Volume 3, Number 1 (2016) pp 22-48 doi 10.20448/800.3.1.22.46 | Research Articles
As a result of the role ascribed to the concept of customer loyalty as an important organizational critical success factor the consensual focus within research and academic community in recent years has been centered on the need to acquire a useful knowledge on some of its critical antecedents with the aim of using such knowledge as a basis of formulating marketing strategies and enhancing a desirable customer loyalty base. As a response to this need, the present research investigates the effect of customer satisfaction on the loyalty of subscribers in the Nigerian mobile telecommunication industry. Making use of the responses elicited through a self administered and structured questionnaire, from a total of three hundred and seventy six (376) mobile phone subscribers that were picked from the eight local governments of Kano metropolis through the multi-stage sampling technique, it was uncovered through the Pearson moment correlation and multiple regression analysis conducted that customer satisfaction has a positive and significant effect on customer loyalty with Beta coefficient at 0.629 and significant at 0.01. Furthermore, it was equally uncovered that the respondents exhibited an above average mean score in both customer satisfaction and customer loyalty which implies that they are considerably high in these two constructs. In the light of these findings, it was recommended that mobile telecom companies should employ the use of results generated from customer’s profiling research activities as a yardstick in designing customer satisfaction programs to ensure that the performance derived from products/services on offer consistently surpasses customer’s expectation whenever the objective is achieving a desirable customer loyalty base.
Keywords: Customer satisfaction, Customer loyalty, Mobile telecom industry, Subscribers Metropolitan Kano.
Citation | Adewale, A. Adekiya (2016). Customer Loyalty in the Nigerian Telecommunication Industry: The Antecedence of Customer Satisfaction. International Journal of Independent Research Studies, 3(1): 22-46.
Copyright: This work is licensed under a Creative Commons Attribution 3.0 License
Funding : The authors declare that they have no competing interests.
Competing Interests: The author declares that there are no conflict of interests regarding the publication of this paper.
History : Received: 19 May 2016/ Revised: 2 June 2016/ Accepted: 10 June 2016/Published: 16 June 2016
Publisher: Online Science Publishing
With the advent of deregulation and a break up in industry barrier, consequent to the need to achieve liberalization and efficiency, most previously State Owned Enterprises (SOE) in Nigeria including the Nigerian telecommunication industry have in recent years, been witnessing tremendous decrease in entry barrier. Taking advantage of the opportunities provided by this de-regulation, many players both local and foreign have secured the required license for operation thereby making the level of activities in the sector to increase significantly over the past ten years. According to the National Communication Commission (2015) the telecom industry is probably Nigeria’s most vibrant and competitive industry after the petroleum sector. In their opinion, the most prominent of these brands are the Global System for Mobile Communication (GSM) companies: MTN, Globacom, Airtel and Etisalat. Among these corporate brands is shared a whopping 95% of the Nigerian telecommunications business, valued at over 2 trillion naira, and an enviable subscriber base of 140,822,483 (National Communication Commission, 2015). In what is seen as a hot contest to win more subscribers on their networks, each of the major operators are always on their toes in introducing new offerings to the market. While these offerings often come with a façade of innovation, the underlining motivation is the quests to get more subscribers by surpassing what the competitors are doing (IT and Telecom Digest, 2013). In their opinion, after such ground breaking products, the other competitors come out with other products that surpass the previous and the battle for supremacy continues. They further maintained that anytime one flips through the pages of dailies, or watch TV programs, one thing that is most probably seen is an advert or a commercial from a telecom operator announcing one new product or the other and that the next day, one is bound to see another operator coming out with another exciting offer. So goes the battle to win the heart of the teeming subscribers, who now have a high bargaining power, coupled with an ability to switch from one service provider to the other.
From an average industry tariff rate of N50 per minute across networks in the year 2000 today, subscribers can make call for as low as N6 per minute depending on which network and what tariff plan they have chosen (IT and telecom Digest,2013). Though this might be a good bargain for these customers, unfortunately, the end result may not be too palatable for the operators. For instance the National Communication Commission (2013) says that the industry’s average revenue per user (ARPU), which is a financial performance benchmark that measures the average monthly revenue generated by operators from each customer, was put at approximately N1,800 in 2010. However, another reports from the commission in 2015 shows that this figure has fallen to N1000 as at January 2013 thus showing a 45 per cent slide which invariably means drop in revenue for the operators. Furthermore, it is been projected that this current figure of ARPU will slide down to N769 by the ending of 2016 mainly due to competition and prize war.
According to Almossawi (2012) the winner company in such situation, would be those who have the necessary potential and architecture to differentiate their products/services, win customers, draw customers from rivals, and retain existing customers. Hence the concept of customer loyalty as posited by Tseng (2007) who insisted that as the competitive environment increasingly becomes fierce, the most important issue the sellers face is no longer only to provide excellent, good quality products or services, but also to keep loyal customers who will contribute to long-term profitability of the organizations.
As a result of the importance of customer loyalty to the survival and viability of the corporate organization, researches have proliferated in recent years on those critical factors which can act as antecedents in its emergence and sustainability among customers. Put in another way, researchers and industry leaders have in recent years focused on the essential drivers of this construct with the ultimate goal of using such knowledge as a yardstick for effective implementation of customer loyalty program. An important constituent in the customer loyalty antecedent model according to the literature is customer satisfaction. As argued by Smith & Wright (2004) while there exists a relationship between the satisfaction of customers with a firm’s products/services and the financial performance of such firm, such association is however, mediated by less switching and more loyalty among customers (Kim, Park, & Jeong, 2004). This is consistent with Liu (2008) who pointed that customers who are unsatisfied with the products/services received would not be expected to have long run relationships with the company. In a nutshell, customer satisfaction has been highlighted as a reliable precursor to customer loyalty.
While these theoretical arguments are bordered on the premise that customer satisfaction can act as a precursor to customer loyalty, the empirical evidence on such relationship remains scanty, conflicting, and not generalizable to all the relevant market segments in the mobile telecom industry. For instance while the empirically supported result from Khan (2012) revealed that an increase in customer satisfaction will lead to a corresponding increase in customer loyalty in Pakistan, the study was limited to the university student segment of the market hence a need for a comprehensive research that focuses on all relevant segments within the telecom market. Similarly, though, the study on service quality, service satisfaction, and corporate image among the post paid fixed line users of the telecom industry of Malaysia by Yacoob, Ismail, & Ismail (2009) uncovered that all these three factors have a predicting power on customer loyalty. It must however be noted that their study was limited to the post paid customer segment of the market with no attention being given to the more lucrative pre-paid customers. Moreover, to the knowledge of this author, there is lack of evidence on the existence of a research that focuses on the mobile telecom market in Kano Metropolis particularly on the issues raised in this study. Hence the study will fill the highlighted gaps by considering all the relevant pre-paid customer segments of the telecom market in Kano metropolis while at the same time, determining if the result uncovered can be used to support or refute the conflicting findings from similar studies in other environments. It is anticipated that findings will be of immense importance to the mobile telecommunication industries both in Nigeria, and beyond whenever the objective is employing the use of customer relationship strategies in achieving a desirable level of commitment from customers, in addition to ensuring less switching behaviour among them. In the subsequent sections, the literature review, research methodology, discussion, conclusion and recommendation are presented.
Customer loyalty according to Jahanzeb, Fatima & Khan (2011) is a deeply held commitment to rebuy or repatronize a preferred product or service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing despite situational influences and marketing efforts, having the potential to cause switching behavior. Put in another way, a loyal customer is one that re-bought a brand, considered only that brand, and seeks no information on pricing, product quality, and promotional activities that is related to other brands. By following this line of reasoning, a loyal customer within the framework of this study is defined as the subscribers of mobile telecommunication companies in Nigeria who have the tendency to stick to such company even in the face of constant competitive offerings in form of discounts, free airtime, bonanza, advertisement and other promotional offerings from rival mobile telecommunication companies.
Theoretically, the concept of customer loyalty can be seen from different perspective and or orientations. For instance, the transaction cost theory posited that loyalty results when a customer tries to reduce or eliminate switching costs, which might be psychological, physical and economic which indicates that customers are more likely to remain loyal to a brand when there is a perceived high switching cost associated with available alternatives. Perceived risk theory according to Mitchel (1993) affirmed that consumers are more often motivated to avoid mistakes than to maximize utility in purchasing. As argued by this theory, the goal of a consumer is that of avoiding mistakes and he is characterized by feelings of certainty that the consequences of buying a product/service will be unfavorable and he is afraid of the amount that would be lost in form of finance, time, social and other damages if the consequences were not favorable (Carmen, 2007). Furthermore, it has to do with lack of confidence on the stated attribute of a product/service (Hornibrook & Fearne, 2003). From this theory, it can be implied that consumers are more likely to exhibit loyalty to a brand if they perceive the brand as trustworthy and less risky to do business with, regardless of the stated attributes of other alternatives. If Kotler and Armstong (2012) are true in their submission, then companies can achieve a desirable loyalty base from their customers by the fulfillment of their expectations, with the expectation coming from the experience of previous purchases by them, the opinions of friends and relatives, information from the marketer or a competitor. As posited by Genoveva (2015) some of the reasons why firms must develop a long term relationship with their customers can range from the fact that it cost more to acquire new customer, loyal customers tend to spend more; they recommend company services or product to others. Other studies have followed this same line of reasoning by conceding to the inevitability of loyal customers when the objective is maximizing share-holder’s wealth, while also ensuring long-term organizational sustainability.
For instance Vesel&Zabkar (2009) are of the opinion that customer loyalty is focal point for numerous business organizations. Lin & Wang (2006) also maintained that the success of company sales are ensured by customer loyalty and this would go a long way to determine the market competitiveness of the organization. In addition, the submission by Lin & Wang (2006);Chen & Hu (2010) indicates that customer loyalty is a vital element for the continued existence and operation of firms business while Ganesh, Arnold & Reynolds (2000) equally posits that loyal customers build businesses by buying more, paying premium prices and providing new referrals through positive word of mouth over time.
According to Achour, Pujawati&Boerhannueddin (2010) a critical issue for the continuity of any organizations is its capability to retain current customers while making them loyal to its brands. They stated that companies in telecommunications are losing 2-4 percent of their customers monthly and that disloyal customers can amount to millions of lost revenue and profit. In addition, they are of the opinion that 20% of customers of the mobile phone operator, “Orange” defects each year and, on average it costs “Orange” £256 in 1996 to recruit each new customer, with cost of introductory offers, subsidized phones and advertising all taken into account. Hence with almost a million customers, reducing churn rate from 20% to 10% would bring about annual savings of over £25 million. According to Suleiman, Mat, Adesiyan, Mohammed, & Jamal (2012) customer loyalty is the key driver in a company’s profitability and business performance thereby setting it as one of the key strategic goals of the company. Thus superior customer loyalty will lead to increased sales, increased profitability, and consequently, increased financial performance (Ishaq, 2011).
Given the enormous importance of customer loyalty to organizational success including the mobile telecommunication industry, it is considered imperative to have a good knowledge and understanding of the relevant constructs which can act as an antecedent to this crucial organizational based success factor. In response to such need, researchers, academics and industry players strives to determine these antecedents with the ultimate goal of using such knowledge in building a robust tendency for loyalty among customers in organizational settings. For instance if the exhibition of loyalty from customers is bordered on the premise of repurchase behavior and commitment to a chosen brand, then it can be theoretically argued that if all expectations by customers are duly met or surpassed (customer satisfaction) by the firm, then such situation is likely to lead to a repurchase decision by the customer. Thus, while numerous literatures have lend support to this argument on the effect of the former on the later, see for instance, (Odulami & Mathew, 2015; Khan, 2012) it however remains a debatable issue within the Nigerian mobile telecommunication industry due to the in-existence of any significant empirical evidence in this regard. Hence the focus in this study is unraveling the nature of the relationship between customer satisfaction and customer loyalty with the former, being considered as an independent variable, that act as an antecedent to the later.
According to Vavra (1997) the heart of the satisfaction process is the comparison of what was expected with the product or service’s performance and this has traditionally been described as the ‘confirmation / disconfirmation’ process. Furthermore, customers would form expectations prior to purchasing a product or service, while the consumption of or experience with the product or service produces a level of perceived quality that is influenced by expectations (Oliver, 1980). Thus, if perceived performance is only slightly less than expected performance, assimilation will occur, while perceived performance will be adjusted upward to equal expectations. If perceived performance lags expectations substantially, contrast will occur, and the shortfall in the perceived performance will be exaggerated (Vavra, 1997). The implication here is that companies, whose products/service falls significantly below stated attribute, as perceived by customers, are more likely to experience a significant deterioration in customer satisfaction.
Oliver (1997) defines satisfaction as a judgment of sufficient level of satisfaction offered by a product or service during consumption. To make up for the discrepancy in this earlier definition which does not considered what is defined by consumers as a sufficient level, Hansemark & Albinson (2004) came with their own version and defined the construct as an overall customer attitude or behavior towards the difference between what customers expect and what they receive regarding the fulfillment of some desires and needs. For Kotler and Keller (2009) customer satisfaction is a person’s feeling of pleasure or disappointment resulting from comparing a product’s perceived performance (or outcome) in relation to his/her expectations. Hence this indicates the degree of importance that is attached to the construct by customers.
Buzzle & Gale (1987) pointed that satisfaction data are equally important to firms because satisfaction results in profitability through increases in repeat purchase and positive word of mouth. Furthermore, Anderson (1994) reasoned and maintained that customer satisfaction is used to measure company performance at both (internally): to compensate human resource, observe performance and assign funds, as well as for (externally) in that satisfied customers are also source of information for all stake holders (potential customers, public policy makers, competitors and investors).
To identify the various determinant of satisfaction, various approaches have been proposed by different schools of thought. For instance Levitt (1983) proposed a four-ring concept of the total product: core, expected, augmented, and potential products. According to him, each of these four categories is crucial and must be sufficiently considered by firms when trying to boast customer satisfaction. Also, Batra & Ahtola (1990) gave their own contribution by highlighting the classification scheme called utilitarian versus hedonic product outcomes as a method under which the satisfaction determinant features can be classified. They maintained that while utilitarian features are those that provide the basic functions that the product is required to deliver, the hedonic features are those that provide intangible pleasures which imply that consumption has two dimensions and both should be included by organizations whose objective is the provision of a favorable customer satisfaction. Among the relevant theory in the literature that can be used in the explanation of customer satisfaction/dissatisfaction determinant is the need theory: Maslow’s need hierarchy (Maslow, 1970) Alderfer’s existence, resistance, and growth (ERG) theory (Alderfer, 1972) and Herzberg’s dual-factor theory (Herzberg, 1966) which is based on consumers’ needs and their need fulfillment factors (Almossawi, 2012). According to him, these theories imply that a satisfying factor is one that fulfills the needs of customers. For instance Maslow (1970) placed human needs in a hierarchy where the last to be fulfilled is the most refined and superior. He viewed man as a wanting animal in that man does things because of his needs. That is, he directs his actions towards satisfying his needs. In his opinion, all of the needs are structured into hierarchy and only once a lower level of need has been fully met, would he be motivated by the opportunity of having the next need up in the hierarchy satisfied. What this theory implies is that companies can achieve a consistent customer satisfaction by focusing on consistent innovative practices in products and services development, while at the same time, ensuring that different products/services are used in targeting different market segments based on their specific needs and wants at different point in time.
Similarly, Herzberg (1966) conducted his original research in the work environment to discover “satisfiers” and “dissatisfiers” related to job outcomes. Herzberg argued that the two categories of satisfiers and dissatisfiers had separate and distinct influence on workers and therefore, should be identified separately. First, he posited that while dissatisfiers does not necessarily motivates worker, the absence of this category of need will make them to direct their behavior towards getting it. On the other way round, satisfiers are those factors whose presence motivates while their absence does not necessarily cause any dissatisfaction. Hence the implication of this theory for marketing professionals is that core product attributes such as price, product and distribution channels are dissatisfiers and can encourage brand switching behavior when they are not offered to meet customer expectations and requirements. In the same vein, other marketing strategies such as bonanza, discount on bulk purchase are satisfiers, whose presence can stimulate more frequency in purchases from consumers.
The relationship between customer satisfaction and customer loyalty has been a subject of interest within academic literature and services marketing industry. For instance Akbar & Pervez (2009) pointed that one of the conditions of true customer loyalty is total satisfaction. In addition, the argument by Mosahab, Mahamad&Ramayah (2010) indicates that service quality has a direct and indirect impact on customer loyalty in that variation in the quality and value of products and services provided to customer creates variation in customer satisfaction which in turn create a variation in customer loyalty. Furthermore, Vuuren, Lombard &Tonder (2012) concluded that it is in the best interest of business owners to keep customers happy in a bid to win and sustain their loyalty. Consumer satisfactions positively affect loyalty (Oliver, 1999). They are of the view that there is a significant positive relationship between consumer satisfaction and consumer loyalty. According to Rogers (1996) many researchers were of the view that consumer satisfaction influences customer loyalty which in-turn affects profitability. In his opinion, Proponents of this theory include researchers such as Anderson and Fornell (1994); Gummesson (1992); Heskett, Jones, Loveman, Sasser& Schlesinger (1994); Schneider and Bowen (1995).According to (Odulami& Mathew, 2015). Service organizations cannot survive without satisfied customers in that the satisfaction of customers will definitely pave way for consumer loyalty. Nevertheless, Keavency (1995) lend disrepute to these claims by declaring that better prices and service delivery from competitors might break down loyalty and that there is no guaranty of absolute loyalty from customers. Also, Kotler (2003) and Hokanson (1995) argued that being satisfied does not mean being loyal, and that the two concepts have different determinants.
Empirically, Anderson & Sullivan (1993) found a positive relationship between the two concepts in that an increment in customer satisfaction would most likely yield a corresponding increase in customer loyalty. Furthermore, in a study of the Swedish telecommunication industry Zhang & Feng (2009) examined the mediating impact of customer satisfaction on the relationship between (Value offer, service quality, positive brand image, price perception and switching cost) on one hand, and customer loyalty among Swedish mobile telecommunication subscribers on the other hand. It was found that all the factors have a direct impact on both customer satisfaction and customer loyalty. However, customer satisfaction exhibited a higher level of direct impact on customer loyalty when compared with the other independent variables thereby signifying the mediating impact of customer satisfaction. i.e an increase in the positive perception of these factors by subscribers resulted in higher satisfaction which consequently lead to an increase in the opinion that they will remain loyal to their respective network providers which indicate the possible effect of customer satisfaction on customer loyalty. The implication of this study is that companies might likely derive maximum output from their customer relationship tactics when targeted towards cultivating customer loyalty by placing emphasis on the improvement of customer satisfaction. Another related study by Akbar & Pervez (2009) investigated the direct and indirect effects of customers’ perceived service quality, trust, and customer satisfaction on customer loyalty in the telecommunication industry of Bangladesh among (271) subscribers of a major private telecommunication company in the country. Results from the analysis indicated that all the dimensions of services quality were positively and significantly correlated with customer satisfaction and customer loyalty. However, when customer satisfaction and service quality dimensions were treated as independent variable in the model, it was revealed that customer satisfaction has the highest correlation with customer loyalty. This according to them indicates a mediating impact and the importance of customer satisfaction in securing loyalty in the presence of perceived favorable service quality. It was therefore suggested by them that company should focus on increasing customer satisfaction when using favorable service quality as a means of securing higher customer loyalty. In addition, Mosahab, Mahamad & Ramayah (2010) in a bid to clarify the relationship between three variables, service quality, customer satisfaction, and customer loyalty among bank customers in Iran, employed a self administered structured questionnaire that measures service quality, customer satisfaction and customer loyalty in generating response from 147 respondents that are selected through the convenience sampling technique. The Results from the regression analysis indicated that customer satisfaction plays an important mediating role in the relationship between service quality and customer loyalty. Thus a favorable service quality will tend to lead to customer satisfaction which will henceforth lead to an improved customer loyalty. A major shortcoming of this study however, is the adoption of 147 respondents out of an unlimited customer population and the convenience sampling method adopted in picking the respondents. Hence these impedes on the generalization of the findings to the total research population.
Also, the study by Khan (2012) which aimed to build a model for customer relationship management in the telecommunication industry of Pakistan examined the impact of customer satisfaction and customer retention on customer loyalty among subscribers of four (4) mobile telecommunication companies who are students of different universities situated in the country. The convenience sampling method was employed in picking 86 respondents, with responses generated by administering structure questionnaire through the usage of electronic mail and personal interviews. A regression analysis was conducted with customer satisfaction exhibiting a positive, strong and significant relationship with the loyalty variable in an upward direction. However, customer retention was found to have an insignificant impact in the model. Hence this implies that organizations must be aware that customer retention without satisfaction would eventually lead to switching behavior. Additional, Rahmat, Madjid, Djumilah, Hadiwidjojo, Surachman, and Djumahir (2013) uncovered a statistically significant positive relationship between satisfaction and loyalty among customers at bank Rakyat in Indonesia (BRI). While in a much recent study by Genoveva (2015) among selected customers of Starbucks coffee in “Taiwan”, it was uncovered that customer satisfaction impact positively on customer loyalty.
Divergently, the empirically supported study by Almossawi (2012) to ascertain the importance and consequences of satisfaction in the competitive telecom industry in Bahrain, employed a survey involving 228 self administered structured questionnaire on mobile phone users across different age groups. From their findings, it was revealed that 79% of the customers who claimed they are very satisfied with their current mobile phone company admitted they will switch in the presence of better offer from other phone service providers thereby indicating the insignificance of customer satisfaction in preventing switching behavior from customers when there are better offers from rival companies. Nevertheless, these are findings from different mobile telecom market hence the impossibility of generalization to the Nigerian business environment, being characterized by different social-economic and cultural factors. In other words, it is unclear as to the result that might be uncovered here hence the proposition of this hypothesis.
There is no significant relationship between customer satisfaction and customer loyalty among the subscribers of mobile telecom companies in Kano metropolis.
Most theories that attempt to provide an explanation on the relationship between customer satisfaction and customer loyalty are bordered on the premise that consumer’s satisfaction or dissatisfaction respectively resides in people’s ability of learning from their past experience. This can be better explained by the theory of learning which posits that response given to stimuli is usually given either positively or negatively in accordance with the reward implication of the stimuli. As viewed by Dobre (2005) the reward leads to an evaluation of the degree of satisfaction in conformity with purchasing, and it can have an influence on the beliefs and attitudes towards a certain brand. Thus, a possibility of embarking on similar purchasing activities will increase if we perceive the presence of positive consequences in the act of purchasing, or vice-versa (Peyton, Pitts & Kamery, 2003). Some of these theories are highlighted below.
According to Isac & Rusu (2014) Fastener’s Theory of Dissonance (1957) which forms the basis of this theory, posits that that the consumer makes a sort of cognitive comparison between the expectations regarding the product and the product’s perceived performance. As argued by Anderson (1973) if there is a discrepancy between expectations and the product’s perceived performance, such will lead to dissonance. As observed by him, the consumers try to avoid dissonance by adjusting their perceptions of a certain product in order to bring it closer to their expectations. In a similar vein, they can reduce the tension that results from the discrepancy between expectations and the product’s performance, both by distorting the expectations so that they could be in agreement with the product’s perceived performance, and by increasing the level of satisfaction through minimizing the relative importance of experimental disconfirmation (Olson and Dover, 1979). Though while Yi (1990) inferred from this theory and proposes that companies should strive to raise expectations substantially above the product performance in order to obtain a higher product evaluation, Yukse l&Yuksel (2008) are in contradiction of this submission by stating that raising expectations substantially above the product performance and failing to meet these expectations may backfire as small discrepancies may be largely discounted while large discrepancies may result in a very negative evaluation and a brand switching behavior.
This theory, first introduced by Hovland, Harvey and Sherif (1957) presents an alternative approach to evaluating post-usage process that was presented in assimilation theory. This is as a result of the fact that post-usage evaluations lead to results in opposite predictions for the effects of expectations on satisfaction (Cardozo, 1965). This approach states that whenever the customers experiment disconfirmation, they try to minimize the discrepancy between their previous expectations and actual product/service performances by shifting their evaluations away from expectations. For instance while the theory of assimilation asserts that the consumers will try to minimize the expectation-performance discrepancy, the theory of contrast insists on a surprise effect that can lead to exaggerating the discrepancy. As posited by this theory, any discrepancy of experience from expectations will be exaggerated in the direction of discrepancy. Thus, if the firm raises expectations in its marketing communication, and then, customer’s experience from product usage is only slightly less than that promised, the product/service would be rejected as totally un-satisfactory. Divergently, under-promising in marketing communications and over-delivering will cause positive disconfirmation also to be exaggerated (Vavra, 1997). Thus, a useful knowledge impacted by this theory is that companies can secure better repurchase decision from their customers if they deliver more on the stated attribute of products/services.
Another disconfirmation model of customer satisfaction is the assimilation contrast theory. As argued by Hovland, Harvey and Sherif, (1957) this theory posits that satisfaction is a function of the magnitude of the discrepancy between expected and perceived performance. It posits that consumers set a baseline for the rejection and acceptance of a product in accordance with their perception. Put in another way, if performance is within a customer’s latitude (range) of acceptance, even though it may fall short of expectation, the discrepancy will be disregarded, assimilation will operate and the performance will be deemed as acceptable. Similarly, if performance falls within the latitude of rejection, contrast will prevail and the difference will be exaggerated, while the produce/service will be deemed unacceptable. According to Hovland, Harvey &Sherif (1957) this theory is a combination of both the assimilation and the contrast theories in that it equally lend credence to the argument that satisfaction is a function of the magnitude of the discrepancy between expected and perceived performance. Thus, consumers will tend to assimilate or adjust differences in perceptions about product performance to bring it in line with prior expectations but only if the discrepancy is relatively small (Peyton, Pitts, & Kamery, 2003).
Lastly, the confirmation and disconfirmation theory is another means by which the concept of customer satisfaction can be explained (Skogland & Siguaw, 2004) in this theory, it is opined that customers would tend to be satisfied with a product or services when their expectation from such product or services becomes confirmed by the perceived performance derived from its usage, and would tend to be dissatisfied when there is an imbalance/significant difference between their expectation and perceived performance of the product/service. Thus, satisfaction is the result of direct experiences with products or services, and it occurs by comparing perceptions against a standard (e.g. expectations) Mattila& Neil (2003). In their opinion, researches indicates that how the service was delivered is more important than the outcome of the service process, and dissatisfaction towards the service often simply occurs when guest’s perceptions do not meet their expectations. conclusively, the implication of this theory is that services oriented companies such as mobile telecommunication companies can enhance satisfaction among customers in order to stimulate repurchase behavior, by ensuring a consistent availability of customer representative executives who will foster the concept of service delivery on an efficient platform, process and languages that is most understandable by all customers.
The research model is developed based on review of existing literature on the relationship between customer loyalty and customer satisfaction and the hypothesis that have been formulated. An analytical model is developed and presented graphically below in fig 2.1.
Bergqvist&Esping (2003) are of the opinion that research designs are the procedural framework within which the research is conducted. Research design guides the investigator as he collects analysis and interprets observation and makes it possible to draw inferences for the purpose of generalization to a larger population (Nachmais&Nachmais, 1996). Thus, a cross sectional survey design was adopted for this study. In the view of Zikmund (2005) cross sectional survey is the best method available to a researcher when the objective of his research is to sample the opinion or perception of his respondents on issues of concern. This research seeks to determine the opinion of subscribers as regards their perception on service satisfaction and their willingness to remain loyal to their present main subscriber hence, the cross sectional survey approach was found most appropriate.
The populations of this study are the subscribers of Mobile telecommunication companies in Kano. The study examined the eight local government areas within Kano metropolis. It focuses on the subscribers of mobile telecommunication companies that are working or resident in these local government areas. Unfortunately, due to the nature of mobile telecommunication network which allows subscribers to move freely with their mobile phones from one geographical location to the other, it was impossible to get the correct figure of subscribers that are presently residing in these eight local governments from the offices of the companies under consideration hence an estimation of this figure was made by utilizing the statistics on average mobile phone ownership in major cities of Nigeria. According to the National Bureau of Statistics (2013) over 90% of the population in major cities of Nigeria has access to mobile phone. As such, the total population of the subscribers in focus is twenty five million, four hundred fifty nine thousand and seventy three (2545973) and its calculated on the basis of 90% of the total population of the eight local government areas, aforementioned. The populations of these eight local governments from a report by National Population Commission (2006) are as follows: – Kano municipal – 365,525 x 90% = 328,972 Tarauni – 221,367 x 90% = 199230 Fagge –198,828 x 90%= 178945 Nassarawa – 596,669 x 90% = 537002 Gwale – 362,059 x 90%= 325853 Dala - 418,777 x 90% = 376899 Kumbotso – 295,979 x 90%= 266381 Ungongo- 369,657 x 90% =332692. They also agreed that the city is one of the most populated cities in Nigeria and thus, have a cosmopolitan nature that represents all ethnic groups and tribes in the country hence it can provide a representative sample for major cities, tribes, and ethnic groups in the country.
Osuala (2005) opine that an important factor to be considered in sampling procedure is the issue of adequate representation of the population units. In addition, Zikmund (2005) argued that research result would tend to provide for more reliability and generalisability when sampling technique allows for large population elements that represents all the diverse characteristics in the population. Hence, the multi stage sampling technique, which according to Asika (1991) assures precision and thoroughness, was adopted in this study.
First, the cluster sampling method was employed in clustering the geographical boundary of Kano metropolis into eight secondary sampling units: Kano municipal, Tarauni, Gwale, Dala, Nassarawa, Fagge, Ungongo and Kumbotso. Cluster sampling is most appropriate when the objective is to investigate a large number of research elements that are scattered across a wide range of geographical location while operating in an atmosphere of financial constraint, and there is a need to retain the characteristic of probability sampling (Zikmund, 2005).Second, the determination of sample size from each cluster was carried out with the aid of proportional sampling technique. The proportional sampling is such that the items selected for the sample from clusters reflects the proportion of the cluster in the population (Zikmund, 2005). Hence this is done to ensure that subscriber in each local government are proportionally represented according to the population strength of the local governments.
The total sample size for the research is determined by drawing inference from the work of Krejcie & Morgan (1970) which has been adopted by the Universal Accreditation Board (2003) according to them, for a population that ranges from 100,000 to an upward of 10,000,000 a sample size of 384 is appropriate. Hence a total of 384 subscribers that are resident or working in the 8 local governments were employed as the sample size of this research. They were picked by adopting the convenience sampling technique.
Below in table 3.1 is the sample size to be drawn from each local government and the formula employed in arriving at such size.
Eight items from the original work of Sin (2005); Mouri (2005); Oliver (1997) and Fornel (1992) was adopted and modified to suit the specific need of the research, and the present environment. These items measures customer’s satisfaction with financial charges, satisfaction with the proximity of provider’s location, satisfaction with provider’s employees and satisfaction with overall services/products offered.
To measure the loyalty exhibited by customers in the study, (eight) items from the original work ofLam, Shanker, Eramilli& Murphy (2004); Morgan and Hunt (1994); and Zethaml (1988) was adopted and readjusted for local suitability. These items are designed to suit the need of the two major dimensions of loyalty namely attitudinal and behavioral loyalty. It measures the extent, to which respondents are willing to spread positive words of mouth about a brand both in the present and in the future, their tendency to stick with a brand even in the face of more competitive offers from rival brands, and their willingness to continue using the brand for a long period of time. Furthermore, all items were presented in a form through which respondents are expected to respond by showing their degree of agreement or disagreement on a five point Likert scale which range from (1) strongly disagree (2) disagree (3) undecided (4) agree (5) strongly disagree. This range holds if the statements are in positive form and it is reversed if it is a negative form.
Reliability of a study or research is necessary to minimize errors, biases and to overcome copy of another research (Yin, 1994). The objective of reliability is to make a study in a way that if someone else makes the same research, under the same situation, then he/she will find the same results. Zigmund (2005) further maintained that it is the degree of obtaining a consistency across different measures of the same test and the degree to which measures are free from errors and therefore yield consistent results. Hence the researcher conducted a pilot administration of all instruments on fifty (50) mobile phone users in Tarauni local government after which unclear questions were duly rephrased and restructured to be in line with their comments and suggestions. In addition, Cronbach alpha was used to measure the internal consistency of the items after administration on respondents.
The administration of instruments in this study was carried out was carried out in a period of one month and two weeks (1 ½) months specifically between June 2014 and August 2014. In carrying out the administration, the researcher focused on the public/private offices, apartments and business centers that are scattered across the eight local governments under focus in order to pick the subscribers that constitute his sample elements. In conjunction with an assistant; his student at the Kano state school of management, questionnaires was hand distributed to respondents after which they were enlightened on the benefit of the research and the need for them to give objective answers as it represents their true perception on the subject matters. Each respondents was given ample time of a range of 1 to 2 hours to ensure that all question are adequately answered so as to minimize incidence of missing data and omissions.
For the benefit of this study, the researcher employed the use of both descriptive and inferential statistics in the processing of data collected. Descriptive statistics is statistics such as the frequency distribution, mean, median and the standard deviation, which provide descriptive information on a set of data (Sekaran, 2008). Such analysis was employed in the processing of section A and B of the questionnaire which deals with both demographic profiles and the communication behavior of the respondents. The type of analysis that was used in the processing of section C of the questionnaire, which deals with the relationship between customer satisfaction and customer loyalty, was the inferential analysis. Specifically, Pearson product moment correlation was used in determining the strength of association among the variables while the multiple linear regression analysis was adopted to determine the predicting power of the independent variable on the dependent variable. All data processing was carried out by using the statistical package for social sciences (SPSS) 20th edition
A total of 384 copies of questionnaire were administered to respondents, however, only 380 copies were returned. From the returned copies, 4 copies were found to be badly filled and incomplete thereby rendering them unusable leaving the total usable copies to 376 which were consequently employed in statistical analysis.
First, respondents were classified on the basis of gender given the fact that gender could have influence on customer loyalty. The analysis indicated that 194 or 51.6% of the respondents were male while 182 or 48.4% of the respondents were female. This suggests that both gender groups are fairly represented in the study. Furthermore, they were classified on the basis of marital status. Here, analysis revealed that 167 or 44.4% are single, 206 or 54.8% are married, while 3 or 0.8% are divorced. They were further classified on the basis of age. It was found that 89 or 23.7% of the respondents are between 15-25 years, 195 or 51.9% are between 26-36 years, 64 or 17% are between 37-47 years, while 28 or 7.4% are 48 years and above. Similarly, they were classified on the basis of occupation and it was equally found that 168 or 44.7% are civil servants, 12 or 3.2% of are self employed, 103 or 27.4% are students. Furthermore, 82 or 21.8% are employed by the private sector while 11 or 2.9% are unemployed. Regarding educational qualification, 47 or 12.5% have the senior school certificate (SSCE) qualification, 74 or 19.7% have the ordinary national diploma (OND) certificate, 168 or 44.7% have the higher national diploma or bachelor degree, while 87 or 23.1% have post graduate qualifications. Finally, the respondents were classified on the basis of their monthly income. As was revealed by data analysis, 95 or 25.3% earns less than N15,000, 86 or 22.9% earns between N16,000-N31,000, 53 or 14.1% earns between N32,000-N47,000, while 142 or 37.8% earns N48,000 and above.
In order to have in depth knowledge of the respondents in relation to their mobile phone services subscription, analysis was carried out on their main telecom provider, factors that attracted them to use the network, and possession of alternative GSM line.Apparently, 289 or 76.9% of the respondents have MTN as their main provider, 22 or 5.9%, have Airtel as their main provider, 33 or 8.8% have Globacom as their main provider, while 32 or 8.5% have Etisalat as their main telecom service provider. This result seems to be in line with the argument by the Nigerian Telecommunication Communication that MTN is the dominant telecommunication company in the industry. Respondents were further classified on the basis of reasons for choosing their main telecom provider. Here, data analysis revealed that 82 or 21.8% are attracted by the relatively good price of products and service offered by the company, the majority, 101 or 26.9% are attracted through recommendations by friends and family members, Furthermore, 86 or 22.9% are attracted by efficient network, 13 or 3.5% indicated promotional offerings in form of products and service from the company as their reason for using their respective network, 80 or 21.3% are attracted by wider coverage, 13 or 3.5% indicated they subscribed to the line because it was the only network available at that time, while 1 or 0.3% indicated that their subscription was based on the fact that the company is customer focused. These results are interesting in that it revealed the strong influence of word of mouth marketing and the insignificance of promotional offerings in the industry. Finally, they were classified on the basis of alternative line ownership. The analysis revealed that, the majority of respondents, 296 or 78.7% responded that they have an alternative GSM line aside their main line while the minority, 80 or 21.3% indicated that they do not have any alternative GSM line. This finding is in tandem with the report of the National Telecommunication Commission (2014) which indicates that subscribers in the mobile telecom market possess more than one line.
In the opinion of Sekaran (2008) the value of .7 and above is considered acceptable and reliable. To ensure that items are reliable all, comprising a total of (16) were tested. Below is a table of the reliability statistics for the items.
According to Zikmund (2005) the descriptive procedure is useful for obtaining summary comparisons of approximately normally distributed scale variables and for easily identifying unusual cases across those variables. To give a descriptive outlook of the major variables in this study, a descriptive analysis was carried out. The table is presented below.
Table 4.2 above presents the results on the descriptive statistics of satisfaction as perceived respondents in this study. According to the table, the mean average score for respondents in the construct is 3.2546375; the minimum mean score for items is 2.9867 while the maximum mean score is 3.4574. Hence this indicates that the respondent in this study are above average in customer satisfaction.
Table 4.3 above presents the results on the descriptive statistics on customer loyalty as perceived by respondents in this study. According to the table, the mean average score for respondents in the construct is 3.5242; the minimum mean score among items is 3.2580, while the maximum mean score is 3.7340. Hence this is an indication that the respondent in this study are equally high in loyalty towards their telecom providers.
According to Cooper & Schindler (2014) normality statistics are those statistics that is used to assess if a distribution of scores is normal and not asymmetric. They pointed that notable means of testing for normality in a distribution is through the statistics of Skewness and Kurtosis. Below in table 4.4 is the statistics on Skewness and Kurtosis of the major constructs in this study.
Large values of Skewness and Kurtosis indicate non-normality while downward slides of such values indicate movements towards normality (Jahanzeb, Fatima & Khan, 2011). As evidenced by table 4.4 above, all the value on Skewness and Kurtosis for the two constructs are within the range of below +1 and -1 thereby indicating that the distribution of score across respondents are neither tilted extremely to the right or left. Hence the assumption of normality in distribution can be deduced to a large extent.
Pearson’s product moment correlation analysis was used to determine the nature (direct or inverse) and the degree of association between and among variables while the multiple regressions were employed to determine the explanatory power of the independent variables on the dependent variable. Pearson’s correlation analysis was preferred for the former since in the opinion of Zikmund (2005) is a common measure of the relationships between numerical variables measured on likert scale. The correlation matrix showing the strength of association among the variables is presented below in table 4.5.
As indicated by 4.5 above, the correlation coefficient between customer satisfaction and customer loyalty is .629, P = .000 (p< 0.01). In the opinion of Attar &Sweis (2010) value of Pearson correlation coefficient lying in the range of (0.1 – 0.29) suggest a small correlation. Value in the range of (0.3 & 0.49) suggest moderate correlation while the coefficients between (0.5- 1) suggest high correlation. Thus strong positive correlation has been established between customer satisfaction and customer loyalty. In other words, those mobile phone subscribers who expressed higher level of satisfaction with their main service provider tend to be equally higher in customer loyalty. Specifically, about 39.5% of the variance in customer loyalty is associated with the variance in customer satisfaction among them.
According to Hair, Black, Babin, & Anderson (2010) those assumption that are usually required to be satisfied in any linear regression model includes that of linearity and homoscedasticity. These assumptions apply to the independent variables, dependent variable and to the relationship as a whole (Hair et al, 2010). To ensure that the data set in this study are suitable for a multiple linear regression analysis, they are subjected to these tests.
Homoscedasticity implies that the variance of the distribution of the dependent variable should be constant for all values of the independent variable. As argued by Zigmund (2005) a data set is free from heteroscedasticity when there is no pattern to the data distribution and residuals are scattered randomly around the horizontal line through zero of the residual plots. To satisfy this assumption, the residual scores of the independent variable were examined through the normal p-p residual plot, as displayed below in Figure 4.1.
In figure 4.1 above, the p-p plot of the residual of the dependent variable under investigation is displayed. As indicated by the table, the residual scores are concentrated at the center along zero (0) point along the diagonal line thereby indicating that the model is free from any serious heteroscedasticity and the assumption of homoscedasticity is satisfied to a large extent.
Linearity refers to the degree to which the relationship between the independent variable and the dependent variable is linear. As posited by Norusis (2004) if the analysis of residuals does not exhibit any non linear pattern to the residuals, it is assumed that the overall equation is linear and can be examined through residual plots. He maintained that the points should be symmetrically distributed around a diagonal line in the P-P plot. As evidenced by the evaluation of the assumption of linearity in figure 4.1, no non linear pattern is exhibited to the residual which indicates that the overall equation is linear.
Now that the assumption of homoscedasticity and linearity has been satisfied, it is better to investigate the nature of the hypothetical model in a more sophisticated way by conducting a regression analysis to determine if the explanatory variables under study can be used as a predictor of customer loyalty. In any simple linear regression, the general form for the equation of any straight line on the graph is: Y = a+bx + e where “Y” is the dependent variable, “a” is the intercept on “Y” “b” is the beta or slope of the line, x is the dependent variable, while e stands for the error term in the model. The results of analysis are presented below.
In tables 4.5c above, the result of the linear regression of the independent variable, customer satisfaction and the dependent variable, customer loyalty is presented. According to the tables, customer satisfaction has a significant and positive impact on customer loyalty at the 0.01 significant level with the T statistics at 8.313, p = 0.000 (p < 0.01). Hence a rejection of the null hypothesis which predicted a non significant relationship between these two variables. In addition, since the model shows a standardized beta value of 0.629, this is an indication that every unit or 100% change in customer satisfaction will lead to a corresponding change of .629 or about 62.9% change in customer loyalty. It therefore means that if telecom companies focus on improvement of customer satisfaction, such action might likely make subscribers to be more committed to the products/services on offer by the companies.
Furthermore, as shown in table 4.5a, the R square value for the model is 0.394. This means that the predictor variable, customer satisfaction predicts about 0.394 of the variance in customer loyalty. Thus, about 39.4% of the variability in customer loyalty among the subscribers in this study is accounted for by the variability in the combination of customer satisfaction. Also, the one way ANOVA in table 4.5b shows an observed large value of “F” ratio, with a value much greater than one, a significant value of 0.000 and less than 0.01 indicating a strong and significant relationship between the independent variable on one side and the dependent variable, customer loyalty on the other side.
The main objective of this study was to determine the effect of customer satisfaction on the loyalty of subscribers in the Nigerian mobile telecommunication industry. On the basis of this objective, a null hypothesis which proposes that there is no significant relationship between the two constructs was put forward. However, this hypothesis was rejected based on the findings that a positive and highly significant (0.01) relationship exist between the two. In other words, it was uncovered that customer satisfaction exercises a positive and highly significant impact on the tendency of subscribers to remain loyal to their chosen mobile telecommunication company, or switch to another. This seems to be in line with the empirical study by Anderson & Sullivan (1993) which uncovered a positive relationship between the two concepts. It is also in support of the argument by Mosahab, Mahamad&Ramayah (2010) which maintains that service quality has a direct and indirect impact on customer loyalty in that variation in the quality and value of products and services provided to customer creates variation in customer satisfaction which in turn create a variation in customer loyalty. Overall, our finding in this study reveals the paramount importance of customer expectation in relation to the perceived performance of products/services. It indicates that mobile telecom companies can stimulate repurchase intention from subscribers and increase their commitment by making provision for those products/services that aggregate or surpasses expectation. Furthermore, it was equally discovered that the mean score among subscribers in the constructs of customer satisfaction and customer loyalty are well above average. Hence this is an indication that the mobile telecom service providers in the environment in focus are doing a great job in delivering quality products/services to these subscribers on consistent basis and this has hitherto resulted in a high switching cost for them and their willingness to remain as loyal customers.
Based on the findings that were highlighted in this study, one can conclude that the subscribers in Kano metropolitan areas place much emphasis on the ability of their telecom providers to surpass their expectations in terms of products/services. In other words, when the perceived performance of services offering fails to meet the expectation of subscribers, such will tend to lead to a low switching cost and a consequent high switching rate among them most especially, when there is availability of market competitors whom they perceive will deliver more on certain desired attributes. Thus, if telecom companies can provide for superior value offerings while taking into consideration, the concept of customer satisfaction, in conjunction with competitor’s satisfaction, such will be translated into a high switching cost among subscribers, and the ability of the companies to maintain a desirable loyal customer base.
Achour, M., Pujawati P.N., & Boerhannueddin, A. (2010). Customer Loyalty: The Case of Mobile Phone users in Universiti Utara Malaysia. Faculty of Business and Management, University Utara, Malaysia.
Akbar, M.M., &Parvez, N. (2009).Impact of Service Quality, Trust and Customer Satisfaction on Customer Loyalty. ABAC Journal, 29(1): 24-38.
Alderfer, C. P. (1972). Human Needs in Organizational Settings. Free Press, New York.
Almossawi, M.M. (2012). Customer Satisfaction in the Mobile Telecom Industry in Bahrain: Antecedents and Consequences. International Journal of Marketing Studies, 4(6).
Anderson, R.E. (1973)- Consumer Dissatisfaction.: The Effect of Disconfirmed Expectancy on Product Performance, Journal of Marketing, Research, 10: 38-44.
Anderson, E. W., & Fornell, C. (1994). A Customer Satisfaction Research Prospectus. In Roland, T. Rust & Richard, L. Oliver (Eds.), Service quality: new directions in theory and practice (pp. 241-268). Sage, Thousand Oaks, CA. http://dx.doi.org/10.4135/9781452229102.n11.
Anderson, Eugene W., & Sullivan, Mary W. (1993).“The Antecedents and Consequences of Customer Satisfaction for Firms,” Marketing Science, spring, 129.
Anderson, E.W. (1994).Variation in Customer Satisfaction and Retention. Marketing letters. 5 (1): 19-30.
Asika, N. (1991). Research Methodology in the Behavioral Sciences.Lagos, Nigeria. Longman Nigeria plc.
Attar, G.A., & Sweis, R.J. (2010). The Relationship between IT Adoption and Job Satisfaction in Contracting Companies in Jordan. Journal of Information Technology in Construction, 15(3): 44-63.
Batra, R., &Ahtolla, O. T. (1990).Measuring the Hedonic and Utilitarian Sources of Consumer Attitudes.Marketing Letters, 2: 159-170.http://dx.doi.org/10.1007/BF00436035.
Bergqvist, R., & Esping, P. (2003). The Potential of West European Sea- Based International System. Gothenburg, Sweden: ElandersNovum.
Buzzle, R. D., & Gale, B. T. (1987). The PIMS Principles: Linking Strategy to Performance. New York: Free Press.
Cardozo, R. (1965). “An Experimental Study of Customer Effort, Expectation, and Satisfaction”, Journal of Marketing Research, 2(8): 244-249.
Carmen, P.C. (2007). Perceived Risk on Goods and Service Purchases.Esic Market Journal, 129: 183-199.
Chen, P. T., & Hu, H. H. (2010). The Effect of Relational Benefits on Perceived Value in Relation to Customer Loyalty: An Empirical Study in the Australian Coffee outlets Industry. International Journal of Hospitality Management, 29: 405-412.
Cooper, D. R., & Schindler, P. S. (2014). Business Research Method (12th Edn). New York: McGraw-Hill Irwin.
Dobre, C. (2005)-Comportamentulconsumatoruluişipractica de marketing, Ed. Mirton, Timişoara.
Festinger, L. (1957)- A Theory of Cognitive Dissonance. Stanford, CA: Stanford University Press.
Fornell, C. (1992). A National Customer Satisfaction Barometer: The Swedish Experience. Journal of Marketing Research, 56: 6-21.
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, 64: 65-87.
Genoveva, I. (2015). Analyzing of Customer Satisfaction and Customer Loyalty Based on Brand Image and Perceived Service Quality. Journal of US-China Public Administration, 12(6): 497-50 doi: 10.17265/1548-6591/2015.06.008.
Gummeson, E. (1992). Quality dimensions: What to measure in service organizations? In Teresa A. Swartz, David E. Bowen & Stephen W. Brown (Eds.), Advances in services marketing and management: Research and practice (Vol. 1). JAI Press, Greenwich, CT.
Hair, J. F., Black, W. J., Babin, B. J., & Andersen, R. (2010).Multivariate Data Analysis (6th Edn). New Jersey: Prentice Hall.
Heskett, J. L., Thomas, O. J., Gary, W.W., .Earl, S.J., & Schlesinger, L.A. (1994). Putting the Service- Profit Chain to work‟, Harvard Business Review, 72 (March- April), 164-74.
Hokanson, S. (1995). The Deeper you Analyze, the More you Satisfy Customers. Marketing News, 16
Herzberg, E. (1966). Work and the nature of man. Fourth Edition, Prentice Hall. Anderson, E. W., Fornell, C. & Lehmann, D. R. (1994). “Customer Satisfaction, Market Share, and Profitability: Finding from Sweden”. Journal of Marketing, 58 (4), 53-66.
Hansemark, O.C, and Albinson, M. (2004). Customer Satisfaction and Retention: The Experiences of Individual Employees. Managing Service Quality. 14(1), 40-57..
Hornibrook, S.A., &Fearne, A. (2003). Managing Perceived Risk as a Marketing Strategy for Beef in the UK Food Service Industry. Journal of International Food and Agribusiness Management Review, 6(3).
Hovland, C., Harvey, O., Sherif, M.(1957).Assimilation and Contrast Effects in Reaction to Communication and Attitude Change. Journal of Abnormal and Social Psychology, 55(7): 244-252.
Ishaq, M.I. (2011). Perceived Value, Service Quality, Corporate image and Customer Loyalty: Empirical Assessment from Pakistan. Serbian Journal of Management 7 (1) (2012): 25 – 36.
Isac, F.L. &Rusu, S. (2014). Theories of Consumer Satisfaction and the Operationalization of the Expectation Disconfirmation Paradigm .Annals of the „Constantin Brâncuşi” University of TârguJiu, Economy Series, 2.
IT and Telecom Digest (Saturday April 20, 2013). War! In the Nigerian Telecoms Industry.Accessed at www.ittelecomdigest.com/cover-july.htm .
Jahanzeb, S., Fatima, T., & Khan, M.B. (2011). An Empirical Analysis of Customer Loyalty in Pakistan’s Telecommunication Industry. Journal of Database Marketing & Customer Strategy Management, 18(1): 5–15 www.palgrave-journals.com/dbm/.
Keaveney, S.M. (1995). Customer Switching Behavior in Service Industries: An Exploratory Study. Journal of Marketing, 59(2): 71-82
Khan, I. (2012).Impact of Customer’s Satisfaction and Customer’s Retention on Customer Loyalty .Evidence from Pakistan Telecom Industry .International Journal of Scientific & Technology Research, 1(2).
Kim, M., Park, M., & Jeong, D. (2004). The Effects of Customer Satisfaction and Switching Barrier on Customer Loyalty in Korean Mobile Telecommunication Services. Telecommunications Policy, 28(2): 145-59. http://dx.doi.org/10.1016/j.telpol.2003.12.003.
Kotler, P. & Amstrong, G. (2012).Principles of Marketing. New Jersey: Pearson Prentice Hall.
Kotler, P., & Keller, K. (2009).Marketing Management: An Asian Perspective. Pearson Education International, Prentice Hall.
Kotler, P. (2003). Conceptualizing, Measuring, Managing Customer-Based Brand Equity, Journal of Marketing, Vol.57 (1), pp 1-22.
Krejcie, R.V., & Morgan, D.W. (1970).Determining Sample size for Research Activities. The BobbMeril Co Inc, 608. Website: http://opa.uprrp.edu/InvinsDocs/KrejcieandMorgan.pdf.
Lam, S. Y., Shankar, V., Erramilli, M. K., & Murthy, B. (2004). Customer Value, Satisfaction, Loyalty, and Switching Costs: An illustration from a Business-to-Business Service Context. Journal of the Academy of Marketing Science, 32:293–311.
Levitt, T. (1983). The Globalization of Markets”, Harvard Business Review, May–June.
Lin, H. H., & Wang, Y. S. (2006).An Examination of the Determinants of Customer Loyalty in Mobile Commerce Contexts. Journal of Information and Management, 43(3): 271–282.
Liu, L. (2008). Study of the relationship between customer satisfaction and loyalty in telecom enterprise, 2008 IEEE International Conference on Service Operations and Logistics, and Informatics, Vol. 1, pp. 896-901
Maslow, A. H. (1970). Motivation and personality (2nd ed.). Harper and Row, New York.
Mattila, A. & O’Neill, J.W. (2003).’Relationships between Hotel Room Pricing, Occupancy, and Guest Satisfaction: A Longitudinal Case of a Midscale Hotel in the United States’, Journal of Hospitality & Tourism Research, 27(3): 328-341, Sage Publications.
Mitchel, V.W. (1993). Consumer Perceived Risk: Conceptualizations and Models. European Journal of Marketing, 33(1/2): 163-195.
Morgan, R. M., & Hunt, S. D. (1994).The Commitment – Trust Theory of Relationship Marketing. Journal of Marketing, 58 (3): 20 – 39.
Mouri, N. (2005). A Consumer-Based Assessment of Alliance Performance: An Examination of Consumer Value, Satisfaction and Post-purchase behavior; University of Central Florida, 2005, 156 pages; AAT 3193496, available on 01/03/2009 http://proquest.umi.com/pqdweb?did=1014307471&sid=1&Fmt=2&clientId=46934&RQT=309&VName=PQD.
Mosahab, R., Mahamad, O., &Ramayah, T. (2010). Service Quality, Customer Satisfaction and Loyalty: A Test of Mediation. Journal of International Business Research, 3(4).
Nachmias, F.C., &Nachimias, D. (1996).Research Methods in the Social Sciences. London, Arnold.
Norusis, M. (2004).SPSS 13.0 Guide to Data Analysis. Upper Saddle-River, N.J.: Prentice Hall, Inc.
National Bureau of Statistics (2013). Annual Socio Economic Report: access to ICT. Accessed at www.nigeriastat.ng.
National Communications Commission (2013).Industry Statistics (Online at http://www.ncc.gov.ng).
National Communication Commission, (2014). Teledensity Data retrieved on the 2rd April, 2015availableatwww.ncc.gov.ng/indexphp?option=com_contentandview=articleandid=68statistics-industryandcatid=65:cat-web-statisticsitmid=70.
National Communication Commission (2015). Subscriber’s Data. Accessed at http://www.ncc.gov.ng.index e.htm.
National Population Commission (2006).Population of Kano by local Government Area .Accessed at www.nigeriastat.ng/nbsapps/annual.
Odunlami, I.B. & Mathew, A.O. (2015). Impact of Customer Satisfaction on Customer Loyalty: A Case Study of a Reputable Bank in Oyo, Oyo State, Nigeria. International Journal of Managerial Studies and Research (IJMSR), 3(2): 59-69.
Olson, J., Dover, P. (1979). Disconfirmation of Consumer Expectations through Product Trial. Journal of Applied Psychology, 64: 179-189.
Oliver, R. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions, Journal of Marketing Research, 460 – 469.
Oliver, R. (1997). Satisfaction: A Behavioral Perception on the Consumer. New York: McGraw Hill.
Oliver, L. R.(1999). "Whence Consumer Loyalty?", Journal of Marketing, 63(4): 33-44.
Osuala, E.E. (2005). Introduction to Research Methodology. Onitsha, Nigeria. African first Publishers.
Peyton, R.S. & Kamery, R.H. (2003). Consumer Satisfaction/Dissatisfaction: a review of the literature prior to the 1990’s”, Proceedings of the Academy of Organizational Culture, Communication and Conflict. Vol. 7(2).
RahmatMadjid, DjumilahHadiwidjojo, Surachman, and Djumahir (2013).“The Role of customer trust and commitment as Mediator for the relation between satisfaction and loyalty at bank Rakyat Indonesia (BRI) Kendari southeast Sulawesi’’, International Journal of Business and Management Invention, 2.
Roger, B. (1996). Creating Product Strategies. International Thomson Business Press, ISBN 0 415 13256 8. Bus. Strat.Env., 6: 51–52. doi: 10.1002/(SICI)1099-0836(199702)6:1<51.
Schneider, B. & Bowen, D. (1995).Winning the Service Game. Boston: Harvard Business School Press.
Sekaran, U. (2008). Research Methods for Business. New York: John Wiley and sons.
Sin, E. (2005). ‘CRM: Conceptualization and Scale Development. European Journal of Marketing, 39(11/12): 12-90.
Skogland, I. and Siguaw, J.A. (2004).Understanding Switchers and Stayers in the Lodging Industry. Cornell Hotel and Restaurant Reports, 4(1).
Smith, R., & Wright, W. (2004), Determinants of Customer Loyalty and Financial Performance. Journal of Management Accounting Research, 16(Special Issue): 183-205. http://dx.doi.org/10.2308/jmar.2004.16.1.183.
Suleiman, G.P., Nik, M. K., Adesiyan, O.I., Mohammed, A.S., & Jamal, A. (2012). Customer Loyalty in e-Banking: A Structural Equation Modeling (SEM) Approach. American Journal of economics, issue: 55-59 DOI: 10.5923/j.economics.20120001.13.
Tseng, Y.M. (2007). The Impacts of Relationship Marketing Tactics on Relationship Quality in Service Industry: Journal of Business review. 7(2): 310-314.
Universal accreditation board (2003). Accreditation Study Course: Random Sample Size Table. Accessed at http://www.praccreditation.org/secure/documents/coachH016.pdf.
Vavra, Terry G. (1997)- Improving Your Measurement of Customer Satisfaction: A Guide to Creating, Conducting, Analyzing, and Reporting Customer Satisfaction Measurement Programs. American Society for Quality
Vessel, P. and Zabkar, V. (2009).Managing Customer Loyalty through the Mediating Role of Satisfaction in the DIY Retail Loyalty Program.Journal of Retailing and Customer Services, 16: 396- 406.
Vuuren, T.V., Lombard, M.R., &Tonder,E.V. (2012). Customer Satisfaction, Trust and Commitment as Predictors of Customer Loyalty within an Optometric Practice Environment.Southern African Business Review, 16(3), pp.12-26.
Yaacob, M.R., NikIsmail,N.R., & Ismail, N.S.(2009). An Investigation of the Determinants of Customer loyalty of the Maxis Communications Berhad .Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan.
Yi, Y. (1990). A Critical Review of Customer Satisfaction, în Review of Marketing, AMA, 68-123.
Yin, R. K. (1994). Case Study Research: Designs and Methods, (Second Edition), Thousand Oaks, London. Sage Publication Inc.
Yuksel, A. &Yuksel, F. (2008). Customer Satisfaction: Conceptual Issues. The Cornell Hotel and Restaurant Administration Quarterly, December.
Zhang, X., & Feng, Y. (2009).The Impact of Customer Relationship Marketing Tactics on Customer Loyalty-within Swedish Mobile Telecommunication Industry. Master Thesis, Halmstad University.
Zeithaml, V. A. (1988). Consumer Perceptions of Price, Quality, and Value: A means-end model and synthesis of evidence. Journal of Marketing, 52: 2-22. http://dx.doi.org/10.2307/1251446.
Zikmund, W.G. (2005). Sampling Designs and Sampling Procedures: Business Research Methods, Ohio, South -Western.