a major automobile light manufacturing industry to reduce defect rates and increase production capacity in their manufacturing line. The study also proposes a modified framework based on lean principles and FlexSim to identify and reduce waste in the selected industry.

A Lean Six Sigma modified framework has been deployed with DMAIC to reduce the defect rate and increase the production rate. Various tools like value stream mapping, brainstorming, Pareto charts, 5S, kanban, etc. have been used at different phases of DMAIC targeting wastes and inventory in the production line. Also, a simulation model has been utilized for the automobile light manufacturing industry to improve the machine utilization time with varying batch sizes.

The results of the study indicated a 53% reduction in defect rates. Thus, there would be an expected improvement in sigma value from 3.78 to 3.89 and a reduction in defects per million opportunities (DPMO) from 11,244 to 8,493. Additionally, simulation model using FlexSim was developed, and the optimum ordering batch size of raw material was obtained. It was also analyzed that idle time for various stations could be reduced by up to 30%.

The utilized framework helps identify defects for managers to increase production efficiency. The workers, operators and supervisors on the production line also need to be trained regularly for identifying the areas of improvement.

The modified Lean Six Sigma framework used in this study includes FlexSim simulation to make the framework robust, which has not been used with LSS tools in the literature studied. Also, the LSS finds very less application in the manufacturing domain, considering which this study tends to add value in existing literature taking a case of an automobile light manufacturing industry.

This paper aims to present existence comprehensive analysis of state of implementation of benchmarking concepts in Indian automotive companies.

The research is carried out through a mixed method of research approach comprising of a survey of 300 auto companies in India. Out of 300, 48 valid responses together with three additional case studies were used in the data analysis. Inclusion of case studies was aspired to get deeper insight into the issues pertaining to adoption of best practices, and subsequently the implementation of benchmarking activities.

Benchmarking has been unanimously accepted as an effective performance and productivity improvement tool by Indian auto companies. However, Indian automobile manufacturers still see benchmarking as a tool to compare product attributes, quality attributes, operations, and processes. Moreover, it has been perceived as being less applicable at strategic level. Results also show that benchmarking is in its primary stage in the Indian automotive industry, and it still needs much more commitment from top management for its proliferation. Lesser significance is given to competitor benchmarking due to the fear of losing competitive advantage, and the problem of confidentiality. Reasons identified in this study for not using benchmarking include “lack of human resources” as most important, followed by “financial constraints”, and “lack of internal expertise”.

Research results should be generalized and reproduced with a larger sample size. Owing to the scarce application of benchmarking in small and medium enterprises (SMEs), separate study should be carried out to find ways to encourage benchmarking implementation in Indian auto component manufacturing SMEs.

The paper provides insight into the extent of implementation of benchmarking concepts in Indian automobile industry. This study is the first attempt to understand propagation of benchmarking concepts, exclusively among Indian auto companies.

With the advance of the Silk Road Initiative proposed by China, it has been a focus of China government to develop strategic emerging industries. The development of strategic emerging industries needs the support of competitive intelligence on many aspects such as strategical planning, policy making, industrial structure adjustment, and technology innovation. However, so far there are few studies toward the competitive intelligence systems for strategic emerging industries. In this article, we focus on a number of issues related to the competitive intelligence for strategic emerging industries in China. First, we conduct a strengths, weaknesses, opportunities, and threats analysis on the situations of strategic emerging industries in China, based on which the necessity of building a competitive intelligence (CI) service system for strategic emerging industries is discussed. Next, the authors present a framework of a CI service system for strategic emerging industries in China. The principles, components, working process, and product forms are deeply described. The CI service system proposed in this article consists of a cooperation network platform, three layered organizations, and three systems, which integrates organizations, information, people, network, and service platforms into an ecosystem to offer competitive intelligence supports for government, industry, and enterprises. Finally, the authors discuss a case study of the proposed CI service system for the new energy automobile industry.

The purpose of this paper is to investigate the status of lean manufacturing in Indian automotive sector, component manufacturing industries in terms of lean adoption, benefits, motivation, and challenges of implementing lean manufacturing practices.

The research objectives were achieved by conducting a qualitative multicase study approach. Fourteen Indian automotive component manufacturing small and medium-sized enterprises (SMEs) were chosen based on their different product offerings as well as differing approaches to the introduction and implementation of lean initiatives. Data were collected through in-depth, semistructured interviews supported by shop-floor observations.

The findings from the present study suggest that some of the participating automotive component manufacturing SMEs have a relatively good understanding of lean concepts and philosophy. However, there is room for further improvement for most SMEs. Major top five lean practices being implemented were found to be cellular manufacturing, total productive maintenance, 5S, work standardization, and quality management practices. Also, leadership and organizational culture were found to be crucial factors for the success of lean manufacturing.

The fact that the data collected for the research study is based on subjective business evidence obtained from company representatives comprises the main limitation of the present study. So, the results should be considered with caution, as far as the lean adoption in Indian automotive component manufacturing sector is concerned.

Based on the present study, suggestions can be made regarding the successful adoption of lean principles, not only for the participating SMEs but also for the whole of the automotive component manufacturing sector. More specifically, by determining the strength and weakness of automotive component manufacturing SME's effort to adopt lean, suitable managerial initiatives can be undertaken by these companies as well as the whole sector to fully adopt lean and derive the respective benefits.

This paper explores the status of lean adoption in Indian automotive component manufacturing SMEs. Considering the unique characteristics of the automotive component manufacturing industry, the present research would be helpful for making strategies to implement lean in automotive component manufacturing industry setups.

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.