Role of Fiscal Policy in Economic Development?

Fiscal policy refers to the guiding principles of the financial work which are constituted by the state based on political, economic and social development tasks under a certain period. Its purpose is to regulate aggregate demand through government’s spending and tax policies. On the one hand, an increase in government spending will stimulate aggregate demand and increase the national income. Correspondingly, a decrease will depress aggregate demand and reduce national income. On the other hand, a tax is a kind of contraction strength to national income. Therefore, the aggregate demand and the national income will be restrained though increasing government revenue. And they will be increased due to reducing in government revenue as well. The fiscal policy with a distinct class character is formulated by the state, represents the will and interests of the ruling class, and is subject to a certain level of development of social productive forces and economic relations. The state fiscal policy is an integral part of overall economic policy, and is closely linked with the other economic policies. In fact, the development and implementation of fiscal policy must be cooperated with the financial policy, industrial policy and income distribution policy and other economic policy.

The important role played by the fiscal policy in a developing economy can be explained through :

1. Fiscal policy during inflation,
2. Fiscal policy during depression,
3. Fiscal policy and unemployment,
4. Fiscal policy and income inequalities and
5. Fiscal policy and economic growth.

Fiscal Policy during Inflation

Inflation is a period in which the purchasing power with, the people in the economy is high. The first step to curb inflation is to control the purchasing power with the people. This can be done using all the tools of fiscal policy. For instance, during inflation, since the private expenditure is high the government should bring down the public expenditure so that, to that extent the income generation will be controlled. Alternatively, the government can increase the existing tax rates or impose new taxes. This will have the effect of taking away the purchasing power from the rich and well-to-do people thereby curbing the consumption expenditure. The tax revenue will then be used for public expenditure purposes which will also be low during inflation. Hence, there will be effective control of money supply in the economy. Another way in which the fiscal authorities can function is to indulge in public borrowing. The government may start borrowing from the people in large scale so that the disposable income with the people will be reduced bringing down the demand and prices. If voluntary lending is not effective, then the government may resort to involuntary lending or compulsory saving by the people. Through its debt management policy also the fiscal authorities can control inflation. The anti-inflation debt management requires the retirement or payment of bank-held securities or debts through budgetary surplus. But this is very difficult in practice as in a developing country the government cannot have budgetary surplus.

Fiscal Policy during Depression

Depression is a period characterized by low income, low employment and low consumption. Fiscal policy should change this situation. The government must adopt deficit budget in order to increase the income stream in the economy through increased injection of fresh purchasing power into the economy. Secondly, the government must encourage consumption and investment and for this purpose the taxation should be brought down. Liberalized corporate tax policy will also help to increase the corporate expenditure giving the necessary thrust for the revival of economic activity. Public expenditure during this period must be increased. The government can achieve this either through pump priming or compensatory spending. Pump priming refers to the initiation of investment activity by the government through its expenditure on public projects which will be followed up by the increased private investment. Compensatory spending is resorted to when the private investment is not adequate enough. Then the government also injects public investment through public projects. Public debt policy can be suitably modified to fight against depression. The government should borrow more from the rich people and spend this amount in large scale on public works, and social security projects. All these steps will help to protect the economy and enable it to recover from depression.

Fiscal Policy and Unemployment

Fiscal policy plays a vital role in generating employment opportunities in the developing countries. In a developing economy, it should aim at solving the problem of both cyclical unemployment and disguised unemployment. While the former is of temporary nature, the latter has the snow-balling effect. The latter refers to a situation in which more than the required number of people are employed in a job. In other words, by reducing the excess of labor from that job, the productivity or production will not be affected. Hence, it has been found that fiscal policy alone cannot solve this problem of unemployment in a developing economy. It has to be coupled with monetary policy. For instance, during inflationary period, the government should adopt surplus budget, along with hard money policy, while during depression, deficit budget should be combined with cheap money policy.

Fiscal Policy and Income Inequalities

The role of fiscal policy in removing income inequalities in a developing economy cannot be exaggerated. With public expenditure and taxation, the government can very easily achieve income equality. The government should devise its public expenditure scheme by focusing on the poor and down-trodden people in the society. It may provide cheap food, cheap cloth, subsidized housing, free medical aid, free education, etc., to the poor people thereby raising their standard of living. For this purpose, the government should raise funds by imposing taxes on the rich people so as to bring down their purchasing power. It may completely or partially relieve the poor people from the tax net. This has the effect of-taking away as much as possible from the rich people and spending on poor people. It may also resort to large dose of indirect taxes so as to make the rich bear the burden as the poor will be paying such taxes only if they spend on items on which the government has imposed heavy indirect taxes. Therefore, taxation and public expenditure are the two very useful instruments of fiscal policy which can bring about the income equality in a developing economy.

Fiscal Policy and Economic Growth

Economic growth calls for the application of all the tools of fiscal policy. In developing economy, there may be no shortage of real or physical resources, but there may be a severe shortage of financial resources which are required to utilize the physical resources. The object of fiscal authorities should be to mobilize much funds as possible so as to carry out large scale public projects. A very effective method of mobilizing financial resources is taxation. The government can resort to both the direct as well as indirect taxes so as to generate as much funds as possible from all those who have the ability to pay. Different type of direct taxes and indirect taxes may be levied to cover every section of the population. There can be specific taxes to curb certain consumption activities. Another instrument available is public debt. Apart from the voluntary lending schemes the government should also devise schemes to encourage compulsory savings. Resources mobilized in this manner should be spent in such a way that the infrastructural facilities are strengthened first. This should be followed by the expenditure on growth oriented industries and other related activities. Care should be taken to avoid creating or widening sectoral imbalance so that the benefits of growth will be shared by all the sectors in the economy. Government must use its planning machinery to identify the right priorities so that the hard mobilized funds are utilized in the best way possible. In this process now-a-days the governments also resort to deficit financing. It is considered as a means of financing economic development. But too much reliance on deficit financing will also be dangerous. However, fiscal policy can play a vital role in helping to achieve a rapid economic growth.

Contents and Layout of Research Report

Contents of  Research Report

The researcher must keep in mind that his research report must contain following aspects:

1. Purpose of study
2. Significance of his study or statement of the problem
3. Review of literature
4. Methodology
5. Interpretation of data
6. Conclusions and suggestions
7. Bibliography
8. Appendices

These can be discussed in detail as under:

(1) Purpose of study:

Research is one direction oriented study. He should discuss the problem of his study. He must give background of the problem. He must lay down his hypothesis of the study. Hypothesis is the statement indicating the nature of the problem. He should be able to collect data, analyze it and prove the hypothesis. The importance of the problem for the advancement of knowledge or removed of some evil may also be explained. He must use review of literature or the data from secondary source for explaining the statement of the problems.

(2) Significance of study:

Research is re-search and hence the researcher may highlight the earlier research in new manner or establish new theory. He must refer earlier research work and distinguish his own research from earlier work. He must explain how his research is different and how his research topic is different and how his research topic is important. In a statement of his problem, he must be able to explain in brief the historical account of the topic and way in which he can make and attempt. In his study to conduct the research on his topic.

(3) Review of Literature:

Research is a continuous process. He cannot avoid earlier research work. He must start with earlier work. He should note down all such research work, published in books, journals or unpublished thesis. He will get guidelines for his research from taking a review of literature. He should collect information in respect of earlier research work. He should enlist them in the given below:

1. Author/researcher
2. Title of research /Name of book
3. Publisher
4. Year of publication
5. Objectives of his study
6. Conclusion/suggestions

Then he can compare this information with his study to show separate identity of his study. He must be honest to point out similarities and differences of his study from earlier research work.

(4) Methodology:

It is related to collection of data. There are two sources for collecting data; primary and secondary. Primary data is original and collected in field work, either through questionnaire interviews. The secondary data relied on library work. Such primary data are collected by sampling method. The procedure for selecting the sample must be mentioned. The methodology must give various aspects of the problem that are studied for valid generalization about the phenomena. The scales of measurement must be explained along with different concepts used in the study.

While conducting a research based on field work, the procedural things like definition of universe, preparation of source list must be given. We use case study method, historical research etc. He must make it clear as to which method is used in his research work. When questionnaire is prepared, a copy of it must be given in appendix.

(5) Interpretation of data:

Mainly the data collected from primary source need to be interpreted in systematic manner. The tabulation must be completed to draw conclusions. All the questions are not useful for report writing. One has to select them or club them according to hypothesis or objectives of study.

(6) Conclusions/suggestions:

Data analysis forms the crux of the research problem. The information collected in field work is useful to draw conclusions of study. In relation with the objectives of study the analysis of data may lead the researcher to pin point his suggestions. This is the most important part of study. The conclusions must be based on logical and statistical reasoning. The report should contain not only the generalization of inference but also the basis on which the inferences are drawn. All sorts of proofs, numerical and logical, must be given in support of any theory that has been advanced. He should point out the limitations of his study.

(7) Bibliography:

The list of references must be arranged in alphabetical order and be presented in appendix. The books should be given in first section and articles are in second section and research projects in the third. The pattern of bibliography is considered convenient and satisfactory from the point of view of reader.

(8) Appendices:

The general information in tabular form which is not directly used in the analysis of data but which is useful to understand the background of study can be given in appendix.

Layout of the Research Report

There is scientific method for the layout of research report. The layout of research report means as to what the research report should contain. The contents of the research report are noted below:

1. Preliminary Page
2. Main Text
3. End Matter

(1) Preliminary Pages:

These must be title of the research topic and data. There must be preface of foreword to the research work. It should be followed by table of contents. The list of tables, maps should be given.

(2) Main Text:

It provides the complete outline of research report along with all details. The title page is reported in the main text. Details of text are given continuously as divided in different chapters.

• (a)    Introduction
• (b)   Statement of the problem
• (c)   The analysis of data
• (d)   The implications drawn from the results
• (e)   The summary

(a)    Introduction:

Its purpose is to introduce the research topic to readers. It must cover statement of the research problem, hypotheses, objectives of study, review of literature, and the methodology to cover primary and secondary data, limitations of study and chapter scheme. Some may give in brief in the first chapter the introduction of the research project highlighting the importance of study. This is followed by research methodology in separate chapter.

The methodology should point out the method of study, the research design and method of data collection.

(b)   Statement of the problem:

This is crux of his research. It highlights main theme of his study. It must be in nontechnical language. It should be in simple manner so ordinary reader may follow it. The social research must be made available to common man. The research in agricultural problems must be easy for farmers to read it.

(c)    Analysis of data:

Data so collected should be presented in systematic manner and with its help, conclusions can be drawn. This helps to test the hypothesis. Data analysis must be made to confirm the objectives of the study.

(d)   Implications of Data:

The results based on the analysis of data must be valid. This is the main body of research. It contains statistical summaries and analysis of data. There should be logical sequence in the analysis of data. The primary data may lead to establish the results. He must have separate chapter on conclusions and recommendations. The conclusions must be based on data analysis. The conclusions must be such which may lead to generalization and its applicability in similar circumstances. The conditions of research work limiting its scope for generalization must be made clear by the researcher.

(e)    Summary:

This is conclusive part of study. It makes the reader to understand by reading summary the knowledge of the research work. This is also a synopsis of study.

(3) End Matter:

It covers relevant appendices covering general information, the concepts and bibliography. The index may also be added to the report.

Sampling Methods in Research

Sampling

is that part of statistical practice concerned with the selection of an unbiased or random subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for the purposes of making predictions based on statistical inference. Sampling is an important aspect of data collection.

There are two basic approaches to sampling: probabilistic and non-probabilistic sampling.

A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined. The combination of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled units according to their probability of selection. Example: We want to estimate the total income of adults living in a given street. We visit each household in that street, identify all adults living there, and randomly select one adult from each household. (For example, we can allocate each person a random number, generated from a uniform distribution between 0 and 1, and select the person with the highest number in each household). We then interview the selected person and find their income. People living on their own are certain to be selected, so we simply add their income to our estimate of the total. But a person living in a household of two adults has only a one-in-two chance of selection. To reflect this, when we come to such a household, we would count the selected person’s income twice towards the total. (In effect, the person who is selected from that household is taken as representing the person who isn’t selected.) In the above example, not everybody has the same probability of selection; what makes it a probability sample is the fact that each person’s probability is known. When every element in the population does have the same probability of selection, this is known as an ‘equal probability of selection’ (EPS) design. Such designs are also referred to as ‘self-weighting’ because all sampled units are given the same weight.

Nonprobability sampling is any sampling method where some elements of the population have no chance of selection (these are sometimes referred to as ‘out of coverage’/’undercovered’), or where the probability of selection can’t be accurately determined. It involves the selection of elements based on assumptions regarding the population of interest, which forms the criteria for selection. Hence, because the selection of elements is nonrandom, nonprobability sampling does not allow the estimation of sampling errors. These conditions place limits on how much information a sample can provide about the population. Information about the relationship between sample and population is limited, making it difficult to extrapolate from the sample to the population. Example: We visit every household in a given street, and interview the first person to answer the door. In any household with more than one occupant, this is a nonprobability sample, because some people are more likely to answer the door (e.g. an unemployed person who spends most of their time at home is more likely to answer than an employed housemate who might be at work when the interviewer calls) and it’s not practical to calculate these probabilities. In addition, non-response effects may turn any probability design into a non-probability design if the characteristics of non-response are not well understood, since non-response effectively modifies each element’s probability of being sampled.

Let us look at the various types of sampling under each category:

Probability Sampling

1. Simple random sampling
2. Systematic sampling
3. Stratified sampling
4. Multistage cluster sampling

Non-probability Sampling

1. Convenience sampling
2. Quota sampling
3. Judgment sampling
4. Snowball sampling

1. Probability Sampling Methods

A sampling in which every member of the population has a calculable and non-zero probability of being included in the sample is known as probability sampling. Methods of random selection consistent with both the probabilities of inclusion are used in forming estimates from the sample. The probability of selection need not be equal for members of the population. If the purpose of a research is to arrive at conclusions or make predictions affecting the population as a whole, then the choice of a probabilistic sampling approach is desirable.

1.1. Simple Random Sampling:

A sampling process where each element in the target population has an equal chance or probability of inclusion in the sample is known as simple random sampling. For ex, if a sample of 15000 names is to be drawn from the telephone directory, then there is equal chance for each number in the directory to be selected. These numbers (serial no of name) could be randomly generated by the computer or picked out of a box. These numbers could be later matched with the corresponding names thus fulfilling the list. In small populations random sampling is done without replacement to avoid the instance of a unit being sampled more than once.

The benefits of simple random sampling can be reaped when the target population size is small, homogeneous, sampling frame is clearly defined, and not much information is available regarding the population. It is advantageous in that it is free of classification error, and requires minimum advance knowledge of the population. Two striking features are the elimination of human bias and non-dependency on the availability of the element. It is seldom put into practice because of the application problem associated with it. This sampling method is generally not preferred as it becomes imperative to list every item in the population prior to the sampling and requires constructing a very large sampling frame, resulting in extensive sampling calculations and excessive costs.

1.2. Systematic Sampling:

Systematic sampling involves the selection of every kth element from a sampling frame. Here ‘k’ represents the skip interval and is calculated using the following formulae.

Skip interval (k) = population size/Sample size

Often used as a substitute to simple random sample, it involves the selection of units from a list using a skip interval (k) so that every k’th element on the list, following a random start between 1 and k, is included in the sample. For ex, if k were to equal 6, and the random start were2, then the sample would consists of 2^nd, 8^th, 14^th, 20^th …….elements of the sampling frame.

It is to be noted here that if the skip interval is not a whole number then it is rounded off to the nearest whole number. This sampling method can be used industrial operations where the equipments and machinery in the production line are checked for proper functioning as per the specifications. The manufacturer can select every k’th item to ensure consistent quality or for detection of defects. Therefore, he requires the first item to be selected at the random as the starting point and subsequently he can choose every k’th item for evaluation against specifications. It also finds its applicability while questioning people in a sample survey where the interviewer may catch hold of every 10^th person entering a particular shop. However, in every case, the researcher has to determine the skip interval and proceed thereafter. In both the cases, it is necessary to select the first item in the population in a random manner and thereafter follow the skip interval. This method is more economical and less time consuming than simple random sampling.

1.3. Stratified random sampling:

Stratification is the process of grouping the members of the population in homogenous group before sampling. It should be ensured that each element in the population is assigned a particular stratum only. The random sampling is applied within each stratum independently. This often improves the representativeness of the sample by reducing the sampling error.

The number of units drawn for sampling from each stratum depends on the homogeneity of the elements. A smaller sample can be drawn from the known to have the elements with the same value whereas sample can be drawn in much higher proportion from another stratum where the values are known to differ. This is because in the former case the information from the smaller number of respondents can be enumerated to the whole sample stratum. However in the latter case with much variability among the elements the higher elements value will keep the sampling to minimum errors to minimum value. The smaller errors may be due to groups are appreciably represented when strata are combined.

1.4. Multistage cluster sampling:

Clustering involves grouping the population into various clusters and selecting few clusters for study. Cluster sampling is suitable for conducting research studies that cover large geographic area. Once the cluster is formed the researcher can either go for one stage, two stages, or multi stage cluster sampling. In single stage, all the elements from each selected are studied, whereas in two stages, the researchers use random to select few elements from clusters. Multistage sampling involves selecting a sample in two or more successive stages. Here the cluster selected in the first stage can be divided into cluster units.

For example consider the case where a company decides to interview 400 households about the likeability of its new detergent in a metropolitan city. To minimize the resources and time researchers divide the city into separate blocks say 40, each block consist of heterogeneous units. The researcher may opt for the two stage cluster sampling if he finds that individual clusters have little heterogeneity to other clusters. Similarly a multi stage cluster sampling involves three or more sampling steps, it differs from stratified sampling that is done in cluster in contrast to elements within strata as is the case in the stratified sampling. Elements are randomly selected from each stratum in each stratum in case of stratified sampling whereas only selected clusters are studied in cluster sampling.

2. Non-probability Sampling Methods

It involves the selection of units based on factors other than random chance. It is also known as deliberate sampling and purposive sampling. For ex, a scheme whereby units are selected purposefully would yield a non-random sample. In a general sense, it is an umbrella term, which includes any sample that does not conform to the requirements of a probability sampling. Convenience sampling, quota sampling, judgment sampling and snow ball sampling are few ex’s of non-probability sampling.

2.1. Convenience Sampling:

The selection of units from the population based on their easy availability and accessibility to the researcher is known as convenience sampling. For ex, imagine a co., that surveys a sample of its employees to know the acceptance for a new flavor of potato chips that it plans to introduce in the market. This type of sampling is a typical ex of convenience sampling  as the criterion for selecting a sample is convenience and availability. Although this type of research is easy and cost effective, the findings of the sample survey cannot be generalized to the entire population, as the sample is not representative. As there is no  set criterion for selecting the sample, there is a scope for research being influenced by the bias of the researcher. As in the above ex, the researcher may conduct a sample survey involving its own employees to find whether the market, would accept the product.

2.2. Quota Sampling:

In quota sampling, the entire population is segmented into mutually exclusive groups. The number of respondents (quota) that are to be drawn from each of several categories is specified in advance and the final selection of respondents is left to the interviewer who proceeds until the quota for each category is filled. Quota sampling finds extensive use in commercial research where the main objective is to ensure that the sample represents in relative proportion, the people in the various categories in the population, such as gender, age group, social class, ethnicity, and region of residence. For ex, if a researcher wants to segment the entire population based on gender, then he would have two categories of respondents, that is, males and females. If he plans to collect a sample of 30, he may allot a quota of 15 for male and 15 for female respondents. Therefore, the researcher will stop administering the questionnaire to females after he interviews the 15^th female respondent, that is, when the quota of 15 females is filled.

Quota sampling is subject to interviewer bias that may result in:

1. The quota reflecting the population in terms of superficial characteristics.
2. The researcher selecting the respondents based on availability rather than on their suitability to the study.

2.3. Judgment Sampling:

The selection of a unit, from the population based on the judgment of an experienced researcher, is known as judgment or purposive sampling. Here, the sample units are selected based on population’s parameters. It is often noticed that companies frequently select certain preferred cities during test marketing their products. This is because they consider the population of that particular city to be representative of the total population of the country. The same is the case with the selection of specific shopping malls that according to the researcher’s judgment attract a reasonable number of customers from different sections of the society. Polling results predicted on television is also a result of judgment sampling. Researchers select those districts that have voting patterns close to the overall state or country in the previous year. The judgment of the researcher is based  on the assumption that the past voting trends of selected sample districts are still representative of the political behavior of the state’s population. For ex, certain companies test market their new product launches in cities like Mumbai and Bangalore, because the profile of these cities is representative of the total Indian population.

2.4. Snowball Sampling:

Sampling procedures that involve the selection of additional respondents are known as snowball sampling. This sampling technique is used against low incidence or rare populations. Sampling is a big problem in this case, as the defined population from which the sample can be drawn is not available. Therefore, the process sampling depends on the chain system of referrals. Suppose, SG sports Ltd., a manufacturer of sports equipment plans to survey 100 senior players through its new website for getting their feedback on the quality of its products.

However, getting track of such senior senior squash players can be very difficult, as their presence may be very rare or low. Therefore, it collects the details of the first 200 visitors to its website, to list  if any of them is a squash player or knows a squash player. If the visitor is a squash player, then he is requested to refer the names of at least 3 other players known to him. The referred names of the squash players are then called upon for further referrals and this gone on until the sample size of 100 adult players is reached. Although small sample sizes and low costs are the clear advantages of snowball sampling, bias is one of its disadvantages. The referral names obtained from those sampled in the initial stages may be similar to those initially sampled. Therefore, the sample may not represent a cross-section of the total population. It may also happen that visitors to the site or interviewers may refuse to disclose the names of those whom they know.

Sampling Errors in Research

Error is defined as , “an act, assertion, or belief that unintentionally deviates from what is correct, right, or true”. In a business research process, there is sure to be some error in the results because there is the involvement of human intelligence and the use of sampling methods that may not be always accurate. The absolute value of the difference between an unbiased point estimate and the corresponding population parameter is known as a sampling error. It arises because the data is collected from a part, rather than the whole of the population. The sampling error can be more reliable by increasing the sample size. Total survey errors are of two types: Random sampling error & non-sampling error.

1. Random Sampling Error: Random sampling error or sampling error is the difference between the sample results and the results of a census conducted by identical procedures. Although a representative sample is taken, there is always a slight deviation between the true population value and the sample value. This is because the sample selected is not perfectly representative of the test population. Therefore, a small random sampling error is evident. As the sampling error is the outcome of chance, the laws of probabilities are applicable to it. The sampling error is inversely proportional to the sample size. As the sample size increases, the sampling error decreases. Although sampling errors cannot be avoided altogether, they can be controlled through careful sample designs, large samples, and multiple contacts to assure representative response. Random sampling error represents how accurately the sample’s true mean value(x sample), is representative of the population’s true mean value(X population).
2. Non-Sampling error: Non- sampling errors also known as systematic errors occur due to the nature of the study’s design and the correctness of execution. Non-sampling error includes non-observation errors and measurement errors. Non- observational errors occur when data cannot be collected from the sampling unit or variable. Measurement errors arise from various sources like respondents, interviewers, supervisors, and even data processing systems. Non-observation error is further divided into non-coverage and non-response error. In probability sampling, each element of the population has a non-zero chance of selection into the sample. Non-coverage error occurs when an element in the target population has no chance of being selected into the sample. Non-response error occurs when data cannot be collected from the element actually selected into the sample. This may be due to the refusal of the element to cooperate because of language barrier, health limitation, or non availability of the element during the survey period. Selection of faulty sampling frame may also result in a non-sampling error. Sampling frame error is said to occur when certain non potential respondents are included in the sampling frame and certain deserving respondents are rejected.

Sample and Sampling?

Sample and Sampling

A Sampling is a part of the total population. It can be an individual element or a group of elements selected from the population. Although it is a subset, it is representative of the population and suitable for research in terms of cost, convenience, and time. The sample group can be selected based on a probability or a non probability approach. A sample usually consists of various units of the population. The size of the sample is represented by “n”.

A good sample is one which satisfies all or few of the following conditions:

1. Representativeness: When sampling method is adopted by the researcher, the basic assumption is that the samples so selected out of the population are the best representative of the population under study. Thus good samples are those who accurately represent the population. Probability sampling technique yield representative samples. On measurement terms, the sample must be valid. The validity of a sample depends upon its accuracy.
2. Accuracy: Accuracy is defined as the degree to which bias is absent from the sample. An accurate (unbiased) sample is one which exactly represents the population. It is free from any influence that causes any differences between sample value and population value.
3. Size: A good sample must be adequate in size and reliable. The sample size should be such that the inferences drawn from the sample are accurate to a given level of confidence to represent the entire population under study.

The size of sample depends on number of factors. Some important among them are:

1. Homogeneity or Heterogeneity of the universe: Selection of sample depends on the nature of the universe. It says that if the nature of universe is homogeneous then a small sample will represent the behavior of entire universe. This will lead to selection of small sample size rather than a large one. On the other hand, if the universe is heterogeneous in nature then samples are to be chosen as from each heterogeneous unit.
2. Number of classes proposed: If a large number of class intervals to be made then the size of sample should be more because it has to represent the entire universe. In case of small samples there is the possibility that some samples may not be included.
3. Nature of study: The size of sample also depends on the nature of study. For an intensive study which may be for a long time, large samples are to be chosen. Similarly, in case of general studies large number of respondents may be appropriate one but if the study is of technical in nature then the selection of large number of respondents may cause difficulty while gathering information.

Sampling is the act, process, or technique of selecting a representative part of a population for the purpose of determining the characteristics of the whole population. In other words, the process of selecting a sample from a population using special sampling techniques called sampling. It should be ensured in the sampling process itself that the sample selected is representative of the population.

• Population OR Universe: The entire aggregation of items from which samples can be drawn is known as a population. In sampling, the population may refer to the units, from which the sample is drawn. Population or populations of interest are interchangeable terms. The term “unit” is used, as in a business research process, samples are not necessarily people all the time. A population of interest may be the universe of nations or cities. This is one of the first things the analyst needs to define properly while conducting a business research. Therefore, population, contrary to its general notion as a nation’s entire population has a much broader meaning in sampling. “N” represents the size of the population.
• Census: A complete study of all the elements present in the population is known as a census. It is a time consuming and costly process and is, therefore, seldom a popular with researchers. The general notion that a census generates more accurate data than sampling is not always true. Limitations include failure in generating a complete and accurate list of all the members of the population and refusal of the elements to provide information. The national population census is an example of census survey.
• Precision: Precision is a measure of how close an estimate is expected to be, to the true value of a parameter. Precision is a measure of similarity. Precision is usually expressed in terms of imprecision and related to the standard error of the estimate. Less precision is reflected by a larger standard error.
• Bias: Bias is the term refers to how far the average statistic lies from the parameter it is estimating, that is, the error, which arises when estimating a quantity. Errors from chance will cancel each other out in the long run, those from bias will not. Bias can take different forms.

Steps in Sampling Process

An operational sampling process can be divided into seven steps as given below:

1. Defining the target population.
2. Specifying the sampling frame.
3. Specifying the sampling unit.
4. Selection of the sampling method.
5. Determination of sample size.
6. Specifying the sampling plan.
7. Selecting the sample.

1. Defining the Target Population:

Defining the population of interest, for business research, is the first step in sampling process. In general, target population is defined in terms of element, sampling unit, extent, and time frame. The definition should be in line with the objectives of the research study. For ex, if a kitchen appliances firm wants to conduct a survey to ascertain the demand for its micro ovens, it may define the population as ‘all women above the age of 20 who cook (assuming that very few men cook)’. However this definition is too broad and will include every household in the country, in the population that is to be covered by the survey. Therefore the definition can be further refined and defined at the sampling unit level, that, all women above the age 20, who cook and whose monthly household income exceeds Rs.20,000. This reduces the target population size and makes the research more focused. The population definition can be refined further by specifying the area from where the researcher has to draw his sample, that is, households located in Hyderabad.

A well defined population reduces the probability of including the respondents who do not fit the research objective of the company. For ex, if the population is defined as all women above the age of 20, the researcher may end up taking the opinions of a large number of women who cannot afford to buy a micro oven.

2. Specifying the Sampling Frame:

Once the definition of the population is clear a researcher should decide on the sampling frame. A sampling frame is the list of elements from which the sample may be drawn. Continuing with the micro oven ex, an ideal sampling frame would be a database that contains all the households that have a monthly income above Rs.20,000. However, in practice it is difficult to get an exhaustive sampling frame that exactly fits the requirements of a particular research. In general, researchers use easily available sampling frames like telephone directories and lists of credit card and mobile phone users. Various private players provide databases developed along various demographic and economic variables. Sometimes, maps and aerial pictures are also used as sampling frames. Whatever may be the case, an ideal sampling frame is one that entire population and lists the names of its elements only once.

A sampling frame error pops up when the sampling frame does not accurately represent the total population or when some elements of the population are missing another drawback in the sampling frame is over –representation. A telephone directory can be over represented by names/household that have two or more connections.

3. Specifying the Sampling Unit:

A sampling unit is a basic unit that contains a single element or a group of elements of the population to be sampled. In this case, a household becomes a sampling unit and all women above the age of 20 years living in that particular house become the sampling elements. If it is possible to identify the exact target audience of the business research, every individual element would be a sampling unit. This would present a case of primary sampling unit. However, a convenient and better means of sampling would be to select households as the sampling unit and interview all females above 20 years, who cook. This would present a case of secondary sampling unit.

4. Selection of the Sampling Method:

The sampling method outlines the way in which the sample units are to be selected. The choice of the sampling method is influenced by the objectives of the business research, availability of financial resources, time constraints, and the nature of the problem to be investigated. All sampling methods can be grouped under two distinct heads, that is, probability and non-probability sampling.

5. Determination of Sample Size:

The sample size plays a crucial role in the sampling process. There are various ways of classifying the techniques used in determining the sample size. A couple those hold primary importance and are worth mentioning are whether the technique deals with fixed or sequential sampling and whether its logic is based on traditional or Bayesian methods. In non-probability sampling procedures, the allocation of budget, thumb rules and number of sub groups to be analyzed, importance of the decision, number of variables, nature of analysis, incidence rates, and completion rates play a major role in sample size determination. In the case of probability sampling, however, formulas are used to calculate the sample size after the levels of acceptable error and level of confidence are specified. The details of the various techniques used to determine the sample size will be explained at the end of the chapter.

6. Specifying the Sampling Plan:

In this step, the specifications and decisions regarding the implementation of the research process are outlined. Suppose, blocks in a city are the sampling units and the households are the sampling elements. This step outlines the modus operandi of the sampling plan in identifying houses based on specified characteristics. It includes issues like how is the interviewer going to take a systematic sample of the houses. What should the interviewer do when a house is vacant? What is the recontact procedure for respondents who were unavailable? All these and many other questions need to be answered for the smooth functioning of the research process. These are guide lines that would help the researcher in every step of the process. As the interviewers and their co-workers will be on field duty of most of the time, a proper specification of the sampling plans would make their work easy and they would not have to revert to their seniors when faced with operational problems.

7. Selecting the Sample:

This is the final step in the sampling process, where the actual selection of the sample elements is carried out. At this stage, it is necessary that the interviewers stick to the rules outlined for the smooth implementation of the business research. This step involves implementing the sampling plan to select the sampling plan to select a sample required for the survey.

Indian Ethos For Modern Management

Indian ethos for management means the application of principles of management as revealed in our ancient wisdom brought forth in our sacred books like our Gita, Upanishads, Bible and Kuran.

There are 6 basic principles, which come to light in the holy books applicable in today’s management world. They are :

1. Each soul is a potential God
2. Holistic approach
3. Equal importance to Subjectivity/Objectivity
4. Karma yoga
5. Yogah Karmasu Kaushalam
6. Co-operation

Each Soul is a potential God

A human being has a soul, a spark of the Divine. The divine resides in the heart of a person. The Divine means perfection in knowledge, wisdom and power. Therefore a human being has immense potential power or energy for self – development. Thus human efforts can achieve even an apparently impossible goal and convert the impossible into a reality. The partnership of  God and Man can bring about extraordinary or miraculous results; only if man chooses willingly to collaborate with God and actively participates in the affairs of the society by right action under his guidance and grace. He can bring about not only personal development, harmony, happiness but also prosperity of his own organization and the society without injustice to others.

Of course here, also, God helps those who help themselves.

Holistic Approach

Holistic approach in Management is based on spiritual principle of unity, oneness, non-dual or Advaita concept. Under this principle of unity, the universe in an undivided whole where each and every particle is connected with every other particle. Thus, entire Humanity is ONE.

Such an integrated human personality of self-developed manager and worker can assure best and competent management of any enterprise, involving collective works and efforts. It will achieve perfection or excellence in whatever sector you work. This is the ideal of Indian ethos : ‘Atmano Mokshartham Jagat Hitya Cha.’ (For gaining perfection in individual life, as well as for the welfare of the world.). This is the message for all managers and workers given by the Indian ethos for management.

Equal Importance to Subjectivity / Objectivity

Indian ethos for management distinguishes between subject and object. Subject is subtle and intangible. Object is concrete and tangible or visible.

We have the concept of the third eye, the eye of wisdom. It can see even that which the normal two eyes cannot. It can see the intangible i.e. invisible.

Human and ethical values or qualities such as courage, vision, social awareness, fearlessness, integrity, pure and clear mind, truth, etc. are subjective, subtle and intangible concepts. These subjective or subtle qualities are as important as money, materials, machines, information or data as well as human skills. Inner resources of human beings are more powerful than external resources.

Creator is subjective. Creation is objective. Insight i.e., creator is more important than Outsight i.e., creation. Our body, senses, intellect, mind,etc., are objective, seen, tangible. But our soul atman is unseen, intangible, subtlest and subjective. Hence, wisdom manager/ worker is much more important and valuable than knowledge manager/ worker.

Therefore, manager must develop his third eye, ‘Jnana Chakhu’ , the eye of Vision intution, insight, foresight and such other divine qualities or values. This is the essence of Indian ethos for management.

Karma Yoga

It is yoga of selfless service to others. Karma Yoga is all about identifying your priorities and trying to achieve them. Also, a person should have accountability i.e. he should always hold only himself responsible for whatever goes right or wrong. This brings about the union of human being with the Divine.

Gita says that do your duty without ego and without calculations of gain or loss. One should believe in Nishkama Karma i.e. fruits of work should not be thought of while performing the duty.

The memorable words of Gita are “ To work only you have the right and you have no right to the fruits of work”. However, this does not mean that one should work day and night and the returns that he gets should be almost negligible. What the Gita tries to say is that let not the fruits of action motivate you as they might just divert your attention from work. When you are doing a job, put your heart and soul in to it. One has no control over the future hence never waste your present in useless dreams of future hopes and fears of present actions.

Why Do I Work?

1. For my own salvation and personal growth.
2. For the good of the world.

The inner joy of doing something gives the doer a sense of achievement and also helps him in respecting himself more than he used to. Money is important but running behind money all the time leads to tension, stress and total loss of peace. Self-motivation can assure self-development. When work is performed without passion, hatred, arrogance and desire we have individual development and social good.

Indians always had two great truths of successful, harmonious and happy life:

1. Divinity of life can be used through self-development for personal growth and also for social welfare.
2. I cannot cheat you and nature without cheating myself. Working for harmony and peace results in a sense of fulfillment.

It is becoming clear that a chapter, which had a Western beginning in business management, will have to have an Indian ending. Karma Yoga is not just meant for the common man but also for leaders and managers who if act responsibly will in turn influence the behavior of a number of people.

Karma Yoga thus is a good pathway for:

1. Self-purification and Self-development.
2. Individual growth and welfare.
3. Collective growth and welfare.
4. Minimum play of passion, jealousy, hatred.
5. Team spirit and Teamwork.
6. Autonomous management, minimum control and supervision.
7. Manager acts as a Mentor.
8. Self-motivation.
9. Perfection.
10. All round happiness and prosperity.
11. Skills and values united.
12. Conflicts resolved by integration.

Yogah Karmasu Kaushalam

Yoga means excellence at work. Seek to perform your assigned duty or work in an excellent manner. Kaushalam denotes doing work with devotion and without attachment i.e. without being a work-a-holic.  Such detatched attitude enhances its values and improves the concentration and skill of the worker. You work with smartness, determination and ability. Your head, heart and soul co-operate with your hands. You do not hanker over the fruits of action. You have no anticipation of reward, or personal gain. You become a tool of God to perform the work. Any work carried out with full concentration, dedication and with all abilities that a person has, becomes valuable and the person also becomes valuable to others as well as to society. In total quality management(TQM) Karma Yoga and Yogah Karmasu Kaushalam provide valuable contributions. Under this slogan we have one hundred percen concentraion coming from within. The extrinsic incentives e.g., money, other perks, etc. play a very minor role as motivators.

Co-Operation

Healthy competition is a powerful motivator for excellence and success, especially business success. The idea of cut-throat competetion is founded on the concept of ‘struggle for existence’ and survival of the fittest.

Indian ethos says that for human beings the royal road is co-operation as a powerful motive for team work. We are human beings having mind and power of discrimination.

The Gita says : “ By co – operation and mutual help all shall achieve the highest human welfare.” Unity is strength. Even in the holistic approach, we stress the co-operation integration, synthesis and team – spirit for extraordinary performance, for enduring harmony and peace, because in our hearts chamber is living the pure conciousness of the Divine, i.e., Purnatman. Peaceful co-excistence, harmony, not struggle is the rule. Indian insight endorses this in the management of any enterprise.

Excessive competetion at work can destroy many young people and our social life. Co-operation, united efforts and striving for success leads to all round prosperity and success leads to all round prosperity and success in any field of human enterprise.

Features of Indian Ethos and Insight

• Divinity of a human being is not merely a notion but a truth which can be experienced in the stillness of the mind.
• Balance is the keynote of Indian thought. We have synthesis, harmony between the dual concepts.
• The Individual is the central focus.
• Divine element in the individual is only a portion of the universe of the universal or cosmic consciousness.
• Gives greater emphasis on values, human and ethical. Knowledge is not power.
• Indian ethos are based on Indian scripture. Indian thoughts provide eternal knowledge
• All work is worthy and honorable.
• Emphasis on duties and responsibilities.

Power And Politics?

Power and Politics

Objectives:

• The concept of power
• Sources of power
• Interdepartmental power
• Illusion of power
• Political strategies and tactics
• Ethics, power and politics
• Using power to manage effectively.


Power is a pervasive part of organizational life, used by managers to accomplish goals and to strengthen
their own positions. Managers manipulate power to accomplish goals and strengthen their own
positions. Success or failure in using power depends on understanding what it is, how and when to use
it, and understanding its consequences.
The Concept of Power
Power and influence.
Every interaction and social relationship in an organization can be interpreted as an exercise of
power.Influence is a transaction in which person B is induced by person A to behave in a certain way.
Person A has power over person B to the extent A can get B to do something that B would otherwise not do.
The difference between power and influence is : Power represents capability while Influence is the exercise of that capability.Power is not an attribute; it is an aspect of a relationship.
Contrasting Leadership and Power
Leadership focuses on goal achievement. It requires goal compatibility with followers and focuses influence downward.
Power is used as a means for achieving goals. It requires follower dependency. It is used to gain lateral and upward influence. Using power.
Obtaining, maintaining, and using power are all essential to influencing behavior. Dependency is the extent to which something person A wants can be effected by person B determines A's dependence on B; B's power over A depends on how much A needs what B controls.
Where Does Power Come From?
A .Interpersonal power—French and Raven's five power bases:
1. Legitimate power—refers to the ability to influence others because of the position one holds in
the organization. It is also called authority, or the right to command. Characteristics of organizational
authority are: I. It is invested in a person's position.
ii. It is accepted by subordinates. iii. Authority is used vertically; flows from the top down.
Zone of indifference ‐possessing formal power, or authority, does not mean that all orders will be followed. Orders will be followed if they are acceptable to the subordinate. They lie within the zone of indifference. Unacceptable orders, outside the zone of indifference, will not be readily followed. The zone of indifference may be wider or narrower, depending on sources of power other than authority. It may be shaped by cultural factors.
2. Reward power—based on a person's ability to reward a follower for compliance. It occurs when someone possesses a resource that another person wants and will exchange that resource for certain behavior. It supports legitimate power.
3. Coercive power—the power to punish. It is based on fear. It can come from legitimate. It can come informally, e.g., fear of rejection by coworkers.
4. Expert power—based on an individual's special and valued expertise. The lower the
substitutability of the expertise, the greater the expert's power.
5. Referent power—based on an individual's charisma (behavioral style).
Legitimate, reward, and coercive power come from the organization; expertise and referent power reside in the individual and are derived from personal characteristics. One or more of the five bases of power can be used in combination. The use of the type can affect the other power bases (e.g., the use of coercive power can reduce an individual's perceived referent and legitimate power).Research suggests that legitimate and reward powers are positively related; coercive power is negatively related to legitimate and reward power.
B.Power in Groups:
1. Coalitions: are Clusters of individuals who temporarily come together to achieve a specific purpose. It seeks to maximize their size to attain influence. Coalition seeks a broad and diverse constituency for support of their objectives. It occurs more frequently in organizations with high task and resource inter‐dependencies. it also occur more frequently if tasks are standardized and routine.
2. Sexual Harassment: Unequal Power in the Workplace.Unwelcome advances, requests for sexual favors, and other verbal or physical conduct of a sexual nature in a work environment reasonably perceived as hostile or abusive.
C.Power in Organization
1. Structural Power.Power is frequently determined by organizational structure. Structure is the control mechanism by which the organization is governed. Structure allocates decision‐making discretion to various positions, affects the patterns of communication and the flow in information within a system. Structure creates formal power by specifying certain individuals to perform specific job tasks and make certain decisions.
Other forms of structural power exist because of:
a. Resources‐Power stems from access to resources, information and support and the ability to get cooperation in doing necessary work.A top manager has power over a lower‐level manager because he/she controls the lower‐level manager's resources.
b. Decision making power—how much an individual or subunit influences decision‐making affects the amount of power acquired.
c. Information power—power accrues to those with access to important information (the basis for decisions).
2. Interdepartmental power Subunits/departments can gain power by controlling strategic
contingencies—events that are critical in accomplishing organizational goals. Relevant to strategic contingencies, subunit power is influenced by subunit ability to cope with uncertainty, and its centrality and substitutability.
Coping with uncertainty—the three types of coping activities are:
a. Coping by prevention—reducing the probability that some problem will arise.
b. Coping by information—using information (e.g., forecasting) to predict if, when, and impact of uncertainties (making them more certain).
c. Coping by absorption—directly dealing with uncertainty as it impacts the subunit.
Centrality—the degree to which a subunit is central to the organization's workflow (often  measured bythe degree to which the subunit's work contributes to the organization's final output).Research shows centrality can be a significant source of subunit power.Subunits with centrality substantially affect other units.
Substitutability—the ability of other subunits to perform the activities of a particular subunit. The lower a unit's substitutability, the greater its power.
3. EmpowermentConger and Kanungo define it as "a process of enhancing feelings of self‐efficacy among organizational members through the identification of conditions that foster powerlessness and through their removal by both formal organizational practices and informal techniques of providing efficacy information."
Brownwell notes five reasons why empowerment is not universally embraced:
• Managers fear the loss of power, control, and authority.
• Employees are not able to make responsible decisions.
• Empowering employees was attempted before and it failed.
• Sharing proprietary information means leaking ideas, plans, and knowledge to competitors.
• Not everyone wants to be empowered.
Stages of empowerment
a. Identifying organizational conditions that lead to members' feelings of powerlessness.
b. Implementation of empowerment strategies, e.g., participative management, and merit pay.
c. Providing information to subordinates to create feelings of self‐efficacy.
d. Feelings of empowerment by organization members.
e. Empowerment feelings translate into behaviors.
Empowerment in self managed teams.
Empowerment is fostered two ways in SMTs:
i. Decision making control is delegated to the team.
ii. Team members acquire additional skills, knowledge, and experiences.
Power Tactics
Ways in which individuals translate power bases into specific actions
Influence Tactics
• Legitimacy
• Rational persuasion
• Inspirational appeals
• Consultation
• Exchange
• Personal appeals
• Ingratiation
• Pressure
• Coalitions
Preferred Power Tactics by Influence Direction
Upward influence‐rational persuasion Downward influence‐rational persuasion,inspirational appeals, pressure, consultation,ingratiation,exchange, legitimacy Lateral influence‐rational persuasion, consultation,ingratiation,exchange,legitimacy,personal appeals,
coalition
Factors Influencing the Choice and Effectiveness of Power Tactics
• Sequencing of tactics‐ Softer to harder tactics work best
• Skillful use of a tactic
• Relative power of the tactic user ‐Some tactics work better when applied downward or upward
• The type of request attaching to the tactic Is the request legitimate? How the request is
perceived? Is the request consistent with the target’s values?
• The culture of the organization‐Culture affects user’s choice of tactic
• Country‐specific cultural factors‐Local values favor certain tactics over others
Illusion of Power
Some individuals can be perceived as having more power than they really do. They create an illusion of
power.Individuals perceived to be powerful could substantially influence others.
Politics: Power in Action
Political Behavior
Activities that are not required as part of one’s formal role in the organization, but that influence, or attempt to influence, the distribution of advantages or disadvantages within the organization Legitimate Political Behavior‐Normal everyday politics Illegitimate Political Behavior‐Extreme political behavior that violates the implied rules of the game
Politics Is in the Eye of the Beholder (some examples)
Political label Effective management label
Blaming others Fixing responsibility
Kissing up Developing working relationship
Apple polishing Demonstrating responsibility
Passing the buck Delegating authority
Covering your rear Documenting decisions
Source: Based on T. C. Krell, M. E. Mendenhall, and J. Sendry, “Doing Research in the Conceptual Morass
of Organizational Politics,” paper presented at the Western Academy of Management Conference,
Hollywood, CA, April 1987.
Factors that Influence Political Behaviors
Individual factors‐high self monitors, internal locus of control,high Mach personality, Organizational
investment, perceived job alternatives, expectation of success
Organizational factors‐ reallocation of resources, promotion opportunities, low trust, role ambiguity, unclear performance evaluation system, zero‐sum reward practices,democratic decision making,high performance pressures, self serving managers.
Political behaviour leads to favourable outcome like rewards and averted punishments.
Employee Responses to Organizational Politics
Perception of organizational politics leads to decreased job satisfaction, increased anxiety and stress,
increased turnover and reduced performance.
Political Strategies and Tactics
Politically‐oriented behavior (often engaged in by individuals and subunits):
1. Usually lies outside the legitimate power system.
2. Is designed to benefit an individual/subunit often at the organization's expense.
3. Is intentional and designed to acquire/maintain power.
Research on Power
In a study of political behavior of 142 purchasing agents, four primary political tactics were identified:
a. Rule evasion—evading the formal purchasing procedures.
b. Personal‐political—using friendships to facilitate or inhibit the processing of an order.
c. Educational—attempting to persuade engineering to think in purchasing terms.
d. Organizational—trying to change the formal/informal interaction patterns between engineering
and purchasing.
In a study of political behavior in the California electronics industry, 87 managers were questioned about organizational political behavior.13 characteristics were identified as important of which Articulateness, sensitivity, and social adeptness were the leading factors. Though agreement was fairly high among managers, there were some differences depending on their level in the organization, probably because of their different perspectives.Ambitiousness was seen as more important by CEOs than by staff and
managers.Being logical was seen as more important by staff and managers than by CEOs.
Playing politics—politics and political behavior exist in every organization.
Game playing‐According to Mintzberg, many individuals are adept at playing political games. Mintzberg identifies 13 types of political games played by managers and nonmanagers to accomplish various goals:
i. To resist authority (the insurgency game).
ii. To counter the resistance to authority (the counterinsurgency game).
iii. To build power bases (the sponsorship game and coalition‐building game).
iv. To defeat rivals (the line‐versus staff game) and bring about organizational change (the whistleblowing
game).
The insurgency game—played to resist authority (e.g., ordered to reprimand an employee, a foreman
does it ineffectively).
Political influence tactics.
Political tactics:
a. Consultation—seeks support through participation.
b. Rational persuasion—attempts to show a "logically" best course of action.
c. Inspirational appeals—appeals to values and ideals.
d. Ingratiating tactics—designed to make one obligated to another.
e. Coalition tactics—seeks help of others to persuade you.
f. Pressure tactics—uses demands, intimidation, or threats to gain support.
g. Legitimating—used to gain support by claiming the authority to ask for your support.
h. Personal Appeals—used to appeal to your feelings of loyalty and friendship in order to gain your
support.
Exchange tactics—promises that compliance will lead to rewards.
Some tactics work better in influencing upward, some downward, and some laterally. Managers prefer
consultation, rational persuasion, and inspirational appeals.Least appealing were pressure tactics,
upward appeals, and exchange tactics.
Defensive Behaviors‐reactive and protective behaviours to avoid action, blame or change
Avoiding Action
• Overconforming
• Buck passing
• Playing dumb
• Stretching
• Stalling
Avoiding Blame
• Buffing
• Playing safe
• Justifying
• Scapegoating
• Misrepresenting
Avoiding Change
• Prevention
• Self‐protection
Impression management—action taken to control the impressions that other form of an individual.It is an universal phenomenon. Effective impression management can be useful, e.g., in an employment interview. It does not necessarily imply that a false impression is being conveyed.Self‐handicapping refers to any action taken in advance of an outcome that is designed to provide either an excuse for failure or a credit for success. It designed to make the best of an as yet undetermined outcome, e.g., the quarterback who says he has a sore arm prior to the game.
Some Impression Management Techniques are:
Conformity Agreeing with someone else’s opinion in order to gain his or her approval.
Excuses Explanations of a predicament‐creating event aimed at minimizing the apparent severity of the predicament.
Apologies Admitting responsibility for an undesirable event and simultaneously seeking to get a pardon for the action. Acclamations Explanation of favorable events to maximize the desirable implications for oneself. Flattery Complimenting others about their virtues in an effort to make oneself appear perceptive and likable.
Favours Doing something nice for someone to gain that person’s approval.
Association Enhancing or protecting one’s image by managing information about people and things
with which one is associated.
Ethics, Power, and Politics
Criteria to be considered in making ethical decisions:
1. Utilitarian outcomes—the greatest good for the greatest number.
2. Individual rights—respect rights of free consent, free speech, freedom of conscience, privacy,
and due process.
3. Distributive justice—behave equitably and fairly, not arbitrarily.
When a potential behavior cannot pass the three criteria test, it may still be ethical if it passes the
criterion of overwhelming factors: justify behaviors by:1.Overwhelming factors in the nature of the
situation.2.Conflicts within the criteria 3.Incapacity to employ the first three criteria.
Using Power to Manage Effectively
A. Recognizing that there are multiple interests in virtually every organization.
B. Knowing what position relevant individuals and groups hold with respect to
issues important to oneself.
C. Understanding that to get things done one must have power, and in the case of
those who oppose , one must have more power than they do.
D. Recognizing the strategies and tactics through which organizational power is
develop and used.
Questions
1. Discuss the concept of power. What are the sources of power in an organization‐discuss with
examples.
2. What is politics? What are the factors that influence political behaviour? Elaborate the Political
strategies and tactics prevalent in organization.
3. Discuss the relation between Ethics, power and politics. How can power be used to manage
effectively?
4. Write short notes on (a)Defensive techniques (b) Impression Management.