Tianjie Deng, Anamika Barman-Adhikari, Young Jin Lee, Rinku Dewri and Kimberly Bender
This study investigates associations between Facebook (FB) conversations and self-reports of substance use among youth experiencing homelessness (YEH). YEH engage in high rates of…
Abstract
Purpose
This study investigates associations between Facebook (FB) conversations and self-reports of substance use among youth experiencing homelessness (YEH). YEH engage in high rates of substance use and are often difficult to reach, for both research and interventions. Social media sites provide rich digital trace data for observing the social context of YEH's health behaviors. The authors aim to investigate the feasibility of using these big data and text mining techniques as a supplement to self-report surveys in detecting and understanding YEH attitudes and engagement in substance use.
Design/methodology/approach
Participants took a self-report survey in addition to providing consent for researchers to download their Facebook feed data retrospectively. The authors collected survey responses from 92 participants and retrieved 33,204 textual Facebook conversations. The authors performed text mining analysis and statistical analysis including ANOVA and logistic regression to examine the relationship between YEH's Facebook conversations and their substance use.
Findings
Facebook posts of YEH have a moderately positive sentiment. YEH substance users and non-users differed in their Facebook posts regarding: (1) overall sentiment and (2) topics discussed. Logistic regressions show that more positive sentiment in a respondent's FB conversation suggests a lower likelihood of marijuana usage. On the other hand, discussing money-related topics in the conversation increases YEH's likelihood of marijuana use.
Originality/value
Digital trace data on social media sites represent a vast source of ecological data. This study demonstrates the feasibility of using such data from a hard-to-reach population to gain unique insights into YEH's health behaviors. The authors provide a text-mining-based toolkit for analyzing social media data for interpretation by experts from a variety of domains.
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F.A. DiazDelaO and S. Adhikari
In the dynamical analysis of engineering systems, running a detailed high‐resolution finite element model can be expensive even for obtaining the dynamic response at few frequency…
Abstract
Purpose
In the dynamical analysis of engineering systems, running a detailed high‐resolution finite element model can be expensive even for obtaining the dynamic response at few frequency points. To address this problem, this paper aims to investigate the possibility of representing the output of an expensive computer code as a Gaussian stochastic process.
Design/methodology/approach
The Gaussian process emulator method is discussed and then applied to both simulated and experimentally measured data from the frequency response of a cantilever plate excited by a harmonic force. The dynamic response over a frequency range is approximated using only a small number of response values, obtained both by running a finite element model at carefully selected frequency points and from experimental measurements. The results are then validated applying some adequacy diagnostics.
Findings
It is shown that the Gaussian process emulator method can be an effective predictive tool for medium and high‐frequency vibration problems, whenever the data are expensive to obtain, either from a computer‐intensive code or a resource‐consuming experiment.
Originality/value
Although Gaussian process emulators have been used in other disciplines, there is no knowledge of it having been implemented for structural dynamic analyses and it has good potential for this area of engineering.
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Saroj Adhikari, Thunwadee Suksaroj, Orapin Laosee, Cheerawit Rattanapan and Piyapong Janmaimool
This study investigates the willingness of household heads in Madhesh Province, Nepal, to enroll in the National Health Insurance Program (NHIP) and examines the contextual…
Abstract
Purpose
This study investigates the willingness of household heads in Madhesh Province, Nepal, to enroll in the National Health Insurance Program (NHIP) and examines the contextual barriers that may hinder this enrollment.
Design/methodology/approach
A quantitative cross-sectional study was conducted with 319 household heads through face-to-face interviews from May 15 to June 13, 2023. The ability, motivation and opportunity (AMO) framework guided the assessment, employing bivariate and multivariate binary logistic regression analyses to identify significant factors influencing willingness.
Findings
Over 80% of respondents were willing to enroll in NHIP, driven by significant factors such as perceived susceptibility to health issues (AOR = 15.65) and knowledge about NHIP benefits (AOR = 2.20). However, contextual barriers such as the lack of enrollment assistants (73%) and inadequate healthcare package offerings (53%) were prevalent, highlighting that despite a strong desire to enroll, these barriers prevent many from taking action.
Research limitations/implications
The findings highlight the need to address contextual barriers, such as expanding NHIP benefit packages and enhancing enrollment support, to convert willingness into action.
Practical implications
To enhance enrollment rates, it is crucial to address these barriers by increasing the availability of enrollment assistants and improving healthcare packages.
Social implications
Strengthening NHIP can reduce high out-of-pocket expenditures and contribute to achieving universal health coverage in Nepal.
Originality/value
This study provides critical insights into the factors affecting NHIP enrollment in one of Nepal’s lowest-enrollment regions, offering actionable recommendations for policy improvements.
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This study examines whether corporate earnings announcements affect investors' beliefs about future earnings using a sample of companies in the People's Republic of China…
Abstract
This study examines whether corporate earnings announcements affect investors' beliefs about future earnings using a sample of companies in the People's Republic of China. Revisions in financial analysts' consensus forecasts are used as a proxy for the change in the aggregate belief of investors in the market. Changes in the analysts' forecasts dispersion are used to measure the degree of convergence or divergence of the market's belief after the earnings announcements. Results show that both forecast revisions and changes in forecast dispersion are significantly and positively associated with the unexpected element in the earnings announcements. The results indicate that accounting earnings of Chinese companies contain information useful to the market and that the information is reflected in the analysts' subsequent forecasts of the companies' future earnings. The findings are also consistent with results from recent analytical studies, such as Kim and Verrecchia (1994), Barry and Jennings (1992) and Morse, Stephan and Stice (1991), that information disclosure may increase (rather than reduce) the disagreement among investors.
High‐dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high‐dimensional relationships between sets of…
Abstract
Purpose
High‐dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for capturing the high‐dimensional relationships between sets of input and output model variables. It is an efficient formulation of the system response, if higher‐order cooperative effects are weak, allowing the physical model to be captured by the lower‐order terms. The paper's aim is to develop a new computational tool for estimating probabilistic sensitivity of structural/mechanical systems subject to random loads, material properties and geometry.
Design/methodology/approach
When first‐order HDMR approximation of the original high‐dimensional limit state is not adequate to provide the desired accuracy to the sensitivity analysis, this paper presents an enhanced HDMR (eHDMR) method to represent the higher‐order terms of HDMR expansion by expressions similar to the lower‐order ones with monomial multipliers. The accuracy of the HDMR expansion can be significantly improved using preconditioning with a minimal number of additional input‐output samples without directly invoking the determination of second‐ and higher‐order terms. As a part of this effort, the efficacy of HDMR, which is recently applied to uncertainty analysis, is also demonstrated. The method is based on computing eHDMR approximation of system responses and score functions associated with probability distribution of a random input. Surrogate model is constructed using moving least squares interpolation formula. Once the surrogate model form is defined, both the probabilistic response and its sensitivities can be estimated from a single probabilistic analysis, without requiring the gradients of performance functions.
Findings
The results of two numerical examples involving mathematical function and structural/solid‐mechanics problems indicate that the sensitivities obtained using eHDMR approximation provide significant accuracy when compared with the conventional Monte Carlo method, while requiring fewer original model simulations.
Originality/value
This is the first time where application of eHDMR concepts is explored in the stochastic sensitivity analysis. The present computational approach is valuable to the practical modelling and design community.
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Rachel Mosier, Sanjeev Adhikari and Sandeep Langar
Those who believe they excel at architecture or engineering education are more likely to succeed based on self-efficacy principles. To investigate educator self-efficacy and…
Abstract
Purpose
Those who believe they excel at architecture or engineering education are more likely to succeed based on self-efficacy principles. To investigate educator self-efficacy and success in the Online Learning Environment (OLE), a set of relationships are observed which describe correlations between experience and potential.
Design/methodology/approach
An online survey instrument was distributed the fall after COVID-19 university closures. Respondents were asked to reflect on their level of experience teaching and their ability to teach online. All analyzed data were subjected to descriptive and inferential statistics using the SPSS 22.0 statistical software package. The compatibility of the variables with normal distribution was tested using the Kolmogorov–Smirnov and Shapiro–Wilk methods. Variables comparisons were performed using non-parametric tests (Kruskal Wallis test, Mann Whitney U test). The relationships between quantitative variables were examined using the Spearman Rank Correlation and comparisons formed from the qualitative variables were tested using the Pearson Chi-Square and Fisher Exact methods.
Findings
Educator self-efficacy was determined throughout the COVID-19 transition. Possessing online teaching experience is related to the perceptions that architectural education can be delivered entirely online. A relationship was found for educators who previously taught using OLE and who had experience with delivering and developing OLE.
Practical implications
It is incumbent on educators and administrators to continue to learn how to best accommodate student learning. The strong relationship for R1: Total teaching experience (IV) and perceptions of whether AEC education can be delivered completely online, points to having educators with a depth of experience and being open to change. The strong relationship shown for R2: Have you ever taught using an online method before January 2020 and Experience in developing online materials demonstrates that a variety of experience will also support educators in a time of change. These relationships illustrate how educator efficacy can provide support for educators during times of crisis.
Originality/value
U.S. Architectural and Architectural Engineering educator pandemic OLE self-efficacy has not been previously been a focus of research efforts. This research adds to the body of knowledge by demonstrating how relationships between teaching experience and OLE can encourage educator self-efficacy during a crisis. Statistical analyses found a strong relationship between total teaching experience and perceptions that AEC education can be delivered completely online. A strong relationship was found between online teaching experience and positive experiences in developing online materials.
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Amit Kumar Bardhan, Barnali Nag, Chandra Sekhar Mishra and Pradeep Kumar Tarei
An amalgamation of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) has been performed to develop a decision-making framework for…
Abstract
Purpose
An amalgamation of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) has been performed to develop a decision-making framework for improving the overall performance of the microfinance institutions. A primary survey was conducted to collect real-time data from the heterogeneous stakeholders of microfinance institutions across India. The validation of the proposed framework is performed by comparing the results against the conventional method of Analytical Hierarchy Process (AHP).
Design/methodology/approach
This study identifies various dimensions and indicators for measuring the performance of Indian microfinance institutions. Additionally, the ranking and prioritisation of the performance dimensions and indicators is obtained by considering the mutual interrelation between them.
Findings
The study indicates that there exists a significant dyadic relationship between financial performance and social performance for improving the overall performance of the microfinance institutions. Governance is found to unidirectionally influence both financial and social performance. Among all the considered dimensions, financial performance of a microfinance institution is the most critical dimension for improving the overall performance. The top five performance indicators of the Indian microfinance institutions are funding source, borrowing and overhead cost, size of the firm, end-use of the money and depth of outreach.
Research limitations/implications
The study was conducted in the context of Indian microfinance institutions; hence the scope of generalisation of the results is limited. This research considers both subjective and objective aspect of the performance dimensions and indicators from the perspective of multiple stakeholders (i.e. firm, society and regulator). The integrated framework is expected to aid in improving overall performance of microfinance institutions by focusing on the most critical (high prioritised) performance indicators.
Originality/value
An integrated DEMATEL-ANP framework is used in the domain of microfinance to assess the performance dimensions. This study is unique in terms of analysing performance of microfinance institutions from the perspective of heterogeneous stakeholders.
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This study is a response to the paucity of research into early internationalising firms based in India. We seek to explore the internationalisation of small and new Indian firms…
Abstract
Purpose
This study is a response to the paucity of research into early internationalising firms based in India. We seek to explore the internationalisation of small and new Indian firms and the decision-making process of their entrepreneurs/managers.
Methodology/approach
The study uses original, primary data gathered from in-depth, semi-structured interviews conducted with the managers of six such firms to explore the factors that might facilitate, motivate, or impede the efforts undertaken by young Indian firms to embark upon a process of early internationalisation.
Findings
Our findings suggest that, in line with their counterparts from other countries, the early internationalisation of small firms from India is driven primarily by the search for more favourable demand conditions overseas and is facilitated by new technologies. However, we find no evidence suggesting that the emergence of early internationalising firms from India is driven by the search for more favourable production conditions or by the direct international experience and exposure of their founders. In line with prior scholarly work, our research suggests that government support is an important facilitator of early internationalisation of small firms.
Originality/value
The study provides insights into the internationalisation process of INVs from India and contributes to broadening our understanding of the behaviour of firms under a set of specific institutional conditions. Based on our findings, we develop a conceptual framework which can be useful for further empirical testing. Our study is also one of the few to be conducted on a sample of INVs from India.
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R.R. Kumar, P.K. Karsh, Vaishali, K.M. Pandey and S. Dey
The purpose of this paper is to investigate the first three stochastic natural frequencies of skewed sandwich plates, considering uncertain system parameters. To conduct the…
Abstract
Purpose
The purpose of this paper is to investigate the first three stochastic natural frequencies of skewed sandwich plates, considering uncertain system parameters. To conduct the sensitivity analysis for checking the criticality of input parameters.
Design/methodology/approach
The theoretical formulation is developed based on higher-order-zigzag theory in accordance with the radial basis function (RBF) and stochastic finite element (FE) model. A cubic function is considered for in-plane displacement over thickness while a quadratic function is considered for transverse displacement within the core and remains constant in the facesheet. RBF is used as a surrogate model to achieve computational efficiency and accuracy. In the present study, the individual and combined effect of ply-orientation angle, skew angle, number of lamina, core thickness and material properties are considered for natural frequency analysis of sandwich plates.
Findings
Results presented in this paper illustrates that the skewness in the sandwich plate significantly affects the global dynamic behaviour of the structure. RBF surrogate model coupled with stochastic FE approach significantly reduced the computational time (more than 1/18 times) compared to direct Monte Carlo simulation approach.
Originality/value
The stochastic results for dynamic stability of sandwich plates show that the inevitable source uncertainties present in the input parameters result in significant variation from the deterministic value demonstrates the need for inclusive design paradigm considering stochastic effects. The present paper comprehensively establishes a generalized new RBF-based FE approach for efficient stochastic analysis, which can be applicable to other complex structures too.