View of FACTORS INFLUENCING SUBSCRIBER’S PREFERENCES FOR MOBILE SERVICE PROVIDERS: AN INVESTIGATION IN INDORE CITY

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Vol.03, Issue 09, Conference (IC-RASEM) Special Issue 01, September 2018 Available Online: www.ajeee.co.in/index.php/AJEEE

FACTORS INFLUENCING SUBSCRIBER’S PREFERENCES FOR MOBILE SERVICE PROVIDERS: AN INVESTIGATION IN INDORE CITY

1Dr. Sopnamayee Acharya

Assistant Professor, Prestige Institute of management and Research, Indore [email protected]

2Dr. Satnam Ubeja

Assistant Professor, Prestige Institute of management and Research, Indore [email protected]

India is seeing significant changes in the ways of life of extensive segment of the populace.

India is the second biggest portable membership showcase on the planet after China. In the start of the 21st Century, mobile phone utilize turned into a furor, an image of cash and achievement. These days even children discover it a need of life. Cell phone membership has expanded generously in India and it covers over 75% of the Indian populace.

Understanding clients has turned into a major test to the Mobile Service Providers (MSPs), particularly with regards to making and dealing with an intense brand. The present examination explores to recognize the factors impacting subscribers' inclinations for MSPs.

This investigation utilizes essential information gathered through purposive testing of 500 cell phone supporters. A survey, planned by the author, has been circled in the Indore District of Madhya Pradesh State. This investigation finds that 33% of the subscribers incline toward Vodafone and additionally Airtel services. The Chi-square analysis uncovers that there is a significant relationship between inclination of MSPs and respondents' attributes, for example, age, qualification, occupation and family income. There are additionally other six distinct components which are likewise in charge of subscribers' inclinations of MSPs.

Key words: Mobile Service Providers, Subscribers, Chi-square test, subscribers‟ preference.

1 INTRODUCTION

Branding is the statement of reality or organization's esteem, including items, administrations, individuals, promoting, situating and culture. Along these lines, branding is viewed as imperative to the accomplishment of any business including telecom service. The telecom services have been perceived the world- over as a vital instrument for financial improvement for a country. It is one of the prime help service required for fast development and modernization of different segments of the economy. Along these lines, mobile subscription, specifically portable membership has been encountering fast development around the globe. In 1999, there were 490 million memberships around the world.

Today, there are equivalent to the worldwide populace of 7.1 billion. Among this huge development India is the quickest developing cell phone showcase and has the second biggest mobile market about a billion memberships. The cell phone membership construct was 947 million in light of March' 2014 in contrast with the endorser construct 9 04.51 million in light of March' 2014 enlisting a development of 4.70% amid the money related year 2014-15.

The status of cell phone membership base amid the most recent 7 years is delineated in Figure-1 and in spite of a long history, the mobile phone services has developed at a noteworthy pace as far as endorser base at a Compounded Annual Growth Rate (CAGR) of 16 percent for these periods. The quick development of mobile phone services has made telecom operators are thinking of new thoughts and system to give new and simple administrations to their clients. It has been demonstrated that the huge players like Relaince, Bharti Airtel, Vodafone Essar, and Idea pulled in 60% of piece of the overall industry. Moreover, versatile mobile operators have been more cognizant to give world class and best offices to their clients with a specific end goal to keep up their market and draw in crisp memberships.

Figure - 1: Mobile Phone Subscribers (in

%)

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Figure - 2: India's Largest Mobile Telecom operators (in millions) Source: Reports from Telecom Regulatory Authority of India

1.1 Problem Statement

Presently Mobile Number Portability (MNP) enables end users of progress their specialist organization while holding their current number. During the month of Dec 2017, a total 7.43 million requests were received for MNP. With this the cumulative MNP asks for expanded from 330.98 Million supporters toward the finish of Oct 2017 to 338.41 Million toward the finish of Dec 2017. These insights clarify that exchanging conduct of cell phone end users has been expanding pattern from favored support of another.

In this way, the MSPs have awesome mindful to fulfill their significant clients through improve the administration execution. It has held the market position and draw in new clients in the focused period. In this way, MSPs needs to comprehend the statistic example of the supporters and components that dependable to mark decision. The above said articulation figures the accompanying inquiries in the psyches of the scientist.

 Which is a most favored versatile specialist co-op?

 Is there any critical relationship towards inclination of MSPs crosswise over statistic factors?

 What are the components affecting the inclination of MSPs among the end users?

Keeping in mind the end goal to discover the responses for the above inquiries the specialist has attempted this exploration work titled "Factors Influencing Subscriber's Preferences for Mobile Service Providers: An Investigation in Indore City" with the following objectives.

2 REVIEW OF LITERATURE

Zohaib Ahmad and Junaid Ahmad (2014) in their study titled “Consumer Purchase Behavior in Cellular Service Sector” says that the dominant factors quality, price, promotions, and social factors reflects the latest buying behavior of people or not. The study reveals that the social factor is the most dominating factor which determines the purchase behavior and basically reflects the societal image of the consumers.

Arvind and Claudia Kubowicz (2013) in their study mentioned Customers perceive their service provider to be innovative, they are less likely to switch to another provider; the perception of being innovative is equally as important as the perception of the service quality delivered by the provider in the USA mobile service environment”.

Dapeng et al. (2013) explain core service failure, high price, ethical problems, competition, inconvenience, service encounter failure, and influence from reference group are the responsible factors that cause customers to switch mobile phone service providers in China‟s mobile phone service sector.

Lalit and Manish (2009) Network problem was observed to be the most important reason for switching over to other mobile phone service provider among rural customers.

Rajkumar and Chaarlas (2012) analyze the association between the demographic characteristics of respondents and their brand switching.

The authors find that the clients do not switch over brands because of personal issues faced by them.

Rujipas et al. (2012) Mobile phone network subscribers make decision to subscribe mobile phone service by taking mobile phone concerning on identity, usage, and expenses aspects in Thailand and also attitude towards mobile phone and marketing mixed have significant impacts on decision to subscribe mobile phone service.

Ahmed and Jennifer; (2011) says advertising, publicity, word of mouth, price quality, brand personality, corporate image and reputation, customers‟

satisfaction, perceived risk and reference group are the antecedents of brand preference in the context of telecommunications service brands in Jordan (.

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Lalit and Manish; (2009) in their study describe network coverage, price, value- for-money and billing integrity, recommendations from family and friends, customer service and company image are the major factors that selection of mobile phone service provider among rural users.

Juha; (2008) mentioned there is a significant and positive relationship exists between customers‟ price perceptions and their purchase intentions in the Finnish mobile services market.

Vijayakumar & Ruthra Priya;

(2006) found satisfaction derived by the subscribers of Airtel Network has been influenced by the clarity of signals, availability of plan options, low call charges and activation formalities).

2.1 Objectives

 To find out the subscribers‟

preference of MSPs and also to analyze the relationship towards preference of MSPs across demographic factors.

 To find out the influencing factors on preference of MSPs among the subscribers.

2.2 Hypotheses

Ho1: There is no significant association between demographic factors of the subscribers and their preference of MSPs.

Ho2: There is no significant association among the factors that influence subscriber‟s preference towards MSPs.

3 METHODOLOGY

This Empirical study has been utilized both primary and secondary data source however the induction fundamentally relies upon the primary data. The data were gathered from 500 legitimate respondents in different spots of Indore

District in Madhya Pradesh. Self-outlined questionnaire comprised of two sections.

The initial part managed demographic factors like place of living, age, qualification, occupation and income of the respondents. The second part which discussed preference of MSPs and also respondent's agreement level towards factors that impact to preference of MSPs which were estimated with five point scale in particular „strongly disagree,‟ „disagree,‟

„neither disagree nor agree,‟ „agree‟ and

„strongly agree‟ with proper technique.

Purposive sampling technique is most appropriate for present research.

The secondary information has been useful to create hypothetical piece of the study which is gathered from reports of Telecom Regulatory Authority of India (TRAI), diaries, books and different sites.

The tools utilized for this investigation are percentage analysis, chi-square (χ²) test, Kaiser-Meyer-Olkinand Bartlett's Test of Sphericity Approach, Factor Analysis.

4 ANALYSIS AND INTERPRETATION:

Demographic factors of the respondents

Distribution of the respondents in light of their demographic factors (place of living, age groups, educational qualification, Occupational Status and family Income) is given in the table below. It demonstrates that almost 80% of the respondents are living in urban regions.

This is trailed by the greater part of the respondents have a place with the age gathering of upto 25 years, 44.2% of the respondents have larger amount instructive capability, about portion of the respondents are utilized and minimal over 40% of the respondent's family salary is Rs. 10,001 to Rs. 15,000 every month

. Table - 1: Demographic Factors of the Respondents

Factor Attributes No. of Respondents %

Place of Living Urban 400 80

Rural 100 20

Age group (in years)

Up to 25 266 53.2

26-40 183 36.6

41-55 34 6.8

Above 55 17 3.4

Educational Qualification

No formal education (I-VIII) 79 15.8

School level (VIII-XII) 200 40

Higher Education 221 44.2

Occupational Status Pvt./ Govt. Employee 235 47

Businessmen 114 22.8

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Professional 65 13

Student 76 15.2

Agriculturists 10 2

Family Income (Rs. Per month)

Up to 10,000 100 20

10,001 – 15,000 201 40.2

15,001 – 20,000 71 14.2

Above 20,000 128 25.6

4.1 Preference of MSPs

Distribution of the respondents based on their preference of MSPs is given in the figure below and it can be concluded that maximum respondents are using the mobile network Reliance Jio 34.2% and 23% of the respondents are used to the mobile network services provided by Airtel. Then, the service provided by Vodafone services (17.6%), Ideae service (16.8%), BSNL (8.4%) are in preferred way

Figure 3: Preference of MSPs (in %)

Source: Field survey

4.2 Preference of MSPs across Demographic Factors

Ho: There is no significant association between place of living, age groups, educational qualification, and occupational status, family incomes of the respondents and their preference of MSPs.

Table - 2: Relationship of Demographic factors and Preference of MSPs Factor

Factor Χ² df Table Value Result

Place of Living 18.13 10 18.31 at 5% & 23.21 at 1% level Accept Ho

Age group (in years) 79.36 30 43.77 at 5% & 50.89 at 1% level Reject Ho

Educational Qualification 37.52 20 31.41 at 5% & 37.57 at 1% level Reject Ho

Occupational Status 62.16 40 55.76 at 5% & 63.69 at 1% level Reject Ho

Family Income (Rs. Per month) 81.35 30 43.77 at 5% & 50.89 at 1% level Reject Ho

Source: Field Survey

It is observed from the Table – 2 that there is no significant association between rural and urban areas towards preference of MSPs where as there is a significant relationship on preference of MSPs among various age groups of the respondents.

Table – 2 shows that there is a significant relationship on preference of MSPs among various educational qualifications of the respondents. It is also inferred from the Table – 2 that the calculated value of (χ²)

is 62.16 which is lesser than the tabulated value of 63.69 at 1% level but greater than the tabulated value of 55.76 at 5% level. Hence, Reject Ho at 5% level and it is concluded that there is a significant relationship on preference of MSPs among various occupational statuses of the respondents. Lastly it is observed from the Table – 2 that there is a significant relationship on preference of

Respondents Percentage

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MSPs among various family incomes of the respondents.

Respondents’ perception towards preference of MSPs – Kaiser Meyer- Olkin (KMO) and Bartlett’s test of sphericity approach

The KMO measure of sampling adequacy is an index that compares the sizes of the observed correlation coefficients to the sizes of the partial correlation Coefficients. Further, Bartlett‟s test of Sphericity tests whether the correlation matrix is an identity matrix, which would indicate that the factor model is inappropriate or appropriate.

Ho: There is no significant association among the variables that influence subscriber‟s preference towards MSPs.

Table – 3: KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy

0.734

Bartlett‟s Test of Sphericity

χ² 4575.095**

df 171

**Sig. at 1% and * Sig. at 5% level

Bartlett‟s test of sphericity is used to test whether the correlation matrix is an identity matrix. The χ2 test value 4575.095 and the significance level (p<.01) which are given above indicate that the correlation matrix is not an identity matrix, i.e., there exists correlations between the variables.

Kaiser-Meyer-Olkin (KMO) measure of

sampling adequacy is 0.734 which closer to 0.8, and then it is good to use for further test.

4.3 Factor Analysis:

The common intention of Factor Analytic technique is to find way of condensing (summarizing) the information contained in a number of original variables into a smaller group of new composite factors with a minimum loss of information.

In order to Principal Component Analysis (PCA) was used. PCA is usually done when we have a number of observed variables that are believed to influence a given dependent variable, but then these variables are so many that they are correlated. In this situation we want a smaller number of important variables that will account for most of the variance in the observed variables. Further, Varimax rotations have been used in order to simplify the factor structure by maximizing the variance of a column of pattern matrix because it is one of the most popular methods used in several social sciences research papers. In addition Eigen value is also used; it helps to find out the amount of variance in overall data. Finally, determination of the factors based on the factor score are estimated for each factor with a new name given about grouped variables. Factor Analysis technique has been applied to find out the underlying dimensions (factors) that exists in the nineteen variables relating to the responsible factors on preference of MSPs. The results are presented here below.

Table – 4: Influencing factors on Preference of MSPs

Attributes I II III IV V VI Communalities

V1 0.133 0.140 -0.040 0.733 0.044 -0.103 0.589

V2 0.333 0.220 0.300 0.605 0.118 0.295 0.717

V3 0.211 0.723 0.204 0.259 -0.085 0.114 0.696

V4 0.119 0.556 0.239 -0.227 -0.135 0.451 0.653

V5 -0.109 0.082 0.149 0.745 -0.304 0.050 0.691

V6 0.190 0.860 -0.007 0.071 -0.051 -0.105 0.795

V7 0.483 0.623 0.073 0.275 -0.132 0.089 0.728

V8 0.856 0.197 0.054 0.064 -0.132 -0.031 0.798

V9 0.806 0.291 0.132 0.199 -0.065 -0.016 0.795

V10 0.745 0.074 0.161 -0.022 -0.131 0.285 0.685 V11 0.447 -0.255 -0.100 0.489 -0.129 0.443 0.727 V12 0.320 0.251 0.757 -0.005 -0.140 -0.157 0.783

V13 0.114 0.084 0.104 0.069 0.059 0.702 0.532

V14 0.273 0.072 0.541 -0.046 -0.488 0.004 0.612

V15 0.023 0.043 0.854 0.200 -0.015 0.253 0.836

V16 -0.235 -0.035 -0.105 -0.112 0.829 0.218 0.814 V17 -0.055 0.019 0.250 0.045 0.577 -0.470 0.621 V18 -0.005 -0.291 -0.283 -0.133 0.572 -0.112 0.523

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V19 0.586 0.414 0.269 0.033 -0.046 0.226 0.642

Eigen

Value 3.197 2.564 2.107 2.022 1.819 1.527 13.236

% of

Variance 16.825 13.494 11.090 10.644 9.575 8.030 69.665 Cum % of

Variance 16.825 30.319 41.409 52.053 61.628 69.665

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization Table - 4 gives the rotated factor loadings,

communalities, eigen values and the percentage of variance explained by the factors. Out of the nineteen variables, only six factors have been extracted and these factors put together explain the total variance of these perceptions towards influencing factors on preference of MSPs to the extent of 70%. In order to reduce the number of factors and

enhance the interpretability, the factors are rotated. The rotation increases the quality of interpretation of the factors.

There are several methods of the initial factor matrix to attain simple structure of the data. The Varimax rotation is one such method to obtain better result for interpretation is employed and the results

are given in Table - 5

. Table - 5: Responsible Factors on Preference of MSPs: Final Framework

Variables Rotated Factor

Loadings Factor

V8 – Cheaper Call Rate .856

I – 16.825 V9 – Attractive Offers .806

V10 – Free Calls .745 V19– Booster card options .586

V6 – Talk time .860

II – 13.494

V3– Pulse rate .723

V7 – Validity .623

V4 – Free SMS .556

V15– Frequent communication about new schemes .854

III – 11.090 V12– Prompt Customer service .757

V14 – Value added Services .541 V5– Clarity in Tariff .745

IV – 10.644 V1 – Cost of initial pack .733

V2 – Availability of recharge

coupons .605

V11– Network coverage .489 V16 – Advertisement .829

V – 9.575 V17 – Reference group .577

V18 – User trend .572

V13 – Brand name .702 VI – 8.038

Six factors were identified as being maximum percentage variance accounted.

The 4 perceptions V8, V9, V10 and V19 were grouped together as factor I and accounts 16.825 % of the total variance.

The 4 perceptions V6, V3, V7 and V4 constituted the factor II and accounts 13.494% of the total variance. The 3 perceptions V15, V12 and V14 constituted the factor III and accounts 11.090% of the total variance. The 4 perceptions V5, V1, V2 and V11 constitute the factor IV and accounts for 10.644% of the total variance. The 3 perceptions V16, V17 and V18 constituted the factor V and accounts

9.575% of the total variance. The perception of V13 constitute the factor VI and accounts for 8.038%. Thus the factor analysis condensed and simplified the nineteen perceptions and grouped into six factors explaining 70% of the variability of all the variables.

5 CONCLUSION

Mobile network service segment is developing at a quick rate. Prior the subscribers had just constrained decision for their specialist organization however now the subscribers have distinctive administrators in the market. The present supporters pick specific specialist co-op

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which satisfy their each interest identified with versatile system. The examination uncovers that Vodafone, Airtel, and BSNL remain the best three specialist organizations favored by the respondents.

Unmistakably the vast majority of the cell phone subscribers were profoundly impacted by the components, for example, appealing offers talk time highlights, incite client benefit, arrange inclusion, reference gathering and friends' image name. The MSPs need to give more consideration regarding these variables with a specific end goal to hold the current memberships and furthermore to draw in new memberships.

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