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Source: Journal Citation ReportsTM from ClarivateTM 2022

Entrepreneurship and Sustainability Issues Open access
Journal Impact FactorTM (2022) 1.7
Journal Citation IndicatorTM (2022) 0.42
Received: 2019-12-10  |  Accepted: 2020-04-07  |  Published: 2020-06-30

Title

The effect of artificial intelligence on the sales graph in Indian market


Abstract

Artificial Intelligence (AI) has been the biggest revolution of the 21st century impacting every aspect of the business, sales being no different. The paper experiments the effect of marketing on 4500 customers using AI and humans. The outcomes of the research reveal the effectiveness of AI is the same as experienced salesmen and 2.7 times better than inexperienced salesmen is closing the sales calls. The sales graph experienced a dip by over 86.23% when it was revealed to the customer that the interface is with the machine, not humans and reduced the duration of the call substantially. The paper shows that Indians do not believe Artificial Intelligence and still prefer human interface as they do not trust machines over human emotions. The effectiveness of AI drastically reduces despite its superiority over humans in various aspects. The paper identifies the strategies to overcome the trust deficit that exists among Indian customers. The outcomes show how AI can be used, and how marketing could be done using AI in conservative markets such as India.


Keywords

Artificial Intelligence (AI), machines, sales, marketing, human resources


JEL classifications

O31


URI

http://jssidoi.org/jesi/article/563


DOI


Pages

2940-2954


This is an open access issue and all published articles are licensed under a
Creative Commons Attribution 4.0 International License

Authors

Ullal, Mithun S.
Manipal Academy of Higher Education, Manipal, India https://manipal.edu
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Hawaldar, Iqbal Thonse
Kingdom University, Riffa, Bahrain https://www.ku.edu.bh
Articles by this author in: CrossRef |  Google Scholar

Mendon, Suhan
Manipal Academy of Higher Education, Manipal, India https://manipal.edu
Articles by this author in: CrossRef |  Google Scholar

Joseph, Nympha Rita
Applied Science University, Eker, Bahrain https://www.asu.edu.bh
Articles by this author in: CrossRef |  Google Scholar

Journal title

Entrepreneurship and Sustainability Issues

Volume

7


Number

4


Issue date

June 2020


Issue DOI


ISSN

ISSN 2345-0282 (online)


Publisher

VšĮ Entrepreneurship and Sustainability Center, Vilnius, Lithuania

Cited

Google Scholar

Article views & downloads

HTML views: 4146  |  PDF downloads: 1755

References


Bass, Frank M. (1969). A New Product Growth for Model Consumer Durables. Management Science, 15(5), 215-227.

Search via ReFindit


Bennett, C. C., & Hauser, K. (2013). Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach. Artificial Intelligence in Medicine, 57(1), 9-19. https://doi.org/10.1016/j.artmed.2012.12.003

Search via ReFindit


Briggs, G., & Scheutz, M. (2016). The Case for Robot Disobedience. Scientific American, 316(1), 44– 47. https://doi.org/10.1038/scientificamerican0117-44

Search via ReFindit


Brynjolfsson E, Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 358(6370), 1530–1534.

Search via ReFindit


Chaturvedi, M. M., Gupta, M. P., & Bhattacharya, J. (2008). Cyber Security Infrastructure in India: A Study. Emerging Technologies in E-Government, CSI Publication.

Search via ReFindit


Chung, T. S., Wedel, M., & Rust, R. T. (2016). Adaptive personalization using social networks. Journal of the Academy of Marketing Science, 44(1), 66-87. https://doi.org/10.1007/s11747-015-0441-x

Search via ReFindit


Churchill, Jr, G. A., Ford, N. M., Hartley, S. W., & Walker Jr, O. C. (1985). The determinants of salesperson performance: A meta-analysis. Journal of Marketing Research, 22(2), 103-118. https://doi.org/10.1177/002224378502200201

Search via ReFindit


Del Valle, K. (2018) Conversational commerce: A new opportunity for card payments. MasterCard (January 25). https://newsroom.mastercard.com/documents/conversational-commerce-a-new-opportunity-for-card-payments/

Search via ReFindit


Desai, F. (2019). The Age of Artificial Intelligence in Fintech https://www.forbes.com/sites/falgunidesai/2016/06/30/the-age-of-artificial-intelligence-in-fintech/#269da1a15028

Search via ReFindit


Dietvorst, B. J., Simmons, J. P., & Massey, C. (2016). Overcoming algorithm aversion: People will use imperfect algorithms if they can (even slightly) modify them. Management Science, 64(3), 1155-1170. https://doi.org/10.1287/mnsc.2016.2643

Search via ReFindit


Edelman, D., Singer, M. (2015). Competing on Customer Journeys. Harvard Business Review, November, 88-94, 96, 98, 100.

Search via ReFindit


Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115. https://doi.org/10.1038/nature21056

Search via ReFindit


Federal Trade Commission. (2017). Privacy & data security update (2016). https://www.ftc.gov/reports/privacy-data-security-update-2016

Search via ReFindit


Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research, 204(2), 189-198. https://doi.org/10.1016/j.ejor.2009.08.003

Search via ReFindit


Froehlich, S., Gum, F., & Berlinger, K. (2018). U.S. Patent No. 10,052,501. Washington, DC: U.S. Patent and Trademark Office.

Search via ReFindit


Ghassemi, M., Naumann, T., Schulam, P., Beam, A. L., Chen, I. Y., & Ranganath, R. (2019). Practical guidance on artificial intelligence for health-care data. The Lancet Digital Health, 1(4), e157-e159.

Search via ReFindit


Giebelhausen, M., Robinson, S. G., Sirianni, N. J., & Brady, M. K. (2014). Touch versus tech: When technology functions as a barrier or a benefit to service encounters. Journal of Marketing, 78(4), 113-124.

Search via ReFindit


Hawaldar, I. T., Ullal, M. S., Birau, F. R., & Spulbar, C. M. (2019a). Trapping Fake Discounts as Drivers of Real Revenues and Their Impact on Consumer’s Behavior in India: A Case Study. Sustainability, 11(17), 4637. doi:10.3390/su11174637

Search via ReFindit


Hawaldar, I.T., Lokesh, Biso, S.S. & Joseph, N.R. (2016). Factors Affecting Leaders’ Behaviour: A Study of Bahrain Banking Sector. British Journal of Economics, Finance and Management Sciences, 12 (1), 11-21.

Search via ReFindit


Hawaldar, I.T., Rajesha T. M. & Dsouza, L.J. (2019b). Testing the Weak Form of Efficiency of Cryptocurrencies: A Case Study of Bitcoin and Litecoin. International Journal of Scientific & Technology Research, 8 (9), 2301-2305.

Search via ReFindit


Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172. https://doi.org/10.1177/1094670517752459

Search via ReFindit


Köhler, C. F., Rohm, A. J., de Ruyter, K., & Wetzels, M. (2011). Return on interactivity: The impact of online agents on newcomer adjustment. Journal of Marketing, 75(2), 93-108. https://doi.org/10.1509/jm.75.2.93

Search via ReFindit


Leachman, S. A., & Merlino, G. (2017). Medicine: The final frontier in cancer diagnosis. Nature, 542(7639), 36-38.

Search via ReFindit


Leachman, S. A., & Merlino, G. (2017). Medicine: The final frontier in cancer diagnosis. Nature, 542(7639), 36. https://doi.org/10.1038/nature21492

Search via ReFindit


Leung, E., Paolacci, G., & Puntoni, S. (2018). Man versus machine: Resisting automation in identity-based consumer behavior. Journal of Marketing Research, 55(6), 818-831. https://doi.org/10.1177/0022243718818423

Search via ReFindit


Logg, J. M., Minson, J. A., & Moore, D. A. (2019). Algorithm appreciation: People prefer algorithmic to human judgment. Organizational Behavior and Human Decision Processes, 151, 90-103. https://doi.org/10.1016/j.obhdp.2018.12.005

Search via ReFindit


Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science https://doi.org/10.1287/mksc.2019.1192

Search via ReFindit


Martínez-López, F. J., & Casillas, J. (2013). Artificial intelligence-based systems applied in industrial marketing: An historical overview, current and future insights. Industrial Marketing Management, 42(4), 489-495. https://doi.org/10.1016/j.indmarman.2013.03.001

Search via ReFindit


Mimoun, M. S. B., Poncin, I., & Garnier, M. (2017). Animated conversational agents and e-consumer productivity: The roles of agents and individual characteristics. Information & Management, 54(5), 545-559. https://doi.org/10.1016/j.im.2016.11.008

Search via ReFindit


Monostori, L., & Barschdorff, D. (1992). Artificial neural networks in intelligent manufacturing. Robotics and Computer-Integrated Manufacturing, 9(6), 421-437.

Search via ReFindit


Patel, V. L., Shortliffe, E. H., Stefanelli, M., Szolovits, P., Berthold, M. R., Bellazzi, R., & Abu-Hanna, A. (2009). The coming of age of artificial intelligence in medicine. Artificial Intelligence in Medicine, 46(1), 5-17. https://doi.org/10.1016/j.artmed.2008.07.017

Search via ReFindit


Pinto, S., Pinto, P., Hawaldar, I.T. & Sarea, A.M. (2019). Motivation and Blockades for Entrepreneurship among Graduates. International Journal of Scientific & Technology Research, 8 (12), 821-828.

Search via ReFindit


Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717-731.

Search via ReFindit


Saad, S. B., & Abida, F. C. (2016). Social interactivity and its impact on a user’s approach behavior in commercial web sites: a study case of virtual agent presence. Journal of Marketing Management, 4(2), 63-80. https://doi.org/10.15640/jmm.v4n2a5

Search via ReFindit


Schlinger, Henry D. (2003). The Myth of Intelligence, The Psychological Record, 53(1), 15-32.

Search via ReFindit


Sivaramakrishnan, S., Wan, F., & Tang, Z. (2007). Giving an “e‐human touch” to e‐tailing: The moderating roles of static information quantity and consumption motive in the effectiveness of an anthropomorphic information agent. Journal of Interactive Marketing, 21(1), 60-75. https://doi.org/10.1002/dir.20075

Search via ReFindit


Soucy, Pascal (2016). Self-Learning Intelligent Search, Explained, KM World, July 7, 2016, S34.

Search via ReFindit


Srivastava, S. K. (2018). Artificial Intelligence: way forward for India. JISTEM-Journal of Information Systems and Technology Management, 15. http://dx.doi.org/10.4301/s1807-1775201815004

Search via ReFindit


Sternberg, Robert J. (2005). The Theory of Successful Intelligence, Interamerican Journal of Psychology, 39(2), 189-202.

Search via ReFindit


Thompson, C. (2018). May A.I. help you? New York Times. https://www.nytimes.com/interactive/2018/11/14/magazine/tech-design-ai-chatbot.html

Search via ReFindit


Trippi, R. R., & Turban, E. (1992). Neural networks in finance and investing: Using artificial intelligence to improve real world performance. McGraw-Hill, Inc. https://dl.acm.org/citation.cfm?id=573193

Search via ReFindit


Ullal, M., & Hawaldar, I. T. (2018). Influence of advertisement on customers based on AIDA model. Problems and Perspectives in Management, 16(4), 285-298. doi:10.21511/ppm.16(4).2018.24

Search via ReFindit


Vargo, S. L., & Lusch, R. F. (2014). Evolving to a new dominant logic for marketing. In the Service-Dominant Logic of Marketing (pp. 21-46). Routledge.

Search via ReFindit


Wilson, H. J., Daugherty, P., & Bianzino, N. (2017). The jobs that artificial intelligence will create. MIT Sloan Management Review, 58(4), 14. http://ilp.mit.edu/media/news_articles/smr/2017/5841

Search via ReFindit


Wise, L. (2018). June 20 New media doesn't mean new rules: The challenges of chatbots. Social MediaWeek. https://socialmediaweek.org/blog/2018/06/new-media-doesnt-mean-new-rules-the-challenges-of-chatbots/

Search via ReFindit


Wünderlich, N. V., Wangenheim, F. V., & Bitner, M. J. (2013). High tech and high touch: a framework for understanding user attitudes and behaviors related to smart interactive services. Journal of Service Research, 16(1), 3-20.

Search via ReFindit


Xiao, L., & Ding, M. (2014). Just the faces: Exploring the effects of facial features in print advertising. Marketing Science, 33(3), 338-352.

Search via ReFindit


Yoo, Jaewon and Todd J. Arnold. (2016). Frontline Employee Customer-Oriented Attitude in the Presence of Job Demands and Resources: The Influence Upon Deep and Surface Acting, Journal of Service Research, 19(1), 102-117.

Search via ReFindit


Young, James E., Cormier, Derek. (2014). Can Robots Be Managers, Too? Harvard Business Review, April 2 http://blogs.hbr.org/2014/04/can-robots-bemanagers-too/

Search via ReFindit