Corporate strategy and environment: Study based on structural equation modeling

Purpose The purpose of this paper is to investigate and select various significant technology push (TP) strategies affecting sustainable development in manufacturing organizations. The study deploys structural equation modeling (SEM) technique to empirically validate the interrelationships amongst significant TP strategies and sustainable development indicators in SEM-TP Model. Design/methodology/approach Confirmatory factor analysis approach is utilized to generate an effective SEM-TP Model by using AMOS 21 (Analysis of Moment Structures) software. The data have been collected from different manufacturing organizations practicing TP strategies, using a well-framed TP questionnaire for the evolution of SEM-TP Model. Findings SEM modeling of various TP strategies like, innovative capability (IC), research and development, corporate strategy (CS) and export orientation towards achieving sustainable development in manufacturing industries has been performed. SEM-TP Model has been planned and reports obtained before and after modification indices (MI) of the model are correlated, which further establishes improvements in model’s effectiveness. The research concludes that two TP strategies namely, IC and CS are found to be significant in the present context. These strategies have emerged as a foundation for several development initiatives and actively support manufacturing industries in achieving sustainable development. The results obtained from final model may support organizational managers and TP practitioners to improve the overall performance of manufacturing industries involved in the present study. The manufacturing enterprises will be able to frame or enhance their corporate strategies and innovative capabilities in a more appropriate way. Research limitations/implications In the present study, contributions of TP practices are determined to accomplish sustainable development in manufacturing industries. Otherwise, issue-wise independent modeling can also be performed to assess the importance of TP practices towards achieving quality and sustainable development under specific orientations. Practical implications The research gives priority to enhancement in the coordination among various TP practices and sustainable development parameters in the industries, to inculcate TP as a crucial strategy to meet challenges in global markets. Social implications It has been exhibited from model that adequate TP strategies can effectively contribute towards recognition of sustainable development to compete in the highly progressive markets. The results of various interrelationships among TP practices and sustainable development indicators in SEM-TP Model portray the effectiveness of TP practices for accomplishment of organizational and social ambitions. Originality/value The outcomes of the study will help organizational managers, HR executives and TP practitioners in manufacturing industries to know about the significant TP strategies to be followed holistically for achieving sustainable development.

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Testing the Assumption of Uncorrelated Errors for Short Scales by Means of Structural Equation Modeling

Journal of Individual Differences ◽

10.1027/1614-0001/a000135 ◽

2014 ◽

Vol 35 (4) ◽

pp. 201-211 ◽

Cited By ~ 3

Author(s):

André Beauducel ◽

Anja Leue

Keyword(s):

Structural Equation Modeling ◽

Negative Correlation ◽

Structural Equation ◽

Error Score ◽

Classical Test Theory ◽

Test Theory ◽

Equation Modeling ◽

Eysenck Personality Questionnaire ◽

Personality Questionnaire ◽

True Score

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.

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The Measurement Invariance of the Short Dark Triad

Journal of Individual Differences ◽

10.1027/1614-0001/a000322 ◽

2020 ◽

Vol 41 (4) ◽

pp. 207-218

Author(s):

Mihaela Grigoraș ◽

Andreea Butucescu ◽

Amalia Miulescu ◽

Cristian Opariuc-Dan ◽

Dragoș Iliescu

Keyword(s):

Structural Equation Modeling ◽

Item Response ◽

Structural Equation ◽

Dark Triad ◽

Theory And Practice ◽

Equation Modeling ◽

Scale Level ◽

High Stake ◽

Differential Functioning ◽

Item Functioning

Abstract. Given the fact that most of the dark personality measures are developed based on data collected in low-stake settings, the present study addresses the appropriateness of their use in high-stake contexts. Specifically, we examined item- and scale-level differential functioning of the Short Dark Triad (SD3; Paulhus & Jones, 2011 ) measure across testing contexts. The Short Dark Triad was administered to applicant ( N = 457) and non-applicant ( N = 592) samples. Item- and scale-level invariances were tested using an Item Response Theory (IRT)-based approach and a Structural Equation Modeling (SEM) approach, respectively. Results show that more than half of the SD3 items were flagged for Differential Item Functioning (DIF), and Exploratory Structural Equation Modeling (ESEM) results supported configural, but not metric invariance. Implications for theory and practice are discussed.

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Childhood Intelligence Predicts Adult Trait Openness

Journal of Individual Differences ◽

10.1027/1614-0001/a000194 ◽

2016 ◽

Vol 37 (2) ◽

pp. 105-111 ◽

Cited By ~ 6

Author(s):

Adrian Furnham ◽

Helen Cheng

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Social Background ◽

Study Data ◽

Equation Modeling ◽

Direct Effects ◽

Data Set ◽

National Child Development Study ◽

Nationally Representative ◽

The Uk

Abstract. This study used a longitudinal data set of 5,672 adults followed for 50 years to determine the factors that influence adult trait Openness-to-Experience. In a large, nationally representative sample in the UK (the National Child Development Study), data were collected at birth, in childhood (age 11), adolescence (age 16), and adulthood (ages 33, 42, and 50) to examine the effects of family social background, childhood intelligence, school motivation during adolescence, education, and occupation on the personality trait Openness assessed at age 50 years. Structural equation modeling showed that parental social status, childhood intelligence, school motivation, education, and occupation all had modest, but direct, effects on trait Openness, among which childhood intelligence was the strongest predictor. Gender was not significantly associated with trait Openness. Limitations and implications of the study are discussed.

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Celebrity Worship Among University Students in Malaysia

European Psychologist ◽

10.1027/1016-9040/a000029 ◽

2011 ◽

Vol 16 (4) ◽

pp. 334-342 ◽

Cited By ~ 5

Author(s):

Viren Swami ◽

Tomas Chamorro-Premuzic ◽

Khairul Mastor ◽

Fatin Hazwani Siran ◽

Mohammad Mohsein Mohammad Said ◽

...

Keyword(s):

Factor Analysis ◽

Structural Equation Modeling ◽

Structural Equation ◽

Attitude Scale ◽

Equation Modeling ◽

Future Research ◽

The West ◽

Factor Solution ◽

Movie Stars ◽

Three Factor

The present study examined conceptual issues surrounding celebrity worship in a Malay-speaking population. In total, 512 Malay and 269 Chinese participants from Malaysia indicated who their favorite celebrity was and completed the Celebrity Attitude Scale (CAS) as well as a range of demographic items. Results showed that the majority of Malay and Chinese participants selected pop stars and movie stars as their favourite celebrities, mirroring findings in Western settings. In addition, exploratory factor analysis revealed a three-factor solution of the CAS that was consistent with previous studies conducted in the West. Structural equation modeling further revealed that participant’s age was negatively associated with celebrity worship and that self-rated attractiveness was positively associated with celebrity worship. Overall, the present results suggest that celebrity worship in Malaysia may be driven by market and media forces, and future research may well be guided by use of the CAS.

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Further Insights Into the German Version of the Multidimensional Assessment of Interoceptive Awareness (MAIA)

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000404 ◽

2019 ◽

Vol 35 (3) ◽

pp. 317-325 ◽

Cited By ~ 6

Author(s):

Dorota Reis

Keyword(s):

Structural Equation Modeling ◽

Structural Equation ◽

Equation Modeling ◽

Interoceptive Awareness ◽

Multidimensional Assessment ◽

New Instrument ◽

Confirmatory Factor ◽

Complex Models ◽

Approximate Zero ◽

Bayesian Structural Equation Modeling

Abstract. Interoception is defined as an iterative process that refers to receiving, accessing, appraising, and responding to body sensations. Recently, following an extensive process of development, Mehling and colleagues (2012) proposed a new instrument, the Multidimensional Assessment of Interoceptive Awareness (MAIA), which captures these different aspects of interoception with eight subscales. The aim of this study was to reexamine the dimensionality of the MAIA by applying maximum likelihood confirmatory factor analysis (ML-CFA), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM). ML-CFA, ESEM, and BSEM were examined in a sample of 320 German adults. ML-CFA showed a poor fit to the data. ESEM yielded a better fit and contained numerous significant cross-loadings, of which one was substantial (≥ .30). The BSEM model with approximate zero informative priors yielded an excellent fit and confirmed the substantial cross-loading found in ESEM. The study demonstrates that ESEM and BSEM are flexible techniques that can be used to improve our understanding of multidimensional constructs. In addition, BSEM can be seen as less exploratory than ESEM and it might also be used to overcome potential limitations of ESEM with regard to more complex models relative to the sample size.

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Analyzing Observed Composite Differences Across Groups

Methodology ◽

10.1027/1614-2241/a000049 ◽

2013 ◽

Vol 9 (1) ◽

pp. 1-12 ◽

Cited By ~ 101

Author(s):

Holger Steinmetz

Keyword(s):

Monte Carlo ◽

Structural Equation Modeling ◽

Measurement Invariance ◽

Structural Equation ◽

Monte Carlo Study ◽

Equation Modeling ◽

Factor Loadings ◽

Latent Mean Differences ◽

Partial Invariance ◽

Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

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Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

Social Psychology ◽

10.1027/1864-9335/a000356 ◽

2019 ◽

Vol 50 (1) ◽

pp. 24-37

Author(s):

Ben Porter ◽

Camilla S. Øverup ◽

Julie A. Brunson ◽

Paras D. Mehta

Keyword(s):

Structural Equation Modeling ◽

Social Relations ◽

Latent Variables ◽

Structural Equation ◽

Multilevel Structural Equation Modeling ◽

Equation Modeling ◽

Complete Understanding ◽

Social Relations Model ◽

Flexible Framework ◽

Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

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