A comprehensive review of warehouse operational issues

Shah, Bhavin; Khanzode, Vivek

doi:10.1504/ijlsm.2017.081962

Cited by 28 publications

(20 citation statements)

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“…These logistics efforts could be reduced using integrated buffering (Shah and Khanzode, 2015), warehousing (Baligo et al, 2019) and distribution strategies (Hubner et al, 2016). The NVA distribution efforts are controlled through DC location by return pattern analysis (Abushaikha, 2018) and just-right buffering (Shah and Khanzode, 2017a). A customer categorization based on return frequency (Foscht et al, 2013) could be useful to devise customized return policies; however, such a hybrid model isn't yet cited by existing state-of-art literature.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The long-duration return policy attributes to high time value and lesser flexibility whereas; the short-term corresponds to less lenient policy which affects customer satisfaction (Li et al, 2013). Although more liberal returns diminish inherent consumer risk and also enhances satisfaction level (Pacheo et al, 2018), its execution proved to be one of the costliest problem incurring additional distribution and over-storages efforts for the sellers and e-retailers respectively (Shah and Khanzode, 2017a, b). These overstocking charges are incorporated in pricing agreements by sharing it among supply chain partners (Ding and Chen, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Can collaborative buffering strategies reduce distribution costs while improving product returns?: A case of an Asian e-retailer

Shah¹,

Singh²

2021

BIJ

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PurposeIn order to achieve competitive advantage over the physical marketplace, the e-retailers are insisted on endowing with lenient return policies. The piece-wise returns-and-reordering process incurs excessive buffering and unwanted logistics costs which raises overall fulfillment charges. The objective of this study is to re-design e-retail distribution policy by providing temporal storage at logistics service provides' (LSP) location. The impact of recurrent returns on pricing and profit margins are also investigated over time continuum.Design/methodology/approachA framework is developed to reduce the non-value added (NVA) storage and distribution efforts by providing collaborative buffering between LSP and e-retailer. The knapsack based buffering approach is tested and compared with traditional e-retail distribution practices. The revenue sharing concept is mathematically modelled and implemented in GAMS, which finally validated through multiple return scenarios.FindingsThe proposed model outperforms the existing one under all scenarios with different configuration settings of re-ordering, profit margins, and buffer time windows. The distribution cost is found, linearly related to the necessary product buffering space. The findings help to re-design sustainable return policies for individual products so that maximum customer value can be yield with minimum costs.Research limitations/implicationsThis study helps to determine the NVA efforts incurred while storing and delivering multi-time returned products to ensure desired service levels. The revenue sharing model provides pricing strategies for e-retail practitioners deciding which product should store in what quantity for how much time at the shipping agency location so that it fulfils the re-ordering at least waiting and sufficient buffering.Originality/valueThe proposed model extends the role of LPSs as temporary buffer providers to reduce returns-and-reordering fulfilment efforts in the e-retail network. This Collaborative framework offers an opportunity to amend the distribution contracts and policies time by time that enhances e-retailer's performance and customer satisfaction.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Can collaborative buffering strategies reduce distribution costs while improving product returns?: A case of an Asian e-retailer

Shah¹,

Singh²

2021

BIJ

Self Cite

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“…Other methods of improving the order picking process are connected with its organisation. The most popular organisation of picking policies include zone picking, wave picking or batch picking (Shah and Khanzode, 2017).…”

Section: Activitymentioning

confidence: 99%

Impact of the Method of Criteria Normalisation on the Order Picking Route and Time

Dmytrów¹

2020

ERSJ

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“…AS/RSs have been the subject of many investigations according to the several structural, functional, and operational aspects distinguishing these systems (J.P. Gagliardi et al, 2012;Petersen et al, 2005;Roodbergen & Vis, 2009). The main feature of the different reviews is the throughput capacity of the system, that appears to be a crucial performance measure (Shah & Khanzode, 2017). Such an indicator is the reciprocal of the average transaction time.…”

Section: Introductionmentioning

confidence: 99%

An approach for computing AS/R systems travel times in a class-based storage configuration

Schenone

Mangano

Grimaldi

et al. 2020

Production & Manufacturing Research

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This study provides an approach to compute the travel time for AS/R systems in a class-based storage environment. A regression analysis is completed in order to define the importance of the key predictors taken into account and to propose a formulation of travel times. The results show the reliability of the model and allow to evaluate the travel time through the identification of a complete list of predictors. The proposed approach supports managers in theex-ante definition of travel times for a warehouse. A correct evaluation of travel times enables a better monitoring of the performance of warehouse operations and can support practitioners in the choice of the configuration not only in terms of kind of cycle, but also from a policy assignment perspective. From a theoretical point of view, this work can be considered as an attempt to refine the existing methods to compute travel times.

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A comprehensive review of warehouse operational issues

Cited by 28 publications

References 0 publications

Can collaborative buffering strategies reduce distribution costs while improving product returns?: A case of an Asian e-retailer

Can collaborative buffering strategies reduce distribution costs while improving product returns?: A case of an Asian e-retailer

Impact of the Method of Criteria Normalisation on the Order Picking Route and Time

An approach for computing AS/R systems travel times in a class-based storage configuration

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