Search results

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.

There is a great reliance on fiscal incentives to sustain the automotive industry competitiveness due to several structural problems, among them the inefficiency of the supply chain. This paper aims to compare the supply chain structure of traditional automotive industry with the supply chains from South Korea and China. Based on strategic decision and transaction cost theory, this comparison seeks to exploit the factors that led to the inefficiency of automotive supply chains.

The authors used a qualitative approach and applied a multi-method research. They conducted semi-structured interviews with six executives from automakers representing the selected countries, carried individual meetings during one workshop and used secondary data from several sources.

Concepts identified in the research such as reliability, supply chain governance and automaker competencies led the authors to propose that the traditional automakers have higher transaction costs when compared to the new automakers due to the horizontal structure of their supply chain. While new competitors have vertical upstream supply chains, which indicates better profitability, traditional automotive industry is horizontal, depends on fewer Tier 1 suppliers and is disconnected from Tier 2, impacting negatively in the transaction costs and supply chain management.

This study suggests that automotive executives rethink the current upstream supply chain model by identifying the competencies required for their current and future competitiveness and implementing a vertical integration of these competencies.

This research exploited the inefficiency of supply chain as one of the explanations for the low competitiveness of the national automotive industry.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

The purpose of this paper is to analyse cooperation in R&D in the automobile industry in Spain. It first examines to what extent firms cooperate with external actors in the field of technological innovation, and if so, with what type of cooperation partner, paying special attention to the differentiation according to the size of the firms. Second, it aims to study how the firm’s size may affect not only the decision of cooperating but also with which type of partner.

The data in this study came from the surveys done in 2010 and 2013 by the Technological Innovation Panel (PITEC) for firms in the automotive industry. The paper estimates a bivariate probit model that takes into account the two types of cooperation mostly present in such an industry, vertical and institutional, explicitly considering the interdependencies that may arise in their simultaneous choice.

The empirical study confirms that small firms cooperate less frequently than big firms and that giving more importance to information publicly available and having public financial support from local and national governments are important determinants of collaboration agreements, mainly in the case of customers and suppliers.

This paper contributes to the understanding of the motivations of the automotive industry for engaging in R&D cooperation agreements. The authors study how the firm’s size may affect not only the decision of cooperating but also with which type of partner.

Eco-innovation is emerging as one of the most important constructs that improve environmental sustainability of firms. However, it has been shown that companies alone cannot adequately develop eco-innovation activities, which is why they require the implementation of external collaboration activities with intermediaries, suppliers and stakeholders to achieve a higher level of eco-innovation activities and improve business performance of manufacturing firms. Therefore, this research fills this gap by exploring the importance of the relationship between collaboration and eco-innovation.

The research is conducted through an extensive literature review with a research model consisting of 5 measurement scales, 24 items and 4 hypotheses. A self-administered questionnaire was distributed to a sample of 460 firms in Mexico, analyzing the data set through confirmatory factor analysis and structural equation models.

The results obtained from this study suggest that collaboration has significant positive effects both on the eco-innovation of products, processes and management, as well as on the business performance of companies in the automotive industry.

The findings of this study have important implications both for the public administration (e.g. development of policies to support companies and financing programs) and for the managers of companies in the automotive industry (e.g. training program for employees and collaboration with other firms).

This paper fills a research gap by expanding the limited body of knowledge that relates collaboration eco-innovation and business performance, which is why this research aims to fill this existing gap in the literature and explore the relationship between collaboration, eco-innovation and business performance.

Cities remain an understudied unit of analysis for understanding the motives of multinational enterprises’ (MNE) foreign direct investment (FDI), with subnational locations in International Business (IB) research to date predominantly captured via the phenomenon of agglomeration. As regional integration projects, such as the European Union and to a lesser degree NAFTA, increasingly reduce the importance of national institutional environments, this paper argues regional and subnational levels become more important for studying MNE location choice. This paper aims to evaluate the explanatory contribution of regional and subnational levels of analysis to understanding MNE location choice.

A qualitative deductive bottom-up multiple-case study research design is adopted to study the city location choices and FDI motives of six automotive and six commercial banking companies. These purposefully sampled manufacturing and service MNEs have different home countries and regional orientations. Data on their foreign investments across the extended Triad of Europe, North America and Asia-Pacific were collected for the time period of 2000–2021.

Findings suggest that different classes of city tend to attract specific types of FDI and that these patterns might vary across sectors and be influenced by the regional strategic orientations of MNEs. Industry-specific findings reveal the importance of related and support industries and partners in a city location for the automotive MNEs, while the commercial banks seek investment opportunities in cities that allow acquisition targets that have an attractive customer based and will improve their local market knowledge.

The findings provide evidence in support of MNEs in manufacturing and service industries perceiving the attractiveness of three city types in different ways across the Triad regions.

Governments around the world instituted guidelines for calculating energy efficiency of vehicles not only by models, but by the whole universe of new vehicles registered. This paper compiles Multi-criteria decision-making (MCDM) studies related to automotive industry. We applied a Systematic Literature Review on MCDM studies published until 2015 to identify patterns on MCDM applications to design vehicles more fuel efficient in order to achieve full compliance with energy efficiency guidelines (e.g., Inovar-Auto). From 339 papers, 45 papers have been identified as describing some MCDM technique and correlation to automotive industry. We classified the most common MCDM technique and application in the automotive industry. Integrated approaches were more usual than individual ones. Application of fuzzy methods to tackle uncertainties in the data was also observed. Despite the maturity in the use of MCDM in several areas of knowledge, and intensive use in the automotive industry, none of them are directly linked to car design for energy efficiency. Analytic Hierarchy Process was identified as the common technique applied in the automotive industry.

Increased digitalization has influenced various business activities including companies’ business models (BMs) by enabling various new forms of cooperation between companies and leading to new product and service offerings as well as new forms of company relationships with customers and employees. At the same time, this digitalization has put pressure on companies to reflect on their current strategy and explore new business opportunities systematically and at early stages. While research on digitalization in the context of BMs is now gaining increased attention, a research gap still exists in this field since the number of empirical insights is limited. The paper aims to discuss these issues.

Qualitative empirical data collected from 12 key informants working in two distinctive industries, the media and automotive industries, were collected. An investigation was carried out to examine the differences and similarities among how digitalization influences a company’s value creation, proposition and capture, as well as how firms cope with challenges presented by increased digitalization.

The findings of the study show that, whilst digitalization is generally considered to be important, the value proposition itself as also the position in the value network determine the perceived available options for business model innovation (BMI) by digitalization. Moreover, the organizational capacities and employee competences were identified as future challenges that will be faced by both industries.

The findings of this study have revealed that representatives of the media and automotive industries perceive both the pressures and opportunities of digitalization regarding BMI; its application and exploitation, however, remain challenging. This study contributes to the existing body of knowledge by providing empirical insights in the context of digitalization and BMI.

This study is exploratory in nature and designed to address poorly documented issues in the literature. The dimensions of regional distribution or spatial organisation of Industry 4.0 (I4.0), including the potential role of clusters, have only recently been addressed, with most available studies focusing on advanced, mainly Western European countries. Although developing fast, the literature on I4.0 in other countries, such as the Central and Eastern European or post-transition economies like Poland, needs to pay more attention to the spatial distribution or geographical and organisational aspects. In response to the identified knowledge gap, this paper aims to identify the role of clusters in the transformation towards I4.0. This explains why clusters may matter for advancing the fourth digital transformation, how advanced in implementing I4.0 solutions are the residents of Polish clusters and how they perceive the advantages of cluster membership for such implementation. Finally, it seeks to formulate policy recommendations based on the evidence gathered.

The methodology used in this study combines quantitative analysis of secondary data from a cluster benchmarking survey with a case study approach. The benchmarking survey, conducted by the polish agency for enterprise development in 2021, gathered responses from 435 cluster members and 41 cluster managers, representing an estimated 57% of the current clusters in Poland. In addition to quantitative analysis, a case study approach was used, incorporating primary sources such as interview with cluster managers and surveys of cluster members, as well as secondary sources like company documents and information from cluster organisation websites. Statistical analysis involved assessing the relationship between technology implementation and the adoption of management systems, as well as exploring potential correlations between technology use and company characteristics such as revenue, export revenue share and number of employees using Pearson correlation coefficient.

In Poland, implementing I4.0 technologies by cluster companies is still modest. The cluster has influenced the use of I4.0 technologies in 23% of surveyed companies. Every second surveyed company declared a positive impact of a cluster on technological advancement. The use of I4.0 technologies is not correlated with the revenue of clustered companies. A rather bleak picture emerges from the results, revealing a need for more interest among cluster members in advancing I4.0 technologies. This may be due to a comfortable situation in which firms still enjoy alternative competitive advantages that do not force them to seek new advanced advantages brought about by I4.0. It also reflects the sober approach and awareness of associated high costs and necessary investments, which are paramount and prevent successful I4.0 implementation.

The limitations inherent in this study reflect the scarcity of the available data. This paper draws on the elementary survey administered centrally and is confined by the type of questions asked. The empirical section focuses on an important, though only one selected sector of the economy – the automotive industry. Nevertheless, the diagnosis of the Polish cluster’s role in advancing I4.0 should complement the existing literature.

The exploratory study concludes with policy recommendations and sets the stage for more detailed studies. Amidst the research’s limitations, this study pioneers a path for future comprehensive investigations, enabling a deeper understanding of Polish clusters’ maturity in I4.0 adoption. By comparing the authors’ analysis of the Polish Automotive Group (PGM) cluster with existing literature, the authors uncover a distinct disparity between the theoretical prominence of cluster catalysis and the current Polish reality. Future detailed dedicated enquiries will address these constraints and provide a more comprehensive map of Polish clusters’ I4.0 maturity.

This study identifies patterns of I4.0 implementation and diagnoses the role of clusters in the transformation towards I4.0. It investigates how advanced is the adoption of I4.0 solutions among the residents of Polish clusters and how they perceive the advantages of cluster membership for such transformation. Special attention was paid to the analysis of the automotive sector. Comparing the conclusions drawn from the analysis of the Polish PGM cluster in this case study to those from the literature on the subject, it becomes clear that the catalytic role of clusters in the implementation of I4.0 technologies by enterprises, as emphasised in the literature, is not yet fully reflected in the Polish reality.

This paper aims to study the automotive 4.0 context to understand the consumers’ propensity towards high-tech automated cars. The paper analyses the antecedents that lead to the use of innovative vehicles. Theory of planned behaviour (TPB) is adopted and extended by including further constructs, such as environmental aspects and inhibitors.

The advent of smart technologies and the internet of things has given rise to several contributions that look at consumers’ intention towards innovation adoption in the automotive industry. Furthermore, this study rises from the growing interest that sustainable mobility achieved. Based on the previous technology acceptance models and particularly TPB, this paper develops a structured questionnaire. After a pilot survey, the final questionnaire was administered online through email and social media in the Italian context. Structural equation modelling technique has been used for analysing data and testing the conceptual model.

The number of questionnaires filled out was 310, with a sample composed of young adults, characterised by different addiction levels towards technology. The results explain the drivers that lead to accept and adopt high-tech automated vehicles. This topic is still under investigation and offers potential research opportunities, considering the evolution of the market and the consumers’ habits and needs. Future research studies in this area should focus on generalising the present findings in other countries. Moreover, once this technology starts to be adopted, other constructs could be discovered, investigated and included in the model.

Mobility has raised a growing interest with the fast increasing demand for sustainability and growth of innovative solutions embedded in mobility. This research explores the TPB model’s application and the relation between its constructs, environmental aspects, inhibitors and intention to adopt automated vehicles. On this strength, it is possible to identify each construct’s relevance for obtaining social consensus on the market.