Utilizing Analytical Hierarchy Process for Pauper House Programme in Malaysia

In Malaysia, the selection and evaluation of candidates for Pauper House Programme (PHP) are done manually. In this paper, a technique based on Analytical Hierarchy Technique (AHP) is designed and developed in order to make an evaluation and selection of PHP application. The aim is to ensure the selection process is more precise, accurate and can avoid any biasness issue. This technique is studied and designed based on the Pauper assessment technique from one of district offices in Malaysia. A hierarchical indexes are designed based on the criteria that been used in the official form of PHP application. A number of 23 samples of data which had been endorsed by Exco of State in Malaysia are used to test this technique. Furthermore the comparison of those two methods are given in this paper. All the calculations of this technique are done in a software namely Expert Choice version 11.5. By comparing the manual and AHP shows that there are three (3) samples that are not qualified. The developed technique also satisfies in term of ease of accuracy and preciseness but need a further study due to some limitation as explained in the recommendation of this paper

Security based partner selection in Inter-organizational workflow systems

The creation of inter-organizational workflow implies the coalition of partners' efforts and resources in order to achieve a set of common objectives and goals. However, this openness may cause a huge damage to the participating entities due to security breaches. The risk of unsuccessful collaboration should be well studied. Thus, the key for successful collaboration is to select the appropriate collaborators based on specific security criteria for each outsourced task. In this sense, several criteria have to be considered, among them: trust and reputation level, policy similarity level, security level and privacy compliance level. The proposed security based partner selection approach allows us to rank participating entities in the collaboration based on the main security criteria in order to assign each task to the suitable partner with the most appropriate and efficient way

Public initiatives of settlement transformation. A theoretical-methodological approach to selecting tools of multi-criteria decision analysis

In Europe, the operating context in which initiatives of settlement transformation are currently initiated is characterized by a complex, elaborate combination of technical, regulatory and governance-related factors. A similar set of considerations makes it necessary to address the complex decision-making problems to be resolved through multidisciplinary, comparative approaches designed to rationalize the process and treat the elements to be considered in systematic fashion with respect to the range of alternatives available as solutions. Within a context defined in this manner, decision-making processes must often be used to obtain multidisciplinary and multidimensional analyses to support the choices made by the decision-makers. Such analyses are carried out using multi-criteria tools designed to arrive at syntheses of the numerous forms of input data needed to describe decision-making problems of similar complexity, so that one or more outcomes of the synthesis make possible informed, well thought-out, strategic decisions. The technical literature on the topic proposes numerous tools of multi-criteria analysis for application in different decision-making contexts. Still, no specific contributions have been drawn up to date on the approach to take in selecting the tool best suited to providing adequate responses to the queries of evaluation that arise most frequently in the various fields of application, and especially in the settlement sector. The objective of this paper is to propose, by formulating a taxonomy of the endogenous and exogenous variables of tools of multi-criteria analysis, a methodology capable of selecting the tool best suited to the queries of evaluation which arise regarding the chief categories of decision-making problems, and particularly in the settlement sector

A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes

Real estate and land management are characterised by a complex, elaborate combination of technical, regulatory and governmental factors. In Europe, Public Administrators must address the complex decision-making problems that need to be resolved, while also acting in consideration of the expectations of the different stakeholders involved in settlement transformation. In complex situations (e.g., with different aspects to be considered and multilevel actors involved), decision-making processes are often used to solve multidisciplinary and multidimensional analyses, which support the choices of those who are making the decision. Multi-Criteria Decision Analysis (MCDA) methods are included among the examination and evaluation techniques considered useful by the European Community. Such analyses and techniques are performed using methods, which aim to reach a synthesis of the various forms of input data needed to define decision-making problems of a similar complexity. Thus, one or more of the conclusions reached allow for informed, well thought-out, strategic decisions. According to the technical literature on MCDA, numerous methods are applicable in different decision-making situations, however, advice for selecting the most appropriate for the specific field of application and problem have not been thoroughly investigated. In land and real estate management, numerous queries regarding evaluations often arise. In brief, the objective of this paper is to outline a procedure with which to select the method best suited to the specific queries of evaluation, which commonly arise while addressing decision-making problems. In particular issues of land and real estate management, representing the so-called “settlement sector”. The procedure will follow a theoretical-methodological approach by formulating a taxonomy of the endogenous and exogenous variables of the multi-criteria analysis method

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

Formalisation and use of competencies for industrial performance optimisation : a survey.

For many years, industrial performance has been implicitly considered as deriving from the optimisation of technological and material resources (machines, inventories,...), made possible by centralized organisations. The topical requirements for reactive and flexible industrial systems have progressively reintroduced the human workforce as the main source of industrial performance. Making this paradigm operational requires the identification and careful formalisation of the link between human resource and industrial performance, through concepts like skills, competencies or know-how. This paper provides a general survey of the formalisation and integration of competence-oriented concepts within enterprise information systems and decision systems, aiming at providing new methods and tools for performance management

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

Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19

The COVID-19 emergency is affecting manufacturing industries all over the world. Notably, it has generated several issues in the products’ supply and the global value chain in African countries. Besides this, Africa’s manufacturing value-added rate grew only 1.5 since 2018, and the foreign direct investment (FDI) from multinational enterprises (MNEs) remains very low due to high-risk factors. Most of these factors are linked to a non-optimized location selection that can adversely affect plant performance. For these reasons, supporting decision-makers in selecting the suitable country location in Africa is crucial, both for contributing to countries’ growth and companies’ performance. This research aims at presenting a comprehensive multi-criteria decision-making model (MCDM) to be used by MNEs to evaluate the best countries to develop new manufacturing settlements, highlighting the criteria that COVID-19 has impacted. Thus, it has affected countries’ performance, impacting the plant location selection choices. A combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods have also been used for comparative analysis. The criteria used in the proposed approach have been validated with a panel of MNEs experts

Enterprise, project and workforce selection models for industry 4.0.

Abstract Enterprise, project, and workforce selection models for Industry 4.0. Rupinder Kaur The German federal government first coined industry 4.0 in 2011. Industry 4.0 involves the use of advanced technologies such as cyber-physical system, internet of things, cloud computing, and cognitive computing with the aim to revolutionize the current manufacturing practices. Automation and exchange of big data and key characteristics of Industry 4.0. Due to its numerous benefits, industries are readily investing in Industry 4.0, but this implementation is an uphill struggle. In this thesis, we address three key problems related to Industry 4.0 implementation namely Enterprise selection, Project selection and Workforce selection. The first problem involves identification of enterprises suitable for Industry 4.0 implementation. The second problem involves prioritization and selection of Industry 4.0 projects for the chosen digital enterprises. The third and last problem involves workforce selection and assignment for execution of the identified Industry 4.0 projects. Multicriteria solution approaches based on TOPSIS and Genetic Algorithms are proposed to address these problems. Industry experts are involved to prioritize the criteria used for enterprise, project and workforce selection. Numerical applications are provided. The proposed work is innovative and can be useful to manufacturing and service organizations interested in implementing Industry 4.0 projects for performance improvement

Prioritizing warehouse performance measures in contemporary supply chains

Purpose: Due to the importance of efficiency and responsiveness measures rather than just efficiency measures, this research recognizes both measures when considering overall performance of warehouse operations. Thus, the purpose of this study is to prioritize overall performance measures associated with warehouse operations in manufacturing, third-party logistics (3PL) service provider, and retail industry supply chains. Design/methodology/approach: The study uses an integrated approach that involves the Q-sort method to group measures into four categories. Fuzzy analytical hierarchy process (FAHP) was then used to prioritize individual performance measures within each category and integer liner programming model was used to validate prioritized categories, using the judgement of multiple decision makers across three industries. Findings: The result shows that the financial category is a dominating performance category in managing warehouse operations across all three industries selected. Within the financial category, cost of insurance accounted for 25% of total weight of the category, and is considered to be a powerful measure. The financial category is verified by multiple decision makers across three industries, as the most important performance category. Research Limitations/implications: As part of adopting the proposed methodology in practice, it needs to be guided by overall methodology appropriate for industry-specific contexts. Originality/value: Key novel aspects of this study are to categorize warehouse operations measures and analyze their perspectives in different industries, understand dominant categories of warehouse operations measures in the contemporary supply chain and finally to explore to what extent current practices lead to achieving efficiency and responsiveness in the selected industries