Summary Business Research Methods

Table of Content

There are no predetermines for the appropriateness of either qualitative or a quantitative study. A new investigation often starts with qualitative studies exploring new phenomena and, later on, quantitative studies follow to test the validity tot propositions deregulated in previous qualitative studies. Consequently, quantitative methods are more common in the positivist tradition, while qualitative methods are more common in interpretative. There are now general guidelines as to when a qualitative or quantitative method is more appropriate. 5. Research design classifications The essentials of research design: ;k Activity- and time-based plan; Always based on the research question: ;k Guides the selection of sources and types of information; * A framework for specifying the relationships among the stud’s variables; * Outlines procedures for every research activity. The major descriptors classifying research design: Degree of research question crystallization: * Exploratory study; tends toward loose structures with the objective of discovering future research tasks. The purpose is usually to develop hypotheses or questions for further research. Formal study; begins where the exploratory study ends. It begins with a descriptive account of the current situation followed by the hypotheses or research question, and involves precise procedures and data source specifications. The goal is to provide a valid representation of the current state and to test the hypotheses or answer the research questions posed Method of data collection; * Monitoring; includes studies in which the researcher inspects the activities of a subject or the nature of some material without attempting to elicit response from anyone.

The researcher notes and records the information available from obeseВ»actions. Interrogation/communication study; the researcher questions the subjects and collects their responses by personal or impersonal means. (interviews, self-administered or self-reported, before and after a experiment) * Archival sources; the information required to answer a research problem is already available and the researcher can rely on these secondary data. -k Researcher control of variables; * Experimental; the researcher attempts to control and/or manipulate the variables in the study.

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It is appropriate when one wishes to discover whether certain variables produce effects in other variables. Ex-post facto,’ investigators have no control over the variables in the sense of being able to manipulate them, They can only report what has happened or is happening. It is important that they don’t influence the variables, to avoid bias. The purpose of the study; * Descriptive: it the researcher is concerned with finding out who, what, where, when or hove much. * Causal; if it is concerned with learning why (how one variable produces changes in another).

Predictive: builds on theory and attempts to provide answers to the question what is likely to happen in the future. K The time dimension; Cross-sectional; are carried out once and represent a snapshot of one point Longitudinal; are repeated over an extended period. Advantage in time. Is that it can track changes over time and their also more powerful regarding tests of causality. ;k Panel; the researcher may study the same people over time. * Cohort; use different subjects for each sequenced measurement. The topical scope; * Case; place more emphasis on a full contextual analysis Of fewer events or conditions and either interrelations. A single well-designed case study can provide a major challenge to a theory and provide, simultaneously, a source Of ewe hypotheses and constructs. * Statistical study; are designed for breadth rather than depth. They attempt to capture a population’s characteristics by making inferences from a sample’s characteristics. Hypotheses are always tested quantitatively. Generalizations of findings are presented based on the representatives of the sample and the validity of the design. Sample Census; based on the whole population. * The research environment; * Field setting; designs occur under actual environmental conditions. We observe or interrogate people in their usual environment, * Laboratory search; designs occur under staged or manipulated conditions. We are able to manipulate the environment although the laboratory might be designed as the usual environment. Simulation; designs occur artificially. Are used increasingly in research, especially in operations research. Role-playing) * Participants’ perceptions; * Actual routine; participants perceive no deviations from everyday routine. ;k Modified routine; * Participants perceive deviations, but as unrelated to the research; Participants perceive deviations as researcher-induced. 5. Exploratory, descriptive, and causal studies The exploratory study is particularly useful when researchers lack a clear idea Of the problems they Will meet during the study. Through exploration, researchers develop concepts more clearly, establish priorities, develop operational definitions and improve the final research design.

Exploration may also save time and money: if the problem is found not to be as important as it was first thought, subsequent more formal studies can be cancelled. Purposes of exploration: To learn something about the research or management dilemma; * Important variables may not be known or may not be defined thoroughly; To be sure that it is practical to do a formal study in the area; Exploration is sometimes linked to old biases about qualitative research: accusations of successiveness, non-representatives and non-systematic design.

Exploration saves time and money and should not be slighted. Several qualitative techniques adaptable for exploratory research: * In-depth interviewing * Participant observation; ;k Films, photographs and videotapes; * Projective techniques and psychological testing ;k Case studies; * Street ethnography; ;k Elite or expert interviewing; * Document analysis; ;k Proteomics and kinesics. When these methods are combined, four exploratory techniques emerge: Secondary data analysis; studies made by others for their own purposes represent secondary data.

It is inefficient to discover anew through the collection of primary data or original research what has already been done and reported at a level sufficient to solve the research question. A search of secondary sources Will supply excellent background information as well as many good leads. * Experience survey; we will profit by seeking information from persons experienced in the area or study, tapping into their collective memories and experiences. We should seek the ideas about important issues or aspects of the subject, and discover what is important across the subject’s range of knowledge.

Focus groups; most common in the consumer arena. The output of a focus group is often a list of ideas and behavioral observations, These are often used tort later quantitative testing. In exploratory research, the qualitative data that focus groups produce may be used for enriching all levels of research questions and hypotheses, and for comparing the effectiveness of design options. Focus groups are also a useful method in the research process regarding pre-testing questionnaires, experiments and so on.

This is advantageous because pilot groups usually only contain people who could be respondents * Two-stage designs; with this process, exploration becomes a separate first stage with limited objectives: * Clearly defining the research question; k Developing the research design An exploratory study is finished when the researchers hue achieved to following: Established the major dimensions of the research task; * Defined a set Of subsidiary investigative questions that can be used as guides to a detailed research design; ;k Developed several hypotheses about possible asses Of a management dilemma; * Learned that certain Other hypotheses are such remote possibilities that they can be safely ignored in any subsequent study: * Concluded that additional research is not needed or is not feasible. Descriptive studies are more formalized studies and are typically structured with clearly stated hypotheses or investigative questions.

Variety of research objectives: Descriptions of phenomena or characteristics associated with a subject population; * Estimates of the proportions off population that have these characteristics: Discovery of associations among different variables; moieties labeled as a correlation study. The simplest descriptive study concerns a universal question or hypothesis in which we ask about, or state something about, the size, form, distribution or existence or a variable. Causal studies attempt to reveal the relationship between variables. The concept of causality is grounded in the logic of hypothesis testing, which, in turn, produces inductive Such conclusions are probabilistic and thus can never be demonstrated with certainty.

There are three possible relationships between two variables: * Symmetrical; is one Which two variables fluctuate together but we assume the changes in either variable are due to changes in the other. Reciprocal; exists when two variables mutually influence or reinforce each Other. * Asymmetrical; With the we postulate that changes in one variable are responsible for changes in another variable. We evaluate independence and dependence on the basis of: * The degree to which each variable may be altered * The time order between the variables There are four types of asymmetrical relationships: Stimulus-response; an event or change results in a response from some object. (experiments) * Property-disposition; an existing property causes a disposition. Equines and social science research) * Disposition-behavior; a disposition causes a specific behavior. (ex-post facto) * property-behavior; an existing property causes a specific behavior. In testing causal hypothesis projects, we seek three types of evidence: Cooperation between A and B; ;k Time order of events moving in the hypothesized direction; No other possible causes of B; Successful inference-making from experimental designs must meet two ;k Control; requirements: * Random assignment, each person in the study must have an equal chance of exposure to each level of the independent variable. There is always a control group in experimental design.

Randomization is the basic method by which equivalence been experimental and control group is determined. Experimental and control groups must be established so that they are equal. A second method to control uses matching. There might be a reason to believe that different ratios Of alumni support Will come from various age groups. To control by matching we need to be sure that the age distribution of alumni is the same in all groups. Toastmaster; random assignment of subjects to experimental and control groups is the basic technique y which the two groups can be made equivalent. Matching and other control forms are supplemental ways of improving the quality of measurement.

Causation and ex-post facto design: instead of manipulating and/or controlling exposure to an experimental variable, we study subjects who have been exposed to the independent factor and those who have not. We Cannot use assignment Of subjects in ex-post facto research as we did in experimentation. However, we can gather information about potentially confounding factors and use these data to make circumnavigations comparisons. Researchers must necessarily use ex-post facto design to address causal questions. But the cooperation found between variables must be interpreted carefully when the relationship is based on ex-post facto analysis. The term post hoc fallacy has been used to describe these frequently unwarranted conclusions. Chapter 6 sampling strategies 6. Unit Of analyses The unit of analysis: describes the level at which the research is performed and Which Objects are researched (people/employees and higher levels as organizations, departments, divisions but also lower levels as transactions, contracts or management decisions). Not the same thing as the respondent of the researcher questions!!!! The choice of unit of analysis depends on three questions: 1. What is our research problem and what do we really want to answer? 2. What do we need to measure (variables) to answer our research problem? Choose the unit 3. What do we want to do with the results of the study/whom do we address in our conclusions? 6. The nature of sampling Population: total Census: count of the total elements in the population Sample: selecting elements and draw conclusions about the whole population Why do we use sampling of a population? Lower cost – Greater accuracy of results; better interviewing than the whole population – Greater speed of data-collection – Availability Of population elements (the subject on Which the measurement is being taken). Sampling also if the element is infinite. 6. Sample versus census A census study is appropriate if: 1. There’s a small population. 2. Necessary when the elements are quite different from each other. What makes a good sample? 1.

Accuracy: the degree to which bias (overpowered) is absent from the sample. When a sample is drawn properly, some sample elements underestimate the population values and others overestimate them, An accurate sample (unbiased) is one in which the under estimators and the over estimators are balanced along the members of the sample (corner houses are bigger than normal ones) 2. Precision (of estimate): no sample will fully represent its population in all respects. Precision is measured by the standard error of estimate, a type of standard deviation measurement. 6. 4 Types of sampling design Representation: Probability sampling: based on the concept Of random selection.

Simple random sample: each population element has an equal chance of being chosen. Non- probability sampling: non-random and subjective. The researcher picks his subjects by hand. Element selection – unrestricted; if each sample element is drawn individually from the population at large. – Restricted: covers all other forms of sampling 6. Steps in sampling design: 1. What is the relevant population? 2. What are the parameters tot interest? Population parameters; summary descriptors (mean, variance) Sample statistics are used as estimators tot the parameters. What variables are tot interest tort the research? What type of data is used (nominal, ordinal, ratio, interval).

Population reapportion of incidence: the number of elements in a population belonging to the category of interest, divided by the total number of elements in the population 3. What is the sampling frame? The list of elements from which the sample is actually drawn. Ideally, this is a complete and correct list of population members only. However, in practice it’s never this accurate! The use of screening processes is very helpful in this process. 4. What is the type of sample? Probability or Nan-probability sample? In the case Off probability sample these rules apply: 1. Interviewers cannot modify the selections made. . Only those selected elements from the original sampling frame are included. 3.

Substitutions are excluded except as clearly specified and controlled according to predetermined decision rules. 5. What size sample is needed? Some principles that influence the sample size: – The greater the variance within the population, the larger the sample must be to provide estimation precision. – The greater the desired precision of the estimate, the larger the sample must be. – The greater the number tot sub- groups of interest within a sample, the greater the sample size must be, as each pub-group must meet minimum sample size requirements. – About 5% of the population. Precision (inaugurated) is measured by: – The interval range in which they would expect to find the parameter estimate. The degree of confidence they wish to have in that estimate. 6. HOW much Will it cost? 6. Complex probability sampling Next to simple random sampling, there are four other alternative sampling approached. This is because random sampling is expensive, requires a population list and it fails to use all information: 1. Systematic sampling Every kith element in the population is sampled. 2. Stratified sampling. Most populations can be segregated into several mutually exclusive sub- populations (or strata). Examples: Gender, education, specialist etc. Why use stratified sampling? 1. To increase a sample’s statistical efficiency. 2. To provide adequate data for analyzing the various sub-populations. 3.

To enable different research methods and procedures to be used in different strata. 3. Cluster sampling. The population can be divided into groups of elements with some groups randomly selected for study. Why clustering? – The need for more economic efficiency that can be provided by simple random sampling. – The frequent unavailability of a practical sampling frame for individual elements, Area sampling is part of cluster sampling. It identifies geographic area. 4. Double sampling. Collect some information by sampling and then use this information as the basis for selecting a sub-sample for further study. 6. Non-probability sampling Why should we use non-probability?

Example: Probability: measures the what happens to the purchase of cigarettes when the tax will increase 1 Euro Non-probability: measures the positive of negative effect. For example which factors can encourage students to stop smoking (friends, price, information). Next to this its cheaper and costs less time Convenience sampling: non probability samples which are unrestricted; whoever wants to respond (family, neighbors) Purposive sampling: non probability which conforms to certain criteria * judgment; select sample members conform criterion * quota; to improve representatives Snowball sampling Chapter 7 survey research 7. 1 Characteristics of the communication approach To gather primary data, there are two alternatives: 1. Observations.

You can observe behavior, events, people or processes. 2. Communicate. Learn about attitudes, motivations, intentions and expectations. Recitalist; opinions and attitude – geographic coverage – more expensive than observation – is the participant Willing to cooperate? Communication approach: surveying people and recording their responses for analysis. The quality and quantity however, depends heavily on the respondent. Is he or she willing to cooperate and giving enough feedback? Their motivation depends on: – Pressure of competing activities. – Embarrassment and ignorance of interview topic. – Dislike interview topic or content. – Fear of consequences tot participation. Prestige (mezzanine) of research sponsor or agency. Perceived importance tot the topic. – Linking compassion for interviewer. – Self-image as dutiful citizen. – Loneliness. – Confirmation of self-importance. 7. Choosing a communication method A researcher can conduct a survey by personal interview, telephone, mail, computer or a combination. 7. Personal interviewing: Face-to-face survey. The interview is between two persons, one interviewer and one participant. Advantages: – The in-depth of information and details. – The interviewer can assist the participant in the correct interpretation Of the question (opposed to i. E. Mail surveys). Conditions can note conditions. Probe additional questions – Gather supplemental information through observation. . Pre-screen to ensure the correct participant is replying. – Interviewers can use special scoring devices like computer-assisted personal interviewing (CAPS). ; Adapt to linguistic problems that might occur during the interview. Disadvantages: – High costs, in money and in time. (Intercept interview is an exception, because in this case the interviewer targets participants in centralized locations). – Need tort highly trained interviewers. – Not all respondents are available or accessible. The interviewer might influence the participant which causes biased results.

Requirements for a successful personal interview: I _ The participant must possess the information being targeted by the investigative questions. 2. The participant must understand his or her role in the interview as the provider Of accurate information. 3. The participant must perceive adequate motivation to cooperate. Increasing participants receptiveness: I. The participant must believe that the experience Will be pleasant and satisfying. 2. The participant must believe that answering the survey is an important and worthwhile use of his or her time. 3. The participant must dismiss any mental reservations that he or she might have about participation. It’s the task of the interviewer to achieve this!

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