Coping with the postponement boundary problem: an empirical investigation in global food supply chains

Purpose – The postponement boundary problem entails that duties and cross-border trade complexity can lead companies to geographically postpone operations to downstream global facilities. The present study aims at investigating the problem to provide insights into the drivers behind the choice of different postponement strategies for global food supply chains. Design/methodology/approach – A single case study was conducted considering an Italian company exporting olive oil toward the United States. Two global postponement strategies, previously formalized in the literature, were tailored for food supply chains. A multi-methodological approach was adopted, combining data obtained through exploratory case research with empirically grounded analytical modeling. A sensitivity analysis was also performed, to investigate outcomes related to the considered problem when changing key parameters. Findings – Bulky and heavy packing materials account for a big percentage of finished products’ volume and weight, and this can deeply affect strategies’ cost-effectiveness. Postponing packaging operations could allow for taking advantage of lower tariffs levied on bulk goods, contributing to significantly lower duties to be paid. However, important trade-offs could arise related to the required investments, and the fiscal regulatory frameworks must be carefully examined. Originality/value – This study offers an empirical investigation of the postponement boundary problem, which is largely unexplored in the current literature. It also tackles an understudied empirical context as global food supply chains. It summarizes the drivers behind and explores the costs related to the implementation of different strategies, offering an original quantitative approach that could support practitioners’ decision making. Lastly, it formalizes five propositions that could pave the way for further research inquiries

A Critical Comparison of Alternative Distribution Configurations in Omni-Channel Retailing in Terms of Cost and Greenhouse Gas Emissions

New opportunities and challenges forced by the ever-increasing importance of the online channel have arisen for retailers. The retailing industry is moving to a new phase, in which the distinctions between traditional and online channels disappear, namely omni-channel (OC) retailing. At the same time, the awareness of environmentally sustainable processes has been enhanced around the world and the environmental impact that results from the online order fulfilment process is becoming a key issue for logistics managers. The new challenge is to understand how multiple channels can be synergistically managed to provide a seamless customer experience, taking an economic and environmental perspective simultaneously. Retailers need to define the distribution configuration for serving the online demand, making decisions on the integration level between online and traditional channels. In this paper, we developed an assessment model of the operational costs and greenhouse gas emissions for three distribution configurations in OC retailing. The model was also applied to a real case operating in the consumer electronics industry. Results highlighted that the search for synergies between online and traditional flows in both warehouse and transport activities is a key factor for the economic and environmental sustainability of OC systems

Fostering supply chain resilience for omni-channel retailers: A two-phase approach for supplier selection and demand allocation under disruption risks

This study aims to optimize supplier selection and demand allocation decisions for omni-channel (OC) retailers to achieve supply chain resilience under the potential disruption risks. A two-phase approach with resilience factors that covers three main sourcing issues (i.e., supplier evaluation, supplier selection, and demand allocation) is proposed to support the decision-making. In the first phase, we construct a five-dimensional evaluation framework for OC retailers to identify supplier preferences and a hybrid model that combines the best–worst method to determine the weights of the evaluation criteria and evidential reasoning to evaluate potential suppliers. In the second phase, the preferences obtained from multiple suppliers are integrated into a multi-objective mixed-integer linear programming model aiming to minimize expected cost and maximize total purchasing value and geographical segregation based on three key resilience strategies of multiple sourcing, geographic diversification, and local sourcing. The efficiency of the aforementioned resilience strategies as well as the solvability of the proposed model are then validated numerically using a real-world case study and various MOEAs. The outcomes could be used as a decision-making tool to assist OC retailers in the performance assessment and optimal demand allocation among the alternative suppliers by considering costs, purchase value, and resilience simultaneously

Modeling, Analysis, and Design Insights for Shuttle-based Compact Storage Systems

Shuttle-based compact systems are new automated multi-deep unit-load storage systems with lifts that promise both low operational cost and large volume flexibility. In this paper, we develop novel queuing network models to estimate the performance of both single-tier and multi-tier shuttle-based compact systems. Each tier is modeled as a multi-class semi- open queuing network, whereas the vertical transfer is modeled using an open queue. For a multi-tier system, the models corresponding to tiers and vertical transfer are linked together using the first and second moment information of the queue departure processes. The models can handle both specialized and generic shuttles, and both continuous and discrete lifts. The accuracy of the models is validated through both simulation and a real case. Errors are acceptable for conceptualizing initial designs. Numerical studies provide new design insights. Results show that the best way to minimize expected throughput time in single-tier systems is to have a depth/width ratio around 1.25. Moreover, specialized shuttles are recommended for multi-tier systems because the higher cost of generic shuttles is not balanced by savings in reduced throughput time and equipment need

E-fulfilment and distribution in omni-channel retailing: a systematic literature review

Purpose – Given the progressive growth of e-commerce sales and the rising interest in omni-channel (OC) retailing amongst academics and practitioners, the purpose of this paper is to provide an up-to-date literature review on the logistics involved when moving towards OC retailing. Specifically, we have examined the main issues relating to e-fulfilment and distribution, highlighting how the topic has been developed over time, and identifying the most promising research streams for the near future. Design/methodology/approach – A systematic literature review methodology is adopted. The review is based on 58 papers published from 2002 to 2017 in 34 international journals. The papers were analysed and categorised according to their defining characteristics, methodologies adopted and themes addressed. Findings – This paper provides an overview of the main issues relating to e-fulfilment and distribution experienced by companies shifting towards OC, mapped along three dimensions: distribution network design, inventory and capacity management, delivery planning and execution. Despite the growing interest in OC retailing, many key topics are still under-represented, including the evolution of retail distribution networks, assortment planning over multiple channels, the logistics role played by stores in the delivery process and the interplay between different logistics aspects. Originality/value – The paper offers insights into the main logistics issues in MC and OC retailing, as well as highlights potential fields for further investigation. From a managerial perspective, this paper is useful for retailers adopting an OC approach to guide their future efforts concerning their business logistics model

Business logistics models in omni-channel: a classification framework and empirical analysis

Purpose – Companies are currently moving from multi-channel strategies to offer their customers an omni-channel (OC) experience. So far, OC research has been mainly tackled from a sales-based view, with numerous operational challenges to be fully investigated yet. The purpose of this paper is to investigate how companies set the logistics variables in their OC management strategy and the business logistics models currently most adopted. Design/methodology/approach – A two-step methodology was adopted. First, a systematic combining approach with scientific literature review and case studies allowed to derive a framework for classifying the key logistics variables and the related options. The framework was then used to conduct a qualitative survey targeting 92 Italian companies operating in food manufacturing, food retailing and non-food retailing. Collected data were analysed by means of cluster analysis. Findings – Implementing an OC management strategy requires to set 11 logistics variables belonging to four strategic areas: delivery service, distribution setting, fulfilment strategy and returns management. A broad empirical investigation showed the choices made by companies when setting the logistics variables to implement an OC management strategy. Lastly, four business logistics models, differing in terms of both business sector and OC maturity, were discussed. Originality/value – The proposed framework extends earlier studies by including additional significant logistics variables. The empirical analysis provides new insights on how to re-structure the business logistics model in OC, suggesting channel integration and the coexistence of multiple configurations as main enablers of an OC proposition

The role of TNF genetic variants and the interaction with cigarette smoking for gastric cancer risk: a nested case-control study

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to investigate the role of <it>TNF </it>genetic variants and the combined effect between <it>TNF </it>gene and cigarette smoking in the development of gastric cancer in the Korean population.</p> <p>Methods</p> <p>We selected 84 incident gastric cancer cases and 336 matched controls nested within the Korean Multi-Center Cancer Cohort. Six SNPs on the <it>TNF </it>gene, <it>TNF</it>-α-238 G/A, -308 G/A, -857 C/T, -863 C/A, -1031 T/C, and <it>TNF</it>-β 252 A/G were genotyped. The ORs (95% CIs) were calculated using unconditional logistic regression model to detect each SNP and haplotype-pair effects for gastric cancer. The combined effects between the <it>TNF </it>gene and smoking on gastric cancer risk were also evaluated. Multi dimensionality reduction (MDR) analyses were performed to explore the potential <it>TNF </it>gene-gene interactions.</p> <p>Results</p> <p><it>TNF</it>-α-857 C/T containing the T allele was significantly associated with an increased risk of gastric cancer and a linear trend effect was observed in the additive model (OR = 1.6, 95% CI 1.0–2.5 for CT genotype; OR = 2.6, 95% CI 1.0–6.4 for TT genotype). All haplotype-pairs that contained TCT or CCC of <it>TNF</it>-α-1031 T/C, <it>TNF</it>-α-863 C/A, and <it>TNF</it>-α-857 C/T were associated with a significantly higher risk for gastric cancer only among smokers. In the MDR analysis, regardless of smoking status, <it>TNF</it>-α-857 C/T was included in the first list of SNPs with a significant main effect.</p> <p>Conclusion</p> <p><it>TNF</it>-α-857 C/T polymorphism may play an independent role in gastric carcinogenesis and the risk for gastric cancer by <it>TNF </it>genetic effect is pronounced by cigarette smoking.</p