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In the last two decades there has been considerable progress made in the development of alternative estimation techniques to ordinary least squares (OLS) regression. The search for alternative estimators has no doubt been motivated by the observance of erratic OLS estimator behavior in cases where there are too few observations, multicollinearity problems, or simply “information‐poor” data sets. Imprecise and unreliable OLS coefficient estimates have been the result.

Methods and techniques of aggregating preferences or priorities in the analytic hierarchy process (AHP) usually ignore variation or dispersion among experts and are vulnerable to extreme values (generated by particular viewpoints or experts trying to distort the final ranking). The purpose of this paper is to propose a modelling approach and a graphical representation to characterize inconsistency and disagreement in the group decision making in the AHP.

The authors apply a regression approach for estimating the decision weights of the AHP using linear mixed models (LMM). They also test the linear mixed model and the multi‐dimensional scaling graphical display using a case of strategic performance management in education.

In addition to determining the weight vectors, this model also allows the authors to decompose the variation or uncertainty in experts' judgment. Well‐known statistical theories can estimate and rigorously test disagreement among experts, the residual uncertainty due to rounding errors in AHP scale, and the inconsistency within individual experts' judgments. Other than characterizing different sources of uncertainty, this model allows the authors to rigorously test other factors that might significantly affect weight assessments.

This study provides a model to better characterize different sources of uncertainty. This approach can improve decision quality by allowing analysts to view the aggregated judgments in a proper context and pinpoint the uncertain component that significantly affects decisions.

The purpose of this paper is to investigate the accuracy and volatility of different methods for estimating and updating hedonic valuation models.

The authors apply six estimation methods (linear least squares, robust regression, mixed-effects regression, random forests, gradient boosting and neural networks) and two updating methods (moving and extending windows). They use a large and rich data set consisting of over 123,000 single-family houses sold in Switzerland between 2005 and 2017.

The gradient boosting method yields the greatest accuracy, while the robust method provides the least volatile predictions. There is a clear trade-off across methods depending on whether the goal is to improve accuracy or avoid volatility. The choice between moving and extending windows has only a modest effect on the results.

This paper compares a range of linear and machine learning techniques in the context of moving or extending window scenarios that are used in practice but which have not been considered in prior research. The techniques include robust regression, which has not previously been used in this context. The data updating allows for analysis of the volatility in addition to the accuracy of predictions. The results should prove useful in improving hedonic models used by property tax assessors, mortgage underwriters, valuation firms and regulatory authorities.

This research quantifies the economic impact of regional tax policy incentives included in the Gulf Opportunity Zone Act of 2005.

This research utilized linear mixed-effects modeling and multiple regression procedures with a matched sample panel dataset from 2002 through 2008 containing real-world county-level economic data.

The results indicated that the regional tax incentives provided by the GO Zone Act did not generate significant increases in key economic indicators included in this study. These tax incentives were intended to spur economic recovery, but based on research findings, they do not appear to have had the impact desired by Congress.

Archival empirical data for the affected region make this study possible but also limit the ability to generalize these results to other regions. In addition, empirical research utilizing real-world data can be prone to internal validity issues that exist due to lack of environmental controls and other possible causal factors.

This research adds to the existing literature by using real-world county-level economic indicators to test the impact of tax policy investment incentives at the regional level and minimizes some of the issues addressed by prior empirical research and provides evidence on the effectiveness of tax policy investment incentives at the regional level.

Describes a procedure for modelling the costs of production and distribution between several production facilities with economies of scale and many customers who are widely dispersed. The problem takes the form of a large transportation problem on which is superimposed a cost minimization problem involving variable production quantities. These costs involve fixed costs for initiating production and variable costs with diminishing returns to scale. Models the problem as a non‐linear integer programming problem and then solves it using a recently developed non‐linear integer algorithm. Describes two applications in Australia and New Zealand and illustrates how comparison with a mixed‐integer linear programming formulation shows a significant improvement.

This study is a replication of Tosi and Greckhamer's work examining how uncertainty avoidance, power distance, individualism and masculinity/femininity are related to total CEO pay, the ratio of variable to total CEO pay and the ratio of CEO pay to the pay of the lowest level employees in 23 countries. Its main purpose is to investigate whether the replication confirms, questions or extends the results of TG2004.

Tosi and Greckhamer used generalized linear modeling (GLS) to analyze the relationships between Hofstede's four cultural dimensions and CEO compensation. In the replication, the author used GLS to retest the original seven hypotheses with more recent data from Hofstede and test the same hypotheses relying on cultural values and practices scores from the GLOBE study. Further, using firm-level data unavailable for the original study, the author analyzed fixed and random effects in mixed models.

The replication generally confirms the findings of the original study for the effects of power distance, individualism and masculinity on CEO total pay. Results are mixed or indicate the lack of significant effect for other relationships.

This study reexamines the effects of country-level contextual variables in the area of CEO compensation.

The replication presents firm-level CEO compensation and firm performance data from 21 countries, extending the original study and unveiling possible spurious effects.

The purpose of this paper is to illustrate the value of extended time span coverage of state longitudinal education and workforce data system to inform and improve the effectiveness of future high impact expenditure decisions.

It used an analytical 29-year data file created by the author that links seven already-in-place education and workforce administrative record sources. Relying on the path dependency theory, multi-level mixed-effect logistic and multi-level mixed-effect linear regression models are used to test three hypotheses.

The findings are consistent with the hypotheses: inclusion of the multiple steps along a post-secondary education pathway and prior job histories are both critical to understanding workforce outcomes mechanisms; it takes time for the employment outcome effect to be evident and strong following education attainment.

The study concludes with research limitations and implications for decision makers to call for retaining and investing in administrative records with extended time span coverage, particularly for the already-in-place historical administrative records.

The paper is one of the first to demonstrate the value of extended time span coverage in a longitudinal state integrated data system through econometric modeling, using longitudinally integrated data linking seven administrative records covering continuously for 29 years. No matter for prior education or employment pathway, it is only through extended time span coverage that employment outcomes can be well measured and the rich nuances interpreting the mechanisms of education return on investment can be revealed.

The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.

In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.

Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.

Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.

This study seeks to understand how work–life balance (WLB) changes over time, and if relational factors – relationship and sexual satisfaction – may have protective effects. Grounded in Bronfenbrenner’s (1986) family ecological theory a linear mixed effects analysis was used to analyze over 4,000 individual reports of WLB over three years.

The primary finding showed that on average, individuals rated their WLB just above average and their scores decrease over time. While relationship satisfaction did not have significant associations with WLB alone, the interaction between relationship and sexual satisfaction was found to be a protective factor, increasing WLB scores. This indicates that having higher sexual satisfaction can enhance the protective effect that relationship satisfaction has on WLB.

An intriguing finding was the significant difference in WLB scores for men compared to women. On average, men experience significantly lower WLB scores. This could be related to how WLB was measured, or possibly due to gender roles. Future research should further explore this relationship.

The results of this study provide information that researchers’ can consider as they design studies and interventions targeting WLB. An additional hope is that employers will consider these results when they create workplace policy and other initiatives.

This study is one of the first to explore WLB in association with relationship and sexual satisfaction and the interaction between sexual and relationship satisfaction. This chapter tests the interactions between mesosystems in a unique way that enhances researchers understanding of WLB.

Regional economic integration has been a major area of research in the field of international economics and international trade, with little attention being paid to the impact of these economic collaborations on the organizational strategies of firms within the economically integrated regions. By building on the organization‐environment relationship paradigm, this paper aims to address the impact of environmental changes associated with economic integration, market commonality and currency commonality, on the patterns and structures of strategic alliances within members of the economic community.

Using mixed linear models, the study looks at changes associated with the integration of the European Union and their effects on international alliances within the integrated area and among the various member countries.

The findings suggest that the emergence and the adoption of economic integration policies at the country level do impact the patterns and structures of strategic alliances practiced between member countries. Specifically, the adoption of common market policies among members of an economic community has implications on the pattern and structure of strategic collaborative relationships of firms within these member countries.

While regional economic integrations have accelerated, theoretical and empirical research addressing their impact on multinational strategies has yet to catch up.