International Journal of Information Processing and Management 

About: International Journal of Information Processing and Management is an academic journal. The journal publishes majorly in the area(s): Software development & The Internet. Over the lifetime, 72 publications have been published receiving 377 citations.

Simple Additive Weighting Methods of Multi criteria Decision Making and Applications: A Decade Review

Abstract: Various multi-criteria decision making (MCDM) methods have been proposed to solve diverse applications of decision problems. One of the MCDM methods is additive weighting-based method. However, this method is not explicitly disseminated and its applications are not-well received by many MCDM enthusiasts. This paper presents a review of the applications of simple additive weighting (SAW) and fuzzy simple additive weighting (FSAW) from 2003 to 2013. Two classifications of individual approaches and integrated approaches were made in this paper. Related articles appearing in international journals from 2003 to 2013 are gathered and analyzed. From the observation, it was noticed that ten out of nineteen articles or fifty two percent applied SAW or FSAW in the management selection process. This review provides the most prevalent application of the methods and also aids researchers in choosing the appropriate applications of SAW based methods. This paper would offer useful information for other researchers since it provides the latest evidence about SAW and FSAW. Decision making becomes an integral part in our daily lives and will be used for complex problems including problems with multiple conflicting criteria. Multi-criteria decision making (MCDM) is a well-known decision making process based on the progression of using methods and procedures of multiple conflicting criteria into the management planning process (1). In other words, MCDM refers to making decision in the presence of multiple, numerous and usually conflicting that involve numbers of criteria. MCDM provides a step by step procedure for which a consensus decision can be made by a group of decision makers. This well-defined procedure can reduce the amount of arguments or conflicts involved. MCDM plays an important role in solving complicated problems. The development of MCDM discipline is closely related to the advancement of computing technology. With this development, it is possible to conduct systematic analysis of complex MCDM problems. Furthermore, the extensive use of computing software has generated a huge amount of information, which makes MCDM increasingly important and useful in supporting decision making. In literature, multiple attribute decision making (MADM) and multiple objective decision making (MODM) are two basic approaches to MCDM. There exist a number of methods in each of the mentioned approaches. Pohekar and Ramachandran (2) pointed out that every method has its own characteristics and the methods can also be classified as deterministic, stochastic and fuzzy methods. Carlsson and Fuller (3) made an extensive review on MCDM and categorized it into four major categories. One of the categories is value and utility theory approaches. This second category is built around methods which utilize various ways to assess the relative importance of multiple attributes and alternatives. Under this category, most the methods were concentrated on weight determination. It comprises simple additive weighting (SAW), analytic hierarchy process, fuzzy conjunctive/ disjunctive methods, fuzzy outranking methods and max-min methods. It seems that the methods of SAW and fuzzy simple additive weighting (FSAW) are the MCDM methods that used for weight determinations and preferences. Churchman et al., (4) were the first research utilized the SAW method to cope with the portfolio selection problem. This method is also known as a weighted linear combination or scoring method. It is simple and the most often method used multi- attribute decision technique. The method is

Cloud Forensics Issues and Opportunities

Abstract: Cloud computing technology is a rapidly growing field of study, which relies on sharing computing resources rather than having local servers or personal devices to handle applications. Most of the growth in this field is due to transfer of the traditional model of IT services to a novel model of cloud and the ubiquity of access to electronic and digital devices. Cloud computing posed a critical risk and challenges to digital investigators, but provides plenty of opportunities to investigators for improving the digital forensics. Moreover, cloud service providers and customers have yet to establish adequate forensic capabilities that could support investigations of criminal activities in the cloud. Notwithstanding the cloud presents some promising technical and economic benefits, users still resist to use cloud mainly due to security issues because it poses a challenge in doing cloud forensic investigations. Regarding this some research has been done, which propose solutions in doing forensic investigation. In this review paper, we take the first step towards reviewing the cloud forensics works that have been done by other researchers, and then do some discussion and analysis based on our findings to consider the opportunities and challenges confront the cloud forensics based on our findings.

An Intelligent Traffic Light Monitor System using an Adaptive Associative Memory

Abstract: The traffic in urban areas is mainly regularized by traffic lights, which may contribute to the unnecessary long waiting times for vehicles if not efficiently configured. This inefficient configuration is unfortunately still the case in a lot of urban areas, where most of the traffic lights are based on a 'fixed cycle' protocol. To improve the traffic light configuration, this paper proposed monitoring system to be as an additional component (or additional subsystem) to the intelligent traffic light system, this component will be able to determine three street cases (empty street case, normal street case and crowded street case) by using small associative memory. The proposed monitoring system is working in two phases: training phase and recognition phase. The experiments presented promising results when the proposed approach was applied by using a program to monitor one intersection in Penang Island in Malaysia. The program could determine all street cases with different weather conditions depending on the stream of images, which are extracted from the streets video cameras. In addition, the observations which are pointed out to the proposed approach show a high flexibility to learn all the street cases using a few training images, thus the adaptation to any intersection can be done quickly.

Maximizing Productivity Using CRM Within the Context of M-Commerce

Abstract: One of the major subjects in information technology which has an outstanding influence in this field and in marketing and management area is mobile commerce. It is a key concept for variety of businesses. However, it has not fulfilled the expectations. This paper tackles the problems of mobile commerce in three separate approaches. First, it emphasizes the relative significance of customer relationship management and its relationship with mobile commerce. Second, it illustrates the ways of amplifying E-loyalty of the clients within small and medium enterprises. Eventually, the positive relationship among these, three concepts will be discussed. M-Commerce constitutes a substantial future market worldwide. This paper argues that businesses should strengthen and enhance loyalty as well as e-loyalty and M-Commerce activities, to better obtain the customers toward wireless marketing and customer relationship pathways. Moreover to get the extreme profitability businesses must generate value for consumers in a way that is different from what they get used to prior to the latest version of services from the businesses. This paper, introduces a new area of doing business with the assistance of CRM and some evaluators to grasp loyalty under the context of mobile commerce. Furthermore, businesses should consider consumer’s willingness to use successful features of M-Commerce. While performing the project, we expect to achieve productivity and reputation to the organization.

Finding Factors Impacting Productivity in Software Development Project Using Structured Equation Modelling

Abstract: The size of international software industry is over $1000bn. Total revenue earned by the Indian software industry in year 2005 was $30bn and which is expected to grow. The price quoted by vendors to its customers and the rate of the customer service is dependent on the productivity of the project. Given the fact that software development complexity is on an ever-increasing curve, it becomes critical to tackle the issues that influence the productivity levels of the project teams involved. Identification of factors as either aiding or hindering productivity enables management to take steps to encourage the positive influences and to eliminate the negative ones. Hence it is important to understand the factors affecting productivity and how these factors affect productivity when they are present in tandem. Hence this report aims to develop a model using structured equation modelling to find important factors affecting productivity and their impact on productivity. This paper is a further improvement on the paper “Maximizing Productivity by Controlling Influencing Factors and Commercial Software Development”, by Mohapatra, S. The authors expect to come out with a ready model for productivity which can help any software development team in allocating resources to achieve maximum output. The Methodology used for this primary research is collection of data from project and delivery managers across three Indian IT majors and analysing that data employing SEM using a computer aided tool. Results showed that the best fit model consisting of important factors like experience of project team in technology and domain, training for the technology platform to be worked on and domain of work, client support and various other software testing tools availability helps in increasing productivity.