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The emergence of mobile health (mHealth) products has created a capability of monitoring and managing the health of patients with chronic diseases. These mHealth…
The emergence of mobile health (mHealth) products has created a capability of monitoring and managing the health of patients with chronic diseases. These mHealth technologies would not be beneficial unless they are adopted and used by their target users. This study identifies key factors affecting the usage of mHealth apps based on user usage data collected from an mHealth app.
Using a dataset collected from an mHealth app named mPower, developed for patients with Parkinson's disease (PD), this paper investigated the effects of disease diagnosis, disease progression and mHealth app difficulty level on app usage, while controlling for user information. App usage is measured by five different activity counts of the app.
The results across five measures of mHealth app usage vary slightly. On average, previous professional diagnosis and high user performance scores encourage user participation and engagement, while disease progression hinders app usage.
The findings potentially provide insights into better design and promotion of mHealth products and improve the capability of health management of patients with chronic diseases.
Studies on the mHealth app usage are critical but sparse because large-scale and reliable mHealth app usage data are limited. Unlike earlier works based solely on survey data, this research used a large user usage data collected from an mHealth app to study key factors affecting app usage. The methods presented in this study can serve as a pioneering work for the design and promotion of mHealth technologies.
Large terminologies usually contain a mix of terms that are either generic or domain specific, which makes the use of the terminology itself a difficult task that may…
Large terminologies usually contain a mix of terms that are either generic or domain specific, which makes the use of the terminology itself a difficult task that may limit the positive effects of these systems. The purpose of this paper is to systematically evaluate the degree of domain specificity of the AGROVOC controlled vocabulary terms as a representative of a large terminology in the agricultural domain and discuss the generic/specific boundaries across its hierarchy.
A user-oriented study with domain-experts in conjunction with quantitative and systematic analysis. First an in-depth analysis of AGROVOC was carried out to make a proper selection of terms for the experiment. Then domain-experts were asked to classify the terms according to their domain specificity. An evaluation was conducted to analyse the domain-experts’ results. Finally, the resulting data set was automatically compared with the terms in SUMO, an upper ontology and MILO, a mid-level ontology; to analyse the coincidences.
Results show the existence of a high number of generic terms. The motivation for several of the unclear cases is also depicted. The automatic evaluation showed that there is not a direct way to assess the specificity degree of a term by using SUMO and MILO ontologies, however, it provided additional validation of the results gathered from the domain-experts.
The “domain-analysis” concept has long been discussed and it could be addressed from different perspectives. A resume of these perspectives and an explanation of the approach followed in this experiment is included in the background section.
The authors propose an approach to identify the domain specificity of terms in large domain-specific terminologies and a criterion to measure the overall domain specificity of a knowledge organisation system, based on domain-experts analysis. The authors also provide a first insight about using automated measures to determine the degree to which a given term can be considered domain specific. The resulting data set from the domain-experts’ evaluation can be reused as a gold standard for further research about these automatic measures.
Chang'an Automobile and the Chinese automotive industry.
China has become the world's largest producer of automobiles, surpassing the USA and Japan. The Chinese auto industry differs quite significantly from those countries though. While the industry exhibits a substantial degree of concentration in the USA and Japan in early 2011, it remained highly fragmented in China. The Chinese Central Government had announced a desire for consolidation, yet it remained unclear whether a significant shakeout would occur in the near term.Like many Chinese automakers, Chang'an partnered with well‐known global auto makers to develop, produce, and distribute its products. In the coming years, Chang'an hoped to develop more independence from its foreign partners, including the production and distribution of self‐branded cars. However, the company grappled with how it could strive for independence while managing its existing joint ventures. Executives worried too about how to compete with foreign automakers who had achieved global economies of scale.The case provides a rich description of the evolution of the Chinese auto industry, and it documents how the Chinese industry differs from other global markets. Readers can analyze the extent to which they believe scale economies provide foreign firms an advantage over smaller Chinese rivals, and they can evaluate the conventional wisdom regarding the industry's minimum efficient scale. The case also provides a detailed account of Chang'an's rise to prominence. The case concludes by offering an in‐depth description of the firm's key rivals, and it presents the key questions being considered by Chang'an executives in 2011.
Expected learning outcomes
Enables students to examine how and why an industry's structure can differ substantially across geographic markets. Enables students to examine whether the need to achieve economies of scale may cause substantial consolidation in the Chinese auto industry. Provides an opportunity to evaluate the pros and cons of the joint venture strategies employed in China. Provides an opportunity to examine how a relatively small firm can position itself against large multinationals in a high‐growth emerging market.
Business intelligence (BI) has been applied in various domains to take better decisions and it provides different level of information to its stakeholders according to the…
Business intelligence (BI) has been applied in various domains to take better decisions and it provides different level of information to its stakeholders according to the information needs. The purpose of this paper is to present a literature review on recent works in BI. The two principal aims in this survey are to identify areas lacking in recent research, thereby offering potential opportunities for investigation.
To simplify the study on BI literature, it is segregated into seven categories according to the usage. Each category of work is analyzed using parameters such as purpose, domain, problem identified, solution applied, benefit and outcome.
The BI contribution in various domains, ongoing research in BI, the convergence of BI domains, problems and solutions, results of congregated domains, core problems and key solutions. It also outlines BI and its components composition, widely applied BI solutions such as algorithm-based, architecture-based and model-based solutions. Finally, it discusses BI implementation issues and outlines the security and privacy policies adopted in BI environment.
In this survey BI has been discussed in theoretical perspective whereas practical contribution has been given less attention.
A comprehensive survey on BI which identifies areas lacking in recent research and providing potential opportunities for investigation.