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Prior research in tourism and hospitality domain calls for closer attention to model specification when using partial least square-structural equation modeling (PLS-SEM), including the choice of software and algorithm for PLS model estimation. This paper aims to illustrate the significance of choosing appropriate algorithms for testing the nature of relationships by comparing findings using two different PLS-SEM software packages.

Using a field experiment, relationships between visual servicescape aesthetics and affective responses are conceptualized based on literature in environmental psychology and marketing domains. With photographic surrogates as stimuli in two different hospitality service contexts – spa and upscale restaurant – data are collected from 350 respondents.

By comparing results of SmartPLS 3.2 and WarpPLS 5.0 software and theoretical understanding from environmental psychology literature, it is illustrated that the results and their interpretations may not be in line with theory if model specifications are not correctly implemented and are not addressed through usage of software with a relevant algorithm to test them.

The study highlights the implications for model specification issues such as type of variables and nature of relationships that tourism and hospitality researchers often face and also how use of appropriate algorithms can overcome limitations of model testing for complex models and provide empirical rigor to support theory.

本论文使用两种不同的PLS-SEM处理软件来测试理论模型。通过解析模型设定参数问题, 特别是通过结构关系本性分析, 本论文指出选择合适的软件测试模型在酒店旅游领域的PLS研究中是非常关键的。

本论文借助图像拍摄手段采用实验的采样方式, 在两个不同的酒店服务场所—按摩和高档餐厅—搜集350份数据。本论文采用Smart PLS 3.2 和Warp PLS 5.0 软件来测试PLS-SEM。 这两款软件支持线性和非线性理论关系的比较。

通过Smart PLS 3.2 和Warp PLS 5.0 软件得出的报告结果分析, 不同软件处理PLS得出的结果可能有偏差, 而且会不符合理论设定。如果模型设定参数不正确, 通过使用合适的PLS-SEM软件和相关的数据分析加以辅助, 可能会解决参数不正确的问题。

本论文的比较分析结果可能会帮助到酒店和旅游领域的研究者们, 在做对有关PLS-SEM软件选择的时候, 哪些软件可以更加合适的测试模型有着参考意义。

本论文重点指出了模型设定参数的相关问题, 比如旅游酒店领域常见的变量种类和关系属性等。本论文还研究了如何选择合适的数据分析方法来克服测试复杂模型时的限制, 并且提供实践结果来支撑理论。

The aim of this study is to comprehend the behavioural intention of females' perception toward smart healthcare technology. The study also examines the moderation effect of social influences between perceived smart healthcare technology and perceived usefulness among female users.

To test the model, this study collected data from female respondents (n = 913) responses. The data were analyzed by structural equation modeling (SEM) using Smart-PLS 3.2. To complement the findings from structural equation modeling, the study also conducted a post-hoc test via experimental research design. The authors also applied a t-test and PROCESS macro analysis to re-confirm the relationship mentioned above.

The findings revealed that perceived ease of use significantly mediates the relationship between females' perceived smart healthcare technology and intention to use. The findings also show that social influence moderates between smart healthcare technology and the perceived usefulness relationship.

Social influence is one of the major issues while adopting smart healthcare technology because the respondents perceived that they are accustomed to the technologies related to smart health once their surroundings and social environment influence them.

The current study is a pioneer in the context of a developing country and unique in that it makes two contributions: it extends previous research on smart health technology adoption in the healthcare business by considering females, and it gives a broad knowledge of the female healthcare consumers from emerging nations which can be useful for developing technology-driven healthcare services strategies.

Recently, smart retail technology has emerged as an innovative technology that can improve consumer motivation and behavior in smart stores. Although prior studies have investigated factors influencing the adoption of smart retail technology, to the authors’ knowledge, no previous work has investigated the determinants of purchase intentions. The ultimate goal for retailers should be shopping, not technology adoption. However, traditional brick-and-mortar stores and theories focus on investing in utilitarian factors to attract customers. This study proposes that hedonic motivation should also play an important role, as new technologies may arouse customer curiosity and increase pleasant experiences. Therefore, the purpose of this study is to explore utilitarian and hedonic motivations that promote customers' purchase; intentions in smart stores. Specifically, the authors address the research questions: (1) What are the constituents of utilitarian motivation? (2) What are the constituents of hedonic motivation? (3) What are the factors that influence customers' purchase intentions? By answering the questions, the findings help retailers understand how to motivate customers to make purchases in smart stores.

To investigate consumer motivation and purchase intentions, the customers who made purchases in smart stores were invited to participate in the questionnaire survey. This study collected 307 data in smart retail settings. Partial least squares (PLS) software was used to assess the reliability, validity and the paths and significance of all hypotheses.

The results show that perceived ease of use directly and indirectly influences purchase intentions through utilitarian and hedonic motivations. Utilitarian motivation is a formative second-order construct comprised of merchandise price, merchandise quality, location convenience, speed of shopping and product recommendation. Hedonic motivation is a reflective second-order construct composed of control, curiosity, joy, focused immersion and temporal dissociation. The findings provide insights into the successful implementation of smart retail technology and offer retailers to better understand consumer motivation and purchase intentions in smart stores.

This study is the first to examine how consumer motivation influences purchase intentions in smart stores. This study posits and verifies the extended hedonic system acceptance model (HSAM) to explain consumer motivation for shopping in smart retail settings. This study also models the original first-order utilitarian and hedonic constructs as second-order formative and reflective constructs, respectively. Utilitarian motivation regarding functional benefits is developed based on the 5Ps of marketing and situational factors, while hedonic motivation regarding pleasant experiences is proposed based on cognitive absorption.

Despite the enormous benefits, smart homes (SHs) are still not widely adopted by residents in China. Furthermore, research on the intention to use SHs has overlooked the role of family factors. Thus, this study aims to propose a new research model to examine the impact of family factors on the usage intention (UI) of SHs.

This study collected 265 valid data from potential users of SHs in China using a convenience sampling method. The PLS-SEM method was applied to test the research model and related hypotheses.

The empirical results confirm the mediating role of optimism (OP) in perceived family support (PFS)/perceived family trust (PFT) and attitude (AT). Unsurprisingly, the results validated the relationship between perceived usefulness (PU), attitude (AT) and UI of SHs through TAM theory. Besides, this study also identified the moderating effect of perceived risk (PR) between AT and UI.

To improve SH adoption, practitioners should focus on family factors and utilize family influence to promote the spread of smart home reputation. Besides, SH practitioners should enhance user trust and reduce perceived risks through technological upgrades and security measures.

Based on the Social Impact Theory and Technology Acceptance Model (TAM), this study is an empirical attempt to explore the impact of family factors on the intention to use SHs, expanding the research on smart home adoption.

This research aims to reveal the working principles of the decision mechanism that affects the use of neural implant acceptance and to discuss the leading role of digital literacy in this mechanism. In addition, it aimed to examine the theoretical connections of the research model with the conservation of resources (COR) and technology acceptance model (TAM) theories in the discussion.

The authors collected data from 300 individuals in an organization operating in the health sector and analyzed the data in the Smart Partial Least Squares (PLS) 3.3.3. This way, the authors determined the relationships between the variables, the path coefficients and the significance levels.

The study has found that strong digital literacy skills are linked to positive emotions and attitudes. Additionally, maintaining a positive mindset can improve one's understanding of ethics. Ethical attitudes and positive emotions can also increase the likelihood of adopting neural implants. Therefore, it is crucial to consider both technical and ethical concerns and emotions when deciding whether to use neural implants.

The research results determined the links between the cognitive, emotional and ethical factors in the cyborgization process of the employees and gave original insights to the managers and employees.

1. Determination of antecedents that affect individuals' acceptance of neural implant use.

2. Application to 300 individuals working in a health organization.

3. Path analysis using the least squares method via Smart PLS 3.3.3

4. Significant path coefficients among digital literacy, positive emotions, attitude, ethical understanding and acceptance of neural implant use.

Determination of antecedents that affect individuals' acceptance of neural implant use.

Application to 300 individuals working in a health organization.

Path analysis using the least squares method via Smart PLS 3.3.3

Significant path coefficients among digital literacy, positive emotions, attitude, ethical understanding and acceptance of neural implant use.

The purpose of this paper is to develop a structural relationship model to study the relationship between causes and effects of poor communication and information exchange in construction projects using Smart-PLS.

The first method of this research is to identify the causes and effects factors of poor communication in construction projects from the extant of literature. The data used to develop the model was collected using a questionnaire survey, which targeted construction practitioners in the Malaysian construction industry. A five-point Likert type scale was used to rate the significance of the factors. The factors were classified under their relevant construct/group using exploratory factor analysis. A hypothetical model was developed and then transformed into Smart-PLS in which the hypothetical model suggested that each group of the cause factors has a direct impact on the effect groups. The hypothesis was tested using t-values and p-values. The model was assessed for its inner and outer components and achieved the threshold criterion. Further, the model was verified by engaging 14 construction experts to verify its applicability in the construction project setting.

The study developed a structural equation model to clarify the relationships between causes and effects of poor communication in construction projects. The model explained the degree of relationships among causes and effects of poor communication in construction projects.

The published academic and non-academic literature introduced many studies on the issue of communication including the definitions, importance, barriers to effective communication and means of poor communication. However, these studies ended up only on the general issue of communication lacking an in-depth investigation of the causes and effects of poor communication in the construction industry. The study implemented advanced structural modeling to study the causes and effects. The questionnaire, the data and concluding results fill the identified research gap of this study. The addressed issue is also of interest because communication is considered one of the main knowledge areas in construction management.

This study examines the main factors influencing banking customers' behavior toward smart banking services (SBS) adoption in Pakistan. This study extends the unified theory of acceptance and use of technology (UTAUT2) by integrating information privacy concern and big brother effect into an overarching conceptualization.

This study adopts theoretical constructs from the related literature and develops hypotheses. An analysis of 385 banking customers was performed using partial least squares structural equation modeling (PLS-SEM).

The results show that most predictors of behavioral intention, including facilitating conditions, effort expectancy, habit, performance expectancy, hedonic motivation (except for social influence and price value), big brother effect and perceived information privacy concern are significant. Indeed, all predictors of use behavior are also significant. Gender and age differences between individuals further moderate the relationship between UTAUT2 constructs. Moreover, information privacy concern mediates the relationship between big brother effect and behavioral intention.

This cross-sectional study focused only on Pakistan as a developing country, which limits the generalizability of the results.

The roles of social influence and price value must be strengthened by employing marketing strategies and personalized communication. Banks should offer incentives and rewards to customers who recommend SBS to friends and family members. In addition, banks must consider the price factor when offering these services to increase their market share.

This study contributes to the field of technology adoption by providing a unique perspective of SBS adoption in Pakistan. This empirical study is the first to extend the UTAUT2 model by integrating information privacy concern and big brother effect to assess SBS acceptance and use behavior. This study examines SBS adoption issues at the national level, especially in Pakistan.

Bicycle sharing offers a novel way to create smart and sustainable mobility solutions for the future. The purpose of this study is to draw on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework for identifying the factors necessary to predict bike-sharing intention among users in India.

Data were collected through a questionnaire distributed across four major cities in India, and 515 responses were analyzed. A sequential approach was employed to analyze the data using Partial Least Square–Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA).

The findings from PLS analysis revealed that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation and price value are the salient variables that affect users' intentions to participate in bike sharing. In addition, based on fsQCA, six configurations of causal conditions are presented as intermediate solutions that produce the same results. Although antecedent conditions, such as habit and social influence, had an insignificant effect on individuals' BSI, they create conditions sufficient to encourage users' participation in bike sharing in combination with other variables.

A few limitations of this research and the implications of the findings in terms of theory and policy implications are also discussed.

The reported study is one of the earliest to explain bike-sharing adoption in India using the UTAUT 2 model.

This study aims to investigate technology-based health and safety (H&S) management to control the spread of disease on construction sites using a partial least squares structural equation modelling (PLS-SEM) approach.

An extensive literature review is conducted to develop a conceptual framework. The variables identified from the literature review are included in a cross-sectional survey which gathered a total of 203 valid feedback. The variables for challenges are grouped under their relevant construct using exploratory factor analysis. Then, a hypothesized model is developed for PLS-SEM analysis using Smart PLS software. Later, the outcome of the model is further validated by nine construction experts using a semi-structured questionnaire survey.

The results rationalized the relationships between the COVID-19 H&S measures, challenges in implementing COVID-19 H&S measures on construction sites and the innovative technologies in transforming construction H&S management during the COVID-19 pandemic. The possible challenges that obstruct the implementation of H&S measures are highlighted. The potential technologies which can significantly transform H&S management by reducing the impact of challenges are presented.

The findings benefited the industry practitioners who are suffering disruption in construction operations due to the pneumonic plague.

By developing a conceptual model, this study reveals the contribution of technology-based H&S management for construction projects during the COVID-19 pandemic, which remains under-studied, especially in the context of the developing world.

In this digitalization age, smart technologies are on the cusp of changing all business sector including retailing. Today’s consumers desire to shop in a smart store where the physical products on display are connected to the internet world. This study aims to propose a model for investigating Generation Z (Gen-Z) consumers’ expectations towards the smart retail technology (SRT) in the Malaysian context through the application of the stimulus-organism-response framework.

By using a purposive sampling technique, a self-administered questionnaire was conducted. A total of 220 usable responses were collected from Gen-Z consumers who had experience in using SRT. The data were analysed using partial least square structural equation modelling (PLS-SEM).

This study underscores the role of perceived usefulness, perceived enjoyment and perceived value on Gen-Z consumers’ attitude and word-of-mouth (WOM). Expectations on usefulness, enjoyment and value provide some ideas on Gen-Z consumers’ value who put a high emphasis on functional value, fun value and value for money when adopting the SRT. On the other hand, the result also demonstrates the mediating role of consumers’ attitude in connecting perceived value and perceived enjoyment on WOM towards SRT.

The findings of this study provide beneficial insights for a retailer who desire to pursue a smart-related acquisition strategy. Retailers are recommended to embrace on the following three key features: innovative solution (high usefulness), reliable benefits (high perceived value) and fun experience (high enjoyment) to provide Gen-Z consumers with compelling experiences. Additionally, retailers are suggested to acknowledge the importance of managing consumers’ attitude in driving positive WOM evaluations.

This paper responds to Ting et al.’s (2018) call in uncovering values and lifestyles of generation in details. In Malaysia, retailers ought to incorporate of the high level of usefulness, value and enjoyment when designing their SRT to constitute the Gen-Z consumers’ expectations. Moreover, similar to Ting’s conclusion, this cohort members are very much into technologies and they tend to embrace SRT in their lifestyles.