Development and Validation of Extended Multi-Dimensional Scale of Entrepreneurial Ecosystem in the context of Pakistan

The purpose of this research is to validate the multi-dimensional scale of EntrepreneurialcEcosystem in the context of Pakistan. This research is based on 7 constructs with 54 items that affect the entrepreneurial ecosystem in any given region. The sample of 244 respondents are the owners of companies and, startups who participated in this research.The Confirmatory factory analysis showed factor loadings of all constructs greater than 0.40, while partial least square structural equation modeling showed acceptable values of construct reliability, composite reliability, however, average variance extracted was shown to be greater than 0.40 and less than the acceptable value of 0.5 for some constructs, while the HTMT ratio established discriminant validity of the constructs another criterion i.e. Fornell-Larcker criterion also established the discriminant validity of the constructs with some constructs having values less than 0.705, while some of the item outer loadings were found to be between 0.6-0.70 however, within the acceptable range. This research has validated the multi-dimensional scale of the entrepreneurial ecosystem with new sub-domain i.e. support professions and support finance. This scale can be used to measure the strength of the entrepreneurial ecosystem of any region with appropriate homogeneous sample

Elaboration of Social Media Performance Measures: From the Perspective of Social Media Discontinuance Behavior

Social media platforms insist on the so-called “number of visits, clicking, and subscription” as a measurement of social media performance. However, this method of measurement does not take into account dormant user accounts and unintentional clicks or visits. To fully understand social media performance, this study aims to examine the process of users’ discontinuance behavior from the view of technostress creators and socialstress creators through social media fatigue. Also, this study investigates the influence of involvement between social media fatigue and discontinuance behaviors. To understand the impact of technostress and social stress creators on users’ discontinuance behavior, this study conducted an off- and online survey in Korea. Using Confirmatory factory analysis (CFA), this study has a strong academic contribution because it identifies the existing methods measuring social media performance through numbers of accounts or joining in as inaccurate.

Validation of predicting transfer instruments in Spain

Purpose The purpose of this paper is to validate two scales, the factors predicting transfer (FPT) and the effectiveness questionnaire (CdE), in the Spanish Public Administration (SPA). Design/methodology/approach The FPT was administered at the end of the training, and the CdE four months after training. Participants had attended one of the 62 trainings offered by the SPA. With 1,457 participants, exploratory factor analysis (EFA; n = 728) and confirmatory factory analysis (CFA) (n = 729), randomly assigned, were performed on the FPT, and CFA (n = 726) was applied to the CdE. Findings A 30-item and four-factor solution emerged for the FPT through the EFA, which was confirmed by a good model fit through the CFA. A seven-item single-factor solution was confirmed for the CdE. Measurement invariance for the mode of instruction and gender was accepted for both instruments. Research limitations/implications Further research should be done in a more heterogenous sample that includes private organizations, different sectors and sizes. In the human resource development (HRD) field, these results suggest, in line with previous research, the existence of underlying constructs of factors of transfer that migrate across cultures. Practical implications The potential use of the FPT is the diagnosis of factors of transfer, and for the CdE, evaluation of the transfer of interventions at the behavioral level. The instruments are suitable for research and practice that compares online and in-class training. Originality/value The study performs the first rigorous analysis of measurement instruments to evaluate factors that predict transfer in Spain.

Development of a measure to assess acceptance of headache: The Headache Acceptance Questionnaire (HAQ)

Background Disability resulting from headache disorders is attributable in part to avoidant coping. Acceptance of pain connotes a willingness to experience pain in the service of life values, such that meaningful activities and goals are pursued despite pain. Acceptance facilitates positive health outcomes but has rarely been investigated in headache. Because headache disorders manifest differently than other forms of chronic pain, the present study sought to develop and validate a measure of acceptance of headache. Methods Forty-five candidate items were developed and, with input from an expert panel, reduced to 24 items. Five items were eliminated following administration to a development sample and exploratory factory analysis. Nineteen items were administered to a validation sample for confirmatory factory analysis and assessment of psychometric properties. Results Factor analysis produced a unidimensional six-item measure, the Headache Acceptance Questionnaire (HAQ). The HAQ evidenced good internal consistency, convergent validity with headache disability and related psychological constructs, and divergent validity with social desirability. The measure also distinguished between headache diagnostic groups. Conclusions Pending further validation in clinical settings, the HAQ may have utility in assessing psychological responses to headache symptoms, identifying targets of treatment for interventions that focus on reducing avoidance, and studying mechanisms of change.

It’s cool! analysis of factors that influence smart thermostat adoption intention

Smart thermostats represent an innovative smart home technology and a growing commercial opportunity, yet little is known about the salient factors that affect the adoption of such devices. To address this gap in research, we conduct a three-stage study that progresses through belief elicitation, exploratory factor analysis and confirmatory factory analysis within a nomological network. We leverage the mixed methods approach to explore the factorial structure of salient perceived benefits and concerns associated with smart thermostats, and we examine the effects of the emergent factors on the adoption intention. We discover that a novel factor, which we term techno-coolness, is the key predictor of the smart thermostat adoption intention. Techno-coolness encompasses the perceptions that a smart thermostat can make a home look modern and futuristic, be fun to use, and make the user feel technologically advanced. We also find that compatibility concerns as well as privacy concerns are significant impediments to the smart thermostat adoption intention.

The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study

Background The eHealth Literacy Scale (eHEALS) is the most widely used instrument in health studies to measure individual’s electronic health literacy. Nonetheless, despite the rapid development of the online medical industry and increased rural-urban disparities in China, very few studies have examined the characteristics of the eHEALS among Chinese rural people by using modern psychometric methods. This study evaluated the psychometric properties of eHEALS in a Chinese rural population by using both the classical test theory and item response theory methods. Objective This study aimed to develop a simplified Chinese version of the eHEALS (C-eHEALS) and evaluate its psychometric properties in a rural population. Methods A cross-sectional survey was conducted with 543 rural internet users in West China. The internal reliability was assessed using the Cronbach alpha coefficient. A one-factor structure of the C-eHEALS was obtained via principal component analysis, and fit indices for this structure were calculated using confirmatory factory analysis. Subsequently, the item discrimination, difficulty, and test information were estimated via the graded response model. Additionally, the criterion validity was confirmed through hypothesis testing. Results The C-eHEALS has good reliability. Both principal component analysis and confirmatory factory analysis showed that the scale has a one-factor structure. The graded response model revealed that all items of the C-eHEALS have response options that allow for differentiation between latent trait levels and the capture of substantial information regarding participants’ ability. Conclusions The findings indicate the high reliability and validity of the C-eHEALS and thus recommend its use for measuring eHealth literacy among the Chinese rural population.

The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study (Preprint)

BACKGROUND The eHealth Literacy Scale (eHEALS) is the most widely used instrument in health studies to measure individual’s electronic health literacy. Nonetheless, despite the rapid development of the online medical industry and increased rural-urban disparities in China, very few studies have examined the characteristics of the eHEALS among Chinese rural people by using modern psychometric methods. This study evaluated the psychometric properties of eHEALS in a Chinese rural population by using both the classical test theory and item response theory methods. OBJECTIVE This study aimed to develop a simplified Chinese version of the eHEALS (C-eHEALS) and evaluate its psychometric properties in a rural population. METHODS A cross-sectional survey was conducted with 543 rural internet users in West China. The internal reliability was assessed using the Cronbach alpha coefficient. A one-factor structure of the C-eHEALS was obtained via principal component analysis, and fit indices for this structure were calculated using confirmatory factory analysis. Subsequently, the item discrimination, difficulty, and test information were estimated via the graded response model. Additionally, the criterion validity was confirmed through hypothesis testing. RESULTS The C-eHEALS has good reliability. Both principal component analysis and confirmatory factory analysis showed that the scale has a one-factor structure. The graded response model revealed that all items of the C-eHEALS have response options that allow for differentiation between latent trait levels and the capture of substantial information regarding participants’ ability. CONCLUSIONS The findings indicate the high reliability and validity of the C-eHEALS and thus recommend its use for measuring eHealth literacy among the Chinese rural population.