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

Identifying the Key Big Data Analytics Capabilities in Bangladesh’s Healthcare Sector

The study explores the crucial big data analytics capabilities (BDAC) for healthcare in Bangladesh. After a rigorous and extensive literature review, we list a wide range of BDAC and empirically examine their applicability in Bangladesh’s healthcare sector by consulting 51 experts with ample domain knowledge. The study adopted the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method. Findings highlighted 11 key BDAC, such as using advanced analytical techniques that could be critical in managing big data in the healthcare sector. The paper ends with a summary and puts forward suggestions for future studies

Hybrid Organizational Forms In Public Sector's Digital Transformation: A Technology Enactment Approach

The purpose of this paper is to examine how public sector organizations become nimbler while retaining their resilience during digital transformation. The study adopts a hermeneutic approach in conducting deep expert interviews with 22 senior executives and managers of multiple organizations. The method blends theory and expert views to study digital transformation in the context of enterprise information management. Drawing on Fountain’s (2001) Technology Enactment Framework (TEF), this research poses that organizational form is critical in the enactment of technologies in digital transformation. By extending TEF, we claim that organizations are not in pure bureaucratic or network organizational form during digital transformation; instead, they need a hybrid combination in order to support competing strategic needs for nimbleness and resilience simultaneously. The four hybrid organizational forms presented in our model (4R) allow for networks and bureaucracy to co-exist, though at different levels depending on the level of resiliency and nimbleness required at each point in the continuous digital transformation journey. The main theoretical contribution of this research is to extend TEF to illustrate that the need for co-existence of nimbleness with stability in a digital transformation, results in a hybrid of networks and bureaucratic organization forms. This research aims to guide public sector organizations’ digital transformation with extended TEF as a tool for building the required organizational forms to influence the technology enactment to best meet their strategic needs in the digital era. The results from expert interviews point to the fact that the hybrid organizational forms create a multi-modal organization, extending our understanding of enterprise information management. Depending on the department or business needs a hybrid organizational form mode would be dominant. This dominance creates a paradox in organizations to handle both resilience and nimbleness. Therefore, 4R model is provided as a guide to public sector managers and consultants to guide strutting their organization for digital transformation. text The model (4R), the extended TEF, shows that organizations still work towards networks and bureaucracy; however, they are not two distinct concepts anymore; they co-exist at different levels in hybrid forms depending on the needs of the organization

A Digital Tale of Two Cities—Observing the Dynamics of the Artificial Intelligence Ecosystems in Berlin and Sydney

In entrepreneurial ecosystems (EEs), geographical and contextual factors play a big role in shaping the knowledge bases for digital innovation. While cities around the world compete to be perceived as successful “tech startup hubs”, proactive urban strategies are needed to create knowledge spillovers into EEs. This study explores the evolution of artificial intelligence (AI) knowledge practices in the EEs of Berlin and Sydney by using knowledge-spillover theory of entrepreneurship. The study utilizes a bibliometric analysis of secondary data in combination with exploratory stakeholder interviews conducted for both cities. Findings underline the critical role of experimental knowledge in driving the momentum of the EEs and the supporting role of policies imprinting knowledge practices. The paper shows how the dynamics of EEs can be explored empirically and raises awareness of the role of specialised and integrated policies in determining a city’s overall success in building EEs

Unraveling the capabilities that enable digital transformation: A data-driven methodology and the case of artificial intelligence

Digital transformation (DT) is prevalent in businesses today. However, current studies to guide DT are mostly qualitative, resulting in a strong call for quantitative evidence of exactly what DT is and the capabilities needed to enable it successfully. With the aim of filling the gaps, this paper presents a novel bibliometric framework that unearths clues from scientific articles and patents. The framework incorporates the scientific evolutionary pathways and hierarchical topic tree to quantitatively identify the DT research topics’ evolutionary patterns and hierarchies at play in DT research. Our results include a comprehensive definition of DT from the perspective of bibliometrics and a systematic categorization of the capabilities required to enable DT, distilled from over 10,179 academic papers on DT. To further yield practical insights on technological capabilities, the paper also includes a case study of 9,454 patents focusing on one of the emerging technologies - artificial intelligence (AI). We summarized the outcomes with a four-level AI capabilities model. The paper ends with a discussion on its contributions: presenting a quantitative account of the DT research, introducing a process based understanding of DT, offering a list of major capabilities enabling DT, and drawing the attention of managers to be aware of capabilities needed when undertaking their DT journey

The Interplay among Organisational Learning Culture, Agility, Growth and Big Data Capabilities

This paper examines how an organisational learning culture impacts organisational agility by developing a model based on dynamic capabilities. The model treats agility as a dynamic capability and explains how an organisational learning culture (OLC) triggers a chain reaction through its influence on organisational agility (OA) that ultimately results in company growth. This paper also investigates the role of big data capabilities in transferring learning outcomes into dynamic capabilities. The model is tested through data collected from a survey of 138 Australian companies. Partial least squares structural equation modeling is adopted to empirically demonstrate how agility fully mediates the impact of the learning culture on growth. In addition, this paper further sheds light on the moderating role of big data competencies on the effects of OLC on OA. After presenting the results with implications to theory and practice, the paper ends with suggestions for future studies

The 4th Industrial Revolution and its Impact on Division of Labor in Developing Countries

Technological developments and automation have always been a hope and threat. Technological changes greatly affect employment opportunities and division of labor. It normally offer novel methods of producing and consuming goods and services, suggests rising living standards as well. It frees humans from dangerous, repetitive and boring works. On the other hand it has disruptive consequences for existing work practices and might result in substantial job losses. The recent technological breakthroughs build around the generation, processing and dissemination of information under the umbrella term of the 4th Industrial Revolution. There are two opposite views on the impact of the 4th Industrıal Revolution on labor. So far consequences of digital revolution discussed more with developed country perspective. This paper will focus on developing countries and try to investigate, how coming wave of automation will affect labor in developing world

Unlocking the Relationship between Corporate Entrepreneurship and Firm Performance

This paper explores the relationship between corporate entrepreneurship and performance by developing a comprehensive theoretical model based on Schumpeterian understanding of entrepreneurship supported with the Theory of Planned Behavior from social psychology. The model shows how organizational culture (value) triggers a chain effect through its influence on entrepreneurial orientation (attitude) and managerial support (intentions) that ultimately generate impact on corporate entrepreneurship (behavior). We test our model in an emerging economy context and present our results with implications to theory and practice