Search results

Warehousing remains the most frequently outsourced logistics activity, but empirical research on the third‐party selection process for warehousing remains scarce. The main goals of this research were to identify the most critical factors to customers during third‐party warehousing selection and to compare the perceived performance levels of national and regional third‐party firms on each of the selection criteria. Surveys were sent to warehousing customers in several industries. Responsiveness to service needs, quality of management, and track record of ethical importance were rated by customers as the most important selection criteria. Results indicate that respondents also rated the performance of the typical regional third‐party warehousing firm as significantly better than national firms on six different criteria while national firms were rated significantly higher on only one criterion. It is hoped that this research can provide guidance to logistics managers as they evaluate third‐party warehousing options.

The purpose of this paper is to shed light on the development and change in priority of international warehouse location criteria during a business cycle (i.e. from years 2006 to 2010), by examining the responses of Finnish and Swedish companies on their European‐based facilities. The authors also investigate how the size of European warehouses will develop within medium term.

The authors' research is based on three online surveys completed during years 2006, 2009, and 2010. The 120 respondents were large Finnish and Swedish companies.

Finnish companies tend to focus on the emerging East European markets through their warehousing network structure, while Swedish companies focus more on Western Europe. Selection of warehouse location is dominated by three criteria, namely distribution cost, road transportation connection, and proximity of assembly and manufacturing units. Most of the longitudinal changes occur in less important warehousing criteria; companies seem to see warehousing decisions as less complex, incorporating a lower amount of criteria in the decision. Warehouse size analysis shows that in the future, the average size will slowly continue to increase, however, both small and large warehouses have justification for their existence. Finnish and Swedish respondents were mostly aligned in terms of warehouse location criteria, however, in terms of warehouse size Swedish companies are in favor of larger units.

Research is limited in terms of geography and respondent size. This will limit the generalizability of the results.

This research is based on a longitudinal survey, and provides insight on the evolution of warehouse location criteria in changing economic conditions.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

Applies the concept of buyer‐seller relationship to long‐term planning of wholesaling operations. Current practices indicate that this kind of relational exchange reduces overall costs more than the traditional market exchange. Aims to help to operationalize this partnership by selecting a stable set of manufacturers and warehouses for an entire planning period. Develops a multi‐period optimization model incorporating constraints necessary for such stable solutions. This model requires a large number of variables and constraints, and is computationally challenging for most practical‐sized problems. Therefore proposes heuristic method to decompose the model into subproblems by partitioning the planning period into blocks of years and then synthesize the subproblem solutions. Such decomposition may also be useful to solve large dynamic location planning problems.

Existing supply chain (SC) performance models are not able to cope with the potential of intensive SC digitalisation and establish a relationship between decisions and decision criteria. The purpose of this paper is to develop an integrated knowledge-based system (KBS) that creates a link between decisions and decision criteria (attributes) and evaluates the overall SC performance.

The proposed KBS is grounded on the fuzzy analytic hierarchy process (fuzzy AHP), which establishes a relationship between short-term and long-term decisions and SC performance criteria (short-term and long-term) for accurate and integrated Overall SC performance evaluation.

The proposed KBS evaluates the overall SC performance, establishes a relationship between decisions (long-term and short-term) and decision criteria of SC functions and provides decision makers with a view of the impact of their short-term or long-term decisions on overall SC performance. The proposed system was implemented in a case company where the authors were able to develop a SC performance monitoring dashboard for the company’s top managers and operational managers.

The proposed KBS assists organisations and decision makers in evaluating their overall SC performance and helps in identifying underperforming SC functions and their associated criteria. It may also be considered as a tool for benchmarking SC performance against competitors. It can efficiently point to improvement directions and help decision makers improve overall SC performance.

The proposed KBS provides a holistic and integrated approach, establishes a relationship between decisions and decision criteria and evaluates overall SC performance, which is one of the main limitations in existing supply chain performance measurement systems.

The paper seeks to propose the concept of sustainable enterprise simulation models. The social, environmental and economic models are developed and simulated using iThink in the context of a warehousing and distribution company.

The paper has leveraged the systems dynamic paradigm to conduct sustainable enterprise modelling and iThink™ system to implement the models. It uses the design science research methodology for the proof of concept of the models and modelling processes. The models have been developed for a logistics management company and tested in the business settings. These models were finalised through a number of revisions and iterations of the design, develop, simulate and test and evaluate.

The paper addresses the interconnectivity between disparate sustainability dimensions for developing the models. The validity and usefulness of the sustainability models for the day‐to‐day decision making has been authenticated by the management of the warehousing organisation.

The paper implements system dynamics concepts of sustainability modelling and produces models of various sustainability dimensions which are original in nature and evolution. While the domain in which sustainable enterprise modelling was carried out was warehousing, the concepts and principles that were explored, developed and validated is applicable across most enterprises.

The warehouse industry is one of the backbones in the logistics operation which involves several activities i.e. storage, receiving, picking and shipping of goods/cargoes. This study analyzes the most important warehouse productivity indicators for improving warehouse operation efficiency.

This study presents an empirical methodology of the fuzzy analytical hierarchy process (FAHP) method, an integration between the fuzzy logic method with an analytical hierarchy process (AHP) method incorporated with the adoption of quantitative and systems theories under the modern management theory approach.

The results indicate that the weight values of the main criteria which lead by the criterion “Space (0.4005)” at the top ranking, followed by Information System (0.2445), Labor (0.2065) and Equipment (0.1484). In addition, the weight values and ranking of the 16 sub-criteria are also highlighted which the sub-criterion “Warehouse Management System (0.2445)” scores the highest weight value and followed by Storage Space Utilization (0.1043) and Throughput (0.0722) accordingly.

Finally, this research contributed to enrich the literature, while highlighting a series of recommendations on the top three most significant productivity performance indicators that can be useful in further research.

A generic analysis model developed with the adoption of three study theories: quantitative, system and productivity theories.

Just‐in‐time (JIT) systems have evolved from a few selected implementations in the automobile industry into a widespread business practice. Early understanding of JIT models indicated that JIT can reduce inventory in the production system through the elimination of wasteful activities. This understanding led some researchers to suggest that JIT warehousing or JIT logistics are contradictions in terms since JIT′s purpose is to eliminate warehousing by delivering components just as they are needed. However, more recent studies of JIT practices indicate that an opportunity exists to use JIT benefits. Discusses the benefits of outsourcing logistics functions to external suppliers in order to enhance JIT performance. Additionally, a survey of services provided by JIT logistics suppliers is presented as well as criteria for selecting the “best” logistics supplier.

The purpose of this research is to identify a province in Thailand where total transportation cost for shipping grocery goods from this province to customers in all other provinces is the lowest.

Transportation distances among provinces, freight rate and the number of population in each province were gathered. Total transportation cost was computed by taking distance, tapering freight rate and population including that in original province into account.

Based on pre-set assumptions, it reveals that Saraburi province has the lowest total transportation cost.

This research emphasizes only transportation cost. For future research, other monetary and non-monetary factors such as land, labor, investment incentive, local government regulation should be considered together.

This is an industry-based research especially for retail and fast-moving consumer goods businesses.

This practitioner paper is one of the first to identify population, freight rate and distance-based warehouse location which can be determined as a location for Thailand’s logistics hub, particularly for retail or fast-moving consumer goods business in Thailand.

Agricultural sector not only meets the nutritional requirements of all living creatures but also generates the primary source of the raw material provided by various branches of industry to fulfill their functions. It is of great importance to increase studies on oilseeds which have an important role in Turkey's agricultural products. They are grown in almost all of the country, which are vital for the nutrition and many sectors. The main purpose of the study is to offer an integrated approach to determine potential warehouse locations for oilseeds.

This is the first study that integrates Delphi, analytical hierarchical process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), P-Median and Panel data analysis in a real case. This integrated approach consists of the following steps, respectively: (1) The criteria were determined by the Delphi method. (2) The weights of the criteria were calculated by AHP and the provinces with the highest oilseed warehouse potential in seven regions of Turkey were specified by TOPSIS. (3) Oilseed warehouse numbers and locations were obtained by P-Median. (4) In order to answer whether the distribution network is profitable in the future with the determined center locations, a forecast model based on panel data analysis was created. (5) Regional representatives were determined for 2030, and the distribution network was analyzed again. (6) The costs that arose in 2018 and 2030 were computed and compared by cost analysis. (7) The effect of the change in criteria weights on the alternative results was tested by scenario analysis.

The findings indicated that oilseed crop production potential and oilseed crop production area turned out to be the most important criteria. Furthermore, the results showed that this model is robust and suitable for warehouse location selection studies.

The study can serve as a guide for local and central policy makers with both the criteria it uses and the model it develops.

The main contribution of this study is that the integrated approach has been used for the first time in location selection in a real case.