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The purpose of this paper is to explore the concept of data assets and how companies can assetize their data. Using the literature review methodology, the paper first summarizes the conceptual controversies over data assets in the existing literature. Subsequently, the paper defines the concept of data assets. Finally, keywords from the existing research literature are presented visually and a foundational framework for achieving data assetization is proposed.

This paper uses a systematic literature review approach to discuss the conceptual evolution and strategic imperatives of data assets. To establish a robust research methodology, this paper takes into account two main aspects. First, it conducts a comprehensive review of the existing literature on digital technology and data assets, which enables the derivation of an evolutionary path of data assets and the development of a clear and concise definition of the concept. Second, the paper uses Citespace, a widely used software for literature review, to examine the research framework of enterprise data assetization.

The paper offers pivotal insights into the realm of data assets. It highlights the changing perceptions of data assets with digital progression and addresses debates on data asset categorization, value attributes and ownership. The study introduces a definitive concept of data assets as electronically recorded data resources with real or potential value under legal parameters. Moreover, it delineates strategic imperatives for harnessing data assets, presenting a practical framework that charts the stages of “resource readiness, capacity building, and data application”, guiding businesses in optimizing their data throughout its lifecycle.

This paper comprehensively explores the issue of data assets, clarifying controversial concepts and categorizations and bridging gaps in the existing literature. The paper introduces a clear conceptualization of data assets, bridging the gap between academia and practice. In addition, the study proposes a strategic framework for data assetization. This study not only helps to promote a unified understanding among academics and professionals but also helps businesses to understand the process of data assetization.

In the past two decades, manufacturing has witnessed significant transformations alongside ecological challenges. Meanwhile, industrial 4.0 digital technologies have accelerated industrialisation with potentials of innovation in the context of circular economy. However, current concepts and models are fragmented and impractical. This paper aims to develop a holistic view integrating the three bodies of knowledge – industrialisation, ecologicalisation and digitalisation (IED) – in order to achieve sustainable development.

Critical literature review is conducted across three bodies of knowledge. Key themes are summarised with the identification of research gaps. A theoretical framework is synthesised and developed aiming to achieve synergy from IED with the modules, integration architecture, mechanism and dynamic paths.

First, the authors review and develop three conceptual models of ecologicalised industrialisation (IE3), industrial system digitalisation (D1) and digital technology industrialisation (D2) separately. Second, the authors propose a theoretical framework seeking to synthesise the above three conceptual models together to form the IED. Third, the authors design a process orientated abductive approach to improve and validate the IED framework.

This study contributes to the limited literature addressing the linkage of IED by integration different perspectives to develop theory in a novel way. Practically, it provides important tools for organisations to consider resource cascading in combination with digitalisation during the industrial system design.

Prior studies on product standardization–adaptation in multinational corporations (MNCs) have revealed environmental factors that can influence the choices of MNCs. However, these studies have not shown how these choices are made behind the scenes in new product development (NPD). In many industries, MNCs face the dual pressures for product standardization and adaptation from the environment. This study aims to explore how MNCs facing dual pressures can make choices of product standardization–adaptation in NPD.

A qualitative case study of four high-performing MNCs was conducted. The four MNCs were selected using the theoretical sampling approach. Data were collected, mainly through 74 semi-structured interviews. Coding was conducted and four aggregate dimensions were generated.

This study reveals that choices of product standardization–adaptation are made through a process in MNCs’ NPD, including four steps – organizing for NPD, organizational diversity, cross-unit integration and combination of design practices. In addition, MNCs adopt different process variants to address different environmental pressures.

This research focuses on high-performing MNCs in manufacturing industries. Future research can explore different types of firms.

Managers in MNCs should focus more on the process of choices for product standardization–adaptation, than on the level of product standardization–adaptation. They should also keep monitoring the environmental pressure and employ experienced engineers.

By focusing on NPD, the authors shift the attention from product standardization–adaptation to product feature standardization–adaptation in MNCs, which is a fresh and refined perspective. The authors show a process in NPD composed of activities and mechanisms that managers might use for handling product standardization–adaptation challenges in MNCs. The authors contribute to the area of cross-unit integration in MNCs’ NPD by revealing mental mechanisms for mitigating tensions in cross-unit interactions.

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.

As China emerges as a centre of manufacturing of the world, more and more small and medium sized enterprises (SMEs) start to outsource their production and related supply chain management in China. But it is very difficult to effectively manage the international outsourcing and supply chain mainly because their limited size and resources. International outsourcing agents emerge as a potential solution pursued by many western companies. Currently it has very limited information from both practical and theoretical aspects to understand the agents and their characteristics. This paper, based on four case studies of agents in three major industrial sectors in China, introduces business models and growth paths of the international manufacturing outsourcing agents, and establishes a set of key performance indicators (KPIs) for evaluation. The paper seeks to help western SMEs and hightech startups recognize the Chinese maturing and an ideal system for implementation, and to provide theoretical insights about the agents role and characteristics in international supply networks.

Despite the seminal works of authors like Bartlett, Ghoshal, Nohria, Doz, Williamson, among others, because they focused on mature multinationals, newcomers in international markets find scarce information about the design and implementation of international operations networks. In this paper we analyze the internationalization process of Brazilian and Chinese firms to understand the evolution of their networks, a process influenced by factors inexistent in studies about developed country multinationals, namely global production networks (GPNs) and country-of-origin effects. The key characteristics of their international operations networks seem to be well described by a stage-based approach where emerging country multinationals start as local optimizers and then evolve by taking different strategic positions within the GPN to which they are connected. That upgrading is possible when the implementation of the international operations network reaches a certain level of maturity.

Based on both the observations of case studies during the last few years and on action research work on the global manufacturing strategy development, this paper introduces another type of evolutionary process that looks at the internationalisation of manufacturing systems. The paper seeks to explore the new driving forces and responses of manufacturing systems in terms of their static architectures, dynamic mechanisms, and strategic capabilities in the evolutionary process. Reviews those internationalization models developed during the last 25 years, as well as reviewing manufacturing globalisation over the last 15 years, to gain a comprehensive picture about the international manufacturing system (IMS). Based on the empirical observations of industrial issues and the difficulties faced, a new research framework is proposed that will tackle the wider issues in international manufacturing, covering the manufacturing value creation process, internationalisation process, and inter‐firm collaboration formation process. Argues that it is important for future research to develop the strategy process to synthesise the three dimensions of the IMS.

This paper seeks to explore the interplay and interdependencies of factory and network capabilities. This issue has become progressively more important as companies seek to manage dispersed networks of plants capable of responding to increasingly competitive and volatile environments. The paper draws on field studies of two international manufacturing networks comprising eight factories in six countries. The research used a case‐based methodology that combined multiple interviews and ethnographic research at each location. Factory and network level capabilities were shown to simultaneously affect a suggested set of dimensions of operational performance and a matrix was proposed to visualise this interdependency. The case studies show that decisions regarding factory and network issues are often taken independently of each other despite the fact that they may be heavily interdependent. The cases also highlight the critical dimension of time in factory and network level capability building as well as the need for developing strategy processes that take into account the interdependency of factory and network capabilities.