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Journal ArticleDOI

Exploring the mediating role of social capital in the relationship between financial intermediation and financial inclusion in rural Uganda

TL;DR: In this paper, the mediating role of social capital in the relationship between financial intermediation and financial inclusion in rural Uganda was established. But, the study was cross-sectional, thus, limiting efforts in investigating certain characteristics of the sample over time.
Abstract: The purpose of this paper is to establish the mediating role of social capital in the relationship between financial intermediation and financial inclusion in rural Uganda.,The current study used cross-sectional research design and a semi-structured questionnaire was used to collect data for this study. The study applied structural equation modeling through bootstrap approach in AMOS to establish the mediating role of social capital in the relationship between financial intermediation and financial inclusion.,The results indicated that social capital significantly mediates the relationship between financial intermediation and financial inclusion in rural Uganda. Therefore, it can be deduced that social capital among the poor play an important role in promoting financial intermediation for improved financial inclusion in rural Uganda.,Although the sample was large, it may not be generalized to other segments of the population. Data were collected from only poor households located in rural Uganda. Besides, the study was cross-sectional, thus, limiting efforts in investigating certain characteristics of the sample over time. Perhaps future studies could adopt the use of longitudinal research design.,Financial institutions such as banks should rely on social capital as a substitute for physical collateral in order to promote financial inclusion, especially among the poor in rural Uganda.,This study provides empirical evidence on phenomenon not studied in rural areas in Sub-Saharan Africa where the poor use social capital embedded in customs and norms for doing business. The results highlight the importance of social capital in mediating the relationship between financial intermediation and financial inclusion of the poor in rural Uganda.
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Posted Content
TL;DR: In this article, the authors provide a conceptual review and measurement tools for understanding and measuring social capital in a form readily available for development practitioners, and discuss the respective value of quantitative, and qualitative approaches to the analysis of social capital.
Abstract: The importance of social capital for sustainable development, is by now well recognized. Anthropologists, sociologists, political scientists, and economists have in their own ways, demonstrated the critical role of institutions, networks, and their supporting norms and values, for the success of development interventions. This success often hinges on accurate assessments of social capital in target communities. But the nature, and impact of social capital - the institutions, relationships, attitudes, and values that govern interactions among people - are not easily quantified. "Understanding and Measuring Social Capital" provides a conceptual review, and measurement tools, in a form readily available for development practitioners. The book discusses the respective value of quantitative, and qualitative approaches to the analysis of social capital, illustrating the discussion with examples, and case studies from many countries. It also presents the Social Capital Assessment Tool, which combines quantitative, and qualitative instruments to measure social capital at the level of household, community, and organization, drawing on multidisciplinary, empirical experiences, an application which can provide project managers with valuable baseline, and monitoring information about social capital in its different dimensions.

534 citations

Journal ArticleDOI
TL;DR: In this paper, the authors constructed an integrated model to examine the impact of financial literacy, access to finance and financial risk attitude on SMEs' sustainability, and found that financial literacy was a predictor of access and risk attitude.
Abstract: Role of the knowledge-based resources in promoting sustainability in small and medium enterprises (SMEs) is currently a topic of debate. Financial literacy has been identified as a vital knowledge resource for financial decision making, but insufficient attention has been given to how SMEs’ financial literacy affects their sustainability. Drawing upon a knowledge-based perspective, peaking order theory and dual process theory, we constructed an integrated model to examine the impact of financial literacy, access to finance and financial risk attitude on SMEs’ sustainability. The sample included 291 chief financial officers (CFOs) of SMEs in Sri Lanka. The output of structural equation modelling revealed direct positive effects of financial literacy, access to finance and financial risk attitude on sustainability. Financial literacy also emerged as a predictor of access to finance and financial risk attitude. Moreover, access to finance and financial risk attitude were found to be partial mediators of the relationship between financial literacy and SMEs’ sustainability. Theoretical implications and practical implications for policymakers, industry practitioners and academics interested in promoting sustainability amongst SMEs are discussed.

75 citations

Journal ArticleDOI
TL;DR: A single-mediator structural model is developed with an aim to explore the effect of techno-finance literacy and enterprise risk management practices (applications) on the performance of SMEs in Sri Lankan SMEs and highlights that techno- finance literacy is a significant determinant of two endogenous constructs, namely, SME performance and ERM practices.
Abstract: The knowledge-based view (KBV) in the development of small and medium-sized enterprises (SMEs) is a debatable topic in the current literature. Although convergence of technological and financial literacy (techno-finance literacy) is an essential knowledge-based tool to address rapid digitalization of business, the influence of techno-finance literacy in the development of SMEs is still not adequately researched. Drawing upon KBV, we developed a single-mediator structural model with an aim to explore the effect of techno-finance literacy and enterprise risk management (ERM) practices (applications) on the performance of SMEs. A self-administered structured questionnaire was employed to collect data from 319 chief financial offers (CFOs) in Sri Lankan SMEs. The outcome of our study highlights that techno-finance literacy is a significant determinant of two endogenous constructs, namely, SME performance and ERM practices. Furthermore, ERM practices of SMEs were also positively affected to the SME performance. Moreover, ERM practices were observed to have a partial mediation on the relationship between financial literacy and SME performance. These findings form the basis for theories in techno-finance literacy and SME performance, as well as present managerial implications to enhance the performance of SMEs.

41 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed how CEO's financial literacy influences a firm's technological innovation and investigated the mediating role of alleviating financial constraints of Small and Medium-sized Enterprises (SMEs) in the former relationship.

34 citations

References
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Journal ArticleDOI
TL;DR: This article seeks to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating the many ways in which moderators and mediators differ, and delineates the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena.
Abstract: In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.

80,095 citations

Book
01 Jan 1983
TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
Abstract: In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Book Chapter 3 Review of Univariate and Bivariate Statistics Chapter 4 Cleaning Up Your Act: Screening Data Prior to Analysis Chapter 5 Multiple Regression Chapter 6 Analysis of Covariance Chapter 7 Multivariate Analysis of Variance and Covariance Chapter 8 Profile Analysis: The Multivariate Approach to Repeated Measures Chapter 9 Discriminant Analysis Chapter 10 Logistic Regression Chapter 11 Survival/Failure Analysis Chapter 12 Canonical Correlation Chapter 13 Principal Components and Factor Analysis Chapter 14 Structural Equation Modeling Chapter 15 Multilevel Linear Modeling Chapter 16 Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS Chapter 1: Introduction Multivariate Statistics: Why? Some Useful Definitions Linear Combinations of Variables Number and Nature of Variables to Include Statistical Power Data Appropriate for Multivariate Statistics Organization of the Book Chapter 2: A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques Some Further Comparisons A Decision Tree Technique Chapters Preliminary Check of the Data Chapter 3: Review of Univariate and Bivariate Statistics Hypothesis Testing Analysis of Variance Parameter Estimation Effect Size Bivariate Statistics: Correlation and Regression. Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to Analysis Important Issues in Data Screening Complete Examples of Data Screening Chapter 5: Multiple Regression General Purpose and Description Kinds of Research Questions Limitations to Regression Analyses Fundamental Equations for Multiple Regression Major Types of Multiple Regression Some Important Issues. Complete Examples of Regression Analysis Comparison of Programs Chapter 6: Analysis of Covariance General Purpose and Description Kinds of Research Questions Limitations to Analysis of Covariance Fundamental Equations for Analysis of Covariance Some Important Issues Complete Example of Analysis of Covariance Comparison of Programs Chapter 7: Multivariate Analysis of Variance and Covariance General Purpose and Description Kinds of Research Questions Limitations to Multivariate Analysis of Variance and Covariance Fundamental Equations for Multivariate Analysis of Variance and Covariance Some Important Issues Complete Examples of Multivariate Analysis of Variance and Covariance Comparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated Measures General Purpose and Description Kinds of Research Questions Limitations to Profile Analysis Fundamental Equations for Profile Analysis Some Important Issues Complete Examples of Profile Analysis Comparison of Programs Chapter 9: Discriminant Analysis General Purpose and Description Kinds of Research Questions Limitations to Discriminant Analysis Fundamental Equations for Discriminant Analysis Types of Discriminant Analysis Some Important Issues Comparison of Programs Chapter 10: Logistic Regression General Purpose and Description Kinds of Research Questions Limitations to Logistic Regression Analysis Fundamental Equations for Logistic Regression Types of Logistic Regression Some Important Issues Complete Examples of Logistic Regression Comparison of Programs Chapter 11: Survival/Failure Analysis General Purpose and Description Kinds of Research Questions Limitations to Survival Analysis Fundamental Equations for Survival Analysis Types of Survival Analysis Some Important Issues Complete Example of Survival Analysis Comparison of Programs Chapter 12: Canonical Correlation General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Canonical Correlation Some Important Issues Complete Example of Canonical Correlation Comparison of Programs Chapter 13: Principal Components and Factor Analysis General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Factor Analysis Major Types of Factor Analysis Some Important Issues Complete Example of FA Comparison of Programs Chapter 14: Structural Equation Modeling General Purpose and Description Kinds of Research Questions Limitations to Structural Equation Modeling Fundamental Equations for Structural Equations Modeling Some Important Issues Complete Examples of Structural Equation Modeling Analysis. Comparison of Programs Chapter 15: Multilevel Linear Modeling General Purpose and Description Kinds of Research Questions Limitations to Multilevel Linear Modeling Fundamental Equations Types of MLM Some Important Issues Complete Example of MLM Comparison of Programs Chapter 16: Multiway Frequency Analysis General Purpose and Description Kinds of Research Questions Limitations to Multiway Frequency Analysis Fundamental Equations for Multiway Frequency Analysis Some Important Issues Complete Example of Multiway Frequency Analysis Comparison of Programs

53,113 citations

Journal ArticleDOI
TL;DR: The extent to which method biases influence behavioral research results is examined, potential sources of method biases are identified, the cognitive processes through which method bias influence responses to measures are discussed, the many different procedural and statistical techniques that can be used to control method biases is evaluated, and recommendations for how to select appropriate procedural and Statistical remedies are provided.
Abstract: Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.

52,531 citations

Journal ArticleDOI
TL;DR: In this paper, the concept of social capital is introduced and illustrated, its forms are described, the social structural conditions under which it arises are examined, and it is used in an analys...
Abstract: In this paper, the concept of social capital is introduced and illustrated, its forms are described, the social structural conditions under which it arises are examined, and it is used in an analys...

31,693 citations

Book
01 Jan 2000
TL;DR: Suitable for those new to statistics as well as students on intermediate and more advanced courses, the book walks students through from basic to advanced level concepts, all the while reinforcing knowledge through the use of SAS(R).
Abstract: Hot on the heels of the 3rd edition of Andy Field's award-winning Discovering Statistics Using SPSS comes this brand new version for students using SAS(R). Andy has teamed up with a co-author, Jeremy Miles, to adapt the book with all the most up-to-date commands and programming language from SAS(R) 9.2. If you're using SAS(R), this is the only book on statistics that you will need! The book provides a comprehensive collection of statistical methods, tests and procedures, covering everything you're likely to need to know for your course, all presented in Andy's accessible and humourous writing style. Suitable for those new to statistics as well as students on intermediate and more advanced courses, the book walks students through from basic to advanced level concepts, all the while reinforcing knowledge through the use of SAS(R). A 'cast of characters' supports the learning process throughout the book, from providing tips on how to enter data in SAS(R) properly to testing knowledge covered in chapters interactively, and 'real world' and invented examples illustrate the concepts and make the techniques come alive. The book's companion website (see link above) provides students with a wide range of invented and real published research datasets. Lecturers can find multiple choice questions and PowerPoint slides for each chapter to support their teaching.

25,020 citations