Enablers of post-COVID-19 customer demand resilience: Evidence from fast-fashion MSMEs

This study aims to analyse the resilience of customer demand management in post-coronavirus disease (COVID) 2019, using fast fashion as an example. The paper provides insights for potential applications to micro, small, and medium enterprises (MSMEs). Based on the qualitative analysis and an integrated PDCA-DEMATEL-fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) methodology of fuzzy multi-criteria decision-making, we explored and prioritised the enablers of resilience management for fast-fashion MSMEs. The results reveal that the highest priority enabler is maintaining customer loyalty. Other enablers are associated with e-commerce endorsement, a customer-focused assortment of items, and flexible store operations. The study findings will enable fast-fashion MSMEs to develop effective actions and priorities in operations efforts to promote post-pandemic recovery. Despite the importance of the resilience project and the changing fast-fashion customer patterns, only a handful of studies have explored how resilience can be managed in this field. Thus, the findings can contribute to closing this gap in the context of operations resilience research as well as MSME operations

Application of fuzzy TOPSIS framework for selecting complex project in a case company

Purpose This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions. Design/methodology/approach The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations. Findings A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works. Research limitations/implications The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity. Originality/value The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.© 2021, Ahm Shamsuzzoha, Sujan Piya and Mohammad Shamsuzzaman. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/legalcodefi=vertaisarvioitu|en=peerReviewed

Sustainable and agile manufacturing outsourcing partner selection: a literature review

[EN] Outsourcing to third party to manage non-core activities helps the firm to focus on core activities. Manufacturing firms are outsourcing product development, manufacturing, logistics, customer care etc. to enhance production capacity and flexibility, and to reduce operational costs, which in turn can improve profitability and competitive advantage of the enterprise. Sustainability in operations and supply chain is gaining momentum due to increased global environmental concern, pressures from consumers and communities, and enforced regulations. Volatile and uncertain business environment necessitates the adoption of agility and flexibility to effectively manage manufacturing and supply chain. Globalisation has made the market very competitive and hence manufacturing firms are adopting manufacturing outsourcing to third parties. Selecting a sustainable and agile manufacturing outsourcing partner (MPS) is crucial as it will improve sustainability, efficiency, and effectiveness of the supply chain and competitive advantage to the firm. Detailed literature review on sustainable and agile manufacturing outsourcing partner selection has been carried out from EBSCO data base and Goggle scholar. Selection criteria used are classified into agile, operational, economic, environmental and social. The techniques use are mostly multi criteria decision making methods (MCDM) while few have adopted programming techniques. Discussion, implication and the scope of future work is also provided.Akhtar, M. (2022). Sustainable and agile manufacturing outsourcing partner selection: a literature review. International Journal of Production Management and Engineering. 10(2):143-158. https://doi.org/10.4995/ijpme.2022.1680714315810

A Fuzzy AHP Approach for Supplier Selection Problem: A Case Study in a Gear Motor Company

Suuplier selection is one of the most important functions of a purchasing department. Since by deciding the best supplier, companies can save material costs and increase competitive advantage.However this decision becomes compilcated in case of multiple suppliers, multiple conflicting criteria, and imprecise parameters. In addition the uncertainty and vagueness of the experts' opinion is the prominent characteristic of the problem. therefore an extensively used multi criteria decision making tool Fuzzy AHP can be utilized as an approach for supplier selection problem. This paper reveals the application of Fuzzy AHP in a gear motor company determining the best supplier with respect to selected criteria. the contribution of this study is not only the application of the Fuzzy AHP methodology for supplier selection problem, but also releasing a comprehensive literature review of multi criteria decision making problems. In addition by stating the steps of Fuzzy AHP clearly and numerically, this study can be a guide of the methodology to be implemented to other multiple criteria decision making problems.Comment: Published in "International Journal of Managing Value and Supply Chains (IJMVSC) Vol.4, No. 3, September 2013

Location decision for foreign direct investment in ASEAN countries (A TOPSIS Approach)

TOPSIS approach is applied to select the most suitable ASEAN countries for attracting FDI inflows. The proposed approach also provides a relatively simple tool for this strategic decision making problem. Within the model, ten indicators are defined as determinants of FDI inflows. By using TOPSIS method, the capacity and attraction of ASEAN countries is evaluated and given final rank for period 2000-2005. Results indicate that Singapore is the most attractive for investment among ASEAN countries while ranking of some countries have changed during these years.Foreign direct investment, ASEAN, Ranking, TOPSIS

PENGEMBANGAN SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SUPPLIER MENGGUNAKAN METODE TOPSIS PADA PERUSAHAAN FURNITURE

Sentra Industri Kecil Mebel Trangsan Sukoharjo adalah beberapa perusahaan yang bergerak di bidang industri furniture. Bahan baku utama yang digunakan perusahaan adalah kayu jati. Ada beberapa supplier yang memasok kebutuhan perusahaan. Sebelumnya memilih supplier dengan cara sederhana dan manual, sehingga proses pemilihan supplier kurang efisien dan hasilnya tidak optimal. Hal ini memunculkan beberapa permasalahan, antara lain supplier tidak dapat memenuhi kebutuhan dalam hal volume kayu, sulitnya perusahaan untuk mendapatkan kebutuhan bahan baku pada harga yang kompetitif, jadwal pengiriman menjadi mundur, dan biaya produksi membengkak. Selain itu kondisi supplier selalu berubah-ubah mengikuti perkembangan dunia usaha. Oleh karena itu, dibutuhkan Sistem Pendukung Keputusan yang bersifat dinamik, sehingga perubahan yang terjadi pada supplier dapat dengan cepat diperhitungkan dan prioritas pemilihan supplier yang terpilih dapat segera tersedia. Perancangan sistem melalui tahapan perancangan proses, perancangan database dan perancangan user interface. Penelitian menggunakan metode TOPSIS, yang digunakan untuk meranking atau menentukan prioritas supplier. Hasil dari penelitian ini adalah sebuah Sistem Pendukung Keputusan yang dapat membantu perusahaan dalam memilih supplier. Kata kunci: Sistem Pendukung Keputusan, Pemilihan Supplier, TOPSIS, Database, User Interface