FIC-UAI Publication Database -- Query Results

Bitran, G., & Mondschein, S. (2015). Why individualized contact policies are critical in the mass affluent market. Acad.-Rev. Latinoam. Adm., 28(2), 251–272. Abstract: Purpose – The purpose of this paper is to study the optimal contact policies for customers that belong to the mass affluent market. Design/methodology/approach – The authors formulate a stochastic dynamic programming model to determine the optimal frequency of contacts in order to maximize the expected return of the company. Findings – The authors show that personalized marketing strategies provide a competitive advantage to companies that contact their customers directly through, for example, phone calls or meetings. The authors show that a threshold policy is only optimal for customers with increasing sensitivity to contact. In all other cases, optimal policies might have a less intuitive structure. The authors also study the importance of the size of the customer database and determine the optimal maximum recency when maintenance costs are present. Practical implications – Contact policies should be tailored for each company/industry individually, due to their sensitivity to customers' purchasing behavior. Keywords: Marketing and advertising; Stochastic dynamic programming show.php?record=511
Rojas, F., & Leiva, V. (2016). Inventory management in food companies with statistically dependent demand. Acad.-Rev. Latinoam. Adm., 29(4), 450–485. Abstract: Purpose – The objective of this paper is to propose a methodology based on random demand inventory models and dependence structures for a set of raw materials, referred to as “components”, used by food services that produce food rations referred to as “menus”. Design/methodology/approach – The contribution margins of food services that produce menus are optimised using random dependent demand inventory models. The statistical dependence between the demand for components and/or menus is incorporated into the model through the multivariate Gaussian (or normal) distribution. The contribution margins are optimised by using probabilistic inventory models for each component and stochastic programming with a differential evolution algorithm. Findings – When compared to the non-optimised system previously used by the company, the (average) expected contribution margin increases by 18.32 per cent when using a continuous review inventory model for groceries and uniperiodic models for perishable components (optimised system). Research limitations/implications – The multivariate modeling can be improved by using (a) other non-Gaussian (marginal) univariate probability distributions, by means of the copula method that considers more complex statistical dependence structures; (b) time-dependence, through autoregressive time-series structures and moving average; (c) random modelling of lead-time; and (d) demands for components with values equal to zero using zero-inflated or adjusted probability distribution. Practical implications – Professional management of the supply chain allows the users to register data concerning component identification, demand, and stock levels to subsequently be used with the proposed methodology, which must be implemented computationally. Originality/value – The proposed multivariate methodology allows it to describe demand dependence structures through inventory models applicable to components used to produce menus in food services. Keywords: Contribution margins; Multivariate distribution; Optimization methods; Probabilistic inventory models; Statistical dependence show.php?record=689
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. Keywords: Self-efficacy; Employee turnover; Job tenure; Met expectations show.php?record=510
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. show.php?record=527

Bitran, G., & Mondschein, S. (2015). Why individualized contact policies are critical in the mass affluent market. Acad.-Rev. Latinoam. Adm., 28(2), 251–272.

Rojas, F., & Leiva, V. (2016). Inventory management in food companies with statistically dependent demand. Acad.-Rev. Latinoam. Adm., 29(4), 450–485.

Abstract: Purpose – The objective of this paper is to propose a methodology based on random demand inventory models and dependence structures for a set of raw materials, referred to as “components”, used by food services that produce food rations referred to as “menus”. Design/methodology/approach – The contribution margins of food services that produce menus are optimised using random dependent demand inventory models. The statistical dependence between the demand for components and/or menus is incorporated into the model through the multivariate Gaussian (or normal) distribution. The contribution margins are optimised by using probabilistic inventory models for each component and stochastic programming with a differential evolution algorithm. Findings – When compared to the non-optimised system previously used by the company, the (average) expected contribution margin increases by 18.32 per cent when using a continuous review inventory model for groceries and uniperiodic models for perishable components (optimised system). Research limitations/implications – The multivariate modeling can be improved by using (a) other non-Gaussian (marginal) univariate probability distributions, by means of the copula method that considers more complex statistical dependence structures; (b) time-dependence, through autoregressive time-series structures and moving average; (c) random modelling of lead-time; and (d) demands for components with values equal to zero using zero-inflated or adjusted probability distribution. Practical implications – Professional management of the supply chain allows the users to register data concerning component identification, demand, and stock levels to subsequently be used with the proposed methodology, which must be implemented computationally. Originality/value – The proposed multivariate methodology allows it to describe demand dependence structures through inventory models applicable to components used to produce menus in food services.

Keywords: Contribution margins; Multivariate distribution; Optimization methods; Probabilistic inventory models; Statistical dependence

show.php?record=689

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.

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.