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A THEMATIC PAPER SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF MANAGEMENT

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The results showed that Thai customers have the intention to use chatbots because they experience the convenience value of chatbots through their ability to answer simple questions. The good responsiveness of chatbots also creates value in the eyes of the customer, interestingly, trust has no relationship with the intention to use chatbots. Social commerce or conversational commerce (C-Commerce) is the use of social media such as Facebook, LINE, Instagram, YouTube, etc.

In Thailand, social commerce is growing thanks to the widespread use of social media across the country. They are the top three social media platforms that Thai people use most in Thailand (Pornwasin, 2018). In Thailand, there are not that many Thais who are familiar with the chatbots and they are not inclined to use chatbots if they have other choices.

Although companies have already introduced chatbots, the user experience and usage intent are still low, which could lead to service failures and negative word of mouth. According to the 2019 State of Conversational Marketing Report, customers typically use chatbots to answer their questions, accounting for 32 percent. When money is involved, people are more anxious and hesitant to use technology (Kilens, 2019).

Furthermore, the paper will also show information about the factors that influence the intention to use chatbots.

Table              Page
Table Page

Research Objectives

Research Questions

LITERATURE REVIEW

  • Chatbot
  • Perceived value
  • Trust
  • Customer experience

Zeithaml (1988) stated that perceived value is the customer's final evaluation of a product or service based on the perception of what is given. Woodruff (1997) stated that different definitions of perceived value change according to consumer behavior. Furthermore, perceived value is defined as an exchange between what is received and what is given (Iglesias & Guillen, 2004).

Another definition of perceived value mentioned by Keller (1998) is that it is a combination of cost and quality as perceived by consumers. Day (1999) considered perceived value as an equation of perceived benefits that minimizes the perceived costs of the buyer. Zeithaml (1988) stated that price, quality and perceived value influence people's perception and evaluation of products.

In addition, perceived value positively affects Thai users' intention to use smartphones (Pitchayadejanant, 2011). Boontarig (2012) indicated that perceived value has a strong bearing on elderly people's intention to use smartphone. In this paper, perceived value means a customer's assessment of the perception of what is perceived as more benefits than costs, which is the poor performance of using chatbots.

In addition, Keyser et al. 2015) described customer experience as a combination of sensory, physical, spiritual, cognitive and emotional elements that indicate direct and indirect interactions of customers with companies. Many companies have focused more on customer experience because customers have more complex choices and can interact with companies in multiple channels (Brynjolfsson et al., 2013; Meyer & Schwager, 2007). Chung and Kwon (2009) stated that user experience with mobile banking influences usage intention.

Their findings confirmed that customer experience has a positive impact on the intention to use mobile banking services. Many companies have focused more on the customer experience because customers have more complex choices and can interact with companies in multiple channels. Based on the previous studies, the three factors that are most mentioned are trust, perceived value and customer experience that can influence the intention to use.

Table 2.1 Description of perceived value
Table 2.1 Description of perceived value

RESEARCH METHODOLOGY

Instrument construction

Question design

In addition to the above questions, some interviewees were also asked additional questions that depended on the situation during the interviews. This made them feel comfortable answering questions and more open when they spoke.

Data collection

DATA ANALYSIS

  • Demographic information and chatbot usage
  • Perceived value
    • Convenience
  • Customer experience
    • Responsiveness
  • Trust
    • Reliability
  • Summary

For complex questions, they revealed that chatbots were not suitable for them to talk to, as they were not smart enough to understand and solve their problems. Customers would perceive the value of convenience and intend to use chatbots if they had a good user experience. However, a bad experience can lead to a negative intention to use chatbots by preventing customers from perceiving the value of convenience.

Even customers trusted the companies' chatbots, they did not prefer chatbots to help them solve their specific problems or questions, as they were aware of chatbots' limitations and were not sure that chatbots could help them. Customers' intent to use chatbots depended on the chatbots' ability to solve their complex problems. If customers trust the companies' chatbots, but the chatbots do not have the ability to do so, customers will avoid using chatbots.

So customers trusted chatbots to help them with simple questions because chatbots had the ability to do so. From the interviews, human-like style can make customers trust chatbots as it can make customers feel better to communicate with chatbots. It was one thing mentioned by some participants that they didn't rely on chatbots to help them because the chatbots weren't human, which could be.

Even the companies are trying to make chatbots to be like humans, some customers still preferred to talk to real people to solve their complex problems because they didn't get what they wanted from chatbots when they asked the complex questions. The participants would only use chatbots to help them for the simple or common questions but not for complex questions. There is no support that when customers trust chatbots, they will use chatbots to help them.

They didn't see the value in complex issues and it became more of a cost instead of benefiting their needs. If customers have a good user experience, they will also perceive the value of convenience and have the intention to use chatbots. However, if customers have a bad experience using chatbots, they will not perceive the value of convenience and have no intention of using chatbots.

However, there was no support from the interviews that when people trusted chatbots, they would use chatbots to help them. The human-like style of chatbots made customers feel better, but they also want to know if they were talking to chatbots or real people.

Figure 4.1 Demographic information and chatbot usage
Figure 4.1 Demographic information and chatbot usage

CONCLUSION AND RECOMMENDATION

  • Conclusion
  • Implications
    • Theoretical contributions
    • Managerial implications
  • Limitations
  • Recommendations for future research

However, there was no support that when customers trusted the chatbots, they would use the chatbots to assist them. As long as customers see more benefits than the poor performance of chatbots, they will see convenience value and use the chatbots. Finally, trust plays a role as reliability; however, there is no support that when customers trust the chatbots, they will use the chatbots.

Customer experience is directly related to perceived value, and perceived value is related to intent to use the chatbot. From the interviews, perceived value is related to intention to use when customers have good experience from good response of chatbots. Low responsiveness leads to bad customer experience, which prevents customers from perceiving the value and intent to use chatbots.

Thus, the researcher confirms that perceived value is related to intention to use which is consistent with previous research. However, customer experience is not directly related to the purpose of use, but is related to perceived value. There are several implications for chatbot developers and companies that are implementing or have a goal to implement chatbots in order to increase chatbot adoption rates in Thailand.

However, what customers like from the interviews is that while the chatbots are available to them at all times, the chatbots need to respond quickly with the right answers to both simple and complex customer questions. However, chatbots can also be used to assist in purchasing items, but people are often hesitant to use chatbots to help them when it comes to money (Kilens, 2019). While customers also love chatbots to help them complete the purchase process, some chatbot users are afraid of using chatbots to complete their entire purchase.

In addition, chatbot developers should reduce the complexity of the steps in obtaining customer information to enhance the customer experience. The implementation of chatbots can be the good opportunity to build meaningful relationships with customers if the companies and developers do it right. For further research, researchers should expand the scope of the study to other provinces in Thailand or other counties to understand the perspectives of chatbots by people in different locations.

Paper presented at the 55th Annual Meeting of the Association for Computational Linguistics-System Demonstrations, Vancouver, Canada. Paper presented at the Proceedings of the 2007 International Conference on Collaborative Technologies and Systems, Orlando, USA. Paper presented at the 2003 AAAI Spring Symposium on Human Interaction with Autonomous Systems in Complex Environments, Palo Alto, CA.

Like having a really bad PA” The gap between user expectations and chat agent experience. Retrieved March 23, 2020, from https://kr-asia.com/chatbots-find-fertile-ground-in-thailand-southeast-asias-largest-social-commerce-market. In Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialogue Technologies,.

The global chatbot market is expected to reach $9.4 billion by 2024 – with huge opportunities emerging in retail and e-commerce. Retrieved February 3, 2020, from https://markets.businessinsider.com /news/stocks/global-chatbot-market-anticipated-to-reach-9-4-billion- by-2024-robust-opportunities-to-arise- and-retail-e-commerce-. A meta-analysis of the influence of trust on the technology acceptance model: An investigation of the moderating effect of subject and type of context.

APPENDICES

Gambar

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Figure             Page
Figure 1.1 Marketing automation market by region (USD Billion)
Figure 1.2 Purposes of using chatbots
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