Examining the dimensionality and measurement of user-perceived knowledge and information quality in the KMS context

Wang, Yumin; Wang, Yi-Shun

doi:10.1177/0165551508092260

Cited by 20 publications

(18 citation statements)

References 37 publications

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“…In this respect, the values of the metric for currency Q Curr. (, A) can be computed automatically by using formula (3) …”

Section: B Computation Of the Values Of The Metric Q Curr ( A) Onmentioning

confidence: 99%

“…In addition, T  [0; ] represents the shelf life of the attribute value, which is usually finite and unknown. 3 We then consider the shelf life to be a continuous random variable and assume that it is exponentially distributed. The exponential distribution is a typical probability distribution for lifetime, which has proven its usefulness in quality management.…”

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confidence: 99%

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Assessing data currency — a probabilistic approach

Heinrich

Klier

2010

Journal of Information Science

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Abstract.The growing relevance of data quality has revealed the need for adequate measurement. As time aspects are extremely important in data quality management, we propose a novel approach to assess data currency. Our metric, which is founded on probability theory, enables an objective and widely automated assessment for data liable to temporal decline. Its values are easy to interpret by business users. Moreover, the metric makes it possible to analyse the economic impacts of data quality measures like data cleansing and can therefore build a basis for an economic management of data quality. The approach can be applied in various fields of application where the currency of data is important. To illustrate the practical benefit and the applicability of the novel metric, we provide an extensive realworld example. In cooperation with a major German mobile services provider, the approach was successfully applied in campaign management and led to an improved decision support.Keywords: data quality; data quality assessment; data quality metrics IntroductionBoth the benefit and the acceptance of information systems depend heavily on the quality of data provided by these systems [1][2][3]. Executives and employees need high-quality data in order to perform business, innovation, and decision-making processes properly [4,5]. It is, therefore, not surprising that bad data quality may lead to wrong decisions and correspondingly high costs. According to an international survey, 75 percent of all respondents have already made wrong decisions due to incorrect or outdated data. In addition, they and their staff spend up to 30 percent % of their working time on checking the quality of data provided [6]. Here, ensuring completeness, correctness and currency of data -such properties are known as data quality dimensions [7] -still remains an important problem for many companies and public institutions [8][9][10][11][12][13]. But how good is an organization's data quality? To answer this important question, well-founded and applicable metrics are needed [8,14,15]. In addition, assessing data quality (e.g. master data) is essential for analysing the economic effects of bad or improved data quality as well as for planning data quality measures in an economic manner. In this paper, we present a novel metric for currency, as empirical investigations reveal that time aspects are extremely

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“…In this respect, the values of the metric for currency Q Curr. (, A) can be computed automatically by using formula (3) …”

Section: B Computation Of the Values Of The Metric Q Curr ( A) Onmentioning

confidence: 99%

mentioning

confidence: 99%

Assessing data currency — a probabilistic approach

Heinrich

Klier

2010

Journal of Information Science

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“…Based on the existing measures related to user information satisfaction, e-learner satisfaction, and knowledge and information quality 550 INTR 24,5 (e.g. Baroudi and Orlikowski, 1988;Doll and Torkzadeh, 1988;Palvia, 1996;Piccoli et al, 2001;Wang, 2003;Shee and Wang, 2008;Wang and Wang, 2009) and on the differences in characteristics between traditional web-based learning and blog-based learning (e.g. automatic cross-linking, knowledge repositories, and knowledge maps), this study therefore proposed 31 items to represent various dimensions underlying the ELBS construct, and these were used to form the initial pool of items for the ELBS scale.…”

Section: Research Methodology 31 Generation Of Scale Itemsmentioning

confidence: 99%

“…System content, personalization, learning community, and learner interface Wang and Wang (2009) Perceived knowledge and information quality Content quality, and context and linkage quality Chen (2010) User satisfaction with e-learning systems Information quality, and system quality Wang and Chiu (2011) User satisfaction with e-learning 2.0 systems Information quality, system quality, service quality, and communication quality Udo et al (2011) E-learning quality Web site content, assurance, empathy, responsiveness, and reliability Hassanzadeh et al (2012) User satisfaction with e-learning systems Technical system quality, content and information quality, and educational system quality Wang et al, 2007;Chen, 2010;Wang and Chiu, 2011;Hassanzadeh et al, 2012). However, these studies focussed mainly on the measures of e-learning systems success and on the relationships among system success measures, such as information quality, system quality, service quality, user satisfaction, and system use, rather than on the measure of e-learning satisfaction itself.…”

Section: E-learner Satisfactionmentioning

confidence: 99%

The measurement and dimensionality of e-learning blog satisfaction

Wang

Lin

et al. 2014

Internet Research

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Purpose – The purpose of this paper is to develop and validate a multi-dimensional instrument to measure e-learning blog satisfaction (ELBS). Design/methodology/approach – This study introduces and defines the construct of ELBS, provides an empirical validation of the construct and its underlying dimensionality, develops a generic ELBS instrument with desirable psychometric properties, and investigates the instrument's theoretical and practical applications. Findings – After analyzing data from a calibration sample (n=238) and a validation sample (n=226), this study proposes a five-factor, 20-item ELBS instrument. Practical implications – This empirically validated instrument will be useful to researchers in terms of developing and testing blog-based learning theories, as well as to educators in terms of understanding students’ ELBS and promoting the use of blog-based learning systems. Originality/value – This study is a pioneering effort to develop and validate a multi-dimensional instrument to measure ELBS.

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“…Studies in Information Systems have adopted consultation of experts before testing models, especially in order to build and validate the collection instrument (e.g., Wang & Wang, 2009). Additionally, the perception of managers concerning IT impacts at the levels of processes and firm has been found to present similar results to studies using objective metrics for assessment of IT performance (Tallon, 2013;Tallon & Kraemer, 2007).…”

Section: Data Collection and Informantsmentioning

confidence: 99%

Business value of IT capabilities: effects on processes and firm performance in a developing country

Oliveira

Maçada

Oliveira

2016

RBGN

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Purpose -This article proposes an integrated three-stage model, which tests the impact of IT capabilities at the firm level.Design/methodology/approach -The measurement model was constructed from the following research phases: i) assessment of the variables by experts in the fields of IS and business; ii) survey pretest; and iii) pilot survey. The full survey was applied to managers from IT and business fields in Brazil's largest organizations, and was analyzed through Structural Equation Modelling.Findings -The results of the full survey allow us to conclude about the relationships that exist between IT capabilities, information quality and performance processes. Performance processes partially mediate the impact of IT capabilities on firm performance.Originality/value -The results presented contribute to the academic and management aspects, for they allow: i) to replicate the model in other research contexts (national, international) and evaluating incremental improvements of IT capabilities on firm performance; ii) the identification of intermediate performance indicators, associated with the use of IT, and the concentration of energy of organizations in the measurement of IT effects on business processes; iii) the adoption of the model for horizontal analysis of IT performance in large companies, from the perspective of business and IT managers.

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Examining the dimensionality and measurement of user-perceived knowledge and information quality in the KMS context

Cited by 20 publications

References 37 publications

Assessing data currency — a probabilistic approach

Assessing data currency — a probabilistic approach

The measurement and dimensionality of e-learning blog satisfaction

Business value of IT capabilities: effects on processes and firm performance in a developing country

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