Does reliable information matter? Towards a trustworthy co-created recommendation model by mining unboxing reviews

Abstract

Online review forums provide customers with powerful platforms to express opinions and influence business trends, while allowing firms to collaborate and co-create value with customers. However, information overload due to the huge amount of reviews posted daily complicates the efforts of consumers to locate reliable information when making a purchase decision. Therefore, this study develops a trustworthy co-created recommendation model. The proposed model mines unboxing reviews, calculates the trust scores of the reviewers, and then generates the recommended products by combing this information with customer preferences using a multi-criteria decision-making method. An illustrative example of mobile phones demonstrates the recommendation procedure of the proposed model. The proposed model is evaluated via an empirical experiment to examine the satisfaction of study participants by using a seven-point Likert scale. An analysis of the structural equation modelling results indicates that three factors (i.e. confidence in decision quality, enhanced problem-solving ability, and satisfaction with resource expenditure) significantly and positively affect the purchase decision-making process. Moreover, the proposed model outperforms a baseline model in all four factors, ultimately increasing user satisfaction. In addition to its theoretical framework for co-creating value with customers to develop a trustworthy co-created recommendation model, as supported by various theories of trust, the proposed model provides further insights into the role of customer reviews in designing recommendation models, as well as the extent to which such models impact user decisions.

The impact of customer reviews in social media on the brand reputation for the online accommodation sector

“…Previous works have applied MCDM methods to study social media platforms, online customer reviews or brand reputation (Abirami & Askarunisa, 2017;Abulaish et al, 2019;Gobi & Rathinavelu, 2019;Guijarro et al, 2021;Li et al, 2016;Roy Ghatak et al, 2016). Directly connected to the research question of this study, we find (Hasan & Rahman, 2017), who conducted a study using AHP approach to prioritize the vital factors that affect customer participation in the online platforms of the service sector.…”

Proceedings INNODOCT/22. International Conference on Innovation, Documentation and Education

“…This new form of marketing, called electronic word of mouth (e-WOM), is considered as one of the most critical factors in influential customer purchase behavior besides playing an essential role in the company's image and reputation (Torres & Singh, 2016). e-WOM is defined as any positive or negative explanation, made by potential or current customers about products, services, or brands, by using social media or any platforms on the Internet (Wang, 2016). It can reach a large group of people better than traditional word of mouth; any discussion on social media can become viral marketing (Mangold & Smith, 2012).…”

“…Although Wang (2016) argue there is no difference between WOM and e-WOM because people have the same motivations to use it, Banerjee et al (2017) defend that there is a considerable difference between them in many ways, especially in the source of information, starting with the use of electronic technologies such as blogs, review sites, social media, or online discussion forums. Platforms in which customers can exchange their experience and information, facilitate exchange information between users (Loureiro & Sarmento, 2019).…”

“…Previous works have applied MCDM methods to study social media platforms, online customer reviews or brand reputation (Abirami & Askarunisa, 2017;Abulaish et al, 2019;Gobi & Rathinavelu, 2019;Guijarro et al, 2021;Li et al, 2016;Roy Ghatak et al, 2016). Directly connected to the research question of this study, we find (Hasan & Rahman, 2017), who conducted a study using AHP approach to prioritize the vital factors that affect customer participation in the online platforms of the service sector.…”

Influence of Online Forums on Customers’ Buying Decisions: A Machine Learning Approach

“…In a way Online Forums encompass discussion groups, chat groups, online review forums, logs and blogs amongst others (Dellarocas, 2006). According to Li et al (2016) online forums have the ability to influence business trends due to its customer centric approach allowing customers to be co-creators with firms which has increased the power of the influence exerted by these forums on customer's buying decision making. Similarly, Lu et al (2020) in their study examined how the communication setting of online forums influences consumers' buying decisions.…”