Big data analytics capability and organizational performance measures: The mediating role of business intelligence infrastructure

The growing importance of big data has headed enterprises to advance their big data analytics capability to strengthen their firm performance. This study tests how big data capability impact on business intelligence infrastructure to achieve firm performance measures such as operational performance and marketing performance. This study is based on the recent literature on the knowledge-based view, big data capability, IT capability, and business intelligence. The primary survey of 272 responses from Chinese firms’ IT managers and big data analysts are used to uncover the relationship in the proposed model. The finding shows that the big data analytics capability significantly impacts on business intelligence infrastructure that in turn positively impact on operational performance and marketing performance. Further, the business intelligence infrastructure partially mediates between big data analytics capability and operational performance, and fully mediates between big data analytics capability and marketing performance. This research contributes to the information systems literature such as big data analytic capability, business intelligence, and firm performance measures, and thus offers grounds to extend more widespread studies in this field. This study adds to the literature on the theory and practical bases for big data capability and business intelligence infrastructure.

The role of capabilities in shaping sustainable supply chain flexibility and enhancing circular economy-target performance: an empirical study

Purpose A circular economy is a popular approach considered by many firms to address sustainable development goals strategically. Literature indicates that collaborative relationships among supply chain partners facilitate circular economy practices. However, there is a dearth of studies in lower-middle-income countries indicating the unique challenges industries face whilst practising circular economy principles and how the challenges can be overcome. To address the calls of previous researchers, this study aims to explore the following relationships: engagement and alliance capability whilst data analytics capability plays a mediating role; the relationship between alliance and data analytics capability with sustainable supply chain flexibility whilst industry dynamism is considered as a moderating variable and the relationship between sustainable supply chain flexibility and circular economy-target performance. Design/methodology/approach A cross-sectional survey was performed and data was collected from 760 employees of Indian firms. Covariance-based structural equation modelling was applied to perform the path analysis to determine a firm’s capabilities in shaping sustainable supply chain flexibility and enhancing circular economy target performance. Findings Drawing upon dynamic capability theory, it was first established that engagement capability has a positive and significant influence on alliance capability, whilst data analytics capability played a partial mediating role. Second, it was established that alliance capability and data analytics capability significantly affect sustainable supply chain flexibility, whilst industry dynamism played a moderating role. Finally, it was clear that sustainable supply chain flexibility had a significant and positive effect on circular economy target performance, ultimately enhancing sustainability. Originality/value This study advances the circular economy literature by recommending that firms must consider some critical operational level capabilities to develop their dynamic capability, i.e. sustainable supply chain flexibility, to better meet the competitive market conditions in turbulent business environments.

Analytics Capability in Marketing Education: A Practice-Informed Model

As marketing continues to be transformed by technology and the explosion of big data, academic research has identified a significant need for analytics skills in marketing education. However, it is unclear whether current curriculum approaches to marketing analytics equip students with the skills employers need and prepare them effectively for data-driven marketing roles. This study identifies the knowledge and skills marketing graduates require for analytics practice to bridge the theory-practice gap and increase students’ employability. Our research reveals that a blend of knowledge, soft and technical skills is needed, and that the ability to communicate insights from data to stakeholders is critical. We offer a practice-informed model which demonstrates that conceptual knowledge, technical skills, tools skills and soft skills are required to develop holistic analytics capability for marketing practice. Actionable takeaways for how educators can embed holistic analytics teaching in marketing education are also provided.

A knowledge-based view of analytics capability in purchasing and supply management

PurposeThe purpose of this study is to elaborate on how analytics capability develops within the PSM function. This study is an in-depth exploration of how analytics capability develops within the purchasing and supply management (PSM) function.Design/methodology/approachA multiple case study was conducted of the PSM function of six case firms, in which primary data were collected through semi-structured interviews with PSM analytics stakeholders. The data were analyzed based on an analytics capability framework derived from the literature. Cases were chosen based on them having advanced PSM practices and ongoing analytics projects in the PSM area.FindingsThe findings shed light on how the firms develop their analytics capability in the PSM functional area. While we identify several commonalities in this respect, the authors also observe differences in how firms organize for analytics, bringing analytics and PSM decision-makers together. Building on the knowledge-based view of the firm, The authors offer a theoretical explanation of our observations, highlighting the user-driven side of analytics development, which has largely been unrecognized by prior literature. The authors also offer an explanation of the observed dual role that analytics takes in cross-functional initiatives.Research limitations/implicationsThe exploratory nature of our study limits the generalizability of our results. Further, our limited number of cases and interviewees indicate that there is still much to explore in the phenomenon of developing analytics capability.Practical implicationsOur findings can help firms gain a better understanding of how they could develop their analytics capability and what issues they need to consider when seeking leveraging data through analytics for PSM decisions.Originality/valueThis paper is, to the best knowledge of the authors, the first empirical study of analytics capability in PSM.