Dynamics of short-term and long-term decision-making in English housing associations: A study of using systems thinking to inform policy design

Incorporating consideration of causal mechanisms of complex policy issues and goals is critical for policy design, but tools to support exploration of the interconnections, trade-offs and unintended consequences of a focused policy issue are limited. Understanding how to undertake systems-based policy design is crucial for designing effective policy interventions. Through a case study with two housing associations (HAs) in England, this paper explores how group model building (GMB) workshops, as a systems thinking tool, can elicit complex causal mechanisms to inform policy design. The paper presents a causal loop diagram (CLD) describing English HAs’ decision-making around sustainable and healthy housing in response to housing policies. The CLD illustrates how frequent policy changes and disjointed objectives can create disruptive challenges for HA's long-term decision-making, increasing short-term decision-making, and compromising the delivery of housing policy goals as an unintended consequence. We argue that the systems perspective of the interlinkages between policy design, specifically inconsistencies and changes, and housing organisations’ reactions highlights the importance of the systems thinking approach of policy design to support HAs’ organisational decision-making for sustainability and social issues. Policy design elements that facilitate HAs’ long-term decision-making are discussed. Through the case study, we contribute to the housing policy literature by explicitly showing how policy changes affect HA's decision-making. We advance the integration of policy design and soft operational research fields by describing the systems thinking approaches are used not only on the content of policy design to enhance a particular policy, but also on increasing our understanding of its process, by generating insights about the nature of decision-making dynamics and challenges faced. Limitations and implications for future research are discussed

Housing and Community Development

Researchers in housing and community development design and evaluate policies regarding access to attractive, affordable and sustainable housing and improving the social, physical and economic infrastructure of communities, especially those in the urban core. Practitioners in this field confront political considerations, administrative guidelines and limited funding. Decision science can increase the efficiency and effectiveness of market-rate housing development and provide support for policy responses to issues such as affordable housing, race and class segregation, ineffective and/or inequitable economic development, and sustainable development. This research spans many disciplines, including systems modeling, urban economics, multi-criteria decision modeling, stochastic models and decision support systems, and is often interdisciplinary and applied in nature. A common thread in this work is the need to explicitly address the needs of multiple stakeholders, to capture the public and private nature of housing, and to incorporate best-available evidence regarding markets, policies and impacts of housing and community development. We describe the policy context for this work, review previous research through the lens of descriptive, prescriptive and decision support models, and identify important limitations to work in this area to date. We then describe diverse opportunities for research in this area that can address current policy concerns such as sustainable development, post-disaster reconstruction and individual and group decision support

Contrasting GDSS\u27s and GSS\u27s in the context of strategic change-implications for facilitation

The focus of this paper is on a comparison made between two series of computer supported strategy workshops. Each of the series of five one-day workshops was designed within the context of a project aimed at planning and implementing major strategic change within the organization and the project reported involved over fifty senior managers during a two year period. The subjects of the research had to deal with the reality of an organisational history, and, even more importantly, the knowledge that their contributions to the meetings would influence their future as a managerial group. The project enabled a number of exceptional opportunities to be tapped including i) a researcher as observer throughout the process, and ii) videotaping of each one day meeting. The first series of workshops was designed to generate and structure the strategic issues and context that were to be worked upon during the second series of workshops. Thus the first workshops used a group support system designed toprovide high levels of participation in raising strategic issues, and the second series, a group decision support system designed to enable decisions to be made and implementation plans to be created. These design objectives closely correspond to the tasks set out by McGrath (1984) where a GSS was defined as a support system to primarily aid creativity/idea generating tasks and a GDSS was to support planning/evaluation tasks. The workshops were each embedded within the Strategic Options Development and Analysis methodology (SODA) (Eden and Ackermann, 1992) and, involved a number of different support technologies. In these workshops the usual facilitated procedure was used in tandem with a multiple workstation system which allowed participants to interact with the modelling process, and with a number of manual techniques which were designed to interface with the approach. Thus manual group support (MAGS) was used alongside, and interacting with, both facilitator driven single user group support (SUGS) and multi-user group support (MUGS). To achieve this interweaving of modes the software COPE was used directly in both the SUGS and MUGS modes of support and the underlying concepts used during the MAGS mode mirrors the COPE software. The difference between the two series of workshops comprised i) the purposes behind the usage of each mode of working, and ii) the combinations adopted, i.e. the choice of using particular modes in a particular order which both have implications for facilitation. As a result of the comparison a set of implications which differentiate the role of a facilitator using group support systems (GSS) to the use of group decision support systems (GDSS) has been produced. The implications may be taken firstly as a contribution to the future design and facilitation of each type of meeting, and secondly to the effective design of the each of the systems (GSS and GDSS). The paper begins by considering some of the issues around the research method adopted, provides details of both of the workshop series, lists the characteristics which emerged as a result of the workshops and have implications for facilitation, and then briefly touches on the conclusions

THE IMPACT OF COMPUTER-BASED SUPPORT ON THE PROCESS AND OUTCOMES OF GROUP DECISION MAKING

Interactive computer-based systems to support group decision making (group decision support systems or GDSS) have received increased attention from researchers and practitioners in recent years. Huber (1984) argues that as organizational environments become more turbulent and complex, decisions will be required to be made in less time and with greater information exchange within decision making groups. Thus, it is imperative that studies be undertaken to determine the types and characteristics of group decision tasks most appropriate for support by a GDSS and to determine the features of a GDSS that will support those tasks. A number of prominent researchers in the field of group decision making (Shaw, 1973, 1981; Hackman and Morris, 1975; Fisher, 1974) agree that the decision task itself is probably the most important factor in determining group decision making effectiveness. The characteristics of group decision tasks are many and varied, but according to Shaw (1973) the level of difficulty/complexity of the decision is a fundamental factor in influencing the performance of the group. Some decisions are characterized by information that is clear, concise, easily communicable, and where relationships between important factors in the decision are easily understood. In short, these decisions require relatively little effort to make and are therefore called easy decisions. Decision tasks where the information to be considered in making the decision is incomplete, difficult to understand, and where complex relationships exist within the information available are called complex or difficult decisions. The role of decision task difficulty in the effective use of GDSS is considered ih this study. This research is an initial experimental study, exploratory in nature, that aims to get a first-level understanding of the impact of a computer-based DSS on group decision making. The group decision support system that is used in this study has only those features that specifically support group decision making (alternatives generation and communication, preference ranking and voting support). The reason for this approach is to start a program of research with a simple system in order to determine the particular impact of these features on, not only the outcomes of group decision making (such as decision quality), but on the process of group decision making as well. A controlled 2 x 2 factorial experiment was used to compare the decisions made by groups which had GDSS support with those groups that had no GDSS support and those with a high difficulty task to those with a low difficulty task. Figure 1 shows the relationship among the main variables in the study. The experimental task was a marketing business case in which the company was experiencing declining profits. Each group was asked to find the problem which was causing the declining profits. Difficulty was manipulated by modifying the data in the case. The setting for this experiment was a decision room designed and set up to accommodate face-to-face group interaction. The GDSS treatment entailed the use of one computer terminal per group member so that the GDSS could be used to support group decision making. Each group member in the GDSS treatment also had the use of a pencil, paper, a hand calculator, and a blackboard. For the non GDSS treatment, the terminals were removed and the group used just pencils, paper, hand calculators, and a blackboard to assist in making the decision. The computer hardware consisted of a DEC VAX 11/780 timesharing system using the VMS operating system, and DEC VT-102 terminals. The terminals were connected to the VAX 11/780 using 2400 baud direct lines. The GDSS called Decision Aid for Groups (DECAID) was designed, coded, and tested to make sure that it worked in the experimental setting. The approach to design was to implement the features, and then to refine the system through testing to make those features work as efficiently as possible. The GDSS software performed the basic functions of recording and storing and displaying alternatives that were entered by group members, aggregating and displaying preference rankings that had been entered for those alternatives, and recording votes (either publicly or anonymously) for the various alternatives generated. The system was easy to use and menu driven. Eighty four senior undergraduate business administration students participated in the study. These subjects had taken at least one course each in management science/decision analysis techniques, marketing, management theory/organizational behavior, and all had exposure to case analysis techniques. All subjects had been given training in the use of the GDSS. Measures were taken of decision outcomes (decision quality, decision time, decision confidence, satisfaction with group process, and amount of GDSS usage), and decision process variables (number of issues considered, number of alternatives generated, and participation in the decision making). Decision quality was measured along two dimensions: (1) decision content - how close did the group\u27s decision come to that made by a panel of experts; and (2) decision reasoning -- how similar the group\u27s reasoning in arriving at their decision was to the reasoning of the experts. Decision time was defined as the length of time it took the group to reach a consensus decision. Decision confidence and satisfaction with the group process were measured by individual responses to a post- test questionnaire. The individual responses were then aggregated to give a group value. The amount of GDSS usage was measured by examining the computer logs that were kept during the GDSS sessions. Decision issues were defined as factors that were important in the analysis of the case. Decision alternatives were defined as those issues in the case that the group analyzed as being the possible major problems in the case and hence, possible solutions to the decision task. Participation was measured by counting the number of task related comments made by each individual group member. Issues, alternatives and participation were determined by analysis of the video and audio tapes that were made of the experimental sessions. The major findings of the study are: 1. Decision quality is enhanced when decision making is supported by a GDSS, particularly for high dificulty tasks. 2. Decision time is not affected by use of a GDSS. 3. Confidence in the group decision and satisfaction with the decision making process are reduced when a GDSS is used, irrespective of task difficulty. 4. The number of alternatives considered is increased when a GDSS is used to support group decision making. 5. Participation in the group decision making process is unaffected by GDSS support or by decision task difficulty. The paper concludes by suggesting directions for future research into GDSS. Work is needed to determine the effectiveness of additional features of a GDSS (such as other communication features, modeling features, etc.), to understand the impact of GDSS on the different phases of decision making, and to examine the effect of repeated use of a GDSS on the quality of group decision making

Sustainability focused decision-making in building renovation

An overview of recent research related to building renovation has revealed that efforts to date do not address sustainability issues comprehensively. The question then arises in regard to the holistic sustainability objectives within building renovation context. In order to deal with this question, the research adopts a multi-dimensional approach involving literature review, exploration of existing assessment methods and methodologies, individual and focus group interviews, and application of Soft Systems Methodologies (SSM) with Value Focused Thinking (VFT). In doing so, appropriate data about sustainability objectives have been collected and structured, and subsequently verified using a Delphi study. A sustainability framework was developed in cooperation with University of Palermo and Aarhus University to audit, develop and assess building renovation performance, and support decision-making during the project\u2019s lifecycle. The paper represents the results of research aiming at addressing sustainability of the entire renovation effort including new categories, criteria, and indicators. The developed framework can be applied during different project stages and to assist in the consideration of the sustainability issues through support of decision-making and communication with relevant stakeholders. Early in a project, it can be used to identify key performance criteria, and later to evaluate/compare the pros and cons of alternative retrofitting solutions either during the design stage or upon the project completion. According to the procedure of the consensus-based process for the development of an effective sustainability decision-making framework which was employed in this study, the outcome can also be considered as an outset step intended for the establishment of a Decision Support Systems (DSS) and assessment tool suited to building renovation context

Non-cooperative group decision support systems: problems and some solutions

The purpose of this thesis is twofold; (i) Explore some design issues for building group decision support systems for non-cooperation environments? and (ii) Expand CO-OP, a cooperative multiple criteria group decision support system, to support particular classes of group decisions. From the conceptual standpoint, this work argues for that cooperation is a special case of non-cooperation. The following design requirements are proposed: (i) Negotiation as a capability within model management, (ii) Greater capabilities in database management, and (iii) Increased flexibility for the user interface. The present version of Co-oP has, with this work, implemented the following features: (i) Scrolling windows to handle group problems with large size, (ii) Code optimization to provide fast feedback to members, (iii) Improved heuristics for the Negotiable Alternatives Identifier (NAI), (iv) Implementation of the Mediator module, and (v) Allow more advanced data manipulation to promote data exchange in competitive environments (e.g., data security and .sharing). The above implementation has encompassed approximately 6,000 lines of original pascal code, and 3,000 lines of modified code.http://archive.org/details/noncooperativegr00kardLieutenant Commander, United States NavyLieutenant, Federal Republic of Germany NavyApproved for public release; distribution is unlimited

Integrating Analytical Models with Descriptive System Models: Implementation of the OMG SyML Standard for the Tool-specific Case of MapleSim and MagicDraw

AbstractThe Jet Propulsion Laboratory (JPL) is investing heavily in the development of an infrastructure for building system models using the Systems Modeling Language (SysML). An essential component is a transformation apparatus that permits diverse models to be integrated independently of their nature (e.g. declarative, analytical and statistical). This paper presents one useful case: the integration of analytical models expressed using the Modelica language. Modelica is an open standard, declarative, multi-domain modeling language that allows for complex dynamic systems to be modeled. Maplesoft's MapleSim is one software tool that supports the Modelica language. The tool-neutral specification for the transformation between the languages Modelica and SysML is defined in the SysML-Modelica transformation specification (SyML) standard published by the Object Management Group (OMG). As part of the development efforts, said specification has been implemented using the Query-View- Transformation Operational (QVTO) language. During the process, several critical changes to the current SyML standard were proposed. Furthermore, a number of current limitations related to MapleSim were identified. Despite these issues, a proof-of- concept transformation was successfully implemented. In conclusion, the integration of complex simulation models conforming to the Modelica language with SysML-based system models has shown great promise and is a highly useful tool to support the decision making process in design

Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial.

BACKGROUND: Computerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge. METHODS/DESIGN: The Computerized DEcision Support in ONCOlogy (ONCO-CODES) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio. The trial is designed to evaluate the effectiveness on clinical practice and quality of care of a multi-specialty collection of patient-specific reminders generated by a CDSS in the IRCCS Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) hospital. We hypothesize that the intervention can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to cancer patients. The primary outcome is the rate at which the issues reported by the reminders are resolved, aggregating specialty and primary care reminders. We will include all the patients admitted to hospital services. All analyses will follow the intention-to-treat principle. DISCUSSION: The results of our study will contribute to the current understanding of the effectiveness of CDSSs in cancer hospitals, thereby informing healthcare policy about the potential role of CDSS use. Furthermore, the study will inform whether CDSS may facilitate the integration of primary care in cancer settings, known to be usually limited. The increasing use of and familiarity with advanced technology among new generations of physicians may support integrated approaches to be tested in pragmatic studies determining the optimal interface between primary and oncology care. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02645357

Application of WINGS method to support decision making with inter-dependence of criteria in negotiations

W negocjacjach częste są sytuacje, w których przestrzeń negocjacyjna i wzorce ofert nie są jasno określone. Jeśli dodatkowo między kwestiami negocjacyjnymi mogą pojawić się zależności, wtedy tradycyjne metody, oparte na sumie ważonej ocen cząstkowych, nie są właściwe dla konstrukcji systemu ocen ofert. Jest to miejsce, w którym swoją użyteczność mogą wykazać podejścia o słabszych założeniach. W artykule zaproponowano zastosowanie metody WINGS (Weighted Influence Non-linear Gauge System) celem wsparcia podejmowania decyzji w procesie negocjacji. Metoda WINGS przedstawia ogólne podejście systemowe pomagające rozwiązywać złożone problemy, w których występują powiązane ze sobą czynniki. W szczególności metoda ta może być użyta do oceny wariantów decyzyjnych w sytuacjach, kiedy zależności między kryteriami nie mogą być pominięte. W ramach wstępnego etapu tej metody zespół negocjacyjny konstruuje, reprezentującą problem negocjacyjny, wspólną sieć konceptów (wierzchołków) i ich relacji (łuków). Taka struktura przypomina mapę poznawczą lub przyczynową. Podstawę sieci stanowią wierzchołki, które odzwierciedlają potencjalne warianty (oferty). U wierzchołka sieci leżą kwestie negocjacyjne (czyli cele, względnie odpowiadające im kryteria). We wnętrzu sieci występują wierzchołki pośrednie, tworzące ścieżki przyczynowe prowadzące od ofert do kwestii. Etap wstępny ma za zadanie pomóc zespołowi negocjacyjnemu w określeniu struktury problemu, a także wspiera proces uczenia się i zrozumienia jego istoty. Drugi, główny etap obejmuje fazę ilościową metody WINGS, pozwalającą zbudować ranking kompromisowych ofert. Użyteczność metody zilustrowano dwoma przykładami przygotowania negocjacji: zakupu partii towaru oraz wyboru systemu informatycznego typu ERP.A situation when negotiation space and templates are not clearly defined is very likely in negotiations. If it also happens that criteria cannot be regarded as independent, then no approach based on weighted additive scoring is suitable for building the offer scoring system. This is an area where other approaches with less limiting assumptions can prove useful. This paper proposes to apply the WINGS (Weighted Influence Non-linear Gauge System) method, a general systemic procedure for supporting decision making in negotiations. The WINGS method helps solve complex problems involving interrelated factors. In particular, it can be used to evaluate alternatives when the interrelations between criteria cannot be neglected. In the introductory stage, the negotiating team builds a common network of concepts (nodes) and their relations (arrows) representing the negotiation problem. This structure resembles a cognitive or causal map. The bottom nodes represent potential alternatives (offers), while the top nodes represent objectives (issues). The intermediary nodes create causal paths leading from the alternatives to the objectives. This stage helps the negotiation team to structure the problem; it also supports learning and comprehension. The main stage involves quantitative evaluations with the WINGS method that make it possible to build a ranking of compromise solutions. The usefulness of the procedure is illustrated with two examples of preparation for negotiations: the purchase of a batch of goods and the choice of an ERP system.Artykuł powstał w ramach projektu sfinansowanego ze środków Narodowego Centrum Nauki przyznanych na podstawie decyzji numer DEC-2013/09/B/HS4/[email protected]ł Informatyki i Komunikacji, Uniwersytet Ekonomiczny w KatowicachBrzostowski J., Roszkowska E., Wachowicz T., 2012a, Using Multiple Criteria Decision-Making Methods in Negotiation Support, ,,Optimum. Studia Ekonomiczne”, nr 3(29).Brzostowski J., Roszkowska E., Wachowicz T., 2012b, Using an Analytic Hierarchy Process to develop a scoring system for a set of continuous feasible alternatives in negotiation, „Operations Research and Decisions”, no. 4.Górecka D., Roszkowska E, Wachowicz T., 2014, MARS – a hybrid of ZAPROS and MACBETH for verbal evaluation of the negotiation template, Group Decision and Negotiation 2014 : GDN 2014 : Proceedings of the Joint International Conference of the INFORMS GDN Section and the EURO Working Group on DSS, P. Zaraté, G. Camilleri, D. Kamissoko, F. Amblard (red.), Toulouse University, France.Górecka D., Roszkowska E., Wachowicz T., 2016, The MARS Approach in the Verbal and Holistic Evaluation of the Negotiation Template, “Group Decision and Negotiation”, DOI: 10.1007/s10726-016-9475-92016.Gürbüz T., Alptekin S. E., Işıklar Alptekin G., 2012, A hybrid MCDM methodology for ERP selection problem with interacting criteria, „Decision Support Systems”, 54, doi:10.1016/j.dss.2012.05.006.Kersten G. E., Noronha S. J., 1999, WWW-based negotiation support: design, implementation, and use, „Decision Support Systems” 25, doi:10.1016/S0167-9236(99)00012-3.Kilic H.S., Zaim S., Delen D., 2014, Development of a hybrid methodology for ERP system selection: The case of Turkish Airlines, „Decision Support Systems” 66, doi: 10.1016/j.dss.2014.06.011.de Medeiros (Jr.) A., Perez G., Lex S., 2014, Using Analytic Network for Selection of Enterprise Resource Planning Systems (ERP) Aligned To Business Strategy, ,,Journal of Information Systems and Technology Management”, no. 11.Michnik J., 2013, Weighted Influence Non-linear Gauge System (WINGS) – An analysis method for the systems of interrelated components, ,,European Journal of Operational Research”, 228.Mustajoki J., Hämäläinen R. P., 1999, Web-HIPRE – Global decision support by value tree and AHP analysis, Presented at the INFOR.Systems Modelling: Theory and Practice, 2004, M. Pidd (ed.), John Wiley & Sons.Roszkowska E., Wachowicz T., 2015, Application of fuzzy TOPSIS to scoring the negotiation offers in ill-structured negotiation problems, ,,European Journal of Operational Research” 242, doi:10.1016/j.ejor.2014.10.050.Roszkowska E., Wachowicz T., 2016, Negocjacje. Analiza i wspomaganie decyzji, Wolter Kluwer, Warszawa.Saaty T. L., 2005, Theory and Applications of the Analytic Network Process. Decision Making with Benefits, Opportunities, Costs and Risks, RWS Publications, Pittsburgh.Salo A., Hämäläinen R. P., 2010, Multicriteria Decision Analysis in Group Decision Processes, [in:] Handbook of Group Decision and Negotiation, D.M. Kilgour, C. Eden (eds.), Advances in Group Decision and Negotiation, Springer Netherlands.Wachowicz T., 2013, Metody wielokryterialne we wspomaganiu prenegocjacyjnego rzygotowania negocjatorów, Wydawnictwo Uniwersytetu Ekonomicznego w Katowicach, Katowice.Wei C.-C., Chien C.-F., Wang M.-J. J., 2005, An AHP-based approach to ERP system selection, ,,International Journal of Production Economics” 96, doi:10.1016/j.ijpe.2004.03.004.Wei C.-C., Wang M.-J. J., 2004, A comprehensive framework for selecting an ERP system, ,,International Journal of Project Management” 22, doi:10.1016/S0263-7863(02)00064-9.Wieszała P., Trzaskalik T., Targiel K., 2011, Analytic Network Process in ERP Selection, [in:] Multicriteria Decision Making’10-11, University of Economics in Katowice, Katowice.119-1341(79)11913

Design and evaluation of a voting tool in a collaborative environment

This dissertation researchdesigned, implemented, and evaluated a Web-based Dynamic Voting Toolfor small group decision-making in a collaborative environment. In this dissertation, theliterature on voting tools in current GDSS research is presented. Variousvoting theories and methods are analyzed, and the advantages and weaknessesare compared, so as to gain a better understanding of how to apply thesedifferent voting methods to diverse decision-making situations. A briefoverview of scaling theories is also given, with an emphasis on Thurstone\u27sLaw. The basic features of someweb-based voting tool implementations are reviewed along with a discussionof the pros and cons of Intemet voting. A discussion of Human DynamicVoting (HDV) follows; HDV allows multiple voting and continuous feedbackin a group process. The Dynamic Voting Tool designed and developed bythe author (i.e., Zheng Li) integrated multiple scaling and voting methods,and supported dynamic voting. Its features, user feedback, and futureimprovements are further discussed. A controlled experiment wasconducted to evaluate the effects of the Dynamic Voting Tool (alongwith the List Gathering Tool by Yuanqiong Wang) interacting with smallgroup process. The design and procedures of the experiment, and thedata analysis results extracted from 187 student subjects from New JerseyInstitute of Technology are reported. While the System Survey yieldedvery positive feedback on the voting tool, the hypotheses tested bythe Post-Questionnaire and expert judgments showed no major positivesignificant results. This was probably due to the complexity of thetask and procedures, lack of motivation of the subjects, bad timing,insufficient training, and uneven distribution of subjects, etc. Several field studies usingthe Social Decision Support System (SDSS) Toolkit (List Gathering Tool+ Dynamic Voting Tool) are presented. The SDSS system worked well whenthe subjects were motivated. The field studies show that the toolkitcan be used in course evaluations, or other practical applications. Finally, it is suggestedthat future research can focus on improving the voting tool with truedynamic features, exploring more issues on SDSS systems design and experimentation,and exploring the relationship of voting and GSS