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

An information model for lean, agile, resilient and green supply chain management

Dissertação para a obtenção de Grau de Mestre em Engenharia e Gestão IndustrialIn modern business environments, an effective Supply Chain Management (SCM) is crucial to business continuity. In this context, Lean, Agile, Resilient and Green (LARG), are advocated as the fundamental paradigm for a competitive Supply Chain (SC) as a whole. In fact, competition between supply chains (SC) has replaced the traditional competition between companies. To make a supply chain more competitive, capable of responding to the demands of customers with agility, and capable of responding effectively to unexpected disturbance, in conjugation with environmental responsibilities, and the necessity to eliminate processes that add no value, companies must implement a set of LARG SCM practices and Key Performance Indicators (KPI) to measure their influence on the SC performance. However, the selection of the best LARG SCM practices and KPIs is a complex decision-making problem, involving dependencies and feedbacks. Still, any decision-making must be supported by real and transparent data. This dissertation intends to provide two integrated models to assist the information management and decision-making. The first is an information model to support a LARG SCM, allowing the exchange and storage of data/information through a single information platform. In this model three types of diagrams are developed, Business Process Diagram (BPD), Use Cases Diagram and Class Diagram to assist the information platform design. The second is a decision-making model, designated LARG Analytical Network Process (ANP) to select the best LARG SCM practices/KPI to be implemented in SCs. Both models are developed and validated within the automotive SC, namely in Volkswagen Autoeuropa

What drives inter-organisational knowledge management?:The cause and effect analysis using a multi-layer multi-criteria decision-making framework

Purpose Knowledge management seeks collaborative practices among organisations to generate technical, adapt and share knowledge to obtain a sustainable competitive advantage in cross-border business activities. This paper aims to disentangle the crucial determinants of knowledge management in inter-organisational arrangements settings. Design/methodology/approach In the first stage, after an in-depth literature review, the main knowledge management drivers are identified. In the second stage, based on the identified drivers, the importance and relationship between the drivers are evaluated by expert opinions from academic and executive activists. Eventually, in the last stage, a multi-layer decision-making approach has been proposed and used to determine the relationship and the importance of the drivers. Findings The findings of this paper assess the ranking of the different elements from experts’ opinions and discuss important theoretical and managerial implications. The influential factors were identified through an extensive literature review, which combined with the views of experts from academia and industry (international firms). Furthermore, the ranking of factors based on the experts’ overall opinion was used to discuss theoretical and managerial contributions. Originality/value This research provides a better understanding of the interrelationships between the key drivers of knowledge management, which helps management draw more effective strategies to address the cultural differences between firms. Moreover, understanding of the importance of the systems and structures that define the nature of the collaboration in inter-organisational settings, as well as the risks related to those are presented in this research

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Lean, agile, resilient and green supply chain management interoperability assessment methodology

Dissertação para obtenção de grau de Mestre em Engenharia e Gestão Industrial (MEGI)Supply Chain Management has become a tactic asset for the current global competition situation. Innovative strategies such as Lean, Agile, Resilient and Green emerged as a response, requiring high levels of cooperation and of great complexity. However, the strategic alignment of operations with partners in supply chains is affected by lack of interoperability. The present work provides a framework to enhance SC competitiveness and performance by assessing interoperable SCM Practices applied in automotive industry. Through a pragmatic interoperability approach, this methodology describes in detail the form of application using analytical hierarchical process (AHP) and Fuzzy sets as support decision making models, ensuring a systematic approach to the analysis of interoperability with appropriate criteria for assessment of situations that require high levels of collaboration between partners. Through a case study in a Portuguese automaker, it was possible to test the methodology and analyse which areas lack interoperability in the implementation of SCM practices