This study aims to determine the effects of the variables within the UTAUT 2 model on the intention to use a Fully Electric Car. In this context, data were collected through survey forms from 401 white-collar workers who are considered to have a higher economic status. Initially, validity and reliability analyses were conducted on the scales used in the Smart PLS program, and subsequently, the hypotheses were interpreted using the results obtained from structural equation modeling. In this study, it was found that effort expectancy, social influence, perceived ease of use, hedonic motivation, and habit had a positive and significant impact on the intention to use electric vehicles. Performance expectancy has a negative and significant effect on the intention to use electric cars, while price has no significant effect. It was determined that the intention to use electric vehicles was found to mediate the relationship between perceived ease of use and actual usage behavior. This research can offer significant contributions to literature, particularly by examining the influence of habit on behavioral intention and the effect of hedonic motivation on electric vehicle usage intention. By testing the UTAUT 2 model in the context of electric vehicle acceptance, this study supports the universality and applicability of the model to various technologies. Emphasizing the role of variables such as hedonic motivation and habit in electric vehicle acceptance adds a new dimension to the UTAUT 2 model. Thus, it makes an important contribution to technology acceptance research.

This study aims to develop and validate a scale measuring consumers’ attitudes towards social media influencers (SMIs). In this sense, the study population consisted of social media users who followed at least one social media influencer. The survey method was used as the data collection tool in the study. While creating the scale items, relevant literature as well as expressions and some sentences obtained from short interviews with consumers who use social media and follow at least one social media influencer were used. As part of the research, 821 surveys were accepted as valid and evaluated. After pretesting studies on a group of 258 people, the scale was retested with a new sample of 821 people. The skewness and kurtosis values were between +1.96 and -1.96. The sample had a normal distribution. The EFA analysis revealed that the scale item distribution was compatible with the pretest analysis. Although no random distribution was found with parallel analysis, Kaiser–Guttman analysis was also performed to control the distribution of random scales into their subdimensions. The EFA results showed that the developed scale provided appropriate values. KMO=0.896, Bartlett’s sphericity test=0.000, Bartlett’s<0.05, Cronbach’s alpha=0.889, AVE=0.585, and CR=0.934. As a result of CFA, the values for the goodness of fit were found to be appropriate (x2 (df)=3.144; p=0.000, RMSEA=0.051; CFI=0.994; GFI=0.990; SRMR=0.014; AVE=0.580; CR=0.933), and it was observed that there were no items below the factor value of 0.50. As a result of the invariance analysis, it was understood that the developed scale had invariance properties and was suitable for use with a large audience, as the ∆CFI value was less than 0.01 between both samples. The General Attitudes Scale towards social media influencers has a single factor and consists of six items. The factor loading values of the scale items ranged between 0.53 and 0.90. In this research, it was determined that social media influencers had a significant impact on the participants. The general attitudes of the participants as part of the study had a significant effect on their social media influencers.

A Social Media Influencer (SMI) is a new independent third party that uses social media to shape audience attitudes. SMIs are present on most digital media platforms such as Facebook, Instagram, Twitter and YouTube, and build their sphere of influence by sharing their experiences on a wide range of specific topics such as fitness, fashion, beauty, DIY, vacation, entertainment, etc. with their followers. While making these posts, SMI creates a desire in social media users who are interested in those topics to follow influencers with high influence. This is because similar topics are also of interest to social media users and they feel SMI as a reflection of themselves. Therefore, every behavior of the influencer attracts more attention. This situation makes the job of marketers and brands easier. Because instead of their efforts to reach the target audience by developing many strategies, there is the SMI who brings together potential buyers who have formed their own target audience. In addition, reaching SMIs for advertising deals is less costly than reaching classic influencers. The purpose of this study is to develop and validate a scale that can measure the effect of SMIs' attitudes and behaviors on consumer purchase intention. Accordingly, the population of the study consisted of social media users who follow at least one SMI. Questionnaire method was used as a data collection tool in the research. While creating the scale items, expressions and phrases obtained from short interviews with consumers who use social media and follow at least one SMI were utilized in addition to the relevant domestic and foreign literature. Within the scope of the research, 821 questionnaires were accepted as valid and evaluated. As a result of the Structural Equation Model (SEM) application, it was determined that there is a significant effect of SMI on the effect of purchase intention.

As globalization progresses, people and the environment are also increasingly burdened along supply chains. Green supply chain management practices are the best way for firms to minimize the negative impacts of their activities on the environment. The effect that makes you feel that you have adopted a sustainable perspective is only possible with green supply chain management practices. In addition, artificial intelligence has undoubtedly become one of the most important focal points for businesses that want to take advantage of new opportunities brought by technological developments and transformations. In this study, the general framework of the concept of green supply chain was created and a literature review was conducted of studies integrating artificial intelligence into green supply chain management. In the study, the concepts of "green supply chain management and artificial intelligence" were examined together, and bibliometric analysis was performed and the results were interpreted in order to reveal a panoramic view of the research area through prominent concepts, trends and citation analysis. With this study, it is aimed to shed light on future studies by bringing together the studies carried out in recent years on the integration process of artificial intelligence into green supply chain management. In addition, the study aims to raise awareness of businesses operating in Turkey about green supply chain practices, to develop a positive perspective on artificial intelligence applications, which are digital transformations, and to encourage them to transition to sectoral practices.

Nutritional supplement use has emerged as an important health-related consumption behavior in digitalized environments, with implications for both public health and individual well-being. While prior research has largely focused on general populations, limited attention has been paid to how occupational pressures and digital information contexts jointly shape supplement-related decision-making among highly educated professionals. Addressing this gap, this study examines the behavioral determinants of nutritional supplement use among academics within an intention–behavior framework. Using survey data collected from academic professionals, the proposed model was tested through confirmatory factor analysis and structural equation modeling. The findings reveal that health motivation and academic work stress significantly predict supplement use intention, which, in turn, strongly influences actual consumption behavior. In contrast, digital health literacy and digital marketing exposure do not exert significant direct effects on usage intention. These results provide theoretical insight into the boundary conditions of informational determinants in consumer behavior models, suggesting that intrinsic motivation and contextual stressors may play a more dominant role than digital influences among highly educated consumers. From a practical perspective, the findings highlight the importance of addressing stress-related health coping mechanisms and motivation-driven behaviors in promoting informed supplement use.