Catarina Delgado

Abstract

Abstract
Purpose This study aims to address the topic of ethics, responsibility and sustainability (ERS) orientation of students enrolled in schools of economics and management master's degrees. It examines the effect of educational background and gender on Portuguese students' orientation towards ERS, as well as the extent to which there is a relation between the scientific area of the master degree in which the student is enrolled and his/her ERS orientation. Design/methodology/approach The authors used a sample of 201 students from several master degrees offered by the School of Economics and Management of a large public Portuguese university and analysed their ERS orientation using a survey by questionnaire. Findings Findings suggest that there are differences in orientation across gender, with female students valuing ERS more than their male counterparts. Educational background has minimal effects on the responses. It was also found some sort of selection effect in terms of the scientific area of the master degree and ERS orientation. Originality/value This study contributes to the literature by analysing the issue of whether students with an educational background in economics and management present different ERS orientation than their counterparts, as well as by examining whether there is some sort of self-selection into the study of disciplines in which ERS orientation is likely to be a week. As far as the authors are aware, this is the first study analysing this type of issue regarding ERS.

Abstract

Abstract
This study examines the association between different types of dependency on resources and/or pressures from the international community and the reporting practices on the fight against corruption of companies in an emerging country setting, that of Turkey. More specifically, we focus on the influence of multinationality, cross-listing, and membership of the United Nations Global Compact on this type of reporting. We use ordinal regression analysis to explore the association between the three factors mentioned above and anti-corruption reporting for a sample of Turkish firms on the Borsa Istanbul 100 index, while controlling for some other factors likely to influence anti-corruption reporting. Findings show a low level of reporting. They also suggest that companies with their shares cross-listed and companies which are members of the Uited Nations Global Compact do present higher levels of anti-corruption reporting than their counterparts. © 2019 Elsevier Ltd

Abstract
Purpose: Based on the data obtained from a questionnaire of 595 people, the authors explore the relative importance of consumers, checking whether socioeconomic variables influence their centrality, detecting the communities within the network to which they belong, identifying consumption patterns and checking whether there is any relationship between co-marketing and consumer choices. Design/methodology/approach: A multilayer network is created from data collected through a consumer survey to identify customers’ choices in seven different markets. The authors focus the analysis on a smaller kinship and cohabitation network and apply the LART network community detection algorithm. To verify the association between consumers’ centrality and variables related to their respective socioeconomic profile, the authors develop an econometric model to measure their impact on consumer’s degree centrality. Findings: Based on 595 responses analysing individual consumers, the authors find out which consumers invest and which variables influence consumers’ centrality. Using a smaller sample of 70 consumers for whom they know kinship and cohabitation relationships, the authors detect communities with the same consumption patterns and verify that this may be an adequate way to establish co-marketing strategies. Originality/value: Network analysis has become a widely used technique in the extraction of knowledge on consumers. This paper’s main (and novel) contribution lies in providing a greater understanding on how multilayer networks represent hidden databases with potential knowledge to be considered in business decisions. Centrality and community detection are crucial measures in network science which enable customers with the highest potential value to be identified in a network. Customers are increasingly seen as multidimensional, considering their preferences in various markets. © 2019, Emerald Publishing Limited.