Business Analytics Capabilities Research Articles

Controllership effectiveness and digitalization: Shedding light on the importance of business analytics capabilities and the business partner role

Digital technologies and related capabilities, such as business analytics capabilities (BAC), are transforming firms and management control (MC). While the development of BAC and its underlying dimensions is currently a top priority for many MC departments, it remains unclear from the existing literature how they can benefit from these capabilities in terms of controllership effectiveness. Against this background, our study examines the relationships between three core BAC dimensions (tangible BA resources, intangible BA resources, and human skills for BA) and controllership effectiveness (in terms of controllership output quality and controllership impact on management decisions), with a particular focus on the mediating effects of the business partner role of the MC department. To do so, we adopt the resource-based view and use partial least squares structural equation modeling (PLS-SEM) to analyze survey data from 322 large German firms. The results of our study show that all of the examined relationships are positively mediated by the business partner role, while those between tangible BA resources and both elements of controllership effectiveness, as well as that between human skills for BA and controllership impact on management decisions are even fully mediated by this role. Thus, our results highlight the importance of the business partner role in enabling MC departments to benefit from the development of the BAC dimensions in terms of improved controllership effectiveness. Furthermore, through a series of post hoc analyses, we provide empirical support for our three-dimensional conceptualization of BAC, and for the importance of the business partner role relative to the still dominant scorekeeper role. Theoretical and practical implications are discussed.

Linking business analytics capability and sustainability performance: the mediating role of circular economy implementation

PurposeThough business analytics capability continues to attract considerable industrial and scholarly attention, its holistic performance implications, especially in the post-COVID-19 period, have not been fully understood. Thus, there have been calls for a full understanding of the implications of BAC for achieving holistic, sustainable outcomes among firms. This study therefore examines the influence of BAC on the three dimensions of sustainable performance. We also proposed the mediating role of circular economy implementation.Design/methodology/approachWe tested the proposed model using survey data from 246 managers of manufacturing firms in Ghana. Partial least squares structural equation modelling was employed to validate the model.FindingsOur findings showed that BAC significantly enhances both sustainable performance and circular economy implementation. We also found a significant association between CEI and sustainable performance. We further found significant partial mediation of CEI in the BAC sustainable performance nexus.Practical implicationsOur study offers thoughtful insights for managers, policymakers and the academic community that firms should simultaneously implement circular models alongside building analytics competencies in the quest to achieve balanced performance outcomes.Originality/valueTo the best of our knowledge, our study is among the very few attempts to understand the mechanism that channels the benefits of BAC for a holistic, sustainable outcome.

Decision making performance of business analytics capabilities: the role of big data literacy and analytics competency

PurposeThis study investigates the relationships between data governance (DG), business analytics capabilities (BAC), and decision-making performance (DMP), with a focus on the mediating effects of big data literacy (BDL) and data analytics competency (DAC).Design/methodology/approachThe study was conducted with 178 experienced managers in public service organizations, using a quantitative approach. Structural equation modeling (SEM) and mediation tests were employed to analyze the data.FindingsThe findings reveal that DG and BDL are critical antecedents for developing analytical capabilities. Big data literacy mediates the relationship between DG and BAC, while BAC mediates the relationship between DG and DMP. Furthermore, DAC mediates the relationship between BA capabilities and DMP, explaining most of the effect of BAC on DMP.Practical implicationsThese results highlight the importance of DG in fostering BDL and analytical skills for improved decision-making in organizations.Originality/valueBy prioritizing DG practices that promote BDL and analytical capabilities, organizations can leverage business analytics to enhance decision-making.

Retail Platform Analytics: Practice, Literature, and Future Research

The explosive growth of retail platforms over the past decade has resulted in a significant amount of customer and seller data that can be leveraged for advanced business analytics. As a result, the management of retail platforms with business analytics capabilities has garnered increased attention in the field of operations management. Despite the recognition of the importance of business analytics techniques for retail platforms, a systematic study of their operations is lacking in the literature. Based on our observations of the industrial practice and understanding of the academic literature, we attempt to address this gap by proposing a framework that broadly categorizes retail platform management into three key themes: demand-side management, supply-side management, and matching. For each theme, we identify critical topics, discuss the current practices of platforms, and review relevant literature. We also propose future research questions with directions for the initial modeling and solution strategy, together with applicable data sources and potential insights. At last, to facilitate future research, we provide a roadmap and datasets for further exploration of business analytics applications of retail platforms. Overall, this paper lays a strong foundation for researchers to delve deeper into the exciting and constantly evolving field of retail platform analytics.

Exploring the complementary effects of business analytics capabilities and π-shaped skills on innovation outcomes

ABSTRACT While it is clear that business analytics (BA), on average, adds value to firms, it is less clear why some firms perform better than others in leveraging their data assets. To a large degree, prior research has attributed such differences to the human factor. Nevertheless, there is still limited knowledge concerning what impact competencies of key personnel have on generating value from BA initiatives, and to what extent such outcomes complement a firm’s investment in BA. To examine these questions, this study explores the complementary relationship between BA capabilities and π-shaped skills. It posits that the concurrent presence of both indirectly influences innovation outcomes by fostering a data-driven culture. We build on a sample of 185 individuals with supervisory positions in Turkey to unpack this process. The findings revealed that BA capabilities and π-shaped skills influence a firm’s data-driven culture, which in turn impacts the firms’ marketing innovation, and subsequently its innovative performance. That is, data-driven culture and firms’ marketing innovation are relevant underlying serial mechanisms by which BA capabilities and π-shaped skills influence innovative performance.

Business analytics capabilities in digitally-enabled and non-digitally-enabled companies in an emerging economy

The excess of data has led industries to develop their capabilities to exploit the value of data and gain competitive advantage. In this context, business analysis has become substantive for this purpose in several domains. Surprisingly, business analytics has been at the top of the corporate agenda. While the potential benefits of business analytics are widely highlighted in cutting-edge literature, little is known about the prominence of analytics capabilities for business resilience during and after the COVID 19 pandemic (new normal) in emerging markets. This study examines the relevance of business analytics capabilities to the resilience and economic performance of digitally-enabled and non-digitally enabled companies in an emerging economy. Using a questionnaire, primary data was collected from digitally enabled national and multinational companies in the Brazilian context. The results of this study suggest that analytical capabilities are substantive to the resilience of digitally enabled multinational companies, with an emphasis on tangible, human and operational capabilities. This study fills a gap in the literature and makes significant contributions: (i) it highlights the protagonism of business analytical capabilities in digitally enabled multinational companies, during and after the COVID 19 pandemic in an emerging economy; (ii) serves as a guide for managers when choosing capabilities; (iii) sheds light on non-digitally enabled national companies to achieve resilience in their businesses in times of crises such as the COVID 19 pandemic; and (iv) expands the literature on business analytical capabilities..

공급사슬네트워크에서 비즈니스 애널리틱스의 영향에 관한 연구

The purpose of this study is to empirically investigate the relationship between organizational business analytics capability and supply chain performance in order to identify the impact of business analytics in supply chain network. Specifically, drawing on literature streams in Supply Chain Operations Reference Model and Information Processing Theory, this study conceptualizes the notion of business analytics capability in supply chain network, develops its structure as a reflective model, and tests the constructs and operational measures in the model. And then this study investigates the relationship between analytics capabilities in the plan, source, make and deliver area of the supply chain network and its performance using business process orientation and information system support as moderators that form the basis of our theory. Conducting an empirical study of 170 Korean manufacturing firms, this study, through the successive stages of measurement model analysis, provides empirical evidence for modeling reflective indicator and construct of business analytics capability in supply chain network. As a result, the construct of business analytics capability is posited to reflect a combination through analytics capabilities in the plan, source, make and deliver area of the supply chain network. And the findings suggest the existence of a statistically significant relationship between business analytics capabilities and supply chain performance. The moderation effect of information systems support is considerably stronger than the effect of business process orientation. These findings provide a better understanding of the areas in supply chain network where the impact of business analytics may be the strongest.

EXAMINING THE ROLE OF BUSINESS ANALYTICS CAPABILITY IN FIRMS' AGILITY & PERFORMANCE: EVIDENCE FROM MANUFACTURING SECTOR

The purpose of study is to analyze empirically effect of Business Analytics Capability (BAC) on agility and performance of firms by focusing on role of Information Quality (IQ) and Innovative Capability (IC). The research was conducted using a quantitative research design focusing on workers in manufacturing sector in Pakistan. The data attained from a sample of 350 managerial-level workers in Lahore by means of structured questionnaire survey supports the significant positive relationship between BAC & both FA and FPP. The study reveals the strong and positive relationship between IQ & firms’ adaptability, productivity and significant and positive impact of innovative capability on organizations’ agility and efficiency. The study emphasizes complexity of factors critical for organizational success within organizational context. The significance of results extends beyond reach of study, providing relevant insights into academic and professional contexts. The existing theoretical frameworks can be strengthened by adding these aforementioned antecedents and managers should exploit this opportunity in order to improve organizational agility and performance in the dynamic manufacturing environment.

Unlocking agility: Trapped in the antagonism between co-innovation in digital platforms, business analytics capability and external pressure for AI adoption?

PurposeDigital technology is increasingly important in enhancing organizational agility (OA). Institutional theory and resource-based view were harmonized to analyze firms' adoption of digital technologies. However, previous studies on OA have revealed that external pressures imply the imposition of barriers or technological standards that ultimately restrict OA. This study employs this double theoretical lens to investigate the mediation role of business analytics capability (BAC) in the relationship between co-innovation (CO), i.e. open innovation in digital platforms, and OA, as well as the negative moderating effect of external pressure for artificial intelligence adoption (EPAIA) on this mediation.Design/methodology/approachStructural equation modeling was used to test the moderated mediation with survey data from 229 firms.FindingsThe main result indicates that 72% of OA variance is explained by the effect of CO that is transmitted by the mediator (BAC). However, contrary to the authors' expectations, EPAIA only has a positive moderating effect along the path between BAC and OA.Originality/valueThis work contradicts the prevalent notion of the negative consequences of external pressures for artificial intelligence adoption. Specifically, this study's findings refute the notion that institutional pressures are the source of technical problems that disrupt CO and BAC integration and reduce OA. In contrast, the unexpectedly positive effect of EPAIA may indicate that this type of external pressure can be viewed as a significant sign and an opportunity for the company to adopt the industry's most advanced and effective digital transformation practices.

Business Analytics Capabilities and Decision Quality: The Mediating Roles of Decision Speed and Comprehensiveness

ABSTRACT This paper examines the nexus between business analytics and strategic decision facets using the resource-based theory. Analysis with partial least squares demonstrate that decision comprehensiveness and speed mediate the relationship between business analytics and decision quality. While fuzzy sets analysis demonstrates that business analytics, decision comprehensiveness, and speed are sufficient (but not necessary) conditions for decision quality. When firms utilize business analytics, decision speed and comprehensiveness are mutually inclusive. Theoretical and practical implications are offered.

The Nexus between Business Analytics Capabilities and Knowledge Orientation in Driving Business Model Innovation: The Moderating Role of Industry Type

The importance of business analytics (BA) in driving knowledge generation and business innovation has been widely discussed in both the academic and business communities. However, empirical research on the relationship between knowledge orientation and business analytics capabilities in driving business model innovation remains scarce. Drawing on the knowledge-based view and dynamic capabilities theory, this study develops a model to investigate the interplay between knowledge orientation and BA capabilities in driving business model innovation. It also explores the moderating role of industry type on this relationship. To test the model, data were collected from a cross-sectional sample of 207 firms (high-tech and non-high-tech industries). Descriptive and structural equation modeling (SEM) were used to test the hypotheses. The findings showed that knowledge orientation and BA capabilities are significantly and positively related to business model innovation. Knowledge commitment, shared vision, and open-mindedness are significantly and positively related to BA perception and recognition capabilities and BA integration capabilities. BA capabilities mediated the relationship between knowledge orientation and business model innovation. The path mechanism of knowledge orientation → BA capabilities → business model innovation shows that industry type has a moderating effect on knowledge orientation and BA capabilities, as well as BA capabilities and business model innovation. This study provides empirically proven insights and practical guidance on the dynamics and mechanisms of BA and organizational knowledge capabilities and their impact on business model innovation.

Boosting Innovation Performance through Business Analytics Capabilities under Different Levels of Turbulence: The Crucial Role of Market Agility

Considerable resources were invested by many businesses in developing business analytics capabilities to enhance their performance. Previous research revealed that business analytics capabilities can influence business performance in various methods. Our study seeks to examine the influence of business analytics capabilities on innovation performance through market agility. We also explore these relationships under different turbulent environment. Data were collected from 427 managers in the food industry in Saudi Arabia. Structural equation modelling was used to analyze the collected data. The findings indicated that business analytics capabilities have direct and indirect influence on innovation performance. Market agility partially mediates the link between business analytics capabilities and innovation performance. This relationship is stronger in high turbulent environment. Our study provides meaningful theoretical contributions to business analytics and market agility literature and practical implications for managers in the food sector.

The impact of business analytics capabilities on innovation, information quality, agility and firm performance: the moderating role of industry dynamism

PurposeAs businesses keep investing substantial resources in developing business analytics (BA) capabilities, it is unclear how the performance improvement transpires as BA affects performance in many different ways. This paper aims to analyze how BA capabilities affect firms’ agility through resources like information quality and innovative capacity considering industry dynamism and the resulting impact on firm performance.Design/methodology/approachThis paper tested the research hypothesis using primary data collected from 192 companies operating in Bangladesh. The data were analyzed using partial least squares-based structural equation modeling.FindingsThe results indicate that BA capabilities improve business resources like information quality and innovative capacity, which, in turn, significantly impact a firm’s agility. This paper also found out that industry dynamism moderates the firms’ agility and, ultimately, firms’ performance.Practical implicationsThe contribution of this work provides insight regarding the role of business analytics capabilities in increasing organizational agility and performance under the moderating effects of industry dynamism.Originality/valueThe present research is to the best of the authors’ knowledge among the first studies considering a firm’s agility to explore the impact of BA on a firm’s performance in a dynamic environment. While previous researchers discussed resources like information quality and innovative capability, current research theoretically argues that these items are a leveraging point in a BA context to increase firm agility.

Impact of business analytics and π-shaped skills on innovative performance: Findings from PLS-SEM and fsQCA

This paper proposes that the relationship between business analytics and innovative performance is somewhat more complex than originally thought, as firms still struggle to leverage the benefits of business analytics and artificial intelligence capabilities. To expand on the scholarship in this area of knowledge, our paper cross-fertilizes the literature by amalgamating business analytics capabilities with π-shaped skills. We draw on resource orchestration theory to examine the effects of business analytics and π-shaped skills on a firm's innovative performance, and the moderating role of π-shaped skills. Field data (n = 450) were obtained from individuals with supervisory positions in large Saudi firms and SMEs and analyzed with PLS-SEM and fsQCA techniques. PLS-SEM results reveal that business analytics and π-shaped skills are relevant antecedents for innovative performance. However, the expected moderating role of π-shaped skills on the relationship between business analytics and innovative performance did not hold. FsQCA results reveal that business analytics and π-shaped skills are sufficient but not necessary conditions for high innovative performance. This paper contributes not only to empirical evidence, but also to theory by furthering our understanding of the emergent π-shaped skills concept. Our findings echo the need to expand inquiry into business analytics and skill sets capabilities for better innovative outputs. Implications for theory and practice are discussed.

COVID-19 Pandemic and Research on the Mediating Role of Absorptive Capacity on the Relationship between Business Analytics Capability and Small-to-Medium-Sized Enterprise Performance

This initial study's key purpose was to investigate whether absorptive capacity performed a mediating role on the relationship between business analytics capability and small-to-medium-sized enterprises (SMEs) performance in the United States. The study's findings are more relevant now as the COVID-19 pandemic continues to impact small-to-medium-sized enterprise (SME) businesses in the United States. The study derived from the resource-based view approach, the dynamic capabilities dimension perspective, through the theoretical lens of the reconceptualization of absorptive capacity by Zahra and George (2002). The study empirically tested mediation through a series of regressions based on Baron and Kenny (1996). As recent extensions of the resource-based view theory, absorptive capacity and business analytics embody the dynamic capabilities, business intelligence, and knowledge management for modern business firms to align, modify, and reconfigure during a dynamic and volatile global business environment. Throughout the pandemic, it appears businesses have had to continually regain economic ground. This paper is an effort to apply the findings of research on the importance of absorptive capacity and business analytics capability as it pertains to the reality of the COVID-19 pandemic on SMEs. The study contributed to the theoretical body of knowledge on dynamic capabilities by empirically demonstrating how SMEs may manifest improvement in performance in the twenty-first century by utilizing data in collaboration with business analytics at the realized absorptive capacity dimension. In wake of the ongoing COVID-19 pandemic, exploring the research study's findings may provide insight to help SMEs survive during these difficult times, and even thrive, by increasing their absorptive capacity to utilize data analytics effectively.
 Keywords: Resource-Based View, Absorptive Capacity, Business Analytics, Dynamic Capabilities, Information Technology, Small-To-Medium-Sized Enterprise (SME), COVID-19

The impact of business analytics capability on data-driven culture and exploration: achieving a competitive advantage

PurposeIn today's business setting, the business analytic capability, data-driven culture and product development features are highly pronounced in light of the firm's competitive advantage. Though widespread attention has been given to the above concepts, there hasn't been much research done on how it could support achieving competitive advantage.Design/methodology/approachThis research strongly lies on the theoretical background and empirically tests the hypothesized relationships. The primary survey of 272 responses was analysed by using the partial least squares structural equation modelling (PLS-SEM).FindingsThe findings of this study show a significant relationship for the constructs in the research model except for the third hypothesis. Accordingly, the firm's data-driven culture does not have a significant impact on new product newness.Originality/valueThis study empirically tests the business analytics capability, data-driven culture, and new product development features in the context of a firm's competitive advantage. The findings of this study contribute to the theoretical, practical and managerial aspects of this field.

Towards a business analytics capability for the circular economy

Digital technologies are growing in importance for accelerating firms’ circular economy transition. However, so far, the focus has primarily been on the technical aspects of implementing these technologies with limited research on the organizational resources and capabilities required for successfully leveraging digital technologies for circular economy. To address this gap, this paper explores the business analytics resources firms should develop and how these should be orchestrated towards a firm-wide capability. The paper proposes a conceptual model highlighting eight business analytics resources that, in combination, build a business analytics capability for the circular economy and how this relates to firms’ circular economy implementation, resource orchestration capability, and competitive performance. The model is based on the results of a thematic analysis of 15 semi-structured expert interviews with key positions in industry. Our approach is informed by and further develops, the theory of the resource-based view and the resource orchestration view. Based on the results, we develop a deeper understanding of the importance of taking a holistic approach to business analytics when leveraging data and analytics towards a more efficient and effective digital-enabled circular economy, the smart circular economy.

The effects of business analytics capability on circular economy implementation, resource orchestration capability, and firm performance

Today, most organizations are undergoing a digital transformation. At the same time, the gravity of environmental issues has put sustainability and the circular economy at the top of corporate agendas. To this end, information systems, in particular business analytics, are being highlighted as essential enablers of an accelerated circular economy transition. However, effectively managing this joint transformation is a challenge. Firms struggle to identify which organizational resources they should target and how those should be leveraged towards a firm-wide business analytics capability for circular economy. To address these questions, this study draws on recent literature dealing with smart circular economy and business analytics capabilities along with the resource-based and resource orchestration view to (1) create an instrument to measure firms’ business analytics capability for circular economy, and (2) examine the relationship among a circular economy-specific business analytics capability, circular economy implementation, resource orchestration capability, and firm performance. The proposed research model was tested using partial least squares structural equation modeling of survey data from 125 top-level managers at companies across Europe. The results show that firms with a strong business analytics capability have an increased resource orchestration capability and a greater ability to excel in the circular economy, resulting in improved organizational performance in building a more sustainable competitive advantage in an increasingly competitive business landscape. The effect of business analytics capability on firm performance is not direct but fully mediated through resource orchestration capability and circular economy implementation. The results empirically validate the proposed research model and offer pathways to future information systems research streams to support the operationalization of circular strategies. The study provides the first empirical evidence of a business analytics capability for circular economy and its effect on firm performance.

The Role of Business Capabilities in Supporting Organization Agility and Performance During the COVID-19 Pandemic: An Empirical Study in Indonesia

This study aims to analyze the important role of business analytics capability, information quality, and innovation capability in influencing organization agility and organization performance during the Covid-19 pandemic. Data was collected from 76 companies from various sectors in Indonesia. Structural Equation Model-Partial Least Square (SEM-PLS) analysis was conducted to analyze the relationship between variables and test a series of hypotheses. Importance-Performance Matrix Analysis (IPMA), a useful analysis approach in PLS-SEM, is used, which extends the results of the estimated path coefficient (importance) by adding a dimension that considers the average values of the latent variable scores (performance). The IPMA approach examines not only the performance of an item but also the importance of that item. The results show that business analytics capability has a significant effect on information quality and innovation capability which then affects organization agility. Organizational performance is influenced by organizational agility. IPMA results show that organizational agility has the highest level of impact on organizational performance. This study will assist companies in planning business analytics, improving information quality, increasing innovation capability, and ultimately increasing agility and performance during the Covid-19 pandemic. This study will add to existing knowledge about previous literature, especially in the Covid-19 pandemic situation.

How does business analytics contribute to organisational performance and business value? A resource-based view

PurposeThe purpose of this article is to identify how the organisations are able to improve their business value through acquisition of business analytics capabilities and by improving their performance.Design/methodology/approachWith the help of literature survey, along with standard resource-based view framework, a conceptual model has been developed. These have been statistically tested by collecting the data using the survey questionnaire from 306 selected respondents from various service sector- and product-based organisations in India. To analyse the data we have used partial least square–based structural equation modelling.FindingsThe study highlights that by the help of data acquisition and tool acquisition as two vital components the acquisition of business analytics capabilities could improve the business value of the organisation by strengthening its organisational performance. The findings of this research also indicated that acquisition of business analytics capabilities has a significant influence on an organisation's business process performance and business decision, which in turn significantly influences organisational performance. And organisational performance eventually positively influences its business value. The model was found to provide an explanative power of 71%.Research limitations/implicationsThe proposed research model can provide effective recommendations to the management of the organisations to realise the importance of acquisition of effective business analytics capabilities to eventually improve the business value of the organisation.Originality/valueNo specific studies, as yet, have analysed the effects of acquisition of business analytics capabilities for improving organisational performance mediated through business process performance and business decision. Therefore, this research has explored the distinctive effort to empirically validate this understanding.