Search results

The importance of smart tourism technologies (STTs) has been rising recently, but how STTs are related to tourists' psychological well-being has got little attention. The study intends to show how STTs increase tourists' psychological well-being by capitalizing on the theory of Tourism 4.0. The study investigates the associations between the factors of STTs with the perceived benefit and, subsequently, perceived benefit with the psychological well-being of tourists. Moreover, this study also examines the moderating impact of a growth mindset (GM) between perceived benefits (PB) and tourists' psychological well-being (TPW) in the tourism industry.

Using a structured questionnaire, 243 responses were collected through the convenience sampling method. Partial least square structural equation modeling (PLS-SEM) was used for the analysis.

Findings show that automation, security/privacy concerns, information accuracy, and personalization are significantly related to the PB of tourists. The results also confirm that a GM moderates the relationship between PB and TPW.

The results show the social and managerial importance of the perspective of tourism in developing countries. Based on the tourism 4.0 concept, this study presents a theoretical contribution by expanding practical information regarding the link between STTs and psychological well-being. Moreover, the study shows some directions to the tour operator about improving PB and psychological well-being. The notion of tourism 4.0 is a new paradigm that seeks to unlock the psychological well-being of visitors through the hyper-interconnectedness of humans and technologies.

This study contributes to prior research on technology-based tourism by exploring the uncharted STT variables, PB, GM and psychological well-being. Moreover, the study makes an empirical effort to conceptualize the tourism 4.0 concept on the proposed relationships. Tourist firms should focus on implementing this theory to develop their business.

By applying the theory of consumption value as a conceptual framework, this study aims to investigate the impact of consumption values, namely, functional value (FV), conditional value (CV), social value (SV), emotional value (EV) and epistemic value (EPV) on attitude and repurchase intention in the Halal cosmetics context.

Considering the increasing transmission cases of the new variant of COVID-19, online questionnaires were distributed to 233 Muslim consumers in Indonesia to collect data. The hypotheses were then validated using partial least square-structural equation modeling.

The results showed that FV, CV, SV, EV and EPV positively affect consumer attitudes toward Halal cosmetics. The attitude toward Halal cosmetics also positively affects Halal cosmetics repurchase intention.

Two limitations are recognized for future studies, including the generalizability in consumer generation and the obscurity of what predictors determine consumer consumption values.

Halal cosmetics marketers must ensure that the positioning strategy and the value proposition contain elements of consumption values (functional, conditional, social, emotional and epistemic). In addition, an appropriate marketing communication strategy needs to be developed to strengthen consumer awareness and increase consumer knowledge regarding the values offered related to Halal cosmetics.

To the best of the authors’ knowledge, this study is the first attempt to comprehensively address the theory of consumption values by considering all consumption values to understand consumer repurchase intentions in the context of Halal cosmetics.

Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and improper process design. This study aims to identify the pathways for improving lifting performance to advance lean construction of prefabricated buildings.

This study developed a methodological framework that integrates the discrete event simulation method, the elimination, combination, rearrangement and simplification (ECRS) technique and intelligent optimization tool. Two schemes of precast wall lifting, namely, the enterprise's business as usual (BAU) and enterprise-leading (EL) schemes, were set to benchmark lifting performance. Furthermore, a best-practice (BP) scheme was modeled from the perspective of lifting activity ECRS and resource allocation for performance optimization.

A real project was selected to test the effect of the methodological framework. The results showed that compared with the EL scheme, the BP scheme reduced the total lifting time (TLT) by 6.3% and mitigated the TLT uncertainty (the gap between the maximum and minimum time values) by 20.6%. Under the BP scheme, increasing the resource inputs produces an insignificant effect in reducing TLT, i.e. increasing the number of component operators in the caulking subprocess from one to two only shortened the TLT by 3.6%, and no further time reduction was achieved as more component operators were added.

To solve non-lean problems associated with prefabricated building construction, this study provides a methodological framework that can separate a typical precast wall lifting process into fine-level activities. Besides, it also identifies the pathways (including the learning effect mitigation, labor and machinery resource adjustment and activities’ improvement) to reducing TLT and its uncertainty.