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DOI: 10.4018/IJIDE.292493
Volume 13 • Issue 1
Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
*Corresponding Author
1
Wenyan Huang, Zhejiang Financial College, China & SEGi University, Malaysia*
Leong-Mow Gooi, SEGi University, Malaysia
Mobile coupon technology is no longer new technology for a consumer to adopt. This article aims to
explore key factors affecting the intention to redeem m-coupons for customers who are familiar with
mobile phone technology during the COVID-19 situation. A sample of 581 consumers was collected
using an online questionnaire from Jan to April 2021 in Hangzhou, the first internet and smart city
of China. Data were analyzed using partial least squares structural equation modeling (PLS-SEM)
in Smart PLS 3.0 software. Results show m-coupon attitude and m-coupon proneness are positively
affected by past behavior while negatively affected by using distance, which has a positive relationship
with m-coupon redemption intention. While perceived risk is no longer an influential factor, marketers
and merchants can provide more suitable strategies as small-scale, and regional mobile coupons for
precision marketing and coupons can be bundled with different brands for sale.
China, Familiar With Mobile Technology, M-Coupon Attitude, M-Coupon Proneness, Mobile Coupon, Past
Behavior, Perceived Risk, Pls, Redemption Intention, Under COVID-19 Situation, Using Distance
The prosperity solutions of digital commerce during the pandemic unconsciously affect consumer
behavior towards a more digital way. To better confront the economic downturn and pandemic condition,
touchless coupons become the e-commerce solution, the redemption of which increased 56.5% in March
2020 (Ross Chad, 2020). Over 90% of U.S. shoppers search for deals before making any purchase online
(Stephanie Chevalier, 2021). As for China, Hangzhou municipal government was the first to issue mobile
coupons to stimulate consumption during the pandemic. It issued six rounds of government subsidies
totaling 500 million yuan, covering 5.6 million people, which directly drove consumption of 5.97 billion
yuan and the driving leverage is more than 1:11(Hangzhou government, 2021).
With the development and the convenience of technology, many Chinese people have been
used to enjoy mobile phones to surf the Internet and make a purchase. According to the annual
report “Statistical Report on Internet Development in China” announced by China Internet Network
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Information Center (CNNIC) that China has the most digital natives. The scale of mobile internet users
in China is reaching 1 billion, which will constitute the world’s largest digital society (see in Figure 1).
The mobile shopping market is mature in China. Mobile shopping users have reached 781 million,
an increase of 73.09 million from March 2020, which is accounting for 79.2% of mobile Internet
users (see in Figure 2). Furthermore, mobile payment is widely accepted by Chinese people. As of
December 2020, the number of mobile payment users in China has reached 853 million, an increase
of 87.44 million from March 2020, accounting for 86.5% of mobile Internet users (see in Figure 3).
Therefore, mobile technology is nothing new technology for Chinese people.
Previous studies focused on users’ behavior regarding mobile coupons as new technology
(Hyunjoo Im, 2015, Eunju Yoon, Hyunjoo Im, 2014). These studies adopted the Unified Theory
of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model for the
acceptance of new technology (Shen & Chiou, 2010, Perea Y Monsuwé et al., 2004). Emerging from
the Theory of Reasoned Action (Fishbein, 1979) and the Theory of Planned Behavior (Ajzen, 1991),
these models focus on the user intentions and the actual use of technology (Scherer et al., 2019).
As a large base of Chinese people who are familiar with mobile technology, studies based on the
acceptance of new technology may not fit. Moreover, there are relatively little researches on Chinese
users’ mobile coupon redemption intention. Yet, the purchasing power of Chinese mobile phone users
is huge. According to the National Bureau of Statistics of China, from January to April in 2021, the
national online retail sales were 3763.8 billion yuan, an increase of 27.6% over the previous year
and an average increase of 13.9% in the past two years. Therefore, the understanding of Chinese
users’ mobile coupon redemption intention cannot be ignored. This study attempts to fill the gap in
investigating: what are the key factors influencing the m-coupon redemption intention of Chinese
consumers who are familiar with mobile technology during the epidemic condition.
Figure 1. The scale and proportion of mobile internet users in China (in Million)
Figure 2. The scale and utilization rate of mobile online shopping users in China (in million)
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Coupons are the potential of informing customers and encouraging them to respond to price discounts
particular to redemption (Ward & Davis, 1977). Redemption rate referred to the percentage of
eventually returned coupons to the manufacturer (Reibstein & Traver, 1982). The differences in
redemption behavior among consumers are significantly affected by the proportion of intentions to
redeem (Bagozzi et al., 1992, Ramaswamy & Srinivasan, 1998). Early studies on m-coupon redemption
treat mobile coupon as new technology, which employs the theory of reasoned action (TRA), theory
of planned behavior (TPB), technology acceptance model (TAM), and innovation diffusion theory
(IDT) (Dickinger & Kleijnen, 2008, Jayasingh & Eze,2010, Eunju Yoon, Hyunjoo Im, 2014).
Later work found mobile coupons may not be seen as new technology. The redemption of
m-coupon is the tradeoff between the benefit and the cost of the action. Hence, more hypothesis
models showed up. Empirical researches regarding m-coupon redemption are listed below in Table 1.
The notion of motivation is the certain desire characterized by subjective feeling to perform a particular
behavior on a certain occasion (Baumeister, 2016). Motivation has been known as the reason for the
action. The orientation of motivation concerns the why of the deed (Ryan & Deci, 2000). For example,
Agrifoglio et al.(2012) used it in exploring users’ continuing usage of Twitter. In this study, it was
applied in discovering the drivers of the mobile technology’s experiencer to redeem m-coupons.
Intrinsic motivation (IM) refers to essential involvement in satisfying or enjoyable behavior,
which is inherently non-instrumental (Legault, 2020). Researches have linked intrinsic motivation
and intention based on self-sense enjoyment. Tang et al. (2016) used the sense of self-worth and
socializing as intrinsic motivators in studying the intention of users sharing m-coupons.
Extrinsic motivation (EM) refers to the overall performance of a behavior that is essentially based
on attaining effects that are separable from the conduct itself. In other words, EM is a tool, which is
completed to acquire different results (Legault, 2020). Tang et al.(2016) employed economic reward
and reciprocity as extrinsic motivations in the intention of sharing mobile coupons in SNSs.
The motivation of redeeming mobile coupons is subjective, whether it is out of interest of the person
as intrinsic motivation, or it is externally driven as extrinsic motivation. For example, motivations
Figure 3. The scale and usage of mobile network payment users in China (in million)
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that would move individuals to use microcomputers include enjoyment and fun, usefulness (intrinsic
motivation), and social pressure (extrinsic motivation) (Igbaria et al., 1996).
For this study, mobile coupon attitude, mobile coupon proneness, and perceived risk are considered
as variables driven by motivation. First, Souiden et al.(2019) highlighted attitude towards location-
based coupons is incentive by both monetary gains together with hedonic motives. So, mobile coupon
attitude may also be driven by enjoyment of discounts. Second, Nayal et al.(2020a) claimed that
motivations for coupon-prone consumers are easier driven by coupon deals and feel much enjoyable
when getting a good deal. Therefore, mobile coupon proneness shows an extrinsic motivation of a
person towards using a coupon. Moreover, perceived risk is considered as a subjective expectation
of loss (Crespo et al., 2009), which is linked negatively with self-esteem, rigidity, and risking and
positively correlated to anxiety (Park & Jun 2003), showing an intrinsic motivation of a person
towards using coupons.
On the other hand, there are factors influencing coupon redemption that are objective, which
reflect the real condition of mobile coupons or their users. For example, the face value of a coupon
means the normalized coupon value (Reibstein & Traver, 1982), which is the characteristic of a
coupon itself. The real condition of mobile coupons would not change with different consumers.
Yet, different consumers with different motivations may act differently to the same mobile coupon.
Therefore, previous studies regarded them as exogenous factors or moderators. For example, Muncy
& Wilkie(1987) used coupon face values, coupon drops, and expiration dates as exogenous factors.
Nayal & Pandey(2020a) considered digital coupon face value, expiry date, and distance as moderators.
In this study, past behavior and using distance are considered as reality-based variables, which
are the happened history of the individual and the characteristic of the coupon without any subjective
Table 1. Empirical researches on the intention of mobile coupon redemption
Author/s Subjects Basic
model used Key variables
Dickinger &
Kleijnen (2008)
370 mobile phone
users in Austria TAM
Economic benefit (PU), redemption effort (PEOU), fear
of spamming, attitude, perceived control, past behavior,
social norms.
Jayasingh &
Eze(2010)
824 responses in
Malaysia
Extended
TAM
Perceived usefulness, perceived ease of use, coupon
proneness, perceived credibility, attitude, personal
innovativeness, social influence, compatibility.
Eunju Yoon,
Hyunjoo Im
(2014)
587 US consumers TRA
Perceived enjoyment, perceived shopping efficiency,
attitude, perceived ease of redemption, perceived risk, and
subjective norm.
Achadinha et
al.(2014)
204 Students at
university in Africa -Economic benefit, convenience benefit, positive consumer
attitude, perceived control, and social benefit.
Tseng & Chang
(2015)
466 responses from
students and alumni -Brand familiarity, coupon offer statement, coupon face
value, and psychological effects.
Mendelson et al.
(2015)
223 usable responses
from the U.S. and 97
from India
-
Market maven attitudes, coupon proneness, past m-coupon
use, amount of time shopping, m-coupon attitude,
intention to redeem, social norms, and redemption
attitudes.
Gonzalez (2016) 273 responders from
business students -Coupon proneness, redemption efforts, the intention to
redeem
Nayal et al.
(2021)
637 m-coupon users
in India VAM Coupon proneness, perceived convenience, perceived
privacy risk, and repeat usage behavior.
Gonzalez (2021) 280 mobile coupon
users -The effect of value consciousness, the enjoyment of
mobile coupons, and the impulse buying tendency (IBT).
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feelings. The redemption behavior is affected by motivation, which is formed based on reality. It
stands from the trade-off between the reality provided for the consumer to decide whether he has
the intention to redeem a mobile coupon and whether the motivation adds driving factors for him
to redeem. This forms a model of “reality-motivation-intention” to study consumers’ intention of
redeeming mobile coupons (Framework in Figure 4).
Motivate-Driven Variables of Mobile Coupon Redemption
Mobile coupon attitude. Attitude is the driving force of consumer utility and attributes (Lancaster.
1966). Fishbein and Ajzen (2010) defined attitude as a potential temperament or tendency to react
to a psychological object with some favor or unfavorite. Empirical studies expand the TAM model
to include attitudes as defined by the Theory of Reasoned Action (Jahangir & Begum, 2007), which
indicated an individual’s positive or negative evaluation or general feeling towards performing a target
behavior (Nor et al., 2008). The sense of attitude by an individual is regarded as the main factor of
the willingness to redeem e-coupons (Dickinger & Kleijnen, 2008). Therefore, attitude is adopted as
a motivate-driven variable in this model. When a positive attitude towards m-coupons is raised with
consumers, that would develop an intention to redeem the coupon (Achadinha et al., 2014).
The following are hypothesized:
Hypothesis One: A positive attitude towards m-coupon will be positively related to consumers’
intention in redeeming m-coupon.
Mobile coupon proneness. Coupon proneness is defined as an increase in the tendency to respond
to purchasing offers because the coupon format of the purchase offer has a positive impact on the
purchase valuation (Lichtenstein et al., 1990). Consumers are stimulated by the coupons not only
because of the reduced price but also the psychological gains (Nayal & Pandey, 2020b). Moreover,
Figure 4. Framework for intention to redeem mobile coupons
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coupon-prone consumers tend to treat coupons as a good bargain and do not keep their eyes open for
other products (M. F. Chen & Yi, 2011). We may assume coupon proneness as extrinsic motivation.
This is considered a strong predictor of coupon usage (Gonzalez, 2016). Liu et al.(2015) argued that
coupon proneness has a positive impact on consumers’ acceptance of the M-Coupon application.
The following is hypothesized:
Hypothesis Two: M-coupon proneness is positively related to consumers’ redemption intention of
m-coupon.
Perceived risk. The concept of perceived risk represents a condition of psychological uncertainty
(C. C. Chen et al., 2018). It is defined as an unexpected loss that comes across the process of reaching
a result (Featherman & Pavlou, 2003). Many past studies have shown that perceived risk adversely
affects the behavioral intent and usage behavior of online consumers (Chopdar et al., 2018). It is in
regards to the online environment where consumers need to trust the involved technology to perform
various search and purchase-related tasks (Bianchi & Andrews, 2012). Financial risk, product risk,
and time/convenience risk may occur in the process (Forsythe et al.,2006). Mobile coupon users may
face the perceived risk of leaking their personal information while using the application and services
to acquire the coupon (Im & Ha, 2013). Tang et al. (2019) argue that the perceived risk negatively
influences the mobile coupon redemption intention.
The following are hypothesized:
Hypothesis Three: Perceived risk is negatively related to consumers’ redemption intention of
m-coupon.
Reality-Based Variables of Mobile Coupon Redemption
Past behavior of using mobile coupons. An individual’s past behavior can control at least some of the
omitted variables. Thus, it often better explains his / her current behavioral intent and future actual
behavior (M. F. Chen & Yi, 2011). Bagozzi et al.(1992) argued past behavior does not directly affect
subsequent behavior but intentions of the behavior. Specifically, past behavior is a determinant of
intentions to use coupons. Consumers who have used coupons in the past feel more positively towards
using coupons in general and are likely to try on other types of coupons (Dickinger & Kleijnen, 2008).
For this reason, that past behavior of using mobile coupons may lead to future usage of mobile
coupons, a consumer who has a positive attitude towards mobile coupons would positively use mobile
coupons in the future. Similarly, people who are more inclined to use coupons will be more active
in redeeming mobile coupons. Their behavior today will continue their behavior in the future. For
the perceived risk, more usage of mobile coupons would make consumers more used to redeeming,
thus the behavior becoming less risky. For example, Nayal et al. (2021) highlighted that the repeat
usage behavior of mobile coupons helps to reduce the risk on intention to redeem the mobile coupon.
The following are hypothesized:
Hypothesis Four(a): Past behavior of using m-coupons is positively related to mobile coupon attitude.
Hypothesis Four(b): Past behavior of using m-coupons is positively related to mobile coupon
proneness.
Hypothesis Four(c): Past behavior of using m-coupons is negatively related to perceived risk.
Using distance of mobile coupons. Previous studies highlight the importance of location proximity
in mobile coupon behaviors. Consumers are actively acted on promotional offers where the event was
close to them. Spiekermann et al. (2011) found the redemption rates in 10m distance were five times
as high as in 800m distance when consumers considered redeeming restaurant coupons. Consumers
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are less likely to redeem m-coupons the further they are away from stores that are offering the coupon
(Danaher et al., 2015, Fong et al., 2015). Because long distances traveling to redeem coupons requires
more time and resources to redeem, which makes it risker and less attractive (Nayal & Pandey, 2020a).
Thus, consumers prefer to cash in mobile coupons near, and are more coupon-prone towards the close
distance, and feel riskier by long-distance redemption.
The following are hypothesized:
Hypothesis Five(a): Using distance of mobile coupons is negatively related to mobile coupon attitude.
Hypothesis Five(b): Using distance of mobile coupons is negatively related to mobile coupon
proneness.
Hypothesis Five(c): Using distance of mobile coupons is positively related to perceived risk.
The theory development above is illustrated in a conceptual model in Figure 4. The hypothesis
model includes reality-based variables and motivate-driven variables of consumers’ redemption
intention of mobile coupons.
This study used an online questionnaire to validate six variables: past behavior, m-coupon using
distance, m-coupon attitude, m-coupon proneness, perceived risk, and intention to redeem mobile
coupons. A short introduction about m-coupons was provided at the beginning of the survey to
complete it in a proper and professional manner (Nayal et al., 2021). The target population of interest
for this study consists of consumers who are living in Hangzhou and with daily usage of mobile
phones only. Respondents will be asked whether they are living in Hangzhou, if not, they will be
excluded from this study.
Survey items have been adopted and adapted from previous studies and reviewed by three experts
to validate their content (Gonzalez, 2021). The survey conducts two parts of questions: basic questions
and variable questions. Basic questions include the user’s basic information, like gender, age, job,
and monthly salary. Variable questions included six variables and they were adapted from Nayal &
Pandey (2020b) and being modified with mobile coupon situation and Chinese background. A five-
point Likert scale (1 = strongly disagree, 3 = uncertain, 5 = strongly agree) was used to describe
the respondents’ view of the extent of their agreement and disagreement on each statement for past
behavior, m-coupon using distance, m-coupon attitude, m-coupon proneness, perceived risk, and
intention to redeem mobile coupons (Nayal & Pandey, 2020b). Questions were first written in English
and then was translated into Chinese. The final items for each configuration are listed in Appendix.
Data collection was expanded after a pilot test of fifty respondents. Participants shared feedback
and feelings on the language, logical order, and consistency of the items they contained. There is
no difficulty in understanding or answering the questions. The survey then was conducted on the
Wenjuanxing website (www.wenjuanxing.com). It is a national-wide platform for online surveys.
The questionnaire was posted on the website from January 2021 to April 2021.
According to the IP address of each respondent, a total of 581 questionnaires were issued.
Excluding those whose main living city is non-Hangzhou and invalid questionnaires, a total of 455
valid questionnaires were obtained, with an effective response rate of 78.3%. The study uses SPSS
22.0 and SmartPLS3.0 software for data analysis. Since the research needs to reflect the overall
situation of consumers in Hangzhou, the survey targets do not limit to school students but respondents
from all walks of life. Descriptive analysis of the respondents shows that the proportion of men and
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women is relatively balanced. The age distribution is 33% of people under 30, mainly students and
people who are just entering the workplace. Middle-aged and young people aged 30-40 account for
44.2%. People over 40 years old accounted for 22.8%. The occupational distribution of the sample
is balanced, and the salary level obeys the normal distribution. Table 2 shows the demographics of
our sample. Figure 5 and Figure 6 show details of sample information.
Table 2. Demographics of the sample
Item Category Sample size Percentage(%)
Gender Male 233 51.2
Female 222 48.8
Age
<30 150 33
30-40 201 44.2
>40 104 22.8
Figure 5. Occupational distribution of the sample
Figure 6. Salary level of the sample (monthly salary received)
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This study adopts Partial Least Squares (PLS) to verify the theoretical hypothesis. First, considering
a large number of analytical models based on the intention of Chinese consumers to redeem mobile
coupons has not reached a consistent general conclusion. This study attempts to explore the theoretical
structural relationship of the “reality-motivation-intention” model and evaluate the predictive
effectiveness of exogenous variables. Second, in the actual various satisfaction surveys, the explained
variables and the explanatory variables are usually skewed or bimodal, which conforms to the situation
that the observed variables and latent variables are not normally distributed in the PLS solution process
(Chang et al., 2016). Finally, unlike the structural equation model based on covariance (CB-SEM),
PLS-SEM adopts a principal component analysis-based method to maximize the interpretability of
endogenous variables without generating unreasonable estimates or unrecognizable models (Hair
Jr. et al., 2017).
The measurement model analysis was conducted by construct validity, including two kinds of
validity tests, namely the discriminant validity and the convergent validity (Hair et al., 2013). The
discriminant validity tests the square root of the AVE of each construct is greater than its highest
correlation coefficient with any other construct in both groups (Dewi et al., 2019). Indicating there
is a good linear equivalence relationship between the observed variable and the latent variable, and
the measured variable can better explain the latent variable (Hair et al., 2017).
The Convergent validity analysis comprised of average variance extracted (AVE) and composite
reliability (CR). The average variance extracted (AVE) extracted must be greater than or equal to 0.5
(Fornell & Larcker, 1981) and the composite reliability (CR) of all configurations must be greater than
0.6 (Bagozzi & Yi, 1988), to make all the construct be accepted. Results in Table 4 show a good match.
The reliability coefficient of factor structures was measured using Cronbach’s alpha (Marmaya
et al., 2019). Nunnally (1978) emphasized alpha coefficient values have to be above 0.60 to be
acceptable. According to Hoang & Chu (2008), Cronbach’s Alpha ranging from 0.8 to 1 indicates a
good scale, from 0.7 to 0.8 is usable.
In this research, Cronbach’s alpha is all above 0.831 indicating a good scale. Composite Reliability
is bigger than 0.899 and the average variance extracted (AVE) is greater than 0.5. The measurement
model was successfully validated based on both validity and reliability tests (Table 3 and Table 4).
The evaluation of the model in this study uses the explainable variation (R2) of the endogenous
structure to characterize the degree of explanation of the independent variable of the current model to
the variation of the dependent variable. The larger the value of R2, the stronger the explanatory power
of the measured variable to the latent variable. The explanation level of the willingness to redeem
mobile coupons is 71.2%, and the explanatory power of the model is moderate, which is far beyond
consumers’ research of the 20% requirement (Marmaya et al., 2019). See Table 5 for specific data.
Mobile coupon attitude and proneness positively promote intention to redeem m-coupons. Thus, H1
and H2 are supported. Surprisingly, perceived risk is not significant with mobile coupon redemption
intention. Past behavior would increase consumers’ m-coupon attitude and proneness, H4a, and H4b
are supported. But H4c, past behavior of using m-coupons is negatively related to perceived risk is
not significant. H5a and H5b that m-coupon attitude and proneness negatively influenced by using
distance have been proven significant. H5c shows a reverse conclusion that using distance of mobile
coupons is negatively related to perceived risk. Hypothesis testing results are shown in Table 6 and
results of PLS analysis are in Figure 7.
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Table 3. Factor loadings, average variance extracted, and composite reliability
Latent variable Cronbach’s Alpha Composite Reliability(CR) AVE Factor loading
Redemption intention 0.899 0.926 0.714
0.842
0.864
0.783
0.884
0.847
m-coupon attitude 0.846 0.907 0.765
0.872
0.881
0.871
m-coupon
proneness 0.871 0.912 0.721
0.831
0.85
0.854
0.863
Perceived risk 0.88 0.926 0.807
0.882
0.919
0.893
Past behavior 0.831 0.899 0.748
0.868
0.896
0.829
using distance 0.895 0.927 0.761
0.873
0.891
0.888
0.836
Table 4. Discriminant validity test for the measurement model in PLS
Redemption
intention
m-coupon
attitude
m-coupon
proneness
Perceived
risk
Past
behavior
Using
distance
Redemption
intention 0.845
m-coupon attitude 0.835 0.875
m-coupon
proneness 0.74 0.795 0.849
Perceived risk 0.427 0.449 0.499 0.898
Past behavior 0.697 0.716 0.749 0.412 0.865
Using distance -0.572 -0.625 -0.732 -0.581 -0.735 0.873
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Table 5. Evaluation of the model explanatory ability
R2Communality Redundancy
Using distance 0.587
Past behavior 0.476
m-coupon attitude 0.531 0.504 0.402
m-coupon proneness 0.631 0.524 0.452
Perceived risk 0.335 0.578 0.27
Redemption intention 0.712 0.563 0.501
Table 6. Hypotheses testing results
β T P Testing results
H1: m-coupon attitude -> redemption intention 0.665 12.57 0.000 Supported
H2: m-coupon proneness -> redemption intention 0.197 2.893 0.004 Supported
H3: Perceived risk -> redemption intention 0.03 0.71 0.478 Not Supported
H4a: Past behavior -> m-coupon attitude 0.556 10.796 0.000 Supported
H4b: Past behavior -> m-coupon proneness 0.458 8.537 0.000 Supported
H4c: Past behavior -> Perceived risk -0.033 0.457 0.648 Not Supported
H5a: Using distance -> m-coupon attitude -0.217 3.716 0.000 Supported
H5b: Using distance -> m-coupon proneness -0.396 6.879 0.000 Supported
H5c: Using distance -> Perceived risk -0.605 8.778 0.000 Not Supported
Figure 7. Smart PLS analysis results
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The main findings of this study are presented here. First, the impact of past behavior. The path
coefficient of past behavior on mobile coupon use attitude is 0.556 (β=0.556), and the P-value is
less than 0.001, indicating that past behavior has a positive impact on m-coupon using attitude. For
every 1% increase in past behavior, the attitude of mobile coupon usage will increase by 0.556%.
Consumers who have experience using mobile coupons are more likely to have a positive attitude
towards mobile coupons and check whether there are mobile coupons.
The path coefficient of past behavior on mobile coupon use tendency is 0.458 (β=0.458),
and the P-value is less than 0.001, indicating that past behavior has a positive impact on
m-coupon proneness. For every 1% increase in past behavior, m-coupon proneness will increase
by 0.458%. Past behavior of using m-coupons has been a strong predictor of future usage
intention, which is consistent with the study of M. F. Chen & Yi (2011). Consumers with a
better experience of using m-coupons would feel positive towards the action of redeeming and
cultivating a positive psychological gain.
Second, using distance of m-coupons. The path coefficient of the m-coupon using distance to
the m-coupon attitude is -0.271, and the P-value is less than 0.001, indicating that the use distance
negatively affects the mobile coupon use attitude. For every 1% increase in the using distance, the
m-coupon attitude will decrease by 0.271%. Consumers are more willing to have a positive attitude
towards using mobile coupons that are closer to each other. This conclusion is consistent with Danaher
et al. (2015) and Fong et al.(2015).
The path coefficient of using distance on the m-coupon proneness is -0.396, and the P-value is
less than 0.001, indicating that using distance has a more adverse effect on the m-coupon proneness.
For every 1% increase in the use distance, the tendency of mobile coupons will decrease by 0.396%.
The path coefficient of using distance on the perceived risk of mobile preferences is -0.605,
and the P-value is less than 0.001. The using distance has the greatest impact on the perceived
risk. For every 1% increase in usage distance, the perceived risk of mobile coupons will decrease
by 0.605%, which is contrary to assumptions. It shows that redemption of long-distance mobile
coupons is a decision made by consumers who are willing to spend more energy and resources
to redeem. Therefore, the redemption of mobile coupons is not considered to be a forced choice,
nor do they feel disturbing.
Third, m-coupon attitude. The path coefficient of m-coupon attitude to m-coupon redemption
intention is 0.665, and the P-value is less than 0.001, which has the greatest impact on the intention
to redeem mobile coupons among all the variables. For every 1% increase in usage attitude, the
willingness to redeem mobile coupons will increase by 0.665%. A positive attitude towards mobile
coupons will increase the intention to redeem m-coupons.
Fourth, m-coupon proneness. The path coefficient of m-coupon proneness to m-coupon
redemption intention is 0.197, and the P-value is equal to 0.004, indicating that coupon proneness
positively affects the intention to redeem mobile coupons. For every 1% increase in m-coupon
proneness, the intention to redeem mobile coupons will increase by 0.197%.
Last but not least, perceived risk analysis. Perceived risk is not significant to the path of intention
to redeem mobile coupons, which does not support the original hypothesis. That is to say, consumers
in Hangzhou accept the issuance of mobile coupons, and there exist few concerns related to the risk
of redeeming m-coupons. This result is quite different than other studies. Eunju Yoon, Hyunjoo
Im (2014) showed perceived risk would providing personal information of U.S. consumers which
is negatively related to the attitude of using coupons. Schmitt (2012) found the perceived risk was
slightly negatively correlated to deal-of-the-day website shopping among young consumers in Italy.
Perceived risk is not a determinant in China for m-coupon redeem intention as it may be due to China
being a cashless society.
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At present, academia has begun to research digital coupons, but there are still rare researches focusing
on specific variables (i.e., past behavior, price consciousness, and time value) and different cultural
fields, such as BRICS (Brazil, Russia, India, China, and South Africa) (Nayal & Pandey, 2020b).
Hangzhou is a pioneer in China’s digital city, where citizens are habituated to mobile technology.
This paper studied Hangzhou consumers’ m-coupon redemption intention during the COVID-19
condition with the “reality-motivation-intention” model.
Findings show the intention to redeem m-coupons is mainly affected by consumers’ attitude
and proneness to use it. Among them, the m-coupon attitude has a greater impact on the m-coupon
redemption intention. The behavior of past mobile coupon usage will increase mobile coupon attitude
and proneness. Using distance will reduce the mobile coupon attitude and proneness.
In conclusion, practitioners could focus firstly on the regional m-coupons or m-coupons for
specific malls and complexes. Issuing regional mobile coupons in specific areas can shorten the
distance of redeeming, enhancing the “privilege” and “happiness” of consumers in the business
district, which will play a better promotional role and rising attitude to redeem.
Secondly, for marketers with little market space, choosing to bundle with big brands’ m-coupons
would expand the audience of its own brand. As consumers’ m-coupon proneness tends to stabilize and
their consumption habits have been formed. For the goods that consumers do not have the intention
to buy, the price discount will not able to attract consumers to buy. So, the price advantage is only
useful for known brands.
Finally, with the government support and sponsorship, the wide usage of technology infrastructure
QR Code, the ease-of-use convenience and safety of the M-pay apps, and no charges of any associated
fees with M-pay (Kennedyd, et al., 2020), it seems that using m-coupon would not causing risk threats
to Chinese consumers. Traditional western models may not be suitable for researching Chinese
consumers’ behavior.
This research was supported by the 2021 Hangzhou City philosophy and Social Science Planning
Project [grant number M21JC091].
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Wenyan Huang, CMA, is currently a Lecturer at Zhejiang Financial College, Hangzhou, Zhejiang, China. Her
courses include financial management, financial analysis, basic accounting, etc. She is also a Ph.D. student in
management at SEGi University, Malaysia. She finished her Master’s degree in Business Administration at Zhejiang
Normal University in 2016. Her main research directions are platform value evaluation and behavioral finance. She
is good at data analysis, including the application of STATA, SPSS, Eviews, etc.
Gooi Leong Mow graduated with a Doctor of Philosophy (Ph.D.) in Business Economics from Universiti Putra
Malaysia (UPM), an AACSB accredited institution, in the year 2020. He also obtained his Master of Business
Administration (MBA, International Business) and Bachelor of Science Agribusiness from UPM in the year 2011
and 2008 respectively. Dr. Gooi’s researches focus more on the Time Series Data Analysis, Volatility Forecasting
model’s performance(GARCH Models and STES method) on different series data in different time horizons included
MIDAS(Mixed-data sampling) method and News Impact Curve (NIC). Dr. Gooi is currently working as a lecturer at
SEGi University, Graduate School of Busines. He used to worked with Tiong Nam Berhad as a management trainee
at ERIKG Sdn Bhd Malaysia branch and was promoted from a product executive to a manager, and University
Putra Malaysia(UPM) as a part-time tutor in Technique Quantitative subject (From the year 2014 to 2016).
Table 7. Questionnaire measurement items
Constructs Items Source
Redemption intention
Q1 I will probably redeem the mobile coupons
Nayal &
Pandey
(2020a)
Q2 I am certain to redeem the mobile coupons
Q3 I will use a mobile coupon if I find something I like
Q4 I like to redeem the mobile coupons
Q5 I would consider searching for mobile coupons in the near future
m-coupon attitude
Q1 It is fun to use mobile coupon Nayal &
Pandey
(2020a)
Q2 I always look for coupons before buying products
Q3 I react favorably to mobile coupons
m-coupon proneness
Q1 Mobile coupons have caused me to buy products I normally would not buy
Nayal &
Pandey
(2020a)
Q2 I have favorite brands, but most of the time I buy the brand I have a coupon for
Q3 I am more likely to buy brands for which I have a mobile coupon
Q4 I enjoy using mobile coupons, regardless of the amount I save by doing so
Perceived risk
Q1 In general, I find mobile coupons forced Nayal &
Pandey
(2020a)
Q2 In general, I find mobile coupons disturbing
Q3 In general, I find mobile coupons intrusive
Past behavior
Q1 I often use mobile coupons Modified
based on the
work of M.
F. Chen &
Yi (2011)
Q2 I will search for the Hangzhou government’s mobile coupons every time
Q3 I will use the Hangzhou government’s mobile coupons when I get them
Using distance
Q1 I do not mind traveling provided I have a mobile coupon
Nayal &
Pandey
(2020a)
Q2 If the medium of traveling is economical, I can go far to redeem the mobile coupons
Q3 If I own a car, distance does not bother me to redeem the mobile coupon
Q4 The ambiance of the shopping mall overcomes the pain of the distance traveled to
redeem the mobile coupon
