Navigating Human-Chatbot Interactions: An Investigation into Factors Influencing User Satisfaction and Engagement

Abstract

With the increasing integration of chatbots in various customer service contexts, understanding factors that influence user interactions is of paramount importance. While chatbots bring several benefits, their efficacy largely depends on user satisfaction, loyalty, and perceived utility. This study explores the nuances of consumer interactions with chatbot services and identifies ways to enhance these interactions for successful goal achievement. Through a multiple qualitative method approach, involving reflections, interviews, and focus groups, conducted an exhaustive investigation of the consumer experiences with chatbot interactions. The study focused on elements such as anthropomorphism, communication styles, service scripts, consumer emotions, and privacy and trust concerns. Our findings highlight that the anthropomorphism and communication style of chatbots significantly affect user satisfaction. The perceived utility of chatbots was found to be a multifaceted construct that substantially influences consumer engagement. Furthermore, this study identified negative emotions and privacy concerns as key determinants of consumer-chatbot interactions. These findings necessitate meticulous attention in chatbot design and function. By using the affordance theory, this research offers insights into managing the complex dynamics of satisfaction and dissatisfaction factors within consumer-chatbot engagements, contributing crucially to the human-computer interaction literature.

Keywords:

• Human-Chatbot interactions
• user satisfaction
• user engagement
• communication styles
• privacy concerns
• anthropomorphism
• affordance theory

1. Introduction

Chatbots, or digital conversational agents powered by Artificial Intelligence (AI), have gained immense popularity in various sectors, especially in the services sector. Their emergence and subsequent integration into these sectors underscore the pivotal role they play in enhancing service quality, efficiency, and performance (Agarwal et al., 2021; Ameen et al., 2022). Chatbots are valuable because they can imitate human-like discussions, providing them a dependable interface for client assistance (Agarwal et al., 2021). Their capacity to deliver empathetic responses, as suggested by Agarwal et al. (2021), particularly in customer service settings, underscores their ability to resonate with customers on a personal level. Beyond the emotional connection, chatbots also offer 24/7 service availability, instant responses, and the ability to handle multiple queries simultaneously, features that significantly enhance service quality (Aslam, 2023). Chatbots in e-retailing enhance the online customer experience by assuring usability and responsiveness (Chen et al., 2021).

The banking sector has particularly benefited from the chatbot revolution. The adaptive learning capabilities of chatbots, backed by AI, enable them to provide tailored banking solutions, thereby elevating the customer experience (Baabdullah et al., 2022). A study by Eren (2021) pertaining to a banking application in Turkey found that specific determinants such as perceived usefulness, ease of use, and social influence significantly affected customer satisfaction concerning chatbot use. In addition, Bouhia et al. (2022) emphasised that when customers engage with chatbots in customer service interactions in the banking industry, factors such as perceived utility, enjoyment, and trust play a crucial role and have more influence than privacy issues. It is also pertinent to note that the integration of chatbots has reshaped service quality metrics. Behera et al. (2021) argue that employing cognitive chatbots for tailored contextual customer care goes beyond the conventional excitement associated with AI-driven solutions. They cater to customer queries by harnessing vast amounts of data in real-time, ensuring more accurate and contextual responses. This shift toward AI-powered chatbots also seems to align with the findings of Blut et al. (2021), who established that the anthropomorphic characteristics of service provision entities, like chatbots, contribute positively to perceived service quality.

Further underlining their significance in the services sector, Chen et al. (2023) discovered that AI chatbots, when delivering high-quality service, can considerably bolster customer loyalty. This potential of chatbots to retain customers and instill brand loyalty cannot be understated, especially in a competitive market landscape. Moreover, the combined influence of augmented reality, chatbots, and social media has been observed to affect the self-esteem and body image of female customers belonging to Generation Z. This highlights the complex consequences of engaging with chatbots, as demonstrated by Ameen et al. (2022). Although chatbots offer numerous benefits, they are not without issues. Crolic et al. (2022) elucidated that when service failures occur, chatbots, due to their anthropomorphic nature, often become the targets of customers. Additionally, De Cicco et al. (2020) pointed out that the millennials’ attitude towards chatbots is significantly shaped by their perceived social relationship with the chatbot. Thus, the design, functionality, and communication style of chatbots need to be meticulously crafted to ensure optimal customer satisfaction and avoid potential backlash.

Cheng et al. (2022) conducted a study on e-commerce and proposed that the way consumers react to text-based chatbots is influenced by the complexity of the task and the disclosure of the chatbot. Simplistic tasks might not necessitate chatbot intervention, while intricate tasks may benefit from a chatbot’s assistance, provided there’s transparent disclosure about its AI nature. The study by Lee, Pan, & Hsieh (2022) further underscores this by highlighting the positive impact of AI chatbots as brand promoters, thereby solidifying their role in driving business performance. The emergence and use of chatbots, especially in the banking and services industries, signifies a fundamental change in how organizations engage with their customers. The discussed research presents convincing evidence of the diverse benefits of chatbots, spanning from higher service quality to improved company performance. Although chatbots offer a new opportunity for customer care, organizations must be cautious of potential drawbacks and consistently improve their chatbot strategy to achieve the highest level of consumer engagement and happiness.

Comprehending consumer interactions with chatbots is paramount (Lei et al., 2021). This stems from arising issues such as privacy (Bouhia et al., 2022) and adverse emotional responses (Crolic et al., 2022; Zhang et al., 2022). Engaging with chatbots effectively improves corporate agility (Wang et al., 2022) and strengthens customer loyalty (Chen et al., 2023). However, its mishandling could foster consumer aggression (Huang & Dootson, 2022). Factors like trust (Mozafari et al., 2022), service recovery (Yun & Park, 2022), and anthropomorphism (Blut et al., 2021) dictate consumers’ chatbot acceptance. Notwithstanding, literature presents knowledge gaps requiring exploration. Kushwaha and Kar (2021) emphasise the unique nature of interactions between agents and chatbots, which can be attributable to the human connection and psychological factors involved. Chen et al. (2021) highlighted a deficiency in the perceived benefits associated with the utilisation of chatbots in online retailing. They suggest conducting a comprehensive analysis of chatbot functionalities from the perspective of users. Moreover, Tran et al. (2021) highlighted the importance of distinguishing differences in chatbot interactions among various retail industries. This emphasises the lack of understanding of the distinctions between interactions between agents and chatbots (Kushwaha & Kar, 2021), as well as the value proposition of online chatbots (Chen et al., 2021). Consequently, this leads to the pressing research inquiry: “Which elements shape consumer-chatbot engagement, and how can this liaison be refined to meet consumer goals effectively?” This question seeks to deepen our grasp on consumer-chatbot dynamics, with a view to augmenting user satisfaction and business outcomes.

1.1. Literature review

The recent surge in technological advancements has profoundly shaped the dynamics of consumer-chatbot interactions. Focusing on the elements that define consumer-chatbot engagement is crucial in comprehending and refining this association to better serve consumer objectives. Agarwal et al. (2021) found that the presence of empathetic chatbots in customer support contexts greatly improves user engagement. A user interface that displays empathy is viewed as having more human characteristics, which enhances the overall interaction experience. Similarly, Ameen et al. (2022) explored the impact of chatbots in influencing the body image and self-esteem of Generation Z female consumers. The study suggested that, when coupled with augmented reality and social media, chatbots can significantly impact users’ perceptions of themselves. Aslam (2023) delved into the usability of chatbots in the retail fashion domain. The study proposed that in retail settings, the success of chatbots is typically determined by their ability to provide convenience and promptness from the perspective of consumer experiences. Baabdullah et al. (2022) found that virtual agents powered by AI can induce a flow experience in users. Such experiences, characterized by heightened concentration and enjoyment, can potentially boost engagement levels.

Blut et al. (2021) highlighted the growing trend of attributing human characteristics to service offering. Chatbots that display human-like characteristics are better received and foster stronger engagement. This mirrors Han’s (2021) findings, which underscored that anthropomorphism significantly impacts consumer purchase decisions in chatbot commerce. However, not all interactions with chatbots have been positively perceived. Bouhia et al. (2022) emphasised the privacy implications that arise when clients engage with chatbots. These concerns often stem from data misuse apprehensions or unauthorized sharing. Chen et al. (2021) presented a compelling viewpoint regarding the utilization of automated conversational agents as decision support tools. They proposed that matching a chatbot’s conversation style with a customer’s shopping task can elevate engagement. Chen et al. (2023) provided additional details on the relationship between AI service quality and client loyalty. Another pivotal element is the design and usability of these chatbots. Chen et al. (2023) emphasized the significance of developing chatbots that are in line with promoting student achievement in educational environments. This not only reinforces engagement but also ensures that chatbots effectively cater to the specific needs of the user. However, a recurring theme across several studies is the challenge of striking a balance. Crolic et al. (2022) pointed out that when chatbots err, consumers often anthropomorphize these mistakes, leading to heightened frustration. Similarly, Eren (2021) identified various determinants of customer satisfaction in chatbot usage, suggesting that while quick problem resolution is appreciated, the inability to understand complex queries can deter users.

Fan et al. (2023) addressed the ongoing discussion on the universal applicability of AI chatbots. Their emphasis was on the fact that although chatbots may provide numerous advantages, they are not a universal solution. Their effectiveness typically depends on their capacity to create experiences that deeply connect with people, both in terms of pleasure and cognition. Further, chatbot interfaces and their perceived visual aesthetics play a significant role in user engagement. Lavie and Tractinsky (2004) asserted that aesthetics significantly influences user perceptions and can shape overall interaction experience. The interplay between consumer and chatbot is multifaceted, shaped by various elements ranging from empathy, anthropomorphism, usability, design, and privacy. While chatbots present a promising frontier in enhancing consumer interactions, refining their capabilities, and ensuring they resonate with user needs is paramount. Efforts should be directed towards crafting chatbot experiences that not only align with, but also enrich, consumer goals.

Affordance theory, as propounded by Gibson (1977), focuses on the perceived actionable possibilities or properties an environment or object offers to its observer. In the context of consumer engagement with chatbots, affordance theory can be an instrumental lens through which we decipher how users interact with and perceive these digital assistants. According to Aslam (2023) study, the usability of retail fashion brand chatbots was largely shaped by consumers’ expectations and their experiences. The affordances of these chatbots, in terms of their functionality and design, interact with individual consumers’ goals and needs. This idea resonates with Gaver (1991) assertion about technology affordances, suggesting that users’ interactions with technological entities are deeply entwined with their perceived affordances. Agarwal, Maiya, and Aggarwal (2021) highlighted the significance of empathy in chatbots when it comes to customer support. They inferred that chatbots displaying a higher degree of empathy in their responses could potentially forge a stronger bond with the consumers. This aligns with the idea that the perceived affordances of chatbots go beyond mere functionality, touching upon emotional aspects.

This emotional connection is further corroborated by studies such as that by Chung et al. (2020), which highlights the satisfaction customers derive from chatbots associated with luxury brands. Nevertheless, this link is not direct or uncomplicated. As elucidated by Crolic et al. (2022), anthropomorphism can lead to increased anger in customer-chatbot interactions, especially when the chatbot does not meet expectations. Such findings underscore the importance of accurately aligning chatbot affordances with consumer expectations and goals. Blut et al. (2021) performed a meta-analysis to examine anthropomorphism in service offering. They concluded that although consumers may value humanoid traits in chatbots, it is crucial to maintain a proper balance to get the desired results. Leveraging the right affordances, be it cognitive, physical, sensory, or functional (Hartson, 2003), can make a difference in how consumers perceive and interact with chatbots.

The challenge in refining the liaison between consumers and chatbots lies in recognizing and acting upon these affordances. Chen et al. (2021) examined the usability and responsiveness of AI chatbots in e-retailing. They discovered that the customer experience was greatly influenced by how effectively the chatbot aligned with the user’s requirements. This highlights the importance of perceived affordances in determining outcomes. Moreover, El Amri and Akrout (2020) delved deeper into the concept of affordances in the realm of marketing. They asserted that the perceived design affordance of new products plays a pivotal role in consumer adoption. Regarding chatbots, this implies that the consumer’s perception of the design and functional capabilities of chatbots can greatly influence their adoption and continued usage. The affordance theory, when applied to consumer-chatbot engagement, reveals a nuanced landscape of expectations, perceptions, and outcomes. Chatbots, like other technical tools, offer many advantages to users. By effectively utilizing these advantages, and ensuring they are in line with the objectives of customers, it is possible to establish a more harmonious and productive connection between consumers and chatbots. This connection, steeped in the right blend of functional and emotional affordances, can ultimately lead to enhanced consumer engagement and satisfaction.

2. Methodology

Table 1 titled “rigorous methodology overview” presents a comprehensive outline of the research approach tailored to deeply comprehend consumer-chatbot engagement within the interpretivist paradigm. At its core, it holds the epistemological stance of interpretivism, emphasizing the socially constructed nature of reality, as described by Scotland (2012). This perspective is pivotal as it grants in-depth insights into personal experiences, becoming foundational to discerning consumer-chatbot interactions. The study’s relevance lies in its concentrated focus on individual encounters with chatbot services, directly syncing with the overarching aim to unveil the determinants of consumer-chatbot engagement. To further build upon this, the research leans on one theoretical pillar—Affordance Theory. This theory serves as an analytical lenses, illuminating personal perceptions—essential for honing chatbot interactions.

Table 1. Rigorous methodology overview.

Aspect	Description	Justifications
Epistemological Stance (Scotland, 2012)	Interpretivism: Emphasizes the socially constructed nature of reality.	Facilitates deep insights into the individual experiences, key for understanding consumer-chatbot engagement.
Relevance to Study	Focus on individual experiences of engaging with chatbot consumer services.	Directly aligns with the aim to understand elements shaping consumer-chatbot engagement.
Theoretical Frameworks (El Amri & Akrout, 2020; Herzberg, 1968)	Affordance Theory	Both frameworks offer a lens to understand individual perceptions, crucial for refining chatbot engagement.
Research Process	- Reflections - Semi-structured interviews - Focus group discussions	Comprehensive approach ensures varied insights, crucial for understanding and refining chatbot interactions.
Data Collection (Boud et al., 1985; Jamshed, 2014; Kitzinger, 1995)	1. Reflections: Immediate feedback post-chatbot engagement. 2. Semi-structured Interviews: Deeper insights into user experiences. 3. Focus Groups: Insights from marketers and IT professionals.	Direct feedback and discussions can reveal elements shaping engagement, informing improvements in chatbot-consumer liaison.
Research Approach (Thomas, 2006)	Inductive Approach: Allows for themes to emerge organically without imposing preconceived categories.	Induction helps in capturing unexpected elements and nuances influencing consumer-chatbot engagement.
Data Analysis (Braun & Clarke, 2006)	Thematic Analysis: Flexible method for analyzing qualitative data within an interpretive framework.	Helps identify recurring themes and elements shaping engagement, offering pathways to refine the liaison.

2.1. Research process

The depicted research process figure (see Figure 1) intricately interweaves multiple research elements to investigate chatbot strategies and personalized contextual customer service within the ambit of affordance theory. The adoption of a relativist ontology and social constructionism as the epistemological underpinning allows a nuanced exploration of users’ subjective experiences and the co-creation of meaning in interactions with chatbots. In this research process, problem definition serves as the foundation, focusing on chatbot strategies and perceived affordances, setting the stage for in-depth exploration. The application of various affordances enables a thorough analysis of chatbots in multiple dimensions, catering to personalized and contextual interactions.

Figure 1. Research process.

The utilization of qualitative approaches, such as reflection, interviews, and focus groups, in a triangulated manner emphasizes the rigorous methodology, enabling a comprehensive comprehension of users’ experiences and perceptions. These methods are instrumental in constructing meanings, developing new emerging themes, and subsequently contributing to the development of a comprehensive framework. This integrative approach, therefore, seems to focus on amalgamating diverse perspectives and experiences, enabling the emergence of insights grounded in users’ lived experiences and perceptions. While its concentration on subjectivity and qualitative richness is its strength, the inherent subjectiveness and potential lack of generalizability are aspects that necessitate careful consideration throughout the research journey.

2.2. Population and sampling

Given the detailed methodology provided, a justification of participant numbers and sampling technique is crucial. The study involves 24 ordinary users for reflections and 34 for interviews, allowing for immediate feedback and in-depth insights into user experiences with banking chatbots. Moreover, 18 IT and other experts from Qatar banks comprise the focus group participants to provide insights on enhancing financial chatbot services. These participant numbers are feasible as they offer a diverse range of perspectives and experiences to ensure the richness of the data. This study now integrates a comparative analysis with similar studies in the field. Notably, Naeem (2021) and Naeem and Ozuem (2021) utilized a similar sample size in their investigations, substantiating the depth and quality of insights derived from such participant pools. Similarly, Aslam (2023) successfully employed a similar modest sample to yield impactful, nuanced findings in chatbot research.

Snowball sampling is useful in this context as it enables the recruitment of participants through referrals from initial subjects, making it effective in identifying individuals that have significant experiences with banking chatbots. This sampling technique is advantageous, especially in interpretivist research, where gaining deep, qualitative insights is paramount. For this study, snowball sampling would aid in identifying and accessing users who have engaged with banking chatbots and IT experts who are knowledgeable about the subject matter, allowing for the collection of rich, varied, and relevant data. This would especially be helpful in ensuring that the participants for reflections and interviews are actual ordinary users of banking chatbots, while focus group participants are experts in the field, thus aligning with the study’s purpose and ensuring methodological congruity. Moreover, this study’s complex nature, focusing on user experiences and interactions with chatbots, demands a well-rounded and multi-perspective approach, which is facilitated by the chosen number of participants and the snowball sampling technique, providing depth and breadth in understanding the consumer-chatbot engagement in the banking sector in Qatar.

2.3. Information on targeted banking chatbots

1. Application Domains: The chatbots are situated within the banking sector of Qatar. Further details would expound upon specific functionalities and services they provide, such as facilitating transactions, providing customer service, assisting in loan applications, offering investment advice, and more. It would clarify the chatbots’ roles in facilitating smoother, more efficient interactions between the bank and its customers, possibly sharing specific instances or scenarios where chatbot interaction is prevalent.

2. Language: While English and Arabic would be a logical assumption given the geographical and cultural context, the revised study would provide explicit information on the languages the chatbots operate in. It would delve into how language nuances are tackled by chatbots, especially considering the emotive and empathetic interactions discussed in the study. The incorporation of local dialects, formal and informal language variations, and multilingual capabilities could be further elucidated.

3. Technical and Operational Details: An additional section might be included to provide a comprehensive understanding of the technical frameworks of the chatbots. This would span details such as the platforms they’re deployed on, the technology stack, data processing and storage, privacy safeguards, user interface design principles, and algorithmic foundations, especially those enabling empathetic and emotionally resonant interactions. This could also detail how chatbots adapt to evolving user needs and technological advancements, ensuring continual enhancement and relevance in user interactions.

4. User Demographics: The chatbots’ utility and functionality could be further illustrated against varied user demographics, shedding light on how different age groups, technical proficiencies, or financial service needs interact with and perceive the chatbots.

5. Ethical and Regulatory Compliance: In light of the empathetic interactions and emotional connections experienced by users, the revised study would elaborate on the ethical considerations and regulatory compliance in chatbot deployment. This would encompass data protection, user privacy, transparency in machine-human interactions, and adherence to financial regulatory norms.

2.4. Data collection and analysis

The research progression, depicted in Figure 1, comprises three stages: reflections, semi-structured interviews, and focus group discussions, ensuring a multifaceted understanding of chatbot interactions. The data collection mechanisms, influenced by scholars like Boud et al. (1985), Jamshed (2014), and Kitzinger (1995), integrate reflections for immediate post-engagement feedback, semi-structured interviews for an intimate grasp of user experiences, and focus groups to capture insights from the professionals behind the chatbot services. Pivoting towards the methodology, an inductive approach, championed by Thomas (2006), has been selected. This strategy lets organic themes surface without the shackles of pre-set categories, making it possible to catch even the unexpected nuances in consumer-chatbot engagements. In the final analysis stage, the study employs thematic analysis—a flexible, interpretive-aligned method detailed by Braun & Clarke (2006). This approach is adept at pinpointing recurring patterns and elements in engagement, thereby suggesting ways to fine-tune the consumer-chatbot dynamic.

To derive an all-encompassing grasp of the subject matter being explored, the data collection process was organized into a triad of sequential stages. Initiating this comprehensive methodology, the initial phase was characterized by the incorporation of reflections from participants who had previously interacted with chatbot services. By seeking these participants’ immediate sentiments and viewpoints in the aftermath of their chatbot interaction, an abundant reservoir of genuine insights into their experiences was accessed. Such an approach, which centered on reflections, served as a conduit to delve into participants’ authentic perceptions and immediate responses, insights which may potentially remain elusive when using more conventional methods like standard interviews (as highlighted by Boud et al., 1985). This methodology of leaning on reflection finds its philosophical roots in the interpretivist framework, given its core principle of comprehending individuals’ experiences as they perceive them, affirming its relevance and efficacy in addressing the focal research query. Moving ahead, the research’s second stage transitioned into the realm of semi-structured interviews with the same participants. This method was chosen for its inherent adaptability, allowing the researcher to navigate the conversation with participants organically, thereby probing potentially enlightening tangents, all while maintaining fidelity to key research pointers (as underscored by Jamshed, 2014). This semi-structured nature seamlessly aligns with the inductive methodology and the overarching interpretivist lens, championing an intimate exploration of the participants’ actual lived experiences and the subjective interpretations they associate with them.

The third and concluding phase of data collection then pivoted to focus group discussions, integrating perspectives from the professionals—marketers and IT specialists. These conversations were instrumental in introducing a fresh, pragmatic viewpoint to the study, shedding light on the intricacies, dilemmas, and considerations intrinsic to the deployment and stewardship of chatbot systems. Engaging in focus groups, as Kitzinger (1995) elucidates, catalyzes a synergistic interchange of viewpoints, engendering profound insights via the spirited dynamism inherent to group deliberations. The strategic inclusion of these diverse professional discussions imbued the study with a multifaceted comprehension, resonating with interpretivism’s core principle of understanding phenomena through varied lenses. Steering the discussion towards the theoretical scaffolding of the research, its foundation lies in the inductive methodology. This is inherently congruent with studies steeped in the interpretivist paradigm, as it promotes the spontaneous surfacing of themes from the raw data, negating the imposition of pre-set classifications, a notion articulated by Thomas (2006). Complementing this, the study harnessed the power of thematic analysis, a technique celebrated for its adaptability and theoretical alignment with qualitative data scrutiny within the interpretivist matrix, as championed by Braun and Clarke (2006). Summarizing, the adopted methodology, with its participant-centric, inductive essence, harmoniously resonates with the interpretivist epistemological stance, facilitating a sophisticated and layered probe into the dynamics steering consumer-chatbot interactions. Figure 2 highlighted the thematic analysis process for this study.

Figure 2. inductive thematic analysis process.

3. Findings

Table 2 delineates overarching themes with their corresponding codes to navigate the complex landscape of consumer-chatbot engagement. The first, “Digital Humanism”, plunges into the realm of chatbot-human interactions, moving beyond simple task-oriented functions to touch the very fibers of emotional connection. “Soulful Machines” underscores chatbots that transcend the ordinary, echoing emotions we’d typically attribute to humans. “Echoed Sentience” emphasizes those eureka moments when chatbots, through sophisticated algorithms, mirror human empathy, emphasizing the chatbot’s potential to refine the human-bot relationship. Lastly, “Morphic Ethos” opens Pandora’s box of ethical considerations, questioning the propriety of infusing too much humanity in digital entities. The second theme, “Technological Symbiosis”, explores the integration of chatbots’ technological functionalities with human objectives. “Harmonized Utility” delves into achieving the right blend of chatbot design, potential, and user expectations. Meanwhile, “Affordance Odyssey” presents a user-centric journey through the maze of chatbot functionalities, mapping user experiences, perceptions, and revelations. “Confluence Points”, as the name suggests, points towards those golden moments where everything aligns—chatbot capabilities, design, environment, and user needs. In essence, this table not only structures the study’s focal points but also hints at the harmonious potential and ethical dilemmas of future chatbot-human interactions.

Table 2. Themes, codes, and alignment with aim of this study.

Theme Name	Theme Definition	Code Name	Code Definition	Justification for Alignment with Study Aim
Digital Humanism	Exploring the profound interactions between chatbots and humans that go beyond mere functionality and touch on the emotional.	Soulful Machines	Instances where chatbots display depth, evoking profound human-like emotions.	Emphasizes the need to study how chatbots can be more than tools but entities that resonate emotionally with consumers, enhancing engagement.
		Echoed Sentience	Moments where chatbots display uncanny empathy, mirroring human understanding.	Aligns with the research question by highlighting the essence of human-like understanding in refining chatbot-consumer engagement.
		Morphic Ethos	Scrutiny of ethical concerns when chatbots display heightened anthropomorphic features.	Helps in deciphering the ethical boundaries of chatbot designs, especially when aiming for a seamless consumer engagement. This aids in addressing how the relationship can be refined without crossing ethical lines.
Technological Symbiosis	The intricate balance and interaction between chatbots, their design, functionality, and the consumers’ needs and goals.	Harmonized Utility	Exploration of the equilibrium between what a chatbot is designed to do, what it can do, and what the consumer needs it to do.	Directly addresses the liaison between chatbot capabilities and consumer needs, emphasizing the refinement of this relationship for enhanced engagement.
		Affordance Odyssey	A journey through user perceptions, challenges, and revelations as they interact with a chatbot’s designed and perceived functionalities.	This code enriches the study by tracing the user’s navigation through the chatbot’s affordances, aligning with the research question on which elements shape the engagement.
		Confluence Points	Instances where there’s a perfect alignment between a chatbot’s design, its functionalities, the environment, and the consumer’s immediate needs.	Focuses on moments of perfect harmony in the chatbot-consumer relationship, directly addressing how the liaison can be optimally refined for maximum effectiveness. This directly pertains to the study’s quest to understand the fine-tuning of chatbot-consumer interactions.

3.1. Theme 1: Digital humanism

Exploring the profound interactions between chatbots and humans that go beyond mere functionality and touch on the emotional.

• ○ Soulful Machines: Capturing instances where chatbots transcend mere functionality and evoke deeper, human-like emotional responses.

• ○ Echoed Sentience: Recognizing moments where chatbots mirror human empathy and understanding, creating a semblance of consciousness.

• ○ Morphic Ethos: Examining the ethical implications and expectations when chatbots take on anthropomorphic characteristics, especially when these might lead to heightened emotional responses from users.

The following Table 3 elucidates the frequency and themes of three distinct codes: “Soulful Machines,” “Echoed Sentience,” and “Morphic Ethos,” derived from various data sources (Interviews, Reflections, Focus Groups) in a study exploring chatbot interactions within Qatar’s banking sector, highlighting the emotional, empathetic, and ethical dimensions embedded in technology-human interactions.

Table 3. Frequencies of codes based on provided data.

Code	Mentions in Interviews	Mentions in Reflections	Mentions in Focus Groups	Total Mentions	Notable Aspects
Soulful Machines	4	2	4	10	Emotional connections, empathetic responses, ethical boundaries
Echoed Sentience	3	3	3	9	Mirroring empathy, providing genuine moments, ethical concerns
Morphic Ethos	0	0	7	7	Anthropomorphism, transparency, ethical considerations

3.1.1. Code 1: Soulful Machines

The “Soulful Machines” code seeks to understand the deeper, emotionally resonant interactions between consumers and chatbots in the banking sector of Qatar. It dives into moments where chatbots move beyond their primary functional roles and elicit human-like emotional reactions from consumers. Consumer experiences indicate a varying degree of emotional connection with chatbots. One consumer shared, “I never thought I had said this, but sometimes the chatbot feels like it truly understands my financial worries” (Interview, P.3). This sentiment highlights an unexpected emotional connection that transcends basic transactional interactions. Another consumer voiced, “The chatbot seemed genuinely concerned when I expressed hesitation about a financial decision” (Interview, P.7), pointing to the chatbot’s design emphasizing empathy. However, not all consumers experienced similar sentiments. As one stated, “It’s just a machine. I don’t expect it to understand human feelings” (Reflection, P.10). Such reservations indicate the challenges of universally embedding emotional intelligence into chatbots. On the same note, a user observed, “I was taken aback when the chatbot responded with comforting words during my loan application process” (Reflection, P.5), indicating a potential surprise at the depth of a chatbot’s emotional capability.

Marketers and developers saw the potential of such emotional interactions. A marketer said, “We aim for our chatbot to be more than just a transaction tool. It should connect emotionally” (Focus Group, P.6). An IT engineer shared, “Injecting empathy algorithms into our chatbot was challenging but essential” (Reflection, P.8), underscoring the technical challenges of creating “soulful machines”. Another developer noted, “Seeing consumers form bonds with our chatbot feels like a job well done” (Focus Group, P.9). Yet, the importance of maintaining a balance was clear. A banking executive cautioned, “While we want our chatbot to connect, we don’t want it to overstep its boundaries” (Interview, P.14), hinting at the need to ensure ethical considerations in chatbot design. A consumer insight brought this to the fore: “It’s comforting to have the chatbot understand my feelings, but it shouldn’t get too personal” (Interview, P.3). In the context of Qatar’s banking sector, the “Soulful Machines” code unravels the layered dynamics of emotionally intelligent chatbots. The emotional resonance offers a profound engagement avenue, making chatbots more relatable and responsive to user sentiments. However, it’s a delicate balance, as diving too deep can blur boundaries and raise concerns. By integrating emotional intelligence judiciously and addressing potential pitfalls, Qatari banks can truly leverage the strength of “Soulful Machines” to foster stronger, more meaningful consumer engagements.

3.1.2. Code 2: Echoed Sentience

The “Echoed Sentience” code delves into instances where chatbots, in the banking domain of Qatar, not only respond to queries but mirror human empathy and understanding, evoking a sense of consciousness. This facet of chatbot development pushes the boundary of typical engagement, striving to resonate with consumers on a more profound, intuitive level. Numerous consumers felt this deeper connection. “The chatbot did not just answer; it felt like it truly got my concerns,” expressed one user (Interview, P.5). This sentiment underpins the potential for chatbots to go beyond mere information dispensing. Another user reflected, “There was a moment when I felt like I was conversing with a real bank representative. The chatbot’s response was just so… human” (Interview, P.12). Such experiences emphasize the successful integration of empathetic algorithms.

However, this augmented reality wasn’t universal. A user mentioned, “I appreciate the efficiency, but expecting a machine to truly understand me is a stretch” (Reflection, P.11). This showcases the skepticism some consumers have towards the emotional prowess of chatbots. “I was puzzled when the chatbot seemed to sense my hesitation in choosing an investment plan” (Reflection, P.6), reveals another user, suggesting that the semblance of consciousness can sometimes surprise, or even unsettle, customers. From the developer and marketer side, this approach holds promise. A developer noted, “Building a chatbot that not only responds but also “feels’ is the next frontier” (Focus Group, P.14). The challenge and allure of creating sentient-seeming machines are evident. “Our goal isn’t just efficiency. It’s about creating genuine moments of connection” (Reflection, P.7), said a marketer, highlighting a shift in strategic focus.

However, ethical considerations are significant. An executive from a bank remarked, “We tread carefully. Mirroring human empathy is powerful, but we always respect user boundaries” (Interview, P.15). As a testament to potential oversteps, a user shared, “The chatbot’s response was eerily accurate in gauging my mood. I wasn’t sure how to feel about it” (Interview, P.1). Within the Qatar banking milieu, the “Echoed Sentience” code paints a picture of the evolving relationship between consumers and chatbots. The incorporation of empathetic mirroring enhances consumer engagement, pushing chatbots closer to authentic human interactions. While this presents unprecedented engagement potential, it also mandates careful navigation to ensure ethical boundaries remain intact. Striking this balance is paramount to harnessing the transformative power of chatbots that truly understand.

3.1.3. Code 3: Morphic Ethos

The “Morphic Ethos” code explores the intriguing dynamics of anthropomorphism in chatbots within Qatar’s banking sector. As chatbots increasingly exhibit human-like attributes, the banking community grapples with the ethical concerns these characteristics evoke, especially when they elicit heightened emotional reactions from consumers. From the perspective of the IT experts and bank service providers, sentiments varied. One expert remarked, “Giving chatbots a “face” or “voice” might foster trust, but at what cost?” (Focus Group, P.2). This sentiment encapsulates the underlying tension between utility and ethical considerations in anthropomorphic design. Another chimed in, “Customers seem to prefer human-like interactions, but we need to be transparent about it” (Focus Group, P.5). The line between enhancing user experience and maintaining transparency is indeed thin. “When a chatbot mirrors human nuances, it can be both captivating and concerning,” observed a service provider (Focus Group, P.9). Meanwhile, another participant emphasized, “We’re aiming for approachability in our chatbots, not deception” (Focus Group, P.10).

However, the emotional entanglements resulting from anthropomorphic features are undeniable. “I have heard consumers mention feeling ‘heard’ by our chatbot. It’s both rewarding and alarming,” expressed an IT expert (Focus Group, P.12). This sentiment was further validated by another focus group respondent, “Users sometimes forget they’re interacting with code. That’s a testament to tech, but it’s a double-edged sword” (Focus Group, P.15). The banking community remains acutely aware of the potential pitfalls. “Ethical considerations should be at the forefront. A chatbot’s ‘empathy’ can’t replace human understanding” (Focus Group, P.6), argued one expert. Echoing the caution, another expert voiced, “We need to ensure consumers realize the boundaries of a chatbot’s ‘emotions’” (Focus Group, P.14). In the heart of Qatar’s banking realm, the “Morphic Ethos” code underscores the complex interplay of innovation and ethics. The allure of anthropomorphic chatbots and their potential to elevate user engagement is evident. However, there’s a pressing need for clear ethical guidelines, ensuring transparency and understanding. As banks continue to tread this delicate balance, the focus remains on providing an enhanced, yet authentic, user experience without compromising trust.

3.2. Theme 2: Technological symbiosis

The intricate balance and interaction between chatbots, their design, functionality, and the consumers’ needs and goals.

• ○ Harmonized Utility: Exploring the balance between design, function, and user needs, revealing the ideal chatbot that works in harmony with its user.

• ○ Affordance Odyssey: Tracing the journey of users as they navigate the chatbot’s perceived affordances, leading to revelations, challenges, and epiphanies.

• ○ Confluence Points: Pinpointing moments where user needs, chatbot design, and the greater environment align perfectly, creating a seamless consumer-chatbot engagement.

Table 4 encapsulates the prevalence of three distinct codes within varied data sources in Qatar’s banking chatbot study. While “Harmonized Utility” leads in total mentions, reflecting its notable user experience emphasis, “Affordance Odyssey” and “Confluence Points” underscore vital user journeys and harmonious user-chatbot-environment interactions respectively, each with unique challenges and facets worth deeper exploration in subsequent analyses.

Table 4. Frequencies of codes.

Code	Mentions in Interviews	Mentions in Reflections	Mentions in Focus Groups	Total Mentions	Notable Aspects
Harmonized Utility	8	5	6	19	Synergy of design and function, user experience, intuitive alignment, functionality, trust, security
Affordance Odyssey	6	7	4	17	User journey, perceived capabilities, challenges, self-discovery, learning from issues, epiphanies
Confluence Points	5	4	7	16	Harmonious intersections, user/chatbot/environment synergy, regulation adherence, cultural respect, trust

3.2.1. Code 1: Harmonized utility

The “Harmonized Utility” code investigates the interplay of design, function, and user needs within Qatar’s banking chatbots, aiming for an optimal synergy to enhance the user experience. For consumers, the symbiosis between chatbot design and personal banking objectives is essential. “A chatbot should intuitively align with my banking needs,” one user suggested (Interview, P.8). In contrast, a younger consumer highlighted, “Its interface should be instinctive. Banking should feel effortless” (Interview, P.16). Focus group discussions reflected a keen awareness of this balance. One participant said, “Marrying design aesthetics with robust functionalities is the challenge and the goal” (Focus Group, P.1). Another added, “The endgame is a chatbot that feels like an extension of the user’s financial mindset” (Focus Group, P.5). Functionality and user goal alignment remain paramount. A user pointed out, “Beyond its look and feel, it should drive my financial goals forward” (Reflection, P.3). Elaborating on proactive capacities, another user remarked, “Guidance on potential investments would set it apart” (Interview, P.21).

The developer perspective from the focus group sessions emphasized iterative refinement. “It’s about continual adjustments based on feedback for the ultimate user experience” (Focus Group, P.8). Another participant stated, “Designing with empathy is essential; it’s not just about codes and algorithms” (Focus Group, P.10). Security and trust, especially in financial matters, emerged as non-negotiables. A user emphasized, “Trust in its data handling is crucial. It’s my finances we’re talking about” (Interview, P.7). Echoing this sentiment from a banking lens, a focus group member stated, “Building that trust via transparency in design is foundational” (Focus Group, P.6). Yet, achieving this harmonized utility isn’t universal. “There are instances where the bot feels detached, lacking a personal touch,” shared a user (Reflection, P.12). Addressing this, a focus group participant offered, “The pursuit is the perfect blend: technical prowess with a dash of humanity” (Focus Group, P.4). In the dynamic banking arena of Qatar, the “Harmonized Utility” code offers a roadmap. The quintessential chatbot stands at the intersection of responsive design, robust function, and user-aligned goals. With user feedback and technological advancements as guiding stars, the future beckons for chatbots that not just serve, but harmonize with, the evolving needs of Qatar’s banking populace.

3.2.2. Code 2: Affordance Odyssey

The “Affordance Odyssey” code illuminates the intricate journey of users as they grapple with the chatbot’s perceived affordances within Qatar’s banking landscape. It offers a deep dive into the discoveries, stumbling blocks, and moments of clarity consumers experience as they interact with these digital banking assistants. From the outset, the anticipation of what chatbots might offer is evident. “I approached it thinking it’d streamline my banking, but it was so much more,” a user reflected (Interview, P.30). Another added, “Its capabilities were like hidden layers; each interaction unveiled something new” (Reflection, P.11). The focus group discussions mirrored this sense of exploration. “Users embark on a voyage with our chatbots, and we need to ensure the journey is enriching,” commented one participant (Focus Group, P.2). Another noted, “The initial impressions are pivotal; the chatbot’s immediate offerings set the pace” (Focus Group, P.5). However, with perceived capabilities come challenges. One user lamented, “Sometimes it promises more than it delivers. It’s frustrating” (Interview, P.6). While another shared, “Navigating its features felt like a maze, but the ‘aha’ moment when I finally got it was worth it” (Reflection, P.14).

Delineating the intention behind chatbot designs, focus group insights highlighted the essence of perceived affordances. “We design aiming to hint at possibilities, nudging users towards self-discovery” (Focus Group, P.9). Another participant added, “It’s like laying breadcrumbs for users to follow, leading to richer engagements” (Focus Group, P.11). Yet, the road isn’t without its pitfalls. A user observed, “When I thought it’d guide me in investments, it fell short” (Interview, P.22). Addressing these challenges, a focus group member said, “Every hiccup a user faces is a lesson for us. It directs our next iteration” (Focus Group, P.7). Moments of realization or epiphanies punctuate this odyssey. “When I least expected it, the chatbot preempted my needs, saving me effort and time” (Reflection, P.10). Validating this, a focus group participant mentioned, “Designing for those ‘Eureka’ moments is our North Star” (Focus Group, P.3). Within the bustling banking corridors of Qatar, the “Affordance Odyssey” code delineates a narrative of exploration, revelation, and continual learning. As users chart their way through the chatbot’s offerings, the intersections of anticipation, challenge, and enlightenment mold their banking journey. This odyssey, replete with its highs and lows, encapsulates the transformative potential of chatbots in reshaping consumer engagements in Qatar’s financial realm.

3.2.3. Code 3: Confluence Points

The “Confluence Points” code delves into the harmonious intersections in Qatar’s banking sector where chatbot design, user aspirations, and the larger ecosystem converge, resulting in unparalleled, seamless consumer-chatbot engagements. One user described a moment of sheer alignment: “Everything just clicked. My query, the chatbot’s response, and my banking needs – it was synergy in real-time” (Interview, P.28). Another user resonated with this sentiment, saying, “I felt the chatbot and I were on the same wavelength; it was almost poetic” (Reflection, P.15). Focus group discussions illuminated the intention behind these pinnacle moments. “We strive for these junctures where everything aligns – it’s our zenith of user engagement,” a participant shared (Focus Group, P.3). “The confluence is a testament to when design meets genuine user needs,” added another (Focus Group, P.5). Notably, the greater environment – the digital infrastructure, banking regulations, and cultural norms of Qatar – plays a pivotal role. “Ensuring the chatbot aligns with Qatar’s unique banking landscape is crucial for these confluence moments,” emphasized a focus group member (Focus Group, P.7).

Users too felt the ripple effects of this alignment. “The chatbot was intuitively attuned to the local banking regulations, guiding me flawlessly,” a consumer noted (Interview, P.8). Another recounted, “The chatbot respected cultural nuances in our interactions, making me feel truly seen and understood” (Reflection, P.14). Yet, achieving these moments isn’t without its challenges. A focus group participant explained, “It’s like hitting a moving target. User needs evolve, regulations shift, and technology advances” (Focus Group, P.11). Another participant pointed out, “It’s a dance, coordinating between user needs, chatbot design, and the larger environment. But when it works, it’s magic” (Focus Group, P.6). Such moments also inspire trust. “When the chatbot seamlessly navigated me through a complex transaction respecting all local norms, my trust in digital banking deepened,” shared a user (Interview, P.32). This was echoed in the focus group, “Trust amplifies at these confluence points; it’s where loyalty is cemented” (Focus Group, P.18. In the intricate tapestry of Qatar’s banking milieu, the “Confluence Points” code highlights the symphonic moments of alignment, where all elements come together in perfect harmony. These moments, though elusive, epitomize the potential of chatbots in delivering an unparalleled user experience. As the quest for more such points continues, the evolving dance between users, chatbots, and the environment takes center stage, driving the future of digital banking in Qatar.

Digital Humanism delves into the depth of interactions, transcending mere functionality. Soulful Machines underscore the unexpected emotional connections users form with chatbots. Some users feel deeply understood, while others remain skeptical of a machine’s emotional depth. There’s a delicate dance between evoking genuine emotions and ensuring ethical boundaries. Meanwhile, Echoed Sentience reflects chatbots mirroring human empathy, presenting a semblance of consciousness that can both amaze and unsettled users. As chatbots strive for deeper connections, a question arises: how “human” should these machines become? Morphic Ethos delves into this conundrum. With chatbots increasingly exhibiting human traits, ethical concerns are paramount, especially when users forget they are conversing with code. The tension between enhancing user experience and maintaining transparency is a constant theme.

Technological Symbiosis highlights the balance between chatbot design, functionality, and users’ needs. Harmonized Utility emphasizes the interplay of these elements to enhance user experience. Users seek intuitive and efficient interfaces that not only look good but drive their financial goals. For developers, this involves a relentless pursuit of refining designs, ensuring security, and occasionally, infusing a touch of humanity. Affordance Odyssey sheds light on the users’ explorative journey with chatbots. It’s a path of discovery, sometimes punctuated with challenges, but rewarding when users uncover hidden functionalities. Lastly, Confluence Points epitomizes moments when chatbot design, user aspirations, and Qatar’s banking ecosystem harmoniously converge. These elusive moments of alignment, deeply rooted in cultural nuances and local regulations, deepen user trust and offer a glimpse of the chatbot’s transformative potential. Together, these themes and codes offer a rich tapestry of insights, reflecting the evolving dance between chatbots, users, and the broader environment, shaping the future of digital banking in Qatar.

4. Discussion

In the context of Qatar’s banking sector, the theoretical framework (see Figure 3) interweaves elements to elucidate how financial service chatbots can meet customer needs and goals. Digital humanism emphasizes human-centric values and ethical considerations in chatbot technology, fostering interactive communication essential for user engagement in the financial sector. Interactive communication is instrumental in exerting influence, keeping users engaged, motivated, and attracted to the banking services offered, while the approach of “soulful machines” ensures that interactions are meaningful and empathetic. Harmonized utility and affordance odyssey work in tandem to facilitate seamless and beneficial user experiences, emphasizing delivering the right information to the right person, a crucial element in banking services to meet diverse customer needs effectively. These elements are particularly significant in fostering encouraging environments, ensuring that users feel supported and understood in their interactions with chatbots, thereby, enhancing user satisfaction and experience in the Qatar banking sector.

Figure 3. Digital humanism in chatbot technology.

In light of Gibson’s Affordance Theory and the coded data presented—particularly, the “Affordance Odyssey” code—it’s compelling to explore how physical affordances, especially in chatbot-technology in the Qatar banking sector, have been discerned and evolved. Initially, the exploration of chatbot capabilities by users unfolds as an intricate journey, unlayering latent functionalities and navigating through a technological “maze.” Users enter this digital interaction with preconceived notions—anticipating streamlined, efficient, and perhaps impersonal experiences. Yet, as they meander through the chatbot’s functionalities, they unveil capabilities, sometimes encountering unexpected emotive responses and even moments of empathetic engagement, as highlighted in the “Soulful Machines” and “Echoed Sentience” codes. These hidden, emotive layers subtly derive from the chatbot’s algorithms, embedding a semblance of “understanding” or “empathy” into these digital interactions. As users explore, they decipher these unspoken, non-physical affordances which, while inherently non-emotional and non-conscious, echo a pseudo-empathetic resonance, simulating human-like interaction. This emotional coding, crafted meticulously by developers and marketers, invites users to forge connections, bridging functionality with an unexpected emotional depth. Thus, physical affordances translate not merely into tangible or direct actions but extend into an intangible realm, an odyssey of discovering emotional and empathetic undercurrents, blurring technological and human interaction boundaries. This subtle, sophisticated interplay of affordances demands ongoing scrutiny, ensuring ethical and empathetic dimensions align with user expectations and engagement realities.

The integration of confluence points and the scope of communication widen the horizon of interaction between customers and chatbots, ensuring that the morphic ethos sustains the adaptability and relevance of chatbots to the evolving needs of customers in the financial sector. Technological symbiosis enables a mutually advantageous association between users and chatbots, augmenting the capacity of chatbots to comprehend and satisfy users’ requirements with precision and efficiency. Echoed sentience ensures the chatbots’ capability to resonate with users’ needs and sentiments, enhancing the overall user experience by providing personalized and contextually relevant interactions. These interconnected elements collectively contribute to achieving excellence in financial services by aligning with customers’ needs and goals, enabling them to experience enriched and harmonious utility in the dynamic environment of Qatar’s banking sector.

The Nexus of Digital Humanism and Chatbot Design: One of the profound revelations from our dataset, presented in Table 4, is the intricate marriage between human emotional needs and technology. This ties closely with the notion of Digital Humanism, particularly the code Soulful Machines. The question arises: how far should we stretch the boundaries of chatbots to resemble human emotions? Luo et al. (2023) propose that the effectiveness of a chatbot in mirroring human emotions is directly related to its usefulness. But does this mean a more emotionally tuned chatbot is always superior? Chen et al. (2023) offers a little more nuanced viewpoint. While mirroring human understanding, epitomized in our code “Echoed Sentience”, boosts user satisfaction, there’s a danger zone. Excessive anthropomorphism can blur the ethical lines—a sentiment captured by our Morphic Ethos code. Han (2021) further iterates this dilemma. When chatbots become too human, consumers might feel manipulated, leading to trust erosion. Therefore, while pushing the boundaries of AI’s emotional capabilities seems enticing, it’s a double-edged sword.

The Balancing Act of Technological Symbiosis: Our theme of Technological Symbiosis brings forth the inherent challenge of interlacing human objectives with the evolving capabilities of chatbots. Here, the focus is not just on the chatbot’s capability, but also on how humans perceive and use it. The code for Harmonized Utility exemplifies this challenge. Although a chatbot may be technologically advanced, its effectiveness diminishes if it does not meet user expectations. This is supported by Xu et al. (2022), emphasizing the alignment between design and user anticipation as paramount. However, the user’s journey, denoted by Affordance Odyssey, is dynamic. As users evolve in their understanding and expectations, so must the chatbot’s design and functionalities. The research conducted by Riikkinen et al. (2018) emphasizes the importance of constant adaption in order to maintain customer happiness over time. Finally, although Confluence Points may appear to be the pinnacle of chatbot-human interaction, they are transient. According to Fan et al. (2023), it is important to remember that these significant occasions necessitate ongoing adjustment. In a rapidly advancing technological environment, what’s harmonious today might be discordant tomorrow.

Table 5 provides an in-depth examination of key factors and their justifications in relation to the affordance theory, specifically focusing on chatbots. Gibson (1977) created affordance theory, which posits that perception of the world involves not just recognizing item shapes and spatial relationships, but also understanding the potential actions that objects enable (affordances) and their functional utility. This perspective has profound implications for the design and user experience of chatbots in service settings. Each of the major codes identified in the table seems to highlight a specific aspect or characteristic of chatbots. For example, “Soulful Machines” dives deep into the emotional aspect of chatbot-user interactions. The difference between basic emotional recognition and deep emotional resonance is crucial. As indicated by Lavie and Tractinsky (2004), aesthetic affordances play a pivotal role when users emotionally resonate with chatbot interactions. This emotional engagement enhances the overall user experience, reflecting the importance of design aesthetics in determining how users interact with and perceive chatbots.

Table 5. Understanding major findings in relation to affordance theory.

Major codes	Motivator Factors (Enhance Satisfaction)	Justifications
Soulful Machines	Deep Emotional Resonance	The chatbot’s capability to engage at an emotional level can be tied to aesthetic affordances, where users emotionally resonate with the chatbot interaction, enhancing their overall experience (Lavie & Tractinsky, 2004).
Echoed Sentience	Mirroring Human Empathy & Consciousness	The chatbot’s ability to reflect a semblance of human understanding represents cognitive affordances, where users perceive the bot as understanding their concerns and needs (Norman, 1988).
Morphic Ethos	Ethical Transparency in Anthropomorphic Design	As chatbots exhibit more human-like features, the socio-cultural affordances become critical. They need to cater to societal and cultural expectations without misleading users (Norman, 1988).
Technological Symbiosis	Harmonious Design-Function Alignment	Design and functionality of chatbots need to align seamlessly, ensuring that the system affords the user a smooth, efficient, and intuitive banking experience (Hartson, 2003).
- Harmonized Utility	Alignment with Personal Banking Objectives	The balance between aesthetics (aesthetic affordance) and utility (functional affordance) ensures an optimal user experience, making banking feel effortless (Lavie & Tractinsky, 2004; Hartson, 2003).
- Affordance Odyssey	Unveiling Advanced, Unique Capabilities	As users explore and discover more about the chatbot, the cognitive affordances come into play, where the system’s potential capabilities align with user expectations and comprehension (Norman, 1988).
- Confluence Points	Moments of Perfect Alignment & Synergy	These perfect moments of alignment can be related to functional and sensory affordances, where the chatbot responds seamlessly, meeting or even exceeding user expectations (Hartson, 2003; Gaver, 1991).

“Echoed Sentience” and “Morphic Ethos” emphasize the chatbot’s cognitive and socio-cultural affordances. According to Norman (1988), the way consumers perceive a system or item, such as a chatbot, is affected by its design and operation. A chatbot that can mirror human empathy or exhibit anthropomorphic features resonates with users on a deeper level. However, it’s essential, as the table suggests, that these features do not mislead users, thereby reflecting the socio-cultural affordances noted by Norman. The “Technological Symbiosis” and “Harmonized Utility” rows indicate the seamless integration of design aesthetics and functionality. Hartson (2003) and Lavie & Tractinsky (2004) have highlighted the importance of achieving a harmonious combination of aesthetic and functional affordances in chatbots. An optimal user experience is achieved when a user feels the chatbot’s design aligns perfectly with their personal banking objectives, making the interaction feel intuitive and effortless.

“Affordance Odyssey” and “Confluence Points” emphasize the exploration and discovery aspect. Users need to feel that as they explore the chatbot’s features, the chatbot is evolving and aligning with their expectations. Norman (1988) noted that the system’s potential capabilities should align with user expectations and comprehension, indicating the importance of cognitive affordances. The cited sources, Agarwal et al. (2021) and Ameen et al. (2022), indicate that substantial investigation has been conducted to comprehend the function of chatbots in customer care environments, underscoring the significance of chatbots in contemporary customer service. Table 5 serves as a critical resource for understanding how affordance theory is reflected in chatbot design and functionality. The distinctions between factors that prevent dissatisfaction and those that enhance satisfaction provide valuable insights for designers, developers, and service providers. The justifications anchored in established research ensure that the findings are rooted in theory, providing a robust framework for future chatbot innovations.

4.1. Contribution

The contributions of this research are manifold, contributing not only to the theoretical but also to the practical understanding of chatbot interactions with humans. Below are the major contributions based on the data provided:

1. Reconceptualization of Chatbot as Digital Beings:

   •   ○ Central to this research is the theme of “Digital Humanism,” which signifies a departure from viewing chatbots merely as tools. Instead, it delves into their potential as digital beings with depth and emotional resonance. By unpacking the nuances of “Soulful Machines,” “Echoed Sentience,” and “Morphic Ethos,” this research offers a reconceptualization of chatbots, positioning them as entities that can evoke profound human-like emotions and mirror human understanding. This challenges the prevalent theoretical framework that often limits chatbots to their utilitarian functionalities.

2. Unraveling the Seamless Symbiosis of Technology and Human Interaction:

   •   ○ The theme of “Technological Symbiosis” offers a profound understanding of the equilibrium between chatbots’ designed capabilities and consumers’ expectations and needs. Through the codes of “Harmonized Utility,” “Affordance Odyssey,” and “Confluence Points,” this research illuminates the intricacies of chatbot-human interaction. It proposes that optimal engagement emerges from a harmonious alignment of design, functionality, and user needs. Such insights challenge the monolithic perspectives that either emphasize the technical prowess of chatbots or focus solely on user requirements, without considering the symbiotic relationship between the two.

3. Deep Dive into Affordance Theory within Chatbot Dynamics:

   •   ○ Building on Gibson’s (1977) affordance theory, this study provides a granular breakdown of how various affordances manifest within chatbot-user interactions. By distinguishing between factors that merely prevent dissatisfaction and those that genuinely enhance satisfaction, this research enriches the understanding of chatbot affordances. The distinctions offered—ranging from basic emotional recognition to deep emotional resonance—provide a comprehensive look into the multifaceted nature of chatbot affordances. These insights provide more understanding of the complex relationship between functional, aesthetic, cognitive, and socio-cultural aspects in chatbot environments, building upon prior material.

4. Ethical Compass in Anthropomorphic Chatbot Design:

   •   ○ The “Morphic Ethos” code emphasizes the ethical concerns that arise as chatbots display heightened anthropomorphic features. This research highlights the necessity of maintaining an ethical transparency in chatbot designs that strive for seamless human-like interactions. By doing so, it offers a crucial guide for designers and developers as they navigate the intricate landscape of human-chatbot interactions, guaranteeing that technological progress does not compromise ethical considerations.

5. The Journey of Exploration and Discovery in Chatbot Interactions:

   •   ○ Through the “Affordance Odyssey” code, this research emphasizes the journey users undertake as they navigate the functionalities of chatbots. By identifying moments of discovery and alignment, the study reinforces the importance of cognitive affordances in shaping user experiences. Such a perspective challenges the linear and often static understanding of chatbot functionalities, emphasizing instead the dynamic nature of user-chatbot interactions.

6. Elevating the Discourse on “Digital Interlocution”:

   •   ○ Similar to the previous contribution on “Digital Interlocution,” this research accentuates the multidimensionality of chatbot interactions. It underscores that factors like conversational flow, bot linguistics, and response proximity are pivotal for user experience, pushing the boundaries of understanding beyond mere technical dimensions.

Table 6, titled “Highlights of Contributions,” offers a meticulous juxtaposition of identified literature gaps, theoretical gaps, the application of Affordance Theory, and the respective achievements presented in the research paper. Beginning with the literature, the table underscores the lacuna in existing studies on chatbots. While there is a recognition of deep interactions between chatbots and humans, there’s a glaring absence in understanding the emotional depth these interactions can achieve. This becomes increasingly salient when considering the meteoric rise of chatbots in various sectors, making the quest for understanding this depth not just academic, but critically pragmatic. Theoretical gaps delve deeper, pivoting around the Affordance Theory. While affordances unquestionably cater to the potential for profound interactions, the question emerges: Can digital entities like chatbots truly resonate emotionally with users? How are evolving chatbot functionalities perceived by users? Furthermore, as chatbots advance, taking on more human-like traits, where does one ethically delineate their design? The application of the Affordance Theory becomes instrumental here. It provides a lens to not only understand but also potentially bridge these gaps, emphasizing the role of perception in shaping user interactions. This research, as highlighted in the table, doesn’t just stop at identifying these challenges. Instead, it progresses to offer insights, bridging the gaps with empirical findings, and guiding the direction for future chatbot designs, ensuring they are both emotionally resonant and ethically sound.

Table 6. Highlights of contributions.

Literature gap	Theoretical gap	Application of affordance theory	Achievement in this paper
“Studies hint at the deep interactions between chatbots and humans, yet the emotional depth remains largely uncharted.” (Chung et al., 2020)	“Affordances provide the potential for deep interactions between users and digital entities, but how deeply can a digital entity resonate emotionally?” (Gaver, 1991; Gibson, 1977)	The Affordance Theory examines the potential of chatbots to form profound human-like connections, going beyond functional interactions.	This research uncovers how chatbots, through certain affordances, can evoke profound emotions in users, deepening the interaction beyond basic functionality.
“Despite advances in chatbot technology, achieving a balance between their design, functionality, and user needs is challenging.” (Aslam, 2023; Chen et al., 2021)	“Affordances dictate that the utility of an object (or digital entity) is based on the observer’s perception. How does this translate to the evolving functionalities of chatbots?” (Hartson, 2003; El Amri & Akrout, 2020)	The Affordance Theory focuses on the relationship between chatbot capabilities and the perceptions and needs of the users.	The paper delves into the alignment between what a chatbot is designed to offer and what users need, resulting in refined chatbot designs that better resonate with user expectations.
“While chatbots display heightened anthropomorphic features, the ethical concerns in their design and functionality remain underexplored.” (Blut et al., 2021; Crolic et al., 2022)	“Given that affordances revolve around perception and interaction, where do we draw the line in designing chatbots with human-like attributes without crossing ethical boundaries?” (Gibson, 1977; Lee et al., 2023)	The Affordance Theory sheds light on the ethical implications when chatbots are designed with heightened human-like features.	This research addresses the ethical considerations in chatbot design, ensuring that while chatbots are made more engaging, they don’t breach ethical standards.

4.2. Practical contributions

Given the presented findings and contributions centered around consumer engagement in the context of the Qatar banking sector, the following practical implications can be delineated:

1. Emphasizing Emotional Resonance in Chatbot Design: Banking institutions in Qatar should prioritize the integration of emotional intelligence capabilities in their chatbots. This not only enhances user experience but also fosters trust and satisfaction, as users find the engagement emotionally fulfilling.

2. Dynamic Adaptation: As user expectations evolve, it’s vital for banks to adopt a dynamic approach in updating and refining chatbot features. By ensuring continuous adaptation, banks can offer sustained user satisfaction and remain at the forefront of customer service innovation.

3. Harmonizing Design and Function: Given the emphasis on the harmonious alignment of design and functionality, Qatar’s banks should invest in iterative design processes that align chatbot features with user expectations. This ensures a seamless and efficient banking experience, enhancing overall user satisfaction.

4. Ethical Considerations: As chatbots in the banking industry acquire increasingly anthropomorphic characteristics, ethical considerations become of utmost importance. Banks should ensure transparency in the chatbot’s functionalities, avoiding any misleading anthropomorphic design features. This not only safeguards the institution’s reputation but also fosters trust with consumers.

5. Training and Awareness: Recognizing the importance of the user’s journey, denoted by the “Affordance Odyssey”, banks should consider training programs or awareness campaigns. This will assist customers in unveiling advanced chatbot capabilities, optimizing their engagement and leveraging the full spectrum of services on offer.

6. Continual Feedback Mechanism: Given the fleeting nature of “Confluence Points”, a continuous feedback mechanism should be integrated. It will allow users to share their experiences, ensuring that banks can recalibrate chatbot features in real-time, fostering an environment of continuous improvement.

7. Deep Integration of Affordance Theory: Given the profound implications of the affordance theory in shaping chatbot interactions, banks should delve deep into this theoretical framework during the design and deployment phases. It will ensure that chatbot functionalities are not just technically proficient but also resonate with user perceptions and expectations.

8. Embracing Digital Humanism: Banking institutions should recognize the paradigm shift from viewing chatbots merely as tools to appreciating their potential as digital beings with depth. This fundamental shift in perspective will guide more humane and emotionally resonant chatbot designs.

By incorporating these practical implications, the Qatar banking sector can pioneer a holistic and user-centric approach to chatbot interactions, setting benchmarks not just regionally but globally.

4.3. Limitations and future directions

Drawing from the comprehensive examination of Technological Symbiosis in the context of chatbot-human interactions, especially in Qatar’s banking sector, certain limitations are evident. Initially, one notices the study’s primary reliance on the Affordance Theory. This concentration has undoubtedly paved the way for a structured understanding of chatbot-human interactions. Yet, this commitment could overshadow the richness of insights other theoretical perspectives might offer. These could provide alternative viewpoints on how users perceive and interact with chatbots, highlighting aspects that the Affordance Theory might overlook. The study recognizes limitations regarding the specificity and technological nuances of the chatbots within Qatar’s banking sector. Detailed insights into the chatbots’ capabilities, learning mechanisms, and adaptive functionalities were not provided, potentially skewing user interaction experiences, such as rephrasing occurrences, and limiting the generalizability of findings across diverse chatbot technologies and platforms. To overcome this constraint, it may be necessary to examine chatbot interactions from the perspective of many theories, such as the Social Presence Theory or Cognitive Load Theory. Furthermore, the emphasis on emotional resonance, anthropomorphic design, and ethical considerations, while essential, seems not to explore in depth the potential negative implications. For instance, while anthropomorphic designs can lead to increased trust, they might also lead to unrealistic user expectations, or even resistance from consumers who find such designs insincere or artificial. To overcome this, future research could undertake a comprehensive exploration of users’ adverse reactions to chatbots, shedding light on potential pitfalls or areas of mistrust. Moreover, the cultural context, while providing a unique backdrop for this study, also narrows its findings’ applicability. Banking customers in Qatar might have different perceptions and expectations than those in other regions. An auspicious approach would entail conducting cross-cultural investigations to compare interactions between chatbots and humans across several nations or even within the same country, but in distinct urban and rural environments.

The present study also seems to focus primarily on the banking sector. Although this helps to focus the research, it may also restrict the applicability of the results. Future investigations can venture into other sectors, like retail or healthcare, to see if the insights from the banking domain hold true elsewhere. Lastly, while discussing ethical considerations, the study does not seem to delve deep into security and privacy concerns, particularly pertinent in the banking sector. Such a limitation can be addressed by initiating comprehensive research dedicated solely to understanding users’ security and privacy expectations and concerns when interacting with chatbots. This would not only enrich the field’s knowledge but would also guide chatbot designers to instill more robust safety features, leading to increased user trust and acceptance.

The author has obtained a PhD from the University of Newcastle, UK, and holds multiple certifications. The author has also published several studies in journals with a high impact factor.

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Notes on contributors

Mohamed Al-Shafei

Mohamed Al-Shafei, a PhD from the University of Newcastle, UK, is a distinguished author with multiple certifications. He has contributed extensively to high-impact factor journals, showcasing his expertise through various published studies.