THE ANALYSIS OF CHINESE CUSTOMER

SATISFACTION TOWARD IPHONE

(A CASE STUDY IN CHINA)

By

Lian Qiaolei (Andy)

ID No. 004201100053

A Thesis presented to the

Faculty of Engineering President University in Partial

fulfillment of the requirements of Bachelor Degree in

Engineering major in Industrial Engineering

2015

ABSTRACT

Industrial engineering is concerned with the design, improvement and installation

of integrated systems of people, materials, information, equipment and energy. It

draws upon specialized knowledge and skill in the mathematical, physical, and

social sciences together with the principles and methods of engineering analysis

and design, to specify, predict, and evaluate the results to be obtained from such

systems. If they want to design or improve the product, they have to get the

feedback from customer to know how the customer satisfaction is and what they

want the product to improve. So it is important and necessary to make customer

satisfaction research for Industrial Engineering. Customer satisfaction is the

comparison between performance expected by customer and actual performance

in the field. If actual performance is higher than customer expectation, then

customers feel satisfied. This research is to find customer satisfaction, the

questionnaire will be distributed in President University and the objective of this

research was to know how the Chinese customer satisfaction is towards iPhone. In

this research, there will use regression, testing hypothesis to analyze the

relationship between Product, Price, Place, Promotion and Brand and Customer

Satisfaction, and use weighted mean to find how Customer Satisfaction is. Then

the company can know Chinese customers are satisfied with the design and

operation system of iPhone, and not satisfied with the price and repair place of

iPhone.

Keywords: Marketing Mix, Product, Price, Place, Promotion, Brand, Customer

Satisfaction, Regression, Hypothesis, Weighted Mean.

CHAPTER I

INTRODUCTION

1.1 Problem Background

Industrial engineering is concerned with the design, improvement and installation

of integrated systems of people, materials, information, equipment and energy. It

draws upon specialized knowledge and skill in the mathematical, physical, and

social sciences together with the principles and methods of engineering analysis

and design, to specify, predict, and evaluate the results to be obtained from such

systems.If they want to design or improve the product, they have to get the

feedback from customer to know howthe customer satisfaction is and what they

want the product to improve. So it is important and necessary to make customer

satisfaction research for Industrial Engineering.

Apple Inc. is an American multinational corporation headquartered

in Cupertino, California, that designs, develops, and sells consumer electronics,

computer software, online services, and personal computers. Its best-known

hardware products are the Mac line of computers, the iPod media player,

the iPhone smartphone, and the iPad tablet computer. It has many online services

such as iCloud, iTunes Store, and App Store. Apple's consumer software includes

the OS X and iOS operating systems, the iTunes media browser, the Safari web

browser, and the iLife and iWork creativity and productivity suites.

IPhone is a line of smartphones designed and marketed by Apple Inc. It runs

Apple's iOS mobile operating system. The first generation iPhone was released on

June 29, 2007; the most recent iPhone models are the iPhone 6 and iPhone 6 Plus,

which were unveiled at a special event on September 9, 2014.

In Q4 2013, according to research firm IDC (International Data Corporation),

Google’s Android mobile operating system had a 78% share of all users globally.

Apple’s iOS had just 18%. Now, IDC predicts that in 2014 Android will claim

80.2% of users and only 14.8% will be on Apple’s iOS system. Mobile app

revenue is growing faster on Android than Apple, also, according. It’s the same

situation — Android growing faster — in mobile ads, according. Apple is holding

on to a sizeable chunk of the market. But Android is eating the rest. The quality of

Android phones is getting better and better, IDC says, and that offers a long-term

challenge to Apple.

In IDC’s forecast, the major growth geographies for phones are China and Asia.

That’s a problem for Apple because Android dominates China and Asia,

according to Distimo. For a long time, that was because Apple’s strategy in the

East — low distribution and high pricing — was feeble. That may be about to

change. Apple had a big launch in China with wireless carrier China Mobile in

January. Apple offers the old-model iPhone 4S in some developing countries as

an entry-level phone. Analysts are now expecting growth for Apple in China. But,

as we know, China has a different culture with West Country, and they have the

different user habit. So, how can know what are Chinese people expect? How is

Chinese people satisfaction toward iPhone?

Hence, it is very necessary and important to make a research to know how

Chinese people satisfaction toward iPhone is before they export their market in

China. By doing the research, the researcher can find what are they satisficed and

expected, then send back to company to improve the cell phone.

This research try to find customer expectation to the iPhone based on Product,

Price, Place, Promotion and Brand that will make customer satisfied.

1.2 Problem Statement

From descriptions as mentioned in the background, there are several statements

which underlie this report writing.

1. How Chinese customer satisfaction is to iPhone?

2. How does the company increase Chinese customer satisfaction?

1.3 Objectives

The main objectives of this research are:

1. To determine Chinese customer satisfaction to iPhone.

2. To analyze and find the ways to increase Chinese customer satisfaction.

1.4 Scope of Research

In this research, the scopes applied are:

This research will be conducted in China.

This research will focus on 4Ps and brand: product, price, place, promotion

and brand.

The respondents are the Chinese customers.

1.5 Limitation of Research

In relation to the limitation of the time and sources in conducting this research,

some limitations in conducting this research are:

Stipulation of respondents is only Chinese customer at that time.

The area of this research is some place of China, not all of the areas.

1.6 Assumption and Hypothesis

This research was done in China, which assumes the effectiveness of the

Marketing mix and Brand with Customer Satisfaction. The hypotheses used to

solve the problem showed as follow:

H0 There is no correlation between Marketing Mix and Brand with Customer

Satisfaction.

H1 There is a correlation between Marketing Mix and Brand with Customer

Satisfaction.

1.7 Research Outline

There are five chapters which used in this thesis, which are:

Chapter I Introduction

This chapter consists of the background of thesis, project

identification, objective, scope and assumption of the study.

Chapter II Literature Study

This chapter delivers the previous study on customer satisfaction

and 4Ps, sampling design, sampling design, validity, reliability,

factor analysis.

Chapter III Research Methodology

The steps of this thesis are explained in this chapter. Beginning

by observing the objective field, determining the problem until

the ways solve the problems is described in this chapter.

Chapter IV Data Calculation and Analysis

The data observation is processed and analyzed in this chapter.

The result of data analysis is determining what factor influence

customer satisfaction towards iPhone in President University.

Chapter V Conclusion and Recommendation

This chapter will give them conclusion result of this thesis and

also recommendation for the future research.

CHAPTER II

LITERATURE STUDY

2.1 Customer Satisfaction

Satisfaction is as a judgment following a consumption experience – it is the

consumer’s judgment that a product provided (or is providing) a pleasurable level

of consumption-related fulfillment (Oliver 1997).

Most research confirms that the confirmation or disconfirmation of

pre-consumption expectations is the essential determinant of satisfaction. This

means that customers have a certain predicted product performance in mind prior

to consumption.

During consumption, customers experience the product performance and compare

it to their expected product performance level. Satisfaction judgments are then

formed based on this comparison.

The resulting judgment is labeled positive disconfirmation if the performance is

better than expected, negative disconfirmation if it is worse than expected and

simple confirmation if it is as expected. In short, customers evaluate product

performance by comparing what they expected with what they believe they

received.

2.1.1 Definition of Customer

A customer (sometimes known as a client, buyer, or purchaser) is the recipient of

a good, service, product, or idea, obtained from a seller, vendor, or supplier for a

monetary or other valuable consideration. Customers are generally categorized

into two types:

Intermediate customer or trade customer

Customer who is a dealer that purchases goods for re-sale.

Ultimate customer

Customer who does not in turn re-sell the things bought but either passes them to

the consumer or actually is the consumer.

External customer

Customer of an organization is a customer who is not directly connected to that

organization.

Internal customer

Customer is a customer who is directly connected to an organization, and is

usually (but not necessarily) internal to the organization. Internal customers are

usually stakeholders, employees, or shareholders, but the definition also

encompasses creditors and external regulators.

2.1.2 Definition of Satisfaction

According to Kotler (1991) satisfaction is the statement level of someone

according to perceived product performance than expected. Satisfaction and

dissatisfaction is a response to consumer fulfillment, which the degree of

fulfillment causes pleasure and displeasure.

2.2 Customer Satisfaction Factors

Customer satisfaction is a combination of a customer's prepurchase expectation

and post purchase evaluation of the shopping experience. A positive experience

will result in a satisfied customer. A business benefits from satisfying its

customers through increased revenues due to customer retention and new

customers due to word-of-mouth endorsements. Customer satisfaction can be

influenced by a variety of factors. Knowing what these factors are can help your

business consistently satisfy its customers.

Quality of Service

Succeeding in this aspect of satisfaction requires employing a certain type of

employee. A business where the employees are courteous and provide customers

individualized attention is more likely to produce a satisfying shopping experience

than one that does not. Additionally, knowledgeable employees willing to provide

prompt assistance are more likely to satisfy a customer. A business must also be

able to deliver accurate and dependable service on what it sells.

Quality of the Facility

A clean, visually appealing business is more likely to satisfy a customer than one

that is not. According to a study from Australia's University of Ballarat, factors

that influence a customer's perception include: cleanliness, modern equipment,

visually appealing materials associated with the service such as brochures and

neat, clean and professional-looking employees.

Price of Product

The price is another factor that influences satisfaction. A customer is often very

concerned about whether or not the seller may take advantage of him by charging

too high of a price. This is particularly true where a buyer feels the seller is at an

advantage because he has no choice but to purchase the product. A customer that

is charged what he believes to be a fair price is more likely to be satisfied with his

shopping experience. However, too high of a price may be perceived as unfair and

cause a customer to feel exploited. You can influence a customer's perception

about the price by explaining to him what factors go into determining the price,

such as services and fees associated with the product.

Quality of Product

The quality of a product or service also influences a customer's level of

satisfaction. A customer's expectations as to the quality of a product are often

influenced by price. If a product or service is of a higher price, a customer will

expect a higher standard of performance. Whether or not the product meets the

customer's expectations will affect his level of satisfaction. A product that meets

or exceeds a customer's expectations is more likely to result in a satisfied

customer than one that does not.

2.3 Advantage of Customer Satisfaction Survey

The advantages of customer satisfaction to a business are hard to overestimate.

They may be grouped into four categories: customer retention, advertising savings,

pricing buffers, and business intelligence. These benefits are available to

managers who actively cultivate a positive customer experience.

A high degree of customer retention is usually a major goal of a company. To

implement a customer-retention program takes company-wide participation. Many

businesses spend a significant part of the marketing budget attempting to

capitalize upon the advantages of customer satisfaction. Customer retention

statistics may be difficult to obtain, and these studies may be misinterpreted.

Business experts often state that the costs to sell to an existing customer are less

than those to acquire a new customer. Established customers are already aware of

the business and does not need to change establish buying habits. Customer

service is a key cornerstone of the maturation of the new customer status to that of

an established customer.

Related Articles

Customer satisfaction surveys are a form of research in which you ask your

customers for their views on issues that indicate how well or how badly your

company is performing. Satisfaction surveys are a valuable tool for small

businesses, helping you gain a better understanding of your customers'

requirements and concerns so that you improve your products and your standards

of service in line with customers' needs. By monitoring customer satisfaction and

responding to problems, you can improve customer loyalty and protect revenue

and profitability.

Feedback

The information from a customer satisfaction survey provides your company with

valuable feedback on the issues that are important to your customer. You can

design surveys to find out how well your products meet customers’ needs or how

satisfied they are with different aspects of the service you offer. The feedback can

highlight problems that you were not aware of, giving you the opportunity to

respond and take remedial action.

Listening

A satisfaction survey provides a channel for customers to express their views. This

is important in an environment where increasing numbers of consumers share

their views and opinions on social networking sites that are outside your control.

Asking your customers for their views on your company’s products and

performance indicates that you’re prepared to listen to customers and take account

of their views.

Understanding

By sharing the results of a customer satisfaction survey with your employees, you

can build an understanding of company operations from the customers’

perspective. Employees in departments such as accounts or order processing may

not feel that their work is relevant to customer satisfaction. By including questions

in the survey such as “how satisfied are you with the accuracy of invoices” or

“how satisfied are you with the length of time taken to process orders,” you can

highlight the importance of the work of those departments and build a

customer-focused attitude.

Priorities

Analyzing the responses to a satisfaction survey highlights your company’s

strengths and weaknesses from your customers’ perspective. Focus on areas of

your business that achieve very low satisfaction scores and prioritize improvement

programs so that you can remedy any serious problems in those areas. The

improvement programs can take the form of changes to business processes or

employee training. If the survey indicates poor performance in areas such as order

processing or telephone response, you may be able to improve performance by

automating the processes using information technology. Responses that highlight

problems with employee attitudes or knowledge indicate a need for training.

Retention

Customer satisfaction levels have an impact on your ability to retain customers. If

the survey indicates low levels of satisfaction across a large number of questions,

you face the risk of customers defecting to competitors. Research firm B2B

International points out those customers’ attitudes can fall into three distinct zones:

zone of defection, zone of indifference and zone of loyalty. The zones correspond

to different levels of customer satisfaction. The higher the level of satisfaction you

can achieve, the more likely you are to retain loyal customers, something that is

extremely important for a small business, which likely has a smaller customer

pool.

Progress

A single satisfaction survey gives you a snapshot of customers’ views at a given

point of time. By conducting a number of surveys over a period of time, you can

measure the results of any improvement programs you have undertaken. Ask

customers the same set of questions in each survey and analyze the results to

assess progress.

2.4 Customer Satisfaction Measurement Technique

When we have a great food experience at a new restaurant, we usually want to go

back. Positive evaluations result in greater customer satisfaction, which leads to

customer loyalty and product repurchase.

But how do we effectively measure customer satisfaction?

Many strategies exist, but overlooking the fundaments of how to measure

customer satisfaction can be detrimental to your business. Here are 6

key customer satisfaction measurements that are critical to your business success.

1. Surveys to Measure Overall Satisfaction

This assesses your customers' experience with your product or service. It’s the

direct response to perceived quality based on the perceived needs and expectations

customers had.

Overall satisfaction can be measured through a survey conducted from your

customers after they finished the purchase process. Survey Monkey has a

comprehensive set of surveys you can use to assess your customer’s satisfaction.

Another great tool that we recommend you to experiment with is Floq, an app that

allows you to create professional looking surveys that can easily be implemented

via e-mail, link, or on your website as a pop-up.

Another survey tool commonly used is Google Forms. This free tool allows you to

easily set up surveys.

2. Objective Measurement Approach for Loyalty

Customer loyalty is an excellent mirror for customer satisfaction as it’s used to

describe the behavior of repeat customers, as well as those who offer good ratings,

reviews and testimonials. Loyalty can also be measured via a survey after the

purchase process, it is however more powerful to measure the actual behavior

than the intention.

This can be done with the Objective Measurement Approach. Recommended by

Bob Hayes in Business Broadway, this framework allows you to analysis the

historical records inside your CRM system - for example purchase scores or

online behavior - and relate them to other metrics related to your business model,

such as consistency of subscription renewals.

3. Apps for Attribution Satisfaction

One of the best ways to measure the satisfaction regarding a certain product or

feature (could be with your support service) is by providing a reasonable context

which customers can relate to. Asking your customers whether the support team

was friendly or whether they felt rushed allows you to understand how important

these elements are for the whole picture.

One popular tool to assess attribution satisfaction is Quarto a platform which

allows you to gather the answers from these questions as well as set up the linking

webpages from your website in order to make it easy for your customer’s to let

you know their review.

Another easy and interesting tool is temper an app that allows you to monitor the

customer mood, spot frustrating experiences for further development, and clearly

understands customer satisfaction regarding different pages, different products or

scenarios. It also is useful for A/B testing.

4. Measure your Exit and Abandonment Rates with Tracking Tools

A high exit or abandonment rate measured in your analytics tool is a direct

behavioral indication of customer dissatisfaction. Exits and abandonments are

natural phenomenon in ecommerce, but an unnatural high percentage indicates

that your page and process could be optimized.

It's hard to make a judgment about exactly what is wrong with your page based

solely on the numbers inside your tracking system. To get insight about the true

causes it is useful to implement a feedback tool on these pages, for example a live

chat window that pops up after a certain time.

5. Net Promoter Score

This may well be the most popular way of measuring your clients' loyalty. It

measures the likeliness of a customer referring you to someone else. The customer

is asked how likely he would recommend you on a scale from 1 to 10.

From the image above you can easily understand that assessing your NPS score is

quite easy. Take the percentage of all the respondents who are standing as

promoters of your brand and subtracts by the percentage of detractors. This is an

excellent benchmarking metric. Make sure you understand the context in which

the question is being asked, to whom and when, and try to use the opportunity to

ask those detractors what can you do to improve your service.

6. "Things gone wrong"

This is a negative measure and your goal is to minimize its score to zero points.

What you’ll be measuring with the TGW is the rate of complaints per product you

sell. In the worst possible scenario your score is 1 or higher, meaning that you get

at least 1 complaint per unit sold. TGW is calculated by dividing the number of

complaints by the total number of units sold.

However you should be careful when analyzing the results from this measure as

many people don’t autonomously complaint, they simply never buy from you

again. Therefore having a good TGW score doesn’t necessarily mean that things

are going well.

2.5 4 Ps and Brand

1. Product is the goods and services that your business provides for sale to your

target market. When developing a product you should consider quality, design,

features, packaging, customer service and any subsequent after-sales service.

A product is seen as an item that satisfies what a consumer demands. It is a

tangible good or an intangible service. Tangible products are those that have

an independent physical existence. Typical examples of mass-produced and

tangible object are motor cars and disposable razors. A less obvious but

ubiquitous mass-produced service is a computer operating system. Every

product is subject to a life-cycle including a growth phase followed by a

maturity phase and finally an eventual period of decline as sales falls.

Marketer must do careful research on how long the life cycle of the product

they are marketing is likely to be and focustheir attention on different

challenge that arise as the product move. The marketer must also consider the

product mix. Marketers can expand the current product mix by increasing a

certain product line’s depth or by increasing the number of product line.

Marketers should consider how to position the product, how to configure the

product mix so that each product complements the other. The marketer must

also consider product development strategies.

2. Price concerns the amount of money that customers must pay in order to

purchase your products. There are a number of considerations in relation to

price including price setting, discounting, credit and cash purchases as well as

credit collection.

Price is the amount a customer pays for the product. The price is very

important as it determines the company’s profit and hence, survival. Adjusting

on the price has a profound impact on the marketing strategy, and depending

on the price elasticity of the product, often it will affect the demand and sales

as well. The marketer should set a price that complements the other elements

of the marketing mix. When setting a price, the marketer must be aware of the

customer perceived value for the product. There are a lot of pricing strategies

such as: marketing skimming pricing, market penetration pricing and neutral

pricing.

3. Place is in regards to distribution, location and methods of getting the product

to the customer. This includes the location of your business, shop front,

distributors, logistics and the potential use of the internet to sell products

directly to consumers.

Companies di nit directly to consumers, but rather focus on the cultivation of

dealers and sales network established linkages between businesses and

consumers through distribute their product. Refers to providing the product at

a place which convenient for consumers to access, here are various strategies

such as intensive distribution, selective distribution, exclusive distribution and

franchising can be used by the marketer to complement the other aspects of

the marketing mix.

4. Promotion refers to the act of communicating the benefits and value of your

product to consumers. It then involves persuading general consumers to

become customers of your business using methods such as advertising, direct

marketing, personal selling and sales promotion.

Companies focus on sales behavior change to stimulate consumer to

short-term behavior (such as profit sharing, buy one get one, the marketing

and the atmosphere, etc.) contributed to the growth in consumption, to attract

consumers or lead to other brand, to boost sales ahead of consumption growth.

All the methods of communication that a marketer provides information to

different parties about the product. Promotion comprises elements such as:

advertising, public relations, sales organization and sales promotion.

Advertising covers any communication that is paid for, from cinema

commercials, radio and Internet advertisements through print media and

billboards. Public relations is where the communications is not directly paid

for and includes press releases, sponsorship deals, exhibitions, conferences,

seminars or trade fairs and events. Word-of mouth is any apparently informal

communication about the product by ordinary individuals, satisfied customer

or people specifically engaged to create word of mouth momentum. Sales staff

often plays an important role in word of mouth and public relations.

5. Brand is the name, term, design, symbol, or any other feature that identifies

one seller's product distinct from those of other sellers.

A brand is a product, service, or concept that is publicly distinguished from

other products, services, or concepts so that it can be easily communicated and

usually marketed. A brand name is the name of the distinctive product, service,

or concept. Branding is the process of creating and disseminating the brand

name. Branding can be applied to the entire corporate identity as well as to

individual product and service names. Brands are often expressed in the form

of logos, graphic representations of the brand. In computers, a recent example

of widespread brand application was the "Intel Inside" label provided to

manufacturers that use Intel's microchips. A company's brands and the public's

awareness of them is often used as a factor in evaluating a company.

Corporations sometimes hire market research firms to study public recognition

of brand names as well as attitudes toward the brands.

Relationship with Customer Satisfaction

The research is planned to analyze Chinese customer satisfaction toward iPhone

mobile phone. In this research, it will provide and give the final result objectively

and prudently.

According to topic, this research is been analyzed by making questionnaires

through the data collection of Chinese customers’ satisfaction of using iPhone.

From this statement, the Dependent Variable and Independent Variable is shown in

the chart below:

Figure 2.1 the relation between dependent variable and independent variable

Dependent Variable

Customer

Satisfaction

Product

Place

Price

Promotion

Brand

Independent Variable

2.6 Sampling Design

2.6.1 Size of Population

The effective population size(Ne) is defined as "the number of breeding

individuals in an idealized population that would show the same amount of

dispersion of allele frequencies under random genetic drift or the same amount of

inbreeding as the population under consideration." Ne is usually less than N (the

absolute population size) and this has important applications in conservation

genetics.

2.6.2 Sampling Size

Sample size is the number of observations used for calculating estimates of a

given population. For example, if we interviewed 20 random students at a given

school to see if they liked a subject, these 20 students" would be our sample size.

Sample sizes can decrease the expenses and time by allowing researchers to

estimate information about a whole population without having to survey each

member of the population.

Before any clinical studies or polls are taken, statisticians usually determine how

many individuals, or what sample size, should be sufficient for conclusive results.

Different formulas help to determine this number, represented by "n," depending

upon the type of estimator needed. The formula for calculating population size

will be described as follow:

𝛈 =𝑵

𝟏+𝑵𝒆𝟐 (2 - 1)

N= Number of population

Confidence level= 95%

e=Sampling error =5%

Sampling proportion=50%

2.7 Validity

According to Colin P. and Julie W(2006) Validity refers to how well a test

measures what it is purported to measure. While reliability is necessary, it alone is

not sufficient. For a test to be reliable, it also needs to be valid. Validity is

necessary because it can help us to determine what types of tests to use, and help

us to make sure researchers are using methods that are not only ethical, and

cost-effective, but it also is a method that truly measures the idea or construct in

question. The formula for calculating validity will be described as follow:

𝐫 =𝑵(∑ 𝒙𝒚)−(∑ 𝒙 ∑ 𝒚)

√{𝑵 ∑ 𝒙𝟐−(∑ 𝒙)𝟐

}{𝑵 ∑ 𝒚𝟐−(∑ 𝒚)𝟐

} (2 - 2)

Where:

r = Correlation number

N = total respondents

x = Data or score for each item

y = Data or score for all item

2.8 Reliability

According to Colin P. and Julie W (2006), Reliability is the degree to which an

assessment tool produces stable and consistent results. Research requires

dependable measurement. (Nunnally) Measurements are reliable to the extent

that they are repeatable and that any random influence which tends to make

measurements different from occasion to occasion or circumstance to

circumstance is a source of measurement error. (Gay) Reliability is the degree to

which a test consistently measures whatever it measures. Errors of measurement

that affect reliability are random errors and errors of measurement that affect

validity are systematic or constant errors. The formula for calculating Cronbach

Alpha will be described as follow:

𝛂 =𝑵∗�̅�

𝟏+(𝑵−𝟏)∗�̅� (2 - 3)

Where:

α = instrument reliability′s coefficient

r̅ = the average inter − ltem correlation among the item.

N = number of item

A commonly accepted rule for describing internal consistency using Cronbach's

alpha is as follows, however, a greater number of items in the test can artificially

inflate the value of alpha and a sample with a narrow range can deflate it, so this

rule should be used with caution:

Table 2.1 Internal consistency

Cronbach’s alpha Internal consistency

𝛂 ≥ 𝟎. 𝟗 Excellent (High-stakes testing)

𝟎. 𝟕 ≤ 𝛂 < 𝒐. 𝟗 Good (Low-Stakes testing)

𝟎. 𝟔 ≤ 𝛂 < 𝟎. 𝟕 Acceptable

𝟎. 𝟓 ≤ 𝛂 < 𝟎. 𝟔 Poor

𝛂 < 𝟎. 𝟓 Unacceptable

2.9 Weighted mean

Weighted Mean is an average computed by giving different weights to some of the

individual values. If all the weights are equal, then the weighted mean is the same

as the arithmetic mean. Whereas weighted means generally behave in a similar

approach to arithmetic means, they do have a few counter instinctive properties.

Data elements with a high weight contribute more to the weighted mean than do

elements with a low weight. The weights cannot be negative. Some may be zero,

but not all of them; since division by zero is not allowed. Weighted means play an

important role in the systems of data analysis, weighted differential and integral

calculus

The formula of weighted mean is:

�̅�𝑤 =∑(𝑤×𝑥)

∑ 𝑤 (2 – 4)

Where:

�̅�𝑤 = symbol for the weighted mean

W = weight assigned to each observation

∑(𝑤 × 𝑥) = sum of the weight of each element times that element

∑ 𝑤 = sum of all of the weight

The following table is the interpretation scale of the weighted mean, the basic

concept of this interpretation is that people would categorize one lower option into

higher value option when it has value more than 0.5 from the original designated

value.

Table 2.2 Scale interpretation of answer distribution

Scale Range Description

1 1.00 – 1.49 Strongly disagree

2 1.50 – 2.49 Disagree

3 2.50 – 3.49 Neutral

4 3.50 – 4.49 Agree

5 4.50 – 5.00 Strongly agree

2.10 Regression

Regression is the use of mathematical and statistical techniques to estimate one

variable from another especially by the application of regression coefficients,

regression curves, regression equations, or regression lines to empirical data.

There are some classical assumptions eligibility criteria that have to be met:

1. Normality Test

Normality tests are used to determine if a data set is well-modeled by a normal

distribution and to compute how likely it is for a random variable underlying

the data set to be normally distributed.

Normal probability plot is a graphical technique to identify substantive

departures from normality. This includes identifying outliers, skewness,

kurtosis, a need for transformations, and mixtures. Normal probability plots

are made of raw data, residuals from model fits, and estimated parameters.

2. Heteroscedasticity Test

Heteroscedasticity is a major concern in the application of regression analysis,

including theanalysis of variance, because the presence of heteroscedasticity

can invalidate statistical tests of significance that assume that the modelling

errors are uncorrelated and normally distributed and that their variances do not

vary with the effects being modelled. Similarly, in testing for differences

between sub-populations using a location test, some standard tests assume that

variances within groups are equal.

3. Multicollinearity Test

Multicollinearity is a statistical phenomenon in which two or more

predictor variables in a multiple regression model are highlycorrelated,

meaning that one can be linearly predicted from the others with a non-trivial

degree of accuracy. In this situation the coefficient estimates of the multiple

regressions may change erratically in response to small changes in the model

or the data. Multicollinearity does not reduce the predictive power or

reliability of the model as a whole, at least within the sample data themselves;

it only affects calculations regarding individual predictors. That is, a multiple

regression model with correlated predictors can indicate how well the entire

bundle of predictors predicts the outcome variable, but it may not give valid

results about any individual predictor, or about which predictors are redundant

with respect to others.

2.11 Multiple Regressions

Multiple regression analysis is used in situation where two or more independent

variables are hypothesized to affect one dependent variable. Multiple regression

analysis provides a mean of objectively assessing the degree and the character of

the relationship between independent variables and dependent variables. The

regression coefficient later used to indicate the relative importance of each of the

independent variables in the predication of the dependent variable. The model

equation is shown as follows:

Y = β0 + β1X1 + β2X2 + β3X3 + ⋯ + βnXn + e (2 – 5)

Where:

Y = Independent Variable

β0 = Constant

βi = Xi regression coefficient (i = 1, 2, 3 …. n)

Xi = Dimension score of dependent variable Xi

2.12 F Test

F-test is a statistical test that is used to determine whether two populations having

normal distribution have the same variances or standard deviation. This is an

important part of Analysis of Variance (ANOVA). However in case the population

is non normal, F test may not be used and alternate tests like Bartlett’s test may be

used. Generally the comparison of variance is done by comparing the ratio of two

variances and in case they are equal the ratio of variances are equal.The formula

will be showed as follow:

F =𝑅2

𝑘⁄

(1−𝑅2)(𝑛−𝑘−1)⁄

(2 – 6)

Where:

R = Multiple correlation coefficient

k = Number of independent variables

n = Number of sample

Hypothesis formulation:

H0 = β1 = β2 =β3 =β4 =β5= ..... = βn = 0, mean that simultaneously the independent

variables do not have significant influence on the dependent variable.

H1 =β1 ≠ β1 ≠ β1 ≠ β1 ≠ β1 ≠ …. ≠ β1 ≠ 0, mean that simultaneously the

independent variables have significant influence on the dependent variable.

Accepted Criteria:

H0 = accepted if F count < F table at α = 10%

H1 = accepted if F count > F table at α = 10%

2.13 T Test

The t-test is a statistical test that is used to determine if there is a significant

difference between the mean or average scores of two groups. The t-test

essentially does two things:

1. It determines if the means are sufficiently different from each other to say that

they belong to two distinct groups. This is done by getting the average score of

each group, and then getting the difference of the two means.

2. The T-Test also takes into account the variability in scores of the two groups.

This is called the standard error, which simply answers the question: "how far

is each score from the group mean?" If scores do not deviate far from the

mean, the standard error will be low, which is what you want. But if there is a

lot of fluctuation in the scores, you will get a high standard error.

Then, the formula can be shown as follow:

T =𝑟√𝑛−2

√1−𝑟2 (2 – 7)

Where:

T = Hypothesis testing

r = Coefficient regression

n = Number of sample

Hypothesis formulation:

H0 = β1 = β2 =β3 =β4 =β5= ..... = βn = 0, mean that partially the independent

variables do not have significant influence on the dependent variable.

H1 =β1 ≠ β1≠ β1≠ β1≠ β1≠ …. ≠ β1≠ 0, mean that partially the independent

variables have significant influence on the dependent variable.

Accepted Criteria:

H0 = accepted if F count < F table at α = 10%

H1 = accepted if F count > F table at α = 10%

2.14 Coefficient of Correlation R and Determination (R2)

Coefficient of multiple determinations defines as the proportion variation in the

dependent variable that is explained or accounted for the co variation in the

independent variables. From the calculation of R, it can be seen the relationship

between independent variable and dependent variable is positive or negative

relationship. Meanwhile determinants R2 are used to view the contribution of

independent variables in explaining the dependent variable.

CHAPTER III

RESEARCH METHDOLOGY

3.1 Framework

This chapter contains a detail description of project framework as illustrated in

Figure 3.1. These following sections will explain more explanation of the detailed

steps and methodology of the research.

Figure 3.1 Research Methodology Diagram

INITIAL OBSERVATION:

Discussion and Interview

Direct observation

PROBLEM IDENTIFICATION

Identify the problem

Defining objective, scope and

assumption

LITERATURE STUDY

Customer satisfaction

4Ps

RESEARCH METHOD

Sampling design

Questionnaire design

DATA COLLECTION

Real questionnaire

DATA CALCULATION AND ANALYSIS

Summary of questionnaire result and

analysis

CONCLUSION AND

RECOMMENDATION

Conclusion of objective answer

Recommendation improvement to

company

PROBLEM IDENTIFICATION

LITERATURE STUDY

RESEARCH METHOD

DATA COLLECTION

DATA CALCULATION AND

ANALIZE

CONCLUSION AND

RECOMENDATION

INITIAL OBSERVATION

3.2 Initial Observation

Observation is an objective conducted at the research site. Therefore study

conducted the Chinese customer who use iPhone intended to find the problem that

occurred in this research and give suggestion to Apple company.

3.3 Problem Identification

The problem identification is explaining the problem background, from the

description as mentioned in the background; identifying the problem and defining

the objective, scope and also the assumption. In this report, it is trying to analysis

the Chinese customer satisfaction towards iPhone.

3.4 Literature Study

After the problem had been identified, the next step is making a literature studies.

The literature study is aim to explain the theories, concept that will be used in the

report, to make the reader easy to understand.

3.5 Research Method

3.5.1 Sampling Design

The target population of this research is the Chinese customer who using iPhone.

The number of Chinese customer who using iPhone is unknown, so there will

choose 200 respondents as the sample size.

3.5.2 Questionnaire Design

The design of questionnaire is the first step for making observation. But

beforewriting the first question, it is important to have a very clear idea about

what will be achieved in the questionnaire. Write down the research goals, and

think about what information that need to be elicited from respondents to meet

those goals.

Think also about how to analyze each question to get the results. Remember there

is a difference between things that it needs to know, and those it would be nice to

know. Eliminate unnecessary lines of questioning at the planning stage.

In this research, the questionnaire was made based on five aspects: product,

promotion, price, place and brand. In these five aspects, it already contains the

most part about mobile phone. Likert Scale is showed as follow:

Table 3.1 Likert Scale

Scale Rating

1 Strongly Disagree (SD)

2 Disagree (D)

3 Neutral (N)

4 Agree (A)

5 Strongly Agree (SA)

Table 3.2 Statement of Questionnaire

Question SD D N A SA

PRODUCT ( X1) 1 2 3 4 5

1. iPhone has an attractive mobile phone design.

2. iPhone is good quality mobile phone.

3. iPhone has a great operation system.

4. iPhone is on the right size, so it is easy to hold.

5. iPhone is on the right size, so it is easy to touch the corner of

screen.

PRICE( X2)

6. iPhone’s price is affordable.

7. iPhone always has a discount.

8. iPhone’s price is more preferably than other mobile phone with

similar quality.

9. For the product’s value offered, the price set is not expensive.

Table 3.2 Statement of Questionnaire (Continued)

PLACE ( X3)

10. I can easily find shop to buy iPhone.

11. I can easily find place to repair (service) my iPhone.

12. I prefer buy iPhone directly at store than at online shop.

13. I can directly buy iPhone from selling person with door to door.

PROMOTION( X4)

14. I like iPhone’s posters and billboards.

15. iPhone TV ads are very attractive.

16. I want to buy iPhone after watching its TV ads.

17. I like iPhone’s endorser (someone who become model in an

ads).

BRAND ( X5)

18. I buy the brand iPhone because it is a worldwide brand.

19. If I want to buy a mobile phone, I will think to buy iPhone on

the first selection.

CUSTOMER SATISFACTION ( Y)

20. Overall, I am satisfied with iPhone.

3.6 Data Collection

In collecting data, two methods will be used for data collection in order to review

and complete all sides of data correction. These two methods are primary methods

and secondary methods. For primary methods, this research will use sample

survey. A sample survey is a study that obtains data from a subset of a population,

in order to estimate population attributes. All the data in this research are collected

by questionnaire which is a set of carefully planned written questions related to a

particular research topic which, when submitted to and answered accurately by

properly selected persons called respondents, will supply data to complete the

research project.

In addition, in order to make sure the research correctly and completed, there also

need to use secondary method which collects data through the previous researches,

journals, articles, forums, news, websites and other related the topic resources.

Data collection will be done by spreading questionnaires to the male and female

customer who are using or ever used iPhone.

3.6.1 Pre – test Questionnaire

In this research, this research will prepare 20 questions for pre-test questionnaire.

The pre-test questionnaire had spread to 30 respondents to pre-test Validity and

Reliability.

3.6.2 Statistical Treatment

This research is the analysis of Chinese customer satisfaction towards iPhone that

will through statistical treatment of data to discuss the result to prove result of the

topic.

3.6.2.1 Validity test

Validity is generally considered the most important issue in psychological and

educational testing because it concerns the meaning placed on test results. Though

many textbooks present validity as a static construct, various models of validity

have evolved since the first published recommendations for constructing

psychological and education tests. Measuring the validity data is important on

doing the research, the research can continue only if the data is valid.

3.6.2.2 Reliability test

The purpose of reliability test is to measure an internal consistency and stability of

related items in a group. After makes the data valid, one more step should be

passed there’s reliability testing. This testing aims to show stability and accuracy

from variables that used in an instrument. Accurate questionnaire is question that

clear, understandable, and details. Accurate questionnaire may deflect the right

question which is means when the question is asked for several times, the

interpretation would be the same from one respondent to another.

3.7 Data Collection and Analysis

After validity and reliability of data have been tested, the next step is to calculate

the data that collected from the customers. After the calculation, it can be easily to

see how customer satisfaction is toward iPhone. And the next step is only to

analysis the result and finds the way to improve the product.

3.8 Conclusion and Recommendation

In this part, all the research already has been done, the conclusion should be

drawn. This is the last step after us doing the research. From the result, it can be

seen that the conclusion and give the recommendation to company to improve the

product performance and also customer satisfaction.

CHAPTER IV

DATA CALCULATION AND ANALYSIS

4.1 Company Profile

Apple, Inc. designs, manufactures, and markets mobile communication and media

devices, personal computers, portable digital music players, and sells a variety of

related software, services, peripherals, networking solutions, and third-party

digital content and applications. Its products and services include iPhone, iPad,

iPod, Mac, iPod, Apple TV, a portfolio of consumer and professional software

applications, the iOS and OS X operating systems, iCloud, and accessories,

service and support offerings. The company also sells and delivers digital content

and applications through the iTunes Store, App Store, iBooks Store, and Mac App

Store. It sells its products worldwide through its retail stores, online stores, and

direct sales force and third-party cellular network carriers, wholesalers, retailers,

and value-added resellers to the consumer and also sells third-party iPhone, iPad,

Mac and iPod compatible products, including application software, and

accessories, through its online and retail stores. The company was founded by

Steven Paul Jobs, Steve Wozniak and Ronald Gerald Wayne on April 1, 1976 and

is headquartered in Cupertino, CA.

In March 2013, the Company acquired a Silicon Valley startup, WiFiSlam, which

makes mapping applications for smart phones. Effective July 19, 2013, Apple Inc

acquired Locationary Inc. Effective July 20, 2013, Apple Inc acquired

Hopstop.com Inc. Effective August 28, 2013, AppleInc acquired AlgoTrim AB, a

Malmo-based developer of prepackaged software. In November 2013, Apple Inc

bought PrimeSense Ltd. Effective December 2, 2013, Apple Inc acquired Topsy

Labs Inc. In February 2014, Apple Inc acquired Burstly Inc. Effective April 3,

2014, Apple Inc acquired Novauris Technologies Ltd. Effective August 1, 2014,

Apple acquired Beats Electronics LLC (Beats).

4.1.1 Mission

Apple Computer is committed to protecting the environment, health and safety of

our employees, customers and the global communities where we operate. We

recognize that by integrating sound environmental, health and safety management

practices into all aspects of our business, we can offer technologically innovative

products and services while conserving and enhancing recourses for future

generations. Apple strives for continuous improvement in our environmental,

health and safety management systems and in the environmental quality of our

products, processes and services.

4.1.2 Vision

Apple is committed to bringing the best personal computing experience to

students, educators, creative professionals and consumers around the world

through its innovative hardware, software and Internet offerings.

4.2 Pre-Test Questionnaire

Before distributing the questionnaires, a pre-test for questionnaire with 30

questions distributed was given to customers to find out the feasibility of the

questionnaire. The explanation below shows the result of a pre-test questionnaire

on the review of the validity and reliability.

4.2.1 Validity Pre-test Result

Based on the calculation, the result for pre-test questionnaires with 30 respondents

shows mean corrected item-total between variables on r = 0.361. It means that

according to corrected item-total correlation table, if r result is greater than r table,

the variable is valid. If r result is smaller than r table, the variables are not valid.

Table 4.1 Validity Test Result for Pre-Test

Variables Statement r table Corrected

Item-Total

Correlation

Status

V1 iPhone has an attractive mobile phone design. 0.361 .737 Valid

V2 iPhone is good quality mobile phone. 0.361 .842 Valid

V3 iPhone has a great operation system. 0.361 .898 Valid

V4 iPhone is on the right size, so it is easy to hold. 0.361 .567 Valid

V5 iPhone is on the right size, so it is easy to

touch the corner of screen.

0.361 .673 Valid

V6 iPhone’s price is affordable. 0.361 .898 Valid

V7 iPhone always has a discount. 0.361 .389 Valid

V8 iPhone’s price is more preferably than other

mobile phone with similar quality. 0.361 .885 Valid

V9 For the product’s value offered, the price set is

not expensive. 0.361 .575 Valid

V10 I can easily find shop to buy iPhone. 0.361 .740 Valid

V11 I can easily find place to repair (service) my

iPhone. 0.361 .626 Valid

V12 I prefer buy iPhone directly at store than at

online shop. 0.361 .529 Valid

V13 I can directly buy iPhone from selling person

with door to door. 0.361 .263 Invalid

V14 I like iPhone’s posters and billboards.

0.361 .776 Valid

Table 4.1 Validity Test Result for Pre-Test (Continued)

V15 iPhone TV ads are very attractive. 0.361 .786 Valid

V16 I want to buy iPhone after watching its TV ads.

0.361 .568 Valid

V17 I like iPhone’s endorser (someone who become

model in an ads). 0.361 .740 Valid

V18 I buy the brand iPhone because it is a

worldwide brand. 0.361 .842 Valid

V19 If I want to buy a mobile phone, I will think to

buy iPhone on the first selection. 0.361 .814 Valid

V20 Overall, I am satisfied with iPhone.

0.361 .613 Valid

From the validity table above, statement in variable 13 has r (0.263) lower than r

table (0.361). It means variable 13 is invalid and will be removed from

questionnaire. The questionnaire will be distributed to customer in 19 statements.

4.2.2 Reliability Pre-test Result

Reliability test measures whether the questionnaire is accurate, precise, and

consistent. In this research, Cronbach’s Alpha formula is used to determine the

reliability. Furthermore, Microsoft Excel 2007 and SPSS 16.0 will be used in

dealing with statistical tools. The result of reliability test for the questionnaire is

shown in table 4.2 below.

Table 4.2 Reliability Test Result for Pre-Test

The Cronbach’s alpha is 0.965, it is higher than 0.700. From the result above, it is

Reliability Statistics

Cronbach's

Alpha N of Items

Standard

Alpha

Remark

.951 20 0.700 Reliable

possible that the questionnaire is acceptable to be used in this research.

4.3 Data Collection

After analyzing pre-test questionnaire to determine validity and reliability

statement in questionnaire, it was found that one variable statement was not valid

and it will be erased from the questionnaire. Thus, the number if variables in the

statement are 19 variable statements. After removing the invalid questionnaire, the

questionnaire is ready to distribute again. This questionnaire is distributed to 200

respondents and collected the data from the respondents.

4.4 Respondents Characteristics

This research used questionnaire to gather the data and classified the

characteristics of respondents into four categories, which are gender, age, job,

how much money they want to spend to buy a phone, and how many years they

have used iPhone

4.4.1 Gender

The diagram below is the result of gender presentation based on the data gathered.

Figure 4.1 Major

59%

41%

Gender

Male

Female

Based on the figure 4.1 above, the male respondents’ percentage are higher than

female’s percentage. The female respondents are 41% while the male respondents

59% of are total respondents.

4.4.2 Age

The diagram below shows age of respondents based on the data gathered.

Figure 4.2 Batch

Based on the figure 4.2 above, most if the respondents in this research are 21-30

years old (30%) and 31-40 years old (30%), then it is followed by 41-50 years old

(16%), 17-20 years old (16%) and 50-65 years old (8%).

4.4.3 Jobs

The diagram below is the result of job percentage based on the data gathered.

17-20 21-30 31-40 41-50 50-65

Responden 32 60 60 32 16

Presentation 16% 30% 30% 16% 8%

0

10

20

30

40

50

60

70

Age Chart

Figure 4.3 Gender

Based on the figure 4.3 above, most if the respondents of this research are

Employee (27%), then it is followed by Students (25%), Government Employee

(16%), Entrepreneur (13%), Housewife (12%) and others (7%).

4.4.4 Expense to buy a phone

The diagram below shows the result of respondents’ expense to buy a phone based

on the data gathered.

Figure 4.4 Age Chart

Government

Employee

Employee

Entrepreneur

Housewife

Student Others

Respondent 32 54 26 24 50 14

Percentage 16% 27% 13% 12% 25% 7%

0102030405060

Jobs

< RMB1000

RMB 1001 – RMB 2000

RMB 2001 – RMB 3000

RMB 3001 – RMB 4000

RMB 4001 – RMB 5000

> RMB5000

Respondent 30 48 42 38 26 16

Percentage 15% 24% 21% 19% 13% 8%

0102030405060

Expense to buy a phone

Based on the figure 4.4 above, most of respondents’ expenses to buy a phone are

between RMB 1001 – RMB 2000 (24%), then it is followed by RMB 2001 –

RMB 3000 (21%), RMB 3001 – RMB 4000 (19%), less than RMB 1000 (15%),

RMB 4001 – RMB 5000 (13%) and more than RMB 5000 (8%). At here, the

Chinese money 1 RMB equal to 1000 Rupiah.

4.4.5 Number of years for using iPhone

The diagram below shows the number of years that respondents using iPhone.

Figure 4.5 Number of years for using iPhone

Based on the figure 4.5 above, most of respondents are using iPhone 2 - 3 years

(50%), then it is followed by less than 1 year (40%), 4 – 5 years (7%) and more

than 6 years (3%).

4.5 Validity and Reliability Questionnaire

After distributing questionnaire to 200 respondents and getting an assessment

from respondents, the result is tested using 19 variables of validity and reliability

test. Here are the summary of validity and reliability test.

< 1 2 – 3 4 – 5 > 6

Respondent 80 100 14 6

Percentage 40% 50% 7% 3%

0

20

40

60

80

100

120

Number of years for using iPhone

Table 4.3 Validity Test of Fixed Questionnaire

Variables Statement r table Corrected

Item-Total

Correlatio

n

Status

V1 iPhone has an attractive mobile phone

design.

0.138 .845 Valid

V2 iPhone is good quality mobile phone. 0.138 .824 Valid

V3 iPhone has a great system operation. 0.138 .646 Valid

V4 iPhone is on the right size, so it is easy to

hold.

0.138 .844 Valid

V5 iPhone is on the right size, so it is easy to

touch the corner of screen.

0.138 .728 Valid

V6 iPhone’s price is affordable. 0.138 .698 valid

V7 iPhone always has a discount. 0.138 .738 Valid

V8 iPhone’s price is more preferably than other

mobile phone with similar quality.

0.138 .863 Valid

V9 For the product’s value offered, the price set

is not expensive.

0.138 .771 valid

V10 I can easily find shop to buy iPhone. 0.138 .495 valid

V11 I can easily find place to repair (service) my

iPhone.

0.138 .698 Valid

V12 I prefer buy iPhone directly at store than at

online shop.

0.138 .861 valid

V13 I like iPhone’s posters and billboards. 0.138 .776 Valid

V14 iPhone TV ads are very attractive. 0.138 .844 Valid

V15 I want to buy iPhone after watching its TV

ads.

0.138 .704 Valid

V16 I like iPhone’s endorser (someone who

become model in an ads).

0.138 .565 Valid

V17 I buy the brand iPhone because it is a

worldwide brand.

0.138 .575 Valid

V18 If I want to buy a mobile phone, I will think

to buy iPhone on the first selection.

0.138 .576 Valid

V19 Overall, I am satisfied with iPhone. 0.138 .588 Valid

Table 4.4 Reliability Test Result of Fixed Questionnaire

Based on table above, it can be conclude that all variables are valid and reliable.

After getting result from validity and reliability test, then each variable statement

is calculated to know the score.

4.6 Data Analysis

This section will provide the results of the tests which was done the calculation by

SPSS 20. The tests follow the steps that the data analysis use Regression, Testing

Hypothesis and Weight Mean method.

4.6.1Regression

4.6.1.1 Normality Test

From the figure 4.6 and 4.7 follow, the normal probably plot of regression

standardizes residual with product, price, place, promotion and brand as

independent variable and customer satisfaction as dependent variable approximate.

It can be concluded that the data has followed a linear relationship model and the

standardize deviation has followed the normal standardized distribution.

Reliability Statistics

Cronbach's

Alpha

N of Items Standard

Alpha

Remark

.956 19 0.700 Reliable

Figure 4.6 Histogram

Figure 4.7 Normal P-P Plot

4.6.1.2 Heteroscedasticity Test

The figure 4.8 follow shows the data are normally distributed because the points

are spread each other and not made a pattern. If the points tends to make a pattern,

its means the data are not normally distributed and considered to become

heteroscedasticity. Also the points spread with not make a certain pattern above

the below the 0 and Y axis.

Figure 4.8 Scatterplot

4.6.1.3 Multicollinearity Test

Table 4.5Multicollinearity Test Result

Model Collinearity Statistics

Tolerance VIF

1 (Constant)

X1

X2

X3

.141

.121

.346

6.807

8.237

2.886

X4

X5

.131

.380

7.631

2.633

Based on the table 4.5 above, it can be seen that there is multicollinearity since the

tolerance values are less than 1 and the VIF<10.

4.6.2 Model Testing

4.6.2.1 Coefficient Correlation (R)

Coefficient correlation is used to measure the strength and direction of the linear

relationship between two variables depending on the level of measurement of

variables. If R values are close to 1, it means that it have strong relationship and

can predict correlations between variables X and Y.

Table 4.6 Coefficient Correlation (R)

Model Summaryb

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .707a .500 .488 .631

a. Predictors: (Constant), X1, X2, X3, X4, X5

b. Dependent Variable: Y

Based on the table 4.6 above shows, R value is 0.707 which means that

independent variables (Product, Price, Place, Promotion and Brand) have a strong

significant relationship and impact to dependent variables (Customer

Satisfaction).

4.6.2.2 Coefficient Determination (R2)

Coefficient of determination (R2) is used to measure how far the model’s ability to

explain variation in the dependent variable. R2 values are getting close to 1,

meaning the independent variables provide almost all the information needed to

predict the variation in the independent variable. The coefficient of determination

being used is the value of Adjusted R Square because it is more reliable in

evaluating the regression model. Adjusted R Square value can go up or down

when the independent variable is added to the model.

From the table 4.6 above, it shows that the value of Adjust R Square is 0.488. It

means that the change if dependent variable (Customer Satisfaction) 49% can be

explained by the independent variables (Product, Price, Place, Promotion and

Brand). And the other 51% is explained by other caused outside the model.

4.6.3 Regression Model Result

Table 4.7 Coefficients Table

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

(Constant) .424 .453 .936 .350

X1 .042 .033 .650 1.287 .020

X2 .194 .043 .170 4.467 .000

X3 .215 .036 .035 6.009 .000

X4 .013 .053 .518 .252 .008

X5 .246 .078 .460 3.154 .002

Based on the table 4.7 above, the result of the regression equation can be seen as

below:

Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5

Y = 0.650X1 + 0.170X2 + 0.035X3 + 0.518X4 + 0.460X5 + ε

Where:

Y = Customer Satisfaction

X1 = Product

X2 = Price

X3 = Place

X4 = Promotion

X5 = Brand

From the regression linear above, it can be concluded that The equation have a

constant of -1.895 which means if Product, Price, Place, Promotion and Brand

being constant, the amount of customer satisfaction toward iPhone is -1.895.

Independent variable Product (X1) has positive influence on Customer

Satisfaction toward iPhone with coefficient of 0.650.

Independent variable Price (X2) has positive influence on Customer Satisfaction

toward iPhone with coefficient of 0.170.

Independent variable Place (X3) has positive influence on Customer Satisfaction

toward iPhone with coefficient of 0.035.

Independent variable Promotion (X4) has positive influence on Customer

Satisfaction toward iPhone with coefficient of 0.518.

Independent variable Brand (X5) has positive influence on Customer Satisfaction

toward iPhone with coefficient of 0.460.

4.6.4 F Test

The result of F test is to examine the effect of independent variables toward the

dependent variable. The result of F test can be seen below:

Table 4.8 ANOVA Table

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 77.511 5 15.502 38.874 .000b

Residual 77.364 194 .399

Total 154.875 199

a. Dependent Variable: Y

b. Predictors: (Constant), X1, X2, X3, X4, X5

Based on the table 4.8 above, it can be seen that F value is 38.874 which means

independent variables (Product, Price, Place, Promotion and Brand) has strong

impact to dependent variable (Customer Satisfaction). This data also shows that

the null hypothesis (H0) can be rejected and the alternative hypothesis (H1) are

accepted.

4.6.5 T Test

The purpose of T test is to determine the significant level of influence of each

independent variable toward dependent variable. The result of T test can be seen

below:

Table 4.9T Test

Model t Sig.

1

(Constant) .936 .350

X1 1.287 .020

X2 4.467 .000

X3 6.009 .000

X4 .252 .008

X5 3.154 .002

Based on the table 4.9 above, it can be concluded that the all the independent

variables (Product, Price, Place, Promotion and Brand) have a significant effect to

dependent variable (Customer Satisfaction), since all the sig all less than 0.05.

This data also shows that the null hypothesis (H0) can be rejected and the

alternative hypothesis (H1) are accepted.

4.6.6 Interpretation of the Result

The result of F test shows that Product, Price, Place, Promotion and Brand have

significant influence on Customer Satisfaction. The result of F test is 38.874 with

sig. 0.000 < 0.05. The result of F test shows that the Product, Price, Place,

Promotion and Brand have a big influence on Customer Satisfaction of iPhone.

T test result shows that there is a big significant influence toward Customer

Satisfaction from Product, Price, Place, Promotion and Brand, since all the

significant are less than 0.05.

4.6.7Weighted Mean

4.6.7.1 Analysis of Product

Table 4.10 Distribution of Product

NO. SD D N A SA Mean

1 0 0% 9 4.5% 25 12.5% 32 16.0% 134 67.0% 4.46

2 0 0% 0 0% 34 17.0% 32 16.0% 134 67.0% 4.50

3 0 0% 0 0% 25 12.5% 12 6.0% 163 81.5% 4.69

4 0 0% 14 7.0% 39 19.5% 50 25.0% 97 48.5% 4.15

5 0 0% 9 4.5% 41 20.5% 67 33.5% 83 41.5% 4.12

The table 4.10 above shows the distribution of the answers toward the factor

product of iPhone. For the first statement, iPhone has an attractive mobile phone

design, 0 respondents (0%) answered strongly disagree and 9 respondents (4.5%)

answered disagree, 25 respondents (12.5%) answered neutral, 32 respondents

(16.0%) answered agree while 134 respondents (67.0%) answered strongly agree.

For the second statement, iPhone is good quality mobile phone, 0 respondents

(0%) answered strongly disagree and 0 respondents (0%) answered disagree, 34

respondents (17.0%) answered neutral, 32 respondents (16.0%) answered agree

while 134 respondents (67.0%) answered strongly agree.

For the third statement, iPhone has a great operation system, 0 respondents (0%)

answered strongly disagree and 0 respondents (0%) answered disagree, 25

respondents (12.5%) answered neutral, 12 respondents (6.0%) answered agree

while 163 respondents (81.5%) answered strongly agree.

For the fourth statement, iPhone is on the right size, so it is easy to hold, 0

respondents (0%) answered strongly disagree and 14 respondents (7.0%)

answered disagree, 39 respondents (19.5%) answered neutral, 50 respondents

(25.0%) answered agree while 97 respondents (48.5%) answered strongly agree.

For the fifth statement, iPhone is on the right size, so it is easy to touch the corner

of screen, 0 respondents (0%) answered strongly disagree and 9 respondents

(4.5%) answered disagree, 41 respondents (20.5%) answered neutral, 67

respondents (33.5%) answered agree while 83 respondents (41.5%) answered

strongly agree.

The weighted mean of iPhone has an attractive mobile phone statement is 4.46.

Weighted mean of iPhone is good quality mobile phone statement is 4.50.

Weighted mean of iPhone has a great operation system statement is 4.69.

Weighted mean of iPhone is on the right size, so it is easy to hold statement is

4.15, and weighted mean of iPhone is on the right size, so it is easy to touch the

corner of screen statement is 4.12. In factor Product, the statement 3 iPhone has a

great operation system got the highest weighted mean 4.69, which means that

most of customers are satisfied with the operation system of iPhone.

4.6.7.2 Analysis of Price

Table 4.11 Distribution of Price

NO. SD D N A SA Mean

6 0 0% 12 6.0% 49 24.5% 79 39.5% 60 30.0% 3.94

7 0 0% 9 4.5% 12 6.0% 139 69.5% 40 20.0% 4.05

8 0 0% 18 9.0% 41 20.5% 58 29.0% 83 41.5% 4.03

9 0 0% 18 9.0% 41 20.5% 56 28.0% 85 42.5% 4.04

The table 4.11 above shows the distribution of the answers toward the factor

product of iPhone. For the sixth statement, iPhone’s price is affordable, 0

respondents (0%) answered strongly disagree and 12 respondents (6.0%) answered

disagree, 49 respondents (24.5%) answered neutral, 79 respondents (39.5%)

answered agree while 60 respondents (30.0%) answered strongly agree.

For the seventh statement, iPhone always has a discount, 0 respondents (0%)

answered strongly disagree and 9 respondents (4.5%) answered disagree, 12

respondents (6.0%) answered neutral, 139 respondents (69.5%) answered agree

while 40 respondents (20.0%) answered strongly agree.

For the eighth statement, iPhone’s price is more preferably than other mobile

phone with similar quality, 0 respondents (0%) answered strongly disagree and 18

respondents (9.0%) answered disagree, 41 respondents (20.5%) answered neutral,

58 respondents (29.0%) answered agree while 83 respondents (41.5%) answered

strongly agree.

For the ninth statement, For the product’s value offered, the price set is not

expensive, 0 respondents (0%) answered strongly disagree and 18 respondents

(9.0%) answered disagree, 41 respondents (20.5%) answered neutral, 56

respondents (28.0%) answered agree while 85 respondents (42.5%) answered

strongly agree.

The weighted mean of iPhone’s price is affordable statement is 3.94. Weighted

mean of iPhone always has a discount statement is 4.05. Weighted mean of

iPhone’s price is more preferably than other mobile phone with similar quality

statement is 4.03, and weighted mean of for the product’s value offered, the price

set is not expensive statement is 4.04. In factor Price, the statement 7 iPhone

always has a discount got the highest weighted mean 4.05, which means that most

of customers always can get discount.

4.6.7.3 Analysis of Place

Table 4.12 Distribution of Place

NO. SD D N A SA Mean

10 0 0% 3 1.5% 53 26.5% 76 38.0% 68 34.0% 4.05

11 0 0% 8 4.0% 43 21.5% 91 45.5% 58 29.0% 4.00

12 0 0% 18 9.0% 3 1.5% 127 63.5% 52 26.0% 4.07

The table 4.12 above shows the distribution of the answers toward the factor

product of iPhone. For the tenth statement, I can easily find shop to buy iPhone, 0

respondents (0%) answered strongly disagree and 3 respondents (1.5%) answered

disagree, 53 respondents (26.5%) answered neutral, 76 respondents (38.0%)

answered agree while 68 respondents (34.0%) answered strongly agree.

For the eleventh statement, I can easily find place to repair (service) my iPhone, 0

respondents (0%) answered strongly disagree and 8 respondents (4.0%) answered

disagree, 43 respondents (21.5%) answered neutral, 91 respondents (45.5%)

answered agree while 58 respondents (29.0%) answered strongly agree.

For the twelfth statement, I prefer buy iPhone directly at store than at online shop,

0 respondents (0%) answered strongly disagree and 18 respondents (9.0%)

answered disagree, 3 respondents (1.5%) answered neutral, 127 respondents (63.5%)

answered agree while 52 respondents (26.0%) answered strongly agree.

The weighted mean of I can easily find shop to buy iPhone statement is 4.05.

Weighted mean of I can easily find place to repair (service) my iPhone statement

is 4.00, and weighted mean of I prefer buy iPhone directly at store than at online

shop statement is 4.07. In factor Place, the statement 12 I prefer buy iPhone

directly at store than at online got the highest weighted mean 4.07, which means

that most of customers prefer buy iPhone at store rather than at online.

4.6.7.4 Analysis of Promotion

Table 4.13 Distribution of Promotion

NO. SD D N A SA Mean

13 0 0% 9 4.5% 38 19.0% 60 30.0% 93 46.5% 4.19

14 0 0% 3 1.5% 21 10.5% 96 48.0% 80 40.0% 4.27

15 0 0% 3 1.5% 18 9.0% 139 69.5% 40 20.0% 4.08

16 0 0% 2 1.0% 41 20.5% 88 44.0% 69 34.5% 4.12

The table 4.13 above shows the distribution of the answers toward the factor

product of iPhone. For the thirteenth statement, I like iPhone’s posters and

billboards, 0 respondents (0%) answered strongly disagree and 9 respondents

(4.5%) answered disagree, 38 respondents (19.0%) answered neutral, 60

respondents (30.0%) answered agree while 93 respondents (46.5%) answered

strongly agree.

For the fourteenth statement, iPhone TV ads are very attractive, 0 respondents (0%)

answered strongly disagree and 3 respondents (1.5%) answered disagree, 21

respondents (10.5%) answered neutral, 96 respondents (48.0%) answered agree

while 80 respondents (40.0%) answered strongly agree.

For the fifteenth statement, I want to buy iPhone after watching its TV ads, 0

respondents (0%) answered strongly disagree and 3 respondents (1.5%) answered

disagree, 18 respondents (9.0%) answered neutral, 139 respondents (69.5%)

answered agree while 40 respondents (20.0%) answered strongly agree.

For the sixteenth statement, I like iPhone’s endorser (someone who become model

in an ads), 0 respondents (0%) answered strongly disagree and 2 respondents

(1.0%) answered disagree, 41 respondents (20.5%) answered neutral, 88

respondents (44.0%) answered agree while 69 respondents (34.5%) answered

strongly agree.

The weighted mean of I like iPhone’s posters and billboards statement is 4.19.

Weighted mean of iPhone TV ads are very attractive statement is 4.27. Weighted

mean of I want to buy iPhone after watching its TV ads statement is 4.08, and

weighted mean of I like iPhone’s endorser ( someone who become model in an

ads) statement is 4.12. In factor Promotion, the statement 14 iPhone TV ads are

very attractive got the highest weighted mean 4.27, which means that most of

customers felt iPhone’s TV ads are very attractive.

4.6.7.5 Analysis of Brand

Table 4.14 Distribution of Brand

NO. SD D N A SA Mean

17 0 0% 0 0% 3 1.5% 112 56.0% 85 42.5% 4.41

18 0 0% 0 0% 25 12.5% 92 46.0% 83 41.5% 4.29

The table 4.14 above shows the distribution of the answers toward the factor

product of iPhone. For the seventeenth statement, I buy the brand iPhone because

it is a worldwide brand, 0 respondents (0%) answered strongly disagree and 0

respondents (0%) answered disagree, 3 respondents (1.5%) answered neutral, 112

respondents (56.0%) answered agree while 85 respondents (42.5%) answered

strongly agree.

For the eighteenth statement, If I want to buy a mobile phone, I will think to buy

iPhone on the first selection, 0 respondents (0%) answered strongly disagree and 0

respondents (0%) answered disagree, 25 respondents (12.5%%) answered neutral,

92 respondents (46.0%) answered agree while 83 respondents (41.5%) answered

strongly agree.

The weighted mean of I buy the brand iPhone because it is a worldwide brand

statement is 4.41, and weighted mean of if I want to buy a mobile phone, I will

think to buy iPhone on the first selection statement is 4.29. In factor Brand, the

statement 17 I buy the brand iPhone because it is a worldwide brand got the

highest weighted mean 4.41, which means that most of customers buy iPhone is

because it is a worldwide brand.

4.6.7.6 Analysis of All Variables

Table of 4.15 Mean of All Variables

Variables Statement Mean

3 iPhone has a great operation system. 4.69

2 iPhone is good quality mobile phone. 4.50

1 iPhone has an attractive mobile phone design. 4.46

17 I buy the brand iPhone because it is a worldwide brand. 4.41

18 If I want to buy a mobile phone, I will think to buy iPhone on the first

selection.

4.29

14 iPhone TV ads are very attractive. 4.27

13 I like iPhone’s posters and billboards. 4.19

4 iPhone is on the right size, so it is easy to hold. 4.15

16 I like iPhone’s endorser (someone who become model in an ads). 4.12

5 iPhone is on the right size, so it is easy to touch the corner of screen. 4.12

15 I want to buy iPhone after watching its TV ads. 4.08

12 I prefer buy iPhone directly at store than at online shop. 4.07

10 I can easily find shop to buy iPhone. 4.05

7 iPhone always has a discount. 4.05

9 For the product’s value offered, the price set is not expensive. 4.04

8 iPhone’s price is more preferably than other mobile phone with similar

quality.

4.03

11 I can easily find place to repair (service) my iPhone. 4.00

6 iPhone’s price is affordable. 3.94

The table 4.15 above shows all the means of variables which are ranked from the

highest to the lowest. The most significant variable is the operation system of

iPhone with the mean of 4.69, and the second is the quality of iPhone with the

mean of 4.50.

While the lowest rank is the price of iPhone with the mean of 3.94. It is means

that the price of iPhone is too high, so a lot of people cannot afford the price. So

the company should set a lower price, to make it affordable for people to buy it,

and then is the repair place of iPhone with the mean of 4.00. It means the

customer cannot easily find place to repair their iPhone.

CHAPTER V

CONCLUSION AND RECOMMENDATIONS

5.1 Conclusion

This chapter will evaluate the problems that have been answered by the research

and give the conclusion and the recommendation. Based on the research results

and problem analysis, the conclusions as follow as:

1. From the data of respondents, it can be calculated that most customer satisfied

with the operation system of iPhone and the quality of iPhone. But not

satisfied with the price of iPhone and the repair place of iPhone, because they

thought the price of iPhone is too high, they cannot afford it. For the repair

place, they need a global customer service system, because they hope they can

repair iPhone at any country not only the buying place.

2. The company should set a lower price to make morepeople can afford it and

buy it, and build a global customer service system, so the customer can repair

their iPhone at any country.

5.2 Recommendation

Based on the result of this research, the recommendation for the company already

showed in conclusion point 2. There are some advice and input as consideration

for the further research and improvement. Because the limited of this research, so

the further research can be held in China with more customer to increase the

accuracy of study. The research also can be done from other aspect such as quality

service to find customer satisfaction.