Chapter 14

GROUP TWO

SUMMARY CHAPTER 14: THE RESEARCH PROCESS

The chapter went through the different steps in the research process and design of hypothetical deductive studies. The chapter brought out the role of both qualitative and quantitative studies in research. Every hypothetical-deductive study must have had its genesis in prior qualitative investigation. The chapter concluded that both qualitative and quantitative studies are integral part of scientific investigations –each having their distinct role to play.
Scientific research involves the formulation and testing of one or more hypotheses. A hypothesis cannot be proved directly, so a null hypothesis is established to give the researcher an indirect method of testing a theory. Sampling is necessary when the population is too large, or when the researcher is unable to investigate all members of the target group. Random and systematic sampling is the best methods because they guarantee that each member of the population will have an known non-zero chance of being selected. Ultimately the induction and deduction process is what leads to problem solving.

Chapter 13

GROUP TWO

SUMMARY CHAPTER 13: THE RESEARCH REPORT

This chapter described various types of written reports methods and the application to any research discipline. Based on various compositions the intended audiences are critical factors to deal with in any analysis and interpretation of major and minor findings should be well emphasized. A well-thought-out written report and oral presentation are critical. The written report enables the manager to weigh the facts and arguments presented therein & implement the recommendations
The primary aim is to achieve a clear, logical, coherent and concise write-up. The principles of “keep it simple, concise, objective and straightforward” and “clear organization and presentation” must be adhered to whenever possible. Simplicity by way of presenting only the essential issues, precision in quantification, specificity with little exaggeration, proper attention to formatting and layout, and paying attention to the target audience are some of the issues to be taken into account in finalizing a research report.
Research report is considered a major component of the research study for the research task remains incomplete till the report has been presented and/or written. As a matter of fact even the most brilliant hypothesis, highly well designed and conducted research study, and the most striking generalizations and findings are of little value unless they are effectively communicated to others. The purpose of research is not well served unless the findings are made known to others. Research results must invariably enter the general store of knowledge. All this explains the significance of writing research report.

Chapter 11

A Presentation On Sampling By Members Of Team 2.

This chapter seeks to shed more light on sampling as a basic and essential tool in research. It explains how sampling design decisions are important aspects of research design and include both the sampling plan to be used and the sample size that will be needed.

Before going any further, we will need to define/ explain certain terms/words frequently used here;

Population
Population refers to the total number of people, events or things of interest that the researcher wishes to investigate.


Element
An element refers to a single unit of the people, event or things of things of interest in the population.

Population Frame
The population frame is a listing or directory of all the elements that make up the population from which tne sample is drawn.
One of the limitations of the population frame is that it might not always be current or updated.

Sample
A sample is a select group carved out from the population which is going to be used in making generalization on the entire population.

Subject
A subject is a single unit or number from the sample.



Then, what is Sampling?

From the explanations given above, we can refer to sampling as the process or method adopted in creating a select group of subjects to form a sample from the elements in the population.

Why Sampling?
1. Difficulty in gathering information from the entire population
2. The cost implication of gathering data from from the entire population where possible will be very heavy on the researcher
3. There is a tendency of producing more accurate results from sampling rather than the entire population size because of the probability of fewer errors from computing results from a smaller select group.

Types Of Sampling.

There are two major types of sampling designs;
1. Probability Sampling
a. Unrestricted or Simple Random Sampling
b. Restricted or Complex Probability Sampling
i. Systematic sampling
ii. Stratified Random Sampling
iii. Proportionate and Disproportionate Stratified
iv. Cluster Sampling
v. Area Sampling.
vi. Double Sampling.


2. Non-probability Sampling
a. Convenience Sampling
b. Purposive Sampling
i. Judgement Sampling
ii. Quota Sampling.


1.Probability Sampling.
In probability sampling, the elements in the population have a known chance of being selected as sample subjects. This type of sampling is used when the representativeness of the sample is of importance in the interest of the wider generalizability.
Probability sampling can further be broken down into two forms, Restricted or Unrestricted. The Unrestricted or Simple Random Sampling adopts the approach whereby every element in the population has an equal chance of being selected to the sample. However this design could become cumbersome or expensive in a large or complex population hence the development of the Restricted Sampling Design.
The systematic approach involving adopting a unified sequence in choosing subjects from the elements. While the Stratified approach can be adopted in a population whereby the elements in the population have parameters that are segmented or stratified hence he used a systematic design in choosing subjects from the various segments or stratum.
The proportionate or Disproportionate Stratified Sampling design is fallout of the stratified design. Researchers desiring to further create a sample out of each stratum are faced with the challenge of whether to adopt a proportionate or disproportionate design. A proportionate design adopts selecting a unified or proportionate number of subjects from each stratum(eg applying a unified % across of the strata) while the disproportionate adopts a one that isn’t unified.

2. Non-Probability Sampling.
There basically two main types of nonprobability sampling designs: convenience sampling and purposive sampling. Convenience sampling refers to the sampling done with information readily available to the researcher. It usually carried out when quick and timely results are needed. It’s major flaw is that it scores very low in terms of generalization. Purposive Sampling involves sampling from a specific target group and falls into two categories, Judgement and quota sampling design. Judgement sampling though limited in generalization is used when there’s only a select or limited population that can provide information for the research study. While Quota Sampling is adopted when there’s a constraint of either cost, time and the need to adequately represent minority elements in the population.

SAMPLING IN CROSS-CULTURAL RESEARCH.

Cross-Cultural research can basically be defined as the research carried out when comparing or dealing with issues that occur with two or more cultures/ countries/locations involved.
When carrying out sampling in a cross-cultural research the major issue the researcher is faced with is that of the precision and confidence in determining the sample size. Determining the sample size is a major issue any researcher has to deal with when confidently generalizing his/her findings to the population with a high tendency of precision.
What is precision in determining sample size?
Precision refers to how close our estimate is to the population characteristic. In achieving a greater level of precision the researcher has to increase the size of his sample
Confidence?
This refers to how close or certain the researcher is that the estimates will really hold true for the population.

Relationship between Sample Data, Precision & Confidence in Estimation.
The relationship among the sample data , precision & confidence in estimation cannot be overemphasized because the sample data is what is used in making inferences about the population. A good correlation enhances the accuracy of our estimation and in turn increases the confidence of our generalization.
In sum, the sample size is a function of the level of precision and confidence desired.

DETERMINING THE SAMPLE SIZE.
The major factors affecting decisions on sample size are as follows;
1. The extent of precision required
2. The acceptable risk in predicting that level of precision
3. The amount of variability in the population itself
4. The cost and time constraints
5. The size of the population itself

Efficiency in Sampling.

Efficiency in sampling is achieved when for a given level of precision, the sample size could be reduced or for a given sample size, the level of precision could be increased.


Team’s Comment.
Members of team two after intensively reviewing this chapter agrees sampling is a very delicate and key aspect of any thorough research work. Identifying the various sampling designs and the appropriateness of each for different research purposes is also very important.
Knowledge gained from this chapter would go along way in improving our efficiency in carrying out a detailed and useful research study.

Chapter 10

Chapter 9

GROUP TWO


SUMMARY CHAPTER 9: MEASUREMENT, SCALING REALIABILITY, VALIDITY

This chapter deals with different types of measurement and techniques use in research, scaling is used to measure the operationally define dimension and element of a variable. (Rating, and ranking scaling). Ranking scales is used to tap preferences between two or more object, this ranking may not give definitive clues to some of the answers sought. Paired comparison scale is used among small number of objects, respondents are asked to choose between two object at a time.
Goodness of measures, it is very important that the instrument we develop to measure a particular concept is indeed accurately measuring the variable. Reliability of a measure indicates the extent to which it is without bias and hence ensures consistent measurement across time and across the various items in the instrument. Managers knowing different scales and scaling techniques help to administer short surveys by designing questions that use ranking scales as appropriates.

Chapter 8

GROUP TWO

SUMMARY CHAPTER 8: MEASUREMENT OF VARIABLES,:OPERATIONAL DEFINITION AND SCALES.

Variables measurement, object can be physically measured by some calibrated pose no measurement problems. Other measurement can be done like checking your company records to get some information , e g absenteeism/performance of employees in terms of the number of products produced or reject per month. Operational definition, dimensions and elements. Defining a concept to render it measureable is by looking at the behavioral dimension, facets, denoted by the concept.
Scales is a tool by which individual are distinguished as to how they differ from one another on the variables of interest to the study. Nominal scale allows the researcher to assign subjects to certain categories, ordinal scale not only categorize the variables in such a way as to denote difference among the various categories. Interval scale is use to perform certain arithmetical operation on the data collected from respondent

Chapter 7

Chapter 6

GROUP TWO

SUMMARY CHAPTER 6: ELEMENTS OF RESEARCH DESIGN

The chapter discussed the basic research design. The research design includes the purpose of the study which may be exploratory in nature; which involves a situation when there is inadequate information furnished for the research. It could also be descriptive research which is undertaken to establish and illustrate the characteristics of the variables of interest in a situation. The hypothesis testing was also discussed. The type of investigation to be undertaken which could be either casual study or correlation was examined. The chapter also stated that that the unit of analysis referred to the process of gathering data for analysis and the time horizon could be cross-sectional or longitudinal. Finally, the circumstances in which each design would be appropriate were examined.

REFLECTION

In understanding what a researcher is about to do, the manager has to have adequate knowledge of the research design. Before a manager takes up a study he is expected to do a thorough analysis to have an idea of the how rigorous the study maybe. The design to be adopted by the manager is contingent on magnitude of the problem experienced. Knowledge of research design helps managers to study and intelligently comment on research proposals.

Chapter 5

CHAPTER SUMMARY ON THEORETICAL FRAMEWORK & HYPOTHESIS DEVELOPMENT PREPARED BY MEMBERS OF TEAM 2.

This chapter seeks to shed more light on two vital aspects of the research process which are; i) Theoretical Framework, and

ii) Hypothesis Development.

A theoretical framework is a conceptual model of how one makes logical sense of the relationships among the factors that have been highlighted as necessary to a particular research topic.
It can also be referred to as a logically developed, described and elaborate network of associations among the variables deemed relevant to the problem situation and identified through such processes as interviews, observations and literature survey.

From the definition of the term “theoretical framework” we identified some key elements which are;
i) It is logically based
ii) Existence of a relationship among certain factors or variables

What are Variables?

Variables are the various forms, characteristics or qualities of issues we seek research. Variables can take on differing or varying values.
Variables are called what they are because it is assumed that the cases will vary in their scores on these attributes. For example if the variable is someone’s age, we obviously recognize that people can be different ages.

Types of variables.

i) Dependent variable: this can also be termed as the outcome variable. It is the variable of primary interest to the researcher. The aim of the researcher is to understand, describe and predict this variable. An example of a dependent variant could be a study to determine why some people are more satisfied in their jobs than others. Job satisfaction is the dependent variable in this case.

ii) Independent variable: also known as the predictor or explanatory variables. They are the variables that we believe influence the dependable variable in either a positive or negative way. An example is studying why people are more satisfied with their jobs if they are given a lot more freedom and also a pay increase. The independent variable here is the Job freedom and salary increase.

iii) Moderating variable: also termed the contingent variable. It has a strong contingent or modifying effect on both the independent and dependent variable. It’s main function seems to adjust the strength of relationship between the independent and dependent variables. For example is studying the perception that diversity in organizations can make them more profitable but only if managers are specially trained in diversity management. The moderating variable here is the “diversity training”. It adjusts the strength of relationship between diversity (independent variable) and profitability (dependent variable).

iv) Intervening Variance: this is the variable that surfaces between the time the independent variables start operating to influence the dependent variable and the time their impact is felt on it. Citing the example used in describing the Moderating variable, we said that diversity brings about profitability, we add an intervening variance by stating that diversity(independent variance) leads to innovation which in turn leads to profitability. Innovation is the intervening variance.


Why the theoretical framework?

A theoretical framework guides any research and gives direction determining what things to measure and what statistical relationships you will look for. It is the foundation on which the entire research project is based.
It has also been proven to be very important in exploratory studies because it helps the research have a guide and direction in his research work despite whatever his preconceived notions were about the research topic. Things not in your framework go unnoticed.

Having a sound theoretical framework is very essential in any research which primarily seeks to find solution to a problem. The relationship between the literature survey and the theoretical framework is that literature survey provides a solid foundation for developing the theoretical framework. It provides the basic information i.e. the variables and other logical connections that is using in drawing up the theoretical framework.

Essential Components of The Theoretical Framework.

1. The relevant variables should be clearly identified and labelled.
2. Clearly state how the variables are related to another
3. Theorize the nature and direction of the relationships on the basis of the findings of the previous research, and then indicate if the relationship will be negative or positive.
4. Clearly stated reason why the researcher expects the relationships to exist.
5. A systematic diagram of the theoretical framework should be drawn to show the relationships amongst the variables.


HYPOTHESIS DEVELOPMENT.

Hypothesis development is the next stage in the research process after successfully drawing up the theoretical framework.
Hypothesis can be defined as a logical relationship between two or more variables expressed in the form of testable statement. By confirming or rejecting hypothesis, it is expected that solutions can be found to correct the problem encountered.
Hypothesis should have the following characteristics;
i) It should be testable
ii) Availability of variables that can be related and substantiated.

Types of Hypothesis.

i).If-then statements:
This type of hypothesis seeks to test whether there are differences between two groups (or among several groups) with respect to nay variable or variables.
An example of using this statement can be described using this case; Employees who are healthier will take sick leave less frequently.
“If employees are healthier, then they will take sick leave less frequently”


iii) Directional and Non Directional Hypothesis.
If terms such as positive, negative, more than, less than are used, then the hypothesis are directional because the relationship between variables is indicated.
For example:
“The greater the stress experienced in the job, the lower the job satisfaction level of employees.”

On the other hand non-directional hypothesis shows no indication of the direction of the relationship. For example:
“There is a relationship between age and satisfaction.” This statement doesn’t give a direction as to the relationship between age and satisfaction

iii) Null and Alternate Hypothesis
The null hypothesis is a proposition that states a definitive, exact relationship between two variables. The null statement is expressed as no relationship between two variables or no difference between two groups. While on the other hand, the Alternate hypothesis is one which is the opposite of the null, it expresses the existence of a relationship between two variables or indicating differences between groups.




Team Summary.
The review of this chapter has helped in identifying and distinguishing between the various variables associated with any given situation and using the links among the variable in drawing up a theoretical framework.

It has also taught us how to develop a hypothesis which can be tested and applied to a research project.

Chapter 3

BA 306 RESEARCH METHODOLOGY


TECHNOLOGY AND BUSINESS RESEACH

To run a business, useful, timely, accurate, reliable, and valid data are needed. When data in their raw form are evaluated, analyzed and synthesed, useful information become available to managers that help them make good business decisions. Technology in all aspect of business cannot be overstated. Technology as used in this chapter refers to all hardware, software and communication aids that achieve the desire business result.

COMMONLY USED TCHNOLOGIES IN BUSINESS RESEARCH

These include all electronic interactive media such as CD-ROM, the DVD, the browser, the internet and the intranet, and search engine.
The Internet, which is vast global network of computers connecting people and information, has opened up tremendous opportunities through the world. Business research can proceed using the internet using the internet the internet and search engines, even where sources of information on a particular topic are not readily known.

The Electronic Mail, The internet also permits the exchange of electronic mail which has become increasingly become the primary mode of communication in business both within and outside the company.

The Intranet is the internal system of the organization what the internet to its external environment. It links internal data networks of the computer, but prevent access to other outside the company. It also facilities data collection from within the company; for instance, survey can easily conducted through the intranet to assess employee moral.

Browsers, Browser software allows users easy to and navigates through the web.

Web sites, organization create websites to promote their image, communicate with the customers, build , relationships, share information, offer attractive inducements to prospective customers, and ensure that they keep returning. In some cases they even allows online purchase by customers.




SOME SOFTWARE USED IN BUSINESS RESEARCH.
Groupware, Groupware is software that runs on a network so that teams can work on joint projects, and allows people from different departments to access data jointly.

Neural Networks, Neural Networks are designed to trace patterns in a set of data and generalized them. This software enables sale forecast, stock market prediction, detection of weather patterns etc.

CAM/CAD, Computer-aided manufacturing (CAM) software helps engineers to design the manufacturing components and direct the production of the product. Computer aided design (CAD) software creates and display complex drawings with precision, enabling experimentation with different designs.

Enterprise Resource Planning, Enterprise Resource Planning packages from software companies that offer all-in-one integrated business applications have slowly replaced traditional manufacturing, finance and order entry applications, which are usually home designed and do not lend themselves to easy integration

EMERGING APPLICATIONS IN TECHNOLOGY
Handheld Devices, Handheld devices like palm, assisted by new class of software easy data gathering and immediate analyses, and has initiated change in field work.

Interactive voice Technology, CD-ROM, and Rational Database, This technological advances have help businesses to conduct research and increase their operational efficiency.

Digital Whiteboards, allows contents on a board displaying intricate diagrams and voluminous notes to be copied on the pc notepad and transmitted to others, as requested.

Group Videoconferencing, reproduces the face-to-face meeting effect by using large TV monitors or projector.

INFORMATION SYSTEMS AND MANAGERIAL DECISION MAKING
As organizations take on expanded functions and grow in size, it is important for them to be equipped with a good information system from which data can be accessed for analysis by managers at different level. Among the aspect of information systems managers used are; Data Warehousing, Data Mining and Operation Research.

DATA STORAGE AND SURVEILLANCE
Data is the life blood of companies and should be mirrored life in at least two other locations, or at least backed up by on tape and stored in other safe locations.


CONLUSION

Information technology and the development of software to gather, store and analyze information, result of which facilitate decision making. We have specifically examined some of the current possibilities for research afforded by the use of the software from simple data collection to the development of information systems to facilitate further research and decision making.




TEAM 2 MEMBERS
MONDAY
BENJAMIN
ADESHOLA
SOPHIE
EFOSA
HASSANNAT
MOSES
DORIS
OLUSEYI

Chapter 2

Chapter 1

SUMMARY OF CHAPTER ONE

INTRODUCTION:
This chapter talks about the Scientific Research which applies to both Basic and Applied Research.

Scientific Research focuses on solving problems and pursues a step by step logical, organized and rigorous method or approach to identify the problems, gather data, analyze them and draw valid conclusions thereon.

The Hallmark of the Scientific Research is stated below.

1. Purposiveness
2. Rigor
3. Testability
4. Replicability
5. Precision and Confidence
6. Objectivity
7. Generalizability
8. Parsimony

Thus, the primary method s of Scientific Investigation or Research is the Hypothetico Deductive Method.

Deduction is the process in which we arrive at a reasoned conclusion by logical generalization of a known fact. This is to say for example – high performers are highly proficient in their job. So if Seyi is a performer then we conclude that he is highly proficient in his job.

While Induction – is the process where we observe certain phenomena and base on this we arrive at conclusions.








The Seven Step Process in the Hypothetico -Deductive Methods are namely

1. Observation
2. Preliminary Information Gathering
3. Theory Formulation
4. Hypothesizing
5. further Scientific Data Collection
6. Data Analysis
7. Deduction

IN SUMMARY:

In this chapter we obtain a general understanding of what constitutes Scientific Research and the Hallmarks of scientific investigation or research. We also looked at the steps involved in the hypothetical –deductive method of studying a problem in order to solve it. Thus, when managers realize the value of scientific investigation, they are able to understand and accept the need for good research. While this offers the opportunity to effectively solve complex problems encountered at workplace. The manager also realizes the fact that although organizational research cannot offer 100% accuracy in results. Choices and trade-offs among the various criteria of scientific investigation can be made to obtain valid results for purpose of good decision making.