A Hybrid Business-Technical Model for Evaluating IoT Platforms’ Functionality, Reliability, and Usability
A Hybrid Business-Technical Model for Evaluating IoT Platforms’ Functionality, Reliability, and Usability |
||
 |
 |
|
| © 2023 by IJETT Journal | ||
| Volume-71 Issue-10 |
||
| Year of Publication : 2023 | ||
| Author : Adel. A. Nasser, Mujib M. Y. Al-Ashwal, Abdualmajed A. G. Al-Khulaidi, Abdulsalam N. Al- Naqeep, Mijahed Al-jober |
||
| DOI : 10.14445/22315381/IJETT-V71I10P205 | ||
How to Cite?
Adel. A. Nasser, Mujib M. Y. Al-Ashwal, Abdualmajed A. G. Al-Khulaidi, Abdulsalam N. Al- Naqeep, Mijahed Al-jober, "A Hybrid Business-Technical Model for Evaluating IoT Platforms’ Functionality, Reliability, and Usability," International Journal of Engineering Trends and Technology, vol. 71, no. 10, pp. 39-59, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I10P205
Abstract
The implementation and effectiveness of IoT platforms are crucial for data analysis, process optimization, and service control in various sectors. However, evaluating IoT platforms can be challenging due to the lack of detailed technical indicators related to reliability, functionality, and usability and the need to consider business aspects. This study aims to build a comprehensive model for evaluating IoT platforms that meet both the technical requirements and business needs of companies. The study's objective is to determine the functionality, reliability, and usability sub-criteria and measures necessary to evaluate IoT platforms and the business success factors affecting their relative importance in companies based on comparative studies and experts' views. The Fuzzy Delphi method was utilized for the validation process of the proposed model. The items of the proposed model, including assessment criteria, sub-criteria, measures, and factors affecting their relative importance in companies, reached the experts' agreement, except for two sub-criteria that did not meet the assessment requirements. The final analysis indicates that the assessment model includes three main evaluation criteria, twelve sub-criteria with twelve measures, and five factors that affect their relative importance in companies. This study provides an important contribution to the field of IoT platform evaluation and can help decision-makers select the most suitable platform for their specific needs in various sectors.
Keywords
Business-technical model, Business success, Criteria for IoT platform evaluation, Functionality, Reliability, Usability.
References
[1] Ya Cheng et al., “How do Technological Innovation and Fiscal Decentralization Affect the Environment? A Story of the Fourth Industrial Revolution and Sustainable Growth,” Technological Forecasting and Social Change, vol. 162, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Mehar Ullah et al., “Twenty-One Key Factors to Choose an IoT Platform: Theoretical Framework and Its Applications,” IEEE Internet of Things Journal, vol. 7, no. 10, pp. 10111-10119, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Yuriy Kondratenko, Galyna Kondratenko, and Ievgen Sidenko, “Multi-Criteria Decision Making for Selecting A Rational IoT Platform,” 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT), pp. 147-152, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Ioana Marcu et al., “Overview of IoT Basic Platforms for Precision Agriculture,” International Conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures, vol. 283, pp. 124-137, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Khaled Ahmed Nagaty, “IoT Commercial and Industrial Applications and AI-Powered IoT,” Frontiers of Quality Electronic Design (QED), pp. 465-500, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Neha Priya, “Cybersecurity Considerations for Industrial IoT in Critical Infrastructure Sector,” International Journal of Computer and Organization Trends, vol. 12, no. 1, pp. 27-36, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Vaidik Bhatt, and Samyadip Chakraborty, “Improving Service Engagement in Healthcare through Internet of Things-Based Healthcare Systems,” Journal of Science and Technology Policy Management, vol. 14, no. 1, pp. 53-73, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Alessandra Belfiore, Corrado Cuccurullo, and Massimo Aria, “IoT in Healthcare: A Scientometric Analysis,” Technological Forecasting and Social Change, vol. 184, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Seyyed Esmaeil Najafi, Hamed Nozari, and Seyyed Ahmad Edalatpanah, “Investigating the Key Parameters Affecting Sustainable IoT-Based Marketing,” Computational Intelligence Methodologies Applied to Sustainable Development Goals, vol. 1036, pp. 51-61, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[10] P. Brous and M. Janssen, “Advancing e-Government Using the Internet of Things: A Systematic Review of Benefits,” International Conference on Electronic Government, vol. 9248, pp. 156-169, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[11] M. Ullah, and K. Smolander, “Highlighting the Key Factors of an IoT Platform,” 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 901-906, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Alfonso Infante-Moro et al., “Key Criteria in the Choice of IoT Platforms in Spanish Companies,” Applied Sciences, vol. 11, no. 21, p. 10456, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Mahmoud A. Zaher, and Nabil M. Eldakhly, “An Effective Model for Selection of the Best IoT Platform: A Critical Review of Challenges and Solutions,” Journal of Intelligent Systems and Internet of Things, vol. 7, no. 2, pp. 40-50, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Leonardo Babun et al., “A Survey on IoT Platforms: Communication, Security, and Privacy Perspectives,” Computer Networks, vol. 192, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] A.I. Taloba et al., “A Blockchain-Based Hybrid Platform for Multimedia Data Processing in IoT-Healthcare,” Alexandria Engineering Journal, vol. 65, pp. 263-274, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[16] M. Westerlund, S. Leminen, and M. Rajahonka, “Designing Business Models for the Internet of Things,” Technology Innovation Management Review, vol. 4, no. 7, pp. 5-14, 2014.
[Google Scholar] [Publisher Link]
[17] Malihe Asemani, Fatemeh Abdollahei, and Fatemeh Jabbari, “Understanding IoT Platforms: Towards a Comprehensive Definition and Main Characteristic Description,” 2019 5th International Conference on Web Research (ICWR), pp. 172-177, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Mohammad Abdallah et al., “A Proposed Quality Model for the Internet of Things Systems,” 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), pp. 23-27, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Amirfardad Salami, and Alireza Yari, “A Framework for Comparing Quantitative and Qualitative Criteria of IoT Platforms,” 2018 4th International Conference on Web Research (ICWR), pp. 34-39, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Luca De Nardis et al., “Internet of Things Platforms for Academic Research and Development: A Critical Review,” Applied Sciences, vol. 12, no. 4, p. 2172, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Miroslav Bures et al., “A Comprehensive View on Quality Characteristics of the IoT Solutions,” 3rd EAI International Conference on IoT in Urban Space, pp. 59–69, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Ahmed A. Ismail, Haitham S. Hamza, and Amira M. Kotb, “Performance Evaluation of Open Source IoT Platforms,” 2018 IEEE Global Conference on Internet of Things (GCIoT), pp. 1-5, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Stina Nylander, Anders Wallberg, and Pär Hansson, “Challenges for SMEs Entering the IoT world: Success is About So Much More Than Technology,” Proceedings of the Seventh International Conference on the Internet of Things (IoT '17), pp. 1-7, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Dwi Surya Atmaja et al., “Actualization of Performance Management Models for the Development of Human Resources Quality, Economic Potential, and Financial Governance Policy in Indonesia Ministry of Education,” Multicultural Education, vol. 9, no. 1, pp. 1-15, 2023.
[Google Scholar] [Publisher Link]
[25] Ayi Gavriel Ayayi, and Mahinda Wijesiri, “Is there a Trade‐Off between Environmental Performance and Financial Sustainability in Microfinance Institutions? Evidence from South and Southeast Asia,” Business Strategy and the Environment, vol. 31, no. 4, pp. 1552-1565, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Ejae Lee et al., “Exploring the Interrelationship and Roles of Employee-Organization Relationship Outcomes between Symmetrical Internal Communication and Employee Job Engagement,” Corporate Communications: An International Journal, vol. 27, no. 2, pp. 264-283, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Sotiris P. Gayialis et al., “A Predictive Maintenance System for Reverse Supply Chain Operations,” Logistics, vol. 6, no. 1, pp. 1-14, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Mohsen Soori, Behrooz Arezoo, and Roza Dastres, “Internet of Things for Smart Factories in Industry 4.0, A Review,” Internet of Things and Cyber-Physical Systems, vol. 3, pp. 192-204, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Weng Chun Tan, and Manjit Singh Sidhu, “Review of RFID and IoT Integration in Supply Chain Management,” Operations Research Perspectives, vol. 9, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Zainab Fatima et al., “Production Plant and Warehouse Automation with IoT and Industry 5.0,” Applied Sciences, vol. 12, no. 4, pp. 1-34, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Robert G. Hardin IV et al., “Internet of Things: Cotton Harvesting and Processing,” Computers and Electronics in Agriculture, vol. 202, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[32] Abderahman Rejeb et al., “The Internet of Things (IoT) in Healthcare: Taking Stock and Moving Forward,” Internet of Things, vol. 22, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[33] Fazil Subhan et al., “AI-Enabled Wearable Medical Internet of Things in Healthcare System: A Survey,” Applied Sciences, vol. 13, no. 3, pp. 1-18, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[34] Madhukar Patil, and M. Suresh, “Modelling the Enablers of Workforce Agility in IoT Projects: A TISM Approach,” Global Journal of Flexible Systems Management, vol. 20, no. 2, pp. 157-175, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[35] Zhoumingju Jiang et al., “Data-Driven Generative Design for Mass Customization: A Case Study,” Advanced Engineering Informatics, vol. 54, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[36] Partha Pratim Ray, “A Survey of IoT Cloud Platforms,” Future Computing and Informatics Journal, vol. 1, no. 1-2, pp. 35-46, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[37] Galina Ilieva, and Tania Yankova, “IoT System Selection as a Fuzzy Multi-Criteria Problem,” Sensors, vol. 22, no. 11, pp. 1-26, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[38] Kun Wang et al., “Adaptive and Fault-Tolerant Data Processing in Healthcare IoT Based on Fog Computing,” IEEE Transactions on Network Science and Engineering, vol. 7, no. 1, pp. 263-273, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[39] Samuel J. Moore et al., “IoT Reliability: A Review Leading to 5 Key Research Directions,” CCF Transactions on Pervasive Computing and Interaction, vol. 2, no. 3, pp. 147-163, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[40] Tuan Anh Nguyen et al., “Performability Evaluation of Load Balancing and Fail-over Strategies for Medical Information Systems with Edge/Fog Computing Using Stochastic Reward Nets,” Sensors, vol. 21, no. 18, pp. 1-23, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[41] Chetan Kumar et al., “Greening the Cloud: A Load Balancing Mechanism to Optimize Cloud Computing Networks,” Journal of Management Information Systems, vol. 39, no. 2, pp. 513-541, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[42] Leandro Flores da Silva, and Edson Oliveira, “Evaluating Usefulness, Ease of Use and Usability of an UML-based Software Product Line Tool,” Proceedings of the XXXIV Brazilian Symposium on Software Engineering, pp. 798-807, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[43] Vishal Patel et al., “Trends in Workplace Wearable Technologies and Connected‐Worker Solutions for Next‐Generation Occupational Safety, Health, and Productivity,” Advanced Intelligent Systems, vol. 4, no. 1, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[44] Mauro Caporuscio et al., “IoT-Enabled Physical Telerehabilitation Platform,” 2017 IEEE International Conference on Software Architecture Workshops (ICSAW), pp. 112-119, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[45] Esko Penttinen et al., “What Influences Choice of Business-to-Business Connectivity Platforms?,” International Journal of Electronic Commerce, vol. 22, no. 4, pp. 479-509, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[46] Josimar Reyes-Campos et al., “Discovery of Resident Behavior Patterns Using Machine Learning Techniques and IoT Paradigm,” Mathematics, vol. 9, no. 3, pp. 1-25, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[47] Michael Onuoha Thomas, Beverly Amunga Onyimbo, and Rajasvaran Logeswaran, “Usability Evaluation Criteria for Internet of Things,” International Journal of Information Technology and Computer Science, vol. 8, no. 12, pp. 10-18, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[48] Asil Oztekin et al., “A Machine Learning-Based Usability Evaluation Method for eLearning Systems,” Decision Support Systems, vol. 56, pp. 63-73, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[49] Lucio Lamberti, “Customer Centricity: The Construct and the Operational Antecedents,” Journal of Strategic Marketing, vol. 21, no. 7, pp. 588-612, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[50] Alexander Osterwalder et al., Value Proposition Design: How to Create Products and Services Customers Want, John Wiley & Sons, 2015.
[Google Scholar] [Publisher Link]
[51] Michel Wedel, and Wagner A. Kamakura, Market Segmentation: Conceptual and Methodological Foundations, Springer Science & Business Media, 2012.
[Google Scholar] [Publisher Link]
[52] Kevin Lane Keller, Strategic Brand Management, 4th ed., Pearson Education, 2013.
[Google Scholar]
[53] E.F. Brigham, and M.C. Ehrhardt, Financial Management: Theory & Practice, Cengage Learning, 2016.
[Google Scholar]
[54] Preeti Agarwal, and Mansaf Alam, “Investigating IoT Middleware Platforms for Smart Application Development,” Smart Cities-Opportunities and Challenges, vol. 58, pp. 231-244, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[55] Edgar M. Silva, and Pedro Maló, “IoT Testbed Business Model,” Advances in Internet of Things, vol. 4, no. 4, pp. 37-45, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[56] Massimo Garbuio, and Gloria Gheno, “An Algorithm for Designing Value Propositions in the IoT Space: Addressing the Challenges of Selecting the Initial Class in Reference Class Forecasting,” IEEE Transactions on Engineering Management, vol. 70, no. 9, pp. 3171-3182, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[57] Antonio J. Jara, Antonio F. Skarmeta, and María Concepción Parra, “Enabling Participative Marketing through the Internet of Things,” 2013 27th International Conference on Advanced Information Networking and Applications Workshops, pp. 1301-1306, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[58] L. Kaufman, and M.M. Gupta, Introduction to Fuzzy Arithmetic: Theory and Applications, Van Nostrand Reinhold, pp. 229-243, 1988.
[Google Scholar]
[59] Abed Saif Ahmed Alghawli et al., “Application of the Fuzzy Delphi Method to Identify and Prioritize the Social-Health Family Disintegration Indicators in Yemen,” International Journal of Advanced Computer Science and Applications, vol. 13, no. 5, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[60] Stanislav Birko, Edward S. Dove, and Vural Özdemir, “Evaluation of Nine Consensus Indices in Delphi Foresight Research and their Dependency on Delphi Survey Characteristics: A Simulation Study and Debate on Delphi Design and Interpretation,” PLOS ONE, vol. 10, no. 8, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[61] Norshimar Akmar Hashim et al., “The Element of Teaching Strategy in English Listening Skills for Preschool: Fuzzy Delphi Technique Approach,” International Journal of Academic Research in Business and Social Sciences, vol. 10, no. 7, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[62] Alhamzah Alnoor et al., “A Fuzzy Delphi Analytic Job Demands-Resources Model to Rank Factors Influencing Open Innovation,” Transnational Corporations Review, vol. 14, no. 2, pp. 178-192, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[63] Khai Wah Khaw et al., “Modelling and Evaluating Trust in Mobile Commerce: A Hybrid Three Stage Fuzzy Delphi, Structural Equation Modeling, and Neural Network Approach,” International Journal of Human-Computer Interaction, vol. 38, no. 16, pp. 1529-1545, 2022.
[CrossRef] [Google Scholar] [Publisher Link]