Indirect User Research Articles

Owning and Sharing

Intelligent personal assistants (IPA), such as Amazon Alexa and Google Assistant, are becoming increasingly present in multi-user households leading to questions about privacy and consent, particularly for those who do not directly own the device they interact with. When these devices are placed in shared spaces, every visitor and cohabitant becomes an indirect user, potentially leading to discomfort, misuse of services, or unintentional sharing of personal data. To better understand how owners and visitors perceive IPAs, we interviewed 10 in-house users (account owners and cohabitants) and 9 visitors from a student and young professionals sample who have interacted with such devices on various occasions. We find that cohabitants in shared households with regular IPA interactions see themselves as owners of the device, although not having the same controls as the account owner. Further, we determine the existence of a smart speaker etiquette which doubles as trust-based boundary management. Both in-house users and visitors demonstrate similar attitudes and concerns around data use, constant monitoring by the device, and the lack of transparency around device operations. We discuss interviewees' system understanding, concerns, and protection strategies and make recommendation to avoid tensions around shared devices.

Digital experience design of qinhuai lantern based on user journey map

This research extends the design concepts and research methods of user journey maps to the field of intangible cultural heritage, and selects the typical lotus lantern material package in Qinhuai lanterns as an example to explore the digital experience design of lanterns. On-site research methods are used to understand users, define target users and build personas. AEIOU recording framework is used to record user behavior, analyze and reorganize user behavior with card classification, and summarize user behavior flow. The Likert Smiley Scale is used to ask children to evaluate specific behaviors, get emotional curves, and summarize design opportunities from the perspective of valley filling. Given the pain points in the experience of the target user children and the indirect user parents, the lotus lantern material package is digitally redesigned from four perspectives of materials, connection methods between materials, functions and storage to meet the users' emotional experience. This research method and process have certain reference significance for experience design research on the same type of intangible cultural heritages.

Combining Direct and Indirect User Data for Calculating Social Impact Indicators of Products in Developing Countries

Abstract Evaluating the social impacts of engineered products is critical to ensuring that products are having their intended positive impacts and learning how to improve product designs for a more positive social impact. Quantitative evaluation of product social impacts is made possible through the use of social impact indicators, which combine the user data in a meaningful way to give insight into the current social condition of an individual or population. Most existing methods for collecting these user data for social impact indicators require direct human interaction with users of a product (e.g., interviews, surveys, and observational studies). These interactions produce high-fidelity data that help indicate the product impact but only at a single snapshot in time and are typically infrequently collected due to the large human resources and cost associated with obtaining them. In this article, a framework is proposed that outlines how low-fidelity data often obtainable using remote sensors, satellites, or digital technology can be collected and correlated with high-fidelity, infrequently collected data to enable continuous, remote monitoring of engineered products via the user data. These user data are critical to determining current social impact indicators that can be used in a posteriori social impact evaluation. We illustrate an application of this framework by demonstrating how it can be used to collect data for calculating several social impact indicators related to water hand pumps in Uganda. Key to this example is the use of a deep learning model to correlate user type (man, woman, or child statured) with the raw hand pump data obtained via an integrated motion unit sensor for 1200 hand pump users.

Impact of indirect user participation on public transport financing

The regional public transport performs with around 11 billion passengers a part of approx-imately 16.3 % of all passenger transports in Germany. It is financed from tariff revenues (user financing) and, for the most part, through public subsidies. The costs for the regional public transport are only covered by 50 % by direct users. Further 50 % are covered by public funds. The demographic development in Germany and with it declining passenger numbers, legal changes at European and national level as well as the over-indebtedness of public authorities result in a significant change of the framework conditions for the regional public transport. The aim of the paper was to draw up reform proposals for public transport in Germany so that it could continue to meet the four main objectives set. The results of those proposals for reform are transferred to a defined project area enabling to measure specifically the monetary impact. By forecasting the results of the project across the country, we want to verify whether the four main public transport objectives can be achieved using possible additional financial instruments involving indirect users, even under changing conditions, provided the proposed reforms are applied.

FDCO: attribute-based fast data cloud-outsourcing scheme for mobile devices

We propose an attribute-based fast data cloud-outsourcing (FDCO) scheme, which shows great performance in mobile devices. Technically, this work is a CCA-secure online/offline key encapsulation scheme based on ciphertext-policy attribute-based encryption with public validity test and indirect user revocation mechanism. We adapt it to a mobile cloud-outsourcing scenario and present a concrete system. Our scheme is equipped with the following desirable properties: First, encapsulation needs only several lightweight online modular addition/multiplication operations, which is appealing to mobile users. Second, it is equipped with an efficient indirect user revocation mechanism to support access credential revocation. Third, it supports public encapsulation validity test, which enables auditors to filter invalid data, so as to prevent attackers from sending invalid data to stuff users’ accounts. Finally, we prove its security against chosen-ciphertext attacks (CCA) in the standard model. We conduct theoretical analyses and extensive experiments to show that our scheme is practical and efficient in application.

Social-aware mobile data offloading algorithm through small cell backhaul network: Direct and indirect user influence perspectives

Mobile data offloading is a promising solution to mitigate the explosive increasing traffic load in a mobile network operator (MNO)’s core network, where the MNO can deliver the mobile traffic without traversing the core network. Most of all, the social networking traffic has increased sharply due to the proliferation of online social networking services (SNSs), such as Facebook and Instagram. Thus, an effective mobile data offloading algorithm that considers the social context needs to be developed. In this paper, exploiting the social context from two perspectives, we propose the model to estimate the application selection probability considering a direct influence by each user and indirect influence by other users. Based on this, we propose the mobile data offloading algorithm considering the social context via small cell backhaul network, in order to maximize the quality of service (QoS) of a user and reduce the core network load of an MNO to the maximum. The results of the performance evaluation show that the proposed algorithm considering the social context can enhance the QoS of users and alleviate the core network load better than the other algorithm that does not exploit the social context.

User interaction-oriented community detection based on cascading analysis

Detecting user communities in online social networks (OSNs) is of great importance for understanding social dynamics. Compared to user connections, user interactions have been shown to be more meaningful for reflecting peer relationship in OSNs. To this end, we propose a user interaction-oriented community detection method based on cascading analysis. Specifically, user interactions are analyzed from a large collection of social object sharings (e.g., blog posts, photo shares). Both direct and indirect user interactions associated with each social object sharing are then extracted and the cascading relations among these interactions are captured using a graph representation. The proposed method makes use of such cascading relations to extract groups of actively interacting users and adopts a super graph approach to cluster these user groups for detecting communities. An extensive evaluation of our method was performed using three real OSN datasets and compared with three state-of-the-art overlapping community detection methods, namely two general methods applied to the interaction graph and an interaction-based method. Our method outperformed the compared methods, as demonstrated by several evaluation metrics, and produced more robust and stable detection results across different datasets.

Implantação do módulo de Gestão da Configuração do framework ITIL: um estudo de caso

Este trabalho se baseia no funcionamento de um dos modelos de gestão de serviços de TI mais utilizados pelas organizações de todo o mundo, o ITIL. Com o objetivo de expandir o conhecimento na área, a principal proposta deste artigo é expor experiências, pontos de vistas, críticas e valor agregado gerados durante e após a implantação do módulo de Gestão da Configuração da ITIL em um órgão público brasileiro. Por ser um caso de sucesso, o principal objetivo é mensurar o nível de satisfação do usuário direto e indireto do módulo em questão, explorando os principais benefícios de uma implantação baseada nas melhores práticas do campo, além de propor melhorias e sugestões aos processos de implantação futuros.

Using the Medical Research Council framework for development and evaluation of complex interventions in a low resource setting to develop a theory-based treatment support intervention delivered via SMS text message to improve blood pressure control

BackgroundSeveral frameworks now exist to guide intervention development but there remains only limited evidence of their application to health interventions based around use of mobile phones or devices, particularly in a low-resource setting. We aimed to describe our experience of using the Medical Research Council (MRC) Framework on complex interventions to develop and evaluate an adherence support intervention for high blood pressure delivered by SMS text message. We further aimed to describe the developed intervention in line with reporting guidelines for a structured and systematic description.MethodsWe used a non-sequential and flexible approach guided by the 2008 MRC Framework for the development and evaluation of complex interventions.ResultsWe reviewed published literature and established a multi-disciplinary expert group to guide the development process. We selected health psychology theory and behaviour change techniques that have been shown to be important in adherence and persistence with chronic medications. Semi-structured interviews and focus groups with various stakeholders identified ways in which treatment adherence could be supported and also identified key features of well-regarded messages: polite tone, credible information, contextualised, and endorsed by identifiable member of primary care facility staff. Direct and indirect user testing enabled us to refine the intervention including refining use of language and testing of interactive components.ConclusionsOur experience shows that using a formal intervention development process is feasible in a low-resource multi-lingual setting. The process enabled us to pre-test assumptions about the intervention and the evaluation process, allowing the improvement of both. Describing how a multi-component intervention was developed including standardised descriptions of content aimed to support behaviour change will enable comparison with other similar interventions and support development of new interventions. Even in low-resource settings, funders and policy-makers should provide researchers with time and resources for intervention development work and encourage evaluation of the entire design and testing process.Trial registrationThe trial of the intervention is registered with South African National Clinical Trials Register number (SANCTR DOH-27-1212-386; 28/12/2012); Pan Africa Trial Register (PACTR201411000724141; 14/12/2013); ClinicalTrials.gov (NCT02019823; 24/12/2013).

Incorporating user values into housing design through indirect user participation using MEC-QFD model

This study aims to incorporate user values into housing design. Incorporating user values is essential for developing quality housing. Data was gathered in three stages using the Means-End Chain and Quality Function Deployment models. To identify the factors that create values, the MEC model was conducted using soft laddering interviews with 15 apartment occupants in Bushehr, Iran. Next, weight assessments were done for value creators. With data from the first phase, a hard laddering questionnaire survey of MEC was created and distributed among 150 respondents. Nine architects developed design strategies in a focus group discussion to establish the House of Quality of QFD based on responses. The developed strategies involved four main categories including Building Organizational Emphasis, Interior Design Emphasis, Exterior Design Emphasis, and Indoor Environmental Emphasis. The combination of MEC and QFD facilitates indirect user participation and fulfills person environment congruence.

First impressions are lasting impressions: intention to participate in mobile health projects within developing countries

With healthcare infrastructure and health services remaining inadequate in many countries, numerous mobile health (mHealth) development studies have been reported, especially in low- and middle-income countries. This reflects a broad recognition that mobile technologies can play an important role in the provision of healthcare services at the regional, community and individual levels. However, implementing large-scale mHealth programmes has proven difficult; hence the use of mHealth pilots or feasibility studies as precursors to full rollouts. Existing literature reports that social, cultural, economic, political, technological and institutional factors influence the successful implementation of mHealth artefacts, yet there remains a dearth of research investigating individuals’ intention to participate in mHealth feasibility projects. Typically, mHealth projects involve a number of key stakeholders, ranging from direct stakeholders (such as healthcare workers who use the applications) to indirect stakeholders (such as the patients themselves who are not direct users of the technologies). Through the lens of impression management and self-determination theories, this study examines the extent to which an indirect user’s first impression, i.e. their initial encounter with the project and the project team on the ground, influences their decision to engage with an mHealth pilot project. Findings indicate that initial impressions formulated by indirect users impact their intention to participate in larger scale mHealth implementations. Through these early impressions participants formulate their perceptions about the project, and this directly influences their decision to engage. Furthermore, an individual’s first impressions can influence other potential participants’ decision to participate, especially in the context of the healthcare worker–patient relationship. The paper concludes that understanding indirect users’ expectations regarding the role of mHealth in addressing societal problems is essential to the success of wider mHealth projects in developing countries.

Time Aware and Data Sparsity Tolerant Web Service Recommendation Based on Improved Collaborative Filtering

With the incessant growth of web services on the Internet, how to design effective web service recommendation technologies based on Quality of Service (QoS) is becoming more and more important. Web service recommendation can relieve users from tough work on service selection and improve the efficiency of developing service-oriented applications. Neighborhood-based collaborative filtering has been widely used for web service recommendation, in which similarity measurement and QoS prediction are two key issues. However, traditional similarity models and QoS prediction methods rarely consider the influence of time information, which is an important factor affecting the QoS performance of web services. Furthermore, it is difficult for the existing similarity models to capture the actual relationships between users or services due to data sparsity. The two shortcomings seriously devalue the performance of neighborhood-based collaborative filtering. In this paper, the authors propose an improved time-aware collaborative filtering approach for high-quality web service recommendation. Our approach integrates time information into both similarity measurement and QoS prediction. Additionally, in order to alleviate the data sparsity problem, a hybrid personalized random walk algorithm is designed to infer indirect user similarities and service similarities. Finally, a series of experiments are provided to validate the effectiveness of our approach.

Estimating user interaction strength in distributed online networks

SummaryUser interactions are indispensable for any online network to thrive, especially for BitTorrent‐like and Web real‐time communication‐based distributed online networks that rely on users' collective contributions instead of the help of central servers. User interactions provide fine‐grained information for many applications, such as security enhancement and cooperation promotion. To date, several schemes for estimating user interaction strength in centralized online networks have been proposed. In contrast, we present design, deployment, and analysis of UISE for user interaction strength estimation in distributed online networks. Among the strong points of UISE is that it captures both direct and indirect user interactions, and that it scales with only partial information dissemination. We apply UISE to devise the first distributed scheme for online time estimation and we implement it into Tribler, a distributed online network for media and social applications like file sharing, streaming, and voting. We demonstrate the accuracy and the scalability of UISE with different information dissemination protocols and user behaviors using simulations, emulations, and a real‐world deployment. Copyright © 2015 John Wiley & Sons, Ltd.

The Impact of an Increase in User Costs on the Demand for Emergency Services: The Case of Portuguese Hospitals.

Evidence on the impact of user costs on healthcare demand in 'universal' public National Health Services (NHS) is scarce. The changes in copayments and in the regulation of the provision of free patient transportation, introduced in early 2012 in Portugal, provide a natural experiment to evaluate that impact. However, those changes in user costs were accompanied with changes in the criteria that determine which patients are exempt from copayments, implying that simple comparisons of user rates would be biased. In this paper, we develop a new methodology to evaluate the impact of increases in direct and indirect user costs on the demand for emergency services (ES) in the presence of compositional changes in co-payment exempt and non-exempt populations. Our results show that the increase in copayments did not have an effect in moderating ES demand by paying users, but we find significant effects of the change in transport regulation. Thus, our results support the conclusion that indirect costs may be more important than direct costs in determining healthcare demand in NHS-countries where copayments are small and wide exemption schemes are in place, especially for older patients. Copyright © 2015 John Wiley & Sons, Ltd.

Trustworthy Service Discovery for Dynamic Web Service Composition

As the number of services available on the Web increases, it is vital to be able to identify which services can be trusted. Since there can be an extremely large number of potential services that offer similar functionality, it is challenging to select the right ones. Service requestors have to decide which services closelysatisfy their needs, and theymust worry about the reliability of the service provider. Although an individual service can be trusted, a composed service is not guaranteed to be trustworthy. In this paper, we present a trust model that supports service discovery and composition based on trustworthiness. We define a method to evaluate trust in order to discover trustworthy services. We also provide a method to perform trust estimation for dynamic service composition, and we present results of two experiments. The proposed model allows for service requestors to obtain the most trustworthy services possible. Our mechanism uses direct and indirect user experience to discover the trustworthiness of the services and service providers. Moreover, composing services based on quantitative trust measurements will allow for consumers to acquire a highly reliable service that meet their quality and functional requirements.

IsoCam

We introduce a novel user interface and system for exploring extremely detailed 3D models in a museum setting. Three-dimensional models and associated information are presented on a large projection surface controlled by a touch-enabled surface placed at a suitable distance in front of it. Our indirect user interface, dubbed IsoCam , combines an object-aware interactive camera controller with an interactive point-of-interest selector and is implemented within a scalable implementation based on multiresolution structures shared between the rendering and user interaction subsystems. The collision-free camera controller automatically supports the smooth transition from orbiting to proximal navigation, by exploiting a distance-field representation of the 3D object. The point-of-interest selector exploits a specialized view similarity computation to propose a few nearby easily reachable interesting 3D views from a large database, move the camera to the user-selected point of interest, and provide extra information through overlaid annotations of the target view. The capabilities of our approach have been demonstrated in a public event attended by thousands of people, which were offered the possibility to explore submillimetric reconstructions of 38 stone statues of the Mont’e Prama Nuragic complex, depicting larger-than-life human figures, and small models of prehistoric Nuraghe (cone-shaped stone towers). A follow-up of this work, using 2.5m-high projection screens, is now included in permanent exhibitions at two Archeological Museums. Results of a thorough user evaluation, involving quantitative and subjective measurements, are discussed.

Entity ranking using click-log information

Log information describing the items the users have selected from the set of answers a query engine returns to their queries constitute an excellent form of indirect user feedback that has been extensively used in the to improve the effectiveness of search engines. In this work we study how the logs can be exploited to improve the ranking of the results returned by an entity search engine. Entity search engines are becoming more and more popular as the is changing from a of documents into a web of things. We show that entity search engines pose new challenges since their model is different than the one documents are based on. We present a novel framework for feature extraction that is based on the notions of entity matching and attribute frequencies. The extracted features are then used to train a ranking classifier. We introduce different methods and metrics for ranking, we combine them with existing traditional techniques and we study their performance using real and synthetic data. The experiments show that our technique provides better results in terms of accuracy.

Innovation for and by the People with Disabilities: A Case Study in Improvement of the Manual Wheelchair

This paper focuses on information-driven engineering, where information is gathered by means of innovation for people and by the people. This case study was carried out on innovation of a manual wheelchair. Through active participation of person with disability (direct users) and their carers (indirect user), knowledge awareness of the early design was increased. Computer aided engineering tools were used for the development of virtual prototype (VP) and after further feedback from direct and indirect users design was adjusted. Additionally, Physical prototype was built to practically demonstrate the new features to users and finally the prototype was readjusted to bridge user requirement even more. This innovation process identifies additional improvement aspects and contributes beyond fundamental personal needs and increases well being.

Mining information across multiple domains: A case study of application to patent laws and regulations in biotechnology

Abstract In this paper, we present a framework that can process a user query for retrieval of information from documents of different properties across multiple domains, with specific application to patent laws and regulations. The framework has three basic components. The first component is ontology mapping and generation. What happens is that the keywords entered by users are mapped into a subset of relevant keywords. This step is performed by looking up those words in an ontology database. The second component is the joint and cross search in various document domains; in our case, they are patents and scientific publications. The last component is to modify the search results by applying user feedback statistics. The results of feedback will be saved as metadata for future uses. A case example is given to demonstrate how results from multiple domain searches can be combined using ontology and cross referencing. We use an example of well-known biotechnology patents on erythropoietin (EPO) and give detailed analysis on each document domain with this keyword. Relationships between each domain are demonstrated. A user feedback mechanism is also discussed in this paper. The ability to take user feedback into the framework is important. There is no doubt that domain knowledge from expert or experienced users could be a very good compliment to the proposed system. Both direct and indirect user feedbacks are discussed.

Whither Australia: Will Availability of Water Constrain the Growth of Australia's Population?

AbstractSupply of water for cities and for food production will not be a major factor limiting the growth of Australia's population in coming decades. The water needed to sustain the population of Australia can be divided into two kinds. Direct water requirements are those that meet the immediate needs of the people – potable water supply and waste removal. Indirect water requirements refer to the water needed to sustain the economy and the standard of living – food production, manufacturing, mining, etc. Agriculture is the largest indirect user, using between 50% and 70%, while household use, including sewerage and drainage, uses less than 30%. Industry uses the remaining 20%. In this paper, we do not deal with the issue of water quality but note its significance, especially as regards the salinisation of water resources in rural Australia. Australia has abundant water when expressed on a per capita basis, although this is unevenly distributed around the continent. Per capita, the densely populated south‐eastern and south‐western parts of the continent have low to average run‐off available when compared with other populated regions of the world. What is more important is the extreme inter‐annual variability of that run‐off. Previous attempts to measure the size of the population that could be supported in Australia, based on the availability of water, have produced estimates up to 280 million. Outside of the well‐watered edges of the continent, water has always been seen as a factor that limits Australia's population. However, water supply is a necessary but not sufficient basis for population growth, as can be seen from examples (such as the Ord Irrigation Scheme) where providing abundant water has failed to trigger major population growth. The largest increases in population in coming decades are predicted to occur in the capital cities where there has been a substantial reduction in water use through demand management in recent years. Urban water demand has proven to be extremely elastic. New sources of urban water, including desalination, groundwater, recycled sewage, and increased run‐off in urban stormwater, will easily provide sufficient water for a growing urban population over coming decades. Water used in irrigated agriculture at present supplies the needs of Australia's 20 million people and an estimated 40 million in other countries. With increased efficiency in the delivery and use of water for irrigation combined with export substitution, water for food production is not likely to limit population. In this paper, we have not dealt with the issue of environmental flows in rivers or with the provision of water to wetlands, although we acknowledge that they are both significant issues for policy development. We conclude that the size of the population of Australia is less important than how that population behaves in regard to the management of water resources.