1. PERSPECTIVA EPISTEMOLÓGICA SOBRE LA REFERENCIA
1.3. Heterogeneidad de los fenómenos referenciales
Data collection methods include secondary data collection, experiment, interview, case study,
focus group, survey, etc. The choice of method for a particular study depends on the specific
research questions and the purpose of the study. In this study, focus groups were first piloted
(see Section 5.2.1.3) in order to check how the representatives of the target group would
understand focus group questions. After revising the question structure and wording, two
focus groups (see Section 5.3) were used to obtain more information to determine fictitious
company, brand and cause names, and to elicit salient beliefs, and probe the relevant
information in relation to consumer cynicism. Then the respondents of the focus groups were
contacted again to identify the high/low brand-cause fit on which the main research would
focus (see Section 5.2.4). The findings from the focus groups were then used to develop the
experimental treatments for the factorial experimental research. A pre-testing (see Section
6.4), which included an expert panel discussion and a convenience sample of respondents,
was conducted in order to check the validity and reliability of the questionnaire before the
main survey. Another pilot study (see Section 6.5) was then used to test the questionnaire
before conducting the main study. The convenience sample of respondents that participated
in focus groups and pilot studies were all excluded from the main quantitative study. Finally,
the questionnaire was developed to collect the data in order to test the research hypotheses
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Figure 4.1 Key Steps of Research
Focus group
Aim: to determine fictitious names for company, brand, and causes. To elicit salient beliefs and probe the relevant information in relation to consumer cynicism; to determine high/low brand-cause fit. Focus group protocol was developed.
Aim of Piloting of focus groups: to assess the discussion format, length of time required, and relevant issues when managing a discussion; to obtain comments on how the focus group questions come across from representatives of the target group. (Two individuals participated in the piloting of the focus group)
Focus group data collection: 2 groups (one consisting of 8 participants, the other of 7).
Determine Brand-cause fit: Focus group participants were contacted again to determine high/low brand- cause fit from the chosen brand name and chosen causes.
Quantitative design
Draft questionnaire was developed based on literature and the findings of focus groups. As the research adopted a 2 × 2 factorial experimental design, four types of questionnaires containing four different experimental stimuli/scenarios were developed.
Pre-testing of Questionnaire
Aim: To clarify that the target population understand the wording of the questions.
Sample Size: Three colleagues and four students (the debriefing method, which involved discussing each question and the associated problems with the scholarly experts and respondents).
Pilot Study
Aim: To refine the scale items and ensure the target population understand the questions.
Sample Size: 12 undergraduate students.
Quantitative data collection Aim: To explore how well the collected data fit the proposed model.
Sample Size: Sample size of 420 was collected.
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Quantitative methods and statistical analysis were used in this research. The main
quantitative methods include surveys and experiments. Survey is a type of descriptive
research and experiment is designed to examine causal relationships (Iacobucci and Churchill,
2009). This study aims to examine the effect of combining natural disaster and ongoing
causes and brand/cause fit conditions in a CRM offer on consumer cynicism and its
attitudinal consequences. The majority of the literature on CRM has also used quantitative
rather than qualitative methodologies (e. g. Piliavin and Charng, 1990; Skitka, 1999; Ellen et
al.,2000; Cui et al., 2003). These studies have consistently used experimental designs that
have evaluated the effect of brand-cause fit or donation situation or cause types on the CRM
offers. Therefore, an experimental design is appropriate for the current study. The experiment
was conducted in the context of CRM.
According to Malhotra and Birks (2012), there are four main types of experimental design:
pre-experimental, true experimental, quasi-experimental, and statistical experiment (see
Figure 4.2). Pre-experimental designs entail experiments in which there is no randomisation
of respondents to experimental groups. Pre-experimental designs include one-shot case study,
one-group pre-test-post-test, and static group. A true experimental design entails a higher
control of the experiment and the subjects are exposed to the arranged stimuli randomly (Kirk
2003). Quasi-experimental designs entail experiments where only some, but not all aspects of
experimentation are included. Statistical experimental designs entail experiments in which
there is typically statistical control, and external variables are analysed. A factorial
experimental design is deemed appropriate for this thesis. Factorial designs enable the
research to measure the effect of two or more independent variables (or factors) on the
dependent variable (Malhotra and Birks, 2012). In this research, the factors include brand-
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scenario-based experiment was employed. Scenario-based experiments entail the design of
hypothetical scenarios containing experimental manipulations. The hypothetical scenarios are
typically embedded into self-completion questionnaires, which are randomly assigned to
respondents.
Figure 4.2 A Classification of Experimental Designs
Source: Malhotra and Birks (2012)
There are limitations that are associated with experiment designs, including scenario-based
experiments, such as the concerns about the ecological and external validity of
experimentation (Malhotra and Birks, 2012). The extent to which the situation depicted in the
hypothetical scenarios is realistic (ecological validity) and can be generalised to real life
situations (external validity) is often questioned. In order to offset the above-mentioned Experimental Designs
Pre-experimental True Experimental Quasi-
experimental Statistical One-shot case study One-group pre- test-post-test Static group Pre-test-post-test control group Post-test only control group Solomon four- group Time series Multiple time series Randomised blocks Latin square Factorial design
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limitation, the use of pre-testing is highly recommended (e.g., Lynch, 1982; Perdue and
Summers, 1986). Accordingly, a preliminary survey and pre-testing were conducted prior to
the main study.
Randomization is considered a key element when conducting experiments. Based on
randomization, three types of experimental design are identified: between-subject, within-
subject, and hybrid (Field and Hole, 2003). Between-subject designs refer to the random
assignment of experimental conditions (treatments) to different groups of respondents, which
means that each group is exposed to one experimental condition only. Within-subject designs
refer to the assignment of all experimental conditions to each participant, which indicates that
each participant is exposed to multiple experimental conditions in sequence (Cash et al.,
2016). Hybrid designs (also referred to as ‘mixed’) involve a combination of between-subject
and within-subject designs. All three designs have advantages and disadvantages (see Table
4.2. Compared to within-subject designs, between-subject designs minimize the risk of the
fatigue effect on the respondents. Fatigue and boredom can occur when respondents are
subject to more than one experimental condition. Respondents change their responses as they
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Table 4.2 Between-subject versus Within-subject Designs
Source: Field and Hole (2003)
In consideration of the fatigue or carry-over effects that are typically associated with within-
subject designs, a between-subject design was chosen for this research. As suggested by Field
and Hole (2003), counterbalancing can help to address the carryover effect in between-
subject designs. However, the implementation of counterbalancing remains a great challenge
especially when there are several experimental conditions involved (Field and Hole, 2003).
Counterbalancing would have been difficult as this research includes several experimental
conditions, i.e., the effect of brand-cause fit and donation situation (natural disaster versus
ongoing cause). As such, the between-subject design was deemed more appropriate.
In this study, the experiment has a 2 × 2 factorial design in which independent variables,
namely, types of donation situation (natural disaster versus ongoing cause) and brand-cause
fit (high versus low) were manipulated. As shown in Figure 4.3, four experimental conditions
were outlined: a natural disaster cause and a high brand/cause fit condition, a disaster cause
and a low brand/cause fit condition, an ongoing cause and a high brand/cause fit condition, an
ongoing cause and a low brand/cause fit condition.
Between-subjects Within-subjects
Simplicity High Low
Fatigue effect Low High
Economy Low High
Sensitivity Low High
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Experimental design is commonly used in CRM studies (e.g., Ellen et al., 2000; Cui et a.,
2003; Pracejus and Olsen 2004; Ellen et al., 200; Nan and Heo, 2007; Hou et al., 2008; Das et
al., 2016; Melero and Montaner, 2016; Vyravene and Rabbanee, 2016). Many of these studies
focus on the influence that CRM has on consumers’ positive attitudes, however, the negative
effect of CRM is less well documented in marketing studies (Grolleau et al., 2016). The
quasi-experimental design adopted by this research allows for comparison between the
impacts of different types of CRM offers on consumer cynicism, which is regarded as one of the negative effects of firms’ conducting CRM campaigns (Hawkins, 2012).
Figure 4.3 Experimental Conditions
High
Brand-cause fit
Low
Disaster Type of donation situation Ongoing Natural Disaster cause
High brand-cause fit
Ongoing cause
High brand-cause fit Natural Disaster cause
Low brand-cause fit
Ongoing cause
102 Stimulus for Experimental Design
Experiment stimuli were created in order to achieve one of the objectives of the current
research (i.e., to investigate the effect of brand-cause fit and the effects of natural disaster and
ongoing cause on consumer cynicism). Fictitious names were used to prevent any existing
bias towards real companies and product brand names (Goldberg and Hartwick, 1990). This
required the choice of a fictitious company name and a fictitious brand name. This practice is
common in CRM studies (i.e., Herr et al., 1991; Bone, 1995; Laczniak, et al., 2001; Yoon et al., 2006; La Ferle et al., 2013). Similar to Lafferty’s (2007) work, this study used “NND” as
a fictitious company name. The chosen fictitious company was shown to respondents during
focus group sessions in order to ensure that “NND” has no specific associations.
The type of products (i.e., hedonic versus. utilitarian) chosen for CRM can also affect consumers’ evaluation of the campaign (Melero and Montaner, 2016). The feeling of guilt
associated with hedonic purchase can affect the link with a cause (Hagtvedt et al., 2016;
Melero and Montaner, 2016). Utilitarian products tend to be associated with less emotional
responses. In order to effectively investigate consumer cynicism without the potential
influence of guilt, this research used utilitarian products. Toothpaste is often chosen to
represent utilitarian products in CRM studies (i.e., Baghi, et al., 2009; Lafferty, et al., 2014;
Müller, et al., 2014; Das et a., 2016; Hagtvedt et al., 2016; Johansson et al., 2016; Melero and
Montaner, 2016). Based on the reasoning above, in this study, toothpaste was selected as a
product because it is also relevant to the sample population, and is a product with which they
would be familiar.
Moreover, the type of donation situation was also manipulated by varying the non-profit
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NPOs). In order to choose a cause that was perceived to be connected to natural disasters, the
non-profit organization included in the CRM initiative focused on supporting people affected
by natural disasters. Social problems or high humanity were used to represent the ongoing
causes. Thus, the fictitious non-profit organizations created for the disaster condition were:
National Flood Relief, Dental Fund for Tsunami Victims, Extreme Weather Relief, and
Natural Disaster Recovery Fund. For the ongoing cause condition, the fictitious non-profit
organizations were: Dental Fund for Orphans, Road Safety Trust, Save the Dolphins, and
AIDs Trust. During the focus groups, these fictitious causes were shown to the respondents to
ensure they understood them. Following the focus group, from a list of eight fictitious causes,
the respondents were asked to rate how compatible they felt each cause was with the selected
brand of toothpaste if they were to form a partnership.
After obtaining the results of the stimuli mentioned above from the focus groups, a
description of the fictitious brand partnering with the fictitious cause was developed. It was
evidenced that donation amount and the format of donation amounts (i.e., percentage versus
absolute) played an effect on brand and consumer intention to purchase (e.g., Müller et al.,
2014; Kleber, et al., 2016). To minimize experimental bias, no specifics were given as to the
amount of contribution by the company. Respondents saw only that the company would contribute “a portion of the proceeds” from the purchase of toothpaste to the designated cause.
Respondents were asked to read a short description of the CRM practice that the fictitious
company participates in before answering the questions on the questionnaire. The
introduction was as follows:
“NND is a company that manufactures toothpaste products. NND’s toothpaste brand XXX
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of consumers. The toothpaste brand XXX has recently teamed up with YYY and would make
a donation to this cause each time consumers purchase its products. The YYY is a non-profit organization that supports…[a brief introduction of the charity]. For every product bought,
XXX [brand name] toothpaste a portion of the proceeds will go to this worthy cause”.
After reading the above experimental stimuli, respondents then completed a questionnaire. The other variables of this study’s conceptual model were assessed in the questionnaire. The
questionnaire was identical for all conditions. A pilot test (see Section 6.5) administered to 12
undergraduate students, excluded from any further participation, revealed whether any
changes in wording were necessary.