Proceedings of World Business and Social Science Research Conference

advertisement
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
Value Based Attributes for Mobile Internet Provider
Ganjar M. Disastra and Heppy Millanyani
Human need for communication plus their mobility raises the need for mobile
operators. Changes in telecommunications industry have force them to offer mobile
internet service. Fierce competition has made these mobile internet service providers
(mobile ISPs) gave attractive promotions programs. But in the end, consumer will only
choose offering with the best value because according to Kotler and Keller, the buyer
chooses the offerings he or she perceives to deliver the most value (Kotler & Keller,
2012:32).
What value(s) is needed by the customer should be explored by these mobile ISPs.
The aim of this study is to explore what factors are valued by consumers when they
are choosing a mobile ISP, and to know consumers' assessment of its performance
and also to know consumers’ expectations about these factors.
This study uses descriptive statistics, factors analysis with varimax rotation and
importance performance analysis. Data collection obtained through focus group
discussions, interviews and survey involving 400 respondents.
Factors valued by consumers in choosing a mobile ISP has categorised the 13
attributes as follows: Price, Sales Promotion, Quota, Customer Service, Feature,
Advertising, Variation, Brand Image, Stability, Coverage, Speed, Ease of Activation
and Reload.
Using IPA, this study has compared the importance and performance of the mobile
internet provider selection factors. Factors are considered important by consumers
and have performed well are ease to activate and ease to reload. Factors are
considered important by consumers but haven’t performed well include Stability,
Coverage, Quota, and Speed.Factors are considered less important by consumers
but have performed well include sales promotion, feature and advertising.Factors that
are considered important by consumers and haven’t performed well include price,
customer service, variation and brand image.
Keywords: value, mobile internet service provider, importance performance analysis.
1. Introduction
Human need for communication plus their higher mobility raises the need for mobile
operators. With these mobile operators, people now can stay connected to anyone, wherever
they are. Along with the development of technology, the need to communicate that was mostly
done by phone or texting, is now being replaced by exchanging messages on social media,
making conversation via skype or writing to each other via email. Such changes make the
telecommunications industry today is not voice-centric anymore, but have switched to a datacentric. This is in line with the opinion of AT & T CEO Randall Stephenson that there have been
changes in the use of new patterns of smart phones. So that in the future, mobile operators will
only issue data package service, where voice and text will be replaced with data services
(source: www.neraca.co.id).
Indonesia is a country with a big number of mobile phone users. In September 2012,
Business Wire Research and Markets announced the results of their prediction on the number
__________________________________________________________________
Ganjar M. Disastra, Marketing Management Program, Telkom University, Jl. Telekomunikasi No.1 Bandung.
[email protected]
Heppy Millanyani, Marketing Management Program, Telkom University, Jl. Telekomunikasi No.1 Bandung.
[email protected]
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
of Indonesian mobile operator users that in 2016 will reach 360 million (source:
www.businesswire.com). This illustrates the magnitude of the opportunities in Indonesia’s
telecommunications industry. The magnitude of this opportunity has made a lot of mobile
operators emerge. Until early 2000s, Indonesia only has three mobile operators, namely PT.
Telekomunikasi Indonesia (Telkomsel), PT. Indosat Tbk (PT Satellite Palapa Indonesia
(Satelindo)), PT. XL Axiata Tbk (PT Excelcomindo Pratama Tbk). According to the same report,
the current competition is becoming increasingly fierce with the presence of seven other cellular
operators, namely PT Telekomunikasi Indonesia Tbk (Telkom Flexi), PT Bakrie Telecom Tbk, 3
Indonesia (PT Hutchinson CP Telecommunications), PT Natrindo Phones Mobile (Axis), PT
Mobile-8 Telecom Tbk, Smart Telecom Indonesia and PT Sampoerna Telekomunikasi
Indonesia.
In line with those expressed by the CEO of AT & T before, all mobile operators are now
offering data package service with attractive promotions programs. These mobile operators
(now will be referred as mobile internet service provider or mobile ISP) utilize various kinds of
methods to promote their data package service in order to be chosen by the customer. Even
Telkomsel which is the market leader, still feel the need to offer a bundling package at the price
of Rp. 100,000 where customers will get 500MB of data in 3G networks for three consecutive
months. Other operator offers starter packs with no expiration date (always on). Even there’s a
mobile ISP which offers its customers to use first, and pay later.
Based on writers’ observation, the programs have been effectively introducing products
to the consumer. Consumers initially attracted by low prices and the amount of data that can be
obtained before eventually decided to subscribe to a particular mobile ISP. But when consumers
finally consume the service and they, for example, get a slow connection, consumers will be
dissatisfied and will easily switch to another mobile ISP that gives better value.
Therefore, in addition to a good promotional program, mobile ISP should provide
additional value for customers in order to win the competition. Because in the end, according to
Kotler and Keller, the buyer chooses the offerings he or she perceives to deliver the most value
(Kotler & Keller, 2012:32). The creation of value has been put forward as the purpose of a firm
(Slater, 1997) and as a precursor to customer satisfaction and loyalty (Woodall, 2003).
According to Drucker (1973), the mission and purpose of every business is to satisfy the
customer. This satisfaction is achieved when superior customer value is delivered by the firm
(Landroguez, et.al., 2013:237).
Given the situation, mobile ISPs should deliver product with the most value to win the
competition by satisfying the customer. What value(s) is needed by the customer should be
explored by these mobile ISPs. This study wanted to explore what factors are valued by
consumers when they are choosing a mobile ISP, and to know consumers' assessment of its
performance and also to know consumers’ expectations about these factors.Therefore the
objective of this study are as follow :
1.
2.
3.
4.
5.
6.
To explore what factors valued by consumers in choosing a mobile internet service provider.
To know consumers’ perception refarding the factors’ performance.
To know consumers’ expectations regarding mobile internet service provider.
To know what factors are considered important by consumers and have performed well.
To know what factors are considered important by consumers but haven’t performed well.
To know what factors are considered less important by consumers but have performed well.
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
7. To know what factors that are considered important by consumers and haven’t performed
well.
2. Literature Review
Mobile Internet in Indonesia
Indonesia has the lowest level of overall internet penetration in Southeast Asia by only 21
percent of Indonesians aged between 15 and 49 use the Internet. Based on communication
ministry data, at end of June 2011, there are 45 million internet users in Indonesia, which 64
percent or 28 million users on the age of 15 to 19. In 2013, according to APJII’s (Asosiasi
Pengelola Jasa Internet Indonesia or Association of Indonesian Internet Service Business)
survey, this number will increase to 82 million. Based on 2011 Nielsen's survey, 48 percent of
internet users in Indonesia used a mobile phone to access the internet, whereas another 13
percent used other handheld multimedia devices (source:http://en.wikipedia.org).
Seeing this big opportunity in mobile internet industry, many telecomunication providers
are offering mobile internet service. All of the GSM major cellular telecommunication providers
offer the high-speed mobile Internet service 3G and even 3.5G HSDPA (High Speed Downlink
Packet Access), but only in the big cities. They include Indosat, Telkomsel, Excelcomindo (XL)
and 3. Also, the usage of Evolution-Data Optimized (EV-DO) has been applied into service by
Indonesian CDMA cellular provider, which includes Mobile 8, Indosat, Esia, Smart, and Telkom
Flexi (source:http://en.wikipedia.org). These telecomunication providers is referred as mobile
internet service provider (mobile ISP).
Value Mix
In order to win among the fierce competition, mobile ISP should provide additional value
for customers. Naumann (1995) said that the key success factor is the firm’s ability to create
and deliver superior customer value compared to its competitors (Landroguez, et.al., 2013:235).
Because in the end, according to Kotler and Keller, the buyer chooses the offerings he or she
perceives to deliver the most value, which is primarily a combination of quality, service and
price. (Kotler & Keller, 2012:32).
Value can be defined as the ratio of perceived benefit to perceived cost (Value,
2002:134). Value has paramount impact on customer purchase decision and satisfaction. A
product or service with appropriate performance and cost is said to have good value. Value, in
other words, equals function divided by cost (Ho&Cheng, 1999:204). Furthermore they
explained that value mix is conceptualized as the combination of function, quality and price (see
figure 1).
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
Figure 1: Components of Value Mix
Performance
Feature
Reliability
Conformance
Durability
Serviceability
Use
Function
Customer
Needs
Aesthetic
Function
Function
Aesthetics
Perceived Quality
Value
Mix
Quality
Price
Source: Ho & Cheng, 1999:205
Cooper and Slagmulder (1997) suggested that quality and function are considered as two
separate but closely related characteristics. To define quality under the concept of value mix, a
narrower scope is adopted. That is, quality means conformance to specifications. Moreover,
functions of a product or service are its specifications which can further be divided into two
groups:
1. Use specifications, which are action oriented, are designed to fulfill the operating
requirements of a product or service desired by customers. Examples of performance
specification are the usable life (in terms of hours) of a light tube, the maximum output (in
terms of watts) an amplifier can deliver, the shortest time (in terms of minutes) for delivering
a fast food order, etc.
2. Aesthetic specifications, which may not be action-oriented, are designed to fulfill the
aesthetic requirements demanded by customers. Examples of aesthetic specifications are
shape, size, weight, color, smell, texture, etc (Ho & Cheng, 1999:206).
Customers do not evaluate the value of a product or service solely based on its functions;
its quality does matter. A product or service is said to have good quality when it can deliver what
it promises or claims, that is, high conformance to specifications. Garvin (1987) identified eight
dimensions on which customers focus when assessing the quality of a product or service. They
are listed as follows:
1. Performance (primary operating characteristics).
2. Features (characteristics that supplement the basic functioning of products)
3. Reliability (probability of a product malfunctioning or failing within a specific time period);
4. Conformance (the degree to which a product’s design and operating characteristics meet
established standards);
5. Durability (the amount of use one gets from a product before it deteriorates);
6. Serviceability (the speed, courtesy, competence, and ease of repair);
7. Aesthetics (how a product looks, feels, sounds, tastes, or smells); and
8. Perceived quality (inferences about quality based on image, brand name and advertising
rather than product attributes and, of course, is subjectively assessed) (Sebastianeli &
Tamimi, 2002:442).
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
Performance, features, reliability, conformance, durability and serviceability are
associated with the use specification, while aesthetics and perceived quality are related to the
aesthetic specification. Manufacturers and service providers should recognize that different
customer groups focus on different sets of quality dimensions. It appears that both performance
and features of a product or service are considered by virtually all customers. However,
serviceability, aesthetics and perceived quality would be more important in the evaluation of
service quality, whereas reliability, conformance and durability would be critical in determining
product quality in general. Value mix describes customers’ determination of the value of a
product or service in terms of function, quality and price. Cost, as not regarded by customers, is
excluded. It is these three elements (function, quality and price) which form the value mix that
every organization should consider when designing and delivering product and service
(Ho&Cheng, 1999:207).
Based on the above definitions, we propose the following value based attributes:
Table 1: Proposed Value Based Attributes
Components
Attributes
Price
List price
Function
Data quota
Coverage
Quality
Features
Customer service
Connection stability
Connection speed
Overall product quality
Overall service quality
These attributes were then discussed in focus group discussions (FGD) amongst selected
consumers. FGD were conducted to reveal attributes consumers considered the most important
regarding mobile ISP. Results of these discussions are as follows:
- Participants of FGD agreed that proposed attributes in the table above is important.
- Among other things, they also considered promotional programs, ease of activation, ease of
reload, advertising campaign, provider’s reputation, brand ambassador and data package
variation as important factors regarding mobile ISP.
These attributes were further discussed in more depth FGD to screened which ones is the most
valued by consumers regarding mobile ISP. The selected attributes were then asked in
questionnaires.
Importance Performance Analysis
Importance-performance analysis (IPA) technique first introduced into the field of
marketing in the late 1970s. IPA is an analytical technique that firms use both to evaluate their
competitive position and to set priorities in order to enhance customer satisfaction (Martilla and
James, 1977 in Keyt, et.al., 1994:35). It has been a popular multi-attribute technique for
evaluating marketing actions, as it yields insights into which elements of a value proposition the
management should focus on. IPA decomposes a value proposition by classifying its most
important attributes in two dimensions, that is, the importance of each attribute and judgments
of its performance (Martilla and James, 1977). Based on average rankings from a sample of
customers, these two elements are combined in order to generate managerial
recommendations as seen in figure 2 (Arbore & Busacca, 2011:409).
The IPA was introduced by Martilla and James (1977) as a method for developing
effective marketing programs. Through such simple data processing, organizations can directly
examine different types of attribute and form strategies and plans, based on each of the four
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
quadrants in IPA map. In the questionnaire survey, respondents were asked two questions
about each quality attribute:
1. How important is this attribute?
2. How well did the organization perform?
The analysis pattern is formed simply by two axes – importance and performance – based on
the above questions. The median determines the central tendencies of importance and
performance for attribute and is considered as a classifier in the IPA map. Several scholars
used the mean instead of median to represent the central tendencies in the IPA map. Therefore,
as in the model, the mean value became the main statistic for analyzing and comparing attribute
importance and performance. Figure 2 depicts a traditional graph of an easily interpretable, two
dimensional map. The interpretation of the importance-performance map is provided in the four
quadrants, as below:
1. Concentrate here. Customers believe that attribute is very important, but indicate low
satisfaction with the organization’s performance.
2. Keep up the good work. Customers believe that attribute is very important and indicate high
satisfaction with the organization’s performance.
3. Low priority. Organizational performance in terms of attribute is low, but customers do not
perceive them to be very important.
4. Possible overkill. The organization is judged to be excellent in terms of attribute, but
customers give only slight importance to them (Lee & Yen, 2008:491).
Figure 2: Traditional Importance-Performance Map
3. Methodology
Data Collection
There are two types of data required in the study. The first is secondary data including
newspaper, previous publication, and textbook. The second is primary data that collected
through interview, focus group and questionnaire. The questionnaire for this study included two
main sections.
The first section of the questionnaire consisted of 13 mobile internet provider attributes,
for which consumers were asked to indicate the perceived importance of the attributes when
they choose a mobile internet provider, and the second section are their perceptions of actual
mobile internet provider performance during their experience.
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
These attributes were identifed based on a review of relevant literature and focus group
discussions. To identify the relevant mobile internet provider attributes, a list of 16 attributes was
screened out in the first stage. This list of attributes was then discussed with a group of
academic professionals and mobile ISP consumers. After a careful screening analysis, 13 of the
16 attributes were selected. These 13 attributes were regarded as the influential factors in
mobile ISP selection.
The questionnaire was structured so that each mobile internet attribute was rated using a
4 point Likert scale, ranging from 1, least important to 4, most important, in the importance part,
and from 1, strongly disagree, to 4, strongly agree, in the performance part.
Sampling Method
The sample chosen in this study are 400 mobile internet consumers using convenience
sampling technique. As convenience sampling define, sample members are people who easy to
acces according research purpose (Riduwan & Akdon, 2010:242).
Data Analysis
Descriptive statistics were computed in this study including the respondent’s
demographic profiles and on the 13 mobile provider attributes. Exploratory factor analysis with
VARIMAX rotation was also employed on the perceived importance of the 13 mobile internet
provider attributes. The objectives of using factor analysis were to create correlated variable
composites from the 13 mobile internet provider attributes so as to identify a convenience set of
factors that explained most of the variances among the attributes.
The determination of including attribute in a factor was based on the KMO and Bartlett
test. KMO & Bartlett’s Test of Sphericity is a measure of sampling adequacy that is
recommended to check the case to variable ratio for the analysis being conducted. While the
KMO ranges from 0 to 1, the world-over accepted index is over 0.6. Also, the Bartlett’s Test of
Sphericity relates to the significance of the study and thereby shows the validity and suitability of
the responses collected to the problem being addressed through the study. For Factor Analysis
to be recommended suitable, the Bartlett’s Test of Sphericity must be less than 0.05.
Important Performance Analysis was then employed to compare the consumer’s
perceptions of the derived factors’ importance and perfomance (from factor analysis). In this
study, factor means of the perceived importance and performance of each factor were
calculated and plotted into a graphical grid. Cross-hairs (vertical and horizontal lines), mean
values of the importance and performance attribute were calculated to separate the derived
factors into four identifiable quadrants.
4. Findings and Discussion
Demographic Characteristics of Respondents
A total of 400 respondents completed the questionnaire in the seven-day survey period.
From this 400 respondents, 46.75 percent were male and 53.25 percent were female. Tables
below show the demographic characteristics of the respondents, respectively.
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
Table 2: Respondent’s Characteristic by Gender
SEX
Male
Female
TOTAL
PERCENTAGE
46.75
53.25
100
According to table1, 62.5% respondents were aged under 21, 31.5% were aged 21 – 30
years old, 2% were aged 31-40 and 4% above 40. This is almost similar to the data from
communication ministry, that there are 45 million internet users in Indonesia, which 64 percent
on the age of 15 to 19 (source:http://en.wikipedia.org).
Table 3: Respondent’s Characteristic by Age
AGE
20 or below
21 – 30
31 – 40
Above 40
TOTAL
PERCENTAGE
62.50
31.5
2.0
4.0
100
With regard to the education level, the results showed that the majority of respondents
were students in high school or university, whereas about 16 percent of the respondents were
workers.
Table 4: Respondent’s Characteristic by Occupation
OCCUPATION
Student (Junior High School)
Student (Senior High School)
Student (University)
Workers
TOTAL
PERCENTAGE
1.3
12.3
70.0
16.5
100
The survey also indicated that 32.8% respondents were using provider A, 18.8% using provider
B, 28.8% using provider C, 2.8 percent using provider D, 12.8% using provider E, 4.8% using
provider F and only 0.3% using provider G.
Table 5: Respondent’s Characteristic by Provider Used
PROVIDER
A
B
C
D
E
F
G
TOTAL
PERCENTAGE
32.8
18.8
28.0
2.8
12.8
4.8
.3
100
Factor Analysis Results
The perceived importance of the 13 mobile internet provider attributes was factoranalysed, using principal component analysis with orthogonal VARIMAX rotation, to identify the
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
underlying dimensions. The exploratory factor analysis was conducted in order to gain a better
understanding of the underlying structure of the data (Pitt & Jeantrout, 1994). It also served to
simplify the subsequent IPA procedures.
Table 6
KMO and Bartl ett's Test
Kaiser-Mey er-Olkin Measure of Sampling
Adequacy .
Bart lett 's Test of
Sphericity
Approx. Chi-Square
df
Sig.
.858
1362.044
78
.000
Table 7: MSA, Factor Loading, Eigenvalue & Communalities
MSA
(ANTI IMAGE
MATRICES)
FACTOR
LOADING
1
List Price
Sales Promotion
Data Quota
Customer Service
Features
Advertising
Data Package Variation
Provider’s Reputation
0.854
0.935
0.908
0.858
0.895
0.905
0.877
0.895
0.586
0.546
0.578
0.594
0.678
0.572
0.595
0.451
2
Connection Stability
Coverage
Connection Speed
0.833
0.811
0.887
0.814
0.844
0.671
3
Ease of Activation
Ease of Reload
0.777
0.713
0.779
0.847
FACTORS/ ATTRIBUTES
EIGENVALUE
COMMUNALITIES
4.480
0.358
0.377
0.418
0.416
0.498
0.457
0.393
0.404
1.280
0.691
0.742
0.604
1.120
0.747
0.766
Results of the factor analysis suggested a three-factor solution, included 13 provider
attributes with eigenvalues greater than 1.0, and The Measure of Sampling Adequacy from AntiImage Matrices was greater than 0.50. The factor analysis in this study proved to be acceptably
valid with the following observations:
1. The overall signifcance of the correlation matrix was 0.000 with a Bartlett Test of Sphericity
value of 1362.044, suggesting that the data matrix had sufficient correlation to factor
analysis. It appeared unlikely that the population correlation matrix was an identity and the
use of factor analysis was considered appropriate.
2. The Kaiser-Meyer-Olkin (KMO) overall measure of sampling adequacy was 0.858, which
was meritorious (Kaiser, 1974). Since the KMO value was above 0.80, the variables were
interrelated and they shared common factors.
3. The communalities ranged from 0.358 to 0.766 with an average value above 0.5, suggesting
that the variance of the original values were fairly explained by the common factors. The
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
results of the factor analysis produced a clean factor structure with relatively higher loadings
on the appropriate factors.
Table 8: Mean Ratings Of Importance and Performance
ATTRIBUTES
IMPORTANCE
MEAN
STD DEV
PERFORMANCE
MEAN
STD DEV
1
List Price
Sales Promotion
Data Quota
Customer Service
Features
Advertising
Data Package Variation
Provider’s Reputation
3.44
3.15
3.51
3.41
3.38
3.38
3.3
3.28
0.662
0.750
0.671
0.658
0.638
0.694
0.686
0.713
3.01
2.93
2.89
2.98
2.95
2.77
2.98
3.12
0.594
0.627
0.644
0.606
0.568
0.710
0.654
0.641
2
Conection Stability
Coverage
Conection Speed
3.77
3.71
3.74
0.477
0.580
0.521
2.95
2.82
2.83
0.639
0.733
0.753
3
Ease of Activation
Ease of Reload
3.53
3.49
0.595
0.656
3.13
3.27
0.626
0.575
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
Importance Performance Analysis Results
Figure 3: IPA Diagram
3.80
1
6
3
7
5
8
2
9
3.40
11
E
IMPORTANCE
3.60
10
12
13
3.20
4
2.70
2.80
2.90
3.00
3.10
3.20
3.30
PERFORMANCE
1
Connection Stability
8
Ease of Reload
2
List Price
9
Customer Service
3
Coverage
10
Features
4
Sales Promotion
11
Advertising
5
Data Quota
12
Data Package Variation
6
Conection Speed
13
Provider’s Reputation
7
Ease of Activation
Quadrant I: Concentrate Here
Attributes in this quadrant are perceived to be very important to respondents, but
performance levels are fairly low. This sends a direct message to the provider that improvement
efforts should be concentrated here. Four attributes were identified in this quadrant. They were
connection stability, coverage, data quota, and connection speed.
This condition is in line with the reality where there are many customers who complained
about those attributes of their mobile ISP. According to the survey conducted by Ericsson
Consumer Research Lab, as much as 79% of customers often have problem with the network’s
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
coverage at least once a week. Even 52% of customers stated that they face this problem
several times a day. (source : http://www.beritasatu.com)
The majority of respondents also expressed dissatisfaction with the mechanism of data
quota imposed by the provider. Based on researchers’ observations, complaints arise because
this has made customers only have limited access. Furthermore, this complain also arise
because customer’s inability to control the internet quota owned. Because of the above
reasons, mobile ISPs should allocate more resources to improve the attributes that are in this
quadrant.
Quadrant II: Keep Up The Good Work
Attributes in this quadrant are perceived to be very important to respondents, and at the
same time, the organisation seems to have high levels of performance on these activities. The
message here is To Keep up the Good Work. Two mobile internet attributes were identified in
this quadrant. They were: ease of activation and ease of reload.
Fierce competition among mobile ISPs has made them creating ways to provide
customer with ease of activation and ease of reload. There are many sellers on every street
corner offer credits for their mobile internet service, make it easier for customers to reload their
pulse back. Plus, nowadays many mobile ISPs do not use physical vouchers to reload anymore.
They prefer to sell the more convenient electronic voucher. Nevertheless, the small amount of
attributes in this quadrant indicates that there is still a lot of homework to be done by the mobile
ISPs to satisfy their customers' expectations.
Quadrant III: Low Priority
Attributes in this quadrant are with low importance and low performance. Although
performance levels may be low in this cell, managers should not be overly concerned since the
attribute in this cell is not perceived to be very important. Limited resources should be expended
on this low priority cell. Three mobile internet provider attributes were identified in this quadrant.
They were sales promotion, feature and advertising.
Efforts are being made by mobile ISPs on these attributes, such as the massive ad
impressions on television, newspapers, magazines, and so forth. Some providers even involve
in hostile competition to attract the attention of customers. Mobile ISPs also give sales
promotion efforts vigorously by giving free package bonuses at service’s activation or service’s
rel. However, the customers still consider that these attributes of a low performance. This is not
a problem, because these attributes level of importance are also low.
Quadrant IV: Possible Overkill
This cell contains attributes of low importance, but relatively high performance.
Respondents are satisfied with the performance of the organisations, but managers should
consider present efforts on the attributes of this cell as being overutilised. Four mobile internet
attributes were identified in this quadrant. They were list price, customer service, data package
variation and provider’s reputation.
Fierce competition among mobile ISPs has made them lower the price to make it more
affordable and appealing for customers. When compared with previous years, especially in the
early 2000s, tariffs imposed on mobile internet service now are far cheaper. Based on
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
observations, Indonesian customers can access the internet on a mobile service provider with a
price of Rp. 5,000 only.
The same as customer service, variety of products and provider’s reputation attributes.
Each
mobile
ISP
has
given
good
performance
in
these
attributes.
However, the customers seem to be quite pragmatic in the use of mobile ISPs, so they do not
overly concerned with it. To that end, mobile ISPs should be able to allocate their resources on
more important attributes in quadrant I.
5. Conclusion
Factors valued by consumers in choosing a mobile internet service provider has
categorised the 13 attributes as follows: Price, Sales Promotion, Quota, Customer Service,
Feature, Advertising, Variation, Brand Image, Stability, Coverage, Speed, Ease of Activation
and Reload.
Using IPA, this study has compared the importance and performance of the mobile
internet provider selection factors. Factors are considered important by consumers and have
performed well are ease to activate and ease to reload. Factors are considered important by
consumers but haven’t performed well include Stability, Coverage, Quota, and Speed.Factors
are considered less important by consumers but have performed well include sales promotion,
feature and advertising.Factors that are considered important by consumers and haven’t
performed well include price, customer service, variation and brand image.
References
Arbore, Alessandro., Bruno Busacca. 2011. Rejuvenating Importance Performance Analysis.
Journal of Service Management, Volume 22 No. 3, pp. 409-430. Emerald Group
Publishing Limited.
Evans, George. 2002. Measuring and Managing Customer Value. Work Study, Volume 51
Number 3, pp. 134-139. MCB UP Limited.
Ho, Danny C.K., Eddie W.L. Cheng. 1999. Techniques Quest For Value Mix. Managing Service
Quality, Volume 9 Number 3, pp. 204-208. MCB University Press.
Keyt, John C., Ugur Yavas, Glen Riecken. 1994. Importance Performance Analysis, A Case
Study in Restaurant Positioning. International Journal of Retail and Distribution
Management, Volume 22 No. 5, pp. 35-40. MCB University Press.
Kotler, Philip, Kevin Lane Keller. 2012. Marketing Management 14th edition. England, Pearson
Education Limited.
Landroguez, Silvia Martelo, Carmen Barosso, Gabriel Cepeda-Carrion. 2013. Developing an
Integrated Vision of Customer Value. Journal of Services Marketing, 27/3, pp. 234-244.
Lee, Yu-Cheng, Tieh-Min Yen. 2008. Modify IPA for Quality Improvement: Taguchi’s Signal-toNoise Ratio Approach. The TQM Journal, Volume 20 No. 5, pp. 488-501. Emerald Group
Publishing Limited.
Proceedings of World Business and Social Science Research Conference
24-25 October, 2013, Novotel Bangkok on Siam Square, Bangkok, Thailand, ISBN: 978-1-922069-33-7
Sebastianelli, Rose. Nabil Tamimi. 2002. How Product Quality Dimensions Relate To Defining
Quality. International Journal of Quality and Relialibity Management, Volume 19 No. 4,
pp. 442-453. http://en.wikipedia.org/wiki/Internet_in_Indonesia
http://www.beritasatu.com/digital-life/136254-studi-kepuasan-pengguna-jaringan-3g-diindonesia-paling-rendah.html
Download