“…For example, Wang, Tong, Takeuchi and George [4] identified increasingly non-US-based studies as one of four major trends in CSR studies. A literature review of CSR studies also shows an increasing number of CSR studies focusing on emerging economies such as India [55][56][57] and Saudi Arabia [58,59].…”
Corporate social responsibility (CSR) is an essential business practice in industry and a popular topic in academic research. Several studies have attempted to understand topics or categories in CSR contexts and some have used qualitative techniques to analyze data from traditional communication channels such as corporate reports, newspapers, and websites. This study adopts computational content analysis for understanding themes or topics from CSR-related conversations in the Twitter-sphere, the largest microblogging social media platform. Specifically, a probabilistic topic modeling-based computational text analysis framework is introduced to answer three questions: (1) What CSR-related topics are being communicated in the Twitter-sphere and what are the prevalent topics or themes in CSR conversation? (topic prevalence); (2) How are those topics interrelated? (topic correlation); (3) How have those topics changed over time? (topic evolution). The topic modeling results are discussed, and the direction for future research is presented.
“…For example, Wang, Tong, Takeuchi and George [4] identified increasingly non-US-based studies as one of four major trends in CSR studies. A literature review of CSR studies also shows an increasing number of CSR studies focusing on emerging economies such as India [55][56][57] and Saudi Arabia [58,59].…”
Corporate social responsibility (CSR) is an essential business practice in industry and a popular topic in academic research. Several studies have attempted to understand topics or categories in CSR contexts and some have used qualitative techniques to analyze data from traditional communication channels such as corporate reports, newspapers, and websites. This study adopts computational content analysis for understanding themes or topics from CSR-related conversations in the Twitter-sphere, the largest microblogging social media platform. Specifically, a probabilistic topic modeling-based computational text analysis framework is introduced to answer three questions: (1) What CSR-related topics are being communicated in the Twitter-sphere and what are the prevalent topics or themes in CSR conversation? (topic prevalence); (2) How are those topics interrelated? (topic correlation); (3) How have those topics changed over time? (topic evolution). The topic modeling results are discussed, and the direction for future research is presented.
“…Many of those studies focus on business students. Deploying similar methods, several studies have analyzed such future managers' attitudes toward or perception of the responsibilities involved in CSR in places such as the US (Aspen Institute, 2002Institute, , 2008Kolodinsky et al, 2010;Ng & Burke, 2010;Wong et al, 2010), Europe Lämsa et al, 2008;Matten & Moon, 2004;Zopiatis & Krambia-Kapardis, 2008) China (e.g., Wang & Juslin, 2011) and Asia (Murphy et al, 2016). No such studies involving Ibero-American students have been conducted, however.…”
“…Secondly, gender (GENDER) was also measured with a dummy variable, taking 1 for men and 0 for women. Many articles focused on student attitudes and perceptions on CSR and/or stakeholders have considered gender as a relevant explanatory variable (e.g., [80][81][82]). Although different effects have been found, most studies conclude that women tend to exhibit greater sensitivity to CSR [83], have stronger ethical orientation [80], and attach more importance to environmental issues [81].…”
Nowadays, students are more aware of the impact of companies on their stakeholders and the need for properly handling their expectations to operationalize corporate social responsibility. Nevertheless, little is known about how certain individual traits may relate to their stance on the issue. This exploratory research contributes to stakeholder theory by analysing the effect of the individual’s decision-making process, including the consideration of their social preferences, on their orientation toward stakeholder management. Here, we draw upon a theoretical model for resource-allocation decision-making consisting of reciprocal and non-reciprocal components. Our data, from undergraduate students enrolled in different degrees, were collected through a questionnaire and two social within-subject experiments (ultimatum and dictator games). Thus, our results show that the presence of a reciprocal component when decisions are made is positively linked to an instrumental orientation toward stakeholders. In addition, a greater non-reciprocal component in the decision-making process corresponds to a more normative orientation.
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