A Structural Model Approach for Assessing Information Security Value in Organizations

2018 ◽  
Vol 9 (4) ◽  
pp. 47-69
Author(s):  
Daniel Schatz ◽  
Rabih Bashroush
Keyword(s):  
Information Security ◽  
Latent Variables ◽  
Structural Equation ◽  
Structural Model ◽  
Equation Modeling ◽  
Security Investment ◽  
Income Sources ◽  
Proposed Model ◽  
Security Value ◽  
Information Security Investment

Data is rapidly becoming one of the most important assets in global markets, and criminals are spotting opportunities to exploit new potential income sources. In response to this, organizations are dedicating increasing resources to information security programs. However, faced with unrelenting breach reports and rising costs, decision makers inevitably wonder which type of security investment is economically viable. In this article, the authors present an empirically tested model describing the underlying key constructs for assessing information security value in an organization. Based on identified latent variables previously put forward in the literature, the authors use a partial least squares structural equation modeling approach to verify the model's soundness. They identify five crucial variables for value-focused information security investment. The relationships among these latent variables are then investigated and contributions of the structural model assessed. The key findings are finally presented to highlight opportunities for security practitioners to apply the proposed model.

scholarly journals Empirical Validation of Personal and Situational Traits in Usage of Transactional e-Government Services

2021 ◽  
pp. 47-60
Author(s):  
Jongheon Kim ◽  
David Ang* ◽  
Gang-hoon Kim
Keyword(s):  
Technology Acceptance ◽  
Information Disclosure ◽  
Structural Equation ◽  
Structural Model ◽  
Internet Survey ◽  
Equation Modeling ◽  
Measurement Scales ◽  
Government Services ◽  
Research Areas ◽  
Proposed Model

With technology advanced and the flourishing of wired or wireless networks in our daily life, privacy and trustability of transaction media have become highly cherished value. Individuals often make choices in which they surrender a certain degree of privacy in exchange for outcomes or convenience that are perceived to be worthy of the risk of information disclosure. This research attempts to facilitate understandings of the utility of the Technology Acceptance Model (TAM) which is a strongly supported and well-established vehicle in information research and incorporates privacy, risk, and trust factor that are previously regarded as separate research areas from TAM. In addition, it also suggests individual dispositions as precursory factors and examines how they affect users’ risk and trust perception in using transactional e-government services. The proposed model was tested using data gathered from 309 respondents from an internet survey. Structural equation modeling (SEM) using Mplus was employed to validate measurement and structural model. Based on this outcome, the measurements were redefined as composite scores, and subsequent path analysis was conducted to test the proposed hypotheses. The findings provide the structural or causal model of the proposed model attainable, but it requires the development of reliable and valid measurement scales.

scholarly journals Welfare and Wealth in Iran: Rural and Urban Dichotomies

2019 ◽  
Author(s):  
Sediqe Shafiei ◽  
Shahram Yazdani ◽  
A Hamid Zafarmand ◽  
Mohammad-Pooyan Jadidfard ◽  
sareh Shakerian
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Structural Model ◽  
Well Being ◽  
Equation Modeling ◽  
Comprehensive Model ◽  
Contributing Factors ◽  
Rural And Urban ◽  
Effective Policy ◽  
Relationship Of

Abstract Objective : Increasing social welfare and reducing poverty are to ensure the well-being of all classes of a society. Cities and villages are distinguished by cultural and economic disparities. The purpose of this study was to develop and present a comprehensive model on welfare and wealth components and their relationship with each other , as well as determining the contributing factors and variables affecting them by presenting a comprehensive model. Results : The Structural Equation Modeling ( SEM ) method was used to analyze the data and investigate the causal relationship of latent variables. Observed variables and latent variables of the model were analyzed and tested by using AMOS and SPSS (version 21) statistical methods, in two exploratory and confirmatory steps. Wealth and welfare were identified as two separate subjects in the conceptual model and in the final structural model for rural households. Unlike, in the urban community, they were recognized as a single category in the final structural model. The results of this study can provide the clear hints for effective policy making to break the cycle of deprivation and poverty in Iranian rural and urban population.

Toward Measuring Adolescent Environmental Perception

1999 ◽  
Vol 4 (3) ◽  
pp. 139-151 ◽  
Author(s):  
Franz X. Bogner ◽  
Michael Wiseman
Keyword(s):  
Structural Equation Modeling ◽  
Secondary School ◽  
Latent Variables ◽  
Structural Equation ◽  
Two Dimensions ◽  
Equation Modeling ◽  
Environmental Perceptions ◽  
Factor Analyses ◽  
Structural Relationships ◽  
Proposed Model

This study presents a scale developed to measure two dimensions of environmental perceptions—reactions towards preservation and towards utilizing nature and/or the environment—consisting of two and three subscales, respectively. The empirical part consists of a reanalysis of data from four national samples, now analyzed together as one sample. The results of the four subsamples (of some 4,500 secondary school pupils in total) have been published elsewhere as bilateral studies. The aim of the present analysis is to identify a scale that is valid for the entire European sample: By means of factor analyses and structural equation modeling 20 items were extracted. Two latent variables, “Utilization” and “Preservation,” were hypothesized and related in a causal fashion, whereby “Utilization” influences “Preservation.” By application of the methods of linear structural relationships, the proposed model yields a good fit to the data.

MODELING OF SEA SURFACE TEMPERATURE BASED ON PARTIAL LEAST SQUARE - STRUCTURAL EQUATION

2021 ◽  
Vol 14 (2) ◽  
pp. 170-182
Author(s):  
Miftahuddin Miftahuddin ◽  
Retno Wahyuni Putri ◽  
Ichsan Setiawan ◽  
Rina Suryani Oktari
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Model ◽  
Partial Least Square ◽  
Least Square ◽  
Sea Surface ◽  
Equation Modeling

Variability of Sea Surface Temperature (SST) is one of the climatic features that influence global and regional climate dynamics. Missing data (gaps) in the SST dataset are worth investigating since they may statistically alter the value of the SST change. The partial least square-structural equation modeling (PLS-SEM) approach is used in this work to estimate the causality relationships between exogenous and endogenous latent variables. The findings of this study, which are significant indicators that have a loading factor value > 0.7 are as follows: i) sea surface temperature (oC) as a measure of the latent variable changes in SST, ii) wind speed (m/s) and relative humidity (%) as a measure of the latent variable of weather, and iii) air temperature (oC), long-wave solar radiation (w/m2) as a measure of climate latent variables. The size of the Rsquare value is influenced by the number of gaps. The results of the boostrapping show that the latent variables of weather and climate have a significant effect on changes in SST which are indicated by the value of tstatistics > ttabel. The structural model obtained Changes in SST (η) = -0.330 weather + 0.793 climate + ζ. The model shows that the weather has a negative coefficient, which means that the better the weather conditions, the lower the SST changes. Climate has a positive coefficient, which means that the better the climate, the SST changes will also increase. Rising sea surface temperatures caused by an increase in climate can lead to global warming, impacting El-Nino and La-Nina events.

scholarly journals ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R

2019 ◽  
Vol 19 (2) ◽  
pp. 85
Author(s):  
Holipah Holipah ◽  
I Made Tirta ◽  
Dian Anggraeni
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Structural Model ◽  
Measurement Model ◽  
Equation Modeling ◽  
Multiple Group ◽  
Indicator Variables ◽  
Group 2 ◽  
Homogeneous Data ◽  
Group 1

Structural Equation Model (SEM) is a statistical technique with simultaneous processing involves measurement errors, indicator variables, and latent variables. SEM is used to test hypotheses that state the relationships between latent variables when latent variables have been assessed through each of the indicator variables. Multiple Group SEM is a basic model analysis that uses more than one sample. This analysis aims to determine whether the components or models of measurement and structural models are invariant for the two sample groups. In this study, the data generated by some requirements. First, the data generated with sample size n = 250. The first generated data is homogeneous data where the measurement model is the same as the structural model in group 1 and group 2, while the second data is non-homogeneous data where the measurement model and the structural model in group 1 and group 2 is not the same. The data was analyzed using the help of the lavaan package available in R to obtain SEM estimation results and Goodness of Fit Model from some data that was formed. From the results of the merger of the two groups, it shows that the invariant of the two models with the largest df (63) which is Fit Mean model states the simplest model. However, the smallest df (48) with Fit.configural model states the most complex model. Keywords: SEM, Multiple Group, R Program

scholarly journals Impact of Working Environment on Job Satisfaction: Findings from a Survey of Japanese Dental Hygienists

2021 ◽  
Vol 18 (6) ◽  
pp. 3200
Author(s):  
Ayako Okada ◽  
Yuki Ohara ◽  
Yuko Yamamoto ◽  
Yoshiaki Nomura ◽  
Noriyasu Hosoya ◽  
...  
Keyword(s):  
Job Satisfaction ◽  
Latent Variables ◽  
Structural Equation ◽  
Structural Model ◽  
Working Environment ◽  
Equation Modeling ◽  
Job Retention ◽  
Dental Hygienists ◽  
Working Environments ◽  
High Level

In Japan, there is currently a shortage of dental hygienists. The number of dental hygienists as a workforce at dental clinical practice is not sufficient. Several factors affect career retention and job satisfaction of hygienists and these factors are considered to correlate with each other to construct networks. The aim of this study was to present a structural model of job satisfaction of Japanese dental hygienists and to determine the characteristics of unmotivated hygienists. The Japan Dental Hygienists’ Association has conducted a survey on their working environments every five years since 1981. Questionnaires were sent to all members of the association (16,113) and 8932 answers were returned. The data of 3807 active dental hygienists who worked at clinics were analyzed. Items associated with job satisfaction were derived from two latent variables, namely, the intrinsic psychosocial factors for the value of the work and extrinsic employment advantage. Based on the structural equation modeling, the association of value was higher than that of advantage. Most of the hygienists wished to continue working as dental hygienists. More than 60% felt their work required a high level of expertise. The value of the profession is deeply rooted in job satisfaction, motivation, and job retention of Japanese dental hygienists. Working environments where dental hygienists make great use of their specialized skills can lead to high career retention which prevent them from taking career breaks.

scholarly journals Responses of Visual Forms to Neighboring Competition: A Structural Equation Model for Cotinus coggygria var. cinerea Engl.

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1073
Author(s):  
Yujuan Cao ◽  
Jiyou Zhu ◽  
Chengyang Xu ◽  
Richard J. Hauer
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Structural Model ◽  
Urban Forest ◽  
Landscape Management ◽  
Equation Model ◽  
Equation Modeling ◽  
Analytical Technique ◽  
Individual Trees ◽  
Cotinus Coggygria

Background: The visual forms of individual trees in peri-urban forests are driven by a complex array of simultaneous cause-and-effect relationships. Materials and Methods: Structural Equation Modeling (SEM), as a specialized analytical technique, was used to model and understand the complex interactions. It was applied to find out responses of visual forms to neighboring competition in a peri-urban forest dominated by Cotinus coggygria var. cinerea Engl. in Beijing, China. Research Highlights: Light interception and space extrusion have substantial effects on visual forms, expressed as crown forms and foliage forms. The structural model in SEM tested hypothetical correlations among latent variables, namely neighboring competition, crown forms, and foliage forms. Results: The fitted model suggested a direct negative effect of neighboring competition on crown forms and an insignificant negative direct effect on foliage forms. Moreover, an indirect positive effect on foliage forms mediated by crown forms was revealed. Conclusions: The fitted SEM and associated findings should facilitate peri-urban forest landscape management by providing insight into causal mechanisms of visual forms of individual trees and thereby assisting in the visual quality promotion.

scholarly journals Perception Model for Selecting Patentable Technologies

2020 ◽  
Vol 8 (11) ◽  
pp. 65-85
Author(s):  
Cleide Ane Barbosa Da Cruz ◽  
Ana Eleonora Almeida Paixão ◽  
Cristiane Toniolo Dias
Keyword(s):  
Structural Equation Modeling ◽  
Latent Variables ◽  
Structural Equation ◽  
New Technologies ◽  
Science And Technology ◽  
Equation Modeling ◽  
Proposed Model ◽  
Perception Model ◽  
Structured Questionnaire

With the development of new technologies, it is necessary to develop new tools for verification and assessment for their protection by the institutions. Therefore, this study aims to build and validate the perception model for selecting patentable technologies. In relation to the methodology, a structured questionnaire was applied with the members of the National Institutes of Science and Technology (INCT), and structural equation modeling was used to examine the relationships between latent variables. The results show that five hypotheses were tested, all of which were tested and validated. Two complementary models were developed, the first being, to better adjust the model, the market construct was removed. The second model analyzed the four constructs, but it was noticed that, without the market construct, the adjustment indices are more adequate, according to what is presented in the literature as recommended indices. Thus, it is noted that the proposed model can contribute to improving the process of appreciating the technologies produced by Universities.

Structural Equation Modeling in Special Education Research

1995 ◽  
Vol 16 (3) ◽  
pp. 178-183 ◽  
Author(s):  
Alan D. Moore
Keyword(s):  
Special Education ◽  
Education Research ◽  
Structural Equation Modeling ◽  
Experimental Research ◽  
Latent Variables ◽  
Structural Equation ◽  
Structural Model ◽  
Multivariate Data ◽  
Measurement Model ◽  
Equation Modeling

Structural equation modeling is a method for analysis of multivariate data from both nonexperimental and experimental research. the method combines a structural model linking latent variables and a measurement model linking observed variables with latent variables. its use in special education research has been limited to date, but the approach offers promise as a method useful in theory-based research. a nontechnical introduction to the method and cautions concerning the limits of its use are presented.

Understanding consumer motivation to share IoT products data

2020 ◽  
Vol 12 (1) ◽  
pp. 5-22
Author(s):  
Sushant Bhatnagar ◽  
Rajeev Kumra
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Structural Model ◽  
Measurement Model ◽  
Human Interaction ◽  
Third Party ◽  
Equation Modeling ◽  
Product Reviews ◽  
Moral Obligations ◽  
Content Type

Purpose Almost every study undertaken by academicians or practitioners on the Internet of Things (IoT) has mainly highlighted the privacy concerns and information security issues with the IoT products. On the contrary, this paper aims to explore the motivators that could encourage customers of an IoT product to share their IoT product’s data with a third-party aggregator system to facilitate computer-generated product reviews which are defined as electronic Word of Thing (eWOT) in this paper. Design/methodology/approach An experiment was conducted with customized e-commerce prototypes of eWOT. Structural equation modeling analysis was conducted to test the measurement model by using confirmatory factor analysis and thereafter a structural model to test the relationships amongst the latent variables. Findings This paper found that five consumer motivators (personal innovativeness, enjoyment of helping, anticipated extrinsic rewards, moral obligations and venting negative feelings) contribute to eWOT intention. Practical implications This research advances the understanding of human interaction with computer-generated product reviews and opens up avenues for future studies in online consumer behavior in the IoT context. Originality/value This paper presents motivators for eWOT intention to share IoT product data. This is done through a novel concept of an experimental IoT-based prototype, namely, eWOT. These eWOT reviews can be generated from the IoT products data by applying analytics and using natural language generation. To the best of the authors’ knowledge, no other study has been conducted on this subject.

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