Preamble

Formation and Influence Mechanisms of Service Robot-Work Environment Fit

School of Cultural Tourism, Guangdong University of Finance and Economics, Guangzhou; School of Business, Sun Yat-sen University.

The rapid development of artificial intelligence and robotics has made it possible for enterprises to utilize robots to create value for customers. However, instances of service failure, forced decommissioning, or the idling of robots are also frequent occurrences.

Existing research primarily focuses on the influence mechanisms of service robots on customers and employees, while rarely addressing the fit between robots and their specific work environments. Based on Person-Environment Fit theory, this study proposes the concept of Service Robot-Work Environment Fit and attempts to explore its internal dimensions and measurement methods. Furthermore, this research examines the antecedents of Service Robot-Work Environment Fit from multiple perspectives, as well as the dual-path influence mechanisms of this fit on both employee value and customer value creation. The expected research results will contribute to the theoretical development of service robotics and provide guidance for specific management challenges faced by enterprises in the intelligent era, such as human-machine collaboration, value co-creation, and intelligent transformation.

关键词

Service robots, value co-creation, value co-destruction, Person-Environment Fit theory. The application of service robots in management practice is becoming increasingly widespread. They can liberate employees from repetitive, routine tasks, improve corporate efficiency, reduce labor costs, and provide customers with novel service experiences \cite{Zhang_et_al_2024}. However, robots can also lead to service failures. For instance, check-in robots in lobbies may malfunction; in-room assistant robots might repeatedly wake customers due to snoring; and customers may feel that robot-prepared dishes lack "wok hei" (the breath of a wok) and "soul." Chain restaurants such as "Heweilai" and "Xiaolongwang" have experienced a wave of robot "layoffs." Japan's fully automated Henn na Hotel dismissed more than half of its robot staff because managers realized that a fully robotic workforce could not meet customer service expectations and actually increased the workload of human employees. In such cases, companies can neither utilize robots to improve service quality and efficiency nor maintain the emotional care and "service with warmth" that the industry prides itself on. In many service contexts, emotional exchange is a vital component of service, and human-robot collaboration represents the future of industry development \cite{Simon_et_al_2020}. The impact of insufficient suitability or systemic misalignment between service robots and work environments on corporate management cannot be ignored. How to promote the fit between service robots and the work environment to fully leverage their advantages and achieve value co-creation is an urgent practical problem for managers to solve.

Academic research on service robots has explored their definitions and characteristics that distinguish them from industrial robots \cite{Wirtz_et_al_2018}. Studies have focused on their impact on customers \cite{Yan_et_al_2025} and have begun to pay attention to the interaction between employees and robots \cite{Liu_Zhang_et_al_2025}. Although certain achievements have been made, there are limitations in research focus, research interests, and analytical perspectives. First, research focuses on the service robot itself, overlooking the issue of whether it fits and matches its work environment. Research has not provided a clear answer regarding which aspects service robots and the work environment need to be "in sync" to achieve goals such as liberating employees, reducing organizational costs, and providing customers with services that feature both high emotional engagement and high-tech characteristics. Second, research interests emphasize

influence mechanisms over organizational intervention. Although studies have clarified how robots affect customer cognition, emotion, and behavior, they have not answered how to more effectively utilize service robots, nor have they considered the agency of the organization in the process of human-robot value co-creation. Third, the analytical perspective is predominantly customer-oriented; research on the interaction between employees and service robots remains insufficient. Few studies analyze the multi-dimensional interactions generated by multiple service actors and their impact on value co-creation. Whether the application of service robots allows employees more time and energy to engage in more personalized, professional, creative, and emotional "deep service," whether employees can successfully complete their role transitions, and whether customers receive more "warm" service from employees alongside the novel experiences brought by robots are all questions that remain to be addressed.

Based on Person-Environment Fit theory, this study first proposes the concept of Service Robot-Work Environment Fit. It examines its internal structure from the perspective of different interacting actors and explores the formation mechanism of this fit under the influence of robot characteristics and work design characteristics from the perspectives of work design and value co-creation. Furthermore, it investigates the dual-path influence mechanism of this fit on employee value and customer value creation.

The core objective is to explore the internal structure, antecedents, and influence mechanisms of Service Robot-Work Environment Fit. The research findings will theoretically supplement service robot theory and practically provide guidance for management issues such as human-robot synergy and value co-creation, which are of great concern to service enterprises adopting robots.

2.1 服务机器人的定义和特征

Service robots are robotic entities that perform useful service tasks for humans or equipment, excluding industrial automation applications. Compared to industrial robots, service robots are characterized by autonomy, adaptability, and flexibility; they are capable of interacting, communicating, and engaging with stakeholders such as employees and customers to provide services \cite{Wirtz et al., 2018}. This definition distinguishes service robots from general artificial intelligence (AI) and smart devices. While AI focuses less on hardware and more on programs and algorithms—providing robots with autonomous, flexible, and interactive attributes—it is not a service robot in itself because it lacks a physical form \cite{Jörling et al., 2019}. Conversely, although smart speakers and wearable devices possess physical embodiments, they cannot operate autonomously, as autonomy implies the ability to plan actions based on the environment \cite{Tuomi et al., 2021}. Only robotic entities that possess a physical body, exhibit a high degree of autonomy in their operations, can flexibly respond and adapt to their environment, and assist customers or enterprises in completing service tasks are classified as service robots.

These robots can utilize sensors to collect input data, analyze this data instantaneously, formulate plans, and execute decisions immediately using physical actuators. More sophisticated service robot systems are also capable of learning from previous interactions, adapting, and optimizing their future behavior.

Although the aforementioned studies have laid a foundation for our understanding of service robots and their characteristics, the problem of "fit" between robots and their work environments has become increasingly prominent as more service enterprises introduce them. Issues have emerged where the introduction of service robots fails to effectively enhance the customer experience, fails to meet customer needs, or imposes additional workloads on employees. However, the academic community has focused primarily on the service robots themselves and their specific characteristics, analyzing their impact on customers and employees. Little attention has been paid to the matching relationship between service robots and the work environment, and consequently, research regarding the measurement and quantification of this fit remains virtually non-existent.

2.2 服务机器人对顾客的影响研究

Service robots influence customer evaluations and behavioral intentions by acting upon their cognitive and emotional states. Research has demonstrated that the physical appearance of robots—such as anime-like, animal-like, or humanoid forms (Milman et al., 2020; Yoganathan et al., 2021)—significantly impacts customer perceptions.

Surface-level characteristics, including language style (Choi et al., 2019; Lu et al., 2021; Yan et al., 2025), vocal tone (Han et al., 2023; Xie & Lei; El Halabi & Trendel, 2024), cuteness (et al., 2021, 2020), and gender (Seo, 2022), all influence customer attitudes toward service robots. Regarding deep-level characteristics, factors such as a robot's competence (et al., 2022; Guan, Zhang, et al., 2025), intelligence type (Schepers et al., 2022), social interactivity (Kim et al., 2022), service proactivity (C. Liu), and empathy (de Kervenoael et al., 2020) also exert an influence on customers. Furthermore, demographic characteristics such as customer gender, age, and prior experience shape human-robot interaction (Ayyildiz et al., 2022; Cha, 2020; Lee & Yen, 2023; Loureiro et al., 2021; Wang & Papastathopoulos, 2024). Psychographic factors, including customer innovativeness (Kim et al.), motivation (Hwang et al., 2020), and service expectations (al., 2021; et al., 2021), play equally vital roles. These factors collectively affect customer trust in service robots (Tussyadiah et al., 2020), responsibility attribution for service outcomes (Jörling et al., 2019), and perceived service value and experience (de Kervenoael et al.; Qiu et al., 2020; Mcleay et al., 2021). These perceptions, in turn, influence intentions for value co-creation (X. Liu & Li, 2022), willingness to use the robot (Lin et al., 2022), customer loyalty (Belanche et al., 2021), compensatory consumption behavior (Mende et al., 2019; Guan, Zhang, et al., 2025; Santiago et al., 2024), recommendation intentions (Yang et al., 2024), and purchase intentions (Song & Luximon, 2021). However, robots do not always produce positive effects. When acting autonomously in open and dynamic environments, they may commit errors—such as sensor anomalies, mechanical or computational failures, or failures to respond to environmental changes (Cameron et al., 2021). Such failures can lower customer evaluations of the robot's capabilities, leading to perceptions of poor reliability and untrustworthiness, which ultimately discourages usage.

To remedy service failures, robots can employ strategies such as apologizing, explaining the cause of the error, seeking assistance, and promising improvement. These strategies influence customer evaluations of the robot's cuteness, competence, and warmth, as well as their willingness to interact with the robot (Cameron et al., 2021; Choi et al., 2021). Following a service failure, the specific entity providing the recovery (e.g., an employee, a fellow customer, or a robot) also affects customer evaluations of the service experience through perceived role congruency (Ho et al., 2020). While the aforementioned studies provide a foundation for understanding how service robots influence customers, achieving value co-creation among customers, employees, and robots depends on whether an organization can effectively redesign service processes, reshape service teams, and provide necessary support (Xiao & Kumar, 2021). Redesigning service processes requires clearly defining which tasks are performed by employees versus robots and ensuring seamless collaboration between them. Reshaping service teams involves hiring the right human staff and deploying appropriate robots to ensure that robots function correctly across various service scenarios, that human employees are willing to collaborate with them, and that complex service issues beyond a robot's capability are properly resolved. Support activities include training for both employees and customers, communicating to staff that robots are intended to enhance productivity rather than replace them, and allowing employees autonomy in how they interact with robots. It also involves continuous testing and hardware/software updates to improve service capabilities. However, existing research has focused primarily on the effects of surface-level and deep-level robot characteristics, largely overlooking the organizational agency required to create a favorable work environment and facilitate human-robot interaction. In the context of human-robot value co-creation, achieving a strong fit between service robots and the work environment necessitates active organizational intervention.

2.3 服务机器人对员工的影响研究

The application of service robots has both negative and positive impacts on the psychological states and behaviors of employees. Regarding negative effects, the integration of robots into work teams can diminish employees' sense of team identification. Even the mere mention of the term "robot" can trigger negative emotions among service staff, as they perceive service robots as a primary driver of rising unemployment rates.

Factors such as the unrealistic anthropomorphism of robots, low usability, excessive workload, technical insecurity, and technical uncertainty can lead employees to resist the sustained use of service robots \cite{Fu et al., 2022} and reduce their willingness to collaborate with them \cite{Ali et al., 2023}. Furthermore, employees' awareness of AI and robotics, coupled with job insecurity (characterized by strong feelings of threat and powerlessness) and the work stress stemming from robotic advantages, can increase turnover intentions \cite{Chen & Cai, 2022; Pan et al., 2025; Zhang et al., 2023}. Robot awareness can also negatively impact service innovation behavior through emotional exhaustion \cite{Liang et al., 2022} or reduce organizational commitment, leading to job burnout and diminished professional competence.

Research has also found that robot anthropomorphism can cause employees to perceive threats to their job security, leading them to resist the company's deployment of robots and resulting in lower employee morale \cite{Tojib et al., 2023}. The competitive role of robots negatively affects employee well-being through identity threats and work alienation (Liu & Xie, 2021). Conversely, regarding positive impacts, a high-quality human-robot interaction experience can foster positive cognitions, emotions, and attitudes among employees.

Positive outcomes include lower work fatigue, high service enthusiasm, and enhanced motivation \cite{Guan, Zhang, et al., 2025}, as well as high levels of human-robot collaboration intentions \cite{Wu & Zhang, 2024}, workplace inspiration \cite{Zhang, et al., 2024}, learning tension \cite{Guan et al., 2024}, and perceived value \cite{Lin et al., 2024}. These factors further stimulate employees to take proactive actions, such as seeking help from robots or engaging in job crafting \cite{Song et al., 2022}. This leads to higher job engagement, competitive productivity, and more positive feedback \cite{Wu & Zhang, 2024}, as well as increased in-role and extra-role behaviors \cite{Yang et al., 2024}, service innovation behaviors \cite{Li et al., 2024}, and learning and knowledge management behaviors \cite{Guan et al., 2024; Guan, Zhang, et al., 2025; Liu, Zhang, et al., 2024}. Additionally, employee job autonomy can be enhanced, turnover intentions reduced \cite{Zhang et al., 2023}, and the sense of work meaningfulness and well-being improved (Liu & Xie, 2021). Since many tasks in the service industry require emotional labor, many enterprises have integrated robotic services with human staff. This integration has a profound impact on various stakeholders. In the process of human-robot value co-creation, different stakeholders focus on different aspects: customers focus more on the functional and socio-emotional value provided by robots; employees perceive robots as bringing both costs (such as extended working hours and learning requirements) and benefits (such as increased well-being); while managers focus on the organizational costs and benefits of introducing robots, technical learning difficulties, compatibility issues, and potential competitive advantages.

Therefore, it is necessary to adopt a dialectical perspective to examine the influence paths of the relationship between service robots and the work environment on the value creation of different stakeholders.

3 研究构想

Existing research on service robots has largely treated them as objective entities within the workplace, focusing primarily on their impact on customer cognition, emotions, and behavioral intentions \cite{刘欣，谢礼珊，}. This perspective has two significant limitations. First, it overlooks the relationship between the robot as a service agent and its work environment, leaving researchers unable to explain phenomena such as firms "firing" service robots or leaving them idle. Second, it fails to recognize the critical role of the organization in enabling service robots to reach their full potential. Furthermore, it ignores the fact that value formation in multi-actor interaction contexts—involving employees, service robots, and customers—is increasingly complex and dynamic, where both value co-creation and co-destruction may occur. To address these gaps, this study proposes the concept of service robot-work environment fit, examining the factors influencing this alignment from the dual perspectives of robot characteristics and work design characteristics.

This research demonstrates the factors influencing service robot-work environment fit while simultaneously focusing on how this fit affects value creation for both internal and external customers (i.e., employees and customers). Specifically, after clarifying the theoretical foundations, internal dimensions, and measurement scales of service robot-work environment fit, we construct an antecedent-consequence model. This model is used to analyze the formation mechanisms of this fit, clarify its impact on employee and customer value creation, and explore the underlying mediating mechanisms and boundary conditions.

3.1 服务机器人

Theoretical Foundation, Conceptual Structure, and Scale Development of Service Robot-Work Environment Fit

The concept of Service Robot-Work Environment (SR-WE) fit is developed based on Person-Environment (P-E) fit theory, the service encounter triad, and the concepts of compatibility and congruence.

P-E fit theory emphasizes the compatibility between individuals and their environments \cite{Kristof, 1996}. When individual attributes align with environmental characteristics, individuals tend to hold positive attitudes and successfully complete tasks; that is, fit produces positive outcomes for the individual. As service robots become new "employees" within organizations, the question of whether they fit their work environment also arises. The service encounter triad (as shown on the left in [FIGURE:1]) indicates that there are three key elements in the service delivery process: the service organization, the contact personnel, and the customer \cite{Bitner, 1995}. When firms introduce autonomous, adaptive, and flexible service robots into the workplace, the traditional customer-employee (or organization) dyadic interaction shifts toward a triadic interaction involving the customer, the employee, and the service robot—or even more complex multi-actor interaction models (as shown on the right in [FIGURE:1] \cite{Odekerken-Schröder et al., 2021}). This suggests that SR-WE fit is a complex, multidimensional concept.

Compatibility emphasizes that innovative technologies should be consistent or aligned with the user's preferred work styles, past experiences, needs, and values \cite{Karahanna et al., 2006}. Furthermore, some scholars have already begun to address the issue of robot fit. For instance, \cite{Murphy et al., 2016} proposed "perceived fit" to measure the degree of alignment between new technology applications in hotels and the brand image. \cite{McLeay et al., 2021} introduced "perceived innovation-responsibility fit" to describe the perceived inconsistency between the innovative aspects of cutting-edge technology (such as artificial intelligence) and the ethical and social responsibilities upheld by the service provider.

Work-matching issues also exist between employees and robots \cite{Xiao & Kumar, 2021}. Robots must also align with service concepts and specific tasks \cite{Tuomi et al., 2021}. Based on this, the present study defines SR-WE fit as the degree of congruence and compatibility between service robots and their work environment within the context of human-robot interaction service scenarios. This includes alignment with the service enterprise's positioning, branding, strategic development, and the specific tasks performed, as well as compatibility with the interacting employees and customers. It encompasses both supplementary fit, achieved when characteristics are consistent, and complementary fit, formed when characteristics offset one another. Starting from the primary subjects that interact with service robots—organizations, employees, and customers—this study presupposes that service robot-work environment fit consists of three dimensions.

SR-WE fit includes three aspects: Service Robot-Enterprise (SR-E) fit, Service Robot-Frontline Employee (SR-FLE) fit, and Service Robot-Customer (SR-C) fit.

1. Service Robot-Enterprise Fit refers to the extent to which the service robot aligns with the firm's positioning, brand, strategic development, and the nature of the work. Enterprises introduce robots into the workplace with the expectation of reducing costs, improving service efficiency, and creating a better experience for customers. Therefore, from the enterprise perspective, service robots must match the brand image and the tasks they perform, ensuring that the robot's technology, knowledge, and abilities meet specific job requirements, and that its appearance and intrinsic characteristics enhance the brand image and develop competitive advantages.

2. Service Robot-Frontline Employee Fit refers to the compatibility achieved between service robots and frontline employees during work. This often occurs when the service robot aligns with the employees' current work methods, styles, and needs, or when the two complement each other in terms of knowledge, skills, and abilities. For service robots to be effective in the workplace, they must cooperate well with employees to co-create value for customers. Thus, from the employee perspective, it is necessary to achieve compatibility with existing work habits while ensuring a reasonable division of labor where strengths are complementary.

3. Service Robot-Customer Fit refers to the compatibility achieved between the service robot and the customers being served during the service process. This fit may be surface-level, such as gender; for example, research by \cite{Yu, 2020} indicates that in the hotel industry, customers express higher levels of pleasure and satisfaction with female-looking service robots than with male-looking ones. It may also involve deeper-level matching, such as alignment in communication styles or knowledge compatibility.

This classification is based on the service encounter triad, suggesting that service robots must achieve fit with different actors within the work environment. Research on fit structures could also consider the relationship between service robot attributes (e.g., mechanical vs. emotional) and work environment attributes (e.g., simple vs. complex) to classify different types of fit. In the context of enterprises introducing service robots as a new type of "employee," the specific components of SR-WE fit and whether there are other unique manifestations still require further exploration through qualitative research. By conducting in-depth interviews with managers, frontline employees, and customers of service enterprises, this study explores the conceptual structure of SR-WE fit and develops and tests a measurement scale based on these qualitative findings.

3.2 服务机器人

Antecedents of Service Robot-Work Environment Fit

Based on Mind Perception Theory and Work Design Theory, this study constructs a theoretical model of the factors influencing "Service Robot-Work Environment Fit." Furthermore, the model incorporates organizational characteristics to analyze the boundary conditions of these relationships. The conceptual model is illustrated in [FIGURE:1].

Theoretical Framework and Model

The research model explores the antecedents of service robot-work environment fit through three primary dimensions: robot characteristics, work design characteristics, and organizational orientation.

1. Robot Characteristics
The model distinguishes between two levels of robotic attributes that influence integration:
- Surface-level Anthropomorphic Features: These include the physical appearance and sensory traits of the service robot.
- Deep-level Anthropomorphic Features: These refer to the cognitive and emotional capabilities perceived by employees and customers, such as perceived agency and experience.

2. Work Design Characteristics
The study examines how the specific nature of tasks and the structural design of the service environment interact with robotic implementation to determine the level of fit.

3. Organizational Characteristics (Boundary Conditions)
The model proposes that the impact of robot and work characteristics on environment fit is moderated by the organization's strategic focus. These orientations are categorized into three domains:
- Technology-Oriented: Innovation orientation, reflecting the organization's drive to adopt and integrate cutting-edge solutions.
- Employee-Oriented: Organizational investment, representing the resources and support provided to staff during the technological transition.
- Customer-Oriented: Customer orientation, focusing on how the deployment of robots aligns with enhancing the service experience and meeting client needs.

[FIGURE:1]: Theoretical Model of the Antecedents of Service Robot-Work Environment Fit

3.2.1 机器人表层和深层类人特征对服务机器人

The Impact of Work Environment Fit: Mind Perception Theory posits that individuals perceive the presence of a "mind" in entities through two dimensions: agency and experience. Agency refers to the capacity for thinking, reasoning, planning, and executing personal intentions, whereas experience involves the capacity for sensation, consciousness, and the ability to feel emotions \cite{Gray2007, YoganathanOsburg}. When non-human agents, such as service robots, possess human-like cues—such as the ability to engage in natural conversation, a mobile body, a head, two arms, two legs, a human name and gender, or mental capacities like agency and emotionality—the human brain performs associative processing. This activates psychological content typically reserved for real humans \cite{Epley2018}, leading individuals to attribute a certain degree of mind to the non-human agent \cite{Soderlund2021}. According to Mind Perception Theory, the presence of surface-level and deep-level human-like characteristics in service robots facilitates the projection or analogy of human cognitive and emotional traits onto the robot by both employees and customers \cite{Fiske2002}. This leads to the perception that the service robot possesses service resources similar to those of humans, thereby eliciting positive cognitive and emotional responses. Conversely, service robots that differ significantly from humans may fail to respond correctly to actors, resulting in negative evaluations and a decreased willingness to engage in social interaction \cite{EtAl2019}. Taking anthropomorphism as an example, individuals generally perceive highly anthropomorphic robots as friendlier, more helpful, and more trustworthy; they are seen as having higher warmth and competence, and as performing well in functional tasks without serious errors. Such characteristics can significantly enhance user engagement, positive affect, and positive evaluations of the robot. In contrast, robots lacking authentic anthropomorphic features are perceived as lacking empathy. Non-humanoid robots offer services that are seen as less attractive, leading to resistance toward their use \cite{Fu2022}. Similarly, enhancing the intelligence and empathetic capabilities of service robots can increase their perceived credibility among actors.

The empathy level of service robots influences the relationship between anthropomorphism and both perceived usefulness and perceived enjoyment \cite{Shi2022}. Their ability to recognize and proactively respond to customer emotions can lead to positive customer evaluations.

The following propositions are presented: Enhancements in the (1) surface-level human-like characteristics (e.g., anthropomorphism) and (2) deep-level human-like characteristics (e.g., empathy) of service robots can promote the formation of service robot-work environment fit.

3.2.2 机器人

The Impact of Employee Work Design Characteristics on Service Robot-Work Environment Fit

Work design determines how tasks are decomposed and assigned to specific individuals to achieve coordination and complete overall organizational goals. Designing work requires considering motivational characteristics such as skill variety, task identity, task significance, autonomy, and feedback \cite{Hackman & Oldham, 1975}. Furthermore, it must account for social characteristics, such as interdependence and interaction with those outside the organization \cite{Grant & Parker, 2009}, as well as work context characteristics, including the physical environment, working conditions, and ergonomics \cite{Humphrey et al., 2007}. Together, these elements influence overall job performance.

The introduction of service robots into the workplace necessitates the integration of these robots into employee teams \cite{Wirtz et al., 2018} to achieve effective human-robot collaboration.

This requires enterprises to redesign service processes and reshape human-machine service teams \cite{Xiao & Kumar, 2021}. For example, work tasks must be decomposed to determine which are performed by service robots and which by human employees. It is also necessary to judge whether their respective tasks are interdependent and to what degree, arrange for the seamless connection of these tasks, and clarify whether the robot or the human employee plays the primary or supporting role.

If a robot exhibits low independence and frequently requires assistance from employees, it indicates a high level of dependence on human skills. This suggests that the robot's intelligence is insufficient to handle complex tasks \cite{X. Li & Li, 2020}.

This leads to a human perception of low intelligence in service robots—specifically, that they can only perform simple, routine, and repetitive tasks while failing to complete complex systemic tasks \cite{Wirtz et al., 2018}. Such perceptions hinder the fit between the service robot and its work environment, likely creating an additional workload for employees and leading to customer disappointment. Research indicates that while customers view the introduction of robots into service environments as an innovation, they perceive robots that work completely independently as more innovative than those that merely support existing staff \cite{McLeay et al., 2021}. Based on this, the present study proposes the following proposition: Well-designed robot-employee work characteristics will promote the formation of service robot-work environment fit, whereas poor work design (such as high task dependence of the robot on human employees) will impair the formation of this fit.

3.2.3 组织对匹配形成的催化作用

The introduction of service robots represents an innovative practice in restructuring service production systems \cite{Mingotto et al., 2021}. Their design requires a balance between anthropomorphism and professionalism, while their skill configurations must integrate standardized operational modules with dynamic learning capabilities. Furthermore, firms are required to redesign work processes to facilitate human-robot collaboration \cite{Xiao & Kumar, 2021}. This complexity implies that the fit between service robots and the work environment is essentially an adaptive evolution of an organizational multi-system comprising people (including both employees and customers) and technology. The formation of this fit depends not only on the robot and job design but also on the deep coupling of the organization's strategic goals, resource allocation, and cultural values with the characteristics of the robot and the work environment. Based on the relationships between different actors in this new environment [FIGURE:1], organizations can formulate specific strategies or tactics for technology, employees, and customers to promote the formation of this fit.

Regarding service robot technology, firms must possess an innovation orientation. Innovation orientation enables the rapid, effective, and timely acquisition of market information and leverages existing knowledge to facilitate innovative activities; thus, it is often regarded as a core driver for enhancing organizational capabilities, innovation performance, and gaining competitive advantage \cite{Hurley & Hult, 1998; Ordanini & Parasuraman, 2011}. In the context of service robot applications, the unique catalytic value of innovation orientation—distinguished from traditional scenarios—lies in an openness to new ideas and things \cite{Hurley & Hult, 1998}. It is an organizational capability involving strategic choice, organizational adaptation, and resource reallocation, thereby promoting multi-dimensional innovation across processes, technology, products, and management \cite{Siguaw et al., 2006}. On one hand, firms with a high innovation orientation are more likely to embrace service robots, viewing them as vehicles for innovation rather than mere cost centers. Consequently, they proactively adjust resource allocation—such as deeply participating in the robot's appearance design, skill configuration, and iterative optimization—to align with the corporate brand image and work tasks. They may even tolerate initial efficiency losses during the technical adjustment phase to secure long-term advantages. On the other hand, an innovation orientation shapes an atmosphere that encourages trial and error and tolerates risk \cite{Hurley & Hult, 1998}, effectively alleviating the anxiety brought about by change and continuous experimentation. This drives the transformation of organizational practice from passive adaptation to technology toward the proactive shaping of a human-machine ecosystem. Accordingly, this study derives the following inference:

In the process of forming the fit between service robots and the work environment, particularly the fit with the firm, the firm's innovation orientation plays a positive catalytic role. For employees in a changing environment, organizational investment is a crucial catalyst for promoting the fit between service robots and frontline staff.

By providing material rewards and assisting in employee growth and development, organizations receive reciprocity from employees based on the principles of social exchange \cite{Guan et al., 2020}. Unlike previous research focusing on the unidirectional incentive effect of organizational investment within the dyadic relationship between employees and the firm \cite{e.g., Guan et al., 2020; Jia et al., 2014}, this study focuses on its unique incentive role within the context of service robots embedded in work scenarios.

Specifically, organizational investment helps employees build a resource pool to cope with challenges in the work environment and stimulate proactive behavior. On one hand, material investment—including compensation, performance bonuses for human-robot collaboration, and special subsidies—directly alleviates anxiety regarding technological substitution by reducing employees' perception of economic risk. This makes them more willing to invest resources into learning human-robot collaboration skills, thereby facilitating the human-machine fit.

On the other hand, developmental investment—such as a supportive work environment, customized human-robot collaboration training courses, cross-departmental collaboration opportunities, career development, participation in robot design and development decisions, fair treatment, respect, and care—provides employees with opportunities for capacity building and psychological support. This helps them overcome barriers such as technophobia and role ambiguity. Research has also found that perceived organizational support, a supportive climate, and training and development programs can significantly mitigate the negative impacts of technological change on employees, such as turnover intentions and techno-anxiety \cite{Li et al., 2019; Zhang et al., 2025}. Such systematic organizational investment in material support, skill enhancement, and psychological empowerment helps employees view robots as collaborative partners, thereby catalyzing the formation of fit.

Accordingly, this study proposes: In the process of forming the fit between service robots and the work environment, particularly the fit with frontline employees, the firm's organizational investment plays a positive catalytic role.

Regarding the recipients of the service, firms must possess a customer orientation to create sustainable competitive advantage \cite{Deshpandé et al., 1993; Tuominen et al., 2023}. This orientation not only focuses on satisfying customer needs but also emphasizes value co-creation, incorporating the entire process of value production and delivery \cite{Vargo & Lusch, 2016}. Unlike traditional scenarios where employees serve customers directly and the implementation of customer orientation depends on the employees' service awareness and skills, the introduction of service robots expands the connotation of customer orientation to the collaborative co-creation among the technological carrier, employees, and customers. Robots must match customers' functional needs through technical parameters (such as response speed and task completion) and meet customers' emotional expectations through interaction design (such as tone of voice and anthropomorphic expression). In this context, the catalytic effect of a firm's customer orientation on the fit between service robots and customers exhibits unique characteristics. High customer-oriented firms are better at extracting value signals from customers' latent needs; for instance, Borghi and Mariani found that customers' perceptions of the entertainment and novelty of robot services can be transformed by firms into functional designs and interaction logics. Furthermore, through internal cross-departmental synergy—such as the marketing department collecting customer feedback, the R&D department optimizing robot programming, and the service department testing the human-robot interaction experience—firms ensure that the robot remains customer-centric throughout its entire lifecycle from prototype to deployment. Moreover, customer orientation drives firms to establish closed-loop mechanisms from service and feedback to optimization, allowing them to understand customer evaluations, analyze needs, and iterate the robot's hardware and software accordingly. These measures all contribute to the formation of fit. Based on this, this study proposes:

In the process of forming the fit between service robots and the work environment, particularly the fit with the customers served, the firm's customer orientation plays a positive catalytic role.

3.3 服务机器人

The Dual-Path Influence Mechanism of Work Environment Fit on Value Creation

Based on Value Co-creation Theory and supplemented by Conservation of Resources (COR) Theory, this study focuses on the dual-path influence mechanisms and boundary conditions of service robot "work environment fit" on value creation for both employees and customers. The conceptual model is illustrated in [FIGURE:1].

The research model investigates the dual-path effects of work environment fit on employee and customer value creation across three primary interfaces: the individual interface (regulatory focus), the interaction interface (social support), and the organizational interface (developmental human resource practices). The model posits that self-management behaviors serve as a critical path, where effective self-management promotes value creation, while social loafing behaviors result in value destruction. This framework provides a comprehensive view of how the integration of service robots into the work environment shapes behavioral outcomes and subsequent value generation.

3.3.1 服务机器人

The Dual-Path Effect of Service Robot-Work Environment Fit on Employee and Customer Value Creation: The co-creation path of employee and customer value through service robot-work environment fit is realized via challenge appraisal and self-management behavior. This mechanism manifests as a process where an employee's positive appraisal of stressors motivates them to implement self-management behaviors, which in turn influences value formation.

Stressors are work-related factors that compel individuals to deviate from their normal psychological or physiological functioning. In this sense, service robot-work environment fit represents a stressor for employees, specifically a challenge stressor. A high degree of fit between service robots and the work environment may necessitate adjustments in job content and roles, requiring employees to upgrade their skills to adapt to new tasks. This constitutes a form of stress that employees can overcome and which is beneficial to their job performance and personal growth, such as higher levels of job responsibility and work complexity \cite{Cavanaugh et al., 2000}. According to Cognitive Appraisal Theory \cite{Lazarus & Folkman, 1984}, employees evaluate stressors by comparing their own resources against environmental demands. When employees believe their resources can meet these demands, a challenge appraisal is formed. This cognitive appraisal arises from stressors associated with potential gains or personal growth opportunities (Jiang & Wang, 2014), leading employees to perceive the current situation as conducive to self-development and focusing their attention on potential rewards, growth, or learning \cite{Prem et al., 2017}. Research has also found that challenge stressors are positively related to challenge appraisals \cite{Webster et al., 2011; Zhang & Li, 2018}. Accordingly, it can be inferred that service robot-work environment fit positively influences employees' challenge appraisals. A challenge appraisal of stress is associated with growth, rewards, and benefits, and can stimulate a sense of achievement. Consequently, individuals generally exhibit positive psychological and behavioral responses when facing challenging work requirements, and self-management behavior is precisely such a positive coping mechanism. A challenge appraisal means that employees evaluate external stimulating events as challenges, remain confident about the future, and focus on the opportunities and growth they can gain within the work context, thereby stimulating proactive role behaviors \cite{Bliese et al., 2017}. When employees appraise the stress brought by service robots as challenging, they become more focused on self-improvement, which prompts proactive behaviors to seek growth and development \cite{Mitchell et al., 2019}. Challenge appraisals also enhance employee motivation.

This motivation prompts employees to adopt problem-focused coping behaviors \cite{Searle & Auton, 2015}. When employees maintain a positive attitude toward service robots and believe the stress they cause is related to personal growth, it indicates they have the resources and confidence to overcome this stress. They view collaborating with robots in production as a challenging work requirement beneficial to personal development, which triggers the implementation of development-oriented self-management behaviors. Accordingly, it can be inferred that challenge appraisal positively influences employees' self-management behaviors.

Self-management behavior refers to a series of actions where individuals proactively apply knowledge and adopt specific action strategies to achieve desired goals (Zhang et al., 2005). Dimensions of employee self-management behavior include personal goal setting, self-directed learning, self-observation and evaluation, and self-reinforcement and correction \cite{Houghton & Neck, 2002; Renn et al., 2011}. By engaging in activities such as formulating work plans and goals, proactively participating in training and learning, gathering feedback on job performance, and conducting positive self-evaluation and reflective improvement, employees achieve higher job satisfaction, quality of work life, and individual performance \cite{Cohen et al., 1997}. Similarly, employee self-management behaviors help customers obtain higher value. Because employees set clear goals for their work, continuously learn to improve their capabilities, proactively seek performance gaps, and engage in self-motivation and improvement based on results \cite{Houghton & Neck, 2002}, these behaviors better satisfy customer needs, thereby creating value for them. That is, self-management behavior not only helps employees realize work value and better adapt to changing environments and continuous growth, but also plays a vital role in the realization of customer value. Accordingly, it is inferred that self-management behavior promotes the creation of employees' psychological value (e.g., work thriving, psychological well-being) and work value (e.g., job performance, innovation performance), as well as customers' functional and emotional value.

In summary, this study proposes the following proposition: Service robot-work environment fit stimulates employees' challenge appraisals, which in turn positively influences their self-management behaviors, ultimately leading to the creation of employee and customer value. The value co-destruction path of service robot-work environment fit for employees and customers is realized through diffusion of responsibility and social loafing behavior. This mechanism manifests as employees perceiving a diffusion of responsibility due to the involvement of multiple actors in service production, leading to social loafing behaviors that subsequently affect value formation.

In human-robot interaction contexts, the service providers consist of both employees and service robots, who together form a new service team \cite{Xiao & Kumar, 2021}, while customers also frequently participate in the service production process \cite{Bieler et al., 2022; Menguc et al., 2020}. This results in service outcomes being influenced by multiple actors, including service robots, employees, and customers. Although high fit and compatibility indicate alignment between the robot and organizational positioning—and smoother interactions between employees, customers, and robots—fit cannot resolve the ethical issues brought by technology. Research has found that while digital technology improves organizational efficiency, it can also lead to problems such as employee deskilling and diffusion of responsibility (Xie et al., 2021; \cite{Raisch & Krakowski, 2021}). Human-robot collaboration causes responsibility to be diffused between individuals and robots, making the "free-rider" effect more likely (Huang & Li, 2021). Highly integrated robots become deeply embedded in service processes, forming a human-robot responsibility collective. This leads to blurred boundaries of responsibility between employees and robots (Zheng et al., 2025), making responsibility tracing difficult and diluting the employee's sense of responsibility. For example, when a hotel navigation robot accurately guides a customer, employees may assume the robot has assumed full responsibility for guidance, thereby reducing their own willingness to intervene and blurring service responsibilities. Accordingly, it can be inferred that service robot-work environment fit positively influences the diffusion of responsibility.

Diffusion of responsibility, also known as the bystander effect, is a phenomenon where individuals in a group feel less responsible than they would if acting alone; it is a common mechanism of moral disengagement \cite{Bandura et al., 1996}.

According to the mechanism of moral disengagement, if the sole service provider is the employee, they clearly recognize their responsibility in serving the customer. However, when multiple actors are responsible for the service outcome, employees may believe they bear only partial rather than full responsibility, or even feel that other actors (such as the service robot) should bear more responsibility. This perception induces social loafing, where individuals exert less effort in a team or collective task than they would when working alone \cite{George, 1992}, which is considered a form of unethical behavior. When firms use work teams composed of employees and service robots to serve customers, service performance is presented in a team format. Because individual contributions cannot be clearly identified within team performance and the visibility of service tasks is low, the willingness of human employees to exert effort decreases, leading to social loafing \cite{George, 1992; Price et al., 2006}. Accordingly, it can be inferred that diffusion of responsibility positively influences employees' social loafing behavior.

Social loafing implies that employees exert less effort during service, such as failing to respond promptly to customer needs, not proactively helping customers, or shifting service tasks to the service robot. Research has noted that frontline employees in the hotel industry exhibit more severe behaviors such as evading and shirking responsibilities during team collaboration \cite{Luo et al., 2013}. Such behavior leads to negative consequences, including impaired team coordination and hindered service processes, which directly lower customer evaluations of overall service quality and may even damage the firm's brand image. Social loafing also causes employees to reduce their workload, actively lower work efficiency, decrease expectations of success, and reduce commitment to the group. Since frontline employees are typically viewed as representatives of the firm \cite{Liao & Chuang, 2004}, their service level, attitude, and capability are crucial to the customer experience and have long-term impacts on organizational performance \cite{Wu et al., 2021}. Social loafing behavior hinders the realization of employees' psychological value (e.g., work thriving, psychological well-being) and work value (e.g., job performance, innovation performance), as well as customers' functional and emotional value. In summary, the following hypothesis is proposed:

Service robot-work environment fit triggers a diffusion of responsibility effect, fostering social loafing behavior among employees, and ultimately damaging both employee and customer value.

3.3.2 个体、互动和组织界面因素的调节作用

Based on Conservation of Resources (COR) theory, this study utilizes factors from different interfaces as moderating variables to analyze the boundary conditions of service robots in creating value for both employees and customers. An employee's promotion orientation is expected to strengthen the value co-creation path. This is because promotion-oriented employees focus more on information and resources related to success in order to achieve self-development and advancement \cite{Higgins1992, Lockwood2002}. They view service robots as vital work resources and enabling factors; consequently, they actively embrace the work transformations brought about by service robots, perceiving them as challenging stressors and proactively adjusting themselves to adapt to changes in the work environment. Furthermore, they view these changes as opportunities for personal success and growth, which helps stimulate self-management behaviors such as planning, performance monitoring, and seeking training opportunities. Conversely, an employee's prevention orientation strengthens the value co-destruction path. Prevention-oriented employees are more concerned with information and resources related to avoiding failure and negative outcomes \cite{Higgins1992, Lockwood2002}, prioritizing the safe completion of tasks and exhibiting more conservative behaviors \cite{Forster2003}. They tend to decouple their own tasks from those of the robot, strictly demarcating their respective spheres of responsibility to ensure their own resources remain intact, which makes them more prone to diffusion of responsibility. Simultaneously, a prevention orientation easily triggers negative emotions \cite{Brockner2001}; workplace changes cause these employees to perceive greater difficulties and challenges, exacerbating withdrawal and conservative behaviors such as reducing workloads or exerting less effort in their tasks.

Based on the above, the following propositions are formulated: (1) Promotion orientation strengthens the path of "Service Robot-Work Environment Fit $\rightarrow$ Challenge Appraisal $\rightarrow$ Self-Management Behavior $\rightarrow$ Value Creation," thereby promoting value creation for both employees and customers; (2) Prevention orientation strengthens the path of "Service Robot-Work Environment Fit $\rightarrow$ Diffusion of Responsibility $\rightarrow$ Social Loafing Behavior $\rightarrow$ Value Destruction," thereby exacerbating value destruction for both employees and customers.

Social support refers to the emotional support and material assistance individuals obtain from their social networks, such as family members, friends, customers, and others \cite{Cohen1985}, and serves as a critical resource for individuals coping with stress. Research has found that social support not only has an additive effect on an individual's physical and mental health but also plays a protective role in negative situations, enhancing an individual's confidence to cope with environmental challenges \cite{NahumShani2011}. Social support is correlated with an individual's psychological health and life perceptions, such as life satisfaction and positive affect \cite{Chu2010, Cohen1985}, making people more optimistic and positively influencing their subjective well-being. Conversely, a lack of social support can directly lead to negative psychological states such as depression and distress, and can undermine the self-concept. If employees can obtain sufficient social support from their social networks—including colleagues, supervisors, and customers in the workplace, as well as family and friends outside the workplace—they are less likely to suffer from the negative impacts of resource depletion (such as job insecurity caused by service robots) and are more willing to invest existing resources to achieve resource gains \cite{Hobfoll2011}. Based on this, this study proposes the following:

Social support strengthens the "Service Robot-Work Environment Fit $\rightarrow$ Challenge Appraisal $\rightarrow$ Self-Management Behavior $\rightarrow$ Value Creation" path and weakens the "Service Robot-Work Environment Fit $\rightarrow$ Diffusion of Responsibility $\rightarrow$ Social Loafing Behavior $\rightarrow$ Value Destruction" path, thereby promoting value creation for employees and customers. In other words, social support strengthens the value co-creation path and weakens the value co-destruction path.

Developmental Human Resource Practices (DHRP) refer to the supportive strategies and management methods organizations invest in to meet the developmental needs of their employees \cite{Jung2018, Kuvaas2008}. First, these practices emphasize employee career development by providing career advice and guidance to help employees adapt to changing work environments. Second, firms provide employees with opportunities for training.

This helps employees master new knowledge and skills \cite{Marescaux2019}, thereby increasing their technological self-efficacy. Furthermore, developmental HR practices provide employees with fair and reasonable performance feedback, helping them evaluate and improve their technical capabilities while providing incentives that enhance their sense of work meaningfulness and creative potential. Therefore, when an organization implements developmental HR practices, employees perceive that the firm values their development and provides them with sufficient resources; they are then more likely to view workplace stressors as challenges and are willing to assume more responsibility. Conversely, when developmental HR practices are insufficient, the lack of external resource support makes employees more inclined to conserve their own resources and engage in opportunistic behaviors. Research indicates that a supportive organizational climate and transformational leadership can significantly mitigate the negative impacts of human-robot interaction \cite{Li2019, Yu2022}. Developmental HR practices can provide employees with positive psychological experiences, improving their job satisfaction and performance. Research specific to service robots also points out that developmental HR practices positively moderate the positive impact of employee-robot work engagement on psychological empowerment \cite{Liu2025}. Corporate managers and service robot technical professionals need to engage in effective interaction with employees in advance, including redesigning employee service roles, providing more opportunities to learn new skills, encouraging skill enhancement \cite{Beane2019}, motivating employees to work alongside service robots, and helping them master professional knowledge of service robots to handle technical contingencies \cite{Tuomi2021}. Based on this, this study proposes:

The following proposition: Developmental HR practices strengthen the "Service Robot-Work Environment Fit $\rightarrow$ Challenge Appraisal $\rightarrow$ Self-Management Behavior $\rightarrow$ Value Creation" path and weaken the "Service Robot-Work Environment Fit $\rightarrow$ Diffusion of Responsibility $\rightarrow$ Social Loafing Behavior $\rightarrow$ Value Destruction" path, promoting value creation for both employees and customers. That is, developmental HR practices strengthen the value co-creation path and weaken the value co-destruction path.

4 理论构建

Although service robots have been widely deployed in service scenarios such as hotels, restaurants, scenic spots, airports, shopping malls, hospitals, and banks, many have been idled or "laid off" due to their inability to adapt to the environment. Reflecting on the problems behind this phenomenon, and breaking away from previous service robot research that emphasized subjects over relationships, impacts over interventions, and customers over employees, this study proposes the concept of service robot-work environment fit (SR-WE fit). We aim to deconstruct its dimensions and explore its formation mechanisms and subsequent impact on value creation. Based on this conceptualization, this research constructs a theoretical framework through three closely related and progressive stages. The main thread follows the path of "robot and work design characteristics $\rightarrow$ service robot-work environment fit $\rightarrow$ employee and customer value creation," exploring boundary conditions from the perspectives of organizational agency and conservation of resources (as shown in [FIGURE:1]). Specifically, Study 1 focuses on the SR-WE fit itself, including the systematization of its theoretical foundations, the definition of its internal structure, and the development of a measurement scale. Study 2 explores how to promote the fit between service robots and the work environment from the perspectives of robot and work design, while analyzing the moderating roles of technology-oriented, employee-oriented, and customer-oriented factors from an organizational agency perspective to reveal the formation mechanism of fit. Study 3 constructs a "double-edged sword" impact path of "fit $\rightarrow$ employee cognitive appraisal and behavior $\rightarrow$ value creation," while exploring contingency factors across individual, interactive, and organizational interfaces to reveal the influence mechanism of SR-WE fit.

The research framework not only provides a new theoretical perspective for understanding the relationship between service robots and the work environment but also offers guidance for management issues such as human-machine collaboration, value co-creation, and intelligent transformation, which are of great concern to service enterprises adopting robots.

Moderation based on conservation of resources: Technology-oriented, employee-oriented, individual, interactive, robot and work design characteristics; Value creation for employees and customers; Service robot-work environment fit: Research on theoretical foundations, internal structure, and scale development; Research on the dual-path influence mechanism of service robot-work environment fit on employee and customer value creation; Research on the antecedents of service robot-work environment fit.

The theoretical construction of this study comprises three aspects. First, based on the new types of interactive relationships brought about by service robots, we deconstruct SR-WE fit, analyze its theoretical basis and internal structure, and develop a corresponding measurement scale to promote the conceptual and measurement development of "fit." Distinct from previous studies that focused on the fit between technology and brand image \cite{et_al_2022}, technological innovation and corporate responsibility \cite{McLeay_et_al_2021}, or technology and tasks \cite{Tuomi_et_al_2021}, this study explores the internal structure of fit based on the multi-dimensional combinations of service encounters within realistic contexts. We deconstruct it into service robot-enterprise fit, service robot-frontline employee fit, and service robot-customer fit. This approach expands and deepens the understanding of the concept's essence and will further promote the development of service robot theory by extending the content and explanatory scope of fit theory.

Second, this study applies work design theory and mind perception theory to service robot research, exploring the antecedents and boundary conditions of SR-WE fit from an innovative perspective. Previous studies have mostly relied on anthropomorphism theory, social presence theory, and the Technology Acceptance Model (TAM) to analyze the impact mechanisms of service robots on customers. However, these are insufficient for explaining the formation mechanism of SR-WE fit, and the analysis of management strategies and organizational-level factors remains inadequate \cite{Liu_et_al_2022}. This study pioneeringly constructs an antecedent model of SR-WE fit under the influence of robot characteristics (distinguished into surface and deep-level characteristics) and work design characteristics. By considering the moderating effects of organizational strategies and investments oriented toward technology, employees, and customers, the model reflects the complexity of fit formation. The results not only reveal the process of fit formation but also open new avenues for research on related topics in the service field.

Furthermore, based on value co-creation theory, this study reveals the double-edged sword effect of SR-WE fit on value creation. Existing research primarily focuses on the impact of service robots on customer cognition, emotion, evaluation, and behavioral intentions \cite{Santiago_et_al_2024, Liu_Liu_Yang_et_al_2024}. Some scholars have begun to analyze the challenges and opportunities service robots bring to employees, such as job insecurity, negative emotions, and turnover intentions \cite{Chen_Cai_2019, Li_et_al_2019, Pan_et_al_2025}, as well as job engagement, job crafting, and well-being \cite{Liu_Xie_2022, Song_et_al_2022}, though these findings are relatively sparse. This study proposes that SR-WE fit may trigger different cognitions in employees, thereby affecting value formation. In the co-creation path, fit promotes value creation through challenge appraisals and self-management behaviors; in the co-destruction path, fit hinders value creation through diffusion of responsibility and social loafing behaviors. If resources can be replenished at different levels—such as promotion orientation at the individual interface, social support at the interactive interface, and developmental HR practices at the organizational interface—it will help strengthen the value co-creation path and weaken the value co-destruction path. By analyzing the impact of fit from cognitive and behavioral perspectives based on these dual paths, this study provides a systematic and comprehensive research approach to understanding the mechanisms of SR-WE fit, serving as a robust supplement to research on individual cognition and behavior in the context of human-machine co-creation.

In summary, service robots have become a focal point of academic attention in recent years, yielding rich research results \cite{Liu_Xie_2022, Guan_et_al_2024, Liu_et_al_2025, Yan_et_al_2025}. Building upon prior achievements and interdisciplinary theoretical foundations, this study strives for breakthroughs in conceptualization and model construction. By systematically exploring the internal structure, antecedents, and impact mechanisms of service robot-work environment fit on value creation, this research provides a new perspective and theoretical toolkit for analyzing how enterprises handle complex human-machine relationships in service scenarios empowered by intelligent technology.

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(8), 2971 Zhang, L. X., Li, J. M., Wang, L. L., Mao, M. Y., & Zhang, R. X. (2023). How does the usage of robots in hotels affect employees’ turnover intention? A double edged sword study Journal of Hospitality and Tourism Management The f ormation and mpact echanism of service robot work environment fit GUAN Xinhua XIE Lishan , MA Xujing School of Culture Tourism, Guangdong University of Finance and Economics, Guang 510320, China

( 2 School of Business, Sun Yat - sen University, Guangzhou 510275, China )

Abstract

The rapid advancement of artificial intelligence and robotics technology has enabled businesses to deploy robots to create value for customers. However, issues such as service failures caused by robots, forced decommissioning, underutilization remain prevalent. Existing research has primarily focused on the impact mechanisms of service robots on customers and employees, with little attention given with the work environment. Grounded in the erson nvironment heory, his study proposes the concept of service robot work environment explore its connotation structure and measurement methods and investigates its antecedents from mult iple perspectives. Furthermore, investigates the dual path impact mechanism of service robot work environment on employee value and customer value creation. The anticipated findings are expected to advance the theoretical development of service robo ts and provide guidance on specific management challenges faced by enterprises in the intelligent era, including human robot collaboration, value co creation, and intelligent transformation.

Keywords

service robot; value co creation; value co destruction; person environment fit theory