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1 – 10 of 23Stephanie Q. Liu, Khadija Ali Vakeel, Nicholas A. Smith, Roya Sadat Alavipour, Chunhao(Victor) Wei and Jochen Wirtz
An AI concierge is a technologically advanced, intelligent and personalized assistant that is designated to an individual customer, proactively taking care of that customer’s…
Abstract
Purpose
An AI concierge is a technologically advanced, intelligent and personalized assistant that is designated to an individual customer, proactively taking care of that customer’s needs throughout the service journey. This article envisions the idea of AI concierges and discusses how to leverage AI concierges in the customer journey.
Design/methodology/approach
This article takes a conceptual approach and draws insights from literature in service management, marketing, psychology, human-computer interaction and ethics.
Findings
This article delineates the fundamental forms of AI concierges: dialog interface (no embodiment), virtual avatar (embodiment in the virtual world), holographic projection (projection in the physical world) and tangible service robot (embodiment in the physical world). Key attributes of AI concierges are the ability to exhibit semantic understanding of auditory and visual inputs, maintain an emotional connection with the customer, demonstrate proactivity in refining the customer’s experience and ensure omnipresence through continuous availability in various forms to attend to service throughout the customer journey. Furthermore, the article explores the multifaceted roles that AI concierges can play across the pre-encounter, encounter and post-encounter stages of the customer journey and explores the opportunities and challenges associated with AI concierges.
Practical implications
This paper provides insights for professionals in hospitality, retail, travel, and healthcare on leveraging AI concierges to enhance the customer experience. By broadening AI concierge services, organizations can deliver personalized assistance and refined services across the entire customer journey.
Originality/value
This article is the first to introduce the concept of the AI concierge. It offers a novel perspective by defining AI concierges’ fundamental forms, key attributes and exploring their diverse roles in the customer journey. Additionally, it lays out a research agenda aimed at further advancing this domain.
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Gabriele Santoro, Fauzia Jabeen, Tomas Kliestik and Stefano Bresciani
This paper aims to (1) unveil how artificial intelligence (AI) can be implemented in growth-hacking strategies; and (2) identify the challenges and enabling factors associated…
Abstract
Purpose
This paper aims to (1) unveil how artificial intelligence (AI) can be implemented in growth-hacking strategies; and (2) identify the challenges and enabling factors associated with AI’s implementation in these strategies.
Design/methodology/approach
The empirical study is based on two distinct groups of analysis units. Firstly, it involves 11 companies (identified as F1 to F11 in Table 1) that employ growth-hacking principles and use AI to support their decision-making and operations. Secondly, interviews were conducted with four businesses and entrepreneurs providing consultancy services in growth and digital strategies. This approach allowed us to gain a broader view of the phenomenon. Data analysis was performed using the Gioia methodology.
Findings
The study firstly uncovers the principal benefits and applications of AI in growth hacking, such as enhanced data analysis and user behaviour insights, sales augmentation, traffic and revenue forecasting, campaign development and optimization, and customer service enhancement through chatbots. Secondly, it reveals the challenges and catalysts in AI-driven growth hacking, highlighting the crucial roles of experimentation, creativity and data collection.
Originality/value
This research represents the inaugural scientific investigation into AI’s role in growth-hacking strategies. It uncovers both the challenges and facilitators of AI implementation in this domain. Practically, it offers detailed insights into the operationalization of AI across various phases and aspects of growth hacking, including product-market fit, user acquisition, virality and retention.
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Chris Roberts and Thomas Maier
The purpose of this paper is to explore the distinction between human-delivered service and technology-based, automated customer assistance.
Abstract
Purpose
The purpose of this paper is to explore the distinction between human-delivered service and technology-based, automated customer assistance.
Design/methodology/approach
This is a conceptual paper. There is no methodology.
Findings
The concept of service is primarily delivered when a human helps another. When technology is infused into the process and becomes the major component of delivering the aid that is requested, the process is automated customer assistance. Thus, “self-service” is not service. It is automated customer assistance.
Research limitations/implications
The definition of service is refined to describe the process of a human helping another person. When technology is used to provide the needed aid, it is no longer a service. Instead, it is automated customer assistance. The implication is that researchers should closely examine how users assess and perceive the two separate approaches to providing the needed aid.
Practical implications
The definition of service is refined to describe the process of a human helping another person. When technology is used to provide the needed aid, it is no longer a service. Instead, it is automated customer assistance. Researchers should closely examine how users assess and perceive the two separate approaches. Industry professionals should be mindful of the distinction between the delivery of service, which requires staff, and the provisioning of technology to provide assistance, which requires little to no staff. Intentionality should drive when customers are better helped by a human or by technology.
Originality/value
The value provided helps both providers create and users express when human-based service is needed versus assistance provided by technology.
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Barış Armutcu, Ahmet Tan, Shirie Pui Shan Ho, Matthew Yau Choi Chow and Kimberly C. Gleason
Artificial intelligence (AI) is shaping the future of the marketing world. This study is the first to examine the effect of AI marketing efforts, brand experience (BE) and brand…
Abstract
Purpose
Artificial intelligence (AI) is shaping the future of the marketing world. This study is the first to examine the effect of AI marketing efforts, brand experience (BE) and brand preference (BP) in light of the stimulus-organism-response (SOR) model.
Design/methodology/approach
The data collected from 398 participants by the questionnaire method were analyzed by SEM (structural equation modeling) using Smart PLS 4.0 and IBM SPSS 26 programs.
Findings
We find that four SOR elements of AI marketing efforts (information, interactivity, accessibility and personalization) positively impact bank customer BE, BP and repurchase intention (RPI). Further, we find that BE plays a mediator role in the relationship between AI marketing efforts, RPI and BP.
Originality/value
The findings of the study have significant implications for the bank marketing literature and the banking industry, given the limited evidence to date regarding AI marketing efforts and bank–customer relationships. Moreover, the study makes important contributions to the AI marketing and brand literature and helps banks increase customer experience with artificial intelligence activities and create long-term relationships with customers.
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Francesco Paolo Appio, Emanuele Cacciatore, Fabrizio Cesaroni, Antonio Crupi and Veronica Marozzo
The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access…
Abstract
Purpose
The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?
Design/methodology/approach
Using Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.
Findings
The findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.
Originality/value
This paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.
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Dora Agapito and Marianna Sigala
This paper aims to provide a critical reflection on the management of experiences in hospitality and tourism (H&T). The paper investigates the evolution of experience research…
Abstract
Purpose
This paper aims to provide a critical reflection on the management of experiences in hospitality and tourism (H&T). The paper investigates the evolution of experience research, while discussing the emerging challenges and opportunities for management.
Design/methodology/approach
The study adopts a critical and reflective approach for providing future directions of experience research. Three major fields are identified to discuss advances, challenges and opportunities in experience research: conceptualization and dimensions of experiences; relational network for experience management; and theoretical and methodological approaches.
Findings
The paper proposes a mindset shift to guide experience research, but also to redirect and research thinking and managerial practices about the role of experiences in the economy and society. This proposed humanized perspective to experience research and management is deemed important given the contemporary socio-economic, environmental and technological challenges of the environment.
Research limitations/implications
This paper identifies a set of theoretical and managerial implications to help scholars and professionals alike to implement the humanized perspective to experience research. Implications relate to conceptualization, relational network and theoretical and methodological approaches in experience research.
Originality/value
This study critically assesses research challenges and opportunities around customer experience management (CEM) in H&T contexts. This reflective and critical look at customer experiences not only informs future research for advancing knowledge and practice but also proposes a mindset shift about the role and nature of CEM in the society and economy.
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Rajat Kumar Behera, Pradip Kumar Bala, Nripendra P. Rana, Raed Salah Algharabat and Kumod Kumar
With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to…
Abstract
Purpose
With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.
Design/methodology/approach
The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.
Findings
The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.
Originality/value
The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.
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Valtteri Kaartemo and Anu Helkkula
Applications of artificial intelligence (AI), such as virtual and physical service robots, generative AI, large language models and decision support systems, alter the nature of…
Abstract
Purpose
Applications of artificial intelligence (AI), such as virtual and physical service robots, generative AI, large language models and decision support systems, alter the nature of services. Most service research centers on the division between human and AI resources. Less attention has been paid to analyzing the entangled resource relations and interactions between humans and AI entities. Thus, the purpose of this paper is to extend our metatheoretical understanding of resource integration and value cocreation by analyzing different human–AI resource relations in service ecosystems.
Design/methodology/approach
The conceptual paper adapts a novel framework from postphenomenology, specifically cyborg intentionality. This framework is used to analyze what kinds of human–AI resource relations enable resource integration and value cocreation in service ecosystems.
Findings
We conceptualize seven different human–AI resource relations, namely background, embodiment, hermeneutic, alterity, cyborg, immersion and composite relation. The sociotechnical entangled perspective on human–AI resource relations challenges and reframes our understanding of interactions between humans and nonhumans in resource integration and value cocreation and the distinction between operant and operand resources in service research.
Originality/value
Our primary contribution to researchers and service providers is dissolving the distinction between operant and operand resources. We present two foundational propositions. 1. Humans and AI become entangled value cocreating resources in inherently sociotechnical service ecosystems; and 2. Human and AI entanglements in value cocreation manifest through seven resource relations in inherently sociotechnical service ecosystems. Understanding the combinatorial potential of different human–AI resource relations enables service providers to make informed choices in service ecosystems.
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Although previous research has acknowledged the significance of comprehending the initial acceptance and adoption of ChatGPT in educational contexts, there has been relatively…
Abstract
Purpose
Although previous research has acknowledged the significance of comprehending the initial acceptance and adoption of ChatGPT in educational contexts, there has been relatively little focus on the user’s intention to continue using ChatGPT or its continued usage. Therefore, the current study aims to investigate the students’ continuance intentions to use ChatGPT for learning by adopting the stimulus–organism–response (SOR) model.
Design/methodology/approach
This study has employed the SOR model to investigate how UTAUT factors (such as performance expectancy, facilitating conditions, effort expectancy and social influence) influence the cognitive responses of students (e.g. trust in ChatGPT and attitude towards ChatGPT), subsequently shaping their behavioral outcomes (e.g. the intention to continue using ChatGPT for study). A sample of 392 higher students in Vietnam and the PLS-SEM method was employed to investigate students’ continuance intention to use ChatGPT for learning.
Findings
This study reveals that students’ continuance intention to use ChatGPT for learning was directly affected by their attitude toward ChatGPT and trust in ChatGPT. Meanwhile, their attitude toward ChatGPT was built on effort expectancy, social influence, and facilitating conditions and trust in ChatGPT was developed from effort expectancy and social influence.
Originality/value
By extending the analysis beyond initial acceptance, this research provides valuable insights into the factors that influence the sustained utilization of ChatGPT in an educational environment.
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Mengxi Yang, Walton Wider, Shuoran Xiao, Leilei Jiang, Muhammad Ashraf Fauzi and Alex Lee
This research is the first to use bibliometric analysis to provide insight into the landscape and forecast the future of customer experience research in the banking sector.
Abstract
Purpose
This research is the first to use bibliometric analysis to provide insight into the landscape and forecast the future of customer experience research in the banking sector.
Design/methodology/approach
We used bibliographic coupling and co-word analysis to delineate the existing knowledge structure after reviewing 338 articles from the Web of Science database.
Findings
The bibliographic coupling analysis revealed five key clusters: customer engagement and experience in digital banking; customer experience and service management; customer experience and market resilience; digital transformation and customer experience; and digital technology and customer experience—each representing a significant strand of current research. In addition, the co-word analysis revealed four emerging themes: customer experience through AI and blockchain, digital evolution in banking, experience-driven ecosystems for customer satisfaction, and trust-based holistic banking experience.
Practical implications
These findings not only sketch an overview of the current research domain but also hint at emerging areas ideal for scholarly investigation. While highlighting the industry’s rapid adaptation to technological advances, this study calls for more integrative research to unravel the complexities of customer experience in the evolving digital banking ecosystem.
Originality/value
This review presents a novel state-of-the-art analysis of customer banking experience research by employing a science mapping via bibliometric analysis to unveil the knowledge and temporal structure.
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