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This paper aims to explore the determinants of maternal healthcare services (MHS) utilisation in Ghana.

In this paper, logit and negative binomial regressions were used to model data from a recent nationally representative survey (the 2017 Ghana Maternal Health Survey). The analysis is observational, without causal implications. The authors measure MHS utilisation by four indicators: antenatal care (ANC) use, the number of ANC clinic visits, choice of health facility delivery and postnatal care (PNC) use.

Age, parity, education, marital status, wealth, residence and health facilities concentration proved to be significant predictors of MHS use in Ghana. Specifically, older, married and educated women; women of lower parity; those living in urban areas and women from wealthier households were more likely to use MHS. The authors also find that health facilities and personnel predicted higher MHS use. Lastly, women with frequent stillbirths had higher MHS use.

The results for health facilities and personnel suggest that increasing the supply of health centres and workers may enhance MHS use. The authors conclude that women of lower socio-economic status have worse MHS use, meaning empowering such women might increase such women's MHS use.

Existing data suggest falling MHS use in Ghana. Yet, the extant works are based on relatively old data or lack external validity (besides using limited MHS indicators). This paper provides recent and generalisable evidence for public health policies. Additionally, this paper tests the statistical significance of some supply-side factors that have yet to be emphasised in the literature.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2022-0199.

The purpose of this paper is to determine the socio‐economic factors affecting meat sales outlets, as preferred by the consumers of the city of Tokat, Turkey. This paper underlines the social and economic factors leading to healthy meat outlet preferences and focuses the attention of producers, policy makers, sellers and consumers on the issue, which will lead to the creation of a healthier and more aware society.

Within the research, the sample size, preferred as 263, will deviate at a maximum of 6 percent from the main population at 95 percent importance level. The inquiries are proportionally dispersed between the quarters, considering the population, in accordance with the records of 2006. Surveys were carried out by way of direct interviews by the researchers. In the survey, particular attention was paid to ensure that the interviewee was the decision maker in regards to the purchasing of foods. Meat outlets (market places, butchers and hypermarkets) were chosen as the dependent variables of the model. The independent variables were the sex, age and educational background of the consumers, household size, place of residence, the status of the mother, income, price difference, quality difference, hygiene, freshness and the seller's image. The multinomial logit model was used to measure the effect of the independent variables on the dependent variable.

According to the results of the research; such factors as age, household size, place of residence, status of the mother, income, price difference, quality difference, hygiene, freshness and the seller's image are deemed to be the variables affecting the consumers' meat outlet preferences.

Studies of this nature will be particularly beneficial for policy makers, producers and consumers in the sector and the researchers in the field. By extension, conducting such studies aimed at determining consumer habits from the perspective of Turkey, will ultimately help form consumer consciousness, protect consumer health and raise the sellers' income. Defining aptitude of consumers' demands, searching reasons for buying choices will be helpful for the food safety, hygiene and quality standards to become a matter of importance.

This paper underlines the social and economic factors leading to healthy meat outlet preferences and focuses the attention of producers, policy makers, sellers and consumers on the issue, which will lead to the creation of a healthier and more aware society.

The purpose of this paper is to explain the determinant factors of switching behavior in the Thai cellular market before the Mobile Number Portability (MNP) policy is implemented.

A binary logit model and individual survey data from the National Telecommunications Commission 2009 are used to estimate the intention of mobile phone consumers to switch.

The results show that subscriber characteristics, including age, government officer, self‐employed, internet use, central region, and southern region, are significant in explaining the switching behavior of Thai mobile subscribers. They also indicate that the mobile operators' customers are confronted with different switching costs. The subscribers of the largest mobile operator have the highest switching costs. This study also shows that the largest mobile operators will gain more switching subscribers than smaller operators. The implementation of MNP will help to lower the switching costs of smaller mobile operators rather than of larger operators, as the subscribers of smaller operators are more likely to switch and move to larger mobile operators, as the larger operators provide better quality network coverage. The study shows that the expected impact of implementing MNP without national mobile roaming regulations would be worse for smaller mobile operators. The smaller operators need to compete on both price and quality improvement. In the short run, it would not be possible for the smaller operators to compete with the larger operators due to the inequality in the quality of network coverage.

The result is useful to developing countries considering implementing MNP regulation.

The study assesses the significance of environmental uncertainty and its effects on fishing strategies of small-scale fishermen in Ende, Flores, Indonesia. Periodic environmental cycles such as the moon phase can have important effects on fishing strategies by regulating the behavior of stocks and tides. Traditional lunar calendars are used by subsistence fishermen to decide when and where to go fishing. Environmental uncertainty, specifically unprecedented changes in oceanographic and atmospheric conditions, is threatening the predictability of traditional systems of ecological knowledge.

Methods included ethnographic and observational techniques. Interviews (n = 58) and surveys (n = 132) are qualitatively and quantitatively analyzed. A combination of standard statistical tests, multilevel models, and cluster analysis is applied to long-term repeated observations of fishing events (n = 2,633).

Endenese fishermen emphasized the importance of the traditional lunar calendar to allocate their effort in interviews and surveys. This belief does not coincide with observed behavior. Contrary to expectations from the traditional calendar, the lowest probability of fishing happens in the intermediate phases, with fishing also occurring during the full moon. Differences between individuals play an important role in explaining variability in returns. Finally, based on the consideration of variability, three different fishing strategies are identified that suggest an effect of environmental uncertainty in effort regulation.

The paper underlines the importance of studies of variability to identify behavioral flexibility and adaptation. Results emphasize the value of considering individual traits in the analysis of subsistence practices.

The central aim of this paper is to identify some of the motives behind the type of growth strategy followed by Spanish hotel enterprises in recent years.

This study was elaborated from secondary data corresponding to news published on the web page of a digital newspaper specialising in tourism – HostelTur. The information obtained in this way was completed and contrasted using other sources like the BARATZ database (where all the news items published in the economic press since 1981 are collected), and the web pages of hotel enterprises, since many of them publish news about their main actions along with the most relevant events that take place within these organizations.

From a sample of 444 observations, the results suggest that initial profitability, size, age and indebtedness level of firms are some of the factors determining growth strategies in this sector.

The paper throws light on some of the reasons behind the behaviour of Spanish hotel enterprises as far as growth is concerned. The innovative approach of this study, which focuses on the causes rather than on the consequences of certain corporate growth strategies, is its main contribution.

Much research has focused on the police response to domestic violence; however, relatively little research has considered performance differences of various types of police officers. Although there has been widespread adoption of community policing by police departments across the country, it is not conclusive as to whether units with a specific community policing philosophy perform better than traditional units when handling domestic violence calls. The current study addresses this issue by analyzing the factors associated with victim participation; specifically, do officers and detectives operating under a specific community policing mandate produce higher rates of victim participation? Bivariate and multivariate analyses indicate that victim participation rates did not differ by a community policing orientation; rather, situational factors exert the strongest effect on victim participation.

This paper aims to focus on the human side of inbound open innovation by analyzing the effects that the adoption of different knowledge search strategies for innovation has on new recruitment needs.

Building on several theoretical perspectives, the study proposes three hypotheses regarding the relationship between openness and the need to recruit people with high technical and social skills. Using a pooled panel data from the Uruguayan Innovation Survey between 2004 and 2012, the authors identify open strategies followed by the firm.

The estimation results using pooled panel data confirm that the adoption of inbound open search strategies for innovation demands the recruitment of new employees with higher technical and social skills. Technical skills are more likely to be demanded than social skills. The effects observed are moderated by the intensity in the use of knowledge and information sources (KISs).

This paper revisits the analysis of specific knowledge search strategies at the firm level. In doing so, the study looks for the effects of specific strategies combining different knowledge sources and considers different levels of use of external KISs, from narrow to wide. While other studies have analyzed the human factor as a determinant of the success of openness for innovation, this paper re-examines the direction of this relationship. Finally, the study contributes to the evidence from a Latin American country, where these topics have received less attention.

The main aim of the study is to identify some critical microeconomic determinants of financial distress and to design a parsimonious distress prediction model for an emerging economy like India. In doing so, the authors also attempt to compare the forecasting accuracy of alternative distress prediction techniques.

In this study, the authors use two alternatives accounting information-based definitions of financial distress to construct a measure of financial distress. The authors then use the binomial logit model and two other popular machine learning–based models, namely artificial neural network and support vector machine, to compare the distress prediction accuracy rate of these alternative techniques for the Indian corporate sector.

The study’s empirical results suggest that five financial ratios, namely return on capital employed, cash flows to total liability, asset turnover ratio, fixed assets to total assets, debt to equity ratio and a measure of firm size (log total assets), play a highly significant role in distress prediction. The study’s findings suggest that machine learning-based models, namely support vector machine (SVM) and artificial neural network (ANN), are superior in terms of their prediction accuracy compared to the simple binomial logit model. Results also suggest that one-year-ahead forecasts are relatively better than the two-year-ahead forecasts.

The findings of the study have some important practical implications for creditors, policymakers, regulators and other stakeholders. First, rather than monitoring and collecting information on a list of predictor variables, only six most important accounting ratios may be monitored to track the transition of a healthy firm into financial distress. Second, our six-factor model can be used to devise a sound early warning system for corporate financial distress. Three, machine learning–based distress prediction models have prediction accuracy superiority over the commonly used time series model in the available literature for distress prediction involving a binary dependent variable.

This study is one of the first comprehensive attempts to investigate and design a parsimonious distress prediction model for the emerging Indian economy which is currently facing high levels of corporate financial distress. Unlike the previous studies, the authors use two different accounting information-based measures of financial distress in order to identify an effective way of measuring financial distress. Some of the determinants of financial distress identified in this study are different from the popular distress prediction models used in the literature. Our distress prediction model can be useful for the other emerging markets for distress prediction.

While there has been several job satisfaction studies, very few of them are about the university teachers or academics in general. The present work examines not only how satisfied UK academics are with their primary tasks of teaching and research, but also their satisfaction with their pay. Using a binomial logit analysis on a survey data, the study found a strong positive relationship between pay satisfaction and gender, indicating that women academics are more satisfied than the men counterparts. The study also found that research and teaching satisfaction are negatively affected with increasing age and length of service in higher education respectively. Unsurprisingly, research and pay satisfaction are positively associated with rank. It was found that the engineering staff members are dissatisfied with their research but more significantly, their teaching. The implications of these findings are explored.