Solving New Student Allocation Problem (NSAP) with Analytical Hierarchy Process (AHP)

There are many approaches used to solve New Student Allocation Problem (NSAP). Many researchers use application of Genetic Algorithm (GA). However, the study presented in this paper applies an Analytical Hierarchy Process (AHP)technique in solving New Student Allocation Problem (NSAP) handled by Registration Unit at Ungku Omar Polytechnic. The problem is the students are allocated to their class randomly, just by using their registration number and by all means without referring to their intelligence level, knowledge, skills and also their performance. So, in this paper the researcher’s focus is on solving NSAP by using AHP to allocate students into their respective classes with minimum intelligence gap in each class and the number of students in each class does not exceed its maximum capacity. The proposed solution will be tested using real data from the Politeknik Ungku Omar to see the result

Factors influencing the adoption of mobile services consumers' preferences using analytic hierarchy process

The rapid and widespread development of innovations in mobile services is changing societies and improving lives around the world. Due to lagging adoption, many of these new innovations have yet failed to generate revenue that was expected by mobile network operators, application and content developers. There are several factors which are affecting the service adoption by consumers. This paper aims to provide practitioners and academics, an insight on what consumers' preferences are by using an Analytic Hierarchy Approach (AHP). The objective of this paper is to identify factors influencing the adoption of the mobile services. In this study we have considered Payment Mode, Functionality, Added Value and PQCP (perceived quality, cost and performance) as the main service adoption factors. The survey results indicate that Functionality is the most important influencing factor for the respondents, followed by Added Value, PQCP and Payment Mode.Adoption,AHP,Mobile Value Services,Consumer's Preferences

How analytical hierarchy process prioritizing internet banking influencing factors? a research study

Internet banking is a method for conducting financial transactions online that makes use of the internet as a platform. Customers could transact at any time and from any location. Numerous aspects relating to the adoption of internet banking have been analyzed and studied in recent in-depth studies from the literature. This paper will merge these numerous predefined factors into a model by drawing on the various ideas related to the acceptance model. It was decided to adapt the analytical hierarchy process (AHP) method for finding the important numerous components for the model. The finest mathematical calculation method is AHP, which enables decision-makers to prioritize their ranking in order to satisfy various criteria. The goal of this research is to rank the elements that influence the use of online banking. Three main factors such as technical information, website and service availability were chosen as the main factors of the model based on the literature review. Sub-factors such as ease of use, responsiveness, privacy, reliability, security, communication and efficiency were also suggested and combined into a single integrated framework. Utilizing the systematic literature review (SLR) methodology, several factors were found. As a result, the article will enhance understanding of the unique elements supporting the adoption of internet banking

QoS based Web Service Selection and Multi-Criteria Decision Making Methods

With the continuing proliferation of web services offering similar efficacies, around the globe, it has become a challenge for a user to select the best web service. In literature, this challenge is exhibited as a 0-1 knapsack problem of multiple dimensions and multiple choices, known as an NP-hard problem. Multi-Criteria Decision Making (MCDM) method is one of the ways which suits this problem and helps the users to select the best service based on his/her preferences. In this regard, this paper assists the researchers in two conducts: Firstly, to witness the performance of different MCDM methods for large number of alternatives and attributes. Secondly, to perceive the possible deviation in the ranking obtained from these methods. For carrying out the experimental evaluation, in this paper, five different well-known MCDM methods have been implemented and compared over two different scenarios of 50 as well as 100 web services, where their ranking is defined on an account of several Quality of Service (QoS) parameters. Additionally, a Spearman’s Rank Correlation Coefficient has been calculated for different pairs of MCDM methods in order to provide a clear depiction of MCDM methods showing the least deviation in their ranking. The experimental results comfort web service users in conquering an appropriate decision on the selection of suitable service

Some further studies on improving QFD methodology and analysis

Quality Function Deployment (QFD) starts and ends with the customer. In other words, how it ends may depend largely on how it starts. Any QFD practitioners will start with collecting the voice of the customer that reflects customer’s needs as to make sure that the products will eventually sell or the service may satisfy the customer. On the basis of those needs, a product or service creation process is initiated. It always takes a certain period of time for the product or service to be ready for the customer. The question here is whether those customer-needs may remain exactly the same during the product or service creation process. The answer would be very likely to be a ‘no’, especially in today’s rapidly changing environment due to increased competition and globalization. The focus of this thesis is placed on dealing with the change of relative importance of the customer’s needs during product or service creation process. In other words, the assumption is that there is no new need discovered along the time or an old one becomes outdated; only the relative importance change of the existing needs is dealt with. Considering the latest development of QFD research, especially the increasingly extensive use of Analytic Hierarchy Process (AHP) in QFD, this thesis aims to enhance the current QFD methodology and analysis, with respect to the change during product or service creation process, as to continually meet or exceed the needs of the customer. The entire research works are divided into three main parts, namely, the further use of AHP in QFD, the incorporation of AHP-based priorities’ dynamics in QFD, and decision making analysis with respect to the dynamics. The first part focuses on the question "In what ways does AHP, considering its strength and weakness, contribute to an improved QFD analysis?" The usefulness of AHP in QFD is demonstrated through a case study in improving higher education quality of an education institution. Furthermore, a generalized model of using AHP in QFD is also proposed. The generalized model not only provides an alternative way to construct the house of quality (HoQ), but also creates the possibility to include other relevant factors into QFD analysis, such as new product development risks. The second part addresses the question "How to use the AHP in QFD in dealing with the dynamics of priorities?" A novel quantitative method to model the dynamics of AHP-based priorities in the HoQ is proposed. The method is simple and time-efficient. It is especially useful when the historical data is limited, which is the case in a highly dynamic environment. As to further improve QFD analysis, the modeling method is applied into two areas. The first area is to enhance the use of Kano’s model in QFD by considering its dynamics. It not only extends the use of Kano’s model in QFD, but also advances the academic literature on modeling the life cycle of quality attributes quantitatively. The second area is to enhance the benchmarking part of QFD by including the dynamics of competitors’ performance in addition to the dynamics of customer’s needs. The third part deals with the question "How to make decision in a QFD analysis with respect to the dynamics in the house of quality?" Two decision making approaches are proposed to prioritize and/or optimize the technical attributes with respect to the modeling results. Considering the fact that almost all QFD translation process employs the relationship matrix, a guideline for QFD practitioners to decide whether the relationship matrix should be normalized is developed. Furthermore, a practical implication of the research work towards the possible use of QFD in helping a company develop more innovative products is also discussed. In brief, the main contribution of this thesis is in providing some novel methods and/or approaches to enhance the QFD’s use with respect to the change during product or service creation process. For scientific community, this means that the existing QFD research has been considerably improved, especially with the use of AHP in QFD. For engineering practice, a better way of doing QFD analysis, as a customer-driven engineering design tool, has been proposed. It is hoped that the research work may provide a first step into a better customer-driven product or service design process, and eventually increase the possibility to create more innovative and competitive products or services over time

Introducing Importance-Performance-Impact Analysis (IPIA): A method to strategically prioritize resources allocation

The importance–performance analysis (IPA) model has been widely used as a strategic resource allocation tool for improving customer satisfaction. There are several shortcomings associated with IPA which could lead to incorrect decisions. In this paper, we propose a novel analytical framework, the “Importance-Performance-Impact Analysis” (IPIA) to overcome those shortcomings so as to provide managers with a powerful decision making tool. The IPIA takes advantage of several advanced analytical techniques, such as Back Propagation Neural Network (BPNN), Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). We illustrate IPIA using the case of an airline company in China. Two primary data sources were used: A passenger survey to obtain the attribute importance and performance, and an expert panel survey to obtain attribute impact. Resources allocation recommendations for improving passenger satisfaction were then derived from the IPIA. We discuss limitations and provide recommendations for future research

Assessment of socio-techno-economic factors affecting the market adoption and evolution of 5G networks: Evidence from the 5G-PPP CHARISMA project

5G networks are rapidly becoming the means to accommodate the complex demands of vertical sectors. The European project CHARISMA is aiming to develop a hierarchical, distributed-intelligence 5G architecture, offering low latency, security, and open access as features intrinsic to its design. Finding its place in such a complex landscape consisting of heterogeneous technologies and devices, requires the designers of the CHARISMA and other similar 5G architectures, as well as other related market actors to take into account the multiple technical, economic and social aspects that will affect the deployment and the rate of adoption of 5G networks by the general public. In this paper, a roadmapping activity identifying the key technological and socio-economic issues is performed, so as to help ensure a smooth transition from the legacy to future 5G networks. Based on the fuzzy Analytical Hierarchy Process (AHP) method, a survey of pairwise comparisons has been conducted within the CHARISMA project by 5G technology and deployment experts, with several critical aspects identified and prioritized. The conclusions drawn are expected to be a valuable tool for decision and policy makers as well as for stakeholders

Implementation of fuzzy analytical hierarchy process on notebook selection

Notebooks are technological devices widely adopted to assist in human daily life including learning, business, communication and other tasks. Equipped with the distinctive features, notebook was facilitated more simply for one touch screen basis to enable freely in exploring the users’ creativity. This study attempts to examine the process of selecting notebook brand among the consumers. Using AHP (Analytical Hierarchy Process) to help decision support system in the selection of Notebook from decision support systems designed to enhance all decision-process through identifying problems, selecting relevant data and defining the approaches was used to evaluate the selection of alternatives in the decision-making process. The finding reveals that the visibility of decision making into the ranking of priority with alternative choice of notebook can be viewed as follows Zyrex 16%, HP 15%, Asus 14%, Apple 13%, Samsung and Axioo 11%, Acer and Toshiba with priority 10%

Review of a Process Prioritization in Mass Customization

Purpose – The present article aims to analyze the content of process prioritization methods and possibilities of its application in the context of Mass Customization. Design/methodology/approach – As the analysis is based on exploratory approach, qualitative methodology is the main tool used in the research. Moreover, author do not aim at providing conclusive answers to research questions; in opposition, generating relevant insights about a current situation is a goal. Findings – Results suggest that prioritization methods and principles are compatible, necessary and can be successfully applicable to Mass Customization at different process stages or even this concept types. In addition, this research reveals the need to have a combined and multidimensional prioritization at the beginning of Mass Customization processes. Research limitations/implications – Main research limitations can be divided into two parts. Firstly, when prioritization is taken into consideration, it is noticed that a limited scope of research focus on combined prioritization models as well as their effect on organizations results, especially in Public and Non-governmental sector. Secondly, in a case of concept of Mass Customization and its analysis, scientific discussions show extremum transitions to Big Data, Internet platform capabilities and overall customer flow management via modern economic theories in the last decades. Therefore, a lack of sufficient scientific attention to important parts of prioritization severely affect customer input, Design and Infrastructure of Mass Customization. In addition, both parts require not only proper understanding of the theoretical background but also following detail description of practical implication tools and guidelines as well as defining possible application effect. Since this article is based on the theoretical literature review, case studies and comparative analysis towards a practical implication are elaborated briefly. Practical implications – This research may serve as relevant insights into the context of the Mass Customization system and processes, where organizations constantly cope with prioritization by making a number of decisions on product selection, specifications, quantities, or pricing. From the perspective of process prioritization, the research serves as a concise review of main quantitative and qualitative methods, showing their demand of alignment and effect for Mass Customization. Originality/Value – The main value of the presented article can be described as a holistic theoretical focus on different types of prioritization methods and underlying points where it takes effect in Mass Customization concept. Moreover, the selected research object and findings are also valuable and applicable for organizations of different type, sector and working field