Effects Of Exogenous Variables Research Articles

Comparison of Mediation Effects on Interaction and Multigroup Approach in Structural Equation Modeling PLS in Case of Bank Mortgage

“Structural Equation Modeling is one of multivariate statistical method that used to explain multiple relationships between latent variables simultaneously to test a mediation model to conduct a formal test on mediation effects. Application PLS-SEM for exploratory research and theory development are increasing. Under certain conditions, the effect of exogenous variables on endogenous variable is also strengthened or weakened by moderating variable. In SEM, there are two approaches in analyzing moderation variables, namely the interaction method and the multigroup method. This article aims to compare the mediation effect on interaction approaches and multigroup approaches in Structural Equation Modeling. The data used is the case of timeliness of Bank X mortgage payments. In this article, statistical methods are evaluated to compare indirect effect between groups and examine indirect effect on each group. It was concluded that Collectability Status moderates the indirect relationship between Capital and the Timeliness of Payment through Willingness to Pay. Debtors with current collectability status more strongly effect the Timeliness of Payment than debtors with incurrect collectability status. Theresults of testing indirect effects on moderation with interaction and multigroup approaches are not much different. In the multigroup approach, the bootstrap interval bias is smaller than the bootstrap interval bias in the interaction approach. The Q-square Predictive Relevance value in both methods is quite high, indicating that the model is good. On the Current Collectibility Status group Q^2 is 89.3%, in the incurrect Collectibility Status Q^2 is 84.2%. While in the interaction approach, Q^2 is 70.4%. Researcher recommend a multigroup approach to data that has categorical moderation variables because differences between groups can be directly observed without adding interaction variables in the model.”

Cell phone distraction behavior of young pedestrians: evidence from China

Cell phone use while walking escalates pedestrian safety risks, particularly among students, given their heavy reliance on these devices. Psychological factors wield significant influence on individual behavior, particularly among adolescents who navigate a blend of rational and social-reactive pathways in decision-making. Therefore, this paper employs the Prototype Willingness Model (PWM) to scrutinize psychological determinants of students’ cell phone use while walking, drawing on data from 368 valid samples. Structural equation modeling (SEM) dissects the impact of psychological constructs on this behavior, highlighting the significance of both the social response and reasoning pathways within PWM. The study comprehensively analyzes direct, indirect, and overall effects of exogenous variables on behavioral intention and behavior.

Management Implications: Repurchase Decisions in the Retail Technology Supply Chain in the Retail Industry in Digital Retail Companies

This study aims to find out how digital retail companies retain their customers by being active as registered partners who continue to make repurchases. Understanding partner’s positive perceptions is key in improving repurchase decisions. Marketing Strategy, Service Quality and situational factors are studied to understand the strengthening of these positive perceptions. Attitude Towards Norm is known as one of the predictors in influencing purchasing decisions so that the relationship between these variables is also studied in this study. This research method is quantitative. Data obtained from an online questionnaire of 384 respondents. Descriptive analysis was conducted to determine the demographic background of the respondents. Associative analysis was carried out to identify the relationship between Marketing Activities, Service Quality, Attitude Towards Norm, Social Influence and Repurchasing Decision. The results show that all the effects of exogenous variables are found to be significant, except that Service Quality does not directly have a significant effect on Repurchase Decision.

The Influence of Repair Quality on Aircraft Spare Part Demand Variability

Accurate estimation of spare part demand is challenging in the case of intermittent or lumpy demand, characterised by infrequent demand occurrence and variability in demand size. While prior research has considered the effect of exogenous variables on spare part demand, there is a lack of research considering the effects of repair quality and aggregated spare part demand behaviour across fleets of assets under the influence of multiple simultaneously acting drivers of failure. This research provides new insights towards the problem of estimating variable spare part demand through modelling and simulation of the effects of multiple, simultaneously considered spare part demand drivers. In particular, a contribution to the state of the art is introduced by the use of a Branching Poisson Process (BPP) to model repair quality effects for spare part demand generation in conjunction with several demand drivers. The approach is applied in a numerical study which involves component failure characteristics based on real-life data from an aircraft maintenance, repair and overhaul (MRO) provider. It is shown that repair quality improvements drive down the variance in the demand and the total number of failures over time, and outperform the effect of environmental drivers of failure in terms of demand generation.

Evaluation of Waste in Food Services: A Structural Equation Analysis Using Behavioral and Operational Factors

To make the activities of food service companies more sustainable, it is essential to continuously improve their production processes. Understanding which factors are associated with the phenomenon of waste, as well as how they are causally related, is essential for proposing more effective actions to mitigate it. However, the vast majority of studies consider only the analysis of behavioral factors in food waste. To fill this gap, this work evaluates the behavioral and operational dimensions of the phenomenon studied, assessing the implications of the interdependence and causality relations for the respective factors of these dimensions, bringing a broader perspective to the waste problem. The behavioral dimension is developed from the Theory of Planned Behavior (TPB) (Motivation (MO), Intention (IN), and Waste Behavior (CD)) associated with the operational aspects, which are treated in this study as Opportunity (OP), Ability (HB), and Waste Control and Management (CGD), through the use of structural equation modeling (SEM) using the partial least squares in a public food service establishment. The sample size was calculated using the GPower calculator. The composition of the sample was defined considering (i) public profile; (ii) definition of the number of indicators; and (iii) definition of the power of the statistical test and the effect of exogenous variables (f2). Contact was made by sending an email. A return of 102 respondents was obtained. A minimum value of 86 observations was necessary to achieve a statistical power of 80% to identify R2. Highlighting the participation of some indicators, Situational Factors 36%, Environmental Beliefs 29%, Health Risks 40%, Training 35%, and Technical Skills 42%, have a strong influence on the average variance extracted (AVE) in their constructs. The proposed model showed the importance of alignment between the factors of the behavioral and operational dimensions in view of improvements in production processes and reduction of waste in food service units.

Higher Education Governance and Lecturer Performance: The Role of Leadership, Commitment, and Culture

This study aims to formulate a model and analyze the direct influence of Transformational Leadership, Organizational Commitment, and Organizational Culture on Governance and Lecturer Performance in Private Universities. This study uses an associative quantitative approach or research aimed at knowing the effect of exogenous variables on endogenous variables. The population in this study were lecturers in Banten Indonesia; as many as 211 lecturers participated as respondents in this study. Data collection using survey methods and analysis techniques using SEM with Lisrel 8.80 software. Based on the findings of the study and the discussion of its findings, the following conclusions can be drawn: (1) Transformational Leadership Affect Private University Governance; (2) Transformational Leadership Has No Effect on Private College Lecturer Performance; (3) Organizational Commitment Affects Private University Governance; (4) Organizational Commitment Affects Private University Lecturer Performance; and (5) Organizational Culture Affects Private University Governance; (6) Organizational Culture does not affect the Performance of Lecturers of private universities; (7) Governance affects the work of a lecturer at a private university.

Latent-Space Dynamics for Prediction and Fault Detection in Geothermal Power Plant Operations

This paper presents a latent-space dynamic neural network (LSDNN) model for the multi-step-ahead prediction and fault detection of a geothermal power plant’s operation. The model was trained to learn the dynamics of the power generation process from multivariate time-series data and the effects of exogenous variables, such as control adjustment and ambient temperature. In the LSDNN model, an encoder–decoder architecture was designed to capture cross-correlation among different measured variables. In addition, a latent space dynamic structure was proposed to propagate the dynamics in the latent space to enable prediction. The prediction power of the LSDNN was utilized for monitoring a geothermal power plant and detecting abnormal events. The model was integrated with principal component analysis (PCA)-based process monitoring techniques to develop a fault-detection procedure. The performance of the proposed LSDNN model and fault detection approach was demonstrated using field data collected from a geothermal power plant.

Capturing long-memory properties in road fatality rate series by an autoregressive fractionally integrated moving average model with generalized autoregressive conditional heteroscedasticity: A case study of Florida, the United States, 1975–2018

Introduction: Time series models play an important role in monitoring and understanding the serial dynamics of road crash exposures, risks, outcomes, and safety performance indicators. The time-series methods applied in previous studies on crash time series analysis assume that the serial dependency decays rapidly or even exponentially. However, this assumption is violated in most cases because of the existence of long-memory properties in the crash time series data. Ignoring the long-memory dependency could result in biased understanding of the dynamics of road traffic crashes. Method: To fill this research gap, this study proposes an autoregressive fractionally integrated moving average model with generalized autoregressive conditional heteroscedasticity (ARFIMA-GARCH) to capture and accommodate the long-memory decencies in the road fatality rate time series. To further investigate how the factors influencing the fatality risks play a role in the long-memory dependence, the effects of exogenous variables are examined in this study. The analysis is conducted based on the road crash fatality data in Florida, USA over 44 years. Results’ Conclusions: The case analysis confirmed the existence of long-memory property in the crash fatality time series data by both the joint tests of Augmented Dickey-Fuller and the Phillips–Perron, and the integer order of differencing (≤0.5) in the proposed models. The model results reveal that gasoline price and alcohol consumption per capita is positively associated with road fatality risks, whereas unemployment rate and rural/urban road mileage are negatively related to the road fatality risks. Practical Applications: The significant influential factors are also found to account for the long-memory serial correlations between road traffic fatalities to some extent.

Student Entrepreneurial Intention Model in Medan City

This study aims to analyze how the influence of the variables of intellectual intelligence, emotional intelligence, and spiritual intelligence on students' entrepreneurial intentions, using the intervening variables of student creativity and learning achievement. The research was conducted at polytechnic higher education institutions (public and private) in Medan City. The number of research samples was 400 people, and the data were analyzed using a structural equation model with Amos software. For the direct effect of exogenous variables, it was found that students' intellectual intelligence and creativity had a statistically significant impact. In contrast, the variables of emotional intelligence, spiritual intelligence, and learning achievement were not statistically significant. The indirect impact variables used to estimate entrepreneurial intentions are statistically significant, except for the emotional intelligence variable. Furthermore, as an intervening variable, the learning achievement variable provides a partial mediation effect in mediating the influence of the intellectual intelligence variable on entrepreneurial intentions. The learning achievement variable also provides a partial mediation effect in mediating the impact of the spiritual intelligence variable on entrepreneurial intentions. In contrast, the learning achievement variable provides no mediation effect in mediating the influence of the emotional intelligence variable on entrepreneurial intentions.

PENGARUH KEPEMIMPINAN TRANSFORMASIONAL, KOMITMEN ORGANISASIONAL, BUDAYA ORGANISASI DAN TATA KELOLA TERHADAP KINERJA DOSEN PERGURUAN TINGGI SWASTA DI PROVINSI BANTEN

This study aims to formulate a model and analyze the direct influence of Transformational Leadership, Organizational Commitment and Organizational Culture on Governance and Lecturer Performance in Private Universities in Banten. This study uses an associative quantitative approach, or research aimed at knowing the effect of exogenous variables on endogenous variables. Data collection using survey methods, and analysis techniques using SEM with Lisrel 8.80 software. The population in this study were lecturers at Bina Bangsa University, Banten Jaya University and Serang Raya University, as many as 211 lecturers participated as respondents in this study. The results showed that (1) Transformational Leadership Has No Significant and Positive Effect on Governance, (2) Transformational Leadership Has No Significant and Negative Effect on Lecturer Performance, (3) Organizational Commitment Has Significant and Negative Effect on Governance, (4) Organizational Commitment Significant and Positive Influence on Lecturer Performance, (5) Organizational Culture Has No Significant and Negative Effect on Governance, (6) Organizational Culture Has No Significant and Negative Effect on Lecturer Performance, (7) Governance Has Positive and Influence on Lecturer Performance. There is empirical evidence and novelty or new findings that the existence of good governance can improve Lecturer Performance, with a positive correlation direction coefficient.

The Role of Purchasing Decisions Mediating Product Quality, Price Perception, and Brand Image on Customer Satisfaction of Kopi Janji Jiwa

This research study analyses and determines the role of purchasing decisions mediating product quality, price perception, and brand image on Kopi Harapan Jiwa's customer satisfaction. The population in this study were customers of Kopi Janji Jiwa 135 respondents. The use of samples with purposive sampling technique and target customers who have bought or consumed Kopi Janji Jiwa. Stages in data analysis with a structural equation model on partial least squares to see the effect of exogenous variables on endogenous variables. The structural model is known to moderate purchasing decisions, while customer satisfaction has a strong influence. The predictive capability is large, and the model performance between the structural and measurement models is in a good category. According to hypothesis testing, it was found that product quality and price perception did not significantly affect purchasing decisions, but the brand image had a significant influence on purchasing decisions. Product quality and price perception were found to significantly affect customer satisfaction while purchasing decisions were found to have no significant effect. The brand image was found not to have a significant effect on customer satisfaction. Meanwhile, purchasing decisions found a significant influence. In purchasing decisions, there is a significant influence on customer satisfaction.

The Influence of Work Culture, Compensation and Work Spirit on Employee Performance of Health Office in in Pariaman City

The biggest challenge for local governments in realizing the success of health development as well as the biggest hope is how to manage human resources (HR) dynamic, productive hard worker to achieve Indonesia's Vision 2045. The Health Office as OPD that handles the health sector has not yet reached the work target according to the predetermined work plan. To achieve the highest degree of health requires hard work in the health sector. This study is to reveal the influence of work culture, compensation and employee morale in the Pariaman City Health Office. With quantitative methods and a saturated sample of 62 employees, questionnaires, interviews and observations were carried out. Data testing was carried out with validity and reliability. The results of the path analysis state that there are direct and indirect effects of exogenous variables on endogenous variables.There is an influence of work culture, compensation and work morale on the performance of the employees of the Kota Pariaman Health Office by 55% and an indirect effect of 31.6%. The rest is influenced by other variables not examined in this study.

Forecasting Charging Demand of Electric Vehicles Using Time-Series Models

This study compared the methods used to forecast increases in power consumption caused by the rising popularity of electric vehicles (EVs). An excellent model for each region was proposed using multiple scaled geographical datasets over two years. EV charging volumes are influenced by various factors, including the condition of a vehicle, the battery’s state-of-charge (SOC), and the distance to the destination. However, power suppliers cannot easily access this information due to privacy issues. Despite a lack of individual information, this study compared various modeling techniques, including trigonometric exponential smoothing state space (i.e., Trigonometric, Box–Cox, Auto-Regressive-Moving-Average (ARMA), Trend, and Seasonality (TBATS)), autoregressive integrated moving average (ARIMA), artificial neural networks (ANN), and long short-term memory (LSTM) modeling, based on past values and exogenous variables. The effect of exogenous variables was evaluated in macro- and micro-scale geographical areas, and the importance of historic data was verified. The basic statistics regarding the number of charging stations and the volume of charging in each region are expected to aid the formulation of a method that can be used by power suppliers.

Assessing the performance of deep learning models for multivariate probabilistic energy forecasting

Deep learning models have the potential to advance the short-term decision-making of electricity market participants and system operators by capturing the complex dependences and uncertainties of power system operation. Currently, however, the adoption of global deep learning models for multivariate energy forecasting in power systems is far behind the developments in the deep learning research field. In this context, the objectives of this study are to review recent developments in the field of probabilistic, multivariate, and multihorizon time series forecasting and empirically evaluate the performance of novel global deep learning models for forecasting wind and solar generation, electricity load, and wholesale electricity price for intraday and day-ahead time horizons. Two forecast types, deterministic and probabilistic forecasts, are studied. The evaluation data consist of real-world datasets with hourly resolution at the levels of an individual customer and regional and national electricity market bidding zones. The model evaluation criteria include achievable levels of forecasting accuracy and uncertainty risks, hyperparameter sensitivity, the effect of exogenous variables and fieldwise dataset split, and run-time efficiency factors, such as memory utilization, simulation time, electricity consumption, and convergence rate. We conclude that the performance of the global models is more beneficial for intraday forecasts of heterogeneous datasets with nonuniform patterns of time series, but can be affected by the hyperparameter sensitivity and hardware limitations with the growth of dataset dimensionality. The results can serve as a reference point for the quantitative evaluation of deep learning models for probabilistic multivariate energy forecasting in power systems.

Pengaruh Nilai Tukar (Kurs) dan Inflasi terhadap Tingkat Non Performing Financing (NPF) Pada Bank Syariah

The level of Non-Performing Financing at Islamic Banks is higher than conventional banks, while in terms of total assets, Islamic Banks are smaller. This study aims to analyze the effect of exogenous variables consisting of the level of inflation and the exchange rate of the rupiah against non Performing Financing in Islamic banks. This study uses time series data from 2016-2018. The population in this study consisted of Islamic Commercial Banks. The sampling technique used in this research is purposive sampling technique. The data analysis technique used is Multiple Linear Regression. The results showed that the inflation variable had a positive and significant effect on Non Performing Financing. While the Exchange Rate has no effect on Non Performing Finance. Meanwhile, simultaneously the two independent variables affect the independent variables.

Ciclos econômicos na produção, preço e exportação de cacau no Brasil

O presente trabalho buscou analisar, para a cultura cacaueira, a presença de ciclos econômicos na produção, exportação e preços dessa commodity. Através da análise espectral, observou-se a existência de comportamento cíclico em todas as séries. O ciclo bienal compartilhado por todas as variáveis refere-se ao ciclo vegetativo e reprodutivo da planta, ou seja, coincidentes com o cultivo e a maturação biológica do fruto. Os resultados mostraram ainda, um ciclo longo de 4,8 a 11,6 anos, que pode se referir ao efeito das variáveis exógenas na composição do preço internacional do cacau. Essas flutuações cíclicas elevam a instabilidade de preços, gerando desestímulo à produção em períodos de recessão e excedente em períodos de ascensão, resultando em flutuações nas quantidades exportadas.

Efektifitas Penarikan Retribusi Parkir Pasar Ditinjau Dari Kualitas Pelayanan

One of the main components of Regional Original Revenue is regional retribution. Thus in order to improve the ability of Regional Original Revenue, one of them can be achieved by increasing regional revenues from the regional retribution sector. The service quality received by market users as retribution payers will affect the achievement of market retribution targets. The thesis purpose was to analyze the effect of the service quality of Industry and Trade Departement on the effectiveness of withdrawing market parking retribution in Blitar City. 
 The research design was intended to test the research hypothesis and to interpret the causal relationship between independent variables and dependent variables, namely the variable service quality of the market service (X) and the effectiveness of withdrawing market parking retribution (Y). The population was the people who use parking on the market of Blitar City which amounts to an average of 880 people every day. The sample size was 90 respondents with Proportionate Stratifeid Sampling technique. The research instrument used a questionnaire and has been tested for validity and reliability testing. To test or measure the effect of exogenous variables on the endogenous variable used rimple regression analysis. 
 The results showed that there was an effect of the service quality of Industry and Trade Departement affected the effectiveness of withdrawing the parking market retribution in the city of Blitar. The t value was 20,859 that higher than t-table value amount 1,980. The coefficient of determination between the service quality variable of the Trade and Industry Departement (X) with the variable effectiveness of the withdrawal of the market parking retribution (Y) is (0.912)2 = 0.832. This figure indicates that there was 83,2% changes to variable Y explained or determined by variable X. Based on the results, it is expected that the Trade and Industry Departement had improve the quality and quantity of market facilities and infrastructure and parking, so that traders can run their business maximally and consumers are comfortable to shop in traditional markets.

The Solow-Swan model with endogenous population growth

This paper presents a reformulation of the classical Solow-Swan growth model where a dynamic of the endogenous population is incorporated. In our model, the population growth rate continually depends on per capita consumption. We find that – as in the classic Solow-Swan model – there is a steady state for the capital-labour ratio, which is always lower than that deduced from the original model with zero population growth rate, but it is not necessarily unique. Under certain conditions, there is an odd amount, and only the smallest and the largest are locally stable. Finally, a study of comparative static of stationary states is performed by varying the total factor productivity, and the results are compared with those of the original model. It is found that the effects of exogenous variables on endogenous variables differ from the original model.

Examining the Mediation Effect of Exogenous Variables over Brand Switching Behavior: Evidences from Indian Women Consumers

Examining the Mediation Effect of Exogenous Variables over Brand Switching Behavior: Evidences from Indian Women Consumers

“All along the curves”: Bridging the gap between comparative statics and simultaneous econometric models

A simultaneous econometric model of supply and demand provides estimates of own-price effects and the effect of exogenous variables on supply or demand. Most of the time economists use elasticities derived from econometric analysis in a ceteris paribus context, more seldom in a total elasticity setting (Buse in J Farm Econ 40:881–891, 1958). Perhaps even more seldom net effects of exogenous changes on prices and quantities are determined in a Muth (Oxf Econ Pap 16:221–234, 1964) type model. In this paper, we replicate the econometric model by Epple and McCallum (Econ Inq 44:374–384, 2006) and use it to specify a comparative static model that quantifies the period-to-period net effects on price and quantity from observed changes in the exogenous variables. Furthermore, we extend (Braekkan et al. in Eur Rev Agric Econ 45:531–552, 2018) approach for computing unexplained demand shifts by also calculating unexplained shifts in supply. This bridges the gap between comparative statics and simultaneous econometric models. Unexplained supply and demand shifts account for the unexplained variation in the endogenous variables. The data used in this application are from the US broiler chicken market.