Business Research: Types and Areas

Business Research Overview

• It is an organized, systematic inquiry or investigation into a specific problem.
• It aims to find answers or solutions to the problem.
• It is primarily conducted to resolve problematic issues in accounting, finance, management, and marketing or issues interrelated among these areas.

Research Areas

• Accounting: Examines budget control systems, practices, and procedures.
• Finance: Focuses on financial institutions' operations, financial ratios, mergers, acquisitions, and stock exchange behavior.
• Management: Studies employee attitudes, behaviors, human resources management, and the impact of demographics on management practices.
• Marketing: Addresses consumer decision-making, customer satisfaction, market segmentation, product image, advertising, and sales promotion.

Types of Research

• Applied: Solves a current problem faced by a manager, demanding a timely solution.
• Basic/Fundamental/Pure: Generates a body of knowledge by trying to understand how problems in organizations can be solved.

Advantages of Research Knowledge for Managers

• Identify and effectively solve minor problems in the work setting.
• Discriminate between good and bad research.
• Appreciate the multiple influences and effects of factors.
• Take calculated risks in decision-making based on probabilities.
• Prevent vested interests from influencing a situation.
• Relate more effectively to hired researchers and consultants.
• Combine experience with scientific knowledge in decision-making.

Internal Consultants/Researchers: Advantages

• Better chance of acceptance by staff.
• Less time needed to understand the organization's structure and systems.
• Integral part of implementing and evaluating research recommendations.
• Lower cost than an external team for problems of low complexity.

Internal Consultants/Researchers: Disadvantages

• May fall into a stereotyped way of viewing the organization.
• Possibility of powerful coalitions influencing the team to misrepresent facts.
• Might not be perceived as "experts," leading to disregarded recommendations.
• Potential for organizational biases, making findings less objective.

External Consultants/Researchers: Advantages

• Draw on broad experience from working with different organizations.
• Think divergently and convergently, critically assessing various perspectives.
• Greater knowledge of current problem-solving models.

External Consultants/Researchers: Disadvantages

• High cost, unless problems are critical.
• Take more time to understand the organization.
• Seldom get a warm welcome or are readily accepted by employees
• Charge additional fees for assistance in implementation and evaluation phases.

Ethics in Business Research

• Refers to a code of conduct or expected societal norms of behavior while conducting research.

Scientific Research

• Focuses on solving problems through a step-by-step, logical, organized, and rigorous method.
• It identifies problems, gathers data, analyzes them, and draws valid conclusions.

Characteristics of Scientific Research

• Purposiveness: Research has aim or purpose, avoiding waste of resources.
• Rigor: Carefulness, scrupulousness, and exactitude with a good theoretical base and methodology.
• Testability: Scientific hypotheses are testable to determine if they are real.
• Replicability: Replication is possible due to clear design details.
• Precision and Confidence: Precision refers to the probability that estimations are correct; Confidence refers to the probability that estimations are correct
• Objectivity: Conclusions are based on facts derived from data rather than emotions.
• Generalizability: Refers to the scope of findings' applicability in other organizations.
• Parsimony: Simplicity in explaining phenomena/problems and generating solutions.

Hypotheico-Deductive Method

• Involves identifying a broad problem area, defining the problem statement, developing hypotheses, determining measures, collecting data, analyzing data, and interpreting data.

Problem statement

• Includes the general objective and research question.

Determine hypothesis

• Hypotheses should be testable and falsifiable

Falsifiable

• Important because a hypothesis cannot be confirmed but remains provisional until disproved

Determine measures

• Unless the variables in the theoretical framework are measured in some way, we will not be able to test our hypotheses.

Interpretation of data

• Even if the hypothesis is not supported, our research has still been worthwhile.

Reasoning

• Deductive Reasoning: Start with a general theory and then apply this theory to a specific case.
• Inductive Reasoning: Observe specific phenomena and arrive at general conclusions.

Alternative Approaches to Research

• Positivism: Scientific research leads to truth with rigor, replicability, reliability, and deductive reasoning; objective truth
• Constructionism: World is mentally constructed; Qualitative; Aim to understand rules
• Critical Realism: There is an external reality, but cannot be measured objectively; biased researchers
• Pragmatism: Focus on practical, applied research with different viewpoints to solve business problems; inform practice

Research Design

• Blueprint for the collection, measurement, and analysis of data based on research questions.
• Quality depends on the appropriate design choice.
• More sophisticated and rigorous designs mean more costs and resources.

Types of Studies

• Exploratory: Undertaken when little is known about the situation; results are not generalizable.
• Descriptive: Describes characteristics of persons, events, or situations using quantitative or qualitative data; correlational research.
• Causal: Tests whether one variable causes another to change

Conditions for causal study

• The independent and dependent variable should covary
• The independent variable (the presumed causal factor) should precede the dependent variable.
• No other factor should be a possible cause of the change in the independent variable.

Researcher Interference

• Whether a study is correlational or causal is directly impacted by how much the researcher intervenes.
• Correlational Study: Conducted in the natural environment.
• Causal Study: Researcher manipulates variables to study the effects.

Study Setting

• Contrived (Artificial): Causal studies
• Noncontrived (Natural): Correlational studies; field studies

Field experiment

• Cause-and-effect relationships w/ researcher interference
• Lab experiment: Cause-and-effect relationships and strict control

Research Strategies

• Experiments: Deductive, uses manipulation to test hypotheses.
• Survey Research: Collects information to describe, compare, or explain, allowing quantitative and qualitative data

Observation

• Planned watching, recording, analysis and interpretation of behaviour, actions or events.

Case studies

• Focus on gathering data on a certain subject, occurrence, or activity like a specific business unit
• Grounded Theory: Develops theory inductively from the data.
• Action Research: Consultant-led change process, constantly evolving; Constantly evolving project with interplay among problem, solution, effects or consequences, and new solution
• Triangulation: More confidence in result if it uses different methods or sources to lead to the same results (more confident)

Type of triangulation

• Method: Using multiple methods of data collection and analysis
• Data: Collecting data from several sources and/or at different time periods
• Researcher: Multiple researcher collect and/or analyze the data
• Researcher: Multiple theories and/or perspectives are used to interpret and explain the data

Unit of analysis

• Individuals, dyads, groups, organizations, cultures
• Refers to the level of aggregation of the data collected during the subsequent data analysis stage.

Time Horizon

• Cross-Sectional Studies (One-Shot): Data gathered once in days, weeks, or months.
• Longitudinal Studies: Data on the dependent variable gathered at two or more points to answer a research question.

Managerial Implications

• Rigorous studies, more resources, weigh seriousness of problem
• Managers do not fall for the trap of implicit assumptions
• Understand reports

Questionnaire

• Pre-formulated, written questions for respondents.
• Efficient, but high chance of nonresponse error
• Can be administered personally, via mail, or electronically

Personally administered questionnaires

• Data is collected in short period and doubts are clarified. Topics & motives are thoroughly explained

Mail & electronic questionnaires

• Advantage is a wide geographical area, easy to administer & very inexpensive

Guidelines & principles of questionnaire design

• 3 areas of focus which include wording, coding variables, and general appearance of questionnaire.
• Types - content, questions, language used
• Open-ended questions - allow any type of answers
• Close-ended questions - asks respondents to make choices

Positively/negatively worded questions

• Advisable to include both
• Double barrelled Questions - A questions that can give different responses

Ambiguous questions

• Questions that may not be clearly understood by respondents

Leading questions

• Leads respondent to give a particular desired answer

Loaded questions

• phrased in an emotionally charged manner

Social desirability

• Questions word to get a socially desirable response

Sequencing questions

• using the funnel approach is best way, from easy to more complex questions

Personal data

• Should be organized appropriately
• Note the ordinal scaling of the age variable

Ethics

• Privacy & confidentiality of information is a must
• Never violate self-respect
• Subject should not be forced
• Non-participant should be as unintrusive as possible

Measurement

• the assignment of numbers or other symbols to characteristics (or attributes) of objects according to a pre-specified set of rules.

Objects

• These include persons, strategic business units, companies, countries, examples are apple or bananas.

Judge:

• Is someone who has the necessary knowledge and skills to asses “thequality" of something.

Operationalization

• Reduction of abstract concepts, makes it tangible

A valid measure

• Measure includes quantitatively measurable questions or items (elements) that adequately represent the domain or universe of theconstruct; if the construct has more than one domain or dimension, we haveto make sure that questions that adequately represent these domains ordimensions are included in our measure.

Scale

• A tool or mechanism by which individuals are distinguished as to how they differ from one another on the variables of interest
• scaling involves the creation, continuum where our results can be located
• Four scales - nominal, ordinal, interval, ratio

Nominal scale

• Assign them to certain categories/groups

Ordinal scale

• Not only category, but rank in meaningful way

Interval scale

• allows to perform arithmetical operations on data that is collected

Ratio scale

• meaningful measurement
• natural zero
• numbers w/ meaningful differences and a natural zero

Different R scales

• dichotomous, category, semantic, numerical, Itemized, Likert, staple, constant rating, graphic Rating Scale

dichotomous scale

• yes or no

Itemized & Likert scales

• 1 or 5 point, agree or disagree

Constant sum scale

• add a number of points across various items

Ranking scale

• preferences b/w objects and items

Paired Comparisons

• used for small # to choose between 2 at a time

Reliability

• Is the instrument measurement consistent

Validity

• does the instrument measure concept

Content validity

• include enough components

Sample / Sampling

• select efficient #, result can be generalized to the total population

Element

• single member of the population

Population

• group of events of interest
• Sampling Unit:Element/set of elements
• Subject:single member

Parameters

• characteristics of populations
• Reasons:Involved hundreds of elements
• Representativeness

Sampling process

• design, 5 steps
• Probability sampling:Known and non-zero chance
• Non-probability sampling:Not known/pre-determined
• Unrestricted probability:Equal chance - least bias
• Cost - time constraints, least bias
• Elements can be used for different subjects

Complex probability

• Better Efficiency
• Heterogeneity within groups vs Homogeneity
• Disproportionate stratified R Sampling;Cluster Sampling
• Non-prob, double, single+multistage

Non‐probability sampling

• Convenience
• Purposive
• Judgment
• Quota

Sampling Design

• Used for easy quick development
• heterogeneous
• Goal /locality is specific
• Minimal add'l expenditure
• Quick easy
• Expert help

Measuring instruments, data collected

• Must be similar for each country Sample Size
• Larger than 30 or less than 500 appropiate for almost research

Sample to small

• For multiple variable, need minimum size for research

Sampling design, sample

• Helps understand why sampling is used
• Helps in costs
• Understand limitations, apply recommendations
• Quantitative data
• Questionannaires: Code, keyed, edited
• Catecorization scheme

Data coding

• Assign numbers to participations to be put into datebase
• Helps confusion
• Editing data: to be edited after recorded, look for what outliers,inconsistencesi
• Valaues

Data transformation

• Changing value to avoid in next stage Feel for data/Summary, visual
• Frequencies
• Visual (bar charts, pies) Measures
• Central tendency, deviation Relationships