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Barrera, J., Moreno, E., & Varas, S. (2020). A decomposition algorithm for computing income taxes with pass-through entities and its application to the Chilean case. Ann. Oper. Res., 286(1-2), 545–557.
Abstract: Income tax systems with “pass-through” entities transfer a firm's income to shareholders, which are taxed individually. In 2014, a Chilean tax reform introduced this type of entity and changed to an accrual basis that distributes incomes (but not losses) to shareholders. A crucial step for the Chilean taxation authority is to compute the final income of each individual given the complex network of corporations and companies, usually including cycles between them. In this paper, we show the mathematical conceptualization and the solution to the problem, proving that there is only one way to distribute income to taxpayers. Using the theory of absorbing Markov chains, we define a mathematical model for computing the taxable income of each taxpayer, and we propose a decomposition algorithm for this problem. This approach allows us to compute the solution accurately and to efficiently use computational resources. Finally, we present some characteristics of Chilean taxpayers' network and the computational results of the algorithm using this network.
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Ruz, G. A., Varas, S., & Villena, M. (2013). Policy making for broadband adoption and usage in Chile through machine learning. Expert Syst. Appl., 40(17), 6728–6734.
Abstract: For developing countries, such as Chile, we study the influential factors for adoption and usage of broadband services. In particular, subsidies on the broadband price are analyzed to see if this initiative has a significant effect in the broadband penetration. To carry out this study, machine learning techniques are used to identify different household profiles using the data obtained from a survey on access, use, and users of broadband Internet from Chile. Different policies are proposed for each group found, which were then evaluated empirically through Bayesian networks. Results show that an unconditional subsidy for the Internet price does not seem to be very appropriate for everyone since it is only significant for some households groups. The evaluation using Bayesian networks showed that other polices should be considered as well such as the incorporation of computers, Internet applications development, and digital literacy training. (C) 2013 Elsevier Ltd. All rights reserved.
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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.
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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.
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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.
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