Adoption of AI-empowered industrial robots in auto component manufacturing companies

The usage of AI-empowered Industrial Robots (InRos) is booming in the Auto Component Manufacturing Companies (ACMCs) across the globe. Based on a model leveraging the Technology, Organisation, and Environment (TOE) framework, this work examines the adoption of InRos in ACMCs in the context of an emerging economy. This research scrutinises the adoption intention and potential use of InRos in ACMCs through a survey of 460 senior managers and owners of ACMCs in India. The findings indicate that perceived compatibility, external pressure, perceived benefits and support from vendors are critical predictors of InRos adoption intention. Interestingly, the study also reveals that IT infrastructure and government support do not influence InRos adoption intention. Furthermore, the analysis suggests that perceived cost issues negatively moderate the relationship between the adoption intention and potential use of InRos in ACMCs. This study offers a theoretical contribution as it deploys the traditional TOE framework and discovers counter-intuitively that IT resources are not a major driver of technology adoption: as such, it suggests that a more comprehensive framework than the traditional RBV should be adopted. The work provides managerial recommendations for managers, shedding light on the antecedents of adoption intention and potential use of InRos at ACMCs in a country where the adoption of InRos is in a nascent stage

The impact of Industry 4.0 implementation on supply chains

Purpose The study aims to analyse the impact of Industry 4.0 implementation on supply chains and develop an implementation framework by considering potential drivers and barriers for the Industry 4.0 paradigm. Design/methodology/approach A critical literature review is performed to explore the key drivers and barriers for Industry 4.0 implementation under four business dimensions: strategic, organisational, technological and legal and ethical. A system dynamics model is later developed to understand the impact of Industry 4.0 implementation on supply chain parameters, by including both the identified driving forces and barriers for this technological transformation. The results of the simulation model are utilised to develop a conceptual model for a successful implementation and acceleration of Industry 4.0 in supply chains. Findings Industry 4.0 is predicted to bring new challenges and opportunities for future supply chains. The study discussed several implementation challenges and proposed a framework for an effective adaption and transition of the Industry 4.0 concept into supply chains. Research limitations/implications The results of the simulation model are utilised to develop a conceptual model for a successful implementation and acceleration of Industry 4.0 in supply chains. Practical implications The study is expected to benefit supply chain managers in understanding the challenges for implementing Industry 4.0 in their network. Originality/value Simulation analysis provides examination of Industry 4.0 adoption in terms of its impact on supply chain performance and allows incorporation of both the drivers and barriers of this technological transformation into the analysis. Besides providing an empirical basis for this relationship, a new conceptual framework is proposed for Industry 4.0 implementation in supply chains

A new perspective to evaluate the antecedent path of adoption of digital technologies in major projects of construction industry: A case study in China

The adoption of digital technologies is key to the digital transformation of the construction industry. However, the current adoption of digital technologies is limited. This study uses China as a case, combines the DOI and TOE theories to identify impact factors of the adoption of digital technologies in major projects. The configuration analysis is complemented with fuzzy-set qualitative comparative analysis. As a result, the study constructs the “TOE-D Technology Adoption Antecedent Framework”, including 11 antecedents, and identifies three distinct configurations types, namely: “Needs-Resource-Collaboration”; “Resource” under high competitive pressure; and “Resource” under low competitive pressure. Comparing the configurations horizontally, the core or edge characteristics of factor in configurations are analyzed. The results can help major projects in the construction industry to ascertain a combination of elements, which promote the adoption of digital technologies so that project practitioners can make targeted and precise adjustments to enable digital transformation of the construction industry

Success Factors Impacting Artificial Intelligence Adoption --- Perspective From the Telecom Industry in China

As the core driving force of the new round of informatization development and the industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied, and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, the main study of this paper proposes a framework to explore the effects of success factors on AI adoption by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. Particularly, this framework consists of factors regarding the external environment, organizational capabilities, and innovation attributes of AI. The framework is empirically tested with data collected by surveying telecom companies in China. Structural equation modeling is applied to analyze the data. The results indicate that compatibility, relative advantage, complexity, managerial support, government involvement, and vendor partnership are significantly related to AI adoption. Managerial capability impacts other organizational capabilities and innovation attributes of AI, but it is indirectly related to AI adoption. Market uncertainty and competitive pressure are not significantly related to AI adoption, but all the external environment factors positively influence managerial capability. The study provides support for firms\u27 decision-making and resource allocation regarding AI adoption. In addition, based on the resource-based view (RBV), this article conducts study 2 which explores the factors that influence the firm sustainable growth. Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from telecom companies in China. The results indicate that at the firm level, the customer value and operational expenses are significantly related to sustainable growth. Also, at the industry level, industry investment significant impacts sustainable growth. Study 2 provides insights for practitioners the way to keep sustainable growth

A journey towards Industry 4.0 : the supporting role of socio-technical systems

Companies seek to improve their competitiveness and productivity through innovation in processes, products, and equipment. This innovation can be achieved via technologies that bring greater quality, flexibility, efficiency, control, and monitoring to their production. In this sense, the concept of a more intelligent, automated, and digital industry gained interest and culminated in Industry 4.0. Many companies view this industry evolution as capable of delivering immediate improvements and lowering production costs. However, only crediting the technology with gains in productivity, quality, and flexibility has brought frustrations, complexity, and reduced production in company processes. This is due to, among other things, the way Industry 4.0 technologies are understood, implemented, communicated, and used. Literature and empirical studies have shown that companies still lack the technological, cultural, and process maturity necessaries to obtain substantial gains with Industry 4.0, especially small and medium-sized companies. Focusing on this technology implementation process, this thesis aims to investigate how the socio-technical theory can bring improvements and gains in relation to the environment in which technologies such as IoT, big data, analytics, collaborative robots, and 3D printing are implemented. For that, this thesis aims to identify how the socio-technical aspects impact the implementation of Industry 4.0 and its contribution to improving the results with its implementation. The results demonstrate that socio-technical aspects are associated with higher levels of Industry 4.0 implementation as they serve as the basis for technologies to operate in a more organized environment, with workers trained and engaged in their use and with a clear and delimited strategy. Strategic aspects are the most impacting aspects of Industry 4.0 implementation and should be considered fundamental for companies adopting its technologies. The qualitative results highlight such importance and demonstrate how companies have made such a transition both through Industry 4.0 ecosystems, as well as seeking capabilities and knowledge through suppliers, consultancies, associations, and startups. Still, the results showed the importance of collecting, storing, and having the ability to use data for continuous improvement. Well-established lean maturity and the definition of a strategic and technological roadmap that guides the technology implementation process were also essential for the company to focus on a broader context of technologies to the detriment of ad-hoc implementations. Finally, the results also showed that although aspects of strategic definition bring important gains for implementing Industry 4.0, improvements related to workers, such as engagement, qualification, and training, can also bring productivity improvements. In this way, this thesis brings theoretical and empirical gains to a field of growing interest for the industry that demands high investments, impacting not only workers but various organizational, social, and technical aspects of the company. The results discussed here provide empirical evidence of the importance of a socio-technical vision based on more organized processes, a well-defined strategy, and trained, engaged, and participative workers in the transition to Industry 4.0, in contrast to the technocentric vision generally adopted by companies.Empresas buscam melhorar sua competitividade e produtividade através de inovações em processos, produtos e equipamentos. Tais inovações podem ser feitas através de tecnologias que tragam maior qualidade, flexibilidade, eficiência, controle e monitoramento a sua produção. Nesse sentido, o conceito de uma indústria mais inteligente, automatizada e digital ganhou força e culminou no que se denomina de Indústria 4.0. Muitas empresas visualizam essa evolução da indústria como capaz de entregar melhorias imediatas e diminuir custos de produção. No entanto, creditar somente à tecnologia ganhos de produtividade, qualidade e flexibilidade tem trazido frustrações, diminuição na produção e complexidade aos processos das empresas. Isso se deve, entre outras coisas, à forma como as tecnologias da Indústria 4.0 são entendidas, implementadas, comunicadas e usadas. Estudos empíricos têm demonstrado que as empresas ainda não possuem maturidade tecnológica, cultural e de processos para obter ganhos substanciais com a Indústria 4.0. Com foco nesse processo de implementação de tecnologia, esta tese visa estudar como a abordagem sistêmica e holística proposta pela teoria socio-técnica pode trazer melhorias e ganhos em relação ao ambiente em que as tecnologias como IoT, big data, analytics, robôs colaborativos e impressão 3D são implementadas. Para isso, essa tese tem como objetivo geral identificar como os aspectos socio-técnicos impactam a implementação da Indústria 4.0 e sua contribuição para melhorar os resultados com a sua implementação. Os resultados demonstram que os aspectos socio-técnicos estão associados a níveis mais altos de Indústria 4.0 uma vez que servem de base para que as tecnologias possam operar em um ambiente preparado, com trabalhadores treinados e engajados em seu uso e com uma estratégia clara e delimitada. Os aspectos estratégicos são os que mais impactam no nível de adoção de Indústria 4.0 e são fundamentais para a adoção das tecnologias. Os resultados qualitativos ressaltam tal necessidade e demonstram como as empresas têm feito tal transição tanto através de treinamentos, parcerias com startups e organizações governamentais, assim como buscando capabilidades e conhecimento através de fornecedores, universidades e consultorias. Ainda, os resultados evidenciaram a importância de coletar, armazenaram e possuir capacidade de utilizar dados para melhorias contínuas. Maturidade lean bem estabelecida e a definição de um roadmap estratégico e tecnológico que guie o processo de implementação das tecnologias também foi demonstrado como essencial para que a empresa foque num contexto mais amplo de tecnologias em detrimento de implementações pontuais e usos ad hoc. Finalmente, os resultados também demonstraram que apesar de aspectos de definição estratégica trazerem ganhos importantes para a implementação de Indústria 4.0, melhorias relacionadas a trabalhadores, como engajamento, qualificação e treinamento também são capazes de trazer melhorias na produtividade. Dessa forma, essa tese traz ganhos teóricos para um campo crescente e de interesse da indústria e que demandam investimentos altos, impactando não somente os trabalhadores, mas diversos aspectos organizacionais, sociais e técnicos da empresa. Os resultados discutidos aqui trazem evidências empíricas da importância de uma visão socio-técnica pautada em processos mais organizados, estratégia bem definida e trabalhadores treinados, engajados e participativos na transição para a Indústria 4.0 em contraste a visão tecnocentrista geralmente adotada pelas empresas

The contribution of industry 4.0 technologies to increase internal and external operational flexibility of production systems

Manufacturing flexibility is recognized as an essential competitive factor in the company's operational strategy as a response to market uncertainties and turbulence. Industry 4.0 emerges as a new industrial paradigm that allows meeting these types of needs of manufacturing companies, focusing on the creation of an intelligent system along the entire value chain that allows the achievement of flexible and adaptive processes. However, the academic literature has not yet presented empirical evidence on how each specific Industry 4.0 technology can contribute to operational flexibility requirements. Although Industry 4.0 is treated as a solution to this need, it is known that there are different types of implementations of Industry 4.0 depending on the operational objectives pursued and the characteristics of the companies. Therefore, the technological sets of Industry 4.0 can have different forms of contribution to achieve greater flexibility in production processes. The aim of this thesis is to create a framework to help companies implement flexible operations in the context of Industry 4.0. The study followed a mixed approach, combining qualitative and quantitative methods. In quantitative terms, the thesis presents two survey research. The first was conducted with 94 companies in the machinery and equipment sector, through which the effect that different operational objectives – including flexibility – have on the definition of technological arrangements in Industry 4.0, is analyzed. The second was conducted with 379 companies, with the objective of analyzing how the smart supply chain concept contributes to the flexibility of the supply chain, especially in the context of uncertainties.. On the other hand, in qualitative terms, the thesis presents a multi-case study in 11 leading manufacturing companies in the implementation of 4.0 technologies, aiming to understand how these technologies are implemented to achieve different operational flexibility requirements. The present thesis demonstrates that, in fact, 4.0 technologies contribute to operational flexibility, but also explores the limitations and nuances of these contributions in different situations. The main contribution of this study is to provide empirical evidence of the effectiveness of different technologies used in a combined way to increase operational flexibility at its different levels.A flexibilidade da manufatura é reconhecida como um fator competitivo essencial na estratégia operacional das empresas, como resposta a necessidades do mercado, especialmente diante de incertezas e turbulências. A Industria 4.0 surge como um novo paradigma industrial que permite atender esse tipo de necessidades das empresas manufatureiras, sendo seu foco a criação de um sistema inteligente ao longo de toda a cadeia de valor que possibilita a obtenção de processos flexíveis e adaptativos. Contudo, a literatura acadêmica ainda não tem apresentado evidências empíricas sobre a forma como cada tecnologia específica da Indústria 4.0 pode contribuir para os requisitos de flexibilidade operacional. Embora Industria 4.0 seja apresentada como uma solução para essa necessidade, é sabido que existem diferentes tipos de implementação da Indústria 4.0 que dependem dos objetivos operacionais almejados e das características das empresas. Portanto, os conjuntos tecnológicos da Indústria 4.0 podem ter diferentes formas de contribuição para alcançar uma maior flexibilidade dos processos de produção. O objetivo desta tese é criar um framework para auxiliar as empresas na implementação de operações flexíveis no contexto da Indústria 4.0. O estudo seguiu uma abordagem mista, combinando métodos qualitativos e quantitativo. Em termos quantitativos, a tese apresenta duas pesquisas survey. A primeira foi conduzida com 94 empresas do setor de máquinas e equipamentos, através da qual se analisa o efeito que diferentes objetivos operacionais dentre eles a flexibilidade possuem sobre a definição de arranjos tecnológicos da Indústria 4.0. A segunda foi conduzida com 379 empresas, com objetivo de analisar como o conceito de smart supply chain contribui para a flexibilidade da cadeia de suprimento, principalmente no contexto de incertezas. Por outro lado, em termos qualitativos, a tese apresenta um estudo multicasos em 11 empresas de manufatura líderes na implantação de tecnologias 4.0, visando entender a forma como essas tecnologias são implementadas para alcançar diferentes requisitos de flexibilidade operacional. A presente tese demonstra que, de fato, as tecnologias 4.0 contribuem para a flexibilidade operacional, mas também explora as limitações e nuances dessas contribuições em diferentes situações. A principal contribuição deste estudo é fornecer evidências empíricas da efetividade de diferentes tecnologias utilizadas de forma combinada para incrementar a flexibilidade operacional nos seus diferentes níveis

Knowledge exchange as a predictor of business innovation among SMEs in Ogun State, Nigeria.

Purpose: Business innovation is the improvement made on the array of products and services of a firm. Thus, this study investigates the influence of knowledge exchange on business innovations among SMEs in Ogun State, Nigeria. Design / Methodology: The study adopted survey research design. The population of the study comprised 415 staff employed by 55 SMEs in the state. A sample size of 204 was determined with the aid of Taro Yamane determinator. A proportionate sampling technique was used to select respondents through the structured and validated questionnaire that was designed for data collection. Cronbach’s alpha reliability coefficients for the variables ranged from 0.70 to 0.88, while a return rate of 100% was achieved. Data were analysed with descriptive and inferential (simple linear and multiple regression) statistics. Findings: Findings revealed that knowledge exchange had a positive significant influence on business innovation of SMEs in Ogun State. Nigeria The result further indicated that all the measures of knowledge exchange were significant. Based on the findings, this study recommends that SMEs should make more provision for collaboration, improved communication, training and encouragement of staff so as to improve their current achievements in business innovations. Originality / Value: The study has been able to fill some gaps noticed in the literature and also provided empirical justification on the influence of knowledge exchange on business innovation. It has also help to generate new knowledge needed for policy and decision-making relating to accessing innovativeness in SMEs

Industry 4.0 for SMEs

This open access book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies