Eco-Fone Report

ECO-FONE REPORT

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Eco-Fone Report

Introduction

The use of smartphones has tremendously increased with notable changes from 2012 where every age group could be defined by the different gargets. With the increase in the use of smartphones, several businesses also popped up to utilize the new market niche. Governments have been involved in giving policies on the use of smartphones and different articles, such as the Deloitte report, have been done to check on the gradual progress and consumer reports on the use of smartphones. It is according to such reports that businesses get the nuggets and wisdom to start and manage their businesses. Eco-Fone is among the many smartphone businesses that see the need to transform society and keep the pace of growth with the provision of phones. The company wishes to achieve business growth and expansion and perhaps come in touch with profits from its activities. Using Deloitte’s report, the company wishes to come up with strategies to ensure that its goals are met. This report shall focus on some of the ways in which Eco-Fone can be used for its expansion and realize full returns.

Overview of the Mobile Phone Market in the UK

The use of smartphones in the UK has tremendously increased where adults, between 18-75 years, are the main users. Statistics show that among adults, about 77% use smartphones in their everyday activities whereas about 85% possess smartphones (Wilhelm et al., 2015). The 85% owners of smartphones, statistics also indicate that 91% of them use smartphones. Alongside smartphones, penetration of other devices such as tablets and laptops has penetrated the technology market in the UK between 2012 and 2017 (Bardus et al., 2015). However, it is worth knowing that laptops and smartphones have greatly been used in the UK in the years 2016 and 2017. The least utilized gadgets are tablets. UK’s workforce consists of about 33.5 million individuals but 32 million of the workforce is directly involved at work. The workers use their smartphones for different purposes but the highest number of the workers use their phones for emailing, 44%, calendar management, 23%, viewing documents, 26%, and voice calls, 34% (Wilhelm et al., 2015). According to the activities, the following mixed bar graph can be used to represent the information

Summary of Daloitte’s Report

Penetration of smartphones into the technology market has been consistent since 2012. The trend has been an upward mark starting with 52% market dominance in 2012 and ending up with 85% market dominance. The scatter plot below shows the trend from 2012 to 2017

According to the scatterplot, it is worth noting that the increase in smartphone penetration has been consistent. This can be demonstrated by having R2 value of 0.972 which proves that the linear model has a strong fit with very few points as outliers. Using the trend line, the future market penetration can be established using the linear model;

            y = 6.143x – 13052

However, the future trends are not best forecasted by the trend because the percentages are not stagnant or have a common factor they increase with (Choi, 2018). Furthermore, the x-axis variable is the years which is a fixed variable and hence cannot be directly used in the calculation of the future market penetration of smartphones for the years 2018 and 2019 (Choi, 2018). The best forecast model can be established through the same method but having the penetration not in percentages but the exact figures of market penetration and the years vividly explained in terms of the numbers not specific bracket of years as 2017 by 5 years or 3 years (Berenguer et al., 2017). In this manner, the scatter plot can obtain a correct forecast model as shown below (example)

According to the figure above (which uses hypothetical values of number of phones), shows the exact number of smartphones that penetrated the market but not the percentages. The scatterplot gives the forecast model as,

            y = 2857.1x + 8333.3

Therefore, in 2018, after 7 years, the number of smartphones in the market shall be

            y = 2857.1x + 8333.3

            y = 2857.1 (7) + 8333.3

            y = 19999.7 + 8333.3

            y = 28333

Hence, it can be deduced that in 2018, there will be 28333 smartphones that have penetrated the UK technological market. A similar calculation can be done for the proceeding years.

Smartphones and Older Customers

According to a BBC article on the progress made on smartphones among old customers, it is evident that smartphones pose as great assets in doing a lot of things for old customers (Hui, 2016). According to the BBC article, the smartphone market boomed since about 70% of old customers, those between 55 and 75 years, are in possession of app-capable handsets (Kim et al., 2016. The 55-75 age groups, however, tend to have less utility of smartphones compared to the younger age groups of between 18 and 50. The findings according to the article’s research indicate that in 15 minutes, 20% the old customers keep checking their phones which is a point to reckon against the national average of 56% (Cetin., 2016). Among the 55-75 age groups, half of them have Facebook installed in their handsets which is almost a similar ratio against the adult figure of 70% (Hui, 2016). The study focused on a sample size of 1163 individuals who genuinely responded to the research questions.  The old customers may have been driven towards buying the gadgets because some of their activities are greatly anchored on the smartphone’s applications (Kim et al., 2016. The research put forth that quite a good number of parking meters are associated with payment through the phone.

Smartphones have specific applications that give the best convenience in terms of payments on parking meters (Hui, 2016). With such a characteristic, the old customers consider having smartphones. Some of the respondents focused their arguments on the fact that some services in the cities cannot be offered without the use of smartphone apps (Kim et al., 2016. This can be seen in the taxi industry which cannot be met without the use of smartphone apps.

The research equally noted that the modeling of smartphones is done to favor the old customers hence the favors are drawn to them (Botzer et al., 2017). The handset’s screens are made bigger hence they can be easily be assessed by the old whose eye sights are not in good condition. Smartphones are also made of good speakers that are loud and do not affect the ears (Botzer et al., 2017). In phone locking, some of the Android operators have included varied mechanisms that favor the old generation. In Samsung phones and perhaps Apple phones, facial recognition is among the major advancements that are greatly utilized by old customers (Lai et al., 2018). The older generation would prefer picking up a phone and glancing at it as an authentication mechanism rather than fiddling through and putting their glasses on for them to have their passwords on.

Possibility of Expansion to Kingston

The growth of a business or rather the opening of branches in other areas requires the examination of pros and cons (Kim et al., 2015). Eco-Fone, with its interest in opening another shop in Kingston, needs to evaluate the pros and cons. In order to do so, the company should list the possible pros and cons and gauge their results as shown in the table below.

            According to the table, the pros of starting a business across the border to deal in smartphones at Kingston include increased stability for the general industry, increased profits since the industry shall be reaching more and more customers, more innovation activities, competition, and ventures into new markets, having new people who may pose as best employees than never before and improved market demand response (Kim et al., 2015). Alongside the pros are the cons which will pull back the prowess of the business should it be erected (Khedekar et al., 2017). It is worth noting that the cons counteract the pros but quite often, the business is likely to lose direct control of the operations in the new business alongside the parent business, and the quality may drop since the business has to keep the demand and supply at par, there will be an increased cost of production and transportation in the business (Khedekar et al., 2017). Establishing the decision to set up a business at Kingston, the average of both the cons and the pros were analyzed and the best fit was checked (Verma et al., 20018). According to the table, it was noted that the pros averaged 7.4 which was higher than the cons which averaged 6.4. The business should consider setting up another operation across the border at Kingston.

Feasibility Calculations

Given that the company will own the building, they will champion having a repayment mortgage at about 350000 euros, the Excel workout can hence be derived.

Time – 15 years

Mortgage – 350000 euros

Interest rate – 7%

The Excel workout is shown below;

Despite the UK having several mortgage companies, some outstanding companies operate across the border (Verma et al., 2018). A prominent mortgage company in both the UK and Hong Kong is HSBC which is the Hong Kong and Shangai Banking Corporation which has its headquarters in London. The mortgage company has the following logo.

The operation of Eco-Fone is facilitated by two retail shops. The success of the two shops can be compared to check if their returns are similar. The following pieces of information were provided by the company about the two retail shops.

Retail shop A

Sample = 40

Mean = €100

Standard Deviation = €20

Retail Shop B

Sample = 40

Mean = €90

Standard deviation = €40

Significance level = 0.05

Finding out if the net takings of the retail shops are the same, their means have to be compared.

Hypothesis

H0: µ1 = µ2

Ha: µ1 ≠ µ2

Using a p-value calculator, the following results are obtained

According to the results displayed in the table, the p-value is 0.1613 which is way above the alpha level, 0.05, used in the calculation. In relation to the hypothesis, since the p-value is greater than the alpha level, the null hypothesis is rejected hence it can be deduced that the net takings of the retail shops are not the same.  

Customer Questionnaire Results

Periodic questionnaires aid the company in knowing the progress of the company and hence could make adjustments or rather improvements and maintenance where needed. According to the questionnaire, the major four questions, the business focuses on the price/value, quality of services/products, customer support/service, and sales staff. The customers were expected to make a tick mark where they felt the performance was poor (1), excellent (4), Fair (2), and good (3). The results obtained were summarized and the averages were calculated. The averages are as shown below.

According to the averages obtained from the calculation notable deductions can be made. It is worth noting that from the questionnaire, 4 represented Excellent, 3 represented Good, and 2 represented Fair while 1 represented Poor. The averages indicate that none of the services were poor since there is no 1. Customer service has the worst performance which can be translated to fair, according to the questionnaire key. However, the price and quality of products are averagely good according to customer’s remarks. The best-performing factor in the business is the sales staff which is less excellent but more good.

Poisson Distribution Formula

Given that the company, Eco-Fone, utilizes about 10000 invoices in a month, then quality procedures have to be followed to check on the discrepancies (Gu, Zhu, and Nie, 2017). During the sending of 10000 invoices, an average of 2 invoices were returned in the month with an error. With an aim of having the probabilities of returned invoices to be less than 15%, then the company should the Poisson distribution formula in the calculation since the time intervals of the methods are discrete and have disjoint regions (Gu et al., 2017). The business can utilize the Poisson distribution formula to reduce or rather eradicate the errors that may be encountered in sending or receiving invoices.  

                                                          Summary of the Report

The report gives the proceedings that can be adopted by the business to influence its performance. The reports begin by giving a summary of market trends of smartphones in the UK which gives some of the unexploited regions and positions in the phone industry. Since quite several smartphone businesses are worthy competitors, the report gives the possibility of the business considering older customers as the rest of the competitors focus on the youthful ages. There are calculations on the feasibility of the business in terms of approvals from mortgage institutions and also the chances of having another outlet across the border, in Kingston. The success of the business is also based on customer feedback which is examined by the questionnaire. Possible decisions that can be made in the company include setting up another outlet in Kingston. Looking at the results obtained from the ‘pros and cons’ findings, the business will be feasible at Kingston, where a new market and increased profits shall be realized. Another decision fit to be adopted by the business is the Poisson distribution formula for the calculation of probabilities. The probability that will be involved in the business shall involve discrete time which is a focus of the formula for calculation errors in the company. Whenever errors are calculated, they can easily be eliminated or reduced for maximum production.  

Reference List

Bardus, M., Smith, J.R., Samaha, L. and Abraham, C., 2015. Mobile phone and web 2.0 technologies for weight management: a systematic scoping review. Journal of medical Internet research, 17(11), p.e259.

Berenguer, A., Goncalves, J., Hosio, S., Ferreira, D., Anagnostopoulos, T. and Kostakos, V., 2017. Are Smartphones Ubiquitous?: An in-depth survey of smartphone adoption by seniors. IEEE Consumer Electronics Magazine, 6(1), pp.104-110.

Botzer, A., Musicant, O. and Perry, A., 2017. Driver behavior with a smartphone collision warning application–a field study. Safety Science, 91, pp.361-372.

Cetin, M., Ustun, I., Nadeem, T., Nguyen, D. and Rakha, H.A., 2016. Smartphone-based solutions to monitor and reduce fuel consumption and CO2 footprint (No. N16-01). TranLIVE. University of Idaho.

Choi, S., 2018. What promotes smartphone-based mobile commerce? Mobile-specific and self-service characteristics. Internet Research, 28(1), pp.105-122.

Gu, J., Zhu, X. and Nie, K., 2017, May. Modeling Study on the Hazardous Effects of Battlefield Chemical Attack. In 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017). Atlantis Press

Hui, K.Y., 2016. Determinants of Smartphone Adoption among Older Adults in Malaysia (Doctoral dissertation, UTAR).

Khedekar, D.C., Truco, A.C., Oteyza, D.A. and Huertas, G.F., 2017. Home Automation—A Fast‐Expanding Market. Thunderbird International Business Review, 59(1), pp.79-91.

Kim, M., Chang, Y., Park, M.C. and Lee, J., 2015. The effects of service interactivity on the satisfaction and loyalty of smartphone users. Telematics and Informatics, 32(4), pp.949-960.

Kim, M.K., Wong, S.F., Chang, Y. and Park, J.H., 2016. Determinants of customer loyalty in the Korean smartphone market: Moderating effects of usage characteristics. Telematics and Informatics, 33(4), pp.936-949.

Lai, X., Zhang, Q., Chen, Q., Huang, Y., Mao, N. and Liu, J., 2018. The analytics of product-design requirements using dynamic internet data: application to the Chinese smartphone market. International Journal of Production Research, pp.1-25.

Verma, S.C., Sharma, P.L., Chandel, R.S. and Negi, S., 2018. Spatial distribution of green peach aphid, Myzus persicae Sulzer, and its parasitoid, Aphelinus asychis Walker in bell pepper under polyhouse conditions.

Wilhelm, M., Hutchins, M., Mars, C. and Benoit-Norris, C., 2015. An overview of social impacts and their corresponding improvement implications: a mobile phone case study. Journal of Cleaner Production, 102, pp.302-315.

Appendix

Excel formula for PMT

Questionnaire Results