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. disastra31@yahoo.com Heppy Millanyani, Marketing Management Program, Telkom University, Jl. Telekomunikasi No.1 Bandung. heppymilltoo@yahoo.com
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. To explore what factors valued by consumers in choosing a mobile internet service provider. 2. To know consumers perception refarding the factors performance. 3. To know consumers expectations regarding mobile internet service provider. 4. To know what factors are considered important by consumers and have performed well. 5. To know what factors are considered important by consumers but haven t performed well. 6. To know what factors are considered less important by consumers but have performed well.
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).
Figure 1: Components of Value Mix Customer Needs Use Function Aesthetic Function Performance Feature Reliability Conformance Durability Serviceability Aesthetics Perceived Quality Function 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).
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 Price Function Quality Attributes List price Data quota Coverage 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
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.
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.
Table 2: Respondent s Characteristic by Gender SEX PERCENTAGE Male 46.75 Female 53.25 TOTAL 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 PERCENTAGE 20 or below 62.50 21 30 31.5 31 40 2.0 Above 40 4.0 TOTAL 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 PERCENTAGE Student (Junior High School) 1.3 Student (Senior High School) 12.3 Student (University) 70.0 Workers 16.5 TOTAL 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 PERCENTAGE A 32.8 B 18.8 C 28.0 D 2.8 E 12.8 F 4.8 G.3 TOTAL 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
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 Bartlett's Test Kaiser-Mey er-olkin Measure of Sampling Adequacy..858 Bartlett's Test of Sphericity Approx. Chi-Square df Sig. 1362.044 78.000 Table 7: MSA, Factor Loading, Eigenvalue & Communalities FACTORS/ ATTRIBUTES MSA (ANTI IMAGE MATRICES) FACTOR LOADING EIGENVALUE COMMUNALITIES 1 4.480 List Price 0.854 0.586 0.358 Sales Promotion 0.935 0.546 0.377 Data Quota 0.908 0.578 0.418 Customer Service 0.858 0.594 0.416 Features 0.895 0.678 0.498 Advertising 0.905 0.572 0.457 Data Package Variation 0.877 0.595 0.393 Provider s Reputation 0.895 0.451 0.404 2 1.280 Connection Stability 0.833 0.814 0.691 Coverage 0.811 0.844 0.742 Connection Speed 0.887 0.671 0.604 3 1.120 Ease of Activation 0.777 0.779 0.747 Ease of Reload 0.713 0.847 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 Anti- Image 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
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 PERFORMANCE MEAN STD DEV MEAN STD DEV 1 List Price 3.44 0.662 3.01 0.594 Sales Promotion 3.15 0.750 2.93 0.627 Data Quota 3.51 0.671 2.89 0.644 Customer Service 3.41 0.658 2.98 0.606 Features 3.38 0.638 2.95 0.568 Advertising 3.38 0.694 2.77 0.710 Data Package Variation 3.3 0.686 2.98 0.654 Provider s Reputation 3.28 0.713 3.12 0.641 2 Conection Stability 3.77 0.477 2.95 0.639 Coverage 3.71 0.580 2.82 0.733 Conection Speed 3.74 0.521 2.83 0.753 3 Ease of Activation 3.53 0.595 3.13 0.626 Ease of Reload 3.49 0.656 3.27 0.575
IMPORTANCE E Proceedings of World Business and Social Science Research Conference Importance Performance Analysis Results Figure 3: IPA Diagram 3.80 1 6 3 3.60 5 7 8 2 9 3.40 11 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
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
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-to- Noise Ratio Approach. The TQM Journal, Volume 20 No. 5, pp. 488-501. Emerald Group Publishing Limited.
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