Summarisation of the findings

IoT Application development depends on a lot of aspects and the cost of development for these applications have been also influenced by this. There are different available aspects why the cost of different IoT commodities differs due to the business cost metrics. The cost metrics of IoT commodities in business refers to the different quantifiable variations of the cost of the different IoT based commodities (Smart 2017). The variations of cost make it easier to assess the success and failure of the business. The study of the entire IoT cost metrics would make a strategic approach towards understanding the influence behind the price of IoT products.

The entire study pricing scheme plan that has been deduced keeping in mind about the principles of IoT, the architecture of the IoT infrastructure and the business model in which the data is managed in IoT infrastructure, forms the base of the understanding to plan the pricing for the IoT applications and devices. Findings have been conducted to find out the IoT architecture and how the IoT architecture contributes to the pricing of the IoT devices and other IoT based installations (Abbate et al.  2018). The findings have stated that the IoT architecture has a layered dependency when it comes to scale a system. For every business organization, it is necessary to find out what each layer represents and adds value for a business organization. These layers are three in number and can be termed as perception layer, network layer and application layer.

The interaction between the four layers described above represents the actual process of how the architecture of an IoT system functions. Different research paper studies have presented distinct approaches that can be utilized for Internet of Things architecture, in many of these case studies most of them agree in the three-layered structure method. In this research, the primary focus is in the physical layer and the networking layer. These two layers are the foundation of the system. The fundamentals benefits of an IoT system is to improve efficiency and user satisfaction, enhance the flexibility, security and safety, and to abroad business opportunities through the revenue stream.

The findings have also suggested that almost 75 per cent of the business world depends on the Concept Phase proof (Kumar 2018). There are different aspects in the proof of Contact Phase that affects the costing of IoT implementation. As per the findings, it has been found that the major factors that affect business prospects in IoT implementation in the contact phase are the time for the project, the overrunning of the budget, the quality of the data expertise and the entire integration of the project. All these factors work simultaneously and affect the cost of the entire IoT implementation.

It is quite a known factor that business depends on a lot of aspects and the product pricing depends on these factors as well. As per the findings, the following can be regarded as the primary reasons for the affected price of IoT applications in the business world:

Product Cost

Product Cost: This is one of the main concerns when it comes to the price of an application. The IoT applications are layered and come with a lot of sub-products that affects the accumulated cost of the final product. The product cost itself depends on a lot of aspects as well. The cost of the product available in the market are dependent on the accumulation of the fixed costs, variable costs and the semi variable cost of products that occur at different stages of production (Wortmann and Flüchter 2015). The phases during the development of the product, the distribution of the product and the selling phase of the product form the major aspects of cost effect in the product. Since, the IoT devices are layered, the substrates of all the phases affects the final product. The only phase of cost that remains unaffected are the fixed costs of the products and the additional cost affects the production, distribution and levels of sales.

Budget overrunning: Budget is always a critical factor on which the product cost depends entirely during the production phase of the product. This also determines the progress of the project and the management of the entire project. Budget overrunning is a factor that occurs within a production project when the project planning does not follow the determined project timeline. This results in the increased number of days for the completion of the project which eventually raises the budget more that the pre-determined budget (Marinakis et al. 2018). In these situations, where IoT applications are in the production phase, it is usually a critical stage because of the layered structure of the IoT applications and devices accumulate the entire cost of the final product. In addition to this, the overrunning of projects might also agitate the people in the organization, thus this factor can further delay the program further, resulting into more budget overrunning. The more the budget exceeds while developing the IoT applications, the more it affects the price of the products for the IoT applications.

Quality of data integration: Data integration is a business expertise factor that enables the data combination of the different sources so that the business performance during the IoT Application development and the sales performances could be viewed in real time. For this, however, the data needs to be integrated into information that has feasible value and can be turned into meaningful information. The data integration factor also makes sure about the entire costing of the IoT Applications (Uhl and Gollenia 2016). This is because, the quality of data integration acts as the supporting key decision making process and provides an extremely high business endeavour. The data integration quality also affects the price of the IoT application.

Demand and Utility: Price of any commodity also depends upon the demand of the product. Given the current point of time where IoT applications are being used in the market at a huge demand, the price of the commodities would also depend on this factor. The buyers in the market are willing to pay up for the IoT devices and this demand in the market is also affecting the prices of the IoT applications (Lee and Lee 2015). This is because, at every situations, where the customers are willing to buy a product from the market due to huge market demand, the organizations that have been developing the product would set the market price according to the demand in the market at which the buyers would seamlessly buy the product in exchange of finances. However, the proper market demand can be achieved through the proper analysis of the market (De Cremer, Nguyen and Simkin 2017).

Budget overrunning

Therefore, according to the findings it can be said that there are a lot of factors on which the cost price of the different IoT applications depend, but since IoT applications depend upon a layered architecture, it can be said that the device supporting the IoT applications also adds to the variations in cost price for the IoT devices (Niyato et al. 2016). The success rate of the concept of IoT has given rise to increased affect on the IoT cost metrics influencing the price of the IoT applications.

The research questions that have been framed in this regard depend on the IoT application utilization in the Smart Home systems. In the unprecedented new business system the universal consumer electronic products are dealing with right now are all connected devices (Rose, Eldridge and Chapin 2015). Mostly, these devices are connected bi directionally and have the ability to communicate within each other without the need for human interaction. The utilization of the Smart Home system in households nowadays have given rise to the use of these devices that are capable of communicating within each other without the use of human interaction. The costs of the IoT applications also are dependable on that since the IoT applications that have been used as such are dependent on the multi faceted use of different layered devices.

For example, it can be seen that the use of Occupancy sensors are pretty prevalent in the latest times. Occupancy sensors are the devices that are used to control the lightings in a room or an entire household depending on the adjustment of the temperature when the room is no longer in use (Shrouf, Ordieres and Miragliotta 2014). This system does not depend on the single device but there are many devices that make the entire system. The devices that make the entire Occupancy Sensor system are as follows:

Window Contacts: This device helps in the setback of HVAC when the window panels in a balcony or room are left open.

Heating valve: Heating valves are used for controlling the temperature of the room to be energy sufficient enough to be powered by the device.

Plug-in receiver: This device helps in the controlling and the monitoring of the consumer appliances that are currently being used. These appliances are mostly IoT devices.

Room Temperature Sensors: These devices are mostly the controllers that ensure that the appliances that are being used are consuming minimal amount of energy and providing maximum comfort.

Wall Switches: These control the lighting and shading of the entire appliances used for the lighting of the room.

This example has been portrayed to deliver the idea that just a lighting system in IoT depends upon the accumulation of a huge number of devices that works together for lighting up the entire room. Mainly, the integration of the tool with the cost metrics is to demonstrate what influences the pricing of an IoT application for others to be more cost aware during the planning of IoT architecture. The combination of such information is critical for the current growth in such market and to increase the succeed rate mentioned before. At the end, a solid and measurable evaluation can be given to others that are interested in knowing the characteristics and pricing models in an IoT application to plan accordingly (Charbonneau et al. 2017). These devices interact between each other to switch off and switch on the room lighting systems by making sure that the room is left unused. Each device is connected to each other that indicate that nobody is present in the room by measuring the temperature in the entire room and thus they switch the lights of (Perera, Jayawardena and Chen 2015)f. Likewise, when there is a presence of someone detected by the appliances, they again start interacting between each other to switch the lights back on. This is the fact due to which it can be estimated that the devices or appliances that comprise the Occupancy sensor is dependable on each other and it cannot function without each other. Therefore, if a person indicates interest in buying an automated room lighting system, he or she has to purchase the entire system comprising all of the devices (Yüksel and Sener 2017). This provides a window to the business organization who has been trying to attract customers in buying their products for automated home lighting systems. This strategy is applied by the organization allows them to sell all the dedicated devices to the customer who are planning to integrate automated home lighting system, so that the customer’s interest shift does not from any of the devices. The business organizations thus strategize their products so that the integration of the entire IoT application can be purchased by a person. This comprises one of the reasons why the IoT cost matrix influences the cost of the IoT applications.

Quality of data integration

Next, the research question frames the viability of the demand of the appliances that is growing in the market and how the cost of the appliances has been influencing with the demand of the customers. The demand of the appliances also is responsible for the price hike and empirical examples can even prove this. The latest influence of the smart speakers are right now viable within the market which at this point of time have been at a dominating stage. In the United States of America alone, one in every six American citizens owns a smart speaker. Considerably it has been found that the dominance of the smart speakers have been doubled within a period of about six months (Milosevic and Markovic 2016). Now the scenario depicts that almost 10 per cent of the American household own a smart speaker. This is just an example of the virtual assistance IoT appliances that have been dominating the market ever since they have been launched. The market is regarding the virtual assistance smart speakers to be the future of the automation done within the smart homes. The virtual assistance has the ability to not only control the smart home devices but also has the ability of controlling other home appliances as well (Pang et al. 2015). It can be seen from the market analysis that when the price of a product is decreased, it can raise the demand of the product temporarily. However, when a product is in high demand, it can be seen that the price of the product does not affect the buyers. Therefore, from the aspect of business, an organization can opt for increasing the price of a commodity or product that is extremely high in demand. This also forms the empirical example of the influence of demand for the IoT applications with the context of smart speakers. Thus, it also justifies the research question that feasible puts together the fact about how the increased demand of the IoT applications has affected the cost metrics of the products.

The specific context behind the literature review depends on the two aspects of theoretical aspects and empirical context behind the price of IoT applications that has been influenced by the cost metrics in the market (Bradley et al. 2015). The topic of discussion in this case has two approaches, one which has much more bookish context of the literature review that has been conducted before and the other has the most practical implementation of the theoretical aspect that has been presented in the literature review.

Theoretical approach: Theoretical approach behind the entire project prospect and the findings of the literature review for the affect of IoT cost metrics in the pricing of the IoT applications describe how the different aspects behind the business organizations have affected the price variations for the applications. Firstly, the price depends upon the product cost. This can be explained via geographical prospects gradually. It is a known fact that the base cost price is same for a device in every geographical situation. However, what affects the product price is the market price that is made up of the base manufacturing price and the taxes that are implied upon them based on the geographical location. The entire market price thus varies and gets affected due to the final market price in various different areas. This is an aspect of the theoretical aspect of a product price that influences the variety of market price for the IoT application products. Secondly, the demand of the product also has a theoretical aspect why the price of IoT application is affected. With increased demand, there are prospects for a business organization to implement cost according to the business needs and even for extra profit. The reason why the price hike in this aspect does not affect the demand in any way can be explained again by a theoretical approach. If a product has immense demand over the market, like the IoT applications already have, then at any means the price hike would not affect the demand. Theoretically it can also be said that if a product price is made less for a small amount of time then the entire product demand would also become more, since they are inversely proportionate to each other but that is only for a shorter period of time. For the highly demanded product like the IoT devices, it is not at all a permissive factor as in recent times or the times further, it is speculated that the product price variation would not affect the product demand in any aspect. Third and lastly, the structural architecture of a product also is responsible for the product pricing and its variations. There are products that need to be bought alone, and there are also products that need to be brought in an assembled sort comprising of various different products that helps in performing the similar tasks. This also is a factor for the IoT applications since they are mostly found in assorted and accumulated devices serving the same purpose. The theoretical approach behind this puts forward the fact that the accumulation of different assorted products also defines how the product pricing has affected the IoT application cost variations. This means that if the products were made available to buy from different sources, the assorted price would have been much higher than the cost of the accumulated products bought from the same source. The compatibility issue also forms a cost factor. For example, the Amazon Alexa cannot control the Google Home speakers. Therefore, the Amazon products have to be bought together. In the same way this factor can let Amazon implement higher prices, but that would not affect the demand, as any person buying the Amazon Alexa would automatically have to buy Amazon products for it to handle the other appliances.

Demand and Utility

Empirical approach: For the empirical approach towards this context where it has to be found by the literature review that IoT cost metrics at affecting the price of the applications based on IoT Technologies has a more practical approach. This means that empirical approach is mostly things that have been experienced in the practical world by real people. Personal experiences also present the idea of theoretical aspects to see how it actually works in the real world. Sometimes it may not be possible that the theoretical approach towards a business modulation actually has feasibility in the real world. This paragraph would put forward how the things that have been experience personally around the humankind to see the IoT cost metrics influencing the price of IoT applications (Stokes 2018). The thin line between theoretical and empirical approach towards the entire aspect of cost metrics influencing the price of the IoT application is blurred with the real life examples. One of the examples, where Amazon Alexa is considered for the empirical context, clearly states that the theoretical approaches behind the price variation is not at all affected by the empirical aspect. This means that the way by which business is handled in the recent times is not much different from what the theory taught, even if the technological approaches in business has been progressing further.

The applied strategy helps the business organizations to make sure that the encashment of the layered structure of the IoT applications is utilized well and customers are made to believe that the organization is selling all the products in an accumulated way. The theory behind this generated the demand of a customer to channelize into product pricing. When a product is heavily in demand within a certain market, it is easier for the business organizations to implement higher price for the product. This is because; as per the economics aspects are concerned, even for higher price range of a highly demanded product, the product would still be brought and there would be no change in the demand of the product due to the increased price.

For a Smart Home System, empirically putting, it can be said that the system that has been developed as a part of the plan for setting up the Smart Home System is the accumulation of various devices that would work simultaneously to integrate the home system altogether. The pricing scheme is planned according to this system which would enable any customer to make sure that the entire planning behind an automated smart home system would come under one roof to chose from and would make sure that that the entire project to enable home automated system would not opt out any device required. The scheme plan would also make sure how the customer can estimate the budget for enabling automated home system and book the services accrordingly:

Category	Smart Device	Price
Speaker	Amazon Echo (2nd Gen)	£89.99
Apple HomePod	£299
Google Home	£129
Ultimate Ears Megablast	£269.99
Home Hub	Google Home Hub	£139
Speaker	Google Home Mini	£49
Amazon Echo Show	£219.99
Sonos One	£189
Amazon Echo Dot (3rd gen)	£49.99
Google Home Max	£399
JBL Link 300	£249.99
Amazon Echo Plus (2nd gen)	£139.99
Ultimate Ears Blast	£110.70
Amazon Echo Spot	£119.99
Light Bulbs	Philips Hue	£114.99
LIFX A19	£49.99
Nanoleaf Light Panels	£179.95
Hive Active Light	£16.09
Sengled Element Classic Starter Kit	£49.99
LIFX Mini Color	£19.99
Security Camera	NetGear Arlo Q	£444.97
Hive View	£179
Netgear Arlo Go	£339
Nest Cam IQ	£269
Hive Camera	£119
Logi Circle	£141.17
Netatmo Presence	£209
Nest Cam Outdoor	£162
Thermostat	Nest Thermostat E	£205
Hive Active Heating 2	£119
Honeywell Evohome	£208.94
Tado Smart Thermostat	£59
Nest Thermostat E	£199
Ecobee3 Lite Smart Thermostat	£315.55
Vacuum Cleaning	Dyson Cyclone V10 Absolute	£449.99
Shark IF250UK	£339
Dyson V8 Absolute	£349
Gtech AirRam MK2	£199.99
Dyson Light Ball Multi Floor	£199.98
Dyson 360 Eye robot vacuum cleaner	£734.97
iRobot Roomba 980 robot vacuum cleaner	£809.99
Eufy RoboVac 11	£209.99
Neato Botvac Connected	£439.99
Shark ION Robot 750	£229.99
Shark IONFlex 2X DuoClean	£339.00
Smart Plug	Belkin WeMo Insight Smart Plug	£99.03
Eve EnElgato Eve Energy Smart Switchergy	£44.95
TP-Link HS200 Smart Wi-Fi Light Switch	£119.99
Lock	August Smart Lock Pro	£117.86
Kwikset Obsidian Smart Lock	£99.03
Yale Keyless	£109.99
Samsung SHP-DP930	£283.73
Home Hub	Wink Hub 2
Smoke Detector	Nest Protect
Total cost of Implementation	£11031.73

In the latest business era context, business and technology goes hand in hand. Just like business depends on technology, technology also depends on business for therefore, the propagation. It is business and the substrates of business elements that make a technological product spread equally through the entire market. If it is put otherwise, business is the only way for a technological product to reach the market and eventually to the customers. The customers make the products and its propagation the understandable to a business organisation in finding out if the product is going to be in demand of the customers or not (Yamaguchi et al. 2017). Based on the demand of the products, the manufacturing process and various other business aspects the price of a product or a commodity is set. For the further propagation of the technological product or any other product developed by an organisation the demand of the customers and further analysis of the market matrix is checked to make sure if the product price can vary. Empirical examples can be presented to set the ideals for finding the relevance between the findings and the real life examples. The proposed framework can be explained with littlest details that are experienced every single day. This can be presented in order to make sure that whatever the literature review previewed to be the affecting factors for and IoT application is not far different from the experiences that people have every day. For example, following would be a chart provided for the budget required for an average customer to apply smart locking system within a smart home system:

Type of Application	Home System	Average Cost (GBP)
Locking System	August Smart Lock Pro	117.86
Locking System	Kwikset Obsidian Smart Lock	99.03
Locking System	Yale Keyless	109.99
Locking System	Samsung SHP-DP930	283.73
Total Price	610.61

Implications of the research questions

                                        Table 1: Home System for Smart Locking

                                                 (Source: Created by Author)

The above table defines that when a person needs to opt for a system for locking their smart home, it is impossible that only one system would be enough for locking the entire house (Rifkin 2014). If a customer needs to lock the entire household using a smart locking system it would require that all the above products be bought together. Business organizations can put together this fact by strategizing it into tying up of several business organizations into selling these products in an accumulated way. It has also been found that this strategy is helping the price quotation for the organizations as well and the profit is shared between the different organizations. This factor also influences the price of IoT applications as it is creating a scope for business organizations to implement their business pricing techniques into a single accumulated Smart Locking system.

However, this is just the theoretical approach of a product and its price variance in the business market. Empirically speaking, the experience of a user or a group of users of a product or a device make sure about the quality and the making of the product according to the business organisation and based on that the understanding of the market and the theoretical aspects make sure about the IoT course metrics that influences the price of the IoT applications. For example, the various IoT devices that we find all around us determines the demand of the product in the market, the accumulation of the layered architecture of the device and how it can vary for its price in the market. Finally, it can be said that the measurable techniques having a solid and measureable evaluation technique can be feasibly explained to others who would be interested to plan the entire business system according to the strategy. The working of the different architectural structure of IoT products has been compelling the buyers to buy the products for including all the relevant devices rather than buying the specific product. For example, if we consider the case of the smart home speaker Amazon Alexa, it can be clearly seen that buying just the Alexa smart speakers would not suffice. The product has the subsequent additional devices that can be controlled with the virtual artificial intelligence speakers called Alexa like Amazon Echo Dot, Amazon Fire TV Stick and Amazon microphones and surround speakers. It may be possible that few of the devices can be opted out of the entire layered system, but it is not possible that these products be absolutely discarded entirely. The Alexa intelligent speaker cannot perform when it would not have any devices to control. Amazon Fire Stick on the other hand can perform on its own, however; for having a better performance with an IoT based product it can be identified that a customer would buy the entire collection of devices for setting up a smart speaker atmosphere in the Smart Home system (Chen et al. 2014). When a company applies this strategy it takes a notice of the shift of the customer’s interest form one device to the other. When a customer is looking forward to buying a home automated lighting system, the company takes a the applied strategies in question and the cost is set in such a way that the customer will not be keen on buying the appliance from assembled sources but whatever the price range may be, they would buy the entire product from the same source. Therefore, using this strategy, the organizations can opt for integrating the IoT applications and their prices from the similar source using the layered structure, which would not affect the product pricing since the customer would buy the entire layered structure for the application at one go.

Conclusion:

Therefore, in conclusion it can be said that the IoT cost metrics depend upon the various aspects of business including the structural architecture of the IoT applications as well. This has been deduced from analysing the different kind of IoT applications that are currently available in the market and that are running the business prospects of various organizations. This deduction is based on the analysis performed on the theoretical and empirical aspects of the situation as well. From these analyses, the conclusion is thus reached. Findings have been conducted to find out the IoT architecture and how the IoT architecture contributes to the pricing of the IoT devices and other IoT based installations. The findings have stated that the IoT architecture has a layered dependency when it comes to scale a system. For every business organization, it is necessary to find out what each layer represents and adds value for a business organization. The IoT applications are layered and come with a lot of sub-products that affects the accumulated cost of the final product. The cost of product depends on the different aspects of business within the market. The different aspects that are available within the market depend mostly on the variable accumulation comprising of the fixed cost, the semi variable cost and the variable costs as well. These stages creep in at the various stages of manufacturing process of a product. However, given the analysis of the above reports, the most important of all these factors are the budget of the manufacturing of the product, which happens to be and extremely critical factor behind the cost of a product. The budget of a product depends on the project progression and they way by which the entire manufacturing program is conducted along. When a pre defined product timeline is not followed, the project is seen to be going beyond the fixed budget because of the timeline overrunning. Budget overrunning and scheduled timeline overrunning are directly proportional to each other. The increased number of days to complete the project is thus raising the budget much more than the scheduled planned budget. The cost of the IoT applications also are affected by the data integration factor as analyses have proved. This is because, the quality of data integration acts as the supporting key decision making process and provides an extremely high business endeavour. The data integration quality also affects the price of the IoT application. Price of any commodity also depends upon the demand of the product. Given the current point of time where IoT applications are being used in the market at a huge demand, the price of the commodities would also depend on this factor. The buyers in the market are willing to pay up for the IoT devices and this demand in the market is also affecting the prices of the IoT applications.

All these factors prove the base of the research, which clearly deduces the fact that IoT cost metrics and the various aspects of business from the theoretical and business approach has influenced the price variations for the IoT applications.

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