Marketing Research
Preface
1
Introduction
1.1
Approaches to Research
1.1.1
Theory First Approaches
1.1.2
Empiric First-Apporaches
1.1.3
A Shift to Observable-to-construct links
1.1.4
Conceptual Contributions
1.1.5
Disruption-Driven Anomalies Apporach
I CONSTRUCTS
2
Construct vs. Variable
3
Satisfaction
4
Innovation
4.1
Innovation Measure
4.2
New Product Development
4.3
Research and Development
5
Market Entry
6
WOM / Virality
6.1
Structural Virality
6.1.1
Network Structure and position
6.1.2
Seeding Strategies
6.2
Mechanisms/ Processes
6.2.1
Impression Management
6.2.2
Emotion regulation
6.2.3
Information acquisition
6.2.4
Social bonding
6.2.5
Persuading others
6.3
Moderators
6.3.1
Tie Strength
6.4
Drivers of Virality
6.4.1
Social Currency
6.4.2
Accessibility
6.4.3
Emotions
6.4.4
Usefulness
6.4.5
Narratives
6.5
Other variables
6.5.1
Controversality
6.5.2
Popularity
6.5.3
Contractuality
6.5.4
Locus of Control
6.5.5
Horizontal/Vertical Individualism
6.5.6
Linguistic style
6.6
Negative Virality
6.7
Articles
7
Sarcasm
II SUBSTANCE
8
Branding
8.1
Brand Elements
8.1.1
Brand Name
8.1.2
Brand Logos
8.1.3
Brand Slogans
8.2
Brand Marketing
8.2.1
Brand Advertising
8.2.2
Brand Promotion
8.3
Brand Equity
8.3.1
Brand Loyalty
8.3.2
Brand Awareness
8.3.3
Brand Associations
8.3.4
Perceived Quality
8.4
Brand Authenticity
8.5
Brand Relationship
8.5.1
Brand Love
8.6
Reputation
8.7
Brand Evaluation
8.8
Brand Favorability
8.9
Branding Portfolio Management
8.9.1
Brand Architecture/Portfolio
8.9.2
Brand Extensions
8.10
Strategic Branding Decisions
8.10.1
Brand Crisis/ Recovery
8.10.2
Global Brand Strategy
8.10.3
Competitors
8.11
Brand-Consumer Interaction
8.11.1
Brand Experience
8.11.2
Brand Cocreation
8.11.3
Brand Community
9
Virtual Environment
9.1
Email
9.2
Social Media
9.3
Who-Generated Content
9.4
Images
9.5
Mobile and Smartphone
9.6
Review
9.7
Slacktivism
9.8
e-Marketplace
9.9
Social Listening Platforms
9.9.1
Fake Check Platform
9.10
Live Streaming
9.11
Augmented Reality
9.12
Artificial Intelligence
9.13
Search Engine
9.14
Customer Engagement
9.15
Wisdom of the Crowds
10
Advertising
10.1
Behavioral Approach
10.1.1
Cognitive and Affective
10.1.2
Involvement
10.1.3
Visual Cues
10.2
Econometric Approach
10.2.1
Product Placements
10.2.2
Deceptive Advertising
10.2.3
Advertising Effects
10.2.4
Estimation of Advertising Effects
10.2.5
Spillovers
10.2.6
Attribution of Advertising Effects
10.2.7
Advertising Content
10.2.8
Consumer Demand for Ads
11
Communication
11.1
Information Theory
11.1.1
Entropy
11.1.2
Divergence
11.1.3
Channel Capacity
12
Sales
12.1
Sales from Rank
12.2
Salespeople
13
Customer Lifetime Value (CLV)
13.1
Example
13.2
Referral value (CRV)
14
Celebrity Endorsement
15
Nudges
16
Marketing-Finance Interface
16.1
Marketing Value
16.2
Business Valuation
16.3
M&A
16.4
Stock Return Response Modeling
16.5
Tobin’s Q
16.6
Corporate Agility
16.7
Firm Complexity
16.8
Initial Coin Offerings
16.9
Initial Public Offerings
17
Privacy
17.1
Psychology of Privacy
17.2
Organizational Perspective
17.3
Privacy Paradox
17.3.1
Tradeoff
17.3.2
No tradeoff
17.4
Privacy Calculus/ Economics of Privacy
17.5
GDPR
III METHODOLOGY
18
Metrics
18.1
Finance
18.1.1
Return on Investment (ROI)
18.1.2
Economic Value Added
18.1.3
Market Value Added
18.1.4
Unexpected size-adjusted advertising investments
18.1.5
Shareholder Complaints
18.1.6
Profitability
18.1.7
Firm Size
18.1.8
Sales Growth
18.1.9
Financial Flexibility
18.1.10
Cash flows
18.1.11
Financial Leverage
18.1.12
Stock return
18.1.13
Financial Flexibility
18.1.14
Book Equity
18.1.15
Net Contribution
18.1.16
Diversity
18.2
Marketing
18.2.1
Trust
18.2.2
Sentiment
18.2.3
Purchase Intention
18.2.4
Brand Reputation
18.2.5
Capabilities
19
Data
19.1
MongoDB
19.2
WRDS
19.3
YouTube
19.3.1
OAuth
19.3.2
API
19.3.3
Python
19.4
Consumer Expenditure
19.5
Gender, Age, Nationality
19.6
Google Trends
19.6.1
Relative Search
19.6.2
Absolute Search
19.7
Baidu Index
20
Modeling in Marketing
20.1
Definitions
20.2
Quasi-Experimental
20.3
Transformation
20.3.1
Log-transformation
20.4
Endogeneity
20.4.1
Control Function
20.5
Variance Info Factors
21
Analytical Models
21.1
Building An Analytical Model
21.2
Hotelling Model
21.3
Positioning Models
21.4
Market Structure and Framework
21.4.1
Cournot - Simultaneous Games
21.4.2
Stackelberg - Sequential games
21.5
More Market Structure
21.6
Market Response Model
21.7
Technology and Marketing Structure and Economics of Compatibility and Standards
21.8
Conjoint Analysis and Augmented Conjoint Analysis
21.9
Distribution Channels
21.10
Advertising Models
21.11
Product Differentiation
21.12
Product Quality, Durability, Warranties
21.12.1
Akerlof (1970)
21.12.2
Spence (1973)
21.12.3
S. Moorthy and Srinivasan (1995)
21.13
Bargaining
21.13.1
Non-cooperative
21.13.2
Cooperative
21.13.3
Nash (1950)
21.13.4
Iyer and Villas-Boas (2003)
21.13.5
Desai and Purohit (2004)
21.14
Pricing and Search Theory
21.14.1
Varian and Purohit (1980)
21.14.2
Lazear (1984)
21.15
Pricing and Promotions
21.15.1
Narasimhan (1988)
21.15.2
Balachander, Ghosh, and Stock (2010)
21.15.3
Goić, Jerath, and Srinivasan (2011)
21.16
Market Entry Decisions and Diffusion
21.17
Principal-agent Models and Salesforce Compensation
21.17.1
Gerstner and Hess (1987)
21.17.2
Basu et al. (1985)
21.17.3
Raju and Srinivasan (1996)
21.17.4
Lal and Staelin (1986)
21.17.5
Simester and Zhang (2010)
21.18
Branding
21.19
Marketing Resource Allocation Models
21.19.1
Case study 1
21.19.2
Case study 2
21.19.3
Case study 3
21.20
Mixed Strategies
21.21
Bundling
21.22
Market Entry and Diffusion
21.23
Principal-Agent Models and Salesforce Compensation
21.23.1
Basu et al. (1985)
21.23.2
Lal and Staelin (1986)
21.23.3
Raju and Srinivasan (1996)
21.23.4
Joseph and Thevaranjan (1998)
21.23.5
Simester and Zhang (2010)
21.24
Meta-analyses of Econometric Marketing Models
21.25
Dynamic Advertising Effects and Spending Models
21.26
Marketing Mix Optimization Models
21.27
New Product Diffusion Models
21.28
Two-sided Platform Marketing Models
22
Empirical Models
22.1
Attribution Models
22.1.1
Ordered Shapley
22.1.2
Markov Model
22.2
Sales Funnel
22.2.1
Example 1
22.2.2
Example 2
22.3
RFM
22.3.1
Visualization
22.3.2
RFMC
22.4
Customer Segmentation
22.4.1
Example 1
22.4.2
Example 2
22.5
Shopping carts analysis
22.5.1
Multi-layer pie chart
22.5.2
Sankey Diagram
22.5.3
Sequence in-depth analysis
22.6
Geodemographic Classification
23
Model Building
24
Structural Models
24.1
Top Seminal Papers
24.2
To get started in this area
24.2.1
Books
24.3
Structural modeling and Causal Inference
25
Qualitative Research
25.1
Inter-rate reliability methods
25.1.1
Percent Agreement
25.1.2
Cohen’s Kappa
25.1.3
Fleiss’kappa
25.2
Krippendorff’s Alpha
25.2.1
Kendall’s W
25.2.2
Intraclass correlation coefficients
25.2.3
Light’s kappa
26
Measurement Scales
27
Preference Measurement
27.1
Conjoint Analysis
27.1.1
Full-Profile
27.1.2
Choice-based
27.1.3
Adaptive
27.1.4
Hybrid
27.1.5
Max-Diff
27.1.6
Self-explicated
27.1.7
Hierarchical Bayes analysis
27.1.8
Application
28
Image Processing
29
Surveys
29.1
Anchoring Vignettes
29.1.1
Nonparametric method
29.1.2
Parametric method
30
Experiment
IV OTHERS
31
Report
32
Review Process
32.1
Review at JM
32.2
Review Process Back end
33
Scientific Writing
34
CB Seminar
34.1
Overview
34.2
Social Influence
34.3
Interpersonal perception and consumer lay beliefs
34.4
Emotions, mood and affect
34.5
Persuasion and attitude change
34.6
Judgment and decision making and behavioral pricing
34.7
Goals and Motivation
34.8
Culture and consumer behavior
34.9
Prosocial behavior and morality
34.10
Consumer well-being & Food Consumption Decisions
34.11
Digital marketing and WOM
34.12
Experiential consumption and time
35
Marketing Mix Models
35.1
Discrete Choice Models and Continuous Heterogeneity
35.2
Structural Models, Endogeneity
35.2.1
Background
35.2.2
Examples
35.3
Cross-Category and Store Choice Models
35.3.1
Background
35.3.2
Examples
35.4
Policy Applications of
Discrete Choice Models
35.4.1
(Khan, Misra, and Singh 2015)
35.4.2
(A. Rao and Wang 2017)
35.4.3
(Tuchman 2019)
35.4.4
(Seiler, Tuchman, and Yao 2020)
35.5
Frontier Papers
35.5.1
(Neumann, Tucker, and Whitfield 2019)
35.6
Advertising Response Measurement
35.6.1
(Terui, Ban, and Allenby 2011)
35.6.2
(Narayanan and Kalyanam 2015)
35.6.3
(Lewis and Rao 2015)
35.6.4
(Gordon, Zettelmeyer, et al. 2019)
36
Strategic Dynamic Models
36.1
Market Entry
36.1.1
(Peter N. Golder and Tellis 1993)
36.1.2
(J. Johnson and Tellis 2008)
36.1.3
(Zervas, Proserpio, and Byers 2017)
36.2
Product Adoption and Diffusion
36.2.1
Background
36.2.2
Discussion
36.3
Take-off Disruption
36.3.1
Disruptive Technologies
36.3.2
(Peter N. Golder and Tellis 1997)
takeooff
36.3.3
(Chandy and Tellis 2000)
Incumbent’s curse
36.3.4
(Tellis, Stremersch, and Yin 2003)
International Takeoff
36.3.5
(Hauser, Tellis, and Griffin 2006)
Review on Innovation
36.3.6
(Chandrasekaran and Tellis 2008)
Global Takeoff
36.3.7
(Sood and Tellis 2011)
Predict takeoff
36.3.8
(M. Zhang and Luo 2016)
Restaurant survival from Yelp
36.4
Advertising Response (Effectiveness)
36.4.1
(Tellis, Chandy, and Thaivanich 2000)
Direct TV ad
36.4.2
(Tellis and Franses 2006)
Optimal Data Interval for estimating ad response (on sales)
36.4.3
(T. S. Teixeira, Wedel, and Pieters 2010)
Ad Pulsing to prevent consumer ad avoidance
36.4.4
(Sethuraman, Tellis, and Briesch 2011)
Advertising effectiveness meta-analysis
36.4.5
(Liaukonyte, Teixeira, and Wilbur 2015)
TV advertising on online shopping
36.4.6
(Tirunillai and Tellis 2017)
TV ad on Online chatter: synthetic control
36.5
Marketing Return
36.5.1
(Fornell et al. 2006)
Customer satisfaction and stock return
36.5.2
(S. Srinivasan and Hanssens 2009)
Marketing and Firm Value
36.5.3
(Sood and Tellis 2009)
Innovation and Stock Return
36.5.4
(Jacobson and Mizik 2009b)
36.5.5
(Jacobson and Mizik 2009a)
36.5.6
(Borah and Tellis 2014)
Choice of Payoff from announcements (Innovations)
36.5.7
(Tirunillai and Tellis 2012)
Chatter effect on stock performance
36.6
Creativity
36.6.1
(Bayus 2013)
Crowdsourcing New Product Ideas over Time
36.6.2
(Toubia and Netzer 2017)
Idea generation, creativity, prototypicality
36.6.3
(Y. “Max”. Wei, Hong, and Tellis 2021)
Machine leaning creativity
36.6.4
Can AI do ideation? 2022
36.6.5
(Berger and Packard 2018)
Content Atypicality
36.6.6
(Stephen, Zubcsek, and Goldenberg 2016)
The Effects of Network Structure on Redundancy of Ideas
36.7
Quality
36.7.1
(Tellis, Yin, and Niraj 2009)
Network effects and quality in high tech
36.7.2
(Peter N. Golder, Mitra, and Moorman 2012)
An Integrative Framework for Quality
36.7.3
(Tirunillai and Tellis 2014)
Mining Quality from Consumer Reviews
36.7.4
(Borah and Tellis 2016)
Spillover Effects in Social Media
37
WashU Analytical Model
37.1
Platforms
37.1.1
(Jiang, Jerath, and Srinivasan 2011)
Amazon’s mid-tail
37.1.2
(Zou and Zhou 2021)
search neutrality
37.1.3
Diao et al. 2021 P2P rideshare vs. taxi
37.1.4
(Gal-Or and Shi 2022)
Subscription platform
37.1.5
(Long, Jerath, and Sarvary 2022)
Design Amazon marketplace
37.1.6
(Hajihashemi, Sayedi, and Shulman 2021)
Personalized Pricing with Network Effects
37.2
Dynamic Pricing and Bundling
37.2.1
(Prasad, Venkatesh, and Mahajan 2017)
Bundling
37.2.2
(Diao, Harutyunyan, and Jiang 2019)
Intertemporal price, consumer fairness concern
37.2.3
(Dana and Williams 2022)
Intertemporal price
37.2.4
(Kolay and Tyagi 2022)
Event bundle
37.3
Consumer Fairness
37.3.1
(Fu et al. 2021)
Unfair machine learning algorithms
37.4
Decentralized Channels
37.4.1
(Jiang and Tian 2022)
Reactive capacity on product quality and profitability in uncertain markets
37.4.2
(Hu, Zheng, and Pan 2022)
Wholesale vs. Agency
37.5
Consumer Search
37.5.1
(Jiang and Zou 2020)
Consumer Search and Filtering on Online Retail Platforms
37.5.2
(Yanbin Chen et al. 2021)
Consumer Search with blind buying
37.5.3
(X. Li and Xu 2022)
Superior knowledge, price discrimination, and customer inspection
37.6
Review paper
38
Marketing Strategy
38.1
Intro
38.2
Branding
38.3
Channels and Customer Management
38.4
Human Capital
39
Others
V CASE STUDIES
40
Case Studies in Branding
40.1
Apple
: Innovation and Design as Brand Identity
40.2
Nike:
Building a Global Brand Through Storytelling and Innovation
40.3
Tesla: Revolutionizing the Automotive Industry Through Innovation and Sustainability
40.4
Amazon: Transforming Retail and Beyond
40.5
Zoom: Connecting the World Through Video Communications
40.6
Beyond Meat: A Plant-Based Revolution
40.7
TikTok: A Dance with Global Success
40.8
Coca-Cola: Quenching the World’s Thirst for Over a Century
40.9
Netflix: Redefining the Future of Entertainment
40.10
Airbnb: Disrupting the Hospitality Industry
40.11
Starbucks: Brewing Success Through Innovation and Responsibility
40.12
The Walt Disney Company: A Kingdom of Creativity and Innovation
40.13
McDonald’s: Serving Success with a Side of Innovation
40.14
Dove (Unilever): Crafting Beauty and Confidence
40.15
IKEA: A Symphony of Design, Affordability, and Sustainability
40.16
LEGO: Building Blocks of Innovation and Success
40.17
Slack: Revolutionizing Workplace Communication
40.18
Patagonia: A Case Study in Sustainable Business Practices
40.19
Spotify:
Transitioning from music sales to subscription streaming
40.20
Warby Parker:
Disrupting the traditional eyewear market with an online-first approach
40.21
Allbirds: A Case Study in Sustainable Footwear Innovation
41
Case Studies in Advertising
References
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Marketing Research
19.1
MongoDB
in
Mongo
shell to check the location of your MongoDB files
db.adminCommand("getCmdLineOpts")