International Journal of Information Technology & Decision Making

Community source development has emerged as a new way of developing enterprise applications, leading to a unique type of open source development involving collaborative investment decisions by multiple institutional partners. A critical research question is what motivates partnering institutions to invest jointly in community source development, knowing that the result will become open source. We study this research question by investigating cooperative behaviors among partner institutions involved in community source such as Kuali. We apply option pricing to model cooperative investment decisions under uncertainty with the Black–Scholes (BS) model in comparison with the net present value (NPV) approach. Our analytical results reveal that several institutional characteristics such as size, financial power, and IT capability affect how institutions make cooperative decisions in community source development regardless if either the BS model or the NPV approach is used as the utility function. These business insights help deepen the understanding of the emerging community source phenomenon.

In this paper, a simple approach to allocating fixed costs and common revenue among different units is presented. It is based on centralized data envelopment analysis (DEA) and uses a weighted, slacks-based, nonradial metric. The approach is units-invariant and takes into account the inefficiencies in the assessed decision making units (DMUs). The approach works when the fixed cost is a complement of another input as well as when no other inputs exist. The proposed approach is compared with existing allocation methods using several datasets from the literature.

As we may have a set of possible values when comparing alternatives (or criteria), the hesitant fuzzy preference relation becomes a suitable and powerful technique to deal with this case. This paper mainly focuses on the multiplicative consistency of the hesitant fuzzy preference relation. First of all, we explore some properties of the hesitant fuzzy preference relation and develop some new aggregation operators. Then we introduce the concepts of multiplicative consistency, perfect multiplicative consistency and acceptable multiplicative consistency for a hesitant fuzzy preference relation, based on which, two algorithms are given to improve the inconsistency level of a hesitant fuzzy preference relation. Furthermore, the consensus of group decision making is studied based on the hesitant fuzzy preference relations. Finally, several illustrative examples are given to demonstrate the practicality of our algorithms.

We study the effects of considering different criteria simultaneously on portfolio optimization. Using a single-period optimization setting, we use various combinations of expected return, variance, liquidity and Conditional Value at Risk criteria. With stocks from Borsa Istanbul, we make computational studies to show the effects of these criteria on objective and decision spaces. We also consider cardinality and weight constraints and study their effects on the results. In general, we observe that considering alternative criteria results in enlarged regions in the efficient frontier that may be of interest to the decision maker. We discuss the results of our experiments and provide insights.

In this paper, we develop a hybrid bi-objective credibility-based fuzzy mathematical programming model for portfolio selection under fuzzy environment. To deal with imprecise parameters, we use a hybrid credibility-based approach that combines the expected value and chance constrained programming techniques. The model simultaneously maximizes the portfolio return and minimizes the portfolio risk. We also consider an additional important criterion, namely, portfolio liquidity as a constraint in the model to make it better suited for practical applications. The proposed fuzzy optimization model is solved using a two-phase approach. An empirical study is included to demonstrate applicability of the proposed model and the solution approach in real-world applications of portfolio selection.

Data envelopment analysis (DEA) assumes that the data set is precise when performing efficiency evaluation of peer decision making units (DMUs). The current paper proposes a multiple linear regression analysis (MLRA) approach to estimate missing values if some of the entries in the data set are missing. Its algorithm to derive the estimations is also proposed. In order to verify the credibility of the proposed approach, an example of 30 US commercial banks is applied to case analysis. Using the proposed algorithm, the efficiencies of all DMUs are obtained. A Friedman test and a Kendall's Tau rank correlation analysis statistically examine the results. Moreover, the efficiency interval and efficiency distribution for a DMU are obtained considering random errors of the estimations. After that, an example of public secondary schools serves to illustrate the applications in the end.

Trust is not only one key ingredient of prosperous organizations and societies, but also an essential factor in decision-making processes. And when it comes to trust, the latest advances in computing sciences area are increasingly supporting the related processes by deployment of so-called trust management systems. These systems are slowly advancing from their early stages of evolution toward more sophisticated and already operationally deployable solutions. As there seems to be no "Swiss-army knife" like methodology for trust management, it is reasonable to assume that not only one, but a few of them will be deployed in the future, depending on their basic principles of functioning,purposes and contexts of use. Therefore there still exists a gap in this area with unaddressed issues where humans (or humans-like agents) would be in focus. Quality Assessment Dynamics, QAD, which is presented in this paper, is taking these issues into account. It is based on operands and operators that model human ways of reasoning as described in many natural languages. Further, it is a formal system and therefore enabled for deployment in computing environments. This way QAD complements existing trust management methods and provides additional means for decision making through deployment in simulations and in trust management engines, while being understandable to ordinary users without requiring sophisticated expert knowledge.

Successful customer relationship management (CRM) depend on strategic skills and reflect the sharpness of long-term cooperation and organizational values. The purpose of the study will explore operational and analytical implementation of information system (IS) may lead to market strategy and CRM performances of a hotel. A CRM performance model was formulated by ISs success perspective in the study, and we collected international tourism hotel samples by mailing questionnaire survey in Taiwan. We mailed 232 questionnaires to hotels, of which 151 returned completed questionnaires and we test the model and hypotheses by structural equation modeling (SEM) and multilevel analysis for our research. As this result of the study, the role of IS will transfer from the transaction process system to a strategic supporting role, collecting information is important process to hoteliers, staffs prepare to personalize service for a guest in advance when they have more information about guest. And the capability of leveraging analytics in operations can be a critical differentiator for hotel to stay competitive. As a business discipline, this research could be directed toward helping managers and practitioners decide CRM implementation priority, and improve both business processes and competitiveness through the deployment of a CRM system.

Real estate brokerage services have developed from individual stores into a chain-store system, and the location of those stores plays a key role in their operation. The purpose of this study is to define and quantify the factors that affect the selection of a site for real estate brokerage services. Mutual relationships between the factors and sub-factors for site selection and their relative weights are also discussed to provide a complete set of decision evaluation models, then how to reduce the gaps to achieve the aspiration level. This research uses a new hybrid Multiple Criteria Decision Making (MCDM) model, combining the Decision Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based Analytic Network Process (DANP), and VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) methods to solve these problems. The DEMATEL technique is used to build an influential network relations map, and DANP is expected to obtain the influential weights using the basic concept of Analytic Network Process (ANP), to solve the dependence and feedback problems in the real world. Then, the VIKOR method is used to integrate the performance gaps from criteria to dimensions and overall. As the result shows, there is an interactive and auto-feedback relationship among the four dimensions. Among the 11 evaluation criteria, the income and consumption level is the most important consideration for selection of the site. The number and density of population ranks second in this regard. This study uses VIKOR method for selection of the best site, among three potential sites. Site A is closest to the aspiration level. Site A is better in this regard than the other two sites. The study develops and provides a decision-making system for the site selection in the real estate brokerage services.