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Automotive industry is one of the most important industries in the economy of countries due to its extensive relationship with other industries; high production and employment rate play a significant role in the sustainable development of countries. Therefore, the improvement of value creation integration strategies in this industry is very important because it is related to the level of economic sustainability of countries. The purpose of this study is to analyze the integration matrix of the creating sustainable value process in the automotive industry.

This research is a development/mixed methodology that aims to symmetrically combine the relationship between the components of sustainable value creation integration through Mick Mac matrix analysis to identify the most effective drivers of the research subject in the Iranian automotive industry. Therefore, in this study, first, in the qualitative part, meta-synthesis analysis and Delphi analysis were used to identify the thematic components of the integration of the process of creating sustainable value and to determine the theoretical adequacy of the components. Then, in a small part, an attempt was made to explain the approved components, based on the symmetric matrix analysis in the Mic Mac diagram, in the automotive industry to determine a more stimulus for integrating the sustainable value creation process, with the participation of 16 automotive executives.

Based on the results in the qualitative section, 8 thematic components were identified to evaluate the integration of the sustainable value creation process, and after Delphi approval, these components were approved in terms of theoretical adequacy. The results in the quantitative part based on matrix analysis showed that the most motivating component in integrating the process of creating sustainable value in the automotive industry is the development of innovative ideas. To create integration in creating sustainable value, it is necessary to create a positive impact of creative ideas in the three components of balancing performance with the changing needs of K3 customers, the dynamics of communication with K8 suppliers, reducing the diversity of materials used in K5 production.

This paper is considered as a research that contributes to the broader research area of the automotive industry by unpacking the concept of value creation from a sustainability perspective. This is the first study to review extensively of integrating sustainable value creation process into the automotive industry. Although an area of research importance in terms of developing theoretical literature and applied basis in increasing the effectiveness of competitive strategies. But less research has examined this issue, and conducting this research and expanding it to the level of sustainability value literature can enhance its institutional and research capacities at the international level and contribute to the coordination of the development of theoretical.

The aim of this study is to develop a framework for the implementation of a Supplier Kanban System.

The research was conducted within a factory focusing on the warehousing and supplier-related operations using an action research methodology.

The study period spanning over six years was aimed to reduce the inventory and the manpower required to manage this inventory. This initiative led to a substantial average savings of more than 500,000 Malaysian ringgit annually.

The focus of the study is on a framework for implementing a Supplier Kanban System in a small or medium-sized company within the automotive industry.

This framework is designed to be self-sufficient such that the members of the organisation can use it without the help of external experts or consultants.

Reduction in inventory stored in the warehouse, the amount of redundant work carried out by the employees and other non-monetary improvements which are difficult to monetise resulted in a much better work environment and happier employees.

The change in the paradigm of the manufacturing value chain affects the Tier 1 and 2 suppliers in Malaysia. The lines and value chains posing challenges to the suppliers have brought the idea of the Supplier Kanban System. The Supplier Kanban System adopted the action research cycles and continuous learning cycles, and this process was documented and developed as the Framework for the Implementation of a Supplier Kanban System.

Smart manufacturing (SM) lies at the core of Industry 4.0. Uniform adoption of SM across business partners is crucial to exploit its value creation potential. However, firms' willingness to invest in SM is limited by insufficient or inconclusive evidence on its performance-related benefits. To close this gap, this paper develops and tests a model linking SM adoption to firms' financial performance. Improvements along the four dimensions of operational performance (i.e. cost quality, delivery and flexibility) mediate this relation.

This study follows an empirical research approach. In particular, survey data from 234 automotive component suppliers are analyzed via covariance-based structural equation modeling to explore the link between SM adoption and operational performance. Survey data are then matched with secondary data from balance sheets of 81 firms to investigate the impact of SM on financial performance via partial least square structural equation modeling.

Findings highlight that adoption of SM results in improvements in cost, quality, delivery performance, thus suggesting that SM is a mean to overcome performance trade-offs. Improvements in operational performance enabled by SM do not give rise to superior financial performance, thus implying that SM might support firms in maintaining the competitive position in the market, but could be insufficient to generate higher margin.

Results have implications for SM research and for manufacturing executives engaged in the adoption of SM, as they provide a detailed analysis of the impact of SM on operational performance and clarify the effect that SM adoption has on financial performance.

Product Lifecycle Management (PLM) systems have gained wide popularity for their role in manufacturing organizations for creating, managing and distributing product data. These systems are one of various enterprise systems which are required for smooth functioning and meeting the scaling up requirements organization. However, with introduction of cloud technology and other industry 4.0 initiatives, there has been focus on moving the on-premises IT application to the cloud. Such a move needs to be carried out by identifying and evaluating various challenges. This paper aims to discuss the aforementioned objective.

The challenges identified through literature review have also been confirmed to be present via interview, system observation and documentation review through case study-based validation in an automotive component manufacturing industry.

The article identifies needs and challenges of cloud PLM systems and presents a generic framework for developing an approach for cloud PLM journey for an organization. The article also provides an approach for resolving the different challenges to realizing the designed system.

The simplified generic framework has been presented for use by industry professionals and researchers for designing cloud PLM systems that would fulfill expectations of different levels of stakeholders.

Smart Manufacturing (SM) lies at the core of Industry 4.0. Operations management research has investigated the determinants of SM advancement but there is still limited understanding of the linkages between SM and organizational factors and about whether both the technological and organizational subsystems for SM are guided by firms’ competitive priorities. To close these gaps, building on operations strategy theory, this paper aims to empirically test a model positing that competitive priorities drive SM advancement. The relation between competitive priorities and SM advancement is assumed to be mediated by organizational microfoundations.

Using data from a single respondent survey with 234 firms in the automotive component industry, structural equation modeling is adopted to test the model hypotheses. Relevant constructs are measured with reference to the lead plant for SM.

Findings highlight that SM advancement is driven by the need to simultaneously compete in terms of cost, quality and delivery, thus suggesting that manufacturers view SM as a mean to develop multiple manufacturing capabilities. Organizational microfoundations fully mediate the relation between competitive priorities and SM advancement.

Results have implications for SM research, as they provide an understanding of the strategic priorities of firms engaging in SM. Findings also bear relevance for manufacturing executives engaged in the SM transformation, as they provide quantitative evidence that shaping an adequate organizational environment is a prerequisite for SM advancement.

This paper aims to present a simple and innovative fuzzy methodology-based lean performance measurement system (L-PMS) for an Indian automotive supply chain. The paper also enlightens the influence of coronavirus disease 2019 (COVID-19) on supply chains and the practical implications of the unprecedented disruptions on the performance measurement systems.

The L-PMS is divided into three phases. In the first phase, the key performance indicator (KPI) list, as deemed fit by the organization, is prepared using literature and suggestions from the case organization. The list contains 61 KPIs measuring 24 performance dimensions in seven functional areas of the supply chain. In the second phase, the KPI performance data (actual, best and worst) are collected using the enterprise resource planning (ERP) system. In the last phase, the leanness score of the case organization is calculated at four levels – KPI, dimension, functional area and overall organization.

The overall leanness score of the case organization is 60%. The case organization uses KPIs from all seven functional areas, but it needs to improve the number of KPIs in administration and supplier management functional areas. The case organization uses only quantitative KPIs. However, the performance dimensions at the middle level are adequate. The leanness level of the case organization in different areas is highly variable (ranges from 45% to 91%).

The major limitation of the study is that the case study is done at a single organization.

The managers at the different levels of the hierarchy can use the lean performance measurement score to leverage the better performing areas/dimensions/KPIs and improve poor performing areas/dimensions/KPIs. The lean performance measurement at functional area level can help leadership to give responsibility to different people for the improvement of leanness with respect to different dimensions/functional areas. The disruptive impact of COVID-19 should clearly be understood by the managers to make appropriate decisions based on the severity as measured at different levels.

According to the authors' best knowledge, this is the first lean performance measurement application at the four hierarchical levels (KPI, performance dimension, functional area and overall organization).

In 2016, the ISO/TS 16949 quality management standard for the automotive industry evolved to IATF 16949. The update brought new requirements that need to be analyzed before being implemented in organizations. Therefore, the purpose of this article is to propose guidelines to assist organizations in the automotive sector in the implementation of the elements added in the update to the IATF 16949 standard.

To fulfill this objective, the identification and analysis of the elements added in the evolution from ISO/TS 16949 to IATF 16949 was carried out, and four case studies were conducted in Brazilian automotive companies.

The main elements added to IATF 16949 with the update of the standard are the use of process failure mode effects analysis (PFMEA) for risk analysis; the development of a communication channel for employees to report cases of misconduct and non-conformities; procedures for controlling repaired/reworked products and temporary changes; and the inclusion of autonomous maintenance for the full implementation of total productive maintenance (TPM).

The main practical implication/contribution of the research is the proposed guidelines, which can support managers and automotive companies that want to implement, or will go through, the IATF certification process. The article's originality lies in the combination of a theoretical framework and case study analyses to develop the guidelines.

Industry 4.0-driven digitalisation is said to offer a way to redesign traditional compliance-oriented quality management (QM) models. However, despite a rising academic and practitioner interest, it is still unclear how companies transform their current QM models to meet the real-time needs of the new manufacturing paradigm. The purpose of this study is to explore practices for the digitalisation of QM and to uncover the digitalisation journey.

An exploratory research approach of an embedded case study of a multinational auto-component manufacturer was adopted to achieve the research aim.

A guiding framework called the “Quality 4.0 transition framework” was developed based on literature and expert knowledge. The framework is made up of three building blocks, i.e. the foundation of “as-is” digitalisation maturity assessment; pillars representing horizontally and vertically integrated QM processes, and roof signifying reinforcement of total quality management (TQM) principles at all levels.

The study provides empirical evidence of the case company's digitalisation journey to avert product recall due to field failure issues. The study contributes to theory and practice in many ways. First, the study uses empirical data from a real-world case to understand how digitalisation affects QM processes. Next, the guiding framework for the Quality 4.0 transition adds to the existing literature on the digitalisation of business processes.

In this study, the authors assess the current state of lean product development and the lean production shop floor, along with the impact of the former on process quality and the latter on product quality and customer complaint reduction. The interplay between process and product quality and customer complaint reduction is assessed, along with their impacts on business performance.

Data were collected from 377 managers working at auto-component manufacturing firms in India. Confirmatory factor analysis was used for scale validation, and structural equation modelling was employed to test the research hypotheses.

The results of the statistical analyses reveal the positive influence of a lean production shop floor on process quality and lean product development on product quality and customer complaint reduction, and thereby on business performance.

The findings of this research provide insights into the interplay between lean and quality factors and their influence on customer complaint reduction and business performance. Practitioners can use the proposed model to strategically design unique products and improve the efficiency and effectiveness of the production shop floor, which can help enhance the product and process quality. This can reduce customer dissatisfaction and improve the business performance.

Few studies have simultaneously investigated the influence of lean product development and lean production shop floors in the Indian manufacturing context. To the best of our knowledge, this study is one of the first attempts to include customer complaint reduction as a construct in a lean model. It helps identify and prioritise the enablers of business performance and provides valuable insights for practitioners to strengthen lean implementation to attain a competitive edge.

Nowadays, many firms are finding ways to enhance the survivability of sustainable supply chains (SUSSCs). The present study aims to develop a model for the SUSSCs of small and medium enterprises (SMEs) during the COVID-19 pandemic.

With the help of exhaustive literature review, constructs and items are identified to collect the responses from different SMEs. A total of 278 complete responses are received and 6 hypotheses are developed. Hypotheses testing have been done using structural equation modeling (SEM).

Major constructs identified for the study are supply chain (SC) performance measurement under uncertainty (SPMU), supply chain cooperation (SCCO), supply chain positioning (SCP), supply chain administration (SCA), supply chain feasibility (SCF) and the SUSSCs. From statistical analysis of the data collected, it can be concluded that the considered latent variables contribute significantly towardsthe model fit.

The present study contributes to the existing literature on disruptions and survivability. The study can be further carried out in context to different countries and sectors to generalize the findings.

The research findings will be fruitful for SMEs and other organizations in developing strategies to improve survivability during uncertain business environments.

The study has developed a model that shows that the identified latent variables and their indicators contribute significantly toward the dependent variable, i.e. survivability. It contributes significantly in bridging the research gaps existing in context to the survivability of SMEs.