Search results

This paper discusses data-collection strategies that use digitized historical newspaper archives to study social conflicts and social movements from a global and historical perspective focusing on nationalist movements. I present an analysis of State-Seeking Nationalist Movements (SSNMs) dataset I, which includes news articles reporting on state-seeking activities throughout the world from 1804 to 2013 using the New York Times and the Guardian/Observer. In discussing this new source of data and its relative value, I explain the various benefits and challenges involved with using digitized historical newspaper archives for world-historical analysis of social movements. I also introduce strategies that can be used to detect and minimize some potential sources of bias. I demonstrate the utility of the strategies introduced in this paper by assessing the reliability of the SSNM dataset I and by comparing it to alternative datasets. The analysis presented in the paper also compares the labor-intensive manual data-coding strategies to automated approaches. In doing so, it explains why labor-intensive manual coding strategies will continue to be an invaluable tool for world-historical sociologists in a world of big data.

This study aims to contribute to the literature on board gender diversity by soliciting university students' views on several perceptions raised by academics concerning the suitability of women to serve on corporate boards. In particular, if the opinions of male students differ from those of female students, this showing any gender bias.

The study is part of a much more comprehensive investigation into board gender diversity. It adopts a questionnaire approach, with this paper focussing on twelve research statements. Two hundred and ninety-six university students completed the questionnaires at a public university in the Czech Republic during March–April 2023. A pilot questionnaire was conducted in February 2023, resulting in minor changes being made. The data is analysed using SPSS and MedCalc® statistical software.

Whilst, in some respects, it supports the literature in relation to the observations highlighted in the research statements concerning female traits/characteristics, there is unmistakable evidence of gender bias in the respondents' opinions regarding the qualities women can bring to corporate boards. Overall, this research shows a negative bias by male respondents towards the positive attributes females can bring to the boardroom. This bias may influence the selection of female directors in the future. This research suggests that the apparent discrimination against women is not just because they are female but from a perceived mismatch between inferred female characteristics and male stereotype leadership requirements. There is, however, no gender bias with respect to students' leadership aspirations.

The findings of this research should help with policy-making decisions concerning the selection of future corporate board directors and help break down any negative gender selection bias. The paper adds to the discussion and debate about ethical issues related to business and broader society concerning gender diversity in senior management roles. It also adds to the political debate on the issue of legislative gender initiatives.

The research respondents' perceptions may well influence the decision-making process for the selection of future corporate directors. Whilst these current perceptions may, and invariably will, change over time, it is important to identify them at an early stage in the respondents' careers. This research gives a better understanding of the perceived qualities that women bring to corporate boards from an inexperienced perspective.

The Million Farmers School (MFS) program—also known as Kisan Pathshala was launched to impart training to the farmers by the government of the state of Uttar Pradesh (India) in December 2017. This study estimates the impact of training on agricultural knowledge of the farmers.

The study is based on household survey conducted in Uttar Pradesh (UP), India, during March–May 2019. The authors employed matching methods, the two-stage least square (2SLS)-residual and endogenous switching regression approaches to control for selection bias and endogeneity.

The results suggest that knowledge outcomes are significantly better among participants vis-à-vis non-participants. The results are robust to different model specifications. Further, the benefits are observed across different regions and social groups.

The MFS program can go a long way in enhancing agricultural know-how and the farmers' economic well-being, bringing a transformative change in the agricultural landscape of UP.

This study is based on a field survey data and analyzes various aspects of the program's impact, design and implementation, and offers implementation advice for greater efficacy in future.

The aim of this paper is to evaluate whether the acceptability of different types of business- and individual-level non-compliance has different impacts on the likelihood of participation in undeclared work.

To evaluate this, data is reported on the EU27 and the UK from the special Eurobarometer survey no. 498, using a novel statistical methodology that deals with two potential sources of bias: sample selection error (avoidance to answer to the question about participation to undeclared work) and misclassification in the response variable (false statements about engagement in undeclared work).

This reveals the association between tax morale and participation in undeclared work. It shows that citizens find far more unacceptable undeclared work conducted by firms than individuals, but both are significantly associated with participation in undeclared work although the greatest effect is clearly exerted by individual-level tax morale.

This paper uses a methodology that accounts for the potential bias related to sample selection error and misclassification in the response variable of participation in undeclared work and sheds light on different components of tax morale.

This paper aims to test the impact of remittances receipt on agricultural productivity. The paper empirically assesses whether heterogeneity in economic activity of farming households affects the effects of remittances on productivity of tradable and nontradable crop farming households in Ghana.

The authors employ propensity score matching (PSM) methods to address potential endogeneity issues that could arise from the estimation due to selection bias. This paper uses the seventh round of Ghana living standard survey dataset for Ghana.

The authors find that, the involvement of farming households in other economic activities alters the impact of remittances on crop yield. This differential impact also varies according whether the crop is tradeable or not.

Policy can reduce the cost of sending remittances and include financial literacy modules in the farmer training modules to increase farmers' knowledge on investment of remittance in agricultural production.

The authors distinguish the paper from others by controlling for crop types (particularly tradeable or otherwise and gestation period), farming of a second or more crops and engagement of smallholder farmers in nonfarm economic activities.

This article analyzes the hypothesis that analysts issue higher long-term earnings growth (LTG) forecasts following a market-wide investor sentiment.

This study analyzed 193 publicly traded Brazilian firms listed on B3 (Brasil, Bolsa, Balcão), totaling 2,291 observations. To address the potential selection bias resulting from analysts' preference for more liquid firms, this study used the Heckman model in the analysis with samples with only one analyst and the entire sample. The study also applied other robustness tests to ensure the reliability of the findings.

The results suggest that market-wide investor sentiment influences LTG when the firm's stocks are difficult to value. Market optimism did not reflect five-year profit growth after the forecast issue, suggesting lower forecast accuracy during high investor sentiment values.

Volatile-earnings firms have relevant implications in LTG forecasts during bullish moments. According to the study’s evidence, investors' decisions and policymakers' and regulators' rules should consider analysts' expertise as independent information when considering LTG as input for valuation models, even under market optimism.

This paper contributes to the literature on the influence of investor sentiment on analysts' forecasts by incorporating two crucial elements in the discussion: the scenario free from herding behavior, as usually only one analyst issues LGT forecast for Brazilian firms, and the analysis of research hypotheses incorporates the difficulty of pricing a firm given the uncertainty of its earnings as an explanation to bullish forecast.

Given the importance of growth-oriented entrepreneurship in the context of economic development and the need to understand how rural communities can be developed, the purpose of this research paper is to determine how the drivers of growth expectations differ between urban and rural settings.

The methodology is threefold: firstly, a descriptive analysis with non-parametric testing is conducted; then pooled regression model is used to analyse the predictors of growth expectations in both contexts, and finally, coarsened exact matching is used to identify possible self-selection bias.

In contrast to mainstream entrepreneurship theory, it is found that entrepreneurs’ intrinsic knowledge, skills and abilities are not significant in the rural-specific model. The only exception is entrepreneurs’ educational level, the importance of which is emphasised as a pivotal factor in increasing high-growth ventures in rural communities. Additionally, when self-selection is eliminated, rurality worsens growth intentions.

There is evidence that some growth-oriented entrepreneurs self-select into rural communities. Because the high-growth entrepreneurial dynamics in rural areas are unique, public policies should target purpose-driven entrepreneurial education. This includes encouraging “lifestyle entrepreneurship” (e.g. retirees returning to rural areas to become entrepreneurs), preventing entrepreneurial brain drain in rural areas and attracting highly educated urban entrepreneurs to exploit opportunities in rural areas.

This research attempts to contribute to the ongoing debate regarding the factors that drive high-growth entrepreneurs in rural areas by analysing rural entrepreneurs in the high-growth context of a developing economy. The focus is on Chile – a country that is rarely investigated compared to the USA or Europe – to extend the literature on high-growth ventures and entrepreneurial ecosystems.

This study aims to examine the impact of consumer risk appetite, biases (specifically negative recency bias), and the importance of reviews in enhancing information quality. By analyzing these variables, the authors gain insights into their role in enriching the overall information spectrum available to consumers. The findings contribute to a better understanding of how risk appetite, biases and consumer reviews shape the quality of information.

The questionnaire assessed the relationship between dependent and independent variables by asking participants to rate their experiences in relevant scenarios. Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

The efficiency of reviews and ratings is greatly influenced by consumer risk appetite. Businesses should focus on clients who are willing to take risks and balance positive and negative feedback. It is essential to comprehend how customers understand reviews. Credibility is increased by taking biases into account and encouraging unbiased criticism. Promoting thorough reviews strengthens influence. Monitoring and making use of these elements improve online reputation and commercial success.

The research has limitations due to the simplicity of the attributes taken into account and the requirement for a larger sample size. Overcoming barriers to promote consistent client feedback is essential, and tailored emails can help with assessment generation. Increased customer participation in writing evaluations can be achieved by removing obstacles and highlighting the advantages of participation.

Businesses and buyers rely on this “organically” generated content as the basis of their promotional strategy and buying decisions. Most of the research is related to consumer reviews, their behavior and the importance of social validation. However, some critical aspects related to this need further investigation.

The adoption of solar energy by households is an important avenue of protecting the environment and enabling energy access in rural areas, especially in developing countries like Uganda, where energy access is low. Therefore, this study aims to investigate the factors that influence the households’ willingness to adopt solar photovoltaic (PV) energy and how soon the households are willing to adopt solar PV energy for business use in Uganda.

Heckman’s two-step selection model was used to determine the willingness and urgency of adopting solar PV energy for business use in selected districts in Eastern Uganda. The respondents were selected purposively at the household level at a given point in time.

Results show that sex, household head estimated income, mode of acquisition and repayment terms of solar technology positively influence both willingness and urgency to adopt solar energy for business use in households. However, financial disclosure only influences willingness to adopt solar. Then, age and energy need only significantly influence how soon the household is willing to adopt solar PV energy for business use.

This study’s findings essentially apply to the individual factors that determine the willingness and urgency to adopt solar PV energy for business use by households. Hence, further research is needed to understand the external and industrial factors which could strengthen the predictive potential of the elements in this study.

This study underscores the need for regulatory enforcement on the supply and usage of quality, reliable and affordable solar equipment which are suitable for business use. Also, the need to promote and finance the usage of solar PV as a green energy source for household businesses has been emphasized.

The study simultaneously examines the willingness and urgency to adopt solar PV energy for household business purposes using Heckman’s two-step selection model. This has hitherto remained unknown empirically.

This paper aims to examine whether the cooperation between female chief financial officers (CFO) and the proportion of female directors would impact investment efficiency. The investigation is grounded in the increasing number of female top managers globally and the notion that female tends to cooperate more with other female than with male.

This study uses publicly listed firms in Bursa Malaysia from 2016 to 2020, which yielded a sample of 2,022 firm-year observations. The authors used multivariate ordinary least square regression to test the relationship, and to correct for the selection bias, the Heckman selection and PSM test were used.

The authors find a positive relationship between female CFOs and investment efficiency. A higher proportion of female directors accentuates this result. The findings support the homophily argument that similar characteristics (gender) promote cooperation. This shows that cooperation between female CFOs and directors improves investment efficiency. The results suggest that the improvement in investment efficiency could relate to higher managerial discretion for female CFOs and their ability to collaborate with female directors. These results are robust to a series of additional endogeneity tests. The findings have important implications for policymakers and firms to encourage more appointments of females in top management positions.

By highlighting the cooperation between female CFOs and female directors, this study contributes to the understanding that cooperation among females improves investment efficiency.