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With the application and development of intelligent clothing and wearable technology, the term “micro-interaction” has gradually entered people’s lives. The paper aims to discuss this issue.

The paper takes the concept of “micro-interaction” as the design principle, starting from the consumer demand, combing the realization mode of the intelligent safety clothing in recent years, and finds out the existing problems in the design of the intelligent safety clothing.

Under the concept of micro-interaction, a new theoretical model has been proposed to study intelligent safety clothing. Finally, the paper also emphasizes the importance of the industrialization of the proposed model.

The paper proposes a new research and development mode for intelligent clothing in safety protection area which is a pioneering study and can be valuable for safety clothing manufacturers to produce more functional and attractive products.

This paper aims to review the extant intelligent home specifications and put forward a new dimension for the specifications of intelligent home (IHS).

This study adopts a learning (bottom‐up) algorithm which emphasizes the importance of learning and adaptability to the dynamic environmental changes in the IHS.

The study finds that the intelligent home has been characterized by automation, integration of facilities and communication. However, it is contended here that an intelligent home specification in such a hard‐wired (top‐down) approach cannot be sustained in the light of the continuous changes of user requirements. Hence, adaptation to users' needs must be encompassed in a system of home intelligence.

This study provides a framework for all stakeholders to work for a common goal and a platform for benchmarking the performance of intelligent home in the long run.

This is the first to adopt the learning (bottom‐up) algorithm in defining home intelligence.

Outlines the current research work on intelligent sensors and intelligent transducers which will be required in complex systems. Discusses the elements of an intelligent sensor and concludes that these require analogue filtering, data conversion and compensation, and a digital communication link to a common signal bus. Explains what is meant by a systems approach to intelligent sensors with layered information processing. Concludes that unless a deeper understanding of the basics of sensor systems is acquired new intelligent sensor design will be very difficult.

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.

This chapter introduces the concept of an intelligent organization in the context of the twenty-first-century knowledge economy. An intelligent organization is one in which individuals behave intelligently, work is grounded in intelligent methods and choices, and rich stocks of intelligence in the form of knowledge capital to support intelligence work and choices. Intelligence is defined as both a thing and attribute and behavior and way of working. The chapter also highlights examples of intelligent behaviors and or organizational pathologies. The chapter also highlights the importance of becoming aware of intelligent and unintelligent choices.

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 paper defines and explores the concept of intelligent spirituality. It is a deeply-grounded, emotionally-inspiring, spirituality that is human-centered, pragmatic, and intelligent. While the name is new, the idea itself has a well-respected pedigree. The American pragmatist philosopher, educator, and activist, John Dewey, more than anyone else, defined the parameters of intelligent spirituality, demonstrated its usefulness in the modern world, and, perhaps most importantly, exemplified it as a living option in his daily activities.

For those interested in the contemporary “spirituality movement” – advocates, critics, or spectators – and especially how it affects today’s business organizations, the idea of intelligent spirituality, as discussed here, provides a useful set of precise criteria to evaluate some of the many changes which are occurring in corporate America and are defended under the banner of spirituality in business. Can one distinguish, for example, between legitimate and illegitimate spirituality? Are some forms of spirituality more useful than others? To what extent can spirituality play a positive role in contemporary business? Is spirituality necessarily related to coerciveness and intolerance in business? This paper explores the assumptions of intelligent spirituality and attempts to answer these questions.

Researchers explore the impact of an intelligent assistant in virtual teams by applying the theoretical lens of a transactive memory system (TMS) to understand the relationships between trust in a specific technology, knowledge sharing and knowledge application.

An online survey was administered to a Qualtrics-curated panel of individual, US-based virtual team members utilizing an intelligent assistant with team collaboration software. Partial least squares structural equation modeling (PLS-SEM) was utilized to examine the hypothesized relationships of interest.

Results suggest that knowledge application is strongly influenced by trust in a specific technology and knowledge sharing. Additionally, a transactive memory system positively increases trust in the intelligent assistant, and similarly, trust in the intelligent assistant has a significant positive relationship with knowledge sharing.

The research model contributes to our understanding of the impact of an intelligent assistant in virtual teams. Although the transactive memory system construct has been explored in various contexts and models, few have explored the impact of an intelligent assistant and trust in a specific technology.