American Journal of Research in Humanities and Social Sciences ISSN (E): 2832-8019 Volume 8, | Jan., 2023 P a g e | 99 www.americanjournal.org WAITING-LINE MANAGEMENT AND REPEAT PATRONAGE OF FAST FOOD CENTRES IN RIVERS STATE, NIGERIA NDU, EUGENE CHIGOZIE Department of Hospitality and Tourism Management, University of Port Harcourt. Email: eugene.ndu@uniport.edu.ng ORCID: https://orcid.org/0009-0001-3182-5377 BISSONG, NNEKA IFEOMA Department of Hospitality and Tourism Management, University of Port Harcourt. Email: essencenn@yahoo.com A B S T R A C T K E Y W O R D S This study investigated the relationship between waiting-line management and repeat patronage of fast food centres in Rivers State, Nigeria. Primarily, it examined the effect of waiting-line management strategies dimensioned by customer engagement, staff empathy, waiting environment and perceived waiting time on repeat patronage. It was hypothesized that there is no significant relationship between each of these dimensions and repeat patronage; giving rise to four hypotheses. Cross-sectional survey design was adopted for the study; and data were obtained from 384 customers of 15 major fast food centres in Rivers State. This was subjected to statistical analysis using Partial Least Square Structural Equation Modelling (PLS_SEM) aided by SMART PLS. The results showed that customer engagement, staff empathy, waiting environment and perceived waiting time all had significant positive correlations with repeat patronage at beta (β) values of 0.574, 0.630, 0.489 and 0.591 respectively. This affirmed that waiting-line management is a veritable predictor of repeat patronage. Consequentially, managers of fast-food centres are urged to design and implement efficient and effective waiting-line management systems geared towards enhancing customers’ satisfaction and loyalty for continuous patronage. In doing this, priority attention should be given to waiting environment and staff empathy. Customer Engagement, Perceived Waiting time, Repeat Patronage, Staff Empathy, Waiting Environment Introduction The ability of modern business to satisfy customers has increasingly become more complex due to changes in consumer taste and development in modern technology (Tung et al., 2019; Udeze & Oko, 2020). This reality is especially predominant in the service industry like fast food restaurants whose American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 100 www.americanjournal.org major deliverable is to provide a swift dining experience to satisfy customers’ needs (Ndu & Iheanacho, 2018). Modern fast food businesses cannot be considered among the successful unless they develop means to reaching and satisfying their consumers better than their rivals (Aline et al., 2019; Simiyu & Makhamara, 2020). This has occasioned the need for these business organisations to constantly monitor, analyse and develop innovative ways not only to capture the attention of consumers but to meet and surpass their expectation. Kotler and Armstrong (2010) provide a definition of customer satisfaction as the degree to which the purported performance of a product or service by the consumer aligns with their expectations. Scholars (Ademe, 2021; Horsfall & Didia, 2020; Ndu, 2018; Ndu & Iheanacho, 2018) explained that customers’ satisfaction is essential key to having a thriving fast food business due to its ability to engender repeat purchase and customers ‘loyalty to organisation. Therefore, the ability of fast food centres (FFCs) to maintain and grow their market share in today's competitive climate relies on their expertise to pinpoint avenues to satisfying their consumer (Satish & Satich, 2022) amidst fierce competition. One of such avenues to accomplishing this might be effective waiting-line management (Kamau, 2012; Polas et al., 2018). Waiting-line management within FFC establishments appears to be a critical factor influencing customer satisfaction. The nature of waiting-lines and the efficiency with which they are managed can significantly impact the overall dining experience and subsequently, customer satisfaction (Smith et al., 2018). While various factors contribute to customer satisfaction, the waiting-line management process, involving aspects such as customer engagement, staff empathy, and the waiting environment, emerges as a focal point in determining the overall quality of service delivery in FFCs (Parasuraman et al., 1988). Unfortunately, this has not been largely explored in literatures; especially within the context of FFCs in Rivers State. This obviously has created a gap which this study seeks to address. Previous studies on customers’ satisfaction and repeat purchase behaviour in fast food establishments have been centrally focused on service/product quality (Ndu, 2018; Ndu & Iheanacho, 2018); strategic positioning and Marketing (Ademe, 2021; Ejiogu et al., 2024), Food Quality (Ezema-Kalu & Onuoha, 2018; Horsefall & Didia, 2020) amongst others. A few studies that have considered this discussion were domiciled in other industries like banking sector and outside Nigeria (Kamauo, 2012; Polas et al., 2018). It is noteworthy to mention that the urgent need to conduct a study of this nature in fast food establishments is imminent, especially within the competitive landscape of Rivers State, Nigeria, where a burgeoning population demands swift and efficient services from FFCs. This study therefore sought to champion this course by investigating the relationship between waiting-line management and repeat patronage in the context of Fast Food Centres in Rivers State. The problem of sales growth and repeat patronage has continued to plague operations leaders of FFCs in Rivers State. The industry has experienced numerous instances of customer discontentment, which in severe circumstances have resulted to substantial customer attrition, outlet closures, or even the liquidation of FFC brands (Ndu & Iheanacho, 2018). This rate of business failure and collapse of FFCs in Rivers State is quite alarming with notable instances form big fast food brands like Mr Biggs and Sizzler. These once bubbling fast food centres have shut down most of their outlets (Daily Trust, 2017; Ndu & Iheanacho, 2018) while the existing ones are just trying to survive. Other brands that have similar experiences include Joewenedy, Wendy and Native fingers. The trajectory is undesirable; it could further deepen the problem of unemployment and insecurity. This could also discourage potential investors that may be considering delving into fast food business. Another notable problem observed is the poor attitude of employees in fast food restaurants. Many at time they fail to treat American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 101 www.americanjournal.org customers with empathy, respect and concern. The level of customer engagement is still abysmally poor. Also the waiting environments of many fast food centres, particularly eating areas are sometime not well kempt. This experience particularly discourages customers from waiting patiently for their services. It is important to remember that service providers risk losing clients when their expectations are not fulfilled; as customers often do not like a long waiting-time. Since no FFC manager likes to see her customer list dwindle, onus is therefore on FFC operations managers to guarantee that service delivery lives up to client expectations. This study therefore sought to address these challenges examining how managers of FFCs can engender customer’s repeat patronage through effective waiting-line management. To this end, the dimensions of waiting-line management as itemized by Parasuraman et al (1988) which included customer engagement, staff empathy and waiting environment; as well as perceived waiting time were used to evaluate the relationship on repeat purchase. Hence, the study objectives were evaluation of the relationship between: 1. Customer Engagement and Repeat Patronage of FFCs in Rivers State Nigeria. 2. Staff Empathy and Repeat Patronage of FFCs in Rivers State Nigeria. 3. Waiting Environment and Repeat Patronage of FFCs in Rivers State Nigeria. 4. Perceived Waiting Time and Repeat Patronage of FFCs in Rivers State, Nigeria. It was hypothesized that: H0:1 There is no significant relationship between Customer Engagement and Repeat Patronage of FFCs in Rivers State, Nigeria. H0:2 There is no significant relationship between Staff Empathy and Repeat Patronage of FFCs in Rivers State, Nigeria. H0:3 There is no significant relationship between Waiting Environment and Repeat Patronage of FFCs in Rivers State, Nigeria. H0:4 There is no significant relationship between Perceived Waiting Time and Repeat Patronage of FFCs in Rivers State, Nigeria. The significance of this study stems from the fact that it provides insights into how effective waiting- line management affects the repeat patronage intentions of customers in fast food centres. This would help Fast Food Centres understand the importance of reducing customer waiting-times and improving their experience while on the waiting-line. Second, the study identified the factors that influence customer satisfaction in queuing management. This information will be useful in developing strategies and tactics that can be implemented to improve waiting-line management and enhance repeat patronage. Also, insights from this study would be beneficial to researchers seeking to conduct studies on this area; thereby, making it a veritable tool and point of departure for future research endeavours. The study scope at the content level covered themes like waiting-line management, perceived waiting time, customer engagement, staff empathy, waiting environment and repeat patronage. Whereas at the geographic level, it was limited to Rivers State, Nigeria; with the unit of analysis being at the micro level since it focused on customers of the FFCs. Literature Review The review of major concepts of this study was executed in line with the diagrammatic framework of the study as shown in figure 1. American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 102 www.americanjournal.org Figure 1: Diagrammatic Framework of the Study Variables Source: Researchers’ Conceptualisation, 2023 Based on the Identified Variables of the Study Concept of Waiting-line Management Waiting-lines, often referred to as queues, are an integral aspect of service encounters and have been explored through the lens of various academic disciplines, including operations management, psychology and marketing. In operations management, the study of waiting-lines is deeply rooted in queuing theory, which provides a mathematical framework for understanding and optimizing the dynamics of waiting-lines. From a psychological perspective, the concept of waiting-lines intersects with the broader field of consumer behaviour. The experience of waiting involves not only objective factors, such as the actual duration of the wait, but also subjective elements tied to the customer's perception of time and the overall waiting environment. Waiting-line management therefore, refers to the set of strategies and tactics used by businesses and organisations to optimize the management of customer queues and waiting times. These strategies may include techniques such as process analysis, customer segmentation and service level agreements (SLAs) to improve queue efficiency and customer satisfaction (Sekaran & Bougie, 2016). It is the process of actively managing customer waiting times in a way that reduces perceived waiting times and improves customer satisfaction. This may involve implementing a range of tactics such as queue design, staffing levels and service policies that work together to minimize customer waiting times and maximize customer satisfaction (Chen & Shen, W ai ti n g- lin e M an ag e m e n t Customer Engagement Staff Empathy Waiting Environment Perceived Waiting Time Repeat Patronage American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 103 www.americanjournal.org 2018). It may also include using metrics such as average waiting time, queue length and abandonment rates to monitor queue performance, as well as implementing tools such as self-service kiosks, digital signage and mobile apps to improve customer experiences (Kumar & Sridhar, 2016). Strategies for Waiting-line Management Several Strategies have emerged over the years to managing waiting-lines. Waiting-line management has transcended beyond the traditional queue management system. Some of the strategies for waiting- lines management include: Single Line Queuing: Single-line queuing is a type of waiting-line management strategy in which customers form a single line and wait their turn to be served by the next available service agent. Single- line queuing is more efficient and fairer compared to multiple-line queuing, where customers choose which line to join (Larson & Odoni, 2013). This approach maximizes the impact of the ‘first-come, first-served’ rule; and prevents customers from getting frustrated by seeing others being served before them even though they arrived later. Single Line Multiple Server: The Single Line Multiple Server (SLMS) configuration is a fundamental model in queuing theory, employed to study and optimize the efficiency of service systems where a single queue feeds into multiple servers. This configuration finds application in various service industries, including but not limited to healthcare, telecommunications, and transportation. Research by Gupta and Jain (2014) highlights the relevance of SLMS in hospital settings, where patients often face diverse medical needs. This queue management system helped distribute the patient load among multiple servers, minimizing the risk of bottlenecks and optimizing resource utilization. However, the effectiveness of SLMS is contingent on factors such as staff coordination and workload balancing. Multiple Lines Queuing: Multiple lines queuing is a type of waiting-line management strategy in which customers form several lines, with each line leading to a different service agent. While this approach may appear to be more efficient, it can be unfair as customers in one line may wait longer than those in another line, and it can also lead to longer waiting times overall (Koole & Mandelbaum, 2014). Multiple lines of queuing can also be stressful for customers who are unsure which line will move the quickest. Single Server Multiple Line: The Single Server Multiple Line (SSML) involves a single server catering to multiple waiting-lines, creating a scenario where customers from different queues contend for the attention of a solitary service provider. One of the key advantages of SSML configurations is their applicability in situations where there is a need to differentiate between customer classes or service priorities. Despite its advantages, SSML configurations also pose challenges, particularly in terms of fairness and equity in service provision. Queue prioritization and fairness, emphasized the need for equitable service distribution among different waiting-lines. This aspect becomes crucial, especially in contexts where customers may perceive unfairness in the allocation of service resources. Multiple Line Multiple Server: This queuing model involves the presence of multiple lines through which customers queue, and multiple servers simultaneously catering to the needs of waiting American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 104 www.americanjournal.org customers. This arrangement is pertinent in various service-oriented settings, such as Fast Food Centres (FFCs), healthcare facilities and telecommunications, where efficient customer service is paramount. A key advantage of MLMS lies in its potential to enhance service efficiency and reduce customer waiting times. However, the implementation of MLMS is not without challenges. One notable concern is the need for effective queue management to ensure fair and orderly service. Virtual Queuing: Virtual queuing is a type of waiting-line management strategy that uses technology to allow customers to join a queue without physically waiting. Customers receive a notification when their turn is approaching, and they can then proceed to the service point. Virtual queuing has been found to improve the overall customer experience and reduce perceived waiting times significantly (Kim & Yoon, 2014). Priority Queuing: Priority queuing is a type of Waiting-line management strategy that prioritizes certain customers based on their status, such as VIPs or customers with disabilities. This approach can be effective in providing more efficient and personalized service to these customers, but it can also lead to longer waiting times for other customers, which may negatively impact their experience (Koole & Mandelbaum, 2014). Self-Service Queuing: Self-service queuing is a type of waiting-line management strategy that allows customers to perform tasks independently, such as checking out using a self-service kiosk. This approach can help reduce waiting times and improve the overall customer experience by reducing the workload of service agents (Kim & Yoon, 2014). Managing customer waiting times is essential for providing a positive customer experience. Organizations can adopt different types of waiting-line management strategies, such as single-line queuing, multiple-line queuing, virtual queuing, priority queuing and self-service queuing, depending on their specific needs and goals. Dimensions of Waiting-lines Management For the purpose of this study, the identified proxies for waiting-line management include customer engagement, staff empathy, waiting environment and perceived waiting time. Customer Engagement Customer engagement has been defined by Brodie et al. (2013) as a psychological state that occurs when customers are willing to invest their attention, time and resources in a brand. This definition emphasizes the depth of customer involvement and the emotional commitment inherent in engagement. The literature emphasizes the role of technology as a catalyst for customer engagement. Social media platforms in particular, play a crucial role in facilitating two-way communication between brands and customers. Kumar and Pansari (2016) assert that leveraging social media channels enables brands to actively participate in conversations, respond to customer queries and solicit feedback, thereby fostering a sense of belongingness and co-creation. This aligns with the notion of customer engagement as a dialogic process, emphasizing the importance of reciprocal communication (Hollebeek, et al., 2014). Engagement extends beyond mere behavioural interactions and includes cognitive and emotional elements; emphasizing a holistic understanding of customer-brand relationships (Vivek et al., 2012). Hollebeek (2011) further emphasizes the dynamic nature of American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 105 www.americanjournal.org engagement, stressing its continuous and evolving nature as customers interact with brands over time. Engaged customers are more likely to exhibit loyalty, repeat purchase behaviour and positive word- of-mouth (Bowden, et al., 2009). Their emotional connection to the brand translates into a higher likelihood of forgiveness in the face of service failures (Verleye et al., 2013). Moreover, engaged customers are instrumental in co-creating value, actively participating in the innovation process and contributing to the development of new products and services (Prahalad & Ramaswamy, 2004). Staff Empathy Staff empathy is a critical dimension in the realm of service quality; representing a core element in the interaction between service providers and customers across various industries. Empathy, involves the ability of service staff to understand and share the feelings of customers, demonstrating a genuine concern for their well-being. Empathy, rooted in social psychology, is recognized as a crucial element in interpersonal relationships and communication. In the service industry, staff empathy plays a pivotal role in shaping customers' perceptions and experiences. As noted by Davis (1996), empathy involves both cognitive and affective dimensions, encompassing an understanding of the customer's perspective and an emotional responsiveness to their needs. This dual nature of empathy positions it as a powerful mechanism for fostering positive interactions and enhancing overall service quality. The outcomes of staff empathy are manifold, impacting both customers and organizations. One of the primary outcomes is enhanced customer satisfaction. When customers perceive that service staff genuinely understand and care about their needs, it fosters a positive emotional connection, contributing to overall satisfaction (Homburg et al., 2009). Empathetic interactions also play a pivotal role in building customer loyalty, as customers are more likely to return to establishments where they feel a genuine connection with the service providers (Verhoef et al., 2009). Waiting Environment Waiting environment refers to a setting or situation where individuals gather in anticipation of a particular event or activity. These environments are designed to accommodate and engage attendees while they wait for the event to begin. The primary goal of an event waiting environment is to enhance the overall experience of attendees by providing a range of facilities, amenities and entertainment options that keep them engaged and entertained during the waiting period. These environments aim to minimize the perceived waiting time and create a positive impression on the attendees, ensuring that they have a memorable and enjoyable experience throughout their visit. Designing an effective event waiting environment in fast food centres requires careful consideration of various factors, including crowd management, spatial layout, seating arrangements, amenities and entertainment options (Huang, 2019). The spatial layout and seating arrangements in waiting environments play a significant role in determining the comfort and satisfaction of attendees (Kumar et al., 2014). Additionally, the arrangement of amenities such as food and beverage stations, restrooms and charging stations, should be strategically placed to ensure easy accessibility and convenience for attendees. To entertain and engage attendees during the waiting period, event waiting environments often provide a variety of entertainment options. These may include live performances, interactive displays, games, virtual reality experiences or multimedia installations. Research has shown that providing interactive and engaging activities can significantly reduce perceived waiting time and enhance the overall experience (Huang, 2019; Kumar et al., 2014). By offering entertainment options that cater to diverse preferences American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 106 www.americanjournal.org and demographics, event organizers can keep attendees engaged and ensure they have a positive waiting experience. Perceived Waiting Time Perceived waiting time refers to the manner in which members of the public or attendees of an event subjectively define the length of time they must wait. Perceived waiting time refers to the amount of time that patrons anticipate spending on the queue. The perception of waiting time by individuals is subjective and contingent on their specific experiences; furthermore, one's reaction to waiting time is a consequence of cognitive processes (Maister, 1985). There are economic and psychological costs associated with waiting. Customers invariably show preference for dining establishments that offer prompt service. Thus, it has been established that the contentment of consumers regarding the waiting time is affected by the perceived waiting time (Oliver & Westbrook, 1993). Customers make pre- dinner predictions regarding the duration of the wait. They become dissatisfied if the actual waiting time exceeds the perceived time (Maister, 1985). Satisfaction with the waiting experience is influenced by the duration of the delay, with consumers seeking assistance in a timely and pleasant manner. When the perceived waiting time is shorter than the actual service time, customers become excessively satisfied. However, as the wait time increases, consumers become impatient and pessimistic. Consequently, client satisfaction may be enhanced when the product is delivered in advance of the anticipated waiting period (Dabholkar, 2015). Repeat Patronage Repeat patronage refers to the occurrence of customers returning to a business or service provider to make additional purchases or utilize their services again. In the Quick Service industry, repeat patronage plays a pivotal role in ensuring long-term success and growth. Customer satisfaction is a key driver of customer loyalty. Satisfied customers are more likely to develop an emotional connection with the Quick Service and exhibit repeat patronage behaviour (Homburg et al., 2009). Building a base of loyal customers ensures a stable revenue stream and positive word-of-mouth promotion. The cost of acquiring new consumers is usually higher than the cost of keeping old ones. Research shows that keeping an existing client costs five times less than acquiring a new one. By prioritizing customer satisfaction and fostering repeat patronage, quick service companies (Fast food centres) can reduce marketing and acquisition costs while maximizing profitability. Repeat patronage helps build a strong foundation for a positive brand image. More so, repeat patronage forms the foundation for sustainable growth in the Quick Service industry. By focusing on customer satisfaction, fast food centres can establish a loyal customer base, leading to repeat patronage and long-term financial stability. It is noteworthy that in a highly competitive industry, customer satisfaction can provide a significant competitive advantage. Satisfied customers are less likely to switch to competitors and are more forgiving of occasional service failures (Homburg et al., 2009). This enables fast food companies to differentiate themselves from competitors and maintain a competitive edge in the market. Theoretical Underpinning Theoretically, this study was predicated on the fundamental ideas of Queuing Theory; which is a mathematical approach that focuses on the study of queues or waiting-lines. It provides a framework for understanding and analyzing the behaviour of systems that involve waiting times, service rates and American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 107 www.americanjournal.org arrival patterns (Gross & Harris, 1998). This theory has practical applications in various fields, including operations research, telecommunications, transportation, healthcare, and Service. The theory offers a robust framework for comprehending and managing waiting-lines within systems, leading to enhanced efficiency, customer satisfaction, and overall performance. By analysing system dynamics and optimizing resource allocation, organizations can improve efficiency, customer satisfaction and overall performance (Erlang, 1909; Gross & Carl, 2019). The use of queuing theory was initially in the telecommunications industry and can be traced back to the early 20th century, with its initial development influenced by researchers such as Agner Krarup Erlang and David George Kendall (Erlang, 1909; Kendal, 1953). Ever since then, the theory had been widely adopted in various industries to solve challenges including resources allocation and waiting- lines management (Bhat & Kishor, 1987; Gross & Harris, 1998). Queueing theory advocates for the analysis, modeling and optimization of systems that involve the flow of entities, such as customers, requests, or tasks, through a service facility or network. Its primary goal is to understand and improve the performance of these systems by studying factors such as waiting times, queue lengths, service rates, and resource utilization (Bertsimas & Nakazato, 2020; Gross & Harris, 1998; Hillier & Lieberman, 2014). By applying mathematical models and statistical techniques, queuing theory aims to address various operational challenges with the ultimate aim of enhancing service speed, customer satisfaction and resource utilization (Guerreiro et al., 2021; Takács et al., 2018). The rationale for adopting queuing theory in this study stems from the fact that the theory plays a crucial role in waiting-line management and customer satisfaction in fast-food restaurants by enabling efficient resource allocation, optimizing service speed, implementing effective queue management strategies, predicting wait times and enhancing overall service quality (Gross & Carl, 2019; Guerreiro et al., 2021; Takács et al., 2018). By applying Queuing Theory principles, the study can evaluate crucial factors such as arrival patterns, service rates, and waiting times, which directly impact customer satisfaction in fast food centres. Additionally, the theory can be used as a guide to improving waiting- line management strategies, optimizing venue layouts, determining staffing levels and implementing effective queuing systems to enhance customer experience and overall satisfaction (Guerreiro et al., 2021; Shortle et al., 2018; Takács et al., 2018). Empirical Literature Customer Engagement and Repeat Patronage Customer engagement, a multidimensional and dynamic construct, has garnered substantial attention in contemporary marketing literature. The outcomes of customer engagement are manifold and extend beyond immediate financial metrics. Engaged customers are more likely to exhibit loyalty, repeat purchase behaviour and positive word-of-mouth (Bowden et al., 2009). Their emotional connection to the brand translates into a higher likelihood of forgiveness in the face of service failures (Verleye et al., 2013). The study conducted by Prahalad and Ramaswamy (2004) revealed that engaged customers are instrumental in co-creating value, actively participating in the innovation process and contributing to the development of new products and services. The evolving role of customer engagement is particularly pronounced in the digital era. With the proliferation of online channels and social media, customers are not passive recipients but active participants in brand communication. Brands that harness the potential of social engagement of customers are better positioned to build communities American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 108 www.americanjournal.org around their products or services, leading to a sense of belonging among customers (Füller et al., 2009) and commitment to repeat patronage. Staff Empathy and Repeat Patronage There have been a number of studies conducted on staff empathy and client loyalty. Customer loyalty is a direct result of happy customers' perceptions of staff competency, according to research by Kim et al. (2015). Customers are more likely to stay loyal and return if they are satisfied with the competency of the personnel, according to research by Dube and Renaghan (2018). According to Brown and Turley (2016), customers' perception of staff competence is influenced by various factors, such as their communication skills, technical knowledge, attitude and appearance. They found that staff who possess these attributes are more likely to provide exceptional service and enhance customers' experience, which leads to repeat patronage. Likewise, Johnson and Neuhofer (2017) emphasized the importance of emotional competence, such as empathy and friendliness, in enhancing customer satisfaction and repeat patronage in the event industry. Waiting Environment and Repeat Patronage The waiting area significantly affects consumer happiness and loyalty, according to research by Aksoy and Kervan (2015). Customers who had a good time while waiting for an event are more likely to come back and tell others about it. On the other hand, customers who had a bad time while waiting were also less inclined to come back or suggest the business to others, according to the survey. Lee and Jang (2018) conducted research on how customers' satisfaction and behavioural intentions were affected by the waiting environment. Customers' good experiences throughout the event's waiting time were associated with more positive behavioural intentions, including future visits and word-of-mouth recommendations, according to the research. In the context of online buying, Huang and Chen (2017) investigated how the waiting environment affects consumer pleasure and loyalty. According to the research, the amount of time a client has to wait and the quality of that wait significantly affects their level of happiness and loyalty. The survey also indicated that consumers who were satisfied with their wait time were more inclined to buying more from the online shop. Similarly, Hui et al (2012) found that the use of pleasant music in the waiting area led to increased customer satisfaction and repeat patronage. These studies suggest that the use of atmospherics in the waiting environment can positively influence customer behaviour. Perceived Waiting Time and Repeat Patronage Research indicates that when perceived waiting time rises, satisfaction levels decrease (Kumar & Gupta, 2018). Customers anticipate the waiting time before visiting eateries. Dissatisfaction occurs when the real waiting time exceeds the perceived time. Customers consistently want to acquire services promptly and enjoyably. If it takes a long time, consumers may feel bored and disheartened. Customers may not feel happy when they get the goods after a longer waiting period than they anticipated (Dabholkar, 2015). Affirming this, Kim and Hyun (2018) examined the association between queue management and customers' happiness. Wait management was found to have substantial impact on consumer happiness, according to the study's survey of 299 visitors. Customer American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 109 www.americanjournal.org satisfaction was determined by many aspects, including perceived waiting time, line design and queue fairness, according to the research. It was found specifically that when perceived waiting time is considered satisfactory by customers, there overall satisfaction increased and consequently their willingness to patronise the business again. Similarly, a study by Lee et al. (2018), investigated the effects of queue line management on customer experience and behavioural intentions in a shopping mall. The study used a survey of 331 shoppers and found that queue line management significantly influenced customer experience and behavioural intentions. Specifically, the study found that perceived waiting time, queue fairness, and queue design were crucial factors in determining customer experience and behavioural intentions and repeat purchase. Methodology Due to the fact that the elements of this study are not under the control of the researchers, the cross sectional survey design was adopted for this study; with data gathered from primary sources using a 5-point Likert-like scale. The target population comprised customers of fast food centres in River State. Nigeria; making it an infinite population. The Cochran’s formula for sample size determination in an unknown population was utilized to arrive at a sample size of 384 respondents. Data for the study was gathered through the use of questionnaire which was purposively distributed to 15 major fast food centres in Rivers State. To guarantee the instrument's validity, professionals in the field examined several copies and offered feedback on each. These suggestions were considered and included into the final version of the survey to ensure its face validity. By using confirmatory factor analysis (CFA), we were able to determine that the study instrument met the criteria for convergent and discriminant validity, as suggested by Bagozi et al. (1991) and Hair et al. (2014). Cronbach’s alpha value and composite reliability were used to ensure the instrument's reliability. Partial Least Square Structural Equation Modelling; which according to Hair et al. (2014) is a multivariate data analysis approach that searches for linear correlations between many independent variables and multiple dependent variables was adopted for statistical data analysis. Results and Discussions Consistent with the study's sample size, a total of three hundred and eighty-four (384) copies of the questionnaire were distributed; out of which 367 copies were retrieved, resulting to a response rate of 91.8%. Out of this number, two hundred and eighty-one (281) copies were found to be useful for the analyses; resulting to 70.3% valid response rate. For the descriptive statistics, the threshold for mean value was set at 2.5 as suggested by Asawo (2009). The analysis comprised two major steps. First is the assessment of the instrument to confirm its’ validity and reliability; the second part is the test of hypotheses. Table 1: Results of the Measurement Model with Descriptive Analysis and Factor Loadings Constructs Item Scale Mean S.D Loadings Cronbach Alpha CR AVE Sq. Root of AVE Customer Engagement CE Item 1 2.841 0.973 0.783 0.776 0.857 0.600 0.775 CE Item 2 3.140 0.729 0.862 CE Item 3 3.581 1.009 0.734 CE Item 4 3.102 0.969 0.712 Staff Empathy SE Item 1 3.105 0.948 0.805 0.780 0.822 0.607 0.779 American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 110 www.americanjournal.org SE Item 2 3.662 0.926 0.691 SE Item 3 3.463 1.006 0.834 Waiting Environment WE Item 1 3.780 0.942 0.708 0791 0.865 0.618 0.786 WE Item 2 3.780 0.931 0.844 WE Item 3 3.613 0.910 0.848 WE Item 4 3.792 0.817 0.734 Perceived Waiting Time PWT Item 1 3.169 1.004 0.741 0.784 0.860 0.607 0.785 PWT Item 2 3.304 0.992 0.769 PWT Item 3 3.169 1.004 0.854 PWT Item 4 3.304 0.992 0.746 Repeat Patronage RP Item 1 3.690 0.849 0.755 0.879 0.911 0.673 0.820 RP Item 2 3.791 0.889 0.782 RP Item 3 3.811 0.873 0.834 RP Item 4 3.820 0.803 0.896 RP Item 5 3.864 0.803 0.829 Source: Researchers’ Computation, 2023. The table 1 shows the descriptive results, and the outcome of model assessment for the study. The results of the convergent validity analysis for the final model hypothesis are also shown in the table. The descriptive statistics result as portrayed with mean and standard deviation scores were satisfactory as they exceeded the minimum threshold. Statistically significant factor loadings are shown for all items in the model's variables. These factor loadings are greater than 0.7, which is the minimum allowable according to Hair et al (2014) and Ndu and Ajao (2019). In addition, as shown by Hair et al. (2014, 2010), the AVEs are higher than the minimally acceptable threshold of 0.5. As a result, the convergent validity is considered satisfactory. To assess the reliability of the model/instrument, the analysis also revealed the several reliability indicators such as Cronbach Alpha (α) and Composite Reliability (CR) for each of the constructs. The result on the table clearly showed that a favourable score for each of the construct as none of them fall below the recommended threshold of 0.70. The internal consistency of the research instrument is therefore satisfactory. The implication of this connotes that each of the variables in the model are quite consistent with one another. Table 2: Correlation Matrix Showing that Discriminant validity of Latent Variables Constructs CE SE WE PWT RP Customer Engagement 0.775 Staff Empathy 0.671 0.779 Waiting Environment 0.593 0.679 0.786 Perceived Waiting Time 0.557 0.589 0.597 0.724 Repeat Patronage 0.753 0.718 0.630 0.732 0.820 0 Source: Researchers’ Computation, 2023. Note: CE – Customer Engagement SE – Staff Empathy WE – Waiting Environment PWT – Perceived Waiting Time RP – Repeat Patronage The table 2 above showed the assessment result for the discriminant validity of each of the identified latent construct in this study. The essence of discriminant validity according to Hair, et al (2010) is to measure the degree to which two conceptually similar constructs are distinct to each other. Examining the construct-to-construct correlations on the table revealed that the Square roots of AVE along the American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 111 www.americanjournal.org diagonal of the correlation matrix being greater than all the off-diagonal correlation value on the row and columns proved that discriminant validity of the research instrument/model is acceptable (Hair et al., 2010). Structural Model and Hypotheses Testing Figure 2: Structural Path Model Showing Hypotheses Results Source: Smart PLS Output, 2023 Interpretation of Model Figure 2 showed the path analysis result for the relationship between the dimensions of waiting-line management and repeat patronage. Specifically, the result showed that there is a positive relationship between the dimensions of waiting-line management and repeat patronage. The first structural path which represented the first hypothesis of the study showed that there is a positive relationship between customer engagement and repeat patronage with a beta value (β) of 0.574 at P 0.00 < 0.05 and T-Value 3.156 > 1.96. Thus the null hypothesis was rejected. The second structural path which represented the second hypothesis of the study showed that there is a positive relationship between staff empathy and repeat patronage with a beta value (β) of 0.630 at P 0.00 < 0.05 and T-Value 2.093 > 1.96. Thus the null hypothesis was rejected. The third structural path which represented the third hypothesis of the study showed that there is a positive relationship between waiting environment and repeat patronage with a beta value (β) of 0.489 at P 0.00 < 0.05 and T-Value 11.700 > 1.96. Thus the null hypothesis was rejected. The fourth structural path showed that there is a positive relationship between perceived waiting time and repeat patronage with a beta value (β) of 0.591 at P 0.00 <0.05 and T-Value 10.614 American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 112 www.americanjournal.org > 1.96. Thus the null hypothesis was rejected. Furthermore, collectively waiting-line management has significant positive influence on repeat patronage with R2 value of 0.512, indicating a moderate predictive capacity of 51%. Therefore, the results showed that waiting-line management has significant relationship with repeat patronage. Table 3: Path Analysis Result of the Direct Hypothesis S/N Hypothesized Path Path Coefficient (β) R2 Value P-Value Standard Error T Value Decisions 1. CE -> RP 0.574** 0.330 0.000 0.015 3.156 Not Supported 2. SE -> RP 0.630** 0.397 0.000 0.011 2.093 Not Supported 3. WE ->RP 0.489** 0.239 0.000 0.097 11.700 Not Supported 4. PWT -> RP 0.591** 0.307 0.000 0.029 10.614 Not Supported **P<0.01 *P<0.05 Source: Researchers’ Computation, 2023. Table 3 summarised the structural model of the study which confirmed the existence of a substantial relationship between waiting-line management and repeat patronage. The result showed that structural path of each identified dimensions of waiting-lines management. It was revealed that staff empathy → Repeat patronage has the strongest relationship with beta (β) value of 0.630 and R2 value of 0.307. While the lowest was waiting environment → Repeat patronage with beta (β) value of 0.489 and R2 value of 0.239. Discussions The findings from the study indicate a statistically significant correlation between waiting-line management and repeat patronage of fast food centres with a collective R2 value of 0.512. This connotes a 51.2% predictive capacity of WIM over RP; while other factors beyond the scope of this study could be responsible for the remaining 48.8%. Specifically, the study showed that the first structural path which represented the first hypothesis of the study showed that there is a positive relationship between customer engagement and repeat patronage. The second structural path which represented the second hypothesis of the study showed that there is a positive relationship between staff empathy and repeat patronage. The third structural path which represented the third hypothesis of the study showed that there is a positive relationship between waiting environment and repeat patronage. Similarly, the fourth structural path showed that there is a positive relationship between perceived waiting time and repeat patronage with. This confirmed that repeat patronage could be encouraged if managers of Fast Food Centres conduct their operations systems effectively to engender a smooth running waiting-line management systems. These findings were supported by Yu and Lee (2021) when they found that customers who perceived better queue line management reported higher levels of customer satisfaction and were more likely to revisit the restaurant. Similarly, Zhang, et al. (2019) explored the impact of queue management on customer experience and satisfaction in theme parks. As regards the result on impact of perceived waiting time on repeat patronage, generally different researchers supported that as perceived waiting time increases, the satisfaction level fall down (Kumar & Gupta, 2018). Supporting evidence was found in Dabholkar (2015) who concluded that customers become satisfied when they get their product earlier than their expected waiting-time. American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 113 www.americanjournal.org Undoubtedly, other empirical evidences showed that customers who thought the restaurant handled their waiting time better were happier overall and more inclined to come again (Kim & Hyun, 2018; Lee et al., 2018). As regards the result on staff empathy, similar findings were reported by Kim, et al. (2015) who found in their study that customers are more likely to stay loyal and return if they are satisfied with the empathy of the personnel. This was also in tandem with outcome of research conducted by Dube and Renaghan (2018). Likewise, Johnson and Neuhofer (2017) emphasized the importance of emotional competence, such as empathy and friendliness, in enhancing customer satisfaction and repeat patronage in the event industry. The result on customer engagement was also found to be in agreement with previous findings of Bowden et al. (2009). They reported in their study that engaged customers are more likely to exhibit loyalty, repeat purchase behaviour, and positive word-of-mouth. Their emotional connection to the brand translates into a higher likelihood of forgiveness in the face of service failures (Verleye et al., 2013). This was view was also champion scholars like (Füller et al., 2009; Prahalad & Ramaswamy, 2004) who all conclude that brands that harness the potential of social engagement of customers are better positioned to build communities around their products or services, leading to a sense of belonging among customers. As regards the result on waiting environment, it was found that the waiting area significantly affects consumer happiness and loyalty, according to research by Aksoy and Kervan (2015). Research conducted by Lee and Jang (2018) gave a corroborating evidence that customers' satisfaction and behavioural intentions were affected by the waiting environment. Customers' good experiences throughout the event's waiting time were associated with more positive behavioural intentions, including future visits and word-of- mouth recommendations, according to the research. Huang and Chen (2017) also indicated in their survey that the amount of time a client has to wait and the quality of that wait significantly affects their level of happiness and loyalty. The survey also indicated that consumers who were satisfied with their waiting environment were more inclined to buy more from the online shop. Similarly, Hui et al (2012) found that the use of pleasant music in the waiting area led to increased customer satisfaction and repeat patronage. Research by Park and Lee (2009) found that the quality of service provided by staff members in the event waiting environment was positively related to customer satisfaction and repeat patronage. These studies suggest that the use of atmospherics in the waiting environment can positively influence customer behaviour. Implications of the Study The analytical findings mentioned above give useful insights into the complex dynamics of customer satisfaction in quick-service restaurants (FFCs) in Rivers State, Nigeria. The robust positive associations between, staff empathy and customer engagement on repeat patronage shows that these factors when well harnessed could engender favourable customer experience especially in fast food restaurants. These results indicate that creating a better waiting atmosphere and reducing the perceived waiting times have a major impact on improving the overall customer satisfaction. Moreover, these observations have practical consequences for managers in the quick-service restaurant (FFC) industry, highlighting the need to invest in the development of enjoyable waiting areas as well as implementing strategies to reduce customers' perception of waiting time. As the fast food business progresses, the issue of waiting time becomes more imminent due to higher demands. This study has therefore imposed responsibility on FFC managers to prioritise staff empathy towards their customers, while they wait in lines. American Journal of Research in Humanities and Social Sciences Volume 8, Jan., 2023 P a g e | 114 www.americanjournal.org Conclusions and Recommendations The findings of this research explicitly confirmed that waiting-line management has a substantial positive impact on the repeat patronage of fast food centres in River State, Nigeria. Specifically, it achieved predictive abilities of 51.2% on the behavioural intentions of customers to patronise the business repeatedly. As a result, it can be concluded that adequate waiting-line management strategies could be highly instrumental to improving repeat patronage of fast food centres in Rivers State, Nigeria. In line with the findings of this study, the following recommendations were put forward: i. Empathy connotes that staff put themselves in the shoe of the customers by showing willingness to help them. Therefore, managers should ensure that the right employees with courtesy and sense professionalism be stationed to attend to customers. Their ability to manage unhappy customers could reduce their level of dissatisfaction. ii. Prioritize Staff Empathy Training: Recognizing the role of staff empathy on repeat purchase, managers of fast food centres must find it necessary to invest in staff training programs that would emphasize empathy in customer interactions. Furthermore, they should motivate, encourage and reward empathetic attitude towards customers. This would help engender empathy as one of the core values in the organisation. Also to deter apathetic attitude, punitive measures should be put in place to discipline erring employees. iii. One significant challenge spotted out in this study is the unpredictability of customer flow, especially during peak hours. Restaurants need to find a balance between accommodating walk- ins customers and reservations. To achieve this, managers should consider setting up order delivery unit or consider suitable partnership with delivery agents/companies so that customers can make orders at the comfort of their home/offices without necessarily visiting the fast food centre. iv. On the issue of customer engagement, clear signage, friendly staff interactions, and providing amenities in the waiting area should also be put into consideration since this would contribute to a positive waiting experience. v. Fast food Centres are urged to regularly seek feedback from customers in order to identify areas that require improvement in their waiting-line management system. vi. Fast Food Restaurants should adopt more innovative approaches to waiting-line management such as online reservation apps, pager systems, and digital waitlists to enhance efficiency. These tools not only reduce wait times but also provide valuable data for optimizing operations. vii. Comfortable Waiting Area: As regards waiting environment managers are urged to make reasonable investment to create a comfortable waiting area with amenities like Wi-Fi or entertainment to improve the overall waiting experience of customers. By so doing, customers may not find it difficult or offensive to patiently wait for their orders. References 1. Ademe, D. G. (2021). Customer relationship and customer satisfaction of fast food restaurants in Port Harcourt. American Journal of Economics and Business Management, 4(3), 105-122. 2. 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