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As sustainability becomes more important in manufacturing, researchers recommend using the four-stage Hayes and Wheelwright (H-W) model of strategic manufacturing effectiveness (SME) to integrate sustainable manufacturing practices (SMPs) at a strategic level. However, there is limited research on this topic. This paper investigates SMPs encompassing four sustainable manufacturing capabilities (SMCs): pollution control, pollution prevention, product stewardship, and clean technology. It relates these SMCs to the four SME stages of the H-W model, both of which form a continuum of stages.

A theoretical model on the congruence between SMCs and SME stages is first established using organizational theories to identify the dominant combinations. This model is then tested by examining 178 SMPs of four large manufacturing firms.

The study reveals that the SMPs of the case firms clearly show SMC and SME stage characteristics. Few deviations from the relationships established in the theoretical model are observed, leading to a revision of the model. A major finding is that SMPs within an SMC category can span multiple SME stages.

The study proposes a revised model based on a small sample of case firms, which may limit its broader applicability.

Manufacturing practitioners can use the findings of this study to plan SMPs that align with their SME goals.

Towards incorporating sustainability in the H-W model, this is the first major exploratory study that establishes congruent relationship between SMCs and SME stages of the H-W model.

Sustainable manufacturing is gaining prominence in light of the rising environmental and social concerns worldwide. One major task to enhance manufacturing sustainability is assessment of the current state of sustainability of a manufacturing firm. This paper reviews the existing sustainability assessment approaches applicable for manufacturing firms and observes that most of these approaches are not easy to apply for reasons such as high amount of skill, data and time requirement. Towards bridging this gap, this study proposes a sustainability assessment approach.

The assessment approach proposed in the paper uses a predefined list of potential sustainable manufacturing practices (SMPs) covering the primary and support activity domains of a manufacturing firm's value chain. It proposes a method to assess the extent of implementation of SMPs and identify associated drivers and barriers for each SMP area/category along the value chain of a firm as well as at overall firm level. A case study from textile industry is presented to demonstrate the utility of this approach.

The sustainability assessment approach adopted in this study uses less time and skills as well as ensures comprehensive coverage of SMPs. It provided valuable information to the management of the case company on how sustainable their practices are and why?

The study highlights the importance of sustainability assessment at SMP area/category level as well as explores practice area/category specific drivers and barriers. It provides a useful approach for a quick assessment of the current state of sustainability in manufacturing firms.

The researchers maintain that when a firm tackles “green concerns,” there could be several repercussions for manufacturing strategy decision areas (MS DAs). However, such repercussions are complex and have not been widely researched. This paper aims to propose a conceptual maturity stage model to study the configuration of MS DAs.

Firms exhibit different levels of “green” maturity in their journey and tend to make different choices in green technologies (GTs), resulting thereby in other compatible choices in their MS DAs. Extant literature has been synthesized in this light to build a conceptual maturity stage model in two steps. First, what is the GT that is involved! The second step discusses the possible implications of such a GT for MS DAs. Further, such information is organized according to a firm’s four maturity stages for all GTs that may be applicable. A case study has been undertaken to illustrate the model.

The results show good potential for the proposed conceptual model to examine the repercussions of MS DAs in industrial cases, and thereby develop relevant theories on this subject.

The proposed model was applied to a paint manufacturing company, which potentially limits the findings’ generalizability to other industries and/or geographies.

The proposed conceptual model can help managers assess the maturity stages of manufacturing to determine suitable adjustments that may be required in configuring MS DAs to improve their positions.

This is among the very few models to explore the repercussions of green manufacturing for MS DAs according to the four-stage maturity model.

This paper aims to develop an approach to design a warehouse that uses class-based storage policy in a way that minimizes both space cost and material handling cost.

The authors argue for and develop an optimization model for joint determination of lane depth, lateral width and product partitions for minimizing the sum of handling and space costs. In doing so, the assumption of perfect sharing is also relaxed. Using computational experiments, the authors characterize the operating conditions based on pick density and cost ratio. The authors further outline an approach to decide the conditions under which it is advantageous to implement multiple classes.

More classes are preferred when both the pick density and cost ratio are higher and vice versa. Factors such as demand skewness, lane depth and stacking height affect the space-sharing dynamics.

The paper gives the practical insights on when the conditions under which it is advisable to partition a warehouse into a certain number of classes instead of maintaining and when to maintain as a single-class block. It also gives a method to estimate the space-sharing factor, given a combination of operating parameters.

Very few studies have seen class-based storage policy in the context of block stacked warehouse layout. Further, block stacking designs have mostly been approached with the objective of minimizing just the space cost. This study contributes to the literature by developing an integrated model, which has the practical utility.

Warehouses, essential nodes in the supply chain, significantly contribute to sustainability issues, accounting for about 11% of emissions related to logistics activities. The purpose of this study is to review articles on sustainable warehouse management (SWM) from the Scopus database to analyze trends, synthesize existing knowledge, and identify research gaps for future studies.

The review uses text mining of initial relevant documents to create a search string for paper retrieval. Text mining is further used to generate a dendrogram of the most frequently used words in the research papers, which is then analyzed to identify themes and sub-themes in SWM.

The dendrogram reveals four major themes and their sub-themes within SWM, including two novel themes: sustainable warehouse in green logistics and sustainable warehouse location. In addition, 12 research recommendations are identified through content analysis and are subsequently linked to specific Sustainable Development Goals (SDGs).

The methodological innovation in keyword selection for searching relevant papers and identifying themes serves as a structured template for researchers to explore further.

The research recommendations, aligned with the SDGs, aim to assist managers in making informed decisions and operational strategies to enhance factors associated with the Building Research Establishment Environmental Assessment Method and the sustainable performance of warehouses.

This study is novel in its application of text-mining techniques to generate a search string for identifying relevant papers and discerning themes by analyzing the dendrogram.