202,393 research outputs found

    From traditional to new hotel revenue management metrics: An exploratory study on the potential of NRevPAR and RevPAC

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    Purpose – This research aims to uncover the weaknesses of traditional hotel revenue management metrics (RM) and evaluate the potential application of two new metrics, specifically net revenue per available room and revenue per available customer. Design/Methodology/Approach – Initially, a focus group roundtable discussion was conducted with 15 participants who held managerial positions in various hotel chains. The objective was to identify critical hotel revenue metrics to be included in the subsequent online questionnaire. An online questionnaire was then distributed to HSMAI members in Asia, the Americas and Europe, as well as through personal contacts. In addition to quantitative analyzes, the data were also content analyzed to reveal the weaknesses of the existing RM performance assessment tools based on the technology-organization-environment framework. Findings – Considering the positive results, the application of the new metrics would be well accepted by RM. However, the weaknesses of the traditional RM metrics in terms of data quality and robustness, completeness of measurements, comparability with industry, and organizational support should be considered when designing the new RM metrics. Originality of the research – This study is the first to offer insights into the potential of designing new RM measures. It also provides guidance on what to consider when developing new RM metrics

    A brokerage system for enhancing wireless access

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    This paper contributes to the management of a network infrastructure formed by distinct wireless access technologies, which are administered by several cooperating mobile operators. These wireless technologies may cover a public area, which at specific times of the day are overwhelmed by a large number of users. A new management solution is proposed that controls the heterogeneous network infrastructure in a distributed way, using policies and metrics, and ensuring a Quality of Service (QoS) level associated with each terminal connection. The QoS level is supported through a novel, vertical and dynamic aggregation of performance information about the wireless access, originated at distinct technologies. A closed innovative control loop among a flexible brokerage service in the network, and agents at the mobile terminals, counteracts any abnormal data load. This allows the terminals to make well-informed decisions about their connections to improve on the QoS offered to the application layer. In this way, depending on the management policies of the brokerage service and the quality metrics, wireless access technologies that by default only offer a best-effort connection service can be enhanced in a very straightforward way. The obtained results highlight the advantages for using this new distributed solution to manage the heterogeneous network infrastructure in several distinct usage scenarios.info:eu-repo/semantics/acceptedVersio

    DEVELOPMENT OF A SPRAYER PERFORMANCE DIAGNOSTIC TOOL USING IMPROVED MAPPING AND ERROR QUANTIFICATION PRACTICES

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    While sprayer technologies have advanced greatly over the past decade and a half, chemical application errors are still prominent in many in-field operations. Over-application of pesticides can cause harm to the crop, reducing yield, and result in added pollution to the environment. Under-application of pesticides fails to control pests within the field, again lowering crop yields, and causing profit loss for the producer. Current operator feedback from in-field pesticide application operations conveys limited information and often times does not allow the operator to visualize a true representation of their performance. Farm Management Information Systems (FMIS) typically do not account for overlap, varying application rates across the width of the spray boom during turns, or off-rate errors due to controller response. Improved mapping systems and product distribution summaries would allow operators to make better-informed decisions leading to improved management practices during spraying operations. The Pesticide Application Coverage Training (PACT) tool was developed to deploy data analytics methodologies to sprayer operations data collected during field applications. The goal was to provide improved operator feedback allowing for better management practices by providing enhanced feedback to operators over the course of two years. Data were collected for multiple Nebraska fields and processed by the PACT program which generated high-resolution as-applied maps and quantified error reports. PACT program output metrics were compared with currently available sprayer feedback software and previous studies related to high-resolution as-applied maps. Field-average metrics were not found to be significantly different when comparing the PACT program with these systems. However, when examining how in-field errors were distributed amongst various application rate ranges, significant differences were found. Differences in errors broken down by application rate ranges implied successful inclusion of previously unaccounted for error types by the PACT program. In addition, the program showed potential for technology adoption decision support. The PACT program successfully improved upon current sprayer operator feedback systems which will offer a platform for supporting better management practices in the future. Advisor: Joe D. Luc

    Performance of Network and Service Monitoring Frameworks

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    The efficiency and the performance of anagement systems is becoming a hot research topic within the networks and services management community. This concern is due to the new challenges of large scale managed systems, where the management plane is integrated within the functional plane and where management activities have to carry accurate and up-to-date information. We defined a set of primary and secondary metrics to measure the performance of a management approach. Secondary metrics are derived from the primary ones and quantifies mainly the efficiency, the scalability and the impact of management activities. To validate our proposals, we have designed and developed a benchmarking platform dedicated to the measurement of the performance of a JMX manager-agent based management system. The second part of our work deals with the collection of measurement data sets from our JMX benchmarking platform. We mainly studied the effect of both load and the number of agents on the scalability, the impact of management activities on the user perceived performance of a managed server and the delays of JMX operations when carrying variables values. Our findings show that most of these delays follow a Weibull statistical distribution. We used this statistical model to study the behavior of a monitoring algorithm proposed in the literature, under heavy tail delays distribution. In this case, the view of the managed system on the manager side becomes noisy and out of date

    The Making of Cloud Applications An Empirical Study on Software Development for the Cloud

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    Cloud computing is gaining more and more traction as a deployment and provisioning model for software. While a large body of research already covers how to optimally operate a cloud system, we still lack insights into how professional software engineers actually use clouds, and how the cloud impacts development practices. This paper reports on the first systematic study on how software developers build applications in the cloud. We conducted a mixed-method study, consisting of qualitative interviews of 25 professional developers and a quantitative survey with 294 responses. Our results show that adopting the cloud has a profound impact throughout the software development process, as well as on how developers utilize tools and data in their daily work. Among other things, we found that (1) developers need better means to anticipate runtime problems and rigorously define metrics for improved fault localization and (2) the cloud offers an abundance of operational data, however, developers still often rely on their experience and intuition rather than utilizing metrics. From our findings, we extracted a set of guidelines for cloud development and identified challenges for researchers and tool vendors
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