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The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

Qualitative research that involves the use of human participants calls for the need to protect those participants to give their honest view during data collection. This is an important part of every primary data collection in qualitative studies using interviews. This paper aims to investigate all available ethical considerations that need to be observed by the researcher when conducting primary data collection through interview and to explore the theories that underpin the ethics in qualitative studies.

This paper systemically reviewed existing qualitative data on ethics and gathered information that were analysed and presented on the topic area.

The findings show that ethical considerations deal with the various approaches adopted by the researcher to make the participants feel safe to participate in any given researcher. During an interview process in qualitative research, the findings show that anonymity, voluntary participation, privacy, confidentiality, option to opt out and avoiding misuse of findings are ethical considerations that must be observed by the researcher. The outcome of the investigation also shows that deontology and utilitarianism, rights and virtue are the main theories that underpin ethical considerations in research.

The rights of the research participants need to be respected in qualitative research to assist in gathering accurate information to achieve the objectives of study. This and other ethical principles such as anonymity, privacy, confidentiality, voluntary participation and option to opt out guide the researcher to systematically adhere to data collection approaches that yield valid results in qualitative data collection using interviews.

This study aims to investigate the preferences of 96 educational researchers on the use of digital technologies in scientific research.

The study was designed as a quantitative-dominant sequential explanatory mixed-method research.

Despite the spreading use of advanced technologies of big data and data mining, the most preferred digital technologies were found to be data analysis programs, databases and questionnaires. The primary reasons of using digital technology in scientific research were to collect data easily and quickly, to reduce research costs and to reach a higher number of participants.

The use of digital technologies in scientific research is considered a revolutionary action, which creates innovative opportunities. Through digitalized life, probably for the first time in history, the educational researchers have analytical information, which we can benefit from more than the individual's own statements in research involving human factor. However, there are a few studies that investigated the preferences of educational researchers who use digital technologies in their scientific research.

Information Systems research on emotions in relation to using technology largely holds essentialist assumptions about emotions, focuses on negative emotions and treats technology as a token or as a black box, which hinders an in-depth understanding of distinctions in the emotional experience of using artificial intelligence (AI) technology in context. This research focuses on understanding employees' emotional experiences of using an AI chatbot as a specific type of AI system that learns from how it is used and is conversational, displaying a social presence to users. The research questions how and why employees experience emotions when using an AI chatbot, and how these emotions impact its use.

An interpretive case study approach and an inductive analysis were adopted for this study. Data were collected through interviews, documents review and observation of use.

The study found that employee appraisals of chatbots were influenced by the form and functional design of the AI chatbot technology and its organisational and social context, resulting in a wider repertoire of appraisals and multiple emotions. In addition to positive and negative emotions, users experienced connection emotions. The findings show that the existence of multiple emotions can encourage continued use of an AI chatbot.

This research extends information systems literature on emotions by focusing on the lived experiences of employees in their actual use of an AI chatbot, while considering its characteristics and its organisational and social context. The findings inform the emerging literature on AI.

Empresa Brasileira de Pesquisa Agropecuária (Embrapa, the Brazilian Agricultural Research Corporation), owned by the Brazilian Government, is one of the most efficient agencies for promoting sustainable tropical agriculture in the world. However, although information is available, farmers do not always put the technologies and knowledge into practice. There is a large difference between the average productivity of farmers and crop or herd potential. Thus, this paper aims to describe and analyze the process of technology transfer of the Embrapa Agrobiology Unit.

The study reviewed the classical and diffusionist models of technology transfer (TT) in Brazilian agriculture and the role of the government in innovation. This was based on documentary research and structured interviews with four employees, supported by a structured roadmap composed of four categories for analysis: the role of TT; the organizational structure of the area; the TT strategies; and the ways of delivery, methods and tools of TT. By a qualitative approach, the results were treated through content analysis.

The results indicated that the area of TT at Embrapa went through a recent restructuring, which included the interchange and collective construction of knowledge (ICC) in its TT process, to turn entrepreneurship into reality. The company is dedicated to bringing knowledge to the most important people: farmers. This has been done through a participatory TT model, which has involved multiplier agents from the research stage to the transfer stage.

Some limitations were found, among them, the fact that only internal members of Embrapa were interviewed, limiting the view of the TTICC staff and without knowing the multiplier agents’ opinion and other actors involved in the process. In addition, it is a qualitative research that is subject to the interpretation of the researcher.

This study contributed to reflections about the TT process and how it can be used by different actors, along with the role of the State in innovation.

In addition to contributing to the development of products, processes and technologies for the economic, social and environmental development of Brazil, Embrapa has been outstanding in generating knowledge for the advancement of science. Its results have had impacts not only nationally but also worldwide. Embrapa has played a key role in Brazilian agriculture as well as in livestock, mainly, in supporting governmental projects and in the implementation of public policies.

The aim of this study was achieved, as there was a possibility of describing and analyzing the technology transfer process at Embrapa Agrobiology Unit, located in the city of Seropédica, Rio de Janeiro. It is concluded that Embrapa has been committed to involving the farmer in the process of interchange, collective construction of knowledge and technology transfer. The farmer has become the focus of this process, reducing the development of “shelf” researches and increasing the participation of the farmer or of the multiplier agent. The importance of studying and knowing the process of technology and knowledge transfer to the public of interest should be highlighted, and especially the reasons why this technology or knowledge are often not adopted by the public. It was possible to identify that Embrapa has noticed the difficulties of farmers and realized that the best way the best way of transforming technological solutions and knowledge into innovation is by involving the farmer in the process of construction and of transfer. Thus, the farmer gives greater credibility to the technology or generated knowledge because this is something that he himself helped build. In the sphere of contemporary institutional knowledge management, Embrapa has had as its main point of departure the demand and the needs of society. For this, it has created means to ensure the participation of different actors because they signal the construction of technological solutions and of innovation and they are the ones who know the real situation. However, this is a recent progress within Embrapa that has evolved and generated results. Thus, research, science and technology institutions must go beyond technology transfer and must ensure the involvement, participation and interaction of the public of interest to promote significant change, social, economic and environmental development and transformation. Embrapa observed this from the referential framework that included technology transfer, interchange and the collective construction of knowledge.

Three-dimensional (3D) printing (3DP) offers a promising value proposition across multiple manufacturing industries. Despite the variety of production benefits the technology entails, its rate of adoption is still low compared to industry forecasts. In face of this challenge, industry as well as academia requires more information and guidance. This review aims to examine the characteristics of the existing body of research on the organizational adoption of 3DP as well as its underlying theoretical concepts. The most common criteria driving adoption will be derived, such as to facilitate the managerial decision-making process. Pathways for future research will be presented.

This study underlies a bibliometric literature review and additionally applies content analysis to systematically investigate the existing body of research and group decision criteria along the four major pillars of strategic decision-making.

The contributions of this paper are threefold. First, the bibliometric analysis reveals interesting aspects of the existing body of research. The most prominent characteristics of the contemporary literature are reflected along descriptive indicators, such as industry, method, model, origin, research outlet or adoption drivers, thus granting relevant insights into academia and practice. Second, the most notable adoption models are carefully analyzed on their inherent attributes and their application fit for the context of organizational 3DP adoption. Findings, for instance, revealed the dominance of diffusion of innovation (DOI) across the existing body of research and divulge that this construct is generally applied in combination with user-centered decision frameworks to yield more precise results. Third, an ample range of opportunities for future research are detected and thoroughly explained. Among others, the authors identified a clear lack of information on the impact environmental variables and contingency factors exerted on the organizational adoption of 3DP. Guidance in relation to the sourcing of industry data, usage of adoption frameworks and avenues for future scientific projects is supplied.

This study represents the first semi-systematic literature review on the organizational adoption of 3DP. Thus, it not only offers a valuable evaluation guide for potential adopters but also determines a future research agenda.

This study aims to focus on a key unanswered question about how digitalization and the knowledge processes it enables affect firms’ strategies in the international arena.

The authors conduct a systematic literature review of relevant theoretical and empirical studies covering over 20 years of research (from 2000 to 2023) and including 73 journal papers.

This review allows us to highlight a relationship between firms’ international strategies and the knowledge processes enabled by applying digital technologies. Specifically, the authors discuss the characteristics of patterns of knowledge flows and knowledge processes (their origin, the type of knowledge they carry on and their directionality) as determinants for the emergence of diverse international strategies embraced by single firms or by populations of firms within ecosystems, networks, global value chains or alliances.

Despite digital technologies constituting important antecedents and critical factors for the internationalization process, and international businesses in general, and operating cross borders implies the enactment of highly knowledge-intensive processes, current literature still fails to provide a holistic picture of how firms strategically use what they know and seek out what they do not know in the international environment, using the affordances of digital technologies.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.