In this article we analyze the case of TD-SCDMA system standardization in China. Specifically, we focus on the leading role that government-controlled enterprises (GCEs) played in the standardization, and how the Chinese government supported GCEs. The case study findings advance current knowledge on how governments support standardization efforts in a catching-up context. We found that, under strong government support and with GCEs’ leadership, a latecomer country such as China, with certain technological capabilities and in economic, social, and institutional contexts that favor indigenous innovation, can pursue path-breaking innovation with complex technological systems. Governments should engage in various tactics to support GCEs that lead the standardization process. Most importantly, governments should intervene in scoping decisions on technological systems and research and development forces in the standard development stage, and offer moral suasion in the standard diffusion stage. We provide practical implications for governments that support GCEs in technology catching-up.

This paper studies how large State-owned enterprises (SOEs) in China are approaching the technological innovation frontier and contributes to the literature on technological catching up and leapfrogging by identifying three models or strategies of approaching the innovation frontier. In addition to the well-recognised technology transfer based strategy, pursuing emerging technologies and reinventing mature technology could also be effective, with reinventing mature technology as the most important strategy. The paper also finds that strong internal R&D capability, rather than manufacturing capability as suggested by the extant literature, is the basis of all three models. This also implies that making big organisational transformations such as changing a technology transfer centred R&D function to a proprietary technology development centred R&D function, changing a manufacturing centred culture to an innovation centred culture, and reshaping the innovation network, is an important precondition to approach the innovation frontier.

Firms in emerging markets have traditionally followed one of two strategies to catch up with multinational enterprises (MNEs): developing customized products, services, or innovative business models or buying and absorbing technology from MNEs. In the era of globalization, these strategies are no longer effective. The new strategy to succeed is innovation-based differentiation, developing core technologies and advanced product offerings that are delivered at a low cost and with excellent customer service. Using this strategy, leading local firms are quickly catching up with MNEs in market development, technology development, or both.

With the advancement of digital technology and Industry 4.0, artificial intelligence (AI) is gradually embedded in human resource management and has become an important digital foundation to support the sustainable transformation of enterprises. However, the research in the manufacturing context, particularly through the challenge perspective at different levels, remains fragmented. This work represents a systematic review of 347 articles from Scopus and Web of Science from 2000 to 2025 and employs a dual-method analysis strategy embracing metrics and in-depth coding on 100 core publications. Excel, Bibliometrix, CiteSpace, Latent Dirichlet Allocation (LDA), and VOSviewer were utilized for quantitative analysis, while open–axial–selective coding of the Grounded theory approach was applied to generate qualitative results. The findings revealed six key challenges in integrating AI-HRM within manufacturing and six approaches to solve the identified issues. The Challenge–Approach Matching Matrix was constructed, illustrating the suitability of different pathways for addressing specific challenges. Analysis of thematic evolution in AI-HRM research resulted in the identification of three distinctive phases and demonstrated a consistent shift from technology-centric approaches towards human–machine collaboration. The primary contribution of this research lies in proposing a Multi-Level Embedded Framework providing a complex view of AI-HRM in a manufacturing sector at micro, meso, and macro levels. The absence of sustainable HR transformation through AI integration was identified as the critical challenge at the macro level. This research provides theoretical and practical implications for designing the sustainable HRM system based on ESG principles and favors the United Nations Sustainable Development Goals 9 and 12.

(2018). Reflections on “Effective Strategies to Catch Up in the Era of Globalization”. Research-Technology Management: Vol. 61, No. 3, pp. 16-18.