Warehouse Location Decision in Pakistan:A Real Case Study

The manufacturing industry in Pakistan ispassing through a critical phase of its history. In the changing market placeconsumer are increasingly vigilant and demanding better quality, morecompetitive prices and shorter lead times. Maintaining cost effectivemanufacturing along with it distribution to the different customers across thecountry is becomes challenging day by day. In this paper, we propose anadditional new warehouse location in Pakistan using transportation cost as adecision factor. Initially the proposed warehouse will be run by the third partywarehouse service provider on temporary basis, so that it lower down theinventory level of Lahore warehouse from 0.4 million liters to 0.2 millionliters, saves approximately 1.5 Million Rs. / year with improved customerservice

A knowledge base system for overall supply chain performance evaluation : a multi-criteria decision-making approach

Due to the advancement of technology that allows organizations to collect, store, organize and use data information system for efficient decision making (DM), a new horizon of supply chain performance evaluation starts. Today, DM is shifting from “information-driven” to “data-driven” for more precision in overall supply chain performance evaluation. Based on the real-time information, fast decisions are important in order to deliver product more rapidly. Performance evaluation is critical to the success of the supply chain (SC). In managing SC, there are many decisions to be taken at each level of multi-criteria decision making (MCDM) (short-term or long-term) because of many decisions and decision criteria (attributes) that have an impact on overall supply chain performance. Therefore it is essential for decision makers to know the relationship between decisions and decision criteria on overall SC performance. However, existing supply chain performance models (SCPM) are not adequate in establishing a link between decisions and decisions criteria on overall SC performance. Most of the decisions and decision attributes in SC are conflicting in nature and performance measure of different criteria (attributes) at different levels of decisions (long-term and short-term) is different and makes it more intricate for SC performance evaluation. SC performance heavily depends on how well you design your SC. In other words, it is quite difficult to improve overall SC performance if decisions criteria (attributes) are not embedded or considered at the phase of SC design. The connection between the SC design and supply chain management (SCM) is essential for effective SC. Many companies such as Wal-Mart, Dell, etc. are successful companies and they achieve their success because of their effective SC design and management of SC activities. The purpose of this thesis is in two folds: First is to develop an integrated knowledge base system (KBS) based on Fuzzy-AHP that establish a relationship between decisions and decisions criteria (attributes) and evaluate overall SC performance. The proposed KBS assists organizations and decision-makers in evaluating their overall SC performance and helps in identifying under-performed SC function and its associated criteria. In the end, the proposed system has been implemented in a case company, and we developed a SC performance monitoring dashboard of a case company for top managers and operational managers. Second to develop decisions models that will help us in calibrating decisions and improving overall SC performance

Multi-Criteria Decision-Making Methods Application in Supply Chain Management: A Systematic Literature Review

Over the last decade, a large number of research papers, certified courses, professional development programs and scientific conferences have addressed supply chain management (SCM), thereby attesting to its significance and importance. SCM is a multi-criteria decision-making (MCDM) problem because throughout its process, different criteria related to each supply chain (SC) activity and their associated sub-criteria must be considered. Often, these criteria are conflicting in nature. For their part, MCDM methods have also attracted significant attention among researchers and practitioners in the field of SCM. The aim of this chapter is to conduct a systematic literature review of published articles in the application of MCDM methods in SCM decisions at the strategic, tactical and operational levels. This chapter considers major SC activities such as supplier selection, manufacturing, warehousing and logistics. A total of 140 published articles (from 2005 to 2017) were studied and categorized, and gaps in the literature were identified. This chapter is useful for academic researchers, decision makers and experts to whom it will provide a better understanding of the application of MCDM methods in SCM, at various levels of the decision-making process, and establish guidelines for selecting an appropriate MCDM method for managing SC activities

Sustainable warehouse evaluation with AHPSort traffic light visualisation and post-optimal analysis method

Sustainable warehousing is essential for organisations to achieve overall supply chain sustainability. Warehousing facilities have the greatest potential for reducing socio-environmental impact. Yet, both research and practice have given relatively less attention to considering all aspects of sustainability in warehouses. In order to address this gap, this study proposes combining both input from professionals and from a literature survey of triple-bottom-line theory in order to develop a sustainable warehouse criteria framework, thus contributing to sustainable organisational warehouse evaluation. The method supporting the evaluation of this framework is based on the integration of a multicriteria AHPSort traffic light visualisation technique and novel post-optimal analysis. Furthermore, the authors deployed this framework and integrated methodology in an Indian manufacturing company to evaluate and classify seven of their warehouses for decision making. The traffic light visualisation technique presents and conveys the results better than numbers. Finally, the new post-optimal analysis provides recommendations for cost efficient improvements. The findings of this study present valuable insights and guidelines for industrial managers and practitioners, especially those from the Indian manufacturing industry, for sustainable warehouse decision-making, and for improving their overall corporate sustainability performance

Analyzing the impact of environmental collaboration among supply chain stakeholders on a firm’s sustainable performance

In the era of industrialization, environmentalists are more concerned with the environment and so are continuously interested in investigating organizational factors that can facilitate the transition towards sustainability. This research systematically investigates the impact of the supply chain partner’s collaborative approach towards green practices on a firm’s sustainability performance. Stakeholder and coordination theories are used to underpin the study. A structural equation modeling technique is adopted to analyze data collected from 126 green supply chain professionals working at various manufacturing firms operating in Pakistan using a survey questionnaire. The results indicate significant and positive impacts of institution pressure and customer monitoring on the adoption of green supply chain management (GSCM) practices by organizations. This study also explains that organizational GSCM practices, external GSCM practices and performance measures have positive and significant relationships. These findings reveal that it is important for managers to address external GSCM pressures by adopting green practices and being a focal firm should undertake GSCM initiatives in collaboration with their suppliers and customers to achieve a holistic impact which ultimately leads to betterment in overall sustainability performance

The role of green recruitment on organizational sustainability performance: A study within the context of green human resource management

In light of the increasing recognition among modern business communities regarding the importance of implementing environmentally sustainable practices, this study thoroughly examines the concept of green recruitment (GR) and its subsequent impact on organizational sustainability performance (OSP). Situated within the shift from conventional to contemporary organizational frameworks that prioritize capacity, this study emphasizes the crucial importance of integrating sustainability into recruitment processes. This alignment ensures that human resource practices are in line with both environmental and organizational goals. The primary purpose emerges as a thorough examination and identification of sixteen critical factors that intersect GR and OSP, using insights from both the current literature and expert viewpoints, so this fills a crucial gap in the existing research. This study utilizes an integrated ISM-DEMATEL strategy to systematically reveal the hierarchical and relational patterns that are inherent in the connections between GR and OSP variables. This technique allows for a thorough comprehension of how these variables interact with each other. The findings highlight several important variables, emphasizing the complex network of interdependencies among the elements studied. The suggested model in this research encapsulates its originality, as it not only sheds light on the interdependent interactions for policy- and decision-makers but also establishes a foundation for future research in this field.</jats:p

Supply chain mapping for improving “visilience”: A hybrid multi‐criteria decision making based methodology

Supply chain mapping is gaining heightened attention due to its vital role in improving supply chain visibility and resilience. Despite its crucial role in uplifting supply chain resilience, the critical elements of supply chain mapping are yet to be determined. The study adopts a twofold approach to identify and prioritize the dimensions and sub‐dimensions of supply chain (SC) mapping. At the first stage, through an extensive review of literature, 43 sub‐dimensions of SC mapping were identified. In the second stage, Gray ‐ DEMATEL‐based Analytic Network Process (GDANP) was employed by taking the input from 25 experts selected from Oil and Gas industry of an emerging market. The findings reveal three major dimensions of SC mapping followed by 15 sub‐dimensions. Among the dimensions, upstream mapping contains the highest priority weights, followed by midstream and downstream mapping. The findings suggest a step‐wise strategy to adopt SC mapping where upstream mapping should be given the first priority. The major contribution of this study is to develop a framework for measuring the extent of SC mapping of a firm using GDANP

Supplier sustainability performance evaluation and selection: a framework and methodology

This study proposes a supplier sustainability performance evaluation framework for evaluating and selecting suppliers based on their sustainability performance. An integrated model which uses fuzzy-Shannon Entropy to determine the sustainability criteria weights and fuzzy-Inference system to prioritize suppliers from the individual sustainability dimensions perspective is proposed to aid in the evaluation and selection. A Pakistan manufacturing company is used to exemplify the applicability and usefulness of the proposed suppliers' sustainability performance evaluation decision framework. The results show that amongst the economic, environmental and social sustainability dimensions, three criteria, namely: ‘Quality’ (10.87%), ‘Cleaner Technology Implementation’ (11.51%) and ‘Information Disclosure’ (13.75%), respectively, are the topmost ranked criteria. Across the triple-sustainability dimensions, suppliers 3 was ranked the topmost suppliers overall. This means that, to improve the sustainability of the company's supply chain, supplier 3 is most appropriate and recommended amongst the four suppliers for partnership. Managerial implications, limitations and further research directions are discussed

Supply chain performance measurement and improvement system:a MCDA-DMAIC methodology

PurposeThe purpose of this study is to adopt a supply chain performance measurement (SCPM) framework as proposed by (Dweiri and Khan 2012) to model a novel SCPM index (SCPMI) system to measure and improve supply chain performance (SCP).Design/methodology/approachThe adopted SCPM framework developed by Dweiri and Khan (2012) is used to model a generic SCPMI framework aided by analytic hierarchy process (AHP) method and inputs from industrial experts. To exemplify the applicability and efficiency of the generic SCPMI system, an automobile assembling company from an emerging economy was used. This SCMPI system is used to measure, improve and measure post-improvement SCP guided by DMAIC (define, measure, analyze, improve and control) methodology.FindingsThe study’s initial measurement results showed an average SCP of the case company over a four-month period as 82 per cent. DMAIC methodology was used to identify inherent problems and proposed improvements. The post-improvement SCP measurement saw an improvement from an average of 82 to 83.82 per cent over the four-month period.Practical implicationsThe proposed generic SCPMI framework aided by AHP-DMAIC has been successfully implemented in a case company. After implementation, managers and decision-makers saw an improvement in their SCP. The proposed SCPMI system and results can be useful for benchmarking by manufacturing organizations for continuous SCP improvement.Originality/valueAn original SCPMI framework proposed is general in nature and can be applied in any organization

Supply chain mapping: a proposed construct

During COVID-19, supply chain (SC) mapping has appeared as one of the critical supply chain capabilities that could make a striking difference in organisations’ supply chain performance. Despite its crucial role in responding to SC disruptions, there is a void in the literature on this topic. In this context, the prime objective of the current study is to introduce a comprehensive measure of SC mapping accounting for its various dimensions. A review of the literature is conducted to identify the relevant dimensions and sub-dimensions of SC mapping. Next, two rounds of focused group discussions are conducted in order to refine the identified dimensions and to add any relevant dimensions of SC mapping. Third, we employ exploratory factor analysis to develop the construct of SC mapping. The findings reveal that SC mapping has three major dimensions, namely upstream mapping, downstream mapping, and midstream mapping, with a total 25 items. The developed construct can be used to operationalise the SC mapping and to examine its antecedents and precedents