International Journal of Decision Support Systems (9 papers in press)

Regular Issues

• Impact of a multi-criteria rating in e-commerce: the moderating effect of self-depletion on trust and purchase intention  
  by Virgile Schmit, Thierry Baccino 
  Abstract: Self-depletion is known to have a wide range of effects on the decision-making process. Two experimental studies investigate whether a purchase decision-making on an e-commerce product webpage is affected by the state of self-depletion when using a multi-criteria rating scale. A questionnaire was built to measure trust, distrust and purchase intention and was submitted to one hundred and twenty-two participants (categorised in two groups according to their self-depletion test) who have to judge different mp3 (Mpeg Audio Layer 3) players presented on a webpage. In both studies, the variance of ratings were investigated with the presence of a global rating (1st exp.) and the valence of the global rating (2nd exp.) of the products. Main results show that self-depletion moderated the effect of variance of the ratings on the judgment and also lead to a polarisation effect. Trust and purchase intention are highly correlated, while distrust is only loosely correlated to purchase intention, supporting the view of a dual trust-distrust construct, instead of a continuum.
  Keywords: Electronic word-of-mouth; Self-Depletion; Trust; Purchase intention; Multi-dimensional rating; Multi-Criteria Decision Making.
  
  
• SIM-UTA: Evaluating reorganization scenarios in a healthcare organization  
  by Panagiotis Manolitzas, Evangelos Grigoroudis, Nikolaos Matsatsinis, Athanasios Spyridakos 
  Abstract: Hospitals across the globe face the challenge to respond to public demand for more effective and transparent healthcare services. In order to optimize the services provided by hospital organizations, several methodological approaches have been developed in the operational research domain. The aim of this paper is to present a new methodology for the improvement of healthcare services in an emergency department of a hospital. The proposed SIM-UTA approach combines simulation techniques and MCDA tools (UTASTAR method) in order to help the management of the hospital to optimize specific aspects of the emergency departments operation. In order to illustrate the applicability of the methodological approach, a real-word case study in a Greek hospital is presented. The results show that the most important factor for the emergency department is the total length of stay, while the evaluation of several alternative reforms underline that the implementation of a fast track unit may give significant improvements. SIM-UTA may serve as a useful tools for decision support, taking into account several factor, like working loads, waiting times, length of stay etc.
  Keywords: UTASTAR method; simulation; decision support; emergency department; hospitals.
  
  
• A Decision Support System for Prevention and Costing of Occupational Injuries  
  by Marion S. Rauner, Michaela-Maria Schaffhauser-Linzatti, Johannes Bauerstätter, Bernhard Schwarz, Paul Harper, Klaus Wittig, Beate Mayer 
  Abstract: Shrinking budgets and decreasing economic growth force accident insurance institutions to focus on cost reduction programmes as well as on prevention measures. For this reason, we developed sophisticated decision support systems (DSSs) from 2001 to 2012 during three projects for the main of the four largest Austrian accident insurance institutions (Allgemeine Unfallversicherungsanstalt, AUVA), to support their policy makers three-fold. First, we apply complex calculation schemes with an underlying population model to predict short-term and long-term occupational accident costs on an individual case basis for the AUVA using micro-simulation. Second, a further analysis of these costs allows AUVA policy makers to define risk groups which is essential to derive prevention programmes and their corresponding budgets (e.g., utilization of personal protective equipment, improvement of transportation safety, enhancement of safe driving). Third, we reveal possible improvements in collecting and structuring data for the AUVAs data warehouse for better forecasting of subsequent occupational accident costs and the underlying risk groups. Beyond the focus on AUVA interests, we integrated main cost components for companies where casualties are working (e.g., continued remuneration) and for the economy (loss in productivity for professional/non-professional work, sickness benefit). As a main result of our DSS for all three projects from 2001 to 2012, protection clothes or specific timing of working breaks decrease costly accidents. The results of the first two project periods (2001-2005) helped reduce risks of falling, while the third project (2011-2012) pointed out to focus on traffic injuries in the next years. In the future, AUVA should focus on prevention strategies in the following industries: preparatory site operations, building installation, and other finishing trades.
  Keywords: Decision Support System; Occupational Injury Costs; Prevention; Micro-Simulation; Austria.
  
  
• Modelling and performance analysis of smart waste collection system: A Petri Nets and discrete event simulation approach  
  by Taha Benarbia, Abdel Moumen Darcherif, Daniel (Jian) Sun 
  Abstract: In recent years, many cities around the world are turning to becoming smarter, during which new and performance services in all areas have developed, including transport and smart mobility, sustainable environment, waste collection, and energy. With regard to the waste collection, all cities have the mission to reduce waste production and to implement efficient waste recovery and collection systems. To deal with such issues, the use of ICT (Information and Communication Technologies) to transmit data is believed as an important solution. However, waste collection operators face the challenge of waste collection routing management to reduce the costs of transportation and decrease energy consumption. This paper proposes a waste collection strategy model based on real time inventory control of smart waste collection vehicles routing problem, in the framework of stochastic Petri Nets (PN), including inhibitor arcs and discrete event simulation. The stochastic PN approach has been developed so that it is suitable for the modelling, performance assessment and simulation analysis for control and collection management purposes of such stochastic systems. Moreover, the developed model and simulation show the potential of using PN models to predict the critical situations, analyze collection strategy efficiency, and improve system performance. Results from the numerical example indicate that the overall vehicle travel distance for waste collection has been significantly reduced by estimating the exact moment to launch the collection service, as well as resolves the conflict between vehicles (controlling the assignment of vehicles among collectors) during the relocation service. A variety of simulation scenarios were introduced to assess the real time impact by monitoring the collection process. The approach proposed in this study might be used to develop a decision-making support for analysis and performance optimization of smart waste collection services.
  Keywords: Smart waste collection; stochastic Petri Nets; discrete event simulation; decision making; vehicle routing problem.
  
  

Special Issue on: Information and Communications Technology in Agriculture and Tourism

• Traffic Flow Forecasting for City Logistics: A Literature Review & Evaluation  
  by Evripidis Kechagias, Sotiris Gayialis, Grigorios Konstantakopoulos, Giorgos Papadopoulos 
  Abstract: This article presents a thorough literature review and evaluation of road traffic forecasting methods. More specifically, the literature review concerns the study of scientific articles, in order to draw conclusions on the best-applied methods and future directions of their implementation in city logistics. The algorithms(methods), through which the traffic forecast is carried out, are categorized and analyzed, focusing on their potential implementation in freight transportation systems. It is beyond dispute that the proper use of traffic congestion information can significantly improve public confidence in road networks and reduce traffic congestion as well as its harmful environmental and social impacts. This analysis and the knowledge gained will be used in an on-going research project in order to support the application of traffic forecasting algorithms in the functionality of a vehicle routing and scheduling information system. This review is a useful tool for academias and practitioners who study the adoption of traffic forecasting algorithms in IT solutions in order to schedule deliveries and routes in city logistics environment effectively.
  Keywords: Traffic Forecasting; Algorithms; Urban Freight Transportation; City Logistics; Travel Time; Literature Review.
  
  
• Strategic Decision Support Systems for Short Supply Chain Development in the Agrifood Sector  
  by Fotis Kitsios, Chrysanthi Charatsari, Maria Kamariotou 
  Abstract: There has been an interest in short food supply chain recently which has stemed from the need of improving the flow both of products and information from suppliers to customers. Although, many tools have been developed in order to increase the performance of supply chain, they havent succeeded in helping managers make strategic decisions concerning the operations of the short food supply one. In the agrifood sector, practitioners face short food supply chains as integrated systems that incorporate all the processes of traditional supply chains. Thus, Decision Support Systems (DSSs) are required to help managers handle these processes properly. Most of the existing studies focus on the improvement of individual firms or processes more than on the design of an entire food supply chain. So, the purpose of this paper is to propose such a strategic DSS model that based on the Strategic Information Systems Planning (SISP) process, could provide a holistic approach to effective decision making in short supply chain in the agrifood industry. This model supports product managers to improve the effectiveness of food supply operations.
  Keywords: Strategic Information Systems Planning; Decision Support Systems; Short food supply chains; Logistics; Agrifood sector.
  
  
• Supporting decisions for the application of combined natural and engineered systems for water treatment and reuse  
  by Georgios Arampatzis, Patricia Stathatoub, Panagiotis Scaloubakas, Dionysis Assimacopoulos 
  Abstract: Combined natural and engineered systems for water/wastewater treatment are well suited for application in many rural and semi-rural areas, especially those with water demand and wastewater production peaks related to tourism, farming and their nexus. The planning, implementation and operation of cNES is not a trivial task. A Decision Support System for the implementation of cNES, based on a user-oriented approach, is presented. Decision support is organised not into tools or tasks, but into a set of services targeted all potential user types, identified and parametrised through users analysis. Six decision-making stages identified, leading to the specification of three generic types of services. (i) An information service, based on a knowledge repository. (ii) A suite of tools service, implemented as a sustainable ecosystem of decision support tools. (iii) A guidance service, based on a knowledge reasoning system that identifies typical application cases and produces analytic roadmaps towards achieving user goals.
  Keywords: cNES; DSS; User-Oriented; Decision Services; Knowledge Repository; Mathematical Modelling; Knowledge Reasoning; Roadmaps; Environmental Impact Assessment; Water Resources Management.
  
  
• Using multicriteria decision analysis to evaluate the effect of digital transformation on organisational performance: evidence from Greek tourism SMEs  
  by Dimitrios Mitroulis, Fotis Kitsios 
  Abstract: The phenomenon of digital transformation has changed the traditional economy, leading to valuable changes in the tourism industry. Customer experience is heavily influencing the decision processes. The implementation of new digital technologies could enable tourism firms' transformation and improve their organisational performance. Although the prior literature discusses the benefits of digital transformation, the measurement of its impact on organisational performance is still vague. The aim of this study is to evaluate the level of CEOs, CIOs and other senior executives' satisfaction and to propose solutions on how to increase the level of satisfaction by using multicriteria analysis. A multicriteria user satisfaction analysis was employed so that the satisfaction could be measured and moreover, to reveal the strengths and weaknesses of satisfaction. The results of the questionnaire revealed that
  Keywords: digital transformation; digital technologies; organizational transformation; digital innovation; Multicriteria Satisfaction Analysis (MUSA); tourism industry.
  
  
• Non-linear data envelopment analysis models for technologies with undesirable outputs  
  by Maria Trnovska, Margareta Halicka 
  Abstract: This paper compares two non-linear data envelopment analysis models for environmental evaluation: the Russell measure model and the hyperbolic measure model. Since both of the models can be formulated as rnsemidefinite programs, they are computationally tractable. The applicability of the models in sustainable rnagriculture is demonstrated in an illustrational example comparing the performance of 29 countries.
  Keywords: data envelopment analysis; semidefinite programming; undesirable outputs; rnsustainable agriculture; environmental technology; Russell measure model; hyperbolic measure model.