摘要
透過實地調查268名參與者(包括缺失數據)，我們研究不同類型的銷售代理人員(真人與人工智能)之間如何對顧客身體感到不自在而影響購買意願。透過引用參考零售銷售人員，他們普遍認為好的銷售員就是那些能與消費者近距離接觸的人。 一項有關鄰近程度的研究證明，購買意願、店家忠誠度與實際消費狀況是會被此受到不利影響。 (Tobis Otterbring, 2020)
同樣，對於這項工作，我們代表了這兩項研究AI與真人相比之下，在生理上的不適感被操縱和測量的結果顯示，消費者有人工智能代理而不是人類代理（機器人技術而不是機器人）在暗示銷售策略或介紹時站得很近，購買意願會受到負面影響。代理商的類型和直銷策略(購物壓力)和AI代理人的直銷策略下,都會間接影響讓顧客感到不舒服。
這些發現在未來可適用於零售商廣泛的產品，如護膚品
和化妝品，利用人工智能作為銷售代理，帶來更好的受益。

Abstract
By conducting field studies, with a total sample of 268 participants (including missing data) , we have studied how physical discomfort between different types of sales agents (human vs. artificial intelligence) and customers can impact on customers’ purchasing intentions. By referencing a general belief among retail salespeople, they all truly believe that good sales agents are those who associate with close proximity between with consumers. A study conducted on proximity has proven that along with proximity, “purchase intentions, “store royalty” and actuals spendings” were negatively affected. (Tobis Otterbring, 2020) Similarly, to this work, we represent, across two studies in which physical discomfort of an AI agent compared to a human agent were both manipulated and measured, and results reveal that purchasing intentions is negatively impacted when consumers have AI agents instead of human agents (in forms of robotics not bots) standing closely while implying sales tactics or introductions. Type of agents and agents’ proximity to customers (shopping pressure) both have mediating effect in ways that customers did not feel comfortable while they were under directive sales tactics by the AI agents. These findings are practical for future extensive products retailers such as skin care and cosmetics to better benefit from the use Artificial agents solely as sales agents.

Table of Contents

Thesis Validation Letter………..……………………………………….....i
Abstract (Chinese)……………………………………………………...…ii
Abstract (English) …...…………………………..…………………...…..iii
Table of figures ………………………………………….……………......v
Table of Tables ……..………….……………...………………………….v
List of Abbreviations ……...………...………………………………........v
Chapter 1 : Introduction
1.1 Research scope...………………………………………………...….…1
1.2 Research Questions and Relevance …..……..……….…...……….......2
1.4 Research Procedure …..…………………………………………….....3
Chapter 2 : Literature review
2.1 Explanation of “AI Agent”…………………………………………….3
2.1.1 Future of AI Agents in Sales Departments…...……………………...3
2.2 AI Acceptance …...…………………………………………………....5
2.3 Shopping pressure tactics and customers’ physical discomfort ……....6
2.4 Credibility and Acceptance (CA)…………………...……….………...8

Chapter 4 : Methodology
4.1 Theoretical Foundation……………………………………………....11
4.2 Methods……………………………………………………………....11
4.2.1 Questionnaire Design……………………………………….……...11
4.2.2 Measured physical discomfort for both types of agents………........12
4.2.3 Measured credibility scores on purchasing intention……….…...…12
4.2.4 Demographics…………………………… ……...……….…….......13


Chapter 5: Conclusion and Discussion
5.1.1 Hypotheses testing………………………………………………….14
5.1.2 Physical Discomfort and PI Analysis………………………………14
5.1.3 Credibility Score Analysis………………………………………….16

Chapter 6 : Discussion and Future Research
6.1 Summary ………………………………………………………...…17
6.1.2 Limitations……………………….……………………………….18
6.1.3 Future Discussions………………………………………………..18
References………………...…………………………………………….30
Survey Outline………………………………………………….......…..33

Table of Figures:
Figure 2-1……………………………………………………………..…4
Table of Tables:
Table 4-1: Demographics…..………………………………..…….….…13
Table 5-1 Hypotheses Results ……………..………………....……....…15
Table 5-2: Pearson Correlation………………..……………….......……16
Appendix 4-1 Questionnaire design…………………………………….26
Appendix 5-1 Chi-Square…………………………………………….....28
Appendix 5-2 Chi-Square……………………………………………….29
Appendix 2-1: Coefficient tables…………….…………………….……27
Appendix 2-2: AI Understandings…….…….……………………......…10
Appendix 2-3: AI Acceptance……………………………………...…….8

List of Abbreviations:
• Communication Relations Management (CRM)
• Artificial Intelligence (AI)
• Performance Expectancy ( PE)
• Effort Expectancy ( EE)
• Purchasing Intentions (PI)
• Credibility and Acceptance ( CA )
• Unified Theory of Acceptance and Use of Technology (UTAUT1)
• Physical Discomfort (DI)
• Directive Pressure Tactic (DRP)
• Aggressive Pressure Tactic (AGGP)
• Effect Expectancy (EE)
• Performance Expectancy (PE)

References


Tobis Otterbring, F. W. (2020, November 28). Too close for comfort? The impact of salesperson-customer proximity on consumers' purchase behavior. pp. 1-15.
Seymour, S. (2014). p. p.194.
Esmark, N. (2018). Retail invaders: When employees' invasion of customer space increases purchase intentions. Journal of the Academy of Marketing Science, 477-496.
Narmadhaa. (2021).
EnfRoy, A. (2022, December 8). Adam EnfRoy. Retrieved from https://www.adamenfroy.com/artificial-intelligence-statistics
Vermes, K. (2019, July 11). Retrieved from Komarketing: https://komarketing.com/industry-news/report-40-of-marketers-using-ai-are-seeing-heightened-sales-and-marketing-performance-4062/
XIan, X. (2021).
World Ecoomic Forum. (2022, January). Retrieved from Ipsos: https://www.weforum.org/agenda/2022/01/artificial-intelligence-ai-technology-trust-survey/
Haytko, D. L. (n.d.). A push or a Nudge.
Gursoy, D. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. Washington: International Journal of Information Management 49.
Haytko, D. L. (2017). A push or a Nudge: Understanding Consumer Perceptions of Sales Pressure. Rutgers Business Review.
Dawar N., & Bendle N. (2018, June). Marketing in the age of Alexa.
Cheng, Y., & Jian,H. (2020). How Do AI-driven Chatbots Impact User Experience? Examining Gratifications, Perceived Privacy Risk, Satisfaction, Loyalty, and Continued Use. Journal of Broadcasting and electronic media. p. 64.
P.Esch, Cui, G., & Jain, S. (2020). Stimulating or Intimidating: The Effect of AI- Enabled In-Store Communication on Consumer Patronage Likelihood. Journal of Advertising .
Writer, A. s. (2020, March 27). Aithority. Retrieved from AI technology insights: https://aithority.com/ait-featured-posts/how-is-ai-changing-crm/
Xian, X. (2021, November 3). Psychological Factors in Consumer Acceptance of Artificial Intelligence in Leisure Economy: A Structural Equation Model .
JesusBobadilla, Gutierrez, A., Ortega, F., & Zhu, B. (2018, May). Reliability quality measures for recommender systems.
Weng, J. T., & Cyril de Run, E. (2013, January 7). Consumers' personal values and sales promotion preferences effect on behavioural intention and purchase satisfaction for consumer product.
Morvitz, V., Chandon, P., & Reinartz, W. (2005, April). Do Intentions Really Predict Behavior? Self-Generated Validity Effects in Survey Research.
Cheng, Y., & Jiang, H. (2020). How Do AI-driven Chatbots Impact User Experience? Examining Gratifications, Perceived Privacy Risk, Satisfaction, Loyalty, and Continued Use. Department of Communication.
Umer, S., Mohanta, P. P., Rout, R. K., & Pandey , H. M. (202, June 12). Machine learning method for cosmetic product recognition: a visual searching approach.


Tobis Otterbring, F. W. (2020, November 28). Too close for comfort? The impact of salesperson-customer proximity on consumers' purchase behavior. pp. 1-15.
Seymour, S. (2014). p. p.194.
Esmark, N. (2018). Retail invaders: When employees' invasion of customer space increases purchase intentions. Journal of the Academy of Marketing Science, 477-496.
Narmadhaa. (2021).
EnfRoy, A. (2022, December 8). Adam EnfRoy. From https://www.adamenfroy.com/artificial-intelligence-statistics
Vermes, K. (2019, July 11). From Komarketing: https://komarketing.com/industry-news/report-40-of-marketers-using-ai-are-seeing-heightened-sales-and-marketing-performance-4062/
XIan, X. (2021).
World Ecoomic Forum. (2022, January). From Ipsos: https://www.weforum.org/agenda/2022/01/artificial-intelligence-ai-technology-trust-survey/
Haytko, D. L. (n.d.). A push or a Nudge.
Gursoy, D. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. Washington: International Journal of Information Management 49.
Haytko, D. L. (2017). A push or a Nudge: Understanding Consumer Perceptions of Sales Pressure. Rutgers Business Review.
Dawar N., & Bendle N. (2018, June). Marketing in the age of Alexa.
Cheng, Y., & Jian,H. (2020). How Do AI-driven Chatbots Impact User Experience? Examining Gratifications, Perceived Privacy Risk, Satisfaction, Loyalty, and Continued Use. Journal of Broadcasting and electronic media. p. 64.
P.Esch, Cui, G., & Jain, S. (2020). Stimulating or Intimidating: The Effect of AI- Enabled In-Store Communication on Consumer Patronage Likelihood. Journal of Advertising .
Writer, A. s. (2020, March 27). Aithority. From AI technology insights: https://aithority.com/ait-featured-posts/how-is-ai-changing-crm/
Xian, X. (2021, November 3). Psychological Factors in Consumer Acceptance of Artificial Intelligence in Leisure Economy: A Structural Equation Model .
JesusBobadilla, Gutierrez, A., Ortega, F., & Zhu, B. (2018, May). Reliability quality measures for recommender systems.
Weng, J. T., & Cyril de Run, E. (2013, January 7). Consumers' personal values and sales promotion preferences effect on behavioural intention and purchase satisfaction for consumer product.
Morvitz, V., Chandon, P., & Reinartz, W. (2005, April). Do Intentions Really Predict Behavior? Self-Generated Validity Effects in Survey Research.
Cheng, Y., & Jiang, H. (2020). How Do AI-driven Chatbots Impact User Experience? Examining Gratifications, Perceived Privacy Risk, Satisfaction, Loyalty, and Continued Use. Department of Communication.
Umer, S., Mohanta, P. P., Rout, R. K., & Pandey , H. M. (202, June 12). Machine learning method for cosmetic product recognition: a visual searching approach.