Nowadays, many people refer to online customer reviews that are available on most shopping websites to make a better purchase decision. An automated review helpfulness prediction model can help the websites to rank reviews based on their level of helpfulness. This study examines the effect of review title features on predicting the helpfulness of online reviews. Moreover, a new method is proposed to categorize action verbs in a review text. Text, reviewer, readability, and title features are the four main categories that are used in this article. We examine our proposed prediction model on two real-life Amazon datasets using machine learning techniques. The results show a promising performance of the model. However, feature importance analysis reveals the low importance of title features in the predictive model. It means that the title characteristics cannot be a powerful determinant of online review helpfulness. The results of this study can be beneficial to both buyers and website owners to have a deep insight into online reviews helpfulness.

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Purpose -This paper's main purpose is to provide a systematic approach for mapping the value exchange in B2B relationship marketing. This approach affords a preliminary analysis in order to distinguish business customers' different value dimensions (tangibles and intangibles) and to set sights on determining suitable metrics to evaluate and quantify the value of each customer. Design/methodology/approach -The paper uses a combination of qualitative research approaches, namely an exploratory case study, in-depth interviews, and consensus expert opinion. The empirical study took place over three months to maximize the proposed approach's expediency in the practitioners' B2B environment and to increase the validity of the research findings. Findings -In addition to developing a new framework originating in the value network approach for mapping, modeling and analyzing business customers' value network (BCVN), the findings posit a proposed systematic approach for practitioners and marketing scholars to scrutinize the multidimension values of business relationship marketing. Practical implications -For companies and their business customers alike, the benefits of the systematic approach proposed in this paper are an efficient analytical system giving an opportunity to B2B marketers and managers to understand their business customers' network in detail. Originality/value -The implicit concept of maximizing customer lifetime value within the business customers' network appeals for an applied approach to better understand and analyze the real value of business customers to retain them.