Pengembangan model minat menggunakan airbnb dengan metode pls-sem = Development of intention to use airbnb model using pls-sem method

Bellina, Stella (2019) Pengembangan model minat menggunakan airbnb dengan metode pls-sem = Development of intention to use airbnb model using pls-sem method. Bachelor thesis, Universitas Pelita Harapan.

	Text (Title) Title.pdf Restricted to Repository staff only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (1MB)
Preview	Text (Abstract) Abstract.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (246kB) | Preview
Preview	Text (ToC) ToC.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (318kB) | Preview
Preview	Text (Chapter1) Chapter1.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (223kB) | Preview
	Text (Chapter2) Chapter2.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (499kB)
	Text (Chapter3) Chapter3.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (218kB)
	Text (Chapter4) Chapter4.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (568kB)
	Text (Chapter5) Chapter5.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (578kB)
	Text (Chapter6) Chapter6.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (166kB)
Preview	Text (Bibliography) Bibliography.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (255kB) | Preview
	Text (Appendices) Appendices.pdf Restricted to Repository staff only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (1MB)

Abstract

Sharing economy merupakan salah satu pasar peer-to-peer (P2P) yang terus berkembang dengan pesat. Salah satu platform sharing economy dalam bidang pariwisata dan perhotelan adalah Airbnb. Ketika konsumen menyewa akomodasi dengan Airbnb, banyak faktor yang harus dipertimbangkan oleh konsumen. Oleh karena itu, tujuan dari penelitian ini adalah menguji hubungan prediktif antar konstruk yang mempengaruhi minat konsumen dalam menyewa akomodasi melalui Airbnb. Pengujian dilakukan dengan metode PLS-SEM (Partial Least Squares-Structural Equation Modeling) karena PLS-SEM sangat tepat untuk penelitian yang bertujuan mengembangkan teori. Analisis PLS-SEM dilakukan dengan mengkonseptualisasi model, menentukan metoda analisis algoritma dan resampling, menggambar diagram jalur, dan mengevaluasi model. Sedangkan evaluasi model dilakukan dengan mengevaluasi model pengukuran dan struktural. Evaluasi model struktural dilakukan dengan melihat nilai R-square dan nilai T-value (harus >1,96) dari uji signifikansi. Pada penelitian ini dibuat model yang terdiri dari 13 variabel dan 14 hipotesis. Berdasarkan penelitian yang telah dilakukan dengan menggunakan data 48 responden, terdapat 5 hipotesis yang terbukti karena memiliki nilai T-value >1,96. Kelima hipotesis tersebut beserta dengan nilai T-value-nya adalah pemenuhan janji oleh Airbnb berpengaruh positif terhadap kepercayaan konsumen (7,086), kemudahan penggunaan aplikasi/website (4,735) dan fasilitas yang disediakan akomodasi Airbnb (7,715) berpengaruh positif terhadap perceive value, perceive value (3,897) dan pengalaman sebelumnya (3,095) berpengaruh positif terhadap minat konsumen menggunakan Airbnb. Karena hanya terdapat 5 hipotesis yang terbukti, diusulkan model baru yang mungkin dapat membuktikan lebih banyak hipotesis. Model usulan tersebut terdiri dari 12 variabel dan 11 hipotesis. Berdasarkan penelitian yang telah dilakukan, ditemukan bahwa terdapat 7 hipotesis yang terbukti dan memiliki nilai T-value >1,96, yaitu pemenuhan janji Airbnb bepengaruh positif terhadap kepercayaan konsumen pada Airbnb (6,935), kemudahan dalam menggunakan website/aplikasi (4,651) dan fasilitas yang disediakan akomodasi (7,862) berpengaruh positif terhadap perceive value, serta WoM (2,354), kepercayaan (2,527), perceive value (3,909), dan pengalaman sebelumnya (3,104) berpengaruh positif terhadap minat konsumen dalam menggunakan Airbnb. / Sharing economy is one of the peer-to-peer (P2P) markets that continues to grow rapidly. One of the sharing economy platforms in the tourism and hospitality sector is Airbnb. Compared to traditional electronic commerce, trading on Airbnb has more unique characteristics. When consumers rent accommodation through Airbnb, many factors must be considered. Therefore, the purpose of this study is to test the predictive relationships between constructs that influence consumer intention in renting accommodation through Airbnb, the test is carried out using the PLS-SEM (Partial Least Squares-Structural Equation Modeling) method because PLS-SEM is very suitable for research aimed at developing theory. PLS-SEM analysis is done by conceptualizing the model, determining the method of analysis algorithm and resampling, drawing path diagrams, and evaluating the model. While the model evaluation is done by evaluating the measurement and structural models. The purpose of structural model evaluation is to measure the relationship between constructs, where testing is done by looking at the R-square value and T-value (must be >1.96) from the significance test. In this study, a model consisting of 13 variables and 14 hypotheses was created. Based on the research that has been done using the data from 48 respondents, it’s found that there are 5 proven hypotheses because they have T-value >1.96. The five hypotheses along with their T-value are Airbnb’s promises fulfillment has a positive effect on consumer’s trust (7.086), user friendly application/website has a positive effect on perceive value (4.735), facilities provided by Airbnb accommodation have a positive effect on perceive value (7.715), perceive value has a positive effect on consumer’s intention to use Airbnb (3.897) and previous experience has a positive effect on consumer’s intention to use Airbnb (3.095). Because there are only 5 proven hypotheses, new models that might prove more hypotheses are proposed. The proposed model consists of 12 variables and 11 hypotheses. Based on the research that has been done, it was found that there are 7 proven hypotheses which have T-value >1.96, those are Airbnb’s promises fulfillment has a positive effect on consumer’s trust (6.935), user friendly website/application (4.651) and facilities provided by Airbnb accommodation (7.862) have a positive effect on perceive value, and WoM (2.354), trust (2.527), perceive value (3.909), and previous experience (3.104) have a positive effect on consumer’s intention to use Airbnb.

Actions (login required)

View Item