The association between need for touch and desire for unique products and consumer (inter)dependent problem-solving

Some people cannot buy products without first touching them, believing that doing so will create more assurance and information and reduce uncertainty. The international consumer marketing literature suggests an instrument to measure consumers' necessity for pohysical contact, called Need for Touch (NFT). This paper analyzes whether the Need for Touch structure is empirically consistent. Based on a literature review, we suggest six hypotheses in order to assess the nomological, convergent, and discriminant validity of the phenomenon. Departing from these, data supported four assumptions in the predicted direction. Need for Touch was associated with Need for Input and with Need for Cognition. Need for Touch was not associated with traditional marketing channels. The results also showed the dual characterization of Need for Touch as a bi-dimensional construct. The moderator effect indicated that when the consumer has a higher (vs. lower) Need for Touch autotelic score, the experiential motivation for shopping played a more (vs. less) important role in impulsive motivation. Our Study 3 supports the NFT structure and shows new associations with the need for unique products and dependent decisions.

Methane combustion kinetic rate constants determination: an ill-posed inverse problem analysis

Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.