Factors influencing Industry 4.0 adoption

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sabai Khin ◽  
Daisy Mui Hung Kee
Keyword(s):  
Decision Making ◽  
Conceptual Model ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Content Type ◽  
Advantages And Disadvantages ◽  
Factors Influencing ◽  
Use Of Technology ◽  
Market Opportunities ◽  
The Right

PurposeThe digital transformation towards Industry 4.0 (I4.0) has become imperative for manufacturers, as it makes them more flexible, agile and responsive to customers. This study aims to identify the factors influencing the manufacturing firms’ decision to adopt I4.0 and develop a triadic conceptual model that explains this phenomenon.Design/methodology/approachThis study used a qualitative exploratory study design based on multiple case studies (n = 15) from the manufacturing industry in Malaysia by conducting face-to-face interviews. The data were analysed using NVivo. The conceptual model was developed based on grounded theory and deductive thematic analysis.FindingsResults demonstrate that driving, facilitating and impeding factors play influential roles in a firms’ decision-making to adopt I4.0. The major driving factors identified are expected benefits, market opportunities, labour problem, customer requirements, competition and quality image. Furthermore, resources, skills and support are identified as facilitating factors and getting the right people, lack of funding, lack of knowledge, technical challenges, training the operators and changing the mindset of operators to accept new digital technologies are identified as impeding factors.Research limitations/implicationsDue to its qualitative design and limited sample size, the findings of this study need to be supplemented by quantitative studies for enhanced generalizability of the proposed model.Practical implicationsKnowledge of the I4.0 decision factors identified would help manufacturers in their decision to invest in I4.0, as they can be applied to balancing advantages and disadvantages, understanding benefits, identifying required skills and support and which challenges to expect. For policymakers, our findings identify important aspects of the ecosystem in need of improvement and how manufacturers can be motivated to adopt I4.0.Originality/valueThis study lays the theoretical groundwork for an alternative approach for conceptualizing I4.0 adoption beyond UTAUT (Unified Theory of Acceptance and Use of Technology). Integrating positive and negative factors enriches the understanding of decision-making factors for I4.0 adoption.

scholarly journals Exploring the role of anticipated emotions in product adoption and usage

2018 ◽  
Vol 35 (3) ◽  
pp. 300-316 ◽  
Author(s):  
Debora Bettiga ◽  
Lucio Lamberti
Keyword(s):  
Decision Making ◽  
Conceptual Model ◽  
Structural Equation ◽  
Consumer Products ◽  
Product Adoption ◽  
Radical Product ◽  
Content Type ◽  
Product Decision ◽  
Anticipated Emotions

Purpose This study aims to explore the role of positive and negative anticipated emotions on adoption and continued usage of consumer products. The components of value eliciting anticipated emotions are investigated as well. Design/methodology/approach The conceptual model proposed is tested in two empirical studies, one focussing on functional and hedonic products and one on incremental and radical product innovations. Data are collected through online surveys on consumers and are analysed using structural equation modelling. Findings Results confirm the ability of anticipated emotions to influence product decision-making process. Moreover, anticipated emotions mediate the influence of value perceptions on product attitude. Findings show that these relationships vary greatly between initial adoption and further usage of the product. Practical implications Findings from this study may help marketers in the development of the right brand strategies and communication campaigns, aimed at building emotional connections with the consumer which prompt product adoption and usage. Originality/value Anticipated emotions, the predictions about the emotional consequences of a behaviour, have been acknowledged as strong drivers of consumer choices. Despite that, the role of anticipated emotions in product decision-making has not been explored yet. The present research, by means of a novel conceptual model, uncovers the role of anticipated emotions in both product adoption and continued usage decisions and depicts the components of value arousing such anticipated emotions.

Customers’ willingness of irresponsible industry 4.0 companies to co-create sustainable practices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manuela Escobar-Sierra ◽  
Alejandra García-Cardona ◽  
Fidel León-Darder
Keyword(s):  
Conceptual Model ◽  
Industry 4.0 ◽  
Structural Equation ◽  
Equation Modeling ◽  
Sustainable Practices ◽  
Content Type ◽  
Responsible Behavior ◽  
Technological Developments ◽  
Structural Equation Modeling Model ◽  
Method Approach

Purpose In this regard, this paper aims to wonder how willing to co-create sustainable practices customers of irresponsible Industry 4.0 (I4.0) companies are? With this purpose, the authors began introducing I4.0 and sustainability, showing their theoretical gaps. Design/methodology/approach I4.0 has recently spread with its technological developments and social, economic and political ambitions, facing challenges-related, for example, to the implementation of sustainable practices and the stakeholders’ participation. Findings Then the authors conduct a literature review following a sequential mix-method approach that begins with a bibliometric analysis and ends with a content study to propose a conceptual model for I4.0 and sustainability. Once the authors understood the theoretical gaps in the framework of the conceptual model, the authors conducted an empirical verification between clients of a Colombian company of the I4.0 belonging to the logistic sector, specifically of the deliveries, asking them about the labor issues that the company faces with delivery people and their willingness to co-create. The authors analyzed the collected data through a structural equation modeling model, where the authors found that customers’ willingness to co-create depends on intrinsic behaviors like “responsible behavior,” followed by extrinsic behaviors such as “helping.” Originality/value In fact, stakeholders may support companies, but customers must learn how to assume a critical posture during their purchase decision.

scholarly journals Prevention of cybercrimes in smart cities of India: from a citizen’s perspective

2019 ◽  
Vol 32 (5) ◽  
pp. 1153-1183 ◽  
Author(s):  
Sheshadri Chatterjee ◽  
Arpan Kumar Kar ◽  
Yogesh K. Dwivedi ◽  
Hatice Kizgin
Keyword(s):  
Conceptual Model ◽  
Structural Equation ◽  
Smart Cities ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Content Type ◽  
Actual Usage ◽  
Factors Influencing ◽  
Technology Adoption Model

PurposeThe purpose of this paper is to identify the factors influencing the citizens of India to prevent cybercrimes in the proposed Smart Cities of India.Design/methodology/approachA conceptual model has been developed for identifying factors preventing cybercrimes. The conceptual model was validated empirically with a sample size of 315 participants from India. Data were analyzed using structural equation modeling with SPSS and AMOS softwares.FindingsThe study reveals that the “awareness of cybercrimes” significantly influences the actual usage of technology to prevent cybercrimes in Smart Cities of India. The study reveals that government initiative (GI) and legal awareness are less influential in spreading of the awareness of cybercrimes (AOC) to the citizens of the proposed smart cities.Research limitations/implicationsThe conceptual model utilizes two constructs from the technology adoption model, namely, perceived usefulness and ease of use. The study employs other factors such as social media, word of mouth, GIs, legal awareness and organizations constituting entities spreading awareness from different related literature works. Thereby, a comprehensive theoretical conceptual model has been proposed which helps to identify the factors that may help in preventing cybercrimes.Practical implicationsThis study provides an insight to the policy maker to understand several factors influencing the AOC of the citizens of the proposed Smart Cities of India for the prevention of cybercrimes.Originality/valueThere are few existing studies analyzing the effect of AOC to mitigate cybercrimes. Thus, this study offers a novel contribution.

scholarly journals Customer experience management: asking the right questions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ian R. Hodgkinson ◽  
Thomas W. Jackson ◽  
Andrew A. West
Keyword(s):  
Decision Making ◽  
Business Models ◽  
Management Practices ◽  
Management Practice ◽  
Customer Experience ◽  
Content Type ◽  
Customer Data ◽  
Customer Experience Management ◽  
New Perspective ◽  
The Right

Purpose Customer experience is more critical than ever to firms’ successes and future growth opportunities. Typically measured through aggregate satisfaction scores, businesses have been criticized for oversimplifying what experience means. The purpose of this study is to provide a new perspective on experience management and offers a novel way forward for customer-centric strategizing. Design/methodology/approach Mapping the current digital technologies being used across businesses in all sectors to engage and connect with customers more effectively, this paper outlines some of the fundamental challenges of experience management and future opportunities to enhance business practice. Findings Businesses are capturing what they know about customers, rather than what a customer thinks and feels about the firm. Many experience management initiatives create customer pains (not gains), while for businesses, decision-making can be jeopardized by fake customer data. A framework based upon the five experience dimensions is presented for optimal customer-driven decision-making. Practical implications Going beyond aggregate satisfaction scores that serve as an output rather than an input into businesses strategizing, the paper presents an actionable framework for targeted investments and enhanced experience management practices. Originality/value Businesses are seeking to grow intelligent customer experience analysis capabilities to disrupt traditional business models toward greater customer-centricity and to track the digital spread of positive and negative experiences. Examining how this is being done and where the weaknesses lie by bridging management practice and the scientific literature, this paper provides new knowledge to advance customer-centric strategies for growth and profitability.

An agent-based simulation model for IING’s adoption from a perspective of kinetic energy and potential energy

Kybernetes ◽  
2018 ◽  
Vol 47 (3) ◽  
pp. 605-635 ◽  
Author(s):  
Li Wang ◽  
Qingpu Zhang
Keyword(s):  
Decision Making ◽  
Kinetic Energy ◽  
Potential Energy ◽  
Agent Based Simulation ◽  
Content Type ◽  
Agent Based ◽  
Factors Influencing ◽  
Social Physics ◽  
Physical Energy ◽  
Energy Theory

Purpose Internet-based intangible network good (IING) has revolutionized multiple industries in recent years. This paper aims to reveal the laws of consumer’s decision-making on IING from a perspective of kinetic energy and potential energy. Design/methodology/approach In this paper, 4 aspects and 17 factors influencing IING adoption were generalized. Based on the theory of social physics, an agent-based simulation model, introducing physical energy theory to depict consumer’s decision-making, was built. An agent’s kinetic energy reflects the agent’s perceived effect of mass media on the agent’s decision-making on IING adoption. An agent’s potential energy reflects the agent’s perceived effect of social interactions on the agent’s decision-making on the adoption of IING. An agent’s final energy is the sum of the kinetic energy and potential energy, which reflects the agent’s final decision. Findings Some factors mainly influence the diffusion velocity, while other factors have a dramatic impact on both diffusion velocity and diffusion scale. The agent’s personality can make a difference at the early and middle stages of IING adoption, but a faint impact at the later stage because of the effects of network externalities and word of mouth. There is a critical value of the number of initial adopters which can dramatically speed up IING adoption. Practical implications This study provides new insights for firms on the effects of factors influencing consumers’ decision-making on IING adoption. Originality/value This paper defines a new kind of innovation, IING, and generalizes IING’s special characteristics. As a new application of social physics, the physical energy theory has been creatively introduced to depict consumer’s decision-making on IING adoption. A kinetic and potential energy model of IING adoption has been built. Based on simulation experiments, new insights of IING adoption have been gained.

Industry 4.0 – organizing routines or innovations?

2018 ◽  
Vol 48 (2) ◽  
pp. 238-254 ◽  
Author(s):  
Maximiliane Wilkesmann ◽  
Uwe Wilkesmann
Keyword(s):  
Work Environment ◽  
Industry 4.0 ◽  
Transport Systems ◽  
Future Research ◽  
Successful Implementation ◽  
Content Type ◽  
Stage Of Development ◽  
The Future ◽  
Control Authority ◽  
The Right

Purpose The rise of new information and communication technologies forms the cornerstone for the future development of work. The term Industry 4.0 refers to the vision of a fourth industrial revolution that is based on a network of autonomous, self-controlling, self-configuring, knowledge-based, sensor-based and spatially distributed production resources. All in all, different forms of the application of the Industry 4.0 concept can be observed, ranging from autonomous logistic transport systems drawn upon the idea of swarm intelligence to smart knowledge management systems. This paper aims to develop a theoretical framework to analyze different applications of Industry 4.0 on an organizing continuum. The general research questions are: What forms of organizing digitalized work lead to the reproduction of routines, and what forms foster innovation within Industry 4.0? The authors thus analyze the consequences of different forms of organizing work on workers’ perceptions and the results of the working process. Design/methodology/approach This paper provides case studies for different stages of the organizing continuum in the context of Industry 4.0. The cases and a further analysis of all 295 funded projects are based on the Platform Industry 4.0 Map, which is part of the Industry 4.0 initiative of the German Federal Ministry of Economic Affairs and Energy and the German Federal Ministry of Education and Research. The consequences for people acting in such organizational and digitally supported structures are discussed. Findings A variety of applications of Industry 4.0 can be found. These applications mainly vary in the dimensions of the degree of formalization, the location of control authority, the location of knowledge and the degree of professionalization. At the right side of the organizing continuum, the digitalization organizes a work environment that supports highly qualified humans. They have broad leeway and a high degree of autonomy to design and create innovative forms of digitalization for tomorrow. At the left side of the organizing continuum, Industry 4.0 structures a work environment with narrow leeway, a low degree of autonomy and a top-down structure of control authority predetermined by digital applications. In this case, employees fill the gaps the machines cannot handle. Research limitations/implications As the paper focuses on Industry 4.0 developments in Germany, the comparability with regard to other countries is limited. Moreover, the methodological approach is explorative, and broader quantitative verification is required. Specifically, future research could include quantitative methods to investigate the employees’ perspective on Industry 4.0. A comparison of Industry 4.0 applications in different countries would be another interesting option for further research. Practical implications This paper shows that applications of Industry 4.0 are currently at a very early stage of development and momentarily organize more routines than innovations. From a practical point of view, professional vocational and academic training will be a key factor for the successful implementation of digitalization in future. A joint venture of industry and educational institutions could be a suitable way to meet the growing demand for qualified employees from the middle to the right-hand of the organizing continuum in the context of Industry 4.0. Social implications Industry 4.0 is designed by men, and therefore, humans are responsible for whether the future work situation will be perceived as supportive or as an alienated routine. Therefore, designers of Industry 4.0, as well as politicians and scientists, absolutely must take the underlying outcomes of digitalized work into account and must jointly find socially acceptable solutions. Originality/value This paper provides a promising avenue for future research on Industry 4.0 by analyzing the underlying organizational structures of digital systems and their consequences for employees. Moreover, the paper shows how Industry 4.0 should be organized to simply reproduce routines or to support innovation.

Artificial Intelligence Inroads Into HR

2022 ◽  
pp. 231-246
Author(s):  
Swati Bansal ◽  
Monica Agarwal ◽  
Deepak Bansal ◽  
Santhi Narayanan
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Human Resources ◽  
Generation Y ◽  
Industry 4.0 ◽  
Career Aspirations ◽  
Work Life ◽  
Human Decision ◽  
The Right ◽  
Talent Acquisition

Artificial intelligence is already here in all facets of work life. Its integration into human resources is a necessary process which has far-reaching benefits. It may have its challenges, but to survive in the current Industry 4.0 environment and prepare for the future Industry 5.0, organisations must penetrate AI into their HR systems. AI can benefit all the functions of HR, starting right from talent acquisition to onboarding and till off-boarding. The importance further increases, keeping in mind the needs and career aspirations of Generation Y and Z entering the workforce. Though employees have apprehensions of privacy and loss of jobs if implemented effectively, AI is the present and future. AI will not make people lose jobs; instead, it would require the HR people to upgrade their skills and spend their time in more strategic roles. In the end, it is the HR who will make the final decisions from the information that they get from the AI tools. A proper mix of human decision-making skills and AI would give organisations the right direction to move forward.

The future of manufacturing industry: a strategic roadmap toward Industry 4.0

2018 ◽  
Vol 29 (6) ◽  
pp. 910-936 ◽  
Author(s):  
Morteza Ghobakhloo
Keyword(s):  
Language Processing ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Core Competencies ◽  
Building Blocks ◽  
Design Principles ◽  
Ongoing Research ◽  
Holistic View ◽  
Content Type ◽  
Technology Trends

Purpose The purpose of this paper is to conduct a state-of-the-art review of the ongoing research on the Industry 4.0 phenomenon, highlight its key design principles and technology trends, identify its architectural design and offer a strategic roadmap that can serve manufacturers as a simple guide for the process of Industry 4.0 transition. Design/methodology/approach The study performs a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0. The study further benefits from a comprehensive content analysis of the 178 documents identified, both manually and via IBM Watson’s natural language processing for advanced text analysis. Findings Industry 4.0 is an integrative system of value creation that is comprised of 12 design principles and 14 technology trends. Industry 4.0 is no longer a hype and manufacturers need to get on board sooner rather than later. Research limitations/implications The strategic roadmap presented in this study can serve academicians and practitioners as a stepping stone for development of a detailed strategic roadmap for successful transition from traditional manufacturing into the Industry 4.0. However, there is no one-size-fits-all strategy that suits all businesses or industries, meaning that the Industry 4.0 roadmap for each company is idiosyncratic, and should be devised based on company’s core competencies, motivations, capabilities, intent, goals, priorities and budgets. Practical implications The first step for transitioning into the Industry 4.0 is the development of a comprehensive strategic roadmap that carefully identifies and plans every single step a manufacturing company needs to take, as well as the timeline, and the costs and benefits associated with each step. The strategic roadmap presented in this study can offer as a holistic view of common steps that manufacturers need to undertake in their transition toward the Industry 4.0. Originality/value The study is among the first to identify, cluster and describe design principles and technology trends that are building blocks of the Industry 4.0. The strategic roadmap for Industry 4.0 transition presented in this study is expected to assist contemporary manufacturers to understand what implementing the Industry 4.0 really requires of them and what challenges they might face during the transition process.

Artificial intelligence: HR friend or foe?

2019 ◽  
Vol 18 (2) ◽  
pp. 47-51
Author(s):  
Peter Hogg
Keyword(s):  
Artificial Intelligence ◽  
Well Being ◽  
Business Leaders ◽  
Business Decision ◽  
Content Type ◽  
Use Of Technology ◽  
Challenges And Opportunities ◽  
The Uk ◽  
The Right ◽  
Productivity Dilemma

Purpose While the use of artificial intelligence (AI) in the workplace is on the rise, few understand how it will affect our jobs. Will it be a hindrance? A threat? Or the solution to the current productivity dilemma? As with any new, and largely untested, technology, AI brings both challenges and opportunities that we need to be conscious of. Design/methodology/approach The current and potential future implementation of AI technologies at Schneider Electric is assessed. Findings In HR, it is our responsibility to help navigate business leaders towards making the best business decision, often with the use of technology. AI, like analytics before it, has huge potential. Originality/value What we know for sure, is that the development of human talent has become one of the top priorities for global CEOs. With severe talent shortages in the UK, finding the right candidates for the job and investing in their professional development and well-being to keep them for longer look like no-brainers.

Identification and prioritization of factors influencing organization risk tolerance level

2019 ◽  
Vol 16 (4) ◽  
pp. 417-435
Author(s):  
Mohammad Khalilzadeh ◽  
Shiba Masoumi ◽  
Isa Masoumi
Keyword(s):  
Decision Making ◽  
Risk Tolerance ◽  
Project Manager ◽  
Validity And Reliability ◽  
Statistical Population ◽  
Content Type ◽  
Tolerance Level ◽  
Factors Influencing ◽  
Critical Issues ◽  
Decision Making Model

Purpose Identifying and prioritizing the risks are considered as critical issues in risk management; otherwise, non-considering the risks will lead to the problems such as delays in project implementation, increased costs, loss of reputation, loss of clients, reduced revenue and liquidity and even bankruptcy. The paper aims to discuss these issues. Design/methodology/approach In this paper, the factors influencing the organization risk tolerance level were identified. Then, the factors increasing and decreasing the risk tolerance level were determined by a decision-making model. Finally, a comprehensive model was considered for risk measuring and preparing a risk failure structure chart, in order to determine the factors influencing it as well as the measurement criteria and then they were ranked using the taxonomy method. In this study, the size of the statistical population was 130 (six small and medium manufacturer and service provider companies). Based on Cochran’s sample size formula, 97 questionnaires containing 30 questions were randomly distributed among the population. Validity and reliability of the questionnaire were confirmed. The data were analyzed by SPSS 22. Findings Given the hypotheses of this study, the first hypothesis was rejected and the other hypotheses were accepted. The final ranking was done using the taxonomy method; the personality of the project manager was ranked at first; income, credit and capital were ranked second and the number of personnel was ranked third. Moreover, the TOPSIS method was used for ranking to compare the results. Originality/value In this research, the identification and ranking of these factors have taken place in several small- and medium-sized organizations; in addition, the rankings are conducted using the taxonomy decision-making method.

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