Multi-Channel and Omni-Channel Retailing in the Scientific Literature: A Text Mining Approach

Electronic commerce appeared as a new way of managing businesses in the digital era. However, it has also been accelerated by recent pandemic situation. Retailers had to find strategies reaching customers online environment. Thus, concepts such multi-channel and omni-channel retailing have gained attention both retailers researchers this field. This paper aims at using text-mining approach order reveal focus on theme period that precedes covers COVID-19 pandemic. The research methodology follows five steps are necessary obtain relevant collection documents will further provide content be analyzed. These refer to: (1) Creating database for analysis purposes; (2) identifying geographic areas separating collection’s documents; (3) framing thematic dictionary descriptors; (4) exploring text mining approach; (5) correspondence analysis. discussion main findings is constructed starting with temporal distribution design descriptors. Then, provides information frequency descriptors reveals clusters along link All them presented separately regions. Finally, versus years proximity maps preferred topics less approached themes. Among findings, one can highlight: greatest contributor terms related interest United States; higher number connections (and stronger) among America compared other two regions; some categories specific particular year, which means there different themes under lens depending period; most frequently used included following from dictionary: Online retail environment Consumer behavior, regardless region. In end paper, limitations guidelines future elaborated.