Metrics for Measuring Data Quality - Foundations for an Economic Oriented Management of Data Quality

The article develops metrics for an economic oriented management of data quality. Two data quality dimensions are focussed: consistency and timeliness. For deriving adequate metrics several requirements are stated (e. g. normalisation, cardinality, adaptivity, interpretability). Then the authors discuss existing approaches for measuring data quality and illustrate their weaknesses. Based upon these considerations, new metrics are developed for the data quality dimensions consistency and timeliness. These metrics are applied in practice and the results are illustrated in the case of a major German mobile services provider

Classification of data collection methods (= Deliverable 3.1 of the OrganicDataNetwork project - Report on collection methods)

In this report, a number of evaluation and quality criteria for data collection and compilation methods were defined. The results of an online survey on all existing organic market data collection methods in Europe were compiled and assessed. Subsequently the quality of existing data collection and processing approaches was evaluated using the following data quality dimensions: relevance, accuracy, comparability, coherence, accessibility and clarity, and timeliness and punctuality. The quality assessment was carried out exemplary to determine some good examples of data collection and processing. These cases were chosen because they delivered a very holistic and comprehensive presentation of their approaches regarding data collection methods, analyses, quality checks, and publication

Service quality in alcohol treatment: a research note

Purpose - To evaluate service quality in a UK privately funded alcohol treatment clinic. Methodology - Data were gathered via interviews with two groups of participants using the SERVQUAL questionnaire. The first group comprised 32 patients and the second 15 clinic staff. The SERVQUAL instrument measures service quality expectations and perceptions across five service dimensions and identifies gaps between service expectations and perceptions of what was delivered. Findings – Patients’ service quality expectations were exceeded on four of five dimensions. However, staff members felt services fell below expectations on four of five dimensions with the ‘reliability’ service dimension emerging as the common service element falling below expectations for both participant groups. It was concluded that achieving consistent service delivery and increasing empathy between staff and patients improves overall service quality perceptions. Research limitations - Relies on self-report methods from a relatively small number of individuals. Originality - There have been limited research studies measuring alcohol treatment service quality in the private sector

Examining client perceptions of partnership quality and its dimensions in an IT outsourcing relationship

This paper reports on an empirical study of the multidimensionality of partnership quality in IT outsourcing arrangements and the relationships between these dimensions of partnership quality. A two-phase national survey was conducted to collect empirical data to confirm the dimensions of partnership quality in an IT outsourcing arrangement from the client organisation perspective and to identify the significant relationships between these dimensions using a second generation multivariate analysis technique—partial least squares (PLS). The findings from results of the data analyses show that inter-organisational trust, shared business understanding and to a lesser extent, functional and dysfunctional conflict between the client organisation and the outsourcing vendor in an IT outsourcing relationship are the key determinants of partnership quality. The key outcome variable for high partnership quality between the client organisation and the outsourcing vendor in an IT outsourcing relationship is mutual beneficial sharing of risks and benefits. Commitment in an IT outsourcing relationship is confirmed as a multidimensional construct of behaviour commitment and temporal/continuance commitment and was found to be influenced by the other dimensions of partnership quality. The key findings of this study provide support for the notion that trust and shared business understanding are key drivers in the IT outsourcing partnership style relationship ensuring that the sharing of risks and benefits are realised and conflict is minimised leading to a high quality and ultimately successful partnership between the client organisation and the outsourcing vendor. Furthermore our findings indicate that behavioural commitment to the contractual obligations of an IT outsourcing relationship sustains an ongoing temporal commitment to the partnership between the client organisation and the outsourcing vendor

Toward a framework for data quality in cloud-based health information system

This Cloud computing is a promising platform for health information systems in order to reduce costs and improve accessibility. Cloud computing represents a shift away from computing being purchased as a product to be a service delivered over the Internet to customers. Cloud computing paradigm is becoming one of the popular IT infrastructures for facilitating Electronic Health Record (EHR) integration and sharing. EHR is defined as a repository of patient data in digital form. This record is stored and exchanged securely and accessible by different levels of authorized users. Its key purpose is to support the continuity of care, and allow the exchange and integration of medical information for a patient. However, this would not be achieved without ensuring the quality of data populated in the healthcare clouds as the data quality can have a great impact on the overall effectiveness of any system. The assurance of the quality of data used in healthcare systems is a pressing need to help the continuity and quality of care. Identification of data quality dimensions in healthcare clouds is a challenging issue as data quality of cloud-based health information systems arise some issues such as the appropriateness of use, and provenance. Some research proposed frameworks of the data quality dimensions without taking into consideration the nature of cloud-based healthcare systems. In this paper, we proposed an initial framework that fits the data quality attributes. This framework reflects the main elements of the cloud-based healthcare systems and the functionality of EHR

Service quality in a post-crisis context: emotional effects and behaviours

Purpose – The purpose of this paper is to analyse the influence of service quality dimensions as determinants of the emotional and relational behaviours experienced by the client in bank branches in the post-crisis context experienced by Spanish financial institutions. Design/methodology/approach – Data taken from a total of 1,125 customers were analysed through structural equations modelling (EQS6.1) to test the relationships of the proposed model’s variables. Findings – The results support the hypotheses stated, with the exception of the influence of a service quality dimension (servicescape) on emotions during the service. In fact, the dimensions of the service quality of an intangible nature (personnel, outcome and social) are determinants of the positive emotions and relational behaviours of clients around the service provided by the branches. For its part, servicescape quality, of a more tangible nature, exerts indirect influence on the other dimensions that compose the quality of service. Practical implications – This paper provides senior bank executives established evidence on the degree of influence of the different dimensions in relation to the quality of service in the bank branch. Furthermore, it emphasises the importance of emotional factors during service as essential elements in strengthening customer–staff relationships under a non-transactional dynamic. Originality/value – This paper has adopted an analytical holistic, theoretical and empirical perspective on the impact of the different dimensions of service quality (servicescape, personnel, outcome and social) as well as to the emotions experienced by banking customers during services and its lasting effect on customer engagement and customer advocacy

IMPROVING PERCEPTUAL DIMENSION OF KNOWLEDGE QUALITY BY AUDIT TECHNIQUES

This paper present the problems linked to the knowledge quality concept, taking into account the logical, the structural and the perceptual dimensions of knowledge quality. The logical dimension is based on data and software applications quality and can be improved by technical and computerized environment control audit. The structural dimension is discussed in connection with modularity, data base object model and redundancy check. To improve the perceptual dimension of knowledge quality we analyze the possibility of using the performance audit techniques. Thus way it can be offered to the managers the perception that data and knowledge have been well evaluated, in according with clear hypothesis, operational risks and with no missing analytical data. Two indicators, GPS - Quantitative Precision of the Supplier and TSD Total Stock Duration, are presented as examples of how the perceptual dimension can be improved by the performance audit.Knowledge Quality, Quality Dimensions, Perceptual Dimension, IT Audit

Big data quality dimensions: a systematic literature review

Although big data has become an integral part of businesses and society, there is still concern about the quality aspects of big data. Past research has focused on identifying various dimensions of big data. However, the research is scattered and there is a need to synthesize the ever involving phenomenon of big data. This research aims at providing a systematic literature review of the quality dimension of big data. Based on a review of 17 articles from academic research, we have presented a set of key quality dimensions of big data.Although big data has become an integral part of businesses and society, there is still concern about the quality aspects of big data. Past research has focused on identifying various dimensions of big data. However, the research is scattered and there is a need to synthesize the ever involving phenomenon of big data. This research aims at providing a systematic literature review of the quality dimension of big data. Based on a review of 17 articles from academic research, we have presented a set of key quality dimensions of big data