Performance Measurement System Based on Supply Chain Operations Reference Model: Review and Proposal

Current study provides a performance measurement system (PMS) based on Supply Chain Operations Reference (SCOR) adapted for the service sector. A systematic literature review was conducted on 16 performance measurement systems, which included 44 performance indicators and various performance metrics. Performance indicators and metrics were sorted according to conceptual similarities and then related to the five management processes intrinsic to SCOR model (plan, source, make, deliver and return). Indicators researched in a review of the literature were classified into six groups, namely, financial, velocity, sustainability, quality, resource utilization and customer services. The proposed PMS fills a gap in literature by forwarding a tool for the evaluation of the supply chain performance within the service sector

A preliminary study on post-occupancy evaluation of four office buildings in the UK based on the Analytic Hierarchy Process

There is a lack of a systematic decision-making criterion to select appropriate indicators for Post-Occupancy Evaluation (POE) analysis due to the fact that significant levels of various POE determinants are indeterminate. The present work aims to identify the degree of importance of a set of POE determinants based on Analytic Hierarchy Process (AHP). A case study of POE for four office buildings in the UK has been conducted using the AHP to ascertain the significance levels of three main factors identified, namely, Indoor Environment Quality (IEQ), Occupants’ Performance (OP) and Workplace Quality (WQ) as well as three groups of sub-factors affiliated to the main factors based on questionnaire surveys of the building occupants. The results show that the priority factors of the three main evaluation metrics, IEQ, OP, WQ are 0.595, 0.183 and 0.222, respectively, indicating that of these three factors the IEQ is the paramount factor in relation to the POE level of the office buildings. Moreover, the global priorities of all sub-factors linked to the main factors are obtained, providing a strategy reference of choosing indicators as per the priorities for a continuing POE in the further survey and measurement

Bridging the Gap between Security/Risk and Quality

An IT security vulnerability can be considered as an inherent weakness in a target system that could be exploited by a threat source. The underlying hypothesis in our proposal is that each identified attribute associated with the target entity to be controlled should show the highest quality satisfaction level as an elementary indicator. The higher the quality indicator value achieved per each attribute, the lower the vulnerability indicator value and therefore the potential impact from the risk standpoint. In the present work, we discuss the added value of supporting the IT security and risk assessment areas with measurement and evaluation (M&E) methods and strategy, which are based on metrics and indicators. Also we illustrate excerpts of an M&E case study for characteristics and attributes of Security, and their potential risk assessment.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Bridging the Gap between Security/Risk and Quality

An IT security vulnerability can be considered as an inherent weakness in a target system that could be exploited by a threat source. The underlying hypothesis in our proposal is that each identified attribute associated with the target entity to be controlled should show the highest quality satisfaction level as an elementary indicator. The higher the quality indicator value achieved per each attribute, the lower the vulnerability indicator value and therefore the potential impact from the risk standpoint. In the present work, we discuss the added value of supporting the IT security and risk assessment areas with measurement and evaluation (M&E) methods and strategy, which are based on metrics and indicators. Also we illustrate excerpts of an M&E case study for characteristics and attributes of Security, and their potential risk assessment.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Prevent Low-Quality Analytics by Automatic Selection of the Best-Fitting Training Data

Data analysis pipelines consist of a sequence of various analysis tools. Most of these tools are based on supervised machine learning techniques and thus rely on labeled training data. Selecting appropriate training data has a crucial impact on analytics quality. Yet, most of the times, domain experts who construct analysis pipelines neglect the task of selecting appropriate training data. They rely on default training data sets, e.g., since they do not know which other training data sets exist and what they are used for. Yet, default training data sets may be very different from the domain-specific input data that is to be analyzed, leading to low-quality results. Moreover, these input data sets are usually unlabeled. Thus, information on analytics quality is not measurable with evaluation metrics. Our contribution comprises a method that (1) indicates the expected quality to the domain expert while constructing the analysis pipeline, without need for labels and (2) automatically selects the best-fitting training data. It is based on a measurement of the similarity between input and training data. In our evaluation, we consider the part-of-speech tagger tool and show that Latent Semantic Analysis (LSA) and Cosine Similarity are suited as indicators for the quality of analysis results and as basis for an automatic selection of the best-fitting training data

Classification of Performance and Quality Indicators in Manufacturing

A critical aspect in operations management is to represent the firm goals properly. This is usually done by translating the organisational results and objectives in ‘performance measurements'. The scientific literature shows many applications in different fields such as quality, production, logistics, marketing, etc. Nevertheless, a general theory formalising basic and application concepts is still lacking. This paper shows a classification of ‘performance indicators' in manufacturing, providing a mathematical structure to the concept of ‘indicator'. This approach is based on the formalism of the Representation Theory. All the mentioned concepts are explained and discussed through practical example

Do altmetrics correlate with the quality of papers? A large-scale empirical study based on F1000Prime data

In this study, we address the question whether (and to what extent, respectively) altmetrics are related to the scientific quality of papers (as measured by peer assessments). Only a few studies have previously investigated the relationship between altmetrics and assessments by peers. In the first step, we analyse the underlying dimensions of measurement for traditional metrics (citation counts) and altmetrics - by using principal component analysis (PCA) and factor analysis (FA). In the second step, we test the relationship between the dimensions and quality of papers (as measured by the post-publication peer-review system of F1000Prime assessments) - using regression analysis. The results of the PCA and FA show that altmetrics operate along different dimensions, whereas Mendeley counts are related to citation counts, and tweets form a separate dimension. The results of the regression analysis indicate that citation-based metrics and readership counts are significantly more related to quality, than tweets. This result on the one hand questions the use of Twitter counts for research evaluation purposes and on the other hand indicates potential use of Mendeley reader counts

Towards evaluation design for smart city development

Smart city developments integrate digital, human, and physical systems in the built environment. With growing urbanization and widespread developments, identifying suitable evaluation methodologies is important. Case-study research across five UK cities - Birmingham, Bristol, Manchester, Milton Keynes and Peterborough - revealed that city evaluation approaches were principally project-focused with city-level evaluation plans at early stages. Key challenges centred on selecting suitable evaluation methodologies to evidence urban value and outcomes, addressing city authority requirements. Recommendations for evaluation design draw on urban studies and measurement frameworks, capitalizing on big data opportunities and developing appropriate, valid, credible integrative approaches across projects, programmes and city-level developments