scholarly journals Mechanism Underlying the Formation of Virtual Agglomeration of Creative Industries: Theoretical Analysis and Empirical Research

2021 ◽  
Vol 13 (4) ◽  
pp. 1637
Author(s):  
Xu Chen ◽  
Chunhong Liu ◽  
Changchun Gao ◽  
Yao Jiang
Keyword(s):  
Digital Technology ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Creative Industries ◽  
Theoretical Research ◽  
Creative Economy ◽  
Cultural Resources ◽  
Questionnaire Surveys ◽  
Network Collaboration ◽  
Geographical Space

Industrial agglomeration serves as an effective model for developing the creative economy and manifests itself as the interdependence of creative subjects in geographical space. The traditional methods of resource agglomeration have undergone tremendous changes due to the development of digital technology. These transformations have given birth to a new organizational form of the virtual agglomeration of creative industries. The present work uses field interviews and grounded theoretical research methods to construct a theoretical model of this new organizational phenomenon. Questionnaire surveys and empirical testing using structural equation models are here combined to systematically analyze the formation mechanism of the virtual agglomeration of creative industries. The results show that digital technology, virtual platforms, digital creative talents, digitization of cultural resources, and government policies have driven the formation of the virtual agglomeration of creative industries. This has been achieved through network collaboration, freedom of participation, and trust guarantee mechanisms. The effect of emerging consumer demand on the virtual agglomeration of creative industries is not significant. In addition, the implications of this research are also considered and discussed.

scholarly journals The Effects of Public Health Emergencies on Altruistic Behaviors: Empirical Research on the COVID-19 Pandemic in China

2020 ◽  
Author(s):  
Xiaotong Jin ◽  
Ershuai Huang ◽  
Wei Song ◽  
Taiyang Zhao
Keyword(s):  
Public Health ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Altruistic Behavior ◽  
Sense Of Control ◽  
Negative Effects ◽  
Public Health Emergencies ◽  
Negative Effect ◽  
Questionnaire Surveys ◽  
Viral Components

Abstract Background: The coronavirus disease 2019 (COVID-19) pandemic constitutes a public health emergency that threatens all of society. During this time, it is important for people to help each other by providing support related to the viral components of the pandemic while also assisting with difficulties experienced at the social level. However, the nature of the infection itself puts everyone at risk, which may prevent altruistic behaviors. In other words, the pandemic has created a dilemma in which individuals may need to choose between their personal safety and continuing to help others. As such, this study explored how public health emergencies affect altruistic behaviors in the context of COVID-19.Methods: Questionnaire surveys were distributed to 1508 residents from 31 provinces across China in February 2020 during the outbreak of COVID-19. Structural equation models were then implemented to test multiple research hypotheses using the obtained data.Results: Findings showed that the severity of the pandemic had both positive and negative effects on altruistic behaviors. Empathy mediated the positive relationship between the severity of the pandemic and altruistic behavior, while the sense of control mediated the negative effect between the severity of the pandemic and altruistic behavior.Conclusions: In the context of public emergencies such as the COVID-19 pandemic, altruistic behaviors can be enhanced by strengthening the factors of empathy and sense of control. These findings are useful for a government’s altruistic behavior promotion and disaster risk management.

Integration quality, value co-creation and resilience in logistics service supply chains: moderating role of digital technology

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yingjie Ju ◽  
Hanping Hou ◽  
Jianliang Yang
Keyword(s):  
Supply Chain ◽  
Digital Technology ◽  
Structural Equation ◽  
Equation Model ◽  
Theoretical Research ◽  
Content Type ◽  
Logistics Service ◽  
The Relationship ◽  
Moderating Role

PurposeUsing the logistics service supply chain (LSSC) as a research object, this study focuses on the relationship between integration quality (IQ), value co-creation (VCC), and LSSC resilience. Moreover, it discusses the moderating role of digital technology (DT).Design/methodology/approachBased on data about China, this study used the structural equation model to test the research hypothesis. To verify the validity of each construct, this study used various established scales in the literature to conduct exploratory and confirmatory analysis.FindingsThe results show that IQ is an essential antecedent variable that promotes VCC and LSSC resilience. Moreover, this study confirms that DT has a positive moderating effect on the relationship between IQ, VCC, and resilience.Originality/valueThis study constructs a research framework to examine LSSC resilience and expands the theoretical research on the VCC theory in the supply chain literature. Moreover, this paper studies supply chain integration from a new perspective, that is, IQ, which is more in line with the reality of LSSC.

Factors Influencing Intention to Technological Use in Older Adults. The TAM Model Aplication

2021 ◽  
pp. 016402752110637
Author(s):  
Antonio V. Martín-García ◽  
Rosa Redolat ◽  
Sacramento Pinazo-Hernandis
Keyword(s):  
Older Adults ◽  
Digital Technology ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Functional Adaptation ◽  
Perceived Ease Of Use ◽  
Tam Model ◽  
Main Determinants

The use of digital technology by older adults has improved in recent years in response to the need for their functional adaptation to an increasingly technological social context. Understanding this type of technological adaptation has recently become an important field of inquiry in both social and gerontological studies. Working within this framework, the aim of this study is to identify the main determinants that influence the intention of older people to use digital technology in their daily lives, using the Technological Acceptance Model. A study was carried out with the participation of 1155 people over 65 years of age in Spain. Confirmatory Factor Analysis and structural equation models (SEM) were performed. The results show that the TAM is a useful model to explain the intention of older adults to use Digital Technology, showing a high predictive power, highlighting Perceived Usefulness and Perceived Ease of Use as the main predictor variables.

Measuring the Big Five in Self-Report and Other Ratings

2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara
Keyword(s):  
Big Five ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Error Variance ◽  
The Self ◽  
Self Report ◽  
Sources Of Information ◽  
Third Person ◽  
Fit Indexes ◽  
Response Modes

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.

Collective Efficacy and Organizational Commitment in an Italian City Hall

2009 ◽  
Vol 14 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Laura Borgogni ◽  
Silvia Dello Russo ◽  
Laura Petitta ◽  
Gary P. Latham
Keyword(s):  
Organizational Commitment ◽  
Collective Efficacy ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Practical Significance ◽  
City Hall ◽  
Italian City ◽  
Public Sector Managers ◽  
The Individual ◽  
Level Group

Employees (N = 170) of a City Hall in Italy were administered a questionnaire measuring collective efficacy (CE), perceptions of context (PoC), and organizational commitment (OC). Two facets of collective efficacy were identified, namely group and organizational. Structural equation models revealed that perceptions of top management display a stronger relationship with organizational collective efficacy, whereas employees’ perceptions of their colleagues and their direct superior are related to collective efficacy at the group level. Group collective efficacy had a stronger relationship with affective organizational commitment than did organizational collective efficacy. The theoretical significance of this study is in showing that CE is two-dimensional rather than unidimensional. The practical significance of this finding is that the PoC model provides a framework that public sector managers can use to increase the efficacy of the organization as a whole as well as the individual groups that compose it.

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

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