Shaojun Ji

Bio: Shaojun Ji is an academic researcher. The author has contributed to research in topics: Wine. The author has co-authored 1 publications.

User value identification based on an improved consumer value segmentation algorithm

Abstract: PurposeThe purpose of this study is to propose a new consumer value segmentation method for low-dimensional dense market datasets to quickly detect and cluster the most profitable customers for the enterprises.Design/methodology/approachIn this study, the comprehensive segmentation bases (CSB) with richer meanings were obtained by introducing the weighted recency-frequency-monetary (RFM) model into the common segmentation bases (SB). Further, a new market segmentation method, the CSB-MBK algorithm was proposed by integrating the CSB model and the mini-batch k-means (MBK) clustering algorithm.FindingsThe results show that our proposed CSB model can reflect consumers' contributions to a market, as well as improve the clustering performance. Moreover, the proposed CSB-MBK algorithm is demonstrably superior to the SB-MBK, CSB-KMA and CSB-Chameleon algorithms with respect to the Silhouette Coefficient (SC), the Calinski-Harabasz (CH) Index , the average running time and superior to the SB-MBK, RFM-MBK and WRFM-MBK algorithms in terms of the inter-market value and characteristic differentiation.Practical implicationsThis paper provides a tool for decision-makers and marketers to segment a market quickly, which can help them grasp consumers' activity, loyalty, purchasing power and other characteristics in a target market timely and achieve the precision marketing.Originality/valueThis study is the first to introduce the CSB-MBK algorithm for identifying valuable customers through the comprehensive consideration of the clustering quality, consumer value and segmentation speed. Moreover, the CSB-MBK algorithm can be considered for applications in other markets.

Beyond a tug-of-war: Motivation-based segmentation of visitors to a national arts festival

Abstract: Travel motivation is a leading research interest and of value to various tourism sectors, including festivals and events. Most national arts festivals in South Africa compete for the same market, and it is crucial to understand what motivates visitors to attend such events. Utilizing a multi-year destination-based data collection technique at Woordfees produced a combined sample size of 1005 responses. Four phases of analysis: a descriptive analysis to profile the respondents; an exploratory factor analysis (EFA) on motives for attending the festival; a cluster analysis based on the motives for attending the festival; and an analysis of significant differences between the market segments was performed. Two motivation factors were identified: festival attributes and attraction and escape, socialization, and enjoyment. Three market segments are identified: arts, ambivalent, and hedonic festival seekers. Arts and ambivalent festival seekers are more motivated by festival attributes and attraction (pull motive), while the hedonic festival seeker is more motivated by escape, socialization, and enjoyment (push motive). Motivation-based segmentation provides an excellent alternative perspective based on an Afrikaans literary festival. Although similar segments are expected to be present at other national arts festivals, more personalization could be implemented to satisfy market needs based on motivation to attend.