The fiercely competitive business environment of present means organisations are endeavouring to gain dominance. In order to achieve such advantage organisations require business research. A proficient research study gives businesses deeper understanding of the environment enabling them to generate tailored and hence successful strategies.
Within the marketing industry, there has long been the notion that ‘sex' is a powerful marketing method, however this belief has steamed mainly from work in the western world (La Tour and Henthorne, 2003), and there is little knowledge on its effect within disparate cultures (Ford et al, 2004). With the rapid escalation of globalisation, organisations are expanding their reach on an international scale, yet in many cases, are continuing to use out-dated sectional practices. The continued and growing use of sexual advertising by western firms in the developing world is testament to this (Liu et.al, 2009). Many academics dispute the use of standardised practices and argue the need for specificity between markets (Griffith et al, 2003).
As a result, global empirical research has been conducted in order to examine their diverse interpretations and fill this considerable gap of knowledge. Owing to the field of consumer responses being “unavoidably interdisciplinary” (Wan et al, 2014), there are many different techniques in which to investigate such a field. The aim of this essay therefore, is to critically examine and discuss the strength and weaknesses of the three main research methods, in investigating an international business topic such as the impact of sexual advertising in a global context. Three articles were chosen to illustrate the range of methodologies specifically, quantitative research methods, qualitative research methods; and mixed methodologies respectively.
Finally, this essay will then critically consider the various advantages and disadvantages of collecting primary and secondary data to achieve a veracious and panoptic argument.
When conducting research it is first necessary to identify and establish your research problem and develop your hypotheses (Sreejesh et al 2014). Then you need to design the ‘framework' of the research via your methodologies (Sreejesh et al 2014). The design should reflect your research question and the end results needed to be obtained (Sreejesh et al 2014). There are two main factors to consider when doing so; do you need data qualitative data, advocated by interpretivist philosophers (Goldkuhl 2012), quantitative data advocated by positivist philosophers (Goldkuhl 2012), or a mixture? And do you need primary or secondary data? Using a schematic diagram such as figure 1 can often assist when making theses significant decisions.
Quantitative Research Methods
The research article published by Liu et al (2009), uses quantitative data as its design method in order to asses “Consumer responses to sex appeal advertising: a cross-cultural study”.
Quantitative methods focus on quantity and thus predominantly use numbers to gauge by ‘how much' and to ‘what degree' (Rasinger, 2013), defined by Bryman (2012) as “A research strategy that emphasises quantification”. Quantitative methods hence provide many advantages in data collection. There emphasis on large sample sizes, random candidate selection, and uniform scaling, enables results to be extrapolated to a population level (Carr, 1994). With regards to the research question of said paper, this is highly beneficial, as the aim is to “examine the effect of sex appeal on ad and brand evaluation among Australian, Chinese and US consumers”. Qualitative data hence allows the data collected to make claims at a national population level, rather than just between test subjects.
The use of quantitative data allows quick and easy comparison of data sets between the various sub-groups, which is definite. Where as qualitative data can be open to greater exegesis (Sreejesh et al 2014), Bryman (2012) classified positivism as nomothetic research. The exemplar study (Liu et al 2009), although it does not specifically categories so in its abstract aims, recurrently promotes the uses of its findings to force international organisations to change their marketing practices. When we consider Sallee and Flood's (2012) argument that stakeholders favour the use of quantitative data when making decision, the use of such data in this study would allow greater validly to impel firms to adapt their sexual advertising dependant to individual markets.
Qualitative data however is not all encompassing and does have its shortcomings. It tends to neglect meaning and context, and Blaikie (2007) explicitly claims quantitative data is insufficient for understanding societal difference, which is the goal of the study. Although this study may provide data showing “country had a significant effect on consumer's attitudes” (Liu et al, 2009), it does not give rational as to why or for what reason. In their practical implications Liu et al (2009) claim their study provides “understanding” on “how consumers in different cultures respond”. Using the definition of “understanding” that you “perceive the intended meaning of” (Oxford dictionary 2018) this claim is feeble. Unlike qualitative research that provides situational understanding Bae et al (2015), quantitative research fails to ascertain meanings and explanations (Rahman, 2016). As a result the use of solely quantitative methods here is not ideal in justifying their practical implications. However due to the advantages of generalisation as stated, quantitative methods would still be the most advantageous design for this study.
Qualitative Research Methods
The research article studied, published by Bae et al (2015), uses qualitative data as its design method in order to asses “Offensive advertising in the fashion industry: sexual objectification and ethical judgments of consumers”.
The definition of qualitative methods can be somewhat indistinct owing to the fact they lack a distinct code of practices (Denzin & Lincoln, 2011) but Babbie (2014) define them as a method of observation to collect non-numerical data. Qualitative methods are hence refereed to as an “overarching concept” (Rahman, 2016), encompassing the capability to investigate many topics. This immediately highlights their potential in examining an interdisciplinary field such as consumer responses.
A principle attribute of qualitative data is its adequacy in providing detail. In a case such as this specific research article, this is highly beneficial. It compares two international organisations namely Dolce & Gabbana and American Apparel who both use sexual advertising but with opposite consequences. Quantitative data on such a topic would simply confirm consumers have different perspectives towards the two companies, however qualitative data enables a holistic discussion further than this, highlighting ‘how' the perspectives are different. For example D&G's advertising is described by consumers as “glamorous” and “elegant” where as AA is described as “pornographic” and “trashy” (Bae et al 2015). This design method would allow AA easily ascertain how their advertising is being viewed, and how they need it to be viewed in order to be successful.
Interpretivism is claimed to display a comprehensive understanding of participants perceptions (human experience) (Rahman, 2016), allowing “insight into underlying cognition” thus providing information on “feelings, thoughts and behaviors” (Bae et al, 2015). In a case such as this where the aim is to “understand consumers perceptions” ” (Bae et al, 2015), the use of qualitative data is hence favourable. In this research study qualitative data allows discussions and conclusions to be drawn regarding consumer “Perceptions” and “Opinions”. This aids them in forming a coherent argument to claim, “it would seem wise for AA to cease its inappropriate marketing campaigns” (Bae et al, 2015).
However qualitative methods do have their deficiencies. One major drawback is that the use of qualitative research results in smaller sample sizes due to their laborious, as well as complex, data collection and analysis (Richards and Richards 1994; Flick, 2011). Consequently, smaller sample sizes, and their conclusions drawn are less generalisable (Leung, 2015). With regards to the research article it is clear only small sample sizes where collected for D&G and AA (340 and 443 respectively (Bae et al, 2015)). Therefore any claims they make towards the “fashion industry” as a whole, as is the title of the paper, are weak. In their conclusions they state “our findings confirm that advertising using sexual appeals is no longer a compelling factor for consumers”, which is hence highly speculative. They may have evidence that this is the case within AA, but to make generalised claims regarding consumers is conjectural. However, the majority of their argument does stick closely to AA and D&G customers, with their core verdict to advise AA being well founded. Issues only arise when they try to make wider-ranging claims.
Mixed methodologies Research
The article published by Wan et al (2014), utilises a technique known as ‘mixed methodologies' in order to asses “Consumer responses to sexual advertising: the intersection of modernization, evolution, and international marketing” and answer their extensive list of sixteen different hypothesises.
‘Mixed methodologies' is a research approach where a combination of both qualitative data and quantitative data is used by the researcher in order to answer the research question. According to Malina et al (2011) using a “mixed method approach provides the best opportunity for addressing research questions”, this is due to the fact that this method engages both qualitative and quantitative methods concurrently to creating a more cogent argument than adopting such methods individually.
Combining both methods can be a fruitful exercise as their varying data natures allows complementation, gap filling, weaknesses strengthening, and thus validation. For example quantitative data provides numbers showing effect or impact, malleable to statistical analysis, however it is weak in providing context or meaning. The reverse is true with regard to qualitative data, which provides description and understanding but lacks precisions. Using the two in combination can thus counterbalance these weaknesses, providing meaning to numbers, and providing stronger evidence for conclusions.
With regards to the research article this is hence beneficial as the article focuses on assessing consumers attitudes. Measuring attitudes is a complex task, which in contrast to physical science, are ambiguously scaled (Sreejesh et al 2014). As previously mentioned qualitative research provides “insight into underlying cognition” (Bae et al, 2015), and quantitative research provides insight into “how much and to what degree” (Rasinger, 2013). As a result combining the two would be superior to any one alone (Tariq and Woodman, 2013). It would allow results to be relatable to a societal context (Blaikie 2007) and also scalable to an international context (Carr, 1994), both imperative qualities of the research question.
However mixed methodologies do still have their flaws. The combination of methodologies can be viewed as controversial owing to the fact they “belong to separate and incompatible paradigms” opening it to criticism from ‘purists' in both camps (Tariq and Woodman, 2013). Using both in combination can be time consuming and require greater resources (Tariq and Woodman, 2013), which can be exacerbated by the fact researchers are often qualified in one research camp and thus can face expertise limitations in the ‘other' (O'Cathain et al, 2008). With regard to this research article this is evident when we consider all research was conducted and completed in November 2012 (Wan et al, 2014), yet the paper was not accepted until February 2014. This may also be a result of presentation of the combination of data can be complicated to illustrate comprehensively and take time to organise. This is highlighted when we consider the abundance of different tables and figures throughout the result and discussion section. However when we consider the papers ability to sufficiently answer the research question and abundant list of hypothesises, this extra time and endeavour has enabled a through and absolute argument to be produced.
Primary vs. Secondary data
Another factor one should consider when designing their research method is the use of primary and secondary data. Primary data defined as “original data collected for a specific research goal” (Hox and Boeije 2005), can provide great advantage. It allows the investigator to specifically design a unique and tailored procedure with great control, permitting “causal interpretation” described as “internal validity” (Hox and Boeije 2005). The research article of Liu et al (2009) uses primary data in its investigation; here it is useful as it allows the researches to design a specific collection protocol to examine consumer responses. It would be difficult to utilise secondary data in such a case, as in its originality report it states, it is the “first reported empirical study” within its specific field (Hox and Boeije 2005). However it does have its limitations due to this specificity as it can a very prolonged process.
On the other hand secondary, “data originally collected for a different purpose and reused for another research question” (Hox and Boeije 2005), allows investigators to utilise previously published data as evidence for their study. It has its advantages, as it does not require arduous data collection, as the results are already there. In the case of Bae et al (2015) in which secondary data is used, it is greatly advantageous. As previously stated they implement a qualitative data design, which can be very time consuming, using secondary can counterbalance this negative. Also with regard to the sample size, which as stated in qualitative methods tends to be smaller, secondary data can also counterbalance this, allowing larger data sets to be collected without any further physical research. However in contrast to primary data, secondary data can be irrelevant, difficult to locate and difficult to evaluate (Hox and Boeije 2005).
With regard to Wan et al (2014)'s study, they in fact utilise a mixture of both primary and secondary data. Here the mixture of both is testament to its mixed research design. The fact is has a multi-layered factorial testing system it would be very indeterminate to use just one data type. Primary data alone would be incredibly time consuming and narrow for its extensive and global aims, for example defining level of modernisation would be very confined compared to using secondary data of “per capita income”. Also secondary data alone would be difficult to design a specific procedure with controlled variables when for example measuring consumer responses to their specially designed advertisement.
In conclusion there are clearly an array of different variables to consider when designing a extensive and complete research project, most notably the form of data collected; qualitative/quantitative/mixed/primary/secondary. Each data form has its own advantages as well as disadvantages, which must be critically considered with regards to the specific research question and aim of the study. This is evident in the three papers critically analyses. It is clear extensive consideration has been taken. Each has contrasting methodologies but each also has slightly different research objectives. Although they may all be researching the same umbrella topic of “sexual advertising” they each come with their own individual angle and purposes, hence making the differences in methodologies pertinent. There may also be negatives to using a certain methodology for a specific study as shown, however this is to be expect as no one method is all-encompassing, the aim is to select the best suited and most beneficial method.
Therefore there is no ‘one best method' it is highly case dependent, and many factors should be considered when making such a selection, specifically the end result that needs to be obtained.
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