scholarly journals Regional differences in the abiotic environment contribute to genomic divergence within a wild tomato species

2019 ◽  
Author(s):  
Matthew JS Gibson ◽  
Leonie C Moyle
Keyword(s):  
Local Adaptation ◽  
Structural Equation ◽  
Genomic Variation ◽  
Equation Modeling ◽  
Nucleotide Polymorphisms ◽  
Evaporative Demand ◽  
Abiotic Environment ◽  
Wild Tomato Species ◽  
Tomato Species ◽  
Wide Range

The wild currant tomato Solanum pimpinellifolium inhabits a wide range of abiotic habitats across its native range of Ecuador and Peru. Although it has served as a key genetic resource for the improvement of domestic cultivars, little is known about the genetic basis of traits underlying local adaptation in this species, nor what abiotic variables are most important for driving differentiation. Here we use redundancy analysis (RDA) and other multivariate statistical methods (structural equation modeling (SEM) and generalized dissimilarity modeling (GDM)) to quantify the relationship of genomic variation (6,830 single nucleotide polymorphisms) with climate and geography, among 140 wild accessions. RDA, SEM, and GDM each identified environment as explaining more genomic variation than geography, suggesting that local adaptation to heterogeneous abiotic habitats may be an important source of genetic diversity in this species. Environmental factors describing temporal variation in precipitation and evaporative demand explained the most SNP variation among accessions, indicating that these forces may represent key selective agents. Lastly, by studying how SNP-environment associations vary throughout the genome (44,064 SNPs), we mapped the location and investigated the functions of loci putatively contributing to climatic adaptations. Together our findings indicate an important role for selection imposed by the abiotic environment in driving genomic differentiation between populations.

scholarly journals Practicing Green Residence Business Model Based on TPB Perspective

2021 ◽  
Vol 13 (13) ◽  
pp. 7379
Author(s):  
Chao Wu ◽  
Shuling Liang ◽  
Weijiong Wu ◽  
Yuxiang Hong
Keyword(s):  
Business Model ◽  
Purchase Intention ◽  
Structural Equation ◽  
Behavioral Control ◽  
Steel Structure ◽  
Equation Modeling ◽  
Perceived Behavioral Control ◽  
Intention To Purchase ◽  
Wide Range ◽  
Green Business

Green residence is the future of urban development, it is also an attempt to implement the green business model in the residential business field. The key to the success of a green business model is that a wide range of customers can accept its green value proposition and react to it through their purchase decisions. This study aims to develop a theory of a planned behavior (TPB) research model to predict individuals’ intention to purchase green residence. This study took steel structure residence as an example, which was widely recognized as one emerging type of green residence. The samples were selected in Baotou city of Inner Mongolia, P.R. China. Data analysis was performed using the structural equation modeling (SEM) with data obtained from a survey of 208 respondents using SPSS19.0 and AMOS17.0. The results found that the individuals’ intention to purchase green residence was significantly affected by attitude, subjective norm, and perceived behavioral control. Moreover, the empirical evidence showed that these influences differed between different gender groups. Specifically, women responders had a stronger effect on the path attitude impact on purchase intention than men. These findings can provide implications for practicing the green business model of real estate enterprise.

The Practice of Structural Equation Modeling

2014 ◽  
pp. 2521-2530
Author(s):  
Ho Yin Wong ◽  
Jason Sit ◽  
Jia-Yi Hung
Keyword(s):  
Structural Equation Modeling ◽  
Statistical Modeling ◽  
Structural Equation ◽  
Sem Analysis ◽  
Modeling Technique ◽  
Equation Modeling ◽  
Business Analytics ◽  
Wide Range ◽  
Stage Process ◽  
Point Of Reference

The aim of this chapter is to act as a point of reference for researchers, especially new users, who would like to use structural equation modeling (SEM) to perform business analytics. SEM is a multipurpose statistical modeling technique that can be applied in various business disciplines and is a useful tool to conduct business analytics. This chapter explains some common terminologies in the SEM literature and states general steps of performing SEM analysis along with an integration of the wide range of views and empirical findings on the topic. The chapter discusses the assumptions of SEM analysis, followed by a three-stage process of conducting, which includes assumptions, specification, evaluation, and modifications.

scholarly journals Reflection on success and failures: scale development and validation

2020 ◽  
Vol 32 (8) ◽  
pp. 615-626
Author(s):  
Makoto Matsuo
Keyword(s):  
Positive Psychology ◽  
Work Engagement ◽  
Convergent Validity ◽  
Structural Equation ◽  
Discriminant Validity ◽  
Equation Modeling ◽  
Future Research ◽  
Content Type ◽  
Strengths Use ◽  
Wide Range

Purpose Although positive psychology emphasizes the importance of reflecting on success in promoting strengths use and self-efficacy, no research has developed a measure of reflection on success. The purpose of this study is to develop and validate the scales for reflection on success and failures. Design/methodology/approach Study 1 was conducted to extract the dimensions of reflection on success and failures using survey data from nurses (n = 298), whereas Study 2 involved validation of the scales using a two-wave survey of physical therapists (n = 291). Findings In Study 1, the factors of “reflection on success” and “reflection on failures” were extracted by exploratory factor analysis. In Study 2, the discriminant validity of the two scales was established via confirmatory factor analyses. The structural equation modeling results indicated that reflection on success promoted work authenticity, work engagement and strengths use, while reflection on failures only promoted work engagement, indicating the convergent validity of the scales. Research limitations/implications As the research subjects were medical professionals in Japan, the scales need to be validated with samples from a wide range of occupations and cultural backgrounds, in future research. Originality/value The present research expands the literature on reflection and strengths-based approach by introducing the “success–failures” dimension based on positive psychology, broaden-and-build theory and job demands–resources theory.

Is Self-Compassion Universal? Support for the Measurement Invariance of the Self-Compassion Scale Across Populations

Assessment ◽  
2020 ◽  
Vol 28 (1) ◽  
pp. 169-185 ◽  
Author(s):  
István Tóth-Király ◽  
Kristin D. Neff
Keyword(s):  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Secondary Data ◽  
The Self ◽  
Equation Modeling ◽  
Exploratory Structural Equation Modeling ◽  
Self Compassion ◽  
Wide Range ◽  
Compassion Scale

The Self-Compassion Scale (SCS) is a widely used measure to assess the trait of self-compassion, and, so far, it has been implicitly assumed that it functions the same way across different groups. This assumption needs to be explicitly tested to ascertain that no measurement biases exist. To address this issue, the present study sought to systematically examine the generalizability of the bifactor exploratory structural equation modeling operationalization of the SCS via tests of measurement invariance across a wide range of populations, varying according to features such as student or community status, gender, age, and language. Secondary data were used for this purpose and included a total of 18 samples and 12 different languages ( N = 10,997). Multigroup analyses revealed evidence for the configural, weak, strong, strict, and latent variance–covariance of the bifactor exploratory structural equation modeling operationalization of the SCS across different groups. These findings suggest that the SCS provides an assessment of self-compassion that is psychometrically equivalent across groups. However, findings comparing latent mean invariance found that levels of self-compassion differed across groups.

scholarly journals Factors Influencing BIM Adoption for Construction Enterprises in China

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Ruixue Zhang ◽  
Yuyan Tang ◽  
Liang Wang ◽  
Zeyu Wang
Keyword(s):  
Construction Industry ◽  
Influencing Factors ◽  
Structural Equation ◽  
Equation Modeling ◽  
Key Factors ◽  
Process Data ◽  
Construction Enterprises ◽  
Factors Influencing ◽  
Hypothesis Model ◽  
Wide Range

The construction industry is one of the important pillars of the Chinese national economy. BIM, as a new information technology tool, provides an intelligent digital representation of buildings to support diverse activities and brings about a wide range of benefits throughout the life cycle of projects. However, BIM has not been widely adopted in construction enterprises in China. It is necessary to make a comprehensive and systematic analysis of the influencing factors for BIM adoption. This paper sums up 13 influencing factors from four aspects, namely, technology, economy, institution, and environment aspect. The questionnaire survey and statistical analysis were used to collect and process data which is applied to determine the influencing factors. Based on relevant literature, a hypothesis model was established by the structural equation modeling method. SPSS software and AMOS software were used to test the model. Then, the key factors influencing BIM adoption are induced. The results show that the key factors that influence BIM adoption in China include personnel quality, investment in personnel training, BIM standardization, and the influence of senior managers in the organization. Combined with the above conclusion, this paper puts forward some suggestions for promoting BIM adoption and specific measures to realize the wide application of BIM technology in the Chinese construction industry.

A New Dimension of Organizational Justice: Procedural Voice

2009 ◽  
Vol 105 (2) ◽  
pp. 411-426 ◽  
Author(s):  
Denise Jepsen ◽  
John Rodwell
Keyword(s):  
Structural Equation Modeling ◽  
Organizational Justice ◽  
Latent Variable ◽  
Structural Equation ◽  
Factor Model ◽  
Model Fit ◽  
Equation Modeling ◽  
Wide Range

Dimensionality of the Colquitt justice measures was investigated across a wide range of service occupations. Structural equation modeling of data from 410 survey respondents found support for the 4-factor model of justice (procedural, distributive, interpersonal, and informational), although significant improvement of model fit was obtained by including a new latent variable, “procedural voice,” which taps employees' desire to express their views and feelings and influence results. The model was confirmed in a second sample ( N = 505) in the same organization six months later.

scholarly journals Influencing Factors of Facial Spa Treatment on Visit Intention: An Importance-Performance Matrix Analysis (IPMA) Approach

2021 ◽  
Vol 21 (3) ◽  
pp. 1087-1100
Author(s):  
Sook-Fern Yeo ◽  
Cheng-Ling Tan ◽  
Kah-Boon Lim ◽  
Elaine Lam
Keyword(s):  
Service Quality ◽  
Structural Equation ◽  
Brand Image ◽  
Target Population ◽  
Matrix Analysis ◽  
Equation Modeling ◽  
Performance Matrix ◽  
Wide Range ◽  
Spa Treatment ◽  
Age Range

Nowadays, grooming is considered an essential part of life to maintaining and up keeping a healthy and hygienic outlook which plays a key role in social bonding. As it turns out, the desire to looking good has spawned a wide range of beauty products causing the beauty industry to thrive and grow at a rapid rate. In other words the Malaysian Beauty Salon Markets have become big business today, driven by a rising population, disposable incomes, urbanisation and increasing influence of western culture to look good and to feel good. The beauty market is valued at USD 119.24 million and is expected to grow at a CAGR of 5.23% in the next five years, to USD 153.86 million in 2015. As a result of a highly fragmented in this market, the need for differentiation from other salons is impendency for this industry. This research aims to study the different attributes of customer's concerns and reveals the final factors that generate customer intention to visit facial spa treatment centres in Malaysia. The effort is devoted to identifying those dimensions of services provided in facial spa treatment centres for instance, atmospheric, service quality, price, brand image and location which aid to build up a greater relationship with their patrons. Data is collected via questionnaires distribution from the target population of the female with the age range from 16-63 years old. A sample size of 308 was studied and data analysis involving Structural Equation Modeling SmartPLS version 3.0 software were used. Service quality reached the conclusion as the strongest predictor in influencing customer intention to visit facial spa treatment centres, followed by the factors of price and brand image. Further to that, an Importance-Performance matrix analysis was conducted in order to identify factors that need to be given priority for spa owners in Malaysia. These findings made contributions beyond the high context services for instance beauty salons, massage salons, hair salons, nail salons, financial consulting and medical care with the matching services characteristics.

scholarly journals A Study Investigating How the Characteristics of High Reliability Organisations Can Be Measured in the Construction Industry in Australia

2020 ◽  
Vol 17 (21) ◽  
pp. 8273
Author(s):  
Andrew Enya ◽  
Shane Dempsey ◽  
Manikam Pillay
Keyword(s):  
Construction Industry ◽  
Structural Equation ◽  
Construction Projects ◽  
Safety Management ◽  
High Reliability ◽  
The Body ◽  
Equation Modeling ◽  
Toxic Substances ◽  
Measurement Instruments ◽  
Wide Range

Construction activities involve a lot of risk as workers are exposed to a wide range of job hazards, such as working at height, moving vehicles, toxic substances, and confined spaces. The hazards related to a construction project are mostly unpredictable because construction projects move quickly due to project deadlines, and changing work environments. As a result of this, the industry accounts for one of the highest numbers of work-related claims, and the fourth highest incidence rate of serious claims in Australia. This research investigates how key safety management factors can measure the characteristics of high reliability organisations (HROs) in the construction industry in New South Wales Australia. To address the problem, a model is presented that can predict characteristics of HRO in construction (CHC). Using structural equation modeling (SEM), and confirmatory factor analysis (CFA), the model and measurement instruments are tested and validated from data collected from construction workers. The results identified the factors that effectively measure CHC, and the findings can also be used as a safety management strategy and will contribute to the body of knowledge in research.

The role of breadth and depth of vocabulary knowledge in second language listening comprehension

2020 ◽  
Vol 3 (1) ◽  
pp. 55-81
Author(s):  
Payman Vafaee
Keyword(s):  
Second Language ◽  
English Learners ◽  
Structural Equation ◽  
Listening Comprehension ◽  
Standardized Test ◽  
Vocabulary Knowledge ◽  
Equation Modeling ◽  
Measured Variable ◽  
Relative Contribution ◽  
Wide Range

Abstract The purpose of the current study was to examine the extent by which second language breadth and depth of vocabulary knowledge (BVK and DVK, respectively) were predictors of successful listening comprehension. To this end, along with a standardized test of listening comprehension ability, aural measures of both BVK and DVK were administered to 262 English learners within a wide range of proficiency level. The data were subjected to structural equation modeling, and the results showed that BVK and DVK were not measured in a psychometrically distinct way in the current study. This did not allow any conclusions about the relative contribution of BVK and DVK to listening ability at the construct level. However, at the measured-variable level, the findings showed that the DVK test scores were better predictors of success in listening comprehension than the ones from the BVK test.

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