Integrating Multiple Criteria Decision-Making Models Into the Decision Support System Framework for Marketing Decisions

The paper focuses on integrating the multiple criteria decision making (MCDM) models within the decision support system (DSS) framework to encourage greater use of these models. A DSS framework and the criteria used for the choice of a model is discussed. Based on these criteria MCDM models generally used in the marketing field are evaluated. The possibility of using a mixture of MCDM models within the DSS framework is also explored. Following this, the role of the MCDM models in DSS is delineated. It is argued that, within the problem-solving process, the confluence of MCDM models and DSS plays a vital role in developing high-quality solutions

Integrating Multiple Criteria Decision-Making Models Into the Decision Support System Framework for Marketing Decisions

The paper focuses on integrating the multiple criteria decision making (MCDM) models within the decision support system (DSS) framework to encourage greater use of these models. A DSS framework and the criteria used for the choice of a model is discussed. Based on these criteria MCDM models generally used in the marketing field are evaluated. The possibility of using a mixture of MCDM models within the DSS framework is also explored. Following this, the role of the MCDM models in DSS is delineated. It is argued that, within the problem-solving process, the confluence of MCDM models and DSS plays a vital role in developing high-quality solutions

The Antecedents and Consequences of Social and Economic User Satisfaction in Online Social Shopping Community: The User Experience Perspective

Online social shopping communities are gradually becoming prevalent with the dissemination of e-commerce and social media. Community users or consumers can generate their own contents or engage in social activities while shopping without switching between platforms. The level of engagement and actual purchase, however, are unsatisfactory. Although, prior scholars have examined possible factors (e.g. satisfaction, experience) that can improve participation or purchase in community, they have failed to explore their internal relationships. In this research, we unpack the concept of user satisfaction and adopt the four-dimension user experience principle to improve participation and purchase intention more efficiently. We assume that different components of user experience may have distinct influences on economic and social user satisfaction. Moreover, the impacts of economic and social satisfaction on participation and purchase may differ. An empirical survey of users in online social shopping communities in China will be conducted to test the assumptions. Potential implications for theory and practice will also be discussed

Some considerations to carry out a composite indicator for ordinal data

Composite indicators (CIs) are important and useful tools in many elds to assess, compare and rank performances, development stage, quality and many other different targets. CIs are an overall measure of a multidimensional, not directly observable, concept and are obtained by means of a set of manifest variables (elementary indicators) that contribute to dene the overall measure. In this paper, some matters regarding methods to build CIs are reviewed, assuming elementary indicators are ordinal and quantication is necessary to convert observed data into a numerical form. Scoring methods, aggregating functions and weighting systems are considered. In particular, a scoring method based on the observed distribution or the use of dissimilarity indices for quantication together with the Kendall-T association or a heterogeneity measure for weighting are suggested. Some of the reviewed procedures are compared using students' satisfaction data. \ua9 Universit\ue0 del Salento

Research and Applications of the Processes of Performance Appraisal: A Bibliography of Recent Literature, 1981-1989

[Excerpt] There have been several recent reviews of different subtopics within the general performance appraisal literature. The reader of these reviews will find, however, that the accompanying citations may be of limited utility for one or more reasons. For example, the reference sections of these reviews are usually composed of citations which support a specific theory or practical approach to the evaluation of human performance. Consequently, the citation lists for these reviews are, as they must be, highly selective and do not include works that may have only a peripheral relationship to a given reviewer\u27s target concerns. Another problem is that the citations are out of date. That is, review articles frequently contain many citations that are fifteen or more years old. The generation of new studies and knowledge in this field occurs very rapidly. This creates a need for additional reference information solely devoted to identifying the wealth of new research, ideas, and writing that is changing the field

Consuming Information Systems: An Economic Model of User Satisfaction

This paper has two major objectives. The first objective intends to answer the following question which is of significant interest to information system (IS) researchers and practitioners: How does user satisfaction (satisfaction) respond to changes in system use and system attributes? The second and more ambitious objective is to promote the application of economic theories in user behavior research. In contrast to prior research that conceived the development of user satisfaction as an information valuation and integration process, we consider such development to be embedded in the IS consumption process, that is, users gain utility (satisfaction) from consuming (using) the system. This perspective enables us to re-conceptualize user satisfaction as a proxy of utility and apply utility research in economics to study user satisfaction. An economic model of user satisfaction was developed. Two empirical studies were conducted to examine the research model. The findings confirmed the consumptive nature of user satisfaction. Apart from enriching our understanding of user satisfaction, this research demonstrates the usefulness of economic theories in user behavior research

Analyzing decision making in software design

A model is given for the analysis of rationality in design decision making. We define a formal means for answering the query, To what extent has a designer, on a particular occasion, using an explicit definition of 'good', decided rationally?A decision rationality classification scheme is proposed. This scheme incorporates non-compensatory decision analysis techniques (dominance and conjunctive cut-off) as well as compensatory techniques (simple and hierarchical additive weighting, linear assignment, concordance, and displaced ideal). A formal definition of design decision is derived by extending the Lehman, Stenning, Turski transformational model of the software design process. Their view of artifact specification mappings between linguistic systems is extended to include the concomitant effect of the mapping on resource expenditure.A formal specification for decision control knowledge is defined. This representation is the union of that knowledge required to support the various decision analysis techniques. Presumed to operationalize a designer's goals, the knowledge representation scheme includes five levels:1. Each objective expresses some relevant design concern for an artifact and/or resource characteristic.2. Each criterion expresses some relevant decomposition of a superior objective or criterion.3. Each attribute expresses the bottom-most decomposition for a superior criterion. Each attribute may have a weight indicating its relative contribution to its superior criterion.4. For each attribute, a value function expresses the designer's preference ordering over observed performance for an attribute.5. For each attribute, an observation channel describes an observer independent metric over some specification (either resource or artifact) rendered in some linguistic system and a procedure for application of that metric.Our model is applied to problems in Structured Design and conceptual data modeling. We argue that a comprehensive design history must include not only the transformations applied but also the rationale used in deciding their application. This rationale must include decision control knowledge governing both artifact (product) and resource (process) facets of design decision making. The principal contribution of this work is that the opacity of the decision intensive aspects of design are reduced thereby taking a necessary step for increasing the efficiency and effectiveness of software development

The effects of dimensionality and item selection methods on the validity of criterion-referenced test scores and decisions.

Many of the measurement models currently used in testing require that the items that make up the test span a unidimensional space. The assumption of unidimensionality is difficult to satisfy in practice since item pools are arguably multidimensional. Among the causes of test multidimensionality are the presence of minor dimensions (such as test motivation, speed of performance and reading ability) beyond the dominant ability the test is supposed to measure. The consequences of violating the assumption of unidimensionality may be serious. Different item selection procedures when used for constructing tests will have unknown and differential effects on the reliability and validity of tests. The purposes of this research were (1) to review research on test dimensionality, (2) to investigate the impact of test dimensionality on the ability estimation and the decision accuracy of criterion-referenced tests, and (3) to examine the effects of interaction of item selection methods with test dimensionality and content categories on ability estimation and decision accuracy of criterion-referenced tests. The empirical research consisted of two parts: in Part A, three item pools with different dimensionality structures were generated for two different tests. Four item selection methods were used to construct tests from each item pool, and the ability estimates and the decision accuracies of the 12 tests were compared in each test. In Part B, real data were used as an item bank, and four item selection methods were used to construct short tests from the item bank. The measurement precision and the decision accuracies of the resulted tests were compared. It was found that the strength of minor dimensions affect the precision of the ability estimation and decision accuracy of mastery tests, and that optimal item selection methods perform better than other item selection methods, especially when test data are not unidimensional. The differences in measurement precision and decision accuracy among data with different degrees of multidimensionality and among the different item selection methods were statistically and practically significant. An important implication of the study results for the practitioners are that the presence of minor dimensions in a test may lead to the misclassification of examinees, and hence limit the usefulness of the test