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Big data analytics (BDA) increasingly provide value to firms for robust decision making and solving business problems. The purpose of this paper is to explore information quality dynamics in big data environment linking business value, user satisfaction and firm performance.

Drawing on the appraisal-emotional response-coping framework, the authors propose a theory on information quality dynamics that helps in achieving business value, user satisfaction and firm performance with big data strategy and implementation. Information quality from BDA is conceptualized as the antecedent to the emotional response (e.g. value and satisfaction) and coping (performance). Proposed information quality dynamics are tested using data collected from 302 business analysts across various organizations in France and the USA.

The findings suggest that information quality in BDA reflects four significant dimensions: completeness, currency, format and accuracy. The overall information quality has significant, positive impact on firm performance which is mediated by business value (e.g. transactional, strategic and transformational) and user satisfaction.

On the one hand, this paper shows how to operationalize information quality, business value, satisfaction and firm performance in BDA using PLS-SEM. On the other hand, it proposes an REBUS-PLS algorithm to automatically detect three groups of users sharing the same behaviors when determining the information quality perceptions of BDA.

The study offers a set of determinants for information quality and business value in BDA projects, in order to support managers in their decision to enhance user satisfaction and firm performance.

The paper extends big data literature by offering an appraisal-emotional response-coping framework that is well fitted for information quality modeling on firm performance. The methodological novelty lies in embracing REBUS-PLS to handle unobserved heterogeneity in the sample.

The purpose of this paper is to investigate the early career values and individual factors of objective career success among graduates from a top-tier French business school.

The authors conducted a quantitative analysis of 629 graduates classified in three job markets according to income: the traditional business market, the alternative market and the high-potential business market. The graduation dates span a period of 12 years before the 2008 Recession.

The findings suggest that membership of each job market is associated with distinct early career values (when choosing/leaving the first job). Moreover, the authors confirm that the presence of a mentor, international experience, job-hopping and gender, all affect objective career success.

The paper discusses implications for business career development and higher business education.

The originality of this study lies in the identification of the individual factors of objective career success among French business graduates and the links between objective career success and early career values.

Block chain technology (BCT) has emerged as a promising solution for the co-ordination and aid mechanism issues in the context of humanitarian supply chain (HSC). However, implementation of BCT in HSC discerns several barriers. Therefore, the purpose of this study is to identify and model the block chain implementation barriers in the context of HSC.

In the present study, 14 potential barriers to BCT adoption in HSC have been identified through literature survey. The survey comprises white papers, pilot studies, conference proceedings and journal articles. Further, the identified barriers were finalised in consultation with a team of experts. The team comprised experienced stakeholders working in the humanitarian domain and BCT development. The barriers were categorised into four (technological, organisational, exogenous and economic) perspectives adopting the kappa statistics. Further, the barriers were prioritised using fuzzy best worst method (FBWM) approach. Later, sensitivity analysis was performed to check the robustness and viability of the model.

The findings from the study indicate that the barriers, such as “data privacy, ownership, and security issues” (B1), “funding issues and cost complexity” (B3) and “technological complexities” (B8), are relatively more influential. The HSC stakeholders and BCT developers are required to identify the safety mechanism against the misuse of victim’s data. The funding issues and technological complexities are interrelated and need synergetic cooperation between blockchain developers, donors, humanitarian organisations (HOs) and other HSC stakeholders. Further, “lack of awareness and understanding among stakeholders” (B6) and “interoperability, collaboration and cross-pollination among HOs” (B5) were identified as least influential barriers to BCT adoption in HSC.

In literature, limited study has been observed on determining barriers to BCT implementation. A more systematic method and statistical confirmation is necessary to establish further new confronting barriers. This study is limited to Indian context.

To the best of the authors’ knowledge, this study is first of its kind to use an FBWM approach for prioritising the barriers to BCT adoption in the context of HSC. The study provides potential barriers to BCT and categorises them into four different perspectives, along with their degree of influence.