Estimation Of Structural Models Research Articles

Full Quantity or Full Credit? Choosing the Right Buyback Policy for a Behavioral Retailer

Problem definition: Despite extensive research on buyback contracts in supply chain management, little attention has been given to a direct comparison between a traditional full-quantity, partial-credit (FQ) buyback contract and an alternative full-credit, partial-quantity (FC) contract, especially when considering the behavioral biases of the retailer. This study aims to fill this research gap by exploring how these biases influence contract performance and offer practical guidelines for suppliers. Methodology/results: Through controlled laboratory experiments and structural model estimation, we show that the ordering decisions made by human retailers are jointly affected by three behavioral biases—loss aversion, prospective accounting, and psychological cost of inventory error—and these biases differ in magnitude between the two contracts. Incorporating these biases into a behavioral retailer’s utility function, we then analytically examine which buyback policy the supplier should choose. When the wholesale price is exogenously given, the supplier should adopt the FC contract for high-margin (low-cost) products. Conversely, when the supplier has the power to set both the wholesale and buyback prices, the FC contract is generally more beneficial for low-margin products. Finally, when the product cost is sufficiently high, a wholesale price contract may be advantageous over buyback policies. Managerial implications: The managerial implication of this paper is significant for suppliers who have to choose between different buyback policies. The paper suggests that the supplier should carefully consider not just the economic, but also the behavioral dimensions when making contract decisions, particularly when dealing with a retailer influenced by behavioral biases. Specifically, the choice between FQ and FC contracts is influenced by two key environmental factors: the production cost of the product and the nature of wholesale pricing. Understanding these elements allows suppliers to be flexible in contract choices and design appropriate return policies for their downstream supply chain partners. Funding: P. Yu was supported by the National Natural Science Foundation of China [Grants 72371038 and 72033003] and the Fundamental Research Funds for the Central Universities [Grant 2024CDJSKPT16]. T. Feng was supported by the National Natural Science Foundation of China [Grant 72131004]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0574 .

The Relationship between Organizational Culture and Product Innovation with Employee Productivity and Financial Performance of Fintech Companies in Indonesia

This study looks into the connections between employee productivity, organizational culture, financial performance, and product innovation in Indonesian fintech companies. A quantitative study was carried out with the data that was gathered from 180 individuals. The data were analyzed using descriptive statistics, model fit evaluation, measurement model assessment, structural model estimation, and mediation analysis. The findings show that financial performance, staff productivity, product innovation, and organizational culture are all positively correlated. Product innovation is strongly influenced by organizational culture, and this has a favorable effect on worker productivity and financial performance. Furthermore, through both staff productivity and product innovation, mediation research demonstrates strong indirect benefits of organizational culture on financial performance. It was discovered that there is no substantial correlation between organizational culture and financial performance. The aforementioned results underscore the need of cultivating an accommodating organizational culture that stimulates creativity and efficiency in order to attain exceptional financial outcomes within the Fintech sector.

Multiply robust estimation of marginal structural models in observational studies subject to covariate-driven observations.

Electronic health records and other sources of observational data are increasingly used for drawing causal inferences. The estimation of a causal effect using these data not meant for research purposes is subject to confounding and irregularly-spaced covariate-driven observation times affecting the inference. A doubly-weighted estimator accounting for these features has previously been proposed that relies on the correct specification of two nuisance models used for the weights. In this work, we propose a novel consistent multiply robust estimator and demonstrate analytically and in comprehensive simulation studies that it is more flexible and more efficient than the only alternative estimator proposed for the same setting. It is further applied to data from the Add Health study in the United States to estimate the causal effect of therapy counseling on alcohol consumption in American adolescents.

The Effect of Technology Integration, Work-Life Balance, and Job Stress on Employee Well-Being in the Art Industry in Jakarta

This quantitative study investigates the impact of technology integration, work-life balance, and job stress on employee well-being within the art industry in Jakarta. Through a cross-sectional survey of 150 professionals, data were collected and analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS 3). The measurement model assessment confirmed the reliability and validity of the measurement instrument, while the structural model estimation revealed significant direct and indirect effects among the variables. The findings indicate that technology integration positively influences employee well-being, while work-life balance and job stress play significant roles in shaping employee welfare. These results underscore the importance of organizational strategies and interventions aimed at promoting a healthier, more supportive work environment within the art industry. The study contributes to a deeper understanding of the factors influencing employee well-being in the context of creative professions and provides valuable insights for organizational leaders, policymakers, and practitioners.

The Impact of Infrastructure Development, Education, Tourism, and Agriculture on Regional Economic Growth in Indonesia

In order to better understand the complex links between infrastructure development, education, tourism, agriculture, and regional economic growth in Indonesia, this study uses structural equation modeling with partial least squares or SEM-PLS. The research makes uses of a 287-observation dataset and applies rigorous measurement model evaluation, bootstrapping analysis, structural model estimation, and model validation against multiple fit indices. The results show a strong positive correlation between each sector—agriculture, tourism, education, and infrastructure development—and regional economic expansion. The necessity for comprehensive, integrated development strategies is highlighted by the interconnectedness of these interactions. In order to promote balanced and resilient regional economic growth, the findings provide policymakers with useful insights and highlight the significance of ongoing investments in infrastructure, education, and sustainable tourism and agricultural practices.

The Impact of Trust in Platform Providers on User Participation and Economic Benefits in the Sharing Economy in Indonesia

This research investigates the effect of trust in platform providers on user participation and economic benefits in the sharing economy within the context of Indonesia. Utilizing a quantitative approach, Structural Equation Modeling (SEM) with Partial Least Squares (PLS) path analysis was employed to analyze data collected from a sample of 150 participants. The measurement model assessment confirmed the reliability and validity of the latent constructs, while the structural model estimation revealed significant positive relationships between trust in platform providers and user participation, trust in platform providers and economic benefits, as well as user participation and economic benefits. Mediation analysis further demonstrated the mediating role of user participation in the relationship between trust in platform providers and economic benefits. The moderation analysis did not reveal any significant moderation effects. Overall, the findings contribute to understanding the dynamics of trust, user behavior, and economic outcomes in the Indonesian sharing economy context, offering insights for platform providers, policymakers, and researchers.

The Effect of Innovation, Entrepreneurship and Business Development on the Economic Independence of Muslims

This research investigates the impact of innovation, entrepreneurship, and business development on the economic independence of Muslims in Indonesia through a quantitative analysis. A sample of 120 respondents representing diverse demographic backgrounds was surveyed, and Structural Equation Modeling (SEM) with Partial Least Squares (PLS) was employed to analyze the data. The measurement model assessment confirmed the reliability and validity of the constructs, while the structural model estimation revealed significant positive relationships between innovation, entrepreneurship, business development, and economic independence. Hypothesis testing further validated these relationships, indicating that all three factors—innovation, entrepreneurship, and business development—have a significant positive effect on economic independence among Muslims in Indonesia. The findings underscore the importance of fostering innovation ecosystems, nurturing entrepreneurial talent, and creating conducive business environments to promote economic autonomy within the Muslim community. These insights have implications for policymakers, practitioners, and stakeholders seeking to design targeted interventions for inclusive economic development and sustainable growth in Indonesia.

The Influence of Social Capital, Entrepreneurial Competence and Entrepreneurial Ecosystem in Shaping Business Incubators in Indonesia

This study looks into how the entrepreneurial ecosystem, social capital, and entrepreneurial competence interact to influence how successful Indonesian business incubators are. Partial Least Squares Structural Equation Modeling (PLS-SEM) was the quantitative method used to examine the data collected from 275 entrepreneurs and incubator stakeholders. The evaluation of the measurement model demonstrated appropriate average variances extracted, strong loadings, and high composite reliabilities, all of which supported the validity and reliability of the selected indicators. Each latent variable's uniqueness was confirmed by discriminant validity analysis. Significant positive correlations between social capital, entrepreneurial competence, the entrepreneurial ecosystem, and the efficacy of business incubators were found by the structural model estimation. The suggested theoretical framework was validated by hypothesis testing, which showed that these elements interact to affect the performance of business incubators in Indonesia. A good fit was shown by the model fit assessment, supporting the structural model's validity. The results enhance our understanding from a theoretical and practical standpoint, offering policymakers, entrepreneurs, and stakeholders a comprehensive framework to maximize the conditions necessary for the success of business incubators.

Causal Effects of Time-Varying Exposures: A Comparison of Structural Equation Modeling and Marginal Structural Models in Cross-Lagged Panel Research

The use of structural equation models for causal inference from panel data is critiqued in the causal inference literature for unnecessarily relying on a large number of parametric assumptions, and alternative methods originating from the potential outcomes framework have been recommended, such as inverse probability weighting (IPW) estimation of marginal structural models (MSMs). To better understand this criticism, we describe three phases of causal research. We explain (differences in) the assumptions that are made throughout these phases for structural equation modeling (SEM) and IPW-MSM approaches using an empirical example. Second, using simulations we compare the finite sample performance of SEM and IPW-MSM for the estimation of time-varying exposure effects on an end-of-study outcome under violations of parametric assumptions. Although increased reliance on parametric assumptions does not always translate to increased bias (even under model misspecification), researchers are still well-advised to acquaint themselves with causal methods from the potential outcomes framework.

The shortcomings of equal weights estimation and the composite equivalence index in PLS-SEM

PurposeThe purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).Design/methodology/approachThe authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.FindingsThe results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.Research limitations/implicationsIn light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.Practical implicationsThe results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.Originality/valueTo the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

Least square estimation of non-linear structural models

A new method for estimating a wide class of structural equation models (SEM) is proposed and evaluated. A weighted least squares approach is used that estimates parameters and latent variables. This new approach is flexible enough to handle non-linear and non-smooth models and allows us to model various constraints. The method includes various strategies to deal with the problem of choosing weights. The principle strengths and weaknesses of this approach are discussed, and simulation studies are performed to reveal the problems and potential of this approach.

Designing school choice mechanisms: A structural model and demand estimation

AbstractDesigning the markets that allocate public school seats is a crucial policy consideration. This paper compares the design of school choice mechanisms in terms of economic efficiency, stability, and strategic behavior. We estimate demand for schools using data from a large US public school system with novel indicators of students' levels of strategic sophistication. We find important benefits of reserving a set of seats to be assigned by a pure lottery. In settings that share features in common with the school system we study, our findings suggest that non‐selective criteria such as lotteries induce a large increase in truth‐telling.

Expectation Formation with Correlated Variables

Abstract We experimentally study how people form expectations about correlated variables. Subjects forecast a time-series variable A. In treatment Baseline, subjects only observe past values of A. In treatment Correlated, they additionally observe a correlated variable B; A is equally predictable and has the same univariate properties in both treatments. Subjects are significantly less accurate and underreact more in Correlated, inconsistent with Bayesian learning. A structural-model estimation indicates that subjects (i) underestimate the level of correlation and (ii) are insensitive to actual correlation. Our study provides first direct evidence of correlation neglect in the domain of expectation formation.

Marketing Capabilities, Market Orientation and Food Security of Biofortified Cassava Producers in Nigeria

This paper proposed that marketing capability is a critical component of market orientation. As such, knowledge of intelligence and competitive strategy, aspects of market capability obtained through training is essential for market orientation. Cross-sectional survey was used. Data were collected with a structured questionnaire and analysed using the structural equation model (SEM). The structural model and path estimates indicate that all the constructs intervene in food security, implying that a systemic approach rather than individual strength can help achieve food security. The study's findings support the perspective that marketing capabilities have spill-over effects that improve market orientation and food security performance. Therefore, BoP producers through training can generate significant marketing capabilities that can improve the food market. It highlights the importance of producers adopting a market-oriented approach. The study recommended a multi-stakeholder engagement model toward integrating biofortification into public and private policies and programmes. This would encourage investment and continuous training of producers on how to improve communication and customer relationship management to stimulate consumption and supply.

INDONESIA’S PALM OIL EXPORT TO MALAYSIA AND THAILAND

<p class="MainHeading"><em>The economic recovery after the COVID-19 pandemic has significantly increased the demand for palm oil in Indonesia and globally. This study analyzes the regulation and valuation of palm oil trade between Indonesia and Malaysia and Thailand. In addition, the study focuses on Indonesia's exports to her two major countries in Southeast Asia. Based on prescriptive legal analysis, relevant stakeholders have enacted several new regulations to ensure the stability and availability of palm cooking oil. The Indonesian central government has enacted several new regulations related to palm cooking oil to ensure availability and affordability in the domestic market as well as to support exports abroad. A Structural Time Series Model (STSM) estimates that the trade value of Indonesian palm oil exports to Malaysia and Thailand will stabilize in 2022. Indonesia's export policy needs to take into account cyclical, seasonal and irregular patterns. Stakeholders should check for irregular factors such as 2020, 2021, the economic crisis, and the COVID-19 pandemic.</em><em> </em><em>Competent authorities must consider all aspects, especially international prices and palm oil exports, in order to implement best guidelines in a timely manner and to further review existing regulations. All palm oil stakeholders have adapted to the new regulations introduced by the government to ensure domestic supplies of palm cooking oil are available and affordable, and the remaining palm oil and its derivatives can be exported abroad.</em></p>

Estimation of marginal structural models under irregular visits and unmeasured confounder: calibrated inverse probability weights

Clinical information collected in electronic health records (EHRs) is becoming an essential source to emulate randomized experiments. Since patients do not interact with the healthcare system at random, the longitudinal information in large observational databases must account for irregular visits. Moreover, we need to also account for subject-specific unmeasured confounders which may act as a common cause for treatment assignment mechanism (e.g. glucose-lowering medications) while also influencing the outcome (e.g. Hemoglobin A1c). We used the calibration of longitudinal weights to improve the finite sample properties and to account for subject-specific unmeasured confounders. A Monte Carlo simulation study is conducted to evaluate the performance of calibrated inverse probability estimators using time-dependent treatment assignment and irregular visits with subject-specific unmeasured confounders. The simulation study showed that the longitudinal weights with calibrated restrictions improved the finite sample bias when compared to the stabilized weights. The application of the calibrated weights is demonstrated using the exposure of glucose lowering medications and the longitudinal outcome of Hemoglobin A1c. Our results support the effectiveness of glucose lowering medications in reducing Hemoglobin A1c among type II diabetes patients with elevated glycemic index (ge 8.5 %) using stabilized and calibrated weights.

SECOND TIME SWEETER? MARITAL MATCHING BETWEEN FIRST AND SECOND MARRIAGES

ABSTRACT We use data from the National Longitudinal Survey of Youth, 1979 (NLSY79) to examine changes in matching patterns between first and second marriages in the US. Using Becker''s (1973, 1974) efficient marriage market hypothesis and following Dalmia and Sicilian (2008), we develop an empirical framework to understand the importance of individual traits in spouse selection. Our structural model estimates indicate that positive assortative mating (degree of homogamy) strengthens in second marriages over first marriages. The share of couples who marry up (hypergamy) and marry down (hypogamy) falls substantially as individuals sort to partners who are more similar to them in many aspects, particularly age, education, and hours worked, in their second marriage. Finally, we find the matching patterns of second marriages to be similar to those of ongoing first marriages, providing further evidence that “likes do marry likes.” Keywords Marital assignments, assortative mating, market efficiency

Longitudinal effects of lipid indices on incident cardiovascular diseases adjusting for time-varying confounding using marginal structural models: 25 years follow-up of two US cohort studies.

This study assesses the effect of blood lipid indices and lipid ratios on cardiovascular diseases (CVDs) using inverse probability-of-exposure weighted estimation of marginal structural models (MSMs). A pooled dataset of two US representative cohort studies, including 16736 participants aged 42-84 years with complete information at baseline, was used. The effect of each lipid index, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), ratios of TC/HDL-C, LDL-C/HDL-C, and TG/HDL-C on coronary heart disease (CHD) and stroke were estimated using weighted Cox regression. There were 1638 cases of CHD and 1017 cases of stroke during a median follow-up of 17.1 years (interquartile range: 8.5 to 25.7). Compared to optimal levels, the risk of CVD outcomes increased substantially in high levels of TC, LDL-C, TC/HDL-C, and LDL-C/HDL-C. If everyone had always had high levels of TC (≥240mg/dL), risk of CHD would have been 2.15 times higher, and risk of stroke 1.35 times higher than if they had always had optimal levels (<200mg/dL). Moreover, if all participants had been kept at very high (≥190mg/dL) levels of LDL-C, risk of CHD would have been 2.62 times higher and risk of stroke would have been 1.92 times higher than if all participants had been kept at optimal levels, respectively. Our results suggest that high levels of HDL-C may be protective for CHD, but not for stroke. There was also no evidence of an adverse effect of high triglyceride levels on stroke. Using MSM, this study highlights the effect of TC and LDL-C on CVD, with a stronger effect on CHD than on stroke. There was no evidence for a protective effect of high levels of HDL-C on stroke. Besides, triglyceride was not found to affect stroke.

Workplace Favoritism and Workforce Sustainability: An Analysis of Employees’ Well-Being

The goal of sustainability in business is the maximization of resources for long-term productivity at a minimized negative impact for all key stakeholders. Several functions of human resources management are designed to achieve this goal. However, HRM practices can sometimes spiral down and result in the perception of favoritism–a practice that recruits or rewards relationship over merit. Hence, this project was designed to measure the impact of favoritism on the development of a sustainable hospitality workforce through the measures of subjective well-being, psychological capital, and knowledge hiding behavior. With the aid of randomly selected employees and estimation of structural models, the study validates the deleterious impact of favoritism and organizational politics on employee outcomes and by extension the sustainability of the workforce. Practical and theoretical recommendations are provided.

Farmers' risk preferences in 11 European farming systems: A multi‐country replication of Bocquého et al. (2014)

AbstractWe replicate Bocquého et al. (2014), who used multiple price lists to investigate the risk preferences of 107 French farmers. We collected new data from 1430 participants in 11 European farming systems. In agreement with the original study, farmers' risk preferences are best described by Cumulative Prospect Theory. Structural model estimates show that farmers in the new samples are, on average, less loss averse and more susceptible to probability distortion than in the original study. Explorative analyses indicate differences between estimation approaches, as well as heterogeneity between and within samples. We discuss challenges in replications of economic experiments with farmers across farming contexts.