Search results

The paper aims to enrich current debate about human–technology dichotomy in socio-economic settings by decoding and systematizing the main phases through which it has been approached in managerial and social studies.

A multi-interpretative framework is built thanks to the adoption of a qualitative approach inspired by the inductive logic, and for analyzing the historical evolution of the approach to human–technology dichotomy and for explaining them through an innovative conceptual model.

An innovative conceptual model is proposed for depicting connections and evolutions among the main four phases in the evolution of the approaches to human–technology dichotomy.

Reflections and conceptual model herein can support researchers in rereading the multiple theoretical and practical contributions provided with reference to human and technology relations in socio-economic settings.

The paper can support managers and entrepreneurs in defining and evaluating managerial approaches for efficiently enhancing human–technology interaction.

The paper proposes an innovative conceptual model based on a multi-interpretative framework for decoding the historical evolution of the approaches to human–technology dichotomy in business settings. New variables are added to the current debate about the topic for building an original interpretive viewpoint.

The purpose of this conceptual paper is to demonstrate how memes perpetuate trauma with a schematic. This conceptual paper uses the “begin with the end in mind” meme to format the presentation of the necessary components for the schematic of how trauma persists across generations. It is the third paper in a series of applications of the recursive, test-operate-test schematic to the systemic effects of the information processes involved in trauma. The schematic presented permits evaluations of solutions to interrupt the generational trauma cycle.

The required schematic components are described. Trauma (actual or perceived threat to survival) will be briefly discussed. Evolutionary processes that create the psychophysiology necessary to support nominal social expectations (NSEs) memes and metaphors will be summarized. The development of NSEs will be discussed. Metaphors and memes necessary for the creation of the schematic and esoteric events at level Learning IV will be briefly described. Finally, Figure 3, which illustrates the maintenance of NSEs and attempts to prevent their violation, will be explained.

It is asserted that functional human social behavior requires NSEs. Trauma is found to persist through the presence of anti-nominal NSE memes that are transduced by the individual into anti-nominal metaphors, which then damage grid, place and dentate gyrus cell (GPDG) neurophysiology. The damaged neurocircuits allow the use of anti-nominal NSE metaphors within our individual neurophysiology. Furthermore, anti-NSE memes interfere with the self-organized criticalities (SOCs) of genetic-epigenetic processes necessary for the intergenerational transfer of functional social behavior. When anti-NSE nominal metaphors are transduced back into anti-NSEs, social niche memes, the trauma process is reiterated. Anti-NSE memes and metaphors are found to be inappropriate criteria central to the maintenance of persistent trauma. Therefore, anti-NSE memes have hijacked our epigenetics and our social niches. Solutions are available because during our evolution, the Homo clade developed esoteric capabilities and the ability to bring back what information we can from those encounters. This physiology operates around the 5HT2A neural receptors that process hallucinogens, such as psilocybin. Accessing this resource system, either through naturally occurring altered states of consciousness or through micro-dose pharmaceutical psilocybin and related neurotransmitters, produces a significant structural change in the GPDG system to reset the NSE system illustrated in the schematic to its nominal status so that we can maintain nominal NSE relationships within our meme niche(s).

The source of persistent trauma in our social niche(s), the means by which the trauma is maintained and the means to mitigate and perhaps eliminate persistent trauma are identified. Based on these three conclusions, it is difficult to make decisions regarding corrective actions because of ubiquitous anti-NSE memes and because of the limitations of our ordinary consciousness.

If we wish to survive as a species, we will need to discover the criteria necessary to maintain our niche(s) congruent SOCs and use them instead of tyrannical memes described by Dawkins (1989) to make decisions about ourselves and our niche(s).

Significant courage is required to identify the memes that maintain trauma because many of them are culturally sacred cows. Unfortunately, we have known since Bremner's (1995) MRI study of posttraumatic stress disorder that trauma causes brain damage. Fortunately, our NSE genes compel us to pursue restitution of the memes that maintain our trauma-inducing cultures.

Several original assertions are presented. While the Homo clade ancestors began the creation of the social niche(s) that led to Homo sapiens sapiens, it is asserted that the australopiths created the NSE memes which are the foundation behaviors that permit our social niche(s). Furthermore, NSEs were produced by enhanced intentionality skills and NSEs were created by both genetic and memetic processes. The evolution of intentionality-NSE neural networks is asserted as the source of intentional material manipulation. While anti-NSE memes are claimed as the source of persistent trauma, the practice of esoteric technologies is presented as a solution to persistent trauma.

This paper aims to provide insight into the evolving relationship between humans and machines, understanding its multifaceted impact on our lifestyle and landscape in the past as well as in the present, with implications for the near future. It uses bibliometric analysis combined with a systematic literature review to identify themes, trace historical developments and offer a direction for future human–machine interactions (HMIs).

To provide thorough coverage of publications from the previous four decades, the first section presents a text-based cluster bibliometric analysis based on 305 articles from 2,293 initial papers in the Scopus and Web of Science databases produced between 1984 and 2022. The authors used VOS viewer software to identify the most prominent themes through cluster identification. This paper presents a systematic literature review of 63 qualified papers using the PRISMA framework.

Next, the systematic literature review and bibliometric analysis revealed four major historical themes and future directions. The results highlight four major research themes for the future: from Taylorism to advanced technologies; machine learning and innovation; Industry 4.0, Society 5.0 and cyber–physical system; and psychology and emotions.

There is growing anxiety among humankind that in the future, machines will overtake humans to replace them in various roles. The current study investigates the evolution of HMIs from their historical roots to Society 5.0, which is understood to be a human-centred society. It balances economic advancement with the resolution of social problems through a system that radically integrates cyberspace and physical space. This paper contributes to research and current limited knowledge by identifying relevant themes and offering scope for future research directions. A close look at the analysis posits that humans and machines complement each other in various roles. Machines reduce the mechanical work of human beings, bringing the elements of humanism and compassion to mechanical tasks. However, in the future, smart innovations may yield machines with unmatched dexterity and capability unthinkable today.

This paper attempts to explore the ambiguous and dynamic relationships between humans and machines. The present study combines systematic review and bibliometric analysis to identify prominent trends and themes. This provides a more robust and systematic encapsulation of this evolution and interaction, from Taylorism to Society 5.0. The principles of Taylorism are extended and redefined in the context of HMIs, especially advanced technologies.

This conceptual article presents a schematic of rat maternal behavior and niche stress epigenetic effects as a case study that is then aligned with current evolutionary concepts, which raises new questions regarding immigrant assimilation and niche dynamics.

The necessary background material for rat maternal and niche(s) stress factors are incorporated into a recursive, test-operate-test (rTOT), information-only-transfer, schematic (Patterson, 2023), which is an extension and refinement of the test-operate-test-exit (TOTE) schematic of Miller et al. (1960).

The generated epigenetic rTOT demonstrates the fundamental evolutionary unit of the flexible organism within its niche(s). The rTOT also confirms that epigenetic processes, epigenetic inheritance and phenotype plasticity are significant conceptual tools for understanding evolution. The teleology of rat adaptations for niche fitness via maternal behavior has been demonstrated. Sterling's (2011) allostasis, or predictive homeostasis, is extended to include species-niche(s) interaction(s) that are governed by recursive information feedback loops that function via self-organized criticality (SOC) for species and niche(s). Use of a rat model for biosocial issues in humans is strengthened.

Epigenetic rTOT only covers the species side of the evolutionary unit. Niche(s) require(s) a separate rTOT schematic. The information modeled does not include the entire system producing epigenetic effects but models a substantial portion of it.

Epigenetic rTOT demonstrates the utility of phenotypic plasticity, epigenetics and epigenetic inheritance as explanations for inheritable behavior patterns. rTOT is a useful computational model for evolutionary issues. The issues involved in niche modeling using an rTOT schematic are briefly reviewed.

When the demonstrated epigenetic model of rat genetics and inherited behavior are applied to the issues of immigrant enclaves, epigenetic complications for the difficulties of assimilation into the culture within which the enclaves are embedded become apparent. However, the questions raised must be addressed with extreme care to avoid cultural imperialism. Such cultural issues must be modeled with an rTOT application that covers the materials involved. The limitations of human Learning III restrictions when attempting to model Learning IV issues are addressed. Research into the means by which abuse and trauma are maintained by epigenetic means is urgently needed.

The rTOT schematic visualizes rat maternal behavior and stress epigenetic effects that produce inheritable behavior patterns, which answers Jablonka's (2017) request for new computational modeling representations. The concept of allostasis, or predictive homeostasis, (Sterling, 2011) is extended to the niche(s) of the organism under study so that allostasis becomes a fully cybernetic concept governed by SOC for both the organism and its niche(s). This new case study confirmed evolutionary effects of epigenetics, epigenetic inheritance and phenotypic plasticity. Niche control of organism evolution is presented. Epigenetic applications for immigrant assimilation issues have been suggested and niche dynamic questions have been raised.

The importance of learning in development in increasingly dynamic contexts can help individuals and organizations adapt to disruption. Artificial intelligence (AI) is emerging as a disruptive technology, with increasing adoption by various human resource management (HRM) functions. However, learning and development (L&D) adoption of AI is lagging, and there is a need to understand of this low adoption based on the internal/external contexts and organization types. Building on open system theory and adopting a technology-in-practice lens, the authors examine the various L&D approaches and the roles of human and technology agencies, enabled by differing structures, different types of organizations and the use of AI in L&D.

Through a qualitative interview design, data were collected from 27 key stakeholders and L&D professionals of MSMEs, NGOs and MNEs organizations. The authors used Gioia's qualitative research approach for the thematic analysis of the collected data.

The authors argue that human and technology agencies develop organizational protocols and structures consistent with their internal/external contexts, resource availability and technology adoptions. While the reasons for lagging AI adoption in L&D were determined, the future potential of AI to support L&D also emerges. The authors theorize about the socialization of human and technology-mediated interactions to develop three emerging structures for L&D in organizations of various sizes, industries, sectors and internal/external contexts.

The study hinges on open system theory (OST) and technology-in-practice to demonstrate the interdependence and inseparability of human activity, technological advancement and capability, and structured contexts. The authors examine the reasons for lagging AI adoption in L&D and how agentic focus shifts contingent on the organization's internal/external contexts.

While AI-HRM scholarship has primarily relied on psychological theories to examine impact and outcomes, the authors adopt the OST and technology in practice lens to explain how organizational contexts, resources and technology adoption may influence L&D. This study investigates the use of AI-based technology and its enabling factors for L&D, which has been under-researched.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

Integrating individual and relational centric voice literature, the authors draw on self-presentation theory to analyse the role of status pursuit in employee voice. Status pursuit is believed to be ubiquitous as it is linked to access to scarce resources and social order pecking.

The authors present a cross-level conceptual model outlining relational nuances of employee status pursuit that drive upward voice.

The model integrates status pursuit with peer- and leader-related facets, focusing on three targets of voice: immediate leader (supervisor), diagonal leader (supervisor of another team/unit) and co-workers. The model highlights how employee voice can be directed to diverse targets, and depending on interpersonal attributes, how it serves as underlying links for upward voice.

While employee voice can help to address important workplace concerns, it can also be used to advance employees' self-interest. Though there is a wealth of research on the importance of employee voice to organisational performance and individual wellbeing, especially through collective representation such as trade unions, there is a lack of literature on how employees navigate the social-relational work setting to promote their interests and develop status.

The aim of this paper is to offer a comprehensive overview of the field of international human resource management (IHRM) research by tracing its evolutionary development over a 24-year period. The study seeks to understand how the field has progressed by considering historical research themes and their subsequent integration into more recent scholarly work, thereby identifying current and emerging research trends.

This paper employs bibliometric analysis to examine the evolutionary path of IHRM research from 1995 to 2019. A dataset of 1,507 articles from journals specializing in IHRM, international business and general management was created. Analysis at the keyword, thematic and network levels was conducted to identify trends, historical context and the interrelatedness of research themes.

The analysis reveals that IHRM research has gone through several phases of thematic focus, from initial emphasis on cultural differences and expatriate management to more recent topics like global talent management and digital transformation. Earlier research themes continue to be incorporated and re-contextualized in modern scholarship, highlighting the field’s dynamic nature.

This paper is one of the first to use a bibliometric approach to systematically examine the evolution of IHRM research. It not only provides a historical perspective but also outlines future research trends, incorporating the institutional logic perspective. The findings offer deep insights that are valuable for researchers, practitioners and policymakers interested in the development of IHRM research and its practical implications.

This study aims to explore human–machine interactions in the process of adopting artificial intelligence (AI) based on the principles of Taylorism and digital Taylorism to validate these principles in postmodern management.

The topic has been investigated by means of a case study based on the current experience of Carrozzeria Basile, a body shop born in Turin in 1970.

The Carrozzeria Basile’s approach is rooted in scientific management concepts, and its digital evolution is aimed at centring humans, investigating human–machine interactions and how to take advantage of both of these.

The research contributes to both Taylorism management and the literature on human–machine interactions. A unique case study represents a first step in comprehending the phenomenon but could also represent a limit for the study.

Practical implications refer to the scientific path to facilitate the implementation and adoption of emerging technologies in the organisational process, including employee engagement and continuous employee training.

The research focuses on human–machine interactions in the process of adopting AI in the automation process. Its novelty also relies on the comprehension of the needed path to facilitate these interactions and stimulate a collaborative and positive approach. The study fills the literature gap investigating the interactions between humans and machines beginning with their historical roots, from Taylorism to digital Taylorism, in relation to an empirical scenario.

The importance of mental wellbeing and the need for organizations to address it is increasing in the post-pandemic context. Although Artificial Intelligence (AI) is increasingly being adopted in HRM functions, its adoption and utility for enabling mental wellbeing is limited. Building on the Open System Theory (OST) and adopting the technology-in-practice lens, the authors examined the roles of human and technology agencies in enabling mental wellbeing.

The study was conducted in two stages; in Stage 1, the authors adopted a case methodology approach to examine the feasibility of a technology company's offerings to assess mental wellbeing. In Stage 2, the authors followed the grounded theory approach and interviewed 22 key stakeholders and HR leaders of diverse organizations. The authors used Gioia's approach to analyze the data.

The study demonstrates the interdependence and inseparability of human activity, technological capability and structured context. Specifically, the authors observe that AI adoption is pushing the boundaries of how organizations could support employees' mental health and wellbeing. These technological advancements and adoption are likely to facilitate the evolution of agentic practices, routines and structures.

This study carries two important implications. While the advent of cutting-edge technologies appears to affect employees' mental wellbeing, the study findings indicate the assistive role of technology in supporting mental wellbeing and facilitating changes in organizational practices. Second, the ontology of technology-in-practice shows how human–machine agencies gain newer relevance from the interactions that unite them. Specifically, per OST, technology (from an external context) can potentially change how mental wellbeing practices in organizations are managed. The authors extend the existing literature by suggesting that both human agents and internal contexts effectively limit the potential of technology agents to change existing structures significantly.

The authors address the need for more research on the technology-management interface, and the boundaries of technology-enabled wellbeing at work. While AI-HRM scholarship has primarily relied on micro-level psychological theories to examine impact and outcomes, the authors borrow from the macro-level theories, such as the OST and the technology-in-practice to explain how AI is shifting the boundaries of human and machine agencies for enabling mental wellbeing.