Disciplined autonomy: How business analytics complements customer involvement for digital innovation

The rise of big data and the fluid boundaries of digital products are driving companies to use business analytics (BA) to power their customer involvement. The complementarity view offers unique competence to generate value from BA because capability complementarity is less likely to be replicated or imitated. Unlike prior studies on BA-enabled value realization, our research investigates the interactions of BA and customer involvement capabilities using the complementarity view. We tested our model using data collected from 317 IT companies in China. Our results suggest that BA value realization requires both a top-down mechanism in which BA skills provide global guidance for alignment with a company’s goals and a bottom-up mechanism in which BA culture empowers local autonomy for adaptation to ever-changing needs. Our BA-complemented mechanisms provide research and practice with a way to concurrently use BA and customer involvement capabilities to address the duality of digital innovation. We further suggest that BA skills are necessary but insufficient for digital innovation because BA culture demonstrates a stronger effect in complementing organizations’ existing capabilities than BA skills do.     

Creating business value with process mining

Information systems research has a long-standing interest in how organizations gain value through information technology. In this article, we investigate a business process intelligence (BPI) technology that is receiving increasing interest in research and practice: process mining. Process mining uses digital trace data to visualize and measure the performance of business processes in order to inform managerial actions. While process mining has received tremendous uptake in practice, it is unknown how organizations use it to generate business value. We present the results of a multiple case study with key stakeholders from eight internationally operating companies. We identify key features of process mining – data & connectivity, process visualization, and process analytics – and show how they translate into a set of affordances that enable value creation. Specifically, process mining affords (1) perceiving end-to-end process visualizations and performance indicators, (2) sense-making of process-related information, (3) data-driven decision making, and (4) implementing interventions. Value is realized, in turn, in the form of process efficiency, monetary gains, and non-monetary gains, such as customer satisfaction. Our findings have implications for the discourse on IT value creation as we show how process mining constitutes a new class of business intelligence & analytics (BI&A) technology, that enables behavioral visibility and allows organizations to make evidence-based decisions about their business processes.     

Business analytics in supply chains - The contingent effect of business process maturity

The paper analyzes the effect of the use of business analytics on supply chain performance. It investigates the changing information processing needs at different supply chain process maturity levels. The effects of analytics in each Supply Chain Operations Reference areas (Plan, Source, Make and Deliver) are analyzed with various statistical techniques. A worldwide sample of 788 companies from different industries is used. The results indicate the changing impact of business analytics use on performance, meaning that companies on different maturity levels should focus on different areas. The theoretical and practical implications of these findings are thoroughly discussed.     

Impacts of essential elements of management on IT application maturity — A perspective from firms in China

This paper explores the impacts of essential elements of management on IT application maturity (ITAM). A game theoretical model is established to show that a firm's IT application maturity should match with its essential elements of management. In order to further validate the analytical result, a data set with 137 firms was collected via a survey instrument. Using reliability and factor analysis on the dataset, a four-dimension measurement construct of IT application maturity is proposed together with a three-dimension measurement construct of essential elements of management. Empirical analysis is then conducted to address research questions on the impacts of essential elements of management on IT application maturity. It is found that while a firm's strategic cooperation capability has no significant effect on IT application maturity, its internal coordination capability positively influences all four dimensions of IT application maturity. For the firm's execution capability, although it shows no significant effect on the overall IT application maturity, it does positively affect the technology and man-machine synergy dimensions of IT application maturity. The findings of this study offer practical guidance for organizations to better align their IT application maturity with essential elements of management.     

An exploration of the relationship between software development process maturity and project performance

Software projects have a high rate of failure. Organizations have tried to reduce the rate through methodological approaches but with little perceived success. A model of software development maturity (the capability maturity model (CMM)) describes managerial processes that can be used to attack software development difficulties from the managerial control perspective at five maturity levels. Our study examined performance of projects in relation to the activities at these various levels of maturity. A survey of software engineers indicated that the activities associated with the managerial control of development related positively to project performance measures. However, not each level of maturity demonstrated observable benefits, indicating that greater caution is needed in the planning and implementation of the activities.     

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.     

Scalable aggregation predictive analytics

We introduce a predictive modeling solution that provides high quality predictive analytics over aggregation queries in Big Data environments. Our predictive methodology is generally applicable in environments in which large-scale data owners may or may not restrict access to their data and allow only aggregation operators like COUNT to be executed over their data. In this context, our methodology is based on historical queries and their answers to accurately predict ad-hoc queries’ answers. We focus on the widely used set-cardinality, i.e., COUNT, aggregation query, as COUNT is a fundamental operator for both internal data system optimizations and for aggregation-oriented data exploration and predictive analytics. We contribute a novel, query-driven Machine Learning (ML) model whose goals are to: (i) learn the query-answer space from past issued queries, (ii) associate the query space with local linear regression & associative function estimators, (iii) define query similarity, and (iv) predict the cardinality of the answer set of unseen incoming queries, referred to the Set Cardinality Prediction (SCP) problem. Our ML model incorporates incremental ML algorithms for ensuring high quality prediction results. The significance of contribution lies in that it (i) is the only query-driven solution applicable over general Big Data environments, which include restricted-access data, (ii) offers incremental learning adjusted for arriving ad-hoc queries, which is well suited for query-driven data exploration, and (iii) offers a performance (in terms of scalability, SCP accuracy, processing time, and memory requirements) that is superior to data-centric approaches. We provide a comprehensive performance evaluation of our model evaluating its sensitivity, scalability and efficiency for quality predictive analytics. In addition, we report on the development and incorporation of our ML model in Spark showing its superior performance compared to the Spark’s COUNT method.     

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.     

Quantifying the impact of requirements definition and management process maturity on project outcome in large business application development

Using data from two surveys of people knowledgeable about requirements for, and the success of the development of, large commercial applications (CAs) in hundreds of large organizations from around the world, this paper reports a high positive correlation between an organization’s requirements definition and management (RDM) maturity and that organization’s successful performance on CA development projects. Among the organizations that responded with a filled survey, an organization that is assessed at a high RDM maturity is significantly more successful in its CA development projects than is an organization that is assessed at a low RDM maturity, when success in CA development projects is measured as (1) delivering CAs on-time, on-budget, and on-function, (2) meeting the business objectives of these projects, and (3) the perceived success of these projects. This paper presents a comprehensive framework for RDM, describes a quality RDM process, and describes RDM maturity and how to measure it. It describes the two surveys, the first of which ended up being a pilot for the second, which was designed taking into account what was learned from the first survey. The paper concludes with advice to practitioners on the application of the RDM maturity framework in any organization that wishes to improve its RDM and its performance in the development of large CAs.     

Harnessing business analytics value through organizational absorptive capacity

Business analytics (BA) is a resource-intensive, risky endeavor. However, the literature has not addressed the important question of how to assimilate BA technologies for competitive advantage. We build a research framework and outline the BA assimilation mechanisms through organizational absorptive capacity (AC). Data were collected from 600 companies across six countries and analyzed using partial least squares. The findings revealed that organizational AC plays a crucial mediating role between BA competency and BA assimilation, leading to competitive advantage. This study contributes significantly to both information technology assimilation and BA value research by incorporating the role of organizational AC.     

It governance in the public sector: a conceptual model

Information technology governance (ITG) has been identified as an organizational ability of great importance for IT strategic alignment and the delivery of business though IT. However, the results and contribution of ITG are poorly understood. This work presents an explanatory model of the effects of IT governance mechanisms on IT and organizational performance of public organizations. To test the model, data was collected from a survey conducted in 146 Brazilian public organizations. Partial least squares analysis was applied to test the proposed model. The results indicate that (i) IT performance is positively correlated with organizational performance, (ii) relational mechanisms between IT and a business are determinant factors for the performance of IT, and also positively correlated with organizational performance, and (iii), decision structure and process maturity are not significantly correlated with IT performance.     

Investigating the role of an enterprise architecture project in the business-IT alignment in Iran

Ensuring that IT and business have a more mature alignment relationship is recognized as being critical to an organization’s success. To achieve alignment leveraging, enterprise architecture (EA) is considered fundamental as a comprehensive approach to planning and managing IT actions within the organization, based on its business requirements. This paper reports on a study to assess the effect of successful EA projects on the business-IT alignment in Iranian organizations, using the Luftman’s maturity model as the assessment tool. The implications of our findings in this study as well as its limitations are discussed to assist in detecting the flaws in the existing EA frameworks and to propose improvements.     

Advanced machine learning approaches to personalise learning: learning analytics and decision making

The aim of the paper is to present methodology to personalise learning using learning analytics and to make further decisions on suitability, acceptance and use of personalised learning units. In the paper, first of all, related research review is presented. Further, an original methodology to personalise learning applying learning analytics in virtual learning environments and empirical research results are presented. Using this learning personalisation methodology, decision-making model and method are proposed to evaluate suitability, acceptance and use of personalised learning units. Personalised learning units evaluation methodology presented in the paper is based on (1) well-known principles of Multiple Criteria Decision Analysis for identifying evaluation criteria; (2) Educational Technology Acceptance & Satisfaction Model (ETAS-M) based on well-known Unified Theory on Acceptance and Use of Technology (UTAUT) model, and (3) probabilistic suitability indexes to identify learning components’ suitability to particular students’ needs according to their learning styles. In the paper, there are also examples of implementing the methodology using different weights of evaluation criteria. This methodology is applicable in real life situations where teachers have to help students to create and apply learning units that are most suitable for their needs and thus to improve education quality and efficiency.     

Information technology and new organizational forms: choosing chaos over panaceas

This paper examines five aspects of the critical relationship between information technology (IT) and new emergent forms of organizations. First, there appears to be an unhealthy tendency among IT professionals to elevate any single, highly successful practical experience instantly into an overarching paradigm for managerial success. Second, there is a corresponding tendency for IT researchers to focus their efforts on the search for the single universal formula that will transform any type of organization in any situation from mediocrity to excellence. Third, IT researchers assign a pre-eminence to IT in organizational transformation that neglects many other important social and environmental factors. Fourth, management theorists seem unable to cope with the unpredictability, the multivariate nature and the ‘messiness’ of human organizations in cultural contexts. Even studies that make qualitative allowances will still imply a surreal causal analysis that is mostly speculation. Fifth, several critical factors influence the interaction of changes in IT and emergent organizational forms: these include organizational learning, structural premise and power.     

How to improve the assessment of BPM maturity in the era of digital transformation

For almost 30 years, the way of building business process management maturity models (BPM MMs), the importance assigned to individual maturity levels, and the criteria and critical success factors chosen for BPM maturity assessment have not changed significantly, despite the fact that during those three decades, the business environment and organizations themselves have changed enormously. The impact of hyperautomation and the increasing pace of change require the integration of maturity assessment with the BPM implementation methodology, including the repetition of maturity assessment for selected groups of processes. This causes an urgent need to adapt both process maturity assessment methods and BPM MMs to changing working conditions and business requirements. This conceptual paper is based on a model approach. The framework presented in the article continues and at the same time clearly deviates from the tradition of building BPM MMs on the basis of the Capability Maturity Model (CMM). It proposes a two-stage comprehensive process of organizational process maturity assessment, fully integrated into the process of BPM implementation and further business process management. The presented framework makes it possible to assess the process maturity of Industry 4.0 organizations in which dynamic knowledge-intensive business processes (kiBPs) play a key role in creating value.

     

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.     

Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities

A central question for information systems (IS) researchers and practitioners is if, and how, big data can help attain a competitive advantage. To address this question, this study draws on the resource-based view, dynamic capabilities view, and on recent literature on big data analytics, and examines the indirect relationship between a firm’s big data analytics capability (BDAC) and competitive performance. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which, in turn, positively impact marketing and technological capabilities. To test our proposed research model, we used survey data from 202 chief information officers and IT managers working in Norwegian firms. By means of partial least squares structural equation modeling, results show that a strong BDAC can help firms build a competitive advantage. This effect is not direct but fully mediated by dynamic capabilities, which exerts a positive and significant effect on two types of operational capabilities: marketing and technological capabilities. The findings suggest that IS researchers should look beyond direct effects of big data investments and shift their attention on how a BDAC can be leveraged to enable and support organizational capabilities.     

E-government adoption in public administration organizations: integrating institutional theory perspective and resource-based view

We develop and test a theoretical model to investigate the adoption of government-to-government (G2G) information systems in public administration organizations. Specifically, this model explains how top management commitment (TMC) mediates the impact of external institutional pressures on internal organizational resource allocation, which finally leads to the adoption decision. The hypotheses were tested using survey data from public administration organizations in China. Results from partial least squares analyses suggest that coercive and normative pressures positively affect TMC, which then positively affects financial and information technology (IT) human resources in the G2G adoption process. In turn, financial and IT human resources are confirmed to positively affect the intention to adopt G2G. Surprisingly, we do not find support for our hypothesis that mimetic pressures directly influence TMC. Rather, a post hoc analysis implies that mimetic pressures indirectly influence TMC via the influence of coercive pressures. Our findings provide important managerial implications for public administration organizations.