Generalized approaches to the maxbet problem and the maxdiff problem,with applications to canonical correlations

Van de Geer has reviewed various criteria for transforming two or more matrices to maximal agreement, subject to orthogonality constraints. The criteria have applications in the context of matching factor or configuration matrices and in the context of canonical correlation analysis for two or more matrices. The present paper summarizes and gives a unified treatment of fully general computational solutions for two of these criteria, Maxbet and Maxdiff. These solutions will be shown to encompass various well-known methods as special cases. It will be argued that the Maxdiff solution should be preferred to the Maxbet solution whenever the two criteria coincide. Horst's Maxcor method will be shown to lack the property of monotone convergence. Finally, simultaneous and successive versions of the Maxbet and Maxdiff solutions will be treated as special cases of a fully flexible approach where the columns of the rotation matrices are obtained in successive blocks.The author is obliged to Henk Kiers for computational assistance and helpful comments.     

Ingroup bias and the ‘black sheep’ effect: Assessing the impact of social identification and perceived variability on group judgements

Two studies compared the relative strength of motivational assumptions drawn from SIT (e.g. Tajfel, 1978) and memory-based assumptions drawn from the differential familiarity hypothesis (Linville, Fischer and Salovey, 1989) in explaining ingroup bias and the black sheep effect (Marques, 1986, 1990). In Study 1, 15 subjects estimated member distributions and gave overall ratings of an ingroup and two outgroups. In Study 2, 42 subjects performed similar tasks for ingroup or outgroup, and evaluated likeable and unlikeable group members. Results showed, first, that overall group ratings account better for ingroup bias than do central tendencies of group distributions. In addition, likeable and unlikeable ingroup members were, respectively, upgraded and downgraded relative to their outgroup counterparts. Finally, whole ingroup ratings as well as judgements of likeable and unlikeable ingroup members proved more independent from variability and central tendency of underlying distributions than did similar outgroup judgements. Results are discussed in light of motivational and knowledge-based determinants of group judgements.     

The effect of a non-informative cueing signal in a three-choice reaction-time task

Summary Many studies have shown that in a simple reaction-time (RT) task a non-informative leading cue decreases RT to a subsequent target presented in the same region as the cue. This facilitation lasts about 150 ms; it is then replaced by a sustained inhibition. Experiment 1 tests the hypothesis that the initial facilitation is due to motor, rather than perceptual, processes by using choice RT. Facilitation is greater and lasts longer in choice than in simple tasks, thus supporting the hypothesis. Experiment 2 shows that facilitation occurs even when the subject actively orients his or her attention away from the cue.     

Alternating least squares algorithms for simultaneous components analysis with equal component weight matrices in two or more populations

Millsap and Meredith (1988) have developed a generalization of principal components analysis for the simultaneous analysis of a number of variables observed in several populations or on several occasions. The algorithm they provide has some disadvantages. The present paper offers two alternating least squares algorithms for their method, suitable for small and large data sets, respectively. Lower and upper bounds are given for the loss function to be minimized in the Millsap and Meredith method. These can serve to indicate whether or not a global optimum for the simultaneous components analysis problem has been attained.Financial support by the Netherlands organization for scientific research (NWO) is gratefully acknowledged.     

Least-squares approximation of an improper correlation matrix by a proper one

An algorithm is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. The proposed algorithm is based upon a solution for Mosier's oblique Procrustes rotation problem offered by ten Berge and Nevels. A necessary and sufficient condition is given for a solution to yield the unique global minimum of the least-squares function. Empirical verification of the condition indicates that the occurrence of non-optimal solutions with the proposed algorithm is very unlikely. A possible drawback of the optimal solution is that it is a singular matrix of necessity. In cases where singularity is undesirable, one may impose the additional nonsingularity constraint that the smallest eigenvalue of the solution be , where is an arbitrary small positive constant. Finally, it may be desirable to weight the squared errors of estimation differentially. A generalized solution is derived which satisfies the additional nonsingularity constraint and also allows for weighting. The generalized solution can readily be obtained from the standard unweighted singular solution by transforming the observed improper correlation matrix in a suitable way.     

Concept learning,memory and transfer of dot pattern categories

In the first experiment, subjects rated the similarity of a sample of pairs of random dot patterns generated from 3 prototypes consisting of either 4, 6, or 9 dots. The results of the experiment tended to confirm the structure imposed on the patterns by the construction method. In the second experiment, subjects learned to classify random patterns generated from 2 prototypes with either short or long interprototype distance and consisting of either 4, 6, or 9 dots in a traditional concept identification task. After acquisition, memory for old and new distortions and the prototype, which was not presented during learning, was assessed. The tendency to call a pattern “new” increased with the distance between the pattern and its prototype. In a subsequent transfer test, all subjects saw patterns of either 4, 6, or 9 dots. Performance was above chance and the transfer from larger to smaller patterns tended to be greater than the transfer from smaller to larger patterns. This is consistent with a process of schema formation based on features common to most exemplars of the category. The results are discussed in relation to several theories of concept learning and schema abstraction.     

Value-based adoption of augmented reality: A study on the influence on online purchase intention in retail

The increasing use of digital technology-based retail services provides new opportunities for digital marketing. In this paper, we investigate how augmented reality (AR) technology can be leveraged as part of the firm's strategy. We explore the online purchase intention through AR smart glasses (ARSG), considering consumers' value assessment through a cost–benefit analysis and the influence of technical, experiential and social AR value drivers. We develop an augmented value-based adoption model addressing four main objectives: (1) Evaluate the effect of the perceived value of ARSG, (2) Evaluate the effect of immersion (experiential dimension), (3) Evaluate the effect of AR devices and technical complexity (technical dimension) and (4) Evaluate the importance of subjective norms (social dimension) on the online purchase intention through AR technology. Based on an ESIC Tech Lab experiment with two types of ARSG from market leaders and AR retail apps, the study uses survey data from 253 participants. The results suggest that the technical dimension has an ambiguous effect, with tech-complexity enhancing directly the perceived value of ARSG for online purchase while reducing the net value of consumers' economic cost–benefit analysis. We find strong evidence that the experiential and social AR dimensions (in the form of immersion and subjective norm) have a significant positive influence on consumers' purchase intention online, which are better predictors than the pure economic cost–benefit assessment (through usefulness and difficulty). Furthermore, the technical innovativeness of consumers is found to increase directly the online purchase intention through ARSG.