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Aji and Sutikno 433
Volume 10, Number 4, December 2015
The Extended Consequence of Greenwashing:
Perceived Consumer Skepticism
Hendy Mustiko Aji
(Corresponding Author)
Email: hendymustikoaji@gmail.com
&
Bayu Sutikno
Faculty of Economics and Business
Gadjah Mada University
Bulak Sumur Street, Yogyakarta, Indonesia
ABSTRACT
In a review of more than 1,000 self-described “green” or eco-friendly products,
one organization [TerraChoice, 2010] found that all but one of the products
exhibited some form of greenwashing. “Greenwashing” is a type of spin in
which public relations or marketing is used deceptively to promote the perception
that a company and its products or services are environmentally safe or
“friendly.” This study examined the construct of perceived consumer skepticism
as the extended consequence of greenwashing, thus extending the study by
Chang and Chen [2013], which examined the link between greenwashing and
green trust, with a view to the extended and final consequences. The authors of
the current study formulated 10 hypotheses, developed a structural model with
six variables, and tested the relationships in the model using a purposive
sampling technique that involved an online and offline survey of a sample of
green consumers in Yogyakarta, Indonesia. This study found that greenwashing
has a positive association with green consumer skepticism (GCC), perceived
consumer skepticism (PCS), and green perceived risk (GPR). Furthermore, the
study found a surprising link between GCC-PCS-GPR and green trust (GT). The
study also discussed the practical implication of these findings and offers
suggestions for future research.
Keywords: Green marketing, greenwashing, perceived consumer skepticism
434 The Extended Consequence of Greenwashing:
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1. INTRODUCTION
Environmental issues have become increasingly popular among consumers
worldwide and are a popular topic for research and discussion in academic circles
and the industrial sector. Rising concerns about global warming have made
consumers even more conscious of environmental issues [Chen, 2008]. With
increased consumer interest in environmentally friendly products and services,
manufacturers have devoted considerable effort to the marketing and sales of so-
called “green” products [Bhatia and Jain, 2013]. The popularly of green products
has caused manufacturers to adopt eco-friendly practices that affect not only the
production process, but also the final product itself [Kivimaa and Kauto, 2010].
To sell these products, manufacturers create advertising that makes eco-friendly
or green claims in order to target consumers who lead a green lifestyle [Divine
and Lepisto, 2005]. Green marketing is viewed as the best concept and strategy
to respond to market needs and wants.
Many environmental claims focusing on the green (environmental) attribute,
however, are ambiguous and deceptive [Chen and Chang, 2012].
Environmentalists and some consumers are crying foul, saying that many
companies are making their products out to be greener than they really are [Hsu,
2011]. Of the more than 1,000 self-declared green products reviewed by
TerraChoice [2010], as cited by Lane [2012], it was found that all but one
exhibited some form of greenwashing. “Greenwashing” is a type of spin in which
public relations, advertising, or marketing is used deceptively to create the
perception that a product or service is “green.” This practice has given some
consumers the negative intent to purchase these products or services [McGrath,
1992; Newell et al., 1998). The practice also increases consumer confusion when
it comes to purchasing products with environmental features.
The objective of this study is to extend the study by Chen and Chang [2013]
by proposing perceived consumer skepticism (PCS) and switching intention as
the extended consequences of greenwashing. Chen and Chang [2013] examined
the direct relationship connecting greenwashing to green trust (GT), and the
indirect relationship between greenwashing and green trust (GT), with green
consumer confusion (GCC) and green perceived risk (GPR) as mediating
variables. All hypotheses in their study were supported, but there are gaps in the
study that can be filled.
Established theory of advertising and switching behavior implies that
consumers tend to be skeptical of ads, especially green ads, and that consumers
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Volume 10, Number 4, December 2015
may have the intention to switch if they are ethically injured. Consumers are
particularly skeptical of advertising that proclaims the “greenness” of a product.
In academic literature, this behavior is known as “perceived consumer
skepticism” (PCS). The construct, which was introduced by Mohr, Eroglu, and
Ellen [1998], refers to the tendency among consumers to disbelieve
environmental claims made in advertising [Matthes and Wonneberger, 2014].
The problem is a serious one because consumers are indeed skeptical of green
claims [Sheehan and Atkinson, 2012] that are motivated by profit [Albayrak,
Cabeer, Moutinho, and Herstein, 2011].
Moreover, Keaveney [1995] has shown that the ethical problems caused by
greenwashing may lead to switching intention and later to switching behavior.
Chen and Chang’s [2013] study did not include the problem of perceived
consumer skepticism (PCS) nor the problem of switching intention. The current
study takes these two problems into account, thus distinguishing the current
research from the work by Chen and Chang [2013]. It is hoped that this empirical
study will provide a theoretical contribution to academic literature on the subject
of greenwashing.
2. LITERATURE REVIEW
In their book, Kottler and Keller [2012] said that the starting point of a
business is not the company but the market. In order to survive competition,
therefore, a company has to adjust its vision and mission to match what the
market needs and wants. Since today’s consumers are more conscious of the
environment, they make a significant effort to buy eco-friendly products and
services [Roberts, 1996; Kalafatis et al., 1999]. Green marketing targets “green”
consumers by purportedly making “eco-friendly,” “environmentally friendly”
products. Before specifically explaining the variables observed, we offer the
following definition and brief explanation of green marketing concepts. Once one
grasps the definition and concept of green marketing, it is easy to understand
greenwashing.
2.1. Green Marketing
It all began on Earth Day 1990 when millions of people around globe
gathered in their communities to protest the rapidly declining health of the planet
[Gallicano, 2011]. Since then, public concern about environmental issues has
increased steadily [Choi, 2005, cited from Kaufman et al., 2012]. As a result,
436 The Extended Consequence of Greenwashing:
Perceived Customer Skepticism
International Journal of Business and Information
companies have responded by developing what they describe as environmentally
friendly products [Kohl, 1990].
Scholars have defined many other terms for green marketing, such as
“ecological marketing,” “environmental marketing,” or “responsible marketing”
[Polonsky, 2011]. Green marketing is a concept and strategy adopted by a
company to advertise its green practices as an expression of its concern for
environmental issues. Manju [2012] refers it to a holistic concept wherein the
production, marketing, consumption, and disposal of products and services occur
in a manner that is less detrimental to the environment. Green marketing that was
previously focused primarily on the ecological context has been shifted to
sustainability issues so that the main focus now is on the socioeconomic and
environmental context [Mohanasundaram, 2012]. The various other terms for
green marketing have a common focus on the exchange process, with a proviso
that exchange considers and minimizes environmental harm [Polonsky, 2011].
Because the issues strongly affect consumer perception and lifestyle, marketers
have to carefully advertise their green products, so that customers do not perceive
that they are being misled by deceptive advertising.
The specter of deceptive advertising has led to increased confusion among
consumers regarding the environmental claims made about many products. The
situation is further clouded by the ambiguous meaning of terms such as
“environment-friendly” and “ozone-friendly” [Newell et al., 1998]. Questionable
advertising prompted the U.S. Federal Trade Commission (FTC) to investigate
and prosecute misleading environmental claims. The prosecutions reflect the
FTC’s aim to police a chaotic marketplace teeming with ambiguous labels
[Schmidt, 2009]. The FTC published the following criteria describing deceptive
environmental ads [Cohen, 1974]:
1. Factually incorrect
2. Subject to multiple interpretations, one of which is false
3. Guilty of omitting relevant information
4. True, but the proof is false
5. “Literally” true but creates a false impression
Such deceptive, ambiguous, and misleading practices are described in academic
literature as greenwashing.
2.2. Greenwashing
“Greenwashing” is defined as the act of misleading consumers regarding
the environmental practices of a company or the environmental benefits of a
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Volume 10, Number 4, December 2015
product or service [Greenpeace, n.d]. Some scholars define the term as the
intentional misrepresentation of a firm’s environmental efforts (or the lack
thereof) [Alves, 2009, 2011; and Furlow, 2010]. A few years ago, consumers
began using social media to campaign against greenwashing practices. In
response, TerraChoice [2009] identified seven company “sins” with regard to
misleading advertisements for green products:
1. Sin of the hidden trade-off. This is a claim that a product is “green,”
based on a narrow set of attributes, without mentioning other important
issues. An example would be an advertisement for paper-making in
which the source of raw materials is highlighted rather than the process
of production (which may be environmentally harmful).
2. Sin of no proof. This is an environmental claim that cannot be
substantiated by easily accessible supporting information or by a reliable
third-party certification.
3. Sin of vagueness. This is a claim that is so poorly defined or so broad
that its real meaning is likely to be misunderstood by the consumer. An
example is the tagline “100% natural” or “all natural,” when in fact one
or more of the “natural” ingredients may be an environmentally harmful
chemical.
4. Sin of worshipping a fake label. This is a product advertisement that,
either through words or images, gives the impression of a third-party
endorsement, when in fact no such endorsement exists.
5. Sin of irrelevance. This is an environmental claim that may be truthful,
but is unimportant or unhelpful for consumers seeking environmentally
safe products.
6. Sin of the lesser of two evils. This is a claim that may be true within the
product category, but may distract the consumer from the greater
environmental impact of the category as a whole.
7. Sin of fibbing. This includes environmental claims that are simply false.
438 The Extended Consequence of Greenwashing:
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2.3. Previous Research Findings
Greenwashing is an interesting issue that has not been frequently
discussed or examined empirically in green marketing literature. We present,
therefore, an overview of the findings of the study by Chen and Chang [2013]. In
their study, greenwashing was confirmed to have a positive significant
relationship to GCC and GPR. The path coefficient for greenwashing-GCC was
0.23, which is significant at p-value < 0.05, and the path coefficient for
greenwashing-GPR was 0.23, also significant at p-value < 0.05. Their findings
support established theory in greenwashing literature. Chen and Chang [2013]
also related GCC and GPR to GT. As a result, they found that GCC and GPR
were negatively associated with GT. The path coefficients were both significant
at p-value < 0.05, with a score of -0.225 and -0.217. GPR-GT findings in their
2013 study confirmed the findings of their 2012 study.
2.4. Hypotheses Development
The following section presents hypotheses developed during the current
study in seven crucial areas:
• Greenwashing and green consumer confusion
• Greenwashing and perceived consumer skepticism
• Greenwashing and green perceived risk
• Green consumer confusion and green trust
• Perceived consumer skepticism and green trust
• Green perceived risk and green trust
• Proposed extended consequences of greenwashing
2.4.1. Greenwashing and Green Consumer Confusion
Deceptive and ambiguous ads about a product in relation to its
environmental features will certainly generate serious consumer confusion.
“Green consumer confusion” was defined in one study as a state of mind that
affects information processing and decision-making so that the consumer may or
may not be aware of being confused [Mitchell and Papavassiliou, 1999]. The
term was redefined in another study as the consumer’s failure to develop a
correct interpretation of the environmental features of a product or service during
the information-processing procedure [Turnbull et al., 2000].
In either case, the consumer is confused about whether the product is
really green, or just the opposite. This confusion causes the consumer to develop
some negative perceptions about the product’s environmental features. One such
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Volume 10, Number 4, December 2015
perception is the notion that the environmental campaign is just a part of the
company’s marketing strategy. Another perception is that, in advertising green
products, the company is not motivated purely by environmental concerns, but
rather by profit orientation. Whatever the case, marketers must strive to create
consumer perceptions that are consistently positive because perceptions of
greenwashing can damage the consumer’s attitude toward a company [Peattie et
al., 2009]. Ultimately, the perceptions generated by misleading ads may destroy
the market by causing consumers to be suspicious of green products [Polonsky et
al., 2010; Chen and Chang, 2012].
There are three types of green consumer confusion, as categorized by
Mitchell, Walsh, and Yamin [2005]: (1) unclarity confusion, (2) similarity
confusion, and (3) overload confusion. Unclarity confusion is defined as a lack
of understanding, in which consumers are forced to re-evaluate their current
beliefs about a product. This type of confusion may be caused by technological
complexity, ambiguous information or dubious product claims, conflicting
information, or incorrect interpretation [Mitchell, Walsh, and Yamin, 2005].
Similarity confusion is the potential alteration of a consumer’s choice or an
incorrect brand evaluation caused by the perceived physical similarity of
products or services [Mitchell, Walsh, and Yamin, 2005]. Overload confusion is
caused by a too much decision-relevant information regarding the choice of
brands. With such a vast quantity of information available, it may be difficult for
consumers to focus on the vital points, thus causing confusion [Mitchell, Walsh,
and Yamin, 2005].
Connecting the three types of confusion to the topic, greenwashing
would overload consumers with information and could make it more difficult for
them to evaluate the product [Walsh et al., 2007]. Ambiguous and deceptive
green claims may create confusion among consumers with regard to its
environmental features. We hypothesized, therefore, that there is a positive
relationship between greenwashing and green consumer confusion.
H1
:
Greenwashing is positively associated with green consumer
confusion.
2.4.2. Greenwashing and Perceived Consumer Skepticism
Obermiller et al. [2005] stated that consumers are more skeptical about
advertising than any other form of communication. Often, consumers do not have
the expertise or ability to verify the environmental and consumer values of green
440 The Extended Consequence of Greenwashing:
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International Journal of Business and Information
products, which results in misperceptions and skepticism [Ottman et al., 2006].
Highly skeptical consumers would be more likely to respond less favorably to
advertising [Anuar, et al., 2013]. Skepticism is one potential cognitive response
to advertising exposure [Pomering and Johnson, 2009]. Cognitive responses are
message-relevant thoughts that arise during deliberation as a result of one’s
relating message material to other message content or to prior knowledge and to
attitudes stored in memory, with persuasion reflecting net favorableness of one’s
cognitive responses [Meyers-Levy and Malaviya, 1999; Pomering and Johnson,
2009]. Skepticism may also be defined as the disbelief of stated claims [Darley
and Smith, 1993; Ford et al., 1990; Pomering and Johnson, 2009]. To the extent
that one is skeptical, one is more likely to examine the claims made in
advertisements in a critical way and not accept them at face value [Mangleburg
and Bristol, 1998; Pomering and Johnson, 2009]. In this context, we
hypothesized that greenwashing has a positive relationship with perceived
consumer skepticism.
H2
:
Greenwashing is positively associated with perceived consumer
skepticism.
2.4.3. Greenwashing and Green Perceived Risk
Apart from its effects on consumer confusion and skepticism, green
advertising that is misleading, ambiguous, and deceptive may cause the consumer
to build a perception of risk associated with the products consumed. Perceived
risk is connected with the possible consequences of a wrong decision [Peter and
Ryan, 1976]. Assae [2004] identified several types of perceived risk:
• Financial risk: A function of the cost of a product relative to the
consumer’s disposable income
• Social risk: Failure of the purchase to meet the standards of an important
reference group
• Psychological risk: The loss of self-esteem when the consumer
recognizes that an error has been made
• Peformance risk: The possibility that the product will not work as
anticipated
• Physical risk: The possibility of bodily harm as a result of product
performance
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Volume 10, Number 4, December 2015
All of these risks are associated with, and are relevant to, the greenwashing issue.
Assael [2004] also identified several factors associated with perceived risk:
• Consumers are highly involved with the product.
• There is little information about the product category.
• The product is new.
• The product is technologically complex.
• Consumers have little self-confidence in evaluating brands.
• There are variations in quality among brands.
• The price is high.
• The purchase is important to consumers.
With regard to environmental features labeled on green products, consumers
will perceive that consumption of those products will later harm not only their
image or reputation for environmental protection, but also their own health.
Chen and Chang [2013] confirmed those possibilities (except for health risks)
with significant loading scores. We hypothesized, therefore, that greenwashing
is positively associated with consumer perceived risks.
H3
:
Greenwashing is positively associated with green perceived risk.
2.4.4. Green Consumer Confusion and Green Trust
Because of their growing concern about the trustworthiness of ads,
consumers are very critical in assessing advertisements. They feel that they
cannot easily trust advertising that claims the goodness of a product, particularly
with regard to environmental friendliness. Again, perceptions about ads play a
very important role in consumer decisions about purchasing. Moreover, the
customer trust issue is relevant and vital.
Trust is the level of willingness to depend on one object, based on the
expectation of its ability, reliability, and benevolence [Ganesan, 1994; Hart and
Saunders, 1997; Chen and Chang, 2012]. “Green trust” is the willingness to
depend on one object, based on the belief in, or expectation of, its credibility,
benevolence, and ability with regard to environmental performance [Chen, 2010].
Product advertising that is perceived as misleading or unproven will confuse
consumers about the product’s environmental features. Ultimately, they will
distrust the advertisers as well as their products. Consumers who feel
uncomfortable from information ambiguity and incongruity will perceive
unclarity [Cox, 1967; Chen and Chang, 2012]. Those who are confused about a
442 The Extended Consequence of Greenwashing:
Perceived Customer Skepticism
International Journal of Business and Information
product will be reluctant to trust it [Mitchell and Papavassiliou, 1999]. More
specifically, Kalafatis and Pollard [1999] and Chen and Chang [2013] confirmed
that consumer confusion about green marketing is negatively associated with
trust with respect to green claims. We hypothesized, therefore, that green
consumer confusion and green trust have a negative relationship.
H4
:
Green consumer confusion is negatively associated with green
trust.
2.4.5. Perceived Consumer Skepticism and Green Trust
Skepticism is the disbelief of stated claims (Darley and Smith, 1993;
Ford et al., 1990; Pomering and Johnson, 2009). The skeptical consumer will not
accept advertising claims at face value [Mangleburg and Bristol, 1998; Pomering
and Johnson, 2009]. The common thread in the various definitions of ad
skepticism is trust. Indeed, ad skepticism often refers to the consumer's lack of
trust in advertising [Boush et al., 1993, 1994; Mangleburg and Bristol, 1998].
Green consumers are thought to make green purchasing decisions either
by the level of compromise required to purchase a green product or by the level
of confidence in the product [Peattie, 2001; Albayrak et al., 2011]. Consumers
who are confident about buying green products generally trust the product’s
claim regarding its environmental features. Matthes and Wonneberger [2014]
stated that, instead of saying that consumers tend to distrust green ads, one needs
to determine whether all consumers are skeptical of green ads or whether it is just
green consumers who tend to distrust green campaigns. In this study, we
hypothesized that there is a negative relationship between green consumer
skepticism and green trust:
H5
:
Perceived consumer skepticism is negatively associated with
green trust
.
2.4.6. Green Perceived Risk and Green Trust
According to the expectancy-disconfirmation paradigm, a comparison of
consumer expectations and perceptions would lead to either confirmation or
disconfirmation [Oliver, 1996; Chen and Chang, 2013]. That paradigm is
consistent with expectation-confirmation theory, which states that the consumer
will first form an initial expectation prior to purchase of a product or service and
then build perceptions about its performance after a period of initial consumption
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Volume 10, Number 4, December 2015
[Valvi and West, 2012]. To some extent, customers may disconfirm their
expectation because of negative perceptions. In the context of environmental
concern, these perceptions are associated with green product advertising.
From the standpoint of negative perceptions, perceived risk is related not
only to the environment itself, but also to the consumer’s physical body. Peter
and Ryan [1976] defined perceived risk as perception that is connected with the
possible consequences of a wrong decision. “Green perceived risk” is the
perception that is connected with the possible consequences of a wrong decision
with regard to environmental performance. Chen and Chang [2013] defined the
term as the expectation of negative environmental consequences associated with
purchase behavior. Perceived risk is a combination of negative consequences and
uncertainty. Consequently, the assessment of perceived risk would affect a
consumer’s purchase decision [Peter and Ryan, 1976; Chen and Chang, 2012]. It
would also influence consumer attitudes [Mitchell, 1999]. The risk that
consumers face is, to some extent, noticed and felt more strongly than the benefit
they gain. This view is consistent with the theory that consumers are keen to
minimize the perceived risk rather than to maximize their utility [Mitchell, 1999].
The level of perceived risk would affect a consumer’s decision making
about whether to trust or distrust [Harridge-March, 2006; Chen and Chang,
2012]. If consumers feel high risk toward a product or brand, they would not trust
the product or brand [Mitchell, 1999]. This logic is supported by several
researchers who found that the higher the risk perceived by consumers, the lower
their trust in the product or brand associated with green claims [Mitchell, 1999;
Warrington et al., 2000; Corritore et al., 2003; Harridge-March, 2006; Gillespie,
2008; Eid, 2011; Chen and Chang, 2012). Therefore, we hypothesized:
H6
:
Green perceived risk is negatively associated with green trust.
2.4.7. Proposed Extended Consequences of Greenwashing
In this study, we extended the consequences of the greenwashing-green
trust link because academic studies never merely end at consumer attitude toward
a product or brand. In this context, it is believed that greenwashing consequences
will not stop at green trust. Greenwashing may have even further effects on
consumer intention and behavior. In his theory of planned behavior (TPB) Ajzen
[1991] identifies consumer attitude as one of the drivers of consumer intention
and behavior. It has been proved that the TPB can explain and predict ethical as
well as unethical behavior in many domains of life, including green purchase
444 The Extended Consequence of Greenwashing:
Perceived Customer Skepticism
International Journal of Business and Information
[Kalafatis et al., 1999]. Chang [1998] also proved that the TPB can predict
unethical behavior. In the following paragraphs, we examine the relationship
between green consumer confusion (GCC)-perceived consumer skepticism
(GCS)-green perceived risk (GPR) and customer intention to switch from green
products to non-green products.
GCC-PCS-GPR and Customer Switching Intention. Marketers of green
products must manage matters so that consumer perception is
consistently positive. Perceptions of greenwashing can damage
consumer attitudes toward a company [Peattie et al., 2009] as well as a
product. Consumer attitude toward a product or brand will affect
consumer purchase intention and behavior, according to Ajzen’s [1991]
theory of planned behavior. If consumers perceive that they are confused,
they may abandon their purchase decision [Mitchell and Papavassiliou,
1999; Chen and Chang, 2012], an act of disloyalty [Walsh et al., 2007],
or may switch to another product.
The effects can be caused as well by perceived consumer skepticism and
risk. Obermiller et al. [2005] found that the proposed link between
advertisement and purchase intention does not exist when consumers are
skeptical about the advertisement. In his research on the green purchase
intentions of Egyptian consumers, Mostafa [2006] showed that
skepticism negatively influences purchase intention. His questionnaire
included two items relating to skepticism:
“Over the next one month, I will consider switching to other
brands for ecological reasons.”
“Over the next one month, I plan to switch to a green version of
a product.”
With regard to the perceived risk-switching intention link, Mitchell
[1999] stated that, if consumers perceive high risk toward a product, they
probably would not buy the product. In other words, perceived high risk
negatively influences green purchase intention [Wood and Scheer, 1996;
Chang and Chen, 2008]. In the current study, we hypothesized that
perceived consumer skepticism toward environmental claims is
positively related to switching intention.
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Volume 10, Number 4, December 2015
H7
:
Green consumer confusion is positively associated with customer
switching intention.
H8
:
Perceived consumer skepticism is positively associated with
customer switching intention.
H9
:
Green perceived risk is positively associated with customer
switching intention.
Green Trust and Customer Switching Intention. Green trust is the
willingness to depend on one object, based on the belief in, or
expectation of, its credibility, benevolence, and ability with regard to
environmental performance [Chen, 2010]. Marketers whose advertising
is perceived as misleading and unproven confuse consumers with regard
to environmental features. Consumer trust in environmental claims will
diminish because consumers perceive some risks with respect to
greenwashing. The perceived risk may be either environmental or
physical (their own bodies). In either case, they are hesitant to consume
the green-claimed product, and may switch from the green product to a
non-green product. The result would be entirely different if they initially
perceived the green product as trustworthy. In this study, we
hypothesized:
H10
:
Green trust is negatively associated with customer switching
intention.
3. RESEARCH METHODS AND DATA COLLECTION
This section discusses the survey, sample, and data collection process as well
as the measurement of constructs.
3.1. Survey, Sample, and Data Collection
To test the relationships in the proposed model, we conducted a survey
using the purposive sampling technique. The survey was designed to collect more
data and to generalize the results for a specific consumer segment (green
consumers in Yogyakarta, Indonesia). Only those with a basic knowledge of
green products and green advertising were selected for the sample. Data was
collected from respondents via both online and paper-based questionnaires.
446 The Extended Consequence of Greenwashing:
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International Journal of Business and Information
Online questionnaires powered by Google Forms were randomly distributed to
respondents via social media and some online green communities. Paper-based
questionnaires were distributed to students at universities in Yogyakarta. Some
lecturer-partners who have classes at several of these universities were asked to
help distribute the offline questionnaires. The questionnaires were back-
translated from English to Bahasa Indonesia.
A total of 300 paper-based questionnaires were distributed offline. Of
these, 200 were returned, for a response rate of 66% and a ratio of 0.32. Of the
200, however, only 93 contained data that could be used in the study. A total of
108 responses were received from the online questionnaire. Of these, only 41
(ratio of 0.38) contained data that could be used in the study. In total, there were
134 questionnaires with qualified and usable data.
Structural equation modeling (SEM) was used to assess the measurement
model and structural model. We used IBM SPSS AMOS 21 for this purpose.
Four pre-tests were conducted to test respondents’ understanding about items in
the questionnaire. Using the data collected from the four pre-tests, we loaded
items on each factor without cross-loadings. The reliability of all items was
considered good since the Cronbach’s alpha scores were above the required
threshold of 0.60.
3.2. Measurement of Constructs
The survey instrument used a five-point Likert-style scale that ranged
from 1 = “strongly disagree” to 5 = “strongly agree.” The 5-item scale was taken
from Laufer [2003] and Chen and Chang [2013]. For the survey, we selected
operational definitions for six variables (Table 1). The survey items were based
on the study by Walsh et al. [2007] and Walsh and Mitchell [2010]. Table 2
presents the items for each variable and indicates the source of the items used.
Aji and Sutikno 447
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Table 1
Operational Definition of Variables
Variables Definition Source
1 Greenwashing The act of misleading a consumer
about the environmental practices
of a company or the environmental
benefits of a product or service
Greenpeace [n.d]
2 Green Consumer
Confusion Consumer failure to develop a
correct interpretation of the
environmental features of a product
or service during information
processing
Turnbull et al.
[2000]
3 Perceived
Consumer
Skepticism
Consumer cynical perception about
ads because of the prevalence of
misleading green claims
Matthes and
Wonneberger
[2014]
4 Green Perceived
Risk Perception that is connected with
the possible consequences of a
wrong decision
Peter and Ryan
[1976]
5 Green Trust A willingness to depend on a
product or service based on the
belief or expectation of its
credibility, benevolence, and ability
regarding environmental
performance
Chen [2010]
6 Switching Intention The extent to which a consumer is
willing to switch from one product
(green product) to another (non-
green product)
Nimako et al.
[2014]
448 The Extended Consequence of Greenwashing:
Perceived Customer Skepticism
International Journal of Business and Information
Table 2
List of Items for Each Variable
Variable [Adopted from]
1. Greenwashing [Laufer, 2003]
1. This product misleads with words in its environmental features.
2. This product misleads with visual or graphics in its environmental features.
3. This product has a green claim that is vague or seemingly unprovable.
4. This product overstates or exaggerates how its green functionality actually is.
5. This product leaves out or masks important information, making the green claim
sound better than it is.
2. Perceived Consumer Skepticism [Matthes and Wonneberger, 2014]
1. Most green claims in advertising are intended to mislead rather than to inform
customers.
2. I do not believe most green claims made in advertising.
3. Because green claims are so exaggerated, consumers would be better off if such
claims in advertising were eliminated.
3. Green Perceived Risk [Mohr, 1998]
1. There is a chance that there will be something wrong with the environmental
performance of this product.
2. There is a chance that this product will not work properly with respect to its
environmental design.
3. There is a chance that you will get a penalty for using the product.
4. There is a chance that using this product will negatively affect the environment.
5. Using this product would damage your green reputation or image.
4. Green Consumer Confusion [Chen and Chang, 2012]
1. It is difficult to detect the product in terms of environmental features.
2. It is difficult to recognize the differences among environmental-claimed products.
3. You are confused about deciding which green products should be purchased.
4. You rarely feel sufficiently informed about environmental features.
5. You feel uncertain about environmental features.
-continued
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Volume 10, Number 4, December 2015
Table 2 (Cont’d)
List of Items for Each Variable
5. Green Trust [Chen and Chang, 2013, from Chen and Chang 2012]
1. You feel that this product’s environmental reputation is generally reliable.
2. You feel that this products environmental performance is generally dependable.
3. You feel that this product’s environmental claims are generally trustworthy.
4. This product’s environmental concern meets your expectation.
5. This product keeps promises and commitment for environmental protection.
6. Switching Intention [Burnham et al., 2003]
1. How likely are you to switch to a competing service provider during the next
year?
2. What is the chance that you will stay with your service provider for the next
year?
4. RESULTS AND ANALYSIS
This section begins with a discussion of the independent t-test (online versus
offline data) and the non-response bias test. It then discusses and analyzes the
measurement model and presents four structural models. Following a general
discussion, we pinpoint the limitations of the current study and offer suggestions
for future research.
4.1. Independent t-Test: Online Versus Offline Data
In order to make sure that there were no significant differences between
data collected online and offline, we conducted an independent t-test by
comparing both means and by checking whether both were significantly
different. The t-test revealed that, except for the PCS construct, there were no
significant differences in the means for constructs from the 41 online
questionnaires and the 93 offline questionnaires. Although the PCS data for
online and offline questionnaires were found to be different, the significance
level was not really satisfactory since its score (0.03) was significant at p-value =
0.01, but insignificant at p-value = 0.05. From this, it could be implied that, at
significance level 0.01, there were no differences for all constructs between data
collected online and offline, thus providing support for combining online and
offline data. Table 3 presents the results of the independent t-test.
450 The Extended Consequence of Greenwashing:
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Table 3
Results of the Independent t-Test
Variables
Means
Std. Deviation
Sig.
(2-tailed)
Online
Offline
Online
Offline
Greenwashing
3.62
3.43
0.83
0.73
0.19NS
GCC
3.69
3.46
0.96
0.77
0.42NS
GPR
3.72
3.62
0.72
0.66
0.15NS
GT
3.59
3.44
0.78
0.62
0.25NS
PCS
2.48
2.78
0.81
0.64
0.02*
SI
3.39
3.06
0.90
1.08
0.80NS
Note: * p-value > 0.01; NS = not significant
4.2. Non-Response Bias Test
Non-response bias involves situations in which the people who do not
return a questionnaire have different opinions from those who do return it. In the
current study, 100 of the 300 offline questionnaires were not returned, and, of the
200 that were returned, only 93 contained usable data. Given this fact, it was
necessary to determine whether bias occurred in the offline questionnaire. There
were no non-respondents to the online questionnaire since each respondent was
required to complete the questionnaire before submitting it. Incomplete online
questionnaires were automatically rejected by the system. The results shown in
Table 4 indicate insignificance (2-tailed) in the t-test for equality means for all
constructs. This finding means that there is no difference between the data from
respondents and the data from non-respondents.
Table 4
Results of Non-Response Bias Test
Offline
Variables
Means
Std. Deviation
Sig.
(2-tailed)
NR
R
NR
R
Greenwashing
3.52
3.44
0.74
0.73
0.45NS
GCC
3.67
3.62
0.67
0.66
0.64NS
GPR
3.44
3.45
0.60
0.62
0.89NS
GT
2.79
2.78
0.67
0.64
0.97NS
PCS
3.54
3.47
0.79
0.77
0.49NS
SI
3.15
3.06
1.02
0.94
0.55NS
NR = Non-respondent R = Respondent NS = not significant
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4.3. Measurement Model
The means, standard deviations, and correlation matrix are shown in
Table 5. The data indicated that there were positive correlations among five of
the six variables – greenwashing, green consumer confusion, perceived consumer
skepticism, green perceived risk, and switching intention. The exception was
green trust. All variables correlated with green trust were found to have a
negative correlation. In addition to testing the common method variance (CMV),
we used Harman’s one-factor test. All items were included in an exploratory
factor analysis. Using the principal components analysis method, we limited the
number of factors to be extracted to 1, without any rotation. The percentage
variance for the extraction sum of squared loadings was 34.5%, which means that
there was no CMV problem in this study.
Table 5
Correlations of Constructs
Var.
Mean
Std.
Dev.
GW
GCC
PCS
GPR
GT
SI
GW
3.49
0.76
1
GCC
3.65
0.67
0.42**
1
PCS
3.53
0.83
0.57**
0.43**
1
GPR
3.49
0.67
0.45**
0.48**
0.51**
1
GT
2.70
0.71
-0.48**
-0.34**
-0.50**
-0.48**
1
SI
3.16
0.99
0.30**
0.28**
0.38**
0.27**
-0.40**
1
Note: *p < 0.05, **p < 0.01
We ran data from the 134 questionnaires that were returned in order to
test the reliability and confirmatory factor analysis. There were 5 items for
greenwashing; 5 items for green consumer confusion; 3 items for perceived
consumer skepticism; 5 items for green trust; and 2 items for switching intention.
All of the items had a Cronbach’s alpha greater than the required score of 0.60,
which indicated that the items in this study were reliable. All items were then
simultaneously tested to check loading factors in CFA. It was found that 1 item
in green consumer confusion and 1 item in green perceived risk had scores that
were too low. Those two items were deleted from the model. The analysis
results are presented in Table 6.
452 The Extended Consequence of Greenwashing:
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International Journal of Business and Information
Table 6
Cronbach’s Alpha and Standardized Regression Weight Scores for Variables
Variables
Items
Loadings
Cronbach’s
Alpha
Score
Greenwashing
GW1
0.764
0.847
GW2
0.741
GW3
0.712
GW4
0.716
GW5
0.696
Green Consumer Confusion
GCC2
0.636
0.799
GCC3
0.713
GCC4
0.700
GCC5
0.756
Perceived Consumer Skepticism
PCS1
0.881
0.794
PCS2
0.708
PCS3
0.691
Green Perceived Risk
GPR1
0.730
0.757
GPR2
0.708
GPR3
0.536
GPR4
0.622
Green Trust
GT1
0.635
0.815
GT2
0.744
GT3
0.661
GT4
0.671
GT5
0.727
Switching Intention
SI1
0.930
0.819
SI2
0.748
4.4. Structural Model
The conceptual model for this study is presented in Figure 1. It depicts
the six variables and the 10 hypotheses formulated with regard to links between
the variables. Figure 2 and Table 7 present the results for the full model. At the
base of the model in Figure 2 are several scores, beginning with GFI = 0.832. In
a structural model, the score of GFI = 0.832 was not considered really good.
However, GFI is not the only standard to test the model fit. It can also be tested
using RMSEA, CMIN/DF, and CFI. In the current study, the scores for RMSEA
(0.060), CMIN/DF (1.481), and CFI (0.914) were above the required threshold.
There were six paths that were estimated significant, and four that were not found
to be significant. Even so, the effects of nine paths were in line with the
Aji and Sutikno 453
Volume 10, Number 4, December 2015
proposed hypotheses in this study. Because four paths were not significant,
however, one can conclude that four hypotheses were not supported.
Figure 1. Conceptual Model for Current Study
Figure 2. Results for the Full Model
454 The Extended Consequence of Greenwashing:
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International Journal of Business and Information
Table 7
Summary of Results for the Structural Model
Hypothesis
Proposed
Effect
Path
Coefficient
Results
H1
(+)
0.62**
H1 is supported.
H2
(+)
0.73**
H2 is supported.
H3
(+)
0.67**
H3 is supported.
H4
(-)
-0.12
H4 is not supported.
H5
(-)
-0.40*
H5 is supported.
H6
(-)
-0.29*
H6 is supported.
H7
(+)
0.14
H7 is not supported.
H8
(+)
0.23
H8 is not supported.
H9
(+)
-0.01
H9 is not supported.
H10
(-)
-0.28*
H10 is supported.
Note: **p<0.01, *p<0.05
The results shown in Figure 2 and Table 7 demonstrate that an increase
in greenwashing will cause an increase in consumer confusion, skepticism, and
perceived risk relating to the environment and the consumer’s green image. The
current study found an insignificant path estimation between green consumer
confusion and green trust, which is surprising. The result is the opposite of that
presented in Chen and Chang’s [2013] study, which found a significant effect
between green consumer confusion and green trust. By way of explanation, we
can say that, with regard to the environment, people in Indonesia are at a
different stage than those residing in more developed countries. Although green
marketing practices in Indonesia are not as intense as they are in developed
countries, the increased focus on green marketing and green products in the mass
media has attracted the attention of Indonesian consumers and has stirred their
curiosity. It will be interesting to see the results when future research tests the
relationship between green consumer curiosity and green trust.
On the other hand, the results of this study supported H6, which
associates the negative effects of green perceived risk on green trust. This result
supported the findings of Chen and Chang’s [2013] study with regard to the
negative association between perceived consumer skepticism and green trust. The
more skepticism that the consumer perceives, the lower his or her trust in the
green product. This finding is a further contribution to academic literature. This
study also found that switching intention does not have a significant direct
relationship to three constructs (green consumer confusion, perceived customer
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Volume 10, Number 4, December 2015
skepticism, and green perceived risk). Yet, because these three constructs had a
significant relationship to green trust, it could be implied that green trust
mediated the link of those three constructs to switching intention.
To enrich the discussion about the structural model, we then conducted
several path tests to compare the model fit of the original model with that of the
new models. We also conducted the test to determine the relationship between
GCC and GPS as well as between PCS and GPR.
Path Test Model (1)
The first path test found that the new path addition connecting GCC to
PCS was not significant, with a regression weight of 0.06 (p-value >
0.05). The relationships between new path GCC and GPR and between
new path GPR and PCS, however, were significant. The remaining path
scores did not differ from those of the original model. The GFI (0.837)
for path test model (1) was slightly better than that for the original model
(0.832). The results for path test model (1) are depicted in Figure 3 and
are summarized in Table 8.
Figure 3. Results for Path Test Model (1)
456 The Extended Consequence of Greenwashing:
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International Journal of Business and Information
Table 8
Summary Results for Path Test Model (1)
Hypotheses Weight Model Fit
GW -> GCC
0.56**
CMIN/DF = 1.423
GFI = 0.837
CFI = 0.925
RMSEA = 0.056
GW -> PCS
0.48**
GW -> GPR
0.35**
GCC -> PCS
0.06NS
GCC -> GPR
0.45**
GCC -> GT
-0.11NS
PCS -> GT
-0.43**
GPR -> PCS
0.23*
GPR -> GT
-0.23NS
GT -> SI
-0.53**
Note: **p<0.01, *p<0.05, NS = not significant
Path Test Model (2)
The results for path test (2) indicated that the relationship between GPR
and GT was negative, which was significantly different from the result
for path test (1). But, the relationship of GCC to PCS and GT was not
different from that shown in path test (1). The overall model fit for path
test (2) was GFI = 0.831 and RMSEA = 0.060, which is similar to the fit
for path test (2), which had scores of GFI = 0.837 and RMSEA = 0.056.
To improve the model fit, we deleted the insignificant path connecting
GCC to PCS. The results for path test model (2) are shown in Figure 4
and Table 9.
Figure 4. Results for Path Test (2)
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Volume 10, Number 4, December 2015
Table 9
Summary Results for Path Test Model (2)
Hypotheses Weight Model Fit
GW -> GCC
0.59**
CMIN/DF = 1.477
GFI = 0.831
CFI = 0.915
RMSEA = 0.060
GW -> PCS
0.49**
GW -> GPR
0.64**
GCC -> PCS
0.08NS
GCC -> GPR
-
GCC -> GT
-0.14NS
PCS -> GT
-0.41**
GPR -> PCS
0.26*
GPR -> GT
-0.27*
GT -> SI
-0.53**
Note: **p<0.01, *p<0.05, NS = not significant
Path Test Model (3)
The results for path test (3) shown in Figure 5 and Table 10 indicate that,
although we deleted the insignificant path from GCC to PCS, the
remaining significance score and model fit did not improve.
Figure 5. Results for Path Test Model (3)
458 The Extended Consequence of Greenwashing:
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Table 10
Summary Results for Path Test Model (3)
Hypotheses Weight Model Fit
GW -> GCC
0.60**
CMIN/DF = 1.473
GFI = 0.831
CFI = 0.915
RMSEA = 0.060
GW -> PCS
0.52**
GW -> GPR
0.64**
GCC -> PCS
-
GCC -> GPR
-
GCC -> GT
-0.15NS
PCS -> GT
-0.41**
GPR -> PCS
0.26*
GPR -> GT
-0.27*
GT -> SI
-0.53**
Note: **p<0.01, *p<0.05, NS = not significant
Path Test Model (4)
In path test (4), the path from GPR to PCS was eliminated. The results,
shown in Figure 6 and Table 11, were not really different from the
original model. The only difference was that, in model (4), the direct
relationships between GCC, PCS, and GPR were eliminated. The results
indicated that, although those relationships were deleted, the model fit
still did not improve. The regression weight and model fit comparisons
between model 1-4 and original model can be seen in tables 12 and 13.
Figure 6. Results for Path Test Model (4)
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Volume 10, Number 4, December 2015
Table 11
Summary Results Path Test Model (4)
Hypotheses Weight Model Fit
GW -> GCC
0.67**
CMIN/DF = 1.488
GFI = 0.830
CFI = 0.912
RMSEA = 0.061
GW -> PCS
0.73**
GW -> GPR
0.61**
GCC -> PCS
-
GCC -> GPR
-
GCC -> GT
-0.15NS
PCS -> GT
-0.42**
GPR -> PCS
-
GPR -> GT
-0.28*
GT -> SI
-0.53**
Note: **p<0.01, *p<0.05, NS = not significant
Table 12
Regression Score Comparison Between Original Model and Models 1-4
Hypotheses Original Model Model 1 Model 2 Model 3 Model 4
GW -> GCC 0.62** 0.56** 0.59** 0.60** 0.67**
GW -> PCS
0.73**
0.48**
0.49**
0.52**
0.73**
GW -> GPR
0.67**
0.35**
0.64**
0.64**
0.61**
GCC -> PCS
-
0.06NS
0.08NS
-
-
GCC -> GPR
-
0.45**
-
-
-
GCC -> GT
-0.12NS
-0.11NS
-0.14NS
-0.15NS
-0.15NS
PCS -> GT
-0.40**
-0.43**
-0.41**
-0.41**
-0.42**
GPR -> PCS
-
0.23*
0.26*
0.26*
-
GPR -> GT
-0.29*
-0.23NS
-0.27*
-0.27*
-0.28*
GT -> SI
-0.53**
-0.53**
-0.53**
-0.53**
-0.53**
GCC -> SI
0.14NS
-
-
-
PCS -> SI
0.23NS
-
-
-
GPR -> SI
-0.01NS
-
-
-
Note: **p<0.01, *p<0.05, NS = not significant
460 The Extended Consequence of Greenwashing:
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International Journal of Business and Information
Table 13
Model Fit Comparison between Original Model and Models 1-4
Model Fit
Original
Model
Model 1
Model 2
Model 3
Model 4
CMIN/DF
1.481
1.423
1.477
1.473
1.488
GFI
0.832
0.837
0.831
0.831
0.830
CFI
0.914
0.925
0.915
0.915
0.912
RMSEA
0.060
0.056
0.060
0.060
0.061
In conclusion, there were no significant differences in model fit between
the original model and models 1-4. The results for model 1, however,
showed that there was a significant relationship between GCC and GPR
(reg. weight = 0.45, p-value < 0.01), even though the relationship
between GPR and GT was found not significant. Moreover, the
relationship between GPR and PCS was significant in models 1-4, and
GPR to GT was significant in the original model and in models 2-4. In
view of these results, we recommend that future research be conducted to
extend the models presented in the current study by adding deeper
theoretical support for the relationship between GCC/PCS, GCC/GPR,
and GPR/PCS.
4.5. Discussion
In our measurement model, not all items for GCC and GPR were used.
Because of a loading issue, we excluded the first item for GCC, which stated, It
is difficult to detect the products in terms of environmental features, and we
excluded the last item for GPR, which stated, Using this product would damage
your green reputation or image. Both items did not group into specified factors.
The first item for GCC converged in the GPR column, and last item for GPR
converged in the PCS column. As stated earlier, we think that personal image or
reputation with respect to green products is not a major concern in developing
countries like Indonesia. Our result differed from that of Chen and Chang [2013],
which found no problems with any of the items for GCC and GPR. It should be
noted, however, that Chen and Chang [2013] conducted their study in Taiwan,
where green marketing is perhaps practiced more formally.
In our structural model, which correlates all variables, we found that H4,
H7, H8, and H9 were not supported. We found it surprising that H4 (green
Aji and Sutikno 461
Volume 10, Number 4, December 2015
consumer confusion is negatively associated with green trust) was not supported.
This finding is in contrast to theory and the findings of previous studies. The
theory states that, when consumers are confused by misleading and unclear
advertising or messages, the situation will raise their suspicions and undermine
their trust. Furthermore, Mitchell and Papavassiliou [1999] stated that consumers
are reluctant to trust a product if they are confused about the product. Studies
conducted by Kalafatis and Pollard [1999] and Chen and Chang [2013] also
confirmed that GCC was negatively associated with GT. Although the
relationship was not significant, the direction was negative, providing support for
previous studies. We may argue that the relationship between GCC and GT was
not direct. There may be another variable that would help to explain it. Since
green products offer several values specifically concerning environmental safety
and health, consumers do not directly distrust them. Perhaps, green perceived
value may be the mediating variable.
Hypotheses 7-9 relate GCC, PCS, and GPR to switching intention. In the
current study, we connected those variables to switching intention. This
approach has not yet been considered in greenwashing literature, perhaps because
of the theory that consumers may switch if they are confused or skeptical or
perceive risks associated with green products. This study found that the three
variables did not have a significant relationship to switching intention. It can be
inferred that, even though consumers are confused or skeptical and perceive
certain risks associated with green products, they do not easily decide to switch
to non-green products. Figure 2, shown earlier, indicated that the relationship
between PCS and GPR was fully mediated by GT. This result may therefore be a
significant contribution to greenwashing literature with regard to considering the
switching intention variable in relationship to GT. In this context, the exception
was made for GCC, which did not have a direct effect on switching intention, as
well as an indirect effect via GT. As stated earlier, perhaps the insignificant
relationship can be explained by value perception (green perceived value).
4.6. Limitations and Future Research Direction
In this study, we conducted four pre-surveys to test items included in our
questionnaire. During the first and second pre-survey trials, many respondents
were confused about the questions, mostly because they were unfamiliar with
green product features, and also because we operationally defined greenwashing
in a very general way, when in fact greenwashing may be found in several
industries. Both factors were limitations. Respondents’ understanding improved
462 The Extended Consequence of Greenwashing:
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for the third and fourth pre-survey trials. With respect to the limitations of the
current study, we offer these comments and suggestions for future research
direction:
1. In emerging countries like Indonesia, green marketing is not a formal
practice as it is in developed countries. Future research should take
this factor into consideration. Furthermore, future studies should
specify which green product in which industry is to be scrutinized.
Future researchers may choose, for example, the food and beverage
industry, or the automotive industry, or another industry of their
choice.
2. Because of the insignificant direct relationship between GCC and
green trust and the significant relationship between PCS and green
trust, we suggest that future researchers add green perceived value as
a mediating variable. We suggest also that it would be interesting for
future studies to test the indirect relationship between GCC-PCS-GT
and between CGG-GPR-GT in the context of a different location.
3. We think it would be worthwhile to conduct an experimental survey
to examine the causal impact of greenwashing. Through such a
survey, future researchers can extend the current study to include an
analysis of consumers’ green purchase behavior.
5. CONCLUSION AND IMPLICATIONS
This study proposed extended relationships, which are perceived consumer
skepticism (PCS) and switching intention (SI). Data were separated between
online and offline questionnaires. An independent t-test showed that data from
both sources were not significantly different, which allowed us to combine both
as a single data. As to the proposed extended consequences of greenwashing, this
study found only PCS, a finding that was confirmed by statistical computation.
Respondents generally felt that green ads were misleading and they were
therefore skeptical about the ads. We found that variable switching intention was
significant only as the consequence of green trust (GT). Our results, therefore,
confirmed that PCS is the extended consequence of greenwashing and that
switching intention (SI) is the consequences of green trust (GT).
Of the 10 hypotheses examined, six were not supported. We argued that a
mediating variable needs to be added to explain the unsupported hypotheses. It
Aji and Sutikno 463
Volume 10, Number 4, December 2015
seems that Indonesian consumers still perceived several values that can be gained
by purchasing and consuming green products. We therefore recommend that
future researchers consider green perceived value as the variable mediating the
relationship between GCC and GT. In this way, the current study makes a
theoretical contribution to greenwashing literature and also contributes the
measurement model discussed earlier. Following are the implications for
companies in all sectors:
1. Companies must stop all deceptive advertisements and claims with
respect to environmental protection, specifically with regard to “green”
products and services. This action will reduce consumer confusion,
skepticism, and perceived risk regarding green products.
2. Companies must also enhance green trust in order to retain customers
and to prevent them from switching to non-green products.
3. Although green marketing and environmental practice in developing
countries like Indonesia are not as advanced as in developed countries,
companies must recognize that the potential market for green products in
these countries is strong, as long as they avoid deceptive and vague
advertising.
The last factor, in particular, makes Indonesia a good potential location for
future research on greenwashing. Regardless of the country in which future
research is conducted, researchers should clearly specify the industry in which
they plan to scrutinize green products; they should test mediating variables as
discussed in this study; and they should test causal relationship by conducting an
experimental survey.
We hope that the research results of this study will be useful to managers,
practitioners, academicians, and other researchers, and that by serving as a
reference, it will make a significant contribution to future research.
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ABOUT THE AUTHORS
Hendy Mustiko Aji is an M.Sc. student in the Faculty of Economics and Business,
Universitas Gadjah Mada, Indonesia. He obtained his bachelor of international
business management degree from Universiti Utara Malaysia (2011), and his
bachelor of management degree from Universitas Jenderal Soedirman-Indonesia
(2012). He has research interest in marketing, with a focus on general marketing
theory, green marketing, Islamic marketing, consumer behavior, and strategic
marketing.
Bayu Sutikno is an associate professor in the Faculty of Economics and Business,
Universitas Gadjah Mada, Indonesia. He received his bachelor of management
degree from Universitas Gadjah Mada-Indonesia (1999), his master’s degree in
strategy and management from NHH-Norway (2002), and his doctor of philosophy
degree in marketing from NCU-Republic of China (2011). He has presented
academic papers in the United States, Italy, China, Australia, Japan, Indonesia,
UEA, and South Korea, with a focus on marketing strategy, channels of distribution,
and global marketing.
