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PurposeThe purpose of this paper is to examine when and how organizations build big data analytics capability (BDAC) to improve supply chain agility (SCA) and gain competitive advantage.Design/methodology/approachThe authors grounded the theoretical framework in two perspectives: the dynamic capabilities view and contingency theory. To test the research hypotheses, the authors gathered 173 usable responses using a pre-tested questionnaire.FindingsThe results suggest that BDAC has a positive and significant effect on SCA and competitive advantage. Further, the results support the hypothesis that organizational flexibility (OF) has a positive and significant moderation effect on the path joining BDAC and SCA. However, contrary to the belief, the authors found no support for the moderation effect of OF on the path joining BDAC and competitive advantage.Originality/valueThe study makes some useful contributions to the literature on BDAC, SCA, OF, and competitive advantage. Moreover, the results may further motivate future scholars to replicate the findings using longitudinal data.

The current study aimed to explain the effect of big data analytics capabilities on firm performance in the telecommunication sector of Pakistan. The proposed research model examines the effect of big data analytics capabilities on firm performance in the presence of chain mediating effect of data integration capability and data-driven decision-making, along with moderating influence of analytics culture. The research model was developed using the proven theory of resource-based view. In this cross-sectional study, an online questionnaire was used including 34 response items for data collection, whereas SPSS and Smart-PLS 4.0 were used for descriptive statistics & inferential analysis respectively. The results of this study indicate that adoption of big data analytics capabilities positively influence firm performance. It also confirms about the effective implementation of data driven decision making & data integration capability leads to better performance of the organization. However, no moderation of analytics culture on firm performance was found. The results also suggest the managers to take effective decision-making based on data integration for enhancing business performance. Study faces some potential challenges due to high data volume availability, small sample size methodological and sector specifics limitations. Study suggests the potential for future research evaluating this model with two serial mediations like process-oriented dynamic capabilities, business process agility etc. along with some moderators such as customer knowledge management etc. to identify the response in more complicated connections.

The problems faced by the engineering procurement construction (EPC) industry in Indonesia are related to this research, including the presence of more competitive competitors, ineffective planning and project implementation, and the lack of tools in systematic decision-making (DM). This study attempts to use big data analytic capability (BDAC) to improve the quality of DM to enhance performance and improve competitiveness, insightful and predictive information. This study also aims to close the gap between hierarchical DM and the use of BDAC to increase the chances of winning projects and reducing losses in project implementation. This study was conducted on companies engaged in the EPC industry in Indonesia under the Association of Indonesian National Design and Build Companies (AINDBC). The results of this study indicate that BDAC, as a basis for DM, has a positive influence on firm performance (FP) through the process of selecting formulation and implementation strategies and more efficient use of project budgets. The limitation is that the construct of FP cannot be explained by the formulation strategy, but it can be explained by the implementation of strategy (IS). The difference in the results of this study and previous studies is due to differences in product and market characteristics, which are strategic components of the relationship between marketing strategy and FP. The EPC company can increase speed, accuracy and precision of the strategic DM process by using BDAC. Managers or practitioners, who are pioneers in developing and implementing BDACs, are required to increase the quality of DM.

PurposeThrough the lens of resource-based view (RBV), knowledge-based view (KBV) and DCV, this paper aims to investigate the relationship of entrepreneurial leadership (EL) on the project success (PS) and further examines the mediating effect of knowledge infrastructure capability (KIC), knowledge-based dynamic capability (KBDC) and Big data analytic capability (BDAC).Design/methodology/approach The data were collected from 467 employees working on project in software companies. The data were evaluated using SMART-PLS, a structural equation modeling (SEM) tool.FindingsThe study revealed a significant impact of EL on the PS, the study also found the significant mediation role of KIC, KBDC and BDAC on the EL and PS relationship.Originality/valueThe research gives valuable insight into the effective role of EL as a contemporary leadership style in project-based firms. Also, this research is one of the first to examine knowledge-oriented dynamic capabilities (DC) as a knowledge fulcrum in project execution. These DC have been empirically proven to facilitate EL in achieving PS and support the firm in competing in an uncertain environment.

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.

Many organizations are increasingly investing in building dynamic capabilities to gain competitive advantage. New products play an important role in gaining competitive advantage and can significantly boost organizational performance. Although new product development (NPD) is widely recognized as a potentially vital source of competitive advantage, organizations face challenges in terms of developing the right antecedents or capabilities to influence NPD performance. Our research suggests that organizations should invest in building alliance management capability (AMC), big data analytics capability (BDAC) and information visibility (IV) to achieve their desired NPD success. Informed by the dynamic capabilities view of the firm (DCV) we have stated seven research hypotheses. We further tested our hypotheses using 219 usable respondents gathered using a pre-tested instrument. The hypotheses were tested using variance based structural equation modelling (PLS-SEM). The results of our study paint an interesting picture. Our study makes some significant contribution to the DCV and offers some useful directions to practitioners engaged in NPD in the big data analytics era. We demonstrate that AMC and BDAC are lower-order dynamic capabilities and that AMC has a positive and significant influence on BDAC. In turn, AMC and BDAC influence NPD under the moderating influence of IV. Ours is one of the first studies to empirically establish an association among three distinct dynamic capabilities which are often considered in isolation: AMC, BDAC and NPD. Our findings support emergent views on dynamic capabilities and their classification into various orders. Lastly, we provide empirical evidence that information visibility acts as a contingent variable to both AMC and BDAC effects on NPD. We end our paper by outlining some limitations of our study and by offering useful future research directions.

Though the concept of green dynamic capability has been increasingly gaining traction among academics, practitioners, and policymakers, its association with green innovation adoption remains unclear. The present study addresses this gap and aims to provide clarity by distinguishing green innovation adoption in the context of developing countries. Drawing on dynamic capability and stakeholder theory, this research shed light on the significance of green dynamic capability for green innovation adoption. Additionally, this study examines the moderating role of environmental dynamism and big data analytics capability in the link between green dynamic capability and green innovation adoption. Adopting a two-wave research design, the sample for this study contained SMEs from Pakistan and Malaysia. Data was obtained from 220 SMEs (105 from Pakistan, 115 from Malaysia). To test the hypotheses, covariance-based structural equation modelling was performed to analyze causal relationships in the model, by using AMOS 23 software. The results showed that green dynamic capability positively impacts green innovation adoption, but environmental dynamism does not positively moderate between green dynamic capability and green innovation adoption. In addition, big data analytics capability positively moderates between green dynamic capability and green innovation adoption. We believe that this study opens a new avenue in the environmental literature under which green innovation adoption is useful for SMEs.

The relationship between Analytics Capability of an Organization (ACO) and both Supply Chain Disruption Orientation (SCDO) and Supply Chain Resilience (SCR) in order to achieve adequate operational performance in an era of environmental uncertainty is carried out in this study. Total three hypotheses (seven sub-hypotheses) using a survey of 405 respondents are collected via a pre-tested instrument and tested further. Results indicated the influence of ACO on both SCDO and SCR to achieve the desired degree of operational performance. However, under the moderation of environmental uncertainty, the link between ACO and SCDO was not supported, although the link between ACO and SCR was supported and this further enhanced operational performance. Further investigation of unsupported hypotheses using statistical analysis was conducted to gain deeper insights. It is explained how ACO impacted dynamic capabilities to influence operational performance. The contribution to theory of this study lies in explaining the role of dynamic capabilities that emerge from analytics as compared to the traditional view of supply chain classification. Further, the influence of environmental uncertainty on positioning dynamic capabilities strategically to address disruption in supply chains is discussed in the present study.

Green approaches remain little disseminated in the healthcare sector despite growing interest in recent years from practitioners and researchers. Big Data Analytics Capability (BDAC) can play a critical role in the integration of environmental concerns into operations and supply chain management (OSCM) and further strengthen the environmental performance of healthcare facilities. According to the literature, the integration of the environment into operations process remains insufficient to achieve high levels of performance and requires efforts in green process innovation. However, this relationship between BDAC and green process innovation remains poorly justified empirically. To address this theoretical gap, we investigated the relationship between BDAC, environmental process integration, green process innovation in OSCM and environmental performance. The main contribution of this study is the valuable knowledge on how BDAC influences environmental process integration and green process innovation to enhance environmental performance. Moreover, the study highlights the mediating role of green process innovation on environmental performance, a finding that has not been mentioned in the extant literature. The paper provides valuable insight for managers and stakeholders that can assist them in supporting the application of BDAC in healthcare OSCM to create sustainable value.

How should firms configure organizational capabilities to achieve competitive advantage in complex digital environments? To answer this question, we investigate parsimonious configurations for high firm performance in digital environments characterized by organized complexity. We adopt a configurational perspective accompanied by a fuzzy-set qualitative comparative analysis (fsQCA) to explicate complex nonlinear relationships among key digital and non-digital capabilities in the form of conjunction, equifinality, and asymmetry in producing the outcome. With this approach, we shift attention from individual capabilities to configurations of capabilities to develop a better understanding of the complex role of IT in the digital world. Our analyses, using a rare and unique dataset of 376 observations for organizations in healthcare, education, manufacturing, and service sectors in the United States, reveal three key findings. First, IT-enabled information analytics capability alone is neither necessary nor sufficient in any configuration for high performance; however, it is an important component of the configurations in which it plays multifaceted roles varying from an enabling role in some contexts, to no role or a counterproductive role in other contexts. Second, we document a few parsimonious configurations emergent from complex nonlinear interactions among six organizational capabilities. Interestingly, these configurations often have an isomorphic structure that produces both high financial performance and high customer performance simultaneously. Third, the structures of configurations for high performance differ from those of not-high performance, suggesting an asymmetric view of causality that underpins organizational performance. Together, the findings provide implications for further research on complexity theory in digital business strategy, and for managers to view and redesign digital business strategy as configurations of IT and organizational capabilities.