Patient flow in the “outpatient-emergency+inpatient” mode: A conceptual model and data analysis

2014 ◽  
Author(s):  
Xin-li Zhang ◽  
Ting Zhu ◽  
Li Luo ◽  
Chang-zheng He ◽  
Zi Liu ◽  
...  
Keyword(s):  
Data Analysis ◽  
Conceptual Model ◽  
Patient Flow ◽  
Mode A

Transformative Life Experience as a Glimpse Into Potentiality

2020 ◽  
pp. 002216782093748
Author(s):  
Pninit Russo-Netzer ◽  
Jonathan Davidov
Keyword(s):  
Data Analysis ◽  
Lived Experience ◽  
Conceptual Model ◽  
Life Experience ◽  
Hermeneutic Phenomenology ◽  
Common Features ◽  
Theoretical View ◽  
Depth Interviews ◽  
Phenomenological Exploration

Many clients cope with the consequences of transformative life experience (TLE) in psychotherapy. TLE often involves a radical, profound reorganization of or change in one’s life because of resulting formative, life-changing choices. Yet the essence of the mechanism people use to process and make sense of a TLE is unclear. This study is a phenomenological exploration of such experiences that aims to offer a heuristic theoretical view of how such change is constructed and played out. Data were collected through in-depth interviews with 120 adults who had coped with the consequences of a TLE. Data analysis was guided by a hermeneutic phenomenology paradigm that postulates that people account for their experience within the four existentials of temporality, spatiality, corporality (embodiment), and relationality. Those lifeworld existentials were utilized as a framework and lens through which to organize the data. This procedure was followed by a hermeneutical interpretation to identify common features of lived experience along all four domains of analysis with the purpose of constructing a conceptual model that illustrates the essence of change during TLE. Implications are considered for utilizing theoretical and applied insights from the model.

scholarly journals Conceptual usage model of big data generated by social media

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Jolanta Sabaitytė ◽  
Roberta Karpovičiūtė
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Big Data ◽  
Data Analysis ◽  
Conceptual Model ◽  
Decision Support Tool ◽  
Virtual Space ◽  
Management Tools ◽  
Support Tool ◽  
Customer Profiles

The digital revolution and the communication platforms provided by the Web 2.0 virtual space era, such as social media, social networks, other tools and channels, create new opportunities for better marketing decisions based on user-generated data analysis. Every day customers of social media and other virtual tools are creating huge amounts of their actions-caused data, and businesses lack management tools supporting this process, which could create knowledge in the areas of deeper cognitive customer profiles and preferences. The growing number of social media users indicates the popularity of these communication tools among the information society, but science today lacks a deeper knowledge of social media-generated data and other algorithms for this kind of data usage. Therefore, the purpose of the article can be defined as the development of a conceptual model of big data generated by social media usage in business. The formation of the conceptual model is based on the analysis of big data assumptions and application possibilities, social media classification peculiarities and different channel specifics, identification of big data analysis methods and analysis of big data applications generated by social media. The conceptual model creates preconditions for deeper knowledge of user-generated big data in nowadays’ widely used communication platforms, as well as creation of the decision support tool for marketing specialists in order to use big data from social media in deeper cognitive customer profiles and preferences. The methods employed in this research are literature and other references analysis, synthesis and logical analysis of information, comparison of information, systemisation and visualisation.   Keywords: Big data, data mining, social media, social networks, internet marketing.

scholarly journals DIDŽIŲJŲ DUOMENŲ PANAUDOJIMAS SOCIALINĖJE MEDIJOJE / THE BIG DATA USE IN SOCIAL MEDIA

2019 ◽  
Vol 11 (0) ◽  
pp. 1-13
Author(s):  
Roberta Karpovičiūtė ◽  
Jolanta Sabaitytė
Keyword(s):  
Social Media ◽  
Big Data ◽  
Data Analysis ◽  
Conceptual Model ◽  
Large Data ◽  
Decision Support Tool ◽  
Virtual Space ◽  
Management Tools ◽  
Support Tool ◽  
Digital Revolution

The digital revolution and the communication platforms provided by the web 2.0 virtual space era, such as social media, social networks, other tools and channels, create new opportunities for better marketing decisions based on user-generated data analysis. Every day customers of social media and other virtual tools are creating huge amounts of their actions caused data, and business lack management tools for the support of this process, which could create knowledge in the area of customer profiles and preferences deeper cognition. Growing numbers of social media users indicate the popularity of these communication tools among the information society, but science today lacks a deeper knowledge of social media generated data and other algorithms for this data usage. Therefore, the purpose of the article is defined as the development of the conceptual model of big data generated by social media usage in business. The formation of the conceptual model is based on the analysis of big data assumptions and application possibilities, social media classification peculiarities and different channel specifics, identification of big data analysis methods and analysis of large data applications generated by social media. The conceptual model creates preconditions for deeper knowledge of user-generated big data in nowadays widely used communication platforms, as well as creation of the decision support tool for marketing specialists in order to use big data from social media in deeper customer profile and preferences cognition. Methods employed in this research are: literature and other references analysis, synthesis and logical analysis of information, comparison of information, systemization and visualization.

The Propensity to Use FinTech: Input from Bankers in the Kingdom of Bahrain

2020 ◽  
Vol 19 (01) ◽  
pp. 2040025 ◽  
Author(s):  
Anjum Razzaque ◽  
Richard Thomas Cummings ◽  
Magdalena Karolak ◽  
Allam Hamdan
Keyword(s):  
Data Analysis ◽  
Middle East ◽  
Conceptual Model ◽  
Multiple Regression ◽  
Perceived Risk ◽  
Financial Risk ◽  
Reliability And Validity ◽  
Survey Instrument ◽  
Perceived Benefits ◽  
Perceived Benefit

This study aims to assess why users are willing/hesitant to continue using FinTech services based on their perceived benefits and risks pertaining to the use of FinTech technology. Data was collected, using an adopted survey instrument, from bankers based in Bahrain, the financial and FinTech hub of the Middle East. Data analysis was applied to assess the reliability and validity of this study’s conceptual model along with its nine hypotheses with 374 valid responses subsequently being analysed using multiple regression via SPSS version 23. The empirical findings of this study supported all the hypotheses, revealing that both perceived benefit and risks affect the intent to continue using FinTech. Perceived benefit has a stronger effect than the perceived risk, and convenience perceived most beneficial while financial risk perceived riskiest for using FinTech technology by the bankers of Bahrain.

Mentoring for the Educational Leadership Professoriate: Perspectives From Jay D. Scribner Mentoring Award Recipients and Mentees

2018 ◽  
Vol 14 (3) ◽  
pp. 236-260 ◽  
Author(s):  
Donald G. Hackmann ◽  
Joel R. Malin
Keyword(s):  
Data Analysis ◽  
Educational Leadership ◽  
Conceptual Model ◽  
Career Stages ◽  
Research Partnerships ◽  
Group Mentoring ◽  
Institutional Contexts

This article presents findings from a study of Jay D. Scribner Award recipients. The purposes were to learn why professors engage in mentoring and to identify activities and supports provided to mentees. Interviews were held with the 12 recipients and 24 mentees who submitted letters in support of their nominations, with Mertz’s conceptual model of mentoring guiding data analysis. Findings revealed mentoring activities were based upon mentees’ career stages and institutional contexts, and aligned with Mertz’s mentoring continuum. Relationships emerged informally, included individual and group mentoring, were characterized by relational equality, and resulted in long-term research partnerships and friendships.

scholarly journals Formalization and Knowledge Representation in Advanced Engineering Informatics

2022 ◽  
pp. 8-14
Author(s):  
Mohammad Biglarbegian
Keyword(s):  
Data Analysis ◽  
Knowledge Representation ◽  
Conceptual Framework ◽  
Conceptual Model ◽  
Research Area ◽  
Bottom Up ◽  
Engineering Knowledge ◽  
Analysis Techniques ◽  
Scientific Approach ◽  
Social Scientific

The primary goal of this article in the research area of Advanced Engineering Informatics (AEIs) is to depict and formalize engineering knowledge that is multidimensional. This paper introduces conceptual framework and rationality as implicit methodologies to regularize knowledge. The objective of professionals, as well as the circumstances in which they work, should be considered when depicting and standardizing knowledge. The constructs of epistemology, rationality, and context are used to communicate various alternative data analysis techniques and practices that expert can use to institutionalize intricate engineering expertise and to substantiate whether a specialized conceptual model can support engineers with their challenging operations. A bottom-up method of research in advanced engineering, encompassing engineers, is suggested in this article. A social scientific approach to engendering knowledge for formalization and validating it is also recommended by us for scientists.

Sign in / Sign up

Export Citation Format

Share Document