Lustre, Hadoop, Accumulo

Data processing systems impose multiple views on data as it is processed by the system. These views include spreadsheets, databases, matrices, and graphs. There are a wide variety of technologies that can be used to store and process data through these different steps. The Lustre parallel file system, the Hadoop distributed file system, and the Accumulo database are all designed to address the largest and the most challenging data storage problems. There have been many ad-hoc comparisons of these technologies. This paper describes the foundational principles of each technology, provides simple models for assessing their capabilities, and compares the various technologies on a hypothetical common cluster. These comparisons indicate that Lustre provides 2x more storage capacity, is less likely to loose data during 3 simultaneous drive failures, and provides higher bandwidth on general purpose workloads. Hadoop can provide 4x greater read bandwidth on special purpose workloads. Accumulo provides 10,000x lower latency on random lookups than either Lustre or Hadoop but Accumulo's bulk bandwidth is 10x less. Significant recent work has been done to enable mix-and-match solutions that allow Lustre, Hadoop, and Accumulo to be combined in different ways.Comment: 6 pages; accepted to IEEE High Performance Extreme Computing conference, Waltham, MA, 201

Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store Placement

The problem of identifying the optimal location for a new retail store has been the focus of past research, especially in the field of land economy, due to its importance in the success of a business. Traditional approaches to the problem have factored in demographics, revenue and aggregated human flow statistics from nearby or remote areas. However, the acquisition of relevant data is usually expensive. With the growth of location-based social networks, fine grained data describing user mobility and popularity of places has recently become attainable. In this paper we study the predictive power of various machine learning features on the popularity of retail stores in the city through the use of a dataset collected from Foursquare in New York. The features we mine are based on two general signals: geographic, where features are formulated according to the types and density of nearby places, and user mobility, which includes transitions between venues or the incoming flow of mobile users from distant areas. Our evaluation suggests that the best performing features are common across the three different commercial chains considered in the analysis, although variations may exist too, as explained by heterogeneities in the way retail facilities attract users. We also show that performance improves significantly when combining multiple features in supervised learning algorithms, suggesting that the retail success of a business may depend on multiple factors.Comment: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, Chicago, 2013, Pages 793-80

The impact of nonlinear dynamics on the resilience of a grocery supply chain

Purpose of this paper: In an effort to improve operational and logistical efficiencies, UK grocery retailers combined primary and secondary distribution increasing the importance of designing resilient replenishment systems in the distribution centre. This paper has the purpose to analyse the resilience performance of the distribution centre stock ordering system within a grocery retailer. Design/methodology/approach: A system dynamics approach is used for framing and building a credible representation of the real system. Mathematical analysis of the nonlinear model based on nonlinear control engineering techniques in combination with system dynamics simulation have been used to understand the behaviour of stock and shipment output responses in the distribution centre given step and periodic demand signals. Findings: Preliminary mathematical analysis through nonlinear control theory techniques has been undertaken in order to gain initial insights in the understanding of the replenishment control model. This practice allowed the researcher to identify specific behaviour change in the DC stock and shipment responses, which are key indicators for assessing supply chain resilience, without going through a time-consuming simulation process. Transfer function analysis and describing function serve as a guideline for undertaking system dynamics simulation. Value: This paper aims to fill the gap in the literature of supply chain resilience by using quantitative system dynamics methods to assess the resilience performance of a grocery retailer. In this way, we also supplement the literature with empirical data. Moreover, we explore different analytical methods since simulation is the predominant method for quantitative analysis of system dynamics. Research limitations/implications (if applicable): This research is limited to the dynamics of single-echelon supply chain systems. Although the EPOS sales data and the store replenishment system have been considered in the validation process, this study has focused on analysing the resilience performance of the DC replenishment system only. Considering the multi-echelon supply chain is intended for further research activities. Practical implications (if applicable): The findings suggest that the distribution centre replenishment system can be re-designed in order to improve the supply chain resilience performance. The ‘As Is’ scenario produces slow response of stock levels and inventory targets are never recovered due to a permanent offset

Impact of Performance and Expressiveness Value of Store Service Quality on the Mediating Role of Satisfaction with Store

This study explores the extent to which store service attributes having appeal for consumer self-image impacts store satisfaction and patronage intentions and discovers that this "expressiveness" value has significant associations with both. By using the adapted RSQS for measuring service quality in the Indian appare! retail context, this paper finds that service expressiveness value is distinct from the performance value obtained from service delivery. This paper provides empirical evidence that the mediation effect of satisfaction varies depending on consumer perceived value from service and that it is neither as universal nor as strong as retailers and researchers lend to believe.

Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error

A decision-making approach for investigating the potential effects of near sourcing on supply chain

Purpose - Near sourcing is starting to be regarded as a valid alternative to global sourcing in order to leverage supply chain (SC) responsiveness and economic efficiency. The present work proposes a decision-making approach developed in collaboration with a leading Italian retailer that was willing to turn the global store furniture procurement process into near sourcing. Design/methodology/approach - Action research is employed. The limitations of the traditional SC organisation and purchasing process of the company are first identified. On such basis, an inventory management model is applied to run spreadsheet estimates where different purchasing and SC management strategies are adopted to determine the solution providing the lowest cost performance. Finally, a risk analysis of the selected best SC arrangement is conducted and results are discussed. Findings - Switching from East Asian suppliers to continental vendors enables a SC reengineering that increases flexibility and responsiveness to demand uncertainty which, together with decreased transportation costs, assures economic viability, thus proving the benefits of near sourcing. Research limitations/implications - The decision-making framework provides a methodological roadmap to address the comparison between near and global sourcing policies and to calculate the savings of the former against the latter. The approach could include additional organisational aspects and cost categories impacting on near sourcing and could be adapted to investigate different products, services, and business sectors. Originality/value - The work provides SC researchers and practitioners with a structured approach for understanding what drives companies to adopt near sourcing and for quantitatively assessing its advantage

Notions of Knowledge Management

{Excerpt} Knowledge management is getting the right knowledge to the right people at the right time, and helping them (with incentives) to apply it in ways that strive to improve organizational performance. Data are facts, and information is interpreted data. Knowledge is created and organized by flows of information, shaped by their holder. It is tacit or explicit. Tacit knowledge is nonverbalized, intuitive, and unarticulated knowledge that people carry in their heads. It is hard to formalize and communicate because it is rooted in skills, experiences, insight, intuition, and judgment, but it can be shared in discussion, storytelling, and personal interactions. It has a technical dimension, which encompasses skills and capabilities referred to as know-how. It has a cognitive dimension, which consists of beliefs, ideals,values, schemata, or mental models. Explicit knowledge is codified knowledge that can be expressed in writing, drawings, or computer programs, for example, and transmitted in various forms. Tacit knowledge and explicit knowledge are mutually complementary forms of meaning