Enjoyable queuing and waiting time

2017 ◽  
Vol 28 (2) ◽  
pp. 543-566 ◽  
Author(s):  
Chih-Chin Liang
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Waiting Time ◽  
Structural Equation ◽  
Group Analysis ◽  
Customer Experience ◽  
Consumer Electronics ◽  
Equation Modeling ◽  
Queuing Model ◽  
Customer Perceptions

Time theory studies abstractly argue that, depending on the customer experience, time spent waiting may be positive, negative, or even neutral, and it can affect the perceived passing of time and enjoyment of the overall customer experience. However, a company can manipulate customer perceptions of waiting time. Positive perceptions of waiting time can then be used for marketing purposes. Customer perceptions of waiting time can be reduced by making the queuing process enjoyable, by improving the waiting environment, and by making promotional activities enjoyable. To validate the aforementioned factors and develop the enjoyable queuing model, this study surveyed 1571 customers queuing at service companies in Taiwan, including 409 customers of upscale restaurants, 430 customers of restaurants, 439 customers of food stands, and 293 customers queuing at consumer electronics shops to purchase newly released iPhones. The applicability of the enjoyable queuing model was evaluated by partial least squares structural equation modeling, and group differences were evaluated by partial least squares multi-group analysis. The analytical results for each case and managerial implications are presented.

scholarly journals Applying the Theory of Planned Behavior to Examine Pro-Environmental Behavior: The Moderating Effect of COVID-19 Beliefs

2020 ◽  
Vol 12 (24) ◽  
pp. 10556
Author(s):  
Caterina Lucarelli ◽  
Camilla Mazzoli ◽  
Sabrina Severini
Keyword(s):  
Climate Change ◽  
Theory Of Planned Behavior ◽  
Least Squares ◽  
Partial Least Squares ◽  
Planned Behavior ◽  
Structural Equation ◽  
Environmental Behavior ◽  
Group Analysis ◽  
Policy Implications ◽  
Equation Modeling

The COVID-19 pandemic and climate change issues present evident interdependencies which justify the spread of connected beliefs. We examine possible changes in individuals’ pro-environmental behavior in light of this pandemic, using the Theory of Planned Behavior (TPB) framework. A questionnaire survey was submitted to the same sample of individuals, before and during the pandemic. Our evidence, based on Partial Least Squares Structural Equation Modeling (PLS-SEM), shows that the COVID-19 pandemic has not led to a weakening in TPB construct relationships, or in related Pro-Environmental Behavior (PEB). Conversely, through our Partial Least Squares-Multi-Group Analysis (PLS-MGA), we show that individuals with greater awareness of interdependencies between the COVID-19 and climate change exhibit both higher Intention and reinforced Pro-Environmental Behaviors. This finding reveals interesting policy implications in terms of innovative behavioral drivers that should be employed to steer public support towards climate-oriented initiatives.

scholarly journals Investigation of the Relationship between the Perceived Public Transport Service Quality and Satisfaction: A PLS-SEM Technique

2021 ◽  
Vol 13 (23) ◽  
pp. 13018
Author(s):  
Karzan Ismael ◽  
Szabolcs Duleba
Keyword(s):  
Service Quality ◽  
Least Squares ◽  
Partial Least Squares ◽  
Public Transport ◽  
Public Transportation ◽  
Structural Equation ◽  
Group Analysis ◽  
Equation Modeling ◽  
Private Vehicle ◽  
Significant Difference

Public transportation (PT) service quality is recognized as a cornerstone of infrastructure development in many countries. Understanding the satisfaction level of public transport users towards provided service quality is vital. However, there is still a lack of research to identify the specific relationship between the experience of service quality and private vehicle (PV) users’ satisfaction. Therefore, this paper aimed to examine the different satisfaction attributes of PV users due to the COVID-19 pandemic and to make possible suggestions to policymakers on how to adapt to these changed attitudes. The paper highlights that some satisfaction issues became more significant, while the importance of others was mitigated due to the unusual circumstances. In this study, variance-based Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to test the proposed hypotheses. Further, Partial Least Squares Multi-Group Analysis (PLS-MGA) was conducted for investigating the perception of age and gender groups on the basis of gap analysis. An online panel and printed questionnaire survey were used to collect data in Budapest, Hungary in October and November 2020 during COVID-19 from the perception of 100 PV users. The findings show that perceived service quality and accessibility are statistically significant in the formation of PV users’ satisfaction but safety and security were not significantly related to satisfaction. Additionally, results from PLS-MGA reveal that there was a significant difference among gender and age groups in achieving satisfaction associated with safety and security. The conclusions of this study are not only beneficial for the theory of this field but also contribute to practice for policymakers in terms of providing better service with specific identification of how to encourage more private vehicle users to use public transportation.

scholarly journals eWOM in C2C Platforms: Combining IAM and Customer Satisfaction to Examine the Impact on Purchase Intention

2021 ◽  
Vol 16 (5) ◽  
pp. 1612-1630
Author(s):  
Salvador Bueno ◽  
M. Dolores Gallego
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Purchase Intention ◽  
Structural Equation ◽  
Source Credibility ◽  
Positive Impact ◽  
Equation Modeling ◽  
Research Model ◽  
Argument Quality ◽  
The Impact

This study is focused on communications that come from consumer-to-consumer (C2C) ecommerce relationships. This topic is directly associated with the electronic word-of-mouth (eWOM) phenomenon. eWOM is related to the set of positive or negative opinions made by potential, actual, or former customers about a seller. The present study proposes a structural equation modeling with partial least squares (PLS-SEM) research model to analyze consumers’ opinions impact on attitude toward purchasing. This model is based on the Information Adoption Model (IAM) in combination with an ecommerce satisfaction perspective, comprising five constructs: (1) service quality, (2) ecommerce satisfaction, (3) argument quality, (4) source credibility and (5) purchase intention. The model was tested by applying the Smart Partial Least Squares (SmartPLS) software for which 116 effective data from customers of the Taobao C2C platform were used. The findings reveal that all of the defined relationships were supported, confirming the positive impact of all the proposed constructs on the purchase intention. In this respect, the findings suggest that C2C platforms should strengthen the analyzed connections to grow the business and to promote transactions. Finally, implications and limitations related to the explanatory capacity and the sample are identified.

scholarly journals PERBANDINGAN ANTARA UNWEIGHTED LEAST SQUARES (ULS) DAN PARTIAL LEAST SQUARES (PLS) DALAM PEMODELAN PERSAMAAN STRUKTURAL (STUDI KASUS MODEL ANALISIS PRESTASI BELAJAR MAHASISWA TAHUN PERTAMA PROGRAM STUDI S1 MATEMATIKA FMIPA-INSTUTUT PERTANIAN BOGOR)

2017 ◽  
Vol 2 (1) ◽  
pp. 21
Author(s):  
Muhammad Amin Paris
Keyword(s):  
Least Squares ◽  
Student Learning ◽  
Partial Least Squares ◽  
Structural Equation ◽  
Weighted Least Squares ◽  
Generalized Least Squares ◽  
Primary Data ◽  
Equation Modeling ◽  
Multivariate Techniques ◽  
Mathematics Students

Structural Equation Modeling (SEM) is one of multivariate techniques  that can estimates a series of interrelated dependence relationships from a number of endogenous and exogenous variables, as well as latent (unobserved) variables simultaneously. Estimation of Parameter methods that is often applied in SEM are Maximum Likelihood (ML), Weighted Least Squares (WLS), Unweighted Least Squares (ULS), Generalized Least Squares (GLS) and Partial Least Squares (PLS). This research aims to compare ULS method and PLS method in estimating parameter model of achievement of student learning in first year undergraduate Mathematics students, FMIPA, Bogor  Agricultural University ( IPB). This research use secondary and primary data which amounts to 112. The result of this research indicates that ULS method is more accurate than PLS methods. The analysis done with ULS method shows that motivation, capability and environmental had an effect to achievement of student learning.

scholarly journals A bibliometric study of global research activity in relation to the use of partial least squares for policy evaluation

2021 ◽  
pp. 49-54
Author(s):  
Rosanna Cataldo ◽  
Laura Antonucci ◽  
Corrado Crocetta ◽  
Maria Gabriella Grassia ◽  
Marina Marino
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Policy Evaluation ◽  
Structural Equation ◽  
Bibliometric Study ◽  
Equation Modeling ◽  
Path Modeling ◽  
Research Activity ◽  
Knowledge Database ◽  
Scopus Database

Structural equation modeling (SEM), especially partial least squares path modeling (PLS-PM) has become a mainstream method in many fields of research. In the last years it has been increasingly disseminated in a variety of disciplines. The researchers have been promoting this new statistical methods for the evaluation of policies. Generally, policy evaluation applies evaluation principles and methods to examine the content, implementation or impact of a policy. To better understand and characterize this trend, a bibliometric study of international papers on this subject has been developed in order to describe the use of SEM and PLS-PM approaches in the policy evaluation in the almost last 20 years. A total of 450 articles from 2000 to 2020 have been selected and analyzed in order to discover the research trends in this field and the main dimensions and words related to the terms “decision making” and “SEM-PLS” approach, that are most commonly employed in the scientific literature. The research has been conducted in theWeb of Science from ISI Web of Knowledge database and Scopus database, with the aim of identifying the major themes, authors, areas, types of the sources, titles, years of publication and countries of these publications, as well as the main themes related to the two topic analyzed

Partial least squares structural equation modeling of chemistry attitude in introductory college chemistry

2018 ◽  
Vol 19 (4) ◽  
pp. 1270-1286 ◽  
Author(s):  
James Ross ◽  
Leslie Nuñez ◽  
Chinh Chu Lai
Keyword(s):  
Structural Equation Modeling ◽  
Least Squares ◽  
Partial Least Squares ◽  
Structural Equation ◽  
At Risk Students ◽  
Affective Domain ◽  
Equation Modeling ◽  
College Chemistry ◽  
The Subject ◽  
Introductory College

Students’ decisions to enter or persist in STEM courses is linked with their affective domain. The influence of factors impacting students’ affective domain in introductory college chemistry classes, such as attitude, is often overlooked by instructors, who instead focus on students’ mathematical abilities as sole predictors of academic achievement. The current academic barrier to enrollment in introductory college chemistry classes is typically a passing grade in a mathematics prerequisite class. However, mathematical ability is only a piece of the puzzle in predicting preparedness for college chemistry. Herein, students’ attitude toward the subject of chemistry was measured using the original Attitudes toward the Subject of Chemistry Inventory (ASCI). Partial least squares structural equation modeling (PLS-SEM) was used to chart and monitor the development of students’ attitude toward the subject of chemistry during an introductory college chemistry course. Results from PLS-SEM support a 3-factor (intellectual accessibility,emotional satisfaction, andinterestandutility) structure, which could signal the distinct cognitive, affective, and behavioral components of attitude, according to its theoretical tripartite framework. Evidence of a low-involvement hierarchy of attitude effect is also presented herein. This study provides a pathway for instructors to identify at-risk students, exhibiting low affective characteristics, early in a course so that academic interventions are feasible. The results presented here have implications for the design and implementation of teaching strategies geared toward optimizing student achievement in introductory college chemistry.

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