Abstract
Purpose: Craft beer tourism and beer festivals are subjects of increasing academic discourse, although few theoretical frameworks exist that focus on the measurement of attendee satisfaction at such festivals. Craft beer lovers visit many of these breweries and attend festivals to experience local, regional, national and international brews. The goal of this study is to establish a reliable way of assessing how satisfied attendees were with their experience at a particular craft beer festival.
Design/methodology/approach: A quantitative methodology in the form of a survey research design was used. A total of 313 usable questionnaires were collected from attendees at the Capital Craft Beer Festival in Pretoria, South Africa. This study used the importance-performance analysis (IPA) model to determine which event performance attributes would improve customer satisfaction.
Findings/results: The findings revealed that 8 items in the importance–performance grid were located in the ‘low priority’ quadrant, 3 items were in the ‘concentrate here’ quadrant, 1 item was in the ‘possible overkill’ quadrant and 15 items were in the ‘keep up the good work’ quadrant, which indicated that those attributes generated high satisfaction and that event organisers should sustain their performance.
Practical implications: This study should improve event services for practitioners and policymakers by enabling them to recognise visitors’ demands more easily and to respond better to those demands.
Originality/value: This study examined the discrepancies between visitors’ expectations and perceived performance by using the IPA model, which was created by Martilla and James in 1977.
Keywords: culinary events; beer festivals; service quality; importance-performance; satisfaction.
Introduction
Since 2008, event tourism has grown substantially at numerous destinations internationally (Ho et al., 2022), with festivals, one-time events that celebrate the local culture of a host destination, showing a reasonable growth in recent years. They showcase many different themes, such as religious, historical, economic, artistic and culinary (wine, food & beer festivals) themes (Hermann et al., 2019; Ho et al., 2022; Tkaczynski et al., 2022). A niche market that is demonstrating continued growth in the field of culinary tourism is craft beer tourism, which includes visiting breweries and attending beer shows and beer festivals to experience local beers and explore beer styles (Bachman et al., 2021; Beckman et al., 2020). The scholarly discussion on beer tourism has explored various subjects, including market segmentation, brewery tour organisation, experiences at beer museums, exhibitions, beer festivals, ale trail development and the impact of beer tourism on destination growth (Bachman et al., 2021; Beckman et al., 2020; Cabras et al., 2020; Hermann et al., 2019, 2021; Smith & Asirvatham, 2022; Stone et al., 2020).
Howlett (2013) asserts that the beer tourism niche is a relatively recent development in the tourism industry, and that certain destinations with a rich brewing heritage have been able to enter this lucrative tourism market successfully. Canada, the United Kingdom (UK), Australia, South Africa and the United States (US) are recognised as showing an increasing demand for foreign craft beer tourism markets (Chirakranont & Sunata, 2021). As Dunn and Wickham (2016) contend, ‘craft breweries have the ability to offer premium quality experiential services as part of their product offering’. This is comparable to other premium niche culinary tourism sectors, such as the whisky and wine sectors. The craft beer sector and craft beer tourism have grown more in South Africa than in the other countries in sub-Saharan Africa (Ikäheimo, 2020; Rogerson & Collins, 2019).
The craft beer sector is an emerging sector predominantly consisting of small business operations. Almost two-thirds of South Africa’s brewers have fewer than 15 employees each. There are currently over 200 craft beer manufacturers in South Africa, up from fewer than 50 in 2008 (Hermann et al., 2019). It is estimated that they collectively account for 1% of the nation’s total beer production. These establishments are also known as ‘craft breweries’, and, less often, as ‘micro-breweries’. Craft breweries are typically small businesses that ‘brew different types of beer on a small scale’, as opposed to the larger mass-producer breweries that ‘often have been in business for more than a century and have survived the consolidation process of the twentieth century’ (Cabras, 2021; Garavaglia & Swinnen, 2018).
The wide range of craft beers produced by these brewers includes more than 75 well-known types such as pale ale, porters, stouts, sours and India pale ales (Beckman et al., 2020). The US and Europe are home to 46% and 43% of the world’s craft brewers, respectively, while Australia (3%), Japan (1.6%), Canada (4.5%), New Zealand (1%) and South Africa (4.5%) lag far behind those countries, but represent a growing market (Baiano, 2021). Attendees at craft beer events often attend those events because they are unable to visit the various breweries’ own tasting rooms (Beckman et al., 2020). These events are often associated with entertainment by popular musicians and artists from the host destinations (Manis et al., 2020). They also enable attendees to learn more about pairing beer with local foods, such as chocolate, cheese, chicken or burgers (Ncala, 2018). Rogerson and Collins (2015) mention that craft beer festivals could assist in the growth of rural economies and improve the image and appeal of an area or region to potential investors.
According to Hermann et al. (2021) and Viljoen et al. (2018), festival tourism in South Africa has increased because of the more than 600 events held annually over the last 20 years. Over those two decades, a distinct subculture of beer lovers emerged, complete with its own social norms and language (Maciel & Wallendorf, 2017). Beer-related events, including beer festivals, have also been affected by this shift. Previously there had been two main types of beer festivals: those that were open to the public and free of charge, with an emphasis on beer consumption volume, and those that charged admission and sold premium beers to the curious masses (Ikäheimo, 2020). Two examples of the latter sort of festival, with tens of thousands of attendees each, are the United States’ Great American Beer Festival in Denver, Colorado (since 1982), and the United Kingdom’s Great British Beer Festival in London (since 1977), while the renowned Oktoberfest in Munich, Germany (held for the first time in 1810) is the best example of the former. It now appears that a third sort of event is on the rise because of the success of craft beer (Ikäheimo, 2020). Two of the most renowned events of their kind in Europe are the Beavertown Extravaganza in London and the Mikkeller Beer Celebration in Copenhagen (MBCC 2017). The objective of these festivals is to satisfy the most discriminating craft beer connoisseurs by offering a selection of low-volume, high-quality beers on a relatively small scale (Beckman et al., 2020).
South Africa hosts some of the world’s most well-known beer festivals, such as the Cape Town Festival of Beer, SA on Tap (Johannesburg), the Sandton Craft Beer Fair (Johannesburg) and the Clarens Craft Beer Festival (Rogerson & Collins, 2019). In light of the proliferation of specialised festivals and events in South Africa, the objective of this study was to evaluate the satisfaction levels of attendees at the Capital Craft Beer Festival (CCBF) by doing an importance-performance analysis (IPA). The CCBF was held for the first time in 2012, and takes place every June in Pretoria. The event lasts all day, and attendees can sample craft beers and various foods and beverages, as well as watching live entertainment.
Literature review
Importance-performance analysis model
According to Sozen and O’Neill (2020), the graphical IPA model ranks service constructs from most to least important. The IPA, which Martilla and James formulated in 1977, is a tool that is used to evaluate product qualities in order to ascertain which attributes are most critical in terms of performance. The information obtained can then be used to prioritise product and service enhancements (Stergiou, 2018). As an expectation-disconfirmation model, the IPA model suggests that customer satisfaction is a function of how well various product or service features perform and how significant they are to the customer (Cai & Chi, 2021; Sever, 2015; Stergiou, 2018). This is a simple but useful way to explore quality attributes on two levels: performance and importance. Studies based on the IPA model typically use either a stated or derived measure of importance. Stated measures are collected directly from the target population via a Likert scale or direct rating scales, ranking or constant sum-scales, while derived measures are collected inferentially by correlating the attribute-level data of performance with an outcome variable such as customer satisfaction (Mikulić et al., 2012).
Policymakers can gain a snapshot that aids in effort concentration by plotting survey importance and performance ratings onto a two-dimensional plot (Figure 1), where performance is displayed on the horizontal axis and importance is on the vertical axis (Stergiou et al., 2018). This plot is divided into four quadrants with varying management conclusions by crosshairs, which are horizontal and vertical lines. For example, if an attribute is located in the ‘concentrate here’ quadrant, it may require management’s attention in order to improve performance when the relevance of the attribute is high and the performance is poor. These quadrants assist managers in creating quality-based marketing plans by demonstrating how to assess currently implemented marketing tactics.
 |
FIGURE 1: Importance-performance analysis grid matrix. |
|
The four quadrants depicted in Figure 1 are briefly described as follows.
Quadrant (I) high importance and low performance (Concentrate here)
Characteristics that fall into this quadrant are regarded as having a high level of importance but a poor level of performance. According to Draper (2018) and Stergiou (2018), this suggests that festival organisers identify characteristics that they require to attend the event. As a result, the expectations of attendees are not being met.
High achievement and significant importance in Quadrant II (Maintain the commendable work)
The high levels of performance in this quadrant reflect the high degrees of significance that customers attribute to the many areas of service quality (Wilkins, 2010). Attributes that fall in this quadrant indicate a successful festival according to the attendees’ standards of performance in areas that attendees deem relevant (Phadermrod et al., 2019).
Quadrant III: Low value and low performance
Attributes in this quadrant are regarded as minor weaknesses because of their low importance and performance (Phadermrod et al., 2019). This quadrant, labelled ‘low priority’, indicates that attributes deemed unimportant are being delivered by the festival at an adequate level, as reported by attendees (Draper, 2018). Attributes in this quadrant require little attention, as the attendees at the festival see these attributes as being of lower importance (Phadermrod et al., 2019).
Possible overkill in Quadrant IV: Low importance, strong performance
The attributes that are classified as ‘possible overkill’ are of low importance but high performance. The distribution of marginal resources is based on attributes that are minor assets and have a minimal impact on the overall competitiveness of the festival or event (Azzopardi & Nash, 2013). Attendees at the festival assigned minimal significance to these attributes; suggesting that there may be a potential squandering of scarce resources that are being utilised inefficiently and could be redirected (Draper, 2018; Sever, 2015).
Despite the IPA method originally being established for advertising purposes, its applicability has expanded to include various industries, including tourism (Azzopardi & Nash, 2013; Coghlan, 2012; De Nisco et al., 2015; Deng & Pierskalla, 2018; Draper, 2018; Dwyer et al., 2012; Ngwenya et al., 2023; Taplin, 2012), food services (Pratt et al., 2020; Sampson & Showalter, 1999; Tontini & Silveira, 2007), education (Litvin & Powell, 2022; O’Neill & Palmer, 2004; Phadermrod et al., 2019), motor repair services (Boshoff, 1986), healthcare (Abalo et al., 2007; Yavas & Shemwell, 2001), banking (Joseph et al., 2005; Yu, 2008), airlines (Chao et al., 2013) public administration (Van Ryzin & Immerwahr, 2007), information technologies (Skok et al., 2001) holiday destinations (De Nisco et al., 2015) and winery visits (Haverila et al., 2021).
Assessing satisfaction at a craft beer festival
Festivals form a significant part of the world’s leisure industry and are becoming increasingly important to society and the economy. As a result, festival organisers and festival experts rely heavily on information pertaining to attendees and their spending behaviour (Wong et al., 2015). Apart from the financial side, there is also a need for a better understanding of attendee satisfaction. What the attendees want, their previous experiences and how they respond to marketing messages all play a role (Haverila et al., 2021). For example, Rajaguru and Hassanli (2018) state that the expectancy-disconfirmation theory of Oliver (1980) is one of the best ways to explain the connection between the calibre of service and the level of customer satisfaction. The comparison can be evaluated using this theory to assess the comparison between what a customer would expect and the perceived service actually received. This theory serves as the foundation of service quality research and the hypothesis that a higher level of service perception when compared to preconceived expectations would lead to satisfaction (Hermann & Nemaorani, 2023). Most of the time, a positive or negative opinion of the event is formed by comparing expectations and perceptions (Rajaguru & Hassanli, 2018). The level of satisfaction could change because of factors that cannot be controlled, such as how good the service is seen to be perceived by others, how visitors feel, social interactions and other events (Koo et al., 2014; Liu et al., 2024). Some factors relating to an event that can be changed are its location, staff, parking, effective queue management, the variety and quality of food and beer, the price of the ticket and the quality of the event programme (Yuan & Jang, 2008), which includes entertainment such as live shows and demonstrations. These factors affect how satisfied people are and how likely they are to recommend and return to the event (Hattingh & Swart, 2016).
Torres (2014) and Hall et al. (2016) argue that festivals can only succeed if they provide high-quality service to their attendees, and that researchers and festival organisers should be cognisant of service quality and customer satisfaction to improve the experience they offer attendees. As the advent of the service quality theory in the early 1980s (Collins, 2017), the correlation between high-quality service, satisfied customers and repeat business has been the subject of much research in the field of tourism. Perhaps the best-known tool for gauging perceptions of service quality is the SERVQUAL instrument, developed by Parasuraman et al. (1988). This instrument measures the perceptions of service quality based on the variables reliability, assurance, tangibility, empathy and responsiveness. Customers’ impressions, according to Bowdin et al. (2011, p. 387), ‘are based on the technical (performance outcomes) and functional (process-related) qualities of the experience’, which implies that SERVQUAL’s functional areas of concern are where satisfaction with service quality should be prioritised. Destination marketing, which influences consumer purchases, relies heavily on customer satisfaction (Pizam et al., 2016; Torres, 2014; Welthagen and Lötter, 2020). Torres (2014) and Pizam et al. (2016) assert that Oliver’s (1980) expectation-disconfirmation model forms the theoretical foundation of the phenomenology of customer satisfaction. The expectations (E) and evaluation (P) of the festival service provider are both measured by the SERVQUAL model, which is based on the disconfirmation paradigm, and are useful for identifying service gaps and areas for service improvement.
To enhance the quality and keep customers content, numerous researchers (Cole & Chancellor, 2009; Tkaczynski & Stokes, 2010; Yoon et al., 2010) have evaluated the festival quality dimensions, which are made up of several service attributes. Welthagen and Lötter (2020) propose, however, that a deeper investigation into festival satisfaction is required. According to Tanford and Jung (2017), customer satisfaction is an aggregate rating of the quality of the product or service received. It is generally accepted that enhancing the quality of a product or service would boost customer satisfaction, which, in turn, would increase the likelihood of various positive outcomes (Yoon et al., 2010), such as repeat business, revenue, market share, favourable recommendations and product combinations (Hermann & Nemaorani, 2023). With a deeper understanding of the elements and factors affecting perceived service quality, there is a greater ability for service providers, specialists and marketers to improve the festival’s quality (Wong et al., 2015). Once this has been achieved, it is possible to earn repeat business from satisfied attendees.
Research design and methodology
This study adopted a quantitative methodological approach rooted in the positivist paradigm of social sciences, aiming to examine the relationship between festival attendees’ satisfaction and perceived service quality attributes at the CCBF. The methodology was structured around the application of IPA, which facilitated the dual measurement of the importance and performance of various festival attributes, as well as the overall satisfaction levels of respondents.
Data were collected through a structured, self-administered questionnaire distributed onsite during the festival (18 June 2022). Items in the questionnaire were derived from an extensive literature review on food festival service quality, drawing on validated instruments from studies including Hattingh and Swart (2016), Mason and Paggiaro (2012), Smith and Costello (2009) and Hermann et al. (2021). These sources informed the development of a list of festival attributes aligned with the SERVQUAL dimensions to evaluate service quality.
The survey instrument comprised four sections. Section A captured socio-demographic and behavioural data, including gender, age, home language, marital status, employment status and place of residence. Section B assessed the perceived importance of a set of festival attributes using a 5-point Likert scale (1 = Not important, 5 = Very important). Section C evaluated respondents’ satisfaction with the festival features, grouped into five categories: personnel, live entertainment, site features, facilities and services, and pricing, also using a 5-point Likert scale (1 = Very dissatisfied, 5 = Very satisfied). Section D measured overall satisfaction and motivations for attendance using multiple-choice formats.
Data collection was conducted by trained students from Tshwane University of Technology University, who administered the questionnaires in designated festival areas during the event. Convenience sampling was used, targeting festivalgoers who were willing to participate. Prospective respondents were briefed on the study’s objectives, assured of confidentiality and informed of their right to voluntary participation. Of the 400 questionnaires distributed during the festival, 313 were deemed valid for analysis, thanks to full completion. Based on the reported attendance of approximately 7000 patrons, a minimum representative sample size of 364 was calculated in accordance with the recommendations of Jennings (2010). Although the final sample fell slightly below this threshold, the number of valid responses was substantial, reliable based on Cronbach’s alpha scores, and provided a meaningful basis for analysis.
Data analysis involved two stages. Firstly, descriptive statistics were used to summarise importance and satisfaction ratings. Secondly, quartile regression analysis, Wilcoxon signed rank test and Spearman’s correlation were performed to determine the significance of each festival attribute in influencing satisfaction. The IPA framework proposed by Martilla and James (1977) was used to evaluate performance gaps across the identified attributes. The reliability of the instrument was confirmed through Cronbach’s alpha, with all tested constructs exceeding the acceptable threshold of 0.70, indicating internal consistency (Field, 2013).
Ethical considerations
Ethical approval to conduct this study was obtained from the Tshwane University of Technology Faculty of Management Sciences Research Ethics Committee (No. FCRE2022/FR/05/014-MS (2)).
Results
Sample profile results
The findings revealed an equal (50/50%) split between male and female respondents and that a significant portion of the respondents fell in the age range of 33–42 years. Most respondents indicated that their home language was Afrikaans (44.09%) and that they resided in Pretoria. Furthermore, the results indicated that most of the respondents (66.13%) were employed full-time. Most respondents (38.66%) indicated that their annual income was between R0 and R100 000, ranging from R10 000 to R30 000 per month. The majority of respondents were visiting the event for the first time, while most attended the festival with friends or family (54.95%). The respondents had mostly heard about the festival through social media (46.33%), while most indicated that their reasons for attending the festival were to spend time with family and friends (30.35%), followed by those who went there to listen to and enjoy live music (25.56%).
Importance-performance analysis results
In all, 27 service attributes were measured, summarised and interpreted using the IPA framework to determine their contribution to customers’ dissatisfaction or satisfaction. Table 1 displays the mean importance and performance ratings of these attributes as well as a descriptive comparison between the means. The P-I score (performance minus importance) displays a descriptive gap. Cronbach’s alpha scores range between 0.81 and 0.97, indicating a high internal consistency and reliability of the data.
| TABLE 1: Mean differences between importance and performance attributes. |
The importance-performance grid for the 27 festival attributes is displayed in Figure 2. The grid is divided into five dependent variables, which are as follows: pricing (18–21), staff (22–27), live entertainment (1–5) and site elements (6–12), amenities and services (13–17). Although the characteristics are presented in this order in Table 1, they were arranged in a random order in the questionnaire. The outcomes of the data analysis are presented descriptively in Table 1. The gap analysis measured the average performance deficit by comparing the average importance. When the average performance is higher than the average importance, a positive gap results. When the gap between mean performance and mean importance is negative, however, event organisers and administrators should act.
 |
FIGURE 2: Importance-performance analysis results. |
|
As seen from Table 1, the following festival attributes received positive gaps: Sticking to the programme schedule (P > I gap = –0.278), promptness of artists (P > I = –0.252), variety of music (P > I = –0.093), availability of staff (P > I = –0.019), and control of alcohol (P > I = –0.016). These results, highlighted in Table 1, indicate that the mean performance of these attribute items exceeded the mean importance from the results obtained from respondents of the event. Management should strive to keep the festival’s qualities performing at their current level because the findings show that they are functioning well in these areas. Table 1 further indicates that the following festival attributes received negative gaps: Adequate seating and spacing (P < I = 0.211), toilet cleanliness (P < I = 0.201), food and beverage availability (P < I = 0.166), overall safety and security (P < I = 0.153), and food and beverage variety (variety of beer/brewery) (P < I = 0.150). These results show that the mean importance is lower than the mean performance, which means that the recommendation about these attributes to CCBF management is that they signify a waste of scarce resources that are used inefficiently and might be reassigned elsewhere.
Crosshairs (vertical and horizontal lines) then separate this gap analysis map into four sections, each of which reveals a unique result (Figure 2). The ability to portray the results of an IPA graphically on a two-dimensional grid that is simple to understand is one of the attractive attributes of this type of study. The 27 attribute ratings for Table 1 are represented as 27 points on the importance-performance grid that is shown in Figure 2. The statistics are relative to the characteristics that are presented in Table 1. Marketing efforts are referred to by the labels that are placed on the quadrants A, B, C and D. An example of this would be the phrase ‘Concentrate here’, which refers to a region (A) in which qualities are significant and also where performance can show improvement. Concentrating constructive action in this one area would result in the best possible outcomes.
The 27 items were plotted on the IPA matrix (Figure 2) after collecting the implicitly derived importance and satisfaction performance of all tourism satisfaction variables. The grid was based on the average importance and performance scores. The ‘Keep up the good work’ quadrant contained 15 attributes, as illustrated in Table 2 and Figure 2. These attributes indicate that both the importance and performance of these attributes were high; these are the strengths of the festival. These attributes include responsiveness of staff, availability of staff, friendliness of staff, promptness of staff, reliability of staff, efficiency of staff, sound quality, quality of artists or entertainers, adequate signage and communication, overall safety and security, food and beverage availability, food and beverage variety, hygiene and/or cleanliness, control of alcohol and food and beverage quality. The ‘Concentrate here’ quadrant captured only three attributes (toilet cleanliness, availability and food and beverage prices). These indicate that the importance exceeds the perception of performance. The eight attributes in the ‘Low priority’ quadrant, which represents the attributes that respondents rated as matching the importance, but not exceeding it by a significant margin, include the (variety of music, promptness of artists, quality of viewing, adequate seating and spacing, parking availability, entrance ticket prices, parking price and vendor, exhibit and crafts prices). Sticking to the programme schedule is the only attribute included in the ‘Possible overkill’ quadrant.
| TABLE 2: Importance-performance analysis matrix of festival attributes. |
Although most of the elements related to service quality fall in either Quadrant B or C, both of which have some correlation between importance and performance, the actual importance and performance ratings should be investigated. Qualities that fall in Quadrant B show how well the festival met the guests’ expectations for performance in the areas they thought important. Those qualities stand for significant advantages and a competitive edge that must be preserved.
The qualities in Quadrant C are seen as minor deficiencies that do not necessarily call for additional work if better performance is not attained. These traits also represent an urgent danger from competitors. The items in the other quadrants also require close inspection before being categorised as performing satisfactorily or unsatisfactorily. On closer inspection, several problem areas were revealed.
In order to further analyse the results and to determine whether any significant gaps existed in service delivery, a regression analysis, Wilcoxon signed rank test, and Spearman’s rank order correlation were conducted, as depicted in Table 3.
Quantile regression (QR) was used to examine the relationship between the independent variables, importance and performance, and the dependent variable comprising 27 festival attribute items. Quantile regression offers a robust alternative to traditional least squares regression by enabling analysis across the entire conditional distribution of the dependent variable, not merely its mean (Shasha et al., 2022). This approach is particularly effective in uncovering relationships at various quantile levels, capturing a broader range of potential impacts (Davino et al., 2014). Table 3 presents the QR model outputs, reporting the 50th percentile (median), interquartile range (P25 – P75), and the range of observed values. The subsequent section details QR findings specific to attendees’ evaluations of the CCBF’s performance attributes. These results precede and are complemented by an IPA, offering a comprehensive view of the determinants of attendee satisfaction.
To assess the discrepancies between perceived importance and performance of festival attributes, the Wilcoxon signed rank test was used. This non-parametric test is appropriate for large paired samples (n > 10) and does not assume a normal distribution (Chatterjee & Suklabaidya, 2021). It evaluates whether median differences exist between paired observations without relying on the assumption of normality (Harris & Hardin, 2013). Table 3 presents the test results, including Z-scores and two-tailed p-values.
The analysis revealed that most paired comparisons yielded statistically significant results (p < 0.05), with the exception of performance versus importance for price-related variables and for staff attributes. Significant Z-scores ranged between –3.748 and 0.479, exceeding the critical threshold of ± 1.645 for a 95% confidence interval, thus leading to the rejection of the null hypothesis for most attributes. The notable exceptions – price and staff – did not show significant discrepancies, suggesting minimal perception gaps in these areas.
Attributes related to live entertainment, site elements and amenities and services exhibited statistically significant differences between importance and performance (Z > 1.645), indicating meaningful perception gaps. Despite these differences, the overall magnitude of the effect was small, suggesting that the CCBF generally met attendee expectations. This implies that the event delivery closely aligns with what attendees consider important.
In addition to the Wilcoxon analysis, Spearman’s rank order correlation was used to explore the relationship between attendee satisfaction and various festival attributes. This non-parametric technique is ideal for assessing ordinal relationships without normality assumptions (Astivia & Zumbo, 2017). The correlation analysis was computed based on the range of Pearson correlation coefficient (r) strengths presented next. The Pearson correlation coefficient measures the linear correlation between two variables, X and Y. The coefficient can range from –1 to +1, where –1 indicates a perfect negative linear correlation, 0 means no linear correlation, and +1 indicates a perfect positive linear correlation. The interpretation of Pearson correlation coefficient values is as follows: no correlation: a value of zero implies no relationship; low degree: 0.00 – 0.199 = very weak correlation; 0.20 – 0.399 = weak; 0.40 – 0.599 = moderate; high degree: 0.60 – 0.799 = strong; 0.80 – 1.000 = very strong (Astivia & Zumbo, 2017). Table 3 presents Spearman’s rho values, revealing significant positive correlations across most attribute dimensions:
- Live entertainment: Importance variables and overall satisfaction had a moderate correlation (r = 0.48, p = 0.001) between satisfaction and variables such as sound quality, artist performance, variety of music, promptness, and adherence to the schedule. This indicates that enhancing live entertainment features could further boost overall satisfaction. The live entertainment construct which includes importance variables and overall satisfaction exhibited a moderate correlation, but statistically significant association was reported (r = 0.48, p = 0.001). The organisers should make sure that they provide high-quality live entertainment as a top priority. The beer festival would be more enjoyable for everyone if this were to happen.
- Site elements: Weak but statistically significant correlations (r = 0.41, p = 0.001) were found for signage, parking, toilet facilities, seating, and safety. These findings suggest that although their direct impact on satisfaction is limited, high-quality site elements are vital for shaping positive experiences. The site elements construct demonstrated a weak but statistically significant correlation (r = 0.41, p = 0.001). These findings suggest that although the direct impact of high-quality site elements on satisfaction is limited, they are vital for shaping positive experiences.
- Amenities and services: This dimension also showed a moderate correlation (r = 0.48, p = 0.001), covering food and beverage availability, variety of offerings, and brewery diversity. Ensuring excellence in amenities would likely improve overall event satisfaction. The amenities and services construct demonstrated a moderate correlation, and a significant association was observed (r = 0.48, p = 0.001), encompassing food and beverage availability, variety of offerings, and brewery diversity. Improvements in the amenities and services construct might be associated with changes in overall event satisfaction.
- The pricing construct exhibited a weak yet statistically significant correlation (r = 0.37, p = 0.001) for attributes including ticket pricing, parking fees, and vendor prices. Given the income profile of many attendees, careful pricing strategies are essential for maintaining affordability and satisfaction.
- For staff attributes (r = 0.39, p = 0.001) a modest yet statistically significant correlation was reported for staff responsiveness, friendliness, and reliability. While staff-related factors were not perceived as highly divergent in importance and performance, they remained influential in shaping the attendee experience. Overall, the correlation findings affirmed that attendee satisfaction was significantly associated with the importance attached to various festival attributes. While some dimensions exhibited only moderate or weak correlations, all were statistically significant, underscoring their collective contribution to the perceived success of the event. The evidence suggests that CCBF organisers largely succeeded in aligning festival delivery with participant expectations, although targeted improvements in entertainment quality, site infrastructure, and service provision could enhance overall outcomes.
Implications for the Capital Craft Beer Festival management
The findings of this study generated several suggestions for enhancing the sustainability of the CCBF. To increase visitor retention, the organisers should strengthen digital customer relationship management through their website. This includes integrating an online feedback mechanism, promotional campaigns, loyalty programmes and regular e-newsletters. The facilitation of ticket purchases via the official website or linking to a secure external platform, alongside features such as Google Maps navigation, virtual tour videos and information on safety protocols, would improve the user experience. In addition, reservation systems for both attendees and vendors, and information on community engagement initiatives, would enhance transparency and accessibility.
Given the socio-economic diversity of the attendees, it is essential to maintain affordable pricing. Organisers are advised to avoid excessive price increases while considering differentiated ticketing strategies – such as bundling entry with premium amenities (e.g., food, beverages, VIP access) – to appeal to higher-income segments without alienating core patrons.
Site infrastructure significantly influences attendee satisfaction. Parking, in particular, warrants attention, as most visitors arrive in private vehicles. Expanding parking availability and promoting alternatives like the Gautrain could alleviate pressure. Social media remains the most effective promotional channel, reflecting the influence of peer recommendations. On the other hand, traditional media (radio, television, print) has a minimal impact. To retain the existing market and grow others, especially in Gauteng, targeted advertising through Afrikaans-language platforms, such as Jacaranda FM, is recommended.
The festival experience could be further improved by enhancing the live entertainment components. Sound quality, programming coherence, and artist scheduling directly impact attendee satisfaction. While staff-related aspects were not the most critical to satisfaction levels, they remain important to the overall experience. Thus, continuous investment in staff training, responsiveness, and professionalism is essential.
Collectively, these strategies could assist festival organisers in aligning service delivery with visitor expectations, thereby fostering long-term event viability and growth.
Conclusion, research limitations and future research
This study contributes to the growing body of literature on the relationship between customer expectations and perceptions of festival attributes. Drawing on data from 313 attendees at the CCBF in Pretoria, South Africa, the study applied IPA to assess service delivery and attendee satisfaction. It represents the first known quantitative application of the IPA framework to a beer festival, and the first at any festival event in Africa. The high reliability coefficients confirm IPA’s suitability for evaluating service dimensions in festival contexts, particularly in the craft beer industry. Future research in this domain might benefit from the newly developed service quality metric derived from this study’s findings.
While previous studies aimed to develop broad service evaluation tools for culinary festivals, this research emphasised specific dimensions that are relevant to the beer festival context. Those attributes were informed by earlier work by Hattingh and Swart (2016), Mason and Paggiaro (2012), Smith and Costello (2009) and Hermann et al. (2021). The integration of beer, a consumable product central to the festival experience, distinguishes this festival from other events such as art festivals, which often emphasise educational or cultural enrichment. The five key constructs evaluated were live entertainment, site elements, facilities and services, pricing and staff.
The operationalisation of these constructs revealed that staff performance was paramount to overall satisfaction. Attendees identified staff responsiveness and approachability, and service reliability as essential. A deficiency in this area detracts from the festival experience, potentially outweighing positive evaluations in other areas. This aligns with Slevitch and Oh’s (2010) assertion that ‘must-be’ attributes have a disproportionate influence on customer satisfaction. Supporting findings from Smith and Holmes (2012), this study underscores the importance of employing staff who are knowledgeable about both the festival and local tourism offerings. Encouraging staff to attend related events may enhance their engagement and capacity to assist visitors effectively.
Other priority attributes include high sound quality, stringent safety measures, hygiene standards and control of underage alcohol consumption. Attendees also emphasised the importance of value-for-money pricing across all categories; entrance, food and beverages, vendor offerings, parking and related services. Interestingly, musical aspects such as artist promptness, quality and variety were rated as less critical. Parking access emerged as a key concern, given that most attendees travel by private vehicle. Future events should consider expanding parking facilities and promoting alternative transportation options, such as the Gautrain, to improve accessibility.
The Kruskal–Wallis equality-of-populations rank test indicated that several constructs significantly shaped perceptions of festival attributes. Although cross-festival generalisations are complex because of variation in context, this study offers a practical framework for festival evaluation. By aligning services with the expectations of diverse visitor segments, organisers can enhance experiences, strengthen local engagement, and support regional economic development.
The results further suggested that nearly all evaluated attributes were considered important by attendees, reflecting high expectations. While the organisers appeared to meet these expectations in many areas, resource allocation should prioritise attributes with the greatest performance gaps. Such targeted improvements may strengthen both attendee satisfaction and long-term event sustainability.
Several limitations of the study must be acknowledged. The use of convenience sampling restricts the generalisability of findings beyond the sample. Intoxication among respondents later in the day also compromised data quality, as did the perceived complexity and length of the questionnaire. Future research would benefit from administering simplified online surveys to increase completion rates and reduce fatigue-related bias. Furthermore, the time-intensive nature of data collection across the event duration may have affected the quality of responses. Finally, the study was limited to one craft beer festival in South Africa. To improve the generalisability and robustness of the model, future research should replicate this study across multiple festivals in various regions. Broader geographic sampling would allow for comparisons across event types and audience profiles, helping to refine theoretical models and inform evidence-based festival management practices.
Acknowledgements
The authors wish to sincerely thank the individuals and organisations listed below. This study would have not been feasible without their kind help and cooperation. The authors would like to express their gratitude to Mr Johan Auriocombe, as well as special thanks to Mrs Cathy Dippnall for language and editing. Mrs Tshifhiwa Nemaorani for statistical assistance and Professor T.I. Mogashoa for patience and words of encouragement.
This article is based on research originally conducted as part of Mzwake Muzi Masombuka’s master’s thesis titled ‘Attendee satisfaction at the Capital Craft Beer Festival: An Importance-Performance Analysis’, submitted to the Faculty of Management Sciences, Tshwane University of Technology in 2022. The thesis was supervised by Dr L.C. Welthagen and Prof. U.P. Hermann.
Competing interests
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
Authors’ contributions
M.M.M. was the main researcher and compiled the project and wrote the manuscript. L.C.W. supervised the project, co-wrote the manuscript and was responsible for experimental and project design. U.P.H. made conceptual contributions and experimental and project design. All authors contributed to the article, discussed the results and approved the final version for submission and publication.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The data that support the findings of this study are available from the corresponding author, M.M.M., upon reasonable request.
Disclaimer
The views and opinions expressed in this article are those of the authors and are the product of professional research. The article does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or the publisher. The authors are responsible for this article’s results, findings and content.
References
Abalo, J., Verela, J., & Manzano, V. (2007). Importance values for importance-performance analysis: A formula for spreading out values derived from preference rankings. Journal of Business Research, 60(2), 115–121. https://doi.org/10.1016/j.jbusres.2006.10.009
Astivia, O.L.O., & Zumbo, B.D. (2017). Population models and simulation methods: The case of the Spearman rank correlation. British Journal of Mathematical and Statistical Psychology, 70(3), 347–367. https://doi.org/10.1111/bmsp.12085
Azzopardi, E., & Nash, R. (2013). A critical evaluation of importance–performance analysis. Tourism Management, 35, 222–233. https://doi.org/10.1016/j.tourman.2012.07.007
Bachman, J.R., Hull, J.S., & Marlowe, B. (2021). Non-economic impact of craft brewery visitors in British Columbia: A quantitative analysis. Tourism Analysis, 26(2–3), 151–165. https://doi.org/10.3727/108354221X16079839951439
Baiano, A. (2021). Craft beer: An overview. Comprehensive Reviews in Food Science and Food Safety, 20(2), 1829–1856. https://doi.org/10.1111/1541-4337.12693
Beckman, E., Shu, F., & Pan, T. (2020). The application of enduring involvement theory in the development of a success model for a craft beer and food festival. International Journal of Event and Festival Management, 11(4), 397–411. https://doi.org/10.1108/IJEFM-01-2020-0002
Boshoff, C. (1986). Importance-performance analysis: A comparative study of motor repair service customers. South African Journal of Business Management, 17(4), 196–201. https://doi.org/10.4102/sajbm.v17i4.1056
Bowdin, G., Allen, J., O’Toole, W., Harris, R., & McDonnell, I. (2011). Events management (3rd ed.). Butterworth-Heinemann.
Cabras, I. (2021). Craft beers and breweries in the United Kingdom: Where now, what next? In Case studies in the beer sector, Ignazio (pp. 37–48). Woodhead Publishing.
Cabras, I., Lorusso, M., & Waehning, N. (2020). Measuring the economic contribution of beer festivals on local economies: The case of York, United Kingdom. International Journal of Tourism Research, 22(6), 739–750. https://doi.org/10.1002/jtr.2369
Cai, R., & Chi, C.G.Q. (2021). Pictures vs. reality: Roles of disconfirmation magnitude, disconfirmation sensitivity, and branding. International Journal of Hospitality Management, 98(103040), 303–320. https://doi.org/10.1016/j.ijhm.2021.103040
Chao, C.C., Lirn, T.C., & Shang, K.C. (2013). Market segmentation of airline cargo transport. Service Industries Journal, 33(15–16), 1672–1685. https://doi.org/10.1080/02642069.2011.638920
Chatterjee, S., & Suklabaidya, P. (2021). Gap between perception and satisfaction: Exploring food tourism in New York. International Journal of Hospitality and Tourism Systems, 14(1), 90–97.
Chirakranont, R., & Sunanta, S. (2021). Applications of experience economy in craft beer tourism: A case study in Thailand’s context. Sustainability, 13(18), 10448. https://doi.org/10.3390/su131810448
Coghlan, A. (2012). Facilitating reef tourism management through an innovative importance-performance analysis method. Tourism Management, 33(4), 767–775. https://doi.org/10.1016/j.tourman.2011.08.010
Cole, S.T., & Chancellor, H.C. (2009). Examining the festival attributes that impact visitor experience, satisfaction and re-visit intention. Journal of Vacation Marketing, 15(4), 323–333. https://doi.org/10.1177/1356766709335831
Collins, A. (Ed.) (2017). Service quality (SQ): Perspectives management and improvement strategies (pp. 1–20). Novinka.
Davino, C., Furno, M., & Vistocco, D. (2014). Quantile regression: Theory and applications. John Wiley and Sons.
De Nisco, A., Riviezzo, A., & Napolitano, M.R. (2015). An importance-performance analysis of tourist satisfaction at destination level: Evidence from Campania (Italy). European Journal of Tourism Research, 10, 64–75. https://doi.org/10.54055/ejtr.v10i.179
Deng, J., & Pierskalla, C.D. (2018). Linking importance-performance analysis, satisfaction, and loyalty: A study of Savannah, GA. Sustainability, 10(3), 704. https://doi.org/10.3390/su10030704
Draper, J. (2018). Applying importance-performance analysis to services of a visitor information center. Tourism and Hospitality Research, 18(1), 84–95. https://doi.org/10.1177/1467358415627300
Dunn, A., & Wickham, M. (2016). Craft brewery tourism best-practices: A research agenda. Annals of Tourism Research, 56, 140–142. https://doi.org/10.1016/j.annals.2015.10.009
Dwyer, L., Cvelbar, L.K., Edwards, D., & Mihalic, T. (2012). Fashioning a destination tourism future: The case of Slovenia. Tourism Management, 33(2), 305–316. https://doi.org/10.1016/j.tourman.2011.03.010
Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage.
Garavaglia, C., & Swinnen, J. (Eds.) (2018). Economics of the craft beer revolution: A revolution in the global beer industry (pp. 3–51). Palgrave MacMillan.
Hall, S., Oriade, A., & Robinson, P. (2016). Assessing festival attendees’ behavioral intentions through perceived service quality and visitor satisfaction. Event Management, 20(1), 27–40. https://doi.org/10.3727/152599516X14538326024955
Harris, T., & Hardin, J.W. (2013). Exact Wilcoxon signed-rank and Wilcoxon Mann-Whitney rank sum tests. Stata Journal, 13(2), 337–343. https://doi.org/10.1177/1536867X1301300208
Hattingh, C., & Swart, K. (2016). The motives for visitors to attend a food and wine event in Cape Town and their satisfaction levels. African Journal of Hospitality, Tourism and Leisure, 5(2), 1–14.
Haverila, M., Haverila, K., & Twyford, J.C. (2021). Identification of key variables and constructs in the context of wine tasting room: Importance-performance analysis. International Journal of Wine Business Research, 33(1), 80–101. https://doi.org/10.1108/IJWBR-02-2020-0006
Hermann, U.P., Boshoff, L., & Ncala, T.T. (2019). Understanding beer festival attendee motivations to a craft beer festival in South Africa. Journal for New Generation Sciences, 17(2), 18–30.
Hermann, U.P., Lee, C., Coetzee, W., & Boshoff, L. (2021). Predicting behavioural intentions of craft beer festival attendees by their event experience. International Journal of Wine Business Research, 33(2), 254–274. https://doi.org/10.1108/IJWBR-05-2020-0019
Hermann, U.P., & Nemaorani, T.M. (2023). Determination of visitors’ intentions to revisit a natural history museum in a national park. Koedoe-African Protected Area Conservation and Science, 65(1), 1769. https://doi.org/10.4102/koedoe.v65i1.1769
Ho, J.M., Tiew, F., & Adamu, A.A. (2022). The determinants of festival participants’ event loyalty: A focus on millennial participants. International Journal of Event and Festival Management, 13(4), 422–439. https://doi.org/10.1108/IJEFM-01-2022-0006
Howlett, S. (2013). Bureaus and beer: Promoting brewery tourism in Colorado. MSc dissertation. University of Nevada.
Ikäheimo, J. (2020). Exclusive craft beer events: Liminoid spaces of performative craft consumption. Food, Culture & Society, 23(3), 296–314. https://doi.org/10.1080/15528014.2020.1741065
Jennings, G. (2010). Tourism research (2nd ed.). John Wiley and Sons.
Joseph, M., Allbright, D., Stone, G., Sekhon, Y., & Tinson, J. (2005). Importance-performance analysis of UK and US bank customer perceptions of service delivery technologies. International Journal of Financial Services Management, 1(1), 66–88. https://doi.org/10.1504/IJFSM.2005.007985
Koo, S.K.S., Byon, K.K., & Baker, T.A., III. (2014). Integrating event image, satisfaction, and behavioral intention: Small-scale marathon event. Sport Marketing Quarterly, 23(3), 59.
Litvin, S.W., & Powell, E. (2022). Festival attendees: A motivation and performance analysis of a young adult literature festival. Event Management, 26(4), 733–745. https://doi.org/10.3727/152599521X16367300695780
Liu, X., Zakaria, J., & Mohd Said, O.F. (2024). How event quality affects satisfaction and revisit intention from the theory of planned behaviour. South African Journal of Business Management, 55(1), 4727. https://doi.org/10.4102/sajbm.v55i1.4727
Maciel, A.F., & Wallendorf, M. (2017). Taste engineering: An extended consumer model of cultural competence constitution. Journal of Consumer Research, 43(5), 726–746. https://doi.org/10.1093/jcr/ucw054
Manis, K.T., Chang, H.J.J., Fowler, D.C., & Blum, S.C. (2020). Inaugural events and beer tourist behavior: Capitalizing on the craft beer movement. Event Management, 24(2–3), 311–334. https://doi.org/10.3727/152599519X15506259856525
Martilla, J.A., & James, J.C. (1977). Importance-performance analysis. Journal of Marketing, 41(1), 77–79. https://doi.org/10.1177/002224297704100112
Mason, M.C., & Paggiaro, A. (2012). Investigating the role of festival scape in culinary tourism: The case of food and wine events. Tourism Management, 33(6), 1329–1336. https://doi.org/10.1016/j.tourman.2011.12.016
Mikulić, J., Paunović, Z., & Prebežac, D. (2012). An extended neural network-based importance-performance analysis for enhancing wine fair experience. Journal of Travel & Tourism Marketing, 29(8), 744–759. https://doi.org/10.1080/10548408.2012.730936
Ncala, T.T. (2018). Visitor satisfaction at a craft beer festival. M. Tech. dissertation, Pretoria, Tshwane University of Technology.
Ngwenya, P.J., Hermann, U.P., & Welthagen, L.C. (2023). Assessing visitor satisfaction at a South African zoo by means of an importance-performance analysis. International Journal of Leisure and Tourism Marketing, 8(1), 36–52. https://doi.org/10.1504/IJLTM.2023.138751
Oliver, R.L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405
O’Neill, M.A., & Palmer, A. (2004). Importance-performance analysis: A useful tool for directing continuous quality improvement in higher education. Quality Assurance in Education, 12(1), 39–52. https://doi.org/10.1108/09684880410517423
Parasuraman, A., Zeithaml, V., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring customer perceptions of service quality. Journal of Retailing, 64(1), 12–40.
Phadermrod, B., Crowder, R.M., & Wills, G.B. (2019). Importance-performance analysis-based SWOT analysis. International Journal of Information Management, 44, 194–203. https://doi.org/10.1016/j.ijinfomgt.2016.03.009
Pizam, A., Shapoval, V., & Ellis, T. (2016). Customer satisfaction and its measurement in hospitality enterprises: A revisit and update. International Journal of Contemporary Hospitality Management, 28(1), 2–35. https://doi.org/10.1108/IJCHM-04-2015-0167
Pratt, S., Suntikul, W., & Agyeiwaah, E. (2020). Determining the attributes of gastronomic tourism experience: Applying impact-range performance and asymmetry analyses. International Journal of Tourism Research, 22(5), 564–581. https://doi.org/10.1002/jtr.2356
Rajaguru, R., & Hassanli, N. (2018). The role of trip purpose and hotel star rating on guests’ satisfaction and WOM. International Journal of Contemporary Hospitality Management, 30(5), 2268–2286. https://doi.org/10.1108/IJCHM-01-2017-0044
Rogerson, C.M., & Collins, K.J.E. (2015). Developing beer tourism in South Africa: International perspectives. African Journal of Hospitality, Tourism and Leisure, 4(1), 1–15.
Rogerson, C.M., & Collins, K.J.E. (2019). Entrepreneurs in craft beer and tourism: Perspectives from South Africa. Geo Journal of Tourism and Geosites, 27(4), 1158–1172. https://doi.org/10.30892/gtg.27404-423
Sampson, S.E., & Showalter, M.J. (1999). The performance-importance response function: Observations and implications. Service Industries Journal, 19(3), 1–25. https://doi.org/10.1080/02642069900000027
Sever, I. (2015). Importance-performance analysis: A valid management tool? Event Management, 48, 43–53. https://doi.org/10.1016/j.tourman.2014.10.022
Shasha, W., Nawaz Abbasi, B., & Sohail, A. (2022). Assessment of Olympic performance in relation to economic, demographic, geographic, and social factors: Quantile and Tobit approaches. Economic Research-Ekonomska Istraživanja, 36(1), 1–25. https://doi.org/10.1080/1331677X.2022.2080735
Skok, W., Kophamel, A., & Richardson, I. (2001). Diagnosing information systems success: Importance-performance maps in the health club industry. Information and Management, 38(7), 409–419. https://doi.org/10.1016/S0378-7206(00)00076-8
Slevitch, L., & Oh, H. (2010). Asymmetric relationship between attribute performance and customer satisfaction: A new perspective. International Journal of Hospitality Management, 29(4), 559–569. https://doi.org/10.1016/j.ijhm.2009.09.004
Smith, S., & Costello, C. (2009). Culinary tourism: satisfaction with a culinary event utilizing importance-performance grid analysis. Journal of Vacation Marketing, 15(2):99–110.
Smith, K.A., & Holmes, K. (2012). Visitor centre staffing: Involving volunteers. Tourism Management, 33, 562–568. https://doi.org/10.1016/j.tourman.2011.06.010
Smith, S., & Asirvatham, J. (2022). Rural craft beer tourism: Consumer attributes and regional economic impact. Journal of Gastronomy and Tourism, 6(3), 123–134. https://doi.org/10.3727/216929722X16354101932050
Smith, S., & Costello, C. (2009). Culinary tourism: Satisfaction with a culinary event utilizing importance-performance grid analysis. Journal of Vacation Marketing, 15(2), 99–110. https://doi.org/10.1177/1356766708100818
Sozen, E., & O’Neill, M. (2020). An exploration of quality service in brewing sector. Journal of Quality Assurance in Hospitality & Tourism, 21(1), 105–128. https://doi.org/10.1080/1528008X.2019.1619499
Stergiou, D.P. (2018). An importance-performance analysis of young people’s response to a wine tourism situation in Greece. Journal of Wine Research, 29(4), 229–242. https://doi.org/10.1080/09571264.2018.1532878
Stergiou, D.P., Airey, D., & Apostolakis, A. (2018). The winery experience from the perspective of Generation Z. International Journal of Wine Business Research, 30(2), 169–184. https://doi.org/10.1108/IJWBR-03-2017-0018
Stone, M.J., Garibaldi, R., & Pozzi, A. (2020). Motivation, behaviours, and travel activities of beer tourists. Tourism Review International, 24(2–3), 167–178. https://doi.org/10.3727/154427220X15912253254437
Tanford, S., & Jung, S. (2017). Festival attributes and perceptions: A meta-analysis of relationships with satisfaction and loyalty. Tourism Management, 61, 209–220. https://doi.org/10.1016/j.tourman.2017.02.005
Taplin, R.H. (2012). Competitive importance-performance analysis of an Australian wildlife park. Tourism Management, 33(1), 29–37. https://doi.org/10.1016/j.tourman.2011.01.020
Tkaczynski, A., Rundle-Thiele, S., Arli, D., & Gill, C. (2022). Going … going … going … not yet gone! Enhancing small-scale festival survival. Event Management, 26(3), 513–529. https://doi.org/10.3727/152599521X16288665119422
Tkaczynski, A., & Stokes, R. (2010). FESTPERF: A service quality measurement scale for festivals. Event Management, 14(1), 69–82. https://doi.org/10.3727/152599510X12724735767679
Tontini, G., & Silveira, A. (2007). Identification of satisfaction attributes using competitive analysis of the improvement gap. International Journal of Operations and Production Management, 27(5):482–500.
Torres, E.N. (2014). Deconstructing service quality and customer satisfaction: Challenges and directions for future research. Journal of Hospitality Marketing & Management, 23(6), 652–677. https://doi.org/10.1080/19368623.2014.846839
Van Ryzin, G.G., & Immerwahr, S. (2007). Importance-performance analysis of citizen satisfaction surveys. Public Administration, 85(1), 215–226. https://doi.org/10.1111/j.1467-9299.2007.00641.x
Viljoen, A., Kruger, M., & Saayman, M. (2018). The art of tastings: Enhancing the arts festival experience. International Journal of Event and Festival Management, 9(3), 246–265. https://doi.org/10.1108/IJEFM-03-2018-0023
Welthagen, L., & Lőtter, M.J. (2020). Examining the relationship between music festival attributes and attendee satisfaction. Journal for New Generation Sciences, 18(2), 56–69.
Wilkins, H. (2010). Using importance-performance analysis to appreciate satisfaction in hotels. Journal of Hospitality Marketing and Management, 19(8), 866–888. https://doi.org/10.1080/19368623.2010.514554
Wong, J., Wu, H.C., & Cheng, C.C. (2015). An empirical analysis of synthesizing the effects of festival quality, emotion, festival image and festival satisfaction on festival loyalty: A case study of Macau Food Festival. International Journal of Tourism Research, 17(6), 521–536. https://doi.org/10.1002/jtr.2011
Yavas, U., & Shemwell, D.J. (2001). Modified importance-performance analysis: An application to hospitals. International Journal of Health Care Quality Assurance, 14(3), 104–110. https://doi.org/10.1108/09526860110391568
Yoon, Y.S., Lee, J.S., & Lee, C.K. (2010). Measuring festival quality and value affecting visitors’ satisfaction and loyalty using a structural approach. International Journal of Hospitality Management, 29(2), 335–342. https://doi.org/10.1016/j.ijhm.2009.10.002
Yu, F.F. (2008). Analyst coverage and earnings management. Journal of Financial Economics, 88(2), 245–271. https://doi.org/10.1016/j.jfineco.2007.05.008
Yuan, J., & Jang, S. (2008). The effects of quality and satisfaction on awareness and behavioral intentions: Exploring the role of a wine festival. Journal of Travel Research, 46(3), 279–288. https://doi.org/10.1177/0047287507308322
|
Hide
Show all
Email this article (Login required)
