IKEA Business Research Paper

IKEA is a world renowned furniture and home goods provider. Like all international businesses they have challenges and dilemmas that effect how they approach different aspects of their business. By identifying issues and how to combat them by analyzing accurate data IKEA can better handle situations and ensure continued profitability and company success Statistical Analysis The first level of measurement that IKEA used was nominal measurement. With this level of measurement, items were assigned into groups or categories.

This evaluated data was definitive and was captured with the questions that have a “yes” or “no” answer.

The next measurement level was the ordinal level of measurement. This level signified several specific reason behind the assignment and indicated an approximate ordering of the measurements. This evaluated the captured data using median and mode, with questions that have the answer choice for example; satisfied and unsatisfied. This allowed IKEA to determine how often customers were satisfied or unsatisfied with their goods and services.

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The third level deals with the interval which classified along with ordered the measurements; this level specified the distances between each interval on the scale were equivalent along the scale from low interval to high interval. The final level was the ratio level of measurement, this level the measurements can have a value of zero and the divisions between the points on the scale have an equivalent distance between them, and the rankings assigned to the items are according to their size (Marchal, William & Whaten 2009).

To evaluate the data, each answer will be given a ranking; excellent (100% satisfaction), average (50% satisfaction), and terrible (0% satisfaction).

This was used to measure the level of consumer satisfaction. Challenges to Validity and Reliability Validity and reliability are the two critical factors to be considered during a sample design and data collection. Survey is a very expensive approach. Therefore it is very important to do it right in the first time.

Carefully evaluating the potential challenges to validity and reliability of survey question, data and analysis is crucial. Cooper, D & Schindler, P (2006) indicated that there were four major faults of the survey instrument design are 1) the respondent error; 2) the situation error; 3) the measurer; and 4) the data collection instrument (Cooper, D. R. , & Schindler, P. S. 2006. ) At least two potential challenges for the survey should be considered. Different ethic group membership could have different answer to a same question.

For example, the customers in some countries may be reluctant to select “extremely satisfied” or “extremely satisfied” in the survey questionnaire to express their satisfaction level. This could cause the external validity issues when collecting the data. A defective instrument can cause distortion in a way of too confusing and ambiguous. When the researchers design the questionnaire, they should consider the participants’ education level and comprehension capability. Leading questions, ambiguous meanings, mechanical defects are also mistakes that could cause instrument errors.

For example, in the questionnaire one question is “What are the main reasons you chose IKEA for your shopping needs? ” This is an open question to the customers, the outcome of the answers may not be able to quantify for data analysis. It will be better to list the possible reasons to let the customers to choose. The researchers have to carefully determine the instrument scales Steps to Minimize Challenges Our reasoning for the minimization of these potential challenges is to save the company time and money.

Having a properly outlined and well prepared survey will lead to validity and reliability. Both validity and reliability are again the two critical factors to consider in the sample design and data collection processes. As stated in our previous section, we have chosen to utilize the following two challenges: ethnical differences and evaluation of the potential challenges to validity and reliability of survey question, data and analysis. Consideration for both challenges can be addressed and identified under the four major faults of the survey instrument design.

In order to properly prepare the survey and minimize challenges, IKEA must act as the end user. What essentially will happen is that IKEA will see how the final output questions can be effected by multiple factors. These factors can include the following but are not limited to: age, race, background, and educational background. When looking into these factors they will help to identify potential initial faults of the survey. Finally, the questions should be compared and analyzed to avoid more simplistic issues.

The following simplistic issues that could occur and IKEA should be prepared for are the following: leading questions, ambiguous meanings, mechanical defects, and comprehension. When covering all of the bases listed in the above paragraphs only then can IKEA’s final questionnaire/survey be complete. There is no way to eliminate the margin for error in any test such as a questionnaire. However when properly addressed the potential for challenges effecting data validity and reliability can be minimized. Classification of Findings

Currently, IKEA’s main focus is on profit sustainability and determining if true brand loyalty or short term effects of the world’s recession have affected buying behaviors which has lead to an increase in profits. IKEA can classify the order of power using the fundamental categories; nominal, ordinal, interval and ratio. The nominal measurement scales categorize or put items in groups. The data that can be collected from a nominal scale will be definitive. For example IKEA will be able to determine regular customers from first time buyers and will be better able to analyze the data accordingly.

The data reported that 8 out of 10 IKEA shoppers were returning customers. This data suggests that the economy did not have an effect on determining on where consumers were deciding to shop. With the ordinal level of measurement, it will evaluate the captured data using median and mode, with questions that have an answer choice. The data retrieved showed that for every 10 customers 9 were satisfied, which suggested that customers were returning customers because of true satisfaction and company loyalty.

The interval along with ratio determines the distances between each interval on the scale are equivalent along the scale from low interval to high interval (Marchal, William & Whaten 2009). This will help to determine trend. This will happen from data being retrieved from questions like; what was your main reason for shopping at IKEA? If you could change something about your shopping experience what would it be? The ratio level is where the points on the scale have an equivalent distance between them, and the rankings assigned to the items are according to their size (Marchal, William & Whaten 2009).

To evaluate the data each answer will be given a ranking; excellent (100% satisfaction), good (75% satisfaction), average (50% satisfaction), poor (25% satisfaction) and terrible (0% satisfaction). From the data collected it shows that there was 100% satisfaction 90% of the time. From this data we can conclude that customers are generally satisfied. By collecting data in an accurate and reasonably cost effective manner IKEA can determine their business success and shortcomings. This allows management to make educated decisions to continue company profitability and success.