Managing tomorrow's daily consumer goods logistics value network

Kallionpää, Erika; Helander, Nina; Rantala, Jarkko

doi:10.1504/ijscor.2015.069938

Cited by 4 publications

(3 citation statements)

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“…Unquestionably, like energies, logistics activities are essential for the economy as they share vital economic linkages with employment and economic growth ( World Economic Forum, 2020 ; Wong and Tang, 2018 ; Magazzino and Schneider, 2020 ). Inversely, poorly managed, inefficient logistics operations increase the operational and capital costs associated with under-utilization and waiting time ( Kallionpaa et al, 2015 ; Windmark and Andersson, 2015 ). At the firm level, such performance finds explanations in the logistics (inter and intra) organization, and it has been corroborated by several papers ( Flynn et al, 2010 ; Vaccaro et al, 2010 ; Christopher, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: A quantile regression evidence

Magazzino

Alola

Schneider

2021

Journal of Cleaner Production

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Section: Introductionmentioning

confidence: 99%

The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: A quantile regression evidence

Magazzino

Alola

Schneider

2021

Journal of Cleaner Production

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“…Lin et al (2014) conducted a literature review on the GVRP and pointed out that the vehicle scheduling problem and the VRP needs to be addressed. One main research direction of GVRP is fuel consumption with the consideration of the distance, load conditions and the speed (Abdoli et al, 2017;Kancharla and Ramadurai, 2018;Poonthalir and Nadarajan, 2018;Kallionpaa et al, 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

A green vehicle routing model based on modified particle swarm optimization for cold chain logistics

Yan

Lim

Tseng

2019

IMDS

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Purpose This paper studies green vehicle routing problems of cold chain logistics with the consideration of the full set of greenhouse gas (GHG) emissions and an optimization model of green vehicle routing for cold chain logistics (with an acronym of GVRPCCL) is developed. The purpose of this paper is to minimize the total costs, which include vehicle operating cost, quality loss cost, product freshness cost, penalty cost, energy cost and GHG emissions cost. In addition, this research also investigates the effect of changing the vehicle maximum load in relation to cost and GHG emissions. Design/methodology/approach This study develops a mathematical optimization model, considering the total cost and GHG emission. The standard particle swarm optimization and modified particle swarm optimization (MPSO), based on an intelligent optimization algorithm, are applied in this study to solve the routing problem of a real case. Findings The results of this study show the extend of the proposed MPSO performing better in achieving green-focussed vehicle routing and that considering the full set of GHG costs in the objective functions will reduce the total costs and environmental-diminishing emissions of GHG through the comparative analysis. The research outputs also evaluated the effect of different enterprises’ conditions (e.g. customers’ locations and demand patterns) for better distribution routes planning. Research limitations/implications There are some limitations in the proposed model. This study assumes that the vehicle is at a constant speed and it does not consider uncertainties, such as weather conditions and road conditions. Originality/value Prior studies, particularly in green cold chain logistics vehicle routing problem, are fairly limited. The prior works revolved around GHG emissions problem have not considered methane and nitrous oxides. This study takes into account the characteristics of cold chain logistics and the full set of GHGs.

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“…In a more traditional business sense, logistics is the component of the business management responsible with planning and implementation of the flow of resources between creation and consumption sites, involving on their way processing and storage [9]. Many companies depend on their logistics component in order to maintain profitability and credibility in front of their business partners [14] [6]. The performance of their logistics department is affected by the performance of their suppliers, changes in legislation, unpredictable variations in fuel costs, transportation fees and delays, labor rates, etc [5].…”

Section: Introductionmentioning

confidence: 99%

Quality Control in Logistics Activities Through Internet of Things Technology

Băutu¹,

Autu²

2016

SBNA

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Modern companies depend on their logistics in order to maintain their purchases-inventory-sales chain to the desired level of performance (i.e. profitability). Many past situations demonstrate that errors, inefficiencies and disruptions in this chain can cause companies to miss opportunities, loose profitability, and even go bankrupt. An important factor to high quality logistics is the quality and availability of information about key processes. Internet of Things (IoT) technology allows companies to gather real-time information on processes, people and equipment, and to integrate it in their own informational systems. This paper discusses the use of IoT technology to monitor logistics activities in order to provide support data for performance assessments.

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Managing tomorrow's daily consumer goods logistics value network

Cited by 4 publications

References 0 publications

The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: A quantile regression evidence

The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: A quantile regression evidence

A green vehicle routing model based on modified particle swarm optimization for cold chain logistics

Quality Control in Logistics Activities Through Internet of Things Technology

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