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Table of Contents
Aim..
Objectives.
Sources of data.
Methods.
Time-frame.
Review of the scientific literature.
References.
Aim of the research is to analyse the importance of IoT or Internet of Things to fulfil the needs of the modern business ecosystem.
Existing dataset will be used to collect secondary information for analysing the significance of IoT in the 21st business context. For this purpose, different scientific literatures will be reviewed. Alongside, primary data will be collected from the employees and managers of different IoT companies situated in London, UK. Questionnaire will be used to collect primary quantitative data from the employees through online survey and primary qualitative data will be acquired through online interview.
Deductive approach will be utilised to collect and analyse research data on the basis of research objectives and questions. The data will be compared with the existing literature, concepts and theories related to the importance of IoT. On the other hand, descriptive research design will be used to scientifically observe and evaluate the usage of IoT in the business operations from scientific literature as well as primary data sources to analyse the behaviour of IoT in organisations. The equipment that will be used to collect primary data will be close-ended questionnaires for survey and open-ended questionnaires for interviews and MS Excel will be used to analyse research data.
IoT usage in business
IoT or Internet of Things is used by businesses to record and transfer data for monitoring the business operations. It is effective to make more informed decisions that can boost efficiency. In recent times, 30% of the business organisations depend on IoT devices to take new strategies. It is expected that the IoT market that includes software, hardware, telecom and system integration services can face a growth to $520 billion by 2021 (Lee, 2019). Investment on IoT has been $235 billion spent in 2018 across the world. IoT is used in track maintenance, analyse business insight and customer experience and create new business models through data monitoring.
Significance and challenges of IoT
IoT is important for the businesses to analyse the customer data and determine connected equipment in manufacturing, supply chain and other operations which is necessary for demand forecasting and inventory management (Hakanen and Rajala, 2018). It can increase productivity and efficiency and as per a report, the business has gained $154 million of revenue through industrial IoT. Tracking of the materials in the supply chain becomes easy and distribution becomes error-free that can boost customer attraction and satisfaction. Real-time data management can reduce waste and extra cost. However, implementation of IoT is a business that requires huge investment and skilled employees are required due to its high complexity that can become a challenge for the business (Ju et al., 2016).
Hakanen, E. and Rajala, R., 2018. Material intelligence as a driver for value creation in IoT-enabled business ecosystems. Journal of Business & Industrial Marketing.
Ju, J., Kim, M.S. and Ahn, J.H., 2016. Prototyping business models for IoT service. Procedia Computer Science, 91, pp.882-890.
Lee, I., 2019. The Internet of Things for enterprises: An ecosystem, architecture, and IoT service business model. Internet of Things, 7, p.100078.
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