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The differential responses by a consumer in purchasing decisions is used by many firms in market segmentation and design advertising, products etc., based on consumer characteristics. Such segmentation usually involves purchasing rates as the major factor influencing the buyer’s behavior and targets such groups as “heavy users”, “brand loyals”, and similar consumer groups. This study, however, stresses on the importance of other parameters like “awareness”, “general liking”, and “intention to purchase” in defining consumer groups, along with purchase rates. The research is based on the hypothesis that a single segmenting variable like purchase rate is not enough to define consumer characteristics, but require an extended regression model, which includes associated parameters like customer’s awareness to the product features and competing products, his/her likes and dislikes on a particular product group and the degree of intention to purchase.
The major concepts used in the study are the consumer’s overt behavior, learning and cognition. The concept of overt behavior is measured using the variable – purchase rate. Learning can be measured by variables like advertising awareness, motivation, and various preconceptions. Cognitive ability of a consumer is measured using the variables such as his/her attitudes, comprehension, intention to purchase and level of satisfaction. In addition, the study also uses demographic variables related to the consumer’s household. Following is a comprehensive list of variables identified in this study:
Endogenous Variables: Attention, Perceptual Bias, Stimulus Ambiguity, motive, Overt Search, Attitude, Intention to Purchase, Brand Comprehension, Confidence, Purchase and Satisfaction Level.
Exogenous Variables: Exposure to Media, Word-of-Mouth Conversation Activity, Receipt of Samples/Coupons and Price Paid.
Socio-demographic Variables: Mealtime Group, Homemaking Skill, Leadership, Household Size, Size of City, Age of Housewife, Housewife’s Education, Housewife’s Employment, Household Income, Housewife’s Time-Per-Week in Kitchen, Size of Meal and Prior Purchase Behavior.
The study assumes multiple-variable relationship among criterion variables and includes demographic descriptors of the decision units. Explicit functional relationships are defined using flow charts and general functional equations relating the variables, leading to preliminary testing of linear specifications of the complex relationships among different elements of the system.
The research is designed using a statistical model, which evolves under certain benchmarking criteria. The starting point of the design is a linear model under the hypothesis that no segments exist. The design then expands the equation by searching for regression coefficient inequalities and suggests a causal and correlational study among the concepts that are identified for the study.
The study measures different variables using the natural rank order within each of the explanatory variables, all of which are discrete category measures. For example, “income” takes on values from 1 to 5, corresponding to increasing income levels. The variables are measured by splitting the values monotonically into smaller and smaller divisions.
The research was conducted on a consumer panel, which was established in a test market that consisted of 300,000 households and 1,000,000 people. A sample of 70,000, selected systematically (probabilistic systematic sampling + judgment) from area telephone directories, received recruitment letters and screening questionnaires. About 8,300 people responded and 1,100 were selected for the panel. After the screening questionnaire, members reported every 2 weeks on their purchases of fife food product classes identified for the study. The eating habits, involvement in homemaking, impulsiveness, gregariousness, time pressures, and concerns with nutrition were measured using mailed questionnaires. Respondents were also asked whether they had ever heard of brands in the related product class. And for each brand they had heard of, they were asked about the usage of these products, their attitudes towards that brand, importance of these attitudes in their purchase decisions, and the likelihood of their purchasing the brand in the next month. Another phase of telephone interviews was conducted over the telephone and only those families who completed all phases of data collection procedure were used for analysis. After screening out a handful of other data points due to missing data, produced a final sample of 693 households used for the study.
The results are provided as tables and cross-tabs and analyzed equation by equation. First, attitude is analyzed as a dependent variable and the results show a significant increase in the coefficient of determination of this segmented specification. The study finds that the coefficient of previous purchase divides for respondents whose intention level is smaller than 2 and is raised significantly when intention is greater than or equal to 2.0, indicating that previous purchase is a strong segmenting variable. Analysis of intention to purchase as a dependent variable show that communication activities like word-of-mouth, company at meal etc., have a significant impact on buyer’s behavior. Heavy purchasers had a lower attitude coefficient, and homemaking skills turned out to be significant for people with measured confidence of 4.0 or higher. Analysis of purchase as the dependent variable show that the sole endogenous variable had a statistically significant coefficient, but re-specification of the variable to include a broader set of exogenous variables, divided it into several categories of dummy variables, each of which implies positive relationships between intention and purchase.
The research ends with a discussion of results and a summary. Market segments for a convenience food product were defined in terms of parametric relationships between three criterion variables (attitude, intention to purchase, and purchase) and a variety of causal factors including endogenous behavioral measures and exogenous socioeconomic variables. Goodness-of-fit measures and tests of significance on coefficients were used to detect different interrelationships. The analysis show that the segment identified turned out to be composed of relationships among endogenous variables, a disappointment to the focus of study, because these variables are not subject to direct manipulation but rather are phenomena, which intervene in the decision process. Sociodemographic measures used in the study provided a basis for segment identification. The study, however, does not clearly summarize the results and say about whether the hypothesis is supported or not. It just concludes by indicating that more time and money are required for a segmentation study like this.
The research is well designed and focuses on the hypothesis. The sampling procedure and measurements are well suited for the field of study. But the results are not discussed well, and often tend to be too technical and difficult to understand. I would recommend interpreting the mathematical results to plain English so that it is easier to understand by companies/individuals who are looking at the results of similar research, to improve their market segmentation strategies. A longitudinal study, including the same panel, on the behavioral changes would also help in getting an accurate picture of the buyer behavior model.
Most often we forget to realize the impact that we can make as an individual to build up a system that works with integrity. We always look at the short-term impact and decide that it is difficult to change the system single-handedly. When the underlying system is so corrupt, people often consider bribes and corruption as part of the system. Things can improve dramatically when people are educated more on the way they can affect the integrity of the system. In India, it used to be very difficult, in the past, to get a driver’s license or a phone connection without bribing the public official. Things have now improved considerably as people have realized that, with little patience, the system would continue to work even without bribing these people. With more informative movements and educational clips through media, we are on the verge of having a corruption-free system.
It is also sometimes argued that one has no right to engage in another country’s corruption because you will not be there to live with the consequences. I am always confused regarding such arguments. We know that the consequences of corruption is bad for all. One would think that if you are not going to experience the consequence, it is fine to engage in a corruptive act. I believe that the resistence should come from local citizens because they are the ones who are going to live with the consequences. There is no righteousness, whether you are a foreign or a local citizen, when it comes to a corruptive act.
This article from World Business helps us understand an important period in history—the decade when the U.S. dollar kept falling. The constant rise in the Japanese yen caused extreme problems for Japanese companies. This proves that the principles are same regardless of which currency happens to be up or down at a particular moment in time.
The article says “the wholesale prices exporters could command had essentially been cut by two thirds.” What it means is that the yen had appreciated against US dollar from $1 = 240 yen in 1985 to $1 = 80 yen in early 1995. In order to remain competitive in the market, Japanese exporters had to cut down their profits by two thirds.
The company profiled here did worse and worse as the yen got stronger. As the yen got stronger, the company’s exports became less profitable and their products became less competitive compared to the other low-wage Asian economies. In order to improve things, Endaka reduced employee bonuses and relied on quality manufacturing and service. They invested in R&D to build low-cost semi-automatic machines to compete with their low-waged Asian rivals. The company also setup a new plant in Bangkok to gain a cost advantage.
Reducing employee bonuses and building low-cost machines reduces the operating costs, thereby keeping the prices same as before, to be competitive in the market. This allows them to export at the same price without passing through the exchange rate fluctuation. Starting a plant in Bangkok whose currency was on the decline, helped the company to compete against other low-waged countries, there by reducing the production costs.
The article was written at the exact time that the yen reversed and started its decline. When the yen starts to decline, the firm’s exports will become cheaper and more competitve in the world markets. The firm should now export more. The firm should also reduce the amount of imports which they had relied on during the period when yen was appreciating. They should also return to their previous bonus scale to revive employee satisfaction and morale.
This was an interesting article in Business Week. The article discusses the influence of China in bringing the prices of manufactured goods down in the global market.
In the past few years, there have been reasons for the Chinese yuan to go down, and reasons for it to go up. Some of the countries including South Korea, Thailand, Indonesia and Russia had all suffered severe currency crashes, which was a huge set-back for the Chinese export manufacturers. They experienced fierce competition from these countries and requested the Chinese government to reduce the value of yuan.
In a few years after the Chinese government fixed the value of yuan, Chinese manufacturers were flooding the world market with cheap goods in almost all industrial sectors. This caused panic among other countries as they noticed that the Chinese prices were becoming global prices and feared that it would be difficult to bring robust/free-market pricing to these sectors. As a result, these countries, including the trading partners of China started putting pressure on China to make the yuan appreciate.
We have studied the impact of inflation on exchange rates. It is also equaly important to understand the impact of deflation. During deflation, the prices of domestic goods and services go down, making foreign imports less attractive. As a result, less currency is supplied to the foreign exchange and the value of currency eventually goes up.
China is one of the few remaining countries to fix its currency’s exchange rate rather than let it sell at the free market (supply & demand) equilibrium value. Having a fixed exchange rate for the yuan, Chinese exporting manufacturers are much more competitive in global markets. Even with other favorable conditions, other countries find it hard to compete against Chinese exporters who have the benefit of a pegged yuan. These countries are also worried about the pricing trend set by China, which they fear would become the global prices in all the industrial sectors. These prices cause imbalances in the developing world. Industries and service sectors in other countries had started plunging because of a pegged yuan. Hence, other countries are keeping a close watch on China’s exchange rate policy, trying to let the Chinese government float the yuan at free-market rates.
Letting the currency to float is expected to increase the value of yuan which makes China’s exports more expensive and less competitive in world markets. This would drop China’s exports, and as a result, would wipe out the weakest producers and hammer the banking sector. As a result, unemployment rates would sky rocket. Hence China would leave its exchange rate exactly where it is.
Chinese banks are holding a lot of bad debt and many are technically insolvent (liabilities exceed assets). This bad debt can cause a decline in China’s growth and less currency available in the world market. The decline in growth also leads to deflation. As a result, the value of yuan could go up.
This was an article from BusinessWeek Online. The article compares currency fluctuations with Christmas morning because exporters have waited such a long time for the dollar to fall. (The dollar was high from 1995-2002.) Now they’re disappointed.
Why has the falling dollar boosted exports less than expected? The less than expected growth in exports is because of the global economic slowdown and soft economies of other countries. Seasonal buying patterns of consumers also play a major role. Consumers have to wait for a while to make sure that the exchange rates are not reverted.
Exporters don’t expect to see any effects from the dollar’s fall for some time even if there are prior contracts in effect or the buyers have overstocked inventory. But in the long run exporters gain from these when the dollar falls.
Eventually, the declining dollar has to help exporters because the products become cheaper and more competitive in global markets.
Exporters will also focus their attention on China pegging the yuan to the dollar. By pegging the Chinese yuan to the dollar, Chinese exporting manufacturers are much more competitive in global markets. Even with a declining dollar, US exporters find it hard to compete against Chinese exporters who have the benefit of a pegged yuan. Hence the US exporters are focused on China pegging the yuan and are looking for a float in the Chinese currency.
The article assumes the Chinese yuan will go up if the Chinese government lets it float instead of pegging it. That would be good news for some and bad news for others.
If the Chinese government lets yuan to float, the value of yuan will go up. As a result, the operating costs of anyone who is manufacturing in China or buying parts or goods from Chinese manufacturers will increase.
