Search results

Entrepreneurship researchers use various types of screening criteria to select samples for study. In that selecting these criteria is, in effect, choosing a definition or model of entrepreneurship, the consequences are immense and have had a direct impact on the generalizability of research and theory development in our field. The purpose of this study is to help entrepreneurship researchers better understand these consequences and, thereby, improve our understanding of entrepreneurial phenomenon. Four of the most commonly used screening criteria are included in this study: firm age, firm size, firm growth, and innovation. Based on a sample of 368 manufacturing firms, the results indicate that few firms fit all or even most of the considered screening criteria and independent-dependent variable relationships vary considerably by screening criteria selection.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this paper is to predict the daily accuracy improvement for the Jakarta Islamic Index (JKII) prices using deep learning (DL) with small and big data of symmetric volatility information.

This paper uses the nonlinear autoregressive exogenous (NARX) neural network as the optimal DL approach for predicting daily accuracy improvement through small and big data of symmetric volatility information of the JKII based on the criteria of the highest accuracy score of testing and training. To train the neural network, this paper employs the three DL techniques, namely Levenberg–Marquardt (LM), Bayesian regularization (BR) and scaled conjugate gradient (SCG).

The experimental results show that the optimal DL technique for predicting daily accuracy improvement of the JKII prices is the LM training algorithm based on using small data which provide superior prediction accuracy to big data of symmetric volatility information. The LM technique develops the optimal network solution for the prediction process with 24 neurons in the hidden layer across a delay parameter equal to 20, which affords the best predicting accuracy based on the criteria of mean squared error (MSE) and correlation coefficient.

This research would fill a literature gap by offering new operative techniques of DL to predict daily accuracy improvement and reduce the trading risk for the JKII prices based on symmetric volatility information.

This research is the first that predicts the daily accuracy improvement for JKII prices using DL with symmetric volatility information.

As many businesses faced economic disruption due to the Covid-19 pandemic and sought financial relief, existing bank relationships became critical to getting a loan. This study examines factors associated with the development of personal relationships of rural small businesses with community bank representatives.

We applied a mixed-method approach. We employed descriptive statistics, principal factor analysis and logistic regression for data analysis. We distributed an online survey to rural small businesses in five states in the United States. Key informant interviews with community bank representatives supplemented the survey results.

A business owner’s trust in a banker was positively associated with the establishment of a business–bank relationship. However, an analysis of individual trust’s components revealed that the nature of trust is complex, and a failure of one or more components may lead to decreased trustworthiness in a banker. Small businesses that preferred personal communication with a bank were more inclined to relationship banking.

Due to the relatively small sample size and cross-sectional data, our results may not be conclusive but should be viewed as preliminary and as suggestions for future research. Bankers should be aware of the importance of trust for small business owners and of the actions that lead to increased trustworthiness.

The study extends the existing knowledge on the business–bank relationship by focusing mainly on social (instead of economic) factors associated with the establishment of the business–bank relationship in times of crisis and high uncertainty.

Prior studies argue that social capital is vital for firm growth. Adding to this line of research, this paper provides more evidence regarding the contribution of bonding and bridging social ties to various aspects of small-l and medium-sized enterprise (SME) development. Building on the original data from Russia, this paper investigates the effects of firm-internal and firm-external relational ties on SME performance and geographic expansion. The findings indicate that horizontal bridging ties facilitate specific strategies of SME growth. Thus, this paper supports prior research conducted in the Asian context, and allows for extending the outcomes of bonding and bridging social capital into broader institutional settings. In addition, this study raises the question of relationship between the composition of social capital and distinct organizational characteristics of SMEs. Finally, the paper discusses the implications for future research, and outlines some practical recommendations for SMEs operating in emerging markets.

Correct registration for the value-added tax (VAT) is a key aspect of tax compliance; it is vital in ensuring adequate tax revenue collection in all countries but particularly in developing countries such as South Africa. Non-registration hinders sufficient tax revenue collection, stifles economic growth and causes unfair competition with formal businesses. The purpose of this study is to determine whether changes in the VAT rate affect the registration decisions of businesses, ultimately impacting upon tax compliance behaviour and tax revenue collection.

An online 2 × 2 between-subjects field experiment was conducted, as part of a broader study, to consider compliance with registration requirements by small business entities in South Africa, specifically when there are changes in the VAT rate.

Although the study establishes that changes in the VAT rate tend not to have a significant impact on the registration decisions of such taxpayers, it nonetheless indicates that the magnitude of the change in the VAT rate may be influential on registration decisions, whether relating to compulsory or voluntary registration. More particularly, the greater the magnitude of the VAT rate decrease (increase), the more likely it is that taxpayers will register (deregister) for VAT purposes, indicating that the magnitude of changes in the VAT rate do have an impact on VAT registration decisions and therefore on tax compliance more generally.

Not only does the study add to the limited knowledge available on registration decisions of small businesses, but also gives valuable guidance to policymakers in terms of determining the VAT rate for the country.

Not only does the study add to the limited knowledge available on registration decisions of small businesses, but it also gives valuable guidance to policymakers in terms of determining the VAT rate for the country.

Qualitative researchers have been criticised for not justifying sample size decisions in their research. This short paper addresses the issue of which sample sizes are appropriate and valid within different approaches to qualitative research.

The sparse literature on sample sizes in qualitative research is reviewed and discussed. This examination is informed by the personal experience of the author in terms of assessing, as an editor, reviewer comments as they relate to sample size in qualitative research. Also, the discussion is informed by the author’s own experience of undertaking commercial and academic qualitative research over the last 31 years.

In qualitative research, the determination of sample size is contextual and partially dependent upon the scientific paradigm under which investigation is taking place. For example, qualitative research which is oriented towards positivism, will require larger samples than in-depth qualitative research does, so that a representative picture of the whole population under review can be gained. Nonetheless, the paper also concludes that sample sizes involving one single case can be highly informative and meaningful as demonstrated in examples from management and medical research. Unique examples of research using a single sample or case but involving new areas or findings that are potentially highly relevant, can be worthy of publication. Theoretical saturation can also be useful as a guide in designing qualitative research, with practical research illustrating that samples of 12 may be cases where data saturation occurs among a relatively homogeneous population.

Sample sizes as low as one can be justified. Researchers and reviewers may find the discussion in this paper to be a useful guide to determining and critiquing sample size in qualitative research.

Sample size in qualitative research is always mentioned by reviewers of qualitative papers but discussion tends to be simplistic and relatively uninformed. The current paper draws attention to how sample sizes, at both ends of the size continuum, can be justified by researchers. This will also aid reviewers in their making of comments about the appropriateness of sample sizes in qualitative research.

A survey of young microfirms was conducted to investigate their growth intentions. The findings confirm the distinct profiles of four types of firms categorized on the basis of current and future employment: Lifestyler, Entrepreneur, Manager, and Mover. They differ in terms of the owner's perceptions of the desirability and practicality of growing their firm, and with respect to the moderating variables of industry affiliation, business location, and investment level. Research issues and service implications for business support agencies are identified.

Despite being a viable source of funds, African sovereign bond markets are relatively underexplored. The empirical literature fails to consider the impact of exclusively macroeconomic factors and the volatile contexts in which African markets operate. The purpose of this paper is to fill the vacuum by proposing a context-sensitive theoretical framework. The study targets, specifically, macroeconomic factors and assesses the extent to which they affect bond market development.

Using panel data on sovereign bond markets from 26 African economies, the study extends previous methodologies used in similar studies by accounting for downside risk in a generalized method of moments (GMM) framework and employing tighter robustness measures.

This study finds that inflation, domestic debt, external debt, GDP at PPP, fiscal balance and exports are important macroeconomic drivers of sovereign bond market development in African emerging economies.

While GMM estimation is beneficial in the presence of endogeneity between the dependent variables that are instrumented with lagged independent variables, it guarantees consistency but, not unbiased estimations.

Market-oriented government funding with well-defined debt management strategies must be implemented to support the development of sovereign bond markets. External debt must be set at a sustainable level, and government should be dedicated to the confirmation of this. Furthermore, inflation rates must be kept low and stable.

If policymakers are to take this study seriously, bond markets may begin to be viable sources of funds for African emerging economies.

This study introduces a methodology for measuring bond market development that considers the systemic volatility in emerging markets and proposes a theoretical framework for African emerging economies. In addition, the authors identify a new macroeconomic determinant of bond market development in the region.

Successful firms are important sources of productivity, employment and economic stability in societies. As the micro-level origins of firm innovations are increasingly attracting attention amongst innovation scholars, the purpose of this study is to investigate the role of managerial innovativeness, i.e. small firm managers' innovative behaviour for firm performance. Specifically, the present study investigates managerial innovativeness as a predictor of small firms' product innovativeness and market performance.

This research model suggests that managerial innovativeness is positively linked to firms' market performance and that product innovativeness partially mediates the relationship between managerial innovativeness and market performance. The model was tested using partial least squares structural equation modelling (PLS-SEM) with a dataset (N = 93) collected from small logistics firms in South-Eastern Finland.

The findings support the authors' hypotheses and show that managerial innovativeness had a direct effect on firms' product innovativeness and market performance. The authors also found that firms' product innovativeness mediated the relationship between managerial innovativeness and firms' market performance.

This is one of the few studies that shed light on and show that managerial innovativeness is significantly and positively related with small firms' product innovativeness and market performance, whereas earlier research tended to focus on managers' personalities, traits, characteristics or managerial actions, leaving managerial innovativeness unexplored.