DEVELOPMENT OF DATA ANALYTICS USE, INNOVATION AMBIDEXTERITY, SUPPLY CHAIN COLLABORATION, AND SUSTAINABLE SUPPLY CHAIN PERFORMANCE MODELDATA ANALYTICS USE, SUSTAINABLE SUPPLY CHAIN PERFORMANCE, INNOVATION AMBIDEXTERITY, SUPPLY CHAIN COLLABORATION, ORGANIZATION FORMALIZATION, TRANSFORMATIONAL LEADERSHIP
The uncertainty and complexity of the business environment are challenges for sustainable supply chain performance. Environmental uncertainty and complexity can be overcome by utilizing the availability of data that is currently widely available. Data analytics is an effective means for companies to...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/81958 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The uncertainty and complexity of the business environment are challenges for sustainable supply chain performance. Environmental uncertainty and complexity can be overcome by utilizing the availability of data that is currently widely available. Data analytics is an effective means for companies to excel in facing the rapid and ever-changing market dynamics of today. However, the use of analytical data cannot run alone. It is important for companies to integrate and collaborate on various capabilities they have.
The main objective of this study is to understand how the use of analytical data can affect sustainable supply chain performance. This study develops a conceptual model based on several basic models. The conceptual model formed consists of the mediating effects of innovation agility and supply chain collaboration as well as the moderating effects of organizational formality and transformational leadership in influencing data analytics use on sustainable supply chain performance.
Research data were collected using questionnaires distributed to companies in Indonesia that have implemented analytical data and collaborated in the supply chain for at least the past two years. The collected data were then processed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique.
The test results show that the use of analytical data significantly affects the performance of sustainable supply chains mediated by innovation agility and supply chain collaboration. The use of analytical data is significantly supported by the positive moderation of organizational formality factors and transformational leadership style on innovation agility and supply chain collaboration.
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