A consumer perspective e-commerce websites evaluation model

Existing website evaluation methods have some weaknesses such as neglecting consumer criteria in their evaluation, being unable to deal with qualitative criteria, and involving complex weight and score calculations. This research aims to develop a hybrid consumer-oriented e-commerce website evaluation model based on the Fuzzy Analytical Hierarchy Process (FAHP) and the Hardmard Method (HM). Four phases were involved in developing the model: requirements identification, empirical study, model construction, and model confirmation. Requirements identification and empirical study were to identify critical web-design criteria and gather online consumers' preferences. Data, collected from 152 Malaysian consumers using online questionnaires, were used to identify critical e-commerce website features and scale of importance. The new evaluation model comprised of three components. First, the consumer evaluation criteria that consist of the important principles considered by consumers; second, the evaluation mechanisms that integrate FAHP and HM consisting of mathematical expressions that handle subjective judgments, new formulas to calculate the weight and score for each criterion; and third, the evaluation procedures consisting of activities that comprise of goal establishment, document preparation, and identification of website performance. The model was examined by six experts and applied to four case studies. The results show that the new model is practical, and appropriate to evaluate e-commerce websites from consumers' perspectives, and is able to calculate weights and scores for qualitative criteria in a simple way. In addition, it is able to assist decision-makers to make decisions in a measured objective way. The model also contributes new knowledge to the software evaluation fiel

Handbook of Computational Intelligence in Manufacturing and Production Management

Artificial intelligence (AI) is simply a way of providing a computer or a machine to think intelligently like human beings. Since human intelligence is a complex abstraction, scientists have only recently began to understand and make certain assumptions on how people think and to apply these assumptions in order to design AI programs. It is a vast knowledge base discipline that covers reasoning, machine learning, planning, intelligent search, and perception building. Traditional AI had the limitations to meet the increasing demand of search, optimization, and machine learning in the areas of large, biological, and commercial database information systems and management of factory automation for different industries such as power, automobile, aerospace, and chemical plants. The drawbacks of classical AI became more pronounced due to successive failures of the decade long Japanese project on fifth generation computing machines. The limitation of traditional AI gave rise to development of new computational methods in various applications of engineering and management problems. As a result, these computational techniques emerged as a new discipline called computational intelligence (CI)

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

Automated Service Identification Methods: A Review

Service identification represents the first phase in service modelling, a necessary step in SOA. This research study reviewed and analyzed the issues related to automation issues of service identification. However, the importance of service identification methods’ (SIM) automation and their business alignment are emphasized in literature, reviewing existing service identification methods (SIMs) reveals the lack of business alignment, automation as challenging issues. We close the gap by proposing ASIF which relies on automating the SIMs’ steps to identify business aligned services based on business processes and business goals

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

Mathematical fuzzy logic (MFL) specifically targets many-valued logic and has significantly contributed to the logical foundations of fuzzy set theory (FST). It explores the computational and philosophical rationale behind the uncertainty due to imprecision in the backdrop of traditional mathematical logic. Since uncertainty is present in almost every real-world application, it is essential to develop novel approaches and tools for efficient processing. This book is the collection of the publications in the Special Issue “Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences”, which aims to cover theoretical and practical aspects of MFL and FST. Specifically, this book addresses several problems, such as:- Industrial optimization problems- Multi-criteria decision-making- Financial forecasting problems- Image processing- Educational data mining- Explainable artificial intelligence, etc

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Multiple-Criteria Decision Making

Decision-making on real-world problems, including individual process decisions, requires an appropriate and reliable decision support system. Fuzzy set theory, rough set theory, and neutrosophic set theory, which are MCDM techniques, are useful for modeling complex decision-making problems with imprecise, ambiguous, or vague data.This Special Issue, “Multiple Criteria Decision Making”, aims to incorporate recent developments in the area of the multi-criteria decision-making field. Topics include, but are not limited to:- MCDM optimization in engineering;- Environmental sustainability in engineering processes;- Multi-criteria production and logistics process planning;- New trends in multi-criteria evaluation of sustainable processes;- Multi-criteria decision making in strategic management based on sustainable criteria

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

An ANFIS-based compatibility scorecard for IoT integration in websites

Cyber-physical systems and Internet of Things (IoT) form two different levels of the vertical digital integration. Integration of websites with IoT-connected devices has compelled creation of new web design and development strategies where websites are designed keeping in mind the permutations of smart devices. The design should be seamless across different devices and the website design company or web designer should be well informed and aware of the different considerations for design with IoT interactions. In this work, we expound the effectiveness of IoT integration in website design. To realize an IoT-powered IT ecosystem as an essential technology for improving customer experience, a strength–weakness–opportunity–threat analysis is done. Further, with an intent to apprehend the integration support that an existing GUI front end may provide to a smart device, an ANFIS model is proposed to determine the compatibility of an e-commerce website for integration with IoT devices. A dataset of 600 e-commerce websites from.com domain is used to train and test the learning model. Seven features (page loading speed, broken links, browser compatibility, resolution, total size, privacy and security, and interface and typography) which impact the compatibility of IoT integration in websites have been used. Evaluation criteria for assigning score to each feature has been identified. Finally, the compatibility score, the IoTScoresite which evaluates the websites’ integration capabilities and support to IoT devices is generated by adding all the feature scores. The preliminary results generated using the prediction model clearly determine the worthiness of website for IoT integration