Examining Customers' Intention and Attitude Towards Reading Restaurants' Menu Labels by Using the Theory of Planned Behaviour

1 International Tourism and Hospitality Journal (ITHJ)
https://rpajournals.com/ithj

ITHJ
International Tourism and Hospitality Journal
Journal Homepage: https://rpajournals.com/ithj
Examining Customers' Intention and Attitude Towards
Reading Restaurants' Menu Labels by Using the Theory
of Planned Behaviour
Iman Shawky*1
Mostafa Abo El Enen2
Amr Fouad3
Alexandria University, Egypt1,2
Pharos University, Egypt3
Abstract
Availability of nutritional information through menu labels is important not only for consumers, as it
helps them make informed and healthier food choices, but also for restaurants as a marketing tool.
While the Theory of Planned Behaviour (TPB) focused on attitudes, subjective norms, perceived
behavioural control, and intention constructs; this study depended on that theory to examine effects
of menu nutritional information on customers' attitude and intention to read such information. This
aim was accomplished through a number of sub-objectives and hypotheses towards reading menu
labels by which investigating new relationships on the (TPB) in the context of independent or
standalone, four, and five-star restaurants in Alexandria, which considers the second major
conurbation in Egypt. Furthermore, A five-point Likert scale questionnaire was used for testing
hypotheses. The results indicated that customers had a positive attitude and intention to read menu
labels. Besides, there was no correlation between subjective norms and the behaviour, and similarly
between both attitude and behaviour of reading menu labels. Finally, the study presented suggestions
to restaurants' decision makers for using various methods to display menu labels effectively.
Keywords: Hotels' Restaurants, Independent or Stand-Alone Restaurants, Nutritional Menu
Labelling, Planned Behaviour Theory
Introduction
The restaurant industry is considered a major contributor in national economics and one of the most
important sectors of the labour force (Hallak, Assaker, O’Connor, & Lee, 2018). In the United
States; around 14.7 million persons work in that industry, which will be expected to reach to 16.1
million by 2026 (National Restaurant Association, 2016). Also, in Egypt, employees work in the
food service industry, which reached 5.9% of total civil employees in the public business sector
(Central Agency for Public Mobilization and Statistics, 2018).
Researchers discussed that developing countries are suffering from obesity, which becomes
prevalent in them (Borai, Soliman, Ahmed, & Kassim, 2018; Hassan, El-Masry, Batrawy, Khalil,
Ali, Al Tohamy, et al., 2018). They pointed it out because of its negative effects on quality of life
(Li, Fujiura, Magaña, & Parish, 2018) and definitely increasing medical expenses (Li, et al., 2018);
RPA
Journals
International Tourism and Hospitality Journal 2(4): 1-14 (2019)
Print ISSN: 2616-518X
Online ISSN: 2616-4701
*Corresponding author: Iman Shawky1
; E-mail: iman.shawky@alexu.edu.eg


since outsourcing food, which is prepared outside home, is highly in unhealthy and unbalanced
components (Feldman, Hartwell, Brusca, Su, & Zhao, 2015; Paddock, Warde, & Whillans,2017)
which may cause other diseases (Lim, 2018). All these proved that it is necessary for restaurants'
customers to be aware of nutrition information of the menu items (Nurdiantami, Watanabe, Tanaka,
Pradono, & Anme, 2018). However, obesity of most customers goes back to their lack of physical
exercise not to the restaurants' responsibility (Aldaihani & Ali, 2018; Ditlevsen, Sandøe, & Lassen,
2019).
On the one hand, the World Menu Report Global Research, 2012, stated that most of
customers have a desire for the availability of nutritional information when eating out.
Consequently, some governments have developed specific regulations for restaurants, up to twenty
branches, to include calorific information on menus and menu boards to help customers order
nutritional food they need (Green, Brown, & Ohri-Vachaspati, 2015; White, Lillico, Vanderlee, &
Hammond, 2016).
Studying the effect of menu nutritional information on customers' intention and attitude
will provide valuable insights about what influences customers to choose healthier food. It helps
marketers and menu planners establish adequate strategies which allow the restaurant industry to
gain revenues (Chu & Jones, 2014).
While few researches focused on examining Egyptians issues of restaurants' nutrition
information, this study tries to identify factors that motivate customers to read menu labels by
testing relations among subjective norms, attitude, behaviour, and perceived behavioural control.
Literature Review
A Menu as a Marketing Tool for Restaurants
Menus are the first item that welcomes guests (El-Sherie & Ghanem, 2013). They become a
marketing mean as they attract customers and give them a first impression of restaurants (Baiomy,
Jones, Elias, & Dinana, 2013). Therefore, the purposes of menus are to provide accurate and
attractive information for provided dishes (Fakih, Assaker, Assaf, & Hallak, 2016). Also,
encourage easy navigation between hunger and satisfaction for customers (Leib, Reynolds, Taylor,
& Baker, 2017). Therefore, restaurateurs should ensure that information provided match customers’
expectations and satisfaction also can stimulate their desires (Beldona, Buchanan, & Miller, 2013).
Theory of Planned Behaviour
There are a number of theories seeking to model the process whereby attitudes might be translated
into behaviour, while other behavioural factors are taken into account (Volkova & Mhurchu, 2015).
One of the most commonly used and accessible frameworks is Ajzen’s (TPB). It is formed on the
premise that the combination of attitude towards the behaviour, subjective norms, and perceived
behavioural control are significantly correlated with behavioural intentions, which in turn are the
proximal determinants of behaviour (Connor & Whiteford, 2014).
Behavioural Intention
Intention is defined as a plan for acting a specific behaviour and the more important factor for
direct forecasting behaviour (Ajzen, 1991). This can be illustrated that, intentions not only are the
motivational elements that affect behaviour but also are signs of the level of people's willingness to
do something. So, customers do behaviours when their intentions come to be stronger (Ajzen &
Fishbein, 2000). Thus, while the strength of intention is referred to a positive or negative attitude,
the behaviour is more likely to happen and is affected by the intention (Kim, Ham, Yang, & Choi,
2013; Islam, Jantan, Khan, Rahman, & Monshi, 2018).
In restaurants' field, Jun & Arendt, (2016) examined factors that affect customers' intention
to choose healthy food, in which low calories and fats, by using value-attitude-behaviour model.
The results showed that health value has a positive effect on attitude and intention to behaviour.
This is also supported from the research of (Aldaihani & Ali, 2018). Moreover, attitude towards


healthy food has a positive impact on intention to purchase such type of food. Also, attitude
towards the taste of healthy menu items has an impact on the intention to purchase or repurchase,
recommend to relatives and friends, and spread positive word of mouth about these items.
Similarly, Kim & Ham (2016) suggested factors that utilized to measure the intention to read menu
labels before ordering food; such as customers' willing to read nutritional labelling, the willing to
make efforts, the planning and the wanting to read such information.
Furthermore, Stran, Knol, Severt, & Lawrence, (2016) explained that if customers have the
intention to read calorie information, it can be expected that they will actually read it in case of
both the availability of it, and the time to read it. Likewise, Kim, Kim, Choi, & Ham, (2018)
investigated the intention to select healthy food in restaurants and measuring that by focusing on
the plan, willing, intention and customers' ability to make efforts to choose healthy items on menus.
Subjective Norms
Ajzen (1991), referred to subjective norms as a social pressure that is perceived to do or not to do
the behaviour, while Delvarani, Othman, & Ghazali, (2013) defined them as the perceived pressure
from others to perform or not perform a specific behaviour. Furthermore, Stran, et al., (2016)
described them as a perceived health behaviour that is approved or disapproved by others in the
personal social life. Likewise, Close, Lytle, Chen, & Viera, (2018) interpreted them as the beliefs
of others that are perceived regarding behaviour.
From previous mentioned definitions, subjective norms can be concluded as the opinion of
others who are close to individuals, affect decision making, and lead their behaviour to perform or
not perform an action.
Moreover, subjective norms significantly moderate the relationship between attitudes and
buying intention, also influence attitude towards buying intention (Al-Swid, Huque, Hafeez, &
Shariff, 2014); particularly they play an important role in forming the intention to purchase green
food (Ham, Jeger, & Ivković, 2015), as well as between perceived behaviour control and intention
to consume organic food (Al-Swid, et al., 2014).
In addition, many studies indicated subjective norms to be as a predictor for intentions to
read nutrition information; such Delvarani, et al., (2013) who found that subjective norms are
positively and significantly related to intention to use menu labelling between customers' quick
service restaurants in Malaysia. On the other hand, Kim, et al., (2013) demonstrated no relationship
between subjective norms and intention to read menu labels in casual dining restaurants in Korea.
While, Stran, et al., (2016) reached that subjective norm is one of the constructs affecting college
students' intention to read posted calories on the full service menus.
Accordingly, this research employs subjective norms as a key construct of interest in
proposing an association between subjective norms and intention to read the nutrition information
on the menu in a restaurant setting. In addition, it suggests that subjective norms are a major
intention determinant to behaviour.
Attitude
It refers to “the degree to which a person has a favourable or unfavourable evaluation or appraisal
of the behaviour in question” (Ajzen, 1991: 188). To illustrate; performing a particular behaviour is
reflected by the psychological state of the person who performs the individual's positive or negative
evaluation (Carrasco & Lucas, 2015). That means, Attitude originates from a combination of more
specific, salient, behavioural beliefs which reproduce perceived outcomes related to the targeted
behaviour.
While behavioural beliefs produce a positive or negative attitude towards that behaviour
and related to the outcomes of doing it; Ajzen (1991) proposed that a favourable or unfavourable
attitude is precisely proportional to the strength of the behavioural mind-set regarding a likely
outcome of action derived from an expectancy-value model.
As attitude plays an important role in forming consumer's intention to read menu labelling
(Wansink & Love, 2014), the preferred information about menu items leads customers to have a
positive attitude towards the restaurant which present such information (Fakih et al., 2016). And


when favourable nutritional information and health claims are added to restaurants' menus and pre-
packaged food, a customer's favourable attitude towards both the menu item and the product will
increase. Similarly, the attitude towards the risk of heart diseases after eating will decrease
(Newman, Burton, Andrews, Netemeyer, & Kees, 2018).
Thus, the present study posits a relationship exists between attitude and behavioural
intention to read nutritional labelling in stand-alone and hotel restaurants.
Perceived Behavioural Control
According to Ajzen, (1991: 188), perceived behavioural control is identified as “the perceived ease
or difficulty of performing the behaviour”. Also the (TPB) depends on it when actual resources and
opportunities of the actual behaviour have difficulties to be measured. Besides, it originates from
the control beliefs which are all perceived resources and opportunities to perform a specific
behaviour, and assessment the significance level of such resources and opportunities for the
achievement of the results. That means beliefs of barriers to use menu labelling affect positively on
its usage (Jeong & Ham, 2018).
While Stran, et al., (2016) measured the perceived behavioural control by asking about
customers' confidence to have the ability to read nutritional information to make their healthy
choices, Shin, Im, Jung, & Severt, (2018) measured it towards organic menus by questioning the
customers about available resources in the form of money, time, and the perceived presence of the
capability and confidence to choose them.
To collect all mentioned theory's items, attitude, subjective norms, and perceived
behavioural control are associated with customer intention to use menu labelling in fast food
restaurants (Delvarani et al., 2013). Also, they associated with the intention of using calorie labels
(Stran, et al., 2016).
Research Objective
The primary aim of this study was to investigate menu labels' effects on customers' intention and
attitude to read such information in independent or stand-alone and hotels' restaurants in
Alexandria. This aim was accomplished through a number of sub-objectives towards reading menu
labels. Firstly, to investigate subjective norms effects on customers' attitude. Secondly, to
investigate subjective norms effects on customers' intention. Thirdly, to examine subjective norms
effects on customers' behaviour. Fourthly, to explore the attitude effects on customers' behaviour.
Fifthly, to study the effects of attitude towards reading menu labels on customers' perceived
behavioural control. Sixthly, to investigate the attitude effects on customers' intention. Seventhly,
to study effects of customers' perceived behavioural control on their intention. Finally, to examine
the effect of customers' perceived behavioural control on their behaviour.
Hypotheses
According to what have been mentioned above, the present study tried to achieve its main
objective by investigating new relationships among the (TPB) dimensions. Thus, the hypotheses
towards reading menu labels are;
H1: There is a relationship between subjective norms and attitudes.
H2: There is a relationship between subjective norms and intention.
H3: There is a relationship between subjective norms and behaviour.
H4: There is a relationship between attitudes and behaviour.
H5: There is a relationship between attitudes towards behaviour and perceived behavioural
control.
H6: There is a relationship between attitudes towards behaviour and intention.
H7: There is a relationship between perceived behavioural control and intention.
H8: There is a relationship between perceived behavioural control and behaviour.


Methodology
This study depended on the descriptive approach to capture a clear picture about attitude and
intention of restaurants' customers towards reading menu labelling in targeted restaurants in
Alexandria, Egypt. It could be also categorized as exploratory one; since it aimed at discovering
new relations on the (TPB) model. Also, it desired to understand both customers' attitude and
intention to read menu labels by relaying on the model.
Furthermore, the study adopted mixed methods for collecting and analysing data; a
quantitative method by using the check list to investigate the extent to which targeted restaurants
apply nutrition labels, as well as the questionnaire form to test the research hypotheses. In addition,
the research used a probability sample technique to ensure generalizability particularly in
Alexandria. Besides, a positivist approach was used; in which predetermined and highly structured
data collection techniques are utilized to differentiate between customer's attributes and opinions.
Moreover, the deductive approach was used to test the theory (Hyde, 2000). Accordingly, the
survey constructed according to guidelines by Ajzen 2002. Thus, the study's population was
conducted on customers who dine at stand-alone and hotel restaurants in Alexandria, as seen in
Table 1.
To get the actual number of Alexandria's restaurants; both the Egyptian hotels guide
(Egyptian Hotel Association, 2015-2016) and the records of the Egyptian Ministry of Tourism
published in 2017 were utilized.
Stratified random sampling used and the sample was divided into three stages. First,
restaurants were separated into two sectors; stand-alone and hotels' restaurants which are all
belonged to four and five-star restaurants category. Second, restaurants selected from the
mentioned categories by using a stratified random sample. Third, the small simple random
customers' sample was selected, see Table 2.
A five-point Likert scale questionnaire comprised demographic data, theory of planned
behaviour constructs, and finally types of information and restaurants that customers need, as was
presented in Table 3.
Furthermore, a pre-test was conducted by involving a sample of university students to
assess the degree of understanding the survey questions. Thus, the questionnaire's questions were
developed based on related previous studies; which proved afterwards to meet the validity
requirements. Also, three stages were conducted in order to pilot the questionnaire. It was presented
to colleagues, academic experts, and targeted restaurants' respondents for responding and
identifying the extent to which each sentence is appropriate; firstly, the questionnaire was
accessible for twenty post graduates who are preparing for their master degree at the Department of
Hotels Management in Faculty of Tourism and Hotels in Alexandria University. Secondly, twenty
four questionnaires were distributed among four academic staff who were specialized in the hotel
management researches at the same faculty, besides twenty academic staff who were specialized in
nutrition and food science. That allowed the researchers to gain insightful feedback about the
appropriate fitting words to be employed in the questions, layout and design. Finally, face to face
interviews with nine managers in five-star restaurants in Alexandria were conducted.
The internal validity is supported by the use of randomization, while the external validity is
supported by the incidence of a community sample of both males and females of diverse races
/ethnicities with a variety of BMIs (though BMI data were self-reported).
The researchers used the "Cronbach's Alpha Measurement" to assess the reliability of the
whole questionnaire (Bonett & Wright, 2015). Thus, while the value of Cronbach's Alpha for each
construct of the questionnaire that exceeds 0.60 can be perceived accepted, the overall value of the
questionnaire was (0.764).


Table 1: Population and Sample of the Study
Elements of the Target
Population
Four and five-star stand-alone/independent restaurants (chains and independent)
in Alexandria
Four and five-star hotels' restaurants (chains and independent) in Alexandria
Sampling Design Probability sample
Sampling Technique Stratified random sample
Random Sample Size
45 Restaurants
16 Hotels' restaurants
Equal Sample Size 20 Questionnaire distributed for every restaurant
Sample Subject The restaurants' customers
Table 2: Sample Size
Category of
Restaurants
Number of Restaurant
Total
% of Total
Population
Sample
SizeChain Independent
Stand-alone/Independent
Restaurants
star-4 27 27 54 74% 40
5-star 3 16 19 26% 5
Total 30 43 73 100% 45
Hotels' Restaurants
4-star 12 4 16 54% 9
5-star 14 - 14 47% 7
Total 26 4 30 100% 16
Results and Analysis
Out of the 1220 questionnaires, 950 were collected, but only 790 questionnaires were valid, which
counted for 65% of the total satisfying response sample rate, see Table 3. Moreover, Statistical
Package for Social Sciences (SPSS, V.23) was employed to analyse the collected quantitative
research data.
Table 3: Respondents' Profile
Item Frequency %
Gender
Female 460 58.2
Male 330 41.8
Nationality
Egyptian 722 91.3
Foreigners 68 8.61
Age
Less than 20 166 21.1
20 to 39 460 58.2
40 to 59 114 14.4
60 and more 50 6.3
Marital Status
Single 564 71.4
Married 94 11.9
Married with children 126 15.9
Other (………..) 6 .8
Educational Level
Secondary school 30 3.8
Two years after secondary school 12 1.5
University student 148 18.7
Bachelor's degree 596 75.4
Doctorate degree 4 .5
Monthly Income
Less than 1000 L.E 154 19.5
From 1000 to less than 3000 186 23.5
From 3000 to less than 5000 312 39.5
From 5000 to less than 7000 54 6.8
7000 and more 84 10.6


Theory of Planned Behaviour (TPB) variables
The variables were contained in five subsections, as observed in Table 4, the overall responses are
high with a value range from 2.02 (standard deviation- STD 0.25) to 3.61 (STD 1.05) and the
overall mean for all dimensions is 3.26 (STD 0.84).
The mentioned mean's values indicated that the customers in the targeted restaurants had
the attitude, perceived behavioural control, subjective norms, and intention to read menu labels.
Table 4: Descriptive Statistics for the (TPB) Dimensions
TPB Model (Mean = 3.10) Mean S.D Rank
Attitude 3.61 1.047 1
Subjective Norms 3.58 1.058 2
Perceived Behavioural Control 3.56 1.066 3
Intention 3.56 1.066 3
Behaviour 2.0203 0.24838 4
Correlation among Variables
Table 5 presented a multi correlation matrix of study's variables. Spearman (r) correlation analysis
was conducted to investigate the relationship between these variables. Moreover, regression
analysis was also utilized to understand which independent variables (attitude, subjective norms,
and perceived behavioural control) are related to the dependent variables (intention and behaviour),
and to explore the forms of those relationships.
The results demonstrated that, subjective norms were significantly and positively correlated
with the attitude towards reading menu labels (r = .969, P < 0.01). That agreed with Kim et al.,
(2013) which indicated that consumers’ perceived subjective norms were more likely to help
consumers gain a positive attitude towards behaviour from the consequences of the behavioural
intention.
As well, subjective norms were correlated positively and significantly with the intention to
read menu labels (r = .985, P < 0.01), that was in line with Delvarani, et al., (2013) and Stran et al.,
(2016), it also supported Latiff, Ruslee, & Ayob, (2016) who found that subjective norms were
correlated significantly and positively with the intention to buy food products with labels.
Furthermore, subjective norms were not significant and correlated to the behaviour of
reading and using menu labels, and that was in line with Ge, Behnke, & Almanza, (2014).
Similarly, that was somewhat contradictory to the previous findings; where subjective norms were
having a positive effect on the intention to read menu labels. In addition, attitude towards reading
menu labels was significantly and positively correlated to perceived behavioural control (r = .961,
P < 0.01). That was in an agreement with Din, Zahari, & Shariff, (2012) and Stran, et al., (2016).
Moreover, attitude was significantly and positively correlated to the intention to read menu
labels (r = .956, P < 0.01). That was parallel with Stran (2013) and stated that attitude predicted
greater intention to use calorie information in full-service restaurants. Furthermore, this was in
agreement with previous studies about dietary behaviour (Grønhøj, Bech-Larsen, Chan, & Tsang,
2012; Fila & Smith, 2006).
Frequencies that Customers Eat at Restaurants per Week
1 466 59.0
2 244 30.9
3 54 6.8
4 18 2.3
5 and more 8 1.0
Kinds of Restaurants that Usually Customers Eat at
Fast food chain restaurants 386 48.9
Fine dining 276 34.9
Small local 20 2.5
Cafes 108 13.7


Also, attitude was not significantly and correlated to behaviour to read and use menu
labels. Although that was consistent with Howlett, Burton, Bates, & Huggins, (2009) who declared
that the disclosing of nutrient information significantly changes initial product attitudes and
purchase intentions, it was different from Song, Huang, Chen, Zhu, Li, Wen, et al. (2015) who
pointed that attitude towards nutritional labels affects the use of the label.
Besides, the perceived behavioural control significantly and positively correlated with the
intention to read menu labels (r = .992, P < 0.01). That matched with Stran (2013) who pointed out
that perceived behavioural control is predictive of intent to use menu labels, and confirmed by Kim
et al., (2013). Also resemble Stran, et al., (2016) who suggested that the (TPB) may help explain
factors involved in the intention to use posted calorie information on a restaurant menu.
In addition, the perceived behavioural control was not significant and correlated to the
behaviour of reading menu labels. In contrast, Ajzen (1991) pointed that perceived behavioural
control may directly affect the behaviour.
Table 5: Correlation among Study Variables
Variables
Subjective
Norms
Attitude Perceived
Behavioural
Intention Behaviour
Subjective Norms 1
Attitude .969** 1
Perceived Behavioural .990** .961** 1
Intention .985** .956** .992** 1
Behaviour .040 .036 .040 .040 1
* Correlation is significant at the 0.05 level (2-tailed).
** Correlation is significant at the 0.01level (2-tailed).
Multi Regression Tests
The results in Table 6 showed a significant and strong positive relationship between subjective
norms and customers' attitude towards menu labels. That recorded 96.8% (R2
= .968) and indicated
that the observed variability in the degree of attitude is explained by the degree of subjective
norms. Also, Beta coefficient (β = .984, P < 0.01) indicated that subjective norms were a significant
predictor of attitude and positively correlated with it. Thus, the attitude increment towards reading
menu labels' degree of restaurants' customers was a function of the degree of subjective norms. So,
H1 was accepted.
Moreover, the results revealed a significant and strong positive relationship between
subjective norms and intention to read menu labels. That recorded 91.1% (R2
= .911) and indicated
that the observed variability in the degree of intention to read menu labels was explained by the
degree of subjective norms. While Beta coefficient (β = .986, p< 0.01) indicated that subjective
norms were a significant predictor of intention and positively correlated with it, the rise in the
intention to read menu labels was related to the improvement in the degree of subjective norms.
Thus, the improvement of the intention to read menu labels was a function of the degree of
subjective norms. Accordingly, H2 was accepted.
Furthermore, there was no significant relationship between subjective norms and behaviour
of reading menu labels. That recorded 3% (R2
= .003) which indicated that the observed variability
in the degree of behaviour of reading menu labels was explained by the degree of subjective norms.
While Beta coefficient (β =.052, p > 0.01) indicated that subjective norms were not a significant
predictor of behaviour of reading menu labels, the increment of customers' behaviour of reading
menu labels was not a function of the degree of subjective norms. Therefore, H3 was not accepted.
Also, there was no significant relationship between attitude and behaviour of reading menu
labels. That recorded 0.1% (R2
= .001) which indicated that only 0.1% of the observed variability
in the degree of behaviour of use is explained by the degree of attitude. While Beta coefficient (β
=.048, P > 0.01) indicated that attitude was not a significant predictor of the behaviour, the
increment of the behaviour of reading menu labels was not related to the improvement in the
degree of attitude. Thereby, H4 was not accepted.


In addition, there was a significant and strong positive relationship between attitude and
perceived behavioural control towards reading menu labelling. That recorded 94.7% (R2
= .947)
which indicated that the observed variability in the degree of perceived behavioural control was
explained by the degree of attitude. While Beta coefficient (β = .973, P < 0.01) indicated that
attitude was a significant predictor of perceived behavioural control and positively correlated with
it, the increase of the perceived behavioural control was related to the improvement in the degree of
the attitude towards reading menu labels. Thus, H5 was accepted.
Similarly, there was a significant and strong positive relationship between attitude and
intention to read menu labels. That recorded 94.3% (R2
= .943) which indicated that the observed
variability in the degree of intention to read menu labels was explained by the degree of the attitude
towards reading menu labels. While Beta coefficient (β = .971, P < 0.01) referred that attitude was
a significant predictor of intention to read menu labels and positively correlate with it, the
increment in the intention to read menu labels was a function of the degree of attitude towards
reading menu labels. Therefore, H6 was accepted.
Likewise, there was a significant and strong positive relationship between perceived
behavioural control and intention to read menu labels. That recorded around 99.0% (R2
= .990)
which indicated the observed variability in the degree of intention to read menu labels was
explained by the degree of perceived behavioural control. While Beta coefficient (β = .995, p <
0.01) indicated that perceived behavioural control was a significant predictor of intention and
positively correlated with it, the increase in the intention to read menu labels was related to the
development in the degree of perceived behavioural control. Therefore, H7 was accepted.
Moreover, there was no significant relationship between perceived behavioural control and
behaviour of reading menu labels. That recorded that 3% (R2
= .003) which indicated that the
observed variability in the degree of behaviour of reading menu labels was explained by the degree
of perceived behavioural control. While Beta coefficient (β=.052, p > 0.01) indicated that perceived
behavioural control was not a significant predictor of the behaviour to read menu labels, the
perceived behavioural control directly influenced customers' behaviour of reading menu labels.
Table 6: Regression Coefficients
Hypothesis R R2
Adjusted R2
B Sig. Hypothesis
H1 (NEW) .984 .968 .968 .973 .000 Accepted
H2 .986 .911 .971 .992 .000 Accepted
H3 (NEW) .52 .003 .001 .012 .144 Rejected
H4 (NEW) .048 .002 .001 .011 .175 Rejected
H5 (NEW) .973 .947 .947 .992 .000 Accepted
H6 .971 .943 .943 .989 .000 Accepted
H7 .995 .990 .990 .995 .000 Accepted
H8 (NEW) .052 .003 .001 .012 .141 Rejected
Recommendations
Accordingly, the present study provide some recommendations which are; restaurants'
decision makers should corporate with health educators, nutritional and marketing experts to
provide customers with nutritional menu labelling in useful and attractive ways. In addition, they
should examine and determine the effective methods to present their menu labelling. Also, they try
exploring strategies that affect their customers' subjective norms, attitude, perceived behavioural
control, and intention to read menu labels. Besides, they should train their staff to know how to use
menu labels to be able to answer customers' nutritional questions.
Discussions and Implications
This study mainly investigated the factors affecting reading menu labels in stand-alone/independent
and hotels' restaurants in Alexandria; as menu labelling can lead to useful future legislations (Giles
& Temby, 2014). Additionally, it aimed at assessing various relationships among the variables that
lead to the intention by using the (TPB).


Additionally, it provided a baseline for whether participants want menu labelling in
restaurants to be mandated or not. For the managerial implications, the study found that although
menu labelling plays an important role for restaurants, some obstacles were preventing applying it,
for instance; the increasing operational costs, training for employees, the time for applying it
(Thomas, 2015), variations on menus, little space on them, and little flexibility to change them.
Moreover, if menu labelling was mandated in large chain restaurants as consumers want, small
restaurants which have little resources would struggle to apply it. So, the study presented a
framework for restaurants' operators to understand the consumer behaviour towards reading menu
labels, which could be beneficial for the population of Egypt. Thus, foodservices restaurants have
to deliver such information in a friendly, comprehensive, and informative way to encourage
customers to choose healthy food.
Furthermore, the results demonstrated that Egyptian legislators should set regulations by
which restaurants present nutritional information on their menus in understandable, accessible, and
direct way; since customers want such information to be mandated for restaurants especially fast
food chain restaurants, which should suggest healthy items on their menus and menu boards.
For consumers' implications, around 63% of Egyptians suffer from overweigh while 90%
do not eat healthy food (Ministry of Health and Population, 2017) because they do not have the
information that helps them to choose their suitable food. So, menu labelling in restaurants will be
beneficial for them to choose their food. Besides, the nutritional information impact indirectly on
the selection of healthy and sustainable items from the menu. Also affect the increasing awareness
about the healthy items and teaches customers to choose such items (Lassen, Lehmann, Andersen,
Werther, Thorsen, Trolle, et al., 2016).
Then, for marketers' implication, delivering menu labels including the nutritional
information claim to be an effective strategy for them since providing such information in
restaurants can gain more economic and social benefits such as sustainability of the restaurant
industry (Leiserowitz, Kates, & Parris, 2006), restaurants' sales, revenues, and brand images (Jang,
Kim, & Bonn, 2011; Namkung & Jang, 2013). Thus, any advancement in technology and
educational system in Egypt will lead to appear new customers segments that care about their
health.
As well as this, equipping menus with such information in restaurants in Egypt will help
them gain good reputation because they pay attention to improving customers' health. Likewise,
menu labelling is considered a corporate social responsibility since customers see the restaurants
offering the nutritional information which can be trusted, therefore they likely to repeat their visits
and be loyal to those restaurants.
Future Direction
This study has some limitations mentioned in the above section, however, future researchers can
conduct further researches in the following areas; investigate the actual behaviour of reading menu
labels and the menu labels' effect on eating healthy food to complete what the current research has
not been explored. Moreover, the evaluation of the influence of the long period before and after
implementing menu labels can be explored in future.
Conclusions
The primary aim of this study was to investigate the effect of menu nutritional information on
customers' attitude and intention to read such information in independent and hotels' restaurants in
Alexandria. This aim was accomplished through some sub-objectives towards reading menu labels
and by using the (TPB) to discover new relationships.
The main important results showed that none of the targeted restaurants provided menu
labels. Furthermore, there was a strong positive relationship between subjective norms and the
intention of reading menu labels. Likewise, there was a positive correlation between attitude and
perceived behavioural control. Also, there was a strong significant correlation between both


attitude and intention to read menu labels. Moreover, customers' perceived behavioural control
affect positively on their intention to read menu labels.
In addition, there was no correlation between both perceived behavioural control and the
behaviour of reading menu labels. Finally, the study presented suggestions for restaurants' decision
makers to use various policies of using menu labels to attract new consumers.
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