| Working Paper |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A compared R&D-based and patent-based cross impact analysis for identifying relationships between technologies |
0 |
0 |
1 |
161 |
2 |
2 |
5 |
523 |
| An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
33 |
| An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction |
0 |
0 |
0 |
193 |
1 |
2 |
7 |
695 |
| An extended Huff-model for robustly benchmarking and predicting retail network performance |
0 |
0 |
2 |
54 |
0 |
0 |
6 |
212 |
| Analyzing existing customers’ websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing |
0 |
0 |
2 |
158 |
0 |
2 |
5 |
674 |
| Assessing and exploiting the profit function by modeling the net impact of targeted marketing |
0 |
0 |
0 |
316 |
0 |
0 |
0 |
1,056 |
| Banking behaviour after the lifecycle event of “moving in together”: An exploratory study of the role of marketing investments |
0 |
0 |
0 |
188 |
1 |
1 |
1 |
721 |
| Bayesian Kernel-Based Classification for Financial Distress Detection |
0 |
0 |
1 |
324 |
0 |
0 |
1 |
799 |
| Bayesian Network Classifiers for Identifying the Slope of the Customer - Lifecycle of Long-Life Customers |
1 |
2 |
4 |
1,135 |
2 |
6 |
17 |
4,395 |
| Benefits of Quantile Regression for the Analysis of Customer Lifetime Value in a Contractual Setting: An Application in Financial Services |
1 |
1 |
8 |
569 |
2 |
4 |
16 |
1,471 |
| Binary quantile regression: A Bayesian approach based on the asymmetric Laplace density |
1 |
2 |
7 |
479 |
3 |
14 |
37 |
1,609 |
| CRM at a Pay-TV Company: Using Analytical Models to Reduce Customer Attrition by Targeted Marketing for Subscription Services |
0 |
1 |
4 |
3,230 |
4 |
10 |
105 |
10,847 |
| Cash Demand Forecasting in ATMs by Clustering and Neural Networks |
0 |
0 |
3 |
239 |
1 |
3 |
15 |
960 |
| Churn Prediction in Subscription Services: an Application of Support Vector Machines While Comparing Two Parameter-Selection Techniques |
0 |
3 |
15 |
907 |
1 |
7 |
35 |
2,438 |
| Churn prediction in subscription services: an application of support vector machines while comparing two parameter-selection techniques |
0 |
0 |
0 |
0 |
0 |
1 |
5 |
36 |
| Constrained optimization of data-mining problems to improve model performance: A direct-marketing application |
0 |
0 |
2 |
819 |
1 |
1 |
12 |
3,120 |
| Customer Attrition Analysis For Financial Services Using Proportional Hazard Models |
0 |
1 |
12 |
3,631 |
1 |
6 |
24 |
9,311 |
| Customer Base Analysis: Partial Defection of Behaviorally-Loyal Clients in a Non-Contractual FMCG Retail Setting |
2 |
2 |
4 |
1,709 |
4 |
6 |
21 |
5,049 |
| Customer-Adapted Coupon Targeting Using Feature Selection |
0 |
0 |
1 |
240 |
1 |
2 |
3 |
822 |
| Data Augmentation by Predicting Spending Pleasure Using Commercially Available External Data |
0 |
0 |
0 |
287 |
1 |
2 |
2 |
770 |
| Deep Habits in Consumption: A Spatial Panel Analysis Using Scanner Data |
0 |
0 |
1 |
51 |
0 |
0 |
1 |
140 |
| Direct and Indirect Effects of Retail Promotions |
0 |
3 |
11 |
779 |
2 |
7 |
23 |
3,112 |
| Does Attitudinal Commitment to Stores Always Lead to Behavioral Loyalty? The Moderating Effect of Age |
0 |
1 |
2 |
413 |
0 |
1 |
4 |
1,426 |
| Dynamic cross-sales effects of price promotions: Empirical generalizations |
0 |
0 |
0 |
298 |
0 |
0 |
0 |
1,160 |
| Empathy as Added Value in Predicting Donation Behavior |
0 |
0 |
1 |
116 |
0 |
1 |
2 |
414 |
| Enhanced Decision Support in Credit Scoring Using Bayesian Binary Quantile Regression |
0 |
0 |
0 |
157 |
0 |
0 |
0 |
301 |
| Ensemble classification based on generalized additive models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
16 |
| Ensemble classification based on generalized additive models |
0 |
0 |
0 |
122 |
1 |
1 |
7 |
612 |
| Ensemble classification based on generalized additive models |
0 |
0 |
0 |
22 |
1 |
1 |
2 |
200 |
| Ensembles of probability estimation trees for Customer churn prediction |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
8 |
| Enterprise architecture management for small and medium sized enterprises: a case study and tool support |
0 |
1 |
4 |
264 |
0 |
1 |
8 |
649 |
| Evaluating the Added Value of Pictorial Data for Customer Churn Prediction |
0 |
0 |
0 |
26 |
0 |
0 |
0 |
115 |
| Exploiting Randomness for Feature Selection in Multinomial Logit: a CRM Cross-Sell Application |
0 |
0 |
0 |
264 |
0 |
0 |
1 |
642 |
| Handling class imbalance in customer churn prediction |
0 |
0 |
0 |
437 |
1 |
3 |
10 |
1,150 |
| IMPROVING CUSTOMER RETENTION IN FINANCIAL SERVICES USING KINSHIP NETWORK INFORMATION |
0 |
0 |
0 |
73 |
0 |
2 |
4 |
262 |
| Implicit Contracts and Price Stickiness: Evidence from Customer-Level Scanner Data |
0 |
0 |
0 |
28 |
1 |
2 |
2 |
157 |
| Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models |
1 |
1 |
4 |
171 |
1 |
1 |
10 |
463 |
| Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models |
0 |
0 |
0 |
46 |
1 |
1 |
4 |
241 |
| Improved Multilevel Security with Latent Semantic Indexing |
0 |
0 |
0 |
18 |
0 |
1 |
1 |
83 |
| Improved marketing decision making in a customer churn prediction context using generalized additive models |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
21 |
| Improving Customer Acquisition Models by Incorporating Spatial Autocorrelation at Different Levels of Granularity |
0 |
0 |
0 |
43 |
0 |
0 |
0 |
106 |
| Improving Customer Attrition Prediction by Integrating Emotions from Client/Company Interaction Emails and Evaluating Multiple Classifiers |
0 |
1 |
5 |
243 |
3 |
6 |
25 |
728 |
| Improving Customer Complaint Management by Automatic Email Classification Using Linguistic Style Features as Predictors |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
19 |
| Improving Customer Complaint Management by Automatic Email Classification Using Linguistic Style Features as Predictors |
0 |
2 |
6 |
1,084 |
1 |
7 |
21 |
3,727 |
| Improving campaign success rate by tailoring donation requests along the donor lifecycle |
0 |
0 |
1 |
164 |
0 |
1 |
4 |
438 |
| Improving customer attrition prediction by integrating emotions from client/company interaction emails and evaluating multiple classifiers |
0 |
0 |
0 |
1 |
1 |
1 |
2 |
21 |
| Improving purchasing behavior predictions by data augmentation with situational variables |
0 |
0 |
0 |
102 |
0 |
0 |
3 |
527 |
| Including Spatial Interdependence in Customer Acquisition Models: a Cross-Category Comparison |
0 |
0 |
0 |
14 |
0 |
0 |
1 |
84 |
| Incorporating sequential information into traditional classification models by using an element/position- sensitive SAM |
0 |
0 |
1 |
801 |
5 |
10 |
27 |
3,681 |
| Integrating the Voice of Customers through Call Center Emails into a Decision Support System for Churn Prediction |
0 |
0 |
4 |
1,188 |
0 |
2 |
20 |
2,994 |
| Integrating the voice of customers through call center emails into a decision support system for churn prediction |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
21 |
| Investigating Purchasing Patterns for Financial Services using Markov, MTD and MTDg Models |
0 |
0 |
1 |
665 |
0 |
0 |
3 |
2,350 |
| Investigating the post-complaint period by means of survival analysis |
0 |
0 |
0 |
133 |
1 |
1 |
1 |
428 |
| Investigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial services |
1 |
2 |
8 |
642 |
1 |
4 |
14 |
1,406 |
| Joint Optimization of Customer Segmentation and Marketing Policy to Maximize Long-Term Profitability |
0 |
1 |
5 |
2,490 |
0 |
1 |
8 |
11,258 |
| Joint optimization of customer segmentation and marketing policy to maximize long-term profitability |
0 |
0 |
0 |
67 |
0 |
0 |
1 |
204 |
| Kernel Factory: An Ensemble of Kernel Machines |
0 |
0 |
0 |
109 |
1 |
1 |
1 |
447 |
| Mining Ideas from Textual Information |
0 |
0 |
0 |
210 |
1 |
1 |
10 |
673 |
| Model-supported business-to-business prospect prediction based on an iterative customer acquisition framework |
1 |
4 |
16 |
132 |
3 |
7 |
32 |
336 |
| Modeling Partial Customer Churn: On the Value of First Product-Category Purchase Sequences |
0 |
0 |
0 |
133 |
0 |
0 |
4 |
490 |
| Modeling complex longitudinal consumer behavior with Dynamic Bayesian Networks: An Acquisition Pattern Analysis application |
0 |
0 |
0 |
305 |
0 |
0 |
0 |
878 |
| Neural Network Survival Analysis for Personal Loan Data |
0 |
0 |
4 |
601 |
2 |
2 |
12 |
1,582 |
| Predicting Customer Loyalty Using The Internal Transactional Database |
0 |
0 |
4 |
2,343 |
9 |
11 |
21 |
6,537 |
| Predicting Customer Profitability During Acquisition: Finding the Optimal Combination of Data Source and Data Mining Technique |
0 |
0 |
2 |
132 |
0 |
1 |
7 |
357 |
| Predicting Customer Retention and Profitability by Using Random Forests and Regression Forests Techniques |
0 |
1 |
3 |
1,393 |
0 |
1 |
11 |
4,245 |
| Predicting Mail-Order Repeat Buying: Which Variables Matter? |
0 |
0 |
4 |
997 |
1 |
3 |
11 |
4,022 |
| Predicting Online Purchasing Behavior |
0 |
1 |
6 |
2,412 |
3 |
6 |
30 |
7,075 |
| Predicting Partial Customer Churn Using Markov for Discrimination for Modeling First Purchase Sequences |
0 |
0 |
1 |
165 |
1 |
2 |
9 |
659 |
| Predicting home-appliance acquisition sequences: Markov/Markov for Discrimination and survival analysis for modeling sequential information in NPTB models |
0 |
0 |
0 |
475 |
3 |
7 |
18 |
1,961 |
| Predicting web site audience demographics for web advertising targeting using multi-web site clickstream data |
0 |
0 |
1 |
445 |
0 |
0 |
6 |
1,469 |
| Predicting website audience demographics for web advertising targeting using multi website clickstream data |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
37 |
| Price Rigidity in Europe and the US: A Comparative Analysis Using Scanner Data |
0 |
0 |
1 |
24 |
0 |
0 |
3 |
222 |
| Price rigidity in Europe and the US: A comparative analysis using scanner data |
0 |
0 |
0 |
56 |
0 |
0 |
5 |
203 |
| Protecting Research and Technology from Espionage |
0 |
0 |
0 |
57 |
1 |
1 |
1 |
195 |
| Quantitative Cross Impact Analysis with Latent Semantic Indexing |
0 |
0 |
0 |
17 |
0 |
1 |
1 |
92 |
| Random Forrests for Multiclass classification: Random Multinomial Logit |
0 |
0 |
4 |
841 |
0 |
1 |
9 |
2,010 |
| Random Multiclass Classification: Generalizing Random Forests to Random MNL and Random NB |
0 |
0 |
2 |
420 |
1 |
2 |
6 |
1,107 |
| Reconciling Performance and Interpretability in Customer Churn Prediction using Ensemble Learning based on Generalized Additive Models |
0 |
0 |
0 |
96 |
0 |
0 |
1 |
279 |
| Reconciling performance and interpretability in customer churn prediction modeling using ensemble learning based on generalized additive models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
29 |
| Semantic Compared Cross Impact Analysis |
0 |
0 |
0 |
14 |
0 |
0 |
0 |
65 |
| Separating Financial From Commercial Customer Churn: A Modeling Step Towards Resolving The Conflict Between The Sales And Credit Department |
0 |
1 |
4 |
482 |
1 |
3 |
13 |
2,049 |
| Technology Classification with Latent Semantic Indexing |
0 |
0 |
0 |
50 |
0 |
0 |
0 |
144 |
| The Impact of Sample Bias on Consumer Credit Scoring Performance and Profitability |
0 |
0 |
0 |
396 |
0 |
0 |
3 |
994 |
| The Kinked Demand Curve and Price Rigidity: Evidence from Scanner Data |
0 |
0 |
0 |
222 |
2 |
4 |
6 |
1,759 |
| The Relevant Length of Customer Event History for Churn Prediction: How long is long enough? |
0 |
0 |
0 |
117 |
0 |
0 |
2 |
347 |
| The Role of Marketer-Generated Content in Customer Engagement Marketing |
0 |
0 |
0 |
2 |
0 |
1 |
11 |
142 |
| The Role of Seed Money and Threshold Size in Optimizing Fundraising Campaigns: Past Behavior Matters! |
0 |
0 |
0 |
66 |
1 |
1 |
3 |
185 |
| The kinked demand curve and price rigidity: evidence from scanner data |
0 |
0 |
1 |
337 |
2 |
5 |
13 |
3,232 |
| Using Predicted Outcome Stratified Sampling to Reduce the Variability in Predictive Performance of a One-Shot Train-and-Test Split for Individual Customer Predictions |
0 |
0 |
1 |
101 |
0 |
0 |
2 |
487 |
| Weak Signal Identification with Semantic Web Mining |
0 |
0 |
1 |
58 |
0 |
0 |
1 |
174 |
| Why promotion strategies based on market basket analysis do not work |
0 |
0 |
5 |
2,181 |
1 |
4 |
20 |
8,228 |
| Total Working Papers |
8 |
31 |
180 |
40,951 |
78 |
190 |
808 |
137,416 |
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