A Conceptual and Pragmatic Review of Regression Analysis for Predictive Analytics

2017 ◽  
pp. 1761-1776
Author(s):  
Sema A. Kalaian ◽  
Rafa M. Kasim ◽  
Nabeel R. Kasim
Keyword(s):  
Regression Analysis ◽  
Organizational Performance ◽  
Predictive Analytics ◽  
Organizational Outcomes ◽  
Regression Analyses ◽  
Organizational Productivity ◽  
Intelligent Information ◽  
And Performance ◽  
Analytical Tools ◽  
Web Server Logs

Regression analysis and modeling are powerful predictive analytical tools for knowledge discovery through examining and capturing the complex hidden relationships and patterns among the quantitative variables. Regression analysis is widely used to: (a) collect massive amounts of organizational performance data such as Web server logs and sales transactions. Such data is referred to as “Big Data”; and (b) improve transformation of massive data into intelligent information (knowledge) by discovering trends and patterns in unknown hidden relationships. The intelligent information can then be used to make informed data-based predictions of future organizational outcomes such as organizational productivity and performance using predictive analytics such as regression analysis methods. The main purpose of this chapter is to present a conceptual and practical overview of simple- and multiple- linear regression analyses.

A Conceptual and Pragmatic Review of Regression Analysis for Predictive Analytics

2017 ◽  
pp. 277-292
Author(s):  
Sema A. Kalaian ◽  
Rafa M. Kasim ◽  
Nabeel R. Kasim
Keyword(s):  
Regression Analysis ◽  
Organizational Performance ◽  
Predictive Analytics ◽  
Organizational Outcomes ◽  
Regression Analyses ◽  
Organizational Productivity ◽  
Intelligent Information ◽  
And Performance ◽  
Analytical Tools ◽  
Web Server Logs

Regression analysis and modeling are powerful predictive analytical tools for knowledge discovery through examining and capturing the complex hidden relationships and patterns among the quantitative variables. Regression analysis is widely used to: (a) collect massive amounts of organizational performance data such as Web server logs and sales transactions. Such data is referred to as “Big Data”; and (b) improve transformation of massive data into intelligent information (knowledge) by discovering trends and patterns in unknown hidden relationships. The intelligent information can then be used to make informed data-based predictions of future organizational outcomes such as organizational productivity and performance using predictive analytics such as regression analysis methods. The main purpose of this chapter is to present a conceptual and practical overview of simple- and multiple- linear regression analyses.

Predictive Analytics

2015 ◽  
pp. 12-29 ◽  
Author(s):  
Sema A. Kalaian ◽  
Rafa M. Kasim
Keyword(s):  
Logistic Regression ◽  
Big Data ◽  
Multilevel Modeling ◽  
Polynomial Regression ◽  
Predictive Analytics ◽  
Intelligent Information ◽  
Complex Relationships ◽  
Analytical Tools ◽  
Existing Data ◽  
Organizational Performances

Predictive analytics and modeling are analytical tools for knowledge discovery through examining and capturing the complex relationships and patterns among the variables in the existing data in efforts to predict the future organizational performances. Their uses become more common place due largely to collecting massive amount of data, which is referred to as “big data,” and the increased need to transform large amounts of data into intelligent information (knowledge) such as trends, patterns, and relationships. The intelligent information can then be used to make smart and informed data-based decisions and predictions using various methods of predictive analytics. The main purpose of this chapter is to present a conceptual and practical overview of some of the basic and advanced analytical tools of predictive analytics. The chapter provides a detailed coverage of some of the predictive analytics tools such as Simple and Multiple-Regression, Polynomial Regression, Logistic Regression, Discriminant Analysis, and Multilevel Modeling.

Predictive Analytics

2017 ◽  
pp. 49-66
Author(s):  
Sema A. Kalaian ◽  
Rafa M. Kasim
Keyword(s):  
Logistic Regression ◽  
Big Data ◽  
Multilevel Modeling ◽  
Polynomial Regression ◽  
Predictive Analytics ◽  
Intelligent Information ◽  
Complex Relationships ◽  
Analytical Tools ◽  
Existing Data ◽  
Organizational Performances

Predictive analytics and modeling are analytical tools for knowledge discovery through examining and capturing the complex relationships and patterns among the variables in the existing data in efforts to predict the future organizational performances. Their uses become more common place due largely to collecting massive amount of data, which is referred to as “big data,” and the increased need to transform large amounts of data into intelligent information (knowledge) such as trends, patterns, and relationships. The intelligent information can then be used to make smart and informed data-based decisions and predictions using various methods of predictive analytics. The main purpose of this chapter is to present a conceptual and practical overview of some of the basic and advanced analytical tools of predictive analytics. The chapter provides a detailed coverage of some of the predictive analytics tools such as Simple and Multiple-Regression, Polynomial Regression, Logistic Regression, Discriminant Analysis, and Multilevel Modeling.

Connecting Group Dynamics, Governance, and Performance: Evidence From Charter School Boards

2020 ◽  
Vol 49 (5) ◽  
pp. 1035-1057 ◽  
Author(s):  
Michael R. Ford ◽  
Douglas M. Ihrke
Keyword(s):  
Organizational Performance ◽  
Small Group ◽  
Charter School ◽  
Group Dynamics ◽  
Organizational Outcomes ◽  
School Level ◽  
Nonprofit Performance ◽  
Small Group Dynamics ◽  
Nonprofit Governance ◽  
And Performance

In this article, we build on the existing literatures on small group dynamics and public and nonprofit governance by exploring the link between small group dynamics, governance, and nonprofit performance. The results provide evidence that nonprofit governing boards can improve organizational performance by improving their governance behaviors. Specifically, we link survey data from Minnesota nonprofit charter school board members to hard measures of organizational performance in a path analysis predicting school-level math and reading proficiency levels. We find that boards exhibiting better group dynamics are more active in key governance areas, and that active governance is linked to increased organizational outcomes. Our findings advance scholarly understanding of nonprofit governance by identifying a pathway between nonprofit board governing dynamics and sustainable organizational performance gains. We conclude with practical advice on how nonprofit boards can increase their organizational performance through improved small group dynamics.

Thinking Styles and Leadership Skills of Managers on Organizational Productivity

2021 ◽  
pp. 448-458
Author(s):  
Garima Saini ◽  
Shabnam
Keyword(s):  
Organizational Performance ◽  
Team Building ◽  
Leadership Skills ◽  
Organizational Productivity ◽  
Organizational Goals ◽  
Executive Manager ◽  
Management Approaches ◽  
And Performance ◽  
Managerial Positions ◽  
Managerial Psychology

Psychological aspects, a great concern of managerial psychology, include emotions, thinking, attitudes, and motivation of the employees in managerial positions, which ramifies the productivity of the organization. Managerial thinking and leadership skills are important components in achieving organizational goals. Organizational productivity is a strong indicator for managers in the growth which has direct relationship with organizational performance. Efficacious leadership skills in managers like interpersonal skills, team building, flexibility, emotional intelligence helps in meeting the goals which simultaneously increases the organization productivity and performance of the employees. Strategic management approaches by the managers to increase productivity at successive levels. An executive manager is an agent of change who lets a subordinate work according to him and then he converts the follower into a leader through team quality management (TQM) programs and effectiveness. The managerial implications are discussed which helps to establish cooperative innovations.

scholarly journals A Taxonomy of Quality Standard Adoption: Its Relationship with Quality Management and Performance in Tourism Organizations In Spain

2020 ◽  
Vol 11 (21) ◽  
pp. 22-37
Author(s):  
Juan José Tarí ◽  
Jorge Pereira-Moliner ◽  
José F. Molina-Azorín ◽  
María D. López-Gamero
Keyword(s):  
Quality Management ◽  
Organizational Performance ◽  
Continuous Improvement ◽  
Management Practices ◽  
Professional Community ◽  
Quality Standard ◽  
Regression Analyses ◽  
Starting Point ◽  
Travel Agencies ◽  
And Performance

This work aims to identify quality standard adoption levels and their relationship with quality management practices and performance (customer, employee and social results, and organizational performance) in tourism organizations in Spain. This work uses 279 tourism organizations in the following subsectors: hotels, travel agencies, restaurants, and rural accommodations. The work applies cluster and regression analyses. Results show three levels of adoption and a lower degree of development of the continuous improvement dimension. Organizations with a significantly lower level of development of the quality standard have started to integrate the quality requirements in their daily practices to some extent and where continuous improvement practices are little developed. These organizations have significantly lower results than those organizations with higher adoption of quality. The results also indicate that a greater level of adoption of a quality standard leads to a higher development of QM practices. These results are interesting for managers, destination managers, and the wider tourism professional community. It contributes to supplementing previous studies about taxonomies of quality standard adoption in the particular case of tourism organizations in Spain and may serve as a starting point for further research on that topic.

scholarly journals The performance factors of non-profit basketball clubs

2020 ◽  
Vol 1 (1) ◽  
pp. 17-39
Author(s):  
Igor Ivaskovic
Keyword(s):  
Regression Analysis ◽  
Organizational Performance ◽  
Causal Relationship ◽  
The Other ◽  
Direct Impact ◽  
Regression Analyses ◽  
Non Profit ◽  
Performance Factors ◽  
Sport Clubs ◽  
And Behavior

Using the data from 73 non-profit basketball clubs from four post-transitional Southeast European countries the article examines the potential causal relationship between 165 variables divided into four groups (organizational environment, strategies, human resource management (HRM), and behavior and feelings of organizational members) and two different aspects of organizational performance, namely competitive-financial and recreational-non-financial. The multiple regression analyses results disclose direct impact of the strategic focus on the organizational performance. The study provides explanation how the importance of different objectives from an aspect of club leadership affect the chances of enhancing the sport clubs performance from both perspectives. Higher performance is achieved by specialized clubs that pursue only one aspect of performance and strive for those goals that positively affect the same performance perspective. On the other hand, the HRM – performance analysis shows that many HRM factors correlate with organizational performance. However, regression analysis did not confirm any significant direct impact, which indicates that this causal relationship is indirect.

Integration of Quality and Innovation Practices for Global Sustainability: An Empirical Study of Indian SMEs

2017 ◽  
Vol 18 (1) ◽  
pp. 210-225 ◽  
Author(s):  
Hima Gupta
Keyword(s):  
Factor Analysis ◽  
Regression Analysis ◽  
Empirical Study ◽  
Organizational Performance ◽  
Exploratory Factor Analysis ◽  
Reliability And Validity ◽  
Descriptive Statistics ◽  
Global Sustainability ◽  
And Performance ◽  
Innovation Practices

The purpose of this article is to pragmatically analyze the effects of quality and innovation practices on the organizational performance from the sustainability perspective. Further, the researcher also aims to understand the effect of quality and innovative initiatives on the global sustainability as a whole. The study uses data obtained from a survey of 126 organizations comprising manufacturing (121) and services (5) both in India. The respondents chosen to answer the questions must have sufficient knowledge of innovation practices being deployed in the organizations at large. Descriptive statistics were used in order to determine the sustainability-oriented innovation practices deployed. Exploratory factor analysis (EFA) was applied to extract the factors and to provide the basis for gauging their reliability and validity. In addition, regression analysis was used to see the effect of sustainability-oriented practices on organizational performance as a whole. The sustainability-oriented innovation practices are definitely conducive to foster growth and performance benefits, provided and supported by this research based on theoretical and practical inputs taken from the leading manufacturing hubs in India.

PENGARUH BUDAYA ORGANISASI, KEPEMIMPINAN DAN IKLIM ORGANISASI TERHADAP KINERJA PEGAWAI RUMAH SAKIT BHAYANGKARA PADANG

2020 ◽  
Author(s):  
Silvia Agustin
Keyword(s):  
Organizational Culture ◽  
Regression Analysis ◽  
Organizational Climate ◽  
Employee Performance ◽  
Test Validity ◽  
Workplace Culture ◽  
Work Culture ◽  
Eligibility Criteria ◽  
Reliable Instrument ◽  
And Performance

The purpose of this study are: 1) To clarify whether there is influence organizational culture, leadership and organizational climate on employee performance Bhayangkara Padang Hospital and 2) Measure the influence of organizational culture, leadership and organizational climate on employee performance Bhayangkara Padang Hospital. Based on test validity workplace culture, leadership, work climate and performance in mind all the items declared invalid meet the eligibility criteria are good and reliable instrument. Work Culture regression analysis obtained by value t = 2.091 while t table = 1.988, so t count> t table and the significance value is 0,040 this value is smaller than α = 0.05 not significant effect on employee performance Padang Police Hospitals. Leadership regression analysis obtained by value t = 1.762 while t table = 1.988 so that t

Performance Measurement using Balance Score Card and its Applications: A Review

2015 ◽  
Vol 4 (3) ◽  
Author(s):  
Shradha Gawankar ◽  
Sachin S. Kamble ◽  
Rakesh Raut
Keyword(s):  
Performance Measurement ◽  
Organizational Performance ◽  
Performance Management ◽  
Balanced Scorecard ◽  
Strategic Change ◽  
The Balanced Scorecard ◽  
Balance Score Card ◽  
Measurement Framework ◽  
Score Card ◽  
And Performance

This paper aims to propose the idea of briefly explaining the balance scorecard by highlighting its use, application in depth. A critical enabler in achieving desired performance goals is the ability to measure performance. Despite the importance of accurately measuring organizational performance in most areas of academic research, there have been very few studies that have directly addressed the question of how overall organizational performance is or should be measured. Perhaps more importantly, none of these studies seems to have significantly influenced how overall organizational performance is actually measured in most of the empirical research that uses this construct as a dependent measure. The most popular of the performance measurement framework has been the balanced scorecard abbreviated as BSC. The BSC is widely acknowledged to have moved beyond the original ideology. It has now become a strategic change management and performance management process. The approach used in this paper is the combination of literature review on evolution of balance score card and its applications in various sectors/organizations/ areas. This paper identify that the balanced scorecard is a powerful but simple strategic tool and the simplicity of the scorecard is in its design. By encompassing four primary perspectives, the tool allows an organization to turn its attention to external concerns, such as the financial outcomes and its customers expectations, and internal areas, which include its internal processes to meet external requirements and its integration of learning and growth, to successfully meet its strategic expectations. This paper provides a comprehensive overview of the balanced scorecard combined with application and strategy, which are now in a better position to begin to recognize managements expectations and to discover new ways to build value for workplace learning and performance within organization.

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