The Impact of Unethical and False Advertising on Social Media Towards Consumer Buying Behaviour: An Examination Among
Young Adults in Malaysia
Meerat Tayyab Mukhtar Qureshi1*, Kanesh Gopal2*
1 1School of Management and Marketing, Taylors University, Malaysia
2Faculty of Accounting, Finance and Business, Tunku Abdul Rahman University College, Malaysia
*Corresponding Author: [email protected], [email protected]
Accepted: 15 February 2023 | Published: 1 March 2023
DOI:https://doi.org/10.55057/ijbtm.2023.5.1.13
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Abstract: Multiple discussions and papers exist regarding the impact of false advertising on consumer behaviour. However, there has been little information on false and unethical advertising through social media platforms in Malaysia. Existing research have focused on various other information such as the impact of deceptive advertising on women purchasing behaviour in Pakistan, the influence of false claims from advertisements conveyed through word-of-mouth, the effect it has on gender-based customers, etc. This paper focuses on the impact of false advertising found in social media and e-commerce platforms on consumer buying behaviour, with an emphasis on young adults. It further identifies the importance of adhering to the principles of ethics in terms of advertising. The study consists of a sample size of 103 young adults in Malaysia. The Pearson Correlation Test had shown a significant correlation between all three independent variables, with a strong relationship was discovered between intent to purchase and perceived risk with the buying behaviour of consumers. The results of this study showed that advertisements on online platforms manipulated the purchase behaviour of consumers, specifically young adults in Malaysia.
Keywords: Unethical and false advertising, social media, customer buying behaviour, young adults in Malaysia
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1. Introduction
Businesses and marketers generally advertise on social media due to the vast advantages it brings to their business. According to Appel et al. (2020), the top social networks that businesses use to advertise to a massive audience include Facebook, Instagram, Twitter, Pinterest, LinkedIn and Snapchat, respectively. With over 2 billion users, Facebook is the most popular social media space, providing unparalleled opportunities that virtually reach out to mass audiences. Data Commons (2018) reported that Malaysia’s population is approximately 31 million. A large percentage of the total population has access to such platforms and engage in online purchases. In this paper, the dependent variable is consumer buying behaviour, while the independent variables Include reliability and truthfulness in the source of information received from advertisements, female stereotyping in online advertisements, purchasing power and the intention to take risks in purchase decision.
Although numerous discussions and papers exist regarding the impact of false advertising on consumer behaviour, little to no information is present when it comes to false and unethical advertising through social media platforms, specifically in Malaysia. As previously mentioned, existing research only focused on one aspect of information such as the impact of deceptive advertising on women purchasing behaviour in Pakistan, the impact of false claims about advertisements conveyed through word-of-mouth, the impact it has on gender-based customers, etc. To contribute to more research, this paper chose social media and e-commerce platforms to identify the impact of false advertising on consumer buying behaviour and the importance of following ethical principles in terms of advertising.
2. Literature Review
2.1 Reliability and Truthfulness in the Source of Information
Reliability and validity of information provided to consumers through advertisements over social media do affect consumers’ ability to make wise purchasing decisions. This is especially true if they are unaware of the presence of deception, leading to impulsive or bad decisions when purchasing goods online. Consumers have become more vulnerable and prone to making irrational choices (Saguna, 2014). Reliability of advertisements over social media has reduced due to exaggeration (Faerber and Kreling, 2014).
Misleading and deceptive advertising can also be morally objectionable as well as hold the potential to cause harm to consumers as it may claim product features that are untrue and/or do not exist at all (Waller, Fam and Erdogan, 2005). Deceptive advertising will lead to adverse consumer reactions toward the seller, such as suspicion and negative word-of-mouth (Prendergast and Hwa, 2003). In contrast, Romani (2006) argued that consumers cannot always take advantage of calling an advertisement ‘misleading or deceptive’ due to their own lack of understanding or interpretation of the content of the ad itself. Therefore, companies that wish to maintain customer loyalty must make their objectives informative and accurate in terms of product advertising on social media since customers cannot view or hold the product before purchasing. This is the nature of the online channel used to sell products; therefore, marketers must diligently adhere to accurate and precise online ads (Sharma and Sharma, 2014).
Sellers using online platforms must gain their customers trust through their advertising methods. This becomes more vital as consumers are unable to feel or hold the product when purchasing from social media and online platforms. According to Ha (2008), among other mediums of advertising, the least trusted are e-commerce channels and social media. Despite the unreliability and lack of trust in most advertisements out there, nearly half of consumers that view products and service ads are likely to purchase nonetheless, while the other half prefers to physically see the product before purchasing (Salim and Abdullah, 2017). Soh, Reid and King (2009) concluded that after viewing an online advertisement, there are three steps that initially go through a customer’s mind before deciding on whether or not to purchase.
In an argument regarding online advertisements, Pressy and Milton’s (2013) research found that millennials (aged between 16-34) frequently experience feelings of annoyance and can have an unpleasant retail experience when they come across more than needed pop-up advertisements and/or YouTube adverts. The unpleasant emotion leads to the belief that traditional offline methods of advertising are more reliable since online methods feel more
‘forced’ and ‘in the face’, pushing them to make a purchase. The negative attitude and frustration towards extensive ‘flashy’ and ‘loud’ advertising over networks, such as Facebook
and YouTube videos, automatically prompts consumers to lose interest in making a purchase (Hemsley et al., 2018).
Despite the unreliability and frequency of ads over social media, customers still prefer to continue using free online services instead of paying for ad removal. Sellers will still be able to reach out to their target audience one way or another (Hadija, Barnes and Hair, 2012).
According to Payne and Pressley (2013), in digital marketing, advertisers tend to go overboard and exaggerate the product features. They benefit in such a sly and tactful manner that the consumer goes through physiological pressure from advertising persuasiveness, leading to the decision of unintentional purchase. Online ads over social media are often accused of promoting different types of materialism, falsifying content and demeaning personal and religious values, especially to the younger target audience (Suggett and Paul, 2017).
2.2 Female Stereotyping
Another aspect that affects consumer buying behaviour is gender stereotyping and the incorrect portrayal of using gender roles to create eye-catching advertisements. Gender manipulation and the use of women as a symbol of attraction and sex to sell online products mostly target male consumers, which is highly unethical and inappropriate (Nooh, 2018).
To oppose the claim that it is necessary to use women as a ‘sex symbol’ for selling more products faster, Cohan (2001) argues that it is possible to use women in online ads without degrading them. Schroder, Wulf and Hofstee (2002) compared gender stereotyping between masculine and feminine countries. It was concluded that masculine countries tend to create advertisements that place females in less of a working role and more as sex objects. However, Malaysia is considered to be a feminine country in Hofstede’s dimensions since it values relationships and selflessness (which are indicators of low masculinity and high femininity) (Isa et al., 2019).
To break away from stereotypes against women, businesses must improve their marketing techniques and the way they communicate their message across to online consumers.
According to Tan, Ling and Theng (2002), advertisement present on social media in the region of Malaysia and Singapore does not depict gender roles realistically as it only represents the class segregation ideology that is present in our society.
According to Pressy and Milton (2013), ethical marketing is strongly recommended so as to not violate company values, the customers or their race, religion, gender and ethnicity with the subject of their advertisements. Doing so would hurt sentiments and transform the ad content into something unethical. Although advertising agencies always set certain rules and regulations to follow, they find ways to bend these rules and get the message across. This usually does not turn out in the favour of the seller and is deemed inappropriate (Singh and Vij, 2017). It is very rare that sellers intentionally engage in the bait-and-switch method, which is an illegal form of false advertising that invites customers by tempting them with a bargain of a product that is either of poor quality or no longer available (Noel, Babor and Robaina, 2018).
Jones (1991) stated that advertisements must not include stereotypes of gender, particularly those using females as symbols of attraction to sell the product or service. Other unethical female stereotypes include a woman’s inability to park a car, being responsible for cooking in a household, etc. The concept of “attractive and glamourising” women, particularly in a product or service advertisement targeting the opposite gender, is a highly unethical practice and is condemned in countries like Bangladesh where such adverts are removed from online
platforms and banned from television by local authorities. Such ads tempt and raise foul intentions toward purchase decisions (Huq, 2016).
It has been noted that throughout generations, sexes in advertisements have been depicted in the most traditional manner. Women were presented in an inferior way with soft and weak characters, entirely dependent upon a manly figure for survival, and thereby lacking all capabilities of being independent (Kilbourne, 1990). In support of all feminists and in favour of women empowerment, the portrayal of women should be altered since it is known that they are excellent multitaskers who maintain a work-life balance. Women are better managers at complex work situations as well (Srivastava and Nandan, 2010). Rusello (2009) found that one of the most common and popular idea spread by advertisements was the ‘beauty and attractiveness of women’. This was accomplished by portraying the ideal woman as beautiful, clear skin, thin and tall. However, these ads not only create false images among consumers, but also increase the pressure on women to live up to these false standards and increase insecurities.
For example, Victoria’s Secret models never used a plus sized woman in their campaigns and/or runway shows.
Sellers and advertisers must ensure that they are creating more fair and ethical content;
patronizing women through adverts may not only hurt their sentiments and make them feel resentful towards a brand or a business, but it has psychological implications as well.
Demeaning their image will lower their self-confidence, making them question themselves (Hentschel, Heilman and Peus, 2019). Unfortunately, advertisers these days are delivering more and more unfair, misleading and exaggerating ads just for the sake of selling their products. This not only hurts the female sentiment, but companies will also lose their credibility and competitiveness in the market (Grau and Zotos, 2016).
2.3 Perceived Risk and Consumer Purchase Power
The customer’s purchasing power is measured by how they spend their money and what they deem to be most value (Akbar, 2011). Consumer buying power is a factor in this case because despite seeing unethical and deceptive advertisements, if they still see value in the product, they will make the purchase solely based on online advertisements (Folarin and Ogundare, 2016). According to Kawa, Rahmadiani and Kumar (2013), customers with higher purchasing power will make quick online purchase decisions since they are able to afford that decision. If they are scammed with a deceptive product, they can easily bear the loss incurred in terms of financial and time value. It will not impact their wealth compared to those consumers with a relatively lower buying power who will go through many stages of thinking and reviewing in order to believe what they see online. Low buying power consumers tend to trust the brick and mortar means of trade over social media and/or e-commerce purchasing channels (Shah, Zahoor and Qureshi, 2019).
This also includes a customer’s intention and willingness to take risks despite the unethical element and deception in advertising claims of the product as well as the possibility of receiving incorrect products. A consumer’s purchasing power is the deciding factor of how consumers are willing to either ignore or accept the perceived risk that comes with purchasing a product through social media. This risk includes the risk of losing finances, privacy risk as well as after sales risk (Ji, Zheng and Chen, 2012). Customers willing to take all sorts of risks and can afford purchasing through social media will have a positive consumer buying behaviour than those who are not willing to take risks and would prefer seeing the product before making purchase decisions (Alam and Siddiqui, 2019).
Perceived risk is an expression of uncertainty faced by a customer as a consequence of their purchase decisions; the higher the expectations from an online purchase, the higher the degree of risk a customer will experience (Ariffin, Moh and Goh, 2018). Perceived risk in online transactions is also defined as a two-dimensional construct that consists of anxious customers making uncertain purchase decisions and later owning up to the consequences of taking an unfavourable action (Schierz, Schike and Wirtz, 2010).
According to Zviran (2008), website operators collect cookies that include customer information. Sometimes, they decide to distribute customer personal data or such data is often leaked and hacked without consent. The possibility of this occurring in the virtual environment makes online shoppers more privacy conscious. Customers are reluctant or tend to avoid online purchases because most are scared of losing their credit card information or experience identity theft. They prefer brick and mortar over online purchases (Ariff et., 2014). Online visuals and attractive advertisements should be more focused on leaving a positive impact on consumer perception to positively affect their buying behaviour instead of solely focused on deception or following unethical practices to scam consumers (Ha, Janda and Muthaly, 2011).
Duncan and Nelson (1985) examined 157 respondents and found that consumers are easily influenced. They tend to increase their purchasing power if online advertisements are visually attractive and entertaining. Ads influences them in a way that they accept the product and are willing to spend because of the recreational impact the advertisement has left on their mind. In a similar study by Chang (2006), it was proven that among 152 participants, entertaining advertisements are directly linked to a positive customer satisfaction which impacts their behavioural intentions toward positive purchases. They are willing to spend more because of the utility and satisfaction they have received based on the advertisement only, regardless of its deceptive or unethical nature. However, it should be noted that entertainment in adverts does not always require humour and humour does not always mean demeaning one segment of the population or creating a superiority complex of one race over another. However, humour is a dangerous method to use in advertisements since it can be risky as not every demographic will be entertained by the same concept (Miller, 2002).
2.4 The Dependent Variable - Consumer Buying Behaviour
Consumer buying behaviour is analysing the purchase intention of customers as well as the factors that influence the decisions made (Kotler, 1994). Unethical and deceptive advertising greatly influences consumer buying behaviour, as explained by the independent variables listed below. Consumer buying behaviour, as the dependent variable, has many factors that alter the outcome, such as: reliability and accuracy of information source regarding products sold online, honesty in product performance and its features and lastly, the attitude of customers towards the use of gender stereotypes in online advertisements. These factors will either positively or negatively affect customer buying behaviour when it comes to purchasing products sold on social media platforms.
Consumer buying behaviour are actions displayed by consumers when searching, purchasing, using, evaluating and disposing of products and services that will satisfy their needs and wants.
It answers what, where, when, why and how individuals make purchases and the factors that facilitate them to execute the purchase (Schiffman and Kanuk, 2007). In the ever-changing dynamic business environment, consumers are constantly looking for something new and fancy to grab their attention. According to Madden and Weinberger (1982), boring advertisements will not retain existing customers or bring new ones.
Complex buying behaviour is exhibited when consumers are about to make expensive purchases. It requires high consumer involvement and thought processes since these goods are often once in a lifetime purchase and considered high risk. Dissonance-reducing buying behaviour is similar as it requires high involvement from customers but with fewer availability of goods. This makes the choice tougher since dissonance-reducing buying behaviour often leaves customer with fewer choices and prompt forced buying practices (Alfred, 2013).
Habitual buying behaviour is relatively self-explanatory and is depicted when a consumer has low involvement and there is an ease of product substitution present. Not much thought is put into this type of purchase, therefore it becomes easier for sellers to convince customers who have this mindset (Castro et al., 2018). Variety seeking buying behaviour is displayed when there is low customer involvement, however, there is a significant difference when it comes to the sellers and the way they advertise to consumers. It should be noted that consumer buying decisions are based on their buying behaviour, therefore sellers and advertisers should market their products while considering different consumer perceptions and understanding their reactions (Ryans, 1996).
From the literature review, as seen in the previous segment, the research questions and study objectives are as follows:
Research Questions
• Does the reliability and truthfulness of the information provided in social media advertisements affect consumer buying behaviour?
• Does female stereotyping and the promotion of unethical behaviour in social media advertisements affect consumer buying behaviour?
• Does customer purchasing power and intention to take risk despite unethical advertisements on social media affect customer buying behaviour?
Research Objectives
• To determine if reliability and truthfulness of information provided in social media advertisements impact consumer buying behaviour
• To determine whether female stereotyping and the promotion of unethical content in social media advertisements impact consumer buying behaviour
• To determine whether customers purchasing power and intent to take risks to purchase through social media advertisements impact consumer buying behaviour.
Based on the literature review, the following hypotheses were created:
• H1: Reliability and truthfulness in sources of information regarding a product has a positive relationship with consumer buying behaviour.
• H2: A higher perceived risk and low purchasing power have a negative relationship with consumer buying behaviour.
• H3: Female stereotyping in online adverts have a negative relationship with consumer buying behaviour.
2.5 Conceptual Framework
Figure 1: The Framework
3. Methodology
A very important part of this research is to explain the research approach; it is the blueprint to make the reader understand the data collection process, data measurement and data analysis.
In this study, the primary data has been collected through quantitative methods.
3.1 Research Design
Multiple arguments are present as to why quantitative research is chosen over qualitative.
Quantitative research, according to Nielsen (2011), is used to quantify behaviours, opinions, attitudes and other variables from a population. This type of research involves the use of statistical mathematical tools, such as SPSS, to analyse the collected data and understand the results. The method of research in this paper in terms of primary data collection is therefore quantitative where Google Forms was used to create a survey which was later sent to the chosen sample population. The secondary data for this research was derived from online journals, online magazines, e-books as well as research conducted and published by universities, such as The Harvard Business Review. All secondary data were carefully screened and selected to ensure accuracy. The secondary information obtained is a mixture of both old findings as well as up-to-date conducted research.
The respondents included the Malaysian population aged between 18-44 since they form a large portion of the target population that actively uses social media. They are also aware of e- commerce platforms and their functions. This segment of the Malaysian population regularly engages in social media activities and online purchases using these platforms. They have the highest experience. Google Forms and surveys were used to reach the target respondents. The survey questions were based on independent variables to further understand the occurrence of these variables in advertising and how they affect the chosen respondents. The link to the survey was forwarded to the chosen age range and they were asked to spread the word to others to obtain as many respondents as possible within that selected age group.
3.2 Sample Respondents
The sample respondents for this study include: i) only the Malaysian population and ii) population aged between 18-44 years old. The reason the survey results were only obtained from the Malaysia population was due to personal preference.
Through research, customers leave negative reviews on social media and e-commerce platforms after purchasing products that fall under false advertising. This research attempts to determine the consumer perception regarding ads over social media and the factors that lead them to make the purchase decision. Despite the existence of unethical and questionable methods in advertising, Malaysian consumers still purchase these products. The questionnaire will provide greater insight concerning the Malaysian population from the selected age group.
For better and quicker analysis, the sample size was restricted to Malaysian consumers only.
The population age was chosen to be between 18-44 years of age because as stated before, according to the Malaysian e-commerce statistics, most consumers with internet access who understand online purchases fall under this age category.
3.3 Sampling Technique
Convenience sampling technique was used for this research to select respondents. Convenience sampling is a type of non-probability sampling where the population is sampled simply because they are ‘convenient’ sources of data for research. A particular criterion is not present for this type of sampling since people who are available and willing to participate can take part (Etikan, 2016).
Due to the time restriction of conducting research within the span of a semester, this type of sampling is the most suitable. According to Jager, Putnick and Bornstein (2017), there are multiple advantages and arguments in support of this type of sampling method. It allows flexibility in research in terms of availability and time. Data is readily available and efficient since it is less time consuming to collect at the expense of the researcher. Travelling distances or segregating the population to collect information were not required.
It is also cost effective since forms do not require printing and all sorts of data collection and distribution can be accomplished through digital means. There are fewer rules to follow in this sampling method as it entirely depends on the availability and consent of the sampled population.
3.4 Instrument Design
The questionnaire was divided into four short sections that split into questions and ratings based on the independent variables and the dependent variable of this study. However, before the respondents reach the variable-related sections, they are required to fill in basic information such as gender, age group and occupation. This is to acquire a better understanding of the background of respondents. The question types included both open-ended questions (allowing respondents to express their perspective and opinions) as well as closed-ended questions with multiple choice and agree-disagree questions portraying hypothetical scenarios.
The concluding section of the questionnaire consists of an open comment section that allows the consumer to anonymously reveal, if they choose to, their own personal experiences (if any) regarding false and unethical advertising. If present, respondents can share their reaction. The results were anonymously published in the later sections of this research.
Table 1: Independent and Dependant Variables
Variables Sources of Question
Consumer Buying Behaviour (DV) (Schiffman and Kanuk, 2007) Reliability and Truthfulness (IV) Soh, Reid and King (2009) Female Stereotyping and Unethical Content (IV) Jones (1991), Huq (2016)
Intention to Purchase and Perceived Risk (IV) (Schierz, Schike and Wirtz, 2010) Legends:
IV: Independent Variable DV: Dependent Variable
4. Data Analysis and Results
This section includes four types of testing methods to interpret the data: i) Descriptive statistics, ii) Reliability test, iii) Pearson’s correlation and iv) Multiple regression.
4.1 Scale and Software
To measure the research variables, a 5-point Likert scale was used. The values ranged from 1 to 5 (1-Strongly disagree to 5-Strongly agree). The software used for analysis is the SPSS Statistics 25 by IBM, where data was entered for all mentioned tests to produce statistical results.
4.2 Descriptive Statistics Test
The descriptive statistics analysis is used to summarise unstructured data in an organised manner by describing the mean and frequency of the sampled population (Larson, 2006).
According to the results achieved by the SPSS outputs, the following are the details regarding the sampled demographics from this survey. Below is a summary of the statistics as well as a detailed analysis.
Table 2: Demographic data on Age, Employment status and Frequency of Purchase Statistics Summarised
Employment Status Age Frequency of Purchase
N Valid 103 103 103
Missing 0 0 0
Mean .7767 1.7767 1.5631
Std. Deviation .46298 1.13701 .74977
From a total of 103 received responses, 5.8% were under the age of 18, and 49.5% were between the age range of 18 to 29. 16.5% of respondents fall between 30 to 39 years of age, while 17.5% are in the age range of 40-49%. The remaining 10.7% are the age of 50 and above.
Table 3: Demographic data on age Age
Frequency Percent Cumulative Percent
Under 18 6 5.8 5.8
18-29 51 49.5 55.3
Valid 30-39 17 16.5 71.8
40-49 18 17.5 89.3
50+ 11 10.7 100.0
Total 103 100.0 100.0
The employment status results are as follows in Table 4. 24.3% of respondents are students, whereas 73.8% are employed individuals. Only 1.9% are unemployed.
Table 4: Employment Status Employment Status
Frequency Percent Cumulative Percent Valid
Student 25 24.3 24.3
Employed 76 73.8 98.1
Unemployed 2 1.9 100.0
Total 103 100.0
Lastly, the frequency of online purchases was also examined. 5.8% from the total of 103 respondents claimed to make purchases every day, 41.7% make purchases once a week, 42.7%
purchase once a month and the remaining 9.7% do not use online platforms to make purchases.
Table 5: Purchase Frequency Frequency of Purchase
Frequency Percent Cumulative Percent
Valid
Every day 6 5.8 5.8
Once a week 43 41.7 47.6
Once a month 44 42.7 90.3
Never 10 9.7 100.0
Total 103 100.0
4.3 Reliability Test
The reliability test, or Cronbach’s alpha, is the measure of reliability in the presence of multiple Likert scale questions. This is applied to determine whether or not the used scale is reliable (Taber, 2017). All displayed reliability tests link the independent variables to the dependent variable.
The reliability tests between consumer buying behaviour and the reliability of advertisement have a relative value of 0.871, female stereotyping in advertisements at a reliability of 0.720, and intention to make a purchase affecting consumer buying behaviour, the reliability scale acquired the value of 0.713, indicating an acceptable scale.
Table 6: Reliability Tests
Variable Cronbach Alpha N
Reliability of Advertisement 0.871 5
Female Stereotyping 0.720 5
Intent to Purchase and Perceived Risk 0.713 5
4.4 Pearson’s Correlation Test
The Pearson’s correlation test results produce a correlation coefficient (r) that measures the strength of the relationship between a pair of variables (Schober, Boer and Schwarte, 2018).
The following table interprets the link between the dependant variable (consumer buying behaviour) and the independent variables.
Table 7: Pearson Correlation Correlations
Reliability Female Stereotyping
Intent to Purchase and Perceived Risk
Consumer Buying Behaviour
Reliability
Pearson
Correlation 1 .345 .290 .241*
Sig. (2-tailed) .000 .003 .015
N 103 103 103 103
Female Stereotyping
Pearson
Correlation .345 1 .261 .125
Sig. (2-tailed) .000 .008 .210
N 103 103 103 103
Intent to Purchase and Perceived Risk
Pearson
Correlation .290 .261 1 .631
Sig. (2-tailed) .003 .008 .000
N 103 103 103 103
Consumer Buying Behaviour
(DV)
Pearson
Correlation .241* .125 .631 1
Sig. (2-tailed) .015 .210 .000
N 103 103 103 103
*Correlation is significant at the 0.05 level (2-tailed)
The correlation between consumer buying behaviour versus reliability in advertisement as well as female stereotyping in advertisements is at 24.1% and 12.5%, respectively. These results show small or low correlation between the independent variables with the dependent variable.
The correlation between consumer buying behaviour and intent to purchase and perceived risk is remotely stronger, at 63.1%, in comparison to other variables. Therefore, it can be concluded that consumer buying behaviour has the highest correlation with intention to purchase and perceived risk, signifying a better relationship with consumer buying behaviour.
4.5 Regression Test
The r-squared value is a regression test component that represents the percentage of variance in the dependent variable, which is collectively explained by the independent variables. For this study, the r-squared value is 0.251, whereas the R value is 0.523.
Table 8: Regression Test Model summary
Model R R square Adjusted r square Std. Error of the
estimate
1 .523a .273 .251 2.52589
A. Predictors: (constant), intent_to_purchase_and_risk, female_stereotype, reliability
To further assess the collected data, the ANOVA results for the variables are presented as follows:
Table 9: ANOVA Results ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 234.828 3 78.276 12.269 .000b
Residual 625.251 98 6.380
Total 860.078 101
a. Dependent Variable: consumer_buying_behaviour
b. Predictors: (Constant), intent_to_purchase_and_risk, female_stereotype, reliability
5. Future Recommendations and Conclusion
A total of 103 respondents were surveyed for this model. This research concluded that two out of three tested variables that assess consumer buying behaviour have been proven to be statistically significant based on the results.
5.1 The Outcomes
The p-values obtained during the statistical analysis indicate that two out of three independent variables are regarded as statistically significant. Based on the results, the first hypothesis being that the reliability of content in advertising has a positive effect on consumer buying behaviour is considered statistically significant. It was accepted since it shows a 24.1% correlation with the dependent variable, consumer buying behaviour. Hence, this hypothesis is accepted since the reliability and truthfulness in advertising do have a positive relationship with consumer buying behaviour. The more reliable and truthful the content of online advertising is, the more positive the impact upon consumer buying behaviour and purchase decisions will be.
The second hypothesis was also found to be statistically significant. This variable also exhibited the highest correlation with consumer buying behaviour (at 63.1%), therefore, the hypothesis can be accepted. If a risk to purchase is detected by the consumer via online advertisements, it will discourage purchase due to the risks involved. The intention to purchase will diminish.
The third and final hypothesis, being that female stereotyping has a negative relationship with consumer buying behaviour, was found to be statistically significant at a weaker correlation result, since it has the lowest correlation with consumer buying behaviour (12.5%). This hypothesis was also considered to be statistically quite weak and the results may imply that the presence and/or absence of female stereotyping content in advertising has little to no impact on consumer buying behaviour when it comes to making purchases online via social media platforms.
5.2 Research Limitation
The biggest limitation of this research was the time restraint. If more time was available, the survey could have reached more respondents throughout Malaysia, resulting in better analysis and an average statistical output. In addition, more variables could have been added and tested to determine the influence on consumer buying behaviour. This would have resulted in more accurate results to judge the factors that may affect consumer purchasing behaviour.
5.3 Recommendations for Future Research
Future research should include gender in the demographics data to understand the differences in the frequency of purchases made online according to genders. It was statistically proven that there are striking differences between genders when it comes to spending habits; men typically spend 15% more than women using credit cards, whereas women spend 85% through online compulsive purchases, making them more prone and gullible to advertising (Andriani and Nugraha, 2018). Online, women spend more on categories such as healthcare, retail, clothing, makeup and wellbeing, whereas men tend to spend their money on meals out, clothing and motor vehicles. Using genders for future research can narrow down categories. Additionally, future research can develop a more appropriate scale to measure the variables that scored low on the reliability test, thereby acquiring better and more accurate results.
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