Abstract
Purpose
The purpose of this paper is to formulate and validate a measurement model to evaluate the service quality of cultural centers. This study aims to expand the domain of service quality measurement models by extending the SERVQUAL model to an alternative measurement tool called the ARTQUAL model based on three different preferences and scenarios including concert halls, theater halls and art galleries.
Design/methodology/approach
The data were collected from 15 cultural centers. Structural equation modeling (SEM) was utilized in the current research to study the association between aesthetic environments and service quality. An exploratory factor analysis took place to formulate the fundamentals of the measurement model. The validation process is based on a hybrid framework integrating the covariance-based SEM along with the partial least square technique to present a robust validity of the ARTQUAL model. Ultimately, an extensive managerial analysis has been established to show the practicality of the ARTQUAL model.
Findings
This study provides empirical evidence that the ARTQUAL instrument is proven to be valid, reliable and appropriate to evaluate the service quality of cultural centers. Based on the real-world managerial analysis, the ARTQUAL model showed a significant practicality in quality evaluation of aesthetic environments.
Research limitations/implications
One of the most important limitations of quantitative studies, based on aesthetic features, is the cultural preferences. This limitation is due to the nature of cultural preferences and partialities applied in different countries based on the definition of quality involving aesthetic aspects such as age, sex and culture. Meanwhile, the findings of this study can guide the service management experts to better understand and improve customers’ perceptions and orientations of service quality in aesthetic environments.
Originality/value
This paper presents a novel service quality measurement model in order to evaluate the service quality of cultural centers. The originality of the current study is not merely limited to the suggestion of a new quality measurement model, a hybrid statistical validation framework has been provided as well. Therefore, this study provides valuable guidelines to both practitioners and academics to enhance the quality of service measurements in cultural centers.
Keywords
Citation
Ijadi Maghsoodi, A., Saghaei, A. and Hafezalkotob, A. (2019), "ARTQUAL: A comprehensive service quality model for measuring the quality of aesthetic environments and cultural centers", International Journal of Quality & Reliability Management, Vol. 36 No. 9, pp. 1490-1521. https://doi.org/10.1108/IJQRM-01-2019-0004
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited
1. Introduction
One of the most strategic elements in competitive and dynamic organizations in the twenty-first century is the leadership of service. The subject of customer satisfaction is now at a critical importance level from the perspective of service industry (Ko and Chou, 2019; Kuo et al., 2018; Valencia-Arias et al., 2018). The substantial relationship between service quality and customer satisfaction has been extensively overviewed in various applications during the past few years (Kuo et al., 2018; Parasuraman et al., 2005). The SERVQUAL model is one of the most influential service quality measurement instruments, which has been developed from the gap model by Parasuraman et al. (Parasuraman et al., 1991; Valencia-Arias et al., 2018). The SERVQUAL model is still used in many applications and developments of service quality fields based on various implications considering further criticism by Cronin and Taylor (Cronin and Taylor, 1994; François et al., 2007).
The statement “[…] if one can explain music, thee may find the primary key for all human thoughts or in implying that failure in taking music seriously weakens any account of the human condition […]” by Claude Lévi-Strauss (Reimer and Palmer, 2002) reveals the importance of aesthetics in human interactions. Similar to other service providers such as banks, healthcare services, restaurants and hotels, the quality of services in cultural centers also has a remarkable influence on audience satisfaction. Consequently, aforementioned quality measurements are important for various individuals: first, audience: due to the limitations of budgets that people would spend on events such as performing arts, it is the customers’ priority to attend the event with the highest quality. Second, artist(s): one of the most critical factors for artists is to select the location for presenting their arts and crafts. Almost every artist challenges the problem of selecting a performing location which could help them shine their brightest light. Third, managers and art directors: one of the main goals of any service provider is to satisfy customers. As mentioned above, if cultural centers were to be considered as service providing organizations, it would be important for managers to gain the most optimal satisfaction from the customers. These measurements could be obtained via service quality measurement models. Although there is a wide variety of research regarding service quality models considering applications and developments in the past few years, it is expected to see at least few types of research concerning quality in artistic research (Lagrosen and Lagrosen, 2017). Surprisingly, there are very few studies available overviewing such environments and activities. The primary purpose of this study is to present a comprehensive instrument to measure the service quality of cultural centers, which is called the ARTQUAL model. There is not a single study that has tackled such problem regarding quality of service in cultural centers. This research examines three types of cultural centers including concert halls, theater halls and art galleries with the ARTQUAL measurement model considering aesthetic factors along with managerial criteria. Aspects of the ARTQUAL model have been obtained based on an in-depth exploration of the previous literature on the service quality and the soul concept of quality in performing arts along with aesthetic presentations. A statistical modeling has been carried out with the application of structural equation modeling (SEM) considering partial least square (PLS) approach and covariance-based SEM (CB-SEM) along with the factor analysis method to present a valid structure and confirm the basic foundations of the ARTQUAL model.
The remainder of the present paper is prepared as follows. A comprehensive literature review and explanation of the research gap are demonstrated in Section 2. The proposed research methodology is described in Section 3. Furthermore, Section 4 presents findings and results on the application of ARTQUAL in multiple scenarios in cultural centers. Section 5 demonstrates multiple managerial insights based on the ARTQUAL instrument as well as real-world case studies. Finally, Section 6 presents conclusions and recommendations for the further research.
2. Literature review
2.1 Survey on applications and developments of service quality measurement models
“Conformity” and “product specifications” are just a few of many terms that could be found in the literature of quality in a product. Searching through the quality of product literature results in discovery of an extensive research background. However, in-depth overview of the service quality literature shows that the previous research on the service quality is very limited. The reason for this condition is the modality, consumption and evaluation of the service (Galeeva, 2016; Parasuraman et al., 1994). Parasuraman et al. (1985) suggested the gap model containing ten aspects of service quality which give rise to developments of the SERVQUAL instrument covering five aspects (dimensions) of service quality consisting of tangibles, reliability, responsiveness, assurance and empathy. Aspects of the five-dimensional SERVQUAL model are demonstrated in Table I.
There are many developments that have been applied to the SERVQUAL model considering various applications since 1988. Cronin and Taylor (1992) developed the SERVPERF model based on the service performance consisting of 22 questions similar to SERVQUAL instrument. However, SERVQUAL model measures the quality of the provided service in comparison with the perception of the quality from the customers’ perspective. Consequently, the SERVPERF model only measures the service quality performance based on customers’ perspective. Rodrigues et al. (2011) proposed a comparison of SERVQUAL and SERVPERF models based on the application of these two metrics in an empirical study. Dabholkar et al. (1996) developed the Retail Service Quality Scale (RSQS) based on the SERVQUAL model which includes 5 dimensions and 28 questions. The proposed instrument by Dabholkar et al. has been validated with a confirmatory factor analysis (CFA) via a partial disaggregation technique. Leen and Ramayah (2011) proposed a statistical validation of the RSQS model based on the Malaysian business setting in the northern region of Malaysia considering the fashion and clothing industry. Stevens et al. (1995) developed the DINESERV model including 29 items within 5 aspects to measure the service quality of restaurants based on customers’ perception. Keith and Simmers (2011) proposed a comparison measuring the service quality perceptions of the restaurant experience based on the difference between comment cards and DINESERV instrument in 82 major chain restaurants of the USA. Evidently, there are extensive areas of research regarding service quality models in various domains (Dopeykar et al., 2018; Javed and Ilyas, 2018; Mazzawi and Alawamleh, 2019; Ramanathan et al., 2018; Valencia-Arias et al., 2018; Zun et al., 2018).
Unfortunately, in the lights of the fact that cultural centers are considered as organizations that provide services, analysis of such environments shows a narrow and limited area of research in the previous literature. Tkaczynski and Stokes (2010) created the FESTPERF measurement model based on extension of the SERVPERF instrument in order to tackle service quality measurement problems in festivals. The FESTPERF model consists of three dimensions to measure the service quality of a festival applied in a practical case study of Australian jazz and blues festival. Tkaczynski (2014) also suggested further developments of the FESTPERF by applying the proposed quality measurement model in other special events with some minor modifications. Dorcic (2015) presented a new application of the FESTPERF approach in a food festival to test the validation of the mentioned model in different circumstance which shows that the measurement results in an understanding of increase in visitors’ satisfaction levels. Accordingly, there are many studies that present analysis of aesthetic factors from different perspectives, but the only study that has examined the relationship between aesthetics factors and service quality is a research conducted by Lagrosen and Lagrosen (2017). They proposed a theoretical study to present an aesthetic service quality model based on an empirical analysis at the Gothenburg Symphony Orchestra.
2.2 The concept of the quality in aesthetic environments
“[…] If something fulfills its function, it is inherently beautiful […]” said Socrates about human functions and importance of aesthetics considering philosophical approaches. Also, as R. Schumann said: “[…] to send light into the darkness of men’s hearts – such is the duty of the artist […]” where the fundamental role of an artist appears. Without a doubt, understanding the beauty and elegance is one of the most prominent human privileges. The mankind has experienced different forms of beauty in the sphere of time uninterruptedly. There are many research studies and experiments that have been conducted through the centuries consisting of aesthetics (Bardzell, 2009; Saito, 2007). In this study, an overview of the quality concept in aesthetic environments has been presented to build the foundation of the ARTQUAL measurement model. Different aspects of quality including managerial factors, aesthetic elements and performance-related issues have been reviewed. Consequently, the following aspects define the fundaments of the ARTQUAL service quality measurement model.
2.2.1 Management, policy and professionalism
One of the important factors in terms of increasing the customer’s satisfaction in any organization is to improve and establish an order. Continuous improvement in managerial elements can result in the establishment of a systematic organization which aims to obtain satisfaction. The current study has overviewed different aspects of managerial elements, e.g., policy and strategy, professionalism, stage management, visual management and brand management considering cultural centers and aesthetic environments in order to define fundamentals of the ARTQUAL model. Fisher et al. (2010) developed two success measurement scales on performing musical groups in which the model would alert group-specific changes that might need to be made in order to maintain the continual improvement to achieve the optimal success. Pegg and Patterson (2010) proposed an exploration in music festivals in an Australian cultural setting to gain a better understanding of visitors’ motivations and experiences they seek, which results in more clear insights of changing the nature of visitors’ motivations. Andersson et al. (2012) conducted two studies to analyze the effect and influence of background music on consumer behavior in two different retail stores. Morris (2013) proposed an analysis of the increasing integration of social media into music making and marketing to reflect on the changing occupational and creative roles for artists and fans as entrepreneurs and workers, respectively. Muñiz et al. (2014) explored the branding insights of Pablo Picasso, where he demonstrates that having an inherent knowledge of the principles of branding is not limited to contemporary artists. Tschacher et al. (2015) developed the Art Affinity Index (AAI) instrument to evaluate art relation and art knowledge consisting of the visitors of fine arts museum in Switzerland. The AAI instrument examined the effect of knowledge and expertise on the perception and obligation of art which was formulated using exploratory factor analysis (EFA), and then validated through a CFA process. McIntosh (2016) analyzed the business of online music video distribution through Vevo platform based on user experience, artist promotion and content monetization. Kim and Tucker (2016) proposed an exploration of the profiles and entertainment quality variables at two venues in the Southeastern USA to determine customers overall satisfaction of live events. Chandra and Uchil (2017) provided understandings of the design research process and outcomes of an online art gallery planned by a design studio. Soloski (2017) investigated the fundamental causes of the high number of the audience in theaters considering broadways shows in the past few years.
2.2.2 Ergonomics, reliability, form, performance and aesthetics
The main objective of the current study is to develop a comprehensive service quality measurement instrument to evaluate cultural centers and aesthetic environments. Therefore, reviewing the previous literature regarding the managerial aspects would be inadequate. Consequently, in the current section, various research studies within the core concept of the quality in performance arts have been offered. Benford (2010) proposed an analysis of performing musical interaction based on theories such as human–computer interaction to obtain the relationship between the proposed theories associated with the design of embedded musical interfaces. Lamont and Webb (2010) investigated the fundamental meaning of a favorite piece of music and specified preferences of listeners based on short and long time-spans. Chatterjee et al. (2010) suggested an instrument designed to assess art attributes including 24 paintings from the Western Canon which is called Assessment of Art Attributes based on formal-perceptual and conceptual-representational attributes used in advancing neuropsychological studies. Brown et al. (2011) investigated in a range of opinions from a working group meeting and from previous literature in order to evaluate and assess standardized soundscape preference considering indoor and outdoor acoustic environment. Packer and Ballantyne (2011) examined the impact of music festival attendance with consideration of young people’s psychological and social well-being based on a range of music festivals due to gaining a better understanding of attendees’ perspective. Also in the proposed study of Packer and Ballantyne, aspects of social and festival experiences have been analyzed. Brand et al. (2012) answered an important question “what makes a successful jazz gig?” based on the reciprocal relationship between seven jazz musicians and ten audience members in a London jazz club at various performances. Lehmann and Kopiez (2013) conducted two studies through the influence of on-stage behavior on the subjective evaluation of rock guitar solo performances which resulted in the high importance level of show elements. Landy (2013) discussed concerns of aesthetics and technical challenges experienced in terms of both contemporary electroacoustic music practice and aesthetic applications of technology. Bangert et al. (2015) explored the musical decision-making process on a group of violinists considering sightreading, practicing and performing. Nicholson et al. (2015) examined the music performance anxiety of 130 professional musicians in three different musical performance settings. Savioja and Svensson (2015) overviewed the state-of-the-art techniques and developments that are based on geometrical acoustics principles considering specular vs diffuse reflections and diffraction. Choi et al. (2016) examined the influence of flow and satisfaction on the realistic performing arts on the quality of performance. D’haeseleer et al. (2017) proposed an investigation of vocal quality of theater actors based on vocal complaints and risk factors for developing voice disorders considering before and after a theater performance. Hallqvist et al. (2017) analyzed the phonatory and resonator characteristics of nonclassical styles of singing consisting of six professional singers of musical theater and the soul styles of singing.
2.3 Research gap and contributions of the current study
To the best of authors’ knowledge, there is not a single study that presents a comprehensive service quality measurement model for cultural centers. There is only one research study which analyzed the relation between aesthetic factors and service quality (Lagrosen and Lagrosen, 2017), and the proposed approach is not applicable to measure the quality of service in other cultural centers. Therefore, this paper presents a novel service quality measurement model to evaluate cultural centers based on the previous literature on quality concept in terms of aesthetics and previous service quality measurement models. Furthermore, the originality of the current paper is not limited to the suggestion of a new quality measurement model, but also a hybrid approach consisting of statistical validation that has been applied to establish fundamentals of the ARTQUAL. The mentioned validation approach is based on SEM. Both CB-SEM and variance-based SEM (PLS-SEM) have been applied to present the most valid results. None of the previous studies in the service quality literature have utilized such methodology. In many research studies, the researchers emphasize on comparing the differences between CB-SEM and PLS models, but these approaches are rather harmonizing and complementary than competitive (Hair et al., 2011; Rigdon, 2012, 2014). Ultimately, both EFA and CFA have been applied in the validation process. It is worth mentioning that the principals of the ARTQUAL instrument are identified based on the validity of the literature and the practicality of real-world concepts of quality in aesthetic environments. In the current study, three types of cultural centers including seven concert halls, seven theater halls and seven art galleries have been analyzed to gain a better understanding of the ARTQUAL model and show the validity of the proposed instrument based on the mentioned statistical validation process.
3. Research methodology
3.1 Data collection, sample and respondents’ characteristics
Three different types of cultural centers in Tehran, Iran, during 2017 and early 2018 were chosen for the data collection procedure. The sample comprised customers and the audience of seven concert halls, seven theater halls and seven art galleries, all located in different areas of Tehran. This study is established based on multiple scenarios because of two reasons: to develop a comprehensive service quality measurement model considering different categories of cultural centers; and to prepare and validate the ARTQUAL instrument based on statistical validation in different scenarios. Flyvbjerg (2006) clarified that to employ in-depth research on any topic “one can study only one case, and the result can be generalized.” Therefore, to check the feasibility of the generalization of the service quality measurement model in each type of cultural centers, seven units have been studied. Accordingly, the suggested cultural centers in this research were not chosen randomly. It was intended to specify a number of particular preferences in cultural centers based on their reputation considering well-known centers along with independent and less-known centers to be able to obtain a profound understanding of the service quality in different circumstances. Similar to other service quality studies, the necessary research data have been collected by using a quantitative survey in the form of a questionnaire, specifically in this study the research data are collected through three questionnaires reliant to the type of cultural center which has been presented in Tables AI–AIII. The foundation of the self-administrated questionnaire is based on the previous literature and multiple experts’ comments including various artists related to each cultural center along with several quality assessment and quality assurance experts within different fields. The measuring scale of the proposed questionnaire is grounded on a five-point Likert scale, ranging from 1=much less than expected to 5=much more than expected (3=as expected). Accordingly, Table II defines the statistical population and characteristics of the respondents in the surveyed cultural centers.
Being a young multicultural country it is important to mention that perception of art is very diverse in such population. Based on Table II, most of the audience composed of female respondents where majority of them fell in the age groups of 20–35 (39.1 percent in art galleries, 40 percent in theater halls and 54.8 percent in concert halls) and 35–45 (29.4 percent in art galleries, 28.7 percent in theater halls and 23.9 percent in concert halls). The fact that most of the respondents were in the range of 20–35 is not surprising due to the nature of the performances and the exhibitions that were offered in the mentioned cultural centers. This study has investigated various forms and types of performance as well as diverse forms of exhibitions but unfortunately, in most of the presented forms of art in Iran, the target-domain of artists is young people. The questionnaires were equally distributed out (each unit 120 questionnaires) across all cultural centers. Out of the 2,520 questionnaires that were distributed out, 1,421 questionnaires were acknowledged. Consequently, the non-response rate is 56.38 percent. Accordingly, incomplete responses have been counted as no response because of the unusable data.
3.2 The ARTQUAL measure
The ARTQUAL model has been developed mainly from the SERVQUAL and SERVPERF instruments, along with FESTPERF and few other measurement models. Accordingly, the ARTQUAL approach was also influenced extensively by the concept of quality in artistic and aesthetic environments which have been overviewed in Section 2.2. There are altogether 9 aspects including 31 items/questions in the ARTQUAL measurement tool for concert halls as demonstrated in Table AI, 9 aspects considering 33 items/questions in the ARTQUAL measurement for theater halls as described in Table AII and 7 aspects considering 31 items/questions in the ARTQUAL measurement for art galleries shown in Table AIII. Figure 1 illustrates the connection between the different aspects of stated situations in ARTQUAL model with the previous service quality measurement tools and aesthetic factors. It would also be worth mentioning that the fundamental reason behind the development of three different settings for the ARTQUAL instrument is the nature of the aesthetic factors and quality concepts in different situations. Although the core concepts of the proposed situations are similar, the nature of the evaluating concepts is not the same as measuring the service quality. As a result, while the ARTQUAL model evaluates service quality of the cultural centers, the basis of the measurement model is based on various situations considering different concepts of quality.
4. Analysis and findings
The current study is a practical and real-world validation of a service quality measurement model of various types of cultural centers. This type of research is practical because of the purpose and nature of the validated model. In regard to content and data collection, the study is descriptive and quantitative. Consequently, the type of review is based on multiple case studies consisting of cultural centers in Tehran, Iran. Given that the success of a cultural center of any type is considered from the viewpoint of the audience, the study population comprises art enthusiasts and supporters. EFA using IBM SPSS 22 was used to formulate the ARTQUAL model. Accordingly, the reliability of the ARTQUAL model has also been analyzed with certain statistical scales by IBM SPSS 22. SEM of the current study has been proposed using a hybrid framework including a variance-based SEM, i.e. the PLS approach, and CB-SEM. To validate the ARTQUAL approach, the CFA has been utilized based on a partial disaggregation technique. The PLS-SEM approach has been analyzed by Smart-PLS 3, whereas the CB-SEM method has been examined by IBM SPSS AMOS 22. As mentioned above, the CFA approach applied in this study is based on a partial disaggregation technique performed on three scenarios of cultural centers based on their fundamental dimensions to measure the service quality of aesthetic environments. The traditional structural equations approach employs total disaggregation method, where in this study the partial disaggregation technique was applied as an alternative. Influencing from the foundation of the RSQS service quality measurement suggested by Dabholkar et al. (Dabholkar et al., 1996; Leen and Ramayah, 2011), partial disaggregation approach has been utilized in the foundation of the ARTQUAL measurement model. The total disaggregation technique has a trend to be complicated and cumbersome because of the possibility of high levels of random errors in typical items and many other factors that must be assessed (Leen and Ramayah, 2011). Conversely, the partial disaggregation method permits the investigator to progress with meaningful research by consolidating items into composites and fusions “to reduce higher levels of random error and yet it retains all the advantages of structural equations, allowing for multiple, multidimensional variables and testing for hierarchical factor structures” (Dabholkar et al., 1996; Leen and Ramayah, 2011). Consequently, to operationalize the partial disaggregation method in this research study, items that relate to an assumed dimension were combined based on experts interpretations to create meaningful composite indicators for each construct instead of several single-item indicators. Due to the fundamental differences in the nature of the cultural centers analyzed by the ARTQUAL model despite the similarity and resemblance of the research methodology, each setting of the ARTQUAL instrument has been investigated separately. Ultimately, to demonstrate a comprehensive description of the methodology along with presenting the finding of the study, the statistical methodology has been described extensively along with the exhibition of findings and results. Figure 2 illustrates the flow diagram of the suggested statistical methodology for formulating the measurement approach via the EFA technique and the validation process through a hybrid framework based on PLS-SEM and CB-SEM to originate and validate a service quality measurement model for cultural centers and aesthetic environments called ARTQUAL.
4.1 Validation of the ARTQUAL measurement
Following the data gathering through identification of the respondents, EFA was conducted to identify and formulate the dimensions based on partial disaggregation method and three settings of the ARTQUAL measurement model including 31 items of concert hall setting (CHS), 33 items of theater hall setting (THS) and 31 items of art gallery setting (AGS). The extraction method was the principal component analysis along with Varimax technique that was applied to rotate the factors, where factors with eigenvalues greater than 1 were retained. None of the variables were eliminated since they were not double loaded onto different factors or had less than 0.4 factor loadings (Hair et al., 2013; Leen and Ramayah, 2011). Kaiser–Meyer–Olkin measure of sampling adequacy was calculated as 0.96, 0.97 and 0.96 for CHS, THS and AGS, respectively. Bartlett’s test of sphericity was significant at the 0.000 level for all of the mentioned settings. Accordingly, Table III demonstrates the EFA for three settings of the ARTQUAL measurement model. In which the mentioned table indicates the factor loadings along with the items and components assigned to disaggregated composites. Table III shows that there are three components extracted from EFA method which were assigned to multiple composites consisting of partial disaggregation method based on experts’ commentaries and theoretical fundaments of the aesthetic environments. The composites that are assigned to each component have different theoretical definitions due to the conceptual differences between ARTQUAL settings. Additionally, comprehensive description of the final composites and components of the ARTQUAL dimensions have been individually demonstrated in Tables IV–VI for CHS, THS and AGS, respectively.
Based on the factors loadings described in Table III, items i29, i2 and i26 in CHS have been assigned to a specified component and composites not only based on their factor loading but also due to the nature of the item based on theoretical fundaments. It is clear that in Table III the computed factor loadings have satisfied the minimum value of the factor loadings that were aforementioned. Therefore, the formulation of the ARTQUAL model has been obtained based on the accurate statistical fundaments.
Furthermore, the reliability test that was implemented for the ARTQUAL model is based on multiple values including overall Cronbach’s α, Cronbach’s α for each composite, and the split-half test. Consequently, in the current study the acceptable value of Cronbach’s α fixed on at/above the 0.70 threshold (Field, 2006; Revelle and Zinbarg, 2009). In which, Table VII shows that the α values are not only acceptable but the consistency and reliability of the model is good and at some point measured as an excellent reliability.
This study has utilized a hybrid statistical validation framework based on both PLS-SEM and CB-SEM methods. For that reason, both confirmation techniques have been used to apply the CFA in the ARTQUAL model combined with partial disaggregation including nine composite dimensions of CHS and THS along with the seven composite dimensions of AGS. The factor loadings obtained from the CFA in CB-SEM approach along with the conceptual SEM model are shown in Figure 3.
The validity of any SEM instrument is measured through utilizing a number of methods such as content validity, convergent validity, discriminant validity and fit indices for the measurement model (Leen and Ramayah, 2011). One of the most important methods in the validation process of an instrument is content validity. Babbie (2012) defined the content validity as a specific degree in which an instrument/model covers the fundamental theories and meanings of the concepts contained within a certain research area. In the current study, the content validity of the ARTQUAL measurement model is satisfactory and adequate enough because the instrument has been carefully constructed and formulated based on the EFA. Also, to present a robust content validity the ARTQUAL model has been supported by a comprehensive literature review. The method that evaluates and questions the degree to which a set of indicators is able to represent a specified dimension is called convergent validity. Consequently, the evaluation process of the convergent validity includes using factor loadings, composite reliability (CR) and average variance extracted (AVE) indicators (Hair, 2009). CR values represent the reflection degree of the construct indicators on the construct values. CR values mathematically defined as: (square of the summation of the factor loadings)/((square of the summation of the factor loadings)+(square of the summation of the error variances)). In which, the obtained indicators in the current study surpass the recommended value of 0.70 as suggested by Hair (2009). The AVE values provides “the amount of variance that is captured by the construct in relation to the amount of variance due to measurement error” (Leen and Ramayah, 2011). AVE values are mathematically defined as: (summation of squared factor loadings)/((summation of squared factor loadings)(summation of error variances)). The minimum value for the latent constructs’ AVEs based on Hair’s suggestion is 0.5. In which, the obtained values are presented with satisfactory values. Nevertheless, Table VIII demonstrated the convergent validity of the ARTQUAL model using the partial disaggregation technique regarding the CB-SEM method. Accordingly, in regard to the results of Table VIII, convergent validity was conventional for the ARTQUAL model in all three settings. It is important to mention that, due to the specified scales of the latent variables (lack of scale) in the calculation of the CB-SEM measurements, one of the variables must be defined as the fixed variable. That is the reason why the values of standard error, critical ratio and p-value of first variables in each factor are empty in Table VIII. The factor loadings for all composites were above the minimum value of 0.50 as suggested by many research studies (Dabholkar et al., 1996; Hair, 2009; Leen and Ramayah, 2011). Consequently, Table IX demonstrates the discriminant validity of the ARTQUAL measurement model. Whenever the square root of the AVE is greater than its correlations within other constructs, the analyzed constructs has reached the criteria for discriminant validity (Leen and Ramayah, 2011).
Ultimately, the final models were then evaluated for compliance with the assumptions of the model utilizing goodness-of-fit (GOF) test. As a result of the GOF test, all the fit values were deemed valid as a study model of the ARTQUAL measurement tool. Therefore, the ARTQUAL model based on CHS, THS and AGS is recognized as a suitable model for the sample data. Table X presents the GOF indices for the ARTQUAL model. The analyzed fit indices fulfilled the suggested values that are supported based on the previous literature.
Finally, based on the calculated results of the CB-SEM method, the statistical evidence shows that the model is well formulated and supported. As a result, the ARTQUAL model tested to be highly suited for measuring service quality of the cultural centers including concert halls, theater halls and art galleries. Nonetheless, to confirm the validity of the ARTQUAL model, this study has utilized the PLS-SEM technique along with the CB-SEM approach to present a measurement model with the highest validity possible applying a double validation framework. Components-based SEM or PLS path modeling (PLS-SEM) allows calculating complex cause-effect relationship models with latent variables. Similar to the CB-SEM method, the PLS-SEM technique has also integrated with partial disaggregation method to analyze the validity of the model. Figure 4 illustrates the CFA analysis utilizing PLS-SEM for the ARTQUAL model.
Table XI demonstrates that the related factor loadings to the dimensions are higher than 0.40 in which the factor loading values are fluctuating between 0.79 and 0.93 that shows excellent values (Hair et al., 2013). Also, the results of the t-test in every factor loading variable are meaningful and accurate lower than 0.01. The CR value for variables is obtained more than 0.70 in each variable. The AVE values describe that the convergent validity of the variables is convenient.
The GOF index value of PLS-SEM approach is calculated as . GOF calculations obtained 0.74, 0.69 and 0.71 in CHS, THS and AGS, respectively, which means the GOF value is obtained as a high and acceptable significance based on the supported literature (Hair, 2009; Hair et al., 2011). As the results of the PLS-SEM, the ARTQUAL model consisting of the related settings including nine dimensions of CHS, nine dimensions of THS and seven dimensions of AGS has been tested to be highly suited for measuring the service quality of cultural centers. Consequently, it is worth mentioning that Tables XII–XIV show the correlation matrix of CHS, THS and AGS factors, respectively. It is clear that in the correlation matrix, while the correlation comparison of a specific element might be high, the cross-comparison of correlations of different factors shows that some factors even have reverse relationships.
5. Discussion and managerial implications
In the current section, the managerial application of the ARTQUAL tool is provided. The primary use of the ARTQUAL instrument as mentioned in previous sections is to measure the quality of service based on the definition of service quality in three settings. Consequently, the final result of the service quality measurement presents a comprehensive outcome based on the performance of the cultural center consisting of the audience perception of the service quality. Furthermore, analysis of the service quality measures based on ARTQUAL instrument also provides a detailed demonstration of strengths and weaknesses of cultural centers to secure the opportunities for improvement of the services. In order to review the service quality performance considering the mentioned settings of the ARTQUAL measurement tool, this study has utilized the radar chart for additional graphical presentations. The foundation of a radar chart consists of an order of equiangular spokes, in the case of the current study each spoke represents aspects of the ARTQUAL model based on specified settings considering cultural centers. The data length of each spoke is relative to the five-point Likert scale across all aspects where a line is drawn connecting the data values of each spoke. One of the main applications of the radar plot is the control of quality improvement to show the performance metrics of an ongoing organization. It is important to mention that the perception of quality in the same cultural center but regarding different performances/exhibitions might be altered due to the perceptional aspects of artistic preferences. Accordingly, due to the copyright policies revealing artists strategies without their permission, this study did not reference the names of the artists who performed in the related events. Eventually, considering various genres and categories of the performance/exhibition, Figure 5 illustrates radar plot of the results from the ARTQUAL investigations.
As it is clear in Figure 5 in almost all of the analyzed performances/exhibitions the most satisfying characteristic is the form and performance. This fact shows that the quality perception of the audience is at a high level. “But this is not enough” as it has been mentioned by most of the audience who had to spend money to attend such events. For instance, in concert halls the most satisfying characteristic besides physical aspects is the form and performance of the performed artist which describes the high quality of the presented performances. Accordingly, professionalism and personal interaction of the concert halls are at the lowest level based on individual analysis of case studies. CHI 7 is a clear example that all of the aspects from the ARTQUAL model have a direct influence on each other to achieve an understanding of audience quality perception. The case of CHI 7 is based on a traditional-folklore music performance in Roodaki Concert Hall. The radar plot shows that the ergonomics and reliability aspects of this performance are at the lowest point. Because of the high temperature in the performing area, first, there were many statements regarding dissatisfaction of the audience which was simultaneous with uncomfortable seats and indecent behavior of the staff which resulted in deprecation of management and artists. Second, high temperature and humidity in the performing area caused perspiration of the string players which caused an out of tuned performance. With the analysis of such events from the CHI 7 – Roodaki Concert Hall, it is clear that the performing artists could have reached better quality perception from the audience by only selecting a different location.
The ARTQUAL measurements for the THS are similar to the concert halls with different theoretic foundations containing nine dimensions to measure the service quality of the theater halls. Form and performance aspect of the ARTQUAL measurement model considering THSs is the most satisfying element of the evaluation model among the physical aspects. For example, THI 1 – Vahdat Hall showed the most satisfaction among the audience compared to other theater halls. The analysis of the ARTQUAL model in THI 1 is based on a famous play by Albert Camus called Caligula which was performed by a group of famous theater actors from Iran and the Netherlands. The performed act achieved a great success based on physical and performance aspects along with high quality in different aspects excluding professionalism. Unfortunately, due to the bad behavior of the staff and security guards there was a high disapproval of the management in the audience perception of professionalism which clearly had an adverse effect on the performers’ brand. Eventually, the ARTQUAL measurements for the AGS have minor similarities to the previous settings but due to the differences in theoretic fundaments of quality concept in art galleries, the aspect contains seven components. Form and performance aspect in the AGS showed the most satisfaction based on audience perception. Due to the nature of art galleries and presenting form of the exhibitions along with form and performance aspect, the physical aspects also showed decent satisfaction intensities similar to the visual stage management. Ultimately, the practical analysis of the ARTQUAL model showed the progressive influence of the measurement aspects. In which, optimization and improvement in one aspect resulted in the overall perception of the service quality.
It is worth mentioning that although this study has achieved the stated research objectives including development of a comprehensive service quality measurement instrument for evaluating cultural centers called ARTQUAL, some limitations still exist. One of the most important limitations in quantitative studies based on aesthetic features is the cultural settings. This limitation is due to the definition of quality involving aesthetic factors, which depends on elements such as age, sex and culture. Moreover, the results of the concluding analysis based on the ARTQUAL instrument may vary due to mentioned preferences in different countries or even various setups considering some personal attributes of audience in cultural centers. Consequently, the possibility of generalizing the ARTQUAL tool with three measurement scenarios for similar applications is great due to the validity of the model. Nevertheless, the proposed suggestion of a multi-scenario service quality measurement model based on aesthetic factors is just a meek establishment of such evaluating models with artistic research scheme which requires further research.
6. Conclusion
Taking into account that cultural centers are considered as organizations, this study aimed at developing a comprehensive service quality measurement tool in order to evaluate the service quality of aesthetic environments for further improvements. The ARTQUAL model was shaped from an extensive literature review on service quality models and quality concepts in artistic research. Furthermore, the fundamentals of the ARTQUAL tool were formulated using EFA which was validated through a hybrid SEM approach containing PLS-SEM and CB-SEM techniques. Due to the conceptual differences of quality perception in the proposed cultural centers, the ARTQUAL model was developed based on three foundations and essential basis. Additionally, the ARTQUAL instrument has been applied on various scenarios and case studies in Tehran, Iran, including seven concert halls, seven theater halls and seven art galleries. To end with, based on the findings of the overviewed cultural centers, an extensive managerial insight of the mentioned case studies has been analyzed. Ultimately, the ARTQUAL service quality measurement model showed a satisfactory validation to evaluate the quality of service considering various scenarios in cultural centers.
Suggestions for future developments of this study may be as follows. First, measurement of the service quality based on artists’ perceptions as customers of cultural centers is also a valuable evaluation which results in providing a better performance/exhibition. Second, this study has been utilized with a hybrid SEM framework based on PLS-SEM and CB-SEM techniques. This is the first time that the mentioned approach has been used in service quality model validating procedures. Therefore, deployment of such hybrid frameworks to validate the measurement models is recommended.
Figures
Figure 1
How different aspects connect with previous service quality measurement models
Figure 2
Flow diagram of the statistical formulation and validation of ARTQUAL measurement instrument
Figure 3
CFA on the ARTQUAL model based on the CHS, THS and AGS (CB-SEM)
Figure 4
CFA on the ARTQUAL model based on the CHS, THS and AGS (PLS-SEM)
Figure 5
Radar plot of the ARTQUAL measurement model
Description of the SERVQUAL dimensions
| Dimension | Definition of SERVQUAL dimensions |
|---|---|
| Tangibles | The presence and looks of facilities, physical equipment and personnel |
| Reliability | The ability to deliver the guaranteed services accurately and dependably |
| Responsiveness | The willingness to guide customers, and deliver prompt services as promised |
| Assurance | The courtesy of employees and their capability to stimulate trust and assurance |
| Empathy | The distribution of individualized attention and dedication to every customers |
Demographic characteristics of the respondents and audience in the cultural centers
| Gender | Age | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Cultural centers | ID | Description | Frequency | Percentage | Male | Female | 10–20 | 20–35 | 35–45 | 45–55 | 55–80 |
| Concert Halls | CH1 | Darbast Platform | 53 | 10.8 | 24 | 29 | 3 | 48 | 1 | 1 | 0 |
| CH2 | Azadi Tower | 73 | 14.8 | 44 | 29 | 3 | 55 | 7 | 6 | 2 | |
| CH3 | Milad Tower | 75 | 15.2 | 33 | 42 | 8 | 45 | 16 | 2 | 4 | |
| CH4 | Ministry of Interior | 81 | 16.4 | 36 | 45 | 13 | 59 | 9 | 0 | 0 | |
| CH5 | Sa’adabad Palace | 100 | 20.3 | 34 | 66 | 7 | 23 | 29 | 19 | 12 | |
| CH6 | Vahdat Hall | 58 | 11.8 | 27 | 31 | 2 | 14 | 38 | 0 | 4 | |
| CH7 | Roodaki Hall | 53 | 10.8 | 37 | 16 | 0 | 16 | 17 | 12 | 7 | |
| Total | 493 | 100 | 235 | 258 | 36 | 260 | 118 | 40 | 29 | ||
| Total percentage | 47.7 | 52.3 | 7.3 | 54.8 | 23.9 | 8.1 | 5.9 | ||||
| Theater Halls | TH1 | Vahdat Hall | 114 | 24.6 | 49 | 65 | 9 | 47 | 39 | 13 | 6 |
| TH2 | Iran-Shahr I | 47 | 10.2 | 19 | 28 | 2 | 18 | 14 | 9 | 4 | |
| TH3 | Paliz theater | 53 | 11.4 | 25 | 28 | 1 | 28 | 14 | 6 | 4 | |
| TH4 | Iran-Shahr II | 49 | 10.6 | 29 | 20 | 3 | 18 | 9 | 12 | 7 | |
| TH5 | Tehran Ind. | 42 | 9.1 | 18 | 24 | 5 | 21 | 13 | 3 | 0 | |
| TH6 | Tehran City Hall | 94 | 20.3 | 43 | 51 | 13 | 36 | 20 | 16 | 9 | |
| TH7 | Shahrzad Theater | 64 | 13.8 | 36 | 28 | 7 | 17 | 24 | 11 | 5 | |
| Total | 463 | 100 | 219 | 244 | 40 | 185 | 133 | 70 | 35 | ||
| Total percentage | 47.3 | 52.7 | 8.6 | 40 | 28.7 | 15.1 | 7.6 | ||||
| Art Galleries | AG1 | Shirin Gallery | 96 | 20.7 | 42 | 54 | 4 | 46 | 25 | 12 | 9 |
| AG2 | Hepta Gallery | 49 | 10.6 | 21 | 29 | 2 | 15 | 17 | 8 | 7 | |
| AG3 | Mohsen Gallery | 75 | 16.2 | 32 | 43 | 11 | 35 | 18 | 7 | 4 | |
| AG4 | O’ Gallery | 84 | 18.1 | 39 | 45 | 7 | 26 | 27 | 15 | 9 | |
| AG5 | Farda Gallery | 42 | 9.1 | 17 | 26 | 3 | 13 | 16 | 7 | 3 | |
| AG6 | TarhAzad Gallery | 71 | 15.3 | 31 | 40 | 4 | 29 | 17 | 12 | 9 | |
| AG7 | Abad Gallery | 48 | 9.9 | 19 | 27 | 2 | 17 | 16 | 7 | 4 | |
| Total | 465 | 100 | 201 | 264 | 33 | 181 | 136 | 68 | 45 | ||
| Total percentage | 43.2 | 56.8 | 7.1 | 39.1 | 29.4 | 14.7 | 9.7 | ||||
Exploratory factor analysis (EFA) for the ARTQUAL model based on three settings including CHS, THS and AGS
| Concert halls (CHS) | Theater halls (THS) | Art gallery (AGS) | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Varimax rotated component matrix | Varimax rotated component matrix | Varimax rotated component matrix | ||||||||||||
| Components | Components | Components | ||||||||||||
| Dimensions | Item/question | A | R | T | Dimensions | Item/question | A | R | T | Dimensions | Item/question | A | R | T |
| Ergonomics (A1) | i1 | 0.715 | 0.337 | 0.387 | Management and policy (A1) | i1 | 0.773 | 0.325 | 0.432 | Brand management (A1) | i5 | 0.706 | 0.451 | 0.374 |
| i6 | 0.681 | 0.388 | 0.355 | i2 | 0.617 | 0.405 | 0.534 | i8 | 0.627 | 0.376 | 0.547 | |||
| i7 | 0.734 | 0.366 | 0.326 | i11 | 0.681 | 0.44 | 0.291 | i12 | 0.657 | 0.412 | 0.435 | |||
| i9 | 0.812 | 0.381 | 0.225 | i12 | 0.695 | 0.437 | 0.413 | i13 | 0.8 | 0.452 | 0.142 | |||
| i10 | 0.779 | 0.366 | 0.217 | i15 | 0.601 | 0.455 | 0.362 | Management and policy (A2) | i14 | 0.623 | 0.6 | 0.301 | ||
| Visual stage management (A2) | i21 | 0.708 | 0.398 | 0.39 | i20 | 0.813 | 0.334 | 0.174 | i20 | 0.738 | 0.527 | 0.051 | ||
| i27 | 0.7 | 0.512 | 0.123 | Brand management (A2) | i9 | 0.606 | 0.486 | 0.44 | i21 | 0.721 | 0.323 | 0.432 | ||
| i28 | 0.84 | 0.129 | 0.415 | i10 | 0.772 | 0.418 | 0.233 | i23 | 0.679 | 0.282 | 0.535 | |||
| Form and performance (A3) | i13 | 0.643 | 0.442 | 0.513 | i18 | 0.664 | 0.534 | 0.32 | i26 | 0.828 | 0.23 | 0.353 | ||
| i29 | 0.556 | 0.638 | 0.352 | Personal interaction (A3) | i21 | 0.714 | 0.228 | 0.281 | i31 | 0.609 | 0.515 | 0.397 | ||
| i30 | 0.607 | 0.48 | 0.36 | i23 | 0.769 | 0.498 | 0.185 | Personal interaction (A3) | i27 | 0.696 | 0.414 | 0.419 | ||
| Professionalism (R1) | i8 | 0.238 | 0.72 | 0.319 | i29 | 0.782 | 0.348 | 0.333 | i28 | 0.769 | 0.341 | 0.354 | ||
| i11 | 0.224 | 0.897 | 0.12 | i32 | 0.661 | 0.496 | 0.373 | i29 | 0.757 | 0.08 | 0.567 | |||
| Personal Interaction (R2) | i12 | 0.499 | 0.625 | 0.428 | i33 | 0.622 | 0.534 | 0.414 | i30 | 0.709 | 0.388 | 0.428 | ||
| i15 | 0.518 | 0.57 | 0.402 | Stage management (R1) | i3 | 0.502 | 0.766 | 0.203 | Visual stage management (R1) | i15 | 0.601 | 0.571 | 0.365 | |
| i16 | 0.436 | 0.61 | 0.533 | i4 | 0.399 | 0.755 | 0.351 | i16 | 0.308 | 0.819 | 0.267 | |||
| Artistic tangibles (R3) | i24 | 0.437 | 0.69 | 0.371 | i5 | 0.494 | 0.706 | 0.201 | i18 | 0.379 | 0.769 | 0.323 | ||
| i25 | 0.286 | 0.652 | 0.555 | Physical aspects (R2) | i6 | 0.317 | 0.739 | 0.453 | Form and performance (R2) | i19 | 0.295 | 0.749 | 0.268 | |
| Physical aspects (R4) | i17 | 0.459 | 0.644 | 0.45 | i8 | 0.451 | 0.731 | 0.325 | i22 | 0.423 | 0.742 | 0.341 | ||
| i18 | 0.486 | 0.547 | 0.268 | i13 | 0.554 | 0.612 | 0.347 | i24 | 0.423 | 0.708 | 0.403 | |||
| i19 | 0.52 | 0.635 | 0.263 | i14 | 0.536 | 0.645 | 0.395 | i25 | 0.309 | 0.732 | 0.437 | |||
| i20 | 0.343 | 0.628 | 0.451 | Professionalism (R3) | i16 | 0.53 | 0.686 | 0.228 | Physical aspects (T1) | i1 | 0.489 | 0.538 | 0.531 | |
| i31 | 0.428 | 0.69 | 0.402 | i19 | 0.536 | 0.503 | 0.456 | i2 | 0.413 | 0.655 | 0.485 | |||
| Management and policy (T1) | i2 | 0.293 | 0.564 | 0.542 | Form and performance (R4) | i22 | 0.379 | 0.777 | 0.328 | i3 | 0.283 | 0.582 | 0.63 | |
| i3 | 0.29 | 0.367 | 0.771 | i24 | 0.448 | 0.695 | 0.392 | i4 | 0.482 | 0.391 | 0.625 | |||
| i4 | 0.477 | 0.199 | 0.717 | i27 | 0.587 | 0.573 | 0.383 | i6 | 0.42 | 0.307 | 0.752 | |||
| i5 | 0.153 | 0.317 | 0.819 | i28 | 0.552 | 0.65 | 0.288 | i7 | 0.217 | 0.565 | 0.699 | |||
| i14 | 0.393 | 0.462 | 0.615 | i30 | 0.59 | 0.525 | 0.374 | Ergonomics (T2) | i9 | 0.369 | 0.33 | 0.79 | ||
| Brand management (T2) | i22 | 0.399 | 0.452 | 0.641 | Ergonomics (T1) | i7 | 0.342 | 0.65 | 0.576 | i10 | 0.409 | 0.463 | 0.668 | |
| i23 | 0.43 | 0.203 | 0.754 | i31 | 0.556 | 0.413 | 0.573 | i11 | 0.466 | 0.399 | 0.659 | |||
| i26 | 0.695 | 0.236 | 0.569 | Accessibility (T2) | i17 | 0.131 | 0.649 | 0.68 | i17 | 0.254 | 0.637 | 0.625 | ||
| i25 | 0.385 | 0.241 | 0.821 | |||||||||||
| i26 | 0.355 | 0.332 | 0.822 | |||||||||||
Dimensions of the ARTQUAL model based on concert hall setting
| Component | Dimension | Dimension term | Definition/description |
|---|---|---|---|
| A | A1 | Ergonomics | The ability to guarantee convenience and comfortability of a concert hall’s ergonomic-related facilities based on the audience’s opinions |
| A2 | Visual stage management | The appearance of the atmosphere/environment and audiovisual effects and the applicability of the appearance to the performance | |
| A3 | Form and performance | The ability to execute and display the performance based on specified aesthetic forms and factors | |
| R | R1 | Professionalism | The knowledge of the performing artist(s)/employees and their ability to encourage trust and gratification |
| R2 | Personal interaction | The willingness to help and communicate with the audience/customers and provide prompt service with courtesy and compassion | |
| R3 | Artistic tangibles | The appearance of the performances’ locations as well as the artists’ appearance and their relevance to the performances’ aesthetic factors | |
| R4 | Physical aspects | The appearance of the physical facilities, equipment and interior/exterior design within the concert hall | |
| T | T1 | Management and policy | The capability of directors and executives to provoke trust and confidence based on the imposition of specified policies and strategies |
| T2 | Brand management | The possibility of increasing satisfaction levels and impact of the show on the quality perception of the audience based on the brand’s values |
Dimensions of the ARTQUAL model based on theater hall setting
| Component | Dimension | Dimension term | Definition/description |
|---|---|---|---|
| A | A1 | Management and policy | The capability of administrators and directors to inspire trust and confidence through utilization of specified policies and strategies |
| A2 | Brand management | The possibility of increasing the satisfaction levels and impact of the performed artwork concerning the audience’s perception of quality based on the brand’s values | |
| A3 | Personal interaction | The willingness to help and communicate with audience/customers and provide prompt service with courtesy and compassion | |
| R | R1 | Stage management | The appearance of atmosphere/environment and audiovisual effects of the stage area and its relevance to the performance |
| R2 | Physical aspects | The appearance of physical facilities, equipment and interior/exterior design within the theater hall | |
| R3 | Professionalism | The knowledge of the performing artist(s)/employees and their ability to encourage trust and gratification | |
| R4 | Form and performance | The ability to perform and display the act/show/artwork based on specified aesthetic factors and elements | |
| T | T1 | Ergonomics | The capability to increase satisfaction within the physical and ergonomic aspects |
| T2 | Accessibility | The ability to guarantee convenience and comfortability regarding ease of access to the performance area |
Dimensions of the ARTQUAL model based on art gallery setting
| Component | Dimension | Dimension term | Definition/description |
|---|---|---|---|
| A | A1 | Brand management | The possibility of increase in the satisfaction level and impact of the artwork’s presentation on the quality perception of the audience based on the brand’s values |
| A2 | Management and policy | The capability of directors and executives to motivate trust and confidence based on the imposition of specified policies and strategies | |
| A3 | Personal interaction | The willingness to help and communicate with the audience/customers and provide prompt services with courtesy and compassion | |
| R | R1 | Visual stage management | The appearance of atmosphere/environment and audiovisual effects and the relevance of the appearance to the exhibition |
| R2 | Form and performance | The ability to execute and display the exhibition of the artwork(s) based on specified aesthetic factors and aspects | |
| T | T1 | Physical aspects | The appearance of physical facilities, equipment and interior/exterior design within the art gallery |
| T2 | Ergonomics | The ability to guarantee convenience and comfortability of the concert hall’s ergonomically related issues based on the audience’s opinions |
Reliability for the ARTQUAL based on three settings including CHS, THS and AGS
| CHS | THS | AGS | |||
| Total Cronbach’s α | 0.963 | 0.971 | 0.967 | ||
| Reliability values for each factor (Cronbach’s α) | |||||
| A1=i1+i6+i8+i11+i12 | 0.940 | A1=i1+i2+i11+i12+i15+i20 | 0.948 | A1=i6+i10+i15+i16 | 0.935 |
| A2=i25+i31+i32 | 0.891 | A2=i9+i10+i18 | 0.916 | A2=i18+i24+i26+i28+i31+i36 | 0.948 |
| A3=i15+i33+i34 | 0.937 | A3=i21+i23+i29+i32+i33 | 0.937 | A3=i32+i33+i34+i35 | 0.939 |
| R1=i9+i13 | 0.825 | R1=i3+i4+i5 | 0.922 | B1=i19+i20+i22 | 0.909 |
| R2=i14+i17+i18 | 0.919 | R2=i6+i8+i13+i14 | 0.944 | B2=i23+i27+i29+i30 | 0.932 |
| R3=i28+i29 | 0.901 | R3=i16+i19 | 0.786 | C1=i1+i3+i4+i5+i8+i9 | 0.951 |
| R4=i20+i21+i22+i23+i35 | 0.921 | R4=i22+i24+i27+i28+i30 | 0.949 | C2=i11+i13+i14+i21 | 0.938 |
| T1=i2+i3+i4+i5+i16 | 0.914 | T1=i7+i31 | 0.844 | ||
| T2=i26+i27+i30 | 0.894 | T2=i17+i25+i26 | 0.879 | ||
| Reliability values of split-half test (Cronbach’s α) | |||||
| Part 1 | 0.932 | 0.963 | 0.949 | ||
| Items | A1, A2, A3, R1, R2 | A1, A2, A3, R1, R2 | A1, A2, A3, R1 | ||
| Part 2 | 0.922 | 0.913 | 0.935 | ||
| Items | R3, R4, T1, T2 | R3, R4, T1, T2 | R2, T1, T2 | ||
| Correlation between forms | 0.932 | 0.963 | 0.906 | ||
| Spearman–Brown coefficient (equal) | 0.965 | 0.981 | 0.951 | ||
| Spearman–Brown coefficient (unequal) | 0.965 | 0.981 | 0.952 | ||
| Guttman split-half coefficient | 0.959 | 0.912 | 0.939 | ||
Convergent validity of the ARTQUAL model
| ARTQUAL settings | Factors | Composite reliability (CR) | Average variance extracted (AVE) | Composites | Factor loadings | SE | Critical ratio (CR) | p-value (***p<0.001) |
|---|---|---|---|---|---|---|---|---|
| CHS | A | 0.73 | 0.60 | A1 | 0.830 | – | – | – |
| A2 | 0.733 | 0.103 | 9.264 | *** | ||||
| A3 | 0.772 | 0.088 | 9.880 | *** | ||||
| R | 0.77 | 0.59 | R1 | 0.758 | – | – | – | |
| R2 | 0.853 | 0.096 | 11.458 | *** | ||||
| R3 | 0.692 | 0.114 | 8.451 | – | ||||
| R4 | 0.762 | 0.107 | 9.343 | *** | ||||
| T | 0.80 | 0.73 | T1 | 0.819 | – | – | *** | |
| T2 | 0.887 | 0.85 | 11.354 | *** | ||||
| THS | A | 0.83 | 0.70 | A1 | 0.844 | – | – | – |
| A2 | 0.855 | 0.087 | 11.979 | *** | ||||
| A3 | 0.809 | 0.078 | 11.282 | *** | ||||
| R | 0.78 | 0.60 | R1 | 0.775 | – | – | – | |
| R2 | 0.761 | 0.110 | 9.520 | *** | ||||
| R3 | 0.757 | 0.098 | 9.882 | *** | ||||
| R4 | 0.804 | 0.100 | 10.479 | *** | ||||
| T | 0.73 | 0.67 | T1 | 0.846 | – | – | – | |
| T2 | 0.787 | 0.160 | 5.539 | *** | ||||
| AGS | A | 0.77 | 0.63 | A1 | 0.867 | – | – | – |
| A2 | 0.789 | 0.081 | 10.663 | *** | ||||
| A3 | 0.732 | 0.079 | 10.042 | *** | ||||
| R | 0.80 | 0.73 | R1 | 0.928 | – | – | – | |
| R2 | 0.765 | 0.146 | 5.769 | *** | ||||
| T | 0.74 | 0.67 | T1 | 0.668 | – | – | – | |
| T2 | 0.951 | 0.193 | 7.586 | *** |
Discriminant validity of the ARTQUAL model
| ARTQUAL settings | Factors | A | R | T | SE | Critical ratio (CR) | p-value |
|---|---|---|---|---|---|---|---|
| CHS | A | 0.78 | 0.086 | 4.855 | *** | ||
| R | 0.53 | 0.77 | 0.086 | 5.710 | *** | ||
| T | 0.70 | 0.73 | 0.86 | 0.096 | 6.283 | *** | |
| THS | A | 0.84 | 0.088 | 3.952 | *** | ||
| R | 0.66 | 0.77 | 0.083 | 3.923 | *** | ||
| T | 0.40 | 0.42 | 0.82 | 0.086 | 5.677 | *** | |
| AGS | A | 0.80 | 0.094 | 4.344 | *** | ||
| R | 0.42 | 0.85 | 0.106 | 5.267 | *** | ||
| T | 0.73 | 0.39 | 0.82 | 0.083 | 3.698 | *** |
Fit indices for the ARTQUAL model based on CHS, THS and AGS
| Goodness-of-fit model indices | Calculated values (CHS) | Calculated values (THS) | Calculated values (AGS) | Recommended value |
|---|---|---|---|---|
| χ2 | 70.374 | 59.156 | 19.036 | |
| df | 24 | 24 | 11 | |
| χ2/df | 2.932 | 2.465 | 1.731 | Lower than 3.00 |
| Goodness-of-fit index (GFI) | 0.979 | 0.932 | 0.970 | Higher than 0.90 |
| Root mean square residual (RMR) | 0.043 | 0.050 | 0.037 | Lower than 0.10 |
| Adjusted goodness-of-fit index (AGFI) | 0.960 | 0.873 | 0.923 | Higher than 0.90 |
| Normalized fit index (NFI) | 0.958 | 0.926 | 0.965 | Higher than 0.90 |
| Tucker–Lewis index (TLI) | 0.957 | 0.931 | 0.971 | Higher than 0.90 |
| Comparative fit index (CFI) | 0.971 | 0.954 | 0.985 | Higher than 0.90 |
| Root mean square error of approximation (RMSEA) | 0.052 | 0.093 | 0.066 | Lower than 0.10 |
Construct measures and statistics for the ARTQUAL model based on CHS, THS and AGS
| Research construct | Original sample | Sample mean | SD | SE | t-statistics | Path coefficient | Cronbach’s α | CR value | AVE value | Factor leading |
|---|---|---|---|---|---|---|---|---|---|---|
| CHS | ||||||||||
| A | ||||||||||
| A1 | 0.785 | 0.788 | 0.042 | 0.042 | 18.439 | 0.786 | 0.822 | 0.894 | 0.737 | 0.876 |
| A2 | 0.844 | |||||||||
| A3 | 0.856 | |||||||||
| R | ||||||||||
| R1 | 0.927 | 0.931 | 0.014 | 0.014 | 63.038 | 0.927 | 0.851 | 0.899 | 0.692 | 0.799 |
| R2 | 0.847 | |||||||||
| R3 | 0.803 | |||||||||
| R4 | 0.877 | |||||||||
| T | ||||||||||
| T1 | 0.821 | 0.826 | 0.035 | 0.035 | 22.976 | 0.822 | 0.841 | 0.926 | 0.863 | 0.927 |
| T2 | 0.931 | |||||||||
| THS | ||||||||||
| A | ||||||||||
| A1 | 0.848 | 0.850 | 0.032 | 0.032 | 26.340 | 0.848 | 0.874 | 0.922 | 0.798 | 0.893 |
| A2 | 0.906 | |||||||||
| A3 | 0.882 | |||||||||
| R | ||||||||||
| R1 | 0.883 | 0.881 | 0.032 | 0.032 | 27.430 | 0.883 | 0.856 | 0.902 | 0.699 | 0.840 |
| R2 | 0.824 | |||||||||
| R3 | 0.828 | |||||||||
| R4 | 0.853 | |||||||||
| T | ||||||||||
| T1 | 0.582 | 0.557 | 0.196 | 0.196 | 2.9614 | 0.582 | 0.799 | 0.908 | 0.832 | 0.917 |
| T2 | 0.908 | |||||||||
| AGS | ||||||||||
| A | ||||||||||
| A1 | 0.885 | 0.888 | 0.021 | 0.021 | 41.628 | 0.885 | 0.841 | 0.904 | 0.759 | 0.886 |
| A2 | 0.873 | |||||||||
| A3 | 0.855 | |||||||||
| R | ||||||||||
| R1 | 0.650 | 0.632 | 0.141 | 0.141 | 4.591 | 0.650 | 0.830 | 0.921 | 0.854 | 0.933 |
| R2 | 0.916 | |||||||||
| T | ||||||||||
| T1 | 0.814 | 0.815 | 0.031 | 0.031 | 26.127 | 0.814 | 0.776 | 0.898 | 0.816 | 0.886 |
| T2 | 0.921 | |||||||||
Correlation matrix of the ARTQUAL model based on CHS factors
| Correlation matrix of CHS factors | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| R1 | R2 | R3 | R4 | T1 | T2 | A1 | A2 | A3 | |
| R1 | |||||||||
| Pearson correlation | 1 | ||||||||
| Sig. (2-tailed) | |||||||||
| n | 170 | ||||||||
| R2 | |||||||||
| Pearson correlation | 0.702** | 1 | |||||||
| Sig. (2-tailed) | 0.000 | ||||||||
| n | 170 | 170 | |||||||
| R3 | |||||||||
| Pearson correlation | 0.435** | 0.556** | 1 | ||||||
| Sig. (2-tailed) | 0.000 | 0.000 | |||||||
| n | 170 | 170 | 170 | ||||||
| R4 | |||||||||
| Pearson correlation | 0.502** | 0.619** | 0.720** | 1 | |||||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | ||||||
| n | 170 | 170 | 170 | 170 | |||||
| T1 | |||||||||
| Pearson correlation | 0.549** | 0.560** | 0.471** | 0.498** | 1 | ||||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | |||||
| n | 170 | 170 | 170 | 170 | 170 | ||||
| T2 | |||||||||
| Pearson correlation | 0.520** | 0.604** | 0.502** | 0.632** | 0.727** | 1 | |||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||||
| n | 170 | 170 | 170 | 170 | 170 | 170 | |||
| A1 | |||||||||
| Pearson correlation | 0.500** | 0.546** | 0.381** | 0.379** | 0.364** | 0.410** | 1 | ||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |||
| n | 170 | 170 | 170 | 170 | 170 | 170 | 170 | ||
| A2 | |||||||||
| Pearson correlation | 0.513** | 0.449** | 0.281** | 0.279** | 0.471** | 0.337** | 0.595** | 1 | |
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
| n | 170 | 170 | 170 | 170 | 170 | 170 | 170 | 170 | |
| A3 | |||||||||
| Pearson correlation | 0.451** | 0.475** | 0.273** | 0.335** | 0.290** | 0.299** | 0.642** | 0.584** | 1 |
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| n | 170 | 170 | 170 | 170 | 170 | 170 | 170 | 170 | 170 |
Note: **Correlation is significant at the 0.01 level (2-tailed)
Correlation matrix of the ARTQUAL model based on THS factors
| Correlation matrix of THS factors | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| R1 | R2 | R3 | R4 | A1 | A2 | A3 | T1 | T2 | |
| R1 | |||||||||
| Pearson correlation | 1 | ||||||||
| Sig. (2-tailed) | |||||||||
| n | 170 | ||||||||
| R2 | |||||||||
| Pearson correlation | 0.539** | 1 | |||||||
| Sig. (2-tailed) | 0.000 | ||||||||
| n | 170 | 170 | |||||||
| R3 | |||||||||
| Pearson correlation | 0.627** | 0.582** | 1 | ||||||
| Sig. (2-tailed) | 0.000 | 0.000 | |||||||
| n | 170 | 170 | 170 | ||||||
| R4 | |||||||||
| Pearson correlation | 0.650** | 0.636** | 0.560** | 1 | |||||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | ||||||
| n | 170 | 170 | 170 | 170 | |||||
| A1 | |||||||||
| Pearson correlation | 0.463** | 0.453** | 0.350** | 0.466** | 1 | ||||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | |||||
| n | 170 | 170 | 170 | 170 | 170 | ||||
| A2 | |||||||||
| Pearson correlation | 0.328** | 0.433** | 0.393** | 0.468** | 0.710** | 1 | |||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||||
| n | 170 | 170 | 170 | 170 | 170 | 170 | |||
| A3 | |||||||||
| Pearson correlation | 0.370** | 0.405** | 0.367** | 0.353** | 0.659** | 0.727** | 1 | ||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |||
| n | 170 | 170 | 170 | 170 | 170 | 170 | 170 | ||
| T1 | |||||||||
| Pearson correlation | −0.289** | −0.267** | −0.252** | −0.317** | −0.317** | −0.235** | −0.290** | 1 | |
| Sig. (2-tailed) | 0.000 | 0.000 | 0.001 | 0.000 | 0.000 | 0.002 | 0.000 | ||
| n | 170 | 170 | 170 | 170 | 170 | 170 | 170 | 170 | |
| T2 | |||||||||
| Pearson correlation | −0.288** | −0.166* | −0.289** | −0.245** | −0.313** | −0.251** | −0.274** | 0.565** | 1 |
| Sig. (2-tailed) | 0.000 | 0.030 | 0.000 | 0.001 | 0.000 | 0.001 | 0.000 | 0.000 | |
| n | 170 | 170 | 170 | 170 | 170 | 170 | 170 | 170 | 170 |
Notes: *,**Correlations are significant at the 0.05 level and 0.01 levels (2-tailed)
Correlation matrix of the ARTQUAL model based on AGS factors
| Correlation matrix of AGS | |||||||
|---|---|---|---|---|---|---|---|
| R1 | R2 | T1 | T2 | A1 | A2 | A3 | |
| R1 | |||||||
| Pearson correlation | 1 | ||||||
| Sig. (2-tailed) | |||||||
| n | 170 | ||||||
| R2 | |||||||
| Pearson correlation | 0.710** | 1 | |||||
| Sig. (2-tailed) | 0.000 | ||||||
| n | 170 | 170 | |||||
| T1 | |||||||
| Pearson correlation | −0.287** | −0.239** | 1 | ||||
| Sig. (2-tailed) | 0.000 | 0.002 | |||||
| n | 170 | 170 | 170 | ||||
| T2 | |||||||
| Pearson correlation | −0.331** | −0.301** | 0.635** | 1 | |||
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | ||||
| n | 170 | 170 | 170 | 170 | |||
| A1 | |||||||
| Pearson correlation | −0.317** | −0.235** | 0.405** | 0.639** | 1 | ||
| Sig. (2-tailed) | 0.000 | 0.002 | 0.000 | 0.000 | |||
| n | 170 | 170 | 170 | 170 | 170 | ||
| A2 | |||||||
| Pearson correlation | −0.313** | −0.251** | 0.385** | 0.551** | 0.665** | 1 | |
| Sig. (2-tailed) | 0.000 | 0.001 | 0.000 | 0.000 | 0.000 | ||
| n | 170 | 170 | 170 | 170 | 170 | 170 | |
| A3 | |||||||
| Pearson correlation | −0.351** | −0.273** | 0.347** | 0.414** | 0.637** | 0.615** | 1 |
| Sig. (2-tailed) | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
| n | 170 | 170 | 170 | 170 | 170 | 170 | 170 |
Note: **Correlation is significant at the 0.01 level (2-tailed)
Questionnaire of the ARTQUAL model based on the concert hall setting
| Dimension composite | Item/question | Definition |
|---|---|---|
| Ergonomics (A1) | i1 | How would you rate sound quality regarding the sitting/standing area and the acoustics? |
| i6 | How comfortable and convenient was the sitting/standing area? | |
| i7 | How was the natural and artificial lighting of the sitting/standing area, as well as the performance area? | |
| i9 | Were you satisfied with the ease of movement in the performance hall, moving routs in the sitting/standing area, as well as the entrance and exit locations? | |
| i10 | How would you rate the heating, ventilation, air conditioning, as well as the additional noises in the concert hall? | |
| Visual stage management (A2) | i21 | How much was the effect and impact of the atmosphere and environment of the concert hall and performing area on your experience? |
| i27 | Were you satisfied with the impact of visual arts (visual arts in the form of lighting and related graphics to the artwork) on the audience? | |
| i28 | Were you satisfied with the special audiovisual effects presented along with the performance? | |
| Form and performance (A3) | i13 | How would you rate the distance between the performing artist(s) and the audience? |
| i29 | How were the audiovisual effects and their relevance to the aesthetic form of the performance? | |
| i30 | Were you satisfied with the transmission and communication of the specified aesthetic and artistic message of the performance? | |
| Professionalism (R1) | i8 | How would you rate the level of the knowledge and skills of the performing artist(s) based on your perception and experience? |
| i11 | Were you satisfied with the skills and assistance of the executive staff of the performance hall including sales managers, technical representatives, security, etc. at the time before and during the performance? | |
| Personal interaction (R2) | i12 | How satisfied are you with the politeness, courtesy and the level of accountability of the executive and sales representatives at the time before the performance as well as in the location of the performance hall? |
| i15 | What is your opinion about the appearance of the staff and the supervisory staff of the concert hall? | |
| i16 | How much did the performing artist(s) communicate with you as the audience? | |
| Artistic tangibles (R3) | i24 | How satisfied were you with the stage decoration and layout, and the relation between the performance and aesthetic designs? |
| i25 | How would you rate the appearance of the performing artist(s) and relevance of the appearance to the aesthetics of the performance? | |
| Physical aspects (R4) | i17 | How would you rate the location layout and spacing of the sitting/standing area? |
| i18 | How would you rate the appearance and exterior quality of the audio and video facilities of the concert hall? | |
| i19 | Were you satisfied with the utilization of the latest state-of-the-art and high-quality audiovisual facilities in the concert hall? | |
| i20 | How satisfied are you with the interior architecture and decoration of the related areas (e.g. restaurant, lobby, etc.) to the performing hall? | |
| i31 | How was the interior and exterior architecture of the concert hall? | |
| Management and policy (T1) | i2 | What do you think about the location of the concert hall considering the distance or proximity of nearby restaurants and entertainment facilities? |
| i3 | How satisfied were you with the security and safety features within the concert hall and the related areas? | |
| i4 | How satisfied were you with the process of purchasing performance ticket(s)? | |
| i5 | What do you think about the time management considering the start time and the timely completion of the performance? | |
| i14 | Were you satisfied with the facilities and extra services and side facilities of the concert hall such as the parking lot, restaurant, coffee shop, resting area, etc.? | |
| Brand management (T2) | i22 | How much the brand of the concert hall influenced you in regard to purchasing the performance ticket(s)? |
| i23 | Were you satisfied with the financial value of the presented performance based on your purchase(s)? | |
| i26 | How satisfied were you with the creativity and innovation in special advertisement, facilities and material at the time before the performance started? |
Questionnaire of the ARTQUAL model based on the theater hall setting
| Dimension composite | Item/question | Definition |
|---|---|---|
| Management and policy (A1) | i1 | What did you think about the time management considering the start time and the timely completion of the performance? |
| i2 | Were you satisfied with the crowd traffic flow and population control in the theater hall? | |
| i11 | How satisfied were you with the process of purchasing performance tickets? | |
| i12 | What did you think about the location of the theater hall considering distance or proximity of nearby restaurants and entertainment facilities? | |
| i15 | How satisfied were you with the security and safety features within the theater hall and the related areas? | |
| i20 | Were you satisfied with the facilities and extra services of the theater hall such as parking, restaurant, coffee shop, resting area, etc.? | |
| Brand management (A2) | i9 | How much did the brand of the theater hall influence you in regard to purchasing the performance ticket(s)? |
| i10 | Were you satisfied with the financial value of the presented performance based on your purchase(s)? | |
| i18 | How satisfied were you with the creativity and innovation in the special advertisement, facilities and material at the time before the performance started? | |
| Personal interaction (A3) | i21 | How satisfied were you with the politeness, courtesy and the level of accountability of the executive and sales representatives at the time before the performance as well as in the location of the performance hall? |
| i23 | Were you satisfied with the skills and assistance of the executive staff of the performance hall including sales managers, technical representatives, security, etc. at the time before and during the performance? | |
| i29 | How was the level of the knowledge and skills of the performing artist(s) based on your perception and experience? | |
| i32 | How much did the performing artist(s) communicate with you as the audience? | |
| i33 | How would you rate the distance between the performing artist(s) and the audience? | |
| Stage management (R1) | i3 | How would you rate the location layout and spacing of the sitting/standing area? |
| i4 | How would you rate the appearance and the exterior quality of the audio and video facilities of the theater hall? | |
| i5 | Were you satisfied with the utilization of the latest state-of-the-art and high-quality audiovisual facilities in the theater hall? | |
| Physical aspects (R2) | i6 | How satisfied were you with the interior architecture and decoration of the related areas (e.g. restaurant, lobby, etc.) to the performing hall? |
| i8 | How satisfied are you with the stage decoration and layout, and the relation between the performance and aesthetic designs? | |
| i13 | How would you rate the interior and exterior architecture of the theater hall? | |
| i14 | How much was the effect and impact of the atmosphere and environment of the theater hall and the performing area based on the performance? | |
| Professionalism (R3) | i16 | What was your opinion about the appearance of the staff and the supervisory staff of the theater hall? |
| i19 | Were you satisfied with the transmission and communication of the specified aesthetic and artistic message of the performance? | |
| Form and performance (R4) | i22 | How would you rate the appearance of the performing artist(s) and the relevance of their appearance to the aesthetics of the performance? |
| i24 | Were you satisfied with the impact of visual arts (visual arts in the form of lighting and related graphics to the artwork) on the audience? | |
| i27 | Were you satisfied with the special audiovisual effects presented with the performance? | |
| i28 | How would you rate the audiovisual effects and their relevance to the aesthetic form of the performance? | |
| i30 | How would you rate the music and special preparation in the pre-run area and pre-performance atmosphere like lobby, entrance hall and so on? | |
| Ergonomics (T1) | i7 | How would you rate the natural and artificial lighting of the sitting/standing area, as well as the performance area? |
| i31 | How would you rate the heating, ventilation, air conditioning, as well as the additional noises in the theater hall? | |
| Accessibility (T2) | i17 | How would you rate the sound quality based on sitting/standing location and acoustics? |
| i25 | How comfortable and convenience was the sitting/standing area? | |
| i26 | Were you satisfied with the ease of movement in the performance hall, moving routs in the sitting/standing area, as well as the entrance and exit locations? |
Questionnaire of the ARTQUAL model based on the art gallery setting
| Dimension composite | Item/question | Definition |
|---|---|---|
| Brand management (A1) | i5 | How much did the brand of the art gallery influence you in regard to attending the exhibition? |
| i8 | Were you satisfied with the financial value of the presented exhibition based on your purchase(s)? | |
| i12 | How satisfied were you with the creativity and innovation in the special advertisement, facilities and material at the time before the exhibition and presentation? | |
| i13 | How satisfied were you with the process of purchasing an artwork in regard to procuring process, packaging, delivery etc.? | |
| Management and policy (A2) | i14 | How satisfied were you with the time management considering the timetable, start and finish time of the art gallery? |
| i20 | What did you think about the location of the art gallery considering the distance or proximity of nearby restaurants and entertainment facilities around the area of theater hall? | |
| i21 | How satisfied were you with the security and safety features of the art gallery and the related areas? | |
| i23 | Were you satisfied with the facilities and extra services and side facilities of the art gallery such as parking, restaurant, coffee shop, resting area, etc.? | |
| i26 | Were you satisfied with the crowd traffic flow, controlling the traffic and population control within the art gallery? | |
| i31 | Were you satisfied with the educational facilities of the art gallery such as conference rooms, workshops, ateliers etc.? | |
| Personal interaction (A3) | i27 | How satisfied were you with the participation and accountability of the artist(s) in regard to the exhibition? |
| i28 | Were you satisfied with the skills and assistance of the executive staff of the art gallery including sales managers, technical representatives, security, etc. at the time before and during the exhibition? | |
| i29 | How was the level of the knowledge and skills of the presented artist(s) based on your perception and experience? | |
| i30 | How were the appearance of the artist(s) and the relevance of the appearance to the aesthetic form of the exhibition? | |
| Visual stage management (R1) | i15 | Were you satisfied with the impact of visual arts (visual art in the form of light and related graphics to the artwork) on the audience? |
| i16 | How was the music and special preparation in the pre-run area and pre-performance atmosphere like lobby, entrance hall and so on? | |
| i18 | Were you satisfied with the special audiovisual effects presented with the exhibition? | |
| Form and performance (R2) | i19 | How satisfied were you with the visual layout of the exhibited artwork? |
| i22 | How much did the artist(s) communicate with you as the audience/customer? | |
| i24 | How would you rate the audiovisual effects and its relevance to the aesthetic form of the exhibition? | |
| i25 | Were you satisfied with the transmission of the aesthetic and artistic communications and messages in regard to the exhibited artwork? | |
| Physical aspects (T1) | i1 | How satisfied were you with the appearance of the decoration and design of the exhibition area of the art gallery as well as the relevance of the embellishment to the artwork? |
| i2 | Were you satisfied with the utilization of the latest state-of-the-art and high-quality audiovisual facilities in the art gallery? | |
| i3 | How was the appearance and exterior quality of the audio and video facilities of an art gallery? | |
| i4 | How satisfied were you with the interior architecture and decoration of the related areas (e.g. restaurant, lobby, etc.) to the art gallery? | |
| i6 | How would you rate the interior and exterior architecture of the art gallery? | |
| i7 | How much was the effect and impact of the atmosphere and environment of the theater hall and performing area based on the performance? | |
| Ergonomics (T2) | i9 | How comfortable and convenience was the sitting/standing area? |
| i10 | Were you satisfied with the ease of movement in the exhibition area, moving routs in the sitting/standing area, as well as the entrance and exit locations? | |
| i11 | How would you rate the heating, ventilation, air conditioning, as well as the additional noises in the art gallery? | |
| i17 | How would you rate the natural and artificial lighting of the sitting/standing area, as well as the exhibition area? |
Appendix 1
Appendix 2
Appendix 3
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