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Preface The functions of business divide into several areas and the general focus of this book is on one of the most important although least understood of these—DISTRIBUTION. The particular focus is on reviewing current practice in distribution costing and on attempting to push the frontiers back a little by suggesting some new approaches to overcome previously defined shortcomings.

Recent literature recognizes the role of warehouses in enhancing the overall logistics performance. Thus, lean thinking has recently found its way in supporting warehouse and distribution centre operations. The purpose of this paper is to examine the relationships among warehouse waste reduction practices, warehouse operational performance, distribution performance and business performance.

A two-stage study was conducted. First, a Delphi technique was adopted to develop a relevant questionnaire. Second, this questionnaire was used to measure the degree of waste reduction in the different warehouse activities and to test the developed research hypotheses. The authors test the hypotheses with a sample of Middle Eastern warehouse operators.

There exists a positive relationship between warehouse waste reduction level and both warehouse operational performance and distribution performance. There was no direct relationship between warehouse waste reduction level and business performance. However, results revealed that the relationship between warehouse waste reduction level and business performance was mediated by warehouse operational performance and distribution performance.

The developed instrument provides a guide for logistics managers as to understand how to reduce waste in each warehousing activity. The results also inform logistics managers of how distribution performance can be improved through lean warehousing. The resulting performance improvements in the distribution operations will ultimately be reflected in the logistics performance of downstream retailers.

The study develops an original instrument for measuring waste reduction in warehouses, and provides insights into the evolving lean warehousing research area. This is the first scholarly work to uncover the relationships among warehouse waste reduction practices, warehouse operational performance, distribution performance and business performance.

Due to the importance of efficiency and responsiveness measures rather than just efficiency measures, this research recognizes both measures when considering overall performance of warehouse operations. Thus, the purpose of this paper is to prioritize overall performance measures associated with warehouse operations in manufacturing, third-party logistics service provider and retail industry supply chains.

The study uses an integrated approach that involves the Q-sort method to group measures into four categories. Fuzzy analytical hierarchy process was then used to prioritize individual performance measures within each category and integer liner programming model was used to validate prioritized categories, using the judgment of multiple decision makers across three industries.

The result shows that the financial category is a dominating performance category in managing warehouse operations across all three industries selected. Within the financial category, cost of insurance accounted for 25 percent of total weight of the category, and is considered to be a powerful measure. The financial category is verified by multiple decision makers across three industries, as the most important performance category.

As part of adopting the proposed methodology in practice, it needs to be guided by overall methodology appropriate for industry-specific contexts.

Key novel aspects of this study are to categorize warehouse operations measures and analyze their perspectives in different industries, understand dominant categories of warehouse operations measures in the contemporary supply chain and finally to explore to what extent current practices lead to achieving efficiency and responsiveness in the selected industries.

The purpose of this study is to gain a better understanding of the impacts of Logistics 4.0 initiatives (focusing on automated warehousing systems) on the economic, environmental and social dimensions of firms' sustainability performance. To achieve this objective, a new framework for the assessment of sustainable warehousing in the 4.0 era is developed.

The framework, developed via the item-objective congruence index, Q-sort method and interviews with experts, is employed to assess performance changes through management interviews in two warehousing companies after the implementation of automation technologies.

Most aspects of both companies' sustainability performance are considerably improved (e.g. productivity, accuracy, air emission, worker safety and supply chain visibility); however, the outcome for some criteria might be worsened or improved depending on each company's solutions and strategies (e.g. increasing electricity bills, maintenance costs and job losses).

The findings provide insight into the effective implementation of warehousing technologies. The proposed framework is also a valid and reliable instrument for sustainability assessment for warehousing operators, which companies can utilise for self-assessment.

This paper contributes to establishing a body of literature that explores the previously unclarified effects of Logistics 4.0 on firms' sustainability performance. The proposed framework, which captures critical concerns of corporate sustainability and technological adaptation, is also the first of its kind for warehouse performance assessment.

The objective of this paper is to propose an approach to comparatively analyze the performance of drugs and consumable products warehouses belonging to different healthcare institutions.

A Cluster Analysis is completed in order to classify warehouses and identify common patterns based on similar organizational characteristics. The variables taken into account are associated with inventory levels, the number of SKUs, and incoming and outgoing flows.

The outcomes of the empirical analysis are confirmed by additional indicators reflecting the demand level and the associated logistics flows faced by the warehouses at issue. Also, the warehouses belonging to the same cluster show similar behaviors for all the indicators considered, meaning that the performed Cluster Analysis can be considered as coherent.

The study proposes an approach aimed at grouping healthcare warehouses based on relevant logistics aspects. Thus, it can foster the application of statistical analysis in the healthcare Supply Chain Management. The present work is associated with only one regional healthcare system.

The approach might support healthcare agencies in comparing the performance of their warehouses more accurately. Consequently, it could facilitate comprehensive investigations of the managerial similarities and differences that could be a first step toward warehouse aggregation in homogeneous logistics units.

This analysis puts forward an approach based on a consolidated statistical tool, to assess the logistics performances in a set of warehouses and, in turn to deepen the related understanding as well as the factors determining them.

The literature on warehouse performance assessments is mainly focussed on the efficiency and effectiveness of an action or activity due to customer demand and tailored fulfilment, with less attention being given to the performance measurement of each function of the warehouse and its overall productivity. Therefore, this study was aimed at revising the key warehouse performance metrics to a set of productivity measurement indicators that can be adopted internationally for benchmarking productivity performance.

A literature review and semi-structured survey questionnaire were used for this study. The importance of warehouse productivity performance was reviewed to revamp the measurement indicators. Through the use of a directed content analysis and descriptive analysis, an extensive study was carried out to analyze existing warehouse productivity indicators.

The findings of this study provide comprehensive references for practitioners and academicians for improving the classification of productivity measurements from existing key performance metrics for warehousing. Also, this paper highlights the warehouse resources related to the respective warehouse operation activities.

The study was limited to productivity performance indicators adapted from Staudt et al. (2015). Furthermore, the samples for this study comprised Malaysian academicians and practitioners in the related field. The findings can be adapted on a global scale as this study implemented general warehouse operation processes.

Consequently, the contributions of this study are that it provides relevant benchmarks for key productivity performance indicators in the warehousing sector that has worldwide applicability and the developed model provides a conceptual platform from which further theoretical and empirical developments can be carried out.

This study primarily explores the influence of green warehousing, logistics optimization and social values and ethics on supply chain sustainability and economic performance. The study further examines the mediating role of supply chain sustainability between economic performance and green warehousing, logistics optimization and social values and ethics.

The study employs a quantitative research approach where survey data are collected from 200 managers of manufacturing companies in Ghana. The dataset is analyzed using partial least square structural equation modeling software (PLS-SEM) SmartPLS 3.

The results show that green warehousing and logistics optimization negatively influence economic performance but improves economic performance through supply chain sustainability. It is further discovered that social values and ethics have a positive influence on supply chain sustainability and economic performance.

This paper proposes and tests a theoretical model that explores the relationships between green warehousing, supply chain sustainability, economic performance, logistics optimization and social values and ethics through the resource dependency theory (RDT) in the manufacturing firms in Ghana.

The purpose of this paper is to propose a maturity model to improve warehouse performance.

This paper will follow De Bruin et al’s (2005) suggested six relevant phases: scope, design, populate, test, deploy and maintain in developing the proposed maturity model. This study concentrates on the first five phases.

The proposed warehouse maturity model can be used as descriptive, benchmarking and a prescriptive with a road map for improvement.

The warehouse maturity model was proposed to let warehouse managers evaluate their practices and assess them by maturity level. Then, the proposed warehouse maturity model can be utilized to develop a set of plans for conducting projects to improve the warehouse practices, techniques and tools.

The proposed warehouse maturity model contributes to fill the shortages of maturity model addressing the warehouse environment. In particular, it provides a useful tool to establish the overall maturity level of a warehouse system. The proposed maturity model supports strategic decisions oriented toward improvement capabilities of the warehouse and to compete based on service level provided.

To examine warehouse worker development associated with managerial coaching in the logistics industry.

Examine the efficacy of this developmental approach in a logistics context, a survey method was used to provide an overview of supervisors' coaching behavior at 18 distribution centers in the United States. Warehouse workers answered questions about their interactions with their supervisors and their own job satisfaction while supervisors answered questions pertaining to the job‐related performance of warehouse workers for whom they were directly responsible.

The study findings indicate that warehouse workers at these distribution centers encounter low levels of supervisory coaching behavior. However, despite these low levels, significant positive associations were found between supervisory coaching behavior, warehouse worker job satisfaction and supervisors' perceptions of their subordinates' job‐related performance.

The findings are based on the perceptions of respondents at the specific distribution centers in our study and therefore should not be interpreted as being generalizable. However, we hope that they will stimulate further empirical research on the growth, development and retention of front‐line logistics workers – an important, but relatively under‐researched, area of supply chain management.

The logistics industry is becoming progressively more service‐oriented and technologically‐driven and greater front‐line worker competence in these areas will be required for many firms to survive.

As the greatest aggregation of labor in the supply chain is in distribution center operations, our findings may encourage logistics organizations to evaluate the feasibility of adopting more people‐oriented supervisory approaches like coaching that focus on personnel development and the provision of more intrinsically‐rewarding work environments.

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.