Question

CASE_2

COMPARING UK AND MALAYSIAN ONLINE SHOPPING BEHAVIOUR

How did I end up here? Daniel mused as he sat staring at his computer screen. Six months earlier, as he left family and friends in Malaysia to complete his master’s degree on an exchange in UK, the future seem bright. Hundreds of kilometers away from home, with a deadline looming that could make or break his future career, he did not know where to start. He had left university with a bachelor’s degree in Marketing from Northern University four years before and since that time had been on a graduate recruitment scheme with one of the largest supermarket chains in Malaysia. His performance in the early stages of a part time master’s programme in Retail Management sponsored by his employer had been good.

This, combined with his high standard of English, meant he had been offered the opportunity to travel to the UK to study for one year on a full-time basis and obtain a double qualification from both his Malaysian and a British institution. The taught classes in the first semester had complemented his previous studies and he had soon identified the area he wanted to investigate for his research project – online supermarket shopping. He decided the aim of his project would be to compare and contrast UK and Malaysian consumer’s behavior of supermarket’s online shopping offerings.

From his observation, almost every student he knew had bought something on eBay, Lelong.com, or Amazon, and many chose to do their supermarket shopping online to avoid wasting time standing in checkout queues. In addition, many supermarkets had diversified their offer away from daily consumables into white goods such as washing machines and even financial services (Colgate & Alexander, 2001); meaning consumers were now looking to these organisations for more than just the weekly household shopping. In other words, shopping convenience and variety of product offerings can give strong attitude towards online shopping.

In class, Daniel’s supervisor had identified the effect of perceived usefulness and perceived ease of use on the attitude towards online shopping (Juniwati, 2014; Suwunniponth, 2014; Ramayah & Ignatius, 2005; Yu et al., 2005). He also emphasized the issue of consumer concerns around security and trust (Beldad et al., 2010; Koufari & Hampton-Sosa, 2004) that can influence the attitude of online shopper.

It has been reported that the intention to purchase online strongly link to the positive attitude on online shopping. When consumers have the intention to purchase online the tendency of making the purchase online is high (Li & Zhang, 2002; Wu, 2003; Yang, Lester, & James, 2007). In this study, Daniel also wants to find out whether consumer characteristics have significant impact on the relationship between attitude and intention to purchase online.

It had been a revelation to see how well developed the retail websites were in the UK, compared with those in Malaysia, and how different the webscape was in the two countries. Statistics he had found showed that in June 2010 there were 51.4 million Internet users in the UK, 82.5% of the population, an increase of 234% between 2000 and 2010. In Malaysia, the figures were 17.7 million users, 60.7% of the population, an increase of 356.8% between 2000 and 2012 (Internet Usage Stats and Marketing Report, 2015).

Daniel decided he needed to identify his population, and from that draw a representative sample. He thought his organisation’s database of existing online customers would be a useful place to start, but he was unsure whether he would be allowed access. In addition, he did not simply want to undertake a large-scale quantitative survey of existing customers as did not think it would produce a picture of the wider situation. One of his objectives was, after all, to identify the Malaysian consumers’ expectations of these online offerings. How could he ensure he limited bias in the respondents’ answer, which would be a threat to the reliability of his findings?

His initial idea to use Facebook to gain access to a bigger population had not been received enthusiastically by his project tutor but he had anticipated the need to justify this suggestion. He argued that using this informal network, and building simple instructions and collecting demographic data in an Internet questionnaire, he would be able to categorize respondents and identify which supermarket website they were evaluating.

So here he was, with an interesting project that fitted perfectly with the need of his employer, which wanted to develop its presence on the Web. His intention was to get an overview of online consumer perceptions and expectations of the online supermarket sites available in the UK and France. He then planned to compare the data collected from the participants to identify the differences between the online activities of the British and Malaysian supermarkets and produce some guidelines to help his employer develop this side of its activities. However, the problem he came back to gain was how to select his sample.

Daniel thought a non-probability approach would fit this exploratory research but, if he was honest, the research methods lectures had totally confused him. A great deal of time had been spent on the explanation of the formula to work out the optimum sample size for a survey, and population. His concern was how to build the argument for using non-probability sampling and be able to justify it to his project tutor, whose own research activity involved large-scale marketing research projects run in conjunction with companies in Malaysia.

So here he was preparing his argument to produce a questionnaire using Survey Monkey and post the link on Facebook. In addition, he would send the link via emails to other friends who did not use Facebook. He would make the request that they all pass the link on their friends and family who fell within the parameters that would be defined in the message accompanying the link.

One point he felt that was in his favour was he had been able to develop a network of contacts during his time in the UK. As one of the few Malaysian students on campus he had taken advantage of his generous nature and tried to meet as many people as possible. His Facebook wall had thousands of postings from his ‘friends’. He was convinced this was the place to start but really needed to get his head around non-probability sampling if he was going to do it well.

             

Based on the given scenario, answer the following questions:

1. Identify the broad problem area.
2. Develop theoretical framework.
3. Suggest TWO (2) theories that related to the framework.
4. Develop THREE (3) research objectives and research questions.
5. Develop THREE (3) directional alternative hypotheses.
6. Suggest appropriate research design in terms of (please justify each answer):
   1. Purpose of study
   2. Researcher interference
   3. Study setting
   4. Research strategies
   5. Time horizon
   6. Unit of analysis
7. State the population for the study.
8. Identify the proper sampling design (probability or non-probability). Justify you answer.

Answer 1

Daniel will be faced with the question of using his marketing assignment as his pilot Analysis is:

• The sample size of Facebook planned data is very limited
• He thinks the online buying behaviour is an easy way out as his topic for pilot study
• His project teacher does not advocate using this subject
• He has chosen database that is open to a very specific subset of his college students, all young and with common purchasing habits.
• The nonprobability of data collection process, a very simple sampling technique in statistics, would produce unreliable findings in statistical review
• His research require a more diverse profile. With just facebook, he can't calculate the variance accurately audience.

Distribution of a connection to an internet questionnaire via facebook via email could jeopardize Daniels findings' statistical representativeness as follows:

• The accuracy of the answer can not be guaranteed, because the variation can not be measured.
• Only the target segment of young students (facebook friends) would exchange hypothetical and conflicting details
• In a long time the email could not be answered because often people will not respond to links and questionnaires.
• For commercial purposes Facebook data relies on user feedback that may not be reliable or trustworthy.
• Daniel's established population is small, and the obtained figures would not be adequate to provide an objective analysis. As the responses are from an similar group.
• The selection approach is very tight, as it only addresses a very small group of young students and on Twitter.
• Distribution will distort the results.

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