Problem Statement: The use of self-report questionnaires may lead to biases such as careless responses that distort the research outcomes. Early detection of careless responses in self-report questionnaires may reduce error, but little guidance exists in the literature regarding techniques for detecting such careless or random responses in self-report questionnaires. Purpose of the Study:The purpose of this study was to examine whether the respondent"s goodness-of-fit test score (RGF) can be used to indicate careless responses in completing self-report questionnaires. It is hypothesized that there is a significant difference of RGF between careless responses and true responses and that RGF of careless responses is higher than RGF for true responses.Method: An experimental research design that made use of a self-reported questionnaire was conducted with 205 respondents divided into two groups. The first group responded truthfully to the questionnaire while the second group responded carelessly to the questionnaire. The validity and reliability of the questionnaire had been tested. One hundred and eighty five respondents were selected as the group of true responses, while another 20 respondents comprised the group of careless responses. T-test of independent sample was used to evaluate the different RGF among true responses and careless responses. 308Ronny Kountur frequency distribution of true responses tends to be normally distributed while the existence of careless responses creates a skewed distribution to the right. The RGF of careless responses is higher than the RGF of true responses.Conclusion and Recommendations: RGF may be used as an indicator of respondent"s careless responses in self-report questionnaires in which more accurate data are expected. Social science research that makes use of self-report questionnaire in measuring affective domain may compute RGF to determine whether careless responses exist.

The primary purpose of this study is to study the moderating effect of entrepreneurial leadership and competitive advantage in the relationship between the business model innovation and the performance of the start-up business. We hypothesized that business model innovation has a significant association with the performance of the start-up, and entrepreneurial leadership or competitive advantage connects substantially to the business model innovation and start-up. Fifty-one respondents participate in this study. The partial least square statistical technique is used to analyse the data, which is appropriate for parametric analysis for such a sample size. The analysis shows a significant relationship between business model innovation and start-up performance. Also, there are significant relationships of entrepreneurial leadership and competitive advantage to business model innovation. However, it shows no direct relationship between entrepreneurial leadership and start-up; the association is not direct but indirect. The null hypothesis that there is no direct association between competitive advantage and start-up performance is rejected. There is a negative association between competitive advantage and start-up. Both entrepreneurial leadership and competitive advantage improve the relationship between business model innovation and start-up. However, they must be interpreted with caution

This study aims to find the dimensions of financial indicators where both ratio and non-ratio indicators are accommodated. It is expected that the new dimensions of financial indicators be found. Both Exploratory and Confirmatory Factor Analysis is used in analyzing the data. Data are taken from 120 companies listed in Indonesian Stock Exchange (IDX). Twenty financial indicators from the financial reports of each company are identified. While it has been a common practice to use ratio in indicating financial performance, it is not common to use an individual value from financial statements as financial indicators. This study shows that financial indicators can be grouped into four dimensions; they are Operational Performance, Asset-Income Performance, Owner Returns Performance and Leverage Performance. All of the non-ratio indicators that are expressed in the amount are grouped in the Asset-Income Performance dimension. New dimensions of financial performance indicators that do not commonly exist in this study, they are Asset-Income, and Leverage Performance. With the new dimension, non-financial performances such as customer satisfaction, corporate social responsibility, reputation, nepotism, and professionalism may be detected.

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A model for estimating the likelihood value of residual risk (Y) is introduced. The model consists of three independent variables: the likelihood value of risk before risk treatment (X1), the quality of risk treatment (X2), and the appropriateness of risk treatment (X3). An experimental research design with a multiple linear regression analysis was used in the estimation. All independent variables, the likelihood value of risk before treatment, the quality of risk treatment, and the appropriateness of risk treatment, can be significantly used to estimate the likelihood value of residual risk. Since no model of estimating residual risk of likelihood had been introduced yet, the findings of this study provide significant contribution to firms or organizations that need to assess the likelihood value of residual risks.