QoS-aware middleware for web services composition: a qualitative approach

Web services exhibit major industrial benefit by their ability to participate in composition processes. Web services composition allows for automated exchange of information among remote processes through the service interface. A well-established end-to-end QoS infrastructure among the involved processes precludes confusion among the developers, vendors and consumers. Most of the research work conducted in this domain has focused on functional QoS requirements such as service response time, delay, cost, etc. This paper elaborates the QoS of web services from the perspective of data freshness and accuracy. Towards this aim, the ‘Region Switching’ (RS) algorithm is introduced in this paper. Within the context of the multiple web services composition scenario, the RS-algorithm allows for accurate identification of the point of information change and the appropriate re-computation over the subset of the pre-established, global service execution plan. Thereafter, a mathematical model is presented to verify the need for re-computation based on certain estimated factors, computed thresholds, and the model design. Such a selective re-computation is worth considering since some services may take a significant amount of time to produce results where a slight change to the information set might not alter the outcome of the service. The proposed concept is implemented by utilising and extending the WS-Notification specification in order to elaborate a middleware that is capable of sensing and routing information change at the level of web services using the publish-subscribe mechanism. The contribution of this paper is threefold. First, it highlights the importance of qualifiable QoS aspect related to the issue of web services composition and monitoring. Second, it describes an algorithm capable of capturing and reflecting the state of web services involved in a composition process, thereby achieving higher QoS. Finally, the paper illustrates the use and extension of the WS-Notification concept in building such systems that would deliver up-to-date information to the user through selective re-computation of the web services composition plan.     

Phenomena-centered Text Analysis (PTA): a new approach to foster the qualitative paradigm in text analysis

Quality & Quantity - Content or text analysis is one of the most common evaluation methods employed in qualitative research. Despite its wide application, however, a clear structure of how such...     

Elderly and technology tools: a fuzzyset qualitative comparative analysis

The number of senior citizens is growing globally and governments are striving to find innovative solutions to deal with complex care demands of this part of the population. Technology has been an answer to this situation; however, it is very important that the elderly accept and actually use the technology. This paper empirically tests the senior technology acceptance model using the fsQCA method to analyse data with a sample of 811 seniors aged 60 and over living in Sweden. The results revealed that the necessary conditions for high “perceived ease of use” and “perceived usefulness” are gerontechnology self-efficacy, gerontechnology anxiety, and cognitive abilities; however, each of these is not sufficient on its own. Self-reported health conditions and physical function also play a peripheral role in achieving the desired outcome. Theoretical and managerial implications are discussed at the end of the paper.     

Key factors affecting the hospital performance: a qualitative study using fuzzy logic

Identifying the key factors affecting the hospital performance helps better planning for hospital high performance. The purpose of this study is to provide a combination of qualitative and quantitative methods to investigate the hospital performance. In the qualitative section of this study, factors associated with hospital performance were detected using literature review, interviews, and expert panels. The findings analyzed by one sample t test and categorized by framework analysis method. In the quantitative section of this study, both direct and indirect relationships between factors were measured by using fuzzy Decision Making Trial and Evaluation Laboratory technique to detect influencing and influenced factors. Finally the key factors affecting the hospital performance were detected.     

Big data for cyber physical systems in industry 4.0: a survey

ABSTRACT

With the technology development in cyber physical systems and big data, there are huge potential to apply them to achieve personalization and improve resource efficiency in Industry 4.0. As Industry 4.0 is the relatively new concept originated from an advanced manufacturing vision supported by the German government in 2011, there are only several existing surveys on either cyber physical systems or big data in Industry 4.0. In addition, there are much less surveys related to the intersection between cyber physical systems and big data in Industry 4.0. However, cyber physical systems are closely related to big data in nature. For example, cyber physical systems will continuously generate a large amount of data which requires the big data techniques to process and help to improve system scalability, security, and efficiency. Therefore, we conduct this survey to bring more attention to this critical intersection and highlight the future research direction to achieve the fully autonomy in Industry 4.0.     

A modular fuzzy inference system approach in integrating qualitative and quantitative analysis of store image

The image situation in a store includes various stimuli, such as color, sound, scent, taste, layout and space, which are important clues for buyers. This paper describes store image response and a fuzzy logic model developed by comprehensive literature studies on image measurements (including atmospheric factors) and perceptual measures. Here, a fuzzy inference system is proposed as an alternative approach to handle effectively the impreciseness and uncertainty that are normally found in store image selection processes. This paper also shows that the proposed decision-making model is application to modified stimulus?Corganism?Cresponse (S?CO?CR) framework for integrating qualitative and quantitative analysis. The result of the simulation indicates a numerical and linguistic change in the store image perception after analyzing three input parameters. This finding is able to provide a solid foundation on which retailers and decision makers can base suitable strategies for ensuring the efficiency and stability of store image management system.     

To trust or not to trust smart consumer products: a literature review of trust-building factors

Management Review Quarterly - Numerous “smart” consumer products are already available on the market, and the diversity of such smart products is expected to increase considerably in...     

Integrating qualitative and quantitative data: index creation using fuzzy-set QCA

This paper demonstrates the use of fuzzy-set Qualitative Comparative Analysis (fsQCA) for index creation. It uses the example of economic, including development, policy towards Latin America in Germany, Spain and the United Kingdom as an example of how fsQCA can be deployed in order to integrate qualitative and numerical evidence into a coherent, comparable framework. Moreover, it shows the usefulness of an index based on fsQCA in the comparison of cases that have strong national idiosyncrasies, making them difficult to compare. FsQCA therefore increases the researcher’s ability to combine different types of data from various backgrounds, making it a useful indexing tool for small to medium-N research in the social sciences.     

Ranking by competence using a fuzzy approach

New approaches in economics of education consider the concept of competence to bringing in the multidimensional feature of labour force quality. Competence includes knowledge, skills, behaviours and attitudes. Each individual suits the combination of these elements to perform a task. Thus, different combinations expectedly lead to different task performance inside an occupation. In this paper, we focus on individual heterogeneity in homogeneous job requirements context. In sequel, we establish a theorem on unit simplex that potentially provides a ranking system by competence. The system is designed under a grade of membership framework, with a technique based on fuzzy sets theory. Under certain conditions, the referred theorem allows a mapping of individual multidimensional feature into the interval [0, 1]. So, the greater the value along this interval, the more competent the individual. An empirical study of a banking sector activity illustrates our research.     

In search of content validity: facet analysis as a qualitative method to improve questionnaire design

In this paper, two scales are examined for the measurement of self-regulation. The item content is evaluated for its specific usefulness for measuring self-regulation of obesity patients. Qualitative facet analysis (QFA), an application of Guttmann’s Facet Theory, is used to investigate whether item content sufficiently covers the intended content area. This form of content analysis constitutes a systematic, effective and critical tool for improving the content validity of questionnaires. It discovers topics that are underrepresented or overrepresented. The method offers a way to clarify the relationship between concrete item phrases and the desired content as defined by construct and theory. It allows the researcher to improve his or her understanding of the items as a stimulus and of the similarities of items, and allows the formulation of a possible structure for confirmative factor analysis. Various ways to improve the content of both scales are identified.     

On estimating the proportion of a qualitative sensitive character using randomized response sampling

In this paper, we present results pertaining to investigations concerning randomized response sampling. We consider a simple generalization for some existing investigations, and then provide the suitable choices for design parameters. It is also demonstrated the superiority of the proposed procedure over Warner (1965) procedure.     

Project analysis using a linear approach (P.A.U.L.A.)

We define a general model (called PAULA) for the valuation, optimal management and selection among mutually exclusive safe projects. By exploiting the formal and financial features of the associated linear problems (primal and dual), we put forward two proposals to define an optimal internal financial law (IFL). They may be used to reduce the multiplicity of the IFLs and to avoid economically arbitrary outcomes.Research projectsCariplo andMurst.     

Relational union organising in a healthcare setting: a qualitative study

This article explores the impact of a relational organising model within a local UNISON NHS branch. While initial outcomes were modest, we argue that relational approaches have the potential to increase branch engagement with organising activity and to provide a focus on the importance of community within the workplace.     

Preparing for analysis: a practical guide for a critical step for procedural rigor in large-scale multisite qualitative research studies

Despite attention to technical aspects of conducting qualitative research, few studies describe procedures for managing pre-analysis activities in large-scale multisite qualitative projects. As part of the data collection for the Criminal Justice Drug Abuse Treatment Studies, a national multisite research cooperative with nine research centers (RCs) conducted 700 semi-structured interviews to evaluate interorganizational strategies in three protocols focused on improving addiction- and health related service delivery in criminal justice settings. Guided by the research cooperative, RCs collaborated on many aspects of the qualitative data activities (e.g., codebook development and coding activities), however, pre-analysis procedures, such as organizing and managing resources, were primarily managed at the RC level. The present study examines these various practices and describes two exemplary approaches to pre-analysis, with emphasis on lessons learned and recommendations for coordinating resources, managing data, and maintaining fidelity to the study procedures for large-scale qualitative projects.     

Representations of Australia in South Korean online news: a qualitative and quantitative approach utilizing Leximancer and Korean keywords in context

This article outlines original empirical research using a quantitative computer-assisted big data approach to survey and evaluate the representation of Australia in popular South Korean online news media sources. This is an exploratory content analysis of news reporting (in Korean and English) on Australia in key Korean digital news media providers and distributors over a six-month-period during which certain key events occurred that drew Korean news media attention to Australia. The research aims to address the fundamental question: what forms and patterns of representation of Australia are present in South Korean online news media? It is designed in large part to understand how Australia is present as a theme in Korean online news, and how this theme is contextualized by associated topics, such as trade, security, or tourism. The quantitative analysis is augmented using a qualitative method: a series of key informant interviews conducted with editors and journalists responsible for the production and prioritization of news. Further, it is interpreted by locating the research in the context of the Australia-South Korea relationship. We summarize the complexities that arise when analyzing large amounts of textual content, especially from two very different languages, discuss the opportunities that arise from mixed methods—by combining big data (breadth) with contextual analysis (depth) and offer suggestions for aspiring researchers.     

Implementing open government: a qualitative comparative analysis of digital platforms in France,Italy and United Kingdom

Open government is spreading throughout the world as a policy agenda oriented to foster transparency, participation and collaboration. Despite its increasing relevance in policy documents, there has been a scarce interest in deepening the analysis of how such agenda has been implemented in different national contexts. By adopting a multidimensional and multilevel perspective, we propose a qualitative comparative analysis of institutional digital platforms able to gather the evolution of open government in three European countries. We retrieved 979 open government platforms in France, Italy, and United Kingdom and analyzed them with an original set of indicators grouped in the three macro-areas of e-government, open data and transparency, participation and collaboration. Our study has methodological and policy implications: from the one hand, we provide the widest and deepest survey of open government platforms so far, contributing to the standardization of research methods on this field. From the other hand, we can observe that open government implementation is characterized by some typical traits, suggesting a trans-national convergence; this evidence is particularly prominent in the e-government and open data areas, whereas Participatory platforms are characterised by higher degrees of fragmentation both at the trans-national and at the intra-national levels. The analysis of open government platforms also reveals that, at the intra-national level, public administrations’ approaches to digital government are not homogeneous, although at different degrees among the three countries involved in our study, suggesting the need of a better integration and coordination by central authorities.

     

A Bayesian approach to experimental analysis: trading in a laboratory financial market

We employ a Bayesian approach to analyze financial markets experimental data. We estimate a structural model of sequential trading in which trading decisions are classified in five types: private-information based, noise, herd, contrarian and irresolute. Through Monte Carlo simulation, we estimate the posterior distributions of the structural parameters. This technique allows us to compare several non-nested models of trade arrival. We find that the model best fitting the data is that in which a proportion of trades stems from subjects who do not rely only on their private information once the difference between the number of previous buy and sell decisions is at least two. In this model, the majority of trades stem from subjects following their private information. There is also a large proportion of noise trading activity, which is biased towards buying the asset. We observe little herding and contrarianism, as theory suggests. Finally, we observe a significant proportion of (irresolute) subjects who follow their own private information when it agrees with public information, but abstain from trading when it does not.