Partner selection in agile supply chains: A fuzzy intelligent approach

Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection

Exploring potential R&D collaboration partners through patent analysis based on bibliographic coupling and latent semantic analysis

The aim of the present research is to provide a new systematic methodology to explore potential R&D collaboration partners using patent information. The potential R&D collaboration partners are visualized as a patent assignee level-map based on technological similarity between patents by using network analysis. The proposed framework utilises two analytic methods to measure technological similarity. The first method, bibliographic coupling analysis, measures technological similarity based on the citation relationship using patent bibliographic information. Second, latent semantic analysis is utilized based on semantic similarity using patent textual information. The fuel cell membrane electrode assembly (MEA) technology field is selected and applied to illustrate the proposed methodology. The proposed approach allows firms, universities, research institutes, governments to identify potential R&D collaborators as a systematic decision-making support tool.This is an Accepted Manuscript of an article published by Taylor & Francis in Technology Analysis and Strategic Management on the 22nd of October 2014, available online: http://wwww.tandfonline.com/10.1080/09537325.2014.971004. This version will be under embargo until the 22nd of April 2016

İMALAT İSÇİLERİNİN SEÇİM KRİTERLERİNİN BULANIK AHS YÖNTEMİ İLE ANALİZİ

An analytical way to reach the best decision is more preferable in many business platforms. When variables are quantitative and number of criteria is not high, then one can use several analysis tools and make his/her decision and solve the problem. However, many times beside the measurable variables, there exist qualitative variables for decision making problems, or people are supposed to prefer the best among the many choices. Even if only linguistic evaluations may be available for such problems, an analytical way to find the solution systematically to make a successful decision is needed. Fuzzy Analytical Hierarchy Process (Fuzzy AHP) is one of the best ways for deciding among the complex criteria structure in different levels. Fuzzy AHP is a synthetic extension of classical AHP method when the fuzziness of the decision makers is considered. In this paper, the criteria set and their importance for the selection of manufacturing employee in a firm producing shoe machines are analyzed. Finally a systematic solution and decision support are provided for management. Birçok is ortamında analitik yöntemler, en iyi kararı vermek adına daha çok tercih görmektedir. Sayısal olarak ölçülebilen degiskenlerin ve kriterlerin varlıgında kullanılabilecek birçok analiz ve problem çözme teknigi bulunabilirken, kalitatif degiskenlerle seçim ya da karar verme zorunlulugu oldugunda farklı yaklasımlara gerek duyulmaktadır. Böyle bir durumda, öznel ve sözel degerlendirmeler yapma zorunlugu dogmakla birlikte, sistematik ve analitik bir yol izlemek basarılı karar vermek açısından kaçınılmazdır. Bu kosularda özellikle karar verme ortamı bulanık veriler içeriyorsa, en çok tercih edilen tekniklerden biri de Bulanık Analitik Hiyerarsi Süreci (Bulanık AHS)dir. Karmasık kriter set ve çoklu düzey yapısında seçenekler içerisinde en iyi seçimi yapma konusunda basarılı kararlar alınmasında sık kullanıma sahiptir. Bulanık AHS karar vericilerin yaptıkları yorum ve degerlendirmelerde belli bir bulanıklık oldugu düsünüldügünde ortaya çıkan ve AHS'nin bir uzantısı olarak gelistirilen sentetik bir yaklasımdır. Bu çalısmada, ayakkabı makinalar üreten bir firma için imalatta çalısacak isçilerin seçiminde hangi kriterlerin gözetildigi ve bu kriterlerin hangi agırlıklarla kararda etkili oldugu bulanık AHS yöntemi ile analiz edilmis, firma yetkilerine sistematik bir çözüm ve karar destegi saglanmıstır

Providing a Hybrid Methodology to Solve the Supplier Selection Problems: Application of MCDM Techniques

The emphasis of supply chain management (SCM) is majorly on the relationship between enterprise alliance and core enterprise. One of the main decision-making problems in SCM is choosing strategic partners, which also is the key to a prosperous SCM. In the present study, SCM is investigated using the analytical hierarchy process (AHP) simulation approach o examine the uncertainty involved in AHP and reduce its risk to some extent. Finally, this approach is employed to solve the problem of supplier selection in SCM

A framework to select commercial bank partner using fuzzy BSC-DEA method

One of the primary concerns of many corporate organizations is to assess the weakness and strength of their future partners in an attempt to reduce all potential risks involved with them. In this paper, we present a BSC-DEA based model to indentify strengths, weaknesses, opportunities and threats of a firm. The proposed model of this paper assumes there are various uncertainties associated with all input/output parameters and uses fuzzy numbers to handle the uncertainties. We also consider a real-world case study of banking industry where four major banks are possible candidates of a partnership and implement the proposed model of this paper for this case study. The results of this study reveal some of the issues such as weakness of electronic banking, services and resource allocation as part of their infrastructure problems

Partner selection in sustainable supply chains: a fuzzy ensemble learning model

With the increasing demands on businesses to operate more sustainably, firms must ensure that the performance of their whole supply chain in sustainability is optimized. As partner selection is critical to supply chain management, focal firms now need to select supply chain partners that can offer a high level of competence in sustainability. This paper proposes a novel multi-partner classification model for the partner qualification and classification process, combining ensemble learning technology and fuzzy set theory. The proposed model enables potential partners to be classified into one of four categories (strategic partner, preference partner, leverage partner and routine partner), thereby allowing distinctive partner management strategies to be applied for each category. The model provides for the simultaneous optimization of both efficiency in its use of multi-partner and multi-dimension evaluation data, and effectiveness in dealing with the vagueness and uncertainty of linguistic commentary data. Compared to more conventional methods, the proposed model has the advantage of offering a simple classification and a stable prediction performance. The practical efficacy of the model is illustrated by an application in a listed electronic equipment and instrument manufacturing company based in southeastern China

A hybrid performance evaluation system for notebook computer ODM companies

[[abstract]]The aim of the paper is to fulfill this need by building a conceptual framework for measuring the business performance of notebook computer ODM (Original Design Manufacturer) companies carried out to investigate how performance is understood and to identify the potential dimensions to improvement. In the process, a multiple criteria procedure is used to assess the performance in these companies. We explore the performance-evaluation systems by using fuzzy AHP and VIKOR techniques. The evidence from the investigation showed that supply chain capability and manufacturing capability are the top two indicators for the notebook computer ODM companies’ performance. Furthermore, it was found that Quanta and Compal have the relative high business performance among these companies. The research provides evidence which establishes whether benchmarking provides a real and lasting benefit to notebook computer ODM companies. A series of managerial implications are set forth and discussed.[[journaltype]]國外[[incitationindex]]SSCI[[booktype]]紙本[[countrycodes]]NG

Is it time to withdraw from china?

This research cross-employs the Social Cognitive Theory (SCT) and three major labor theories comprised of Maslow’s theory, Alderfer’s theory and Herzberg’s theory with Multiple Criteria Decision Making (MCDM) consisting of Factor Analysis (FA), Analytical Network Process (“ANP”), Fuzzy Analytical Network Process (FANP) and Grey Relation Analysis (GRA) to evaluate the four types of innovative investment strategies in China after the Domino Effect of the China’s Labor Revolution. The most contributed conclusion is that the “change of original business at the raising compensation policy” (CBRCP) is the best choice for Taiwanese manufacturers operating in China because it is the highest scores of three assessed measurements in the CBRCP. This conclusion further indicates that manufacturing enterprises have little leverage, in the interim, but to increase employment compensation and benefits to satisfy the demands from the ongoing Chinese labor revolution even though it brings about an incremental expenditure in their manufacturing costs. Therefore, the next step beyond this research is to collect additional empirical macroeconomic data to develop a more comprehensive evaluation model that takes into consideration a more in-depth vertical measurement and horizontal assessment methodologies for developing added comprehensive and effective managerial strategies for surviving in this momentous, dynamically-changing and lower-profit Chinese manufacturing market.China labor revolution; Maslow theory; Alderfer theory and Herzberg theory; Multiple criteria decision making

Partner selection in green supply chains using PSO – a practical approach

Partner selection is crucial to green supply chain management as the focal firm is responsible for the environmental performance of the whole supply chain. The construction of appropriate selection criteria is an essential, but often neglected pre-requisite in the partner selection process. This paper proposes a three-stage model that combines Dempster-Shafer belief acceptability theory and particle swarm optimization technique for the first time in this application. This enables optimization of both effectiveness, in its consideration of the inter-dependence of a broad range of quantitative and qualitative selection criteria, and efficiency in its use of scarce resources during the criteria construction process to be achieved simultaneously. This also enables both operational and strategic attributes can be selected at different levels of hierarchy criteria in different decision-making environments. The practical efficacy of the model is demonstrated by an application in Company ABC, a large Chinese electronic equipment and instrument manufacturer