Applications of Artificial Intelligence in Inventory Management: A Systematic Review of the Literature

Dealing with donations: Supply chain management challenges for food banks

InvestigationS on nursery and main field management techniques for quality seed production of rice hybrid CORH 2

Investigations on nursery and main field management techniques for quality seed production of rice hybrid corh 2

Production potential of rainfed rice based cropping system as influenced by rice varieties and fertilizer management in winter crops

This study aims to investigate the role of industrial Internet platform in facilitating the digital transformation of traditional manufacturing enterprises. While prior research has predominantly focused on industrial Internet platform enterprises, there is a noticeable dearth of research concerning traditional manufacturing enterprises lacking the resources to establish such platforms. To address this research gap, we conduct an exploratory case study and propose an affordances upgrade model that elucidates the digital business transformation process of these manufacturing enterprises leveraging industrial Internet platforms. The research findings can be summarized from two key perspectives. Firstly, the industrial Internet platform offers valuable technical support and potential opportunities for manufacturing enterprises to achieve digital business transformation through three distinct affordances: consonance, resonance, and adaptation. These affordances enable enterprises to align their operations with the capabilities and possibilities provided by the platform, thus facilitating their digital transformation. Secondly, to effectively harness these affordances, enterprises must strategically leverage the platform's technical services and systems in their production and operational practices. Through the accumulation of practical experiences, enterprises gradually transition their production modes from experience institutionalization and standardization to a state of refinement. The dynamic leapfrogging process of digital transformation in traditional manufacturing enterprises, facilitated by the industrial Internet platform, is reflected in the realization of these three affordances and their underlying resource capabilities. This research significantly contributes to the field by expanding the scope of inquiry to encompass traditional manufacturing enterprises and presenting a stage model for their digital transformation utilizing industrial Internet platform. 

Affording digital transformation: The role of industrial internet platform in traditional manufacturing enterprises digital transformation

PurposeEntering a new era of digital transformation, Industry 4.0 (I 4.0) promises to revolutionize the way business has been done, providing unprecedented opportunities and challenges. This study aims to investigate empirically and comparatively analyse the benefits, challenges and critical success factors (CSFs) of Industry 4.0 across four continents and developing and developed economies.Design/methodology/approachThis study used an online survey to explore the benefits, challenges and CSFs of developed and developing economies. In order to ensure the validity of the survey, a pilot test was conducted with 10 respondents. A total of 149 participants with senior managerial, vice-presidential and directorial positions from developed and developing economies spanning four continents were invited to take part in the survey.FindingsThe study ranks benefits, challenges and CSFs across economies and continents. Further, the benefit of Industry 4.0 helping to achieve organizational efficiency and agility differed across the developing and developed economies. Furthermore, the benefit improves customer satisfaction significantly differed across continents; in terms of challenges, Employee resistance to change had a higher proportion in developing economies. The future viability of I 4.0 also differed across the continents. Regarding CSFs, there was no difference across the developing and developed economies. Finally, change management and project management vary across the continents.Research limitations/implicationsThis study contributes to a balanced understanding of I 4.0 by providing empirical evidence for comparative analysis. Moreover, it extends the concept of resource dependence theory to explain how organizations in developing economies and developed economies deploy resources to manage external condition uncertainties to implement I 4.0. Furthermore, this study provides a structural framework to understand the specific benefits, challenges and CSFs of implementing I 4.0, which can be utilized by policymakers to promote I 4.0 in their economies or continents.Originality/valueTo the best of the authors’ knowledge, no studies have empirically demonstrated the comparative analysis of benefits, challenges and CSFs across economies and continents and distinguish an original contribution of this work.

Industry 4.0 benefits, challenges and critical success factors: a comparative analysis through the lens of resource dependence theory across continents and economies

Growth and yield of rice varieties as influenced by phosphorus applications to nursery and main field.

Understanding the dynamics of food banks' demand from food insecurity is essential in optimizing operational costs and equitable distribution of food, especially when demand is uncertain. Hence, Gaussian Mixture Model (GMM) clustering is selected to extract patterns. The novelty is that GMM clustering is applied to identify the possible causes of food insecurity in a given region, understanding the characteristics and structure of the food assistance network in a particular region, and the clustering result is further utilized to explore the patterns of uncertain food demand behavior and its significant importance in inventory management and redistribution of surplus food thereby developing a two-stage hybrid food demand estimation model. Data obtained from a food bank network in Cleveland, Ohio, is used, and the clusters developed are studied and visualized. The results reveal that this proposed framework can make an in-depth identification of food accessibility and assistance patterns and provides better prediction accuracies of the leveraged statistical and machine learning algorithms by utilizing the GMM clustering results. Also, implementing the proposed framework for case studies based on different levels of planning led to practical results with remarkable ease and comfort intended for the respective planning team. 

GMM clustering for in-depth food accessibility pattern exploration and prediction model of food demand behavior

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Industry 4.0 benefits, challenges and critical success factors: a comparative analysis through the lens of resource dependence theory across continents and economies

Growth and yield of rice varieties as influenced by phosphorus applications to nursery and main field.

GMM clustering for in-depth food accessibility pattern exploration and prediction model of food demand behavior