A framework for performance evaluation of channel partners in distribution relationships

Evaluating channel partner’s performance: impact of task environments on the relevance of measurement metrics

Abstract: Purpose The purpose of this paper is to develop a nuanced framework for evaluating a channel partner’s performance in distribution channel relationships. Given a channel partner’s task environment characteristics (high/low munificence, dynamism and complexity), the study examines which performance metrics (output, activity or capability) are most relevant for evaluating its performance levels effectively. Design/methodology/approach The study adopts self-administered cross-sectional survey-based research design. Matched data were collected from 252 channel partners – manager relationship dyads. The latent change score (LCS) model within SEM framework provides mean paired-differences of the relevance ratings for each metrics. This was used to assess the empirical validity of the hypothesized relationships. Findings The study demonstrates the importance of calibrating performance evaluation metrics to a channel partner’s task environment state, made possible by its holistic approach to performance evaluation. Based on an extensive analysis, it shows that no single metric is relevant within all environmental states; rather, it could be dysfunctional, a result that differs from vast majority of the literature. Research limitations/implications Investigates individual linkages between task environment dimensions and performance metrics to provide a fuller understanding of these relationships. Also provides a theoretical framework to support further research on the topic. Practical implications The study provides managerial guidelines (and extensive graphical analysis) for nuanced and dynamic evaluation of channel partners’ performance that can enable firms to identify and promote their most valuable channel partners and prevent the deterioration of others. Originality/value First one to develop and empirically validate a nuanced framework for evaluating performance of exchange partners that operate under diverse task environment states.

Small Construction Business Owners' Strategies for Employee Retention

Abstract: Small Construction Business Owners’ Strategies for Employee Retention by Charles H. Griner, Jr. MS, Troy University, 2006 BBA, University of Mississippi, 1991 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University November 2019 Abstract Thirty-four percent of people in the United States of America work for businesses that employ fewer than 100 people. However, many small business owners lack the strategies necessary to retain their valuable employees. Businesses that fail to retain valuable employees are as much as 28% less efficient. The purpose of this qualitative multiple case study was to explore strategies small construction business owners use to retain their valuable employees. Contingency theory provided the conceptual framework. The participants were three owners of three small businesses in the construction industry located in Mississippi which implemented successful policies and procedures to retain their employees. The data sources for this study were semistructured interviews, financial statements, newspaper articles, websites, and social media. A thematic analysis was used to analyze the data. Three themes morphed to include challenging employees and reward them accordingly, mitigating unplanned turnover, and treating employees and others fairly. Potential implications for positive social change are that increased profits among small business owners may enable them to provide better benefits and pay and incentive increases to their employees. Small business owners with increased profits may also be better equipped to participate in community-based charitable organizations.Thirty-four percent of people in the United States of America work for businesses that employ fewer than 100 people. However, many small business owners lack the strategies necessary to retain their valuable employees. Businesses that fail to retain valuable employees are as much as 28% less efficient. The purpose of this qualitative multiple case study was to explore strategies small construction business owners use to retain their valuable employees. Contingency theory provided the conceptual framework. The participants were three owners of three small businesses in the construction industry located in Mississippi which implemented successful policies and procedures to retain their employees. The data sources for this study were semistructured interviews, financial statements, newspaper articles, websites, and social media. A thematic analysis was used to analyze the data. Three themes morphed to include challenging employees and reward them accordingly, mitigating unplanned turnover, and treating employees and others fairly. Potential implications for positive social change are that increased profits among small business owners may enable them to provide better benefits and pay and incentive increases to their employees. Small business owners with increased profits may also be better equipped to participate in community-based charitable organizations. Small Construction Business Owners’ Strategies for Employee Retention by Charles H. Griner, Jr. MS, Troy University, 2006 BBA, University of Mississippi, 1991 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University November 2019 Dedication I dedicate this study to my mother, Brenda Morris Griner. She provided encouragement and served as an example of what one can accomplish with hard work and persistence. Acknowledgments I would like to thank my chair, Dr. Kenneth Gossett, for being patient with me while I was being impatient. I would also like to thank the faculty, staff, and my fellow students for all of their input and guidance along the way.

Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

Abstract: The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addit...

Multivariate Data Analysis

Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations. Table of Contents 1. Introduction. I. PREPARING FOR A MULTIVARIATE ANALYSIS. 2. Examining Your Data. 3. Factor Analysis. II. DEPENDENCE TECHNIQUES. 4. Multiple Regression. 5. Multiple Discriminant Analysis and Logistic Regression. 6. Multivariate Analysis of Variance. 7. Conjoint Analysis. 8. Canonical Correlation Analysis. III. INTERDEPENDENCE TECHNIQUES. 9. Cluster Analysis. 10. Multidimensional Scaling. IV. ADVANCED AND EMERGING TECHNIQUES. 11. Structural Equation Modeling. 12. Emerging Techniques in Multivariate Analysis. Appendix A: Applications of Multivariate Data Analysis. Index.

Structural equation modeling in practice: a review and recommended two-step approach

Abstract: In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehensive, two-step modeling approach that employs a series of nested models and sequential chi-square difference tests. We discuss the comparative advantages of this approach over a one-step approach. Considerations in specification, assessment of fit, and respecification of measurement models using confirmatory factor analysis are reviewed. As background to the two-step approach, the distinction between exploratory and confirmatory analysis, the distinction between complementary approaches for theory testing versus predictive application, and some developments in estimation methods also are discussed.

Multivariate data analysis

Abstract: I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 10 Structural Equation Modeling: Overview 10a Appendix -- SEM 11 CFA: Confirmatory Factor Analysis 11a Appendix -- CFA 12 SEM: Testing A Structural Model 12a Appendix -- SEM APPENDIX A Basic Stats

The balanced scorecard : measures that drive performance

Abstract: Frustrated by the inadequacies of traditional performance measurement systems, some managers have abandoned financial measures like return on equity and earnings per share. "Make operational improvements and the numbers will follow," the argument goes. But managers do not want to choose between financial and operational measures. Executives want a balanced presentation of measures that allow them to view the company from several perspectives simultaneously. During a year-long research project with 12 companies at the leading edge of performance measurement, the authors developed a "balanced scorecard," a new performance measurement system that gives top managers a fast but comprehensive view of the business. The balanced scorecard includes financial measures that tell the results of actions already taken. And it complements those financial measures with three sets of operational measures having to do with customer satisfaction, internal processes, and the organization's ability to learn and improve--the activities that drive future financial performance. Managers can create a balanced scorecard by translating their company's strategy and mission statements into specific goals and measures. To create the part of the scorecard that focuses on the customer perspective, for example, executives at Electronic Circuits Inc. established general goals for customer performance: get standard products to market sooner, improve customers' time-to-market, become customers' supplier of choice through partnerships, and develop innovative products tailored to customer needs. Managers translated these elements of strategy into four specific goals and identified a measure for each.