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Article
Publication date: 7 December 2023

Hatice Nuriler and Søren S.E. Bengtsen

Institutional framings of doctoral education mostly do not recognize the existential dimension of doctoral experience. This paper aims to offer an expanded understanding of…

Abstract

Purpose

Institutional framings of doctoral education mostly do not recognize the existential dimension of doctoral experience. This paper aims to offer an expanded understanding of experiences of doctoral researchers in the humanities with the concept of entangled becoming. This concept is developed through an existential lens by using Søren Kierkegaard’s philosophy – particularly his emphasis on emotions such as passion, anxiety and despair – and Denise Batchelor’s derived concept of vulnerable voices.

Design/methodology/approach

The conceptual framing is used for an empirical study based on ethnographic interviews with 10 doctoral researchers and supplementary observational notes from fieldwork at a university in Denmark. Two of the interview cases were selected to showcase variation across lived experiences and how doctoral researchers voice their entangled becoming.

Findings

Common experiences such as loneliness, insecurity(ies), vulnerability(ies) or passion for one’s research were identified across the interviews. On the other hand, this study shows that each doctoral journey in the humanities envelops a distinct web of entanglements, entailing distinct navigation, that makes each case a unique story and each doctoral voice a specific one.

Originality/value

Combining an existential philosophical perspective with a qualitative study, the paper offers an alternative perspective for doctoral education. It connects the humanities doctoral experience to the broader condition of human existence and the sophisticated uniqueness of each researcher’s becoming.

Details

Studies in Graduate and Postdoctoral Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-4686

Keywords

Article
Publication date: 23 May 2023

Rosario Huerta-Soto, Edwin Ramirez-Asis, John Tarazona-Jiménez, Laura Nivin-Vargas, Roger Norabuena-Figueroa, Magna Guzman-Avalos and Carla Reyes-Reyes

With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML…

Abstract

Purpose

With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC management

Design/methodology/approach

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.

Findings

As a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.

Practical implications

Many sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.

Originality/value

This paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

Details

International Journal of Retail & Distribution Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-0552

Keywords

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