A Novel Approach to Incubator Evaluations: The PROMETHEE Outranking Procedures

Considerable public resources are devoted to the establishment and operation of business incubators (BIs), which are seen as catalysts for the promotion of entrepreneurship, innovation activities and regional development. Despite the vast amount of research that has focused on the outcomes or effectiveness of incubator initiatives and how to measure incubator performance, there is still little understanding of how to determine incubators that are more effective than others. Based on data from 410 graduate firms, this paper applies the multi-criteria outranking technique PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) and compares the long-term effectiveness of five technology-oriented BIs in Germany. This is the first time that outranking procedures are used in incubator evaluations. In particular, we investigate whether PROMETHEE is a well-suited methodological approach for the evaluation and comparisons in the specific context of business incubation.business incubators, evaluation, performance measures, PROMETHEE, Outranking

An integrated grey-based multi-criteria decision-making approach for supplier evaluation and selection in the oil and gas industry

Purpose The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry. Design/methodology/approach To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers. Findings To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust. Research limitations/implications The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry. Originality/value This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

A framework to identify and prioritise the key sustainability indicators: Assessment of heating systems in the built environment

Sustainability indicators (SIs) are important instruments to quantify, analyse, and communicate complex sustainability information, with a history of application in energy research. It is critical to identify an effective set of indicators which can holistically evaluate the energy systems encompassing the three facets of sustainability: environment, economy, and society. However, the literature has been lacking in either proportionally representing the sustainability dimensions or reflecting the stakeholders’ preferences. This paper develops a framework to identify and prioritise a set of SIs, critically reviewed to ensure reflection of a wide array of factors and conceptions of what sustainability entails. The developed framework utilises a series of methods within three phases: identification, refinement, and prioritisation. Applying the proposed framework to building heating technologies, a set of 22 SIs consisting of 4 economic, 8 environmental, and 10 social indicators were identified. According to the results, the economic indicators of Operation & Maintenance Cost and Net Present Value were found to be the most impactful factors, while environmental SIs contribute the most to the overall sustainability weight. The identified indicators apply to the assessment of heating systems and policies, and the proposed framework could more broadly support analysis of key sustainability criteria in various fields

Introduction to the Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) has been one of the foremost mathematical methods for decision making with multiple criteria and has been widely studied in the operations research literature as well as applied to solve countless real-world problems. This book is meant to introduce and strengthen the readers’ knowledge of the AHP, no matter how familiar they may be with the topic. This book provides a concise, yet self-contained, introduction to the AHP that uses a novel and more pedagogical approach. It begins with an introduction to the principles of the AHP, covering the critical points of the method, as well as some of its applications. Next, the book explores further aspects of the method, including the derivation of the priority vector, the estimation of inconsistency, and the use of AHP for group decisions. Each of these is introduced by relaxing initial assumptions. Furthermore, this booklet covers extensions of AHP, which are typically neglected in elementary expositions of the methods. Such extensions concern different numerical representations of preferences and the interval and fuzzy representations of preferences to account for uncertainty. During the whole exposition, an eye is kept on the most recent developments of the method.Peer reviewe

Decision support system for project monitoring portfolio

Vallejo Antich, RA. (2010). Decision support system for project monitoring portfolio. http://hdl.handle.net/10251/8632.Archivo delegad

Dynamics under Uncertainty: Modeling Simulation and Complexity

The dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc