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Chapter 05: Descriptive, Predictive, and Causal Research Designs

Introduction

  • Learning transforms understanding and application in marketing research.

  • Focuses on quantitative methods to gather primary data.

Value of Descriptive and Causal Survey Research Designs

  • Primary Data: Essential for understanding large target populations.

  • Chapter 4 discussed qualitative methods with smaller samples.

  • This chapter emphasizes the importance of quantitative methods and survey designs in descriptive and causal research.

Descriptive Research Designs

  • Design Selection Factors:

    • Initial problem nature.

    • Research questions and objectives.

  • When to Use:

    • Describe characteristics of market situations or evaluate marketing strategies.

    • Research questions focused on who, what, where, when, how.

    • Identify relationships between variables or differences between groups.

Descriptive Research Surveys

  • Data Collection Approaches:

    • Asking questions.

    • Observation.

  • Data Visualization: Converts quantitative values to graphical formats for clear presentation.

  • Qualitative vs. Quantitative:

    • Qualitative: Produces vivid textual descriptions.

    • Quantitative: Uses statistics to summarize data.

Advantages and Disadvantages of Quantitative Survey Research Designs

  • Advantages:

    • Large sample sizes lead to generalizable results.

    • Identify small differences easily.

    • Easy administration with structured questions.

    • Facilitates advanced statistical analysis.

    • Explore non-directly measurable relationships and concepts.

  • Disadvantages:

    • Developing accurate measurement questions can be challenging.

    • Difficult to obtain in-depth data.

    • Low response rates can skew data reliability.

Types of Errors in Surveys

  • Sampling Error: Difference between sample findings and true population values; can be minimized by increasing sample size.

  • Nonsampling Errors:

    • Include respondent error, measurement design errors, incorrect problem definitions, and project administration errors.

    • Create systematic variation or bias; controllable but not directly measurable.

Respondent Errors

  • Types:

    • Nonresponse Error: Occurs when selected respondents cannot participate or refuse.

      • Solutions: multiple callbacks, follow-up mailings, incentives, shorter questionnaires.

    • Response Error: Arises from human memory or inaccurate recall; affected by selective perception and social desirability.

Types of Survey Methods: Person-Administered Surveys

  • Definition: Use trained interviewers for data collection.

  • Advantages:

    • Adaptable to respondent differences.

    • Builds rapport, creating a comfortable environment.

    • Allows for immediate feedback.

  • Disadvantages:

    • Potential for recording and interaction errors.

    • Higher costs involved.

In-Home Interviews

  • Advantages:

    • Clarification of complex questions through interviewer assistance.

    • Opportunity for product testing or ad evaluation.

    • Comfortable setting for respondents.

  • Disadvantages:

    • Potential for interviewer misconduct.

    • Time-consuming and expensive.

Mall-Intercept Interviews

  • Advantages:

    • Similar benefits to in-home interviews but in less familiar environments.

    • Cost-effective for researchers.

  • Disadvantages:

    • Similar issues as in-home interviews with added travel time.

    • Nonprobability sampling may affect generalizability.

Types of Survey Methods: Telephone-Administered Surveys

  • Benefits of telephone interviews include lower cost, swift data collection, and a wide geographical reach.

  • Disadvantages:

    • Limited to audio interaction; complex questions may be challenging.

    • Reduced availability of landlines.

    • Low participation rates.

CATI (Computer-Assisted Telephone Interviews)

  • Advantages:

    • Cost-effective per interview with real-time data processing.

    • Reduces potential coding errors.

  • Decline in Use: Due to the rise of more flexible and cost-effective online surveys.

Mobile Phone Surveys

  • Increasingly popular due to the prevalence of mobile device usage.

  • Advantages:

    • Immediate data capture, portability, access to respondents without landlines.

  • Disadvantages:

    • Regulatory constraints, potential costs to respondents, and not suitable for complex questions.

Types of Survey Methods: Self-Administered Surveys

  • Definition: Respondents complete surveys independently without interviewer presence.

  • Advantages:

    • Low cost, respondent control over responses, anonymity.

  • Disadvantages:

    • Limited flexibility, high nonresponse rates.

Mail Surveys

  • Advantages:

    • Inexpensive implementation, ability to reach hard-to-contact respondents.

  • Disadvantages:

    • Often suffer from lower response rates and potential misunderstandings.

Mail Panel Surveys

  • Advantages:

    • High response rates and can facilitate longitudinal studies.

  • Disadvantages:

    • May not represent broader target populations.

Drop-Off Surveys

  • Advantages:

    • On-site assistance for questions and motivation to complete.

  • Disadvantages:

    • Typically more expensive than standard mail surveys.

Online Survey Methods

  • Most popular survey method; Advantages:

    • Cost-effective, effective in reaching diverse samples, improves graphical capabilities.

  • Disadvantages:

    • Often not representative, high nonresponse bias, limited generalizability.

Selecting the Appropriate Survey Method: Situational Characteristics

  • Goals include producing usable data rapidly and economically.

  • Considerations involve budget, completion timeframe, and quality requirements (depth, breadth, generalizability, and accuracy).

Selecting the Appropriate Survey Method: Task Characteristics

  • Account for respondent engagement and task simplicity.

  • Assess the required stimuli and sensitivity of research topics.

Selecting the Appropriate Survey Method: Respondent Characteristics

  • Influence of target respondents’ common traits on survey methods.

  • Considerations include incidence rates and willingness to participate.

Predictive Research Designs

  • Aim to explain future outcomes using non-experimental relationships.

  • Analyzed through statistical methods like regression and machine learning.

  • Digital marketing analytics are increasingly facilitating predictive research applications.

Causal Research Designs

  • Focus on causality between independent (X) and dependent (Y) variables, framing questions as "If X, then Y."

  • Involves experiments to manipulate variables and measure effects.

The Nature of Experimentation

  • Causal research elucidates cause-and-effect relationships through experiments, controlling various variables to understand causal impacts.

Validity Concerns with Experimental Research

  • Internal Validity: Accuracy in identifying causal relationships.

  • External Validity: Ability to generalize results to wider populations.

  • Types of experimental designs: pre-experimental, true experimental, and quasi-experimental.

Comparing Laboratory and Field Experiments

  • Lab experiments offer high internal validity but can lack external applicability.

  • Field experiments provide realistic conditions but pose challenges in controlling external variables.

Test Marketing

  • Uses experiments to evaluate market performance in pilot tests and marketing mix applications.

  • Objectives include sales prediction, reaction assessment, and consequence anticipation.

  • Test marketing can incur significant costs.


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Hair_EOMR_6e_Chap005_PPT_Accessible_-_Tagged

Chapter 05: Descriptive, Predictive, and Causal Research Designs

Introduction

  • Learning transforms understanding and application in marketing research.

  • Focuses on quantitative methods to gather primary data.

Value of Descriptive and Causal Survey Research Designs

  • Primary Data: Essential for understanding large target populations.

  • Chapter 4 discussed qualitative methods with smaller samples.

  • This chapter emphasizes the importance of quantitative methods and survey designs in descriptive and causal research.

Descriptive Research Designs

  • Design Selection Factors:

    • Initial problem nature.

    • Research questions and objectives.

  • When to Use:

    • Describe characteristics of market situations or evaluate marketing strategies.

    • Research questions focused on who, what, where, when, how.

    • Identify relationships between variables or differences between groups.

Descriptive Research Surveys

  • Data Collection Approaches:

    • Asking questions.

    • Observation.

  • Data Visualization: Converts quantitative values to graphical formats for clear presentation.

  • Qualitative vs. Quantitative:

    • Qualitative: Produces vivid textual descriptions.

    • Quantitative: Uses statistics to summarize data.

Advantages and Disadvantages of Quantitative Survey Research Designs

  • Advantages:

    • Large sample sizes lead to generalizable results.

    • Identify small differences easily.

    • Easy administration with structured questions.

    • Facilitates advanced statistical analysis.

    • Explore non-directly measurable relationships and concepts.

  • Disadvantages:

    • Developing accurate measurement questions can be challenging.

    • Difficult to obtain in-depth data.

    • Low response rates can skew data reliability.

Types of Errors in Surveys

  • Sampling Error: Difference between sample findings and true population values; can be minimized by increasing sample size.

  • Nonsampling Errors:

    • Include respondent error, measurement design errors, incorrect problem definitions, and project administration errors.

    • Create systematic variation or bias; controllable but not directly measurable.

Respondent Errors

  • Types:

    • Nonresponse Error: Occurs when selected respondents cannot participate or refuse.

      • Solutions: multiple callbacks, follow-up mailings, incentives, shorter questionnaires.

    • Response Error: Arises from human memory or inaccurate recall; affected by selective perception and social desirability.

Types of Survey Methods: Person-Administered Surveys

  • Definition: Use trained interviewers for data collection.

  • Advantages:

    • Adaptable to respondent differences.

    • Builds rapport, creating a comfortable environment.

    • Allows for immediate feedback.

  • Disadvantages:

    • Potential for recording and interaction errors.

    • Higher costs involved.

In-Home Interviews

  • Advantages:

    • Clarification of complex questions through interviewer assistance.

    • Opportunity for product testing or ad evaluation.

    • Comfortable setting for respondents.

  • Disadvantages:

    • Potential for interviewer misconduct.

    • Time-consuming and expensive.

Mall-Intercept Interviews

  • Advantages:

    • Similar benefits to in-home interviews but in less familiar environments.

    • Cost-effective for researchers.

  • Disadvantages:

    • Similar issues as in-home interviews with added travel time.

    • Nonprobability sampling may affect generalizability.

Types of Survey Methods: Telephone-Administered Surveys

  • Benefits of telephone interviews include lower cost, swift data collection, and a wide geographical reach.

  • Disadvantages:

    • Limited to audio interaction; complex questions may be challenging.

    • Reduced availability of landlines.

    • Low participation rates.

CATI (Computer-Assisted Telephone Interviews)

  • Advantages:

    • Cost-effective per interview with real-time data processing.

    • Reduces potential coding errors.

  • Decline in Use: Due to the rise of more flexible and cost-effective online surveys.

Mobile Phone Surveys

  • Increasingly popular due to the prevalence of mobile device usage.

  • Advantages:

    • Immediate data capture, portability, access to respondents without landlines.

  • Disadvantages:

    • Regulatory constraints, potential costs to respondents, and not suitable for complex questions.

Types of Survey Methods: Self-Administered Surveys

  • Definition: Respondents complete surveys independently without interviewer presence.

  • Advantages:

    • Low cost, respondent control over responses, anonymity.

  • Disadvantages:

    • Limited flexibility, high nonresponse rates.

Mail Surveys

  • Advantages:

    • Inexpensive implementation, ability to reach hard-to-contact respondents.

  • Disadvantages:

    • Often suffer from lower response rates and potential misunderstandings.

Mail Panel Surveys

  • Advantages:

    • High response rates and can facilitate longitudinal studies.

  • Disadvantages:

    • May not represent broader target populations.

Drop-Off Surveys

  • Advantages:

    • On-site assistance for questions and motivation to complete.

  • Disadvantages:

    • Typically more expensive than standard mail surveys.

Online Survey Methods

  • Most popular survey method; Advantages:

    • Cost-effective, effective in reaching diverse samples, improves graphical capabilities.

  • Disadvantages:

    • Often not representative, high nonresponse bias, limited generalizability.

Selecting the Appropriate Survey Method: Situational Characteristics

  • Goals include producing usable data rapidly and economically.

  • Considerations involve budget, completion timeframe, and quality requirements (depth, breadth, generalizability, and accuracy).

Selecting the Appropriate Survey Method: Task Characteristics

  • Account for respondent engagement and task simplicity.

  • Assess the required stimuli and sensitivity of research topics.

Selecting the Appropriate Survey Method: Respondent Characteristics

  • Influence of target respondents’ common traits on survey methods.

  • Considerations include incidence rates and willingness to participate.

Predictive Research Designs

  • Aim to explain future outcomes using non-experimental relationships.

  • Analyzed through statistical methods like regression and machine learning.

  • Digital marketing analytics are increasingly facilitating predictive research applications.

Causal Research Designs

  • Focus on causality between independent (X) and dependent (Y) variables, framing questions as "If X, then Y."

  • Involves experiments to manipulate variables and measure effects.

The Nature of Experimentation

  • Causal research elucidates cause-and-effect relationships through experiments, controlling various variables to understand causal impacts.

Validity Concerns with Experimental Research

  • Internal Validity: Accuracy in identifying causal relationships.

  • External Validity: Ability to generalize results to wider populations.

  • Types of experimental designs: pre-experimental, true experimental, and quasi-experimental.

Comparing Laboratory and Field Experiments

  • Lab experiments offer high internal validity but can lack external applicability.

  • Field experiments provide realistic conditions but pose challenges in controlling external variables.

Test Marketing

  • Uses experiments to evaluate market performance in pilot tests and marketing mix applications.

  • Objectives include sales prediction, reaction assessment, and consequence anticipation.

  • Test marketing can incur significant costs.