International Journal of Supply and Operations Management
Volume:11 Issue: 1, Winter 2024

In the current competitive environment and globalization, every organization is trying continuously to get better to stay competitive with their global rivals. So, most Manufacturing companies pursue to improve their productivity to meet the highly demanding business market by using effectively the resources, eliminating wastes, enhancement of process flow, and continuous improvement. There are many tools and strategies to improve productivity. Therefore, selecting appropriate strategies is an essential problem that faces most companies. Lean Manufacturing (LM) is a powerful system that improves efficiency, productivity, quality and reduces costs in any company. One of the reasons to fail the lean program's implementation is the lack of a clear understanding about what are lean performance and its evaluation. Lean level assessment can be considered a guide for the organization through their lean journey where it is the first step that led to the control and finally to improve the enterprise performances. Nowadays fuzzy Multicriteria Decision Making (FMCDM) can be considered one of the most efficient approaches to assess the lean performance level for any manufacturing enterprise to identify if the enterprise is near or far from the ideal implementation of the lean principles. The contributions of this review paper are; highlighting on Fuzzy Technique of order preferences by similarity to ideal solution( Fuzzy TOPSIS) and Fuzzy Multi criteria Optimization and compromise solution (FuzzyVIKOR) as  distance-based methods for assessment  the current lean performance for manufacturing enterprises   and  help them to improve continuously their performance ; review the most common lean assessment methods; highlighting lean dimensions and criteria that can be used in lean assessment  by Fuzzy TOPSIS and Fuzzy VIKOR with illustrate the various criteria weighting methods. This review paper can be considered as a guide for researchers who interest in lean performance assessment that will fill some gaps in field of lean assessment level.

The present work has three broad objectives. First, it intends to develop a novel objective measurement framework for comparing corporate social responsibility (CSR) performance. The extant literature shows a plenty of work has been done for exploring the benefits of CSR. But there is a limitation of work that provides a multi-criteria based objective measurement of CSR performance in financial terms. The second objective of the current work is to examine the impact of the recent COVID-19 on CSR performance of Indian firms. Thirdly, the present study proposes a new hybrid multi-criteria decision making (MCDM) framework with multiple normalizations using two recent models such as Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) and Proximity Index Value (PIV) methods. In line with the objectives set, the ongoing work defines a new set of indicating variables to compare CSR performance from the perspectives of major stakeholders such as customer, society, government, employee, environment and shareholders. Top 20 manufacturing firms listed in the Bombay Stock Exchange (BSE)-100 in India have been selected for comparison. The study period is considered as FY 2019-20 (before pandemic) and FY 2020-21 (after pandemic). It is seen that the firms having higher market capitalization did well in their CSR performance. We observe that the overall CSR performance has not undergone any substantial changes. Further, post COVID-19 more firms from the drugs and pharmaceutical category could able to enter the top bracket. To test the reliability, a comparison with another MCDM models has been done and result is found satisfactory. The sensitivity analysis (SA) has also been conducted to investigate the stability in the outcome of the proposed model. The present work provides the policy makers a stable and reliable MCDM framework for analyzing and accessing their CSR performance with peers and evaluate their market standing to take decisions for future course of action.

In the present manuscript, it is our utmost aim and objective to comprehensively and extensively expound upon two highly innovative and remarkably novel information measures that have been adeptly and appropriately extended to encompass fuzzy sets. These measures have undergone a rigorous and meticulous scrutiny and examination with regard to axiomatic principles, and have evinced numerous and manifold advantageous properties, thus providing a compelling and highly persuasive validation of their reliability, credibility, and overall effectiveness. It is of paramount importance to note that the measures in question have been meticulously and painstakingly designed with the express aim and purpose of effectively quantifying the extent of information that is inextricably embedded and enmeshed within fuzzy sets, and are firmly grounded in the foundational and bedrock principles of information theory, which is an indisputably and irrefutably significant and substantial academic discipline. Our contributions to the field of study are truly and incontestably unparalleled, and offer a fresh, innovative, and unprecedented perspective on the study of fuzzy sets and their associated information content, which is of immense and inestimable value to the overall advancement and progress of the academic discipline.

In this paper, we consider a real-world retailer-led three-echelon CLSC with substitutable products in a beverage industry consisting of a manufacturer, a distributor, and a retailer. The manufacturer produces the same product in two different types of packaging, one being a returnable glass bottle (RGB) and the other being a disposable bottle (OW) and the consumer chooses depending on their preference. The RGB is then returned via the specialized distributor, who must ensure the sorting of the returned bottles and their reverse logistics back to the manufacturer. We analyse the CLSC with the dominant role of the retailer and compare the Stackelberg equilibrium with the Nash equilibrium where all CLSC members are equally strong. We prove that the CLSC can make higher profits if the product mix is skewed towards the RGB product. Our analysis also shows that a retailer-led CLSC can be coordinated with an RS contract to achieve a fair share of a double increase in total profits for all partners if the retailer manages its leadership position and maximises its bargaining power. From a game theoretic perspective, we show that our Stackelberg equilibrium is also acceptable in the pure vertical Nash game. Furthermore, the sensitivity analysis explains why it is so difficult to negotiate and coordinate a real CLSC in a Fast Moving Consumer Goods (FMCG) sector, because it is unlikely that the dominant retailer would participate in the coordination negotiations and give up its margins for the benefit of all CLSCs, which is necessary to ensure the effect of reducing prices for the final consumer. This is all set in the real beverage CLSC using actual cost parameters thus providing valuable managerial insights.

This study aims to examine the direct influence of green marketing on the purchase choices of packaged drinking water (AMDK). Furthermore, the study seeks to analyze the immediate effect of green marketing on the brand image of bottled water goods as well as the direct correlation between brand image and consumers' purchase choices of bottled water products. The study seeks to examine the indirect impact of green marketing on brand image-mediated purchase choices for bottled drinking water products. The influence of green marketing on the consumer's choice to purchase bottled drinking water (AMDK) is both direct and indirect, with the brand image serving as a mediating factor. The present study employs a quantitative/positivistic research approach, which is grounded in the belief that symptoms can be categorized and that their relationships can be understood in terms of cause and effect. Consequently, researchers may effectively investigate the phenomenon by concentrating on a limited number of factors. The research shows green marketing has a positive and significant effect on brand image, green marketing has a positive and significant effect on buyer satisfaction, and brand image has a positive and significant effect on buyer satisfaction. The perception of a firm plays a crucial role in influencing purchasing decisions through green marketing. When a company uses good green marketing, it will not only affect people's decisions to buy, but it will also affect how people think of the brand, which will have an indirect effect on people's decisions to buy. This study investigates how green marketing theory and brand image affect customers' bottled drinking water (AMDK) purchases, which is important for theoretical understanding. This guideline helps AMDK producers embrace green marketing methods to maintain their product brand image. The value of the study lies in the research object, namely bottled drinking water products, especially those that have implemented environmentally friendly products and green marketing as their marketing strategy. Brand image is placed as a mediating variable, which is also a novelty of research, especially for environmentally friendly product brands.

One of the important issues in Iran is to monitor imports and business processes as well as exchange rates. Given the government’s supportive policies for traders, how to implement these policies is challenging. An strategy to implement targeted oversight and policies is to control the actions of active traders based on their background. Data Envelopment Analysis (DEA) is one of the key tools to achieve this goal. The present research is based on Slack-Based Measure DEA Model (SBM-DEA) with an output-based approach which rates traders using real data as well as their background. In this model, 30 input indicators and six output indicators were first considered. Subsequently, given the correlation between them, the number was reduced to five input and four output indicators. After the extraction of effective input and output indicators, traders’ efficiency was measured and rated using DEA model. Then, well-respected traders would receive facilities and various supports. To evaluate the performance of the model, the traders also were ranked using the Best Worst Method (BWM and after results shows better performance of the DEA model. Another result and application is the use of reference decision-making units, who indicate traders that are expected to have good performance by the market knowledge. Recognizing these units allows policy-makers to reduce other traders’ risk by disseminating their behavior. Another important application is traders’ classifications. By knowing the traders, the policy-maker reference can make a good classification of them, which is necessary for different resource allocation or facilitating policies.

This study develops an integrated classic-interval-valued fuzzy TOPSIS approach to assess performance of different departments of a hospital. Although the concept of performance measurement has been discussed in previous studies, its concurrent integration with lean, agile, and green strategies is less investigated. Therefore, this research has been completed in three linked phases as follows. Firstly, the critical metrics of lean, agile, and green strategies are extracted from previous literature. Secondly, a fuzzy TOPSIS approach is developed to compare three departments of a hospital using the investigated metrics of previous phase. According to the obtained results of this phase, the eye, and emergency departments are the best and worst departments, respectively. Next, the obtained results are checked by an interval-valued fuzzy TOPSIS approach for further investigation in the third phase. Similarly, approving the previous results, eye department provides the best performance according to the second approach.  As a contribution, this research showed that different MCDM techniques might provide a same result. Furthermore, the developed methodology can be applied to assess and compare the performance of different departments.