Organizational efficiency is required to be understood for the growth of a company. Artificial neural network is one of the methodologies that is widely used for this purpose. In this paper, this model has been utilized for finding organizational efficiency for construction companies. The basic requirement for the survival of the company are its performance, speed and efficiency. The categorial classification of the organizational efficiency was listed into 5 categories after doing a complete interview with extremely experienced construction executives. Even the 17 variables were developed to profoundly establish 17 measurement items. Pre-test questionnaires were prepared with the bulk of 200 distributed among various people and certainly 195 collected back with the answers. Artificial neural network simulation was applied to it and final four classifications were found for organizational efficiency.
Listing of variables:
Three steps were used for developing the artificial neural network before listing the dependent and independent variables for linear regression. First the categories and related variables were defined followed by self-management questionnaire for design and implementation for the variables. Third is the linear regression along with training of the collected correct data. This data can be utilized for principle component analysis. After the expert interview the five categorial classifications were background of organizational structure (including variable like employee harmonization and responsibilities, subcontracting, distinct project management, coordination and information communication), flexibility along with regulations in organizations (attitude towards reform, familiarity and compliance with regulations), adaptation process of personnel (including cultural advantage and worker’s participation), organizational strategy methods (including planning and setting of objectives), improvement of organizational performance (cost control, quality improvement). Likert 5-point scale is used and despite cultural advantage all the variables score good. The researchers assured the linear regression analysis with 17 independent and dependent variables, eradicating the unimportant variables with every step. Root mean square error were calculated in different statistical methods. The 17 processing elements based on the 17 variables were constructed in a two-hidden layer network input, making a single neuron as network output. The first 8 elements in the first hidden layer followed by next 4 in the second hidden layer were constructed. For third mode, regression analysis as used and for 4th mode is the correlation analysis mode. Artificial neural network constructed through MATLAB was used for questionnaire sampling by dividing them into learning and prediction samples. Mean absolute percentage error is an effective evaluation index utilized to find the desirable performance in the range of Q1 Q4 whew MAPE<0.15 and GOAL >0.5.
Author's conclusion:
The author concluded the underperformance of Q5, making three variables of organizational efficiency inside the reasonable prediction scope. Their unimportance made them strike out. The final conclusion included the 4 categories for classification of construction company. They are flexibility, adaptation process of personnel, norms and regulation of the company and methods to achieve company strategy. The researchers proved that backpropagation artificial neural network with learning speed in variable position can excellently predict the organizational efficiency.
Relevance of article:
The article is quite relevant as it queers the importance of strategy development in organization to understand the performance of their employees. Various categorizations are an initial step to research over more complex variables apart from the provided ones.
Article 2
Overview: The stated study is a product of linear regression to compare the charges in hospitals (Medicare and non-Medicare) going low when the number of Non-Government Organizations (NGO) collaborating with the hospital goes high. The author states that when the involvement of the NGO in an organization is raised, the complex stakeholder management activities are reduced and make the organizations behave more sensibly. The author used the Medicare dataset and sampled some of the medical facilities to expand the database. This expansion was based on illness and availability of data. 366 hospitals were chosen from the dataset of 163072 Medicare costs for a unit hospital. The parameter of mental illness was chosen as there was no death measured for such illness.
Listing of variables:
The number of control variables chosen were:
Licensed bed amount Mortality rate of 30 days
Business structure Distinctions
For listing the dependent variable, the authors chose the attitude of the staff of the hospital while reacting with the patients. Their advice, information and services were counted in. the teaching activities in the hospital was also added with an option of presence of a healthy encyclopedia with the hospital facility. These variables were considered important because it showed the trust of stakeholders in the hospital that in emergency cases the external resources can be utilized. The support groups were also included such as alcoholic anonymous and American heart association’s along with some government organizations, provided they behave like a NGO. With clear understanding, the proposition of awards and distinction was also added.
In case of independent variables, the government approved Medicare costs and non-Medicare costs were included. Govt. approved Medicare costs were named as average covered charges and the later were called as average total payments. The hypothesis of hospital behaving more sensibly and providing less Medicare costs, the Medicare and non-Medicare charges were multiplied.
For hierarchical linear regression analysis, SPSS was used, followed by the two steps on the combined dataset.
Control variable
NGO engagement counts
Author's conclusion:
Two types of hospital were found out at the end of the regression analysis, working on two types of logic.
The hospitals who cordially welcome the stakeholders who are patient care oriented and take the help of every possible resource for taking care of it.
The hospitals who have adequate amount of medical facilities like nurses and doctors and pharmacies and consider themselves one stop shop for the patient’s every requirement.
The author claimed the first type of the hospital to be more effective dominant logic when compared to the second.
Relevance of article:
The article has listed and performed different regression analyses based on the dependent and independent variable. From the subject of statistics, this article is quite relevant, empowering new methods for the statistical learning. Finally, the first article shows how man and machine can merge to solve problems related to business. This of interest to me because I am enthusiastic about artificial intelligence and how it can be used to solve problems that humans alone can’t.