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This study aims to investigate relationships among supplier capabilities, collaboration in new car development, and the competitive advantage of carmakers based on the resource‐based view (RBV).

A survey of first‐tier suppliers in the Korean automotive parts industry was conducted, and pertinent hypotheses were tested by using the ordinary least squares (OLS) method and hierarchical multiple regression analysis (HMRA).

It was found that suppliers' flexibility, engineering and modularization capabilities positively influence collaboration in new car development, which in turn positively affects the competitive advantage of carmakers. This result empirically verifies the RBV proposition that one motive for interfirm collaboration can be the opportunity to gain access to other firms' resources/capabilities. The theory of the RBV was further extended by demonstrating that suppliers' quality improvement and modularization capabilities directly contribute to the competitive advantage of carmakers and that the influence of quality improvement and modularization capabilities on this competitive advantage are robust against technological uncertainty. However, the positive effect of collaboration in new car development on the competitive advantage of carmakers is decreased by the moderating effect of technological uncertainty.

The findings of this study were obtained from a limited population of the Korean automotive industry. This study not only empirically verified the proposition of the RBV but also extended the RBV theory by empirically demonstrating direct relationships between suppliers' capabilities and carmakers' competitive advantages.

Suppliers must enhance flexibility, modularization and engineering capabilities in order to vitalize collaboration with carmakers in new car development. As technological uncertainty increases, carmakers should address in‐house the problems caused by technological uncertainty or delegate related jobs only to suppliers with significant capabilities for quality improvement and modularization.

This is one of the few studies to identify the moderating effect of technological uncertainty on interfirm collaboration.

The purpose of this paper is to study the latest global automotive industry’s competitive strategies comprehensively before being categorized into countries, automakers and other scholars.

In total, 54 most relevant articles have been chosen from various journals and databases between the years 2017 and 2018 with search items “Competitive” and “Automotive” for the most updated review. Based on findings, there are total 133 competitive strategies.

Based on the review and analysis of the literature, all of these three categories, countries, automakers and other scholars, are using new product development (NPD) as a competitive strategy. As a result, further research on NPD, specifically in the automotive industry area, is vital for industry’s competitiveness based on this study.

Firms are advised to be ahead from the competitors in terms of business model or in their management in order to attain sustainability. However, to the authors’ best knowledge, there is no comprehensive review on competitive strategies for automotive globally by countries, automakers and other scholars.

The competitive strategies are reviewed comprehensively so that other than guiding the further research, they can help automakers, especially from developing countries, to improve the strategies suitable to the current trend.

Automotive industry plays a key role in the day-to-day activity of human life by not only providing mobility but also having an enormous impact of the industry on economic, environmental and social activities throughout the globe.

Most of the articles reviewed related to certain country or comparison between the countries, and certain automaker or comparison between the automakers, but still no study about comprehensive review globally covered in the larger scope, divided into three categories; countries, automakers and other scholars even though the study is vital not only to academicians but also to practitioners.

This study empirically tests a model of human capital (HC) factors affecting the organisational competitiveness (OC) of automotive parts suppliers in the Industry 4.0 framework, including concepts such as Toyota Kata (TK), Kaizen and Quality 4.0, during the coronavirus disease 2019 pandemic.

An instrument was created to measure emotional intelligence (EI) and analytical skill (AS) as input variables and OC as the output variable. The instrument was distributed electronically to Tier 1 non-technical employees in Nuevo León and Querétaro, México. A total of 195 surveys were obtained. The instrument used stepwise multiple linear regression.

This study proposes a model to strengthen the OC of Tier 1 automotive parts supply industry from the perspective of HC factors. Furthermore, it is shown that EI and AS have a positive and significant impact on OC.

From an HC perspective, this study provides a useful basis to improve OC for researchers, industry experts and managers at different levels of the automotive industry, including the triple helix (academia, industry and the government).

No studies simultaneously test the relationship of EI and AS to OC; therefore, this study fills a gap in the literature. Furthermore, the study explored the literature on individual Kaizen (IK) and TK, leading to a contrast between the definitions of EI and AS. Finally, for EI, a reference to motivation was found in the IK. In the case of AS, an orientation to ability of problem solving was found in TK.

In this research, the emphasis is multifold. First objective is to study differences amongst India's Make-in-India, Germany's Industry 4.0 and China's Made-in-China 2025 on a macro level. Second objective is to identify where does individual industry segment out of the five broad segments (prioritized by Make-in-India initiative) represented by ten firms in India stand in terms of adoption of Industry 4.0 technologies. Third objective is to identify key barriers for each of these five industry segments. Finally, socio-technical interventions are also proposed aimed at faster adoption of Industry 4.0 technologies.

A mixed methodological approach is followed to achieve the research objectives. First, for the macro-level comparison of three pertinent countries, extant research and industry literature have been relied upon. Thereafter, at a micro level, inputs from experts belonging to focal sectors are included in this study to ascertain the current level of readiness of adoption of Industry 4.0 technologies and the barriers to adoption. Finally, the authors argue for and propose some socio-technical interventions that are aimed at mitigation of barriers for adoption of Industry 4.0 technologies.

It has been ascertained that amongst the ten firms (two each from given focal sectors) considered in the study, the automotive and the software firm are perhaps best placed to adopt the Industry 4.0 technology, while the infrastructure project management firm is least ready for Industry 4.0 technologies. The common barriers to adoption of Industry 4.0 technologies, as elaborated by experts belonging to each of the ten firms, are also identified. These three commons barriers are resistance to change, unclear economic benefits and problems related to coordination and collaboration.

The study is one of first attempts to understand the nuances related to technology readiness across focal industries pertaining to the Make-in-India initiative and Industry 4.0. The study furthers the extant understanding of common and distinct barriers across industries. Employing the soft-systems methodology, the study advocates for a number of socio-technical interventions pertaining to establishment of e-skill ecosystem, community learning clusters and sector-focussed skill acquisition and augmentation. Since the study considers only two firms corresponding to each of the five focal sectors, including more firms across industries could have resulted in further validation of study as well.

Contrasting the initiatives of the three countries results in identification of different thematic focus of the respective initiatives. While India's Make-in-India initiative has a strong social dimension, Germany's Industry 4.0 and Made-in-China 2025 have key objective related to integration of cyber-physical systems and to graduate to innovation-driven country, respectively. Further, analysis on the technology readiness for adoption of Industry 4.0 technologies based on the respective experts' assessment results in understanding of the underlying barriers.

Adopting the soft-systems perspective linking nuances of stakeholders, socio-technical systems and socio-economic characteristics results in several propositions to further the social objectives of India's Make-in-India initiative. These propositions advocate for pathways in which extant strengths in terms of technology, people and existing socio-technical structures can be brought together to cater to the requirements related to employability and skill augmentation of new as well as existing workforce.

Extant research literature is primarily focussed on certain specific topics within Industry 4.0 implementation and is mainly based on conceptual or theoretical basis. From a practitioners' perspective, only a few empirical papers could be found that too are typically focussed on single case studies resulting from pilot applications of Industry 4.0. However, such papers have not examined the broad implications of Industry 4.0 in terms of differences between key countries' manufacturing initiatives, readiness of key sectors, sectoral barriers and accompanying policy-level implications associated with implementation of Industry 4.0. Thus, the objective of this research is to abridge these research gaps.

The primary purpose of the research was to determine whether automotive manufacturers integrate multiple manufacturing initiatives and whether performance measures were impacted directly by these initiatives.

A mail survey questionnaire was used to gather data about the attitudinal attributes associated with implementing multiple manufacturing initiatives (i.e. ISO 9001, ISO 14001, lean manufacturing) and changes in key performance measures, both financial and nonfinancial. Descriptive statistics were utilized to gain a better understanding of the level of implementation of specific initiatives. Different forms of regression analysis were used to try to locate a statistically significant predictive model.

Two surveys of automotive suppliers were conducted during early summer 2001 and 2002 to gather information about multiple initiatives, customer mandates, and performance measurement. The results indicate that suppliers are not integrating the initiatives or linking them to financial and/or nonfinancial performance measurements. It was intended to develop a predictive model linking the implementation of multiple manufacturing initiatives and the impact on changing in performance measures. No statistically significant model was discovered. However, and not surprisingly, the level of implementation of different initiatives varies from one organization to another.

The size of the sample could pose a limitation in terms of generalizabiity. Also, this study was applied to specifically to the automotive supply parts industry and it could be applicable to other manufacturing supply chains.

Automotive industry suppliers have been faced with multiple, mandated requirements from the original equipment manufacturers. Continuing pressures to reduce price, improve quality, while producing an environmental friendly product using lean manufacturing practices has placed a financial strain on suppliers operating with thin profit margins. Are these initiatives being integrated into the overall business strategy and what impact are they having on performance measures? Based on the research, it did not appear to be well integrated. Additionally, a comparative analysis was conducted to note differences between senior management and middle management/professional staff. It was not surprising to find that senior management has higher expectations and opinions regarding implementation levels and performance.

The information in this study is particularly useful to manufacturers or others implementing standards or methodologies and to understand whether there is a direct impact on performance measurements.

With the rapid development of the sharing economy in manufacturing industries, manufacturers and the equipment suppliers frequently share capacity through the third-party platform. This paper aims to study influences of manufacturers sharing capacity on the supplier and to analyze whether the supplier shares capacity as well as its influences.

This paper deals with conditions that the supplier and manufacturers share capacity through the third-party platform, and the third-party platform competes with the supplier in equipment sales. Considering the heterogeneity of the manufacturer's earning of unit capacity usage and the production efficiency of manufacturer's usage strategies, this paper constructs capacity sharing game models. Then, model equilibrium results under different sharing scenarios are compared.

The results show that when the production or maintenance cost is high, manufacturers sharing capacity simultaneously benefits the supplier, the third-party platform and manufacturers with high earnings of unit capacity usage. When both the rental efficiency and the production cost are low, or both the rental efficiency and the production cost are high, the supplier simultaneously sells equipment and shares capacity. The supplier only sells equipment in other cases. When both the rental efficiency and the production cost are low, the supplier’s sharing capacity realizes the win-win-win situation for the supplier, the third-party platform and manufacturers with moderate earnings of unit capacity usage.

This paper innovatively examines supplier's selling and sharing decisions considering manufacturers sharing capacity. It extends the research on capacity sharing and is important to supplier's operational decisions.

Aims to review current trends in the development of robotics 2004‐2008, from a cybernetic viewpoint, and provide; data from the UNECE/IFR World Robotics Survey.

A general review and survey of selected research and development topics.

Illustrates the multi‐ and trans‐disciplinary interests of cybernetics and systems and aims to further research and development activity.

The choice of reviews provides an awareness of the current initiatives and trends in these areas of research and endeavour.

The reviews are selected from a global database and give a studied assessment of current research and development initiatives.

This paper investigated the impact of components and contextual elements of strategic planning on the effectiveness of the strategic planning process. Specifically, the characteristics of planning and the overall effectiveness of planning processes in the automotive industry were studied. A large‐scale survey revealed that certain aspects of these firms’ planning processes were vital for their continued effectiveness. Functional coverage was identified as one of the most important component of strategic planning and provision of sufficient planning resources and the most important contextual element. The practical implications of this research for firms in the automotive industry are discussed.

This paper aims to examine the current state of reverse supply chain management (RSCM) initiatives in several Turkish industries.

This study is based on an exploratory research regarding RSCM activities of Turkish automotive, white goods, electric/electronics, and furniture industries. The sample consists of all the companies included in the Top‐500 Industrial Enterprises List of The Assembly of the Istanbul Chamber of Industry (ISO).

The research findings show that the RSCM initiatives in the considered industries are still in a very early stage. Companies' involvement in product returns is mostly due to the legislative liabilities, and system inadequacies are emphasized as the most important reason for not being able to implement an efficient RSCM.

This paper investigates the reverse supply chain practices of selected industries in Turkey and aims to enable researchers to use this study as a building block in understanding these practices and related problems. The limitation of this study is to solely include the medium and large‐sized companies in the industries.

Reverse supply chain operations contribute to the economic sustainability by reducing waste and saving energy and material. In this research, an empirical study in the electronics, white goods, automotive and furniture industries is conducted, and potential research opportunities are discussed to streamline reverse supply chain activities in the industries. Hence, this study can be viewed as an attempt to increase the level of awareness on reverse supply chain issues.

No field study has been conducted to analyze reverse supply chain activities of the industries in Turkey. This research is a pioneering study and will provide a benchmark for the various research activities on related topics.

The purpose of this paper is to provide a clustering approach to segment supply chain partners in the automobile industry and prioritize services offered by third party logistics service (3PL) providers.

In total, 98 automobile and auto‐parts manufacturers are surveyed to identify service needs, preferences, and outsourcing commitments. By applying a two‐stage clustering approach combined with Ward's minimum‐variance method and the K‐means algorithm, the logistics companies prioritize their services to better satisfy groups of customers with specific preferences.

Four distinctive groups of manufacturers are identified using the two‐stage clustering approach. The clusters separate logistic preferences and outsourcing patterns of after market parts suppliers, original equipment service parts suppliers, original equipment manufacturer parts suppliers, and tier one car makers. The paper finds that distribution and delivery services hold the highest percentage of services outsourced among the manufacturers.

This paper models logistic services as customizable services and develops a data system methodology to define the profiles of automobile manufacturers and their preferred logistic services. Through the analysis of service preferences and clustering, the paper identifies the key logistic services that can be customized for members of the automobile supply chain. A case is provided which demonstrates how a logistics company can provide customized service designs for specific target markets and customers.