Volume 3, Number 1 (2016) pp 1-23 doi 10.20448/806.3.1.1.23 | Research Articles
As a result of the shift from the traditional product orientation towards a customer based selling approach, companies, particularly those in the telecommunication industry are becoming more aware of the need for a better understanding of target customers and how these customers will react to organizational relationship marketing tactics based on their respective demographic characteristics, with a view to use such knowledge as a basis of attracting and maintaining a robust customer loyalty base. This study examines the effect of brand trust on customer loyalty. It went on further to determine the moderating influence of gender, age, and income level, among subscribers in the Nigerian telecommunication industry. A structured and close ended questionnaire was employed in eliciting responses from three hundred and seventy six (376) mobile telecom subscribers who were selected through the multistage sampling technique, from the eight local governments of Kano metropolis. Furthermore, the results from the three step regression analysis conducted indicates that while brand trust exercise a significant and positive effect on customer loyalty, this relationship is however, not moderated by gender, age and income level. In the light of these findings, it was recommended that those companies, whose focus is improving customer loyalty from the viewpoint of brand trust, should carry out such action without any consideration for the three highlighted demographic variables: gender, age and income level, in their segmentation exercise.
Keywords: Brand trust, Customer loyalty, Moderation, Demographic variables, Subscribers, telecommunication Industry.
Citation | Adewale, A. Adekiya; Bamidele, A. Adepoju (2016). The Relationship between Brand Trust and Customer Loyalty: The Moderating Impact of Demographic Characteristics. International Journal of Marketing Practices, 3(1): 1-23.
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 conflicts of interests regarding the publication of this paper.
History : Received: 24 May 2015/ Revised: 10 June 2016 / Accepted: 15 June 2016/Published: 24 June 2016
Publisher: Online Science Publishing
With the introduction in 1992 of the National Communications Commission (NCC) which has the role of creating an enabling regulatory environment for efficient supply of telecommunications services and facilities in the Nigerian telecommunication industry, the industry began to witness the entry of private participants. The reform, which opened up the market to local and private operators, injected competition into the market. Though some companies were issued operating licenses before 1999 full market liberalization however only commenced in earnest with government enacting a new telecom policy document in September 2000 (Tooki, 2011). After full stakeholder consultations, a new law, the Nigerian Communications Act was enacted in 2003 to boost investor confidence and provide clear rules of engagement for industry stakeholders. Consequently, private investment in the sector has grown from about $50m in 1999 to over $25 billion by 2010 with commensurate rapid growth in subscriber lines (Tooki, 2011).
According to Tooki (2011) the high level of competition and an increasing demand, coupled with pressure on the management of these companies to deliver on shareholders earnings and justify increasing investment have resulted in a war fought with neither swords, guns, nor nuclear weapons but a stiff competition cloaked in the garment of war which continues unabated as each operator roll out new offers and products in a bid to outsmart the other while the target remains: to get the larger chunk of the over 100 million mobile subscribers in the country. Hence this has culminated in a barrage of promos and offers that left the subscribers spoilt for choices (Tooki, 2011).
For instance MTN Nigeria kick-started the revolution with the launch of its extra cool in 2006, (particularly introduced to capture the youth market with free mid night calls). Zain Nigeria, (now Airtel) responded to this by also introducing Zain Tru, which offer subscribers one of the cheapest GSM on-net call rates at 25 kobo per second (Monday to Friday) and 21 kobo/second on weekends. Etisalat on the other hand rolled out its easy cliq, another exciting package targeted at youths. The package came with innovative and exciting features like unlimited SMS, free midnight calls, talk n share, bonus on incoming calls, one cliq, one tune, Facebook update service by SMS and cliq ring back tune. With easy cliq, subscribers are automatically rewarded with free airtime for calls received from other networks, and Etisalat lines that are not on easy cliq with the innovative bonus on incoming calls feature. Aside these, the company recently announced that it has revamped its easy life tariff based service with the introduction of return of access fee and easy life postpaid. This package offers subscribers cost effective and affordable call rates as well as free text messages to other Etisalat lines on both prepaid and postpaid lines. Glomobile, launches its Glo Flexi, Glo yarn-me-more and Glo wonderful in 2011. The Glo Flexi is said to offer up to 99 per cent discount on calls made, depending on the time of day and geographical location of the subscriber. The Glo yarn-me-more came with propositions that after the first 60seconds/1minute (daily) call charged at the rate of 55k/s, the subscribers can enjoy 15k/s Glo to Glo calls and 25k/s Glo to other networks calls. Also, the Glo wonderful rewards customer with free minute on every call being made irrespective of the call being on net or off net.
All these are buttresses to the argument by the National Communication Commission (2013) which positions the mobile telecomm market in Nigeria as among the most competitive market in Africa. To further promote efficient competition, the commission has initiated several proceedings which allows conduct that reduces competition in the market to be duly penalized. For instance there are a number of regulatory frameworks such as the Nigerian Communication Act, 2003 Section 91(1) which prohibits licensees from engaging in conduct which has the purpose or effect of lessening competition in the industry. The outcome of this intense competition is a substantial bargaining power for subscribers coupled with tendencies to switch service provider at will. This seems to be in line with the view of Amusu & Olayinka (2006) who noted that as the number of offering within a category multiplies, the differences between them start to become increasingly trivial and loyalty, to the best value replaces any previous loyalty to a brand. Trust is a central component in the development of relationship between organizations and customers and a condition that exists when one party has confidence in an exchange partner’s reliability and integrity (Dithan, 2011). It is the basis of building a mutually beneficiary relationship with customers in order to enhance competitiveness (Barney & Hansen, 1994). Put in another way, trust is an essential element and condition that must be satisfied between customers and organizations in order to make provision for successful long term relationship. As argued by Jahanzeb, Fatima & Khan (2011) trust is found to increase customer’s commitment, which weakens customers’ propensity to switch. In their opinion, it serves as a key element to build customer loyalty. According to Dithan (2011) a high level of trust may turn a satisfied customer to be loyal thus, implying that companies can secure customer loyalty through the indirect influence of customer satisfaction by concentrating on the mediating power of trust. Empirically, the research by Lombard & Vuuren (2012) found that a direct relationship, strong and significant, exists between trust and customer loyalty among 357 patients who assesses an optometric practice in South Africa while other researches see for instance: Adekiya (2015) and, Sarwar, Abbas, & Parvais (2012) all shows that the perception of trust by customers can act as an antecedent to their decision to remain loyal to organizational products/services. While all these researches are concentrated on the exploration of the direct relationship between these two constructs, no concrete attempt have been made to determine the moderating impact of demographical variables: gender, income level and age on this relationship despite the submission by Lee & Cunningham (2001); Saad, Ishak, & Johari (2013); Cole, Drolet, Gutches, Pandrand, Norton, & Peter (2008); Alrubaiee & Al-Nazeer (2010) which highlighted these demographical variables as important elements when the objective is discouraging customers from switching brand, and the argument by Cooil, Timothy, Lerzan & Micheal (2007) which equally posits customer characteristics as major determinant of the ability to retain them, in addition to enhancing their repurchase intention. In other words, a research question that comes to the attention of these researchers is if these critical demographical variables can act as a buffer in a research model that consist of brand trust as an independent variable and customer loyalty as a dependent. In a nutshell, this research seeks to determine the moderating impact of consumer’s demographic characteristics on the relationship if any, between their perception of brand trust on one side and their tendency to remain as loyal customers on the other side. It is narrowed down to the subscribers in the Nigerian mobile telecommunication industry and it is thus, anticipated that the findings uncovered will be useful for marketing managers and industry leaders particularly within the telecommunication industry, whenever the objective is the construction of customer profiling data, aimed at the formulation and implementation of marketing plans and strategies, for the enhancement of organizational competitive advantages. In the subsequent sections, the literature review, research methodology, presentation of results, discussion, conclusion and recommendations are presented.
According to Rousseau, Sitkin, Burt, & Camerer (1998) trust is a psychological state in which individuals are willing to accept vulnerability due to their positive expectations of the intentions or behavior of another. A trust violation occurs when someone demonstrates a lack of skills required for a role, or fails to uphold important ethical principles (Mayer, Davis, & Schoorman, 1995). These are pointers that development and sustainability of trust in organizational setting is built upon the fulfillment of promises made to customers. Morgan & Hunt (1994) define trust as a condition that exists when one group has the confidence to engage in a relationship with another trustworthy and honest party. Drawing inference from this definition, it is arguable to concur that such elements as confidence and reliability are crucial in building trust. Mayer, Davis and Schoorman (1995) in their own view provided one general definition of this construct by saying that it is the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control the other party. According to Dithan (2011) theories of social psychology assert that trust consists of two essential elements: trust in the partner’s honesty and trust in the partner’s benevolence. He maintained that honesty is the belief that one’s partner stands by its word, while benevolence, in his opinion is the belief that one’s partner is interested in the company’s welfare and will not take unexpected actions which will negatively impact the company. As noted by Ruyter, Wetzel & Bloemer (1998) if partners in business relationship trust each other more, they are more emotionally involved and less consciously weighing the benefits against the costs of that relationship. In other words, customers would tend to be more emotionally involved with a brand in the face of increased sincerity and honesty that is being exhibited by the brand even when they perceives the costs/benefits outcome of such relationship as not much favorable.
Ian (2011) posits that if customers trust a company, there is high tendency that they will make recommendations about its products and services to their friends. Furthermore, Liang & Wang (2008) maintains that trust or distrust often takes place with a relationship built up. they declares that as a supplier of product/service actively and consistently makes sincere relationship efforts, such efforts provides evidence to customers that the supplier can be trusted, is concerned about customers’ interests and is willing to make sacrifices for satisfying customers’ needs in the relationship. An act, which they suggests will lead to an increment of customer’s trust in the supplier. By implying from this, it will be reasonable to posit that companies willing to secure customer trust to their brand must be those who are consistent in the exhibition of concern and sincerity to their customers, vice versa.
Despite substantial disagreement about the exact definition or nature of the loyalty concept, common elements among many of the loyalty definitions are that there is a relationship of some sort (i.e., ranging from very shallow to very strong) between an actor and another entity and that the actor displays behavioral or psychological allegiance to that entity in the presence of alternative entities (Melnyk Van Osselaer and Bijmolt, 2008). By following this line of reasoning a loyal customer within the framework of this study is one that rebuys, repartronize, and have declared allegiance to their mobile phone service providers both in terms of behavioral and attitudinal even in the presence of competing alternative providers. In the observation of Jahanzeb, Fatima & Khan (2011) there are evidences from research to prove that customers who exhibit loyalty not only reduce the marketing costs of doing business but also, lessen the need to incur customer acquisition costs. It is in their opinion that it is possible to increase organizational profits by 60 per cent by averting potential migration of 5 per cent. This position was further strengthened by Dithan (2011) who is of the view that transforming indifferent customers into loyal ones, and establishing a long term relationship with them is critical to organizational success. In other words, a viable measure of organizational performance can be in terms of its ability to retain existing customers at a faster rate, against the acquisition of new ones. Similarly, if anything truthful is to be drawn from the observation by Shoemaker and Lewis (1999) then repeat or behaviorally loyal customers will also act as information channels in addition to informally linking networks of friends, relatives and other potential customers to the organization. Thus, since the development and sustenance of a viable customer loyalty base has been highlighted as a critical organizational success factor, researchers and industry leaders have consistently tried to unravel the mysteries that surround some of its important antecedents. In this study, our attention shall be principally focused on brand trust.
By relating trust to the concept of loyalty among customers, Dithan (2011) suggest that a high level of trust may turn a satisfied customer to be loyal which implies that companies can secure customer loyalty through the indirect influence of customer satisfaction by concentrating on the mediating power of trust. As suggested by them, customers will be loyal to telecom companies if they trust that such provider will meet up with their needs in addition to delivering on promises made, and will likely switch from one service provider to another in search of trustworthiness. Results from earlier studies for instance Berry (2002) stressed that in telecom services, trust is the basis for loyalty, and that the biggest cause of failure to retain customers and make them loyal is the lack of trust.
Empirically, Zhang & Feng (2009) in their attempt to determine the mediating nature of customer satisfaction and trust in the relationship between some selected relationship marketing strategies on one hand, and customer loyalty among Swedish mobile subscribers on the other, employed the use of internet survey to sample the opinion of 101 randomly selected students of Halmstad University. A multivariate regression analysis was performed and it was discovered that relationship marketing tactics: service quality, price perception, and value offers all have a positive and significant impact with customer loyalty through the mediating power of customer satisfaction and trust. This implies that these relationship marketing tactics might be used to increase customer loyalty indirectly, through the mediating power of customer satisfaction and trust. Nonetheless, their research was however, characterized by three major limitations: the total number of 101 responses generated out of 700 targeted subjects and a consequent response rate of 14 .4% which is too low, the consequent margin of error of 10% that results from a total student’s population of 7000 which is quite high, and the non- generalizability of the research to the whole Swedish population of mobile subscribers due to the fact that only the students of a particular university were considered.
Similarly, Dithan (2011) conducted a study to demonstrate the effect of some relationship marketing orientation on the loyalty of subscribers to selected telecommunication companies in Uganda. They conveniently selected 400 subscribers whose opinion was sampled on relationship marketing orientations: trust, commitment, communication, reciprocity, satisfaction and their willingness to stay loyal to their respective providers, through a self administered structured questionnaire. The Pearson product moment correlation and the multiple regression analysis were adopted as tools of statistical analysis while the results obtained indicates that the combination of all relationship marketing orientation considered, have a significant and positive relationship with customer loyalty.
Another study by Sarwar, Abbas, & Parvais (2012) designed, to clarify the relationship between customer trust on customer loyalty and retention, in addition to the moderating role of cause related marketing in such relationship was focused on the cellular services industry of Pakistan. Primary data were collated from 150 university students via personally administered questionnaire. Further, the result from the Pearson correlation analysis indicates that both customer trust and cause related marketing have significant relationship with customer loyalty. Other results from a linear regression model revealed that while brand trust has a significant effect on customer loyalty, such effect is however moderated by cause related marketing. This indicates that in securing customer loyalty from the view point of customer trust, telecommunication companies must equally focus on improving cause related marketing activities in the form of corporate social responsibility endeavors, and other related social welfare packages. These are findings from other environment being characterized by different social, cultural and economic phenomenon and it is yet to be decided if such will be the case in the Nigerian mobile telecom industry hence the formulation of this first hypothesis
Hypothesis (1) there is a significant relationship between brand trust and customer loyalty among subscribers in the Nigeria mobile telecommunication industry
According to Kotler & Keller (2009) there are two reasons for popularity of demographic variables as a means of distinguishing among customer groups. First, consumer’s needs, wants, usage rates, and product and brand preferences are often associated with demographic variables; second, demographic variables are easier to measure. They stated that even when the target market is described in non demographic terms, the link back to demographic characteristics is needed to estimate the size of the market and the media that should be used to reach out to them. Some of the important demographic characteristics that have been identified by Melnyk, Van Osselaer and Bijmolt (2008) are gender, lifestyle, age, income level, educational status, generation and social class. In this study we shall concentrate on gender, age group and income level with a view to determine if they have any moderating influence in the relationship between brand trust and customer loyalty.
As observed by Fisher and Dubé (2005) academic research has discovered important differences in cognitive processes and behavior of male and female consumers. These differences are reflected in the widespread use of gender as a segmentation variable in marketing practice (Melnyk, Van Osselaer and Bijmolt, 2008). Their argument was built upon the crust that if male and female loyalties differ, men and women might require a different selling approach, has different levels of customer value, and may respond differently to loyalty programs and other actions aimed at enhancing customer loyalty. By following this line of reasoning, it is arguable to give a concession that gender difference might be having a moderating role in any relationship between brand trust and customer loyalty since brand trust as a construct, has been shown to represent a core attribute when the objective is building a robust customer loyalty enhancement programs.
Drawing inference from the theory of gender difference: interdependence versus independence, Cross and Madson (1997a) argued that females are more interdependent than males. Based on their observations, they strive to feel connected to other people, while at the same time, having interrelatedness with society, social relationships, and social groups, which acts as a more important part of their identity than it is for men. According to this theory, women focus on maintaining relationships as against the men who sees themselves as more independent, are more individualistic, and strive for uniqueness and individuality. To men as against the women, the concerns of society, family members, or other people are secondary to the individual's (Cross and Madson, 1997a). According to them, these differences in self-construal are the result of differences in socialization of males and females starting in early childhood. Though, the argument put forward by Melnyk, Van Osselaer and Bijmolt (2008) indicates that this theory does focus directly on customer loyalty, they however admitted that it can be used to inspire different predictions about customer loyalty. Their argument was based on two major observations (1) since the theory is of the opinion that females are more interdependent than males, then, they are more likely to be loyal customers. (2) If women tend to strive more for establishing and maintaining relationships to people and social contexts, then they may do the same for relationships for example, with service personnel and companies. Empirically, the results from Stan (2015) is absolutely in support of this school of thought by showing that women are more in possession of a significant level of store loyalty than men.
Contrastingly, Baumeister and Sommer (1997) theory of relational versus collective interdependence suggests that while the female consumers may be more loyal than male, such conclusion can only be made depending on the object of loyalty. It pointed that the former are more likely to focus narrowly on dyadic bond while the later will tend to focus more on a broader social structure (group). Put in another way, females are more likely to be loyal to individual employees or sales personnel in a company while males will tend to be more loyal to companies, which may be construed as more group-like (Melnyk, Van Osselaer and Bijmolt, 2008). Thus, if inferences must be drawn from this, it can be presumed that males will be more loyal to telecom companies as a result of the brand image associated with such company while females will be more loyal to individual employees in the company. Nonetheless, this position differs from the opinion of Musikawa (2011) who pointed that female customers are more inclined to maintain a relationship with a company to avoid the emotional difficulty of switching to another company while males are less interested in this relationship but more interested in the best offer.
Regarding gender differences as it effects on the relationship between consumer loyalty and its antecedents, few researches have been conducted in marketing literature and the results are mixed (Stan, 2015).While the study by Mittal and Kamakura (2001) clearly shows that gender difference has a moderating influence on the relationship between customer satisfaction and customer loyalty with customer satisfaction performing a more important role as a driver for men than for women, other studies for example, Helgesen & Nesset (2010) and Frank, Enkawa, & Schvaneveldt (2014) failed to uncover any significant moderating influence of gender in this relationship. Though, the result from Frank et al. (2014) indicates that perceived value has a weaker effect on repurchase intent for women than for men while brand image strongly influences repurchase intent for women than for men, the later study by Stan (2015) contradicts this by showing that gender difference cannot be used as a buffer in these relationships. Nevertheless, since brand image is likely to lead to a perception of trust among consumers (Aaker, 1996), With the later, being highlighted as a precursor to customer loyalty, a notable research question will be if gender difference will have any moderating impact in a research model, consisting of brand trust as an independent variable and customer loyalty as a dependent variable which leads us to the formulation of this hypothesis.
Hypothesis (2) gender difference will act as a moderator in the relationship between brand trust and customer loyalty among subscribers in the Nigerian mobile telecommunication industry.
Mittal and Kamakura (2001) are of the opinion that customer characteristics such as age have a great impact on the level of customer retention. By lending credence to this position, Saad, Ishak and Johari (2013) declares that age allows marketers to determine how want and needs changes as an individual matures. Furthermore, the submission by Hansman and Schutjens (1993) indicates that age is a strong predictor of changes in attitudes and behaviors including those that are incline towards products/services loyalty. According to Yoon (2002) theoretically, it is safe to conclude that older consumers will exhibit more loyalty than their counterparts who are younger. Their argument was based on two reasons: older consumers are more interested in familiar brands; they will tend to remain loyal to brands that are closer to their environment as a result of less mobility in later life. Other researchers for instance Saad et al. (2013) also lend credence to this line of reasoning by declaring that older consumers are more conservative and less willing to try new brands.
Empirically, the study by Uncles and Ehrenberg (1990) among fast moving consumer goods customers in the United States found that there is no significant difference in brand loyalty among the customers while another study by Wood (2004) in Australia discovered a significant difference in the loyalty of younger consumers between 18 and 24 years old across all product categories. Contrastingly, the research by Matzler, Grabner-Kräuter, & Bidmon (2006) among the customers of product categories that ranges from mobile phones, sunglasses, running shoes, and blue jeans in two Austrian cities uncovered that the age of these customers does not have any significant influence on the relationship between brand trust and customer loyalty while a later similar study in Iran by Hanzaee and Andervazh (2012) among three hundred and fifty (350) Iranian shoppers also revealed that this relationship is not moderated by age differences. Put in another way, while some of these empirically supported findings are of the view that companies must lay emphasis on age differences when the objective is improving customer loyalty from the viewpoint of brand trust, others are of the opinion that such action is not necessary in that it might lead to an un-necessary wastage of marketing resources. To subject these positions to further testing, we equally propose this third hypothesis.
Hypothesis (3) age difference will act as a moderator in the relationship between brand trust and customer loyalty among subscribers in the Nigerian mobile telecommunication industry.
According to Saad, Ishak and Johari (2013) income segmentation is a popular demographic variable utilized by a myriad of product and service marketers in that it allows businesses with target markets that cross income levels to promote different products and services to the dissimilar income groups. This can be seen in businesses such as Airline and Hotels where different categories of services are offered at different prices to different customers according to their income level. As argued by East, Harris, & Hammond (1995) research indicates that shoppers who are more price sensitive are less loyal, which indicates that customers in high income groups are more likely to be more loyal than those in lower income groups. Monroe and Petroshius (1981) conceptualize price consciousness as individual differing reluctance to pay for additional or distinguishing features of a product if the price difference is too large while Miyazaki, Anthony, Sprott, & Kenneth (2000) define price consciousness as individual difference variable reflecting the enduring motivation to consider unit price information. Since it can be theoretically argued that consumers who are of higher price sensitivity are more likely to be those in the lower income group, then it is equally arguable that these group of customers will exhibit lower brand loyalty than their counterpart in a higher income group. This position can be attributed to two major reasons: (1) highly price-conscious consumers express lower perceptions of offer value and higher price information search intentions (Alford and Biswas, 2002), (2) the consumers level of price consciousness influences the propensity to search for prices (Urbany, Dickson and Kalapurakal, 1996). All of which influences the tendency for consumer brand switching in the face of lower price offering from other firms.
Furthermore, the research by Gan, Maysami, & Koh (2006) provided an empirically supported evidence that people in higher income category have a tendency to be more loyal to credit card service provider than those who earns lower income while Choi and DeVaney (1995)found income level to be insignificant in the determination of those customers who are likely to be more loyal to a brand. While the above findings are conflicting in nature and thus, remain inconclusive, it might be reasonable to subject the issues raised to further empirical testing whose results will serve as a means by which they (the findings) can either be accepted or refuted hence we formulate this fourth hypothesis.
Hypothesis (4) income level will act as a moderator in the relationship between brand trust and customer loyalty among subscribers in the Nigerian mobile telecommunication industry.
Based on the submission by Zigmund (2005) which pointed the cross-sectional survey design as a research design which deals with eliciting responses from respondents through the survey method at a particular point in time, this particular research adopts this research approach as it is aimed at collecting responses on the perception of brand trust and brand loyalty among the subscribers of mobile telecommunication companies in the environment investigated. The populations of the 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 according to 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 thereby having the capability of providing a representative sample for major cities, tribes, and ethnic groups in the country.
Based on Krejcie and Morgan (1970) work on estimation on sample size, which has been adopted by the universal accreditation board (2003) a total sample size of three hundred and seventy four (384) was arrived at from the total research population highlighted above. Further, the sampling procedure involves clustering the geographical boundary of Kano metropolis and its surrounding environ into eight primary 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 (Zigmund, 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 (Zigmund, 2005). This is done to ensure that subscriber in each local government are proportionally represented according to the population strength of the local governments. Finally, the primary sampling units were picked by adopting the convenience sampling technique.
As the questionnaire is the chief data collection tool in this study, it is essential that the questions are appropriate to what the study is intending to achieve. For such provision the questionnaire adopted in this study was divided into two parts.
Section A: contains 6 questions that measures demographic characteristics of respondents.
Section B: consists of the main variables that were earlier highlighted: brand trust brand loyalty.
First, brand trust, made up of eight items from the work of Sharma & Peterson (2000) was utilized after necessary readjustment for suitability to the Nigerian environment. These instruments were designed to measure such attributes as customer’s level of risk perception, beliefs in the consistency of service providers, employee’s fairness, and in addition, company’s sincerity and honesty. 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 Zeithaml (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. 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 neighboring identical 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.
Validity means “Does the research focuses on what it is meant to”? (Oulton, 1995). According to Walonick (2005) validity refers to the accuracy or truthfulness of a measurement or the extent to which a test measures what it is purported to measure. in his opinion, there are no statistical tests to measure validity in that all assessment of validity are subjective opinion based on the judgments of the researcher and other experts in the field. As such, all the instruments utilized in the study were adopted from the work of experts and researchers in the areas under focus.
After the retrieval of the questionnaires from the respondents, they were appropriately edited, coded, and serially numbered for statistical analysis. 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) of the questionnaire which deals with demographic characteristics of the respondents. The type of analysis that was used in the processing of section B of the questionnaire, which deals with the relationship between brand trust and customer loyalty was the inferential analysis. Specifically, Pearson product moment correlation was used in determining the strength of association between the main variables while the linear regression analysis and the moderated regression analysis were adopted to determine the predicting power of the independent variable on the dependent variable, and the interaction effect of the highlighted demographic characteristics in the relationship between the two main variables respectively. All data processing was carried out by using the statistical package for social sciences (SPSS) 20th edition.
In the conceptual framework in fig 3.1 above, the proposed hypothetical model for the research is displayed. According to the table, there is a significant relationship between brand trust and customer loyalty. However, such relationship is moderated by the highlighted demographical variables: gender, age and income level.
Of the total 384 copies of questionnaire administered to respondents, only 380 copies were returned. From the returned copies, 4 copies were found to be badly filled and incomplete thereby rendering them unusable leaving a total usable copies to 376 which were consequently employed in statistical analysis.
The demographic characteristics of respondents were classified based on gender, age group, income level, educational level, occupation and marital status. Based on the analysis conducted, it was found that 204 or 52.3% of the respondents were male while 186 or 47.7% of the respondents were female. In addition, 177 or 45.4% of respondents are single, 210 or 53.8% are married, while 3 or 0.8% are divorced. Also, 94 or 24.1% of the respondents are between 15-25 years, 202 or 51.8% are between 26-36 years, 66 or 16.9% are between 37-47 years while 28 or 7.2% are 48 years and above. Furthermore, 173 or 44.4% of the respondents are civil servants, 13 or 3.3% of the respondents are self employed, while 108 or 27.7% are students. Also, 84 or 21.5% are employed by the private sector while 12 or 3.1% are unemployed. As regards educational qualification, 50 or 12.8% of the respondents have the Senior School Certificate (SSCE qualification), 77 or 19.7% have the Ordinary National Diploma (OND certificate), 172 or 44.1% have the Higher National Diploma or Bachelor Degree, while 91 or 23.3% have post graduate qualifications. Finally, 99 or 25.4% earns less than N15,000, 89 or 22.8% earns between N16,000-N31,000, 55 or 14.1% earns between N32,000-N47,000, while 147 or 37.7% earns N48,000 and above.
In order to verify the construct reliability of each latent variable that was used, Cronbach’s α was employed in this regard. As shown in the table below, the values for the two main variables meets the reliability threshold of α > 0.75 as suggested by Tenenhaus, Vinzi, Chatelin, & Lauro (2005).
Table 4.2 above presents the results on the descriptive statistics of brand trust as perceived by respondents in this study. According to the table, the mean average score for respondents in the construct is 3.4714; the minimum mean score for items is 3.226, for item (3) while the maximum mean score is 3.6356 and for both items (1) and (5). This indicates that the respondents are moderately high in perception of trust towards their telecom providers.
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 for items is 3.2580, for item (3) while the maximum mean score is 3.7340 and for item (1). Hence this is an indication that the respondent in this study are equally high in loyalty towards their telecom providers.
Similarly, to ensure that all items meet the assumption of normality they were subjected to these tests. The results obtained indicates that both brand trust and customer loyalty has a skewness value of -.647 and -.518 respectively while a Kurtosis value of .824 and .368 were equally respectively obtained for these two constructs.
With inferential statistics, we are trying to reach conclusions that extend beyond the immediate data alone (Dithan, 2011). In their opinion, this type of statistics is used to make judgments of the probability that an observed difference between groups is a dependable one, or one that might have happened by chance. Thus, we are using inferential statistics to make inferences from our data to a more general condition.
First, person correlation was used to determine the strength of association between the construct of brand trust and customer loyalty. The result obtained indicates that these two variables are significantly associated with each other which imply that the initially proposed relationship can now be examined in a more hypothetical manner through the linear regression model. Below is a table that shows the summary of the coefficient of these two variables.
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. As indicated by the table above, the correlation coefficient between brand trust and customer loyalty is .518, p = .000 (p<0.01). This implies that a significant, high and positive association has been uncovered between these two variables. Furthermore, it can be inferred from the table that about 26.8% of the variance in customer loyalty is associated with the variance in brand trust. Put in another way, the subscribers who perceive that they can trust their providers are those who exhibited a higher level of loyalty towards such providers.
In other to determine the effect of the independent variable on the dependent variable, in addition to the moderating influence of the demographical variables that were highlighted, a three step regression analysis was carried out. the first step is a univariate analysis that focuses on the main effect of brand trust on customer loyalty, the second step focuses on the individual effect of gender, age and income level on customer loyalty, while the third step, is a multivariate analysis that focuses on the predicting power of the independent variable, in conjunction with the proposed moderating variables, in a single regression model. Below in table 4.5, 184.108.40.206, 4.8 and 4.9 are outputs that display the outcome of these analyses.
The table in 4.5 above shows the regression output for the relationship between brand trust and customer loyalty. According to the table, brand trust has a positive and significant impact on customer loyalty at the 99% significant level with T statistics at 11.716, p=0.000 (p< 0.001) in addition, with a standardized beta value of .518 that was uncovered, it can be projected that for every unit or 100% increase in brand trust among mobile phone services subscribers, an increase of .518 or 51.8% increase in customer loyalty can be projected by telecom companies. Hence hypothesis (one) which states that there is a significant relationship between brand trust and customer loyalty is accepted.
The table in 4.6 above shows a summary analysis of the relationship between gender and customer loyalty. As evidenced by the table, there exist an insignificant relationship between gender and customer loyalty with T statistics at .803, p=.422 (p>0.001). In addition, the model has a beta coefficient of .041 which implies that a unit change from male to female will only lead to an insignificant increase of .041 or 4.1% in customer loyalty. Hence the second hypothesis which says that gender is a moderator in the relationship between brand trust and customer loyalty can be partially rejected.
The table in 4.7 above shows a summary analysis of the relationship between the age of respondents and their tendency to exhibit loyalty towards their respective telecom providers. As evidenced by the table, there exist an insignificant relationship between age and customer loyalty with T statistics at .082, p=.935 (p>0.001). In addition, a beta coefficient of .004 was uncovered which also implies that a unit increase in the age of respondents will only lead to an insignificant increase of .004 or 0.4% in customer loyalty. Hence the third hypothesis which says that age is a moderator in the relationship between brand trust and customer loyalty can be partially rejected.
The table in 4.8 above shows a summary analysis of the relationship between the income level of respondents and the construct of customer loyalty. As evidenced by the table, there exist an insignificant relationship between income level and customer loyalty with T statistics at -.759, p=.448 (p>0.001). In addition, the beta coefficient of -.039 uncovered implies that a unit increase in respondent income will only lead to an insignificant decrease of .039 or 3.9% in customer loyalty. Thus, we can partially reject the fourth hypothesis which says that income level is a moderator in the relationship between brand trust and customer loyalty.
Finally, the output from the multivariate analysis, showing the effect of brand trust on customer loyalty, in addition to the effect of the three highlighted demographical variables is displayed in table 4.9. According to the table, except for brand trust, which has a significant and positive relationship with customer loyalty at a standardized beta coefficient of .518, the three other demographic variables included in the regression model, seems not to be having any significant relationship with the later which leads us to the confirmation of the deductions earlier put forward that these demographic variables does not have any significant confounding power in the relationship between brand trust and customer loyalty. Put in another way, hypotheses (2), (3) and (4) which respectively proposed that gender, age and income level are moderators in the relationship between brand trust and customer loyalty are fully rejected. Thus, the relationship between brand trust and customer loyalty is not dependent on any of gender, age and income level.
The foundation of this research work is laid upon the formulation of four research hypotheses. After the utilization of appropriate statistical tools, the first hypothesis, which proposes that there is a significant relationship between brand trust and customer loyalty was accepted due to the significant and positive relationship uncovered between these two constructs. Put in another way, it can be projected that a unit increase in brand trust among the subscribers in this study will yield a corresponding increase of 0.518 or 51.1% in customer loyalty. Thus, if subscribers perceives that their service provider have always delivered on its promises in the course of their relationship over the years, and they have never experienced disappointment in such relationship, such perception might likely translate into a prolonged relationship with the provider as against a switch to other providers whose intentions and future actions are yet to be determined.
This finding is absolutely in line with the submission by Dithan (2011) which pointed that customers will be loyal to organizational products/services, if they are of the beliefs that the providers of these products/services will meet their needs and provide what is promised unto them, prior to purchase, and will equally switch from one product/service provider to another in search of trustworthiness. It is also in tandem with Ruyter, Wetzel & Bloemer (1998) who are of the position that if partners in a relationship trust each other more, they are more emotionally involved and less consciously weighing the benefits against the costs of that relationship. Empirically, it shares the same view with the results from the study by Sarwar, Abbas, & Parvais (2012) among mobile phone users in Pakistan which uncovered that 56% of the variance in customer loyalty is accounted for, by these customer’s’ perception of trust towards their respective service providers. Thus telecom companies who are consistent in sincerity and honesty in the delivery of promises to their subscribers are likely to enjoy a superior and favorable loyalty from such subscribers. On the contrary, if subscribers perceive that their service provider is not trustworthy, such might lead to a search for an alternative provider that could be more trusted. What is more is that such subscribers are likely to spread negative word of mouth regarding their experience to others. The implication of these is a dwindled market share for the company, a significant reduction in its rate of return, and consequently, company failure.
Furthermore, the second hypothesis which proposes that the gender group of respondents will act as a moderator in the relationship between brand trust and customer loyalty was rejected due to the result uncovered which indicates that the membership of a particular gender group (male or female) is not a determinant in the uncovered relationship between brand trust and customer loyalty among the respondents. Thus, while the perception of trust among them (respondents) will tend to have a positive impact on their willingness to continue employing the use of organizational products/services, such perception will not translate into a higher level of brand loyalty for either of the two gender groups, highlighted in this study. This finding is in contrast with the report by Melnyk, Van Osselaer and Bijmolt (2008) where it was posited that as a result of the interdependence of female customers, they are more likely to exhibit higher level of loyalty in any relationship, including that, engaged in, with business organizations.
Similarly, the third hypothesis which proposed that the age group of respondents is a significant moderator in the relationship between brand trust and customer loyalty was rejected due to the insignificant moderating influence that was uncovered for this demographic variable. This implies that effect of brand trust on customer loyalty is constant across the subscribers regardless of their age group. Thus, telecom companies can increase the level of commitment to organizational products/services among subscribers by focusing on increasing brand trustworthiness, while at the same time, not using age as a segmentation variable. The finding here is in coherence with the empirically supported results by Matzler, Grabner-Kräuter, & Bidmon (2006) where an insignificant moderating effect was uncovered for customer’s age group, in the relationship between brand trust and customer loyalty. Also, it is absolutely in line with a similar study byHanzaee and Andervazh (2012) where it was also revealed that this relationship is equally not moderated by the age difference among the three hundred and fifty (350) Iranian shoppers, considered.
Finally, the fourth hypothesis, which predicted that the income level of respondents will moderate the relationship between brand trust and customer loyalty was equally rejected due to the insignificant moderating influence of respondent’s income level that was uncovered for this relationship. In other words, the relationship between brand trust and customer loyalty among respondents in a lower financial status is not significantly different from that, uncovered among their counterparts in higher financial status.
Based on the findings from statistical analysis of data and the consequent discussion that ensured, the following conclusion and implications are arrived at: the perception of trust among consumers of organizational products/services (especially, telecommunication related products/services), is essential when the objective is the enhancement of organizational based customer loyalty. Hence, telecom companies can deter their subscribers from switching network by being consistent and truthful in any promises made to them, prior to products/services purchase. Also, it can be concluded that the three demographical variables identified in this study: gender, age and income level are not important factors of consideration whenever the objective is increasing customer loyalty from the viewpoint of trust which implies that the concept of market segmentation on the basis of these demographic characteristics is irrelevant.
5.3. Suggestions for Further Research
The following are some of the probable areas that might call for further investigation by potential researchers in order to further broaden knowledge on the concepts under focus in this particular study.
Aaker, D.A. (1996). Building Strong Brands. The Free Press, NY.
Adekiya, A. A. (2015). Correlates of Customer Loyalty among Prepaid Mobile Phone Subscribers in Kano Metropolis, Nigeria..
Unpublished M.Sc. Dissertation Submitted to the Department of Business Administration and Entrepreneurship, Bayero University, Kano.
Alford, B., L. and Biswas, A. (2002). The Effects of Discount Level Price Consciousness and Sale Proneness on Consumers’ Price Perception and Behavioral Intention, Journal of Business. Research. 55: 775-783.
Alrubaiee,L., & Al-Nazer, N. (2010). Investigating the Impact of Relationship Marketing Orientation on Customer Loyalty: The Customer's Perspective. International Journal of Marketing Studies, 2(1).
Amusu, A., & Olayinka, B. (2006). Essentials of Marketing Management. Ibukun Oluwa Publishers, Lagos.
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.
Barney, J.B., & Hansen, M.H. (1994). Trustworthiness as a Source of Competitive Advantage. Strategic Management Journal, 15: 175-190.
Baumeister, R. F., & Sommer, K. L. (1997). What do men want? Gender Differences and two Spheres of Belongingness: Comment on Cross and Madson. Psychological Bulletin, 122: 38–44.
Berry, L. (2002). Relationship Marketing of Services – Perspectives from 1983-2000’, Journal of Relationship Marketing, 1(1): 59-77.
Choi, H.N., DeVaney, S. (1995), "Factors associated with the use of Bank and Retail Credit Cards", in McKenzie, S.B., Stayman, D.M. (Eds), Proceedings of the Society for Consumer Psychology, American Psychology Association, La Jolla, CA. pp: 152-9.
Cole, C., Laurent, G., Drolet, A., Ebert, J., Gutchess, A., Lambert‐Pandraud, R., Mullet, E., Norton, M.I. and Peters, E. (2008), “Decision Making and Brand Choice by Older Consumers.", Marketing Letters, 19(3): 355‐365.
Cooil B, Timothy LK, Lerzan A, Micheal H (2007). A Longitudinal Analysis of Customer Satisfaction and Share of Wallet: Investigating the Moderating Effect of Customer Characteristics. Journal of Marketing, 71: 67-83.
Cross, S.E. & Madson, L. (1997a). Models of the Self: Self-Construals and Gender. Journal Psychological Bulletin, 122(1): 5–37.
Dithan, N.P. (2011). Relationship Marketing, Word of Mouth Communication and Customer Loyalty in the Telecommunication Industry of Uganda. A Dissertation Report Submitted for the Partial Fulfillment of the Requirement for the Award of the Degree of Master of Science in Marketing of Makerere University, Kampala-Uganda.
East, R., Harris, P., & Hammond, K. (1995) "Correlates of first Brand Loyalty", Journal of Marketing Management, 11(5): 487-97.
Fisher, R.J. & Dubé, L. (2005). Gender Differences in Responses to Emotional Advertising: A Social Desirability. Journal of Consumer Research; ABI/INFORM Global. pp: 850
Frank, B., Torrico, B. H., Enkawa, T., & Schvaneveldt, S. J. (2014). Affect Versus Cognition in the Chain from Perceived Quality to Customer Loyalty: The Roles of Product Beliefs and Experience. Journal of Retailing. http://dx.doi.org/10.1016/j.jretai.201408001
Gan, L., Maysami, R.C., Koh, H.C. (2006), “Credit Card Selection Criteria among Singaporean Consumers”working paper, Economic Growth Centre, School of Humanities and Social Sciences, Nanyang Technological University, Singapore.
Hansman, H., Schutjens, V. (1993), "Dynamics in Market Segmentation: A Demographic Perspective on Age-Specific Consumption", Marketing and Research Today, 21(3): 139-47.
Hanzaee, H. K. and Andervazh, L. (2012). An Analysis of Some Moderating Variables on the Value, Brand Trust and Brand Loyalty Chain. Research Journal of Applied Sciences, Engineering and Technology, 4(10): 1403-1413.
Helgesen, Ø, & Nesset, E. (2010). Gender, Store Satisfaction and Antecedents: a Case Study of a Grocery store. Journal of Consumer Marketing, 27(2): 114-126.
Ian, S. (2011). Organizational Quality and Organizational Change: Interconnecting Parts to Effectiveness. Emerald group publishing limited, 01435124, 32(1/2): 1/128.
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/
Kotler P. and Keller K.L (2009) Marketing Management: an Asian perspective. Pearson Education International, Prentice Hall.
Krejcie, R.V., & Morgan, D.W. (1970). Determining Sample size for Research Activities. The Bobb Meril Co Inc p.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.
Lee, M. and Cunningham, L.F. (2001). “A Cost/Benefit Approach to Understanding Service Loyalty”, Journal of Services Marketing, 15(2): 113‐30.
Liang, C., & Wang, W. (2008). Do Loyal and More Involved Customers Reciprocate Retailer’s Relationship Efforts? Journal of Services Research, 8(1): 63-90.
Matzler, K., Grabner-S.K., & Bidmon, S. (2006). The Value – Brand Trust – Brand Loyalty Chain: an Analysis of Some Moderating Variables. Journal of Innovative Marketing, 2(2).
Mayer, R.C., Davis, J. H., & Schoorman, F. D. (1995). An Integrative Model of Organizational Trust. Academy of Management Review, 20(3): 709-734.
Melnyk, V., van Osselaer, S.M.J., & Bijmolt, T.H.A. (2008). Are women More Loyal Customers than men? Gender Differences in Loyalty to Firms and Individual Service Providers. Journal of Marketing, 73(4): 82–96.
Mittal, V., Kamakura, W.A. (2001), "Satisfaction, Repurchase Intent and Repurchase Behavior: Investigating the Moderating Effect of Customer Characteristics", Journal of Marketing Research, 38(February): 131-42.
Miyazaki, A., D., Sprott, E. David and Manning, C. Kenneth, (2000). Unit prices on retail shelf Labels: An Assessment of Information Prominence. J. Retail. 76(1): 93-112.
Monroe, K.B. and Petroshius, S.M. (1981). Buyers Perceptions of Price: An Update of the Evidence. Perspectives in Consumer Behavior, Glenview, Foresman and Company, IL: Scott, pp: 43-55.
Morgan, R. M., & Hunt, S. D. (1994). The Commitment – Trust Theory of Relationship Marketing. Journal of Marketing 58 (3): 20 – 39.
Musikawa, A. (2011). An Evaluation of Customer Retention Based on Gender and Age during Critical Cash Crisis of 2008. A Case Study of Commercial Banks in Bindura.E3 Journal of Business Management and Economics, 2(2): 084-088.
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 Population Commission (2006). Population of Kano by local Government Area. Accessed at www.nigeriastat.ng/nbsapps/annual.
Oulton, T. (1995). Management Research for Information: Management Decision, 33(5): 63-67.
Rousseau, G.K., Lamson, N., Rogers, W.A. (1998), "Designing Warnings to Compensate for Age-Related Changes in Perceptual and Cognitive Abilities", Psychology & Marketing, 15(7): 643-62.
Ruyter, K., Wetzel, M., & Bloemer, J.M. (1998). On the Relationship between Perceived Service Qualities, Service Loyalty and Switching Costs. International Journal of Services Industries. 9(5): 436-453.
Saad, R., Ishak, H., & Johari, N.R. (2013).The Impact of Demographic Factors toward Customer Loyalty: a Study on credit card users. Elixir International Journal of Marketing Management. Available online atwww.elixirpublishers.com.
Sarwar, M.Z., Abbasi,K. S., & Pervaiz, S. (2012). The Effect of Customer Trust on Customer Loyalty and Customer Retention: A moderating role of cause related marketing. Global Journal of Management and Business Research, 12(6).
Sekaran, U. (2008). Research Methods for Business. New York, John Wiley and sons.
Sharma, N., & Patterson, P. G. (2000). Switching Costs, Alternative Attractiveness and Experience as Moderators of Relationship Commitment in Professional Consumer Services. International Journal of Service Industry Management, 11(5): 470-90.
Shoemaker, S., Lewis, R.C. (1999), "Customer loyalty: the future of Hospitality Marketing", International Journal of Hospitality Management, 18: 345-70.
Stan, V. (2015). Does Consumer Gender Influence the Relationship Between Consumer Loyalty And Its Antecedents? The Journal of Applied Business Research, 31(4).
Tenenhaus, M., Vinzi, V.E., Chatelin, Y.-M., & Lauro, C. (2005). PLS Path Modeling. Computational Statistics & Data Analysis, 48(1), 159-205.
Tooki, A. (2011). A New Dimension to Nigeria’s Telecom Revolution. Accessed at http://businessworldng.com/web/categories/IT.
Urbany, J., E. Dickson, R. Peter and R. Kalapurakal, (1996). Price Search in the Retail Grocery Market. J. Market., 60: 91-104.
Uncles, M.D. & Ehrenberg, A.S.C. (1990). "Brand Choice among older Consumers", Journal of Advertising Research, 30(August/September): 19-22.
Universal accreditation board (2003). Accreditation Study Course: Random Sample Size Table. Accessed at http://www.praccreditation.org/secure/documents/coachH016.pdf.
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).
Walonick, S.D. (2005). A Chapter from Survival Statistics: An Applied Statistics Book for Graduate Studies. Boston, Massachusetts.
Wood, L.M. (2004), "Dimensions of Brand Purchasing Behavior: Consumers in the 18-24 age group", Journal of Consumer Behavior, 4(1): 9-24.
Yin, R. K. (1994). Case Study Research: Designs and Methods, (Second Edition), Thousand Oaks, London. Sage Publication Inc.
Yoon, S. J. (2002). The Antecedents and Consequences of Trust in Online-Purchase Decisions. Journal of Interactive Marketing, 16(2): 47–63.
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
Zigmund, W.G. (2005). Sampling Designs and Sampling Procedures: Business Research Methods, Ohio, South –Western.