the impact of data-driven culture on firm performance in the manufacturing industry: an analytics model

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research paper: the impact of data-driven culture on firm performance in the manufacturing industry: an analytics model abstract: this research paper explores the impact of a data-driven culture on firm performance in the manufacturing industry, specifically focusing on the implementation of an analytics model. the study aims to assess the effects of adopting a data-driven culture on key performance indicators, such as decision-making, operational efficiency, product quality, customer insights, competitive advantage, innovation, resource allocation, risk management, continuous improvement, and return on investment. the research also investigates the organizational factors that facilitate or hinder the successful implementation of a data-driven culture. the findings of this study contribute to a deeper understanding of the benefits of a data-driven culture in the manufacturing industry and provide insights for organizations seeking to enhance their performance through data analytics. keywords: data-driven culture, firm performance, manufacturing industry, analytics model, decision-making, operational efficiency, product quality, customer insights, …

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ation of this data into actionable insights. this cultural shift impacts various facets of a manufacturing firm, from enhancing product quality to optimizing supply chain management. with the increasing complexity of manufacturing processes and the growing demand for customization and quality, the implementation of an analytics model becomes pivotal. such a model enables firms to leverage data for improved decision-making, operational efficiency, and strategic planning. despite the apparent benefits, the adoption of a data-driven culture is fraught with challenges, including the integration of technology, organizational change management, and data governance. research objectives the primary objective of this research is to critically analyze the impact of a data-driven culture on firm performance within the manufacturing industry. this study aims to: evaluate the effects of a data-driven culture on key performance indicators (kpis) such as decision-making, operational efficiency, product quality, and customer insights. examine the role of an analytics model in enhancing …

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tinuous improvement initiatives? what organizational factors are critical in determining the successful adoption of a data-driven culture in the manufacturing industry? this research endeavors to offer comprehensive insights into the multifaceted impact of a data-driven culture, contributing to the existing body of knowledge and serving as a guide for manufacturing firms aspiring to harness the power of data analytics for enhanced performance. 2. literature review data-driven culture in the manufacturing industry yin, stecke, and li (2018) discussed the incorporation of industry 4.0 technologies in manufacturing, which is central to the data-driven approaches in the industry. liao, castelo-branco, cruz-jesus, and oliveira (2019) explored the implementation of industry 4.0 in manufacturing organizations, emphasizing the integration of business functions and production systems with data. key impacts of a data-driven culture on firm performance a study by oliver et al. (2023) looked into the influences and activities associated with data culture, providing a comprehensive …

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as where data-driven approaches are crucial, suggesting potential research gaps in these areas. yin, r. k., stecke, k. e., & li, h. (2018). towards data-driven approaches in manufacturing: an industry 4.0 perspective. international journal of production research. https://www.tandfonline.com/doi/full/10.1080/00207543.2020.1735660 liao, y., castelo-branco, i., cruz-jesus, f., & oliveira, t. (2019). a systematic review of the implementation of industry 4.0 in manufacturing organisations. international journal of production research. https://www.tandfonline.com/doi/full/10.1080/00207543.2021.2002964 waller, d. (2020). a model for creating a data-driven culture. harvard business review. https://hbr.org/2020/08/a-model-for-creating-a-data-driven-culture oliver, m., et al. (2023). understanding data culture/s: influences, activities, and initiatives. journal of the association for information science and technology. https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24489 - conceptual framework for the statistical model - review of previous research utilizing regression analysis or structural equation modeling in similar contexts - development of the statistical model: - selection of predictor variables (xs) related to a data-driven culture · degree of data integration in decision-making processes. · …

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f data-driven training is associated with increased production efficiency. functional form of the model this could be a simple linear relationship, a logistic model if dependent variable is categorical, or a more complex form if warranted by theory and preliminary data analysis. - model estimation approach (e.g., ordinary least squares regression, partial least squares regression, covariance-based structural equation modeling) ordinary least squares regression fits most, because of continuity of dependent variable 3. methodology research design this study adopts a quantitative research approach to examine the causal relationship between various aspects of a data-driven culture in the manufacturing industry and firm performance. the research design is correlational, focusing on how different predictor variables influence the dependent variable of firm performance. data collection methods primary data collection. data will be collected through structured questionnaires distributed to managers and key decision-makers in manufacturing companies. the questionnaire will include scaled items to measure various …

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research paper: the impact of data-driven culture on firm performance in the manufacturing industry: an analytics model abstract: this research paper explores the impact of a data-driven culture on firm performance in the manufacturing industry, specifically focusing on the implementation of an analytics model. the study aims to assess the effects of adopting a data-driven culture on key performance indicators, such as decision-making, operational efficiency, product quality, customer insights, competitive advantage, innovation, resource allocation, risk management, continuous improvement, and return on investment. the research also investigates the organizational factors that facilitate or hinder the successful implementation of a data-driven culture. the findings of this study contribute...

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