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Value is generated through the whole service innovation process in a complex collaborative networked ecosystem. This study aims to enhance understanding of value generation in digital service innovation process with an emphasis on information technology by developing an extended value generation process framework and evaluating on how it is applicable in a real-life networked retail service innovation context. The findings of the study suggest that multiple information technology (IT), process and business related factors affect value creation during the digital service innovation process. The role of information technology is multifaceted, providing both new opportunities and challenges in the service innovation context. The extended framework for exploring the service innovation process provides a more structured way to examine the complex, networked, service innovation ecosystems.

Occupational safety and health is traditionally a challenging area in the labor-intensive construction industry as accidents at work and non-ergonomic work conditions lead to absences and premature retirement of construction workers. Recently, the rise of the Internet of Things (IoT) and its accompanying technologies (e.g. wearable technologies) has enhanced interest in the occupational safety and health of construction work. The level of technology acceptance among construction workers is a crucial element in the adoption of these technologies. The main objectives of this study are to enhance understanding about construction workers’ attitudes towards IoT-based data-intensive work safety and wellbeing solutions and to identify factors that can promote technology adoption. Data for the study was collected through an online survey of 4385 construction workers. Based on the survey data it seems that construction workers would accept the sharing and utilizing data collected from them in the worksite environment if it could help identify employee personal health risks or promote personal and colleagues' occupational safety. Respondents were most concerned about privacy and security regarding wearables in the workplace. It can be concluded that user acceptance and trust building are key components in the adoption of IoT-based occupational safety and health solutions. Future studies should investigate methods for actively involving construction workers in the design and development process of IoT-based work safety solutions and examine technological solutions that promote trust building among construction workers.

Sustainable work aims at improving working conditions to allow workers to effectively extend their working life. In this context, occupational safety and well-being are major concerns, especially in labor-intensive fields, such as construction-related work. Internet of Things and wearable sensors provide for unobtrusive technology that could enhance safety using human activity recognition techniques, and has the potential of improving work conditions and health. However, the research community lacks commonly used standard datasets that provide for realistic and variating activities from multiple users. In this article, our contributions are threefold. First, we present VTT-ConIoT, a new publicly available dataset for the evaluation of HAR from inertial sensors in professional construction settings. The dataset, which contains data from 13 users and 16 different activities, is collected from three different wearable sensor locations.Second, we provide a benchmark baseline for human activity recognition that shows a classification accuracy of up to 89% for a six class setup and up to 78% for a sixteen class more granular one. Finally, we show an analysis of the representativity and usefulness of the dataset by comparing it with data collected in a pilot study made in a real construction environment with real workers.

Data is becoming a more and more important resource for future innovations. Companies are currently considering how to leverage personal data in preventive healthcare and in other sectors. However, there are many challenges hindering the development of data-driven businesses in extant business networks. The purpose of this paper is to explore the success factors of data-driven service delivery networks in the context of preventive healthcare. The results are examples of the benefits and challenges of data availability and usage, based on a qualitative case study, in which a network of actors is integrating resources to solve the needs of their end customers. The results underline the success factors for service delivery networks, creating a baseline for human-centric, personalized and preventive healthcare solutions. The study enriches the theoretical perspective of data, services and service delivery networks by continuing discussion on how big data resources become cooperative assets not only in a firm but also on the network level. This study has multiple implications for practitioners trying to navigate the turbulent waters of the changing business environment and evolving service delivery network of preventive healthcare. Especially small and medium size of firms could use the identified success factors when planning new data-driven services in their networks. Our analysis brings new perspective between a firm and the actors in its network, particularly in the preventive healthcare sector wherein data needs to be shared between actors via consent of the individuals.

This paper reports the results of a field experiment where home-dwelling elderly people used a mobile technology-based service to interact with a home care service to order meals to be delivered to their homes. The primary research focus was on examining the suitability of touch-based interaction in the everyday life activities of elderly users. The eight-week experiment took place in the autumn of 2006. The findings are based primarily on user experience and on the socioeconomic analysis done from the data collected before, during, and after the experiment. The results show that touch-based interaction was easy to learn and adopt, and that the users were able to successfully use it regardless of their physical or cognitive weaknesses. However, the socioeconomic value of the service was questionable. The paper also summarises methodological issues and findings related to user experience evaluation in an experimental setting.

The healthcare and wellness sector currently attempts to provide more proactive service models with data-driven solutions. This study examines the expectations and values related to personal data i.e. data valences from the perspective of service providers and individual users. The study is based on the analysis of extensive empirical material collected through interviews and a collaborative workshop. The data was collected in one cultural context, Finland. The results suggest that the potential service providers and users have similar expectations regarding self-evidence of data while the main differences concern the expectations of transparency. The results of the study propose some basic requirements for the development of personalised data-driven services in future. The study suggests that basic requirements for the development of future data driven services concern expectations to usable data visualisations, data as a motivator, data accuracy and data transparency. Even though there are varying expectations to personal health data and even some concerns, it can be seen that here different ecosystem actors primarily perceived the wider use of personal health and wellness data as a positive trend. It can be concluded that collaborative personal data-driven service ecosystems are an integral part of development towards proactive service models in healthcare.

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