A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance

A Credit Rating Model in a Fuzzy Inference System Environment

One of the most important functions of an export credit agency (ECA) is to act as an intermediary between national governments and exporters. These organizations provide financing to reduce the political and commercial risks in international trade. The agents assess the buyers based on financial and non-financial indicators to determine whether it is advisable to grant them credit. Because many of these indicators are qualitative and inherently linguistically ambiguous, the agents must make decisions in uncertain environments. Therefore, to make the most accurate decision possible, they often utilize fuzzy inference systems. The purpose of this research was to design a credit rating model in an uncertain environment using the fuzzy inference system (FIS). In this research, we used suitable variables of agency ratings from previous studies and then screened them via the Delphi method. Finally, we created a credit rating model using these variables and FIS including related IF-THEN rules which can be applied in a practical setting

A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1) Resource-based view, and (2) Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a noveldevelopment of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed

E-Commerce in Agri-Food Sector : A Systematic Literature Review Based on Service-Dominant Logic

Agricultural e-commerce (AE) has attracted substantial attention within various research disciplines for several years. In this paper, we present a literature review of the recent state of AE research published from 2000 through to 2021 in 83 journals. Based on Service-Dominant Logic (S-D logic) and Qualitative Comparative Analysis (QCA), we identify six research themes, and a theoretical continuum is applied to reveal how research themes and scholarly approaches fit into the S-D logic framework. A general increasing trend in the number of articles confirms the escalating interest in AE research; however, different themes perform unevenly with S-D logic. Even though research themes such as Consumer Willingness are getting closer to S-D logic premises, and ideologies that are increasingly approaching S-D logic have been applied to analyzing AE topics, unfortunately, there remains a paucity of papers that wield S-D logic in the AE field. Our research focuses on an innovative emerging AE field and, simultaneously, provides an approach of integrating S-D logic into analyzing academic papers in the AE domain. This research may shed some light on future possibilities that S-D logic could support the co-creation of value between consumers and agribusiness managers, and other broader disciplines such as management and marketing.Peer reviewe

Green supply chain performance assessment: exploration fuzzy logic to tackle linguistic evaluation information

Green Supply Chain Management (GSCM) has appeared as an environmental innovation integrating environmental concerns into the supply chain management. Due to recent modification in environmental requirements, Govt. rules and regulations that affect manufacturing operations and services; growing attention is being given towards inclusion of environmental management strategies into traditional concept of supply chains. A Green Supply Chain (GSC) aims at confining the wastes within the industrial system so as to conserve energy and prevent the dissipation of harmful materials into the environment. In order to assess GSC performance extent, ‘green attributes’ must be considered along with traditional SC performance indices. The present work aims to discuss a methodology to deal with linguistic evaluation information through fuzzy logic for evaluating green supply chain performance and also attempts in identifying and prioritizing the key factors towards increasing ‘green competitiveness’. Here, the performance criteria/attributes have been evaluated by the expert group through linguistic variables which have further been transformed into Generalized Trapezoidal Fuzzy Numbers (GTFNs). Linguistic assessment of GSCM has been carried out based on different attributes, such as customer value, quality evaluation, performance measurement, appropriate price and environmental effect. Each attribute is followed by several criterions. Because of the vague and inconsistent nature of decision-makers’ linguistic evaluation information associated with GSCM; a fuzzy-based approach is indeed required to convert linguistic data into appropriate fuzzy numbers, for the analysis purpose. Apart from computing overall green performance extent, this research has been extended to identify ill-performing areas of an organizational GSC. Moreover, a case study has been reported in support of application feasibility of the proposed module

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.