Implicit data recommendation based on refined classification and ranking learning

Purpose This paper aims to investigate modeling implicit attitudes as potential drivers of overall brand attitudes and stated behavior and investigate how the results are expected to be different from brand driver models that are based on explicit attitudes. Design/methodology/approach Data are collected via online surveys in five countries across 15 categories with sample sizes for each category/country combination in the range of about N = 1,000. Findings Implicit attitudes result in a higher number of significant effects than their explicit counterparts when used to explain behavioral intentions, brand closeness and brand usage in a multivariate situation with potential 12 brand attitude drivers. The authors also find fewer counter-intuitive effects in the implicit models. The results are consistent across 5 countries and across 15 categories (including CPG products, services and durable goods). They also show that implicit attitudes are less susceptible to response style effects (e.g. social desirability bias). Research limitations/implications The findings have implications for brand building and shopper activation. Further research should look into the impact of using implicit data on finding different brand segmentation and brand mapping results. Practical implications The findings have implications for brand building and shopper activation. Originality/value This paper contributes to the fast-growing field of implicit attitudes. The paper confirms and generalizes previous findings. This is the first paper to the authors’ knowledge that has investigated the impact of implicit attitudes on overall brand attitudes and stated behavior in a multivariate context.

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Permutation Min-Entropy and Statistical Complexity Analysis of Electricity Spot Price

Fluctuation and Noise Letters ◽

10.1142/s0219477515500406 ◽

2015 ◽

Vol 14 (04) ◽

pp. 1550040 ◽

Cited By ~ 1

Author(s):

Qingju Fan ◽

Dan Li

Keyword(s):

Temporal Dynamics ◽

Complexity Analysis ◽

Spot Price ◽

Temporal Correlations ◽

Price Series ◽

Statistical Complexity ◽

Electricity Spot Price ◽

Insight Into ◽

Refined Classification

In this study, we investigate the subtle temporal dynamics of California 1999–2000 spot price series based on permutation min-entropy (PME) and complexity-entropy causality plane. The dynamical transitions of price series are captured and the temporal correlations of price series are also discriminated by the recently introduced PME. Moreover, utilizing the CECP, we provide a refined classification of the monthly price dynamics and obtain an insight into the stochastic nature of price series. The results uncover that the spot price signal presents diverse temporal correlations and exhibits a higher stochastic behavior during the periods of crisis.

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Geometric aspects of self-adjoint Sturm–Liouville problems

Proceedings of the Royal Society of Edinburgh Section A Mathematics ◽

10.1017/s0308210517000105 ◽

2017 ◽

Vol 147 (6) ◽

pp. 1279-1295

Author(s):

Yicao Wang

Keyword(s):

Boundary Conditions ◽

Liouville Equation ◽

Adjoint Action ◽

Principal Type ◽

Unitary Matrices ◽

Adjoint Orbits ◽

Sturm Liouville ◽

Refined Classification ◽

Adjoint Orbit

In this paper we use U(2), the group of 2 × 2 unitary matrices, to parametrize the space of all self-adjoint boundary conditions for a fixed Sturm–Liouville equation on the interval [0, 1]. The adjoint action of U(2) on itself naturally leads to a refined classification of self-adjoint boundary conditions – each adjoint orbit is a subclass of these boundary conditions. We give explicit parametrizations of those adjoint orbits of principal type, i.e. orbits diffeomorphic to the 2-sphere S2, and investigate the behaviour of the nth eigenvalue λnas a function on such orbits.

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Predicting shoreline depositional process regimes using insights from palaeotidal modelling

10.31219/osf.io/3pzv5 ◽

2020 ◽

Author(s):

Daniel Collins ◽

Alexandros Avdis ◽

Martin R. Wells ◽

Andrew J. Mitchell ◽

Peter Allison ◽

...

Keyword(s):

Numerical Simulations ◽

Depositional Processes ◽

Depositional Process ◽

Stratigraphic Record ◽

Refined Classification

This review demonstrates the benefit of numerical tidal modelling, calibrated by integrated comparison to the preserved stratigraphic record, and offers a refined classification and prediction of shoreline process regimes. Wider and consistent utilisation of these concepts, and numerical simulations of other depositional processes, will further improve process-based classifications and predictions of modern and ancient shoreline systems.

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