(2008) argued that Agreeableness is playing important role in determining the user preferences in using new technology. H1, H2 and H3 are validated and H4 (Agreeableness) and H5 (Neuroticism) are not supported. The independent variables explain a high percentage of the variance of OBCE (R2= 43,2%), CGC (R2=27.8%) and UGC (R2=22.3%). Similarly, Baldus etal. In the case of this study the total variance for a single factor is 22.97%. JyRUjX~,;ro6(Q.JX,I?EI5,S,kF2Dhc@yZ:>`\@ch;]~E6_Xo V{H%V2/$YgDdfQQ[U^=zkO'?\9 c6QS=M9FK_1G]Y,}ku76ivkB4i+4x*ay[tyaQ/b>.>&l`vWCmZJD '\/Sz `Bdy|JE/, g_E~SzhI Primary data were collected by using online questionnaire survey to test research hypotheses and conduct the research findings. Thirdly, this paper is considered the only one in Palestine that primarily focused on consumers engagement to the online brands communities partially in banking industry context. Third section details the adaptive model and explains the research questionnaire design. Seeking assistance from the other help the community members to avoid or reduce the uncertainty that are related to their decisions in purchasing the products, services, and brands (Dholakia etal., 2009). Therefore, this concept is defined as the ardent affection a community member has for the brand (Baldus etal., 2015). This paper believes that validation has positive impact on intention to forward CGC. Moreover, the internet versions of a survey sent to via E-mail. Utilitarian is defined as the degree to which the community member wants to gain monetary rewards through participating in brand community. Offline and online bankingwhere to draw the line when building trust in e-banking? 2 0 obj 3099067 (Bentler & Chou, 1987).

Further, Baldus etal. The online community share the common interest through computer-mediated mechanism by aggregation of self-select people (Hennig-Thurau etal., 2004; Shang etal., 2006). The second limitation is related to implementationof this study and generalization of the results on the financial sectors, therefore the researchers are encouraged to conduct research across other industries such as manufacturing or educational sectors, in order to expand the model of this study across many different industries to measure the impact of this model and to generates and compare the results and to get further investigation related to the influence of some of the variables included in this study. Heller Baird and Parasnis (2011) indicated that the customers use their social media to connect and communicate with friends and family, if the companies want from the customers to communicate and interact with them via social media the companies must reward them in order to motive their participation. Rotation method: Varimax with Kaiser normalization. (2009) stated that people who are high in neuroticism are more likely to prefer using Facebook usage. Figure 2 shows the standardized path coefficients and p-values. Simultaneously, the results provide banks with a valuable implication on how banking industry can attract more customers in online brand community website and perceived trust of banks services and products. The survey was carried out among online banking customers who participated in the brand community engagement through the Facebook. The result of the internet growth, enable the customers to share and distribute information about the brand when they participate in the online brand community engagement (Chang etal., 2013). This pilot study analyzed the questionnaire to verify the acceptance level, dimensionality, reliability and validity of the proposed measurement scales. (2013) considered it as new way which users can interact with brand. (2015). For example: Garbarino and Strahilevitz (2004); Bakewell and Mitchell (2006) indicated the differences between men and women considerations during the shopping, the women consider hedonic rewards, but the men consider the utilitarian rewards. The purpose of this paper is to develop and estimate conceptual model of how customers personality traits influence on their intentions to forward through their online brand engagement. This model assumes that personality can be explained by five key factors include; Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness. Conscientiousness is the tendency to be organized, efficient, reliable, and systematic (Barrick & Mount, 1991). @#I!i 0Th WP:4dHZCf^SGt"qR$o6mXwRc -I\ngbvU\z/1N'`cT Openness is described with adjectives imaginable, original, and intelligent (Barrick & Mount, 1991). Therefore, the nurture and creation are considered the two important forces behind brand influence on the behaviour customer. Wang etal. R9z(5;y'pK&TTKS&. %PDF-1.5 This software approached a descriptive analysis to obtain the demographic characteristics of the sample. Hypotheses were tested through SEM (structural equation modelling) by approaching the maximum likelihood analysis and a bootstrapping technique involving 500 consecutive steps with a significance level of 95%. (2015) Defined the Online brand community engagement as the compelling, intrinsic motivations resulting in continuous interacting between the customers and online brand community. A total valid 685 questionnaires were distributed on banks customers in Palestine. It also thought how customers personality influence on the on online brand community engagement. Further, Roos (2017) stated that conscientiousness is associated with planning and self-discipline, and efficiency. % Secondly, the structural model was analyzed through the SPSS 24.0 software suit. Rotated components matrix a. This indicates that the flexibility of thought and tolerance of new idea. In this sense, the sample size to variable ratio is also appropriate. In particular, we had notice few empirical works addressing this issue (Hollebeek, 2011a; Islam etal., 2017). Although number of influential factors of online brand community have proposed in prior literature. Furthermore, the information and products are ranked in internet according to relevant interesting in order to facilitate users to find out what is the most interesting product. Recently, online brand community is managed by both companies and individual investors who have the same interests and passion toward brand. Relating the five-factor model to technology acceptance and use, Communal service delivery: how customers benefit from participation in firm-hosted virtual P3 communities, Narrative processing: building consumer connections to brands, The dark side of ubiquitous connectivity in smartphone-based SNS: An integrated model from information perspective, Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation, A broad-bandwidth, public domain, personality inventory measuring the lower-level facets of several five-factor models, Customer engagement in a Facebook brand community, From social media to social customer relationship management. Figure 2. Indeed, social media has been recognized as a highly effective channel for contacting with customers in the context of brand businesses. Based on the notions above we advance: H2: Extraversion is positively associated with on online brand community engagement. Community engagement is defined by Algesheimer etal. (2008) believed that more openness in personality is strongly related with the preference to use new technology). the customers see and recognized the brand as part of themselves. Malr etal. Hence, we advance: H1: Neuroticism is positively associated with online brand community engagement OBCE. Moreover, experts in the area of marketing and finance were also asked to review the items in order to ensure the consistency of each item. Finally, Intention to forward online company generated content (CGC) and Intention to forward online company generated content (UGC) were adapted from Davis (1989). A panel of ten professionals assessed the methodology as well as the scales in order to warrant content validity and the proper phrasing of the questions. Table 3. pMOF 5R^,4*-=qr> wmGA.|+'9bDo !Bh$+~G'i?&q='D # A principal component analysis (PCA) was also conducted to assess the degree of unidimensionality of the different measurement scales. These findings are consistent with prior research that has investigated significant impact of big five personality factors on online brand community engagement (Ross etal., 2009; Orr etal., 2009; Hollebeek, 2011; Jani and Han., 2014; Islam etal., 2017 ). This research expects that the above users personality factors reflect the unique facets of each human being. The characteristics of the sample represent a relevant limitation, since data were gathered from customers of financial entities operating specifically in the geographical area of the Palestinian authority, also the data were collected from specific social Medias (Facebook). Finally, the researchers encourage future studies in testing the same relationships in banking services through a cross-cultural and using different social media for example (Twitter, YouTube) to implement the study and collecting data, in addition to test and measure this model in the future studies by adding the demographic information to this model, for example the role of the age, income level, and the gender in order to track the nature of the relationships between these constructs. The loyalty for the customers who collect the loyalty points via social media is greater than the customers who collect the points based on transactions only. Its defined as the degree to which the community member wants to help fellow community member through sharing knowledge, experience, or time (Baldus etal., 2015). Specifically, we adapted the personality dimensions (Neuroticism, Extraversion, Openness, Agreeableness and Conscientiousness) from the International Personality Item Pool (Goldberg, 1999; IPIP , 2008). The results confirm the statistical significance of five of the seven tested effects. Moreover, it is important to communicate with customers in order to influence their behaviour and pursue them to engage in the brand community. (2005) develop in their research a conceptual model to estimate the customers intentions and behaviors how influenced by the different aspects of customers relationships with the brand community. Factorial loads of the different indicators were used to assess convergent validity revealing coefficients different than zero and loadings higher than 0.7. (2012) described that customers interact with brand community is divided into purchases behavior (purchasing the brand) and non-purchasing behavior (sharing or recommending the word of mouth. 3 0 obj Thus, this research proposes that the five dimensions affecting personality and psychological traits are expected to play a significant mediating role in the relationship between online brand community engagement and intention to forward CGC and UGC. The sample size in this research is substantial so the research model can be properly assessed. Moreover, extraverted individuals would engage in more frequent use of social media (Ross et al., 2009). hb```"yf6#A ! m'rnknn iQ8}"D'*%B9::8:A@'0|@v"$.`l The result draws remarkable attention to level of customer- engagement to forward for online company generated contents (CGC), and users generated contents (UGC). The community members are interested and motivated to participate in such activities and behaviour like, helping each other in the community, sharing and recommending the WOM, and the other engagement behaviors like writing comments (Algesheimer etal., 2005; Van Doorn et al., 2010) This indicates that users engagein online brand community because they want to share his experience and knowledge to other community member. In fact, UGC holds are influential factor for attracting consumers to engage in social media. The research hypotheses were tested by using structural equation model. Moreover, it seeks understand how customers interaction with brand community contribute to their loyalty behaviour and intention with considering customer personality as crucial factor. The percentage is approximately distributed equally between the men and women, but the majority of respondents, with a preponderant age range of (31-35) years and least majority of respondents for the age less than 18. Demystifying customer brand engagement: exploring the loyalty nexus, Consumer brand engagement in social media: Conceptualization, scale development and validation, Personality factors as predictors of online consumer engagement: an empirical investigation, Personality, satisfaction, image, ambience, and loyalty: Testing their relationships in the hotel industry, A multi-analytical approach to peer-to-peer mobile payment acceptance prediction, Users of the world, unite! This study sought to measure the relationships among personality dimensions (five), online-brand community engagement, intention to forward online company generated contents (CGC) and intention to forward user generated contents (UGC). He or she has to be member in the bank brand community page. 5 Howick Place | London | SW1P 1WG. Descriptive Statistics for Demographic Variables. The Brand Passion dimension was removed from the model. Initially, Baldus etal. Moreover, Roos (2017) argued that people high in agreeableness are trusting and forgiving. Table 1 presents the participants demographic characteristics.