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Abolghasem Karimi, Alireza Rousta, Majid Ahmadi, Saeid Daniali,
Volume 11, Issue 1 (6-2024)
Volume 11, Issue 1 (6-2024)
Abstract
Information search strategies change rapidly in continuous mode, and successive searches gradually teach the user what can be retrieved inside the system. Users must be able to interact with the system appropriately to achieve their information needs. The information revolution is not a new issue, but understanding information seeking behavior is important and vital in this era. In future projects, extraordinary efforts should be made to create intelligent systems. Therefore, success or failure in this matter is not the responsibility of the new information technology, but it requires awareness of human needs and his behavior to obtain information. Therefore, in the companies based in Pardis Technology Park, according to the technology-oriented approach and innovation, it is necessary to pay attention to the issue of market information learning and joint innovative capacities to improve the organization's performance. Generally, because the environment and technology are constantly and rapidly changing, and specifically, the demographic characteristics of customers and their expectations undergo changes and transformations, Certainly, in order to have a successful presence in the national and international arena and their dynamism, as well as greater adaptation to environmental changes, these companies should aim to activate their potentials through improving the performance of the organization. In fact, this research seeks to answer the question of what is the role of explaining the effect of market information learning ability and joint innovative capacities on the organization's performance with an information approach?
Methods and Materoal
This research is based on the applied purpose and according to the descriptive type of correlation, according to the model, we should use the structural equation modeling method. The statistical community of the research is top and middle managers of companies that are members of Pardis Technology Park in Tehran. Using Cochran's formula, 384 people were selected as a sample and 400 questionnaires were distributed by available sampling method and 387 questionnaires were collected in 50 companies. The data collection method of this research was done by library method and using books and articles, and questionnaire was used in the field method. To measure the variable of market information learning ability with 7 items, internal learning ability with 10 items, relational learning ability with 7 items and administrative innovation with 6 items from Teece et al., 1997; Weerawardena et al., 2015; and to measure the variable of service innovation with 4 items and organization performance with 5 items from Thakur & Hale, 2013 questionnaire; and to measure the variable of shared innovative capacities with 3 items, Oly Ndubisi et al., 2019 questionnaire was used.
Resultss and Discussion
Demographic characteristics of the sample include gender, age and education. In the method of structural equation modeling, the fit of the model is checked to ensure the accuracy and correctness of the findings before implementing the model to test the hypotheses. Also, Cronbach's alpha indices of combined reliability of average variance were extracted and the coefficient of determination was used to measure the model. The average values of the extracted variance of all 7 model structures are at the optimal level. The amount of Cronbach's alpha and composite reliability is for all model constructs, so the questionnaire has good and acceptable reliability. The amount of Cronbach's alpha and combined reliability for all model constructs is more than 0/7, so the questionnaire has acceptable and acceptable reliability. The value of R2 for the endogenous constructs of the research confirms the appropriateness of the fit of the structural model. The results of the Q2 criterion for the endogenous structure indicate the appropriate predictive power of the model regarding the endogenous constructs of the research and indicate that the fitting model has appropriate and favorable predictive power. Confirmatory factor analysis is used to measure the reliability and validity of the measurement scale. The final results of the confirmatory factor analysis are reported in Table No. 4. Factor loadings greater than 5% have good validity. Figure 1, shows the confirmatory factor analysis for the whole model. Figure 2, shows the analysis of significant coefficients for the whole model. Since all the numbers on the paths are above 1/96%, it indicates the significance of the paths, the appropriateness of the structural model and the confirmation of all research hypotheses. The GOF criterion was used for the overall fit of the model, Since three values of 0/01, 0/25 and 0/36 are determined as weak, medium and strong values for GOF and on the other hand, the coefficient is in a good condition (0/598), Therefore, the results show that the fit of the model in the statistical population of the research is appropriate. Also, the t-test for all hypotheses is greater than 1/96. Therefore, with 95% confidence, the relationship between the variables is significant.
Conclusion
The present research was done by explaining the effect of market information learning ability and joint innovative capacities on the performance of the organization with an information approach. Organizational performance is a valuable activity at the community level. It also has a fundamental role in the economy and is considered as a useful tool to achieve economic growth and benefits of the organization. In fact, it is like an umbrella that includes all concepts related to the success and activities of the entire organization. In this research, 7 hypotheses were tested and the results of the hypothesis analysis indicate that the ability to learn market information plays a role in the internal learning ability (0/945) and the ability to learn interfaces (0/785) and internal learning ability (0/220) and interface learning ability (0/662) have been effective on administrative innovation. Also, administrative innovation has had an effect on the organization's performance (0/488), and shared innovative capacities have a significant effect on service innovation (0/904). Finally, service innovation has played a role in the organization's performance (0/590).
Methods and Materoal
This research is based on the applied purpose and according to the descriptive type of correlation, according to the model, we should use the structural equation modeling method. The statistical community of the research is top and middle managers of companies that are members of Pardis Technology Park in Tehran. Using Cochran's formula, 384 people were selected as a sample and 400 questionnaires were distributed by available sampling method and 387 questionnaires were collected in 50 companies. The data collection method of this research was done by library method and using books and articles, and questionnaire was used in the field method. To measure the variable of market information learning ability with 7 items, internal learning ability with 10 items, relational learning ability with 7 items and administrative innovation with 6 items from Teece et al., 1997; Weerawardena et al., 2015; and to measure the variable of service innovation with 4 items and organization performance with 5 items from Thakur & Hale, 2013 questionnaire; and to measure the variable of shared innovative capacities with 3 items, Oly Ndubisi et al., 2019 questionnaire was used.
Resultss and Discussion
Demographic characteristics of the sample include gender, age and education. In the method of structural equation modeling, the fit of the model is checked to ensure the accuracy and correctness of the findings before implementing the model to test the hypotheses. Also, Cronbach's alpha indices of combined reliability of average variance were extracted and the coefficient of determination was used to measure the model. The average values of the extracted variance of all 7 model structures are at the optimal level. The amount of Cronbach's alpha and composite reliability is for all model constructs, so the questionnaire has good and acceptable reliability. The amount of Cronbach's alpha and combined reliability for all model constructs is more than 0/7, so the questionnaire has acceptable and acceptable reliability. The value of R2 for the endogenous constructs of the research confirms the appropriateness of the fit of the structural model. The results of the Q2 criterion for the endogenous structure indicate the appropriate predictive power of the model regarding the endogenous constructs of the research and indicate that the fitting model has appropriate and favorable predictive power. Confirmatory factor analysis is used to measure the reliability and validity of the measurement scale. The final results of the confirmatory factor analysis are reported in Table No. 4. Factor loadings greater than 5% have good validity. Figure 1, shows the confirmatory factor analysis for the whole model. Figure 2, shows the analysis of significant coefficients for the whole model. Since all the numbers on the paths are above 1/96%, it indicates the significance of the paths, the appropriateness of the structural model and the confirmation of all research hypotheses. The GOF criterion was used for the overall fit of the model, Since three values of 0/01, 0/25 and 0/36 are determined as weak, medium and strong values for GOF and on the other hand, the coefficient is in a good condition (0/598), Therefore, the results show that the fit of the model in the statistical population of the research is appropriate. Also, the t-test for all hypotheses is greater than 1/96. Therefore, with 95% confidence, the relationship between the variables is significant.
Conclusion
The present research was done by explaining the effect of market information learning ability and joint innovative capacities on the performance of the organization with an information approach. Organizational performance is a valuable activity at the community level. It also has a fundamental role in the economy and is considered as a useful tool to achieve economic growth and benefits of the organization. In fact, it is like an umbrella that includes all concepts related to the success and activities of the entire organization. In this research, 7 hypotheses were tested and the results of the hypothesis analysis indicate that the ability to learn market information plays a role in the internal learning ability (0/945) and the ability to learn interfaces (0/785) and internal learning ability (0/220) and interface learning ability (0/662) have been effective on administrative innovation. Also, administrative innovation has had an effect on the organization's performance (0/488), and shared innovative capacities have a significant effect on service innovation (0/904). Finally, service innovation has played a role in the organization's performance (0/590).
Mahdi Akbari Golzar, Dr Ahmad Naderi,
Volume 11, Issue 2 (9-2024)
Volume 11, Issue 2 (9-2024)
Abstract
Introduction
Blockchain technology was first introduced in 2008 as a peer-to-peer electronic payment system. This technology has since attracted widespread attention in the field of scientific research as well as industry. Blockchain has been examined from various aspects. For example, a body of research examines how blockchain's decentralized approach could completely disrupt current business models, financial systems, organizations, and civil governance. Arguably, the clearest evidence of the growth and pervasiveness of this technology is the combined blockchain market capitalization reaching more than 2.6 trillion cryptocurrencies in 2024. In addition, development activity has been steadily growing over the past decade, and numerous projects have been launched to improve the core design of the blockchain (Bitcoin) (such as Ethereum, Kava, and Solana blockchains, etc.). Several articles have systematically reviewed the studies conducted in the field of blockchain in the country using the meta-combination method, all of which focus on the review of foreign articles. Due to the growth and widespread use of blockchain technology in the country and the increase in the scope of domestic research related to it, a systematic review of the research conducted inside the country also seemed necessary. In this regard, the aim of this article is to systematically review internal articles in the blockchain field, focusing on the human-computer interaction (HCI) field of study.
Methods and Materoal
In this research, we have used the qualitative meta-method for a systematic review of blockchain research. A systematic review is a method of identifying, evaluating, and interpreting past research related to a research question, topic area, or phenomenon of interest. The focus of this review is to summarize the HCI literature on blockchain technology. We organized this literature review in four comprehensive steps, following the PRISMA systematic review protocol.
Resultss and Discussion
We found that the articles in our sample adopted one of the following two perspectives. They conducted their research either on blockchain technology (74 articles, 66%) or specifically on cryptocurrencies (37 articles, 34%). Articles related to blockchain technology mainly discuss the understanding of users' motivation, perceived risks and the application of this technology, and articles related to cryptocurrencies also deal more with the jurisprudential and legal aspects of cryptocurrencies and the analysis of transaction risks and user experience. Most empirical studies that deal with people evolve around cryptocurrency, while contributions to blockchain often lead to products or evaluations of financial and administrative systems.
After providing an overview of blockchain research in the HCI community, we present and discuss the salient themes that emerged from the literature review. We identified 4 main themes:
Blockchain technology was first introduced in 2008 as a peer-to-peer electronic payment system. This technology has since attracted widespread attention in the field of scientific research as well as industry. Blockchain has been examined from various aspects. For example, a body of research examines how blockchain's decentralized approach could completely disrupt current business models, financial systems, organizations, and civil governance. Arguably, the clearest evidence of the growth and pervasiveness of this technology is the combined blockchain market capitalization reaching more than 2.6 trillion cryptocurrencies in 2024. In addition, development activity has been steadily growing over the past decade, and numerous projects have been launched to improve the core design of the blockchain (Bitcoin) (such as Ethereum, Kava, and Solana blockchains, etc.). Several articles have systematically reviewed the studies conducted in the field of blockchain in the country using the meta-combination method, all of which focus on the review of foreign articles. Due to the growth and widespread use of blockchain technology in the country and the increase in the scope of domestic research related to it, a systematic review of the research conducted inside the country also seemed necessary. In this regard, the aim of this article is to systematically review internal articles in the blockchain field, focusing on the human-computer interaction (HCI) field of study.
Methods and Materoal
In this research, we have used the qualitative meta-method for a systematic review of blockchain research. A systematic review is a method of identifying, evaluating, and interpreting past research related to a research question, topic area, or phenomenon of interest. The focus of this review is to summarize the HCI literature on blockchain technology. We organized this literature review in four comprehensive steps, following the PRISMA systematic review protocol.
Resultss and Discussion
We found that the articles in our sample adopted one of the following two perspectives. They conducted their research either on blockchain technology (74 articles, 66%) or specifically on cryptocurrencies (37 articles, 34%). Articles related to blockchain technology mainly discuss the understanding of users' motivation, perceived risks and the application of this technology, and articles related to cryptocurrencies also deal more with the jurisprudential and legal aspects of cryptocurrencies and the analysis of transaction risks and user experience. Most empirical studies that deal with people evolve around cryptocurrency, while contributions to blockchain often lead to products or evaluations of financial and administrative systems.
After providing an overview of blockchain research in the HCI community, we present and discuss the salient themes that emerged from the literature review. We identified 4 main themes:
- Decentralized economy and smart contracts (13 articles, 12%)
- Users' understanding and participation of blockchain technology and cryptocurrencies (48 articles, 43%)
- Application of blockchain technology in a specific field (34 articles, 31%)
- Jurisprudence and legal issues around blockchain and cryptocurrencies (16 articles, 14%).
Conclusion
After completing the systematic review of domestic articles, the most interesting point for us is the difference between domestic articles and international topics. As mentioned in some parts of the article, there are three general interests in the international research space that are less observed in domestic research. The first is issues related to the concept of trust in blockchain technologies. The second is the issues related to technical infrastructure and generally the way of socio-technical interactions in society, and the third is related to blockchain-based micro-projects such as Ethereum, Kava, Solana, etc., which are not considered in Iran.
The blockchain ecosystem has experienced rapid growth over the past decade. While until recently, Ethereum was the only widely used blockchain platform supporting decentralized applications, today several new blockchains (such as Solana, Kava, Polkadot, Terra, etc.) have been launched for decentralized applications. Many believe that this new generation of blockchains, which now offer instant transactions with low transaction fees, promises the third generation of the web. Web 1.0 allowed users to read (consume) content on the Internet. Web 2.0 added authoring options and the ability to generate content, thereby enabling rich interactive Internet applications. Powered by blockchain, Web 3.0 now adds the ability to own, create, and distribute digital assets. The first signs of this paradigm shift are the emergence of decentralized finance (DeFi) and non-fungible tokens (NFT), which so far account for more than two-thirds of transactions on the Ethereum blockchain and are driving user adoption of Ethereum. These topics and developments are being noticed by researchers all over the world, but we did not find any study in these fields inside the country. This issue is particularly important from the aspect that Web 3.0 challenges human interaction and cooperation on the Internet and, in a sense, mixes the human and technological space together.The need to pay attention to these research fields as well as the acceptance of interdisciplinary studies (specifically socio-technical studies) should be taken into account in order to open a gate for understanding the fast-paced global technological developments in the space of social studies and a field for presenting theories. To provide a new society in accordance with the socio-cultural context of Iranian society.
After completing the systematic review of domestic articles, the most interesting point for us is the difference between domestic articles and international topics. As mentioned in some parts of the article, there are three general interests in the international research space that are less observed in domestic research. The first is issues related to the concept of trust in blockchain technologies. The second is the issues related to technical infrastructure and generally the way of socio-technical interactions in society, and the third is related to blockchain-based micro-projects such as Ethereum, Kava, Solana, etc., which are not considered in Iran.
The blockchain ecosystem has experienced rapid growth over the past decade. While until recently, Ethereum was the only widely used blockchain platform supporting decentralized applications, today several new blockchains (such as Solana, Kava, Polkadot, Terra, etc.) have been launched for decentralized applications. Many believe that this new generation of blockchains, which now offer instant transactions with low transaction fees, promises the third generation of the web. Web 1.0 allowed users to read (consume) content on the Internet. Web 2.0 added authoring options and the ability to generate content, thereby enabling rich interactive Internet applications. Powered by blockchain, Web 3.0 now adds the ability to own, create, and distribute digital assets. The first signs of this paradigm shift are the emergence of decentralized finance (DeFi) and non-fungible tokens (NFT), which so far account for more than two-thirds of transactions on the Ethereum blockchain and are driving user adoption of Ethereum. These topics and developments are being noticed by researchers all over the world, but we did not find any study in these fields inside the country. This issue is particularly important from the aspect that Web 3.0 challenges human interaction and cooperation on the Internet and, in a sense, mixes the human and technological space together.The need to pay attention to these research fields as well as the acceptance of interdisciplinary studies (specifically socio-technical studies) should be taken into account in order to open a gate for understanding the fast-paced global technological developments in the space of social studies and a field for presenting theories. To provide a new society in accordance with the socio-cultural context of Iranian society.
Yazdan Shirmohammadi, Fatemeh Safa,
Volume 11, Issue 4 (1-2025)
Volume 11, Issue 4 (1-2025)
Abstract
Tourism is recognized as one of the most dynamic and rapidly growing economic sectors in recent decades, acting as a major driver of economic development, employment generation, and cultural exchange worldwide (Cristó & Sharpley, 2019). Within this broader industry, tourism start-ups play a central role in developing innovative products and services, enhancing destination attractiveness, and increasing stakeholder engagement. The performance of such start-ups, especially in urban tourism ecosystems such as Tehran, is increasingly dependent on their ability to leverage Information and Communication Technologies (ICT), foster knowledge integration, and innovate in both products and services. ICT has emerged as a key enabler of competitiveness in knowledge-intensive and service-oriented industries. It facilitates the acquisition and dissemination of knowledge across organizational boundaries, allowing firms to accelerate internal learning, adopt open innovation practices, and improve overall performance (Harif et al., 2022). Moreover, in the context of start-ups, where agility, adaptability, and resource constraints are often interwoven, strategic application of ICT becomes not just an operational necessity, but a performance catalyst.
Methods and Materoal
The present study employed a descriptive-correlational methodology based on structural equation modeling (SEM) using the SmartPLS 3 software. A total of 280 managers and employees from tourism start-ups based in Tehran were selected through convenience sampling. Standardized questionnaires were used to measure the constructs of interest, including ICT (Azam, 2015), open innovation (Hamed et al., 2018), knowledge integration, knowledge management (Iqbal et al., 2023), service innovation (Hu, 2009), marketing strategy (Koksal & Ozgul, 2007), and firm performance. Validity and reliability of the constructs were confirmed through Cronbach's alpha, composite reliability, Average Variance Extracted (AVE) and discriminant validity measures. Items with factor loadings below 0.4 were removed to ensure model parsimony. The GoF (Goodness-of-Fit) index was computed and interpreted based on Kline's (2010) thresholds to ensure robustness of the overall model.
Resultss and Discussion
The results reveal that ICT significantly influences three critical mediating variables: external knowledge integration (β = 0.60, t = 18.0), open innovation (β = 0.75, t = 26.55), and knowledge management (β = 0.512, t = 7.17). These findings support prior studies that conceptualize ICT not only as a data processing tool but also as a vehicle for organizational learning and innovation (Scuotto et al., 2017; Bhatt & Grover, 2005).Moreover, the integration of external knowledge has a direct and significant effect on knowledge management (β = 0.40, t = 8.59), underscoring the importance of external inputs in shaping internal learning systems and innovation capacity (Liao & Marsillac, 2015). In contrast, the direct relationship between open innovation and knowledge management was not statistically significant (t = 0.18), suggesting that open innovation may be more effective when coupled with internal absorptive capabilities or organizational culture conducive to knowledge utilization.Knowledge management, as a central construct in this model, demonstrated strong effects on both service innovation (β = 0.70, t = 24.96) and organizational performance (β = 0.389, t = 3.87). This aligns with the existing literature that highlights the strategic role of knowledge systems in enabling innovation and competitive advantage (Darroch, 2005; Harif et al., 2022). Furthermore, service innovation itself has a modest yet significant impact on performance (β = 0.17, t = 2.66), echoing previous studies that link new service development to firm-level outcomes (Aas & Pedersen, 2010; Cheng & Huizingh, 2014).Surprisingly, the direct effect of marketing strategy on performance was not significant (t = 1.62), which contradicts the results of some earlier studies (Kitsios & Kamariotou, 2016). However, a significant moderating effect of marketing strategy was found on the relationship between service innovation and performance (t = 3.10, β = 0.138), indicating that when strategically aligned with innovation initiatives, marketing strategies can enhance the impact of innovation efforts.The structural model exhibited strong explanatory power, with R² values of 0.658 for knowledge management, 0.494 for service innovation, and 0.429 for performance. The global GoF value of 0.638 exceeded the threshold for strong model fit (Kline, 2010), confirming the robustness of the conceptual framework.
Conclusion
This study offers multiple contributions to both academic theory and managerial practice. First, it empirically validates the critical role of ICT as a driver of performance in tourism start-ups, particularly through its impact on knowledge integration and innovation mechanisms. Second, it emphasizes the importance of effective knowledge management systems as a bridge between external knowledge inputs and internal innovation outcomes. Third, it suggests that while marketing strategy may not directly influence performance, it plays a valuable role as a moderator when combined with service innovation.The implications for practitioners are clear: tourism start-ups should invest in ICT infrastructure and training not merely for operational efficiency but as strategic assets for learning and innovation. Knowledge integration systems, such as customer databases, supplier collaboration platforms, and staff training modules, should be prioritized. In addition, marketing strategies should be designed to amplify the value created through service innovation.Given the limited geographic focus of the study, future research should replicate this model in other cities and cultural contexts. Mixed-method approaches incorporating qualitative insights could also enrich the findings. Moreover, examining the role of individual characteristics such as entrepreneurial orientation, digital literacy, or organizational culture may shed further light on the boundary conditions of these relationships.
Methods and Materoal
The present study employed a descriptive-correlational methodology based on structural equation modeling (SEM) using the SmartPLS 3 software. A total of 280 managers and employees from tourism start-ups based in Tehran were selected through convenience sampling. Standardized questionnaires were used to measure the constructs of interest, including ICT (Azam, 2015), open innovation (Hamed et al., 2018), knowledge integration, knowledge management (Iqbal et al., 2023), service innovation (Hu, 2009), marketing strategy (Koksal & Ozgul, 2007), and firm performance. Validity and reliability of the constructs were confirmed through Cronbach's alpha, composite reliability, Average Variance Extracted (AVE) and discriminant validity measures. Items with factor loadings below 0.4 were removed to ensure model parsimony. The GoF (Goodness-of-Fit) index was computed and interpreted based on Kline's (2010) thresholds to ensure robustness of the overall model.
Resultss and Discussion
The results reveal that ICT significantly influences three critical mediating variables: external knowledge integration (β = 0.60, t = 18.0), open innovation (β = 0.75, t = 26.55), and knowledge management (β = 0.512, t = 7.17). These findings support prior studies that conceptualize ICT not only as a data processing tool but also as a vehicle for organizational learning and innovation (Scuotto et al., 2017; Bhatt & Grover, 2005).Moreover, the integration of external knowledge has a direct and significant effect on knowledge management (β = 0.40, t = 8.59), underscoring the importance of external inputs in shaping internal learning systems and innovation capacity (Liao & Marsillac, 2015). In contrast, the direct relationship between open innovation and knowledge management was not statistically significant (t = 0.18), suggesting that open innovation may be more effective when coupled with internal absorptive capabilities or organizational culture conducive to knowledge utilization.Knowledge management, as a central construct in this model, demonstrated strong effects on both service innovation (β = 0.70, t = 24.96) and organizational performance (β = 0.389, t = 3.87). This aligns with the existing literature that highlights the strategic role of knowledge systems in enabling innovation and competitive advantage (Darroch, 2005; Harif et al., 2022). Furthermore, service innovation itself has a modest yet significant impact on performance (β = 0.17, t = 2.66), echoing previous studies that link new service development to firm-level outcomes (Aas & Pedersen, 2010; Cheng & Huizingh, 2014).Surprisingly, the direct effect of marketing strategy on performance was not significant (t = 1.62), which contradicts the results of some earlier studies (Kitsios & Kamariotou, 2016). However, a significant moderating effect of marketing strategy was found on the relationship between service innovation and performance (t = 3.10, β = 0.138), indicating that when strategically aligned with innovation initiatives, marketing strategies can enhance the impact of innovation efforts.The structural model exhibited strong explanatory power, with R² values of 0.658 for knowledge management, 0.494 for service innovation, and 0.429 for performance. The global GoF value of 0.638 exceeded the threshold for strong model fit (Kline, 2010), confirming the robustness of the conceptual framework.
Conclusion
This study offers multiple contributions to both academic theory and managerial practice. First, it empirically validates the critical role of ICT as a driver of performance in tourism start-ups, particularly through its impact on knowledge integration and innovation mechanisms. Second, it emphasizes the importance of effective knowledge management systems as a bridge between external knowledge inputs and internal innovation outcomes. Third, it suggests that while marketing strategy may not directly influence performance, it plays a valuable role as a moderator when combined with service innovation.The implications for practitioners are clear: tourism start-ups should invest in ICT infrastructure and training not merely for operational efficiency but as strategic assets for learning and innovation. Knowledge integration systems, such as customer databases, supplier collaboration platforms, and staff training modules, should be prioritized. In addition, marketing strategies should be designed to amplify the value created through service innovation.Given the limited geographic focus of the study, future research should replicate this model in other cities and cultural contexts. Mixed-method approaches incorporating qualitative insights could also enrich the findings. Moreover, examining the role of individual characteristics such as entrepreneurial orientation, digital literacy, or organizational culture may shed further light on the boundary conditions of these relationships.
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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