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This study aims to systematically map the state of work on human–machine collaboration in organizations using bibliometric analysis.

The authors used a systematic literature review to survey 111 articles on human–machine collaboration published in leading journals to categorize the theories used and to construct a framework of human–machine collaboration in organizations. A bibliometric analysis is applied to statistically evaluate the published materials and measure the influence of the publications using co-citation, coupling and keyword analyses.

The results inform that the research on human–machine collaboration in the organizational field is targeted at four aspects: performance, innovation, human resource management and information technology (IT).

This work is the first exploratory piece to assess the extent and depth of research on human–machine collaboration.

With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines.

We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected.

This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers’ skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies.

This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation.

This study aims to investigate the impact on organizational members of team marks and peer feedback in a classroom as an organizational setting, where equals were engaged in a hierarchical form of accountability. It uses Roberts’s framework of hierarchical, socializing, and intelligent forms of accountability and discusses the viability of intelligent accountability in higher education, given the accountability structure for academics.

Autoethnography based on excerpts from the lecturer’s diary.

The blurred boundaries of hierarchical and socializing forms of accountability create both tensions and kinships for students, and these two forms of accountability constantly impact on each other. Although the accounting tools have an individualizing effect on some students, several examples of intelligent accountability are uncovered. It is concluded that academia’s audit culture, which focuses on immediate outcomes, and academics’ ever-increasing workloads make successful innovations less likely.

This study contributes to the accountability literature in revealing a constant dynamic between hierarchical and socializing forms of accountability through examination of a unique setting in which the boundaries between the two are completely blurred. By empirically examining how accounting individualizes and how intelligent accountability emerges, this study contributes to the limited empirical literature on the impact of accountability on individuals, and particularly to studies of classrooms as organizations, with implications for education policies.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Hyperautomation is a technological concept whose popularity has been growing continuously since the German manufacturing industry “initiated” the Fourth Industrial Revolution (Industry 4.0), whereas, on the basis of theory, hyperautomation is a term still new and little recognized. This applies equally to scientific studies (articles, conference reports) and empirical studies (quantitative, qualitative). Therefore, this article attempts to fill definition gap that exists in the literature on management and quality sciences on the term hyperautomation.

The authors use literature review approach to identify the gaps in the existing literature on hyperautomation. They present a nominal definition of hyperautomation, discuss related issues and provide a comparative perspective between hyperautomation and automation.

The article’s findings include a precise definition of hyperautomation and the problems it raises. The authors point out that the term “hyperautomation” is still relatively new and underutilized in the management and quality sciences literature. It also compares hyperautomation to automation from several angles and emphasizes how it affects businesses, industries and other economic sectors.

Authors emphasize that in order to deploy hyperautomation successfully, enterprises must take a distributed and integrated approach.

This article addresses a gap in the management and quality sciences literature about the definition of hyperautomation. Authors give a thorough explanation of hyperautomation, along with relevant problems, useful implications and a comparison between hyperautomation versus automation.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

The purpose of this study is to explore the awareness, perception and attitude of consumers from Georgia toward smart, active and intelligent packaging of food products.

This study is based on a quantitative research method using a survey questionnaire tool to gather data from consumers in Georgia.

The scope of the sample is restricted to only one developing country. Yet, the research results are still significant in creating knowledge about innovative food packaging from different country contexts and to understanding the acceptance of intelligent active packaging by consumers.

Intelligent packaging facilitates companies with their sustainability efforts by reducing waste and environmental impact. It increases the desirability of products as responds to customer demands and leads to consumer satisfaction. Intelligent packaging can increase trust in bioproducts; for example, it is possible to track and check or monitor the origin of a product and prove that the product producer has really manufactured a bioproduct.

The study contributes to the discussion of the applicability and use of packaging with enhanced features in the food industry. In this respect, the performed pilot study fills the gap in the packaging literature by investigating consumers’ perspectives on intelligent packaging in Georgia – a non-EU, post-soviet, developing country.

Technological advancements are reshaping the tourism industry, necessitating the adaptation of business models through digital technology utilisation for intelligent, sustainable and inclusive tourism offerings. The diverse nature of tourism businesses, encompassing size, technology access, risk aversion, labour intensity, and more, presents a spectrum of challenges and opportunities for business model innovation (BMI) and digital transformation (DT) to maintain competitiveness. This study focuses on the core aspects of DT and BMI within the tourism sector, offering pivotal insights to aid tourism companies embarking on the intricate journey of DT and BMI in this evolving landscape.

The study conducts an extensive literature review to identify critical issues and pathways for tourism businesses pursuing DT and BMI. The review is focused on the challenges, opportunities, risks and imperatives that tourism organisations have to navigate in the current DT landscape to renew their business model.

The findings underscore the pressing need for tourism businesses to undergo a holistic DT. While digital technologies are reshaping the essence of tourism value chains, the transformation extends beyond technology adoption to encompass a profound renewal of organisational culture, competencies, structure, leadership and operational models. This paradigm shift is indispensable for crafting more innovative, sustainable and more inclusive tourism development. The paper also provides strategic recommendations and outlines future research directions to fortify the transformational journey of the tourism sector.

The paper provides key insights into supporting DT and BMI in tourism businesses, advancing a nuanced understanding of the multifaceted challenges and opportunities tourism organisations face in the digital age.

Given its ability to improve user interaction and labor productivity, ease human workloads and cut maintenance costs, public sectors are using AI-based robotic technology (AI-RT) at an accelerated rate. There is, however, little knowledge about the variables affecting citizens' participation when services backed by AI-RT are offered. In order to better understand the elements that influence AI-RT citizens' involvement and the moderating function of trusts in governmental organizations, this article draws on ideas from the Consumer Value Theory.

Out of 500 survey forms that were distributed to Indonesian people who had experience in using AI-RT devices in public service hall (e.g. airport’s Auto Gate), 367 returned the completed feedbacks. Data analysis used a step-by-step hierarchical moderated regression examination using SPSS 24 version.

Citizens’ involvement is positively correlated with esthetics and customization and adversely correlated with period expended using the AI-RT. Additionally, the findings imply that citizens who have greater levels of faith in governmental institutions are more likely to benefit favorably from the customization and esthetics of AI-RT.

The AI-RT must be capable of customizing the distribution of the appropriate materials to the appropriate individual at the appropriate moment, and public managers should guarantee that it is esthetically pleasing. Additionally, they ought to place a high priority on winning the trust of the populace in order to increase citizens’ involvement.

This paper was among the initial efforts that discover the determinants of citizens’ involvement in the AI-RT and the moderating effect of trusts in governmental organizations on the links between predictors and predicted variable, especially in an emerging country such as Indonesia.