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This study introduces a practical dominance reinforcement.This reinforcement makes the Modified Even-Swaps even easier.This reinforcement is based on SAW method.SAW method helps to identify dominated alternatives more practically. "Modified Even-Swaps" is a mechanism recently developed for multi-issue negotiation, which is highly complicated to realize and therefore more dependent to sophisticated information and communication technologies (ICTs) when compared to single-issue (price-only) negotiation. This mechanism is based on a modified version of Even-Swaps method finding differences among alternatives in terms of negotiable issues and then making use of those differences to assess value of multi-issue offers. A fuzzy-inference system supports this mechanism for bargaining on several issues simultaneously as well. Number of trade-offs performed significantly influences routines of the Modified Even-Swaps mechanism. In this study, a novel approach providing practical dominance reinforcement is introduced to accelerate the mechanism through eliminating unnecessary trade-offs. This approach proposes to use of "Simple Additive Weighting" (SAW) method in order to combine issues which have high variation among consequences of alternatives under consideration. As a result, these issues utilize a combined consequence for each alternative. Phase of the mechanism aiming to identify dominated alternatives is executed by using revised decision-matrix including consequences of issues having high variation as combined. This revision allows the mechanism to identify dominated alternatives more practically. Possible improvements are demonstrated and discussed with some cases in this study.

Even though fuzzy logic is one of the most common methodologies for matching different kind of data sources, there is no study which uses this methodology for matching publication and patent data within a technology evaluation framework according to the authors' best knowledge. In order to fill this gap and to demonstrate the usefulness of fuzzy logic in technology evaluation, this study proposes a novel technology evaluation framework based on an advanced/improved version of fuzzy logic, namely; interval type-2 fuzzy sets and systems (IT2FSSs). This framework uses patent data obtained from the European Patent Office (EPO) and publication data obtained from Web of Science/Knowledge (WoS/K) to evaluate technology groups with respect to their trendiness. Since it has been decided to target technology groups, patent and publication data sources are matched through the use IT2FSSs. The proposed framework enables us to make a strategic evaluation which directs considerations to use-inspired basic researches, hence achieving science-based technological improvements which are more beneficial for society. A European Classification System (ECLA) class - H01-Basic Electric Elements - is evaluated by means of the proposed framework in order to demonstrate how it works. The influence of the use of IT2FSSs is investigated by comparison with the results of its type-1 counterpart. This method shows that the use of type-2 fuzzy sets, i.e. handling more uncertainty, improves technology evaluation outcomes. (C) 2013 Elsevier Ltd. All rights reserved.

WOS: 000368953700003, Quality function deployment (QFD) is one of the most powerful methodologies in new product development (NPD) because of its systematic support of knowledge creation and sharing. However, greater product complexity, increasing dynamic customer requirements and further decentralization of innovation teams undermine applicability of QFD in modern NPD. Modifying QFD methodology with a multi-issue negotiation mechanism promises to overcome these obstacles because this negotiation-based structure (i) enables QFD to define a large number of interdependent decision parameters while handling complicated design trade-offs, (ii) includes changing customer requirements in real-time rather than a cycle time determined by length of the product development process, (iii) allows decentralized NPD teams to negotiate with each other and customers concurrently. This study presents a multi-issue negotiation based QFD methodology by using a recently developed mechanism for multi-issue negotiation (namely, Modified Even-Swaps) and illustrates strengths and weaknesses along with practical insights with a case study of the development of a washing machine. The QFD methodology proposed in this study provides new options to assess new product alternatives by allowing customer co-creation which is essential in complex and often tacit-knowledge dependent comparisons and also intrinsically helpful for fine-tuning dynamically evolving customer requirements. Moreover, it supports competition-based interactions of decentralized NPD teams. (C) 2015 Elsevier Ltd. All rights reserved., Scientific and Technological Research Council of Turkey (TUBITAK) [BIDEB 2214/A]; Scientific Research Projects Governing Unit (BAPYB) of Gaziantep University, The authors would like to thank the anonymous reviewers for their valuable comments, suggestions and corrections, which greatly improved the quality of the paper. The author from TU Bursa would like to acknowledge the international research fellowship provided by The Scientific and Technological Research Council of Turkey (TUBITAK: BIDEB 2214/A). The author from Gaziantep University would like to acknowledge the financial support provided by Scientific Research Projects Governing Unit (BAPYB) of Gaziantep University.

Data, as being the vital input of system modelling, contain dissimilar level of imprecision that necessitates different modelling approaches for proper analysis of the systems. Numbers, words and perceptions are the forms of data that has varying levels of imprecision. Existing approaches in the literature indicate that, computation of different data forms are closely linked with the level of imprecision, which the data already have. Traditional mathematical modelling techniques have been used to compute the numbers that have the least imprecision. Type-1 fuzzy sets have been used for words and type-2 fuzzy sets have been employed for perceptions where the level of imprecision is relatively high. However, in many cases it has not been easy to decide whether a solution requires a traditional approach, i.e., type-1 fuzzy approach or type-2 fuzzy approach. It has been a difficult matter to decide what types of problems really require modelling and solution either with type-1 or type-2 fuzzy approach. It is certain that, without properly distinguishing differences between the two approaches, application of type-1 and type-2 fuzzy sets and systems would probably fail to develop robust and reliable solutions for the problems of industry. In this respect, a review of the industrial applications of type-2 fuzzy sets, which are relatively novel to model imprecision has been considered in this work. The fundamental focus of the work has been based on the basic reasons of the need for type-2 fuzzy sets for the existing studies. With this purpose in mind, type-2 fuzzy sets articles have been selected from the literature using the online databases of ISI-Web of Science, ScienceDirect, SpringerLink, Informaworld, Engineering Village, Emerald and IEEE Xplore. Both the terms "type-2 fuzzy" and "application" have been searched as the main keywords in the topics of the studies to retrieve the relevant works. The analysis on the industrial applications of type-2 fuzzy sets/systems (FSs) in different topics allowed us to summarize the existing research areas and therefore it is expected be useful to prioritize future research topics. This review shows that there are still many opportunities for application of type-2 FSs for several different problem domains. Shortcomings of type-1 FSs can also be considered as an opportunity for the application of type-2 FSs in order to provide a better solution approach for industrial problems. (C) 2010 Elsevier B.V. All rights reserved.

"Even-Swaps" is a well-known and easy-to-use trade-off methodology which provides several useful features to decision makers. It allows them to find the difference among alternatives in terms of any issue under consideration. In a typical negotiation environment, allocating these differences in terms of a bargainable issue can help the negotiators to clarify the agreement area for each alternative. This allocation can contribute to make bargaining decisions more rationally. However, this feature could not be used in the original version of the Even-Swaps method because of its rigid structure that tries to reveal only the best alternative. The original Even-Swaps method also provides several hypothetical questions to decision makers while performing issue trade-offs. It is believed that the original Even-Swaps method can be improved upon (adapted) by forwarding the hypothetical questions to sellers and by developing a modified/flexible structure which considers all bargainable alternatives. With these modifications are successfully realized, an agent can generate counter offers and interact with sellers for bargaining by means of an appropriate automated-negotiation mechanism. The development of an automated & multi-issue negotiation-mechanism for bargaining also presents unique opportunities for the re-evolution of consumers into customers while contributing to the buyer-seller interactions. In this study, we present a novel multi-issue negotiation mechanism which adapts a modified Even-Swaps method that finds the differences among alternatives and makes use of those differences to assess the value of multi-issue offers. It uses a fuzzy inference system for bargaining on several issues simultaneously. In order to accomplish the steps of the proposed mechanism, a supplementary semi-automated decision-aid tool, so called: "Modified Even-Swaps Agent (MESA)" is developed. A real case-study is presented step by step in order to demonstrate how the proposed mechanism works. (C) 2012 Elsevier Ltd. All rights reserved.