What makes Consumer to Quit? Exploring the Dynamics of Consumer Churning Behaviour for Telecom Sector in Delhi-NCR

INTRODUCTION

Current technological advancements in the telecom sector have eased out the complicated and lengthy processes of earlier times. The journey of this sector from a simple telephone to the internet to the data transfer speed race, it has been remarkable and at this time, it acts as the nervous system of every organisation or even a household. According to the annual report prepared by GSMA Foundation and Boston Consulting Group (BCG) jointly, the Indian telecom sector is growing exponentially and it is expected to add 27 per cent new subscribers by 2020 in the global markets. The Indian telecom industry has reached the second position in the world with 1.17 billion subscribers and 512.26 million internet subscribers by September 2017. Moreover, India has also outshined the USA in 2017 in terms of a number of mobile application downloads which grew 251 per cent since 2015 (GSMA, 2017). The strong consumer demand along with reformist policies of the government have been the two major reasons for this steep growth of the Indian telecom sector in the last one decade (Sharma, et al. 2017). The recent regulations helped in opening up the opportunities for many global players to offer their services and has attracted FDI of US$ 31.75 billion since April 2000 (Department of Industrial Policy and Promotion, 2017). The National Digital Communications Policy 2017 has envisioned that the telecom industry in India would attract the

2020 and app downloads US$ 37.21 billion in 2022. Along with this, the new project of developing 100 smart cities by the government of India would help in increasing the subscriber base by 2 fold and IP traffic 4-fold (TRAI, 2017; GSMA, 2017; Sharma et al., 2017). In this highly competitive scenario, the organization would be successful if they bring out innovative methods to increase their outreach to cater to the needs of the target audience and they focus not only on acquiring new consumers but also reducing the churning ratio. The present generation of telecom services the user is all the more impatient and demanding too, highly aware and technology savvy (Sharma et al., 2017). This generation has adopted technology as a part of their daily life and as Palmer (2009a, 2009b) cited in (Sharma et al., 2017) states very correctly that it acts as their ―third hand and second brain‖. Therefore, this study apt for this scenario and tries to nail down the reasons for consumer quitting and explore the dynamics of consumer churning behaviour in the telecom sector, specifically in the Delhi-National Capital Region. Delhi-NCR has been selected for the study for three main reasons, first, it is the capital of the country, second, it is the test market for the most of the organizations and third, it is at our convenience to reach out to the sample. In this paper, we proposed a model where the influence of loyalty, satisfaction and switching barriers (Customer Relationship Management, Alternative Attractiveness & Switching Cost) have been considered as one of the most important variables in deciding consumer‘s intention to quit or continue with their current supplier. This study would be very helpful for the researchers and managers to prepare a strategy to gain sustainable growth in this highly competitve industry.

In the current scenario, the question of business sustainability is critical and needs a futuristic solution as building a customer base which is loyal and value-oriented, is their utmost dilemma (Sharma et al, 2017; Jain and Ahuja, 2017). In the same way, the customers are also confused as to which company to stick to; when so many telecom companies are available to serve them with the best of services. It is imperative for companies to understand consumer behaviour, by and large, to remain focused on strategic planning in the same direction (Bhattacharya, J. and Das, MK., 2017). Else, their market presence and performance may diminish day after day (Qi et al., 2009, as cited by Lee, Kwak and Lee, 2015; Sharma and Sonwalkar, 2016). Several researchers have stated that the customers change telecom operators due to various reasons such as Lee, Kwak and Lee, 2015; Martins 2015; Molapo & Mukwada, 2011; Ali, Ali, Rehman, Yilmaz, & Safwan, 2010; Shukla, 2004; Blinn et al. 1990). Also, Martins (2015) elaborated in his book titled ‗Win the Customer‘ showcasing the importance of customer service which gets an edge to companies in becoming Great companies, by providing value-based service which is beyond paying any price for it and cannot be replicated too. However, when the same service is provided by different service providers at variable quality measures, it becomes easy for the customers to switch services (Blinn et al. 1990; as cited by Lee, Kwak and Lee, 2015). At this time, knowing the dynamics of consumers churning behaviour will help organizations in retaining them. As it is one of the biggest challenges to finding out strategies which would help in reducing consumers‘ leaking and offering services to satisfy them and meeting their needs related to quality, services, performance, efficiency, etcetera so as to maintain consumer loyalty keeping them satisfied and preventing them from switching to another telecom service provider. Many studies have been conducted to study the retain consumers for the telecom industry. Few of them have been highlighted below in table 1:

Blattberg and Deighton; Rust et al.; Berger et al.; Gupta et al. Van Triest et al. 1996, 2004b, 2006 The research showed the large impact of customer retention expenses on business profitability and importance of customer relationship management Garín-Muñoz et al. 2014 Focus on customer retention is a must, along with customer creating new ones. Zeithaml & Bitner 2006 The need for building long-term relationships with customers in the service industry through a timely solution of consumer complaints and analysing the continuous

Shrivastava & Khandai 2002 Studied customer satisfaction in mobile services through a disconfirmation model involving consumer expectations, desires, perceived the ability to modify the services and self-efficacy. Wang and Lo 2004 Studied CRM in perspectives of consumer behaviour related to service repurchase etc, and relationship quality related to consumer satisfaction and loyalty towards the service provider. Zineldin 2006 Developed a market strategy for rising competitiveness through service quality, CRM and customer loyalty. Frad 2010 Proposed a conceptual framework of people, technology and procedures establishing a relationship with the company with customers and competitors through CRM for ensuring increased market presence. Xu et al. 2014 Studied the Mobile telecommunication service providers offering customized schemes for market capturing. Thaichon et. al. 2014 Studied internet service quality based on network performance in term of speed, connectivity,

customer satisfaction. Myler 2016 Studied Gen Y consumers, who seek tailored plans with controllable overall service package instead of one-size-fits-all plans. Sharma et al. 2017 Studied consumer retention strategies for the telecommunication industry in Central India where loyalty, satisfaction, CRM have found to have a significant influnence on consumer retention. Switching cost was measured as moderating variable.

Based on the review of above-discussed literation consumer loyalty, satisfaction and switching barrier have been finalised for the study. The switching barrier has been again divided into three parts, CRM, alternative attractiveness and switching cost. Below is the discussion of the variables taken into consideration for the research. It has been widely researched and emphasized by the marketing practitioners that to generate consumers who are committed and loyal towards a firm and enhance the firm‘s profitability to run it successfully (Sharma & Panga, 2017; Molapo & Mukwada, 2011; Ali, Ali, Rehman, Yilmaz, & Safwan, 2010; Reichheld, 1996) and increase its market share (Chaudhuri & Holbrook, 2001), as well as increase shareholder value (Sindell, 2000). The financial performance of any firm depends significantly on consumer loyalty (Muhammad, 2012) which is maintained by giving regular benefits to the customers (Anderson and Jacobsen, 2000). In addition, the loyal customers are much cheaper to serve (Ganesh, Arnold, & Reynolds, 2000), more compassionate and forgiving of occasional experiences of dissatisfaction or failure (Yi & La, 2004) and are resistant to competitive overtures (Narayandas, 2005 & Oliver, 1999). Thus, the firms that understand this fact, strategize to keep their

Osotimehin, Hassan and Abass (2015) conducted research on the Nigerian telecom sector where they found that there was a significant relationship between consumer loyalty and consumer satisfaction and service quality. The research also revealed that there are numerous factors like service delivery, the reliability of service, efficient customer care which makes consumers stick to the telecom service providers despite the excessive competitive offers available in the market. According to Lall, (2013) & Sharma, et al, (2017) telecom services have reached saturation level, the companies need to work towards retaining their customers by delivering better service and meeting consumer requirements as per the market growth, in such competitive business environment. So the best way for the firm to remain in the market is to ensure longer stay of the consumers and fasten their loyalty with the firm (Adepoju and Suraju, 2012). For this, the telecommunication firms must continuously assess the degree of consumer sensitivity and expectations related to the service quality most importantly (Osotimehin, Hassan and Abass, 2015; Sharma, et al, 2017) to ensure consumer satisfaction. Many researchers have highlighted that satisfaction is the most important element to drive consumers‘ intention to purchase (Sharma et al, 2017; Sharma & Panga, 2017; Inkumsah, 2013; Shukla, 2004; Szymanski & Henard, 2001; Churchill & Surprenant, 1982). Olotewo (2017) and Mishra (2013) state that consumer satisfaction marks the actual difference between consumer expectation and reality. The consumer does a comparative analysis of his overall experience with the company after he purchased its services, and advocates about the services to others and helps in building trust about the company, further capturing new customers. Also, it helps the consumer in deciding whether he needs to look out for better services in the market or not. So it is a confidence-building factor for the consumers. As mentioned by the researcher Oyeniyi (2011) that Consumer Satisfaction is a covariate of loyalty, repurchase intention and product advocacy. Sharma, et al, (2017) stated that satisfaction has a significant effect on the efficiency level of service. This is because consumer satisfaction leads to bring in more business and more revenue to the firm which it could utilize in enhancing service efficiency. Osotimehin, Hassan and Abass (2015) found in their study that consumer satisfaction and their loyalty go hand in hand and the firms recover the dissatisfied consumers through better service or early solution to their problem, the consumer gets satisfied and would continue with the service in long run. Another component for retaining consumer is switching Barriers. Studies have confirmed that consumers tend to avoid switching if switching Jones, David, & Sharon (2001, p. 261) defined switching barriers as: “Any factor/element that makes it difficult or costly for consumers to change providers”. Researchers have used ‗switching barriers‘ and ‗switching costs‘ interchangeably their studies (Alirez, 2011; Bansal & Taylor, 1999; Bansal, Taylor, & Jame, 2005; Ranaweera & Prabhu, 2003) and many were confused in these terms (Sathish et al. 2011; Balabanis et al. 2006; Colgate et al. 2007). Whereas, Goode & Harris (2007) have argued in their research that there is a slight difference between both the terms though, no clarification was given. On the other hand, (Shrama et al., 2017); (Sharma & Sonwalkar, 2016); (Colgate et al., 2007); (Burnham, Frels, & Mahajan, 2003) have used and defined these dimensions switching barriers & costs very meticulously in their research. Sharma et al., (2017); Rahman et al. (2011) and Holloway (2003) measured switching barriers with CRM, alternative attractiveness and switching costs. Therefore, this study has used also used switching barriers as one of the dimensions to check the consumer churning behaviour along with loyalty and satisfaction. Switching barriers have been measured with perceived switching costs (Matzler et al., 2015); (Wirtz et al., 2014); (Aaker, 2009); (Jones et al., 2000), alternative attractiveness (Mannan et al., 2017); (Chuah et al., 2017); (Kuo et al., 2013); (Oliver, 1997); (Jones et al., 2000); (Kim, Yun, & Kim, 2009; Breivik & Thorbjornsen, 2008; Jones et al. 2007; Goode & Harris, 2007; Holloway & Beatty, 2003; Park et al. 1994) and customer relationship management (CRM) (Bell et al. 2005; Ryals & Payne, 2001). (Zablah et al., 2003); (Mohanty & Das, 2017); (Sheth & Parvatiyar, 1995); (Jeswal, 2017); (Khaligh et al., 2012); (Mehdi and Venkatesh, 2010) The researchers Burnham et al. (2003) cited in (Sharma et al., 2017) developed consumer perceived switching costs typology, after studying the telephone service providers. They divided the switching cost into three major variables as Process costs, Financial costs and Relationship costs (Kukreja and Handa, 2013; Mohsin et al. 2012; Chebat et al. 2010; Aydin et al. 2005; Caruana, 2004). This research has also used the same component to measure the switching costs.

H01: There is no significant influence of Consumer Loyalty on Consumer Churning Behaviour. H02: There is no significant influence of Consumer Satisfaction on Consumer Churning Behaviour.

H06: There is no significant influence of Switching Cost on Consumer Churning Behaviour. H07: There is no significant influence of Process Cost on Consumer Churning Behaviour. H08: There is no significant influence of Financial Cost on Consumer Churning Behaviour. H09: There is no significant influence of Relationship Cost on Consumer Churning Behaviour.

There were two basic objectives of this study first, to identify what makes consumer quit or change their service providers and second, find out the variables which can help in consumers churning intention. Through an in-depth literature review, we identified three factors, loyalty, satisfaction and switching barriers, may help to reduce churning intentions. Switching barriers have been measured through customer relationship management, alternative attractiveness and switching cost. Similarly, switching costs have tested from process cost, financial cost and relationship cost. All the items have been measured on a 5-point Likert‘s scale (From Strongly Disagree to Strongly Agree).

Reliability is help in measuring the consistency of the result. The literature proposes that the value of Cronbach‘s Alpha greater than 0.7 is accepted (Hair et al. 2010); (Zikmund, 2004); (Nunnally & Bernstein, 1994, p. 265); Robinson et al. 1991, pp. 12-13); limit i.e. 0.7.

S. No. Scale No. of Items Cronbach‟s Alpha 1 Churning Behaviour 5 0.955 2 Loyalty 5 0.925 3 Satisfaction 5 0.896 4 Switching Barriers 5 0.809 5 CRM 5 0.898 6 Alternative Attractiveness 5 0.885 7 Switching Cost 5 0.922 8 Process Cost 5 0.901 9 Financial Cost 5 0.909 10 Relationship Cost 5 0.913

The 674 responses collected from the post-paid customer only as data collected by TRAI reveals that post-paid customers generate more value than pre-paid customers (TRAI, 2017). 65 per cent respondent were male and 35 per cent were female. 82 per cent respondent was having postgraduates and 86 per cent respondents‘ annual income was above Rs. 1,000,000/Year with work experience of more than 8 years. 79 per cent respondents had monthly consumption of mobile phone bill was around Rs.800. This data clearly defines that majority of respondents were from a good educational background and appearing well settled in their professional life. They also have above average mobile phone bill consumption. Therefore, organizations have to look after these consumers, as they are the most valuable one and organizations can afford to leave them. The proposed hypotheses were tested by applying a linear regression analysis. Table 3 shows the results of the analysis. It can clearly be seen that all the hypotheses got rejected.

alternative attractiveness, switching cost, financial cost, relationship cost and process cost) on dependent variables (i.e. consumer churning behaviour). In other words, model fitness reports that independent variables performed well while predicting the dependent variable. Value of R2 and

Betas Coefficient of H01 to H09 reported satisfactory and caused variability by independent variables independent variables.

The result supports the hypothesis H01, which shows that loyalty (0.587; 0.000) has a significant influence on consumer churning behaviour. This result is in line with Sharma, et al., (2017) & Osotimehin et al. (2015), where the studies concluded that loyal consumer tends to stick with the organization for a longer time. The previous studies also highlighted that loyal customer would hardly compare prices of competitive service providers. Therefore, telecom service providers try to create loyal customer base which will help them in long term survival. The result rejects the hypothesis H02, which mean that there is a significant influence on satisfaction (0.632; 0.000) on consumer churning behaviour. This means that if the consumer is dissatisfied then there are possibilities that he/she may think of quitting from the current service providers. This finding is in line with (Sharma et al., 2017; Sharma & Panga, 2017; Inkumsah, 2013; Shukla, 2004; Szymanski & Henard, 2001; Churchill & Surprenant, 1982). The service providers try to keep the perceived value high for the brand which will intern leads to high satisfaction. Other than that keeping customers engage with various offers and having clear communication helps in developing a strong bond between service providers and customers. The hypothesis H03 has also been rejected, therefore it suggests that switching barriers (0.754; 0.000) has a significant influence on consumer churning behaviour. This hypothesis is in line (Khaligh et al., 2012; Chuah et al., 2017; Alirez, 2011; Bansal & Taylor, 1999; Bansal, Taylor, & Jame, 2005; and Ranaweera & Prabhu, 2003). This is true that higher switching barriers help in reducing the chances of quitting intentions. Therefore, telecom service providers try to keep switching barriers high by offering good customer services and offer lucrative schemes to increase attractiveness. Promptness also helps in engaging and gaining respect from customers. The results of hypotheses H04, H05 & H06 showcased that there is a significant influence of CRM (0.661; 0.000), alternative attractiveness (0.413; 0.000) and switching cost (0.533; 0.000) on consumer switching intentions. This means that signify the importance of attractiveness where (Sharma et al. 2017) found their study that alternative attractiveness has no positive influence on consumer retention. Whereas, this research confirms that there is a significant influence of competitors marketing strategies on consumer mind and may like to switch if other factors are in support. Another interesting implication of this result is that in the case of low satisfaction experiences, switching costs may become an important factor in reducing the consumer intentions to quit. This has been observed earlier also that the consumers do not switch their service provider if there is a perception of higher switching costs. The hypothesis H07, H08 and H09 also process cost (0.421; 0.000), financial cost (0.318; 0.000) and relationship cost (0.572; 0.000) have significant influence on consumer‘s churning intentions. These results are in line with (Jones et al., 2000; Burnham et al., 2003; Matzler et al., 2015; Wirtz et al., 2014; Aaker, 2009; Kukreja and Handa, 2013).

CONTRIBUTIONS OF THE RESEARCH

This research presents the influence of loyalty, satisfaction, switching barriers on consumers‘ quitting intentions through previous studies. When we talk about consumers‘ willingness to continue their services, this study has made conceptualizing and operationalizing contribution to the literature to find important dimensions of consumer churning behaviour, comprising of loyalty satisfaction and switching barriers. The switching barriers are further divided into three sub-component named as, CRM, alternative attractiveness and switching cost. Switching cost again comparing process cost, relationship cost and financial cost. Hence, the more comprehensive approach has been undertaken in this research as compared to past researches done on the Indian telecom sector. The results of this study also highlighted some managerial implication telecom sector in the country. The results pinpoint that the service providers have to look into their strategies and revive it on a regular interval basis as we discussed earlier that acquiring new a customer is five times costlier than retaining the existing ones. This is possible only when organizations are offering quality services, keeping the higher perceived value and higher switching barriers. Therefore, it is indeed very important for an organization to make a distinction between strategies that lock the consumer by penalizing their exit from a contractual relationship and

As it goes with every study so there are few shortcomings of this research also. This research has used switching cost as one of the independent variables but there are studies where it has also been considered as moderating variable so the future study can undertake switching cost as a moderating variable for reducing consumers‘ quitting intentions. This research is in continuation with the study conducted in MP region three years ago. There are noted changes have been observed in the result when we conducted in the National Capital Region. Therefore, further study can be in another part of the country to generalise the concept. There are studies where loyalty has been tested with satisfaction so future research can also measure the same.

Aaker, D. A. (2009). Strategic Market Management: Wiley-India. Aarts, Henk and Dijksterhuis, Ap. (2000). Habits as Knowledge Structures: Automaticity in Goal-Directed Behaviour. Journal of Personality and Social Psychology, Vol. 78 (1), pp. 53-63. Adepoju, A., Suraju, A. M. (2012). ―The Determinants of Customer Loyalty in Nigeria‘s GSM Market‖, International Journal of Business and Social Science 3(14): 14 p Ali, F. J., Ali, I., Rehman, K. U., Yilmaz, A. K. & Safwan, N. (2010). Determinants of consumer retention in the cellular industry of Pakistan. African Journal of Business Management, Vol. 4 (Issue. 12), pp. 2402-2408. Ali KHR (2013). Analysing the Effect of Consumer Equity on Repurchase Intentions. Intl J. Academic Sci. Business Res. Soc. Sci. pp. 110-125. Alirez, F. (2011). How Quality, Value Image, and Satisfaction Create Loyalty at an Iran Telecom. International Journal of Business and Management, Vol. 6 (Issue. 8), pp. 271-279. Anderson, H., Jacobsen, P. (2000). ―Creating Loyalty: It‘s Strategic Importance in your Customer Strategy‖, in S. A. Brown (ed.), Customer‘s relationship management. Ontario: John Wiley. Balabanis, G., Reynolds, N. & Simintiras, A. (2006). Bases of E-Store Loyalty: Perceived Switching Barriers and Satisfaction. Journal Bansal, H. S. & Taylor, S. F. (1999). The Service Provider Switching Model (Spsm): A Model of Consumer Switching Behaviour in the Services Industry. Journal of Service Research, Vol. 2 (Issue. 2), pp. 200-218. Bansal, H. S., Taylor, S. F., & Jame, S. Y. (2005). Migrating to New Service Providers: Toward a Unifying Framework of Consumers' Switching Behaviours. Journal of the Academy of Marketing Science, Vol. 33 (Issue. 1), pp. 96-115. Bell, S. J., Auh, S., & Smalley, K. (2005). Customer Relationship Dynamics: Service Quality and Customer Loyalty in the Context of Varying Levels of Customer Expertise and Switching Costs. Journal of the Academy of Marketing Science, Vol. 33 (Issue. 2), pp. 169-183. Berger, P. D., Eechambadi, N., George, M., Lehmann, D. R., Rizley, R., & Venkatesan, R. (2006). From customer lifetime value to shareholder value: theory, empirical evidence, and issues for future research. Journal of Service Research, 9(2), pp. 156–167. doi: 10.1177/1094670506293569. Blattberg, R. C., & Deighton, J. (1996). Manage marketing by the customer equity test. Harvard Business Review, 74(4), pp. 136–144. July–August. Blinn, J. D., Duncan, S. R. and Barbara, G. (1990). Cost of Risk Survey: A Yardstick for Management,‖ Risk management 1991, pp. 46-50. Breivik, E., & Thorbjornsen, H. (2008). Consumer Brand Relationships: An Investigation of Two Alternative Models. Journal of the Academy of Marketing Science, Vol. 36 (Issue. 4), pp. 443-472. Burnham, A. T., Frels, J. K., & Mahajan, V. (2003). Consumer Switching Costs: A Typology, Antecedents, and Consequences. Journal of Academy of Marketing Science, Vol. 31 (Issue. 2), pp. 109-126. Caruana, A. (2004). The Impact of Switching Costs on Customer Loyalty: A Study among Corporate Customers of Mobile Telephony. Journal of Targeting, Measurement and Analysis for Marketing, Vol. 12 (Issue. 3), pp. 256-268.

Loyalty. The journal of marketing, Vol. 65 (Issue. 2), pp. 81-93. Chawla, D., & Sondhi, N. (2011). Research Methodology: Concepts and Cases (Vol. Vol. 1). New Delhi: Vikas Publishing House Pvt. Ltd. Chebat, J.-C., Davidow, M., & Borges, A. (2010). More on the Role of Switching Costs in Service Markets: A Research Note. Journal of Business Research, Vol. 64 (8), pp. 823-829. Churchill, G. A., & Surprenant, C. (1982). An Investigation into the Determinants of Customer Satisfaction. Journal of Marketing Research, pp. 491-504. Colgate, M., Tong, V. T.-U., Lee, C. K.-C., & Farley, J. U. (2007). Back from the Brink: Why Customers Stay. Journal of Service Research, Vol. 9 (Issue. 3), pp. 211-228. Cronbach, L. J. (1951). Coefficient Alpha and the Internal Structure of Tests. Psychometrika, Vol. 31, pp. 93-96. Dharmakumar, R. (2013, January 17). India and Technology Multinationals – Part 1. Retrieved January 25, from www.forbesindia.com: http://forbesindia.com/blog/author/rohin-dharmakumar/page/2/ Ganesh, J., Arnold, M. J., & Reynolds, K. E. (2000). Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers. Journal of Marketing, Vol. 64 (Issue. 3), pp. 65-87. Garín-Muñoz, Teresa; Gijón, Covadonga; Pérez-Amaral, Teodosio; López, Rafael (2014): Consumer complaint behaviour in telecommunications: The case of mobile phone users in Spain, 25th European Regional Conference of the International Telecommunications Society (ITS), Brussels, Belgium, pp. 22-25 June 2014. Goode, M. M., & Harris, L. C. (2007). Online Behavioural Intentions: An Empirical Investigation of Antecedents and Moderators. European Journal of Marketing, Vol. 41 (Issue. 5-6), pp. 512-536. GSMA, I. (2017). THE MOBILE ECONOMY 2017. London: GSMA. Research, 9(2), pp. 139–155. doi: 10.1177/1094670506293810. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective (7th ed. ed.). New Jersey: Pearson Prentice Hall. Holloway, B. B. (2003). The Role of Switching Barriers in the Online Service Recovery Process. Ph.D., The University of Alabama. Holloway, B. B., & Beatty, S. E. (2003). Service Failure in Online Retailing: A Recovery Opportunity. Journal of Service Research, Vol. 6 (Issue. 1), pp. 92-105. Inkumsah, A. W. (2013). Factors That Impacted Customer Retention of Banks. A Study of Recently Acquired Banks in the UPSA Area of Madina, Accra (Specifically Access Bank). Journal of Marketing and Consumer Research, Vol. 1, pp. 88-103. Jain, P. and Ahuja, Y., (2017). ―Customer Retention from Collection Orientation to Customer Orientation Strategy - A Case Study of Telecom Player in India‖, ITIHAS - The Journal of Indian Management. Jul-Sep2017, Vol. 7 Issue 3, p5-10. 6p. Jeswal, R. (2017). Consumer Relationship Management. FIIB Business Review, Vol. 6 (3), pp.21 – 22. doi: http://dx.doi.org/10.29368/FIIB.6.3.2017. pp. 21-22 Jones, M. A., David, L. & Sharon, E. B. (2001). Switching Barriers and Repurchase Intentions in Services. Journal of Retailing, Vol. 76 (Issue. 2), pp. 259–274. Jones, M. A., Mothersbaugh, D. L. & Beatty, S. E. (2000). Switching Barriers and Repurchase Intentions in Services. Journal of Retailing, Vol. 76 (2), pp. 259-274. Jones, M. A., Reynolds, K. E., Mothersbaugh, D. L., & Beatty, S. E. (2007). The Positive and Negative Effects of Switching Costs on Relational Outcomes. Journal of Service Research, Vol. 9 (Issue. 4), pp. 335-355. Khaligh, A., Miremadi, A., and Aminilari, M. (2012). The Impact of eCRM on Loyalty and Retention of Customers in Iranian Telecommunication Sector. International

Kim, K., Yun, D., & Kim, D. (2009). Expectations measurements in mobile data service: a case study. International Journal of Mobile Communications, Vol. 7 (Issue. 1), pp. 91-116. Kukreja, J. and Handa, M. (2013). Emotional Labor for Customer Satisfaction. FIIB Business Review. Volume 2, Issue 2. Lall V. J. (2013). Application of Analytics to Help Telecom Companies Increase Revenue in Saturated Markets. FIIB Business Review, Volume 2, Issue 3. Lee, C., Kwak, N., & Lee, C. C. (2015). Understanding consumer churning behaviours in mobile telecommunication service industry: Cross-national comparison between Korea and China. Paper presented at 2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015, Fort Worth, United States. Mannan, M., Md. Fazla Mohiuddin, Nusrat Chowdhury, Priodorshine Sarker, (2017). "Customer satisfaction, switching intentions, perceived switching costs, and perceived alternative attractiveness in Bangladesh mobile telecommunications market", South Asian Journal of Business Studies, Vol. 6 Issue: 2, pp. 142-160, https://doi.org/10.1108/SAJBS-06-2016-0049 Martins, F. (2015). ―Win the Customer: 70 Simple Rules for Sensational Service‖. AMACOM Div American Mgmt. Assn, 2015. Matzler, K., Andreas Strobl, Norbert Thurner, Johann Füller, (2015). "Switching experience, customer satisfaction, and switching costs in the ICT industry", Journal of Service Management, Vol. 26 Issue: 1, pp. 117-136, https://doi.org/10.1108/JOSM-04-2014-0101 Mehdi Rouholamini & Venkatesh, S. (2010). ―Essentials of CRM for Banking Sector‖, Southern Economist, Vol. 49, No.11, Oct 2010, p. 37. Mishra, R. (2013). Linking Cellular Subscriber Satisfaction and Service Quality: An Empirical Study on Delhi-NCR Cellular. FIIB Business Review. Volume 2, Issue 2. Mittal, Vikas, Eugene W. Anderson, Akin Sayrak, and PanduTadikamalla (2005), ‗‗Dual Emphasis and the Long-term Financial Impact of Mohanty, A and Das, S. (2017). Impact of Customer Relationship Management (CRM) on Telecom sector in India. International Journal of Scientific Research in Science and Technology, Volume 3, Issue 8, pp. 431-437. Mohsin, A., Ahmad, R., & Ahmed, A. (2012). Determinants of Customer Switching Behavior in Banking Sector. Studies in Business and Economics, pp. 20-34. Molapo, E. M., & Mukwada, G. (2011). The Impact of Customer Retention Strategies in the South African Cellular Industry: The Case of the Eastern Free State. International Journal of Business Humanities and Technology, Vol. 1 (Issue. 2), pp. 52-60. Muhammad, S. R. (2012). ―Service Quality, Corporate Image and Customer‘s Satisfaction towards Customers Perception: An Exploratory Study on Telecommunication Customers in Bangladesh‖. Business Intelligence Journal 5(1): 8p. Myler, L. (2016). Millennials' Demand For Customization, Control And Immediacy Drives New Jawwy Mobile Service. Available at: 〈http://www.forbes.com/sites/larrymyler/ 2016/05/05/millennials-demand-for-customization-control-and-immediacy-drives new-jawwy-mobile-service/#32fb6766759c〉 (accessed 11.03.16). Narayandas, D. (2005). Building Loyalty in Business Markets. Harvard Business Review, Vol. 83 (Issue. 9), pp. 131–139. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory. New York: McGraw-Hill. Oliver, R. L. (1997). Satisfaction: A Behavioral Perspective on the Consumer. New York: Irwin/McGraw-Hill. Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, Vol. 63 (Special Issue), pp. 33-44. Park, W. C., Feick, a., &Mothersbaugh, D. L. (1994). Consumer Knowledge Assessment. Journal of Consumer Research, Vol. 21 (Issue. 1), pp. 71-82.

China‖, System Research and Behavioral Science (26:3) pp. 391-407. Olotewo, J. (2017). Analysing the moderating effect of customer loyalty on long run repurchase intentions. African Journal of Marketing Management, 9(3), pp. 25-34. Osotimehin, Hassan and Abass (2015). Customers Perception of Service Quality in the Nigerian Telecommunication Sector. J. Econ. Bus. Res. Pp. 510-525. Palmer, K., 2009a. Gen Y: Empowered, Engaged, Demanding. Available at: 〈http:// money. usnews.com/money/blogs/alpha-consumer/2009/09/21/gen-empowered-engageddemanding_print.html〉 (accessed 22.11.15). Palmer, K., 2009b. Gen Y: Influenced by parents and materialism. Available at: 〈http:// money. usnews.com/money/blogs/alpha-consumer/2009/9/22/gen-y-influenced by-parents-andmaterialism_print.html〉 (accessed 22.11.15). Rahman, S., Haque, A., & Ahmad, S. (2011). Choice Criteria for Mobile Telecom Operator: Empirical Investigation among Malaysian Customers. International Management review, Vol. 7 (Issue. 1), pp. 50-57. Ranaweera, C. & Prabhu, J. (2003). The Influence of Satisfaction, Trust and Switching Barriers on Customer Retention in a Continuous Purchasing Setting. International Journal of Service Industry Management, Vol. 14 (Issue. 3/4), pp. 374-395. Reichheld, F. F. (1996). The Loyalty Effect. Harvard Business School Press. Robinson, J. P., Shaver, P. R., &Wrightsman, L. S. (1991). Criteria for Selection and Evaluation. In John P. Robinson, Phillip R. Shaver and Lawrence S. Wrightsman (Eds.), Measures of Personality and Social Psychological Attitudes (Vol. 1, pp. 1-16). San Diego, Calif: Academic Press. Rust, R. T., Lemon, K. N., & Zeithaml, V. A. (2004b). Return on marketing: using customer equity to focus marketing strategy. Journal of Marketing, 68(1), pp. 109–127. doi: 10.1509/jmkg.68.1.109.24030. Ryals, L., & Payne, A. F. (2001). Customer Relationship Management in Financial Services: Towards Information-Enabled Sathish, M., Santhosh, K. K., Naveen, K., &Jeevanantham, V. (2011). A Study on Consumer Switching Behaviour in Cellular Service Provider: A Study with reference to Chennai. Far East Journal of Psychology and Business, Vol. 2 (Issue. 2), pp. 71-81. Seo, D. B., &Ranganathan, C. (2009). Two-Level Model of Customer retention in the US Mobile telecommunications Service Market. Telecommunications Policy, Vol. 32, pp. 182-196. Sharma V., Joseph, S. & Poulose, J., (2017). Determinants of consumer retention strategies for telecom service industry in Central India. Problems and Perspectives in Management, 16 (2), 306-320. http://dx.doi.org/10.21511/ppm.16(2).2017. P. 28. Sharma, V., & Panga, M. D. (2017). Determinants of Switching Behaviour in Consumer Electronic Goods. Prestige International Journal of Management and Research, 10(4), p. 107. Sharma, V., & Sonwalkar, J. (2016). Consumer retention strategies for telecom service industry in India: a theoretical perspective. Journal of Management Research and Analysis, 3(3). Pp. 110-121. Sharma, V., Kapse, M., Sonwalkar, J. (2016). ―Predicting the Consumers‘ Brand Switching Behavior for Cellphones: Application of Markov Chain Models‖, IUP Journal of Marketing Management, Vol. 15, N. 4, pp. 31-43. Sheth, J.N., Jagdish, N., Mittal, B., and Newman, B. (1999). Customer Behavior: Consumer Behavior and Beyond. New York: Dryden. Shukla, P. (2004). Effect of Product Usage, Satisfaction and Involvement on Brand Switching Behaviour. Asia Pacific Journal of Marketing and Logistics, Vol. 16 (Issue. 4), pp. 82-104. Sindell, K. (2000). Loyalty Marketing for the Internet Age. Chicago: Dearborn Financial Publishing Inc. Szymanski, D. M., &Henard, D. H. (2001). Customer Satisfaction: A Meta-Analysis of the Empirical Evidence. Journal of the

Thaichon, P., Lobo, A., Prentice, C., Quach, T.N., 2014. The development of service quality dimensions for internet service providers: retaining customers of different usage patterns. J. Retail. Consum. Serv. 21, pp. 1047–1058. TRAI. (2017). Highlights of Telecom Subscription Data as on 21st November 2017. New Delhi: Telecom Regulatory Authority of India. Van Triest, S., Bun, M. J. G., Van Raaij, E.M. et al. Mark Lett (2009) 20: p. 125. https://doi.org/10.1007/s11002-008-9061-2 Wang, Y., Lo, H. P., (2004). An integrated framework for customer value and customer-relationship management performance: a customer-based., the perspective from China. Managing Service Quality, 14:2/3, pp. 169-182. Wirtz, J., Xiao, P., Chiang, J., Malhotra, N., 2014. Contrasting the drivers of switching intent and switching behaviour in contractual service settings. J. Retail. 90 (4), pp. 463–480. Xu, X., Thong, J.Y., Venkatesh, V., 2014. Effects of ICT service innovation and complementary strategies on brand equity and customer loyalty in a consumer technology market. Inf. Syst. Res. 25 (4), pp. 710–729. Yi, Y., & La, S. (2004). What Influences the Relationship between Customer Satisfaction and Repurchase Intention? Investigating the Effects of Adjusted Expectations and Customer Loyalty. Psychology and Marketing, Vol. 21 (Issue. 5), pp. 351-373. Zikmund, W. G. (2004). Business Research Methods (7thEd.). Singapore: Thomson Asia Pvt. Ltd. Zeithaml, Valarie A.; Bitner, Mary Jo 2006. Services Marketing. New York: McGraw-Hill. Zineldin M., (2006). The royalty of loyalty: CRM, quality and retention. Journal of Consumer Marketing, Vol. 23 (7), pp. 430 – 437.

Associate Professor, Christ Institute of Management, Delhi-NCR