|Journal of Contemporary Issues in Business Research ISSN 2305-8277|
Author(s): Sunil K Sapra
Abstract:The paper presents an econometric application of generalized additive Logit regression models (GALRMs) for brand choice. Our semi-parametric models are flexible and robust extensions of the Logit model. The GALRMs are fit to binary response data by maximizing a penalized log likelihood or a penalized log partial-likelihood. The GAMs allow us to build a regression surface as a sum of lower-dimensional nonparametric terms circumventing the curse of dimensionality: the slow convergence of an estimator to the true value in high dimensions. Four GALRMs are compared with a Logit model for brand choice and the best model is selected using various model selection criteria.
Keywords:Logit model; Generalized additive model; Interactions; Backfitting algorithm; Penalized regression splines.
[Compelete Article-pdf] [pp: 14-22] Article first published online: December 2012
Author(s): Yuval Cohen
Abstract:This paper addresses the problem of allocating work elements with various learning slopes to stations to minimize the makespan of many products produced in an assembly line for lots. The lots are characterized by a low overall demand for each product. There is no buffer permitted in between the stations, and the line operates under learning. Due to the nature of work, station's learning slopes can be different. We propose a two stage optimization methodology: the first stage is an optimization based on a non-linear formulation for work allocation with some constraints relaxation; the second stage drops the relaxations and finds a solution that is the closest to the unconstrained solution found in the first stage. We show that in the presence of learning, the optimal makespan requires assigning different work loads to different stations. This difference depends on the number of cycles in the lot, the station's learning slope, and the station's location along the line. The savings in the optimal makespan value due to the imbalanced loading of work over the balanced loading case are demonstrated.
Keywords:Work Allocation; Learning; Batch assembly; Assembly line.
[Compelete Article-pdf] [pp: 23-40] Article first published online: December 2012
Author(s): Tariq Mehmood1 and Shafaqat Mehmood2
Abstract:This study made an attempt to forecast the Pakistan’s exports to SAARC for a few coming years. Box and Jenkins (1976) methodology of univiriate ARIMA model has been selected as an appropriate econometrics model. This study found ARIMA (1,1,4) as most appropriate model among other ARIMA models to forecast Pakistan’s exports to SAARC. Present study rejected null hypothesis and it has been concluded that in a few coming years, exports from Pakistan to SAARC region will be increased. Pakistan’s exports to SAARC will increase in coming years on an average of 27630 Million Rupee per year. So, the government of Pakistan should invest into those sectors in which Pakistan has export potential to the SAARC countries.
Keywords:ARIMA model; Box-Jenkins methodology; SAARC; Pakistan; Exports; Forecasting.
[Compelete Article-pdf] [pp: 41-54] Article first published online: December 2012Author Affiliations:
- University of the Punjab1
- University of Central Punjab2