Does value chain participation facilitate the adoption of Industry 4.0 technologies in developing countries?

Delera, Michele; Pietrobelli, Carlo; Calza, Elisa; Lavopa, Alejandro

doi:10.1016/j.worlddev.2021.105788

Cited by 48 publications

(35 citation statements)

References 91 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Entrepreneurs who have received formal education, especially tertiary education, are more likely to create innovative ventures (Michelacci & Schivardi, 2020). Thus, education in science, technology, engineering and mathematics (STEM) facilitates the adoption of deep technologies (Delera, Pietrobelli, Calza, & Lavopa, 2022) and, consequently, entrepreneurship (Colombo & Piva, 2020). The STEM education is not restricted to the tertiary level, some countries have overhauled secondary education systems by implementing STEM education models (Hiğde & Aktamış, 2022; Kutnick, Lee, Chan, & Chan, 2020).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Identifying necessary conditions to deep-tech entrepreneurship

Dionísio

Júnior

Morini

et al. 2023

RAUSP

View full text Add to dashboard Cite

Purpose This paper aims to address which resources provided by an entrepreneurial ecosystem (EE) are necessary for deep technology entrepreneurship. Design/methodology/approach The authors used a novel approach known as necessary condition analysis (NCA) to data on EEs and deep-tech startups from 132 countries, collected in a global innovation index and Crunchbase data sets. The NCA makes it possible to identify whether an EEs resource is a necessary condition that enables entrepreneurship. Findings Necessary conditions are related to political and business environment; education, research and development; general infrastructure; credit; trade; diversification and market size; and knowledge absorption capacity. Research limitations/implications The results show that business and political environments are the most necessary conditions to drive deep-tech entrepreneurship. Practical implications Policymakers could prioritize conditions that maximize entrepreneurial output levels rather than focusing on less necessary elements. Social implications Some resources require less performance than others. So, policymakers should consider allocating policy efforts to strengthen resources that maximize output levels. Originality/value Studies on deep-tech entrepreneurship are scarce. This study provides a bottleneck analysis that can guide the formulation of policies to support deep-tech entrepreneurship, as it allows to identify priority areas for resource allocation.

show abstract

Section: Theoretical Backgroundmentioning

confidence: 99%

Identifying necessary conditions to deep-tech entrepreneurship

Dionísio

Júnior

Morini

et al. 2023

RAUSP

View full text Add to dashboard Cite

show abstract

“…In addition, Delera et al (2022) find that the participation of manufacturing firms in developing nations (such as Vietnam) in global value chains serves as a key driver of digital technology adoption and has been found to be positively associated corporate‐level environmental performance. Although these factors (i.e., GDLO, digital transformation, GSCMP, and environmental performance) have relatively close effects and influence on one another (Benzidia et al, 2021; Kim et al, 2021), there is a lack of research integrating them into a single empirical model, such as the recommendation of Calantone et al (2002), to further elucidate the mediating mechanism in the relationship between learning orientation and firm performance, particularly in the context of manufacturing firms in developing nations.…”

Section: Introductionmentioning

confidence: 99%

Digital approach toward environmental sustainability in supply chains: Evidence from Vietnamese firms

Minh

Hoai

Van

et al. 2023

Sustainable Development

View full text Add to dashboard Cite

Despite substantial efforts to examine the factors driving green supply chain management practices and environmental performance in emerging markets, the roles of green digital learning orientation and digital transformation facilitating these practices are still not fully understood. Utilizing the resource‐based view strategy, we investigated how green digital learning orientation impacts environmental performance through green supply chain management practices, while also exploring the moderating effect of digital transformation in the green digital learning orientation and green supply chain management practices link. Our findings, based on data collected from 212 Vietnamese enterprises, indicate that green digital learning orientation has a positive impact on green supply chain management practices, which in turn leads to improved environmental performance. Additionally, the study reveals that digital transformation plays a significant moderating role in the relationship between green digital learning orientation and green supply chain management practices. These findings make a notable contribution to the existing digital transformation and sustainable supply chain literature. The study provides both theoretical and managerial implications, which are discussed in detail.

show abstract

Section: Introductionmentioning

confidence: 99%

“…At the present time, industry 4.0 technologies are the ultimate result of technical progress in information and communication technologies (ICTs) [ 2 ]. These technologies are able to make a more efficient use of resources and information, improving industry processes [ 3 ] and unlocking new opportunities in the development of new products [ 2 ]. In fact, industry 4.0 is built on technologies that allow communication environment, environmental identification, extensive data collection and custom instrument decisions [ 4 ], which are crucial in the optimization and maintenance of railway industry processes and infrastructure.…”

Section: Introductionmentioning

confidence: 99%

Industry 4.0 Technologies Applied to the Rail Transportation Industry: A Systematic Review

Laiton-Bonadiez

Bedoya

Zapata-Cortés

et al. 2022

Sensors

View full text Add to dashboard Cite

Background: Industry 4.0 technologies have been widely used in the railway industry, focusing mainly on maintenance and control tasks necessary in the railway infrastructure. Given the great potential that these technologies offer, the scientific community has come to use them in varied ways to solve a wide range of problems such as train failures, train station security, rail system control and communication in hard-to-reach areas, among others. For this reason, this paper aims to answer the following research questions: what are the main issues in the railway transport industry, what are the technologic strategies that are currently being used to solve these issues and what are the technologies from industry 4.0 that are used in the railway transport industry to solve the aforementioned issues? Methods: This study adopts a systematic literature review approach. We searched the Science Direct and Web of Science database inception from January 2017 to November 2021. Studies published in conferences or journals written in English or Spanish were included for initial process evaluation. The initial included papers were analyzed by authors and selected based on whether they helped answer the proposed research questions or not. Results: Of the recovered 515 articles, 109 were eligible, from which we could identify three main application domains in the railway industry: monitoring, decision and planification techniques, and communication and security. Regarding industry 4.0 technologies, we identified 9 different technologies applied in reviewed studies: Artificial Intelligence (AI), Internet of Things (IoT), Cloud Computing, Big Data, Cybersecurity, Modelling and Simulation, Smart Decision Support Systems (SDSS), Computer Vision and Virtual Reality (VR). This study is, to our knowledge, one of the first to show how industry 4.0 technologies are currently being used to tackle railway industry problems and current application trends in the scientific community, which is highly useful for the development of future studies and more advanced solutions. Funding: Colombian national organizations Minciencias and the Mining-Energy Planning Unit.

show abstract

Does value chain participation facilitate the adoption of Industry 4.0 technologies in developing countries?

Cited by 48 publications

References 91 publications

Identifying necessary conditions to deep-tech entrepreneurship

Identifying necessary conditions to deep-tech entrepreneurship

Digital approach toward environmental sustainability in supply chains: Evidence from Vietnamese firms

Industry 4.0 Technologies Applied to the Rail Transportation Industry: A Systematic Review

Contact Info

Product

Resources

About