Abstract
Purpose Service robots (SRs) increasingly perform service roles in transformative services, yet these roles remain insufficiently clarified in the literature. This study aims to develop a conceptual typology of SR roles designed to mitigate customer vulnerability and enhance well-being, thereby contributing to a positive social impact. Design/methodology/approach This study builds upon a systematic literature review and analyzes 189 empirical studies using a three-phase process to develop a typology of SR roles in transformative services. Findings The study develops a typology of SR roles in transformative services based on four dimensions (anthropomorphism, interaction orientation, service beneficiary and well-being outcome) and illustrates it with examples. The typology highlights pathways through which SRs create social impact: reducing emotional and social vulnerabilities, supporting functional autonomy and capability development and enhancing collective well-being and inclusion. Practical implications The typology provides service managers and SR designers with a framework to understand different types of SR roles in transformative services, guiding them in the design and deployment of diverse SR applications that generate social impact. Originality/value This study contributes by linking Transformative Service Research with social impact in business research. It also proposes a novel typology of SR roles, clarifying how different configurations of SR characteristics, service orientation and service beneficiaries are associated with distinct types of transformative and social impact outcomes. It also outlines a research agenda to guide and stimulate future studies.

Abstract
Since the publication of the 2020 paper, Finding the Gaps About Uses of Immersive Learning Environments: A Survey of Surveys, the landscape of immersive learning environments (ILEs) has continued to evolve rapidly. This update aims to revisit the gaps identified in that previous research and explore emerging trends. We conducted an extensive review of new surveys published after that paper's cut date. Our findings reveal a significant amount of new published reviews (n = 64), more than doubling the original corpus (n = 47). The results highlighted novel themes of usage of immersive environments, helping bridge some 2020 research gaps. This paper discusses those developments and presents a consolidated perspective on the uses of immersive learning environments.

Abstract
Current residential electricity tariffs often combine a flat energy price with a fixed charge linked to contracted power, resulting in electricity bills that are weakly responsive to changes in consumption. This lack of proportionality reduces incentives for energy savings and may undermine demand-side efficiency.This paper proposes a novel Power-Conditioned Pricing (PCP) tariff, in which unit energy prices depend on the power level at which electricity is consumed. By associating higher prices with higher consumption intensity, the proposed tariff introduces progressivity while preserving transparency and regulatory feasibility. The tariff is calibrated to ensure revenue neutrality with respect to the current tariff for each contracted power level.Two complementary calibration strategies are analysed: a profile-based approach using representative regulatory load profiles, and an empirical approach based on statistical distributions derived from real consumer data. To assess consumer responsiveness, electricity bills are evaluated under both vertical and horizontal consumption adjustment models.Results show that bill elasticity increases from values between 0.43–0.73 under the current tariff to values close to unity under PCP, while maintaining revenue neutrality across contracted power levels. These findings suggest that power-conditioned pricing constitutes a promising alternative to current residential tariff structures, better aligned with energy-efficiency and conservation objectives.

Abstract
Matrix manufacturing requires close coordination between collaborative workcells, mobile robots, and battery management resources to support the execution of heterogeneous human-robot operations in reconfigurable production environments. This paper presents a cyber-physical robotic coordination framework for human-robot teams deployed in an industrial matrix manufacturing system, integrating a collaborative workstation, a fleet of mobile programmable cobots, and an automatic battery changer through ROS/OPC UA communication. The framework coordinates task execution, intra-logistics, and energy management through a decision layer that assigns operations to human and robotic agents, relocates idle mobile robots, and triggers battery swaps. Three coordination modules-a Battery Management Module, a Task Allocation Module, and a Robot Relocation Module-implement this pipeline by computing feasible execution plans at each scheduling cycle, accounting for human and robot capabilities, workstation availability, transport times, and battery state. The approach is validated on a deployed industrial matrix manufacturing platform through a disassembly task comprising human-only, robot-only, and human-robot collaborative operations, demonstrating the feasibility of coordinating heterogeneous robotic and human resources in a physical reconfigurable manufacturing environment.

Abstract
Purpose Social service robots (SSRs) are expected to become increasingly common and may present a potential solution in healthcare services, particularly in the care of older adults. This study aims to assess the influence of functional, socioemotional and relational factors on older adults' intention to use SSRs in their homes.Design/methodology/approach This paper follows a sequential research design. In Study1, data were collected using questionnaires completed by older adults. We analyzed the data using PLS-SEM to identify factors influencing the intention to use SSRs. In Study 2, focus group discussions were conducted to discuss quantitative results and gather the opinions of older adults regarding SSRs.Findings The findings reveal that SSR acceptance in aged care is not linear or straightforward but is rather shaped by underlying tensions. Although older adults recognize the functional and emotional value of SSRs, their acceptance is structured by paradoxical tensions related to orientation, authenticity and privacy.Practical implications This paper provides valuable insights for service managers and developers to understand the factors that influence the intention to use SSRs among older adults.Originality/value First, this study demonstrated the validity of sRAM in the context of aged care. Second, it clarifies the SSR's functional and emotional value in the intention to use SSR in aged care. Finally, it also provides a nuanced view of this acceptance by revealing underlying paradoxical tensions.

Abstract
The staggered model is a recent, very general variant of discrete-time quantum walks which, avoiding the use of a coin to direct the walker evolution, explores the underlying graph structure to build an evolution operator based on local unitaries induced by adjacent vertices. Optimising their implementation to increase resilience to decoherence phenomena motivates their analysis with the ZX-calculus. The whole optimisation can be seen as a graph reconfiguration process along which the original circuit is rewrote, significantly reducing the number of (expensive) gates used. The exercise identified an underlying pattern leading to an alternative, potentially more efficient evolution operator.