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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
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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.
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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.
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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.
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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:
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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.
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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
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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
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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.
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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.
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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%
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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
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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,
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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,
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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
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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
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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:
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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%
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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.
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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
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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.
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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.
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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
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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.
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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.
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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
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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
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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
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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
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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
Page 41
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
Page 42
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
Page 43
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
Page 44
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
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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
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Figure 4.6 Histogram
Figure 4.7 Normal P-P Plot
Page 47
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
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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
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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
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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
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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,
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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%)
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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.
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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
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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.
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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.
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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.
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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.
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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.
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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.