Classifying healthcare warehouses according to their performance. A Cluster Analysis-based approach

Cagliano, Anna Corinna; Mangano, Giulio; Rafele, Carlo; Grimaldi, Sabrina

doi:10.1108/ijlm-02-2020-0110

Cited by 4 publications

(4 citation statements)

References 114 publications

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“…On the contrary, if the resulted p-value of the test is lower than the critical threshold of 5%, the null hypothesis has to be rejected. Thus, this means that at least one mean is significantly different compared with the other ones (Cagliano et al 2021 ).…”

Section: Methodsmentioning

confidence: 99%

4.0 technologies in city logistics: an empirical investigation of contextual factors

et al. 2022

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Industry 4.0 technologies, originally developed in the manufacturing sector, can be purposefully implemented to improve City Logistics (CL) processes by automatizing some of their operational tasks and enabling real-time exchange of information, with the ultimate goal of providing better interconnection among the actors involved. This work aims to identify the main social and economic contextual drivers for investing in the application of Industry 4.0 technologies to urban logistics. To this end, a dataset based on the primary collection of 105 CL projects exploiting the main 4.0 technologies has been built. After that, a regression model has been completed including potential economic, strategic, and demographic determinants of investments in CL 4.0. According to the obtained outcomes, Gross Domestic Product, Foreign Direct Investments, Research and Development Expenditure, Employment Rate, and Number of Inhabitants are significant contextual factors for the adoption of Industry 4.0 technologies in last mile logistics. The study might support academicians to investigate novel application fields of Industry 4.0 technologies. Also, it can serve as a roadmap for orienting the investments of private organizations and public entities to promote CL innovation and digitalization. Moreover, Industry 4.0 technology providers might find this study interesting to uncover prospective business sectors and markets. Future research efforts will analyse the impacts of internal business factors on CL 4.0 and the satisfaction levels of urban logistics stakeholders.

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Section: Methodsmentioning

confidence: 99%

4.0 technologies in city logistics: an empirical investigation of contextual factors

et al. 2022

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“…ANOVA, as Milligan (1996) suggests, can be used to confirm clustering solutions. The robustness of the Clustering Analysis performed can be verified using ANOVA (Cagliano et al, 2022). A null hypothesis of ANOVA is there are no significant differences between the groups under examination.…”

Section: Analysis Of Variance (Anova) and Post-hoc Analysismentioning

confidence: 99%

A Data-driven Approach for Planning Stock Keeping Unit (SKU) in a Steel Supply Chain

Wakle,

Toshniwal,

Jain

et al. 2024

Int. j. math. eng. manag. sci.

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In response to the growing complexities in supply chain management, there is an imperative need for a data-driven methodology aimed at optimizing inventory allocation strategies. The purpose of this research is to enhance the efficiency of allocation and operational scheduling, particularly concerning the stock keeping units (SKUs). To achieve this, one year's operational data from a specific organization's SKUs is taken and machine learning tools are employed on the data collected. These tools are instrumental in identifying clusters of SKUs that exhibit similar behaviour. Consequently, this research offers recommendations for rational inventory allocation strategies that are finely attuned to the unique characteristics of each SKU cluster. Results obtained reveals substantial disparities between the recommended strategies for the organization's SKUs and those typically found in the literature such as same strategy cannot be used for all different types for products. This underscores the critical importance of adopting a tailored approach to supply chain management. Furthermore, the research demonstrates the remarkable efficiency of unsupervised machine learning algorithms in determining the optimal number of segments within the SKUs. The current research differentiates from others in a way that in most of the research, the holistic data-driven approach is underutilized, right from the selection of the clustering algorithm to the validation of segments.

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“…At the national level, LPI is generally linked to economic growth, competitiveness, disaster resilience, and sustainability (Çelebi̇ & Civelek, 2019;Furkan FahriAltıntaş, 2021;Khan et al, 2017;Mahlet Demere Tadesse et al, 2022;Santos et al, 2020). Second, limited impacts of LPI subdimensions were explored in specific sectors like retail (Green et al, 2008) and healthcare (Cagliano et al, 2022). However, to our knowledge, the impacts of LPI with all dimensions have not been explored in general logistics firms.…”

Section: Introductionmentioning

confidence: 99%

Türki̇ye’ni̇n Loji̇sti̇k Performans Endeksi̇ni̇n Strateji̇k Bakiş Açisiyla Değerlendi̇ri̇lmesi̇

ARUN,

YILDIRIM ÖZMUTLU

2023

Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi

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Logistics plays a vital role in ensuring the competitiveness of countries in the international arena. The Logistics Performance Index, which reflects countries' international competitiveness, shows a country's efficiency in trade. However, the Logistics Performance Index determines the countries' on-the-ground efficiency of trade supply chains or logistics services from the view of worldwide logistics firms' managers. As a result, the robustness of the underlying data is related to individual logistics firms' factors; moreover, in the common literature, the effects of the Logistics Performance Index on countries' individual logistics firms' logistics performance have yet to be researched. This paper aims to analyze the effects of Logistics Performance Index and its subdimensions on the logistics firms' logistics performance. The data is gathered from the World Bank database between 2007-2018 and the International Association of Forwarding and Logistics Service Providers sectoral databank. Variance-based structural equation modeling with regression analyses is used for measurements. Contrary to the joint logistics and supply chain literature, the results show that infrastructure and tracking sub-dimensions of Logistics Performance Index negatively relate to firms' logistics performance in Turkey.

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Classifying healthcare warehouses according to their performance. A Cluster Analysis-based approach

Cited by 4 publications

References 114 publications

4.0 technologies in city logistics: an empirical investigation of contextual factors

4.0 technologies in city logistics: an empirical investigation of contextual factors

A Data-driven Approach for Planning Stock Keeping Unit (SKU) in a Steel Supply Chain

Türki̇ye’ni̇n Loji̇sti̇k Performans Endeksi̇ni̇n Strateji̇k Bakiş Açisiyla Değerlendi̇ri̇lmesi̇

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