Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing

Kumar, Vikas; Rajan, Bharath; Venkatesan, Rajkumar; Lecinski, Jim

doi:10.1177/0008125619859317

Cited by 442 publications

(256 citation statements)

References 28 publications

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“…When employed in hospitality, they also increase the service performance by improving the service consistency, providing more reliable information and minimizing errors in the service provision (Lu et al 2019). Automation can also contribute to increase customer relationship management (CRM) by assisting employees and managers with information and resources to better serve the customer and to plan and organize accordingly (Kumar et al 2019). For instance, some robot waiters greet customers when entering the restaurant and are able to call the customer by name or lead him or her to they preferred table based on the CRM information (Kabadayi et al 2019).…”

Section: The Influence Of Customers' Attributions On Customers' Intenmentioning

confidence: 99%

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Frontline robots in tourism and hospitality: service enhancement or cost reduction?

2020

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Robots are being implemented in many frontline services, from waiter robots in restaurants to robotic concierges in hotels. A growing number of firms in hospitality and tourism industries introduce service robots to reduce their operational costs and to provide customers with enhanced services (e.g. greater convenience). In turn, customers may consider that such a disruptive innovation is altering the established conditions of the service-provider relationship. Based on attribution theory, this research explores how customers' attributions about the firm motivations to implement service robots (i.e. cost reduction and service enhancement) are affecting customers' intentions to use and recommend this innovation. Following previous research on robot's acceptance, our research framework analyzes how these attributions may be shaped by customers' perceptions of robot's humanlikeness and their affinity with the robot. Structural equation modelling is used to analyze data collected from 517 customers evaluating service robots in the hospitality industry; results show that attributions mediate the relationships between affinity toward the robot and customer behavioral intentions to use and recommend service robots. Specifically, customer's affinity toward the service robot positively affects service improvement attribution, which in turn has a positive influence on customer behavioral intentions. In contrast, affinity negatively affects cost reduction attribution, which in turn has a negative effect on behavioral intentions. Finally, human-likeness has a positive influence on affinity. This research provides practitioners with empirical evidence and guidance about the introduction of service robots and its relational implications in hospitality and tourism industries. Theoretical advances and future research avenues are also discussed.

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Section: The Influence Of Customers' Attributions On Customers' Intenmentioning

confidence: 99%

“…Complementarily, firms introduce automated agents to reduce their costs (Kumar et al 2019). Cost reduction is frequently associated to increased efficiency and job elimination (Meuter et al 2000;Nijssen et al 2016).…”

Section: The Influence Of Customers' Attributions On Customers' Intenmentioning

confidence: 99%

Frontline robots in tourism and hospitality: service enhancement or cost reduction?

2020

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“…Örneğin; Yapay zekâ, bu tür kişiye özel öğrenme yaklaşımıyla yardımcı olabilmektedir. Dolayısıyla yapay zekânın farklı uygulamaları da öğrenme deneyimini kişiselleştirmesine yardımcı olacaktır (Kumar, Rajan, Venkatesan, ve Lecinski, 2019).…”

Section: Yapay Zekâ'nın Yararları Ve Tehditleriunclassified

Eğitimde Yeni Bir Paradigma: “Yükseköğretimde Yapay Zekâ”

Taşçi¹,

Çelebi²

2020

OPUS Uluslararası Toplum Araştırmaları Dergisi

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The developments in technology in recent years have deeply affected societies. Artificial intelligence, one of these developments, has also created a revolution in human life. One of the areas that artificial intelligence affects is higher education. Artificial intelligence, which emerged as a result of the digital revolution, is a challenge to higher education. In this respect, how ready are higher education institutions for artificial intelligence? What revolution can artificial intelligence, an output of the digital age, create in higher education institutions? How ready are higher education leaders mentally and strategically for artificial intelligence? What are the ethical limitations of artificial intelligence in higher education? What are the benefits and challenges of artificial intelligence in improving student success, facilitating student enrollment, and better management of higher education resources? questions are a new paradigm in higher education. In the perspective of these questions, this study suggests that artificial intelligence can strengthen universities when used correctly in higher education. However, to realize this thesis, higher education institutions need to reassess and transform themselves in order to continue their mission of research, education and society.Nowadays,many universities strive to devote time and develop themselves to teach their students the skills and knowledge needed to provide the best possible education. Morever, it is especially important for educators and especially higher education leaders and faculty members to understand how artificial intelligence can support educators. In this respect, in this study, questions the role of artificial intelligence in higher education, as well as the applications of artificial intelligence in higher education, and discusses how optimistic institutions of higher education institutions can prepare for future artificial intelligence

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“…While consumer profiles were once reliant on product registration and demographic information, marketers now have wideranging information than spans from media consumption to online activities, such as which websites were visited and what was posted on social media. As techniques such as machine learning and deep learning become more common within marketing, the ability to segment consumers and deliver highly customized and personalized [10] marketing content will only improve. If we were to ignore the societal implications of this and focus solely on the efficiencies that this would create for organizations, we may be able to come to the unequivocal conclusion that such efficiencies are to be welcomed.…”

Section: A Regulatory Imperative?mentioning

confidence: 99%