Exploring the role of interaction in older-adult service innovation: insights from the testing stage

The global aging trend necessitates service innovation targeting older adults. While design and implementation are common focuses, the critical role of the testing phase remains largely overlooked in existing literature. This is particularly important when considering the diverse needs and interaction dynamics of older adults with technology teams. This study aims to bridge this gap by introducing a comprehensive framework specifically designed for the testing stage of service innovations tailored to older adults. The framework is validated through a four-year empirical research project with a leading Beijing-based service provider for older adults. The study emphasizes that the concept of "older adults" transcends chronological age, encompassing diverse health conditions, socio-economic factors, and technological proficiency levels. A nuanced understanding of this diversity is paramount to developing truly effective and inclusive service innovations. The current research identifies a critical need to move beyond simple technology acceptance models and consider a more holistic approach that encompasses user experience, comfort levels, long-term sustainability, and cultural contexts within the service innovation process. The research specifically focuses on the testing phase, examining how effective interaction and feedback mechanisms can contribute to better alignment with the diverse needs and preferences of older adults. The goal is to provide a framework that redefines the approach to service innovation for older adults, considering the unique challenges and opportunities presented by public service platforms and digital co-design environments. The research anticipates that focusing on the interaction and feedback loop during testing will be instrumental in creating sustainable and impactful service solutions for this growing population.

The literature review examines existing research on value co-creation in service innovation, specifically focusing on the participation of older adults. It explores how the characteristics of older adults, such as their diverse needs, technological proficiency, and preference for authentic engagements, influence service innovation processes. The review highlights the importance of managerial mechanisms, such as the competency of frontline employees and the establishment of emotional bonds with older adults, in orchestrating effective value co-creation. It also discusses the characteristics of service innovation projects for older adults, including the use of public service platforms and user-focused technologies, emphasizing the shift from transaction-based models to relational collaborations. The literature review analyzes the critical role of the testing stage in service innovation, specifically addressing its often-underestimated importance in ensuring the viability and value of service concepts. The review distinguishes the testing phase as a ‘gatekeeper,’ ensuring that only the most promising ideas proceed to the next stage of development. It also examines how the testing stage needs to be adapted to accommodate the unique characteristics of older adults, integrating feedback mechanisms and considering their diverse needs and expectations in the design and evaluation process. Finally, it identifies a need to examine the multifaceted attributes of the testing stage, encompassing aspects beyond technical trials, including lifestyles, cultural backgrounds, and social networks. Several frameworks and methodologies, including video prototyping for service innovation testing, are discussed to provide a comprehensive understanding of the criticality and complexities of the testing phase for service innovations targeting older adults.

This study employs a qualitative case study approach using theoretical sampling to select representative cases for in-depth analysis. Two teams (L-Team and HC-Team) from a prominent Beijing research institution are selected as case studies, based on their four-year involvement in service innovation projects for older adults. Data collection involves semi-structured interviews with team leaders and frontline staff, supplemented by observations and document review. Triangulation methods are used to ensure data accuracy. The editing analysis method is applied to the textual data to identify meaningful patterns and relationships. The analysis focuses on the characteristics of service innovation for older adults, including team composition, capabilities, technology integration, value co-creation, and customer interaction. The study further investigates the dynamic process of the testing stage, encompassing preliminary, mid-term, and post-testing sub-stages. The impact of various factors on testing performance is systematically examined. The researchers applied the evaluative criteria for case study research proposed by Golden-Biddle and Locke (1993) – Authenticity, Plausibility, and Criticality – to assess the rigor and reliability of their findings. The primary data sources were field observation and interviews, complemented by secondary data from market reports and commercial documents to ensure data triangulation and mitigate potential deficiencies. The researchers employed the editing analysis method, which involved meticulously engaging with textual data through cutting, organizing, and reorganizing, to reveal meaningful categories, relationships, and patterns. This method aimed at uncovering significant findings relevant to the research objectives. The study employed multiple data-collection methods including field observation, interviews, and archival data to provide a comprehensive and nuanced understanding of the research topic. Data were analyzed using the editing analysis method to identify key themes and relationships among the variables. This involved a meticulous process of cutting, organizing, and reorganizing the data to extract significant patterns and insights.

The study's key findings highlight several crucial aspects of service innovation testing for older adults. First, it demonstrates how different characteristics of older adults (health status, technological literacy, social engagement) necessitate tailored service innovation approaches across the testing phases (preliminary, mid-term, post-testing). This is exemplified by the comparison of L-Team (community-based services for relatively healthy older adults) and HC-Team (home-based services for older adults with significant disabilities). The findings reveal that L-Team's success relied heavily on face-to-face interactions and community engagement, while HC-Team emphasized targeted communication and personalized care plans. Second, the research identifies how technology's role in service delivery varies across testing phases. In the preliminary stage, market research and community services played a crucial role. In the mid-term and post-testing stages, mobile applications, social media, and community promotion strategies were pivotal for feedback collection and service refinement. Third, team composition and skills significantly impacted the effectiveness of service innovation testing. L-Team, initially technology-focused, transitioned to include frontline staff with strong service expertise and enthusiasm. HC-Team evolved into a medically focused team emphasizing personalized care management. These adaptations enabled both teams to address the specific needs of their target user groups more effectively. Fourth, the importance of experiential learning in service innovation testing is highlighted. Both teams utilized trial-and-error mechanisms, adjusting services based on feedback from older adults and refining service processes through continuous learning. L-Team used a 'learning by doing' approach with expert review and satisfaction surveys. HC-Team focused on service quality and provider monitoring, switching providers if feedback was negative. This demonstrated the importance of incorporating feedback mechanisms to adapt to the dynamic needs of the older adult population and enhance service sustainability. The findings are presented in detail in Tables 1, 2, 3, 4, 5, 6, and 7, which provide a comprehensive overview of the interactions, processes, and outcomes associated with the case studies of L-Team and HC-Team. These tables show how different approaches to managing service innovation, the utilization of technology, and the engagement with older adult customers contribute to the success of service innovation testing in the context of an aging population.

The findings reveal that the testing phase is not merely a technical assessment but a crucial stage for co-creating value with older adults, considering their varied needs and preferences. Effective interaction strategies, tailoring communication methods to specific characteristics of the older adult population, and leveraging appropriate technology are all highlighted as essential elements. The study expands upon existing service innovation models by explicitly incorporating the critical role of the testing phase and demonstrating how different strategies can be implemented to enhance service design and sustainability. The successful implementation of service innovations requires a deep understanding of older adults' unique needs, incorporating their feedback at every stage, and adopting a user-centric approach. The study's findings have implications for service providers, policymakers, and researchers working in the field of aging and service innovation, offering a framework to guide the development of more effective and sustainable services for older adults. The discussion further emphasizes the necessity of continuous learning and adaptation, aligning with established literature on organizational learning and service innovation, while acknowledging the need for future research to explore the long-term effects of the proposed framework and the impact of different organizational cultures and leadership styles on service innovation initiatives.

This study provides a novel framework for the testing phase in service innovation specifically tailored for older adults, highlighting the critical role of interaction and feedback mechanisms. The findings underscore the necessity of considering the diverse needs and preferences of older adults throughout the entire service innovation process. Future research should explore the framework's generalizability across various contexts and service types, quantitatively assess the long-term impact of the framework, investigate the influence of organizational culture and leadership, and expand the scope to include more diverse groups of older adults.

The study's limitations include the focus on specific industries and regions in China, limiting the generalizability of the findings to other contexts. The qualitative nature of the study restricts the use of quantitative data, potentially affecting the representativeness of the results. Future research could address these limitations by incorporating quantitative methods and conducting comparative studies across various geographical locations and service sectors. Additionally, the limited exploration of organizational culture and leadership dynamics warrants further investigation in future research.