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JBE Spring 2017 Volume 28, No. 2 Spring, 2017 Editorial Staff Managing Editor William T. Jackson Editors Mary Jo Jackson Jeff Vanevenhoven The Journal of Business and Entrepreneurship is published by the Association for Small Business and Entrepreneurship (ASBE) and Stetson University. All ASBE members receive one copy of the publication. Subscribe, order back issues or single copies at [email protected]. Submission guidelines can also be found at www.asbe.us. ISSN: 1042-6337 ©2017 Association for Small Business and Entrepreneurship Hosted by: Table of Contents Volume 28, No.2 Spring, 2017 Modeling Business Failure among SMEs: An Artificial Neural Networks and Logistic Regression Analysis Densil A. Williams ...................................................................................................... 2 In or Out: Narcissism and Entrepreneurial Self-Efficacy and Intrapreneurial Intentions Reginald L. Tucker, Randall M. Croom, and Louis D. Marino ................... 28 The Relations Between Entrepreneurs’ Ethnicity, Familism Values, Beliefs, and Use of Financial Planning Dianna L. Stone, Julio C. Canedo, Teresa L. Harrison, and Kimberly M. Lukaszewski ............................................................................................................. 51 An Examination of Faculty Salaries Between the Fields of Strategic Management and Entrepreneurship Todd A. Finkle and Manasi Katragadda .......................................................... 83 Different But Inseparable: The Contingent Association of Instrumental and Emotional Support Mette Søgaard Nielsen ........................................................................................ 128 The Effects of Motivatio over Entrepreneurial Performance: The Case for Mexican Startups Elvira Anzola González and Carlos Canfield Rivera .................................. 150 ----2017-2018 Officers---- Association for Small Business & Entrepreneurship Mary Jo Jackson, Stetson University President Courtney Kernek, Southeastern Oklahoma State University President Elect Janice Black, Costal Carolina University Vice President - Programs Eugenie Ardoin, University of Louisiana at Monroe Vice-President Membership Randall Croom, Stetson University Treasurer & Secretary Henry Cole, University of Louisiana at Monroe Past President ----Editorial Review Board---- Joshua Abor Charles Fischer University of Stellenbosch Pittsburg State University Joe Ballenger Donald W. Garland Stephen F. Austin State University New Mexico State University Jurgita Baltrusaityte-Axelson William C. Green Stockholm School of Economics Sul Ross State University Stephen S. Batory Walter E. Greene Bloomsburg University Greene and Associates James A. Bell Marko Grünhagen University of Central Arkansas Eastern Illinois University Josh Bendickson Robert D. Gulbro Eastern Carolina University Athens State University Thomas M. Box Stephen C. Harper Pittsburg State University University of North Carolina ~ Wilmington Susan Boyd E. Alan Hartman University of Tulsa University of Wisconsin ~ Oshkosh Steve Brown Diana M. Hechavarria Eastern Kentucky University University of South Florida Kent Byus Marilyn M. Helms Texas A&M ~ Corpus Christi Dalton State College Thomas M. Cooney Colin Jones Dublin Institute of Technology University of Tasmania James A. DiGabriele DiGabriele, McNulty & Co. LL Minjoon Jun New Mexico State University Paul Dunn University of Louisiana ~ Monroe M. Riaz Khan University Massachusetts Lowell João J. M. Ferreira University of Beira Interior Naresh Kumar NESH Training and Consultancy Joseph F. Singer University of Missouri Kansas City Agnieszka Kurczeska University of Lodz George Solomon George Washington University Vaidotas Lukosius Tennessee State University Tulus Tambunan University of Trisakti Keishiro Matsumoto University of the Virgin Islands Ayman El Tarabishy George Washington University Shaun McQuitty Athabasca University Leslie Toombs Texas A & M Commerce Teresa V. Menzies Brock University Raydel Tullous University of Texas ~ San Antonio Jay Nathan St. John’s University Jude Valdez University of Texas ~ San Antonio Barbara R. Oates Texas A&M ~ Kingsville Jeff Vanevenhoven University of Wisconsin White Water Linda Ann Riley Roger Williams University Rebecca J. White University of Tampa Philip T. Roundy University of Tennessee at Densil Williams Chattanooga University of West Indies Mona Christopher M. Scalzo Phillip H. Wilson Morrisville State College Midwestern State University Mark T. Schenkel Marilyn Young Belmont University University of Texas ~ Tyler Philip Siegel Florida Atlantic University Dear JBE Readership: Welcome to the spring 2017 issue of the Journal of Business and Entrepreneurship. This year is shaping up to be a great year for the journal as well as the Association for Small Business and Entrepreneurship. As announced in the last issue our acceptance in the SCOPUS ranking system is already paying dividends with greater exposure and recognition. First, all of the hard work in making this happen will result in providing our loyal authors—those that took a chance on using us as their publishing option—greater support in their promotion and tenure aspirations. It also provides considerable national and international exposure thus increasing the number and quality of the submissions to follow. Finally, it is a great reward for all of those that have given their time and energy to maintain the quality of our 27 year existence. There is also additional news related to the Association for Small Business and Entrepreneurship (ASBE). The Executive Committee as endorsed by membership at the last conference have decided to join the Federation of Business Disciplines as a conditional member at that organization’s next conference (Albuquerque, March 2018). We are very excited to be a part of the long history of FBD and feel strongly that this will further advance JBE through this outreach effort. Also, if you haven’t submitted a manuscript to JBE recently (or ever) please consider us as a potential research outlet for your next manuscript. While we are excited about being a part of SCOPUS, we see this as only the beginning of our future growth William T. Jackson (Bill) Mary Jo Jackson Jeff Vanevenhoven Managing Editor Editor Editor MODELING BUSINESS FAILURE AMONG SMEs: AN ARTIFICIAL NEURAL NETWORKS AND LOGISTIC REGRESSION ANALYSIS Densil A. Williamsi Mona School of Business and Management Since the 1980s, there has been a burgeoning literature on business failure. However, the results have been fragmented and inconsistent in most respects. This is mainly due to the less than rigorous analytical tools that have been used to conduct the analysis of the data. To address this problem, this research has applied the artificial neural networks model to predict business failure, a departure from the traditional methods. The results found that the neural networks method is a much more powerful analytical tool to predict business failure than the traditional logistic regression models. The results from the neural networks and their predictive accuracy are presented in the paper along with the predictive accuracy of the logistic regression model. The implications of the work for future research and managers in small firms are also presented. Keywords: Business Failure, Neural Networks, Logistic Regression, SMEs. INTRODUCTION Since the 1980s, there has been a growing literature on business failure as a measure of firm performance (Campbell et al., 2012; Mellahi and Wilkinson, 2004; Thornhill and Amit, 2003; Whetten, 1980). The literature however, remains quite disperse with very few definitive conclusions as to the factors that have led to failure among firms, especially the small and medium-sized enterprises (Mellahi and Wilkinson,2004). This seems to be due mainly to: the less than rigorous and sophisticated methods used to model failure, the divergence in theoretical lenses used to analyze the problem, among other things (Mellahi and Wilkinson, 2004). This study therefore, will depart from the traditional simplified methods such as, linear regression models and qualitative case studies and use a more powerful tool, the Artificial Neural Networks model, Spring 2017 Journal of Business & Entrepreneurship 1 which has never been used in the literature before, to predict the factors that impact on business failure. Neural network models are more flexible and less restrictive in their assumptions about the data and as such, will lead to more robust results. In addition to the Neural Networks model, this study will also apply the logistic regression model to the problem in order to validate the findings even more rigorously. This methodological approach to the problem will help to add new insights to the work and also, further advance the ability of theorists in the field to build a general theory on business failure. The work presented in this paper will try to answer the following questions: a) Which factors are most important in predicting business failure among SMEs? b) Can the neural networks models give a better predictive accuracy than the traditional logit model in predicting business failure? The first question draws on the resource-based view of the firm as the theoretical lens through which to analyze the research problem. Viewing business failure through the resource-based lens, it argues that the fewer resources that a firm possess is the greater the likelihood that it will fail. In essence, the argument is that there is a negative relationship between failure rates and the availability
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