scholarly journals No Substitute for the Real Thing: The Importance of In-Context Field Experiments In Fundraising.

2019 ◽  
Author(s):  
Indranil Goswami ◽  
Oleg Urminsky
Keyword(s):  
Expert Opinion ◽  
Field Experiments ◽  
Ground Truth ◽  
Field Testing ◽  
Warm Glow ◽  
Real Thing ◽  
Impure Altruism ◽  
Natural Field Experiment ◽  
Surprising Finding

We present a complete empirical case study of fundraising campaign decisions that demonstratesthe importance of in-context field experiments. We first design novel matching-basedfundraising appeals. We derive theory-based predictions from the standard impure altruismmodel and solicit expert opinion about the potential performance of our interventions. Boththeory-based prediction and descriptive advice suggest improved fundraising performance from aframing intervention that credited donors for the matched funds (compared to a typical matchframing). However, results from a natural field experiment with prior donors of a non-profitshowed significantly poorer performance of this framing compared to a regularly framedmatching intervention. This surprising finding was confirmed in a second natural fieldexperiment, to establish the ground truth. Theoretically, our results highlight the limitations ofboth impure altruism models and of expert opinion in predicting complex “warm glow”motivation. More practically, our results question the availability of useful guidance, andsuggest the indispensability of field testing for interventions in fundraising.

scholarly journals No Substitute for the Real Thing: The Importance of In-Context Field Experiments in Fundraising

2020 ◽  
Vol 39 (6) ◽  
pp. 1052-1070
Author(s):  
Indranil Goswami ◽  
Oleg Urminsky
Keyword(s):  
Field Experiments ◽  
Real Thing ◽  
The Real

This paper is an empirical case study of fundraising decisions that examines the adequacy of various sources of guidance and demonstrates the unique importance of in-context field experiments.

A novel expert opinion-based approach to compute estimations of flood damage to property in dense urban environments. Barcelona case study

2021 ◽  
Vol 598 ◽  
pp. 126244
Author(s):  
Eduardo Martínez-Gomariz ◽  
Edwar Forero-Ortiz ◽  
Beniamino Russo ◽  
Luca Locatelli ◽  
Maria Guerrero-Hidalga ◽  
...  
Keyword(s):  
Expert Opinion ◽  
Flood Damage ◽  
Urban Environments

Integrating multiple data sources in match-fixing warning systems

2018 ◽  
Vol 18 (5-6) ◽  
pp. 483-504 ◽  
Author(s):  
Marius Ötting ◽  
Roland Langrock ◽  
Christian Deutscher
Keyword(s):  
Generalized Additive Model ◽  
Additive Model ◽  
Ground Truth ◽  
Warning Systems ◽  
Volume Data ◽  
Detection Systems ◽  
Multiple Data ◽  
Log Normal ◽  
Betting Odds

Recent years have seen several match-fixing scandals in soccer. In order to avoid match-fixing, existing literature and fraud detection systems primarily focus on analysing betting odds provided by bookmakers. In our work, we suggest to not only analyse odds but also total volume placed on bets, thereby making use of more of the information available. As a case study for our method, we consider the second division in Italian soccer, Serie B, since for this league it has effectively been proven that some matches were fixed, such that to some extent we can ground truth our approach. For the betting volume data, we use a flexible generalized additive model for location, scale and shape (GAMLSS), with log-normal response, to account for the various complex patterns present in the data. For the betting odds, we use a GAMLSS with bivariate Poisson response to model the number of goals scored by both teams, and to subsequently derive the corresponding odds. We then conduct outlier detection in order to flag suspicious matches. Our results indicate that monitoring both betting volumes and betting odds can lead to more reliable detection of suspicious matches.

scholarly journals Spam Diffusion in Social Networking Media using Latent Dirichlet Allocation

2019 ◽  
Vol 8 (12) ◽  
pp. 881-885
Keyword(s):  
Online Social Networks ◽  
Topic Modeling ◽  
Information Diffusion ◽  
Latent Dirichlet Allocation ◽  
Good Accuracy ◽  
Ground Truth ◽  
Online Social Media ◽  
Diffusion Dynamics ◽  
Dirichlet Allocation

Like web spam has been a major threat to almost every aspect of the current World Wide Web, similarly social spam especially in information diffusion has led a serious threat to the utilities of online social media. To combat this challenge the significance and impact of such entities and content should be analyzed critically. In order to address this issue, this work usedTwitter as a case study and modeled the contents of information through topic modeling and coupled it with the user oriented feature to deal it with a good accuracy. Latent Dirichlet Allocation (LDA) a widely used topic modeling technique is applied to capture the latent topics from the tweets’ documents. The major contribution of this work is twofold: constructing the dataset which serves as the ground-truth for analyzing the diffusion dynamics of spam/non-spam information and analyzing the effects of topics over the diffusibility. Exhaustive experiments clearly reveal the variation in topics shared by the spam and nonspam tweets. The rise in popularity of online social networks, not only attracts legitimate users but also the spammers. Legitimate users use the services of OSNs for a good purpose i.e., maintaining the relations with friends/colleagues, sharing the information of interest, increasing the reach of their business through advertisings

Dynamic behaviors of historical wrought iron truss bridges: a field testing case study

2016 ◽  
Author(s):  
Kaoshan Dai ◽  
Ying Wang ◽  
Andrew Hedric ◽  
Zhenhua Huang
Keyword(s):  
Field Testing ◽  
Dynamic Behaviors ◽  
Wrought Iron ◽  
Truss Bridges ◽  
Testing Case

A methodology for identifying critical factors influencing land value in urban areas: a case study of Kerala, India

2020 ◽  
Vol 38 (5) ◽  
pp. 665-681
Author(s):  
Binoy BV ◽  
Naseer MA ◽  
Anil Kumar PP
Keyword(s):  
Expert Opinion ◽  
Urban Areas ◽  
Environmental Planning ◽  
Delphi Survey ◽  
Land Value ◽  
Critical Factors ◽  
Content Type ◽  
Factors Influencing ◽  
Importance Index

PurposeLand value is a measure of the specific features of a property, excluding buildings and other developments. Land value varies depending on the economic, geographic and political aspects of a particular location. The primary purpose of the paper is to identify the general and location-specific attributes impacting property prices in urban Kerala.Design/methodology/approachThe objective of the current study was achieved through a three-cycle Delphi survey and relative importance index (RII) approach. The experts who aided in the survey had a mutual interest in the subject but came from different backgrounds like property valuation, real estate, urban and environmental planning. The initial group of variables identified from the literature was expanded and scrutinized in the first cycle of the Delphi survey. The variables were grouped into five major categories and 13 subcategories based on the literature and expert opinion. In the subsequent stages, the short-listed variables were rated on a seven-point Likert scale until a consensus was attained. The top-ranked variables were identified through the RII method as the critical factors influencing land value in urban Kerala.FindingsThe results indicate that road accessibility and proximity to nuisance sources are the most crucial parameters. The outcome of the study will provide a better understanding of the dynamics of land value and the influencing factors in urban areas.Originality/valuePrevious studies do not give much consideration for the location-specific variability on the influencing parameters. Property management research has not considered the usage of expert opinion and RII for variable selection.

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