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Volume 3, Issue 2 (9-2016)
Volume 3, Issue 2 (9-2016)
Abstract
Background and Aim: The utilization of technology acceptance model is one of the ways for perceiving the users' attitudes, and this research utilizes it to investigate the factors affecting the students' encouragement to use the social network sites in order to determine which factors encourage the students to use the social network sites as a virtual learning network.
Methods: This research is applied in terms of objective and is among the structural equation modeling-partial least square studies. A questionnaire is designed based on conceptual model after investigating the relevant articles and extracting the possible components, and it is then distributed among students, and finally the analysis is done on collected questionnaires.
Results: The data analysis results indicate the indirect impact of perceived usefulness, perceived ease of use, and perceived complementarity, and the direct impact of attitude towards using the online social network sites and perceived enjoyment on the students' intention to use the social network sites.
Conclusion: The results of this research provide the useful insight for university authorities in local education industry to utilize the social network sites in order to enhance the students' learning effectiveness by perceiving these factors. This study identifies the variables which can affect the development of educational space and investigates the conducted studies on determinates of students' encouragement to use of social networks as e-learning networks, and finally provides an applied comprehensive model by combination of these collected factors. Furthermore, a new research can be conducted on factors affecting the users' encouragement to use social networks for education.
Mahdi Farmani, Mohammad Ghaffari, Mostafa Zandi Nasab,
Volume 6, Issue 1 (4-2019)
Volume 6, Issue 1 (4-2019)
Abstract
Background and Aim: Managing the experience the user has in dealing with the website can play a significant role in improvement of a longer and more valuable relationship. One of the new technologies that can play a role in pleasant, enjoyable and effective experience of the users is gamification. Because this technology transforms every day, repetitive, and formal activities into exciting, challenging and entertaining experiences with the rules of the game and makes a different experience for users; also, provides the intention to use and advice to others. Therefore, the purpose of this study is to Digi Kala website features analysis in the field of gamification focusing on the roles of the mediator of experience and attitude of users and impact of the antecedents on intention to use and word of mouth intention
Methods: This research is applied in terms of purpose and is descriptive in terms of method. The statistical population of the study consisted of all users of Digi Kala online store, which in the period of data collection in July, 2018 were users of this website, and 294 samples were collected by sampling method. The main tool for collecting data was a questionnaire. To analyze and confirm the validity of research, construct validity and convergent validity were investigated. Cronbach's alpha coefficient was used to assess the reliability of the questionnaire. SPSS and LISREL software were used to analyze the data.
Results: All the research hypotheses were approved except for the second hypothesis.
Conclusion: The results of the research show that service quality, system quality and information quality on Digi Kala website affect user experience and user experience on Digi Kala website affects the user's attitude toward it. Also, the user's attitude towards Digi Kala website affects the intention to use and word of mouth intention.
Soheila Shirezhian, Seyed Mehdi Mirmehdi,
Volume 12, Issue 1 (5-2025)
Volume 12, Issue 1 (5-2025)
Abstract
Introduction
In recent years, advancements in technology, particularly in artificial intelligence, have significantly transformed how customers interact with businesses. One of the most prominent manifestations of this transformation is the emergence of chatbots as intelligent digital agents in marketing and customer service. Chatbots are AI-powered programs capable of responding to user inquiries through text or voice interactions, playing a crucial role in enhancing the efficiency of customer-organization communication. These tools enable companies to provide 24/7 services, reduce response times, increase customer loyalty, and save human resources. Unlike human agents, chatbots are unaffected by factors such as fatigue or holidays, ensuring constant availability. However, traditional customer service channels like email, websites, or phone calls remain popular among some customers.
In the retail sector, chatbots facilitate effective customer-brand interactions by offering convenience, flexibility, and easy access. They streamline the online shopping process by providing quick responses and guiding users, creating a seamless and satisfying experience while addressing the impersonal nature of e-commerce. Recent advancements in natural language processing have enabled chatbots to perform complex tasks, such as analyzing customer preferences and delivering personalized responses. These capabilities, combined with the widespread use of messaging platforms, have driven the growth of the chatbot industry. Nevertheless, concerns like data security and privacy pose significant barriers to widespread adoption, requiring careful consideration from system designers. This study, grounded in the Technology Acceptance Model, examines factors such as trust, personal innovativeness, ease of use, social influence, and hedonic motivation to understand the reasons behind users’ acceptance or rejection of chatbots.
Methods and Materoal
This study adopts a quantitative approach with an applied objective, utilizing a descriptive-survey design. The target population consists of Iranian users with experience using AI-based chatbots in online customer service platforms, such as websites, apps, or messaging services. Inclusion criteria required participants to have used at least one service-oriented chatbot and to be familiar with digital tools. Exclusion criteria included incomplete questionnaires, lack of actual chatbot experience, or use of chatbots for non-customer-service purposes (e.g., entertainment or language learning). To enhance accuracy and minimize bias, the influence of the chatbot’s application domain (e.g., retail, banking, education, or healthcare) was analyzed using variance analysis and control of contextual variables.
Data were collected through three primary methods: documentary studies, electronic resources, and field research. The data collection tool was a questionnaire based on a 5-point Likert scale (ranging from “strongly disagree” to “strongly agree”), measuring variables such as trust, hedonic motivation, social influence, personal innovativeness, perceived usefulness, ease of use, attitude, and intention to use. The questionnaire was designed based on standardized scales from prior research, and its content validity was confirmed by experts.
Resultss and Discussion
The findings indicate that trust, personal innovativeness, and ease of use significantly influence the perceived usefulness of chatbots. Trust enhances perceived usefulness by providing accurate and prompt responses. Personal innovativeness strengthens this perception by aligning chatbots with users’ needs, while ease of use, by simplifying interactions, positively affects both perceived usefulness and users’ attitudes. Both perceived usefulness and positive attitudes directly increase the intention to use chatbots. However, social influence and hedonic motivation did not show a significant impact on perceived usefulness, possibly due to customers’ preference for traditional channels or the functional focus of chatbots over entertainment.
Conclusion
This study reveals that trust, personal innovativeness, and ease of use are critical drivers of chatbot adoption. Trust, fostered through reliable and swift responses, enhances the perception of chatbots’ usefulness. Personal innovativeness aligns chatbot functionalities with users’ creative needs, further boosting this perception. Ease of use simplifies interactions, fostering positive attitudes and increasing the intention to use chatbots. The lack of significant impact from social influence may stem from customers’ preference for traditional channels like email or phone calls. Similarly, hedonic motivation’s limited effect could be attributed to the service-oriented nature of chatbots, which prioritizes efficiency over enjoyment.
Chatbots, by automating routine tasks, offering predictive analytics, and enhancing customer experiences, serve as innovative tools in digital services. However, challenges such as data security and privacy concerns remain barriers to broader adoption. Designing user-friendly and trustworthy chatbots can enhance their acceptance and improve the digital customer experience. This study recommends further research on non-users and environmental factors that may hinder the impact of social influence and hedonic motivation to better understand adoption barriers.
In recent years, advancements in technology, particularly in artificial intelligence, have significantly transformed how customers interact with businesses. One of the most prominent manifestations of this transformation is the emergence of chatbots as intelligent digital agents in marketing and customer service. Chatbots are AI-powered programs capable of responding to user inquiries through text or voice interactions, playing a crucial role in enhancing the efficiency of customer-organization communication. These tools enable companies to provide 24/7 services, reduce response times, increase customer loyalty, and save human resources. Unlike human agents, chatbots are unaffected by factors such as fatigue or holidays, ensuring constant availability. However, traditional customer service channels like email, websites, or phone calls remain popular among some customers.
In the retail sector, chatbots facilitate effective customer-brand interactions by offering convenience, flexibility, and easy access. They streamline the online shopping process by providing quick responses and guiding users, creating a seamless and satisfying experience while addressing the impersonal nature of e-commerce. Recent advancements in natural language processing have enabled chatbots to perform complex tasks, such as analyzing customer preferences and delivering personalized responses. These capabilities, combined with the widespread use of messaging platforms, have driven the growth of the chatbot industry. Nevertheless, concerns like data security and privacy pose significant barriers to widespread adoption, requiring careful consideration from system designers. This study, grounded in the Technology Acceptance Model, examines factors such as trust, personal innovativeness, ease of use, social influence, and hedonic motivation to understand the reasons behind users’ acceptance or rejection of chatbots.
Methods and Materoal
This study adopts a quantitative approach with an applied objective, utilizing a descriptive-survey design. The target population consists of Iranian users with experience using AI-based chatbots in online customer service platforms, such as websites, apps, or messaging services. Inclusion criteria required participants to have used at least one service-oriented chatbot and to be familiar with digital tools. Exclusion criteria included incomplete questionnaires, lack of actual chatbot experience, or use of chatbots for non-customer-service purposes (e.g., entertainment or language learning). To enhance accuracy and minimize bias, the influence of the chatbot’s application domain (e.g., retail, banking, education, or healthcare) was analyzed using variance analysis and control of contextual variables.
Data were collected through three primary methods: documentary studies, electronic resources, and field research. The data collection tool was a questionnaire based on a 5-point Likert scale (ranging from “strongly disagree” to “strongly agree”), measuring variables such as trust, hedonic motivation, social influence, personal innovativeness, perceived usefulness, ease of use, attitude, and intention to use. The questionnaire was designed based on standardized scales from prior research, and its content validity was confirmed by experts.
Resultss and Discussion
The findings indicate that trust, personal innovativeness, and ease of use significantly influence the perceived usefulness of chatbots. Trust enhances perceived usefulness by providing accurate and prompt responses. Personal innovativeness strengthens this perception by aligning chatbots with users’ needs, while ease of use, by simplifying interactions, positively affects both perceived usefulness and users’ attitudes. Both perceived usefulness and positive attitudes directly increase the intention to use chatbots. However, social influence and hedonic motivation did not show a significant impact on perceived usefulness, possibly due to customers’ preference for traditional channels or the functional focus of chatbots over entertainment.
Conclusion
This study reveals that trust, personal innovativeness, and ease of use are critical drivers of chatbot adoption. Trust, fostered through reliable and swift responses, enhances the perception of chatbots’ usefulness. Personal innovativeness aligns chatbot functionalities with users’ creative needs, further boosting this perception. Ease of use simplifies interactions, fostering positive attitudes and increasing the intention to use chatbots. The lack of significant impact from social influence may stem from customers’ preference for traditional channels like email or phone calls. Similarly, hedonic motivation’s limited effect could be attributed to the service-oriented nature of chatbots, which prioritizes efficiency over enjoyment.
Chatbots, by automating routine tasks, offering predictive analytics, and enhancing customer experiences, serve as innovative tools in digital services. However, challenges such as data security and privacy concerns remain barriers to broader adoption. Designing user-friendly and trustworthy chatbots can enhance their acceptance and improve the digital customer experience. This study recommends further research on non-users and environmental factors that may hinder the impact of social influence and hedonic motivation to better understand adoption barriers.
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