ALOJA: A benchmarking and predictive platform for big data performance analysis

The main goals of the ALOJA research project from BSC-MSR, are to explore and automate the characterization of cost-effectivenessof Big Data deployments. The development of the project over its first year, has resulted in a open source benchmarking platform, an online public repository of results with over 42,000 Hadoop job runs, and web-based analytic tools to gather insights about system's cost-performance1. This article describes the evolution of the project's focus and research lines from over a year of continuously benchmarking Hadoop under dif- ferent configuration and deployments options, presents results, and dis cusses the motivation both technical and market-based of such changes. During this time, ALOJA's target has evolved from a previous low-level profiling of Hadoop runtime, passing through extensive benchmarking and evaluation of a large body of results via aggregation, to currently leveraging Predictive Analytics (PA) techniques. Modeling benchmark executions allow us to estimate the results of new or untested configu- rations or hardware set-ups automatically, by learning techniques from past observations saving in benchmarking time and costs.This work is partially supported the BSC-Microsoft Research Centre, the Span- ish Ministry of Education (TIN2012-34557), the MINECO Severo Ochoa Research program (SEV-2011-0067) and the Generalitat de Catalunya (2014-SGR-1051).Peer ReviewedPostprint (author's final draft

Empirical Evidence of RFID Impacts on Supply Chain Performance

Purpose - The purpose of this paper is to investigate the actual benefits of radio frequency identification (RFID) on supply chain performance through the empirical evidence. Design/methodology/approach - The research reviews and classifies the existing quantitative empirical evidence of RFID on supply chain performance. The evidence is classified by process (operational or managerial) and for each process by effect (automational, informational, and transformational). Findings - The empirical evidence shows that the major effects from the implementation of RFID are automational effects on operational processes followed by informational effects on managerial processes. The RFID implementation has not reached transformational level on either operational or managerial processes. RFID has an automational effect on operational processes through inventory control and efficiency improvements. An informational effect for managerial processes is observed for improved decision quality, production control and the effectiveness of retail sales and promotions coordination. In addition, a three-stage model is proposed to explain the effects of RFID on the supply chain. Research limitations/implications - Limitations of this research include the use of secondary sources and the lack of consistency in performance measure definitions. Future research could focus on detailed case studies that investigate cross-functional applications across the organization and the supply chain. Practical implications - For managers, the empirical evidence presented can help them identify implementation areas where RFID can have the greatest impact. The data can be used to build the business case for RFID and therefore better estimate ROI and the payback period. Originality/value - This research fills a void in the literature by providing practitioners and researchers with a better understanding of the quantitative benefits of RFID in the supply chain

SciTech News Volume 70, No. 4 (2016)

Columns and Reports From the Editor 3 Division News Science-Technology Division 4 SLA Annual Meeting 2016 Report (S. Kirk Cabeen Travel Stipend Award recipient) 6 Reflections on SLA Annual Meeting (Diane K. Foster International Student Travel Award recipient) 8 SLA Annual Meeting Report (Bonnie Hilditch International Librarian Award recipient)10 Chemistry Division 12 Engineering Division 15 Reflections from the 2016 SLA Conference (SPIE Digital Library Student Travel Stipend recipient)15 Fundamentals of Knowledge Management and Knowledge Services (IEEE Continuing Education Stipend recipient) 17 Makerspaces in Libraries: The Big Table, the Art Studio or Something Else? (by Jeremy Cusker) 19 Aerospace Section of the Engineering Division 21 Reviews Sci-Tech Book News Reviews 22 Advertisements IEEE 17 WeBuyBooks.net 2

Classifying Web Exploits with Topic Modeling

This short empirical paper investigates how well topic modeling and database meta-data characteristics can classify web and other proof-of-concept (PoC) exploits for publicly disclosed software vulnerabilities. By using a dataset comprised of over 36 thousand PoC exploits, near a 0.9 accuracy rate is obtained in the empirical experiment. Text mining and topic modeling are a significant boost factor behind this classification performance. In addition to these empirical results, the paper contributes to the research tradition of enhancing software vulnerability information with text mining, providing also a few scholarly observations about the potential for semi-automatic classification of exploits in the existing tracking infrastructures.Comment: Proceedings of the 2017 28th International Workshop on Database and Expert Systems Applications (DEXA). http://ieeexplore.ieee.org/abstract/document/8049693

The accommodation experiencescape: a comparative assessment of hotels and Airbnb

PURPOSE: Accommodations providers in the sharing economy are increasingly competing with the hotel industry vis-à-vis the guest experience. Additionally, experience-related research remains underrepresented in the hospitality and tourism literature. This paper aims to develop and test a model of experiential consumption to provide a better understanding of an emerging phenomenon in the hospitality industry. In so doing, the authors also expand Pine and Gilmore’s original experience economy construct. DESIGN/METHODOLOGY/APPROACH: Using data from a survey of 630 customers who stayed at a hotel or an Airbnb in the previous three months, the authors performed a multi-step analysis procedure centered on structural equation modeling to validate the model. Findings The authors demonstrate that the dimensions of serendipity, localness, communitas and personalization represent valuable additions to Pine and Gilmore’s original experience economy construct. Airbnb appears to outperform the hotel industry in the provision of all experience dimensions. The authors further define the pathways that underlie the creation of extraordinary, memorable experiences, which subsequently elicit favorable behavioral intentions. PRACTICAL IMPLICATIONS: The findings suggest the need for the hotel industry to adopt a content marketing paradigm that leverages various dimensions of the experience economy to provide customers with valuable and relevant experiences. The industry must also pay greater attention to its use of branding, signage and promotional messaging to encourage customers to interpret their experiences through the lens of these dimensions. ORIGINALITY/VALUE: The study expands a seminal construct from the field of services marketing in the context of the accommodations industry. The Accommodations Experiencescape is offered as a tool for strategic experience design. The study also offers a model of experiential consumption that explains customers’ experiences with accommodations providers