The full potential of e-learning, a trend that is of growing importance lately, will not be reaped unless the users fully utilize the system, triggering extensive research to be conducted in order to provide valuable insight on a myriad of variables influencing user acceptance in e-learning systems. The main purpose of the study is to determine the factors that affect the intention of users to use e-learning and to get results which can guide system developers and researchers. In accordance with this purpose, 203 studies investigating the e-learning acceptance of the users through the Technology Acceptance Model (TAM) were found in the literature. In those studies, variables which are suggested to determine Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) and results of related hypotheses are analyzed. Finally, a model is proposed. In this model, the most widely accepted hypotheses, affecting PU and PEOU according to the literature are included in the original TAM. As a result; it determines Self Efficacy-PEOU, Subjective Norm-PU, Self Efficacy-PU, Interaction-PU, Enjoyment-PEOU, Anxiety-PEOU, Enjoyment-PU, Compatibility-PU, Subjective Norm-PEOU and Interaction-PEOU as variables that have statistical significance in users’ PU and PEOU, respectively. Moreover, the study examines the relationship between the User Satisfaction and original TAM variables, and proposes the Acceptance and Satisfaction Model for E-Learning (ASME) as a model to best explain the dependent variables described above.

Tourism is a rapidly growing industry worldwide, and internet technologies are becoming increasingly important in that industry. Online hotel booking website (OHBW) has become an important tool in the marketing of hotel services. In this study, the factors affecting the trust perception of OHBW users were investigated. Data collected from 456 consumers using OHBWs were analysed using structural equation modelling. The results showed that reputation, security, ease of use and risk significantly affected the user's perception of trust. In addition, the perception of trust has a positive effect on customer loyalty. As a result, this study aims to provide useful findings to OHBW managers and researchers who want to increase customer trust and ensure their loyalty.

Supplier selection (SS), which is a critical stage of supply chain management (SCM), is no longer evaluated solely from the perspective of traditional criteria, due to increasing environmental problems and ethical concerns. In this study, a multidimensional approach including environmental, economic, social, and competency concepts was proposed to evaluate SS, and an integrated approach based on Best Worst Method (BWM) and fuzzy TODIM (an acronym in Portuguese of Interactive and Multi-criteria Decision Making) techniques was developed. In the developed approach, BWM was used to first obtain the importance level of the criteria and then to rank the suppliers with fuzzy TODIM. The proposed approach was tested on an automotive company in Turkey. The outcomes of the analysis revealed that the most important main criteria for SS are economic (0.377) and environmental criteria (0.290). In addition, the sub-criteria with the highest criteria weight were listed as product cost (0.120), on-time delivery (0.112), quality control (0.094), logistics costs (0.069), management commitment (0.054), and flexibility (0.054). The results of this study offer theoretical and practical outputs to companies that want to improve their SS process, selection of suppliers, and contributions of the researchers working on the topic.

Purpose: The aim of the proposed classification approach of potential market alternatives (CAPMA) is to provide exporting countries with a framework for identifying potential market opportunities for their products or services.Design/methodology/approach: In today's global market conditions, with competition increasing daily, companies, businesses and states must seek new markets at the national and international level. Target market selection is a strategic process that directly affects the success of an organization and can lead to important results in the short and long term. The process requires systematic research and digitization of data to analyse target markets.Findings: The study tested the proposed approach by analysing Turkey's potential markets for hazelnut exports and identifying new target markets. A significant part of Turkey's hazelnut exporting is confined to the European geography of Turkey, the leading country in hazelnut production and export. Twenty potential markets were evaluated on the basis of 11 criteria, and feasible alternatives were categorized into four classes. The study revealed that the USA, India, the United Kingdom and Japan were in the category of markets with the greatest potential for increasing exports (Dimension 1).Originality/value: This study has developed a novel approach that allows the comparison of the current market situation with potential market outcomes and creates an accurate classification of target markets.

Digital supply chains (DSCs) are value-driven and collaborative digital systems designed to generate business value for firms through various innovative technologies. Today, we are witnessing companies transitioning from traditional supply chain models to DSCs through digital technologies. The effective selection of digital suppliers during these digital transformation processes is a strategic research topic. Additionally, factors such as the proliferation of information and communication technologies, globalization, and the pandemic have contributed to the expansion of e-commerce platforms. In this rapid growth phase, identifying the right supplier is crucial for the success of e-commerce sites. This study aims to develop an innovative, integrated, and comprehensive decision-making methodology to assist e-commerce platforms in selecting appropriate suppliers for their DSCs. To achieve this, an extended fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method is tested, where criteria and alternative evaluations made by decision-makers (DMs) are characterized by interval-valued intuitionistic fuzzy numbers (IVIFNs). The proposed decision mechanism is tested on the DSS problem of an e-commerce platform specializing in household products. Findings of the application, which uses three experts’ opinion to evaluate four digital suppliers based on the seven criteria, are discussed to help e-commerce sites conduct the DSS process more effectively.