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

Sustainable R&D portfolio assessment.

Research and development portfolio management is traditionally technologically and financially dominated, with little or no attention to the sustainable focus, which represents the triple bottom line: not only financial (and technical) issues but also human and environmental values. This is mainly due to the lack of quantified and reliable data on the human aspects of product/service development: usability, ecology, ethics, product experience, perceived quality etc. Even if these data are available, then consistent decision support tools are not ready available. Based on the findings from an industry review, we developed a DEA model that permits to support strategic R&D portfolio management. We underscore the usability of this approach with real life examples from two different industries: consumables and materials manufacturing (polymers).R&D portfolio management; Data envelopment analysis; Sustainable R&D;

B2C quality evaluation factors from Jordanian consumer perspective

The consumer of B2C business plays a significant role in sustaining B2C business companies. However, many companies neglect to incorporate consumers need in their websites developments, resulting unachieved business objectives.Companies must identify consumers’ factors in their websites developments so that the B2C websites receive higher hits. This study aims to investigate and identify the B2C quality factors from the consumers’ perspective, to rank these factors according to their importance, and to categorize these factors into meaningful groups.Methodology from three phases has been conducted to achieve the objectives.These phases include identification, ranking, and categorization of factors. Data was gathered from the literature and analyzed using SPSS. Simple descriptive statistics such as mean and frequency were used to rank the quality factors. In addition, factor analysis was used to categorize the quality factors. Seventeen quality factors were found to be important from the consumers’ perspective. The seventeen quality factors were further categorized into three groups: E-usage, E-information, and E- services. These categories will be used to construct quality evaluation framework in the next stage of the study

Multiple Criteria Decision Support System for Customer Segmentation using a Sorting Outranking Method

[EN] For companies, customer segmentation plays a key role in improving supply chain management by implementing appropriate marketing strategies. The objectives of this research are to design and validate a multicriteria model to support decision making for customer segmentation in a business to business context. First, the model based on the transactional customer behaviour is extended by a hierarchy with three main criteria: Recency, Frequency and Monetary (RFM), customer collaboration and growth rates. Customer collaboration includes quota compliance, variety of products and customer commitment to sustainability (reverse logistics and shared information). Second, the Global Local Net Flow Sorting (GLNF sorting) algorithm is implemented and validated using real company data to classify 8,157 customers of a multinational healthcare company. Third, the SILS quality indicator has been implemented and validated to assess the quality of preference-ordered customer groups and its parameters have been adapted for contexts with thousands of alternatives. The results are also compared with an alternative model based on data mining (K-means). The multicriteria system proposed allows to segment thousands of customers in ordered categories by preferences according to company strategies. The segments generated are more homogeneous, robust and understandable by managers than those from alternative methods. These advantages represent a relevant contribution to automating supply chain management while providing detailed analysis tools for decision making.Barrera, F.; Segura Maroto, M.; Maroto Álvarez, MC. (2024). Multiple Criteria Decision Support System for Customer Segmentation using a Sorting Outranking Method. Expert Systems with Applications. 238:1-17. https://doi.org/10.1016/j.eswa.2023.12231011723

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

A fuzzy analytic hierarchy process model to evaluate logistics service expectations and delivery methods in last-mile delivery in Brazil

Nowadays, postal services and third-party logistics services (3PL) have been pressured by the increasing demand for delivery services. Therefore, they need to improve their last-mile delivery strategies to meet customers’ expectations. This paper aims to investigate how logistics service expectations affect the delivery process in urban areas using a multiple-criteria decision support system based on the Fuzzy Analytic Hierarchy Process (FAHP). We developed a decision-making model employing six criteria and five delivery methods indicated in the literature and collected information from 27 experts working in academia and local and multinational third-party logistics providers in Brazil to validate this model. The results indicate that cost (21.4%) and tracking and tracing (19.3%) are the most important two criteria in the decision model, and the best delivery methods are smart lockers (21.8%) followed by small trucks (21.3%). Our results suggest that service expectations regarding last-mile delivery are aligned with extensive use of road transport and the increase in e-commerce sales can raise greenhouse gas emissions and compromise the environment in urban areas

AN ONTOLOGY-BASED KNOWLEDGE REPRESENTATION USING ANALYTIC HIERARCHY PROCESS FOR ENHANCING SELECTION OF PRODUCT PREFERENCES

Product alternatives, which emerges from large number of websites during searching, accounts for some hesitation experienced by customers in selecting satisfying product. As a result, making useful decision with many trade-off considerations becomes a major cause of such problem. Several approaches have been employed for product selection such as, fuzzy logic, Neuro-fuzzy, and weighted least square. However, these could not solve the problem of inconsistency and irrelevant judgement that occur in decision making. In this study, Ontology-based Analytic Hierarchy Process (AHP) was used for enhancing selection of product preferences. The model involved three fundamental components: product gathering, selection and decision making. Ontology Web Language (OWL) was utilized to define ontology in expressing product information gathering in a standard and structured manner for the purpose of interoperability while AHP was employed in making optimal choices. The procedure accepts customers’ perspectives as inputs which are classified into criteria and sub-criteria. Owl was created to foster customers’ interaction and priority estimation tool for AHP in order to generate the consistency ratio of individual judgements. The model was benchmarked with Geometric Mean (GM), Eigenvector (EV), Normalized Column Sum (NCS) Weighted Least Square (WLS) and Fuzzy Preference Programming (FPP). First and second order total deviations and violation rate were the performance parameters evaluation with AHP. The results showed that the minimum and maximum units of products are 2,452and 3,574, respectively. These implied that the proposed model was consistent, relevant and reflected a non-violation of judgment in selection of product preferences. &nbsp

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

Framework de Tomada de Decisão para Last-Mile Sustentável

The e-commerce growth, propelled by factors like globalization, urbanization, or the COVID-19 pandemic, has been raising the demand for logistic activities. This affects the entire supply chain, especially the last-mile, as it is considered the most ineffective part of the supply chain and a source of negative externalities. Although various solutions promise to alleviate these problems, understanding them and selecting the best has proven to be difficult due to conflicting criteria, multiple perspectives, and trade-offs. The vicissitudes of complex and sensitive urban contexts like historic centers also contribute to this difficulty. This work contributes an integrated framework that may assist the involved stakeholders in decision-making. To this end, this work is based on a three-part methodology. The extensive systematic literature review developed provided an integrated overview of this fragmented research area. This review confirmed the multidisciplinary nature of the topic, as there is an increasing number of studies conducted under very different perspectives. Furthermore, it was found that the economic dimension is the most considered; the most polluting countries contributed little to the research; and the solutions involve trade-offs. The literature review supported the definition of the hierarchical model that structures last-mile operations in historic centers. This model was evaluated by interviewing a group of experts. After integrating the experts’ feedback, the model was quantified by the same experts according to an AHP-TOPSIS approach. This quantification had as a case study the historic center of Porto, Portugal. The experts considered the three sustainability dimensions identically important. Air pollution was the most valued sub-criterion whereas Visual pollution was the least. All last-mile solutions considered in the model achieved similar results, therefore suggesting a combined distribution strategy. Nevertheless, the use of parcel lockers is the most favorable solution and seems adequate in Porto’s historic center.O crescimento do e-commerce, impulsionado por fatores como a globalização, a urbanização ou a pandemia de COVID-19, tem aumentado a procura por atividades logísticas. Isto afeta toda a cadeia de abastecimento, principalmente a última-milha, por ser considerada a parte mais ineficaz da cadeia de abastecimento e uma fonte de externalidades negativas. Embora existam várias soluções que prometem aliviar estes problemas, entendêlas e selecionar a melhor tem se provado difícil devido a critérios conflituosos, múltiplas perspetivas e trade-offs. As vicissitudes de contextos urbanos complexos e sensíveis como os centros históricos também contribuem para essa dificuldade. Este trabalho contribui um framework integrado que pode auxiliar os stakeholders envolvidos na tomada de decisão. Para este fim, este trabalho é baseado numa metodologia composta por três partes. A extensa revisão sistemática da literatura desenvolvida forneceu uma visão integrada desta área de investigação fragmentada. Esta revisão confirmou o caráter multidisciplinar do tema, pois há um número crescente de estudos conduzidos sob perspetivas muito diferentes. Além disso, verificou-se que a dimensão económica é a mais considerada; os países mais poluentes contribuíram pouco para a pesquisa; e as soluções envolvem trade-offs. A revisão da literatura suportou a definição do modelo hierárquico que estrutura as operações de última-milha em centros históricos. Este modelo foi avaliado entrevistando um grupo de experts. Após a integração do feedback dos experts, o modelo foi quantificado pelos mesmos de acordo com uma abordagem AHP-TOPSIS. Esta quantificação teve como caso de estudo o centro histórico do Porto, Portugal. Os experts consideraram as três dimensões da sustentabilidade identicamente importantes. O subcritério relativo à poluição atmosférica foi o mais valorizado, enquanto o menos foi o relativo à poluição visual. Todas as soluções de últimamilha consideradas no modelo alcançaram resultados semelhantes, sugerindo uma estratégia de distribuição combinada. No entanto, o uso de parcel lockers é a solução mais favorável e é aparentemente adequada para o centro histórico do Porto

Prioritizing Key Success Factor of the Internet of Things Application in Tourism Enterprise

Purpose: The objective of this study is to explore critical success factors in Internet of Things applying and their importance level in tourism companies using the fuzzy theory.   Theoretical framework: This paper uses the TOE framework and adds a customer security variable. Therefore, the framework includes four variables technology, organization, environment, and customer security (TOEC) which are the four aspects of this research framework.   Design/methodology/approach: By integrating FAHP and FAHP extension methods, the study finds that the critical success factors for IoT application in tourism companies, including technology, organization, environment, and customer security.   Findings: The result show that, the first ranking is organization factor, the second ranking belongs to technology, customer securities come with third ranking, and the fourth ranking is environment. This result also indicates that IT Human resources, Technology infrastructure, Top management support, and organization readiness are the prioritized critical success factors for IoT applications in tourism companies.   Research, Practical & Social implications: This paper contributes to the understanding of IoT, its features and highlights the importance of new technology and solutions in tourism industry.   Originality/value: This study fills the gap in the TEO model by adding the factor of customer securities so-called TEOC model