Dealing with digital Information richness in supply chain Management - A review and a Big Data Analytics approach
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1 Florian Kache Dealing with digital Information richness in supply chain Management - A review and a Big Data Analytics approach kassel IH university press
2 Contents Acknowledgements Preface Glossary Figures Tables v vi xii xiii xiv 1 Introduction Motivation Research questions Structure of the dissertation and chapter overview 4 2 Supply chain Management: An overview, research strategies, and methodoiogies Definition of logistics and supply chain management Research strategies in SCM: Ontological, epistemological, and methodological perspectives 12 3 Selection and justification of research methods used in empirical desk research part of the dissertation Literatu re review research Content analysis Contingency analysis Research quality considerations 31 4 A conceptual "framework map" of SCM Development of the Classification framework Dimensions of the "framework map" Dimension: Level of SCM analysis Dimension: Orientation of SCM Dimension: Functional scope of SCM: Collaboration/Integration Dimension: Functional scope of SCM: Risk/Performance Dimension: Functional scope of SCM: Strategy Dimension: Theoretical foundation 58 5 Content analysis application using the "framework map" Material collection Descriptive analysis 67 vii
3 I Distribution of articles across journals and years 68 ; Distribution of journals included in literature reviews of sample 69 ; Formal aspects of the 103 literature review articles (transparency) 72 > Origin of analytic categories for analyzing the contents of the 103 articles (deductive / inductive) Type of data analysis use in literature review sample (qualitative / quantitative) Multivariate data analysis method usage in literature review sample Quality measures applied in literature review sample Grounding of the 103 literature review articles in streams of literature Limitations identified in sample literature reviews Category selection Material evaluation 81 6 Findings from the literature review Dimension: Level of SCM analysis SCM view of literature Conceptual framing of SCM Business functions involved in SCM Dimension. Orientation of SCM Types of flow Direction of flow Dimension: Functional scope of SCM: Collaboration / Integration Collaboration Integration Information-sharing Process improvement orientation Leadership Dimension: Functional scope of SCM: Risk / Performance Supply chain risk management Rewards-sharing (benefits) Supply chain Performance Dimension: Functional scope of SCM: Strategy Supply chain planning Innovation Customer focus Top management support 116 viii
4 6.5.5 Competitive advantage Information technology Lean and agile supply strategies Sustainability Outsourcing Dimension: Theoretical foundation Economics theory Strategie management theory Operations management theory Psychological / sociological theory Contingency analysis Application of contingency analysis to literature review dataset Results and findings of the contingency analysis assessment Interpretation of category interdependencies and interrelations Summary of identified under-represented areas in the dimensions Dimension: Level of SCM analysis Dimension: Orientation of SCM Dimension: Functional scope of SCM: Collaboration / Integration Dimension: Functional scope of SCM: Risk / Performance Dimension: Functional scope of SCM: Strategy Dimension: Theoretical foundation Discussion of the dissertation's desk research part Contribution Academic and managerial implications Strengths of the desk research part Limitations of the desk research part Recommendations for further research Putting theory into practice: An exploratory approach for the assessment of an exemplary under-represented area The digital transformation of businesses: Big Data Analytics and the role of Information The digital transformation of the business landscape Big Data and Analytics: An overview in a management context Definition and key aspects Defining the scope of Big Data Analytics Research question development (RQ5) 217 ix
5 8.4 The value of Big Data Analytics for supporting the provisioning of Information on a business function level A conceptual framework for the assessment of Information requirements Identifying a theoretical foundation for the conceptual framework Development of the conceptual framework Assessing the impact of Big Data Analytics on corporate and supply chain level - A Delphi study approach Definition of the Delphi methodology Characteristics of the Delphi methodology Justification for selected research method Application of the Delphi methodology Design of the Delphi study Selection of experts Data collection process and response rate Presentation of Delphi study results Round 1 (Initial questions) Round 2 (Prioritizing of developed constructs) Round 3 (Validation of group response against individual response) Assessing the findings from the Delphi study Opportunities and challenges of Big Data Analytics on corporate and supply chain level Key opportunities on corporate level Key opportunities on supply chain level Key challenges on corporate level Key challenges on supply chain level Applying the Delphi study findings to the Information requirements framework Interlinking overarching Delphi study constructs with literature review insights Overarching construct "Supply chain visibility and transparency" Overarching construct "Responsiveness" Overarching construct "Integration and collaboration" Overarching construct "IT capabilities and infrastructure" Overarching construct "Information and cyber security" Discussion of the dissertation's field research part Contribution 341 x
6 11.2 Academic and managerial implications Strengths of the field research part Limitations of the field research part Recommendations for further research Conclusion Summarization Reflection 361 References 364 Appendices 397 xi
Dealing with digital information richness in supply chain management A review and a Big Data Analytics approach
Florian Kache Dealing with digital information richness in supply chain management A review and a Big Data Analytics approach Dimension: Collaboration / Integration INTEGRATION COLLABORATION TOP MANAGEMENT
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