People opt to shop online because of the benefits such as comfort, accessibility to multiple products and the choice of purchasing desired products by the click of a button. Buyers can discover an item rendered by multiple sellers at competitive prices and choose the economically viable options, without having to travel to physical stores (Hung 2012). According to recent survey reports by PwC 25% of people from Ireland stated that they indulge in online shopping at least weekly. The trend predicts that the e-commerce industry is expected to show an exponential growth rate of an estimated 14.1 billion Euros in four years (PricewaterhouseCoopers). Ecommerce Europe data reveal that online shoppers in Ireland are 1.9 million, 31% actively search online for product information and 10 % are involved in making a weekly purchase online using their mobile devices. About 28% look for product information using their desktop and 10 % make online purchases on a weekly. 24 % of individuals accessed product reviews on websites or blogs every time before making an online purchase and 21% of individuals accessed websites or applications for product comparison prior to making an online purchase (Europe 2017).
Customers making online purchases do not get to touch or test the products like they do in a conventional retail store. Hence their buying decisions are made based on the data available on the e-commerce site. Vendors try to overcome this shortcoming by giving the customers the chance to share their experiences and assessments of the products they purchase in the form of reviews and ratings (Do-Hyung Park, Jumin Lee and Ingoo Han 2007). The number of individuals who access these online reviews and ratings before making a purchase have increased in recent times and for some, the need to access such information prior to every purchase have become mandatory part of their online purchase experience. This is where the use of product reviews has become more valuable than product ratings to an online customer. Because mere ratings do not provide information about the consumers experience of a product, the review statements are crucial in deciphering the opinions about a product.
It is an accepted notion that online reviews demonstrate the likelihood of a successful transaction and serves as a manual to the preferences to the choices of the consumer (Fagerstrøm, Ghinea and Sydnes 2016). The motivation behind the proposed research study is to examine if negative product review deters customers from purchasing a specific product.
- This study attempts to identify the influence of a review over customer intentions towards purchase.
- To examine the significance of product reviews in altering customer relationships with brands. Whether reviews cause a shift in customer’s orientation towards brand.
- To identify the dependency of customers on product reviews. Whether customers seek reviews and ratings for every product they wish to purchase online.
The research attempts to answer the following
- Do negative reviews alter the consumer’s loyalty towards a brand?
- Do consumers buying decisions rely solely on product ratings and reviews?
- How Influential are textual content compared to product ratings?
Today’s business world is shifting towards a more innovative way of doing things and demand of online goods and services are increasing day by day. The reach and degree of access of online product reviews has been expanding. Nowadays retail sites such as Amazon allow users to write product reviews on their websites. These reviews are easily accessed by the customers, and they are constantly updated by the retail site. Based on a study conducted by Nan, Paul and Zhang (2017) considering that these reviews are anonymous, and they are open to bias, as not all reviews are written based on the consumers experience with a product, it is difficult to gauge the quality of a product based on them (Nan, Paul and Zhang 2017) .
Previous research has been focused on the conversion rates on the retail sites with respect to sales. Through this study the researcher aims to analyze impact of negative reviews on consumer purchase behaviour. For this study the researcher will focus on conducting this study in Ireland.
Product reviews play a key role in consumer decision making process. Internet is a major source of information and often consumers contemplating a purchase, tend to seek access to data regarding the desired products and its features. The magnitude of online reviews has the potential to influence the purchase behaviour of the consumers given that the internet is a medium with little geographical limitations.
Online reviews consist of complicated data structure which is made even more complicated by the customer’s capacity to distort the data. These review structures allow the customers to check and keep tabs on the review history of any individual reviewer and assess them on the basis how they interpret and make assessments on any given product review or a reviewer (Hoffman 2004).
Amazon first started allowing customers to write product reviews in 1995 and the number of online reviews in ecommerce sites have increased exponentially over the years, so as customers dependency on these reviews. The quality and quantity of the content are mitigating factors that affects buyer’s decision, since customers assume that the reviews are written by consumers based on their experiences with a product, it is not uncommon to associate the number of reviews with product popularity. Do-Hyung Park, Jumin Lee and Ingoo Han examined if the quality and quantity of customer reviews influenced buyer’s decision. Their findings reveal correlation between the number of reviews and the customers buying decisions and the impact of quality and quantity of reviews on low involvement and high involvement customers. There is no prescribed format with which customers post online reviews. When accessing quality of reviews, it is helpful to focus on the content, researchers have relied on attributes such as clarity, relevance and fairness to adjudicate the quality. A review is of high quality if it is rationally constructed and grounded on facts pertaining to a product. The researchers found that rational reviews, which provided the customers with enough information about a specific product had a positive impact on customers buying intention. Buying intention increased with the increase in the number of reviews (Do-Hyung Park, Jumin Lee and Ingoo Han 2007). The study focused on positive customer reviews and failed to analyze the impact of negative reviews on purchase intent. It did not take into account the possibility of customers with little knowledge of a product influenced by the quantity versus customers with adequate knowledge influenced by the quality of online reviews (Do-Hyung Park, Jumin Lee and Ingoo Han 2007).
Customers prefer the best information resource available at their disposal this is crucial in terms of decision making. The reliability factor on consumer reviews is much greater than expert reviews because these reviews are based on their experience with the product. Hence negative reviews garner more attention than the positive reviews (Xia and Bechwati 2008). Purchase intent characterizes the customers desire to make a product purchase at a given point in time. The purchase intent is important although it does not necessarily reflect in behaviour. Intent does not signify the actual act of buying however there is a strong correlation between both (Neo 2010).
Online suggestions and reviews have become valuable source of data for consumers. In the online medium, it is challenging for the consumer to assess the products and its value. Consumers are inclined to depend on other consumer’s review’s, recommendations or ratings about a product. They depend on the judgement of other consumers and their experience using the products. This differential method of providing reviews and ratings through online blogs, forums and communities is called as Electronic word of mouth (Hyrynsalmi et al. 2015). The digital era has provided numerous platforms for eWOM such as review sites, social media and user groups, customers make use of these channels to express their views. When evaluating the impact of reviews on the customers decision making process studies indicate that customers tend to rely more on user generated eWOM rather than an expert’s opinion. This is because user generated reviews are believed to be more reliable and persuasive. The general assumption here is that the reviews are written based on an individual’s experience with a product. eWOM also plays a crucial role in market reach and brand awareness and can impact the profitability of an organization. It is said that early adopters have the potential to influence online ratings and reviews and this may affect the online behaviour of future customers. A clear demarcation has been made between quality and quantity as a result of previous research studies. Customers rely more on the quality of content rather than the volume of the content (Do-Hyung Park, Jumin Lee and Ingoo Han 2007).
Studies show a relationship between sales increase and the manner of display of eWOM on shopping sites. Ease of access or visibility of eWOM on a website is influential in driving the sales figures. The effectiveness of eWOM lies on the type of products that are available for purchase online i.e. the impact of eWOM are higher for physical products than a service. The efficacy of eWOM are influenced by factors such as the medium, product attributes and time. A newly launched product has potential for higher sales, when eWOM occur on an ecommerce or review site than a social networking channel. A significant finding in this study is that negative eWOM does not reflect a sales decrease, positive eWOM however has a definite impact on sales increase. The researchers contend that this maybe because customers believe that negative eWOM may be generated by a competitor. This study does not take into account factors such as involvement, previous knowledge and the decision-making process of the customers (Rosario et al. 2016)
There are three Metrix for online word of mouth which are identified in this area:
Valence is represented most frequently by an average rating measure. It has also been represented by some measure of positivity in ratings. The variance in ratings has also been measured in a variety of ways. The volume is represented most commonly by the number of postings. The application of these three Metrix can be done in product performance and related areas as well many research study suggests that variance and volume of online word of mouth has significant effects in consumers purchase behavior (Hoffman 2004).
A study on the modulating role of social influence theory, Lee, Shi, Cheung, Lim and Sia, (2011) found that a positive social impact can reinforce the connection between the customer mentality towards online shopping and the desire to shop. Studies have been undertaken to determine how various sources of data such as reviews on products, reviews by customers, reviews by vendors and reviews on third party website affect the customers purchase behaviour(Hoffman 2004).
Many studies in past have found that posted online ratings exhibit systemic patterns over time. Valence rating trend to shows a downward trend this is due to the process of product life cycle. Consumer who buys at an early stage of product life cycle tend to have significant taste and preferences. However, the taste of preferences of initial customer changes in comparison to later customer. This will show a downward trend due to decreasing ability of the future demand (Hoffman 2004).
Studies have shown that positive reviews help drive sales and the results are dependent on the volume and valence of the reviews and ratings. These ratings are motivating factors behind the customers decision to make a purchase (Hyrynsalmi et al. 2015).
Customer search methods can be divided into two types
- Goal directed search Behavior
- Exploratory search Behavior
The quality of Goal directed search places emphasis on a customer having a requirement for buying. Meanwhile Exploratory search is not planned and is predominantly based on an impulse. Unique qualities of Goal directed search category of customers consider shopping as an undertaking that is duty oriented and their behavior is conditioned towards a goal of swift purchase which is systematic and intended. Whereas Exploratory search category of customers preoccupy themselves with exploratory and directionless browsing without any intention of buying (HoEun Chung and JungKun Park 2009).
It is described as the way the customers or the target audience make sense of the reviews and make assessments about the products that are reviewed about. Cognitive Personalization in Online Customer Reviews originates from the targeted customer and is triggered by external forces. Customers identify customized offers as in alignment with their needs, this has a cumulative effect on their buying decisions.When the consumer read such reviews, they tend to evaluate the data in a personalized way, they tend to view the text as reliable, genuine and authentic. Hence cognitive personalization tend to affect the consumers purchase attitude towards the product positively (Xia and Bechwati 2008).
i. Elaboration Likelihood Model (ELM)
Elaboration Likelihood Model is used to gain insight into the manner in which people are influenced by information. ELM identifies two types of persuasion Central and Peripheral. According to Sussman and Siegal customers tend to deviate towards indirect or peripheral process when their involvement in online reviews are low. This occurs when they concentrate on factors like ratings and popularity which are not textual in nature. On the contrary customers who have high involvement in online reviews will focus on the textual content through central processing. The influence of eWOM lies on the reliability and quality of the source (Mishra and S.M).
- Cognitive Fit Theory
This theory describes how several types of data representation impacts the process of decision making and its outcome. Cognitive fit occurs when there is a consistency between the style of content and the function they represent. If there is an inconsistency or if the information format is complex, then this would considerably impact the decision-making process and the outcome. Because the process of decoding the information load will depend on the individual’s cognitive capability. This theory helps to understand the correlation between the types of content on the ecommerce sites and the behavioral outcome of the customers (Hong, Thong and Tam 2005).
- Expectation Confirmation Theory
This theory outlines two factors for customer satisfaction, Creation of expectations and whether their expectations are satisfied. Prior to purchase the customers would have expectations about the quality of a particular product. The customer would assess the product quality and usability features post purchase. Customer satisfaction or dissatisfaction is derived from a comparison of pre-purchase expectations and post purchase experience of a product. This theory is the foundation by which positive or negative reviews, ratings are generated by customers on ecommerce sites (Cho and Rao 2015).
- Choice confidence in the webrooming purchase process: The impact of online positive reviews and the motivation to touch by Carlos Flavian, Raquel Gurrea, Carlos Orus (2016).
- Balance and Sequence in online reviews: The wrap effect by Nathalia Purnawirwan, Nathalie Dens, Patrick De Pelsmacker (2012)
- Anxious or Angry? Effects of discreet emotions on the perceived helpfulness of online reviews by Yin Dezhi, Samuel D. Bond, Zhang Han (2014)
- A Meta-Analytic Investigation of the role of Valence in Online Reviews by Purnawirawan, Nathalia; Eisend, Martin; De Pelsmacker, Patrick; Dens, Nathalie. Journal of Interactive Marketing (Mergent, Inc.). Aug2015, Vol. 31, p17-27
- Customer Engagement and online reviews by Thakur, Rakhi. Journal of Retailing & Consumer Services. Mar2018, Vol. 41, p48-59.
- Following the breadcrumbs: An analysis of online product review characteristics by online shoppers by Muralidharan, Sidharth; Yoon, Hye Jin; Sung, Yongjun; Miller, Jessica; Lee, Arturo. Journal of Marketing Communications. Apr2017, Vol. 23 Issue 2, p113-134. 22p.
- How negative online information affects consumers brand evaluation: The moderating effects of brand attachment and source credibility by Chiou, Jyh-Shen; Hsu, Arlene Chi-Fen; Hsieh, Chia-Hung. Online Information Review. 2013, Vol. 37 Issue 6, p910-926. 17p.
- Intention to use the Yelp Review Rebsite and Purchase Behaviour after Reading Reviews by Fogel, Joshua; Zachariah, Samson. Journal of Theoretical & Applied Electronic Commerce Research. Jan2017, Vol. 12 Issue 1, p53-67.
- Predicting the effects of eWOM and online brand messaging: Source, Trust bandwagon effect and innovation adoption factors by Wu, Tai-Yee; Lin, Carolyn A. Telematics & Informatics. May2017, Vol. 34 Issue 2, p470-480.
Product reviews are prevalent online and there are dedicated websites that encourage users to post reviews about products or services they have used. Retail websites nowadays also allow the customers to write reviews and post rating for their products. Retail websites such as Amazon require a user account to be able to post reviews, they only need to establish that they have made purchases through the site before, but not necessarily the product they have posted a review for. These reviews are predominantly accessed by the customers to make purchase decision (Tourism 2012). The primary objective of this research is to identify the correlation between the customers buying behaviour and online reviews. The need is to access the influence of negative reviews and ratings on the customer decisions towards purchase. An empirical study needs to be undertaken for this research which is reflective of positivism. The positivist approach relies on facts or realism. The researcher believes in rationales and the ability to justify them through quantifiable means, the interrelationship of factors such as cause and effect. The researcher views reality as objective and aims to find a relationship between the variables through measurable means. Therefore, Quantitative approach is the preferred choice for this research because the researcher seeks to identify the cause – effect relationship by using objectivity and the researcher has no direct involvement in the research outcome through their presence (Arghode 2012).
Research strategy is a sequence of plans the researcher undertakes to conduct the research study, the process by which the researcher intends to answer the research questions. It offers a set of techniques, tools, principles and plan that helps in deriving a solution from a general hypothesis or an existing theory (Şimandan 2010). The research strategy for this particular study entails a deductive approach by making the use of survey which enables the researcher to make use of a large demographic. The nature of the data is primary, and the analysis of the data is through descriptive method. The Descriptive survey research is generally used to test the occurrence of a phenomenon and its prevalence amongst a population. It uses a pre-existing theory to measure the reactions or outcomes of a population (Cipriano). The study is focused on products such as electronic device. The surveys would include closed ended questions and the target demographic would include people aged between 20-40. The goal is to identify the different variables and construct explanations to define the conditions that alter the purchase behaviour in a logical structure.
This research will employ quantitative techniques, the method of collecting data is Primary with the use of Survey which would be emailed to the respondents. Here the respondents are people making online purchases through online retail sites. This method will entail collecting data from large samples, to establish a cause and association with respect to the customer reviews and its effect on the consumers purchase behaviour through an analytical approach. Quantitative technique helps to identify behaviour and trends. The primary aim of applying quantitative method is to determine the what and how of a given situation. The data obtained through this method are structured and numerical, this helps to develop precise and valid measurements for analysis (Goertzen 2017).
The researcher will send a mail to the respondents with the link to the web-based survey. Online survey helps to reach a wide target demographic. Online surveys are advantageous in reaching out participants who are otherwise difficult to access. The challenge with online surveys is that the respondents may take time to fill up the survey which may result in delay. Hence the researcher intends to send follow up reminders to increase the response rate. Additionally, the researcher would also approach people at places such as colleges and hand out questionnaires to be filled. The questions would be framed in a sequential and logical manner to get an effective output without confusing the respondents (Minnaar and Heystek 2013).
The nature of data collected would be primary through the use of survey. The questions will have a logical and sequential format so that it does not cause confusion for the respondents. The researcher would collect surveys from 350 respondents for this study.
- Do you read reviews every time you make a purchase online?
- How many reviews do you read before you purchase an electronic device online?
- What is the minimal number of star ratings must a product have for you to consider buying?
- Do you read online reviews to find out if the quality of the product is good or bad?
- Has a negative review ever deterred you from buying a product in the last 6 months?
When researchers do not apply conditions, ethical issues happen to exist while conducting nonexperimental researches. It is important for the researchers to be aware of the basic principles of nonexperimental studies not because there is less complex or harmfulness in nonexperimental design ethics but also to protect the participants, design’s full disclosure and consent. During a survey research, it is important for the investigator to inform the participants provide details of the survey such as purpose of study, confidentiality of responses, what type of participants are suitable for the study i.e. participant demographics, what will be the impact of the study and who will able to access the collected information (Search Results: SAGE Journals). In 2005, Researchers Bacon and Olsen mention few ethical responsibilities of survey researches that is to utilize the participants time effectively not to waste the time of participant if the collected data is of no use.
The analyses of results are done by using a Descriptive method via one dimensional analysis with the help of graphs and tablature. This method would help in identifying the factors impacting the purchase decisions. The scale of measurements used are as described below. Nominal, Ordinal
|Scale of Measurement|
|Nominal||Arbitrary value is assigned for each category||E.g. Male = 0
Female = 1
|Ordinal||Logical order of data||Small, Medium, Large|
(Analyze Quantitative Data « Pell Institute)
To gain a better understanding of the relation between online reviews and the customer’s purchase behaviour. This study will also help in identifying the extent to which the user generated reviews are accessed and used. This will help establish the reliability factor considering the anonymous nature of the reviews. This study aids in understanding interaction of customers in ecommerce sites and will help in analyzing their choices with respect to specific products and brands. Further, the researcher aims to undertake this study with the objective of acquiring knowledge in the chosen area of research.
Refining the introduction and objective section would take approximately 6 days. The literature review would take around 10 days for completion because of the amount of research that has been done previously and time is required to choose and add pertinent information. Methodology and research design section would take approximately 4 and 5 days respectively. Data collection would require 4 ½ weeks for the preparation, distribution and collection of the survey. The next progression would be the data analysis and interpretation stage which would require 3 weeks due to the complexity involved in assessing the empirical data. The final discussion phase would entail 4 days and the write up would take approximately 3 weeks for completion.
|Refining the research objectives|
|Additional research & refinement|
|Refining the methodology section|
|Checking & editing|
|Preparation of Survey questions|
|Mailing respondents about study|
|Analysing the survey|
|Measuring the data|
|Graphs and Table|
|Identifying the findings|
|Review of the data collected|
|Final Write up|
|Prepare the conclusion|
|review the final report|
|Check and editing the final report|
Table 1. Gantt Chart
Analyze Quantitative Data « Pell Institute.
Arghode, V. 2012. Qualitative and Quantitative Research: Paradigmatic Differences. Global Education Journal, 2012(4), pp.155–163.
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Cipriano, F. Survey Research in Operations Management: A process-based perspective., (2002).
Do-Hyung Park, Jumin Lee and Ingoo Han 2007. The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement. International Journal of Electronic Commerce, 11(4), pp.125–148.
Europe, E. 2017. Ireland B2C Ecommerce Country Report 2017. Ecommerce Foundation.
Fagerstrøm, A., Ghinea, G. and Sydnes, L. 2016. Understanding the Impact of Online Reviews on Customer Choice: A Probability Discounting Approach. Psychology & Marketing, 33(2), pp.125–134.
Goertzen, M. 2017. Introduction to Quantitative Research and Data.
HoEun Chung and JungKun Park 2009. A Role of Referring Website on Online Shopping Behavior. Advances in Consumer Research, 36, pp.850–851.
Hoffman, D.L. 2004. The Impact on Preferences of Consumer Access to Information In Online Shopping Environments. Advances in Consumer Research, 31(1), pp.530–534.
Hong, W., Thong, J.Y.L. and Tam, K. 2005. The Effects of Information Format and Shopping Task on Consumers’ Online Sh…
Hung, L.-P. 2012. Discovering patterns of online purchasing behaviour and a new-product-launch strategy. Expert Systems, 29(4), pp.411–425.
Hyrynsalmi, S., Seppänen, M., Aarikka-Stenroos, L., Suominen, A., Järveläinen, J. and Harkke, V. 2015. Busting Myths of Electronic Word of Mouth: The Relationship between Customer Ratings and the Sales of Mobile Applications. Journal of Theoretical & Applied Electronic Commerce Research, 10(2), pp.1–18.
Minnaar, L. and Heystek, J. 2013. Online surveys as data collection instruments in education research: A feasible option? South African Journal of Higher Education, 27(1), pp.162–183.
Mishra, A. and S.M, S. EWOM: Extant Research Review and Future Research Avenues.
Nan, H., Paul, P.A. and Zhang, J. 2017. On Self-Selection Biases in Online Product Reviews.
Neo, R. 2010. Examining the Impact of Multiple Negative Online Consumer Reviews and Review Helpfulness Ratings on Persuasion. Conference Papers — International Communication Association, p.1.
PricewaterhouseCoopers 2017 Irish Total Retail survey. PwC. Available from: https://www.pwc.ie/survey/2017-pwc-total-retail-survey.html [Accessed October 24, 2017].
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Şimandan, M. 2010. Methodology and Method in Scientific Research. Journal Plus Education / Educatia Plus, 6(2), pp.73–80.
Tourism, M.E. 2012. How online customer reviews work. Available from: https://www.business.qld.gov.au/running-business/consumer-laws/customer-service/managing-customer-reviews/how-work [Accessed November 17, 2017].
Xia, L. and Bechwati, N.N. 2008. Word of Mouse: The Role of Cognitive Personalization in Online Consumer Reviews. Journal of Interactive Advertising, 9(1), pp.108–128.
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