Brand Attachment, Tour Leader Attachment, and Behavioral Intentions of Tourists

2015 ◽  
Vol 42 (3) ◽  
pp. 365-391 ◽  
Author(s):  
Chang-Hua Yen ◽  
Chien-Yu Chen ◽  
Jui-Chang Cheng ◽  
Hsiu-Yu Teng
Keyword(s):  
Attachment Theory ◽  
Travel Behavior ◽  
Behavioral Intentions ◽  
Perceived Value ◽  
Future Research ◽  
Travel Agency ◽  
Brand Attachment ◽  
Travel Decision ◽  
High Level ◽  
Customer Trust

The brand of a travel agency and the tour leader play critical roles in travel decision making. Attachment theory has recently been extended to the domain of travel behavior. However, little academic attention has been paid to travel agency brand and tour leader attachment. The purpose of this study is to examine the effect of brand attachment and tour leader attachment on tourists’ behavioral intentions and to clarify the roles of perceived value and customer trust. The results indicate that brand attachment has an indirect effect on behavioral intentions through perceived value. Tour leader attachment also has both direct and indirect positive influences on tourists’ behavioral intentions. Finally, the influences of brand attachment and tour leader attachment on perceived value are stronger among customers with a high level of trust than among those with a low level of trust. The implications of these findings and future research are subsequently discussed.

scholarly journals The Effect Of The Economic Downturn On The Way People Travel For Leisure And For Business: The Case Of Spain

2015 ◽  
Vol 19 (2) ◽  
pp. 95
Author(s):  
Ramon Diaz-Bernardo
Keyword(s):  
Decision Making ◽  
Travel Behavior ◽  
Future Research ◽  
Economic Downturn ◽  
Business Travelers ◽  
Leisure Travelers ◽  
Travel Decision ◽  
The Way ◽  
Decision Making Criteria

This study contributed to existing literature by investigating how business and leisure travelers make travel-related decisions. By developing scales to measure travel behavior and travel decision-making criteria, this study contributes to the literature on business travelers vs. leisure travelers. Finally, this study proves a convergence in the behavior of business travelers vs. leisure travelers, in their motivations and decision-making criteria, and provides possible explanations for this trend and avenues for potential future research lines.

scholarly journals Psychedelic Science of Spirituality and Religion: An Attachment-Informed Agenda Proposal

2021 ◽  
Author(s):  
Aaron D. Cherniak ◽  
Joel Gruneau Brulin ◽  
Mario Mikulincer ◽  
Sebastian Ostlind ◽  
Robin Carhart-Harris ◽  
...  
Keyword(s):  
Attachment Theory ◽  
Attachment Security ◽  
Future Research ◽  
Religion And Spirituality ◽  
Relational Experiences ◽  
Internal Working ◽  
Spirituality And Religion ◽  
High Level ◽  
Role Of Religion

In this paper, we set an agenda for a psychedelic science of spirituality and religion, based on a synthesis of attachment theory with the Relaxed Beliefs Under pSychedelics (REBUS) model. Attachment theory proposes that people develop internal working models (IWMs) of interactions with others from their relational experiences with caregivers. Such IWMs then function as high-level priors enabling people, for better and for worse, to predict and organize their interpersonal and religious/spiritual relationships. One mechanism by which efficacious psychedelic interventions may work is by relaxing the grip of rigid, defensive priors (e.g., insecure IWMs with regard to others and God), further amplified by corrective relational experiences with the therapist, God, or others. We outline three key proposals to steer future research. First, individual differences in attachment security predict the phenomenology and integration of psychedelic experiences. Second, efficacious psychedelic therapy facilitates increased attachment security as a clinically relevant outcome. Third, attachment-related dynamics (e.g., a sense of connection to others and God, alleviation of attachment-related worries and defenses) are process-level mechanisms involved in the clinical utility of psychedelic treatment. Finally, we discuss the role of religion and spirituality in psychedelic experiences from an attachment perspective.

scholarly journals Psychedelic Science of Spirituality and Religion: An Attachment-Informed Agenda Proposal

2021 ◽  
Author(s):  
Aaron D. Cherniak ◽  
Joel Gruneau Brulin ◽  
Sebastian Ostlind ◽  
Mario Mikulincer ◽  
Robin Carhart-Harris ◽  
...  
Keyword(s):  
Attachment Theory ◽  
Attachment Security ◽  
Future Research ◽  
Religion And Spirituality ◽  
Relational Experiences ◽  
Internal Working ◽  
Spirituality And Religion ◽  
High Level ◽  
Role Of Religion

In this paper, we set an agenda for a psychedelic science of spirituality and religion, based on a synthesis of attachment theory with the Relaxed Beliefs Under pSychedelics (REBUS) model. Attachment theory proposes that people develop internal working models (IWMs) of interactions with others from their relational experiences with caregivers. Such IWMs then function as high-level priors enabling people, for better and for worse, to predict and organize their interpersonal and religious/spiritual relationships. One mechanism by which efficacious psychedelic interventions may work is by relaxing the grip of rigid, defensive priors (e.g., insecure IWMs with regard to others and God), further amplified by corrective relational experiences with the therapist, God, or others. We outline three key proposals to steer future research. First, individual differences in attachment security predict the phenomenology and integration of psychedelic experiences. Second, efficacious psychedelic therapy facilitates increased attachment security as a clinically relevant outcome. Third, attachment-related dynamics (e.g., a sense of connection to others and God, alleviation of attachment-related worries and defenses) are process-level mechanisms involved in the clinical utility of psychedelic treatment. Finally, we discuss the role of religion and spirituality in psychedelic experiences from an attachment perspective.

What Can We Learn From Factorial Surveys About Human Behavior?

Methodology ◽  
2019 ◽  
Vol 15 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Knut Petzold ◽  
Tobias Wolbring
Keyword(s):  
Social Sciences ◽  
Behavioral Intentions ◽  
Actual Behavior ◽  
Full Time ◽  
Factorial Survey ◽  
Survey Experiment ◽  
Intended Behavior ◽  
The Social ◽  
Survey Experiments ◽  
High Level

Abstract. Factorial survey experiments are increasingly used in the social sciences to investigate behavioral intentions. The measurement of self-reported behavioral intentions with factorial survey experiments frequently assumes that the determinants of intended behavior affect actual behavior in a similar way. We critically investigate this fundamental assumption using the misdirected email technique. Student participants of a survey were randomly assigned to a field experiment or a survey experiment. The email informs the recipient about the reception of a scholarship with varying stakes (full-time vs. book) and recipient’s names (German vs. Arabic). In the survey experiment, respondents saw an image of the same email. This validation design ensured a high level of correspondence between units, settings, and treatments across both studies. Results reveal that while the frequencies of self-reported intentions and actual behavior deviate, treatments show similar relative effects. Hence, although further research on this topic is needed, this study suggests that determinants of behavior might be inferred from behavioral intentions measured with survey experiments.

Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Pablo Livacic-Rojas ◽  
Guillermo Vallejo ◽  
Paula Fernández ◽  
Ellián Tuero-Herrero
Keyword(s):  
Repeated Measures ◽  
Statistical Power ◽  
Mixed Model ◽  
Covariance Structure ◽  
Simulation Method ◽  
Future Research ◽  
Repeated Measures Design ◽  
Fixed And Random Effects ◽  
Split Plot ◽  
High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

Children's Perceived Value: Conceptualization, Scale Development, and Validation

2020 ◽  
Author(s):  
Janine Williams ◽  
A Gazley ◽  
N Ashill
Keyword(s):  
New York ◽  
Perceived Value ◽  
Internal Consistency Reliability ◽  
Future Research ◽  
New York University ◽  
Consumer Decisions ◽  
Managerial Implications ◽  
Stage Process ◽  
Development And Validation ◽  
Value Measure

© 2020 New York University Perceived value among children is an important concept in consumer decisions, yet surprisingly no research has operationalized value for this consumer group. To address this omission, and following the guidelines of DeVellis (2016), this investigation reports the findings of a seven-stage process to develop a valid and reliable instrument for measuring perceived value among children aged 8–14 years. Value for children is conceptualized as a multidimensional construct capturing perceptions of what is received and what is given up, which differs from adult measures in terms of its composition and complexity. A 24-item scale is developed that shows internal consistency, reliability, construct validity, and nomological validity. We also demonstrate the validity of the new scale beyond an existing adult perceived value measure. Directions for future research and managerial implications of the new scale for studying children's consumer behavior are discussed.

Website Information Security and Privacy Concerns in 4IR: The Moderating Role of Trust in B2C e-Commerce

10.29007/jlq6 ◽  
2019 ◽  
Author(s):  
Thabang Mofokeng
Keyword(s):  
South Africa ◽  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Success Factors ◽  
Industrial Revolution ◽  
Emerging Market ◽  
Security And Privacy ◽  
Future Research ◽  
Privacy And Security ◽  
Customer Trust

The technology devices introduced in recent years are not only vulnerable to Internet risks but are also unable to elevate the growth of B2C e-commerce. These concerns are particularly relevant today, as the world transitions into the Fourth Industrial Revolution. To date, existing research has largely focused on obstacles to customer loyalty. Studies have tested e-commerce models guided by the establishment of trusting, satisfied and loyal consumers in various international contexts. In South Africa, however, as an emerging market, there has been limited research on the success factors of online shopping.This study examines the influence of security and privacy on trust, seen as a moderator of customer satisfaction, which in turn, has an effect on loyalty towards websites. Based on an exhaustive review of literature, a conceptual model is proposed on the relationships between security and privacy on the one hand, and customer trust, satisfaction and loyalty on the other. A total of 250 structured, self-administered questionnaires was distributed to a purposively selected sample of respondents using face-to-face surveys in Johannesburg, South Africa. A multivariate data analysis technique was used to draw inferences from the data. With an 80.1% response rate, the findings showed that privacy and security do influence customer trust; security strongly influences customer trust and weakly influences satisfaction. In South Africa, customer loyalty towards websites is strongly determined by satisfaction and weakly determined by trust. Trust significantly moderates the effect of customer satisfaction on loyalty. The study implications and limitations are presented and future research directions are suggested.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

scholarly journals Opportunities and Challenges of Green-Lean: An Integrated System for Sustainable Construction

2020 ◽  
Vol 12 (11) ◽  
pp. 4460 ◽  
Author(s):  
Mohammadsoroush Tafazzoli ◽  
Ehsan Mousavi ◽  
Sharareh Kermanshachi
Keyword(s):  
Cost Savings ◽  
Integrated Approach ◽  
Integrated System ◽  
Waste Minimization ◽  
Sustainable Construction ◽  
Future Research ◽  
Safety Improvement ◽  
The Individual ◽  
High Level ◽  
Industry Professionals

Although the two concepts of lean and sustainable construction have been developed due to different incentives, and they do not pursue the same exact goals, there exists considerable commonality between them. This paper discusses the potentials for integrating the two approaches and their practices and how the resulting synergy from combining the two methods can potentially lead to higher levels of fulfilling the individual goals of each of them. Some limitations and challenges to implementing the integrated approach are also discussed. Based on a comprehensive review of existing papers related to sustainable and lean construction topics, the commonality between the two approaches is discussed and grouped in five categories of (1) cost savings, (2) waste minimization, (3) Jobsite safety improvement, (4) reduced energy consumption, and (5) customers’ satisfaction improvement. The challenges of this integration are similarly identified and discussed in the four main categories of (1) additional initial costs to the project, (2) difficulty of providing specialized expertise, (3) contractors’ unwillingness to adopt the additional requirements, and (4) challenges to establish a high level of teamwork. Industry professionals were then interviewed to rank the elements in each of the two categories of opportunities and challenges. The results of the study highlight how future research can pursue the development of a new Green-Lean approach by investing in the communalities and meeting the challenges of this integration.

scholarly journals Time Granularity Impact on Propagation of Disruptions in a System-of-Systems Simulation of Infrastructure and Business Networks

2021 ◽  
Vol 18 (8) ◽  
pp. 3922
Author(s):  
Mateusz Iwo Dubaniowski ◽  
Hans Rudolf Heinimann
Keyword(s):  
Recovery Time ◽  
System Of Systems ◽  
Future Research ◽  
Business Networks ◽  
Simulation Experiments ◽  
Huge Impact ◽  
High Level ◽  
Systems Simulation ◽  
Different Characteristics ◽  
The Impact

A system-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a high level architecture (HLA) simulation of three networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.

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