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1 – 10 of over 8000Mahesh Babu Purushothaman and Kasun Moolika Gedara
This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and…
Abstract
Purpose
This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.
Design/methodology/approach
Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).
Findings
Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.
Research limitations/implications
Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.
Practical implications
The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.
Social implications
By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.
Originality/value
Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.
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Sarah Dodds, Rebekah Russell–Bennett, Tom Chen, Anna-Sophie Oertzen, Luis Salvador-Carulla and Yu-Chen Hung
The healthcare sector is experiencing a major paradigm shift toward a people-centered approach. The key issue with transitioning to a people-centered approach is a lack of…
Abstract
Purpose
The healthcare sector is experiencing a major paradigm shift toward a people-centered approach. The key issue with transitioning to a people-centered approach is a lack of understanding of the ever-increasing role of technology in blended human-technology healthcare interactions and the impacts on healthcare actors' well-being. The purpose of the paper is to identify the key mechanisms and influencing factors through which blended service realities affect engaged actors' well-being in a healthcare context.
Design/methodology/approach
This conceptual paper takes a human-centric perspective and a value co-creation lens and uses theory synthesis and adaptation to investigate blended human-technology service realities in healthcare services.
Findings
The authors conceptualize three blended human-technology service realities – human-dominant, balanced and technology-dominant – and identify two key mechanisms – shared control and emotional-social and cognitive complexity – and three influencing factors – meaningful human-technology experiences, agency and DART (dialogue, access, risk, transparency) – that affect the well-being outcome of engaged actors in these blended human-technology service realities.
Practical implications
Managerially, the framework provides a useful tool for the design and management of blended human-technology realities. The paper explains how healthcare services should pay attention to management and interventions of different services realities and their impact on engaged actors. Blended human-technology reality examples – telehealth, virtual reality (VR) and service robots in healthcare – are used to support and contextualize the study’s conceptual work. A future research agenda is provided.
Originality/value
This study contributes to service literature by developing a new conceptual framework that underpins the mechanisms and factors that influence the relationships between blended human-technology service realities and engaged actors' well-being.
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This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this…
Abstract
Purpose
This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.
Design/methodology/approach
This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.
Findings
Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.
Research limitations/implications
Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.
Practical implications
A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.
Social implications
Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.
Originality/value
The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.
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Sara Perotti, Roman Felipe Bastidas Santacruz, Peik Bremer and Jakob Emanuel Beer
In the last decade, the Industry 4.0 paradigm had started to rapidly expand to the logistics domain. However, Logistics 4.0 is still in an early adoption stage: some areas such as…
Abstract
Purpose
In the last decade, the Industry 4.0 paradigm had started to rapidly expand to the logistics domain. However, Logistics 4.0 is still in an early adoption stage: some areas such as warehousing are still exploring its applicability, and the technological implementation of this paradigm can become fuzzy. This paper addresses this gap by examining the relationship among influencing factors, barriers, and benefits of Logistics 4.0 technologies in warehousing contexts.
Design/methodology/approach
Starting from a Systematic Literature Review (SLR) approach with 56 examined documents published in scientific journals or conference proceedings, a conceptual framework for Logistics 4.0 in warehousing is proposed. The framework encompasses multiple aspects related to the potential adopter’s decision-making process.
Findings
Influencing factors toward adoption, achievable benefits, and possible hurdles or criticalities have been extensively analyzed and structured into a consistent picture. Company’s digital awareness and readiness result in a major influencing factor, whereas barriers and criticalities are mostly technological, safety and security, and economic in nature. Warehousing process optimization is the key benefit identified.
Originality/value
This paper addresses a major gap since most of the research has focused on specific facets, or adopted the technology providers’ perspective, whereas little has been explored in warehousing from the adopters’ view. The main novelty and value lie in providing both academics and practitioners with a thorough view of multiple facets to be considered when approaching Logistics 4.0 in logistics facilities.
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Ting Zheng, Marco Ardolino, Andrea Bacchetti and Marco Perona
This paper has two objectives: first, to investigate the state-of-the-art of Industry 4.0 (I4.0) adoption in Italian manufacturing firms and, second, to understand variations in…
Abstract
Purpose
This paper has two objectives: first, to investigate the state-of-the-art of Industry 4.0 (I4.0) adoption in Italian manufacturing firms and, second, to understand variations in technologies implemented and business functions involved, benefits perceived, and obstacles encountered in I4.0 implementation over a three-year period.
Design/methodology/approach
The approach adopted in this research is descriptive, nesting longitudinal features. The paper presents a descriptive survey of 102 Italian manufacturing companies. The authors also evaluated non-response biases. The longitudinal approach was achieved by comparing the responses of the 40 sub-samples in common with a second similar survey launched three years prior, which aimed to identify patterns of evolution in the adoption of the I4.0 paradigm.
Findings
Survey findings demonstrate that Italian manufacturing companies still have limited awareness of I4.0 technologies, and the adoption of I4.0 technologies differs per technology. Company size and information system coverage level are the two factors that impact the company's technology adoption level. The comparative study shows that knowledge and adoption increase in a three-year interval with an unbalanced involvement of business functions regarding the I4.0 transformation. Indeed, companies are still seeking I4.0 solutions to reduce costs and lead times primarily, and the benefits perceived by companies are shown to be related to the number of I4.0 technologies in use. Finally, when companies put the I4.0 technologies into practice, competence is constantly considered the most significant barrier.
Research limitations/implications
This paper aims at conducting a thorough investigation into the development of I4.0 adoption in manufacturing companies. The main limitation of this study concerns the limited number of subjects involved in the longitudinal study (40) and the focus on a limited geographical area (Italy). In addition, more I4.0 technologies could also be incorporated into the survey protocol to gain further insight into I4.0 development.
Originality/value
The authors provide one of the first attempts to assess the variations of I4.0 implementation concerning technology adoption, business function involvement, and the alteration of benefits and obstacles. Several studies presented in the literature highlight the lack of longitudinal studies investigating the development of the I4.0 paradigm in a specific manufacturing context: this paper is the attempt at filling this gap.
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Agata Leszkiewicz, Tina Hormann and Manfred Krafft
Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other…
Abstract
Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.
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Research into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote…
Abstract
Purpose
Research into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote the benefits of explainability or criticize it due to its counterproductive effects. This study addresses this polarized space and aims to identify opposing effects of the explainability of AI and the tensions between them and propose how to manage this tension to optimize AI system performance and trustworthiness.
Design/methodology/approach
The author systematically reviews the literature and synthesizes it using a contingency theory lens to develop a framework for managing the opposing effects of AI explainability.
Findings
The author finds five opposing effects of explainability: comprehensibility, conduct, confidentiality, completeness and confidence in AI (5Cs). The author also proposes six perspectives on managing the tensions between the 5Cs: pragmatism in explanation, contextualization of the explanation, cohabitation of human agency and AI agency, metrics and standardization, regulatory and ethical principles, and other emerging solutions (i.e. AI enveloping, blockchain and AI fuzzy systems).
Research limitations/implications
As in other systematic literature review studies, the results are limited by the content of the selected papers.
Practical implications
The findings show how AI owners and developers can manage tensions between profitability, prediction accuracy and system performance via visibility, accountability and maintaining the “social goodness” of AI. The results guide practitioners in developing metrics and standards for AI explainability, with the context of AI operation as the focus.
Originality/value
This study addresses polarized beliefs amongst scholars and practitioners about the benefits of AI explainability versus its counterproductive effects. It poses that there is no single best way to maximize AI explainability. Instead, the co-existence of enabling and constraining effects must be managed.
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The research aims to understand how smart speakers are perceived by their actual and potential users, their attitude towards smart speakers and consequently their intention to use…
Abstract
Purpose
The research aims to understand how smart speakers are perceived by their actual and potential users, their attitude towards smart speakers and consequently their intention to use them.
Design/methodology/approach
The authors apply a structural equation modelling (SEM) approach to test the research hypotheses through data coming from a structured questionnaire.
Findings
The results show that the higher the importance attributed to usefulness and ease of use, the higher the positive attitude that in turn positively affects the intention to use smart speakers. A significant relationship also emerged between task technology fit and attitude towards smart speakers, as well as between perceived enjoyment and attitude towards smart speakers. Perceived privacy risk, innovativeness and social attraction have been found to not significantly impact attitudes towards smart speakers.
Originality/value
Although several academic studies have focused on various aspects of smart technologies, only a few studies discuss the factors that push consumers to use smart speakers for activities related to commercial transactions. Therefore, looking at the rapid rise of smart speakers for daily tasks and the gradual acceptance of voice interaction with digital tools, the authors proposed a study about Italian users' intention to use smart speakers. Specifically, to fill the gap in the existing literature, the authors applied a SEM approach to identify utilitarian and hedonic benefits that motivate the use of these devices.
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Hilda Du Plooy, Francesco Tommasi, Andrea Furlan, Federica Nenna, Luciano Gamberini, Andrea Ceschi and Riccardo Sartori
Following the imperative for human-centric digital innovation brought by the paradigm of Industry 5.0, the article aims to integrate the dispersed and multi-disciplinary…
Abstract
Purpose
Following the imperative for human-centric digital innovation brought by the paradigm of Industry 5.0, the article aims to integrate the dispersed and multi-disciplinary literature on individual risks for workers to define, explain and predict individual risks related to Industry 4.0 technologies.
Design/methodology/approach
The paper follows the question, “What is the current knowledge and evidence base concerning risks related to Industry 4.0 technologies, and how can this inform digital innovation management in the manufacturing sector through the lens of the Industry 5.0 paradigm?” and uses the method of systematic literature review to identify and discuss potential risks for individuals associated with digital innovation. N = 51 contributions met the inclusion criteria.
Findings
The literature review indicates dominant trends and significant gaps in understanding risks from a human-centric perspective. The paper identifies individual risks, their interplay with different technologies and their antecedents at the social, organizational and individual levels. Despite this, the paper shows how the literature concentrates in studying risks on only a limited number of categories and/or concepts. Moreover, there is a lack of consensus in the theoretical and conceptual frameworks. The paper concludes by illustrating an initial understanding of digital innovation via a human-centered perspective on psychological risks.
Practical implications
Findings yield practical implications. In investing in the adoption, generation or recombination of new digital technologies in organizations, the paper recommends managers ensure to prevent risks at the individual level. Accordingly, the study’s findings can be used as a common starting point for extending the repertoire of managerial practices and interventions and realizing human-centric innovation.
Originality/value
Following the paradigm of Industry 5.0, the paper offers a holistic view of risks that incorporates the central role of the worker as crucial to the success of digital innovation. This human-centric perspective serves to inform the managerial field about important factors in risk management that can result in more effective targeted interventions in risk mitigation approaches. Lastly, it can serve to reinterpret digital innovation management and propose future avenues of research on risk.
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