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LISREL 8 with PRELIS2 for Windows
... exceeding the 0.7 cutoff value [170]. The SMC indexes generally exceeded the recommended level of 0.5 [171], implying overall acceptance for construct reliability. ...
... This work tested hypotheses mainly using maximum likelihood estimation. The goodness-of-fit for the structure of the proposed conceptual framework was examined in advance using the five indexes suggested in the literature [171][172][173]: (1) normed chi-square (i.e., df / 2 ); (2) the goodness-of-fit index (GFI); (3) adjusted GFI (AGFI); (4) root mean square residual (RMR); and (5) standard root mean square residual (SRMR) [171][172][173]. A normed chi-square value of <3.0 indicates a good fit, and <2.0 indicates an excellent fit [173]; both GFI and AGFI values >0.9 are suggested to ensure a good fit of a structural equation model; and RMR and SRMR values of <0.05 indicate good fit of a model [171]. ...
... This work tested hypotheses mainly using maximum likelihood estimation. The goodness-of-fit for the structure of the proposed conceptual framework was examined in advance using the five indexes suggested in the literature [171][172][173]: (1) normed chi-square (i.e., df / 2 ); (2) the goodness-of-fit index (GFI); (3) adjusted GFI (AGFI); (4) root mean square residual (RMR); and (5) standard root mean square residual (SRMR) [171][172][173]. A normed chi-square value of <3.0 indicates a good fit, and <2.0 indicates an excellent fit [173]; both GFI and AGFI values >0.9 are suggested to ensure a good fit of a structural equation model; and RMR and SRMR values of <0.05 indicate good fit of a model [171]. ...
Under third-party power intervention (TPPI), which increases uncertainty in task environments, complex channel power interplays and restructuring are indispensable among green supply chain members as they move toward sustainable collaborative relationships for increased viability and competitive advantage. From the resource dependence perspective, this work presents a novel conceptual model to investigate the influence of political and social power on channel power restructuring and induced green supply chain collaboration in brander-retailer bidirectional green supply chains of fashionable consumer electronics products (FCEPs). An FCEP refers to the consumer electronics product (e.g., personal computers, mobile phones, computer notebooks, and game consoles) with the features of a well-known brand associated, a short product lifecycle, timely and fashionable design fit for market trends, and quick responsiveness to the variations of market demands. The proposed model is tested empirically using questionnaire data obtained from retailers in the FCEP brander-retailer distribution channels. Analytical results reveal that as an extension of political and social power, TPPI positively affects the reciprocal interdependence of dyadic members and reduces power asymmetry, thereby enhancing the collaborative relationship of dyadic members and leading to improved green supply chain performance. Therein, reciprocal interdependence underlying collaborative relationship is the key to reducing the external environmental uncertainties in the TPPI context.
... We assumed that the environmental factors could affect both phytoplankton and zooplankton, and that phytoplankton and zooplankton could affect each other reciprocally. Lastly, we used LISREL 8 [21] to verify the model. Detailed assumptions and the concept of SEM are explained in [6,22,23]. ...
... After the main environmental forces had been identified, we introduced phy ton and zooplankton densities and diversity indices [20] to predict the interact tween environmental factors and the biotic parameters in a conceptual model (F We assumed that the environmental factors could affect both phytoplankton a plankton, and that phytoplankton and zooplankton could affect each other recip Lastly, we used LISREL 8 [21] to verify the model. Detailed assumptions and the of SEM are explained in [6,22,23]. ...
Environmental impact assessment is a means of preventing and mitigating the adverse effects of economic development activities on the natural environment. It is meant to ensure that decision-makers have sufficient information to consider environmental impacts before proceeding with new projects. Despite their important role in public policy, verification of environmental impact assessments has seldom been conducted. In this study, we used principal component analysis (PCA) to identify the major sources of influence on the coastal waters adjacent to a major tourist facility (an aquarium) in southern Taiwan, followed by the construction of a structural equation model (SEM) to determine the direct and indirect effects of the abiotic factors on phytoplankton and zooplankton density and diversity. Based on the loadings of principal components 1–3, we identified that river input, suspended matter, and seasonal changes were the major factors affecting the coastal area. The SEM further suggested that phytoplankton density and diversity were affected directly by seasonal changes and suspended matter, but only indirectly by river input, owing to the latter’s effect on suspended matter. In contrast, the SEM suggested that zooplankton density and diversity were affected directly by seasonal changes, but indirectly by both river input and suspended matter owing to their effects on phytoplankton density and diversity. Q2 was the season with the highest number of visitors to the aquarium, but none of the abiotic or biotic parameters showed particular differences, implying that the variations in those parameters in the adjacent coastal waters were not related to the visitors. We suggest that PCA and SEM be used in the future in other contexts to verify environmental impact assessments.
... The results of the measurement model showed that χ 2 = 1632.903, df = 129, p < 0.001, although GFI = 0.993, which has a good degree of fit with the observed data (Howell, 1996). However, RMSEA = 0.076 and CFI = 0.872, indicating a poor fit (Hu and Bentler, 1999), means there were factors that affect the model fit. ...
... df = 84, and p = 2.293, which is greater than 0.05 and does not reach statistically significant difference, indicating that this model has good explanatory power. RMSEA = 0.028, which meets the rubric of fitness, i.e., this model is a reasonable fit; GFI = 0.998, which shows that this model has a good degree of fit with the observed data (Howell, 1996); CFI = 0.986, indicating a good improvement compared to the independent model without covariance; and SRMR = 0.066, indicating a good fit (Hu and Bentler, 1999). For this model, the streamlined normative fitness index CN = 993.411, ...
This study focused on the frequency of social media use. Through investigating and verifying the correlations between social media use frequency, online political participation, and social capital, we derived two models of socialization that affect citizen well-being and, accordingly, proposed strategic suggestions for democratic society construction and network management. This study drew upon the 2019 Taiwan Communication Survey database and used structural equation modeling (SEM) as a statistical method to explore the causal relationship between these four variables (social media use, online political participation, social capital and well-being). The data analysis yielded an overall good fit with the overall fit indicators: χ² = 214.417, df = 84, p = 2.293, RMSEA = 0.028, GFI = 0.998, CFI = 0.986, SRMR = 0.066, and CN = 993.411. Future communication scholars who wish to explore issues related to new media users can draw on this model for subsequent research.
... Composite reliability (ρ) is a measure of internal consistency comparable to coefficient alpha (Fornel and Larcker, 1981). However, this measure is superior to Cronbach's α in that it does not assume equal item loadings (Howell, 1996). All scales demonstrated acceptable levels of reliability with Cronbach's αs for the constructs ranging from .73 to .90 for the factors of flow and .93 and .81 ...
... The reflective model also indicated a value .11as RMR, and 0.059, [CI (90%), .051 to .070] as RMSEA, indicating that the theoretical model provided a fit that was not significantly worse than that provided by the measurement model (Howell, 1996). On the other hand, the formative model of flow proposes that concentration, challenge, control, and curiosity are antecedents of flow. ...
As the Web becomes a part of peoples' everyday lives, there is a growing need to understand user behaviour on the Web. Recently, the flow construct has been proposed as important for understanding the nature of user online experience. Researchers assert that the benefits of flow online include increased learning, exploratory and positive behavior, positive subjective experience, and perceived sense of control over their interaction. Overall, flow could affect outcomes such as navigation patterns and repeat visits on commercial Web sites. Although widely studied over the past years, a review of the literature indicates discrepancies among various flow models and some unclear conceptualization and operationalization of the construct. This paper examined flow according to two specific conceptualizations with respect to its measurement, and tests each conceptualization in an identical nomological network. The results indicate that there is better fit of a reflective flow model compared with a formative flow model to the study data. The results of the study may aid in the understanding of the relationships between the higher order flow construct and its first order dimensions, which may help inform system designers to better assess flow and, thus, be more conducive to flow.
... Phytoplankton and zooplankton diversity indices (Shannon and Weaver 1949) were then introduced, coupling with the hydrological parameters, to construct a conceptual SEM to predict the interaction between environmental factors and epilimnetic phytoplankton and zooplankton diversities. Lastly, the model was verified using LISREL 8 (Howell 1996). Phytoplankton diversities can be affected by zooplankton via grazing, while zooplankton can be affected by phytoplankton via food availability, and both can be affected by hydrological factors. ...
In a marine ecosystem, the diversity of phytoplankton can influence the diversity of zooplankton, or vice versa, and both can be affected by the environmental factors. In this study, we used principal component analysis (PCA) to identify the major sources of influence on the coastal water near an industrial park, following by construction of structural equation model (SEM) to determine the direct and indirect effect of the factors on phytoplankton and zooplankton diversity. PCA results indicated that the coastal area was mainly affected by riverine discharge (represented by high PC factor loadings of transparency and turbidity) and seasonal change (represented by temperature). SEM further suggested that both riverine discharge and seasonal influences can directly affect phytoplankton diversity, but indirectly affected zooplankton diversity via changes in phytoplankton. Using PCA to determine the sources of influence followed by construction of SEM allowed us to understand the relative importance of the environmental factors, direct or indirect, on phytoplankton and zooplankton diversity. When environmental changes occur, a new SEM could be constructed using the same category of physical and biological data and then compared to the current model to verify whether the environmental changes were the cause of alterations in planktonic communities in the area.
This work proposes a post-disaster demand-oriented emergency logistics operational model that aims at disaster relief–service distribution to maximize survivor resilience. Rooted in survival psychology and cognition theories, this work proposes a conceptual model which hypothesizes post-disaster survivor perception–attitude–resilience relationships. This is followed by conducting a normative analysis which includes establishing survivor-specific disaggregate attitudinal functions and a post-disaster relief–service distribution optimization model, based on the proposed conceptual model and hypotheses. Using structural equation modeling we conduct an empirical study which verifies that the proposed survivor perception–attitude–resilience conceptual model is valid, supporting the results of the normative analyses. Furthermore, a numerical study of a real earthquake disaster is conducted. Numerical results demonstrate the applicability of the proposed method and its potential advantages in evaluating the performance of an emergency logistics system from the perspective of not only the suppliers but also the demanders.
The management of channel relations has a significant impact on a firm's operational competitiveness; however, there is a lack of published research to better understand the linkages between channel relationships and channel power, noncoercive influence strategies, as well as channel climate and channel solidarity. This paper develops a model showing the linkages among these dimensions of channel relationships. Using linear structural relations (LISREL), a model of the Taiwanese personal digital assistant industry is developed to illustrate these interactions. The corresponding empirical test results indicate that channel climate has a significant impact on channel solidarity; however, this impact may be mitigated by both channel power and the use of noncoercive influence strategies. In addition, both mutual trust among channel members and continuity of the relationship have a positive influence on channel solidarity. Channel members with relatively more power appear able to determine the degree of channel solidarity through the use of effective noncoercive influence strategies.
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