Designing for aging on the move: A user-centered approach to recreational vehicle (RV) lifestyle for the elderly using Kano–AHP–QFD

YinJing1,3Emailcysdesign@163.com

ShengYu2

YongshengCheng3✉

XinxinYang3

1School of Future DesignBeijing Normal University519087ZhuhaiP.R.China

2School of the English Language & CultureXiamen University Tan Kah Kee College363123ZhangzhouP.R.China

3School of Design & InnovationXiamen University Tan Kah Kee College363123ZhangzhouP.R.China

Yin Jing^a,c, Sheng Yu^b, Yongsheng Cheng^c*, Xinxin Yang^c

a: School of Future Design, Beijing Normal University, Zhuhai 519087, P.R.China.

b: School of the English Language & Culture, Xiamen University Tan Kah Kee College, Zhangzhou 363123, P.R.China.

c: School of Design & Innovation, Xiamen University Tan Kah Kee College, Zhangzhou 363123, P.R.China;

*Corresponding author: cysdesign@163.com

Abstract

Against the backdrop of an aging population and ongoing innovations in eldercare models, travel-based retirement—an emerging lifestyle that integrates tourism and senior living—calls for age-friendly recreational vehicle (RV) designs to meet the diverse residential and mobility needs of older adults. In such mobile retirement contexts, we aim to identify optimized design strategies for RVs that enhance living comfort and functional adaptability for elderly users. First, data were gathered through online questionnaires and field interviews to uncover the core needs of elderly RV users. Then, these needs were classified using the Kano model into five types: must-be, one-dimensional, attractive, indifferent, and reverse. Next, the Analytic Hierarchy Process (AHP) was used to prioritize these needs within a demand evaluation system. Subsequently, Quality Function Deployment (QFD) was applied to construct a House of Quality that maps user needs to product design characteristics and identifies key design indicators. Based on the integrated analysis, we distilled six core design elements and developed three RV solutions tailored to elderly users. Finally, user evaluations helped determine the optimal solution. Our findings demonstrate that the combined Kano–AHP–QFD approach effectively quantifies elderly users’ demands, enhancing design rigor and user satisfaction. This methodological framework shows strong practical value in age-friendly RV development and offers a foundation for integrating intelligent technologies and human-centered care into future travel-based retirement solutions.

Keywords:

Kano model

AHP

QFD

RV Design

Travel-based elderly care

1. Introduction

By 2050, about one in five people worldwide, according to UN projections, will be aged 65 or older. China exemplifies this global trend: its over-65 population will surge from 172 million (12 percent) today to an estimated 366 million—over 30% of the total population. This shift, further complicated by the “4 grandparents + 2 parents + 1 child” family structure resulting from the three-decade-long one-child policy, drives elderly individuals toward homogenized institutional services that often neglect emotional and experiential needs.

Against this background, travel-based retirement models in China, especially RV-based lifestyles, show promise for countering loneliness & depression^,, sharpening mental function^7,, and enhancing existential well-being. Meanwhile, China has in recent years introduced a suite of national-level policies addressing campsite approval, utility access, and road connectivity, leading to a surge in RV campsites and improved public service facilities, which in turn drives the standardization of camping tourism services. Consequently, the Chinese RV market grew by 24.3% in 2023, an upward trend in tandem with America and Europe. Notably, around 60% of RV buyers at recent China-held exhibitions were seniors, though the current Chinese and global RV manufacturing industry remains largely oriented toward younger users^,, falling short of age-friendly standards in aspects such as spatial layout and functional configuration. Common issues include narrow interior walkways, complex control interfaces, and safety hazards in bathroom areas—revealing a general lack of consideration for age-related physical and cognitive changes among elderly users. This is particularly true for those craving cross-regional traveling, as age-related declines in fluid intelligence—especially spatial cognition and navigational abilities—can significantly challenge elderly travelers’ ability to safely and effectively navigate unfamiliar environments.

To further elucidate the scholarly advances in RV design for older adults, we review the existing literature and found it spans four main dimensions: user needs identification, spatial improvement, design method innovation, and the integration of intelligent technologies.

Regarding user needs identification, Xia & Cao analyzed their characteristics and travel expectations, and proposed targeted strategies for designing RVs for the new generation of elderly users. Li explored the software-hardware integration and multi-modal interaction design of shared RVs from a user-centered perspective, offering optimized design suggestions. Despite their insights, the two studies are mainly non-empirical or non-experimental personal perspectives, thus compromising the reliability and reproducibility of the design process. A data-based study in this respect is Wu. Through questionnaire surveys on twenty users, Wu²² identified problems such as noise and limited storage in current RVs and recommended promoting smart features, sustainable materials, and modular function customization. While the study provides useful insights into user preferences and design trends, its post-design focus, lack of methodological clarity, and limited engagement with recent literature constrain its academic robustness.

As regards spatial improvement, Chen et al. improved the ergonomic layout of kitchen spaces in a C-type RV, providing valuable guidance for future spatial design. Lin et al., drawing on the Affordance Theory, analyzed cognitive, sensory, behavioral, and functional affordances, and proposed principles of comfort, usability, and contextual relevance for interior space. These space-only studies, though, ignore user demands and lacks implications for the overall vehicle design, including interactive interface, of an age-friendly RV.

In terms of design methods, Wang et al.¹⁴ employed a comparative and practice-based CAD-driven design approach to develop a RV tailored to the emerging Chinese market. More recently, researchers have adopted innovative design methods of designing RVs. Xu et al., for example, addressed design homogeneity by employing an Analytic Hierarchy Process (AHP) model, expert scoring, and fuzzy comprehensive evaluation to identify and refine optimal design schemes. Tu and Li combined the Fuzzy Analytic Hierarchy Process (FAHP) with the Function-Behavior-Structure (FBS) model to analyze user needs and optimize human-machine interactive interfaces. While these studies have made notable contributions to RV design methodologies and partial RV design, they lack a closed-loop, full-chain design process that systematically identifies, prioritizes, and translates user needs into spatial planning, styling, and interactive interfaces through an integrated framework.

As for integration of intelligent technology, Zhang et al.¹⁶ incorporated augmented reality (AR) into RV personalization, enabling users to customize interiors and thereby opening new avenues for the development of the RV industry. This study, however, primarily focuses on how AR can support VR platform optimization, without addressing age-friendly, whole-vehicle customization.

Overall, current research underscores that user needs are central to product design. Nonetheless, the design of recreational vehicles (RVs) for the elderly still leaves considerable room for improvement, and most existing evaluation systems overlook detailed and systematic user experience feedback. These gaps motivated us to propose an integrated design framework. Our approach centers on the elderly’s physiological and behavioral characteristics, combining the Kano model, Analytic Hierarchy Process (AHP), and Quality Function Deployment (QFD) to address two key challenges:

How can elderly users’ needs be systematically identified and prioritized to uncover key pain points in RV design?

How can the needs–function mapping process be enhanced to effectively transform user demands into design solutions for elderly-friendly RVs?

Through a structured process of “needs identification – priority quantification – function mapping,” we aim to establish a replicable demand-driven optimization pathway for RV design.

2. Theoretical framework and design flow

2.1 Kano model

The Kano model is a qualitative tool that classifies user needs into five categories—must-be (M), one-dimensional (O), attractive (A), indifferent (I), and reverse (R) (Fig. 1), unlike Kansei Engineering, which captures users’ affective impressions and maps them to concrete design parameters. The Kano model enables a systematic identification of needs priorities and reveals the relationship between product attributes and user satisfaction, and have therefore been used in multiple disciplines, particularly in product or service development and optimization. Many researchers have incorporated this model into more sophisticated models for design, such as smart product design through a Fuzzy Kano–AHP–DEMATEL–QFD approach, and smartphone and camera design through a Kansei-integrated Kano model. In the field of age-friendly design, the model has informed many strategies^,^,^, (Tu & Zhou, 2025; Li et al., 2025; Lin et al., 2024; Wang et al., 2025). Take Li et al.’s³⁴ research for example. Utilizing the IPA-Kano model, they quantified the needs and perceptions of the elderly and explored the key factors affecting the age-friendly design of Chengdu East Railway Station. This study, though, fails to produce actionable design solutions. More enlightening is Wang et al.’s³⁶ research, which designed a walker product under the combined Kano–AHP–FCE framework. A more relevant study is Jing et al.’s research on designing an daily-use electric vehicle for the elderly. These existing studies on the Kano model have proven its effectiveness in accurately identifying the pain points of elderly users and supporting well-informed design decisions, thus guiding the present study on how to design an age-friendly RV.

Fig. 1

The Kano model

2.2 AHP Model

The Analytic Hierarchy Process (AHP) enables quantitative analysis for multi-criteria decision-making by constructing a hierarchical structure consisting of layers of the goal, criteria, and alternatives, supported by pairwise comparison matrices and consistency checks^,. Its scientific rigor and reliability have made it widely applicable in the study of complex problems^,. In the context of age-friendly design, AHP is often integrated with other techniques to enhance decision-making efficiency^31,36,^,. For example, employing the AHP, along with QFD and Kansei Engineering (KE), Li and Li⁴³ developed a elderly-user-tailored home-use intelligent blood glucose meter that not only meets users’ physiological and psychological needs but also provides an operationally convenient, health-conscious, and aesthetically pleasing experience. These practical applications demonstrate AHP’s notable strengths in balancing multidimensional demands and integrating both subjective and objective weightings, thereby providing systematic decision support for our age-friendly RV design.

2.3 QFD Theory

Quality Function Deployment (QFD), developed by Mizuno and Akao, is a structured methodology that translates user needs into engineering parameters using its core tool—the House of Quality. By prioritizing user requirements and mapping them through correlation matrices, QFD establishes a clear link between customer expectations and design elements during product development, thereby making products more relevant and user-centered. In the field of age-friendly design, QFD has evolved into multidimensional application frameworks, such as AHP–QFD–KE for designing age-appropriate smart blood glucose detector⁴³, Kano–AHP–QFD for a control interface of passenger car center⁴², and KE–QFD a age-friendly restaurant platform. These practices have demonstrated QFD’s methodological strengths in interdisciplinary integration, precise demand translation, and iterative product optimization, thus providing a methodological reference for our research.

2.4 Model construction

By integrating three complementary methods, we developed a Kano–AHP–QFD model that forms a complete process from user needs investigation to product design and development. We began with the Kano model to classify user needs—collected through questionnaire surveys—into five categories: must-be, one-dimensional, attractive, indifferent, and reverse. This classification helped us understand how different types of needs influence user satisfaction. However, since the Kano model does not quantify the priority of each needs, we incorporated the Analytic Hierarchy Process (AHP) to address this gap. By constructing pairwise comparison matrices, we quantified the relative importance of each user needs, which allowed us to prioritize them scientifically and identify key directions for design optimization.

Despite the effectiveness of the Kano–AHP combination in identifying user needs and their priorities, it still lacked a way to translate these needs into concrete design parameters. To solve this problem, we applied Quality Function Deployment (QFD). We used the AHP-generated weights to build a correlation matrix that connects user expectations with specific product design features. This approach enabled us to define technical requirements based on user priorities and focus the design process on what matters most to elderly users. Ultimately, our integrated model helped us transform user expectations into actionable design solutions and provided a solid foundation for targeted, user-centred product development. The overall design process is shown in Fig. 2.

Fig. 2

A flow chart of age-friendly RV design

3. Research process

3.1 Initial needs analysis based on the Kano model

3.1.1 Acquiring user needs

During the needs acquisition phase for elderly RV design, we focused on individuals aged 60 and above with prior RV driving experience to ensure authentic and reliable data. We first identified preliminary user needs through internet research and a review of relevant literature, as analyzed in previous sections. Then using both video and audio recordings (see Fig. 3), we conducted in-depth field interviews with 15 elderly participants, most of whom had droven a long way from North China to Southeast China’s Xiamen city. These interviews explored needs in daily living, functions, and driving.

The recorded materials were transcribed into text using TurboScribe (https://turboscribe.ai/), and subsequently verified manually. Key user needs were extracted using MAXQDA. To ensure the reliability of this process, we achieved a high level of inter-coder agreement (Cohen’s κ = 0.94). Disagreements were resolved through discussion with a third expert. Finally, we conducted member checking by returning the extracted needs to the original interviewees for confirmation and clarification.

Table 1
User needs for elderly RV design
Primary needs	Secondary needs	Explanation
N1 Living	n1 Comfortable to sleep in	The bed area is comfortable and spacious and has privacy.
	n2 Toilet ventilation	Toilet has air exchange and ventilation.
	n3 Separate bathroom	The shower area has a separate space (wet and dry separation).
	n4 Non-slip toilet flooring	The toilet area features a non-slip design.
	n5 Separate kitchen	The kitchen area in the car has a separate enclosed space (to prevent fumes from spreading)
	n6 Spacious kitchen	The kitchen area is spacious and can be operated by two people efficiently.
	n7 Organized storage	Inside the RV, there is a well-organized storage space.
	n8 Spaciousness	It is easy to walk and turn around in the RV, and it is not crowded when placing wheelchairs and other assistive devices.
	n9 Air-drying	The RV has an interior area for drying clothes
	n10 Window lighting	Large windows in the RV can meet the needs of lighting and ventilation.
	n11 Mechanical ventilation	The RV is equipped with mechanical ventilation
N2 Use	n12 Intelligent applications	In-vehicle equipment and facilities can be intelligently controlled (e.g. voice, APP control ...)
	n13 Outdoor space	Outdoor space that can meet the needs of drinking tea and playing chess, fitness and exercise (e.g. awnings, outdoor tables and chairs, etc.)
	n14 Leisure and space	The RV has a leisure area with comfortable seats, convenient access and a spacious area.
	n15 Area needs	The leisure area can meet the needs of meeting guests, working, eating and other daily needs.
	n16 Two-person co-mobility	The RV has interior activity space for two persons (e.g., joint exercise).
	n17 Independent space for two	The RV has a separate interior space for two people
	n18 Medical supplies	The RV supports refrigerated storage of medicines, and has space for first aid equipment, wheelchair crutches, and health testing equipment.
	n19 Space for pets	The RV has an interior space for pets to rest and interact with pets.
N3 Safety	n20 Emergency call	The RV is equipped with an emergency call system (can quickly contact rescue organizations or family members).
	n21 Medical inquiry	The RV provides a medical information lookup feature (e.g., nearby hospitals, navigation ...).
	n22 Activity monitoring	The RV is equipped with a system to intelligently monitor activity status (e.g. fall, fainting monitoring ...).
	n23 Body security	The RV is fitted with body monitoring (monitoring the surroundings of the caravan when parked).
	n24 Good privacy	The RV prevents outsiders from prying into the vehicle.
	n25 Convenient facilities	The RV has convenient boarding and alighting facilities (e.g. handrails, pedals, low step design).
N4 Exterior and interior	n26 Appropriate styling	Exterior styling is stable and simple.
	n27 Comfortable color scheme	Calm, atmospheric colors are used.
	n28 Suitable materials	Seat and bed materials are soft and breathable, with non-slip design.
	n29 Environment-friendly decorations	The materials in the RV are environment-friendly and non-toxic.
	n30 Easy to clean	The interior is easy to clean and wear-resistant.
	n31 Interior lighting	Interior lighting is good, and there are no dead spots at night.
N5 Driving	n32 Vehicle monitoring	The RV includes smart monitoring function (vehicle tire pressure, fault warning).
	n33Vehicle Operation	Driving operation is simple and easy to understand (instrument panel display is clear; control buttons are well laid out and easy to follow).
	n34 Vehicle driving	The RV provides good driving vision (e.g. through anti-glare mirrors that reduce glare from vehicles behind).

Fig. 3

On-site interviews

3.1.2 Kano questionnaire analysis

Following the principles of the Kano model, we designed a five-point scale questionnaire based on the above 34 user needs indicators. Each item of the questionnaire was presented in both positive, neutral, and negative forms to capture respondents’ attitudes more comprehensively. The response options were structured as follows: “I like it that way” (5 points), “It must be that way” (4 points), “I am neutral” (3 points), “I can live with it that way” (2 points), and “I Dislike it that way” (1 point).

To maximize data coverage, we adopted a cross-platform, mixed-mode distribution strategy. Specifically, questionnaires were shared online via targeted communities such as the “Exchange Group for RV Self-driving Traveling” and offline in campgrounds. As a result, we collected a total of 106 responses, 90 (84.9%) of which were valid after excluding incomplete questionnaires and uniform response bias.

The valid responses were subsequently processed using SPSS 26.0. User needs attributes were categorized in accordance with Kano’s classification method (Table 2), enabling a structured understanding of user preferences and expectations.

Table 2
Kano classification for positive/negative questions
Function/Service		Negative questions
Function/Service		I dislike it that way (1 point)	I can live with it that way (2 points)	I am neutral (3 points)	It must be that way (4 points)	I like it that way (5 points)
Positive questions	I dislike it that way (1 point)	Q	R	R	R	R
	I can live with it that way (2 points)	M	I	I	I	R
	I am neutral (3 points)	M	I	I	I	R
	It must be that way (4 points)	M	I	I	I	R
	I like it that way (5 points)	O	A	A	A	Q
Notes: A: Attractive, O: One-dimensional, M: Must-be, I: Indifferent, R: Reverse, Q: Questionable

3.1.3 Better–Worse data calculation and quadrant plotting

To further quantify the impact of each indicator on user satisfaction, we calculated the Better–Worse coefficients, which evaluates how a functional requirement influences user satisfaction and helps orient product development and optimization³³. Specifically, the Better value (B), also known as the satisfaction coefficient, reflects the extent to which meeting a requirement increases satisfaction. It typically ranges from 0 to 1, with values closer to 1 indicating a stronger positive impact. Conversely, the Worse value (W), or the dissatisfaction coefficient, measures the degree to which not meeting a requirement decreases satisfaction. This value usually ranges from 0 to − 1, with scores nearer to − 1 indicating a greater negative impact.

Using SPSS 26.0, we calculated these coefficients based on the response distributions across the five Kano attributes. The calculation formulas are shown in Equations (1) and (2), and the results of the Kano analysis for the preliminary user needs are presented in Table 3.

$B=\frac{{A+O}}{{A+O+M+I}}$

$W=( - 1) \times \frac{{O+M}}{{A+O+M+I}}$

Table 3
Kano attributes and Better-Worse coefficients of RV user needs
User needs Indicators	M/%	O/%	A/%	I/%	R/%	Attributes	B/%	W/%
n1	36.67	18.89	26.67	17.78	0.00	M	45.56	-55.56
n2	30.00	21.11	23.33	25.56	0.00		44.44	-51.11
n10	27.78	26.67	16.67	27.78	1.11		43.82	-55.06
n13	30.00	17.78	24.44	26.67	1.11		42.70	-48.31
n15	32.22	14.44	30.00	22.22	1.11		44.94	-47.19
n32	33.33	24.44	17.78	23.33	1.11		42.70	-58.43
n33	30.00	23.33	23.33	22.22	1.11		47.19	-53.93
n34	27.78	18.89	26.67	25.56	1.11		46.07	-47.19
n3	16.67	35.56	27.78	20.00	0.00	O	63.33	-52.22
n7	20.00	40.00	21.11	18.89	0.00		61.11	-60.00
n14	20.00	35.56	24.44	20.00	0.00		60.00	-55.56
n23	14.44	41.11	27.78	15.56	1.11		69.66	-56.18
n24	6.67	50.00	21.11	21.11	1.11		71.91	-57.30
n27	7.78	36.67	24.44	31.11	0.00		61.11	-44.44
n28	14.44	42.22	18.89	24.44	0.00		61.11	-56.67
n30	15.56	35.56	26.67	21.11	1.11		62.92	-51.69
n31	11.11	42.22	21.11	24.44	1.11		64.04	-53.93
n4	14.44	21.11	46.67	16.67	1.11	A	68.54	-35.96
n5	17.78	17.78	43.33	21.11	0.00		61.11	-35.56
n8	11.11	20.00	46.67	21.11	1.11		67.42	-31.46
n12	10.00	13.33	48.89	27.78	0.00		62.22	-23.33
n18	7.78	22.22	53.33	16.67	0.00		75.56	-30.00
n20	14.44	33.33	36.67	15.56	0.00		70.00	-47.78
n21	12.22	24.44	44.44	17.78	1.11		69.66	-37.08
n25	10.00	24.44	46.67	18.89	0.00		71.11	-34.44
n26	6.67	25.56	40.00	26.67	1.11		66.29	-32.58
n6	12.22	16.67	27.78	42.22	1.11	I	44.94	-29.21
n11	15.56	18.89	23.33	42.22	0.00		42.22	-34.44
n16	13.33	21.11	24.44	40.00	1.11		46.07	-34.83
n17	15.56	17.78	25.56	40.00	1.11		43.82	-33.71
n19	13.33	15.56	21.11	45.56	4.44		38.37	-30.23
n22	13.33	24.44	23.33	37.78	1.11		48.31	-38.20
n9	14.44	42.22	18.89	24.44	0.00		61.11	-56.67
n29	12.22	33.33	12.22	41.11	1.11		46.07	-46.07

According to the Kano attributes of 34 user needs in Table 3, there were 8 M, 9 O, 9 A, and 8 I attributes.

M included n1 (comfortable to sleep in), n2 (toilet ventilation), n10 (window lighting), n13 (outdoor space), n15 (area needs), n32 (vehicle monitoring), n33 (vehicle operation) and n34 (vehicle driving). When the degree of perfection of these needs was high, user satisfaction rose only slightly; otherwise, it decreased significantly.

O included n3 (separate bathroom), n7 (organized storage), n14 (leisure and space), n23 (body security), n24 (good privacy), n27 (comfortable color scheme), n28 (suitable materials), n30 (easy to clean), and n31 (interior lighting). When these needs were perfected to a high degree, user satisfaction increased, and vice versa, it decreased.

A included n4 (non-slip toilet flooring), n5 (separate kitchen), n5 (separate kitchen), n8 (spaciousness), n12 (intelligent applications), n18 (medical supplies), n20 (emergency call), n21 (medical inquiry), n25 (convenient facilities) and n₂₆ (appropriate styling). When these requirements were well developed, user satisfaction increased significantly, and vice versa, the decrease was insignificant.

I included n6 (spacious kitchen), n11 (mechanical ventilation), n16 (two-person co-mobility), n17 (independent space for two), n19 (space for pets), n22 (activity monitoring), n9 (air-drying), and n29 (environment-friendly decorations). There was no significant relationship between these needs and satisfaction. The quadrant analysis graph of Better–Worse coefficient can visualize the distribution of needs attributes for detailed analysis based on the comparison of 34 needs indicators.

3.2 User needs weight analysis based on AHP

3.2.1 Establishing a hierarchical model

While the Kano model is effective in categorizing user demands for age-friendly RV design, it does not clearly prioritize these needs in terms of importance. To identify key areas of focus in the design process, we integrated the Kano model with the Analytic Hierarchy Process (AHP), a widely used method in product development. By consulting five experts in the filed of design, we assigned weights to each need, enabling a structured calculation and ranking of user needs.

Notably, among the above-mentioned four Kano-based groups of user needs, we excluded the I attributes from the current analysis as they exhibited no clear relationship with user satisfaction. As a result, only those classified under M, O, and A attributes were used to construct the hierarchical framework for age-friendly RV design (Fig. 4). In Fig. 4, level 1 (goal) of the hierarchy defines the core objective and decision-making orientation, which, in this study, is the design of elderly-friendly RVs. Level 2 (criteria) identifies key design principles necessary to achieve this objective, which, in this study, are represented by the M, O, and A attributes. Level 3 (sub-criteria) specifies the concrete design elements and actionable strategies.

Fig. 4

A hierarchical structure model of design needs for age-friendly RVs

3.2.2 Estalishing judgment matrices

To establish the weights of each design element, we invited an panel of 20 evaluators, including 15 older adults with RV driving experience, 2 automotive designers, and 3 professors of design. Via pairwise comparison-based scoring on a scale of 1–9, we constructed a judgment matrix, whose scale and explanation are detailed in Table 4.

Table 4
Scale and explanation of the judgment matrix
Scale	Explanation
1	Indicator a is as important as indicator b
3	Indicator a is slightly more important than indicator b
5	Indicator a is significantly more important than indicator b
7	Indicator a is more strongly important than indicator b
9	Indicator a is extremely more important than indicator b
2,4,6,8	Intermediate values of the above neighboring judgments
1/2,1/3,......,1/9	If indicator i is more important than indicator j on a scale of n, the opposite is 1/n.

The judgment matrix for age-friendly RV design is X (Eq. 3).

$X=\left[ {\begin{array}{*{20}{c}} {1.000}&{0.411}&{0.250} \\ {2.433}&{1.000}&{0.244} \\ {4.000}&{4.100}&{1.000} \end{array}} \right]$

The judgment matrices for M, O, and A attributes are shown in equations (4) to (6), respectively.

$M=\left[ {\begin{array}{*{20}{c}} {1.000}&{0.769}&{1.189}&{1.393}&{2.121}&{1.218}&{1.136}&{0.662} \\ {1.300}&{1.000}&{1.060}&{2.063}&{2.121}&{1.280}&{1.174}&{0.609} \\ {0.841}&{0.944}&{1.000}&{0.761}&{1.230}&{0.652}&{0.946}&{0.385} \\ {0.718}&{0.485}&{1.313}&{1.000}&{0.901}&{0.407}&{0.475}&{0.261} \\ {0.471}&{0.471}&{0.813}&{1.110}&{1.000}&{0.323}&{0.346}&{0.222} \\ {0.821}&{0.781}&{1.533}&{2.457}&{3.100}&{1.000}&{0.502}&{0.286} \\ {0.880}&{0.851}&{1.057}&{2.107}&{2.893}&{1.993}&{1.000}&{0.263} \\ {1.510}&{1.642}&{2.600}&{3.833}&{4.500}&{3.500}&{3.800}&{1.000} \end{array}} \right]$

$O=\left[ {\begin{array}{*{20}{c}} {1.000}&{0.949}&{1.402}&{2.711}&{0.316}&{0.400}&{0.937}&{0.820}&{0.547} \\ {1.053}&{1.000}&{1.394}&{2.546}&{0.375}&{0.449}&{1.376}&{0.670}&{0.811} \\ {0.713}&{0.717}&{1.000}&{1.312}&{0.283}&{0.327}&{0.484}&{0.396}&{0.621} \\ {0.369}&{0.393}&{0.762}&{1.000}&{0.204}&{0.327}&{0.417}&{0.382}&{0.298} \\ {3.167}&{2.667}&{3.533}&{4.900}&{1.000}&{0.588}&{1.460}&{0.940}&{1.082} \\ {2.500}&{2.227}&{3.060}&{3.060}&{1.700}&{1.000}&{1.448}&{1.934}&{1.369} \\ {1.067}&{0.727}&{2.067}&{2.400}&{0.685}&{0.690}&{1.000}&{0.493}&{0.558} \\ {1.220}&{1.493}&{2.527}&{2.617}&{1.064}&{0.517}&{2.027}&{1.000}&{0.370} \\ {1.827}&{1.233}&{1.610}&{3.357}&{0.924}&{0.730}&{1.793}&{2.700}&{1.000} \end{array}} \right]$

$A=\left[ {\begin{array}{*{20}{c}} {1.000}&{0.294}&{0.233}&{0.192}&{0.250}&{0.349}&{0.400}&{0.320}&{0.238} \\ {3.400}&{1.000}&{0.349}&{0.265}&{0.349}&{0.545}&{0.628}&{1.570}&{0.591} \\ {4.300}&{2.867}&{1.000}&{0.265}&{0.455}&{1.034}&{0.890}&{1.783}&{0.685} \\ {5.200}&{3.767}&{3.767}&{1.000}&{0.517}&{0.934}&{1.759}&{2.121}&{1.189} \\ {4.000}&{2.867}&{2.200}&{1.933}&{1.000}&{0.813}&{1.003}&{0.833}&{0.739} \\ {2.867}&{1.833}&{0.967}&{1.070}&{1.230}&{1.000}&{0.726}&{0.869}&{0.417} \\ {2.500}&{1.593}&{1.124}&{0.569}&{0.997}&{1.377}&{1.000}&{0.556}&{0.345} \\ {3.127}&{0.637}&{0.561}&{0.471}&{1.200}&{1.150}&{1.800}&{1.000}&{0.333} \\ {4.200}&{1.693}&{1.460}&{0.841}&{1.353}&{2.400}&{2.900}&{3.000}&{1.000} \end{array}} \right]$

3.2.3 Weight calculation

When calculating the weights, we transformed subjective judgments into numerical values by comparing the importance of any two factors. The specific steps were: (1) listing the pairwise comparison results of all factors, (2) calculating the weight of each factor mathematically, and (3) verifying the rationality of the results. This method enabled us to assign weights objectively. According to the judgment matrix, we applied the geometric mean method to find out the average value V_i (Eq. 7).

${V_{_{{_{{\text{i}}}}}}}=\sqrt[n]{{\prod\limits_{{\text{i}}}^{n} {{s_{ij}}} }}$

Where: S_ij means the ith-row and jth-column indicators in the matrix; n denotes the number of indicators.

The results were then combined into the matrix form (Eq. 8).

${V_z}={\left( {{V_1},{V_2},{V_3}, \cdots ,{V_n}} \right)^T}$

Next, the eigenvectors of the X, M, O and A matrices were calculated by the above formula (Eqs. 9–12).

${V_{\text{x}}}={\left( {1.951,0.672,0.376} \right)^T}$

${V_M}={\left( {2.209,1.015,0.934\invalidcharacter 0.467,0.568,0.731,1.089,0.987} \right)^T}$

${V_O}={\left( {1.372,1.094,0.836,1.697,1.554,0.369,0.519,0.822,0.738} \right)^T}$

${V_A}={\left( {1.617,0.848,0.838,0.9341.299,1.589,0.961,0.639,0.275} \right)^T}$

After normalizing the calculation results, we obtained the weights of the primary indicator, denoted as W = {w₁, w_{(2) ,}... ,w_n}. For each primary indicator, the weights of its sub-criteria were also normalized to form a sub-weight vector W_n={w_{(1) (1)}, w1_{(2) ,}... ,w_ij}, where j={1, 2,3... ,n}, thus the resulting weight vectors W_i (Eq. 13).

${W_{\text{i}}}=\frac{{{V_{\text{i}}}}}{{\sum\limits_{{i=1}}^{{\text{n}}} {{V_i}} }}$

Additionally, by normalizing the weights of each criterion layer and sub-criterion layer, we obtained the normalized weight vectors of each indicator X, M, O, and A (Eqs. 14–17).

${W_{\text{x}}}={\left( {0.650,0.224,0.125} \right)^T}$

${W_{\text{M}}}={\left( {0.276,0.127,0.117,0.058,0.071,0.091,0.136,0.123} \right)^T}$

${W_O}={\left( {0.152,0.122,0.093,0.189,0.173,0.040,0.058,0.091,0.082} \right)^T}$

${W_A}={\left( {0.180,0.094,0.093,0.103,0.144,0.177,0.107,0.071,0.030} \right)^T}$

Through these calculations, we obtained the comprehensive weight values of each user needs indicator, namely: comfortable to sleep in > vehicle operation > toilet ventilation > vehicle driving > window lighting > vehicle monitoring > area needs > body security > privacy > outdoor space > separate bathroom > organized storage > non-slip toilet flooring > emergency call > leisure and space > easy to clean > interior lighting > medical supplies > medical inquiry > intelligence > suitable materials > separate kitchen > spaciousness > comfortable color scheme > convenient facilities > appropriate styling, as shown in Table 5.

Table 5
Weight values of user needs indicators
Criteria Level	Weights of the Criteria Level	Sub-criteria Level	Weights of the Sub-criteria Level	Combined Weights	Ranking of Weights
M	0.650	M1	0.276	0.179	1
		M2	0.127	0.083	3
		M3	0.117	0.076	5
		M4	0.058	0.038	10
		M5	0.071	0.046	7
		M6	0.091	0.059	6
		M7	0.136	0.088	2
		M8	0.123	0.080	4
O	0.224	O1	0.152	0.034	11
		O2	0.122	0.027	12
		O3	0.093	0.021	15
		O4	0.189	0.042	8
		O5	0.173	0.039	9
		O6	0.041	0.009	24
		O7	0.058	0.013	21
		O8	0.091	0.020	16
		O9	0.082	0.018	17
A	0.125	A1	0.180	0.023	13
		A2	0.094	0.012	22
		A3	0.093	0.012	23
		A4	0.104	0.013	20
		A5	0.144	0.018	18
		A6	0.177	0.022	14
		A7	0.107	0.013	19
		A8	0.071	0.009	25
		A9	0.031	0.003	26

3.2.4 Maximum eigenroot calculation

To verify the logical rationality of the judgment matrices, we calculated the maximum eigenroot. After establishing the judgment matrices, we derived their maximum eigenvalues through mathematical operations, and then used these values to invert the weight proportion of each factor. Meanwhile, the consistency index (e.g., CR value) was calculated to rule out self-contradiction in the expert scoring. If the results meet the requirements, it means scientific and credible weight allocation. The operation formula is shown in Eq. (18).

${\lambda _{\hbox{max} }}=\sum\limits_{{i=1}}^{n} {\frac{{{{(MW)}_i}}}{{n{W_i}}}}$

Where n denotes the order of the judgment matrix; M means judgment matrix; and W is eigenvectors of judgment matrix A.

3.2.5 Result consistency test

To ensure the logical consistency of the judgment matrices, we performed a consistency check on the calculated weights (Eqs. 19 and 20). If the result fails the check, the ranking of criteria at each level must be re-evaluated.

${C_{\text{I}}}=\frac{{{\lambda _{\hbox{max} }} - n}}{{n - 1}}$

${C_{\text{R}}}=\frac{{{C_{\text{I}}}}}{{{R_{\text{I}}}}}$

Where n denotes the value corresponding to the evaluation scale of the judgment matrices; C_R stands for consistency ratio; and R_I represents consistency indicator.

When C_R≥ 0.1, it means inconsistency in the judgment matrix, and vice versa. The consistency test results of the comparison matrix of each level are shown in Table 6.

Table 6
Consistency test result
Indicator	λ_max	C_I	R_I	C_R	Consistency
X	3.095	0.047	0.520	0.091	Passed
M	8.297	0.042	1.410	0.030	Passed
O	9.303	0.038	1.460	0.026	Passed
A	9.707	0.088	1.460	0.061	Passed

3.3 Initial needs analysis based on QFD quality house

First, based on user needs and their explanations, similar items were categorized and merged. Then, these needs were matched with appropriate design features, resulting in ten key design features. The relative importance of product quality characteristics was ranked using the QFD quality house. In this method, the quality characteristics are represented as the ceiling of the house, the user needs and their weights as the walls, the correlations between user requirements and quality characteristics as the interior, and the correlation weights and absolute weights of the quality characteristics as the basement (Fig. 5).

Fig. 5

QFD quality house

A panel of experts consisting of five professors of industrial design (three specializing in transportation design and two in service design) evaluated the correlation between the user needs and quality characteristics of age-friendly RVs. Via pairwise comparison-based scoring, where a score of 5, 3, 1, and 0 indicates strong, medium, weak, and no correlation, respectively, we obtained the corresponding scores. Then, using Eqs. 21 and 22, we calculated the absolute and relative importance weights of the product quality characteristics (Table 7).

${O_{\text{j}}}=\sum\limits_{{i=1}}^{q} {{O_i}{P_{ij}}}$

${O_k}=\frac{{{O_j}}}{{\sum\limits_{{i=1}}^{q} {{U_j}} }}$

Where Oj represents the absolute importance weight of quality characteristics, Oi stands for the comprehensive weight of user demand, Pij denotes the correlation coefficient between user demand and quality characteristics, and Ok means the relative importance weight of quality characteristics. The results of the weight calculation were then ranked.

Table 7
Comparison of user needs and quality characteristics correlation icons
User needs	Quality characteristics
User needs	Overall weight of user needs	d₁	d₂	d₃	d₄	d₅	d₆	d₇	d₈	d₉	d₁₀
n₁	0.179	5	3	1	3	1	1	1	1	1	1
n₂	0.083	3	3	1	1	1	3	1		1	1
n₃	0.034	3	3		1	1	3	1			1
n₄	0.012	3	5		3	1	3	1	1	1	1
n₆	0.027	3	5		3	1	3	1		1	1
n₇	0.012	5	5		3	1	1	1		1	1
n₉	0.076	3	1	1	1	1	1	1	1	1	1
n₁₀	0.038	1	1		1	1		1	1		1
n₁₁	0.021	3	3		1		1	1			1
n₁₂	0.046	3	3		1	1				1	1
n₁₃	0.013	1	1	3	3	1	1		1		1
n₁₅	0.023	1	1		3	1				3	1
n₁₈	0.018	1	1		3	5				1	1
n₂₀	0.022	1	1		3	5					1
n₂₁	0.013	1	1		3	3				1	1
n₂₃	0.039	3	3		1		1	1	1	1	1
n₂₄	0.009	3	3	1	1	1	1	1		1	1
n₂₅	0.02	3	3		1		3		1	1
n₂₆	0.018	3	1	1	3	1	1	1	1		1
n₂₇	0.042	3	1	1	1	1		1		3	3
n₂₈	0.003	1	1		1		1	5	3	1
n₂₉	0.009	3	1		1	1	1	3	5
n₃₀	0.013	3	1		1	1	3	3	3	3	1
n₃₂	0.059	1		1	3	3					5
n₃₃	0.088			3	1	1					3
n₃₄	0.08			5	1	1					1
Absolute importance weights of quality characteristics		2.491	1.836	1.169	1.789	1.218	0.946	0.671	0.488	0.771	1.461
Relative Importance Weights of Quality Characteristics / %		1	3	6	2	5	7	9	10	8	4
Notes: d₁₌living comfort; d₂₌reasonable functional layout; d₃₌intelligent vehicle control; d₄₌age-friendly design; d₅₌medical & safety assurance; d₆₌easy-to-clean interior decorations; d₇₌attractive appearance; d₈₌well-coordinated colors; d₉₌suitable material structure; d₁₀₌vehicle safety assurance.

According to Table 7, the importance weights of product characteristics in descending order were: d₁ living comfort > d₄ age-friendly design > d₂ reasonable functional layout > d₁₀ vehicle safety assurance > d₅ medical & safety assurance > d₃ intelligent vehicle control > d₆ easy-to-clean interior decorations > d₉ suitable material structure > d₇ attractive appearance > d₈ well-coordinated colors.

3.2 Summary of design points

According to the above data, we summarized the user needs and product quality characteristics and concluded the design opportunity points (Fig. 6).

Fig. 6

Design opportunity points

4. Design of age-friendly RVs based on Kano–AHP–QFD

4.1 Scheme and evaluation

4.1.1 Scheme construction

The above Kano-based needs analysis identified must-be (M), one-dimensional (O), and attractive (A) attributes as key to enhancing user satisfaction. Accordingly, we focused on prioritizing these three types of attributes using AHP and translating the needs into product quality characteristics through QFD. Drawing on the data in Tables 5 and 7, we prioritized the top-ranked design elements in this RV design.

4.1.1.1 Internal space optimization

Elderly users place high demands on comfort and convenience within the living area. We therefore adopted a barrier-free design to ensure that interior passages and turns comply with accessibility standards, facilitating the movement and transfer of wheelchairs or walkers. In addition, users have specific needs for natural lighting and ventilation. Thus, we incorporated large windows and skylights to introduce sufficient daylight and create a bright, pleasant living environment. Storage space was another key concern, and the layout should be systematically and rationally planned. We therefore set appropriately placed storage cabinets and concealed compartments to provide a spacious, comfortable, and user-friendly interior.

4.1.1.2 Advanced driver assistance system (ADAS)

Elderly drivers may face uncertainties such as decreased reaction speed and unstable operation during the driving process. Thus, we might consider installing advanced driver assistance system (ADAS), which has proved feasible for improve road safety for seniors. The adaptive cruise control, for example, was planned to automatically adjust speed based on the vehicle ahead, maintain a safe following distance, and reduce driver fatigue during long-distance travel. Alao, an intelligent parking assistance system could be installed to reduce the stress of parking by automatically detecting parking spaces and performing assisted or fully automated parking^,. Moreover, a fatigue driving monitoring system, when in place, could detect signs of fatigue by monitoring the driver’s facial expressions, eye movements, and steering wheel operation, and alerts the driver to take a rest, thereby reducing the risk of accidents^,.

4.1.1.3 Comprehensive medical support

To enhance medical support, we planned to equip the vehicle with two key modules. The first was a daily health area featuring a locker stocked with various medicines, first aid kits, and stethoscopes. Commonly used medications could be stored in cabinets with compartmentalized drawers and clearly marked reminder labels. The second module was an emergency response system, which was designed to include SOS buttons at the bedside and in the bathroom; when activated, these buttons automatically send the user’s location to a designated contact person.

4.1.1.4 Intelligent interactive interface

To ease operational challenges for elderly users, we planned to incorporate a high-definition touchscreen interface that supports intuitive gestures and tactile feedback. Additionally, an integrated high-precision voice recognition system could enable seamless voice command control. Considering the user’s concern for vehicle safety, we configured the interface to display real-time vehicle status, environmental monitoring data and navigation information to provide clear and instant vehicle driving information. We also designed the interface to be seamlessly connected with smart phones and cloud platforms to support remote monitoring, vehicle positioning and data synchronization.

4.1.1.5 Durable materials

To avoid slipping under the feet of the elderly, we designed the vehicle flooring to be fully covered with non-slip PVC material. All furniture corners and door handles should be obtuse to prevent the elderly from being injured when bumping. The interior seats could be filled with high-density memory foam and covered with breathable and wear-resistant leather or stain-resistant fabrics, thus balancing comfort and durability. The exterior materials and coatings should be corrosion-resistant to ensure the beauty and durability of the vehicle’s appearance.

4.1.1.6 Beautiful styling and well-coordinated colors

We designed the overall styling to be square and mature-looking, adopting a simple and smooth design language, avoiding overly complex surfaces, and presenting a clean and sophisticated visual style. Such a design aligns with elderly users’ pursuit of safety and practicality while improving space utilization. For color matching, we chose a calm and elegant black, complemented by other accent colors to create a harmonious and comfortable visual experience. The overall design would embody modernity and incorporate classic elements, making the vehicle better suited to the aesthetic preferences and daily needs of elderly users while maintaining its visual appeal.

4.1.2 Refining sketch styling

Based on the key design elements identified through the Kano–AHP–QFD analysis, we further refined the functions and styling of the age-friendly RV.

First, the exterior styling should be developed in alignment with the quality attributes derived in the previous section. Building upon these attributes, three preliminary design concepts were hand-sketched to explore potential styling directions. Then, for users to have a better concept visualization, renderings from the line drawings were created using an AI-powered website (https://www.bigbigai.com/).

Second, the interior design should follow the principles of comfort, safety, and age-friendliness, featuring four core functional zones: the sleeping area, living room, kitchen, and bathroom. In the sleeping area, a temperature regulation system was included to enhance sleep quality. In the bathroom, an optimized ventilation layout, dry-wet separation, and a non-slip textured floor were arranged to address both functional and safety needs. In the seating area, a skylight was placed to allow natural lighting and a rotatable table was configured to accommodate daily activities.

Third, for spatial planning, a modular layout and concealed storages can maximize the use of limited space. The passageway width was therefore laid out in compliance with China’s age-friendly standards (≥ 80 cm) to minimize obstacles, complemented by curved furniture edges to reduce the risk of injury.

Apart from the above schemes, smart systems were integrated throughout the vehicle, including voice control, environmental monitoring and warning systems, and emergency call functions. One-touch alarm buttons and access to medical databases were planned in both the bathroom and living room, enabling quick symptom checks and remote consultations. Storage areas were organized according to the habits of older users, with a dedicated medicine freezer to support chronic disease management.

Accordingly, we developed three alternative interior layout schemes, as illustrated in Figs. 7–9.

Fig. 7

Sketch plan 1

Fig. 8

Sketch plan 2

Fig. 9

Sketch plan 3

To assess user satisfaction with the three design solutions, we used questionnaires to solicit opinions from 10 elderly users, 5 professors of industrial design, and 5 users with RV driving experience. Preferences were measured using a five-point Likert scale: 1 – very dissatisfied. 2 – dissatisfied, 3 – unsure, 4 – satisfied, 5 – very satisfied. The results are shown in Table 9.

Table 9
Satisfaction with the three age-friendly RV design solutions
Solution	Very satisfied	Satisfied	Unsure	Dissatisfied	Very dissatisfied	Mean
1	3(15%)	4(20%)	8(40%)	1(5%)	4(20%)	3.05
2	0(0%)	10(50%)	6(30%)	3(15%)	1(5%)	3.25
3	10(50%)	5(25%)	2(10%)	2(10%)	1(5%)	4.05

Among the three design solutions, solution 3 received the highest satisfaction rating (M = 4.05), with 75% of users selecting “satisfied” or “very satisfied”. In contrast, solution 1 had the lowest average score (M = 3.05) and the highest proportion of “unsure” (40%) and “very dissatisfied” (20%) responses, indicating weaker user acceptance. Solution 2 ranked in between, with generally moderate evaluations.

4.1.3 Rendering

4.1.3.1 Exterior rendering

Based on the user evaluation results, solution 3 was identified as the most satisfactory option, receiving the highest preference score among all three proposals. Building upon this solution, we made further refinements through a systematic analysis of spatial layout, facility configuration, and styling proportions. The finalized exterior rendering is presented in Fig. 10. Following that, we modeled the design scheme in 3D and then used KeyShot to apply to the model the materials, lighting, and scene rendering (Fig. 11).

Fig. 10

The rendering of the optimized design

Fig. 11

The rendering of the final solution

4.1.3.2 Interior design

Dimensional data are illustrated in Fig. 12. The RV has an interior length of 455 cm, a width of 208 cm, and a height of 200 cm. The bathroom measures 152 cm in length and 93 cm in width, while the kitchen measures 152 cm in length and 115 cm in width. The lounge area measures 172 cm in length and 208 cm in width, and the bed measures 208 cm in length and 131 cm in width.

Fig. 12

Size data

Figure 13 further illustrates the layout and functions, with Fig. 13a showing the interior layout plan, and the others providing details of each zone.

Fig. 13

Functional zoning

An independent kitchen (Fig. 13b) was planned to isolate cooking fumes, with a side window for effective ventilation. Within the kichen, tiered storage compartments above and base cabinets below were arranged to ensure both accessibility and spatial organization. Notably, in the cabinets, motion-sensing LED strips were added, providing automatic lighting in low-light environments to enhance cooking safety and efficiency. Moreover, a built-in oven was planned at mid-height for better visibility during baking, and space was reserved below for the installation of a washing machine.

For the bathroom (Fig. 13c), we adopted a dry-wet separation layout, using a waterproof divider to physically separate the shower and toilet zones. Notably, for the bathroom flooring, anti-slip mats were planned, to prevent elderly users from slipping. Overhead, a bidirectional ventilation fan was designed to work in tandem with a concealed fresh air system, ensuring continuous air circulation and quick moisture removal. For added safety, a waterproof SOS emergency button was to be installed on the shower wall, which, when triggered, would activate the onboard alarm system and simultaneously send location data to a monitoring terminal. Overall, the structure aimed to strike a multidimensional balance among safety, hygiene, and comfort within a limited space.

On the right side of the lounge (Fig. 13d), a dedicated medical compartment was allocated within a side cabinet for organizing chronic illness medication and first-aid tools. In addition, a wall-mounted smart control panel, supporting both touch and voice interaction, was designed to centrally manage air conditioning, lighting, and entertainment devices. Notably, the air conditioning system was planned to include a draft-free mode to avoid headaches in elderly users. Additionally, a hidden trash bin was incorporated into the door design to save space.

The left side of the lounge area (Fig. 13e) was intended to feature a rotatable, foldable table that can be raised, lowered and extended to serve as a temporary bed. Also, a layered side cabinet was reserved to house a compact refrigerator, while panoramic sliding windows were planned on the adjacent wall, combining UV-resistant glass with built-in blackout curtains. Importantly, an emergency call button was to be placed behind the sofa, designed to trigger an audiovisual alarm and send location information to the monitoring terminal.

Overall, through spatial integration and multiple/redundant interactive mechanisms, our interior layout design supports a highly efficient and safe multi-dimensional living experience.

4.2 Designing the software interface for the age-friendly RV

Based on the key design points identified earlier, we outlined the corresponding functions, focusing primarily on RV features to establish the information architecture of the RoamEase app (Fig. 14).

Fig. 14

Information architecture of “RoamEase"

We began by developing low-fidelity prototypes, based on which we refined the details, replaced placeholder images with context-appropriate graphics, and adjusted some page layouts to create fully fleshed‑out mockups. As for color matching, a calming blue palette—chosen to instill a sense of security—was accented with touches of orange to inject vitality. Throughout, we planned the interface to stay clean and uncluttered, ensuring that older users could quickly locate the buttons and features they need without being distracted by overly complex visuals. Several higher‑fidelity prototypes of the mobile version are shown in Fig. 15.

Fig. 15

Examples of high-fidelity prototypes

Specifically, in the “Home” page, users can browse and post information, fostering interaction among RVbased retirees and travel enthusiasts. An emergency-assistance feature was to be included in this interface, allowing one-tap calling of ambulance services, location-based search for nearby medical facilities, and direct contact with roadside rescue while prominently displaying the user’s profile and current GPS coordinates to expedite help in critical situations.

With the “Smart RV” page, users can monitor and control vehicle systems. For example, in the “Vehicle status” module, users can check fuel, fresh water, and wastewater levels, as well as operate the smart lock remotely to grant temporary access. In the air conditioning system, users could view the cabin temperature and choose between rapid-heat or rapid-cool modes; a combined temperature-control feature even allows temperature-sensitive users to set separate temperatures for the cockpit and living area.

In the “Other Devices” module, users can add and manage other smart appliances—such as security cameras, the washing machine, or smart outlets—directly from the app. The “Where’s My RV” feature helps users to prevent lost-vehicle incidents by showing the RV’s position. The “Itinerary” page presents systemrecommended attractions with filtering options, and once a destination is selected, the app generates both driving directions and a tailored travel plan. The “Preferred Campgrounds” search function provides information on nearby rest and service areas, making it easy to plan stops for vehicle maintenance or supplies. Finally, in the “My Profile” page, users can edit their personal information and access additional app services.

In addition to the mobile app, we also designed a multimodal interactive control terminal (touch + voice), which integrates core system monitoring and equipment management functions. It displays real-time data on fuel, fresh water, and wastewater levels, and supports multi-mode air conditioning control, including automatic activation or shutdown based on preset temperature thresholds.

Users can activate a voice assistant to issue commands verbally. The system can also load high-precision offline maps, marking elderly-friendly service facilities such as medical stations and accessible restrooms, as shown in Fig. 16.

Fig. 16

A selected display of the interior interactive interface

5. Discussions and conclusion

The pressing reality of China’s “growing old before getting rich” has been driving the country towards more diversified elderly care models, one of which is RV-based retirement. There is, however, scarce research on whole-vehicle design of age-friendly RVs. This study addresses this supply–demand mismatch by developing an integrated Kano–AHP–QFD analytical framework to systematically optimize the entire process from user needs identification to product function transformation.

Specifically, through in-depth interviews combined with Kano model analysis, we systematically identified, for the first time, 34 core needs across five dimensions of age-friendly RV design, revealing that neglecting eight must-be (M) requirements would sharply reduce user satisfaction, whereas fulfilling nine attractive (O) requirements would greatly enhance it. Building on this, we employed the AHP to quantify and prioritize key needs, establishing a clear hierarchy: comfortable sleep > vehicle operation > bathroom ventilation. Subsequently, by applying QFD and the House of Quality, we translated these user needs into technical priorities. This resulted in a ranked list of ten key technical characteristics, with living comfort > age-friendly design > vehicle safety assurance at the top. Overall, our design process formed a chain-like transformation mechanism of needs stratification – priority quantification – function mapping.

Guided by this methodological framework, we proposed an innovative RV design solution focusing on barrier-free spatial accessibility, intelligent driver assistance, and integrated medical support. Key features, such as passageways at least 80 cm wide for wheelchair access and a dry–wet separated bathroom with anti-slip flooring, would enhance safety and ensure the quality of travel-based retirement living. These features are meaningful to promoting travel-based elderly care, as safety is a major concern for older people on travel, long-distance travel in particular. They also provide implications for the limited studies on elderly-focused RV campsite optimization, for example, to mandate age-friendly facilities and maximize attractiveness, based on KANO-modeled “must-be” needs such as barrier-free access (e.g., corridors at least 80⁵⁵/90/91.5

cm wide according to China’s, UN’s and USA’s guidelines).

In addition, a dual-module healthcare system that links bedside SOS buttons with real-time health monitoring (Abdulmalek et al., 2022) not only meets older adults’ practical healthcare needs but also provides them with psychological reassurance, addressing both daily care and emergency concerns. Moreover, the ADAS, complemented by the “RoamEase” RV mobile app and onboard interaction system, extends intelligent control and safety assurance functions, thus addressing ADAS acceptance through intuitive and senior-friendly user interfaces⁴⁹ and enriching the overall travel experience for older adults.

Overall, unlike most existing RV research, which primarily employs methods like AHP²⁵, FAHP-FBS integration²⁶, and affordance theory²⁴ to design partial components such as interior layout²³ and styling²⁵, our closed-loop Kano-AHP-QFD approach hierarchically classifies elderly needs (Kano), quantifies priorities (AHP), and maps to holistic design features (QFD). Notably, our research extends Liu et al.’s⁴² Kano–AHP–QFD-based scope from single-interface optimization to a holistic living-mobile ecosystem integrating exterior styling, interior layout, and interactive systems, thus contributing to the “healthcare-on-wheels” lifestyle. Additionally, our research may provide insights for 1) elderly-oriented retrofit or renovation of RVs (e.g. non-slip PVC flooring; curved protective covers for furniture corners and door handles; large touch-screen control panel replacing traditional knobs) and 2) a cross-sector collaboration platform linking automotive enterprises, healthcare, and cultural tourism, to ensure a carefree travel-based retirement lifestyle.

Despite its merits, this research has several limitations. First, a key limitation is the small sample size (15 elderly participants) due to the proximity-based recruitment. Though pragmatic, this sampled group may introduce geographical clustering bias, as participants were locally concentrated despite diverse origins. Future research could expand sampling across multiple regions and integrate mixed-methods (e.g., cross-regional surveys) to enhance the generalizability of age-friendly RV user needs. Second, the current health support module remains basic, lacking integration with advanced AI and embodied intelligence for proactive health management. Future research may integrate “large models + embodied intelligence” to develop AI health management assistants and introduce unobtrusive monitoring technologies to enable dynamically adaptive, proactive iterations.

Author Contribution

Conceptualization, Y.J. and X.Y.; methodology, Y.C.; software, X.Y.; validation, Y.J.,S.Y., X.Y. and Y.C.; formal analysis, X.Y.; investigation, X.Y.; resources, Y.C., S.Y.; data curation, X.Y.; writing—original draft preparation, S.Y., Y.J. and X.Y.; writing—review and editing, S.Y. and Y.C.; visualization, S.Y.; supervision, Y.C.; project administration, Y.C.; funding acquisition, Y.C. All authors have read and agreed to the published version of the manuscript.

Funding:

This research was funded by the 2023 Social Science Planning Program of Fujian Province (Grant No. FJ2023C061), the 2022 Philosophy and Social Science Research Program of Fujian Education System (Grant No. JAS22238), and the 2023 Fujian Province Education Science “14th Five-Year Plan” Project (Grant No. FJJKBK23-036).

Data Availability

Questionnaire data are within the manuscript; video and audio data that support the findings of this study are available on request from the corresponding author [Y.C.]; these data are not publicly available due to their containing information that could compromise the privacy of research participants.

Institutional Review Statement: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of Xiamen University Tan Kah Kee College (No.: PRD20241105)

Conflicts of Interest:

The authors declare no conflicts of interest.

Informed Consent

Statement: Written informed consent was obtained from all subjects involved in the study.

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