Perceived Market Risk in New Ventures: A Study of Early-Phase Business Angel Investment Screening

2020 ◽  
Vol 40 (3) ◽  
pp. 339-354
Author(s):  
Kellilynn M. Frias ◽  
Deidre L. Popovich ◽  
Dale F. Duhan ◽  
Robert F. Lusch
Keyword(s):  
Capital Markets ◽  
New Ventures ◽  
Market Risk ◽  
Business Angels ◽  
Screening Process ◽  
Professional Networks ◽  
Business Angel ◽  
Angel Investment ◽  
Early Phases ◽  
Practical Implications

Business angels are vital sources of funding for new ventures. Yet, acquiring business angel support is difficult. Typically organized in professional networks, business angels collectively evaluate and deliberate about new ventures to determine their worthiness of support. One factor deemed to be critical during this evaluation is market risk. Yet, limited research in Macromarketing examines market risk. To our knowledge, no previous study examines market risk in capital markets, nor do they study angel financing. Neglecting to study angel financing is particularly problematic for macromarketing because this type of finance is much more prominent than venture capital in supporting new ventures. To fill this gap, we begin by exploring the literature by Lusch (and coauthors) linking marketing and capital markets as well as studies of market risk. We then craft fictitious angel investment proposals to measure market risk assessments by business angels and entrepreneurs. We ask which factors impact market risk during the early-phases of the investment screening process (when market risk is weighted more heavily) and identify whether these factors are evaluated differently by entrepreneurs versus business angels. Our findings reveal that commercialization capability, technological compatibility, and intellectual property rights enforceability influence perceived market risk and that entrepreneurs and business angels view these factors significantly differently. We then offer directions for further research related to this study and other work of Lusch. Finally, we suggest practical implications for use by business angels and entrepreneurs.

Who is more likely to become business angels?

2014 ◽  
Vol 6 (1) ◽  
pp. 4-20 ◽  
Author(s):  
Yaokuang Li ◽  
Li Ling ◽  
Juan Wu ◽  
Peng Li
Keyword(s):  
Influence Factors ◽  
Positive Influence ◽  
Clear Understanding ◽  
Logit Analysis ◽  
Business Angels ◽  
Investment Activity ◽  
Content Type ◽  
Angel Investment ◽  
Investment In China ◽  
Practical Implications

Purpose – The paper is aimed to obtain a clear understanding of influence factors that can increase the possibility to be business angels (BA). Design/methodology/approach – This study develops the 3A model in the Chinese context to design questionnaire, and 334 questionnaires are obtained via focus group sample and targeted snowball approach, and the multinomial logit analysis is used to test a serious of hypotheses. Findings – The paper confirmed that the entrepreneurial experience and wealth are determinants of investment for potential BA, and the wealth have both directly and indirectly positive influence on investment activity through risk preference, namely that richer people prefer risk which impel them to invest as BA. Research limitations/implications – There are two limitations in the paper: first, the macro environment in China has not been taken into consideration in the model; second, the source of the sample focuses on the developed cities in the middle and eastern of China, only reflect the characteristic of angels in these areas, which may somewhat diverges from the reality. Practical implications – The paper would contribute to form the policy which could promote the development of angel investment in China. Originality/value – This paper conducts a preliminary exploration of the factors that have impact on Chinese BA' investment activity based on current research.

Shariah-compliant equities and Shariah screening: need for convergence of ethical screening of stocks with Shariah screening

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tauhidul Islam Tanin ◽  
Abu Umar Faruq Ahmad ◽  
Aishath Muneeza
Keyword(s):  
Original Research ◽  
Screening Process ◽  
Screening Criteria ◽  
Content Type ◽  
Practical Applications ◽  
Qualitative Research Methodology ◽  
Qualitative Descriptive ◽  
Stock Screening ◽  
Descriptive Approach ◽  
Practical Implications

PurposeThis study explores the practical application of the Shariah screening process and how it could be enhanced by converging the same with the ethical screening of stocks.Design/methodology/approachThis study adopts a qualitative research methodology by combining the qualitative descriptive approach and content analysis.FindingsThe findings of this research suggest that there is scope to converge ethical screening of stocks with Shariah Screening as the lex loci applicable to Shariah screening is derived from Shariah, which considers ethics as part of determining its rules.Practical implicationsThe data from this study reveal several practical applications, the ultimate goal of which is to help the policymakers and stakeholders understand the relevance of the Shariah screening of stocks and get a streamlined screening process, paving the way to enhance the same using ethical screening criteria to develop its function to become much more relevant irrespective of the denomination of faiths.Originality/valueThis is original research, which is expected to contribute to understanding the extent to which Shariah screening can be enhanced by integrating the ethical stock screening dimension to it.

Innovation for a (high-tech) nation

2018 ◽  
Vol 34 (12) ◽  
pp. 12-14
Keyword(s):  
Competitive Advantage ◽  
Case Studies ◽  
Design Methodology ◽  
Reading Time ◽  
New Ventures ◽  
Innovation Strategy ◽  
High Tech ◽  
Content Type ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings High-tech new ventures are typically beset by significant challenges in their marketplaces. Using effectuation, innovation strategy and the moderating force of opportunity shaping, they are able to gain competitive advantage. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The angel investment decision: insights from Australian business angels

2018 ◽  
Vol 60 (3) ◽  
pp. 3133-3162
Author(s):  
Brett Anthony White ◽  
John Dumay
Keyword(s):  
Investment Decision ◽  
Business Angels ◽  
Angel Investment

scholarly journals Riskmetrics™ Methodology in Assessment of Investment Risk on Capital Markets

2010 ◽  
Vol 9 (1) ◽  
pp. 34-51
Author(s):  
Grzegorz Mentel
Keyword(s):  
Capital Markets ◽  
Stock Exchange ◽  
Risk Measures ◽  
Market Risk ◽  
Investment Risk ◽  
Financial Instruments ◽  
Investment Portfolio ◽  
Warsaw Stock Exchange ◽  
Financial Portfolio

Riskmetrics™ Methodology in Assessment of Investment Risk on Capital Markets In the article the author has presented the methodology of assessment of market risk connected with investing in all sorts of financial instruments such as: shares, bonds and other derivatives, e.g. RiskGrade (RG). The measure has been introduced by RiskMetrics. The article presents the application of RiskGrades methodology while choosing the optimum investment portfolio for a Polish investor who invests in shares in the Warsaw Stock Exchange. Moreover, some other risk measures have been discussed which describe the efficiency of the optimum financial portfolio.

An economic production model with imperfect quality components and probabilistic lead times

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdul-Nasser El-Kassar ◽  
Alessio Ishizaka ◽  
Yama Temouri ◽  
Abdullah Al Sagheer ◽  
Daicy Vaz
Keyword(s):  
Mathematical Model ◽  
Production Process ◽  
Production Cycle ◽  
Lead Times ◽  
Screening Process ◽  
Content Type ◽  
Imperfect Quality ◽  
Reorder Point ◽  
Production Run ◽  
Practical Implications

PurposeThis study investigates a production process that requires N kinds of components for the production of a finished product. The producer orders the various kinds of components from different suppliers and receives the orders in lots at the beginning of each production cycle. Similar to situations often encountered in real life, the lead times are random variables with known probability distributions so that a production cycle starts whenever all N kinds of components become available. Each of the lots received at the start of a production run contains both perfect and imperfect quality components. Once all N kinds of components become available, the producer initiates a screening process to detect the imperfect components. The production of the finished product uses only perfect quality components. The imperfect components are removed from inventory whenever the screening process is completed. The percentage of components of perfect quality present in each lot is a random variable with a known probability distribution.Design/methodology/approachThis production process is described and modeled mathematically and the optimal production/ordering policy is derived based on the mathematical model.FindingsThe formulated mathematical model resulted in the determination of the optimal policy consisting of the optimal number of finished items ordered to be produce during each production run, the number of components ordered from each supplier, and the reorder point. The derived closed form expression for the optimal lot size depends on the minimum of the number of perfect quality components in a lot, whereas the reorder point is determined based on the maximum lead time.Practical implicationsThe modeling approach and results of this study provide practical implications that may be beneficial to both production and supply chain managers as well as researchers.Originality/valueThis modeling approach that incorporates decision-making related to the logistics of acquiring the components and accounts for the probabilistic nature of the lead times and quality of components addresses a gap in the logistics/production literature.

scholarly journals The making of information nations

2019 ◽  
Vol 33 (1) ◽  
pp. 12-26 ◽  
Author(s):  
Merlin Stone ◽  
Jon Machtynger ◽  
Liz Machtynger ◽  
Eleni Aravopoulou
Keyword(s):  
Information Technology ◽  
Global Economy ◽  
New Ventures ◽  
Secondary Data ◽  
Social Implications ◽  
Education Policies ◽  
Content Type ◽  
And Mathematics ◽  
High Level ◽  
Practical Implications

Purpose The purpose of this paper is to identify the main characteristics of what have come to be called information nations and to identify some of the determinants of success in becoming an information nation. Design/methodology/approach The paper is based on a critical review of the literature and of secondary data on information technology and services from studies of the innovativeness of nations. Findings Success in becoming an information nation is not necessarily closely connected with investments in information technology and services by firms and policies supporting these investments by governments, or with education policies designed to support the development of science, technology, engineering and mathematics. Other factors, such as the vibrancy of capitalism, particularly the funding of new ventures, the culture of the nation and its focus on non-scientific determinants of innovation, such as design, are also important. Governments should be careful not to take credit for achievements when their policies are merely coincident with those achievements. Research limitations/implications The main limitations relate to the focus of this article on two sets of nations, South East/East Asia and two Western nations. The review of their performance is relatively high level and needs to be deepened, while the number of nations included in the research needs to be increased. Practical implications This paper has substantial practical implications for government policymakers, in terms of whether and how they should make policy at all in this area, and for companies trying to establish a long-term position in the global economy, in terms of being careful not to go against the very strong economic forces which favour certain kinds of activities in certain countries. Social implications This paper has significant social implications, because much of the thinking about developing information societies relies on generalisations about the creation of information nations that may not hold. Governments and social commentators are encouraged to approach the idea of making “big policies” in this area with some scepticism. Originality/value The content of this paper is not original, but the challenge to policymakers is relatively original, as too often the work of academics is sponsored by governments that are trying to legitimate the value of their own efforts.

scholarly journals It’s a Peoples Game, Isn’t It?! A Comparison Between the Investment Returns of Business Angels and Machine Learning Algorithms

2020 ◽  
pp. 104225872094520
Author(s):  
Ivo Blohm ◽  
Torben Antretter ◽  
Charlotta Sirén ◽  
Dietmar Grichnik ◽  
Joakim Wincent
Keyword(s):  
Machine Learning ◽  
Cognitive Biases ◽  
Early Stage ◽  
Investment Decisions ◽  
Machine Learning Algorithms ◽  
Behavioral Decision Theory ◽  
Business Angels ◽  
Cognitive Limitations ◽  
Investment Returns ◽  
Angel Investment

Investors increasingly use machine learning (ML) algorithms to support their early stage investment decisions. However, it remains unclear if algorithms can make better investment decisions and if so, why. Building on behavioral decision theory, our study compares the investment returns of an algorithm with those of 255 business angels (BAs) investing via an angel investment platform. We explore the influence of human biases and experience on BAs’ returns and find that investors only outperformed the algorithm when they had extensive investment experience and managed to suppress their cognitive biases. These results offer novel insights into the role of cognitive limitations, experience, and the use of algorithms in early stage investing.

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