Search results

Customers today expect businesses to cater to their individual needs by tailoring the products they purchase to their own preferences. The term “Industry 5.0” refers to a new wave of manufacturing that aims to meet each customer's unique demands. Even while Industry 4.0 allowed for mass customization, that wasn't good enough before, customers today demand individualized products at scale, and Industry 5.0 is driving the transition from mass customization to mass personalization to meet these demands. It caters to the individual needs of each consumer by meeting their demands. More specialized components for use in medicine are made possible by the widespread customization made possible by Industry 5.0. These individualized parts are included into the medical care of the patient to meet their specific needs and preferences. In the current medical revolution, an enabling technology of Industry 5.0 can produce medical implants, artificial organs, bodily fluids, and transplants with pinpoint accuracy. With the advent of AI-enabled sensors, we now live in a world where data can be swiftly analyzed. Machines may be programmed to make complex choices on the fly. In the medical field, these innovations allow for exact measurement and monitoring of human body variables according to the individual's needs. They aid in monitoring the body's response to training for peak performance. It allows for the digital dissemination of accurate healthcare data networks. In order to collect and exchange relevant patient data, every equipment is online.

Anthropomorphism in Artificial Intelligence (AI)-powered devices is being used increasingly frequently in consumer-facing situations (e.g., AI Assistants such as Alexa, virtual agents in websites, call/chat bots, etc.), and therefore, it is essential to understand anthropomorphism in AI both to understand consequences for consumers and to optimize firms' product development and marketing. Extant literature is fragmented across several domains and is limited in the marketing domain. In this review, we aim to bring together the insights from different fields and develop a parsimonious conceptual framework to guide future research in fields of marketing and consumer behavior.

We conduct a review of empirical articles published until November 2021 in Financial Times Top 50 (FT50) journals as well as in 41 additional journals selected across several disciplinary domains: computer science, robotics, psychology, marketing, and consumer behavior.

Based on literature review and synthesis, we propose a three-step guiding framework for future research and practice on AI anthropomorphism.

Our proposed conceptual framework informs marketing and consumer behavior domains with findings accumulated in other research domains, offers important directions for future research, and provides a parsimonious guide for marketing managers to optimally utilize anthropomorphism in AI to the benefit of both firms and consumers.

We contribute to the emerging literature on anthropomorphism in AI in three ways. First, we expedite the information flow between disciplines by integrating insights from different fields of inquiry. Second, based on our synthesis of literature, we offer a conceptual framework to organize the outcomes of AI anthropomorphism in a tidy and concise manner. Third, based on our review and conceptual framework, we offer key directions to guide future research endeavors.

The contemporary dynamics impose companies to both innovate and internationalize at the same time while remaining competitive in the international marketplace. With this context in mind, Industry 4.0 technologies have the potential to increase the competitiveness of companies, leading to a new era of “Manufacturing Renaissance.” Recently, conceptual studies have speculated on possible impacts of the adoption of Industry 4.0 technologies in terms of international business. However, empirical studies on this topic are still lacking. Through a multiple case study approach, this study presents exploratory qualitative research investigating the relationship between Industry 4.0 and the internationalization of companies. The analysis of 16 Italian manufacturing exporting companies, which have adopted some of these technologies, has revealed a more intriguing relationship compared to the one presented in current literature, and thus has opened avenues for future research on this issue.

Educational Robotics is a research field aimed at promoting an active engaging learning through the artifacts students create and the phenomena they simulate. In fact, designing, building, and programming a small robot, users discover and learn in a playful and joyful way. Moreover, the constructivist approach fosters the development of creative and critical skills, as well as problem-solving, communication skills, cooperation, and teamwork. This chapter presents the results of a research with university students, carried out at the Università della Calabria (Italy): an Educational Robotics laboratory has been integrated in a Cognitive Psychology Course in order to examine the kind of learning, workgroup retention, and engagement. Outcomes show that engaging experiences can remarkably enhance students’ learning efficiency and retention of the acquired materials. Moreover, a rich interaction can provide entertaining and appealing experiences capable of promoting learning and understanding.

Most analyses of the relationship between the internal distribution of formal organizational power, generally manifested in ownership and governance rights, and innovation efforts apply a principal-agent framework. The key implication of this framework is that firms with distributed formal power are more likely to engage in labor-intensive innovation because external capital providers are unwilling to entrust their investments to a worker controlled firm. In this paper, we critique the principal-agent framework and propose an alternative institutionalist approach, where the type of innovation pursued by firms with distributed formal power is contingent on the norms advanced by the innovation and the alignment of external stakeholders with those norms. After presenting this alternative framework, we illustrate its application with positive and negative cases of capital and labor-intensive innovation at the MONDRAGON cooperatives, a network of worker cooperatives in the Basque region of Spain. We conclude with a set of propositions to guide future research.

Purpose – The purpose of this chapter is to conduct a critical literature review that examines the origins and development of research on service robots in organizations, as well as the key emotional and cognitive issues between service employees, customers, and robots. This review provides a foundation for future research that leverages the emotional connection between service robots and humans.

Design/Methodology/Approach – A critical literature review that examines robotics, artificial intelligence, emotions, approach/avoid behavior, and cognitive biases is conducted.

Findings – This research provides six key themes that emerge from the current state of research in the field of service robotics with 14 accompanying research questions forming the basis of a research agenda. The themes presented are as follows: Theme 1: Employees have a forgotten “dual role”; Theme 2: The influence of groups is neglected; Theme 3: Opposing emotions lead to uncertain outcomes; Theme 4: We know how robots influence engagement, but not experience; Theme 5: Trust is necessary but poorly understood; and Theme 6: Bias is contagious: if the human mind is irrational…so too are robot minds.

Practical Implications – Practically, this research provides guidance for researchers and practitioners alike regarding the current state of research, gaps, and future directions. Importantly for practitioners, it sheds light on themes in the use of AI and robotics in services, highlighting opportunities to consider the dual role of the employee, examines how incorporating a service robot influences all levels of the organization, addresses motivational conflicts for employees and customers, explores how service robots influence the whole customer experience and how trust is formed, and how we are (often inadvertently) creating biased robots.

Industry 5.0 is referred to the subsequent industrialization. The ultimate goal of this transformation is to enable manufacturing solutions through collaboration with man and machine which are more user-friendly and increase work quality in comparison to Industry 4.0. This will be accomplished through the consumption of the creative potential of human specialists in the creation of an industry with more efficient, clever, and precise machines. It is predicted that several exciting breakthroughs and apps will help Industry 5.0 in its plan to gain more productivity and supply personalized goods in an open system. On the other hand, Industry 5.0 has had a greater global and international renown from the very beginning of its existence. Machine learning (ML) technology, the Internet of Things (IoT), and big data will create a collaboration with people, robots, and other intelligent devices. Industry 5.0 continues to serve as an attractive driver for our society's workforce skills and young talent in search of purposeful professional lives. There are some challenges as well, such as working with advanced robots requires people to develop skills. People need to gain proper knowledge about collaboration with smart machines and the robot manufacturers industry. However, this ultimate overhaul is necessary for the industry to certify its reason as a solution provider for our society. These things will unquestionably ensure the long-term sustained development (SD) of any nation's economy.