Identification of factors affecting consumers' intention to use autonomous delivery robots

The purpose of this study is to identify the factors affecting consumers' intentions to use autonomous delivery robots (ADRs) in Turkey. Within the scope of the study, the theoretical model of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was adopted, integrating core constructs such as performance expectancy, social influence, and hedonic motivation, along with psychological and individual variables such as trust in technology, perceived risk, price sensitivity, innovativeness, resistance to change, and technology anxiety. Thus, the consumer acceptance process of ADRs in the context of Turkey has been addressed with a multidimensional perspective. The research method was structured quantitatively. In the study, data collection was carried out through a survey method, and data were gathered via online platforms. In the survey form, scales adapted from previous studies and whose validity and reliability had been tested were included to measure all relevant variables. Convenience sampling was preferred as the sampling method. The sample of the research consisted of participants from various age, gender, and occupational groups across Turkey. Valid data were obtained from a total of 531 participants. This sample provides an important data set for analyzing consumer tendencies in an environment where ADRs have not yet become widespread in Turkey. In the analysis process, the validity and reliability of the scales were tested through exploratory and confirmatory factor analyses (EFA and CFA). Hypotheses were tested and relationships between variables were analyzed using structural equation modeling (SEM). The model's fit indices were generally found to be at acceptable and good fit levels. As a result, the findings of the research revealed that performance expectancy and social influence positively and significantly affect behavioral intention; on the other hand, hedonic motivation, innovativeness, price sensitivity, and technology anxiety do not have significant effects on behavioral intention. In addition, perceived risk and resistance to change were found to negatively and significantly affect behavioral intention, while trust in technology positively and strongly affects behavioral intention. These results are significant both in testing the validity of the theoretical model in the context of Turkey and in shedding light on strategic approaches to support the adoption of ADRs in a sectoral and managerial sense. For future studies, it is recommended to use longitudinal research designs and conduct cross-cultural comparative analyses. In particular, examining the mediating or moderating roles of variables such as technology anxiety, perceived risk, and trust through advanced analysis techniques can contribute to strengthening the contextual validity of the model. In addition, policy and practice recommendations to increase the adoption of autonomous delivery robots at the sectoral level are also important. At the end of the study, pilot projects and field tests to enhance consumer experiences, training and awareness campaigns to support user trust and acceptance, and strengthening cooperation between local governments and the private sector were suggested as important steps to be taken in this area. In this way, it will be possible to adopt a holistic and multi-stakeholder approach to both improve consumer acceptance and develop the technical infrastructure in developing countries like Turkey.