• The Journal of Industrial Distribution & Business
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• v.12 no.8
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• pp.33-39
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• 2021

Purpose: The influence of age on time preference is not identified in the usual cross-sectional analysis. This study aims to test whether age affects time preference after controlling for the effects of individual heterogeneity including cohort effects. Research design, data and methodology: Drawing on a nationally representative panel dataset of Indonesians, we estimate the effects of age on time preference after controlling for unobserved individual heterogeneity as well as potential cohort effects. We measure time preference exploiting information on two sets of multiple price lists: one for a one-year delay, and the other for a five-year delay. Results: When we controlled for time-invariant individual characteristics, including birth cohort effects in a fixed effects model, the older men and women were more patient in a linear fashion, particularly when the delay was longer. To highlight the importance of controlling for individual fixed effects, we repeated the specification without controlling for individual fixed effects in OLS or censored maximum likelihood regression; we found no relation between age and impatience in men or women and for a one or five-year delay. Conclusions: The older men and women are more patient, and time preferences are correlated with unobserved individual heterogeneity.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.1-11
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• 2023

Federated learning (FL) is a ground breaking machine learning paradigm that allow smultiple participants to collaboratively train models in a cloud environment, all while maintaining the privacy of their raw data. This approach is in valuable in applications involving sensitive or geographically distributed data. However, one of the challenges in FL is dealing with heterogeneous and non-independent and identically distributed (non-IID) data across participants, which can result in suboptimal model performance compared to traditionalmachine learning methods. To tackle this, we introduce FedGCD, a novel FL algorithm that employs Graph Neural Network (GNN)-based community detection to enhance model convergence in federated settings. In our experiments, FedGCD consistently outperformed existing FL algorithms in various scenarios: for instance, in a non-IID environment, it achieved an accuracy of 0.9113, a precision of 0.8798,and an F1-Score of 0.8972. In a semi-IID setting, it demonstrated the highest accuracy at 0.9315 and an impressive F1-Score of 0.9312. We also introduce a new metric, nonIIDness, to quantitatively measure the degree of data heterogeneity. Our results indicate that FedGCD not only addresses the challenges of data heterogeneity and non-IIDness but also sets new benchmarks for FL algorithms. The community detection approach adopted in FedGCD has broader implications, suggesting that it could be adapted for other distributed machine learning scenarios, thereby improving model performance and convergence across a range of applications.

• Asian Journal for Public Opinion Research
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• v.1 no.2
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• pp.103-127
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• 2014

This study reviews existing research on the measurement of and the relationship between political diversity and political participation. It addresses the inconsistency in the arguments of existing studies researching the influence of political diversity on political participation. It attempts to find the cause in the variety of approaches to conceptualize and operationalize the two variables. As the measure of political diversity, political network heterogeneity and network attributes are discussed in detail in specific relation to political participation. As for political participation, an in-depth analysis of various ways to understand different forms of political involvement is presented. Implications for public opinion research are discussed.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.279-293
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• 2023

This study investigates network effects to measure how strongly the early adopters affect the brand choice of the potential consumer. By using the Gumbel-Hougaard (GH) copula, this study checks the magnitude of network effects varied from country to country. To consider consumer heterogeneity and network effects in the growth market, this study proposes the multi-brand Gamma/Shifted-Gompertz (m-G/SG) model based on the GH copula. Out of eighteen Western European cellular phone market data and South Korea smartphone data sets, the m-G/SG model provides an improvement in the estimation accuracy over the Libai, Muller, and Peres model. The results show that network effects enhance (i) the polarization of brand choice probabilities as time elapses; (ii) the dominance of the more preferred and the earlier entered brand; and (iii) the deceleration of category-level diffusion. Potential followers can analyze their relationship with earlier entrants through the m-G/SG model and also establish an optimal market entry strategy.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.679-684
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• 2007

This paper proposes a scheme to estimate the technical efficiency of trucks in logistics as performance measure by Data Envelopment Analysis (DEA). The result of technical efficiency estimation shows that there exists a substantial opportunity for improvement in technical efficiency of trucks and also the heterogeneity in the technical efficiency among trucks.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.179-186
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• 2002

We usually execute the blocking under heterogeneity of experimental condition in response surface methodology. We can suggest the measure for evaluating nearly orthogonal blocking under second order models.

• Journal of Information Technology Services
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• v.9 no.1
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• pp.173-197
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• 2010

Though service is recognized as not only a new driver for economy growth but also a source for sustainable value creation, it has been misunderstood in the literatures because of traditional characteristics of service such as inseparability, heterogeneity, intangibility, and perishability. This perspective can be a cause of barrier to approach a service. The purpose of this study is to develop and validate an instrument to measure of the service process. A series of statistical procedures were used to analyze the data, which proved that the instrument is valid and reliable. This study makes a contribution to both academic research and management practice. Theoretically, this study provides a measurement of service process in organizations for identifying service process. In practice, the results of this study will help organizations evaluate their service process innovation.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.383-393
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• 2018

The regional frequency analysis is the method which uses not only sample of target station but also sample of neighborhood stations in which are classified as hydrological homogeneous regions. Consequently, identification of homogeneous regions is a very important process in regional frequency analysis. In this study, homogeneous regions for regional frequency analysis of precipitation were identified by the self-organizing map (SOM) which is one of the artificial neural network. Geographical information and hourly rainfall data set were used in order to perform the SOM. Quantization error and topographic error were computed for identifying the optimal SOM map. As a result, the SOM model organized by $7{\times}6$ array with 42 nodes was selected and the selected stations were classified into 6 clusters for rainfall regional frequency analysis. According to results of the heterogeneity measure, all 6 clusters were identified as homogeneous regions and showed more homogeneous regions compared with the result of previous study.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.853-861
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• 2020

The study aims to measure the productivity of the Saudi banking sector at the retail level using secondary data for 11 local banks from the period 2015-2019. The study uses an extended version of the Cobb-Douglas production function to account for the fact that as banks openup more retail branches, they will need to employ more labor. The extended Cobb-Douglas production function was estimated using the two-way fixed effect model to account for unobserved heterogeneity across Saudi banks resulting from differences in labor competencies and leadership style. Besides, the model accounts for unobserved heterogeneity among Saudi banks due to the advancement in electronic services over time. The results showed that labor, branches, customers' deposits, and fixed deposits have a positive effect on the total value of generated loans. Conversely, ATM has an insignificant effect on generated loans. The average scale elasticity shows that the Saudi banks at the retail level are operating under decreasing returns to scale. The average marginal rate of technical substitution shows that Saudi banks need at least one ATM to replace one unit of labor at the retail level while keeping the same level of output.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.885-919
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• 2006

This paper revisits two conventional beliefs of environmental nonmarket valuation and examines their weaknesses and a new opportunity. The two beliefs are that willingness to pay (WTP) is an appropriate measure of nonmarket behaviour and that exogenous variables are relevant predictors of WTP whilst endogenous variables are not. The contemporary literature in psychology and economics is reviewed to demonstrate departures from these two beliefs. Tackling heterogeneity in stated preferences, both socio-demographic and psychological variables should be measured simultaneously to explain and predict choice behaviours more accurately.