As the social and environmental roles of companies have been emphasized by various stakeholders, the concepts of CSR (corporate social responsibility), ESG (environmental, social, governance), and corporate citizenship have received a great deal of attention in academia and industry. To understand and distinguish corporate responsibility approaches in the literature, this study employs text mining techniques to comprehensively analyze the summary information of 1235 articles (i.e., title, abstract, and keywords) on CSR, ESG, and corporate citizenship. First, frequently occurring terms in text datasets related to CSR, ESG, and corporate citizenship are analyzed to extract conceptual commonalities and differences. Then, correlated topic modeling is applied to the collected text datasets to identify underlying topics widely discussed in CSR, ESG, and corporate citizenship related studies. The results of this study show that corporate citizenship is not only a high-level concept that encompasses ESG and CSR, but also a broad concept with missions that are associated with various societal areas. The findings from this study also reveal that employees, as the principal agents of corporate citizenship practice, are more critical than other stakeholders of corporate citizenship practice.

One of the most challenging problems in last mile logistics (LML) has been the strategic delivery due to various market risks and opportunities. This paper provides a systematic review of LML-related studies to find current issues and future opportunities for the LML service industry. To that end, 169 works were selected as target studies for in-depth analysis of recent LML advances. First, text mining analysis was performed to effectively understand the underlying LML themes in the target studies. Then, the novel definition and typology of LML delivery services were suggested. Finally, this paper proposed the next generation of LML research through advanced delivery technique-based LML services, environmentally sustainable LML systems, improvement of LML operations in real industries, effective management of uncertainties in LML, and LML delivery services for decentralized manufacturing services. We believe that this systematic literature review can serve as a useful tool for LML decision makers and stakeholders.