INDIAN INSTITUTE OF PLANNING AND MANAGEMENT

Project on Exploratory Research & Secondary Data

New Delhi

Submitted to PROF. Manvinder Singh

Submitted By:

Ashish Goel

Gaurav Mehta

Durairaj DS

Ashish Kumar Mundra

Devjyoti Mohanty

Batch: SPRING-SUMMER/2010-12/SA2

ACKNOWLEDGEMENT

I acknowledge with gratitude and appreciation, my indebtedness to my

mentor & guide, Prof Manvinder Singh for allowing our team to work

on this project, “Exploratory Research Design & Secondary Data” I

also thank him for the ideas and basic concepts he delivered and shared

with us, as they helped us a lot in accomplishing this project..

It gave me enormous gratification to articulate my thankfulness and heart

full sense of indebtedness to all my team mates Ashish Goel & Team.

I also put forward my heartiest thanks to Mr. Vishnu K.R, Assistant Vice President, Front Line Focus and Mrs. Priya Vaidyanathan, Manager- Operations for their great support in completion of this project.

Chapter 1 Introduction 1.1 Executive summary

Chapter 2 Research Methodology

Chapter 3 Exploratory Research Design

Chapter 4 Difference between Primary & Secondary Data

Chapter 5 Classification of Secondary Data

Chapter 6 Conclusion to Market Research

Chapter 1

INTRODUCTION

1.1 Executive Summary

This project is an attempt to give knowledge about any company. It aims to make its reader well versed with each and every aspect of Research.

It throws light on the following:-

1. In 1st Chapter you will find the objective of doing the project on Introduction.

2. In 2nd Chapter of this report, you will find that the research methodology of the report is mentioned.

3. In 3rd chapter on Exploratory Research Design.

4. In 4th Chapter you will find on Difference between Primary & Secondary Data.

5. In 5th Chapter you will find on Classification of Secondary Data.

6. In 6th Chapter you will find on Conclusion to Market Research.

This project is overall an attempt to make you aware or to cover every possible aspect of Exploratory Market Design & Secondary Data.

Chapter 2

Research

Methodology

RESEARCH METHODOLOGY

Meaning of Research

Redman and Moray define research as a “systemized effort to gain new knowledge.” Some people consider research as a movement, a movement from the known to the unknown.Research is an academic activity and as such the term should be used in a technical sense. According to Clifford Woody, research comprises defining and redefining problems, formulating hypothesis or suggested solutions; collecting, organizing and evaluating data; making deductions and reaching conclusions; and at last carefully testing the conclusions to determine whether they fit the formulating hypothesis.

Objectives of Research 

The purpose of research is to discover answers to questions through the application of scientific procedures. The main aim of research is to find out the truth which is hidden and which has not been discovered as yet. Though each research study has its own specific purpose but the research objectives can be listed into a number of broad categories, as following:- 1.   To gain familiarity with a phenomenon or to achieve new insights into its Studies with this object in view are termed as exploratory or formulative research studies.2.  To portray accurately the characteristics of a particular individual, situation or a group. Studies with this object in view are known as descriptive research studies.3.   To determine the frequency with which something occurs or with which it is associated with something else. Studies with this object in view are known as diagnostic research studies.

Research Methodology 

Research methodology is a way to systematically solve the research problem. It may be understood as a science of studying how research is done scientifically. In it we study the various steps that are generally adopted by a researcher in studying his research problem along with the logic behind them. It is necessary for the researcher to know not only the research methods or techniques but also the methodology. 

Data Source

The data can be collected from two sources, i.e. Primary and Secondary. I have collected the entire data of this project on Exploratory Research from SECONDARY SOURCES like websites, books, newspapers and magazines.  Research Methodology involves research plan that has following major steps:

1. Defining the Data Source

2. Research Approach

3. Data Analysis

1. Defining the Data Source

The data required for familiarizing with the role of Exploratory Research & Secondary Data, has been collected from the web sites, journals & company individuals.

2. Research Approach

The research was carried out under following major steps:

LEARNING ABOUT THE COMPANY

At the very outset, the information regarding the origin, developments, the present way of working and the current strategy of Major Companies was gathered and thoroughly analyzed which gave the researcher an insight into many company’s profile and

organizational structure was made with the help of company’s web sites, company’s manuals , brochures and other relevant published materials. This helped the researcher to understand the present working scenario and gain familiarity with the organization’s strategic moves.

COLLECTION OF DATA

Under this step the secondary data was collected though company’s website, company’s manuals, brochures and other relevant published material.

3. Data Analysis

After the data about the developments and its future goals had been collected, it was analyzed methodically. The importance and the purpose of move was identified to assess the benefits and the risks faced by the company in the industry.

Chapter 3

Exploratory

Research Design

Exploratory research provides insights into and comprehension of an issue or situation. It should draw definitive conclusions only with extreme caution. Exploratory research is a type of research conducted because a problem has not been clearly defined. Exploratory research helps determine the best research design, data collection method and selection of subjects. Given its fundamental nature, exploratory research often concludes that a perceived problem does not actually exist.

Exploratory research often relies on secondary research such as reviewing available literature and/or data, or qualitative approaches such as informal discussions with consumers, employees, management or competitors, and more formal approaches through in-depth interviews, focus groups, projective methods, case studies or pilot studies. The Internet allows for research methods that are more interactive in nature: E.g., RSS feeds efficiently supply researchers with up-to-date information; major search engine search results may be sent by email to researchers by services such as Google Alerts; comprehensive search results are tracked over lengthy periods of time by services such as Google Trends; and Web sites may be created to attract worldwide feedback on any subject.

The results of exploratory research are not usually useful for decision-making by themselves, but they can provide significant insight into a given situation. Although the results of qualitative research can give some indication as to the "why", "how" and "when" something occurs, it cannot tell us "how often" or "how many."

Exploratory research is not typically generalized to the population at large.

Social Science

In many social science circles, exploratory research "seeks to find out how people get along in the setting under question, what meanings they give to their actions, and what issues concern them. The goal is to learn 'what is going on here?' and to investigate social phenomena without explicit expectations." (Russell K. Schutt, Investigating the Social World, 5th Ed) This methodology can is also at times referred to as a 'grounded theory' approach to 'qualitative research' or 'interpretive research', and is an attempt to 'unearth' a theory from the data itself rather than from a pre-disposed hypothesis.

Earl Babbie identifies three purposes of social science research. The purposes are exploratory, descriptive and explanatory. Exploratory research is used when problems are in a preliminary stage. Exploratory research is used when the topic or issue is new and when data is difficult to collect. Exploratory research is flexible and can address research questions of all types (what, why, how). Exploratory research is often used to generate formal hypotheses. Shields and Tajalli link exploratory research with the conceptual framework working hypothesis.

Applied Research

Applied research in administration is often exploratory because there is need for flexibility in approaching the problem. In addition there are often data limitations and a need to make a decision within a short time period. Qualitative research methods such as case study or field research are often used in Exploratory research.

There are three types of objective in a marketing research project.

Exploratory Research or Formulative Research

Descriptive research

Causal research

Exploratory Research or Formulative Research 'The objective of exploratory research is to gather preliminary information that will help define problems and suggest hypotheses.

Descriptive Research 'The objective of descriptive research is to describe things, such as the market potential for a product or the demographics and attitudes of consumers who buy the product.

Causal Research 'The objective of causal Research is to test hypotheses about (BLANCO) (STEEN) cause-and-effect relationships.

Example of an Exploratory Research

Exploratory Research

Objective: To verify whether the statement “poorer sales” is valid.

Design: We used secondary data analysis as the tool for Construct development of the construct “Poorer Sales” and also for better understanding of the above research objective.

Implementation: We collected sales data from the company’s sales in charge for Bihar-Jharkhand region and compared it with the sales in the Eastern and Central UP Region.

Eastern and Central UP Region

Bihar-Jharkhand Region

2000 - 2001 100% 14%

2001 -2002 100% 14%

2002-2002 Sept (6 months) 100% 13%

Table 1.1 Comparative sales of Drug X in Bihar-Jharkhand Region and

eastern- Central UP. Region*

Eastern and Central UP Region

Bihar-Jharkhand Region

Urban Population 1.55 Cr 1.13 CrNo of towns contributing to 90% of Urban population(Ease of reach)

206 119

Market Potential Index 0.52 0.41

Table 1.2 Market size comparisons between Bihar-Jharkhand Region and

Eastern- Central U.P. Region#

From table 1.2 we can say that sales in Bihar-Jharkhand region should be in the region of 60-70% of the sales of eastern and central UP region. But from table 1.1 we can see that the sales are just about 14%. This means that the sales potential of Bihar-Jharkhand region is not achieved.

Objective: Reasons for poorer sales in Bihar-Jharkhand region compared to eastern-central UP region.

Design: The tool used was Pilot survey of the consumers and retailers. Pilot survey was chosen because the product was not a high involvement one. Also we felt that focus group and depth interviews may not provide us with insights to justify the cost involved.

Implementation: Pilot survey of 11 retail shops and 28 customers. We asked them questions, which were different for retailers and consumers.

We asked 5 retailers in Sakchi, 4 in Bistupur, and 2 in Sonari. Customers were selected from the same regions. Some of them were customers of the drug retailers and a few we chosen at random from the street. We also chose about 10 students from XLRI for the survey.

Observations from the Pilot Survey from consumers:

Preference for taking the drugs prescribed by the doctors

Preference for drugs, which do not cause sedation

People do not normally consider cold as a serious issue. Only if it interferes with their functioning or doesn’t get cured in a week or so they take medication after consultations with doctor.

They feel that there is not much difference between drugs for headache and cold. They take the same drug for all once they find it effective.

They make choices of drugs based more on friends or families’ opinion rather than advertisements.

Preference for other OTC drugs compared to Drug X

They do not think of Drug X when they have Headache or Cold.

They do not compare prices of various cold tablets before purchasing, as the difference is not perceivable enough.

Observations from Pilot Survey of Retail Shops

Drug X is not asked for by name by consumers

Customers prefer prescription drugs like cetrizine to OTC drugs. These prescription drugs are asked for by name even without prescription.

The Margins they get for drug X are relatively less compared to other OTC drugs.

Some of them don’t keep drug X, as the supply is not regular

Research Questions

From the results of the pilot survey we framed the following research questions

1. Are lower margins given by distributors a reason for poorer sales of Drug X in Bihar-Jharkhand region compared to eastern-central UP region?

2. Is the habit of treating common cold as not serious enough to take medicine immediately a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region?

3. Is no top of the mind recall a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region?

4. Is the preference for prescription drugs a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region?

5. Is distribution limitation reasons for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region?

Hypothesis formulation

The hypotheses corresponding to these questions are

Hypothesis 1:

H0: A smaller margin given by distributors is not a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

H1: A smaller margin given by distributors is a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

Hypothesis 2:

H0: The habit of treating common cold as not serious enough to take medicine immediately is not a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

H1: The habit of treating common cold as not serious enough to take medicine immediately is a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

Hypothesis 3:

H0: Not having top of mind recall is not a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

H1: Not having top of mind recall is a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

Hypothesis 4:

H0: Preference for prescription drugs is not a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region

H1: The preference for prescription drugs is a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region

Hypothesis 5:H0: Distribution limitation is not a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

H1: Distribution limitation is a reason for poorer sales of drug X in Bihar-Jharkhand region compared to eastern-central UP region.

Chapter – 4

Difference between

Primary &

Secondary Data

Primary vs. Secondary data Primary data: new data specifically collected in current research

project - researcher is the primary user. Secondary data: data already exist - collected for some other

(primary) purpose - researcher is the secondary user. Secondary data analysis: Chapter 12

Uses/roles of secondary data Background/preparation Complementary – comparison/validation of primary data collected Whole basis of project – re-analysis of data Context setting (in report)Use of Secondary Analysis: Economics, Accounting, Political Science, Geography, History

Advantages and Disadvantages of Secondary Data (SLT, 2003, Section 7.4)Advantages Fewer resource requirements Unobtrusive Often longitudinal Means of comparison with

primary data Can provide contextual data Can result in unforeseen

discoveries Permanence of data – often

stored in archivesDisadvantages Collected for an alternate

purpose May not match your own Difficulty of access Expense Degree of aggregation Data quality

Types of Secondary DataData already collected for some other purpose1. DocumentaryWritten: Organisation documents: personnel records, safety audits Reports: company, government bodies, committees Public documents: books, journals, newspapersNon-written: Television and radio Video and audio tapesCompany/Organization data: INTERNALFinancial accounts; Sales data; Prices; Product development; Advertising expenditure; Purchase of supplies; Human resources records; Customer complaint logsCompany/Organization data: EXTERNALCompany information is available from a variety of sources, e.g.:Biz@advantage; www.whowhere.com; www.hoovers.com – 12,000 companies, USA & others; Australian Stock Exchange (www.asx.com.au); AGSM Annual reports; Compass, Dun & Bradstreet (www.dnb.com), Fortune 500Possible documentary data?Journals and books; Case study materials; Committee minutes; AIRC documentation; Hansard transcripts; Mailing list discussions; Web-site content; Advertising banners

2. Multiple Sources (SLT, 2003)Geographically-based: FT and IMF country reports; ABS Basic Community ProfilesTime-series based: Industry statistics and reports: Employer associations (ACCI, VECCI, AIG) Government publications: Australian Bureau of Statistics; Bureau of Labour

Statistics (U.S.A.)

ABS Subject/Area codesSubject Geographical areas1 General 0 Australia2 Census of population and housing 1 New South Wales3 Demography 2 Victoria4 Social statistics 3 Queensland5 National accounts, international trade & finance 4 South Australia6 Labour statistics and prices 5 Western Australia7 Agriculture 6 Tasmania8 Secondary industry and distribution 7 Northern Territory9 Transport, tourism 8 Aust. Capital Territory

9 External Territories

3. Censuses and SurveysCensuses Australia: 2001 Census data (http://www.abs.gov.au ) International: New Zealand: http://www.stats.govt.nz/ U.S.A.: http://www.stats-usa.gov IPUMSI: http://www.hist.umn.edu/~rmccaa/IPUMSI/On-going and recurring surveys Australian Bureau of Statistics: http://www.abs.gov.au Reserve Bank of Australia: http://www.rba.gov.au/Statistics/ Statistics New Zealand: http://www.stats.govt.nz/ The World Bank: http://www.worldbank.org/data/Ad-hoc surveys Social Science Data Archive (ANU): http://ssda.anu.edu.au The Data Archive (Uni. of Essex, UK): http://www.data-archive.ac.uk/ Interuniversity Consortium for Political and Social Research:

http://www.icpsr.umich.edu Qualitdata: http://qualidata.essex.ac.uk/Secondary Data Sets Longitudinal Survey of Australian Youth: Australian Centre for Educational

Research, 1989 – Present, Progress from 15 through to post university Business Longitudinal Survey: 5100 Australian small-to-medium enterprises, 5

year (1994-98) panel study conducted by ABS World Values Survey: 60 countries, every 5 years (approx.), Attitudes towards

various social, economic and political issues

Considerations with Secondary Data Suitability: Intended for another purpose; Content versus external validity;

Reliability Measurement bias Original research methodology Cost and time

Example Research Problem What distinguishes individuals who join trade unions from those who do not? What distinguishes individuals who leave trade unions from those who do not? Four possibilities: join, leave, stay, go Core research issues: Union instrumentality and ideology; Work and life

context; Economic situation; Family history; Related attitudesChoice of Data Australian Workplace Industrial Relations Survey: 19000 employees in 2000

workplaces National Social Science Survey: 1200 respondents in both 1990 and 1996;

makes it possible to assess change over time Account for differences in: Work, Family, Income, Location, Attitudes

Advantages of secondary data1. Time and economy Generally inexpensive in comparison to collecting one's own data High initial cost: AWIRS 1995 budget of $3 mil. Savings from re-use and re-cycling Often free for academic researchers or can be acquired for tens or hundreds of

dollars E.g. post-graduate students are typically precluded from collecting national

samples because of cost.2. Methodological Advantages Large-scale, representative samples: Longitudinal, broad geographical Strong on external validity (the degree of confidence with which findings about

a sample can be generalised to a population) Often generated by well resourced teams that have access to specialists, for

example, high level sample design expertise Does not normally require approval from ethics committees

Goodness of MeasuresReliability

A matter of whether a particular technique, applied repeatedly to the same object, yields the same result each time.

How stable and consistent is the measuring instrument?Validity The extent to which an empirical measure adequately reflects the real meaning

of the concept under consideration. Are we measuring the right thing?

Reliability Stability: refers to the ability of a measure to maintain consistency over time,

despite uncontrollable testing conditions or the state of the respondents themselves

Internal consistency: indicates how well the items ‘hang together as a set’ and can independently measure the same concept, so respondents attach the same overall meaning to each of the items

Forms of validity Face validity: That quality of an indicator that makes it seem a reasonable

measure of a variable. Criterion related validity: The degree to which a measure relates to some

external criterion. For example, the validity of the VCE tests is shown in their ability to predict the college success of students.Construct validity: The degree to which a measure relates to other variables as expected within a system of theoretical relationships.

Content validity: Refers to how much a measure covers the range of meanings included within a concept.

Evaluating potential secondary data sources1. Assess overall suitability of data to research question(s) and objectives –

measurement validity, coverage2. Evaluate precise suitability of data for analyses needed to answer research

question(s) and to meet objectives – validity, reliability, measurement bias3. Judge whether to use data based on an assessment of costs and benefits in

comparison with alternative sources4. If you consider the data are definitely unsuitable DO NOT proceed beyond this

stage

Conclusions

Secondary data can save time, money and effort However, it needs to be carefully assessed for suitability Be sure to check the research methodology used to collect the data

Use of secondary data

Description of the technique

'Secondary' is used to refer to data that the evaluator was not responsible for directly collecting (as opposed to primary data which is generated by the evaluation itself). Usually, use of previously collected data to evaluate programmes is a use other than the original intent of the data.

In the context of data libraries and archives, 'data' usually means computer-readable data, since data held in this form is more easily made available for additional research and more easily interrogated. Examples include censuses and large surveys carried out by governments, and administrative data (see below). However, in the current context, 'data' is taken to include the whole range of information, since for evaluation purposes it is generally advisable to use as much existing information as possible. Information sources could also include reports and studies of the area under consideration, documents related to the life and management of the programme, information on similar programmes, and so on

The three main sources of secondary information relating to social and economic development programmes are:

Programme management documents; Statistical sources; Past evaluations and research.

The purpose of the technique

Secondary data is likely to provide a wealth of information for a range of purposes, depending on the circumstances for the evaluation. For example:

Programme management documents:

provide the 'raw ingredients' for making evaluative judgments, since they will contain information on planned and actual spending, activities, and outputs;

can be used to inform evaluation indicators; Record the details of the beneficiaries. This will be crucial if the evaluators

plan to involve the beneficiaries directly in the evaluation through fieldwork to collect information to inform the conclusions.

Statistical sources:

provide information on the context for the programme; can be used to assess needs (e.g. the rate of new business creation is far

lower than the European average); can be used to reveal apparent impacts (e.g. the number of new businesses

created has doubled); Show whether the objectives remain relevant (e.g. the rate of business

creation has now caught up with the European average).

Past evaluations and research:

Can play a major role in all stages of evaluation:

reference to specialized literature could help to suggest a relevant indicator; previous studies can identify strengths and weaknesses of different

methodologies, or specific tools (e.g. a tested observation grid, an explanatory model of impacts, an extrapolation coefficient, a reference for comparison);

can be used to make comparisons, for example the rate of return to work from a Job Training scheme in terms of occupational sectors, to see whether there are significant differences, or to better understand the factors of success.

Usually a number of sources are used in tandem, and often can be presented in a way as to suggest conclusions and comparisons that can be made. For example, the comparison of observations from administrative data and statistical sources could

be used to assess the differences between participants and the population as a whole. It is may also be possible to estimate impacts on the basis of secondary data and/or the modeling of the implementation of the programme

Circumstances in which it is applied

Given the range and usefulness of secondary sources, some form of secondary data is used in practically all evaluation work.

It is important to note that the use of Secondary data must take into account the ethics or code of practice in place for the data. The ethical considerations usually relate to the rights of the providers of the information (i.e. the original subjects from which the data were obtained). As a general rule, the use of the information must be acceptable to the provider, and not in breach of the original conditions of collection. Sources of information need to be fully acknowledged.

Meta-evaluation might be considered a special case of secondary analysis (see Meta-evaluation).

The main steps involved

Programme management documents

Usually the programme will have generated information in both synthetic form (i.e. summary reports and review documents), and elementary form (i.e. systematic data stored for each project). Section 2.4.11 deals with the use of administrative data in an elementary form in more detail.

If the terms of reference have been prepared correctly, this document will already contain a list of immediately available information.

The programme management documents are likely to contain information on outputs, that is, what has been obtained in exchange for public spending. This information can be used in a synthetic form, for example from progress reports. Often, project-by-project information on outputs is not readily accessible.

The evaluators will need assistance from the programme managers/officers and operators to gain access to management documents, and this could be time-consuming. Involvement of the relevant people early on in the planning of the evaluation will help to expedite the process. The commissioning authority is responsible for ensuring that the necessary doors are opened, for example by involving in the steering group those who have most of the required information,

or by promising to supply them with a synthesis of the first evaluation conclusions. To facilitate access to information, it is also important for the evaluation team to undertake to maintain the confidentiality of all personal data.

Statistical sources

Unlike management and monitoring information (which concentrate on operators and direct beneficiaries), the statistical sources encompass all the people or businesses in an area whether or not they have had contact with the programme. As a result, the comparison of a before-after statistic cannot provide an estimated impact. At best, it gives information that can be used within the framework of an impact analysis, to impute observed changes to several causes: the programme and exogenous factors (or confounding factors). Thus, for example, statistics can show an increase in unemployment due to a sharp natural rise in the working population, even though the programme has created many new jobs.

In impact analysis, statistics provide useful indications on the evolution of exogenous factors, by measuring various characteristics of the territory or group concerned. They can be used to interpret or qualify observed gross effects or apparent impacts. They also supply extrapolation coefficients that are often used in evaluation. For example, if a statistical study can be used to establish that the average size of businesses created in the past two years is 4.5 jobs; this coefficient can be used in an estimation of impacts, for measuring support for business creation.

Most sources within the context of the Structural Funds will concern an entire region, a State, or even the European Union.

Statistical data are directly accessible from the organizations that produce and publish them (European, national and regional public statistics institutes, private institutes, etc.). Often these data have already been gathered by programme managers or by research organizations (e.g. regional statistical teams).

When directly analyzing statistical sources held as elementary data, it is important to consult the source codebook. This will contain the information needed to write syntax to extract the variables and cases you need from the raw data. The information required will include: the data structure - for example this could be rectangular, or hierarchical; the variables that you are interested in (and type (alpha or numeric) and format (number of decimals, treatment of blanks etc); supplemental variables (e.g. weightings). In some case it is a very time-consuming task to identify and prepare labels to extract the variables and values on your output. The applications used should be suited for the types of analyses that you expect to conduct. Most people use either SPSS or SAS for extracting data because

both have very robust data manipulation capabilities, followed by a conversion to a statistical package to perform the analysis of the results.

The availability of statistics can become a problem when the eligible area of a programme is an administrative rather than a statistical zone. The best way of dealing with this problem is the "best correspondence" approach, which has been applied for the Scottish system of indicators, as shown in Box 1 Correspondence between a statistical unit and an eligible area - United Kingdom, Objective 2 Programme 1994-99.

Estimations of context indicators can also be obtained by means of the interpolation method. For example, a (theoretical) example industrial reconversion programme aims to enable the region to catch up with others as in terms of innovation. In order to quantify this objective, a 'situation indicator' would need to be created, such as the annual number of innovations in the region. The annual number of innovations for 1,000 jobs, on a European scale, is provided by a Community survey carried out regularly on 40,000 firms. Based on the results of this survey, an innovation indicator could be created for the region, using the interpolation method, in the following way:

choose an indicator of structural composition (e.g. number of jobs, broken down into sector of activity) for which the values are known at both a European and a regional level;

note the value of the annual innovation rate at the European level, with its breakdown by sector of activity, and

Estimate the innovation indicator in the region by multiplying regional jobs, sector by sector, by European innovation rates.

Box 2 Italy

Box 1: Correspondence between a statistical unit and an eligible area - United Kingdom, Objective 2 Programme 1994-99

The development programme in the East of Scotland has an eligible area that concerns several statistical units ("local government region level") but there is a lack of correspondence in the way that they are partitioned. The data provided by the Central Statistical Office is therefore not suitable for directly constructing context indicators. An indicator of GDP was nevertheless estimated by aggregating data for the territories of the "central regions" and for Fife and Tayside, of which over half the inhabitants are in an area eligible for the Structural Funds. The territory of Lothian, less than half of which is eligible for Structural Funds, was disqualified.

Past evaluations and research

Conclusions from the evaluations of similar programmes in the same region or other regions can help to rapidly provide answers, at a low cost, to an evaluative question. However, if an evaluation team relies heavily on this type of secondary data, it must verify the external validity of the evaluations consulted to assess the extent to which the conclusions can be generalized to the current context.

It is not advisable to invest too much time in listing and collecting exhaustive bibliographical data. The most effective way of gaining access to this information is by consulting experts with in-depth knowledge of the domain and/or the region concerned by the evaluation.

Key Sources

Source Responsible body

Description

Portrait of the Regions and Regional Map.

Euro stat In this three volume set, published in 1993, each region is presented one by one in an identical format, via maps, diagrams, statistical tables and textual commentaries on their area, regional strengths and weaknesses, population patterns and trends, employment, the economic fabric and the environment.

DG Region publications

Box 2: Italy

In order to better assess the impact of socio economic development policy, the Italian Treasury (Department for Development Policies) has commissioned from the Central Institute of Statistics an analysis disaggregated to the level of the Local Labour Systems, which are built on the basis of the commuter fluxes derived from the National Census. Italy has been divided into 785 LLS of which 365 in the South. The availability of data has enabled a much finer analysis of local economic performance showing where growth of income, employment and productivity is concentrated and where the lagging areas are. This database will be used to understand if the positive outliers are also a consequence of the local development policies put into operation during the 2000-2006 programming period.

Local Sustainability European Good Practice Information Service

DG Region "Local Sustainability" is the European Good Practice Information Service. This guide to local environmental good practice in local sustainability is published and maintained by EURONET Environment, Planning and Development and ICLEI, the International Council for Local Environmental Initiatives. . It has been developed with the financial support of the European Commission, Directorate General XI (Environment, Nuclear Safety and Civil Protection) and with contributions from cities and towns whose good practice projects are presented within.

REGIO database Euro stat Regionalized data in the form of about 70 standard tables per domain: demography; economic accounts; unemployment; workforce; energy; agriculture; transport; and R&D. (Usage is fee-based).

ELIZE database Data from national annual surveys of industrial structures, consisting of: the number of industrial enterprises; employment; salaries and wages; turnover; and investments. The data are broken down into about thirty economic sectors and into two categories of size (+/- 20 employees).

QUID data base DG Region Group’s together context indicators adapted to the Structural Funds. This data base is partly based on Euro stat information.

Data service European Environment Agency

The EEA supports sustainable development and aims to improve Europe's environment through the provision of relevant and targeted information to policy making agents and the public. The data service

provides access to data sets used in EEA periodical reports

Urban Audit DGRegion/Euro stat

Compares indicators on the quality of life for a large number of major European cities.

GISCO Euro stat Cartographically presents all the statistical series existing in REGIO, as well as other regionalized data. The GISCO system also includes the outline of all the areas eligible for Structural Funds. It can therefore easily be used to break down or build up statistical information on different geographical scales. Potentially a very powerful tool for estimating context indicators by interpolation.

Increasing sophistication of computer technology has meant that the option exists to apply Geographical information systems (GIS) techniques to geographically-based socio-economic information. GIS provides a way of assembling any data that can be referred directly or indirectly to a geographical location, and is commonly used in the field of spatial planning to collect, gather, accumulate, analyze, exploit, display and update all spatially referenced data and information, and to present it in a form that makes it easy to read. GIS is able to incorporate socio-economic data, data from censuses, surveys and inquiries, and monitoring data. GIS use a basic structure of special data. All the information is linked to a system of geographical co-ordinates characterized by nodes, lines and areas (and therefore also of points, arcs, polygons, etc.).Principle of a Geographic Information System (GIS) shows the key principles of GIS.

The spatial representation may be direct (cartographic co-ordinates, precise postal address) or indirect (postal code, area of census).

In terms of evaluation, the main added value of a GIS is that it allows the cross-referencing of data that other techniques do not allow. In particular, the tool can compare information on which the geographical references differ, e.g. address of firms assisted and urban areas in difficulty, or areas eligible for assistance and environmentally sensitive areas. GIS also makes it possible to estimate the value of

an indicator for a given area, when its value is registered on different statistical scales.

High-performance information systems can now be applied to the management of public interventions, and because they are able to cope with considerable number of interdependent factors, they are an important way of describing and analyzing the complexities using information from the thematic, spatial and temporal dimensions (see Box 4 Evaluation of the Languedoc-Roussillon IMP in France).

Strengths and limitations of the approach

Secondary data is relatively quickly available and can therefore help to provide the first answers to some of the questions asked in a relatively short timescale. Secondary data can be useful in comparing findings from different studies and examining trends.

The estimation of an impact is always difficult, and using as much existing information as possible will produce the most robust estimation.

Moreover, this data can also be relatively inexpensive; because the costs associated with collecting the data from its original source has already been borne. Secondary data cost are usually known, though there may be additional costs involved due to data conversion, or the need for re-coding of data. Some organizations make a charge for the use of secondary data in order to offset the cost of collecting it (e.g. some Population Census bureaus).

The main drawback of secondary data is due to the fact that the data were not collected to analyze the question in hand. Every research study is conducted with a specific purpose in mind, and is designed to take account of the study purpose; responsibilities for data collection, completeness of the data and classification systems, timing, sampling criteria and delimitations; known biases; operational definitions; and methods of data collection. These considerations will limit the extent to which the data provides an appropriate source of information to address alternative research questions and hypothesis.

In the case of statistical sources, the processes involved in the collection and handling of the data also need to be taken into account. Without rigorous document control systems, there is the potential for errors or mistakes in the data to be introduced. Some sources collected at State or regional level may contain errors, or have missing data, which limits its usefulness.

Secondary use of large scale datasets present particular challenges, because it may take some time to identify the most appropriate source, confirm the quality of the data, and to devise the process of obtaining the data and analyzing it.

The key challenge with secondary data is to be assured that the data appropriately addresses the research question (otherwise there is the dilemma of altering the hypothesis to fit the data). A compromise may be needed between the results provided by the data and the requirements defined by the evaluation team or decision makers, and there needs to be a clear process by which any issues will be resolved and limitations on the use of the data will be dealt with. In some cases, the limitations that exist in terms of the nature and format of the data may be too extreme to permit a valid secondary analysis.

The GIS technique offers considerable potential for integrating and synthesizing information, and its ability to integrate the territorial dimension makes it particularly relevant for the Structural Funds. A GIS also allows easy visualization of information relating to the programme. This characteristic can be extremely useful during the presentation of the results to the various committees and work groups concerned. Moreover, the potential for synthesis facilitates the illustration of the coherence of the measures implemented in the framework of the programmes. Results can be rendered in a user-friendly way, which helps to enhance the awareness of actors (although technical signs and keys are codes that vary, depending on the designers, and need to be explained).

However, the creation of a complete geographical database often proves to be costly in both time and money, the use of a GIS may be complex. Existing data are often collected on different geographic boundaries, or stored in different systems, which requires time consuming transformations or sometimes even a new collection of data. Also, experience tends to show that the tool may generate conflict between territorial officials due to their biased reading of the maps produced.

Chapter – 5

Classification of

Secondary Data

Primary and secondary sources

Although there are several ways to classify sources, one of the most useful is by their primary or secondary nature, a distinction deriving from the field of Historiography. Although there is some variability in the use of these terms outside of Wikipedia, we focus on one particular aspect of the distinction useful for editors:

Primary sources

A primary source is a source cited for some new idea, creative thought, or data originating in that source, and not derived from another author or another source. Primary sources usually have some immediate connection or contact with the source of the new idea, thought, or data. For example, the primary source of some experimental data might be written by the scientist who performed the experiments. The primary source of a quotation might be written by someone who was present when the thing was said. The primary source of a historical theory is usually written by the historian who first conceived that theory. The primary source of information about a fictional universe is usually written by the author of that fictional universe.

Secondary sources

A secondary source is any source cited for its second-hand information from a different work. Secondary sources are not the originators of new ideas, creative thoughts, or data; they merely act as a conduit for such information. For example, if an author compiles research data from several scientists into a table for comparison, she is a secondary source with respect to that data. If an author paraphrases a quotation in another source, she is a secondary source with respect to that quotation. If an author in a historiography summarizes a historical theory from the 1800s, she is a secondary source as to that historical theory. An encyclopedia about a fictional universe is a secondary source as to the works of fiction defining that fictional universe.

Some secondary sources, such as textbooks and treatises, are further described as tertiary sources. However, the tertiary source concept is not as significant and clear-cut as the others, and the category has less relevance to Wikipedia, except for the fact that Wikipedia is itself a tertiary source.

Primary and secondary are relative terms

heyeither a primary or secondary source, depending on how it is used. For example, if an author compiles research data from several scientists into a table for comparison, she is a secondary source with respect to that data. However, she might also make original conclusions about that data. The source would be primary with respect to those new conclusions. If an author paraphrases a quotation in another source, she is a secondary source with respect to that quotation. However, if she draws novel implications about that quotation, or synthesizes that quotation with other quotations, the work would be a primary source with respect to those new conclusions. If an author in a historiography summarizes a historical theory from the 1800s, she is a secondary source as to that historical theory. However, if she provides novel insights linking that historical theory with 1800s culture, the work is a primary source as to those original conclusions. An encyclopedia about a fictional universe is a secondary source as to the works of fiction defining that fictional universe. However, if the encyclopedia "fills in gaps" or makes novel generalizations, the encyclopedia is a primary source as to the author's unique contribution to the field.

Guidelines for primary and secondary sources

If given in their proper context, primary sources can be the most neutral and informative way to present information in a Wikipedia article. Often, however, the import or significance of primary sources is not obvious or is controversial, in which case they should be supported by secondary sources.

Non-controversial and respected secondary sources can be even more neutral and informative than primary sources. Sometimes, however, secondary sources act as filters and add "spin" to primary sources. Therefore, polemical or controversial secondary sources should be balanced with other secondary sources, and typically by reference to the unvarnished primary sources, so that the reader can have a basis to determine which secondary source provides the most credible "spin" on the primary sources.

When available, well-respected tertiary sources, such as textbooks and legal treatises, can be the most neutral secondary sources for use in Wikipedia articles. Frequently, however, the process by which the author collected the information is unclear and not well documented, and sometimes, the author is unknown. In such cases, tertiary articles should be supported by primary and other secondary sources.

First-party and third-party sources

Another way to categorize sources is by whether the cited information is written by the authoritative creator of that information (the "first party"), or by someone else (a "third party"). A source is considered third-party if the author and/or sponsoring/publishing organization are not involved in the subject of the source. Thus, an autobiography is never third-party, as the author is the subject, and an article published by Microsoft on the reliability of Windows XP is not third-party, as the company is describing its own product. On the other hand, a technical review of Windows by someone not involved in operating system development or marketing is likely to be third-party, as is a military history from someone not involved in the conflict in question.

Third-party sources are generally preferred as the author has no obvious incentive to distort the truth or "spin" the facts a certain way. They are thus considered advantageous in ensuring a neutral point of view. However, it should be remembered that a source is not necessarily entirely neutral just because it is third-party, and where a range of views and perspectives exist, they should all be given reasonable coverage. In such situations, care should be taken to avoid giving undue weight to a particular point of view.

CONCLUSION TO MARKET

RESEARCH

However, it is perhaps worth noting that the end products of marketing research are conclusions and recommendations. With respect to the marketing planning function, marketing research helps to identify potential threats and opportunities, generates alternative courses of action, provides information to enable marketing managers to evaluate those alternatives and advises on the implementation of the alternatives.

Too often marketing research reports chiefly comprise a lengthy series of tables of statistics accompanied by a few brief comments which verbally describe what is already self-evident from the tables. Without interpretation, data remains of potential, as opposed to actual use. When conclusions are drawn from raw data and when recommendations are made then data is converted into information. It is information which management needs to reduce the inherent risks and uncertainties in management decision making.

Customer oriented marketing researchers will have noted from the outset of the research which topics and issues are of particular importance to the person(s) who initiated the research and will weigh the content of their reports accordingly. That is, the researcher should determine what the marketing manager's priorities are with respect to the research study. In particular he/she should distinguish between what the managers:

must know should know could know

This means that there will be information that is essential in order for the marketing manager to make the particular decision with which he/she is faced (must know), information that would be useful to have if time and resources within the budget allocation permit (should know) and there will be information that it would be nice to have but is not at all directly related to the decision at hand (could know). In writing a research proposal, experienced researchers would be careful to limit the information which they firmly promise to obtain, in the course of the study, to that which is considered 'must know' information. Moreover, within their final report, experienced researchers will ensure that the greater part of the report focuses upon 'must know' type information.