scholarly journals Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions

2020 ◽  
Vol 34 (02) ◽  
pp. 2236-2243 ◽  
Author(s):  
Weiran Shen ◽  
Binghui Peng ◽  
Hanpeng Liu ◽  
Michael Zhang ◽  
Ruohan Qian ◽  
...  
Keyword(s):  
Mechanism Design ◽  
Search Engine ◽  
Dynamic Pricing ◽  
Social Systems ◽  
Sponsored Search ◽  
Data Set ◽  
Sponsored Search Auctions ◽  
Reserve Prices ◽  
Changes Over Time ◽  
Over Time

In many social systems in which individuals and organizations interact with each other, there can be no easy laws to govern the rules of the environment, and agents' payoffs are often influenced by other agents' actions. We examine such a social system in the setting of sponsored search auctions and tackle the search engine's dynamic pricing problem by combining the tools from both mechanism design and the AI domain. In this setting, the environment not only changes over time, but also behaves strategically. Over repeated interactions with bidders, the search engine can dynamically change the reserve prices and determine the optimal strategy that maximizes the profit. We first train a buyer behavior model, with a real bidding data set from a major search engine, that predicts bids given information disclosed by the search engine and the bidders' performance data from previous rounds. We then formulate the dynamic pricing problem as an MDP and apply a reinforcement-based algorithm that optimizes reserve prices over time. Experiments demonstrate that our model outperforms static optimization strategies including the ones that are currently in use as well as several other dynamic ones.

Tree growth inference and prediction when the point of measurement changes: modelling around buttresses in tropical forests

2009 ◽  
Vol 25 (1) ◽  
pp. 1-12 ◽  
Author(s):  
C. Jessica E. Metcalf ◽  
James S. Clark ◽  
Deborah A. Clark
Keyword(s):  
Tree Growth ◽  
Biomass Accumulation ◽  
Relative Magnitude ◽  
Barro Colorado Island ◽  
Full Data ◽  
Data Set ◽  
Measurement Height ◽  
Changes Over Time ◽  
Climate Responses ◽  
Over Time

Abstract:Estimation of tree growth is generally based on repeated diameter measurements. A buttress at the height of measurement will lead to overestimates of tree diameter. Because buttresses grow up the trunk through time, it has become common practice to increase the height of measurement, to ensure that measurements remain above the buttress. However, tapering of the trunk means that increasing measurement height will bias estimates of diameter downward by up to 10% per m of height. This bias could affect inference concerning species differences and climate effects on tree demography and on biomass accumulation. Here we introduce a hierarchical state space method that allows formal integration of data on diameter taken at different heights and can include individual variation, temporal effects or other covariates. We illustrate our approach using species from Barro Colorado Island, Panama, and La Selva, Costa Rica. Results include trends that are consistent with some of those previously reported for climate responses and changes over time, but differ in relative magnitude. By including the full data-set and accounting for bias and variation among individuals and over time, our approach allows for quantification of climate responses and the uncertainty associated with measurements and the underlying growth process.

The changer and the changed

2019 ◽  
Vol 38 (2) ◽  
pp. 140-159 ◽  
Author(s):  
Sandra L. Laursen ◽  
Kristine De Welde
Keyword(s):  
Gender Equity ◽  
Social Systems ◽  
Historical Analysis ◽  
Theory Of Change ◽  
Content Type ◽  
Representation Of Women ◽  
Gendered Organizations ◽  
Theories Of Change ◽  
Changes Over Time ◽  
Over Time

PurposeThe purpose of this paper is to examine the evolving theories of change of the US National Science Foundation’s (NSF) ADVANCE program to increase the representation of women on academic faculties in science, technology, engineering and mathematics (STEM). ADVANCE supports efforts to transform the cultures and structures of US institutions of higher education by removing gendered barriers to STEM faculty women’s employment, advancement and success, and by developing change strategies that others may adopt.Design/methodology/approachThe empirical study is based on qualitative, longitudinal analysis of nine requests for proposals (RfPs) for the ADVANCE program (2001–2016), complemented by historical analysis of funded ADVANCE projects using public records.FindingsThe analysis identifies changes over time that suggest shifts in NSF’s rationale and theory of change for ADVANCE. Increased guidance directs how institutions should best undertake change, document outcomes and share best practices. The RfPs reveal growing attention to equity, rather than simply to representation, and to intersectionality – how gender, race, social class and other identities intersect to produce disparate experiences and outcomes for individuals differently positioned in social systems. Gendered organizations theory helps to place these experiences and outcomes in a structural context. Iterative processes of organizational learning are postulated to account for these changes over time.Originality/valueWhile many studies have examined ADVANCE projects’ activities and outcomes, none have examined the premises and design of the ADVANCE program itself. This analysis offers insight into how the ADVANCE RfP has driven innovation and learning about transformative institutional change to advance gender equity in STEM.

scholarly journals An investigation of biases in web search engine query suggestions

2019 ◽  
Vol 44 (2) ◽  
pp. 365-381 ◽  
Author(s):  
Malte Bonart ◽  
Anastasiia Samokhina ◽  
Gernot Heisenberg ◽  
Philipp Schaer
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Web Search ◽  
Query Suggestion ◽  
Data Set ◽  
Content Type ◽  
Web Search Engine ◽  
The Stability ◽  
Query Suggestions ◽  
Over Time

Purpose Survey-based studies suggest that search engines are trusted more than social media or even traditional news, although cases of false information or defamation are known. The purpose of this paper is to analyze query suggestion features of three search engines to see if these features introduce some bias into the query and search process that might compromise this trust. The authors test the approach on person-related search suggestions by querying the names of politicians from the German Bundestag before the German federal election of 2017. Design/methodology/approach This study introduces a framework to systematically examine and automatically analyze the varieties in different query suggestions for person names offered by major search engines. To test the framework, the authors collected data from the Google, Bing and DuckDuckGo query suggestion APIs over a period of four months for 629 different names of German politicians. The suggestions were clustered and statistically analyzed with regards to different biases, like gender, party or age and with regards to the stability of the suggestions over time. Findings By using the framework, the authors located three semantic clusters within the data set: suggestions related to politics and economics, location information and personal and other miscellaneous topics. Among other effects, the results of the analysis show a small bias in the form that male politicians receive slightly fewer suggestions on “personal and misc” topics. The stability analysis of the suggested terms over time shows that some suggestions are prevalent most of the time, while other suggestions fluctuate more often. Originality/value This study proposes a novel framework to automatically identify biases in web search engine query suggestions for person-related searches. Applying this framework on a set of person-related query suggestions shows first insights into the influence search engines can have on the query process of users that seek out information on politicians.

De plaats van het voorzetselvoorwerp

2014 ◽  
Vol 19 (2) ◽  
pp. 221-244 ◽  
Author(s):  
Jack Hoeksema
Keyword(s):  
Word Order ◽  
Data Set ◽  
Corpus Study ◽  
Prepositional Phrases ◽  
Subordinate Clauses ◽  
Word Order Variation ◽  
Order Variation ◽  
Changes Over Time ◽  
Regular Position ◽  
Over Time

Abstract This paper presents the results of a corpus study of Dutch complement PPs. On the basis of a collection of 3400 occurrences in negative sentences, the four major word order patterns (regular position, scrambling order, topicalization and extraposition) are studied, both in main and subordinate clauses, and linked to the properties of the prepositional phrases, in particular weight and definiteness. Greater weight corresponds to higher likelihood of extraposition, and definiteness to higher likelihood of scrambling and topicalization. This corresponds well with earlier studies of word order variation in Dutch, but had not been established for the class of complement PPs. Among definite phrases, PPs with so-called R-pronouns, such as hieraan ‘here-on’ and daarvan ‘thereof’ showed especially high preferences for topicalization and scrambling. Negative sentences were selected for this study to avoid cases where regular order and scrambling order could not be distinguished due to lack of adverbial elements in the middle field. The data set is temporally stratified. This made it possible to study changes over time, and the most robust finding was a continuous retreat of the scrambling order throughout the period 1700-2014.

scholarly journals Strategic Bidding Behaviors in Nondecreasing Sponsored Search Auctions

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Chen-Kun Tsung ◽  
Hann-Jang Ho ◽  
Sing-Ling Lee
Keyword(s):  
Search Engine ◽  
High Probability ◽  
Market Value ◽  
Sponsored Search ◽  
Negative Effects ◽  
Bidding Strategies ◽  
Strategic Bidding ◽  
Negative Results ◽  
Sponsored Search Auctions ◽  
The Relationship

To realize the specific results in the sponsored search auctions, most advertisers submit particular bid prices. The bidding behaviors with specific purposes are called as the strategic bidding. However, some strategic bidding behaviors will result in negative effects, such as the elimination of the equilibrium and the payment increase for some advertisers. The bidding behaviors with negative results are termed as the vindictive bidding. We survey four strategic bidding behaviors which include a rational bidding and three vindictive bidding strategies. In this paper, we study the relationship between the effects resulted by the vindictive bidding and the valuations of the vindictive advertisers. In our experiments, the search engine provider (SEP) is benefited by all vindictive bidding behaviors, and the increment of the SEP's revenue is proportional to the degree of the vindictiveness. Bidding vindictively without sacrificing the own utility improves the advertiser's utility with high probability. Moreover, we observe that the SEP's revenue is improved by the following situations. First, the vindictive advertiser with low valuation in the keywords with high market value results in more SEP's revenue than that in the keywords with low market value. The second case is to raise the bidding competition between advertisers.

Averaging Across Asset Allocation Models

2015 ◽  
Vol 235 (1) ◽  
pp. 61-81 ◽  
Author(s):  
Peter Schanbacher
Keyword(s):  
Empirical Study ◽  
Asset Allocation ◽  
Risk Function ◽  
Combined Model ◽  
Data Set ◽  
Individual Model ◽  
Risk Functions ◽  
Changes Over Time ◽  
Simple Average ◽  
Over Time

Summary Combination of asset allocation models is rewarding if (i) the applied risk function is concave and (ii) there is no dominating model. We show that most common risk functions are either concave or at least concave in common applications. In a comprehensive empirical study using standard asset allocation models we find that there is no constantly dominating model. The ranking of the models depends on the data set, the risk function and even changes over time. We find that a simple average of all asset allocation models can outperform each individual model. Our contribution is twofold. We present a theory why the combined model is expected to dominate most individual models. In a comprehensive empirical study we show that model combinations perform exceptionally well in asset allocation.

scholarly journals The Success of Business Forecasting: Comparisons across Industries, Countries and Time

2020 ◽  
Vol 13 (10) ◽  
pp. 108
Author(s):  
Tobias F. Rötheli
Keyword(s):  
Forecast Accuracy ◽  
Data Set ◽  
Electric Machinery ◽  
Forecasting Performance ◽  
Business Forecasting ◽  
The Stability ◽  
Changes Over Time ◽  
German Data ◽  
Historical Periods ◽  
Over Time

This study assesses the accuracy of forecasts by industry branches. Such an investigation provides a perspective on the relative benefits of forecasting in different industries. Accuracy of forecasting is assessed by econometrically investigating expectations data on firms’ production drawn from surveys covering manufacturing. Such data is available for only few countries and few historical periods. We study U.S. data covering the 1980s and German data over the period from 1991 to 2018. We first present rankings of industries according to forecast accuracy for both countries. Then the historical gap between the two countries’ data set is put to use to assess the stability and the dynamics in the relevance of forecasting in different branches of industry. We identify several industries that – across time and place – are among the most (e.g., electric machinery) and least accurate forecasters (e.g., the food industry). By contrast in some industries forecasting performance appear to undergo noticeable changes over time: the reported evidence suggests that forecasting has lost some of its potential in the printing and textile industries while gaining over time in the nonelectric machinery and in the metals industry. The findings can help management to make decisions regarding the allocation of resources to forecasting.

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