The goal of the thesis is to provide investors and established businesses insights into the evolving concept of Internet of Things in the context of a business opportunity. First, the thesis provides comprehensive overview of the IoT concept, its historical development and relevant concepts similar to IoT including its definition and explanation. Second, the thesis discusses IoT as a disruptive technology with implications for general business strategy, current business models, value chains and competitive landscape. Third, it describes overwhelming opportunities for IoT application in various business fields and processes bringing added value to its stakeholders. Visionary concepts and applicable use cases are identified. Finally, the thesis analyses IoT market perception from both customer and business perspective based on quantitative and qualitative data researched. The research is focused mainly on customer awareness and value perception of IoT products as well as major drivers and challenges of the IoT market from business players' perspective. Such analytical insights identify major patterns and dynamism of the IoT market.

Future 450mm semiconductor wafer foundries are expected to produce billions of low cost, leading-edge processors, memories, and wireless sensors for Internet of Everything applications in smart cities, smart grids, and smart infrastructures. The problem has been a lack of wise investment decision making using traditional semiconductor industry models. The purpose of this study was to design decision-making models to conserve financial resources from conception to commercialization using real options to optimize production capacity, to defer an investment, and to abandon the project. The study consisted of 4 research questions that compared net present value from real option closed-form equations and binomial lattice models using the Black-Scholes option pricing theory. Three had focused on sensitivity parameters. Moore's second law was applied to find the total foundry cost. Data were collected using snowball sampling and face-to-face surveys. Original survey data from 46 Americans in the U.S.A. were compared to 46 Europeans in Germany. Data were analyzed with a paired-difference test and the Box-Behnken design was employed to create prediction models to support each hypothesis. Data from the real option models and survey findings indicate American 450mm foundries will likely capture greater value and will choose the differentiation strategy to produce premium chips, whereas higher capacity, cost leadership European foundries will produce commodity chips. Positive social change and global quality of life improvements are expected to occur by 2020 when semiconductors will be needed for the $14 trillion Internet of Everything market to create safe self-driving vehicles, autonomous robots, smart homes, novel medical electronics, wearable computers with streaming augmented reality information, and digital wallets for cashless societies.

The introduction of Physical Unclonable Functions (PUFs) and lightweight consensus algorithms to aid in the bolstering of security and privacy in both IoT and IoE does show a great deal of promise not only in these areas, but in resource cost over traditional methods of blockchain.  However, several previous studies make claims regarding performance of novel solutions without providing detailed information as to the physical components of their experiments.  This comparative study shows that Proof of Authentication (PoAh) performs the best out of three selected consensus algorithms and that the claims made regarding the performance of PUFChain and Proof of PUF-enabled Authentication (PoP) could not be replicated in this instance.