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This paper aims to use coordinated financial statements' system properties that include exogenous and endogenous variables to answer important questions. These questions include the following: What is the financial condition of the firm? What if there is a change in the firm's exogenous variable(s) – how will the financial condition of the firm change? And, how much of a change in the firm's exogenous variable(s) is required for the firm to reach its financial goal(s)?

This paper uses coordinated financial statements to construct solvency, profitability, efficiency, liquidity and leverage (SPELL) ratios to answer the question: what is the financial condition of the firm? It answers what-if questions by changing an exogenous variable(s) and recalculating SPELL ratios. It answers how-much questions by using Excel's Goal Seek algorithm to find the required change in an exogenous variable to reach a firm's goal.

The authors find that coordinated financial statements' system properties can be used to answer important what-is, what-if and how-much questions about the firm.

The usefulness of coordinated financial statements' system properties to answer what-is, what-if and how-much questions about the firm depends – mostly on the accuracy of exogenous data used to represent the firm's external financial environment. Furthermore, the usefulness of what-if and how-much analysis depends on how appropriate the changes are in exogenous variables used to represent alternative scenarios.

Using coordinated financial statements' system properties to answer what-is, what-if and how-much questions provides the firm's financial manager the tools to not only asses the firm's current financial condition but also to assess its ability to respond to opportunities and threats posed by future scenarios.

The ability to assess the financial condition of a firm and to assess its strengths and weaknesses in key to making sound financial decisions. In addition, the consistency imposed on coordinated financial statements makes it an effective tool for discovering errors in its data.

The authors know of no similar work.

This study aims to gain new insight into how a set of maqasid-based consumption intelligence variables mediates exogenous variables (i.e. religiosity, Islamic university role and normative belief) and halal purchase intention as an endogenous variable.

The research model is empirically tested with a data set of 370 responses retrieved from the students of the millennial generation from the cross Islamic state university in Indonesia. Data were analysed with Partial Least Square Structural Equation Modelling (PLS-SEM). The sample size of this study is computed with preliminary power analysis.

The SEM finding revealed that two maqasid-based consumption intelligence variables had mediated the exogenous and endogenous variables, i.e. halal purchase intention. These variables mediating the exogenous and endogenous variables have explained 63.5 R² variances in halal purchase intention. Concerning individual impact size of cognition and motivation as a component of maqasid-based consumption intelligence has shown medium-level effect size (f²) in mediating the halal purchase intention. Interestingly, the exogenous variable does not directly affect halal purchase intention but must be mediated with maqasid-based consumption intelligence variables. However, before including variables of maqasid-based consumption intelligence, the R² was relatively small. It is just 30.4% in R² that explains the variance of halal purchase intention.

This study explores maqasid-based consumption intelligence as a relatively new model to explain the variable halal purchase intention. Therefore, it takes many types of exogenous variables to test how relevant maqasid-based consumption intelligence variables can define endogenous variables. Notwithstanding, this study does not do that because it only limits three exogenous variables (i.e. religiosity, Islamic university role and normative belief). Therefore, in further research, these limitations seem to be perfected by other scholars concerned about halal purchase intention.

The findings of this study allow Islamic universities to mainstream halal issues as a subject of learning, especially concerning consumption ethics. In addition, the empirical results of this study encourage the industry to pay attention to the essential components in determining the halal quality of the products offered because the millennial generation is now very aware of the importance of halal products.

This study contributes to the existing literature on halal purchase intention by testing maqasid-based consumption intelligence variables as mediators. Moreover, this is a pioneer study to consider and construct maqasid-based consumption intelligence as a model that explains halal purchase intention.

In the purview of stress–turnover relationship, the present study aims to explore the endogenous and exogenous aspects of stress and employees' turnover intentions. Further, it also intends to evaluate the mediating role of perceived employee's exploitation between stressors and employee turnover intentions. For that matter, antecedents of stressors were identified and classified into endogenous and exogenous stressors: endogenous stressors relate to the employees' negative psychological contact within an organization and exogenous stressors are various macro-economic factors which have a considerable influence on employees' workplace behavior.

For the purpose of this study, this study choses private school teachers as respondents working in the economically depressed state of India. Thus, data for the present study has been collected from 628 private school teachers of J&K (India) which were randomly selected. In order to ensure valid and reliable statistical inferences from the study, data collected has been validated using confirmatory factor analysis and hypothesis testing has been carried out through structural equation modeling.

It was found that both types of stressors were contributing negatively toward employee's psychological state resulting in undesirable employee organizational relationships manifested as turnover intentions among employees. Moreover, perceived employee's exploitation was found to intensify the relationship of employee turnover as a dependent variable regressed on endogenous, exogenous and occupational stress by fully mediating the stress–turnover intricacies.

The implications of the study include the identification of employees' stressor needs in order to gauge the understanding of the mechanism by which employees react to their environment and develop attitudes toward their jobs. The present study includes a small sample size obtained from private educational institutions only. Therefore, there is a need to take a geographically diverse sample that is inevitable for universal inferences and validity.

Very little research has been conducted to explore endogenous, exogenous and unique stressors such as economic stress and perceived external opportunities which constitute the overall stress. Moreover, to the best of the authors’ knowledge, this is the first study which tests the model empirically that examines the effect of stress–turnover relationship through perceived employee's exploitation in the teaching and educational sector.

Data envelopment analysis (DEA) is based on the production possibility set that involves the process of converting resources or inputs to outputs. Accordingly, most DEA models include endogenous variables and need an additional step to find the influence of exogenous variables on the process. The purpose of this paper is to examine the relationship between the efficiency scores of DEA and the exogenous variables using truncated regression analysis with double bootstrapping along with two additional methods.

First, the authors employ DEA for benchmarking the comparative efficiency of the health care institutes. Next, the authors run and compare truncated, ordinary least square (OLS) and Tobit regression analysis using the double bootstrapping algorithm for finding the influence of exogenous variables on the efficiency of the health care institutes.

The authors confirmed the amount of bias for the Tobit and OLS regression models, which was caused by serially correlated errors. Accordingly, the authors chose results from the truncated regression model with double bootstrapping for examining the influence of exogenous or environment variables on the efficiency scores.

The study includes cross-sectional data on health care institutes in the state of Washington, USA. Collecting data in various states or regions over time is left for future studies.

In this study, three exogenous variables such as Medicaid revenues, locations of health care institutes and ownership types are significant for explaining the relationship between the efficiency scores and a group of the exogenous variables. Managers and policy makers need to pay attention to these variables along with endogenous variables for promoting the sustainability of the health care institutes.

The study demonstrates the usefulness of the truncated regression analysis with double bootstrapping for confirming the relationship between the efficiency scores of DEA and a group of exogenous variables, which is rare in the DEA literature.

This chapter develops a set of two-step identification methods for social interactions models with unknown networks, and discusses how the proposed methods are connected to the identification methods for models with known networks. The first step uses linear regression to identify the reduced forms. The second step decomposes the reduced forms to identify the primitive parameters. The proposed methods use panel data to identify networks. Two cases are considered: the sample exogenous vectors span Rn (long panels), and the sample exogenous vectors span a proper subspace of Rⁿ (short panels). For the short panel case, in order to solve the sample covariance matrices’ non-invertibility problem, this chapter proposes to represent the sample vectors with respect to a basis of a lower-dimensional space so that we have fewer regression coefficients in the first step. This allows us to identify some reduced form submatrices, which provide equations for identifying the primitive parameters.

This article deals with how to test for and evaluate interdependence among control practices in a management control system using structural equation modeling. Empirical research on the levers of control (LOC) framework is used as an example. In LOC research, a path model approach to interdependence has been developed. The appropriateness of this approach is evaluated, developed, and compared with the correlation of residuals approach (seemingly unrelated regression) implemented in the wider complementarity literature. Empirical examples of the different models are shown and compared by using a data set on LOC of 120 SBUs in Sweden. The empirical results show that modeling interdependence among control practices in a management control system as non-recursive (bi-directional) paths or as residual correlations evidently affects the conclusions drawn about interdependence in terms of both presence and magnitude. The two models imply different views on how to conceptualize interdependence and are not statistically and empirically comparable. If using non-recursive path models, several model specification issues appear. To be able to identify such models, this needs to be carefully considered in the theory and research design prior to data collection.

This paper aims to study the monetary transmission mechanism of China from January 1996 to December 2009 under endogenous structural breaks.

The study constructs a benchmark VAR model and then adds the proxy variables for four channels of monetary policy transmission as endogenous or exogenous variables in the model to study the transmission mechanism in China. Considering a number of reforms carried out in the economic and financial field in the past two decades and the possibility of structural changes in the monetary transmission mechanism, the methodology proposed by Qu and Perron is employed to allow for endogenous structural changes in the model.

By conducting a comparative analysis, conclusions can be drawn from this paper that bank lending is always the dominating channel for monetary policy to influence economy in China and the roles of the interest rate channel and the exchange rate channel have been improved in recent years. However, the role of the asset price channel in monetary policy transmission has weakened since late 2001.

This paper combines the quasi‐maximum likelihood procedure proposed by Qu and Perron in 2007 with a benchmark VAR model, thus providing a new approach to study monetary transmission mechanism and the conclusions can be more sensible.

The objective of this chapter is to provide strategy researchers with a general resource for applying structural equation modeling (SEM) in their research. This objective is important for strategy researchers because of their increased use of SEM, the availability of advanced SEM approaches relevant for their substantive interests, and the fact that important technical work on SEM techniques often appear in outlets that may not be not readily accessible. This chapter begins with a presentation of the basics of SEM techniques, followed by a review of recent applications of SEM in strategic management research. We next provide an overview of five types of advanced applications of structural equation modeling and describe how they can be applied to strategic management topics. In a fourth section we discuss technical developments related to model evaluation, mediation, and data requirements. Finally, a summary of recommendations for strategic management researchers using SEM is also provided.