The smartphone industry is one of the most viable sectors that was valued at $714.9 billion and 2019 and it is expected to reach around $1351.8 billion by 2025 (O’Dea, 2020). This forecast is advised in part by increased consumer spending which has in turn driven sales volume for smartphone makers. However, there is a possibility that the growth market may plateau owing to intense penetration levels and a lengthening replacement cycle. A focus on the smartphone industry brings into the fore the profitability variables associated with this economic sector.
Background
The smartphone industry’s six-digit NAICS code is 334220: Radio and Television Broadcasting and Wireless Communications Equipment Manufacturing. The data that will be used in the analysis will be drawn from credible and reliable sources which include reputable websites such as statistica.com and peer-reviewed articles. The smartphone industry is concerned with the manufacture and sale of hardware such as chargers, wearables, and audio accessories, and the provision of services such as cloud storage, insurance, and repairs (Richter, 2019). The history of the smartphone industry dates back to 1996 with the introduction of Nokia’s 9000 Communicator, which ran on GEOS 3.0 and a graphical web browser and a QWERTY keyboard. In 1999, Ericsson launched R380 the first device that was marketed as a smartphone with a Symbian OS (Dedrick & Kraemer,2017). Fast forward, there have been great improvements in smartphones with enhanced storage, fast operating systems, increased functionalities, features that will be used to enhance smartphones in the future. These features have created a highly competitive industry, which has in turn enhanced the availability and affordability of smartphones around the world.
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Purpose
This study aims at describing the smartphone industry’s conduct, structure, performance, factors that determine its ability to cater to local and foreign markets. The study will also focus on independent variables such as the potential for entry, pricing, demand, and technology as they relate to the industry. This analysis would be crucial in determining the profitability of the smartphone industry.
Data Collection
The study will use data from previous statements on the sales trends over time, which indicates the potential that lies within this industry. Data on smartphone sales in the United States from 2007 to 2019 (in million units) is available. This information will be used to analyze this data as well as determine the smartphone industry’s profitability and growth.
Theoretical Framework
A theoretical framework is crucial in explaining the structure of the smartphone industry based on both the independent and dependent variables. The industry variables are linked with the number of smartphones that are sold during the period that will be analyzed in the study. The number of units that are produced is determined by the demand trends in the global market. A higher demand, which is fuelled in part by the smartphone functionalities, advised mass production, and sale (Lim, Teo & Yang, 2020). In the same way, smartphones with better functionalities attract high demand which translates to increase sales volumes and in turn generation of more revenue. the independent variables that will be included in the framework are technology, CR4, market conditions, demand, and potential for entry.
Concentration Ratio
Concentration ratio indicates the proportion that firms occupy in the market while compared to the industry to which they belong. A lower concentration ratio indicates greater completion among the firms in the specific industry while a 100% contraction ratio is indicative of a monopolistic market structure. The smartphone industry is an oligopoly that revolves around Samsung, Apple, Lenovo, LG Electronics, and Huawei taking about 60 percent of the market share ( Park & Kim, 2020). The remaining 40% goes to other smartphone manufacturers making this industry highly competitive.
Technology
Technology plays a crucial role in the manufacture of smartphones and accessories. Artificial intelligence has become the backbone and mainstream for many groundbreaking applications in the smartphone industry. Artificial intelligence goes beyond most applications with Samsung, Huawei, and Apple introducing smartphones containing powerful chips capable of performing 5 trillion operations within a second (Sarker et al., 2020). The incorporation of artificial intelligence technology in the manufacture of smartphones would accelerate sales since customers need high performing gadgets. The industry will benefit from e-commerce, which allows clients to place orders, which further accelerates the revenue that is generated by this industry. In this case, one can conclude that technology is a significant variable that would enhance profitability in this industry.
Demand and Market Conditions
The market conditions are favorable for the smartphone industry considering that clients are always on the lookout for high-functioning gadgets. Lee & Calugar-Pop (2019) note that the smartphone industry is now at an inflection point considering ownership rates are high and are approaching the ceiling. However, the industry still has a potential for growth considering that the smartphone is an integral device due to its ever-expanding array of applications. According to O’Dea (2020), global shipments would be around 1.48 billion units allowing 44.9 percent of people to own a smartphone. The projection points to higher demand and improves market conditions as clients seek to have devices with better functionalities.
Potential for Entry
The smartphone industry is highly competitive meaning that the manufactures must constantly come with effective strategies to maintain significant market share. New entrants to this industry would find it very hard to cut a niche considering that the existing manufacturers are established (Park & Kim, 2020). Moreover, there are numerous barriers to entry revolve around economies of scale, capital intensive production, research development, and the ability to generate and maintain brand loyalty. However, a new entrant who manages to design high-functioning and affordable smartphones and succeed in advertising them would thrive in the industry.
Pricing Behavior
The smartphone industry players have varied pricing strategies and structure something that is based on the device's functionalities. Samsung, Apple, and Google base their pricing on earning competitive advantage making the smartphones to be quite expensive averaging at about $1000 which is too high for most people. It is for this reason that these companies are revising their pricing strategies by launching cheaper versions, which lack the features of the standard smartphones. Other companies base their prices on the cooperative strategy, which allows them to maintain competitive prices. The variations in pricing behaviors in this industry mean that clients are in a position to determine which smartphones they acquire based on how much they are willing to spend.
Integration
The smartphone industry has integrated robotic process automation and assemblage to enhance operational efficiency. Naveen et al (2019) note that the installation of robotic process automation allows companies to manufacture goods in high quantity, at faster rates, and lowered costs. More so, the industry has invested in assembly lines to bring together different components to enhance uniformity. The components are usually sourced from different suppliers where they go through several production lines before they are assembled and supplied around the world.
Research and Development
The smartphone industry is quite dynamic considering that clients are always looking for improved devices that could help them to improve their operations. It is for this reason that the industry spends a significant proportion of its revenue on research and development to meet this need. Moreover, the industry players engage in research and development to come up with practical strategies that reduce operational costs while increasing efficiency (Lim, Teo & Yang, 2020). Currently, industry players are spending significant revenue in researching the 5G network to improve speeds thus improving remote execution and better connectivity.
Research Analysis Profitability
Production capability is closely related to profitability considering that demand is what informs companies to engage in large-scale manufacturing. High production rates correlate with high revenue generation and in turn productivity. The data collected on the sale of smartphones in the US from 2007 to 2019 (in million units demonstrates an upward trend. However, in the last four years, the demand seems to be plateauing as the demand for smartphones slows.
The following table depicts sales trends:
| Year | Sales (Million units) |
| 2007 | 122.58 |
| 2008 | 138.29 |
| 2009 | 172.38 |
| 2010 | 296.65 |
| 2011 | 472 |
| 2012 | 680.11 |
| 2013 | 969.72 |
| 2014 | 1244.74 |
| 2015 | 1423.9 |
| 2016 | 1495.96 |
| 2017 | 1536.34 |
| 2018 | 1556.27 |
| 2019 | 1524.84 |
Table 1: Sales Volume (Statista, 2020).
Based on the table and the graph it is evident that there was a high demand for smartphones in the US from 2007 to 2015. The graph depicts a sharp rise in demand as clients established that smartphones provided a better communication experience. From the graph, it is clear that in 2010 the demand for smartphones had doubled to 296.65 million units from 122.58 million units in 2010. The demand again doubled in 2012 with the sale of 680.11 million units and in 2015 with a sale of 1423.9 million units. From 2016, the sales volume appears to have plateaued and remain slightly above 1495.96 million units with the highest being 1556.27 million units. In 2019, the sales volume was slightly lower at 1524.84 units, which is a slight drop. There is a likelihood that there could be another drop since clients may not be replacing the devices they have soon. However, the industry could experience an increase in sales volume, if there are devices that appeal to the clients.
Conclusion
The smartphone industry has been showing potential for growth since the manufacture of the first device back in 1995. Smartphones have brought a revolution on how people communicate shop, have fun, and conduct their daily activities. The manufacture of smartphones with high functioning features has accelerated demand and revenues by the various manufacturers. However, there is a likelihood that this industry may have plateaued since most people own smartphones. Demand is driven by clients who are looking for advanced smartphones, meaning that the manufactures should direct their efforts in improving smartphone functionalities to remain relevant and profitable.
References
Dedrick, J., Kraemer, K. L. (2017). Intangible assets and value capture in global value chains: The smartphone industry . World Intellectual Property Organization. https://www.wipo.int/edocs/pubdocs/en/wipo_pub_econstat_wp_41.pdf
Lee, P., & Calugar-Pop. (2019). Global mobile consumer survey: the UK cut plateauing at the peak. https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/technology-media-telecommunications/deloitte-uk-plateauing-at-the-peak-the-state-of-the-smartphone.pdf
Lim, K. G. J., Teo, P. C., & Yang, L. Z. (2020). The impact of innovation on competitiveness in the smartphone industry in China. In 8th International Conference of Entrepreneurship and Business Management Untar (pp. 174-176). Atlantis Press.
Naveen, R. K., Harichandana, U., Alekhya, T., & Rajesh, S. M. (2019). A study of robotic process automation among artificial intelligence. International Journal of Scientific and Research Publications , 9 (2),392-397. DOI: 10.29322/IJSRP.9.02.2019.p8651
O’Dea, S. (2020, October 26). Smartphones - Statistics & facts . Statista. https://www.statista.com/topics/840/smartphones/
Park, B. J., & Kim, D. (2020). Competition dynamics between giant entrants and incumbents in a new convergent segment: a case in the smartphone industry. Asian Journal of Technology Innovation, 4 (3), 1-22. https://doi.org/10.1080/19761597.2020.1818109
Richter, F. (2019, December 10). The trillion-dollar smartphone economy . Statistica. https://www.statista.com/chart/20258/estimated-sales-of-smartphones-and-related-products-and-services/
Sarker, I. H., Hoque, M. M., Uddin, M. K.,&Alsanoosy, T. (2020). Mobile data science and intelligent apps: concepts, AI-based modeling, and research directions. Mobile Networks and Applications, 11 (4), 23-42. https://doi.org/10.1007/s11036-020-01650-z
