The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Thanos Papadopoulos - One of the best experts on this subject based on the ideXlab platform.
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big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. The literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource‐based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre‐tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under the moderating effect of big data culture and their utilization for capability building, and how this capability affects cost and operational performance.
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big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. Literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource-based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills, and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre-tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under moderating effect of big data culture and their utilisation for capability building, and how this capability affects cost and operational performance.
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impact of big data Predictive Analytics capability on supply chain sustainability
The International Journal of Logistics Management, 2018Co-Authors: Shirish Jeble, David Roubaud, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Anand PrakashAbstract:The purpose of this paper is to develop a theoretical model to explain the impact of big data and Predictive Analytics (BDPA) on sustainable business development goal of the organization.,The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.,The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support for H4. Although the authors did not find support for H4 (moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.,This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.
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Can big data and Predictive Analytics improve social and environmental sustainability?
Technological Forecasting and Social Change, 2017Co-Authors: Rameshwar Dubey, Stephen J Childe, Zongwei Luo, Angappa Gunasekaran, Thanos Papadopoulos, Samuel Fosso Wamba, David RoubaudAbstract:Although literature indicates that big data and Predictive Analytics (BDPA) convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions (inter alia, national context and culture, and firm size). Grounding our investigation in the dynamic capability views and organisational culture and based on a sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP) and environmental performance (EP) using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains.
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big data and Predictive Analytics for supply chain and organizational performance
Journal of Business Research, 2017Co-Authors: Angappa Gunasekaran, Benjamin T Hazen, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Samuel Fosso Wamba, Shahriar AkterAbstract:Scholars acknowledge the importance of big data and Predictive Analytics (BDPA) in achieving business value and firm performance. However, the impact of BDPA assimilation on supply chain (SCP) and organizational performance (OP) has not been thoroughly investigated. To address this gap, this paper draws on resource-based view. It conceptualizes assimilation as a three stage process (acceptance, routinization, and assimilation) and identifies the influence of resources (connectivity and information sharing) under the mediation effect of top management commitment on big data assimilation (capability), SCP and OP. The findings suggest that connectivity and information sharing under the mediation effect of top management commitment are positively related to BDPA acceptance, which is positively related to BDPA assimilation under the mediation effect of BDPA routinization, and positively related to SCP and OP. Limitations and future research directions are provided.
Rameshwar Dubey - One of the best experts on this subject based on the ideXlab platform.
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big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. The literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource‐based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre‐tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under the moderating effect of big data culture and their utilization for capability building, and how this capability affects cost and operational performance.
-
big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. Literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource-based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills, and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre-tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under moderating effect of big data culture and their utilisation for capability building, and how this capability affects cost and operational performance.
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impact of big data Predictive Analytics capability on supply chain sustainability
The International Journal of Logistics Management, 2018Co-Authors: Shirish Jeble, David Roubaud, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Anand PrakashAbstract:The purpose of this paper is to develop a theoretical model to explain the impact of big data and Predictive Analytics (BDPA) on sustainable business development goal of the organization.,The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.,The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support for H4. Although the authors did not find support for H4 (moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.,This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.
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Can big data and Predictive Analytics improve social and environmental sustainability?
Technological Forecasting and Social Change, 2017Co-Authors: Rameshwar Dubey, Stephen J Childe, Zongwei Luo, Angappa Gunasekaran, Thanos Papadopoulos, Samuel Fosso Wamba, David RoubaudAbstract:Although literature indicates that big data and Predictive Analytics (BDPA) convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions (inter alia, national context and culture, and firm size). Grounding our investigation in the dynamic capability views and organisational culture and based on a sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP) and environmental performance (EP) using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains.
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big data and Predictive Analytics for supply chain and organizational performance
Journal of Business Research, 2017Co-Authors: Angappa Gunasekaran, Benjamin T Hazen, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Samuel Fosso Wamba, Shahriar AkterAbstract:Scholars acknowledge the importance of big data and Predictive Analytics (BDPA) in achieving business value and firm performance. However, the impact of BDPA assimilation on supply chain (SCP) and organizational performance (OP) has not been thoroughly investigated. To address this gap, this paper draws on resource-based view. It conceptualizes assimilation as a three stage process (acceptance, routinization, and assimilation) and identifies the influence of resources (connectivity and information sharing) under the mediation effect of top management commitment on big data assimilation (capability), SCP and OP. The findings suggest that connectivity and information sharing under the mediation effect of top management commitment are positively related to BDPA acceptance, which is positively related to BDPA assimilation under the mediation effect of BDPA routinization, and positively related to SCP and OP. Limitations and future research directions are provided.
Stephen J Childe - One of the best experts on this subject based on the ideXlab platform.
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big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. The literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource‐based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre‐tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under the moderating effect of big data culture and their utilization for capability building, and how this capability affects cost and operational performance.
-
big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. Literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource-based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills, and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre-tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under moderating effect of big data culture and their utilisation for capability building, and how this capability affects cost and operational performance.
-
impact of big data Predictive Analytics capability on supply chain sustainability
The International Journal of Logistics Management, 2018Co-Authors: Shirish Jeble, David Roubaud, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Anand PrakashAbstract:The purpose of this paper is to develop a theoretical model to explain the impact of big data and Predictive Analytics (BDPA) on sustainable business development goal of the organization.,The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.,The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support for H4. Although the authors did not find support for H4 (moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.,This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.
-
Can big data and Predictive Analytics improve social and environmental sustainability?
Technological Forecasting and Social Change, 2017Co-Authors: Rameshwar Dubey, Stephen J Childe, Zongwei Luo, Angappa Gunasekaran, Thanos Papadopoulos, Samuel Fosso Wamba, David RoubaudAbstract:Although literature indicates that big data and Predictive Analytics (BDPA) convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions (inter alia, national context and culture, and firm size). Grounding our investigation in the dynamic capability views and organisational culture and based on a sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP) and environmental performance (EP) using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains.
-
big data and Predictive Analytics for supply chain and organizational performance
Journal of Business Research, 2017Co-Authors: Angappa Gunasekaran, Benjamin T Hazen, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Samuel Fosso Wamba, Shahriar AkterAbstract:Scholars acknowledge the importance of big data and Predictive Analytics (BDPA) in achieving business value and firm performance. However, the impact of BDPA assimilation on supply chain (SCP) and organizational performance (OP) has not been thoroughly investigated. To address this gap, this paper draws on resource-based view. It conceptualizes assimilation as a three stage process (acceptance, routinization, and assimilation) and identifies the influence of resources (connectivity and information sharing) under the mediation effect of top management commitment on big data assimilation (capability), SCP and OP. The findings suggest that connectivity and information sharing under the mediation effect of top management commitment are positively related to BDPA acceptance, which is positively related to BDPA assimilation under the mediation effect of BDPA routinization, and positively related to SCP and OP. Limitations and future research directions are provided.
Angappa Gunasekaran - One of the best experts on this subject based on the ideXlab platform.
-
big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. The literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource‐based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre‐tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under the moderating effect of big data culture and their utilization for capability building, and how this capability affects cost and operational performance.
-
big data and Predictive Analytics and manufacturing performance integrating institutional theory resource based view and big data culture
British Journal of Management, 2019Co-Authors: Rameshwar Dubey, Stephen J Childe, Angappa Gunasekaran, Constantin Blome, Thanos PapadopoulosAbstract:The importance of big data and Predictive Analytics has been at the forefront of research for operations and manufacturing management. Literature has reported the influence of big data and Predictive Analytics for improved supply chain and operational performance, but there has been a paucity of literature regarding the role of external institutional pressures on the resources of the organization to build big data capability. To address this gap, this paper draws on the resource-based view of the firm, institutional theory and organizational culture to develop and test a model that describes the importance of resources for building capabilities, skills, and big data culture and subsequently improving cost and operational performance. We test our research hypotheses using 195 surveys, gathered using a pre-tested questionnaire. Our contribution lies in providing insights regarding the role of external pressures on the selection of resources under moderating effect of big data culture and their utilisation for capability building, and how this capability affects cost and operational performance.
-
Can big data and Predictive Analytics improve social and environmental sustainability?
Technological Forecasting and Social Change, 2017Co-Authors: Rameshwar Dubey, Stephen J Childe, Zongwei Luo, Angappa Gunasekaran, Thanos Papadopoulos, Samuel Fosso Wamba, David RoubaudAbstract:Although literature indicates that big data and Predictive Analytics (BDPA) convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions (inter alia, national context and culture, and firm size). Grounding our investigation in the dynamic capability views and organisational culture and based on a sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP) and environmental performance (EP) using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains.
-
big data and Predictive Analytics for supply chain and organizational performance
Journal of Business Research, 2017Co-Authors: Angappa Gunasekaran, Benjamin T Hazen, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Samuel Fosso Wamba, Shahriar AkterAbstract:Scholars acknowledge the importance of big data and Predictive Analytics (BDPA) in achieving business value and firm performance. However, the impact of BDPA assimilation on supply chain (SCP) and organizational performance (OP) has not been thoroughly investigated. To address this gap, this paper draws on resource-based view. It conceptualizes assimilation as a three stage process (acceptance, routinization, and assimilation) and identifies the influence of resources (connectivity and information sharing) under the mediation effect of top management commitment on big data assimilation (capability), SCP and OP. The findings suggest that connectivity and information sharing under the mediation effect of top management commitment are positively related to BDPA acceptance, which is positively related to BDPA assimilation under the mediation effect of BDPA routinization, and positively related to SCP and OP. Limitations and future research directions are provided.
David Roubaud - One of the best experts on this subject based on the ideXlab platform.
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impact of big data Predictive Analytics capability on supply chain sustainability
The International Journal of Logistics Management, 2018Co-Authors: Shirish Jeble, David Roubaud, Stephen J Childe, Thanos Papadopoulos, Rameshwar Dubey, Anand PrakashAbstract:The purpose of this paper is to develop a theoretical model to explain the impact of big data and Predictive Analytics (BDPA) on sustainable business development goal of the organization.,The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.,The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support for H4. Although the authors did not find support for H4 (moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.,This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.
-
Can big data and Predictive Analytics improve social and environmental sustainability?
Technological Forecasting and Social Change, 2017Co-Authors: Rameshwar Dubey, Stephen J Childe, Zongwei Luo, Angappa Gunasekaran, Thanos Papadopoulos, Samuel Fosso Wamba, David RoubaudAbstract:Although literature indicates that big data and Predictive Analytics (BDPA) convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions (inter alia, national context and culture, and firm size). Grounding our investigation in the dynamic capability views and organisational culture and based on a sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP) and environmental performance (EP) using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains.
