Customer Relationship Management Impact on Air Passengers Brand Preference

Customer Relationship Management Impact on Air Passengers Brand Preference

¹Olugbenga Ezekiel PEARSE, PhD., ¹Olugbenga DABIRI., ²Jude Imokhai AKHABA, PhD

¹Department of Marketing, Lagos State University of Science and Technology, Ikorodu

²Department of Marketing, Lagos State University. Ojo

DOI: https://dx.doi.org/10.47772/IJRISS.2025.906000306

Received: 03 June 2025; Accepted: 07 June 2025; Published: 12 July 2025

ABSTRACT

Businesses are now implementing and using a variety of tactics to accomplish organizational goals, the one of the tactics which is customer relationship management (CRM), has recently come to light as a crucial and genuine tool required by enterprises to satisfy and retain their customers. The main objective of this study was to investigate customer relationship management impact on air passengers brand preference in Nigeria Airline industry. The research design used for this study was survey design. The sample size was 376 respondents using judgmental sampling technique. Taro Yamane formular was adopted which gave 399.99 approximated to 400 sample size. Hence 400 questionnaires were distributed but 376 were correctly filled in and found usable for this study. Primary data with reference to a well-structured and adapted questionnaire was used. The research tools used descriptively were mean and standard deviation and inferentially, analysis of variance (ANOVA) and ordinary least square (OLS) were used. Levene’s test of homogeneity was adopted with Durbin-Watson. Also Cronbach Alpha tests were carried out. The findings of this study revealed that both customer retention rate and net promoter score influence brand preference in Nigeria airline industry, hence this study concludes that both customer relationship management (customer retention rate and net promoter score) has impact on brand preference in Nigeria Airline sector. The study recommends that policymakers, directors and management of airlines together with students and researchers, that customer relationship management has impact on brand preference of air passengers in Nigeria.

Keywords: Customer relationship management, customer retention rate, net promoter score, brand preference.

INTRODUCTION

Organizations face fierce competition in the modern business environment, so it is critical for them to both attract and keep current customers (Fiiwe, Egele, Ozo, & Obasiabara, 2023). Businesses are now implementing and using a variety of tactics to accomplish these goals, such as customer relationship management (CRM), which has recently come to light as a crucial and genuine tool required by enterprises to satisfy and retain their customers. According to Mulyana (2020), CRM is a business-customer relationship that typically includes every facet of an organization’s interaction with its clients, whether in the sale of goods or services. This illustrates how long-term relationships that were developed through relationship management are put into practice.

In order to improve business relationships and customer satisfaction, CRM is a collection of techniques, technologies, and strategies used to manage and analyse customer interactions and data throughout the customer lifecycle (Aloqool, Alharafsheh, Abdellatif, Alghasawneh, & Al-Gasawneh, 2022; Naim, 2022). Companies are searching for methods to raise and maintain customer satisfaction, strengthen customer loyalty, and boost business profitability in light of the fiercer competition in the airline sector (Hanaysha, Al-Shaikh, & Kumar, 2022). CRM is a broad process that concentrates its efforts on treating various customers differently to increase value for both the customer and the organisation. This is because CRM shows that customers define a business, and the goal of any business organisation is to create values that will attract and retain customers. (Hanaysha et al., 2022).

Genuine brand preference and effective and efficient CRM can be developed by a company-wide dedication to comprehending customers’ needs and exceeding their expectations, concentrating on customer-centric marketing strategies, and consistently providing personalised experiences (Ekakitie-Emonena, 2021). Fundamentally, a consistently positive emotional experience, a high perceived value, and satisfaction with brand interaction are what lead to customer preference and loyalty towards a brand (Ghorbanzadeh, 2021). As a result, the main objectives of CRM are to give each individual customer a seamless experience, collect insightful customer data that can be utilised to make better business decisions and cultivate enduring relationships with them, and comprehend the needs and preferences of their customers, all of which will eventually enable the company to personalise customer offerings and increase customer satisfaction. CRM’s primary goal is to design and implement customer-focused strategies by creatively, effectively, and efficiently leveraging customer data (Mustapha, Kareem, Adeniyi & Abdulwasiu, 2023; Herman et al., 2021).

The majority of businesses worldwide are working hard to increase customer preference for their brand in order to foster customer loyalty and sustain a strong base of devoted clients (Rane, Achari, Choudhary, 2023). Due to increased customer awareness brought about by the globalisation of competition, market saturation, economic downturn, and advancements in information technology, long-term success can no longer be attained through product price and quality alone. Rather, long-term customer relationships are the foundation of modern business organisations’ success (Adiyanto, 2019). The airline industry is particularly unique in that it has unique customers, so putting CRM strategies into practice is crucial for businesses to succeed in today’s competitive business environment (Fraihat et al., 2023).

Yet, there are particular difficulties facing Nigeria’s airline industry, including restricted market access, poor connectivity, high fares and costs, deteriorated airport infrastructure, low service quality, responsiveness, unfavorable government interference, and numerous taxes. Additionally, there are issues with inadequate funding access, low level air navigation assistance, unclear policies, poor strategy and implementation, poor corporate governance, corruption, brain drain, a weak regulatory environment, low productivity, overstaffing, and outdated and poorly maintained aircraft (Sylva & Amah, 2021).

Today’s airline travellers are more affluent, picky, and inquisitive about content, price, and quality. They forget things less frequently and ask for and expect greater benefits (Nwaogbe, Ogwude, Ejem & Pius, 2021). Industry rivals provide additional options in addition to the same. The Nigerian airline industry depends on both business and leisure travellers; the former are more likely to travel frequently and to purchase upgraded services, which increase the airlines’ profit margins (Adeniran, Njoku & Stephens, 2023). However, leisure travellers are usually very price sensitive and are less likely to purchase these premium services. Indeed, the airline sector is highly susceptible to expenses like fuel, labour, and loans. According to Abdi, Li, and Càmara-Turull (2023), the airline industry is actually very sensitive to costs like fuel, labour, and loans.

Statement of the Problem

CRM is an essential and strategic tool for managing and improving an organization’s relationship with its clients. The implementation of this strategy is imperative to ensure the appropriate delivery of customer value and the retention of current customers. In particular, it aims to enhance customer satisfaction and loyalty through personalised and responsive service to individual customers (Peter & Peter, 2024).  CRM has shown that a successful company strategy for boosting competitive advantage and establishing long-term relationships over time (Taherdoost, 2023).  According to Clark (2023), businesses require CRM systems to manage their clientele and maximise customer loyalty because acquiring new clients is five times more expensive than keeping current ones. Customers are the most important component of any organisation and determine whether it will succeed or remain in business (Marais, 2021).

Customer needs and priorities, brand preference, and customer retention rate are of  a great concern (Ahmad & Dubey, 2024) and net promoter score (Agag, Durrani, Abdelmoety, Daher & Eid, 2024) are all used by more successful CRMs to keep customers loyal to their brands (Phonga, Ngaa, Hanha & Minha, 2020). Effective management is essential for successful businesses in order to establish and preserve solid customer relationships. Additionally, building positive relationships with customers is one of the best ways to guarantee recurring business for airlines and encourage them to recommend their services to friends and family (Dike & Chukwuanu, 2021). Al-Hawary and Al-Fassed (2022) assert that devoted customers always favour a brand, which typically results in the brand’s products or services being purchased indefinitely. There is also evidence to suggest that even modest increases in customer retention rates can have a significant and impact increases the profits of an organization.

Major challenges faced by Nigerian airline operators include: a lack of a coherent air transport policy; poor management; deteriorating facilities; a poorly secure lighting system that can easily facilitate poor service delivery; an ongoing increase in fares due to the high cost of jet A fuel; delayed or cancelled flights without prior notice; operational inefficiencies; a lack of empathy and unprofessional cabin crew service; a shortage of foreign exchange; and trapped funds. These factors ultimately affected the airline’s ability to survive, making it necessary for the management to implement a proper corporate sustainability model as well as an effective CRM in order to continue operating the business (Aiyegbajeje, 2023). However, a lack of comfort and security as well as dissatisfaction brought on by organisational issues results in non-attractions of customers in choosing a particular brand (Martini, Suardana & Dewi, 2023).

And because they are unable to rethink their approaches, transport companies, Nigerian airlines, are unable to satisfy the high standards of their clientele for quality products at competitive prices, as well as their desire for a wide range of services. Disgruntled customers and a negative reputation for the airline companies could result from these issues and inadequate customer service management (Dike & Chukwuanu, 2021).  This implies a decline in customer satisfaction. Consequently, the high expectations for service attributes among airport users are not being met, leading to low satisfaction levels. Given the number of airlines that operate out of Lagos State’s two main airports, brand preference and customer loyalty will continue to be crucial to the airlines’ ability to grow and remain profitable. This is because that is what ensure customer retention and repeat purchase (Chike & Stephens, 2021).

Numerous scholars have examined the obstacles to the airline industry’s viability in Nigeria as well as the functions of CRM; the majority of these studies, however, concentrate on the inefficiency of the government when it comes to policies and infrastructure. Without much fanfare, the necessity of fortifying a successful CRM that can improve net promoter score and customer retention rate—both of which can impact their customers’ brand awareness and brand association—has been highlighted, indicating the need to close a research gap. Investigating the impact of an efficient CRM (customer retention rate and net promoter score) on air passenger brand preference, as well as its intended effect on customers’ brand awareness and brand association, would close this knowledge gap. Researchers, academicians, practitioners, the aviation industry, policy-makers, and entrepreneurs would all benefit from the findings since it will broaden the boundaries of knowledge.

Objectives of the Study

The main objective of this study was to investigate customer relationship management impact on air passenger brand preference in the Nigeria Airline industry. The specific objectives are to;

1. examine the relationship between customer retention rate and air passengers brand preference.
2. investigate how net promoter score influences air passengers brand preference.

Research Questions

The study provided answers for the following research questions;

1. What is the relationship between customer retention rate and air passengers brand preference?
2. How does net promoter score influences air passengers brand performance?

Research Hypotheses are stated in null.

1. There is no significant relationship between customer retention rate and air passengers brand preference.
2. There is no significant influence of net promoter score on air passengers brand preference

LITERATURE REVIEW

Conceptual Review

Customer Relationship Management (CRM)

Relationship marketing (RM) is the foundation of the customer relationship management (CRM) concept, which is becoming more and more prevalent in contemporary marketing (Rahimi & Kozak, 2021). It is an all-encompassing approach necessary to discover all that can be discovered regarding the behaviour of the client or customers. It is actually a business-customer relationship that includes every aspect of an organization’s interaction with its clients, including sales and service-related interactions. This is a real-world application of the long-term relationships that resulted from relationship management (Mulyana, 2020). CRM is a business strategy that includes a collection of procedures, tools, and technologies for managing and evaluating contacts with clients and potential clients at every stage of the relationship (Ngelyaratan, & Soediantono, 2022)..

An efficient CRM prioritises building strong, mutually beneficial relationships with both current and potential clients in order to retain the former based on lessons learned from the past; additionally, it seeks to attract new clients, forge new connections, boost revenue, foster client preference and loyalty, and, in the end, lower customer care expenses (Okeke, Mabzor & Nwaizugbo, 2023). CRM is a comprehensive approach to attracting, retaining, and collaborating with specific clients to generate increased value for both the company and the client on a win-win basis. It is focused on obtaining pertinent information about clients before making decisions and emphasises strengthening, preserving, and cultivating long-term relationships with clients or customers (Timoshenko & Hauser, 2021).

Authorities from a variety of fields have demonstrated that in order for an organisation to truly succeed over the long term, it must implement an efficient CRM as a strategic tool for managing customer interactions. This can be done by streamlining corporate operations, improving customer service, enhancing marketing efforts, and enhancing sales activities, all with the ultimate goal of identifying, luring, nurturing, and attracting new and existing customers for repeat business in order to achieve sustainable performance with fruitful customer interactions (Adiyanto, 2021; Del Vecchio et al., 2022; Ledro et al., 2022; Zareie & Navimipour, 2021).

The modern airline industry is competitive, making it harder to satisfy customers and maintain brand preference. As a result, it is essential to use CRM effectively to meet customer expectations and achieve organisational objectives (Abdi et al, 2022). This can be achieved by implementing various CRM components, such as quick complaint resolution, customer knowledge, customer empowerment, and customer orientation—the four CRM elements that the company should focus on developing, according to Adiyanto (2021). Enhancing customer relationships, raising customer satisfaction, boosting customer retention and loyalty, and raising net promoter score are the main objectives of businesses implementing CRM. These actions eventually improve brand awareness and brand association, which raises revenue and profitability (Saha, Tripathy, Nayak, Bhoi & Barsocchi, 2021).

CRM is fundamentally about knowing customers—their requirements, inclinations, and actions. This entails gathering and examining client information from a variety of sources, including social media, sales, marketing, and customer support (Prior, 2023). Organisations can personalise their interactions with customers, anticipate their needs, and deliver tailored marketing messages and offers by acquiring insights into customer needs, desires, and behaviour (Del Vecchio et al., 2022). Organisations can attain various advantages and benefits by putting CRM strategies and technologies into practice, such as enhanced net promoter score, better customer satisfaction and loyalty, higher customer retention, lower expenses, and higher revenue and profitability (Nojeem et al., 2023).

For example, airline companies will eventually boost sales and revenue while decreasing marketing efforts and costs if they identify and target high-value customers with highly personalised marketing messages and offers. Similar to this, it has been demonstrated that businesses can improve brand preference, customer satisfaction, and loyalty through better customer service and responsiveness, which increases customer retention and repeat business (Fraihat et al., 2022).

Additionally, since everything in the twenty-first century is online and technology is driving society’s advancements, the internet has a significant impact on society and has accelerated the revolution. Today, technology is seen as a necessary and helpful aspect of human existence (Zareie & Navimipour, 2021). Aiming to improve their performance in delivering values to increase brand awareness and brand association, these have significantly improved CRM tools and performance through the use of contemporary technologies like email marketing platforms, social media monitoring tools, and customer service chatbots. They have also used CRM software to track and analyse customer data, automate sales and marketing processes, and manage customer service interactions more effectively and efficiently (Arobo, 2022).

Even though there are many performance indicators that can be used to measure how successful CRM is in attaining success, such as customer lifetime value (CLV), customer acquisition cost (CAC), churn rate or customer turnover rate, Net promoter score card (NPS), customer retention rate (CRR), and conversion rate, this study only looked at customer retention rate and net promoter score as a true measure of how effective CRM is in raising passenger brand awareness and brand association among.

The AIContentfy team (2023) highlights the close connection and strong relationship between brand awareness and customer loyalty. i.e., a strong, well-known brand that has gained a lot of recognition from customers will instill confidence and trust in them, increasing their loyalty over time. Because it costs significantly more to acquire new customers than it does to retain current ones, customer retention is essential. Additionally, loyal customers are more likely to spread the word about the business or act as brand ambassadors. According to Octavia and Riza (2023), brand awareness refers to a customer’s capacity to identify or recall a brand associated with a particular product category.

The number of customers who can identify or recall a brand within a category is the goal of brand awareness measurement. Potential customers find it easier to choose a brand to buy from when their recognition of the brand is higher (Sitorus et al., 2020). The degree to which customers are aware of a brand, its goods, or services is known as brand awareness. It speaks about the awareness of a brand and all of its characteristics, including name, logo, slogan, and general identity. To put it another way, developing a relationship with customers starts with raising brand awareness. According to Rowe (2021), the foundation lays the groundwork for fostering customer loyalty, trust, engagement, and retention. A customer’s brand awareness increases expectation that customers consider its products or services in the later. This is the reason why a company’s ability to build a strong brand is crucial to its success. Businesses that put money into developing their brands are better able to draw in new clients and hold onto their current clientele, which eventually boosts growth and profitability (Ahmad & Guerrero, 2020).

Akani, Ehio, and Onyegbule (2023) contend that brand awareness is crucial to customer retention because it fosters enduring relationships between customers and businesses. Customers are more likely to come back for repeat business when they are familiar with a brand and have a favourable opinion of it. This is due to the fact that customers are more inclined to believe in and stick with brands they are familiar with and have had good luck with in the past (Rane et al., 2023). Additionally, it can foster a feeling of belonging and a common identity between clients and a business. Customers are more likely to stick with a brand and keep doing business with it when they connect with it. Gaining a personal connection with a brand can lead to higher customer retention rates, as customers are more inclined to stick with it (Jamil et al., 2022). Furthermore, the quality of the goods and services provided can have an impact on brand awareness and customer retention (Eslami, 2020).

Customers are more likely to stick with brands that continuously provide superior goods and services. Companies can help to ensure that customers have positive experiences with their products and services by investing in brand building and upholding a strong brand image. This can increase customer retention (Yang, Hayat, Al Mamun, Makhbul, & Zainol, 2022).

Customer satisfaction plays a major role in keeping customers because customer retention depends on several processes of continuous satisfaction improvement (Octavia & Riza, 2023). Customer retention refers to a customer’s propensity to stick with a brand and express preference for its offerings over those of competitors. Consequently, the company’s ability to retain customers depends on the quality of its offerings (Olson, 2023). To achieve successful customer retention, a business must build and maintain a good relationship with its customers. Long-term clients frequently upgrade their business with a company and make larger purchases (Alayli, 2023). According to Fook and Dastane (2021), retaining present clients is more profitable than pursuing new ones, and contented clients are less likely to switch to rival businesses.

Net promoter score

Fred Reichheld first proposed the idea of the Net Promoter Score (NPS) in 1993 as a way to forecast customer referral and purchase patterns (Rowe, 2021). Many sizable international companies across various industries have embraced it as it has grown in popularity. Reichheld, Darnell, and Burns (2021) claim that the companies with the highest NPS doubled their stock market returns. This metric for market research is based on a single survey question that asks participants to rate how likely it is that they would suggest a business, brand, product, or service to a friend or colleague (Kuhn, 2023).NPS is a customer loyalty metric that assesses a customer’s propensity to recommend a product or service in addition to returning for a subsequent purchase to their family, friends or colleagues for patronage (Roberts, 2022)

In certain industries, the success of Net Promoter Score (NPS) is expected and justified due to its ability to provide a low-cost, easily measurable method of measuring customer satisfaction and loyalty. This makes it simple to track down, keep an eye on, and utilise as a tool to enforce accountability and control management (Baquero, 2022). The airline industry is a highly competitive sector that is involved in the process of globalisation (Park, Lee & Nicolau, 2020). There is now much more demand and expectation for high-quality services. The sector’s current focus on customer service, Purchase intent is included as a metric for the purchase phase of the customer journey, whereas consideration represents the pre-purchase phase (Kuz  & Miškinis, 2021). According to Baehre, O’Dwyer, O’Malley, and Lee (2022), NPS is a measure of the last post-purchase phase in and of itself.

Customer relations, resolving customer issues, promotions, and facility access goes beyond the facilities themselves with both brand recognition and brand (Chung & Tan, 2022; Halpern & Mwesiumo, 2021).

Brand Preference

One component of brand preference is a customer’s preference for a specific brand over others. One element that may affect a purchase is brand preference. In order to prevail in the business market, an organisation typically offers better goods and services. It matters how much customers like a company’s service in comparison to those of other companies. A customer’s decision to select the first does not alter regardless of whether the services are the same or different (Wiyogo & Setiawan, 2022). Gomes (2022) defines brand preference as a customer’s prejudice towards a specific brand. It is the degree to which a client prefers one business over another and chooses its goods or services.

Customers’ inclination to purchase is frequently found to be directly influenced by their brand preference. Customer attitudes towards a brand are reflected in brand preference, which is a behavioural tendency that implies the brand’s intentions and decisions are influenced by these attitudes. Brand preference is frequently identified as a factor that influences customers’ purchase intentions directly. According to Mahgfiroh and Indriastuti (2021) brand preference is a behavioural tendency that represents customer attitudes towards a brand, i.e., how these attitudes influence the brand’s intentions and decisions.

A brand’s preference is a person’s subjective choice or method of use. When choosing a brand to purchase, customers must take preference into account (Valérie, Homburg & Mignola, 2022). Brand memory and brand attitude work together to create brand preference. Customer preferences are largely determined by their experiences as customers. Customers purchase a brand based on how they define and express themselves in relation to their preferred brand, evaluating their self-images in accordance with their customer-brand relationships (Erciş, Deveci & Deveci, 2021). Customers compare one product to another to determine their preferred brand. Brand preference refers to a customer’s propensity for a specific brand. A customer will fall in love with a brand and select the product if it can live up to their expectations (Abidin & Subroto, 2023).

It is the degree to which customers prefer one brand over another; it is the selective demand for a company’s brand rather than a product (Brito, 2023). Advertising that aims to create brand preference must convince the target audience of a brand’s benefits; this is frequently accomplished by enhancing the brand’s standing as a reputable, long-standing name in the market. The target customer will select the specific brand over competing brands in any category if the advertising is successful (Rout & Mishra, 2023). This is dependent on the following factors: self-congruity, appearance, price perception, brand knowledge, and attribute perception (Jacob & Berlianto, 2022; Rai & Bhattarai, 2024).

Theoretical Framework

These are the theories that underpin the study, they include: Expectation Disconfirmation theory and Emotional Attachment theory.

Expectation Disconfirmation Theory

Oliver’s work in 1977/1980 conceptualized Expectancy-Disconfirmation Theory (EDT) (Ma, Tariq, Ali, Nawaz, & Wang, 2022; Penning de Vries & Knies, 2023; Rathjens et al, 2023; Wang & Fan, 2022; Chen et al, 2022; Kokthi, Thoma, Saary & Kelemen-Erdos, 2022).. However, Penning de Vries and Knies (2023) verified that EDT has been utilised to explain people’s contentment with jobs by Smith et al. (1969), products by Oliver (1980), and performance by Ilgen (1971). When it comes to explaining why customers are satisfied with the performance of products and services, the EDT has taken centre stage. It makes the assumption that customers evaluate a service’s performance in relation to their expectations. When the perceived performance meets or surpasses expectations, satisfaction arises (Oliver, 1980). The theory’s central idea, satisfaction is a function of perceived performance and expectations (Zhao, Yao, Liu, & Yang, 2021).

The purpose of EDT is to highlight an individual’s internal factors that determine their level of satisfaction. The primary concept of the model, which was first created in customer behaviour research, is that perceived performance and a referent both influence how satisfied or unsatisfied a person is (Zhang, Chen, Petrovsky & Walker, 2022). Customer satisfaction and expectations about the quality of the product are related. A buyer forms an expectation prior to actually inspecting a product. The foundation of EDT is this comparison of predetermined expectations with actual performance (Awadhi, Obeidat & Alshurideh, 2021; Zhao et al., 2021). When goods and services perform better than expected, customers are typically satisfied, leading to positive disconfirmation. On the other hand, consumers are typically not happy if the goods and services they receive are not as much of their beliefs, which cause negative disconfirmation (Duffett & Cromhout, 2022).

Customer satisfaction is a key factor in this study’s analysis of consumer purchasing behaviour. Customers’ repurchase intentions are typically diminished and switching behaviour results from negative disconfirmation (Zhao et al., 2022). In service environments, customers’ purchase intentions are largely formed by their perceptions of service quality and customer satisfaction. The primary factor that determines customer retention is whether or not the relationship (CRM) between the services that are offered to the customer and their quality and level of satisfaction is satisfactory (Adebayo & Joshua, 2021). A measure of a customer’s enthusiasm, satisfaction, and loyalty to a business is called the net promoter score (Agag et al., 2024).  Positive disconfirmation leads to customer loyalty (Chen et al., 2022).

Emotional Attachment Theory

John Bowlby’s 1958 work served as the basis for the development of Emotional Attachment Theory (EAT) (Beckes & Simpson, 2023). Mary Ainsworth built significantly on Bowlby’s initial research. Her ground-breaking “strange situation” study demonstrated the significant behavioural effects of attachment (Cherry, 2023). According to the theory, attachments are emotional connections that people have with particular subjects; the attached subject determines how strong these connections are. A child’s attachment to her mother is the source of this natural behaviour known as attachment production. Adults can also exhibit this behaviour in romantic relationships, kinship bonds, and friendships that support enduring relationships (Hsu, Chen & Liao, 2021). The theory’s central premise is the emotional bond and relationship (Shimuli, 2022).

EAT focuses on the main connection between later personality development and maternal loss or deprivation. It is regarded as one of developmental psychology’s most important theories. The theory was expanded to include adulthood and business settings (Frydman & Tena, 2023).  The marketing literature considers emotional brand attachment to be a crucial construct. It expresses how strongly a customer feels about a brand. An essential factor in determining consumer behaviours like recurrent brand purchases and the willingness to expend resources to acquire a brand is the emotional attachment to a particular brand preference, which ultimately results in brand loyalty. Over the years, researchers studying consumer behaviour have discovered evidence that shows consumers can form emotional attachments to a variety of marketable entities, such as products or service (Rahehagh & Ghorbanzadeh, 2021). Consumer preferences and loyalty are frequently influenced by the degree of emotional attachment they have to a brand (Schreuder, Zeelenberg & Pronk, 2024).

The theory is applied in this study to explain how brand awareness and brand association help consumers foster long-term relationships with brands. The degree to which consumers can identify and recall a company’s name and products is known as brand awareness. It can be much simpler for a brand to draw in and keep consumers when they are more likely to remember and select it when they need to make a purchase. Nonetheless, brand awareness in consumers’ cognitive processes influences their decisions to buy and how they use products (Zhang, 2020).  Customers who have a strong emotional attachment to a brand are less likely to switch to a competing one (Boateng, Kosiba, Adam, Ofori, & Okoe, 2020).  Nonetheless, brand association aids customers in distinguishing a brand from rivals and assist in making decisions (Karagiorgos, Alexandris, Lianopoulos, & Kouthouris, 2023). Customers derive value from brand associations, which also influence their behaviour (Butt & Muhammad, 2023).

Empirical Review    

Peter and Peter (2024) used a quantitative approach that included surveys for data collection to investigate the relationship between CRM strategies and customer satisfaction. Four hundred customers were given questionnaires, and the stated hypotheses were investigated using regression analysis. Customer satisfaction is positively impacted by customer relationship management, according to the study.

Rai and Bhattarai (2024) investigated the variables influencing brand preference when purchasing a passenger car in Nepal. Utilised were a quantitative approach, positivist epistemology with predetermined hypotheses, and a deductive reasoning approach. The primary data was collected using a structured survey with a six-point Likert scale. 411 passengers who drive in Nepal were included in the sample. Both a causal research design and a judgmental sampling technique were applied. Structural equation modelling was used to determine the impact of price, attributes, brand personality, appearance, and self-congruity on dependent variables through path analysis. According to the study, there is no discernible positive relationship between attribute, price, and appearance and consumer brand preference. Additionally, the study found that when purchasing passenger cars in Nepal, self-congruity and brand personality have an impact on brand preference.

Agag et al. (2024) investigated the relationship between a customer’s promoter score and their electronic word-of-mouth (e-WOM) behaviour in various cultural contexts.  The experimental design was used in two investigations. In the first study, a unique dataset of 4,864 hotel guests was used to compare the e-WOM behaviour that the guests actually engaged in on different online platforms with the intentions indicated by their individual promoter scores. The purpose of the second study was to verify the findings of the first and investigate the impact of national culture on the associations between individual promoter scores and the real e-WOM behaviour. Data were gathered from four different countries: the US, UK, China, and Egypt. According to study one’s ordered logit analysis results, promoter scores have a significant positive impact on the valence of online messages. The findings of study two were corroborated, and it also showed that as collectivism, power distance, uncertainty avoidance, and masculinity increase, so does the influence of net promoter score on both positive and negative word-of-mouth communication.

Okeke et al. (2023) assessed customer retention and CRM. A survey with a cross-sectional design was conducted among employees of broadcast companies located in southeast Nigeria. A structured questionnaire was distributed to the respondents, and a sample of 550 respondents was selected. A total of 402 respondents, or roughly 73.1% of the sample, returned valid and useful responses. 2. Using a structural equation model, it was discovered that customer orientation, customer information processing, ease of use, and customer retention are directly and statistically significantly positively correlated. Customer and customer data are related. Additionally, the analysis demonstrated a strong indirect relationship between CRM and customer retention.

The study conducted by Alanazi (2023) examined the effects of social customer relationship management on the customer loyalty of Saudi Arabia’s five-star hotels. CRM encompassed elements such as customer value, enduring partnership, customer knowledge, technological dependence, trust, and social media interaction. Customers of Saudi Arabia’s five-star hotels make up the study population. Out of 500 customers, a convenience sample was obtained; 413 responses were validly retrieved. Structural equation modelling (SEM) was used in a quantitative manner to investigate the relationship between social customer relationship management dimensions and customer loyalty in Saudi Arabia’s five-star hotels.

In the Covid-19 era, Al Kharraz and Seçim (2023) investigated the effect of customer relationship management on customers’ trust in Paltel, a Palestinian telecommunications company. In order to learn more about the brand preferences of Bhubaneswar residents in this product category, a cross-section of forty (40) respondents were asked to complete a prepared questionnaire and provide a sample of 14 products. The preferred brand with the highest level of brand loyalty is indicated by the survey study. Respondents’ tastes, preferences, and loyalty vary depending on the product category.

The use of Net Promoter Score (NPS) to forecast sales growth in the US sportswear industry over a five-year period was investigated by Baehre, O’Dwyer, O’Malley, and Lee (2022). In order to gather panel data for the study, an online survey was used. A total of 38,644 respondents provided NPS data, yielding 193,220 evaluations of the seven brands. There is a relationship between NPS and potential future sales growth, according to the correlation analysis.

Yang et al.  (2022) study looked at how social media marketing affected Chinese consumers’ intentions to repurchase high-tech products and brand equity, which includes brand awareness and brand image. An online survey was used to gather 477 valid responses for the cross-sectional study design. The outcome of artificial neural networks and partial least squares structural equation modelling (PLS-SEM) and the use of artificial neural networks (ANNs) to analyse data showed that trendiness, interaction, and word-of-mouth had favourable and significant effects on brand awareness. Positive effects on brand image have been found to be attributed to customisation, trendiness, interaction, and word of mouth. Repurchase intention has been found to be influenced by brand image and brand awareness.

Net promoter score (NPS) and customer satisfaction: relationship and effective management were investigated by Baquero (2022). Fuzzy set qualitative comparative analysis (fsQCA) was used in this investigation.  a selection of six hotels (4 and 5*) in Spain’s Balearic Islands. Since 557 surveys were finished in August 2021 and 571 surveys in August 2020, the COVID-19 pandemic, a Black Swan (BS) event, affected both sample groups at two distinct points in its trajectory. According to the fuzzy model results, in the study sample, (1) gastronomy in 2021 (more than a year after the COVID-19 pandemic) and (2) cleanliness and comfort of the room in 2020 (at the start of the pandemic) were the most important factors in achieving a high NPS.

RESEARCH METHODS

The research designed used for this study was survey design. The population of this study according to Eze (2023) reporting National Civil Aviation Authority (NCAA) in 2023 was 16,172,433 passengers. The sample size was 376 respondents using judgmental sampling technique. Taro Yamane formula was used which gave 399.99 approximated to 400 sample size. Hence 400 questionnaires were distributed but 376 were correctly filled in and found usable for this study. This represents 94% returns which were considered satisfactory. Primary data with reference to a well-structured and adapted questionnaire was used which contained questions/statements about the variables under consideration. The research tools used descriptively were mean and standard deviation and inferentially, analysis of variance (ANOVA) and ordinary least square (OLS) were used. Levene’s test of homogeneity was adopted with Durbin-Watson. Also Cronbach Alpha tests were carried out.

Data Analysis and Presentation

This section contains the descriptive results of data. Tables 4.1 – 4.4 describe the bio data, dimensions of  independent and dependent variables.

Table 4.1: Bio data of the respondents – Descriptive Statistics

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

From table 4.1 above, the means of gender, age bracket, highest qualifications, years of travelling by air, frequency of travelling per annum, types of flight, types of travels and most purpose of travelling are 1.2475, 3.8500, 3.4075, 2.0900, 1.3000, 1.2575, 1.6700 and 1.5450 respectively while the standard deviations for the same bio data are 0.43210, 0.98485, 0.80190, 1.35147, 0.49051 0.54492, 0.54483 and 0.70300

Data Presentation based on Dimensions of Independent and Dependent Variables

The dimensions of independent variables for the study are customer retention rate and net promoter score while the dimension of dependent variable is brand preference.

Table 4.1.2: Descriptive Statistics of Customer Retention Rate

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

From table 4.1.2, the means of customer retention rate from CRR_1 to CRR_7 are 4.1125, 4.1375, 3.6700, 3.8300, 4.0425, 3.7325 and 3.6725 respectively while the standard deviations for the same CRR are 0.84060, 0.55168, 1.05778, 0.77304, 0.85588, 0.91270 and 1.06681. the highest mean is CRR_2 and the lowest mean is CRR_3 while the highest standard deviation is CRR_3 and the lowest is CRR_2.

Where CRR_1 is “My brand airline improves on the attributes that customers most valued.” CRR_2 is “My brand airline leaves on a good note on their service delivery.” CRR_3 is “My preferred airline always stays in touch with their customers from time to time.” CRR_4 is “My preferred airline always ask for another chance to render service.” CRR_5 is “My chosen airline provides a perfect customer service at all time.” CRR_6 is “My preferred airline understands motivations for defection to another airline.” and CRR_7 is “My brand airline evaluates customer value from time to time.”

Table 4.1.3: Descriptive Statistics of Net Promoter Score

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

From table 4.1.3, the means of net promoter score from NPS_1 to NPS_7 are 4.0975, 4.1925, 4.0250, 4.0775, 3.7900, 4.1300, and 3.9850 respectively while the standard deviations for the same NPS are 0.67389, 0.75290, 0.55691, 0.54977, 0.80469, 0.70665 and 0.69353. The highest mean is NPS_2 and the lowest mean is NPS_5 while the highest standard deviation is NPS_5 and the lowest is NPS_4.

Where NPS_1 is “Based on your experience of using a brand of airline for some times now, how would you agree to recommend it to a friend or colleague.” NPS_2 is “How would you agree to recommend your airline brand features to a friend or colleague or family?” NPS_3 is “My airline brand customer support service has been recommended to a friend or colleague or family.” NPS_4 is “My airline brand customer support staff has been recommended to a friend or colleague or family.” NPS_5 is “Base on your recent interaction with your preferred airline support staffs, how would you agree to recommend them?” NPS_6 is “Base on your recent patronage of an airline brand, how would you agree to recommend them?” and NPS_7 is “Base on your last  relationship with your preferred airline, how would you agree to recommend them?”

Table 4.1.4: Descriptive Statistics of Brand Preference

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

From table 4.1.4 above, the means of brand preference from BRP_1 to BRP_8 are 3.8875, 4.2550, 4.2100, 3.7450, 3.7750, 3.6325, 3.0825 and 3.5850, respectively while the standard deviations for the same BRP are 1.08063, 0.62124, 0.80469, 0.99873, 0.77192, 1.07019, 1.05521 and 0.87733. The highest mean is BRP_2 and the lowest mean is BRP_7 while the highest standard deviation is BRP_1 and the lowest is BRP_2.

Where BRP_1 is “Preference for my choice airline is an outcome of the brand awareness in the industry.” BRP_2 is “My preference for the airline brand was promoted by others positively promote the brand by word of mouth and social channel.” BRP_3 is “Brand preference have resulted in my brand loyalty to the choice airline.” BRP_4 is “The benefits accrued from the airline brand enhances my brand preference.” BRP_5 is “Emotional and rational attached promote my preference for my airline choice.” BRP_6 is “Logo, design, color and astesthics  of the airline enhance my preference for the airline.” BRP_7 is “My perception of the brand based on my interaction with previous customers enhance my preference for the airline.” BRP_8 is “Been able to correctly identify by viewing the product logo, tagline, advertising campaign resulted in my preference of the airline.”

Pre-Estimation Test-Homogeneity of Variance

The study conducted Levene’s test of homogeneity of variance to know whether or not Analysis of Variance would be a suitable tool in estimating the specified model. The results of the test are provided in tables 4.1 to 4.10.

Customer Retention Rate Dimension

Table 4.2 results demonstrate that the p-value of 0.203 is larger than the criterion of significance of 0.05. These findings require acceptance of the null hypothesis of variance homogeneity and rejection of the alternative hypothesis of variance heterogeneity. As a result, these findings confirm the acceptability of doing Analysis of Variance with Customer Retention Rate as one of the independent variables.

Table 4.2: Results of Test of Homogeneity of Variance on Customer Retention Rate Dimension

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

***p-value< 0.01; **p-value< 0.05

Net Promoter Score Dimension

Table 4.3 results demonstrate that the p-value of 0.310 is larger than the criterion of significance of 0.05. These findings require acceptance of the null hypothesis of variance homogeneity and rejection of the alternative hypothesis of variance heterogeneity. As a result, these findings confirm the acceptability of doing Analysis of Variance with Net Promoter Score as one of the independent variables.

Table 4.3: Results of Test of Homogeneity of Variance on Net Promoter Score Dimension

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

***p-value< 0.01; **p-value< 0.05

Brand Preference Dimension

Table 4.4 results demonstrate that the p-value of 0.471 is larger than the criterion of significance of 0.05. These findings require acceptance of the null hypothesis of variance homogeneity and rejection of the alternative hypothesis of variance heterogeneity. As a result, these findings confirm the acceptability of doing Analysis of Variance with Brand Preference as one of the dependent variable.

Table 4.4: Results of Test of Homogeneity of Variance on Brand Preference Dimension

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

***p-value< 0.01; **p-value< 0.05

Test of Reliability

Cronbach’s Alpha was used to assess the reliability of the study measures, particularly the internal consistency of the rating system utilized and, by consequently, its appropriateness. The test results are provided in table 4.6 below:

Table 4.6: Reliability Coefficient for all Research Statements

(Source: Field Survey,2024 & Computations Aided by SPSS Version 25.0)

According to the data in table 4.6, the scale utilized in the study is internally consistent, since it exhibits a coefficient greater than 0.70, a criterion set by Nunnally (1978), as referenced in Miidom, Nwuche, and Anyanwu (2016). This implies that the research measures are considerably reliable.

Test of Hypotheses

Two research hypotheses were formulated and tested. The results are presented in tables 4.7 to 4.9

H0₁: There is no significant relationship between customer retention rate and air passengers brand preference.

Results in table 4.7 revealed that the partial elasticity coefficient of customer retention rate with respect to customer relationship management is 0.553, indicating that customer retention rate has a positive effect on air passengrs brand preference in Nigeria. This coefficient is also statistically significant (t=11.638, p-value<0.05) to individually influence air passengers brand preference in Nigeria. With these results, the null hypothesis is rejected, while the alternative hypothesis is accepted. The inference there from is that there is a significant relationship between customer retention rate and air passengers brand preference in Nigeria.

Table 4.8: Result on Regression Model Summary^b

As noted in table 4.8, the R Square of 64.40% suggests a very strong model. The 64.40% R Square revealed that the total variation in the customer retention rate is attributed to brand preference, while 35.60% of the total variation in the customer relationship management is accounted for by other factors not captured in the model. The Durbin Watson statistic of 1.909 in table 4.8 indicates no serious presence of serial correlation as coefficient is approximately equal to 2.

Table: 4.9: Result on ANOVA^a

The overall fitness of the model is established based on the results in table 4.9, from which it can be inferred that the one of the dimensions of customer relationship management with respect to customer retention rate has joint significant influence on the brand preference in Nigeria (F= 101.376, p-value =0.000).

H0₂: Net promoter score will not significantly influence air passengers brand preference.

Results in table 4.7 revealed that the partial elasticity coefficient of net promoter score with respect to customer relationship management is 0.471, indicating that net promoter score has a positive effect on air passengers brand preference in Nigeria. This coefficient is also statistically significant (t=6.369, p-value<0.05) to individually influence air passengers brand preference in Nigeria. With these results, the null hypothesis is rejected, while the alternative hypothesis is accepted. The inference there from is that net promoter score significantly influences air passengers brand preference in Nigeria..

As noted in table 4.8, the R Square of 26.10% suggests a very strong model. The 26.10% R Square revealed that the total variation in the net promoter score is attributed to brand preference, while 73.90% of the total variation in the customer relationship management is accounted for by other factors not captured in the model. The Durbin Watson statistic of 2.827 in table 4.8 indicates no serious presence of serial correlation as coefficient is approximately equal to 2.

The overall fitness of the model is established based on the results in table 4.9, from which it can be inferred that the one of the dimensions of customer relationship management with respect to net promoter score has joint significant influence on the brand preference in Nigeria (F= 19.780, p-value =0.000).

Post Estimation Tests

Normality of Residuals

As shown in table 4.10, the mean residual of is 0.0000, indicating that the residuals from the estimated ordinary least square regression are normally distributed and the variance of the residuals is the same for all values of the independent variables.

Table 4.10: Results of Residual Statistics

Charts

Charts

Multi-Collinearity

The results in table 4.11 provided evidence that all the three proxies of supply chain management have no strong inter-correlations and inter-associations with one another based on the collinearity statistics of Variation Inflation Factor (VIF) which for all the independent variables are between 1 and 10, suggesting no problem of multicollinearity.

Table 4.11: Results of Collinearity Diagnostics

(Source: Field Survey, 2024 & Computations Aided by SPSS Version 25.0)

DISCUSSION OF FINDINGS

According to research from the preceding section, airline passengers in Nigeria recognized customer retention rate as a part of customer relationship management, likewise net promoter score was also acknowledged as customer relationship management sub-variable. Additional result showed that the brand preference was extremely reliable and that it more closely mirrored underlying transactions and events of the respondents’ responses. Hence it was found out that Peter and Peter (2024) found out that customer satisfaction is positively impacted by customer relationship management, according to the study. In the Covid-19 era, Al Kharraz and Seçim (2023) finding revealed that the preferred brand with the highest level of brand loyalty is indicated by the survey study. Respondents’ tastes, preferences, and loyalty vary depending on the product category.

The result of the first hypothesis holds that customer retention rate significantly influences the brand preference of airline passengers in Nigeria, which is contrast with Okeke et al. (2023) discovered that the analysis demonstrated a strong indirect relationship between CRM and customer retention.

Also, the result from hypothesis two showed that net promoter score sways the brand preference of airline passengers in Nigeria, which is line with Agag et al. (2024) result which showed that promoter scores have a significant positive impact on the valence of online messages. Also it is the same Baehre, O’Dwyer, O’Malley, and Lee (2022) whose result showed that there is a significant relationship between NPS and potential future sales growth, according to the correlation analysis.

CONCLUSION AND RECOMMENDATIONS 

Conclusion    

The study’s primary goal was to determine the impact of customer relationship management variables influence brand preference of air passengers in Nigeria. Customer retention rate, however, was found to have a significant on brand preference of air passengers in Nigeria. Also, the brand preference of air passengers in Nigeria is strongly related with net promoter score. In general, brand preference of air passengers in Nigeria is significantly impacted by all two variances of CRM techniques. Therefore, it is safe to conclude that CRM techniques have a substantial impact on brand preference of air passengers in Nigeria.

Recommendations

The study recommends that policymakers, directors and management of airlines together with students and researchers, that customer relationship management has impact on brand preference of air passengers in Nigeria, hence this recommendation is based on the study’s findings. Additionally, it recommends that airline passengers should measure their performance by how well their customers relation and service to their customers. As a result, customer retention rate and services ought to be done time which will improve their brand preference. Additionally, the study suggests that net promoter score should be fully and flawlessly created in good shape as this would improve the as brand preference of airline passengers in Nigeria.

REFERENCES

1. Abdi, Y., Li, X., & Càmara-Turull, X. (2023). Firm value in the airline industry: perspectives on the impact of sustainability and Covid-19. Humanities and Social Sciences Communications, 10(1), 1-24.
2. Abidin, Z., & Subroto, A. (2023). The effect of perceived quality, perceived value, brand preference, and customer satisfaction on ERP implementation in construction services. Quantitative Economics and Management Studies, 4(5), 892-903.
3. Adebayo, O. S. & Joshua, M. O. (2021). The impact of service providers on ensuring service quality and customer satisfaction. European Journal of Educational and Social Sciences, 6(1), 76–85.
4. Adeniran, A. O., Njoku, I., & Stephens, M. S. (2023). Factors influencing willingness-to-repurchase airline services in Nigeria. In Innovation, Social Responsibility and Sustainability, 25-64.
5. Agag, G., Durrani, B. A., Abdelmoety, Z. H., Daher, M. M., & Eid, R. (2024). Understanding the link between net promoter score and e-WOM behaviour on social media: The role of national culture. Journal of Business Research, 170, 1-16.
6. Ahmad, G., & Dubey, S. K. (2024). Sustainable luxury fashion in India: A Case of Grassroot by Anita Dongre. Emerging Economies Cases Journal, 1-
7. Ahmad, N., & Guerrero, E. (2020). Influence of social media on brand awareness: A study on small businesses (MBA Thesis, University of Gavle).
8. Aiyegbajeje, F. O. (2023). Assessing the determinants of choice of airline among domestic air travelers in Lagos, Nigeria. Ghana Journal of Geography, 15 (1), 130-155.
9. Akani, G. H., Ehio, V. N., & Onyegbule, C. C. (2023). Brand recognition and customer patronage of deposit money banks in Port Harcourt. Nigerian Journal of Management Sciences, 24(2a), 55-61.
10. Al Kharraz, F., & Seçim, H. (2023). Customer relationship management impact on customers’ trust in the Palestinian telecommunications company Paltel during the Covid-19 era. Electronic Commerce Research, 1-21
11. Alanazi, T. (2023). The effect of social customer relationship management on customer loyalty in Saudi Arabia. Uncertain Supply Chain Management, 11(2), 665-672.
12. Alayli, S. (2023).The impact of loyalty on customer retention: The case of Lebanon. International Journal of Research Publication and Reviews, 4(8), 1350-1359.
13. Awadhi, J., Obeidat, B., & Alshurideh, M. (2021). The impact of customer service digitalization on customer satisfaction: Evidence from telecommunication industry. International Journal of Data and Network Science, 5(4), 815-830.
14. Bhardwaj, S. K. Agarwal, S. & Chauhan, D. (2023). Study on relation between brand awareness and repeat purchases in hospitality sector. Journal of Emerging Technologies and Innovative Research, 10(2), 571-
15. Beckes, L. & Simpson, . J A. (2023, December 22). Attachment theory. Encyclopedia Britannica. https://www.britannica.com/science/attachment-theory
16. Baehre, S., O’Dwyer, M., O’Malley, L., & Lee, N. (2022). The use of Net Promoter Score (NPS) to predict sales growth: insights from an empirical investigation. Journal of the Academy of Marketing Science, 50(1), 67-84.
17. Baquero, A. (2022). Net promoter score (NPS) and customer satisfaction: relationship and efficient management. Sustainability, 14(4), 1 16.
18. Boateng, H., Kosiba, J. P., Adam, D. R., Ofori, K. S., & Okoe, A. F. (2020). Examining brand loyalty from an attachment theory perspective. Marketing Intelligence & Planning, 38(4), 479-494.
19. Brito, M. (2023, April 11). Brand preference: The secret to outshining your competitors. Retrieved on 2/1/2024 from https://www.britopian.com/content/building-brand-preference/
20. Butt, F. K., & Muhammad, L. (2023). Investigating the determinants of brand advocacy in the tourism sector, customer irrational beliefs as a moderator. Journal of Positive School Psychology, 7(5), 759-774.
21. Chen, W., Dong, B., Hsieh, C. W., Lee, M. J., Liu, N., Walker, R. M., … & Zhang, J. (2022). A replication of an experimental test of the expectancy‐disconfirmation theory of citizen satisfaction. Public Administration, 100(3), 778-791.
22. Cherry, K. (2023, February 22). What Is Attachment Theory? The importance of early emotional bonds. Retrieved on 2/1/2024 from https://www.verywellmind.com/what-is-attachment-theory-2795337
23. Chike, U. G., & Stephens, M. S. (2021). Customers’ satisfaction with the level of service in Murtala Muhammed International Airport (MMIA), Lagos, Nigeria. International Journal of Research in Industrial Engineering, 10(1), 35-45.
24. Clark, J. (2023, November, 27). Customer relationship management keys to success in 2024. Retrieved on 2/1/2024 from https://www.fleetowner.com/perspectives/ideaxchange/article/21277794/clark-customer-relationship-management-keys-to-success-in-2024
25. Dike, R. A., & Chukwuanu, C. S. (2021). Effect of customer relationship management on customers’ loyalty in shipping companies in Lagos State, Nigeria. American International Journal of Business Management (AIJBM), 04(05), 52-64.
26. Duffett, R., & Cromhout, D. (2022). The influence of a student-led advertising agency service-learning project on SMME client satisfaction: An Expectancy–Disconfirmation Paradigm. Education Sciences, 12(12), 1-1
27. Ekakitie-Emonena, S. (2021). C.R.M. and environmental factors as predictors of customer preference of electronic brands in the Niger Delta Region. Helsinki Journal of Research Management and Marketing, 21-38.
28. Erciş, A., Deveci, N. K., & Deveci, F. G. (2021). Brand experience, its antecedents and its effects on brand loyalty in online TV streaming platforms: The mediation effect of brand attitude and brand preference. Türkiye İletişim Araştırmaları Dergisi, (38), 342-363.
29. Eslami, S. (2020). The effect of brand experience on brand equity and brand loyalty through the mediating role of brand awareness, brand image and perceived quality. Archives of Pharmacy Practice, 11(S1), 98-104.
30. Fook, A. C. W., & Dastane, O. (2021). Effectiveness of loyalty programs in customer retention: a multiple mediation analysis. Jindal Journal of Business Research, 10(1), 7-32.
31. Fraihat, B. A. M., Abozraiq, A. M., Ababneh, A. M., Khraiwish, A., Almasarweh, M. S. & AlGhasawneh, S. S. (2023). The effect of customer relationship management (CRM) on business profitability in Jordanian logistics industries: The mediating role of customer satisfaction. Decision Science Letters, 12(4), 783-794.
32. Ghorbanzadeh, D., & Rahehagh, A. (2021). Emotional brand attachment and brand love: the emotional bridges in the process of transition from satisfaction to loyalty. Rajagiri Management Journal, 15(1), 16-38.
33. Gomes, M. F. (2022). Cause branding impact on brand preference and the preference repurchase intention model (MSc Thesis, Falcudade de Economia, Universidado do Porto).
34. Hsu, T. H., Chen, C. H., & Liao, W. C. (2021). A fuzzy MCDM analytic model for building customers’ brand attachment preference in car firms. International Journal of Fuzzy Systems, 23(7), 2270-2282.
35. Irshad, M. (2023). Examining the influence of brand nostalgia on brand loyalty through the mediation of brand attachment. International Journal of Business and Management Sciences, 04(03), 58–74.
36. Jamil, K., Dunnan, L., Gul, R. F., Shehzad, M. U., Gillani, S. H. M., & Awan, F. H. (2022). Role of social media marketing activities in influencing customer intentions: a perspective of a new emerging era. Frontiers in Psychology, 12, 1–
37. Karagiorgos, T., Lianopoulos, Y., Alexandris, K., & Kouthouris, C. (2023). The role of brand associations on the development of place attachment into outdoor adventure tourism destinations. Journal of Outdoor Recreation and Tourism, 42, 100617.
38. Kokthi, E., Thoma, L., Saary, R., & Kelemen-Erdos, A. (2022). Disconfirmation of Taste as a Measure of Trust in Brands: An Experimental Study on Mineral Water. Foods, 11, 1–
39. Kuhn, G. (2023, February 24). What is Net Promoter Score (NPS)? [+Benefits & Formula]. Retrieved on 3/2/2024 from https://www.driveresearch.com/market-research-company-blog/what-is-nps-in-market-research-net-promoter-score/
40. Kuz, A., & Miškinis, A. (2021). The impact of globalization on European airline market. Ekonomika, 100(1), 117-138.
41. Ma, W., Tariq, A., Ali, M. W., Nawaz, M. A., & Wang, X. (2022). An Empirical Investigation of Virtual Networking Sites Discontinuance Intention: Stimuli Organism Response-Based Implication of User Negative Disconfirmation. Frontiers in Psychology, 13, 1–13.
42. Mackintosh, A. C. & Didia, J. U. D. (2020). Brand Association and Customer Satisfaction of Fast Food Firms in Rivers State. International Academic Journal of Management and Marketing, 6(6), 1-10.
43. Mahgfiroh, R. K., & Indriastuti, H. (2021). The effect of brand preference and brand conviction on consumer loyalty of Excelso Café. International Journal of Economics, Business and Accounting Research (IJEBAR), 5(3), 1216-1224.
44. Marais, P. (2021, September 6). Organisations’ reason for existence: The contextual delivery imperative. Retrieved on 2/2/2024 from kontextit.com/post/organisations-reason-for-existence
45. Martini, L. K. B., Suardana, I. B. R., & Dewi, L. K. C. (2023). Trust Level, quality, and service brand preference its influence on interest in saving: A case study at a village credit Institution in Bali. Journal of Digitainability, Realism & Mastery (DREAM), 2(08), 13-23.
46. Nibsaiya, S. Sumithra, C. G., & Kumar, M. (2021). Impact of Brand Awareness and Brand Loyalty on Consumer Purchase decision: A study on FMCG products. IUJ Journal of Management, 9(1), 174–186.
47. Nwaogbe, O. R., Ogwude, I. C., Ejem E. A. & Pius, A. (2021). Service quality and passenger satisfaction in air transportation in a developing economy: Evidence from Nigeria. Journal of Aviation Technology and Engineering, 10(1), 30–44.
48. Octavia, B. & Riza, F. (2023). The effect of customer value and brand awareness on customer retention with customer satisfaction as a mediating variable. Journal Research of Social Science, Economics, and Management, 3(2), 443-461.
49. Okeke, T. C., Mabzor, S. C., & Nwaizugbo, I. C. (2023). Customer relationship management and customer retention in the Nigeria broadcast industry: The Mediating Influence of Customer Satisfaction. Nnadiebube Journal of Social Sciences, 4(4), 1-9.
50. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions, Journal of Marketing Research, 17(4), 460–469.
51. Olson, S. (2023, August 16). Customer retention: Metrics, strategies, and examples: Discover tried-and-true customer retention strategies to keep customers coming back. Retrieved on 2/1/2024 from https://www.zendesk.com/blog/customer-retention/
52. Park, S., Lee, J. S., & Nicolau, J. L. (2020). Understanding the dynamics of the quality of airline service attributes: Satisfiers and dissatisfiers. Tourism management, 81, 1–
53. Penning de Vries, J., & Knies, E. (2023). “I expected more from you”: The effect of Expectation-Disconfirmation on employees’ satisfaction with supervisory support. Review of Public Personnel Administration, 43(2), 309-335.
54. Peter, F. O., & Peter, A. O. (2024).  Information  Technology  as  a  tool  for  effective  customer  African Journal of Business and Economic Development, 4(1), 25-34.
55. Qureshi A., Padela, S. M. F., Qureshi, S. & Baqa, S. (2020). Exploring service brand associations: A consumers’ perspective in a rising service economy. Studies of Applied Economics, 39(2), 1-17.
56. Phonga, L. T., Ngaa, T. H., Hanha, N. T., & Minha, N. V. (2020). Relationship between brand association and customer loyalty: The case of online retail industry. Management Science Letters 10, 1543–1552
57. Prior, D.D. (2023). Customer Relationship Management. In: B2B Customer Engagement Strategy. Palgrave Macmillan, Cham.
58. Rai, B., & Bhattarai, G. (2024). Factors affecting brand preference in passenger car buying in Nepal. Innovative Marketing, 20(1), 77-87.
59. Rane, N. L., Achari, A., Choudhary, S. P. (2023). Enhancing customer loyalty through quality of service: Effective strategies to improve customer satisfaction, experience, relationship, and engagement.  International Research Journal of Modernization in Engineering Technology and Science, 05(05), 427 452.
60. Rathjens, B., Van Der Heide, B., Pham, D., Earle, K., Ulusoy, E., Mason, A. J., … & Bredland, A. (2023). Negative online reviews and manager response: applying expectancy disconfirmation theory in a CMC context. Communication Reports, 36(2), 110-122.
61. Roberts, B. (2022,, April 6). Our NPS and how customer experience is measured. Retrieved on 2/1/2024 from https://www.loanpro.io/blog/our-nps-and-how-customer-experience-is-measured/
62. Saha, L., Tripathy, H. K., Nayak, S. R., Bhoi, A. K., & Barsocchi, P. (2021). Amalgamation of customer relationship management and data analytics in different business sectors—A systematic literature review. Sustainability, 13(9), 1-35.
63. Schreuder, P., Zeelenberg, M., & Pronk, T. (2024). How consumers define brand relationships: A prototype analysis. Journal of Product and Brand Management, 33(1), 43-56.
64. Shimul, A. S., & Phau, I. (2023). The role of brand self-congruence, brand love and brand attachment on brand advocacy: a serial mediation model. Marketing Intelligence & Planning, 41(5), 649-666.
65. Supiyandi, A., Hastjarjo, S., & Slamet, Y. (2022). Influence of brand awareness, brand association, perceived quality, and brand loyalty of shopee on consumers’ purchasing decisions, CommIT Journal, 16(1), 9–18.
66. Sylva, W., & Amah, C. F. (2021). Challenges of airlines operations in Sub-Saharan Africa: An empirical investigation of the Nigerian civil aviation sector. International Journal of Business and Management Invention, 10(1), 13-30.
67. Taherdoost, H. (2023). Customer relationship management. In: E-Business essentials. EAI/Springer Innovations in Communication and Computing. Springer, Cham.
68. Valérie, C., Z., Homburg, C., P., & Mignola, P., D. (2022). Relationship between advertisement and consumer brand preference at LG Couture France. Journal of Marketing and Communication 5(2), 42-51.
69. Wang, P., & Fan, F. (2022). Examining and expanding the Expectancy Disconfirmation Model: Evidence from rural China. Discrete Dynamics in Nature and Society, 1-11.
70. Wiyogo, J. N. & Setiawan, R. (2022) The effects of customer satisfaction on brand preference through customer loyalty and brand trust on local cosmetic products in Indonesia. In: Seminar Akuntansi, Manajemen, dan Ekonomi (SAME,) 5, 05-10.
71. Yang, Q., Hayat, N., Al Mamun, A., Makhbul, Z. K. M., & Zainol, N. R. (2022). Sustainable customer retention through social media marketing activities using hybrid SEM-neural network approach. PloS one, 17(3), 1-
72. Zhang, J., Chen, W., Petrovsky, N., & Walker, R. M. (2022). The expectancy‐disconfirmation model and citizen satisfaction with public services: A meta‐analysis and an agenda for best practice. Public Administration Review, 82(1), 147-159.
73. Zhang, X. (2020). The influences of brand awareness on consumers’ cognitive process: An event-related potentials study. Frontiers in Neuroscience, 14, 1-7.
74. Zhao, H., Yao, X., Liu, Z., & Yang, Q. (2021). Impact of pricing and product information on consumer buying behavior with customer satisfaction in a mediating role. Frontiers in Psychology, 12, 1-11