Type-2 TOPSIS:a group decision problem when ideal values are not extreme endpoints

In the traditional TOPSIS, the ideal solutions are assumed to be located at the endpoints of the data interval. However, not all performance attributes possess ideal values at the endpoints. We termed performance attributes that have ideal values at extreme points as Type-1 attributes. Type-2 attributes however possess ideal values somewhere within the data interval instead of being at the extreme end points. This provides a preference ranking problem when all attributes are computed and assumed to be of the Type-1 nature. To overcome this issue, we propose a new Fuzzy DEA method for computing the ideal values and distance function of Type-2 attributes in a TOPSIS methodology. Our method allows Type-1 and Type-2 attributes to be included in an evaluation system without compromising the ranking quality. The efficacy of the proposed model is illustrated with a vendor evaluation case for a high-tech investment decision making exercise. A comparison analysis with the traditional TOPSIS is also presented. © 2012 Springer Science+Business Media B.V.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

GEO Label – quality information interrogation tool for geospatial datasets:towards effective visualization of quality metadata

Although the importance of dataset fitness-for-use evaluation and intercomparison is widely recognised within the GIS community, no practical tools have yet been developed to support such interrogation. GeoViQua aims to develop a GEO label which will visually summarise and allow interrogation of key informational aspects of geospatial datasets upon which users rely when selecting datasets for use. The proposed GEO label will be integrated in the Global Earth Observation System of Systems (GEOSS) and will be used as a value and trust indicator for datasets accessible through the GEO Portal. As envisioned, the GEO label will act as a decision support mechanism for dataset selection and thereby hopefully improve user recognition of the quality of datasets. To date we have conducted 3 user studies to (1) identify the informational aspects of geospatial datasets upon which users rely when assessing dataset quality and trustworthiness, (2) elicit initial user views on a GEO label and its potential role and (3), evaluate prototype label visualisations. Our first study revealed that, when evaluating quality of data, users consider 8 facets: dataset producer information; producer comments on dataset quality; dataset compliance with international standards; community advice; dataset ratings; links to dataset citations; expert value judgements; and quantitative quality information. Our second study confirmed the relevance of these facets in terms of the community-perceived function that a GEO label should fulfil: users and producers of geospatial data supported the concept of a GEO label that provides a drill-down interrogation facility covering all 8 informational aspects. Consequently, we developed three prototype label visualisations and evaluated their comparative effectiveness and user preference via a third user study to arrive at a final graphical GEO label representation. When integrated in the GEOSS, an individual GEO label will be provided for each dataset in the GEOSS clearinghouse (or other data portals and clearinghouses) based on its available quality information. Producer and feedback metadata documents are being used to dynamically assess information availability and generate the GEO labels. The producer metadata document can either be a standard ISO compliant metadata record supplied with the dataset, or an extended version of a GeoViQua-derived metadata record, and is used to assess the availability of a producer profile, producer comments, compliance with standards, citations and quantitative quality information. GeoViQua is also currently developing a feedback server to collect and encode (as metadata records) user and producer feedback on datasets; these metadata records will be used to assess the availability of user comments, ratings, expert reviews and user-supplied citations for a dataset. The GEO label will provide drill-down functionality which will allow a user to navigate to a GEO label page offering detailed quality information for its associated dataset. At this stage, we are developing the GEO label service that will be used to provide GEO labels on demand based on supplied metadata records. In this presentation, we will provide a comprehensive overview of the GEO label development process, with specific emphasis on the GEO label implementation and integration into the GEOSS.

An empirical examination of the strategic decision-making process:the relationship between context, process, and outcomes

Despite concerted academic interest in the strategic decision-making process (SDMP) since the 1980s, a coherent body of theory capable of guiding practice has not materialised. This is because many prior studies focus only on a single process characteristic, often rationality or comprehensiveness, and have paid insufficient attention to context. To further develop theory, research is required which examines: (i) the influence of context from multiple theoretical perspectives (e.g. upper echelons, environmental determinism); (ii) different process characteristics from both synoptic formal (e.g. rationality) and political incremental (e.g. politics) perspectives, and; (iii) the effects of context and process characteristics on a range of SDMP outcomes. Using data from 30 interviews and 357 questionnaires, this thesis addresses several opportunities for theory development by testing an integrative model which incorporates: (i) five SDMP characteristics representing both synoptic formal (procedural rationality, comprehensiveness, and behavioural integration) and political incremental (intuition, and political behaviour) perspectives; (ii) four SDMP outcome variables—strategic decision (SD) quality, implementation success, commitment, and SD speed, and; (iii) contextual variables from the four theoretical perspectives—upper echelons, SD-specific characteristics, environmental determinism, and firm characteristics. The present study makes several substantial and original contributions to knowledge. First, it provides empirical evidence of the contextual boundary conditions under which intuition and political behaviour positively influence SDMP outcomes. Second, it establishes the predominance of the upper echelons perspective; with TMT variables explaining significantly more variance in SDMP characteristics than SD specific characteristics, the external environment, and firm characteristics. A newly developed measure of top management team expertise also demonstrates highly significant direct and indirect effects on the SDMP. Finally, it is evident that SDMP characteristics and contextual variables influence a number of SDMP outcomes, not just overall SD quality, but also implementation success, commitment, and SD speed.

Mobile case-based decision support for intelligent patient knowledge management

Hospitals everywhere are integrating health data using electronic health record (EHR) systems, and disparate and multimedia patient data can be input by different caregivers at different locations as encapsulated patient profiles. Healthcare institutions are also using the flexibility and speed of wireless computing to improve quality and reduce costs. We are developing a mobile application that allows doctors to efficiently record and access complete and accurate real-time patient information. The system integrates medical imagery with textual patient profiles as well as expert interactions by healthcare personnel using knowledge management and case-based reasoning techniques. The application can assist other caregivers in searching large repositories of previous patient cases. Patients' symptoms can be input to a portable device and the application can quickly retrieve similar profiles which can be used to support effective diagnoses and prognoses by comparing symptoms, treatments, diagnosis, test results and other patient information. © 2007 Sage Publications.

Expert System for Decision-Making Problem in Economics

An expert system (ES) is a class of computer programs developed by researchers in artificial intelligence. In essence, they are programs made up of a set of rules that analyze information about a specific class of problems, as well as provide analysis of the problems, and, depending upon their design, recommend a course of user action in order to implement corrections. ES are computerized tools designed to enhance the quality and availability of knowledge required by decision makers in a wide range of industries. Decision-making is important for the financial institutions involved due to the high level of risk associated with wrong decisions. The process of making decision is complex and unstructured. The existing models for decision-making do not capture the learned knowledge well enough. In this study, we analyze the beneficial aspects of using ES for decision- making process.

A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.

Hospital performance:efficiency or quality? Can we have both with IT?

The influence of IT investment on hospital efficiency and quality are of great interest to healthcare executives as well as insurers. Few studies have examined how IT investments influence both efficiency and quality or whether there is an optimal IT investment level that influences both in the desired direction. Decision makers in healthcare wonder if there are tradeoffs between their pursuit of hospital operational efficiency and quality. Our study involving a 2-stage double bootstrap DEA analysis of 187 US hospitals over 2. years found direct effects of IT investment upon service quality and a moderating effect of quality upon operational efficiency. Further, our findings indicate a U-shaped relationship between IT investments and operational efficiency suggesting that IT investments have diminishing returns beyond a certain point.

Extreme Situations Prediction by MultidimenSional Heterogeneous Time Series Using Logical Decision Functions

* The work is supported by RFBR, grant 04-01-00858-a

The System of Quality Prediction on the Basis of a Fuzzy Data and Psychography of the Experts

The system of development unstable processes prediction is given. It is based on a decision-tree method. The processing technique of the expert information is offered. It is indispensable for constructing and processing by a decision-tree method. In particular data is set in the fuzzy form. The original search algorithms of optimal paths of development of the forecast process are described. This one is oriented to processing of trees of large dimension with vector estimations of arcs.

The global plant location decision

The global plant location decision is important since it involves the allocation of significant resources and may influence the long term competitiveness of firms. The decision is also complex, taking into account a wide range of factors. The decision should involve the consideration of both international business issues as well as manufacturing strategy. Firms may be seeking access to markets, to low cost labour, or new skills and competencies. In the past there has been some emphasis on firms offshoring production to lower cost regions. Case studies from the authors’ experience of advising clients in this decision show that for ‘luxury’ products, firms have chosen to invest further capacity in home country engineering and manufacturing to maintain quality and brand integrity, despite the fact that these locations are higher cost. On the other hand, for ‘standard’ products, firms have located additional capacity closer to target markets to access lower costs.

A critical evaluation of the volume, relevance and quality of evidence submitted by the tobacco industry to oppose standardised packaging of tobacco products

OBJECTIVES: To examine the volume, relevance and quality of transnational tobacco corporations' (TTCs) evidence that standardised packaging of tobacco products 'won't work', following the UK government's decision to 'wait and see' until further evidence is available. DESIGN: Content analysis. SETTING: We analysed the evidence cited in submissions by the UK's four largest TTCs to the UK Department of Health consultation on standardised packaging in 2012. OUTCOME MEASURES: The volume, relevance (subject matter) and quality (as measured by independence from industry and peer-review) of evidence cited by TTCs was compared with evidence from a systematic review of standardised packaging . Fisher's exact test was used to assess differences in the quality of TTC and systematic review evidence. 100% of the data were second-coded to validate the findings: 94.7% intercoder reliability; all differences were resolved. RESULTS: 77/143 pieces of TTC-cited evidence were used to promote their claim that standardised packaging 'won't work'. Of these, just 17/77 addressed standardised packaging: 14 were industry connected and none were published in peer-reviewed journals. Comparison of TTC and systematic review evidence on standardised packaging showed that the industry evidence was of significantly lower quality in terms of tobacco industry connections and peer-review (p<0.0001). The most relevant TTC evidence (on standardised packaging or packaging generally, n=26) was of significantly lower quality (p<0.0001) than the least relevant (on other topics, n=51). Across the dataset, TTC-connected evidence was significantly less likely to be published in a peer-reviewed journal (p=0.0045). CONCLUSIONS: With few exceptions, evidence cited by TTCs to promote their claim that standardised packaging 'won't work' lacks either policy relevance or key indicators of quality. Policymakers could use these three criteria-subject matter, independence and peer-review status-to critically assess evidence submitted to them by corporate interests via Better Regulation processes.

Az online-fogyasztói elégedettség mérésére alkalmas skála tesztelése és véglegesítése a vállalati döntéshozók támogatása céljából (Testing and finalizing a scale for measuring online consumer satisfaction to support the companies decision making process)

A versenyképesség, illetve a gazdaságos működés elengedhetetlen feltétele a fogyasztói elégedettség, melynek egyik meghatározó eleme az észlelt és elvárt minőség közti kapcsolat. A minőségi elvárások az internettel, mint napjaink egyik meghatározó csatornájával kapcsolatban is megfogalmazódtak már, így kapott jelentős szerepet az online szolgáltatásminőség meghatározása, illetve ezzel összekapcsolódva az online-fogyasztói elégedettségmérés. A tanulmány célja, hogy szakirodalmi áttekintést nyújtson a témában, és a szakirodalomból ismert E-S-QUAL és E-RecS-QUAL online-fogyasztói elégedettségmérésre szolgáló skálát megvizsgálja, érvényességét a magyar körülmények között letesztelje, és a szükségesnek látszó módosítások elvégzésével egy Magyarországon használható skálát hozzon létre. Az online-fogyasztók elégedettségmérésének alapjaként az online szolgáltatásminőség fogyasztói érzékelésével, illetve értékelésével kapcsolatos elméleteket járja körbe a tanulmány, és ezután kerül sor a különböző mérési módszerek bemutatására, kiemelt szerepet szánva az E-S-QUAL és E-RecS-QUAL skálának, mely az egyik leginkább alkalmazott módszernek számít. Az áttekintés középpontjában azok a honlapok állnak, melyeken vásárolni is lehet, a kutatást pedig az egyik jelentős hazai online könyvesbolt ügyfélkörében végeztem el. ______ Over the last decade the business-to-consumer online market has been growing very fast. In marketing literature a lot of studies have been created focusing on understanding and measuring e-service quality (e-sq) and online-customer satisfaction. The aim of the study is to summarize these concepts, analyse the relationship between e-sq and customer’s loyalty, which increases the competitiveness of the companies, and to create a valid and reliable scale to the Hungarian market for measuring online-customer satisfaction. The base of the empirical study is the E-S-QUAL and its second scale the E-RecS-QUAL that are widely used multiple scales measuring e-sq with seven dimensions: efficiency, system availability, fulfilment, privacy, responsiveness, compensation, and contact. The study is focusing on the websites customers use to shop online.

Vezetési és döntési rendszerek a versenyképesség szolgálatában - Összefoglaló a Vezetési és döntési rendszerek kutatócsoport munkájáról = Management and decision making systems supporting competitiveness

A „Vezetési és döntési rendszerek” alprojekt kutatói a döntéshozatal minőségének és a versenyképességnek a kapcsolatát vizsgálták. Alapkérdésünk az volt, hogy mely vállalatok a sikeresebbek, azok, amelyek a döntéshozatali közelítésmódok közül a szigorúan racionális, analitikus gondolkodást, felfogást favorizálják, vagy inkább a kreativitást ösztönző és középpontba állító, a kreatív döntéshozatali és vezetési stílust követő cégek. Azt tapasztaltuk, hogy a vállalatok menedzsmentjének egyre többször kell megbirkóznia vészhelyzetekkel és azok következményeivel. Az üzleti döntések és az üzleti teljesítmény, az üzleti siker kapcsolatának vizsgálatára külön kutatási irányt jelöltünk meg. A felelős döntéshozatal témakörében a mi kutatásunk a konkrét döntéseket helyezte előtérbe, amely új közelítésmódot jelent. Ugyanis nem csak specifikus CSR gyakorlatokkal foglalkoztunk, hanem konkrét vezetői döntésekben vizsgáltuk meg a CSR és a fenntarthatóság elemeit. ______ Within the framework of the “Management and decision-making systems” subproject we investigated the link between the quality of decision making and competitiveness. Our basic question was the following: which companies are more successful, those who are strictly follow the rational/analytical way of decision making or the others who mainly focus on creative decision making and creative management. We found that nowadays the company managements more often face to crisis situations and their consequences. We initiated a focused research on the relationship of the business decision making, business performance and business success. When we did research in the field of the responsible decision making we focused on concrete decision cases, that was a brand new approach. We have not analyzed the CSR practice, but identified CSR and sustainability elements in concrete management decisions.

Analysis and intuition in strategic decision making. The case of California

Many management scholars believe that the process used to make strategic decisions affects the quality of those decisions. However several authors have observed a lack of research on the strategic decision making process. Empirical tests of factors that have been hypothesized to affect the way strategic decisions are made notably are absent. (Fredrickson, 1985) This paper reports the results of a study that attempts to assess the effects of decision making circumstances focusing mainly on the approaches applied and the managerial skills and capabilities the decision makers built on during concrete strategic decision making procedures. The study was conducted in California between September 2005 and June 2006 and it was sponsored by a Fulbright Research Scholarship Grant.