Original Scientific Article
A 7P Comparison between Restaurant Managers’
and Customers’ Post-COVID-19 Quality Expectations
Marko Kukanja
University of Primorska, Slovenia
marko.kukanja@fts.upr.si
This study examines restaurantmanagement and customer quality expectations (ex-
pected performances) in the post-covid-19 pandemic period. The purpose of this
study is to investigatewhichmarketing-quality (7p) dimensions best explain the con-
struct of restaurant quality expectations after the crisis caused by the covid-19 pan-
demic and to determine whether differences exist between restaurantmanagers’ and
customers’ quality expectations. An online survey was delivered via emails (man-
agers) and social media (customers) in the Republic of Slovenia. A total of 422 valid
online questionnaires were obtained from customers, and 89 completed question-
naires were gathered from managers. The 42-item questionnaire was based on the
principles of the marketing mix. Results of exploratory factor analysis indicate that
six marketing dimensions best explain restaurant quality expectations in the post-
covid-19 pandemic period (in order of importance): Physical evidence, Product,
Promotion, Processes, Placement, and Price. Results also reveal a significant gap in
quality expectations since price is the only dimension where no differences were
found between restaurant managers’ and customers’ quality expectations. This re-
search contributes to the literature by explaining the importance of the different 7p
quality indicators for assuring restaurant quality in the post-covid-19 pandemic
period. By applying a 7p research methodology, we have also facilitated a bench-
marking process for the international restaurant industry.
Keywords: covid-19, managers, customers, restaurant, quality, marketing
https://doi.org/10.26493/2335-4194.15.249-264
Introduction
In service industries, the quality of services offered
constitutes one of the most critical elements for a
competitive advantage of service firms in the global
marketplace and significantly influences service firms’
operational profitability (Kukanja & Planinc, 2018).
Timely and accurate measurement of customers’ ex-
pectations is crucial for improving service quality, cre-
ating a competitive advantage, and the effective allo-
cation of production resources (Samanci et al., 2021).
Similarly, in the restaurant industry, where there is in-
tense competition among restaurant providers, restau-
rant firms should focus on analysing customers’ ex-
pectations to improve the quality of their offerings
and maintain customer satisfaction. Although service
quality is measured from the customers’ mainly sub-
jective perspective, restaurant managers are expected
to understand their customers’ needs and expectations
in order to provide high-quality offerings (Parasura-
man et al., 1985) and maintain competitive and prof-
itable business operations (Wang et al., 2021). There-
fore, a holistic conceptualisation of restaurant service
quality should consider both the customers’ (external)
and managers’ (the inner) quality perspectives.
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Marko Kukanja A 7P Comparison between Restaurant Managers’ and Customers’ . . .
Studies on restaurant service quality that evalu-
ate customers’ quality expectations and perceptions
are frequently reported in the literature. Nevertheless,
significantly fewer studies have analysed both cus-
tomers’ and managers’ quality perceptions (Dedeoğlu
& Demirer, 2015; Kukanja, 2017), and only a few stud-
ies have focused solely on the managerial perspective
(Kukanja et al., 2020). However, with the outbreak of
the Severe Acute Respiratory Syndrome Coronavirus
2 (sars-cov-2), which causes the new covid-19 dis-
ease, the global restaurant industry has suffered its
heaviest blow ever in modern human history (Brizek
et al., 2021), causing a ‘new reality.’ Accordingly, many
researchers have focused on investigating the vari-
ous aspects of restaurant customers’ buying behaviour
changes during the covid-19 pandemic. The main
topics referred to the analysis of risk perceptions (Yost
& Cheng, 2021), social distancing (Wang et al., 2021),
the safety of food packaging (Byrd et al., 2021), and
many others (relevant state-of-the-art research find-
ings are presented in Table 1). To the best of our knowl-
edge, no study has analysed restaurantmanagers’ qual-
ity expectations during the pandemic. In this con-
text, neither has any study’ identified potential differ-
ences between restaurant managers’ and customers’
quality expectations in the post-covid-19 pandemic
period.
In the spring of 2021, the governments of the Eu-
ropean (eu) member states have cautiously started to
loosen the rigorous anti-covid-19 measures. Due to
the widespread vaccination of the population, the im-
plementation of the eu digital covid-19 travel cer-
tificate, and the gradual reopening of restaurant facil-
ities, this study aims to reveal how to improve restau-
rant service quality in the ongoing post-covid-19
pandemic period. It does this by simultaneously com-
paring the quality expectations of both restaurant
managers and customers.
In this study, we implemented a marketing-based
research concept. Using the theoretical principles of
Kotler’s marketing mix, we also aim to identify the
most critical marketing quality dimensions in the
post-covid-19 pandemic period.
By understanding the importance of the different
marketing-quality dimensions and the potential dif-
ferences between managers’ and customers’ quality
expectations (expected performance), the long-term
negative impacts of the pandemic on restaurant firms
can also be minimised if proper recovery strategies
are applied in time. Therefore, identifying potential
differences between managers’ and customers’ quality
expectations might also help strengthen restaurants’
resilience strategies in the post-covid-19 pandemic
period (Yost & Cheng, 2021). Based on research re-
sults, restaurant firms should rethink and optimise
their marketing-mix strategies and improve the qual-
ity of their offerings. Additionally, we believe that this
study will also remain significant for future research
since, according to Zhong et al. (2021), this is most
probably not the last pandemic humanity will face in
the forthcoming years.
This paper is based on amixedmethodological ap-
proach. After the literature review, primary data were
collected using an online questionnaire. The design of
the questionnaires was based on the study of Kukanja
et al. (2017). An exploratory factor analysis (efa) was
performed to investigate the expected quality struc-
ture, and the Wilcoxon Mann-Whitney U test was
conducted to analyse the differences in quality expec-
tations between managers and customers.
The remainder of the paper is organised as follows:
the following sections discuss a literature review, the
methodology and the presentation of research results.
The paper concludes by presenting practical implica-
tions for the restaurant industry and indicating future
research directions.
Literature Review
Restaurant Quality
Based on its customer-oriented concept of subjectivity,
service quality is most often defined as the ability of a
service to fulfil or surpass the gap (the difference) be-
tween customers’ quality expectations andperceptions
(Parasuraman et al., 1985). In the restaurant sector,
service quality is critical because it results in the dif-
ference between customers’ expectations and percep-
tions of quality. Customers have a high-quality expe-
rience when the perceptions exceed the expectations.
Consequently, customer expectations and satisfaction
and the concept of quality management have been im-
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Marko Kukanja A 7P Comparison between Restaurant Managers’ and Customers’ . . .
portant topics in the hospitality literature. Customers’
choices to dine at restaurants and the research in this
area were usually rooted in understanding the criti-
cal quality dimensions that motivate customer buying
behaviour (Yost & Cheng, 2021).
Accordingly, therewere several theoretical attempts
to capture and empirically validate the critical com-
ponents of service quality. One of the most widely
used concepts is the Gap model of service quality by
Parasuraman et al. (1985). This genericmodel presents
the theoretical basis for the implementation of service
quality management in service industries. Moreover,
it provides a scale for the empirical measurement of
service quality based on a 29-item servqual instru-
ment composed of five rater (Reliability, Assurance,
Tangibles, Empathy, and Responsiveness) quality di-
mensions.
Many scholars modified the generic instrument to
meet the specifics of the different service sectors. For
example, Stevens et al. (1995)modified the servqual
instrument to meet the specifics of the restaurant in-
dustry and introduced the dineserv scale, Raajpoot
(2002) introduced tangserv, a scale measuring tan-
gible quality elements, and Chen et al. (2015) devel-
oped grserv – a tool for measuring consumer per-
ceptions of service quality in green restaurants. In ad-
dition, there were also alternative attempts to validate
service quality empirically. For example, Bufquin et
al. (2017) introduced the dinex instrument, which
focuses on social dimensions of connectedness and
homophily, while Kukanja et al. (2017) introduced a
marketing-oriented service quality model that cap-
tures the characteristics of restaurant service quality
based on marketing-mix quality indicators.
The generic servqual model applies a two-step
(the gap) approach for measuring service quality. In
contrast, all other models (e.g. servperf, tang-
serv, dineserv.per) are one-dimensional and focus
solely on the service performance evaluation after the
service encounter. Although they do not provide a nu-
merical evaluation of differences between guests’ qual-
ity expectations and perceptions, they have proved to
be reliable service quality indicators since guests eval-
uate service quality based on their quality expectations
(Kukanja et al., 2017).
Restaurant Customers’ Quality Expectations
(pre-COVID-19 Research)
The pre-covid-19 research projects focused on mea-
suring the perceived service quality, which, from our
research perspective, disables the empirical analysis
and a direct comparison of customers’ quality expecta-
tions. Nevertheless, previous research results stressed
the importance of different quality dimensions that
define a satisfactory dining experience. Several stud-
ies (Gupta et al., 2007; Vanniarajan & Gurunathan,
2009) reported that food (Product) is the crucial qual-
ity dimension affecting guests’ quality perceptions. In
contrast, a large volume of studies (Mosavi & Ghaedi,
2012; Voon, 2012) described the role of People as the
most critical restaurant quality dimension. The impor-
tance of the tangible (visible) quality attributes (Physi-
cal evidence) was also highlighted bymany researchers
(Cheng et al., 2012; Ryu & Han, 2011). In their study,
Kukanja et al. (2017) found that restaurant customers
primarily evaluate restaurant service quality based on
three marketing dimensions (in order of importance):
People, Placement, and Product and Physical evidence.
In this view, it is essential to note that research re-
sults might change according to the different method-
ologies (e.g. rater, 7p) applied to the different stud-
ies. Moreover, customers with different cultural back-
grounds have different quality expectations, which
might also influence their quality perceptions from
restaurant providers (Cha et al., 2019).
Restaurant Managers’ Perceptions of Customers’
Expectations of Quality (Pre-COVID-19 Research)
Managers’ realistic perceptions of guests’ quality ex-
pectations present the first step in the five-step model
of service quality by Parasuraman et al. (1985). More-
over, restaurant managers must identify customers’
quality expectations, as purchasing decisions aremain-
ly driven by customer expectations of restaurant pro-
viders (Kim et al., 2021). Despite its importance for
delivering restaurant service quality, managers’ per-
ceptions of customers’ quality expectations have rarely
been analysed in pre-covid studies. According to
Kukanja (2017), academics have simply not consid-
ered managers’ perceptions of customers’ quality ex-
pectations as a prerequisite for providing high-quality
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services. Briggs et al. (2007) reported that hotel man-
agers frequently misunderstand what level of service
guests expect.
In their study, Dedeoğlu and Demirer (2015) anal-
ysed perceptions of service quality among the different
groups of stakeholders (guests, managers, and staff).
Their findings showed a discrepancy in perceptions of
quality as employees and managers perceived service
performance to be at a high level. In contrast, guests
perceived it to be at a low level. Similarly, Kukanja
(2017) analysed differences between restaurant cus-
tomers and managers and found statistically signifi-
cant differences in quality perceptions between both
groups of respondents. Research results also revealed
that the most critical marketing quality dimension for
both groups of respondents was by far People. Other
marketing quality dimensions were significantly less,
or even not crucial, for ensuring restaurant quality.
In their research, Kukanja and Planinc (2018) as-
sessed the influence of restaurant managers’ qual-
ity perceptions on restaurant firms’ profitability. Ac-
cording to managers’ perspectives, research results
revealed that only two quality dimensions are essen-
tial for ensuring overall restaurant quality – empathy
and assurance, and tangibles. Regarding determining
restaurant firms’ financial success, the results show
that the quality dimensions mentioned above have no
impact on restaurants’ operational profitability.
Restaurant Customers’ Buying Behaviour during
COVID-19 (2020–2021 Research Findings)
As stated above, to the best of our knowledge, no stud-
ies have analysed customers’ and managers’ quality
expectations in the post-covid-19 pandemic period.
Nevertheless, several authors examined the influence
of the pandemic on restaurant customers’ buying be-
haviour during covid-19 (we found no studies for
restaurant managers).
During the pandemic, restaurant customers chan-
ged their buying behaviour. According to Eftimov et
al. (2020), customers started to prepare food at home,
reduced their shopping frequency, searched for alter-
native food supplies, and stockpiled food. Yost and
Cheng (2021) state that covid-19 has left an inefface-
able mark on customers’ buying behaviour by creat-
ing a ‘new normal’ among customers’ spending ability,
movement patterns, and eating habits. In contrast, ac-
cording to Pantano et al. (2021), the pandemic should
not necessarily have a long-term impact on restau-
rant customers’ buying behaviour. Our literature re-
view found relatively few studies that analysed cus-
tomers’ buying behaviour during the pandemic from
the various (partial) perspectives. Accordingly, Table 1
presents the relevant research findings.
As can be seen from the studies presented above,
there is no consensus about changes in customer be-
haviour during the pandemic from the quality man-
agement perspective. Various methodological appro-
aches have been adopted in different online stud-
ies. Moreover, no study applied a ‘traditional’ (e.g.
Servqual), holistic, or a marketing-based approach to
analysing potential changes in customer quality expec-
tations during the pandemic.Most studies stressed the
importance of risk perceptions, imposed safety mea-
sures, and motivations to dine out. Suppose changes
in customer buying behaviour will have a long-term
(a post-pandemic) effect on their quality expectations
and demand. In that case, restaurant managers will
have to readjust their perceptions of guests’ expec-
tations and adapt restaurant quality and marketing-
mix strategies to provide satisfactory quality offerings
(Madeira et al., 2020).
Specifically, from the futuristic andmarketing-mix
perspectives, this study has two objectives. First, to
investigate which marketing-quality dimensions will
best explain quality expectations in the post-covid-
19 pandemic period. Secondly, to explore if statistically
significant differences exist between restaurant man-
agers’ and customers’ quality expectations. Based on
the above-presented research findings, we pose our re-
search questions (rqs) as follows:
rq1 Which marketing-quality dimensions best ex-
plain restaurant quality in the post-covid-19
pandemic period according to restaurant man-
agers’ and customers’ quality expectations?
rq2 Are there are statistically significant differences
between restaurant managers’ and customers’
quality expectations concerning the post-covid-
19 pandemic period?
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Table 1 Restaurant Quality Studies during covid-19 (2020–2021)
Authors Main theme Location, sample size,
and data collection
Major findings
Brewer and
Sebby ()
Effect of online restaurant
menus on consumers’ purchase
intentions
usa; n=  (online) Menu’s visual appeal and informativeness play
a decisive role in consumer purchase inten-
tions.
Byrd et al.
()
Risk perceptions about food
and its packaging
usa; n=  (online) Consumers are less concerned about con-
tracting covid- from food in general than
restaurant food and its packaging.
Dedeoğlu and
Boğan ()
Motivations to visit upscale
restaurants
Turkey; n=  (on-
line)
Socialisation and affect regulation have a sig-
nificant positive effect on visit intention to
upscale restaurants.
Dsouza and
Sharma ()
Analysis of food delivery por-
tals
Maharashtra (India);
n=  (online)
Food quality plays a vital role in customer
satisfaction, indirectly influencing their loyalty
towards the restaurant provider. Implemented
safety measures help to retain the customer
base.
Foroudi et al.
()
Risk perceptions and adaptive
belief
uk; n=  (online) Guests’ self-protective behaviour and adop-
tive belief positively influence their trust in
restaurant providers.
Hakim et al.
()
Perceived risk and intentions to
visit restaurants
Brazil; n=  (online) Perceived safety and brand image are the pri-
mary factors affecting consumers’ intention to
(re)visit a restaurant.
Kim et al.
()
Clean safety food message
framing
Korea; n=  (restau-
rant sales data and 
responses from diners)
Clean safety food message framing affects
customers’ purchasing behaviour.
Luo and Xu
()
Online restaurant reviews usa; n= .
(restaurant online re-
views)
The four most frequently mentioned restau-
rant features are service, food, place, and expe-
rience.
Min et al.
()
Perceived vulnerability, con-
sumer co-creation behaviour,
and repatronage intention
usa; n=  (Qualtrics
web-based survey)
Perceived vulnerability to covid- lever-
ages customers’ repatronage intention, which
is affected by service fairness, trust, and co-
creation behaviour in the restaurant industry.
Continued on the next page
Research Method
Research Process and Instrument Design
A qualitative research study was conducted in the first
section to discover relevant past studies focusing on
customers’ and managers’ quality expectations. From
February to June 2021, studies on the aforementioned
topic were obtained from significant scholarly tourism
and hospitality research databases.
In the next section of the study, quality expecta-
tions were examined using a modified version of a
marketing-based questionnaire for measuring restau-
rant quality (Kukanja et al., 2017). There are 35 mar-
keting-quality indicators in the original questionnaire.
Seven indicators were added to the original version of
the questionnaire (one to each marketing dimension)
to address the specifics of the present crisis. The fol-
lowing items were included: availability of sanitisers
(Zhang et al., 2021); employment of local staff (Wang
et al., 2021); use of local ingredients (Pressman et al.,
2020); possibility of using information technologies
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Table 1 Continued from the previous page
Authors Main theme Location, sample size,
and data collection
Major findings
Pantano et al.
()
Consumer behaviour uk, Spain, and Italy;
n= . (analysis of
tweets)
Consumer behaviour is driven by the need of
escaping from home by having a good meal
(uk), drink alcohol (Spain), and travel (Italy).
Sung and King
()
Preventive behaviour and me-
dia exposure
Taiwan; n=  partici-
pants (online)
Guests’ risk perceptions and fear are positively
influenced by social media coverage.
Tuzovic et al.
()
Wellbeing perceptions Germany; n=  inter-
views (online)
Collective wellbeing comprises three domains:
governmental procedures, restaurants’ offer-
ings, and guests’ perceptions.
Wang et al.
()
Crowdedness and in-restaurant
safety measures
usa and Australia;
n=  usa and 
Australia (online ex-
periment)
usa customers are more sensitive to crowded-
ness, whereas Australians are more sensitive to
other safety protocols.
Wei et al.
()
Dine out intentions usa; n=  (online) Dining involvement positively affects cus-
tomers’ decision to dine out, and country of
origin moderates the relationship between the
perceived importance of preventive measures
and brand trust.
Yang et al.
()
Effects of the pandemic on
stay-at-home orders
usa; n= . counties
(panel data)
An increase of  in covid- cases led to a
. decrease in daily restaurant demand.
Yost and Cheng
()
Risk perceptions and motiva-
tion to dine out
Literature review (con-
ceptual study)
Restaurants that accumulated more customer
trust by fostering transparency are most likely
to recover from the crisis quickly.
Zhong et al.
()
Dining out behaviour Korea and China;
n=  participants
(social media in China
and offline in Korea)
Subjective norms, perceived physical and psy-
chological risks, enjoyment, and precautionary
restaurant measures are vital factors affecting
guests’ dining out behaviour.
(it) (Brewer & Sebby, 2021); information about safety
protocols (Tuzovic et al., 2021); food delivery or take
away (Yang et al., 2020); and the possibility of using
alternative means of payment (Grobys, 2021). As a re-
sult, the participants’ expected performance scores for
42 restaurantmarketing-quality indicators were deter-
mined (see Table 3).
As the virus presents an ongoing threat, the ex-
pected quality performance has been preferred instead
of the perceived (actual) one. This study’s method-
ological (expected performance) concept is based on
a recent study by Samanci et al. (2021), who analysed
managers’ and passengers’ post-covid-19 quality ex-
pectations in the airline sector.
The second section of the survey included ques-
tions about respondents’ demographic characteristics
(age, education, gender, and income) and their buying
behaviour (frequency of restaurant visits and average
spending per person – asp). A pilot studywith 47 par-
ticipants (forty customers and seven managers) con-
firmed that the instructions and research instrument
were understandable and that the survey time was ad-
equate.
The anti-covid-19 measures implemented by the
government of Slovenia were focused on assisting
restaurant providers (e.g. deferral of payment of taxes,
favourable national loans, covering employees’ wages)
and did not directly impact restaurant customers’
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Marko Kukanja A 7P Comparison between Restaurant Managers’ and Customers’ . . .
buying behaviour. Namely, tourist vouchers issued to
Slovenian residents in 2020 could only be spent on ac-
commodation. Accordingly, no variables related to the
influence of governmental support on restaurant cus-
tomers’ buying behaviour were included in the ques-
tionnaire.
Data Gathering and Research Method
An online survey was delivered via emails (managers)
and social media and web links (customers) to avoid
physical contact, as previously done bymany research-
ers (see Table 1). The focus of the research was on sit-
down restaurants which offer table service. Take-away
and self-service facilities were excluded from research
since, from the 7p perspective, these facilities provide
a limitedmarketing-quality experience. Due to the na-
ture of their business, the importance of some qual-
ity indicators might be limited (e.g. professionalism
and recommendations from service staff). In the offi-
cial business register (https://www.ajpes.si/fipo), there
were 8,410 businesses registered as restaurants (nace
code i56).
After a pre-screening process, we excluded from
the sample all facilities that might not operate as sit-
down restaurants. Moreover, not all restaurant firms
had publicly available emails. Therefore, to gather data
from restaurant managers, invitations to voluntar-
ily participate in the study were emailed to 500 ran-
domly chosen restaurant firms with published email
addresses in the business register.
Using a snowball sampling method via social me-
dia and web links, we collected data from restaurant
customers. The target population were domestic cus-
tomers who dined at sit-down restaurant facilities just
before the lockdown in March 2020, as Samanci et al.
(2021) had previously done.
In the participation-invitation letter, the research
goal and instructions for both groups of respondents
were thoroughly presented to minimise any potential
bias in the data gathering process. As stated above,
we performed a pilot study to assure maximum com-
prehensibility of all research items. Respondents were
asked to indicate their restaurant marketing-quality
expectations (expected performance) in the post-
covid-19 pandemic period on a five-point ordinal-
type Likert scale ranging from 1 (not important at
all) to 5 (very important). The survey captured data
from March to mid-May 2021, when on-site dining
with indoor seating was prohibited. We collected 89
completed questionnaires from restaurant managers
(response rate was 17.4) and 422 completed ques-
tionnaires from customers. Participation in the survey
was voluntary, anonymous, and no monetary incen-
tives were given.
Information about respondents’ characteristicswas
presented using descriptive statistical analysis. efa
was performed to extrapolate quality factors, and a
Mann Whitney-U test was applied to investigate dif-
ferences between customers’ andmanagers’ quality ex-
pectations. All datawere analysed using spss (version
26) software.
Research Results
Descriptive Statistics
Findings show that the sample was predominantly
(52) composed of female managers, respondents
were on average forty-four years of age, the largest
proportion of managers had completed secondary ed-
ucation (40), and that almost half of the managers
(47) also own the restaurant they manage. Accord-
ing tomanagers,most guests (32)will spend between
€11–20, followed by those (24.5) spending between
€6–10, and only 11.5 will spend more than €50 when
visiting a restaurant in the post-covid-19 pandemic
period. Most managers (52.5) also believe that cus-
tomers will visit restaurants with the same frequency
as before the pandemic and that their quality expecta-
tions will not significantly change due to the pandemic
(48).
In terms of customers, results indicate that respon-
dents were, on average, thirty years of age, the sam-
ple was predominantly composed of females (64.2),
and that the largest group of respondents had com-
pleted secondary education (45). Results indicating
customers’ buying behaviour in the post-covid-19
pandemic period show that the largest group of re-
spondents (36) is planning an asp of €11–20, 26.1
of them indicated an asp of €6–10, and 2.4 of them
were planning to spend over €50 when visiting a res-
taurant in the post-covid-19 pandemic period. The
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Table 2 Characteristics of Respondents
Variables Managers Customers
Years of age (average) . .
Gender (predominant) Female () Female (.)
Education (majority) Secondary education Secondary education
Expectations about
customers’ buying
behaviour in the post-
covid- pandemic
period
asp: < (.), – (.), – (.),
– (.), > (.).
Dining out frequency: significantly less than before
the pandemic (), less than before the pandemic
(), the same as before the pandemic (.),
more than before the pandemic (.), significantly
more than before the pandemic (.).
asp: < (.), – (.), –
(), – (.), > (.).
Dining out frequency: few times per year
(.), few times per month (.), few
times per week (.), daily (.), not
planning to dine out in the first months
after the pandemic (.).
Table 3 Quality Expectations: Descriptive Statistics
p Indicators Managers Customers
m sd m sd
p i – Product  Selection of dishes . . . .
 Size of portions . . . .
 Food taste . . . .
 Food appearance . . . .
 Food safety perception . . . .
 Use of local ingredients . . . .
Average . . . .
p ii – Physical evidence  Restaurant cleanliness . . . .
 Presentable service staff . . . .
 Sense of comfort . . . .
 Sense of security . . . .
 Restaurant design according to food offerings . . . .
 Availability of sanitisers . . . .
Average . . . .
Continued on the next page
largest group of respondents is planning to dine out a
few times per month (36.5), followed by those who
plan to visit a restaurant a few times per week (18.7),
while 16.3 of respondents indicated that they do not
plan to dine out in the firstmonths after the pandemic.
Interestingly, 89 of respondents reported that the
covid-19 pandemic has not significantly influenced
their restaurant quality expectations.
Characteristics of respondents (demographic pro-
file and perceptions of customers’ buying behaviour in
the post-covid-19 pandemic period) are summarized
in Table 2.
The results presented in Table 3 indicate that all
marketing-quality indicators were evaluated relatively
highly for both groups of respondents. The average
mean values (M) are 4.05 for managers and 3.83 for
customers. The highest-rated dimension for both gro-
ups was Physical evidence (m = 4.64 and m = 4.25, re-
256 | Academica Turistica, Year 15, No. 2, August 2022
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Table 3 Continued from the previous page
p Indicators Managers Customers
m sd m sd
p iii – People  Sufficient number of service staff . . . .
 Imp. of the presence of the rest. manager for quality offerings . . . .
 Distracting presence of other customers . . . .
 Hospitable service staff . . . .
 Professionally competent service staff . . . .
 Employment of local staff . . . .
Average . . . .
p iv – Processes  Appropriate answers from service staff . . . .
 Helpfulness of service staff . . . .
 Responsiveness of service staff . . . .
 Restaurant opening hours . . . .
 Service waiting time . . . .
 Possibility of using IT . . . .
Average . . . .
p v – Promotion  Visible marketing signs . . . .
 Compliments and signs of special attention . . . .
 Recommendations from service staff . . . .
 Special offers and sales campaigns . . . .
 Advertising activities in media . . . .
 Information on safety protocols . . . .
Average . . . .
p vi – Placement  Accessible entrance . . . .
 Accessible parking area . . . .
 Neat surroundings . . . .
 The restaurant is worth the distance travelled . . . .
 The restaurant enhances indirect distribution . . . .
 Possibility of food delivery and takeaway . . . .
Average . . . .
Continued on the next page
spectively), with restaurant cleanliness as its highest-
rated quality indicator. The lowest rated expectations
for managers were related to the dimension Price (m
= 3.65), with alternative payment as its lowest-rated
indicator. For customers, the lowest-rated indicator
wasPromotion (m = 3.39), with advertising activities in
media as its lowest-rated quality indicator. The mean
difference (md) between managers and customers is
md = 0.22, indicating thatmanagers have higher qual-
ity expectations than customers. The dispersion of the
data is presented by the values of standard deviations
(sd). Relatively high values of sd show that the data
is widely spread around the mean values.
Results presented in Table 3 provided preliminary
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Table 3 Continued from the previous page
p Indicators Managers Customers
m sd m sd
p vii – Price  Understandability of prices . . . .
 Accurate bill . . . .
 Value for money . . . .
 Price competitiveness . . . .
 Possibility of surcharges for extra security of services . . . .
 Use of alternative means of payments (e.g. Bitcoins) . . . .
Average . . . .
information regarding the differences in quality ex-
pectations between both groups of respondents. To get
a deeper understanding of the factor structure of qual-
ity expectations and to identify marketing-quality di-
mensions that best explain managers’ and customers’
quality expectations in the post-covid-19 pandemic
period, in the next step, efa was performed.
Exploratory Factor Analysis (EFA)
The decision to use efa was based on the fact that
the generic instrument has not been extensively used
before and that additional research items were intro-
duced.Moreover, we tested the instrument in a specific
(crisis) situation. Since the same research instrument
was used to collect data fromboth samples, we decided
to perform one efa.
The implied research factor model seeks the fewest
factors that can account for the common variance of a
set of indicators and attempts to understand the shared
variance through a small set of latent variables that
link our indicators into a common factor. Based on
this presumption, we decided to use the Principal Axis
Factoring Method (paf). Another decision for using
paf is that we could not confirm a normal dataset dis-
tribution (the Kolmogorov-Smirnov test was used) for
any of the selected indicators.
Based on the values of the Kaiser-Meyer-Olkin
measure of Sampling Adequacy – kmo (0.889) and
the Bartlett’s Test of Sphericity (χ2 = 6092.494; df =
450; p < 0.001), we estimated that all initial indicators
were suitable for performing efa. After the evalua-
tion of the adequacy of communalities (≥0.50) (Hair
et al., 2010), eleven indicators with too-low commu-
nalities (i.6 use of local ingredients; iii.3 distracting
presence of other customers, iii.6 employment of lo-
cal staff; iv.6 possibility of using it; v.4 special of-
fers and sales campaigns, v.5 advertising activities in
media, v.6 information on safety protocols; vi.5 the
restaurant enhances indirect distribution, vi.6 possi-
bility of food delivery and take away; vii.5 possibility
of surcharges for extra security of services, vii.6 use
of alternative means of payment) were excluded from
the analysis.
Accordingly, we proceeded with 31 indicators with
sufficient communalities. The values of the Bartlett’s
Test (χ2 = 6082.476; df = 465; p < 0.001) and kmo
(0.935) indicated satisfactory values of the dataset for
inclusion in the final model. Based on a rotated fac-
tor matrix solution (Maximum Likelihood extraction
method and Varimax with Kaiser Normalization ro-
tation method were applied), we have selected the fi-
nal model with six factors and 22 indicators that ex-
plain 52.58 of the total variance (see Table 4). Only
factors containing three or more indicators with sat-
isfactory factor loadings (≥0.50) were retained in the
final model. Internal consistency was verified by cal-
culating Cronbach’s Alpha (α), which indicated a re-
spectable level (α ≥ 0.75) of internal consistency (Hair
et al., 2010) for all extracted factor groups.
Based on the percentage of their explained vari-
ances, the most significant importance in explaining
quality expectations in the post-covid-19 pandemic
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Table 4 efa: Rotated Factor Solution
Indicators p ii p i p v p iv p vi p vii
i. Selection of dishes .
i. Size of portions .
i. Food taste .
ii. Restaurant cleanliness .
ii. Presentable service staff .
ii. Sense of comfort .
ii. Sense of security .
ii. Restaurant design according to food offerings .
ii. Availability of sanitisers .
iii. Importance of the presence of the manager .
iv. Appropriate answers from service staff .
iv. Helpfulness of service staff .
iv. Responsiveness of service staff .
iv. Service waiting time .
v. Compliments and signs of special attention .
v. Recommendations from service staff .
vi. Accessible entrance .
vi. Accessible parking area .
vi. Neat surroundings .
vii. Understandability of prices .
vii. Accurate bill .
vii. Value for money .
Variance () . . . . . .
period have the following marketing-quality dimen-
sions (in order of importance) – Physical Evidence,
Product, Promotion (and importance of the presence
of the manager), Processes, Placement, and Price. In
terms of the dimension Promotion, one indicator (iii.2
importance of the presence of the restaurantmanager)
was added to the two indicators belonging to the di-
mension Promotion. Accordingly, we have decided to
keep the initial name of the marketing dimension.
After extrapolating quality factors that best present
the marketing construct of quality expectations in the
post-covid-19 pandemic period, we analysed poten-
tial differences between the two independent samples
(groups of respondents).
Mann-Whitney U Test
We performed a Mann-Whitney U test to investigate
the differences between the two independent samples
(different groups of respondents). Themain reason for
choosing the U test lies in the asymmetric distribution
of the data. To perform the U test, we formulated the
null (Ho: Me1 = Me2) and the alternative hypothesis
(h1: Me1 = Me2) for each pair of identified variables
(quality indicators). Research results revealed statisti-
cally significant differences (p ≤ 0.050) exist between
guests’ and managers’ expectations at six quality di-
mensions (see Table 5). Ho was rejected in favour of
h1 for nineteen indicators (i.1 selection of dishes, i.2
size of portions, i.3 food taste, ii.1 restaurant cleanli-
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Marko Kukanja A 7P Comparison between Restaurant Managers’ and Customers’ . . .
Table 5 U Test: Marketing-Quality Dimensions
Item p ii p i p v p iv p vi p vii
Mann-Whitney U test .. .. .. .. .. ..
Wilcoxon W value .. .. .. .. .. ..
Significance < . < . . < . . < .
ness, ii.2 presentable service staff, ii.3 sense of com-
fort, ii.4 sense of security, ii.5 restaurant design fol-
lowing food offerings, ii.6 availability of sanitizers,
iii.2 importance of the presence of restaurant man-
ager, iv.1 appropriate answers from service staff, iv.2
helpfulness of service staff, iv.3 responsiveness of ser-
vice staff, iv.5 service waiting time, v.2 compliments
and signs of special attention, v.3 recommendations
from service staff, vi.1 accessible entrance, vi.2 ac-
cessible parking area, and vi.3 neat surroundings) be-
longing to five quality dimensions (Physical Evidence,
Promotion, Processes, Product, and Placement). At the
same time, Ho was confirmed only for three indi-
cators (vii.1 understandability of prices, vii.2 accu-
rate bill, and vii.3 value for money), belonging to the
marketing-quality dimension Price. Results indicate
that no statistical differences between both groups of
respondents exist only for the marketing-quality di-
mension Price. Results of the U test provided the an-
swer to our rq2.
Discussion
In reviewing the literature, we found no evidence of
comparing restaurant managers’ and customers’ qual-
ity expectations in the post-covid-19 pandemic pe-
riod. Accordingly, the purpose of this work was to
(1) identify the most relevant marketing-quality di-
mensions for assuring restaurant quality in the post-
covid-19 pandemic period (rq1) and (2) investigate
differences between managers’ and customers’ expec-
tations for restaurant quality offerings in the post-
covid-19 pandemic period (rq2).
In terms of differences betweenmanagers and cus-
tomers, the mean comparisons indicated that man-
agers have higher quality expectations than customers
(md = 0.22). Interestingly, the highest-rated dimen-
sion for both groups was Physical evidence, with ‘res-
taurant cleanliness’ as the highest-rated indicator for
both groups of respondents, indicating the impor-
tance of cleanliness and safety perceptions in the post-
covid-19 pandemic period. The lowest rated quality
indicators were ‘use of alternative means of payment’
for managers and ‘advertising activities in the media’
for restaurant customers. Both indicators also prove
not crucial for explaining the overall quality structure
as they were excluded from the efa eliminations pro-
cess.
The efa structure of quality expectations revealed
that the most critical marketing-quality dimensions
for defining managers’ and customers’ quality expec-
tations in the post-covid-19 pandemic period con-
sist of 22 indicators and six marketing-quality dimen-
sions, thus answering rq1. The two most important
quality dimensions are Physical evidence and Prod-
uct. Results indicate the importance of the tangible
elements for assuring restaurant quality in the post-
covid-19 pandemic period. Tangibles were identified
as essential elements of restaurant quality in many
pre-pandemic studies (e.g. Mosavi & Ghaedi, 2012;
Namkung & Jang, 2007; Shapoval et al., 2018). Inter-
estingly, the marketing-quality dimension People did
not prove to be a common latent variable for the over-
all explanation of the quality construct in the post-
covid-19 pandemic period. However, it was relatively
highly evaluated by both groups of respondents (see
Table 3).
This finding is also unexpected since the dimen-
sion People proved to be essential for determining
restaurant quality in all previous marketing-based
quality studies (Kukanja et al., 2017) and many other
rater (Servqual)-based studies (Mosavi & Ghaedi
2012; Voon, 2012). This finding must be interpreted
with caution since the quality of restaurant staff is di-
rectly associated with the quality assurance of other
260 | Academica Turistica, Year 15, No. 2, August 2022
Marko Kukanja A 7P Comparison between Restaurant Managers’ and Customers’ . . .
intangible and many tangible (e.g. neat surroundings)
elements of restaurant quality offerings.
Of seven items included in the generic research
model, only one indicator, ‘availability of sanitisers,’
proved significant for assuring restaurant quality in
the post-covid-19 pandemic period. This finding
additionally reconfirms the importance of safety for
explaining the post-pandemic quality construct. The
other included indicators proved not to be important.
Therefore, we might conclude that the crisis has not
influenced customers’ and managers’ expectations re-
lated to the employment of local staff, use of local in-
gredients, possibility of using it, information about
safety protocols, food delivery or take away, and the
possibility of using alternativemeans of payment. This
is an interesting finding, as, during the pandemic,
managers and customers heavily relied on it, local
customers and suppliers, and the possibility of food
delivery and take away (Brewer & Sebby, 2021; Press-
man et al., 2020; Yang et al., 2020). Overall, we might
conclude that managers and customers will still pre-
fer the ‘traditional’ restaurant quality indicators, such
as cleanliness, food taste, helpfulness and recommen-
dations from service staff, compliments and signs of
special attention, and good value for money (see Ta-
ble 4).
Based on research results, we found that statisti-
cally significant differences exist between managers’
and customers’ quality expectations (rq2). Differ-
ences were found at five quality dimensions (out of
six), indicating a significant gap in quality expecta-
tions between managers and customers. According
to the Gap model (Parasuraman et al., 1985), differ-
ences between customer expectations and manage-
ment’s understanding (knowledge) of those expecta-
tions present the first gap in providing offerings of
satisfactory quality. This gap is also referred to as a
listening or information gap rather than a knowledge
gap in a digitalised big-data world where customers
have free access to social network platforms (Zhang,
2019).
The only quality dimension where no differences
were foundwas in the dimension Price, indicating that
managers and customers have the same quality expec-
tations concerning the understandability of prices, bill
accuracy, and value formoney. These results are some-
what unexpected and challenging to explain, primarily
due to the lack of comparable (marketing-based) re-
search findings. For example, Kukanja (2017) reported
differences between all seven marketing-quality di-
mensions. We might assume that the results of our
study might be somehow related to the price elasticity
of the restaurant industry during and after the pan-
demic. As an economic measure of sensitivity, price
elasticity results in significant demand changes due to
minor changes in price or income levels. Foroudi et al.
(2021) reported that household income significantly
impacted customer buying behaviour during the pan-
demic.
Similarly, Kim et al. (2021) found that customers
seem to be more demanding during the crisis and
consume food items that signal the best value for
money. Based on research results (see Table 5), it seems
that managers are aware of customers’ price sensitive-
ness and will do their best to meet their customers’
price-related quality expectations in the post-covid-
19 pandemic period. As managers are aware of cus-
tomers’ price-related expectations, we might assume
that restaurants will not raise their selling prices to
compensate for the income lost during the lockdown.
These findings are also supported by the same post-
pandemic values of customer asp since most man-
agers and customers reported expecting an asp be-
tween €11–20.
Altogether, from the marketing-mix perspective,
the central issue of this study’s results are the iden-
tified differences (quality gaps) between most of the
identifiedmarketing-quality dimensions (see Table 4),
which also explain themajority of variance of the post-
covid-19 pandemic quality construct.
Conclusion
This research contributes to themarketing and restau-
rant management literature by explaining the signif-
icance of different marketing-quality indicators and
analysing differences between managers’ and custom-
ers’ quality expectations in the post-covid-19 pan-
demic period. By applying amarketing-based research
concept, we have also facilitated an international bench-
marking research process.
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Marko Kukanja A 7P Comparison between Restaurant Managers’ and Customers’ . . .
However, to provide recommendations for future
research, several limitations of this study must be ad-
dressed. This study included only domestic customers.
Consequently, following studies should apply an inter-
national perspective and include the various customer
segments. Future research should also use a combi-
nation of research approaches. A qualitative research
approach, in particular, could provide amore in-depth
analysis of quality expectations. This research was
conducted during a relatively short period. As this is
an ongoing pandemic, future research should take a
longitudinal approach to understand the impact of the
pandemic on the restaurant industry. Moreover, data
gathering that was traditionally performed in person
(face to face) was collected online, which may have
also influenced the quality of the research. From this
point of view, we have obtained a relatively low num-
ber of valid questionnaires frommanagers, which dis-
abled a more rigorous statistical analysis of the data.
Accordingly, future studies focused on the validation
of the marketing-quality scale using a confirmatory
factor analysis (cfa) are welcomed. Respondents were
also asked to indicate their future quality expectations,
whichmay change if the pandemic persists over a long
time. Therefore, quality expectations should be mon-
itored regularly. Another recommendation for future
research refers to the creation of a nomological net-
work. The purpose of the nomological net is to show
how the identified post-covid-19 pandemic quality
construct is theoretically and empirically related to
other concepts in tourism and hospitality marketing
(customer satisfaction and return patronage, brand
equity etc.).
In terms of applicability, our findings offer di-
rections for revising restaurant quality management
strategies and re-modifications of marketing busi-
ness models. Restaurants should promote their of-
ferings following customers’ expectations to provide
satisfying and enjoyable customer experiences. Man-
agers should communicate what type of co-creation
behaviour (e.g. wearing masks, maintaining physical
distance) is required from customers to provide and
maintain a safe restaurant atmosphere, as customers
and managers have the highest expectations regard-
ing Physical evidence. Managers should also correctly
train their personnel (People) on how to provide high-
quality restaurant offerings.
Finally, we recommend that managers constantly
monitor customers’ quality expectations and percep-
tions and adequately adjust their businessmodels. The
digitalisation of the business environment has created
a plethora of new opportunities and challenges. The
online social network platforms present a relatively
easyway to collect preliminary information about cus-
tomer quality expectations. From this point of view,
academia and restaurant associations should also as-
sist the industry in analysing customers’ quality expec-
tations and adjusting restaurant firms’ business mod-
els proactively.
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