There is a lack of understanding on the factors affecting active participation in Business-to-Business (B2B) Online Communities (OC). To address this gap, we developed a model based on two theories: Social Exchange Theory and the Information Systems Success Model. The model was validated by using survey data collected from 40 B2B discussion forums on LinkedIn (n = 521). Our work made a number of significant contributions including an integrated model of factors affecting active participation in B2B OCs and a new validated measure for active participation. Further, we proposed several guidelines which assist B2B OC providers in building and maintaining successful communitities.

Purpose Social media developments in the last decade have led to the emergence of a new form of word of mouth (WOM) in the digital environment. Electronic word-of-mouth (eWOM) is considered by many scholars and practitioners to be the most influential informal communication mechanism between businesses and potential and actual consumers. The purpose of this paper is to extend knowledge about WOM in this new context by proposing a conceptual framework that enables a better understanding of how trust and reciprocity influence eWOM participation in ORCs. Design/methodology/approach This study applies non-probability convenience sampling technique to conduct a quantitative study of data from an online survey of 189 members of ORCs. Partial least squares (PLS) is used to analyse the correlations between individuals’ intention to seek opinion, to give their own opinion and to pass on the opinion of another within ORCs. Findings The data analysis reveals that opinion seeking within ORCs had a direct effect on opinion giving and opinion passing. Ability trust and integrity trust had a positive effect on opinion seeking, while benevolence trust had a direct positive effect on opinion passing. Reciprocity had a direct impact on opinion passing. While reciprocity did not affect opinion giving, the relationship between these two concepts was mediated by integrity trust. Research limitations/implications By studying the complexities that characterise the relationships between reciprocity, trust and eWOM, the study extends understanding of eWOM in ORCs. Originality/value To the best of the authors’ knowledge, this is one of only a few papers that have examined the complex interrelationships between reciprocity, trust and eWOM in the context of ORCs.

PurposeThe study examines how firms may transform big data analytics (BDA) into a sustainable competitive advantage and enhance business performance using BDA. Furthermore, this study identifies various resources and sub-capabilities that contribute to BDA capability.Design/methodology/approachUsing classic grounded theory (GT), resource-based theory and dynamic capability (DC), the authors conducted interviews, which involved an exploratory inductive process. Through a continuous iterative process between the collection, analysis and comparison of data, themes and their relationships appeared. The literature was used as part of the data set in the later phases of data collection and analysis to identify how the study’s findings fit with the extant literature and enrich the emerging concepts and their relationships.FindingsThe data analysis led to developing a conceptual model of BDA capability that described how BDA contributes to firm performance through the mediated impact of organizational learning (OL). The findings indicate that BDA capability is incomplete in the absence of BDA capability dimensions and their sub-dimensions, and expected advancement will not be achieved.Research limitations/implicationsThe research offers insights on how BDA is converted into an enterprise-wide initiative, by extending the BDA capability model and describing the role of per dimension in constructing the capability. In addition, the paper provides managers with insights regarding the ways in which BDA capability continuously contributes to OL, fosters organizational knowledge and organizational abilities to sense, seize and reconfigure data and knowledge to grab digital opportunities in order to sustain competitive advantage.Originality/valueThis article is the first exploratory research using GT to identify how data-driven firms obtain and sustain BDA competitive advantage, beyond prior studies that employed mostly a hypothetico-deductive stance to investigate BDA capability. While the authors discovered various dimensions of BDA capability and identified several factors, some of the prior related studies showed some of the dimensions as formative factors (e.g. Lozada et al., 2019; Mikalef et al., 2019) and some other research depicted the different dimensions of BDA capability as reflective factors (e.g. Wamba and Akter, 2019; Ferraris et al., 2019). Thus, it was found necessary to correctly define different dimensions and their contributions, since formative and reflective models represent various approaches to achieving the capability. In this line, the authors used GT, as an exploratory method, to conceptualize BDA capability and the mechanism that it contributes to firm performance. This research introduces new capability dimensions that were not examined in prior research. The study also discusses how OL mediates the impact of BDA capability on firm performance, which is considered the hidden value of BDA capability.

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