Going digital multinationals: Navigating economic and social imperatives in a post-pandemic world

Industry 4.0 in international business research

The advent of Industry 4.0 promises to transform the global business landscape, the nature of markets and industries, and the way multinationals organize their operations as well as how and where they compete. These changes will have important - indeed profound - implications for IB scholarship. In this article, we explain Industry 4.0 and its distinguishing characteristics; discuss its organizational and strategic implications for multinationals; and outline the fundamental questions it raises for future IB research. To spur future analysis, we also present a conceptual foundation that articulates the new features, processes, and capabilities that support MNEs' pursuit of Industry 4.0-related opportunities surrounding digitalization, intelligence, technology, and innovation. We also discuss what Industry 4.0 means for IB research concerning social engagement, environmental sustainability, and international entrepreneurship. We elucidate how this new landscape shapes the extant IB literature and how future research can push it further along.

Global work in a rapidly changing world: Implications for MNEs and individuals

The COVID-19 pandemic has caused a great “reset” and has challenged many assumptions about work and life in general. Our focus in this paper is on the future of global work in the context of multinational enterprises (MNEs). We take a phenomenon-based approach to describe the important trends and challenges affecting the where, who, how and why of global work. As we highlight implications for organizations and individuals, we offer a set of research questions to guide future research and inform IHRM practitioners.

Does digitalization boost companies’ outward foreign direct investment?

The development of digital economy influences the digital transformation of companies while profoundly affecting the production efficiency, business model and overall strategy of firms, which has an important impact on business decisions, including foreign investment decisions. However, whether and how digitalization affects corporate OFDI has not been sufficiently empirically investigated. Taking Chinese listed companies in Shanghai and Shenzhen A-shares from 2009 to 2020 as samples, this paper constructs corporate digitalization indicators by using “text analysis method” and empirically tests the impact of digitalization on corporate OFDI and its path. The study finds that digitalization significantly promotes corporate OFDI. In terms of the influential mechanism, digitalization promotes corporate OFDI by improving total factor productivity and reducing financing constraints. In addition, external digital economy policies can provide favorable support for the digital transformation of firms. Meanwhile, the impact of digitalization on corporate OFDI is somewhat heterogeneous due to the different resource utilization efficiency and market environment. This study not only reveals the impact mechanism of digitalization on corporate OFDI, but also provides micro evidence for the deep integration of digital economy and real economy. Meanwhile, the findings have important implications for the formulation and implementation of digital policies.

Enhancing Digital Innovation for the Sustainable Transformation of Manufacturing Industry: A Pressure-State-Response System Framework to Perceptions of Digital Green Innovation and Its Performance for Green and Intelligent Manufacturing

Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables the green innovation of the manufacturing industry, was theoretically analyzed in this study. The measurement system of the digital green innovation (DGI) in the manufacturing industry was constructed according to the PSR framework. An evaluation model based on the analytic hierarchy process and the deviation maximization technique for order preference by similarity to an ideal solution method was constructed to measure the level of DGI. The results of this study from Chinese manufacturing are as follows. (i) The measurement system of the level of DGI in manufacturing industry includes a pressure system, state system and response system. (ii) In the past five years, the comprehensive index of the DGI in manufacturing industry has generally shown a trend of fluctuating rise. There are overall low and unbalanced phenomena in all regions. The gap decreased from 0.1320 to 0.1187, showing a gradually narrowing trend. (iii) Compared with other regions, the composite index of DGI is generally higher in the regions with a better ecological environment in the east and a more developed economy in the north. State parameters are higher than pressure and response parameters in most areas. (iv) Compared with other regions, the composite index of DGI in western and southern regions is lower, and the parameters of pressure, status and response are basically coordinated. (v) The application degree of digital technology, the emission intensity of waste water/exhaust gas of output value of one hundred million yuan and the expenditure intensity of digital technology adopted by enterprises are the key influencing factors of DGI in the manufacturing industry. This study not only proposed an evaluation index system of the digital green innovation level, but also puts forward policy guidance and practical guidance of digital technology to accelerate the green and intelligent manufacturing industry.

AIoT Used for COVID-19 Pandemic Prevention and Control

The pandemic of COVID-19 is continuing to wreak havoc in 2021, with at least 170 million victims around the world. Healthcare systems are overwhelmed by the large-scale virus infection. Luckily, Internet of Things (IoT) is one of the most effective paradigms in the intelligent world, in which the technology of artificial intelligence (AI), like cloud computing and big data analysis, is playing a vital role in preventing the spread of the pandemic of COVID-19. AI and 5G technologies are advancing by leaps and bounds, further strengthening the intelligence and connectivity of IoT applications, and conventional IoT has been gradually upgraded to be more powerful AI + IoT (AIoT). For example, in terms of remote screening and diagnosis of COVID-19 patients, AI technology based on machine learning and deep learning has recently upgraded medical equipment significantly and has reshaped the workflow with minimal contact with patients, so medical specialists can make clinical decisions more efficiently, providing the best protection not only to patients but also to specialists themselves. This paper reviews the latest progress made in combating COVID-19 with both IoT and AI and also provides comprehensive details on how to combat the pandemic of COVID-19 as well as the technologies that may be applied in the future.

Exogenous and endogenous change in global value chains

Zhan (J Int Business Policy 10.1057/s42214-020-00088-0, 2021) identifies five major forces that will drive the transformation of global value chains (GVCs) and redefine the global trade and investment landscape. The key to understanding GVCs is to recognize the MNEs that control them. A detailed knowledge of differing contexts is required to predict the outcomes of the dynamic processes identified in his paper, but this must be analyzed on a consistent and coherent theoretical basis. The key argument made in this paper is that the impact of these trends can be traced through exogenous changes that work through the internalization, location, and governance decisions of multinational enterprises (MNEs). MNEs also initiate some of these megatrends directly through the creation of new technologies and products and through their direct influence on civil society and policy at all levels of formulation and implementation. These decisions of MNEs interact and evolve together with pressure from civil society and government policy changes to give outcomes for GVCs that are predictable but will be determined by the context of global, national, and local circumstances.