scholarly journals Exploring the Impacts of Sharing Economy Drivers on Consumers’ Usage Intention

2021 ◽  
Vol 17 (1) ◽  
pp. 1-26
Author(s):  
I Ping Chiang ◽  
Pei-Wen Lin ◽  
Wan-Ling Yang
Keyword(s):  
Partial Least Squares Regression ◽  
Rapid Development ◽  
Academic Research ◽  
Sharing Economy ◽  
Survey Method ◽  
Least Squares Regression ◽  
Sample Analysis ◽  
Online Questionnaire ◽  
Quality Cost ◽  
Practical Operation

In recent years, people have begun to use sharing economy platforms such as Airbnb and Uber. The rapid development of such sharing economy platforms has thus become an important topic. Studies regarding the sharing economy have discussed resource providers but not users. Therefore, this study constructs a model to measure the components of sharing economy drivers and the correlation between those drivers and usage intention, in addition to exploring the differences in the composition of drivers and usage intention between Airbnb and Uber. The survey method was an online questionnaire. The sample analysis uses partial least squares regression to verify the hypothesis and analyze the components that form the sharing economy for drivers. According to the results, sharing economy drivers─Societal drivers, Economic drivers, Technological drivers, affect usage intention, and different combinations of sharing economy components, such as enjoyment, network externalities, perceived quality, cost saving, and efficiency, exist in Airbnb and Uber. For the reference of relevant academic research and practical operation in the future.

Use of reflectance spectroscopy to estimate the organic carbon and CaCO3 contents of soils

2012 ◽  
Vol 61 (2) ◽  
pp. 277-290 ◽  
Author(s):  
Ádám Csorba ◽  
Vince Láng ◽  
László Fenyvesi ◽  
Erika Michéli
Keyword(s):  
Organic Carbon ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Mean Squared Error ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Root Mean Squared Error ◽  
Squared Error

Napjainkban egyre nagyobb igény mutatkozik olyan technológiák és módszerek kidolgozására és alkalmazására, melyek lehetővé teszik a gyors, költséghatékony és környezetbarát talajadat-felvételezést és kiértékelést. Ezeknek az igényeknek felel meg a reflektancia spektroszkópia, mely az elektromágneses spektrum látható (VIS) és közeli infravörös (NIR) tartományában (350–2500 nm) végzett reflektancia-mérésekre épül. Figyelembe véve, hogy a talajokról felvett reflektancia spektrum információban nagyon gazdag, és a vizsgált tartományban számos talajalkotó rendelkezik karakterisztikus spektrális „ujjlenyomattal”, egyetlen görbéből lehetővé válik nagyszámú, kulcsfontosságú talajparaméter egyidejű meghatározása. Dolgozatunkban, a reflektancia spektroszkópia alapjaira helyezett, a talajok ösz-szetételének meghatározását célzó módszertani fejlesztés első lépéseit mutatjuk be. Munkánk során talajok szervesszén- és CaCO3-tartalmának megbecslését lehetővé tévő többváltozós matematikai-statisztikai módszerekre (részleges legkisebb négyzetek módszere, partial least squares regression – PLSR) épülő prediktív modellek létrehozását és tesztelését végeztük el. A létrehozott modellek tesztelése során megállapítottuk, hogy az eljárás mindkét talajparaméter esetében magas R2értéket [R2(szerves szén) = 0,815; R2(CaCO3) = 0,907] adott. A becslés pontosságát jelző közepes négyzetes eltérés (root mean squared error – RMSE) érték mindkét paraméter esetében közepesnek mondható [RMSE (szerves szén) = 0,467; RMSE (CaCO3) = 3,508], mely a reflektancia mérési előírások standardizálásával jelentősen javítható. Vizsgálataink alapján arra a következtetésre jutottunk, hogy a reflektancia spektroszkópia és a többváltozós kemometriai eljárások együttes alkalmazásával, gyors és költséghatékony adatfelvételezési és -értékelési módszerhez juthatunk.

Speech Emotion Recognition Based on Sparse Representation

2013 ◽  
Vol 38 (4) ◽  
pp. 465-470 ◽  
Author(s):  
Jingjie Yan ◽  
Xiaolan Wang ◽  
Weiyi Gu ◽  
LiLi Ma
Keyword(s):  
Dimensionality Reduction ◽  
Emotion Recognition ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Speech Emotion Recognition ◽  
Least Squares Regression ◽  
Computer Science Pedagogy ◽  
Reduction Methods ◽  
Analysis Computer

Abstract Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.

Multivariate micropollutants analysis in marine waters

1995 ◽  
Vol 32 (9-10) ◽  
pp. 341-348
Author(s):  
V. Librando ◽  
G. Magazzù ◽  
A. Puglisi
Keyword(s):  
Multivariate Data Analysis ◽  
Partial Least Squares Regression ◽  
Environmental Chemistry ◽  
Sampling Site ◽  
Principal Component ◽  
Least Squares Regression ◽  
Organic Micropollutants ◽  
Suspended Material ◽  
The Difference

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a function of time. In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of organic micropollutants, particularly since some are known to be carcinogenic. As the number of measured parameters increases examining the data and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Multivariate Data Analysis (MVDA), Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR). The use of the first technique in this work has been applied to the interpretation of the quality of Augusta bay, by measuring the concentration of numerous organic micropollutants, together with the classical water pollution parameters, in different sites and at different times. The MVDA has highlighted the difference between various sampling sites whose data were initially thought to be similar. Furthermore, it has allowed a choice of more significant parameters for future monitoring and more suitable sampling site locations.

Protein Solvent Interaction: Transition of Protein-solvent Interaction Concept from Basic Research into Solvent Manipulation of Chromatography

2018 ◽  
Vol 20 (1) ◽  
pp. 34-39 ◽  
Author(s):  
Tsutomu Arakawa ◽  
Yoshiko Kita
Keyword(s):  
Column Chromatography ◽  
Rapid Development ◽  
Academic Research ◽  
Basic Research ◽  
Protein Stabilization ◽  
Special Issue ◽  
Solvent Interaction ◽  
Protein Formulations ◽  
Solvent Additive ◽  
Downstream Processes

Previously, we have reviewed in this journal (Arakawa, T., Kita, Y., Curr. Protein Pept. Sci., 15, 608-620, 2014) the interaction of arginine with proteins and various applications of this solvent additive in the area of protein formulations and downstream processes. In this special issue, we expand the concept of protein-solvent interaction into the analysis of the effects of solvent additives on various column chromatography, including mixed-mode chromatography. Earlier in our research, we have studied the interactions of such a variety of solvent additives as sugars, salts, amino acids, polymers and organic solvents with a variety of proteins, which resulted in mechanistic understanding on their protein stabilization and precipitation effects, the latter known as Hofmeister series. While such a study was then a pure academic research, rapid development of genetic engineering technologies and resultant biotechnologies made it a valuable knowledge in fully utilizing solvent additives in manipulation of protein solution, including column chromatography.

scholarly journals Mapping the Sharing Economy in China

2020 ◽  
Vol 12 (16) ◽  
pp. 6333
Author(s):  
Chan Liu ◽  
Raymond K. H. Chan ◽  
Maofu Wang ◽  
Zhe Yang
Keyword(s):  
Global Economy ◽  
Rapid Development ◽  
Sharing Economy ◽  
Essential Elements ◽  
Mobile Internet ◽  
Internet Technology ◽  
Short Term ◽  
Bona Fide ◽  
The Government ◽  
Idle Capacity

Harnessing the rapid development of mobile internet technology, the sharing economy has experienced unprecedented growth in the global economy, especially in China. Likely due to its increasing popularity, more and more businesses have adopted this label in China. There is a concern as to the essential meaning of the sharing economy. As it is difficult to have a universally accepted definition, we aim to map the sharing economy and demystify the use of it in China in this paper. We propose seven organizing essential elements of the sharing economy: access use rights instead of ownership, idle capacity, short term, peer-to-peer, Internet platforms mediated, for monetary profit, and shared value orientation. By satisfying all or only parts of these elements, we propose one typology of sharing economy, and to differentiate bona fide sharing economy from quasi- and pseudo-sharing economy. Finally, there are still many problems that need to be solved urgently in the real sharing economy from the perspective of the government, companies and individuals.

scholarly journals Librarians participation in professional development workshops using Zoom in Nigeria

2021 ◽  
pp. 026666692110267
Author(s):  
Ifeanyi Adindu Anene ◽  
Victor Okeoghene Idiedo
Keyword(s):  
Professional Development ◽  
Teaching And Learning ◽  
Survey Method ◽  
Online Questionnaire ◽  
Power Outage ◽  
Network Failures ◽  
Zoom In

The purpose of this study is to investigate the extent to which librarians in Nigeria engaged in professional development workshops during the COVID-19 era. The study adopted a survey method using an online questionnaire. Factors such as saving money, the free nature of workshops, eliminating travel risk, in the comfort of the home, and providing an opportunity for all were mentioned as the benefits of participating in online workshops using Zoom. Buying data bundle, lack of computer/Android phone/smartphone, ignorance or lack of awareness of up-coming workshops, lack of time, power outage, nonchalant attitude towards technology, and network failures were identified as challenges of participation. The Zoom platform can be adopted for organizing workshops and meetings, and for teaching and learning in the post COVID-19 era.

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