Breakout 1: Online Retailing

Part 1: The Added Value of Data Analytics: Evidence from Online Retailers, Ayelet Israeli, Harvard Business School “As retailers adopt more advanced analytics solutions, firm competition might gradually be controlled more and more by automatic algorithms, providing a fascinating direction for researchers to understand these effects.”
Part 2: TBC

Breakout 2: Omnichannel Acquisition

Part 1: Price Dynamics on Amazon Marketplace: A Multivariate Random Forest Variable Selection Approach, JieZhang, University of Maryland
“A framework for assessing values of customers acquired via alternative channels and for designing targeted retention promotions by acquisition channel.”
Part 2: TBC

Breakout 3: Social Media Analytics

Part 1: A Fully Automated Approach for Classifying Marketer Generated Text on Social Media, Jennifer Cutler, Northwestern - Kellogg
“Provides a way of automatically tracking what brands are talking about on social media, circumventing the limitations of extant manual and supervised machine learning approaches.”
Part 2: TBC

Breakout 4: Above-the-line promotions

Part 1: Generalizable and Robust TV Advertising Effects, Anna Tuchman, Northwestern – Kellogg
“Brands invest millions of dollars every year in TV advertising, but many managers acknowledge the difficulty in measuring the effectiveness of their ad spending. Our results indicate that most brands in our data are advertising too much.”
Part 2: TBC

Breakout 5: Online promotion

Part 1: Looking Beyond Sales: Promotion Impact on Profit in Online Retailing, Dominik Papies, Universität Tübingen
“Which brand characteristics are correlated with promotion performance regarding sales, revenue, and profit? …Online retailers cannot maximize unit sales, revenue, and profits simultaneously”
Part 2: TBC

Breakout 6: Customer Experience

Part 1: Identifying substitution patterns using product reviews, Jörn Boehnke, Cornell University
“Our proposed method provides an alternative and easily accessible approach to estimating product substitutability and price sensitivity from consumer generated content alone, without requiring any sales data”
Part 2: TBC

Breakout 7: Customer Communication Analytics

Part 1: Quantity versus Quality: Revisited in the Online Knowledge Community, Yan Xu, Hong Kong Polytechnic University
Part 2: TBC

Breakout 8: Sales Forecasting

Part 1: Forecasting Sales with Full Competitive Search Data: Fusing Dynamics with Big Data, Abhishek Borah, INSEAD
“While competition is a main driver of a firm’s sales, traditionally competitive data are rarely used in modeling and forecasting sales. Managers need to think not just of subjective rivals but a whole set of rivals”
Part 2: TBC

Breakout 9: AI and Marketing Analytics

Part 1: Deep Learning Choice Models: Integrating Theory with Artificial Intelligence, Karsten Hansen, University of California, San Diego
“A critique of [machine learning] algorithms in Marketing is the lack of underlying theory – they are black-box algorithms. In truly big data, state-of-the-art AI algorithms can learn the underlying “correct” choice theory”
Part 2: TBC

Room 1: Big Data

Drowning in Metrics: How Managers Select and Trade-off Metrics, Ofer Mintz, University of Technology Sydney
“Analytics can be broken down as models and metrics. While most focus in marketing literature on models, metric use is crucial for marketing decision-making.”

Room 2: Pricings

Are Groupon Customers Worthwhile?, Sharmistha Sikdar, Tuck School of Business at Dartmouth College
“Business press reports Amazon’s usage of sophisticated pricing algorithms which has caused fierce competition between Amazon and 3P sellers.”

Room 3: Text Mining

A Linguistic Analysis of Forward-looking Firm Vocabulary, Sudhir Voleti, Indian School of Business (ISB)
“Firms' (specifically, their senior managements) develop worldviews based on how they interpret changing market environments matched to internal firm capabilities.”

Room 4: Location / motion analytics

Exercising Self-Control Through Self-Reward, Ran Kivetz, Columbia Business School
“Customary approach in economics & industry is to leverage primarily financial or monetary incentives to promote desired outcomes in a range of consequential domains, including health, education, labor, & prosocial behaviors.”

Room 1: Big Data

SKU outlier identification and prediction using supervised machine learning, Martin Hirche, University of Melbourne
“The relationship between distribution and market share consistently appears as a convex and increasing curve, where brands exponentially obtain higher market share with higher distribution.”

Room 2: Pricings

TBC

Room 3: Text Mining

How Language Shapes Prejudice Against Women…, David DeFranza, The University of Utah
“Understanding the nature and distribution of prejudicial bias in language can help inform more equitable marketing systems and interventions to reduce prejudice against women.”

Room 4: Location / motion analytics

Perils of Location Tracking? Personalized and Interpretable Privacy Preservation…, Natasha Foutz, University of Virginia
“Data collectors need techniques to preserve consumer privacy and advertiser utility before sharing location data with advertisers and facilitate advertisers to become butlers when using data.”

Room 1: Big Data

Combining Empirical Models and Field Experimentation , Ranjan Mishra, ESS Analysis, LLC
“Development and implementation of a large-scale, marketing analytics framework for improving the segmentation, targeting and optimization of a consumer-facing firm’s marketing activities.”

Room 2: Pricings

What's Shared on the Web May Affect Product Prices-Evidence…, Tarique Hossain, California State Polytechnic University
“Information gleaned from buyers’ online activity helps sellers adjust price (e.g., dynamic pricing by Amazon.com).”

Room 3: Text Mining

What Can We Learn from Online Movie Reviews?..., Madhumita Nanda, University of Sydney
“Despite the availability of rich textual information in the online product reviews, the content of these reviews has not been fully utilized to predict the rating of the products and consumer purchase behaviour.”

Room 4: Location / motion analytics

Utilizing Mobile Browsing Behavior to Predict Store Visit…, Evert de Haan, University of Groningen
“Mobile devices play an increasingly important role in the online customer journey. Still high resistance against buying mobile and preferences to purchase on less mobile devices or at offline stores.”

Room 1: Social Ties and Word of Mouth

A Friend in Need is a Friend Indeed: Strategic Contributions in Crowdsourcing, Tingting Fan, The Chinese University of Hong Kong
“Crowdfunding—the use of Internet platforms to raise funds from large numbers of people (e.g., Kickstarter) —has raised over $5.3billion in 2018 worldwide.”

Room 2: Price, Promotion and Demand

An Empirical Analysis of Interstore Promotional Elasticity in the US Supermarket Industry, Yuqing Ma, Monash University
“The study investigates the issue of interstore promotional effects on sales in the context of the US supermarket industry. US supermarkets are ​involved in the never-ending promotional environment in the industry as a result of the emergence of alternatives to retail stores.”

Room 3: Image Mining

Brand Image Mining: A Solution for Brand Logo Detection…, Amos Schikowsky, University of Hamburg
“While the number and importance of brand logos in UCG grows, this trend leads to a loss of control over brand impressions for marketeers and a need for logo detection.”

Room 4: Social Marketing

Absence Versus Presence-Focused GMO Labeling: Impact on Consumer Choice…, Youngju Kim, Neoma Business School
“Recently, the United States Drug Association made a ruling on GMO labelling that presents theoretically interesting research questions pertaining to the impact of GMO labelling on consumer choice.”

Room 1: Social Ties and Word of Mouth

The Effectiveness of Social Advertising: Evidence from a Large-Scale Field Experiment, Song Lin, Hong Kong University of Science and Technology
“There is limited empirical studies that identify the effectiveness of social advertising. The main challenges are identifying social influence form homophily and distinguishing between informational influence and normative influence.”

Room 2: Price, Promotion and Demand

An Empirical Analysis of Third-Degree Price Discrimination for Experiential Goods, Aidin Namin, Loyola Marymount University
“We develop a state-of-the-art analytical third-degree discrimination pricing model (Finite Mixture Modeling) and empirically validate it using a large dataset from the cruising industry in the United States.”

Room 3: Image Mining

Is Centre the Best Location? An Eye-Tracking Study of Text Message Location…, Junbum Kwon, University of New South Wales
“Text messages in print or video ads are essential for ad persuasion as they are the Brand Differentiating Messages. Ad actioners seems to believe that “centre” is always the best place for text messages.”

Room 4: Social Marketing

A War on Sugar? Finding the Sweet Spot in Sugar Reduction Strategies, Kristopher Keller, University of North Carolina at Chapel Hill
“Sugar consumption is at unhealthy levels; now mounting evidence that sugar is linked to diseases. Partly to avoid sugar taxes, brands, too, are actively participating in sugar-reduction efforts.”

Room 1: Customer Loyalty Analytics

Online Word of Mouth and the Performance of New Products, Lachlan Deer, Chicago Booth School of Business
“Consumers now spend more than 135 mins per day on social media. Social media sites contain a treasure-trove of decision relevant information. Online word of mouth is particularly important for new products.”

Room 2: Price, Promotion and Demand

Dissecting Organic Growth: Category Growth vs. Market Share, Arry Tanusondjaja,, Ehrenberg
“The objective of the research is to further understand the mechanisms of organic growth and their relationship with the size of the firm in the market.”

Room 3: Image Mining

Using Image and Text Mining to Investigate Consumer Engagement…, Iman Ahmadi, The University of Warwick
“More than 1/3 of the world population is active on Facebook and Twitter alone. Firms are interested in this consumer engagement as it enhances consumer satisfaction and loyalty and improves word-of-mouth and sales figures.”

Room 4: Social Marketing

Market Expansion While Balancing Social and Financial Objectives…, Jarrod Vassallo, The University of Sydney
“This paper analyses the targeting, entry and expansion decisions of social enterprises while balancing their dual social and financial objectives in an emerging market high risk and low-resource context.”

Room 1: Customer Loyalty Analytics

The Impact of Coalition LP Evolution on Member Purchase…, Wayne Taylor, Southern Methodist University
“Coalition loyalty programs offer incentives to members at multiple businesses (coalition “partners”).”

Room 2: Service Failure

Managing crisis: slicing vs chunking negative news announcements, Ljubomir Pupovac, University of New South Wales
“What drives firms to either make one large recall announcement (chunking) or to make recall announcements piece by piece (slicing)?”

Room 3: Machine learning

Hyderabad, India: Aggregate Demand Estimation Using Machine Learning…, ManishGangwar, Indian School of Business
“Aggregate Demand estimation is the basis for managerial decision making such as pricing, promotions, inventory planning etc.”

Room 4: Consumer Spending Patterns

The Impact of a Mobile Payment App: A Natural Experiment, Steven Lu, The University of Sydney
“Does mobile payment improve firms’ performance by boosting the sales or simple replace other payment methods? Does it vary across products and geographical areas? How does it influence impulse purchases?”

Room 1: Customer Loyalty Analytics

Customer Relationship Management through Goal Setting Features…, Christine Eckert, University of Technology Sydney
“Use of synthetic control methods to compare outcomes (savings, churn, etc) of customers who set a goal against the outcomes of an artificial (control) consumer being a weighted average of customers who did not set goals.”

Room 2: Service Failure

Service Failure in the Public Transportation Industry: Modeling its Impact on Sales, Marc Fischer, University of Cologne/UTS
“Railway is faced with numerous individual service failures perceived by passengers. For efficient resource allocation, knowledge of sales impact of failures are necessary.”

Room 3: Machine learning

Predicting customer future with autoregressive neural nets, Thomas Reutterer, WU Vienna University of Economics and Business
“Hidden layers of a deep neural network model with LSTM (Long Short-Term Memory) cells decide on what's useful to memorize and what not to predict customer behavior.”

Room 4: Consumer Spending Patterns

Mood and Consumption Choices: Evidence from Sunshine Data, Andre Bonfrer, Deakin University
“There is a lack of large-scale empirical evidence on the role that transient consumer sentiment has on consumer spending habits”

Room 1: Customer Loyalty Analytics

IoT, Sensor Data, and Customer Relationship Management: The Case of Usage-Based Automobile Insurance, Miremad Soleymanian, Simon Fraser University (Beedie School of Business)
“Usage-Based Insurance (UBI) is a recent IoT-based innovation by auto insurers that more closely aligns driving behaviors

Room 2: Service Failure

The Long-term Effect of Frequent Product Recalls on the Recalling Firm's Reputation, Dong Liu, University of South Florida
“Firms frequently recall their products. Consumers might be insensitive to frequent product recalls. On the other hand, consumers might be more disappointed with frequent product recalls. The answer to the research problem above is unclear.”

Room 3: Machine learning

Capturing Consumer Heterogeneity with Asymmetric Variational Auto Encoder, Feihong Xia, University of Rhode Island
“The proposed model helps marketers to understand consumers’ diverse preferences over products better and provides better consumer purchase prediction and consumer segmentation based on purchasing behavior.”

Room 4: Consumer Spending Patterns

Life Shocks: The Effects on Food Baskets, Fatima Madani, Monash University
“Lack of comprehensive study on the impact of life events, i.e. period of stability Vs. period of instability.”

Room 1: Access-Based Consumption

Content Monetization and Preview Design, Dai Yao, National University of Singapore
“How pay-what-you-want affects content generation and preview design is an urgent question, but neither academics nor practitioners have an answer yet.”

Room 2: Segmentation

Market segmentation and competitor analytics…, Christopher Holland, Loughborough and Muenster Universities
“It is therefore important to explore how new forms of big data such as online panel data can be used for marketing analytics, particularly to measure and inform.”

Room 3: Models

Agent Based Models: Developing Flight Simulators for Researchers and Managers, Ian Wilkinson, University of Sydney
“ABM is a new methodology for understanding modelling and managing business systems.”

Room 4: Branding and Advertising

Be Typical, But Typical of What? The Role of Sport Event Typicality…, Francois Carrillat, University Technology Sydney
“Marketers are increasingly concerned about the effectiveness of advertisements because consumers’ exposure times to advertising messages is decreasing due to a faster paced lifestyle and a greater competition for their attention.”

Room 1: Access-Based Consumption

Is Streaming Killing the Superstar?, Christian Hotz-Behofsits, Vienna University of Economics and Business
“Over the last years, the total number of streams of the world’s biggest artists declined significantly.”

Room 2: Segmentation

Marketing Segmentation Process of Sports Spectator using Post-Hoc Approach, TatsuruNishio, Yamaguchi University
“The aim of this study is to show the marketing segmentation process with regard to sports spectators by using the spectator data of sports events.”

Room 3: Models

Agent Based Models: Developing Flight Simulators for Researchers and Managers, Nelyda Campos-Requena, Universidad Católica de la Santísima Concepción, Chile / Universidad del Desarrollo, Chile / Macquarie University, Australia
“We aim to compare the market segment predictions from both the MLM and LC to analyze consumers’ preference heterogeneity by exploiting these individual-level parameters.”

Room 4: Branding and Advertising

Branded mobile apps, Lara Stocchi, Flinders University
“Effective ‘pull’ advertising medium1, which has transformed the way firms communicate to consumers increasing familiarity and accessibility of brands by prompting context-dependent brand recall on a frequent basis.”

Room 1: Access-Based Consumption

Up Next: How Playlists Affect Music Consumption…, Nils Wloemert, Vienna University of Economics and Business
“Music consumption is shifting from ownership-based business models (e.g., CDs, downloads) to access-based business models (e.g., streaming services like Spotify).”

Room 2: Segmentation

Spectators' Game Watching Motives & Consumption Behaviours…, Ning (Chris) Chen, University of Canterbury
“An accurate segmentation of sport spectator consumers provides a better understanding on how to market different products to them and encourage behaviours.”

Room 3: Models

A Theory of Negativity Bias, Jihwan Moon, University of New South Wales
“This paper provides a rational model for the negativity bias in a general context and proves the universality of the negativity bias.”

Room 4: Branding and Advertising

Attributing Store Traffic to Advertising: The Case of Home Improvement…, Bhoomija Ranjan, Monash University
“Is advertising effective in driving store traffic? How do individual characteristics such as distance-to-store, demographics affect response to own & rival-brand advertising?”