Special Issue(24-15): Emerging advances in human robot interaction for large complex business marketing innovations
Posted on 2024-08-07
Emerging advances in human robot interaction for large complex business marketing innovations
Technological trends paved the way to revolutionize various sectors for the easy functioning of society. The evolution of advanced techniques is found to set a generative platform for developing business marketing strategies. The incorporation of robotic technologies emphasizes effective marketing management. The advanced techniques of human-robot interaction for business marketing are a great and essential endeavour aiming for progressive global changes.
Advanced innovative approaches enable robots capable of functioning effective interaction expertizing the marketing sector than the previous practices. Innovations in sensor technology result in sophisticated functions that replace humans' functionalities serving as an ideal choice for enhancing the physical interaction between humans and robots. Human-robot interactions are becoming increasingly important in the expanding market due to its significant features of personalized services. The effective HRI (Human-Robot Interaction) plays a vital role in the marketing field in performing complex tasks in the business environment to increase the sale of a product. Researchers envisaged the unique attributes of human-robot interactions like consumer-oriented service, computer-based marketing, and automotive marketing. Adopting human-robot interaction promotes operational assistance for the controller to execute and interrogate automated self-operating robotic technology into the consumer assistance services. Additionally, the intervention of entertainment robots and interactions are found to be the emerging trends used in business marketing. The successful progressions of technologies in developing the effectual interaction connecting humans and robots enhance complex tasks by solving multifaceted problems in business marketing.
Despite many reliable trends in human-robot interaction for complex business marketing, it also lags with certain downsides. Researchers and practitioners are invited to present a theoretical research framework regarding this context. The special issue provides various opportunities to discuss the downsides to tackling and expertise in the system.
List of Topics include but not limited to the following,
- New frontiers in business marketing strategies for the economic development
- Limitations and challenges in implying human-robot interaction for business marketing
- Human-robot interaction for businesses: trends and opportunities
- Advanced innovative approaches through robots for business marketing
- Effective approaches in the field of marketing for the enhancement of businesses
- Risk correlated with the data mishandling and lack of technical knowledge with the interference of robots for businesses
- The new paradigm of business marketing innovations for future development of businesses
- Future perspectives of human-robot interaction for the effective marketing strategies
- Role of robots for the emerging business trends for the future era
- Insights of human-robot interaction for the marketing industries
- Need for new sustainable policies and legislations for the enhancement of business enterprise
- Innovative business marketing strategies: pros and cons
Important Dates:
Submission deadline : Nov 29th 2024
Author notification : Feb 15th 2025
Revised papers due : April 30th 2025
Final notification : June 05th 2025
GE Information:
Dr. Zohaib Mushtaq
Assistant Professor,
Department of Electrical Engineering, College of Engineering and Technology,
University of Sargodha, Sargodha, 40100, Pakistan
Email ID: [email protected], [email protected]
Official Page: https://www.su.edu.pk/facultyprofile/10297
Google Scholar Page: https://scholar.google.com/citations?user=CqfA2GEAAAAJ&hl=en
Research Interests: Artificial Intelligence, Machine and Deep Learning, Data Science, Biomedical Engineering, Feature Engineering
Profile Summary: Dr. Zohaib Mushtaq has completed his PhD in Electrical Engineering from the National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan, and his MS in Electrical Engineering from the Government College University (GCU), Lahore, Pakistan. He earned his PhD degree on a fully funded university scholarship from NTUST. During his doctorate studies, he also received the Research Excellence Award among International Students in Taiwan for the year 2020, organized and sponsored by CTCI. He has vast teaching and research experience and has served as an assistant professor in electrical engineering at Riphah International University Islamabad, a research associate (RA) at NTUST, Taipei, and a lecturer at the Electrical Engineering Dept., University of Management & Technology, Sialkot.
Dr.Wahyu Rahmaniar
Assistant Professor,
Institute of Innovative Research,
Tokyo Institute of Technology, Yokohama 226-8503, Japan.
Email ID: [email protected]
Personal Website: https://wahyurahmaniar.github.io/
Google Scholar Page: https://scholar.google.com/citations?user=V81MER8AAAAJ&hl=en
Research Interests: Real-Time Computer Vision, Artificial Intelligence, Medical Imaging, Robotics, and Control Systems
Profile Summary: Dr.Wahyu Rahmaniar is an assistant professor (specially appointed) at the Tokyo Institute of Technology, Japan. She received the B.S. degree in Electronics and Instrumentation from Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia, in 2009 and the Ph.D. degree in Electrical Engineering from National Central University (NCU), Taiwan, in 2020. She has been a reviewer in several journals, such as Circuit World, Sensor Review, Journal of Robotics and Control, Journal of Electronic Imaging, Sensors (MDPI), BDCC (MDPI), and Scientific Reports (Nature).
Dr.Qazi Mazhar ul Haq
Assistant Professor,
Department of Computer Science and Engineering and IBPI,
Yuan Ze University, Taoyuan, Taiwan.
Email ID: [email protected]
Personal Website: https://dr-qazi.github.io/
Google Scholar Page: https://scholar.google.com/citations?user=AeJN-sYAAAAJ&hl=en
Research Interests: Machine Learning, Artificial Intelligence, Medical Image Processing, Self-driving Cars, Object Detection
Profile Summary: Dr. Qazi Mazhar ul Haq is currently working as an assistant professor in the Department of Computer Science and Engineering and IBPI at Yuan Ze University, Taiwan. He holds a Ph.D. in Electronics and Computer Engineering from the National Taiwan University of Science and Technology. His research interests include object detection, incremental learning, anomaly detection, image processing, deep learning, and 3D object detection.