Adoption Of Robots Research Articles

Trends in adoption of robotics in arthroplasty: an analysis of the Indian landscape.

Robotic-assisted technology in total joint arthroplasty (TJA) offers improved precision in component placement and alignment, addressing challenges, such as ligament imbalance, malalignment, and patient dissatisfaction. In India, where diverse healthcare settings exist, trends in robotic adoption remain underexplored. This study examines the adoption patterns and geographic distribution of robotic systems for TJA in India, highlighting market dynamics over the past 5years. A cross-sectional observational study was conducted using data from manufacturers of robotic arthroplasty systems. Annual installations, tier-wise city classifications, and geographic distributions were analyzed. Statistical methods included descriptive analysis for installation trends, time-series visualization for adoption trajectories, and linear regression to forecast 2025 installations. As of September 2024, 290 robotic systems were installed across India. Among these, the CUVIS system (Meril) accounted for 89 installations (30.7%), followed by CORI (Smith and Nephew) with 66 installations (22.8%), and VELYS (DePuy) with 52 installations (17.9%). The MAKO system (Stryker) contributed 38 installations (13.1%), while MISSO (Meril) and ROSA (Zimmer) had 25 (8.6%) and 20 (6.9%) installations, respectively. Tier I hospitals dominated with 50% of installations, while Tier III and IV facilities accounted for only 10%. Linear regression predicts steady growth, with over 80 new robotic installations in 2025. Robotic technology adoption in Indian TJA has surged, with a strong preference for systems offering precision and versatility. However, barriers such as high costs and limited training impede penetration in lower tier facilities. Addressing these challenges could enhance equitable access and support the integration of robotics into diverse healthcare settings.

Examining the effects of values and risks on outdoor food delivery robot adoption using mixed methods: different stakeholders’ perspectives

Examining the effects of values and risks on outdoor food delivery robot adoption using mixed methods: different stakeholders’ perspectives

The impact of the introduction of industrial robots on workplace injury risk and mortality

In the 19th century, the Luddites protested against the introduction of new technology into the wool and cotton industries, concerned that this would mean a reduction in the quality of their work, less need for their skill and a lower pay. Nowadays, luddite is used to refer to someone who dislikes technology. In modern society, there are similar concerns regarding artificial intelligence (AI) and what its introduction and evolution means for the human workforce. Despite these fears of past and present society, there is no doubt that there are significant benefits associated with the introduction of new technologies. For example, industrial robots play an important role in reducing workplace injury and mortality risk. Associate Professor Masahiro Yoshida, Department of Political Science and Economics, Waseda University, Japan has a background in economics and is interested in the socio-economic drivers and impacts of injuries in the workplace. While the nationwide injury rate improved before the Great Recession, it subsequently began to stagnate. Given accelerated investment in industrial robots, Yoshida found this puzzling and, through his work in this area, found that most industrial robots are utilised in innately safe sectors rather than in more risky sectors, suggesting a profit-seeking reasoning behind investment in robots rather than the prioritisation of workplace safety. He also found that these sectors tend to have a higher dependency on immigrants. This led Yoshida to explore the relationship between the dependency on immigration and the progress of robot adoption across industries.

Air Pollution and the Adoption of Industrial Robots in Firms

ABSTRACTWe document that air pollution can explain the adoption of industrial robots in firms. By leveraging the spatial discontinuity of air pollution caused by the Huai River policy along the Huai River and Qinling Mountains, the research applies a regression discontinuity design to accurately identify the positive impact of air pollution on the adoption of industrial robots in firms. Results obtained from various tests reveal that the relationship between the two is casual. From a mechanistic perspective, this paper posits that air pollution has an adverse effect on labor allocation. However, it also increases labor costs and environmental regulation intensity, thereby inducing firms to adopt more industrial robots. Furthermore, this study finds that industries vulnerable to light pollution, low energy consumption, and labor intensity exhibit a more pronounced positive relationship between air pollution and industrial robot adoption.

Does artificial intelligence suppress firms' greenwashing behavior? Evidence from robot adoption in China

Does artificial intelligence suppress firms' greenwashing behavior? Evidence from robot adoption in China

Blessing or Curse? The Impact of the Penetration of Industrial Robots on Green Sustainable Transformation in Chinese High-Energy-Consuming Industries

The rapid development and widespread application of artificial intelligence (AI) and robots have profoundly impacted the economy, society, and the environment. This article focuses on the relationship between industrial robots and green sustainable transformation in high-energy-consuming industries. Through the Poisson distribution fixed effect, the negative binomial fixed-effect model, and the two-way fixed-effect model, we found that the penetration of industrial robots in high-energy-consuming enterprises (HEEs) has a significant and positive effect on green innovation. In particular, we verified that total factor productivity and ESG, included in the zero-inflation model, have a breakthrough-accelerating role in the application of industrial robots to promote green sustainable transformation. Further analysis indicated that the adoption of industrial robots is also positively correlated with the improvement of corporate green sustainable transformation in non-state-owned enterprises, but state-owned enterprises are not sensitive. In the classification of segmented industries, only the metallurgical industry demonstrates the empowering role of green sustainable transformation. This article provides a new avenue for reshaping the low-carbon green sustainable transformation strategy of HEEs, as well as useful insights, supporting the achievement of carbon peak and carbon neutrality by promoting the application of industrial robots and further improving total factor productivity and ESG performance.

Unveiling Key Drivers for Social Robot Adoption in the Hospitality Sector: Two-Phase Confirmatory Factor Analysis and Structural Equation Modeling Approach

Unveiling Key Drivers for Social Robot Adoption in the Hospitality Sector: Two-Phase Confirmatory Factor Analysis and Structural Equation Modeling Approach

Agricultural Robotics: A Technical Review Addressing Challenges in Sustainable Crop Production

The adoption of agricultural robots is revolutionizing the agricultural sector, offering innovative solutions to optimize production and reduce environmental impact. This review examines the main functions and applications of agricultural robots, with a focus on the crops handled and the technologies employed. The study analyzes the current state of the art regarding the market trend of agricultural robots used in field and greenhouse operations. Several solutions are emerging, some already implemented and others still in the prototype or project stage. These solutions are beginning to spread, though they may still seem far from widespread field application, particularly given the peculiarities and heterogeneity of the global agricultural landscape. In the face of the many benefits associated with the use of agricultural robots, even today some technical bottlenecks and costs limit their widespread use by farmers. The review provides a fairly comprehensive and up-to-date overview of current trends in agricultural automation, suggesting new areas of research to improve the efficiency and adaptability of robotic systems to different types of crops and environments.

The Hidden Cost of Automation: How Robot Adoption Impacts Employees' Sus-tainable Behavior and Environmental Practices

The Hidden Cost of Automation: How Robot Adoption Impacts Employees' Sus-tainable Behavior and Environmental Practices

Adopting Robotics in Desertification Control: Innovative Pathways to Sustainable Development in Africa And Beyond

Desertification is a critical environmental issue that threatens the sustainability of ecosystems, livelihoods, and economic growth, particularly in Africa. This paper examines the role of robotics as a transformative solution to combat desertification, with a focus on enhancing land restoration and sustainable agricultural practices in arid and semi-arid regions. It explores the potential of robotics and autonomous systems to address key challenges in desertification control, such as precision afforestation, resource management, and environmental monitoring. The paper discusses the significant benefits of integrating robotics into desertification efforts, highlighting how these technologies can improve efficiency and effectiveness in ecosystem restoration. Furthermore, it outlines the challenges and limitations associated with the adoption of robotics in Africa, including financial barriers, lack of technical expertise, and inadequate infrastructure. Policy recommendations are provided to promote investment in robotics for environmental management, encourage research and development tailored to Africa's unique challenges, and foster partnerships to ensure equitable access to these technologies. The paper concludes by advocating for the incorporation of robotics into national and regional development agendas, positioning them as essential tools for achieving sustainable development and mitigating the impacts of desertification.

Human–robot interactions and experiences of staff and service robots in aged care

The rise of robotics in aged care is transforming how older adults are cared for, addressing staff shortages and workload. Daily interactions with staff and residents highlight an urgent need to better understand and improve human–robot interactions. This study investigates how 34 staff interacted with 10 service robots in a regional Australian aged care facility over 5 years, focusing primarily on their experience with service robots that transported meals and laundry. Guided by the Almere model, the research employs a qualitative case study approach, drawing on observations, focus groups, and interviews with management, industry leaders, and frontline staff. Findings are categorised into Emotional Reactions, Human–Robot Interaction and Collaboration, Social License and Environmental Dynamics. Results indicate conditional acceptance of service robots with scepticism about the service robots’ reliability and practical utility. Our study highlights the importance of a supportive environment, robust infrastructure and adequate training for successful robotic adoption. It also argues for engaging diverse multi-tiered stakeholders in investigating, designing, and implementing robotics in aged care, emphasising the role of social behaviours and interactions for what we propose as functional social service robots.

In-situ evaluation of hole quality and cutting tool condition in robotic drilling of composite materials using machine learning

Abstract The massive adoption of industrial robots in the manufacturing sector has significantly increased automation of installation and inspection procedures, particularly benefiting the aerospace industry, where large volumes of holes are drilled in each aircraft. However, mechanical drilling remains challenging when dealing with composite materials due to their inherently heterogeneous structure. This work presents a novel approach for in-situ hole quality inspection utilising integrated sensor data of an industrial robotic drill, combined with a machine learning model. Additionally, a novel classification approach for evaluating hole quality is proposed. This study employed a KUKA industrial robot, fitted with a multifunctional end-effector, to drill holes in a composite material used in aerospace applications. An ensemble neural network (ENN) model, which combines an artificial neural network with a genetic algorithm, was used to assess the quality of these drilled holes. The model was specifically developed and tested on the machined holes to relate process input parameters and drilling torques to hole quality. The model predictions were validated with six unseen datasets, of which five were predicted accurately. A full factorial study of the process parameters was conducted using analysis of variance (ANOVA) to investigate the relationship between tool condition and drilling torque. The results of the ANOVA show that tool condition is the largest contributor to drilling torque. The method proposed in this work, which allows real-time monitoring of hole quality, has the potential to improve manufacturing productivity of drilled components while ensuring high-quality end products.

Exploring adoption of humanoid robots in education: UTAUT-2 and TOE models for science teachers

Abstract This study examines the factors influencing science teachers’ intentions to adopt humanoid robots in educational settings. It employs the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) and the Technology-Organization-Environment (TOE) framework as guiding theoretical models. By integrating UTAUT-2, which emphasizes individual factors, and TOE, which addresses organizational and environmental influences, the study constructs a comprehensive model that explores both personal and contextual drivers of adoption. Utilizing structural equation modeling on a sample of 1,150 pre-service and in-service science teachers, the study reveals that the integrated model demonstrates superior predictive power compared to each framework individually. Results highlight the moderating role of professional experience in the adoption process, with significant differences identified between pre-service and in-service teachers. The findings reveal significant differences between pre-service and in-service teachers, illustrating the moderating role of professional experience in the adoption process. This study provides a deeper understanding of how motivational, organizational, and environmental factors interact to influence adoption intentions. These insights provide practical guidance for developing targeted training programs, promoting institutional readiness through well-crafted policy initiatives, and implementing pilot projects to support schools in the effective integration of humanoid robots into educational curricula. These findings provide actionable insights for educational policymakers and practitioners aiming to enhance teaching quality and student engagement through innovative technologies.

(Un)Intended Consequences of Social Robot Adoption in Aged Care: A Hybrid Literature Review

(Un)Intended Consequences of Social Robot Adoption in Aged Care: A Hybrid Literature Review

Achieving pollution abatement and carbon reduction synergistically: How can industrial robots play a role?

Intelligent manufacturing and green development are pivotal issues in China's pursuit of high-quality economic growth. As the core carrier of artificial intelligence-driven production transformations, industrial robots' role in synergizing enterprise pollution control and carbon reduction has rarely been discussed in the literature. Leveraging a unique micro dataset with robot adoption, energy use, emissions, and economic factors, this study investigates the impact and mechanisms of robot adoption on enterprise pollution abatement and carbon reduction. The results unveil simultaneous SO2 and carbon emission intensity reductions after robot adoption. Further analysis attributes such synergistic effects primarily to front-end cleaner production rather than back-end pollution treatment. Promoting lean production, cleaner energy consumption, and technological innovation emerge as critical channels for robot adoption to exert synergistic benefits in pollution abatement and carbon reduction. Additionally, this collaborative abatement effect concentrates in large-scale enterprises, technology-intensive industry enterprises, and non-resource-based region enterprises. By elucidating robotization's micro-level workings, these findings provide valuable insights into green intelligent manufacturing and guide future integration of digital intelligence and green economy.

Robotics in Healthcare

This review explores the integration of robotics in healthcare, focusing on the current state, advancements, and the future potential of robotic systems. These systems, which include surgical robots, rehabilitation robots, and robotic diagnostic systems, have significantly impacted patient outcomes and healthcare efficiency. The review will discuss various data points, benefits, and challenges, as well as ethical concerns surrounding the adoption of healthcare robotics. Emerging technologies like nanobots and AI-integrated robots are poised to further revolutionize the field. This paper provides a critical analysis of these developments, highlighting both opportunities and limitations. The incorporation of robotics into healthcare has brought about a revolutionary change in the way medical services are delivered, significantly improving accuracy, operational efficiency, and patient care outcomes. This paper delves into the advancements, practical applications, obstacles, and prospective developments in the field of healthcare robotics. A structured approach was employed, encompassing a thorough review of recent literature, detailed case study analyses, and assessments of innovative technologies. The study reveals substantial advancements in areas like surgical robotics, rehabilitation devices, and patient support systems, while also identifying persistent challenges such as high costs, ethical issues, and technical constraints. This review highlights the transformative potential of robotics in reshaping modern healthcare and explores strategies to overcome the barriers to its widespread implementation

Exploring the Potential and Perceptions of Social Robots in Tourism and Hospitality: Insights from Industry Executives and Technology Evaluation

The tourism and hospitality industry are undergoing a transformation with the expansion of Artificial Intelligence (AI) and social robots, aiming to enhance customer service, operational efficiency, and overall guest experiences. This paper explores the roles, customer service, operational efficiency, benefits, challenges, and personalization of social robots. Moreover, this study involves a detailed survey with 14 top executives in the tourism and hospitality industry, focusing on their familiarity with, attitudes towards, and potential adoption of social robots in their operations. The objective is to show the industry’s current readiness for technological integration and predict the future impact of social robots on enhancing customer experiences and operational practices in the sector. This paper explores the practical implementation of social robots in tourism and hospitality while forecasting their future role in shaping the industry. Using models like the Technology Acceptance Model (TAM) and the theory of planned behavior, it examines how industry executives are responding to AI-driven robotics. By evaluating current applications and feedback from top-level management, this study contributes to both theoretical and practical discussions on how these innovations may drive operational change, enhance customer service, and reshape the service-oriented nature of the industry.

Systematic Review of Social Robots for Health and Wellbeing: A Personal Healthcare Journey Lens

Social robots have great potential in supporting individuals’ physical and mental health/wellbeing. While they have been increasingly evaluated in some domains, such as with children with autism, their evaluation has not been as extensive in other areas. We present a systematic review of domains in which social robots have been evaluated specifically in health/wellbeing contexts. We ask which robots have been evaluated, who the participants were, and how participants interacted with the robots. PRISMA guidelines for systematic reviews were followed. Articles with children as participants, using a purely robotic device, and in languages other than English were excluded. A total of 9,362 peer-reviewed articles (up to February 2021) from ACM DL, IEEE Xplore, Scopus, PubMed, and PsychInfo were identified. After applying the inclusion/exclusion criteria 443 articles were included in the review. The majority of studies were conducted at care centers while studies in hospitals/clinics have seen relatively limited attention. In many cases, the social robots were not programmed for specific health-related tasks, limiting their application. We also discuss robots used in real-world settings and propose a “Personal healthcare journey,” which includes different stages of one’s life which could benefit from a social robot, with the goal of increasing long-term adoption of social robots for supporting health/wellbeing.

Assessing barriers of automation and robotics adoption in the Indian construction industry: a fuzzy DEMATEL approach

Purpose Despite global advancements, the Indian construction industry lags in adopting technologies like robots, artificial intelligence, drones, unmanned ground vehicles and Internet of Things sensors due to various barriers. This reliance on traditional practices leads to persistent issues such as labour shortages, low productivity, safety risks, cost overruns and delays. Identifying and addressing these barriers is crucial for adopting advanced technologies. Hence, this study aims to identify and assess the influential barriers to construction automation and robotics (AaR) in India using a systematic approach. Design/methodology/approach An extensive literature review identified key barriers, including technological, financial, regulatory, environmental and organisational. A questionnaire survey was conducted among industry professionals, and the Fuzzy Decision-Making Trial and Evaluation Laboratory technique was used to evaluate the interrelationships and relative significance of these barriers. Findings The results of the study reveal the most critical cause barriers as “high initial cost”, “rigidity in organisational processes and procedures”, “interoperability”, “lack of competency” and “lack of standardisation”. These barriers subsequently influence the top two effect barriers such as “market uncertainty” and “ethical concerns”. Practical implications This research offers a systematic and quantitative assessment, enabling stakeholders to make informed decisions and develop strategies to overcome barriers to AaR adoption, unlocking the transformative potential of AaR in India’s construction sector. Originality/value Despite potential benefits, the adoption of AaR in Indian construction remains limited due to various barriers. This study provides novel insights with the first comprehensive assessment of these barriers and their interrelationships.

Drivers and Necessary Conditions for Chatbot Acceptance in the Insurance Industry. Analysis of policyholders’ and professionals’ Perspectives

ABSTRACT The adoption of conversational robots (chatbots) for customer service is expanding across many industries. In the insurance sector, where customer interactions are essential to the use of policies, understanding chatbot acceptance is particularly relevant. This study explores the factors and conditions influencing the acceptance of chatbots for insurance policy management via the unified theory of acceptance and use of technology (UTAUT) framework. The analysis is conducted on two groups: ordinary policyholders and policyholders who are also industry professionals. The explanatory factors evaluated are performance expectancy, effort expectancy, social influence, and trust. The findings indicate that effort expectancy, social influence, and trust positively impact the behavioral intention to use chatbots. Additionally, all the variables are found to be necessary for acceptance. The structural equation model assessment reveals that professional status do not moderate the relationships between explanatory variables and behavioral intention; however, professionals demonstrate a greater intention to use chatbots. Among ordinary policyholders, effort expectancy has the largest effect size on acceptance. For professionals, trust and performance expectancy are the most impactful explanatory variables, with very large effect sizes. These results emphasize that while all variables are essential for acceptance, the relative importance of each variable varies between policyholders and professionals, offering insights for implementing chatbot solutions effectively within the insurance sector.