Effect of a Job Demand-Control-Social Support Model on Accounting Professionals' Health Perception

The Job Demand-Control and Job Demand-Control-Support (JDCS) models constitute the theoretical approaches used to analyze the relationship between the characteristics of labor and occupational health. Few studies have investigated the main effects and multiplicative model in relation to the perceived occupational health of professional accountants. Accountants are subject to various types of pressure in performing their work; this pressure influences their health and, ultimately, their ability to perform a job well. The objective of this study is to investigate the effects of job demands on the occupational health of 739 accountants, as well as the role of the moderator that internal resources (locus of control) and external resources (social support) have in occupational health. The proposed hypotheses are tested by applying different models of neural networks using the algorithm of the Extreme Learning Machine. The results confirm the relationship between certain stress factors that affect the health of the accountants, as well as the direct effect that the recognition of superiors in occupational health has. Additionally, the results highlight the moderating effect of professional development and the support of superiors on the job’s demands

Accountancy as a meaningful work. Main determinants from a job quality and optimization algorithm approach

The primary purpose of the accounting profession is to provide quality information to the market that facilitates the allocation of resources. The context in which it operates must attend to some stressors that can affect the professional’s meaning of the work. Meaningful work (MW) is based on the concept of valuable work and work well done, so it is directly related to the concept of quality at work, which is a constant concern in the accounting profession. The method used to determine meaningful work identifies the set of job quality indexes, as defined by the European Working Conditions Survey (EWCS), related to the MW. This paper has used an integer programming genetic algorithm (GA) to determine the JQIs and the statistically significant combinations. The findings showed that JQIs, skills development and discretion (SD), and physical environment (PE) positively and intensely relate to MW. Likewise, reduction of the work intensity (WI) and improvement of the social environment (SE) are related in the same direction as the MW. On the other hand, the results showed different indicator weightings depending on the age of the accountants. This paper shows the importance that accountants attribute to professional competence and how, throughout their careers, the JQI that most relate to MW is changing, from a social vision to preferences where the care of personal time also prevails

Promoting work Engagement in the Accounting Profession: a Machine Learning Approach

In this paper, a non-linear multi-dimensional (machine learning-based) index for accountants that relates work engagement scores (according to accountants’ perceptions) with the seven Job Quality Indices (JQI) (proposed by Eurofound) has been proposed. The goal of the research is two-fold, namely, (i) to quantify the extent to which the JQI variables explain the work engagement scores, and (ii) to determine which JQI variables most afect the work engagement scores. The best performing regression model achieved a competitive root mean square percentage, highlighting that the selected variables primarily determine the work engagement values. Other important fndings include (i) that the work engagement index is mainly infuenced by the social environment index and (ii) that the skills and discretion and prospects indices are also crucial in the promotion of the work engagement of accountants. The instrument implemented could be employed by human resources practitioners to propose efcient human resources strategies that improve both individual wellbeing and company performance in the accounting sector

The Machine-Part Cell Formation Problem with Non-Binary Values: A MILP Model and a Case of Study in the Accounting Profession

The traditional machine-part cell formation problem simultaneously clusters machines and parts in different production cells from a zero–one incidence matrix that describes the existing interactions between the elements. This manuscript explores a novel alternative for the well-known machine-part cell formation problem in which the incidence matrix is composed of non-binary values. The model is presented as multiple-ratio fractional programming with binary variables in quadratic terms. A simple reformulation is also implemented in the manuscript to express the model as a mixed-integer linear programming optimization problem. The performance of the proposed model is shown through two types of empirical experiments. In the first group of experiments, the model is tested with a set of randomized matrices, and its performance is compared to the one obtained with a standard greedy algorithm. These experiments showed that the proposed model achieves higher fitness values in all matrices considered than the greedy algorithm. In the second type of experiment, the optimization model is evaluated with a real-world problem belonging to Human Resource Management. The results obtained were in line with previous findings described in the literature about the case study

Análisis del bienestar laboral de los profesionales contables a través de modelos computacionales

Este estudio aborda la influencia de este contexto en la salud laboral de los profesionales contables (perceived health), en la implicación laboral (work engagement) y en la percepción de que el trabajo tiene significado (meaningful work). Estos tres conceptos los abordamos de lo más general a lo más concreto

Effect of a Job Demand-Control-Social Support Model on Accounting Professionals’ Health Perception

The Job Demand-Control and Job Demand-Control-Support (JDCS) models constitute the theoretical approaches used to analyze the relationship between the characteristics of labor and occupational health. Few studies have investigated the main effects and multiplicative model in relation to the perceived occupational health of professional accountants. Accountants are subject to various types of pressure in performing their work; this pressure influences their health and, ultimately, their ability to perform a job well. The objective of this study is to investigate the effects of job demands on the occupational health of 739 accountants, as well as the role of the moderator that internal resources (locus of control) and external resources (social support) have in occupational health. The proposed hypotheses are tested by applying different models of neural networks using the algorithm of the Extreme Learning Machine. The results confirm the relationship between certain stress factors that affect the health of the accountants, as well as the direct effect that the recognition of superiors in occupational health has. Additionally, the results highlight the moderating effect of professional development and the support of superiors on the job’s demands

Factores determinantes y moderadores del nivel de salud laboral de los profesionales contables

La información financiera que prepara o revisa el experto contable es la base para la toma de decisiones de terceros. El profesional contable está sometido a diversos tipos de presiones en la realización de su trabajo que influyen en su estado de salud y, en última instancia, en su capacidad para realizar un trabajo de calidad. Nuestro trabajo trata de determinar esos factores determinantes y cómo se pueden moderar. Este trabajo utiliza el marco teórico del Job Demand Control Support (JDCS) desarrollado por Johnson y Hall (1989) y Karasek y Theorell (1990). La presente investigación demuestra la relación que existe entre ciertos factores estresantes que inciden en la salud de los profesionales contables; así como el efecto directo que tiene el reconocimiento de los superiores en la salud laboral. Nuestros resultados también ponen de manifiesto el efecto moderador que tiene el desarrollo profesional sobre las demandas del puesto, así como el apoyo de los superiores. Los datos utilizados proceden de la 6ª edición de la Encuesta Europea de Condiciones de Trabajo (EWCS). Para probar las proposiciones planteadas se aplican diferentes modelos de redes neuronales mediante el algoritmo de Extreme Learning Machine

Effect of a Job Demand-Control-Social Support Model on Accounting Professionals' Health Perception.

The Job Demand-Control and Job Demand-Control-Support (JDCS) models constitute the theoretical approaches used to analyze the relationship between the characteristics of labor and occupational health. Few studies have investigated the main effects and multiplicative model in relation to the perceived occupational health of professional accountants. Accountants are subject to various types of pressure in performing their work; this pressure influences their health and, ultimately, their ability to perform a job well. The objective of this study is to investigate the effects of job demands on the occupational health of 739 accountants, as well as the role of the moderator that internal resources (locus of control) and external resources (social support) have in occupational health. The proposed hypotheses are tested by applying different models of neural networks using the algorithm of the Extreme Learning Machine. The results confirm the relationship between certain stress factors that affect the health of the accountants, as well as the direct effect that the recognition of superiors in occupational health has. Additionally, the results highlight the moderating effect of professional development and the support of superiors on the job's demands

The machine-part cell formation problem with non-binary values: A milp model and a case of study in the accounting profession

The traditional machine-part cell formation problem simultaneously clusters machines and parts in different production cells from a zero–one incidence matrix that describes the existing interactions between the elements. This manuscript explores a novel alternative for the well-known machine-part cell formation problem in which the incidence matrix is composed of non-binary values. The model is presented as multiple-ratio fractional programming with binary variables in quadratic terms. A simple reformulation is also implemented in the manuscript to express the model as a mixed-integer linear programming optimization problem. The performance of the proposed model is shown through two types of empirical experiments. In the first group of experiments, the model is tested with a set of randomized matrices, and its performance is compared to the one obtained with a standard greedy algorithm. These experiments showed that the proposed model achieves higher fitness values in all matrices considered than the greedy algorithm. In the second type of experiment, the optimization model is evaluated with a real-world problem belonging to Human Resource Management. The results obtained were in line with previous findings described in the literature about the case study