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Theoretical Framework

• Author: Tasneem Faiez Alrabee

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Definitions of Theory

• Theories: Generalizations that help us understand reality and the logic of observations.

• Theory: A formal, logical explanation of events, including predictions on relationships among concepts.

• Characteristics:

  • Tested and accepted by the scientific community.

  • Models reality.

  • Provides logical explanations for events.

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Determine Relevant Variables

• Variable: Anything that changes from one instance to another, capable of taking on different values.

• Dependent Variable: The variable being explained or predicted; it is of primary interest to the researcher.

  • Example: Sales of a new product after marketing efforts.

  • Important to note: There can be multiple dependent variables in a study.

• Exercise: If a manager limits a product's availability to increase desirability, identify the dependent variable.

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Independent Variable

• Independent Variable: A variable expected to influence the dependent variable, positively or negatively.

  • Example: New product's success can affect stock market prices.

  • More success in product development leads to higher stock prices.

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Moderating Variable

• Moderating Variable: A variable that modifies the relationship between the independent and dependent variables.

  • Examples: Work diversity, organizational effectiveness, managerial expertise.

• Distinction:

  • Independent Variable: Impacts dependent variable.

  • Moderating Variable: Alters the strength or direction of the relationship between the other two variables.

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Variables Defined

• Independent Variable: The variable that is changed.

• Dependent Variable: The variable affected by the change.

• Example:

  • Size of Plant ➔ Amount of Water ➔ Number of Leaves ➔ Living or Dead?

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Cause and Effect Relationship

• Independent Variable: Manipulated variable.

• Dependent Variable: Measured variable.

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Exam Example Variables

• Independent Variable: Hours of Study.

• Dependent Variable: Exam Score.

• Moderator Variable: IQ.

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Multiple Independent and Dependent Variables

• Independent Variables:

  • Business orientation

  • Involved leadership

• Dependent Variables:

  • Employee participation

  • Perceived level of success

  • Organizational performance

• Moderating Variables:

  • Organizational size

  • Environmental conditions.

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Effect of Four Variables

• Independent Variable: Workforce Diversity.

• Intervening Variable: Managerial Expertise.

• Dependent Variable: Organizational Effectiveness and Synergy.

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Management of Information

• Independent Variables:

  • Size of Company

• Moderator Variable: Types of sources contributing to innovation performance.

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Goals of Theory

• Understanding and Predicting the future based on the relationships of the variables.

• Impactful example: Leadership and its effect on employee productivity.

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What is a Concept?

• Concept (Construct): A generalized idea about a class of objects, attributes, occurrences, or processes that has a name.

• Examples:

  • Business: Leadership, productivity, quality control.

  • Finance: Gross National Product, inflation.

  • Accounting: Assets, liabilities.

  • Marketing: Customer satisfaction, service quality.

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Conceptual Research Model

• Key Points:

  • Service quality

  • Tools of TQM

  • Tangible aspects of QFD and empathy.

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C19 Digitalization Process

• Concept, Variable, IV

• Organizational Performance: Concept, Variable, Measured, D.

• Organizational Retention: Concept, Variable, Measured, D.

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Impacts of Various Factors

• Effects and relationships studied:

  • Social media's role in tourism destination selection.

  • Impact of TQM on organizational performance.

  • Role of TQM tools in improving service quality.

  • Relationship between human capital and financial development.

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Research Propositions and Hypotheses

• Proposition: Statements explaining logical linkages among concepts, asserting universal connections.

• Examples:

  • Treating employees better leads to more loyalty.

• Hypotheses: Testable statements that predict outcomes based on propositions.

  • Example: Increasing benefits by 5% reduces annual turnover.

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Understanding Hypotheses

• Hypothesis: Educated guess about relationships between two or more variables, expressed in testable statements.

• Characteristics:

  1. Empirically testable.

  2. Clear and simple.

  3. Specific and relevant.

  4. Predictable outcomes.

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Relationships between Concepts

• Proposition: A theoretical statement about relationships between concepts.

• Hypothesis: An empirically testable theory yet to be verified.

• Use in deductive theorizing.

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Examples of Propositions and Hypotheses

• Proposition Example: Treating employees better enhances loyalty.

• Hypothesis Example: Offering employees an extra Friday off reduces turnover.

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Comparing Propositions and Hypotheses

• Both provide potential answers to scientific questions, focusing on connections between existing concepts.

• Key Difference: Propositions are conceptual; hypotheses are testable and measurable.

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Categories and Types of Hypotheses

• Simple Hypothesis: Reflects a relationship between two variables.

  • Example: Relationship between TQM tools and service quality.

• Complex Hypothesis: Involves more than two variables.

  • Example: Relationship among TQM tools, service quality, and customer satisfaction.

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Types of Hypotheses

• Non-Directional Hypothesis: Does not predict relationships.

  • Example: Differences in helpfulness between boys and girls.

• Use of conditional statements like