THE EFFECT OF BIG DATA ANALYTICS CAPABILITY ON FIRM PERFORMANCE

Big data analytics (BDA) has emerged as an important area of study for both academics and practitioners. Despite of rising potential value of BDA, a few studies have been conducted to investigate the effect of BDA on firm performance. In this research in progress, according to the challenges of BDA dimensions (volume, variety, velocity, veracity and value) we propose the BDA capability dimensions in line with IT capability concept. BDA infrastructure capability, BDA management capability, BDA personnel capability and relational BDA capability provide the overall BDA Capability concept. The study, by employing dynamic capability, proposes that BDA capability impacts on firm financial and market performance by mediated effect of operational performance. The finding of this research by providing essential BDA capability and its effect on firm performance can apply as a roadmap and fill the gap between managers’ expectation of BDA and what is emerged of BDA implementation

The Relation between Supply Chain Analytics Management Capability and Firm Performance

The global academic and practitioner industries have shown significant interest in the effect and importance of big data analytics and new technologies on supply chains. Based on the organizational information processing theory, this study attempts to investigate how big data driven supply chain analytics management capability influence firm performance. We tested our research hypotheses using variance based structural equation modelling with survey data collected using a web based pre-tested instrument from 201 respondents employed various industries in Turkey. The findings indicate that supply chain analytics Management capability has positive effect on firm performance

[Withdrawn] How Do E-commerce Capabilities Influence Agricultural Firm Performance Gains? Theory and Empirical Evidence

Based on the resource-based view of the firm and from the perspective of organizational agility, thisstudybuilds a model of the factors affecting agricultural firm performance gains in the context of e-commerce and discusses the effects of e-commerce capabilities on firm performance gains. The empirical results show that market capitalizing agility and operational adjustment agility play important mediating roles in conveying positive influences of e-commerce capabilities’ dimensions on financialand non-financial performance gains. Specifically, managerial, analytical, and technical capabilities have different effects on market capitalizing agility and operational adjustment agility, with talent capability performing the most important role. Both market capitalizing agility and operational adjustment agility have positive impacts on financial and non-financial performance gains, respectively

Big data analytics management capability and firm performance: The mediating role of data-driven culture

The effect of big data analytics on firm performance and the effects of intermediary variables on this relationship are not yet clearly understood. Drawing on the dynamic capability view (DCV), this study investigates the mediating effect of a data-driven culture on the relationship between big data analytics management capability and firm performance (i.e., operational and financial performance). Drawing on survey data from 432 big data experts across 132 firms operating in Turkey, our findings indicate that big data analytics management capability and a data-driven culture have significant positive effects on both the operational and financial performance of a firm. In addition, a data-driven culture significantly mediates the links between big data analytics management capability and the measures of both operational and financial performance. Hence, our findings offer a valuable guide for managers utilizing big data or making big data investments to increase firm performance

Interaction of IT investment mandates and mobile savvy affecting mobile office performance in corporates: Focusing on the moderating effects of IT savvy

This study investigates the effect of IT investment portfolios on the performance of mobile business services, as well as the moderating role of IT savvy. This study pulls the concept of IT investment mandates into the conceptual research framework of mobile investment. A survey for the IT specialists working at 123 enterprise-level companies was conducted and hierarchical regression analysis was adopted. Our results show that IT investment and organizational IT capabilities influence the performance of the mobile office and that IT savvy plays as a moderator in the relationship between investment mandates and mobile office performance. This research also may indicate that transactional assets are most helpful factors for a change by the adoption of mobile technology. This study is a rare research paper to explain the impact of IT investment portfolios on the mobile office performance in an academic methodology

Big data analytics in e-commerce: A systematic review and agenda for future research

There has been an increasing emphasis on big data analytics (BDA) in e-commerce in recent years. However, it remains poorly-explored as a concept, which obstructs its theoretical and practical development. This position paper explores BDA in e-commerce by drawing on a systematic review of the literature. The paper presents an interpretive framework that explores the definitional aspects, distinctive characteristics, types, business value and challenges of BDA in the e-commerce landscape. The paper also triggers broader discussions regarding future research challenges and opportunities in theory and practice. Overall, the findings of the study synthesize diverse BDA concepts (e.g., definition of big data, types, nature, business value and relevant theories) that provide deeper insights along the cross-cutting analytics applications in e-commerce

An investigation of analytics and business intelligence applications in improving healthcare organization performance: a mixed methods research

The healthcare ecosystem in the US is currently undergoing series of refinement and reformation due to the need to (i) improve quality of care and (ii) reduce cost. To achieve their key objective, healthcare organizations (HCOs) currently face a fundamental challenge: how to best use or optimize limited resources while providing better care and services to patients? The answer to this question might lie within HCO’s massive data and the ability to identify and apply appropriate analytics and business intelligence (A&BI) techniques and technologies to discern and extract relevant information and knowledge from that data. However, despite the increasing interest in the implementation and utilization of A&BI techniques and technologies by various organizations to improve operational efficiencies and financial performance, HCOs still lag behind other sectors in the adoption and use of A&BI capabilities. Motivated by the “data rich but information poor” syndrome currently facing HCOs, this dissertation applies a mixed method research–case study (interpretivist) and survey (positivist) – to investigate how healthcare organizations can leverage A&BI techniques and technologies to improve their overall performance. In achieving this objective, I illustrate an exemplar of how A&BI techniques and technologies can effectively be applied by specifically answering this high-level research question (RQ): How can A&BI techniques, methods, and technologies be developed and leveraged to improve performance in healthcare organizations? This high-level RQ has been broken down into four sub-questions that will be answered in two different studies in this dissertation. In the first study, I investigate what combination of A&BI techniques and technologies HCOs are currently applying to create value. This study was conducted by using content/literature analysis and case study methods in a large healthcare organization. The second study builds on the first study to investigate, using both interview and survey data, how A&BI capabilities can be developed, cultivated and nurtured as a core competency or capability that significantly helps improve healthcare organizations’ overall performance (such as cost reduction, quick access to providers and treatment, effective diagnostics, etc.). I found very novel and interesting results in both studies that not only address the research questions, but also provide significant theoretical and practical contributions. Major contributions of study 1 include: revising and remodeling of an outdated healthcare value chain (HCVC) framework that is more realistic and applicable to current care delivery practices in the healthcare industry and mapping of A&BI capabilities to the different domains of the revised HCVC framework. Study 2 provides theoretical contribution to the existing literature by conceptualizing and empirically validating A&BI capability as a third-order multi-dimension construct and its significant influence on performance

Assessing Big Data Analytics Capability and Sustainability in Supply Chains

Big data analytics capability (BDAC) is a technology-based capability, which can influence sustainability performance of firms in supply chains. By using BDAC strategically, supply chains could improve their responses to social, environmental, and social changes taking place in uncertain business environments. This paper presents a detailed literature review on the two ends of the equation: BDACs and sustainability in supply chains performance (SSCP). The theoretical perspective of the dynamic capabilities helps us to understand BDAC holistically, a combination of non-human and human capabilities. Then, we adapt the three-bottom-line approach: economic, environmental, and social performance in order to offer a comprehensive measurement of SSCP Based on the overview of the literature, the paper offers metrics to be used in assessing both BDAC and SSCP that can advance the understanding of the relationship between them

The Relation between Supply Chain Analytics Management Capability and Firm Performance

The global academic and practitioner industries have shown significant interest in the effect and importance of big data analytics and new technologies on supply chains. Based on the organizational information processing theory, this study attempts to investigate how big data driven supply chain analytics management capability influence firm performance. We tested our research hypotheses using variance based structural equation modelling with survey data collected using a web based pre-tested instrument from 201 respondents employed various industries in Turkey. The findings indicate that supply chain analytics Management capability has positive effect on firm performance

Theorizing the Concept of Agency in Human-Algorithmic Ensembles with a Socio-Technical Lens

The growing relevance of algorithmic systems, including artificial intelligence, for processes of value creation raise theoretical and practical interest in the conceptualization of actorhood and the balancing of human and technological agencies within socio-technical ensembles. Prominent theories of the IS discipline still reflect a human-centric conceptualization of agency, which we deem challenged by advances in machine learning technology. We therefore motivate a revised theorizing of the concept of agency with a socio-technical lens. For that, we apply an inductive top-down theorizing approach. In this short paper, we present the first inductive step by describing tensions, oppositions and contradictions in the discourse on agency in IS literature of the last 30 years in the AIS Senior Scholars’ Basket of journals. The preliminary findings uncover a conceptual and ontological incoherence surrounding the concept of agency in IS scholarship, and a gap between reviewed publications and the agency claims of algorithmic systems