Linking Finance and Operations in Retailing

Operations Management Working Papers Serie

What Explains Superior Retail Performance?

We analyze the performance of retail firms for the period 1978-97 using public financial data. Our performance measures are long-term stock returns and whether the firm filed for bankruptcy in the period of study. We assume that over a long time period of at least five years, stock returns are a reasonable measure of the overall success of a firm. We have found a very wide disparity in performance between firms. On the one hand, retailers like Wal-Mart, the Gap and Circuit City have had phenomenal success (nineteen year compounded stock returns of 31.2%, 29.5%, and 34.5%, respectively), while on the other, 17% of the public retail firms filed for bankruptcy. We investigate how the following levers managed by the CEO of a retail firm affect performance: return on assets, sales growth, inventory turns, gross margin, financial leverage, and selling, general, and administrative expenses. The nature of the analysis is contemporaneous, providing insights into managerial actions that correlate with success as measured by stock returns, but not a prediction of future stock returns. We find that (1) return on assets, sales growth, standard deviation of return on assets and financial leverage explain more than 50% of the variation in stock returns for periods of ten years or more; (2) retailers in different segmentsâ apparel, department stores, grocery and convenience stores, drugs and pharmaceuticals, jewelry, consumer electronics, home furnishings, toys, and variety storesâ achieve similar return on assets and return on equity by following very different strategies with respect to their gross margins and inventory turns; (3) even within the same segment, high gross margin correlates with low inventory turns, and with high selling, general, and administrative expenses; (4) risk of bankruptcy is related to the mismatch between how fast a firm attempts to grow versus what growth rate it realizes. We also test for a negative correlation between sales growth and return on assets, which is widely believed to be true but is not borne out by our data.Operations Management Working Papers Serie

Design Simulation and Assessment of Cellular Automata Based Improved Image Segmentation System

A variety of methods may be found in the numerous image segmentation techniques. Here a method of text retrieval conducted is typically to produce a collection of localized features. In computer science, object recognition is the problem of automatically "identifying", or classifying, an object. In certain instances, the awareness of artifacts is deeper into image in image segmentation through image processing. The algorithm used for image segmentation has a direct impact on the outcome of the whole approach, therefore it is important to choose carefully. It is important to choose a segmentation method appropriate for a certain framework. There are several ready-to-use segmentation methods, so one by one evaluate the tools to see which works best. Segmentation algorithms have reached such a level of complexity that a research employing them is often considered impractical. The given research undertakes the process of improved graph cut method to select the foreground and background of image through labelling and segmentation of the image. Results have been compared on the performance parameter to analyse the effectiveness of the proposed algorithm for segmentation of the images

Signaling to Partially Informed Investors in the Newsvendor Model

We analyze a signaling game between the manager of a firm and an investor in the firm. The manager has private information about the firm\u27s demand and cares about the short-term stock price assigned by the investor. Previous research has shown that under continuous decision choices and the Intuitive Criterion refinement, the least-cost separating equilibrium will result, in which a low-quality firm chooses its optimal capacity and a high-quality firm over-invests in order to signal its quality to investors. We build on this research by showing the existence of pooling outcomes in which low-quality firms over-invest and high-quality firms under-invest so as to provide identical signals to investors. The pooling equilibrium is practically appealing because it yields a Pareto improvement compared to the least-cost separating equilibrium. Distinguishing features of our analysis are that: (i) we allow the capacity decision to have either discrete or continuous support, and (ii) we allow beliefs to be refined based on either the Undefeated refinement or the Intuitive Criterion refinement. We find that the newsvendor model parameters impact the likelihood of a pooling outcome, and this impact changes in both sign and magnitude depending on which refinement is used

Estimating Demand Uncertainty Using Judgmental Forecasts

Measuring demand uncertainty is a key activity in supply chain planning. Of various methods of estimating the standard deviation of demand, one that has been employed successfully in the recent literature uses dispersion among expertsâ forecasts. However, there has been limited empirical validation of this methodology. In this paper we provide a general methodology for estimating the standard deviation of a random variable using dispersion among expertsâ forecasts. We test this methodology using three datasets, demand data at item level, sales data at firm level for retailers, and sales data at firm level for manufacturers. We show that the standard deviation of a random variable (demand and sales for our datasets) is positively correlated with dispersion among expertsâ forecasts. Further we use longitudinal datasets with sales forecasts made 3-9 months before earnings report date for retailers and manufacturers to show that the effects of dispersion and scale on standard deviation of forecast error are consistent over time.Operations Management Working Papers Serie

What Explains Superior Retail Performance?

We analyze the performance of retail firms for the period 1978-97 using public financial data. Our performance measures are long-term stock returns and whether the firm filed for bankruptcy in the period of study. We assume that over a long time period of at least five years, stock returns are a reasonable measure of the overall success of a firm. We have found a very wide disparity in performance between firms. On the one hand, retailers like Wal-Mart, the Gap and Circuit City have had phenomenal success (nineteen year compounded stock returns of 31.2%, 29.5%, and 34.5%, respectively), while on the other, 17% of the public retail firms filed for bankruptcy. We investigate how the following levers managed by the CEO of a retail firm affect performance: return on assets, sales growth, inventory turns, gross margin, financial leverage, and selling, general, and administrative expenses. The nature of the analysis is contemporaneous, providing insights into managerial actions that correlate with success as measured by stock returns, but not a prediction of future stock returns. We find that (1) return on assets, sales growth, standard deviation of return on assets and financial leverage explain more than 50% of the variation in stock returns for periods of ten years or more; (2) retailers in different segmentsâ apparel, department stores, grocery and convenience stores, drugs and pharmaceuticals, jewelry, consumer electronics, home furnishings, toys, and variety storesâ achieve similar return on assets and return on equity by following very different strategies with respect to their gross margins and inventory turns; (3) even within the same segment, high gross margin correlates with low inventory turns, and with high selling, general, and administrative expenses; (4) risk of bankruptcy is related to the mismatch between how fast a firm attempts to grow versus what growth rate it realizes. We also test for a negative correlation between sales growth and return on assets, which is widely believed to be true but is not borne out by our data.Operations Management Working Papers Serie

MFS transportome of the human pathogenic yeast Candida albicans

<p>Abstract</p> <p>Background</p> <p>The major facilitator superfamily (MFS) is one of the two largest superfamilies of membrane transporters present ubiquitously in bacteria, archaea, and eukarya and includes members that function as uniporters, symporters or antiporters. We report here the complete transportome of MFS proteins of a human pathogenic yeast <it>Candida albicans</it>.</p> <p>Results</p> <p>Computational analysis of <it>C. albicans </it>genome enabled us to identify 95 potential MFS proteins which clustered into 17 families using Saier's Transport Commission (TC) system. Among these SP, DHA1, DHA2 and ACS represented major families consisting of 22, 22, 9 and 16 members, respectively. Family designations in <it>C. albicans </it>were validated by subjecting <it>Saccharomyces cerevisiae </it>genome to TC system. Based on the published available genomics/proteomics data, 87 of the putative MFS genes of <it>C. albicans </it>were found to express either at mRNA or protein levels. We checked the expression of the remaining 8 genes by using RT-PCR and observed that they are not expressed under basal growth conditions implying that either these 8 genes are expressed under specific growth conditions or they may be candidates for pseudogenes.</p> <p>Conclusion</p> <p>The <it>in silico </it>characterisation of MFS transporters in <it>Candida albicans </it>genome revealed a large complement of MFS transporters with most of them showing expression. Considering the clinical relevance of <it>C. albicans </it>and role of MFS members in antifungal resistance and nutrient transport, this analysis would pave way for identifying their physiological relevance.</p

COMMERCIAL-OFF-THE SHELF VENDOR SELECTION: A MULTI-CRITERIA DECISION-MAKING APPROACH USING INTUITIONISTIC FUZZY SETS AND TOPSIS

Commercial-off-the-shelf (COTS) component selection is considered a critical task in effectively developing a component-based software system (CBSS). COTS vendor selection involves selecting the right vendors who can provide reliable COTS components at a suitable price and on time. However, COTS vendor selection is commonly a multi-criteria decision-making (MCDM) issue” associated with many paradoxical criteria for which the decision maker’s knowledge may be uncertain and ambiguous. This paper attempts to present “Intuitionistic Fuzzy Sets (IFS) combined with the technique for order preference by similarity to an ideal solution (TOPSIS) method” to appraise and choose the best COTS vendor under the environment of group decision-making while considering reliability, delivery time, compatibility, vendor support and functionality as benefit criteria. In contrast, price and maintenance are the cost criteria. The considered case study demonstrated the presented case effectively