Test-retest reliability estimates are obtained by repeating the measurement using the same instrument under as nearly equivalent conditions as possible. The results of two administrators are then compared and the degree of correspondence is determined. The greater the differences , the lower is the reliability.
Alternative Form Reliability
Alternative-form reliability estimates are obtained by applying two equal forms of measuring instrument to the same subjects. As in test-retest reliability, the results of the two instruments are compared on an item by item basis and the degree of similarity is determined. The basic logic is the same as in test retest approach.
Two primary problems are associated with this approach. The first is the extra time, expense and trouble involved in obtaining two equivalent measures. The second and more important is the problem of constructing two truly equivalent forms. Thus a low degree of response similarity may reflect either an unreliable instrument or non-equivalent forms.
Internal Comparison Reliability
Internal comparison reliability is measured by intercorrelation among the scores of the items on multiple item index. All items on the index must be designed to measure precisely the same thing. For example; measure of the store image generally involve assessing a number of specific dimensions of the store such as price level, merchandise, service and location. Because these are somewhat independent, an internal comparison of reliability is not appropriate across dimensions. However it can be used within each dimension if several items are used to measure each dimension.
Marketing researchers frequently rely on judgment to classify a consumer’s response. This occurs, for example, when projective techniques, focus groups, observations or open ended questions are used. In these situations, the judges or scorers may be unreliable, rather than the instrument or respondent. To estimate the level of sorer reliability, each scorer should have some of the items he or she scores judged independently by another scorer. The correlation between various judges is a measure of scorer reliability.
Content validity estimates are essentially systematic, but subjective, evaluations of the appropriateness of the measuring instrument for the task at hand. The term face validity has a similar meaning. However face validity generally refers to “non-expert judgments” of the individuals completing the instrument and / or executives who must approve its use. This doesn’t mean that face validity is not important. Respondents may refuse to cooperate or may fail to treat seriously measurements that appear irrelevant to them. Managers may refuse to approve projects lacking in-face validity. Therefore , to the extent possible, researchers should strive for face validity.
Criterion- Related Validity
It can be of two types: (1) Concurrent Validity (2) Predictive Validity
Concurrent validity is the extent to which one measure of a variable can be used to estimate current score on a different measure of the same or closely related variable. For example, a researcher may be trying to relate social class to the use of savings and loan associations. In a pilot study researcher finds useful relationship between attitudes towars savings and loan associations and social class.
Predictive validity is the extent to which an independent’s future level on some variable can be predicted by his/her performance on a current measurement of the same or different variable. Predictive validity is the primary concern of the applied marketing researcher. Some of the predictive validity questions that confront marketing researchers are:
(1) Will measure of attitudes predict future purchases?
(2) Will a measure of sales in a controlled store test predict future market share?
(3) Will a measure of initial sales predict future sales?.
Construct validity- understanding the factors that underlie the obtained measurement- is the most complex form of validity. It involves more than just knowing how well a given measure works; it also involves knowing why it works. Construct validity requires that the researcher have sound theory of the nature of the concept being measured and how it relates to other concepts.
It is necessary to understand what the term scientific means. Scientific research is focused on the goal of problem solving and pursues a step-by step logical, organized, and rigorous method to identify problems, gather data, analyze them and draw valid conclusions therefrom. Thus, scientific research is not based oh hunches, experience and intuition (though these may play a part in final decision making), but is purposive and rigorous. Because of the rigorous way in which it is done, scientific research enables all those who are interested in researching and learning about the same or similar issues, to do are research and come up with comparable findings. Scientific research also helps researchers to state their findings with accuracy and confidence. This helps various other organizations to apply those solutions when they encounter similar problems. Furthermore, scientific investigations tends to be more objective than subjective, and helps managers to highlight the most critical factors at the work place that nee specific attention so as to avoid, minimize or solve problems. Scientific investigation and managerial decision making are integral aspects of effective problem solving.
The term specific, research applies to both basic and applied research. Applied research may or may not be generalized to other organizations, depending on the extent to which differences exist in such factors as size, nature of work, characteristics of the employees, and structure of the organization. Nevertheless, applied research also has to be an organized and systemic process where problems are carefully identified, data scientifically gathered and analyzed and conclusions drawn in an objective manner for effective problem solving.
Answers to issues can be found either by the process of deduction or the process of induction, or by a combination of the two. Deduction is the process by which we arrive at a reasoned conclusions by logically generalized from a known fact. For example, we know that all high performers are highly proficient in their jobs. If jobs is high performer, we then conclude that he is highly proficient in doing his job. Induction, on the other hand, is a process where observe certain phenomena and on this arrive at conclusions. In other words, in induction we logically establish a general proposition based on observed facts. For instance, we see that the production processes are the prime features of factories or manufacturing plants. We therefore conclude that factories exist for production purposes. Both the deductive and the inductive processes are applied in scientific investigations.
Theories based on deduction and induction help us to understand, explain or predict business phenomena. When research is designed to test some specific hypothesized outcomes, as for instance, to see if controlling aversive noise in the environment increase the performance of individuals in solving mental puzzles, the following steps ensue. The investigator begins with the theory that noise adversely affects mental problem solving. The hypothesis is then generated that if the noise is controlled, mental puzzles can be solved more quickly and correctly. Based on this, a research project is designed to test the hypothesis. The results of the study help the researcher to deduce or conclude that controlling the aversive noise does indeed help the participants to improve their performance no mental puzzles. This method of starting with a theoretical framework, formulating hypothesis, and logically deducing form the results of the study is known as the hypothetico – deductive method.
A descriptive study is undertaken in order to ascertain and be able to describe the characteristics of the percentage of members who are in their senior and junior years, sex composition, age groupings, number of semesters until action, and number of business courses taken, can only be considered as descriptive in nature. Quite frequently, descriptive studies are undertaken in organizations in order to learn about and describe the characteristics of a group of employees, as for example, the age, educational level, job status, and length of service of Hispanics or Asians working in the system. Descriptive studies are also undertaken to understand the characteristics of organizations that follow certain common practices.
An explanatory study is undertaken when not much is known about the situation at hand, or when no information is available on how similar problems or research issues have been solved in the past. In such cases, extensive preliminary work needs to be done to gain familiarity with the phenomena in the situation, and understand what is occurring, before we develop a model and set up a rigorous design for comprehensive investigation.
In essence, exploratory studies are undertaken to better comprehend the nature of the problem, since very few studies might have been conducted in that area. Extensive interviews with many people might have to be undertaken to get a handle on the situation and to understand more rigorous research can proceed.
A nominal scale is one that allows the researcher to assign subjects to certain categories or groups. For example, with respect to the variable of gender, respondents can be grouped into two categories – male and female. These two groups can be assigned code numbers 1 and 2. These numbers serve as simple and convenient category labels with no intrinsic value, other than to assign respondents to one of two nonoverlapping or mutually exclusive categories.
If there is any measurement of the value of research, it is usually an after-the-fact event. Twedt reported on one such effort, an evaluation of marketing research done at a major corporation. He secured “an objective estimate of the contribution of each project to corporate profitability.” He reported that most studies were intended to help management determine which one of two (or more) alternatives was preferable. He guessed that in 60 percent of the decision situations, the correct decision would have been make without the benefit of the research information. In the remaining 40 percent of the cases, the research led to the correct decision. Using these data, he estimated that the return on investment in marketing research in this company was 351 percent for the year studied. However, he acknowledges the return on investment figure was inflated because only the direct research costs had been included.
This effort at cost-benefit analysis is commendable even though the results come too late to guide current research decision. Such analysis may sharpen the………….
Studies that engage in hypotheses testing usually explain the nature of certain relationships, or establish the differences among groups or the independence of two or more factors in a situation. Examples of such studies are given below. Hypothesis testing is undertaken to explain the variance in the dependent variable or to predict organizational outcomes.
An interval scale allows us to perform certain arithmetical operations on the data collected from the respondents. Whereas the nominal scale allows us only to qualitatively distinguish groups by categorizing them into mutually exclusive and collectively exhaustive sets, and the ordinal scale to rank-order the preferences, the interval scale allows us to measure the distance between any two points on the scale. This helps us to compute the means and the standard deviations of the responses on the variable