Abstract

Abstract
Governmental investments on the development of high-tech clusters are among the main policies for socioeconomic development, enabling countries to be part of global value networks. Our objective is to identify which are the strategies of countries that want to join global aerospace value networks, by means of an abductive case research. Countries were divided in 3 groups (A; B; C) according to their global aerospace exports share. The analytical framework used to identify the strategies has 3 dimensions: network structure, network governance, and network dynamics. Results show different strategies according to the country's global exports share. While for countries in group A (exports above 1%), a strategy focused on the dimension network structure indicated a sustained high-tech sector. Countries in group C tend to focus on specialization, taking advantage of shifts in technological paradigms to upgrade their development level. The dimension network governance is mainly related to governmental efforts toward the creation of clusters and associations, promoting specialization and collaborative work. Finally, the dimension network dynamics describes the attraction of foreign companies to qualify the clusters at countries who belong to group C, while countries at group A reinforce their research and development activities. The comparison between countries is helpful for governmental representatives who want to develop strategies toward increasing participation in an industrial global value network and for supply chain managers to help selecting the locations for their operations. © 2019 Elsevier Ltd

Abstract
Previous literature shows that there are different environmental factors with different impacts on the adoption of technologies in a supply chain context. Thus, the adoption of technologies in supply chains may vary according to different environmental factors. Despite the existence of several studies about adoption of technologies in supply chain contexts that include environmental factors, there is a gap in identifying which environmental factors influence the adoption of digitalization technologies in supply chains. The purpose of this study is therefore to identify and analyze the environmental factors that influence the adoption of digitalization technologies in the supply chain. An exploratory qualitative research was conducted using semi-structured interviews with Portuguese managers of companies at several tiers of the automotive supply chain. Environmental factors were pointed as particularly critical drivers to promote the adoption of digitalization technologies in the automotive supply chain. Such adoption is mainly driven by the Original Equipment Manufacturer (OEM), through coercive and normative pressures over the other tiers of the supply chain. Relevant factors identified are: Compliance with standards and legislation, market and industry pressures, and benchmark the evolution of supply chain partners. This study contributes to the literature with new knowledge concerning new specificities of the environmental factors that showed an important influence on the adoption decision. © 2019 IEEE.

Abstract
The concept of industry 4.0 (i4.0) encompasses the integration of different technologies into an autonomous, knowledge- and sensor-based, self-regulating production system. Our objective is to synthesize which are the challenges and opportunities of adopting i4.0 from the perspective of technology provider companies. A single-case research was conducted with ten companies at the Portuguese Production Technologies Cluster. Based on i4.0 technologies – Augmented reality; Additive Manufacturing; Big Data; Cloud Computing; Cyber-Physical Systems; Cybersecurity; Smart Robotics; Simulation; and System Integration – interviewees mentioned that the main adoption challenges are the analysis of data generated, integration of new technologies with available equipment and workforce, and computational limitations. The main opportunities are improvements in: efficiency; flexibility; productivity; cybersecurity; quality of products and services; and decision process due to data analysis. Interviewees have also foreseen changes in company's business model through the integration of internal resources with complementary activities of their partners and other cluster companies. © 2019 Elsevier Inc.

Abstract