|
|
del Valle, M. A., Ramos, A. C., Diaz, F. R., & Gacitua, M. A. (2015). Electrosynthesis and Characterisation of Polymer Nanowires from Thiophene and its Oligomers. J. Braz. Chem. Soc., 26(11), 2313–2320.
Abstract: Validating methodology formerly reported, polythiophene electrosynthesised as nanowires from the monomer and some of its oligomers is now described. The work is conducted on a platinum electrode previously modified with a template that tunes the polymer growth inside the confined space of the pores. In addition, it was confirmed that the use of larger chain-length oligomers as starting unit helps to obtain more homogeneous wires, although its adhesion to the supporting substrate works against. Characterisation allows to verify the morphology and to confirm higher levels of doping/undoping of the nanostructures as compared to the corresponding bulky deposits, which points to improved macroscopic properties. It is demonstrated that this strategy allows obtaining nanowires of very small diameter, ranging from 2.8 to 4.0 nm; thus demonstrating that the use of this approach enables the direct obtainment of nanowires upon the electrode surface, with the obvious advantage that this implies.
|
|
|
|
Valle, M. A., & Ruz, G. A. (2015). Turnover Prediction In A Call Center: Behavioral Evidence Of Loss Aversion Using Random Forest And Naive Bayes Algorithms. Appl. Artif. Intell., 29(9), 923–942.
Abstract: It is well known that call centers suffer from high levels of employee turnover; however, call centers are services that have excellent operational records of telemarketing activities performed by each employee. With this information, we propose to use the Random Forest and the naive Bayes algorithms to build classifiers and predict turnover of the sales agents. The results of 2407 sales agents' operational performance records showed that, although the naive Bayes is much simpler than Random Forest, both classifiers performed similarly, achieving interesting accuracy rates in turnover prediction. Moreover, evidence was found that incorporating performance differences over time increases significantly the accuracy of the predictive models up to 85%, with the naive Bayes being quite competitive with the Random Forest classifier when the amount of information is increased. The results obtained in this study could be useful for management decision-making to monitor and identify potential turnover due to poor performance, and therefore, to take a preventive action.
|
|
|
|
Valle, M. A., & Ruz, G. A. (2019). Market Basket Analysis Using Boltzmann Machines. In Lecture Notes in Computer Sciences (Vol. 11730).
|
|
|
|
Valle, M. A., Ruz, G. A., & Masias, V. H. (2017). Using self-organizing maps to model turnover of sales agents in a call center. Appl. Soft. Comput., 60, 763–774.
Abstract: This paper proposes an approach for modeling employee turnover in a call center using the versatility of supervised self-organizing maps. Two main distinct problems exist for the modeling employee turnover: first, to predict the employee turnover at a given point in the sales agent's trial period, and second to analyze the turnover behavior under different performance scenarios by using psychometric information about the sales agents. Identifying subjects susceptible to not performing well early on, or identifying personality traits in an individual that does not fit with the work style is essential to the call center industry, particularly when this industry suffers from high employee turnover rates. Self-organizing maps can model non-linear relations between different attributes and ultimately find conditions between an individual's performance and personality attributes that make him more predisposed to not remain long in an organization. Unlike other models that only consider performance attributes, this work successfully uses psychometric information that describes a sales agent's personality, which enables a better performance in predicting turnover and analyzing potential personality profiles that can identify agents with better prospects of a successful career in a call center. The application of our model is illustrated and real data are analyzed from an outbound call center. (C) 2017 Elsevier B.V. All rights reserved.
|
|
|
|
Valle, M. A., Ruz, G. A., & Morras, R. (2018). Market basket analysis: Complementing association rules with minimum spanning trees. Expert Syst. Appl., 97, 146–162.
Abstract: This study proposes a methodology for market basket analysis based on minimum spanning trees, which complements the search for significant association rules among the vast set of rules that usually characterize such an analysis. Thanks to the hierarchical tree structure of the subdominant ultrametric distances of the MST, the association network allows us to find strong interdependencies between products in the same category, and to find products that serve as accesses or bridges to a set of other products with a high correlation among themselves. One relevant aspect of this graph-based methodology is the ease with which pairs and groups of products susceptible to carrying out marketing actions can be identified. The application of our methodology to a real transactional database succeeded in: 1. revealing product interdependencies with the greatest strengths, 2. revealing products of high importance with access to another product set, 3. determining high quality association rules, and 4. detect clusters and taxonomic relations among supermarket subcategories. This is highly beneficial for a retail manager or for a retail analyst who must propose different promotion and offer activities in order to maximize the sales volume and increase the effectiveness of promotion campaigns. (C) 2017 Elsevier Ltd. All rights reserved.
|
|
|
|
Valle, M. A., Ruz, G. A., & Rica, S. (2018). Transactional Database Analysis by Discovering Pairwise Interactions Strengths. In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (Vol. 2018).
|
|
|
|
Valle, M. A., Ruz, G. A., & Rica, S. (2019). Market basket analysis by solving the inverse Ising problem: Discovering pairwise interaction strengths among products. Physica A, 524, 36–44.
Abstract: Large datasets containing the purchasing information of thousands of consumers are difficult to analyze because the possible number of different combinations of products is huge. Thus, market baskets analysis to obtain useful information and find interesting pattern of buying behavior could be a daunting task. Based on the maximum entropy principle, we build a probabilistic model that explains the probability of occurrence of market baskets which is equivalent to Ising models. This type of model allows us to understand and to explore the functional interactions among products that make up the market offer. Additionally, the parameters of the model inferred using Boltzmann learning, allow us to suggest that the buying behavior is very similar to the spin-glass physical system. Moreover, we show that the resulting parameters of the model could be useful to describe the hierarchical structure of the system which leads to interesting information about the different market baskets. (C) 2019 Elsevier B.V. All rights reserved.
|
|
|
|
Valle, M. A., Ruz, G. A., & Varas, S. (2015). A survival model based on met expectations Application to employee turnover in a call center. Acad.-Rev. Latinoam. Adm., 28(2), 177–194.
Abstract: Purpose – The purpose of this paper is to propose a model of voluntary employee turnover based on the theory of met expectations and self-perceived efficacy of the employee, using data from a field survey conducted in a call center. Design/methodology/approach – The paper formulates a model of employee turnover. First explaining the fulfillment of expectations from initial expectations of the employee (before starting work) and their experience after a period of time. Second, explaining the turnover of employees from the fulfillment of their expectations. Findings – Some of the variability in the fulfillment of expectations can be explained by the difference between expectations and experiences in different job dimensions (e.g. income levels and job recognition). Results show that the level of fulfillment of expectations helps explain the process of employee turnover. Research limitations/implications – This work provides evidence for the met expectation theory, where the gap between the individual's expectations and subsequent experiences lead to abandonment behaviors in the organization. Practical implications – The results suggest two paths of action to reduce the high turnover rates in the call center: the first, through realistic expectations setting of the employee, and the second, with a constant monitoring of the fulfillment of those expectations. Originality/value – A statistical model of survival is used, which is appropriate for the study of the employee turnover processes, and its inherent temporal nature.
|
|
|
|
Valle, M. A., Ruz, G. A., & Varas, S. (2015). Explaining job satisfaction and intentions to quit from a value-risk perspective. Acad.-Rev. Latinoam. Adm., 28(4), 523–540.
Abstract: Purpose – The purpose of this paper is to investigate the effect of risk aversion (RA) on expected income and job satisfaction (JS) with pay in the case of sales agents under a compensation system based on pay-for-performance.
Design/methodology/approach – Data were collected from 125 sales agents of an outbound call center via questionnaires and controlled experiments. Seemingly unrelated equations using maximum likelihood estimation was employed to estimate the proposed model and test relationships. Findings – Findings show that income expectations (IE) respond to a model of trade-off between value and risk. The sales agents trade off their expected value of performance (i.e. expected income) with RA. Additionally, IE and actual performance of the salesperson have influence on JS with pay with opposite signs.
Research limitations/implications – The results of this research may need to be modified to consider jobs with compensation systems with a higher proportion of fixed component of the wage than the variable component. Also, a broader concept of JS and not just related to the pay, should be considered.
Practical implications – Given the importance of RA in the attitudes of employees in relation to their expectations, the authors believe that it should be necessary and useful to incorporate measures of RA in the process of selection and recruitment for these jobs.
Originality/value – This paper assessed an important element as the RA at the micro level inside of an organization. This element could be very important for job environments with high uncertainty in income that could influence JS via employee expectations.
|
|
|
|
Valle, M. A., Varas, S., & Ruz, G. A. (2012). Job performance prediction in a call center using a naive Bayes classifier. Expert Syst. Appl., 39(11), 9939–9945.
Abstract: This study presents an approach to predict the performance of sales agents of a call center dedicated exclusively to sales and telemarketing activities. This approach is based on a naive Bayesian classifier. The objective is to know what levels of the attributes are indicative of individuals who perform well. A sample of 1037 sales agents was taken during the period between March and September of 2009 on campaigns related to insurance sales and service pre-paid phone services, to build the naive Bayes network. It has been shown that, socio-demographic attributes are not suitable for predicting performance. Alternatively, operational records were used to predict production of sales agents, achieving satisfactory results. In this case, the classifier training and testing is done through a stratified tenfold cross-validation. It classified the instances correctly 80.60% of times, with the proportion of false positives of 18.1% for class no (does not achieve minimum) and 20.8% for the class yes (achieves equal or above minimum acceptable). These results suggest that socio-demographic attributes has no predictive power on performance, while the operational information of the activities of the sale agent can predict the future performance of the agent. (c) 2012 Elsevier Ltd. All rights reserved.
|
|
