Toward the development of a big data analytics capability

The era of big data has begun such that organizations in all industries have been heavily investing in big data initiatives. We know from prior studies that investments alone do not generate competitive advantage; instead, firms need to create capabilities that rival firms find hard to match. Drawing on the resource-based theory of the firm and recent work in big data, this study (1) identifies various resources that in combination build a big data analytics (BDA) capability, (2) creates an instrument to measure BDA capability of the firm, and (3) tests the relationship between BDA capability and firm performance. Results empirically validate the proposed theoretical framework of this study and provide evidence that BDA capability leads to superior firm performance.     

Big data and firm performance: The roles of market-directed capabilities and business strategy

Despite being the object of much interest, deep insights regarding why and when investments in big data resources enhance firm performance are lacking in the literature. Building on the resource-based view (RBV) and data provided by 301 senior marketing managers, this study reveals that big data resources primarily improve firm performance by enhancing the market-directed capabilities of the firm. In addition, the data indicate that firms pursuing a differentiation rather than cost-leadership strategy gain most from big data resource investments and that such resources account for 13 % of the variance in the performance of firms pursuing a differentiation strategy.     

Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view

This study examines the antecedents and influence of big data decision-making capabilities on decision-making quality among Chinese firms. We propose that such capabilities are influenced by big data management challenges such as leadership, talent management, technology, and organisational culture. By using primary data from 108 Chinese firms and utilising partial least squares, we tested the antecedents of big data decision-making capability and its impact on decision-making quality. Findings suggest that big data management challenges are the key antecedents of big data decision-making capability. Furthermore, the latter is vital for big data decision-making quality.     

Enabling firm performance through business intelligence and analytics: A dynamic capabilities perspective

This study draws on the sense-seize-transform view of dynamic capabilities as the theoretical lens for examining the role of BI&A in organizations. It views BI&A as the sensing and seizing components of dynamic capabilities that contribute to firm performance by enabling business process change. Findings confirm a positive relationship between BI&A and performance, mediated by business process change capabilities. This study answers the call for a theoretically grounded examination of the relationship between BI&A and firm performance by highlighting the significance of the BI&A seizing capabilities, and the importance of business process change in translating BI&A output into improved performance.     

Business intelligence and analytics use,innovation ambidexterity,and firm performance: A dynamic capabilities perspective

To survive in a dynamic and hyper-competitive business environment, firms are compelled to simultaneously introduce incremental and radical innovations. While it is recognised that business intelligence and analytics (BI&A) can support innovation and provide organisational value, the literature provides a limited understanding of its impact on balancing different innovation activities and ensuring performance gains. In this study, we examine the relationship between BI&A use, innovation ambidexterity, and firm performance by relying on the process theory of IS value creation as well as the dynamic capabilities perspective. We test our model using data collected from medium- and large-sized firms in Slovenia, applying partial least squares modelling. The results support the notion that BI&A use is positively associated with successful balancing between explorative and exploitative innovation activities, which in turn enhances firm performance. Our results also indicate that innovation ambidexterity is enhanced in two ways: indirectly through interaction with the firm’s absorptive capacity, and directly by increasing the possibilities of faster experimentation with offerings of products or services and improved predictability of the value of new products or services.     

Business value of big data analytics: A systems-theoretic approach and empirical test

Although big data analytics have been widely considered a key driver of marketing and innovation processes, whether and how big data analytics create business value has not been fully understood and empirically validated at a large scale. Taking social media analytics as an example, this paper is among the first attempts to theoretically explain and empirically test the market performance impact of big data analytics. Drawing on the systems theory, we explain how and why social media analytics create super-additive value through the synergies in functional complementarity between social media diversity for gathering big data from diverse social media channels and big data analytics for analyzing the gathered big data. Furthermore, we deepen our theorizing by considering the difference between small and medium enterprises (SMEs) and large firms in the required integration effort that enables the synergies of social media diversity and big data analytics. In line with this theorizing, we empirically test the synergistic effect of social media diversity and big data analytics by using a recent large-scale survey data set from 18,816 firms in Italy. We find that social media diversity and big data analytics have a positive interaction effect on market performance, which is more salient for SMEs than for large firms.     

Orchestrating big data analytics capability for sustainability: A study of air pollution management in China

Under rapid urbanization, cities are facing many societal challenges that impede sustainability. Big data analytics (BDA) gives cities unprecedented potential to address these issues. As BDA is still a new concept, there is limited knowledge on how to apply BDA in a sustainability context. Thus, this study investigates a case using BDA for sustainability, adopting the resource orchestration perspective. A process model is generated, which provides novel insights into three aspects: data resource orchestration, BDA capability development, and big data value creation. This study benefits both researchers and practitioners by contributing to theoretical developments as well as by providing practical insights.     

Business analytics and business value: A comparative case study

With growing adoption of business analytics, it is important for investing firms to understand how business value is created from investments. Studies in IT domain have highlighted how higher investment in technology may not bring more returns, rather how IT as an organizational capability acts as a key mediator in value creation. This research extends the model to business analytics, to identify elements of analytics technology assets and business analytics capability and to understand the mechanism of business value creation using multiple case studies. We capture how analytics resources contribute to business performance by developing operational and organizational performance measures.     

The role of information governance in big data analytics driven innovation

The age of big data analytics is now here, with companies increasingly investing in big data initiatives to foster innovation and outperform competition. Nevertheless, while researchers and practitioners started to examine the shifts that these technologies entail and their overall business value, it is still unclear whether and under what conditions they drive innovation. To address this gap, this study draws on the resource-based view (RBV) of the firm and information governance theory to explore the interplay between a firm’s big data analytics capabilities (BDACs) and their information governance practices in shaping innovation capabilities. We argue that a firm’s BDAC helps enhance two distinct types of innovative capabilities, incremental and radical capabilities, and that information governance positively moderates this relationship. To examine our research model, we analyzed survey data collected from 175 IT and business managers. Results from partial least squares structural equation modelling analysis reveal that BDACs have a positive and significant effect on both incremental and radical innovative capabilities. Our analysis also highlights the important role of information governance, as it positively moderates the relationship between BDAC’s and a firm’s radical innovative capability, while there is a nonsignificant moderating effect for incremental innovation capabilities. Finally, we examine the effect of environmental uncertainty conditions in our model and find that information governance and BDACs have amplified effects under conditions of high environmental dynamism.     

IT capabilities and firm performance: A contingency analysis of the role of industry and IT capability type

Previous empirical studies examining the relationship between IT capability and accounting-based measures of firm performance reported mixed results. We argued that prior work has relied on aggregate overall measures of the firm's IT capability, ignoring the specific type and nature of IT capability; and also has not fully considered important environmental conditions that influence the relationship. Drawing on a resource-based view, we advanced a contingency perspective and proposed that IT capabilities’ impact on firm resources was contingent on the “fit” between the type of IT capability/resource a firm possesses and the demands of the industry in which it competes. Specifically, using publicly available rankings as proxies for two types of IT capabilities (internally and externally focused), we empirically examined the degree to which three industry characteristics (dynamism, munificence, and complexity) influenced the impact of each type of IT capability on measures of financial performance. After controlling for prior performance, we found there was general support for the posited contingency model. The implications of these findings are also discussed.     

An integrated big data analytics-enabled transformation model: Application to health care

A big data analytics-enabled transformation model based on practice-based view is developed, which reveals the causal relationships among big data analytics capabilities, IT-enabled transformation practices, benefit dimensions, and business values. This model was then tested in healthcare setting. By analyzing big data implementation cases, we sought to understand how big data analytics capabilities transform organizational practices, thereby generating potential benefits. In addition to conceptually defining four big data analytics capabilities, the model offers a strategic view of big data analytics. Three significant path-to-value chains were identified for healthcare organizations by applying the model, which provides practical insights for managers.     

The promising future of healthcare services: When big data analytics meets wearable technology

As policy-makers and business practitioners across the globe expend extraordinary effort toward the field of e-health, the thriving development of healthcare-wearable technology is creating great opportunities and posing a remarkable future for healthcare services. This paper employs a game theory model to investigate the dynamics of wearable device market. We extend the two-dimensional product differentiation model by incorporating consumer diversity, consumer density, and firms’ big data analytics (BDA) investment strategy. Our model reveals that with differentiated consumer densities firms are more likely to engage in quality competition and the firm that invests in BDA can achieve higher profits. Furthermore, the overall quality of biomedical and healthcare services can be improved under various market conditions. Our findings provide practical guidance to wearable device manufacturers on optimizing competition strategies and offer insights to social planners on potential policy-making to promote better healthcare services.     

Optimizing the energy efficiency of chiller systems in the semiconductor industry through big data analytics and an empirical study

Big data analytics is playing a more and more prominent role in the manufacturing industry as corporations attempt to utilize vast amounts of data to optimize the operation of plants and factories to gain a competitive advantage. Since the advent of Industry 4.0, also known as smart manufacturing, big data analytics, combined with expert domain knowledge, is facilitating ever-greater levels of speed and automaticity in manufacturing processes. The semiconductor industry is a fundamental driver of this transformation; moreover, due to the highly complex and energy-consuming nature of the semiconductor manufacturing process, semiconductor fabrication facilities (fabs) can also benefit greatly from incorporating big data analytics to improve production and energy efficiency. This paper developed a big data analytics framework, along with an empirical study conducted in collaboration with a semiconductor manufacturer in Taiwan, to optimize the energy efficiency of chiller systems in semiconductor fabs. Chiller systems are one of the most energy-consuming systems within a typical modern fab. The developed big data analytics framework allows production managers to ensure that chiller systems operate at an optimized level of energy efficiency under dynamically changing conditions, while fulfilling the chilling demands. Compared to the commonly-used heuristics previously employed at the fab to tune chiller system parameters, by the utilization of big data analytics, it is shown that fabs can achieve substantial energy savings, greater than 12%. The developed framework and the lessons learned from the empirical study are not only generalizable but also useful for practitioners who are interested in applying big data analytics to optimize the performance of other equipment systems in fabs.     

Evolution of the impact of e-business technology on operational competence and firm profitability: A panel data investigation

This study examines the evolution of the impact of e-business technology on operational competence and profitability using a panel dataset of 154 Spanish firms. We find that (1) e-business technology has a positive effect on operational competence that decreases over time and (2) the firm’s proficiency in exploiting a portfolio of operational capabilities has a positive impact on profitability that becomes more substantial over time. The findings provide some insights on how the initial and subsequent IT investments affect operational competence and profitability over time. This study methodologically illustrates how to perform a partial least squares estimation using panel data.     

The dual role of IT capabilities in the development of digital products and services

Past research on the business value of information technologies (IT) has demonstrated the positive contribution of IT capabilities (IT-C) to product innovation performance. However, with the advent of digital technologies, a new kind of product innovations gained importance: digital product and service innovations (DPI). As a consequence of their idiosyncratic characteristics, the usefulness and validity of existing product innovation management concepts cannot be transferred to the context of DPI without further ado. Accordingly, this study reinvestigates the role of IT-C in the specific context of DPI. Therefore, we begin with a differentiation of DPI from traditional, non-digital product innovation. Then, we propose that IT-C affect the performance of DPI projects via two paths. First, based on the notion that DPI rely on the use of innovative IT, we assume that IT-C directly impact DPI performance. Second, following prior research that has argued that the performance contribution of IT-C is mediated by other organizational intermediaries, we assume that IT-C also indirectly contribute to DPI performance through their positive influence on other organizational capabilities. One such organizational capability that mediates the influence of IT-C on DPI performance is a firm’s DPI capabilities (DPI-C). DPI-C allow firms to deploy their digital resources for DPI purposes and, thus, are an important antecedent for DPI performance. To test our assumptions, we use partial least squares–structural equation modeling technique and analyze survey data collected from DPI projects across different industries in Germany, Austria, and Switzerland.     

Business analytics maturity of firms: an examination of the relationships between managerial perception of IT,business analytics maturity and success

This study develops a measure for business analytics (BA) maturity and empirically examines the relationships between managerial perception of IT, BA maturity and BA success. The findings suggest that (1) BA maturity can be measured via BA integration & management support, process-level benefits of BA and technology & data analytics capabilities, (2) BA maturity positively affects organizations’ overall BA success, and (3) managerial perception of IT positively influence organizations’ achievement of BA maturity.     

Business intelligence success: The roles of BI capabilities and decision environments

This study examines the role of the decision environment in how well business intelligence (BI) capabilities are leveraged to achieve BI success. We examine the decision environment in terms of the types of decisions made and the information processing needs of the organization. Our findings suggest that technological capabilities such as data quality, user access and the integration of BI with other systems are necessary for BI success, regardless of the decision environment. However, the decision environment does influence the relationship between BI success and capabilities, such as the extent to which BI supports flexibility and risk in decision making.     

Value co-creation between firms and customers: The role of big data-based cooperative assets

To better understand how big data interconnects firms and customers in promoting value co-creation, we propose a theoretical framework of big data-based cooperative assets based on evidence of multiple case studies. We identify four types of big data resources and four types of associated digital platforms, and we explore how firms develop the cooperative assets by transforming big data resources via the theoretical lens of service-dominant logic. This study offers a new theoretical perspective on value co-creation and an alternative competitive strategy in the era of big data for firms.