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The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

One of the novel concepts in the management literature is intimate co-creation. Considering it as the outcome of workplace persuasion, this study examines its effect via team-member exchange and ethical climate for the assessment of multigroup analysis. Finding a relationship among variables is not the core objective of the study. The core objective was to assess multigroup analysis for examining measurement scales' uniformity or perceptual differences across the male and female groups using measurement invariance.

This was a quantitative study for a survey of faculty members from the top 10 Pakistani universities. It employed state-of-the-art statistical techniques, including the application of the foundational social exchange theory and the utilization of multigroup analysis in structural equation modeling (SEM) with the Analysis of Moment Structure (AMOS). The research methodology was designed to investigate the relationships between workplace persuasion, ethical climate, team member exchange and intimate co-creation. A specific emphasis was placed on assessing whether gender influences these relationships consistently across male and female groups, as determined by measurement invariance tests.

This study underscores the significant impact of ethical persuasion in the workplace on enhancing intimate co-creation among individuals, offering invaluable insights for organizational leaders. Importantly, it emphasizes that gender dynamics do not influence this relationship, underscoring the imperative of addressing gender-related workplace issues to optimize intimate co-creation. This holds particular relevance for service-based organizations, such as universities in this case.

This study makes a significant contribution by exploring the concept of intimate co-creation within the realm of organizational science, while also highlighting the crucial importance of considering workplace gender dynamics. It offers fresh insights into how these dynamics influence group creativity, guiding human resource practices toward fostering innovation within gender-inclusive workplaces. These insights gain added relevance in the evolving post-COVID-19 era and in the context of AI integration. Notably, a distinctive contribution of this study to social exchange theory lies in its innovative application of multigroup analysis to variables related to gender.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.

For the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.

Findings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.

The relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.

The research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.

In this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.

The purpose of this paper is twofold: first, it explores the influencing factors of the government’s trust decision-making in the private sector; second, it explores how these influencing factors affect the government’s trust decisions.

A theoretical model was established, and a questionnaire survey was conducted among 152 professionals. The collected datas were analyzed by the structural equation modeling (SEM) method.

The study identified four critical factors that influence the government’s decision to trust the private sector in public-private-partnership (PPP) projects. All the four factors have a positively correlated impact on the government’s trust decision-making. The structural equation path analysis shows that the most important factor affecting the government’s trust decision-making is the trustee’s (private sector) trustworthy characteristics, and the path coefficient is 0.92. The path coefficients of risk perception and the trustor’s trust tendency are 0.83 and 0.74, respectively. The influence of the legal system environment on government trust decision-making is moderate, with a path coefficient of 0.68.

This paper contributes to the literature in two aspects. First, the factors influencing decision-making to government trust in the private sector in PPP projects have been identified. Second, a comprehensive view of the mechanism of government trust in the private sector in PPP projects has been theorized by the SEM method.

The study aims to test the framework that proposes the role of resources (intellectual capital) in mobilizing entrepreneurial orientation that influences the competitiveness improvement of micro-small-medium enterprises (MSMEs) under the lens of resource orchestration theory.

In this study, 347 respondents from the MSMEs participated through a structured questionnaire. For the data analysis purpose, the structural equation modeling technique was employed using SmartPLS software.

The results suggest human, structural, and relational capital are significant antecedents of entrepreneurial orientation, which leads to competitiveness improvement. The findings also indicate the mediation role of entrepreneurial orientation between intellectual capital and competitiveness improvement.

The current study presumably will supplement the promising research effort to progress the research orchestration theory and also could be a strategic guideline for the managers/owners of the MSMEs.

This study is possibly a novel attempt to divulge the association between intellectual capital (tripartite model) and competitiveness improvement of firms under the lens of resource orchestration theory.

This paper aims to answer these questions: “Is the public adopting energy-saving and water-saving facilities because they want to save energy and water in their psychological perception?”, “Is it convenient to use energy-saving and water-saving facilities?”, “If the inductive design of energy-saving and water-saving facilities attracts the public’s interest, the public is it more willing to install energy-saving and water-saving facilities in a widespread manner?” and “Can inductive energy-saving and water-saving facilities be introduced into the smart manufacturing system of manufacturing industries that require a lot of water to effectively save water and save costs for the company?”.

This paper aims to investigate the attitudes of employees toward using energy-saving and water-saving facilities by constructing a questionnaire based on the ABC (Affect, Behavior, Cognition) model to survey the attitudes of employees from the Southern and Eastern of Taiwan and establishing a structural equation modeling (SEM) to examine the relationship between affect, behavior and cognition while using energy-saving and water-saving facilities.

There are some findings in this paper that the affective design have a strongly significant positive impact for using energy-saving and water-saving facility in the proposed model. People are willing to use energy-saving and water-saving facilities but are more willing to adopt those energy-saving and water-saving products of smart designs, as those take into account the emotional factors. The critical factor for the public to adopt energy-saving and water-saving facilities is smart design, which incorporates emotional elements.

There are still some limitations of this study that the ABC model can only be used as a psychological discussion, and the development and design of related facilities still needs to be jointly developed with professionals in related technical fields. The introduction of induction water supply facilities needs to be considered while the company introduces the design of the smart manufacturing system. Therefore, professionals related to induction water supply should participate in the planning at the initial stage of the company's concept of introducing the smart manufacturing system.

On the practical side, based on preliminary research conclusions, this study proposes to introduce inductive water supply into smart manufacturing systems for manufacturing companies that require a lot of water in their manufacturing processes. In practice, the company can actually save a lot of water, thereby saving costs and reducing waste water discharge.

The results of this study show that the public has a cognition of energy-saving and water-saving. However, there is a Chinese proverb that “easy to know and hard to do”, when actually using facilities, convenience is an important consideration for public. Smart facilities of energy-saving and water-saving, in addition to the benefits of energy-saving and water-saving, it is easy to use, and interacts with users through inductive water supply, which can more emotionally attract people's willingness to use.

This study found that smart facilities, which can more emotionally attract people's willingness to use. On the academic side, this study proves that using the ABC theory to explore the public’s psychological affective, behavior and cognition response to the use of facilities is a very suitable method. On the practical side, based on preliminary research conclusions, this study proposes to introduce inductive water supply into smart manufacturing systems for manufacturing companies that require a lot of water in their manufacturing processes. In practice, the company can actually save a lot of water, thereby saving costs and reducing waste water discharge.

The business ambiguity because of COVID-19 has brought the tourism industry under stress. Using the service-dominant-logic and elaboration-likelihood-model, this study tested the effects of destination-based cognitive, affective and behavioral customer brand engagement (CBE) on customer brand co-creation (CBC). This research also examined the effects of involvement and CBC on customer revisit intention (CRI) during the COVID-19 pandemic. This study also tested the moderating role of customers’ age among the modeled relationships.

Investigating these matters, a sample of 315 tourists was recruited and adopted a mixed-method approach, including structural equation modeling (SEM) as well as fuzzy set qualitative-comparative analysis (fsQCA).

SEM results render that CBE’s dimensions exercise different impacts on CBC, which affect revisit-intention. Results ascertain customer involvement’s direct effects on CBC and revisit intention. Multi-group analysis uncovers that consumer age significantly moderates the CBC and CRI relationship, and their effect increases as consumers get older. The fsQCA results revealed more heterogenous combinations to predict CBC and revisit intention.

This study focuses on CBE, CBC and involvement, and contributes unique insight to tourism marketing research; thus, it identifies plentiful opportunities for further research, as summarized.

This study offers key implications for destinations to build tourism/marketing strategies to strengthen the CBE/CBC or tourist/destination–brand relationship.

Though CBE/CBC and involvement are identified as important research priorities, empirically derived insights among these and related factors remain limited in the course of the COVID-19 crisis.

本文采用结构方程模型(SEM)和模糊集定性比较分析(fsQCA)相结合的方法, 对315名游客进行了调查。

由于新型冠状病毒感染症(COVID-19)产生的业务不定性给旅游业带来了压力。本研究运用服务主导逻辑和精细似然模型, 检验了基于目的地的认知、情感和行为顾客品牌参与(CBE)对顾客品牌共同创造(CBC)的影响。本研究还考察了COVID-19大流行期间参与和CBC对客户重访意愿(CRI)的影响。检验了顾客年龄在模型关系中的调节作用。

SEM结果表明, CBE的维度对CBC有不同的影响, 而这种影响又会影响着重游意愿。结果确定了游客参与对CBC和重访意愿的直接影响。多群体分析发现, 消费者年龄显著调节CBC和CRI关系, 且随着消费者年龄的增长, 其作用增强。fsQCA结果显示需更多的异质组合来预测CBC和再访意向。

-本研究关注CBE、CBC和参与, 为旅游营销研究提供了独特的见解, 因此总结出了许多进一步研究的机会。

本研究为目的地建立旅游/营销策略以加强CBE/CBC或游客/目的地-品牌关系提供了重要启示。

尽管CBE/CBC和参与被认为重要的研究重点, 但在covid −19危机期间, 从这些因素和相关因素中得出的经验见解仍然有限。

Para investigar estas cuestiones, se seleccionó una muestra de 315 turistas y se utilizó un enfoque metodológico mixto que incluía el modelo de ecuaciones estructurales (SEM) y el análisis cualitativo-comparativo de conjuntos difusos (fsQCA).

La confusión empresarial debida a la pandemia del COVID-19 ha sometido al sector turístico a una fuerte tensión. Utilizando la lógica dominante del servicio y el modelo de elaboración de verosimilitud, este estudio examinó los efectos del compromiso cognitivo, afectivo y comportamental del cliente con la marca del destino (CBE) en la cocreación de la marca (CBC). Esta investigación también analizó los efectos de la implicación y la CBC en la intención de revisita (IRC) durante la pandemia COVID-19. Este estudio también evaluó el papel moderador de la edad de los clientes entre las relaciones establecidas.

Los resultados del SEM muestran que las dimensiones de la CBE ejercen diferentes impactos sobre la CBC, que afectan a la intención de revisita. Los resultados determinan los efectos directos de la implicación del cliente sobre la CBC y la intención de revisita. El análisis multigrupo revela que la edad del consumidor modera significativamente la relación entre el CBC y el IRC, y que su efecto aumenta a medida que los consumidores envejecen. Los resultados del fsQCA revelaron combinaciones más heterogéneas para predecir el CBC y la intención de volver a visitar.

Este estudio se centra en la CBE, la CBC y la implicación, y aporta una visión única a la investigación del marketing turístico, por lo que identifica numerosas oportunidades para futuras investigaciones.

Este estudio ofrece implicaciones clave para que los destinos construyan estrategias de turismo/marketing en el fortalecimiento de la relación CBE/CBC o turista/destino-marca.

Aunque la CBE/CBC y la implicación se identifican como importantes prioridades de investigación, las percepciones derivadas empíricamente entre estos factores y otros relacionados siguen siendo limitadas en el transcurso de la crisis del COVID-19.

Smart manufacturing (SM) lies at the core of Industry 4.0. Uniform adoption of SM across business partners is crucial to exploit its value creation potential. However, firms' willingness to invest in SM is limited by insufficient or inconclusive evidence on its performance-related benefits. To close this gap, this paper develops and tests a model linking SM adoption to firms' financial performance. Improvements along the four dimensions of operational performance (i.e. cost quality, delivery and flexibility) mediate this relation.

This study follows an empirical research approach. In particular, survey data from 234 automotive component suppliers are analyzed via covariance-based structural equation modeling to explore the link between SM adoption and operational performance. Survey data are then matched with secondary data from balance sheets of 81 firms to investigate the impact of SM on financial performance via partial least square structural equation modeling.

Findings highlight that adoption of SM results in improvements in cost, quality, delivery performance, thus suggesting that SM is a mean to overcome performance trade-offs. Improvements in operational performance enabled by SM do not give rise to superior financial performance, thus implying that SM might support firms in maintaining the competitive position in the market, but could be insufficient to generate higher margin.

Results have implications for SM research and for manufacturing executives engaged in the adoption of SM, as they provide a detailed analysis of the impact of SM on operational performance and clarify the effect that SM adoption has on financial performance.

The mental healthcare is experiencing an ever-growing surge in understanding the consumer (e.g., patient) engagement paradox, aiming to vouch for the quality of care. Despite this surge, scant attention has been given in academia to conceptualize and empirically investigate this particular aspect. Thus, drawing on the Stimulus-Organism-Response (S-O-R) paradigm, the study explores how patients engage with healthcare service providers and how they perceive the quality of the healthcare services.

Data were collected from 279 respondents, and the derived conceptual model was tested by using Smart PLS 3.2.7 and PROCESS. To complement the findings of partial least squares (PLS)-based structural equation modeling (SEM), the present study also applied fuzzy set qualitative comparative analysis (fsQCA) to identify the necessary and sufficient conditions to explore substitute conjunctive paths that emerge.

Findings show that patients’ perceived intimacy (PI), cohesion and privacy enhance the quality of mental healthcare service providers. The results also suggest that patients’ PI, cohesion and privacy have indirect effects on the perceived quality of care (PQC) by the service providers through consumer engagement. The fsQCA results derive that the relationship among conditions leading to patients’ perception of the quality of care in regard to mental healthcare service providers is complex and is best reflected as multiple and conjectural causation configurations.

The findings from this research contribute to the advancement of studies on patients’ experiences by empirically examining the unique dynamics of interaction between consumers (patients) and mental healthcare service providers, thereby enriching both the literature on social interactions and the understanding of the consumer–provider relationship.

The results of this study provide practical implications for mental healthcare service providers on how to combine the study variables to enhance the quality of care and satisfy more patients.

A significant research gap has ascertained the inter-relationship between PI, cohesion, privacy, engagement and PQC from the perspective of mental healthcare service providers. This research is one of the primary studies from a managerial and methodological standpoint. The study contributes by combining symmetric and asymmetric statistical tools in service marketing and healthcare research. Furthermore, the application of fsQCA helps to understand the interactions that might not be immediately obvious through traditional symmetric methods.