The Measurement of Sustainable Regional Manufacturing Industry: The Case of China

Since the introduction of Made in China 2025 and its focus on sustainable development and manufacturing industry transformation, appropriate evaluation methods to accurately assess the development of China’s manufacturing industry have become essential. Therefore, this research constructed an innovative evaluation index system for manufacturing development based on seven dimensions: innovation, structural optimization, economic benefits, efficiency enhancements, green development, international competition, and social benefits. An objective combination weighted-gray correlation-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) evaluation model was applied to the Sichuan Province manufacturing industry data from 2009 to 2018 to create a representative sample, in which the overall development level from 2009 to 2016 took on an inverted U-shaped curve that reached its maximum in 2013, fell to its lowest point in 2016, and then began a steady upward trend marked by innovation and efficiency improvements; however, sustainability fell. Based on these results, this research provides a scientific reference for policy-makers with recommendations for innovation-driven development strategies, green development promotion, and social benefit improvements with the aim of promoting more sustainable development of China's manufacturing industry.

Application of Fuzzy Topsis and Taguchi Methods for Optimization Problems With Disruptive Risk

Ranking and choosing research projects and analyzing experiments are usually difficult and complex responsibilities for professional research councils at universities and research centers. Its complexity stems from having more than one variable in each project, and the participation of many decision-makers in the ranking process and selection of research projects based on many variables. The fuzzy set theory provides the required flexibility to show the uncertainty about the lack of knowledge, and also it can manage the uncertainty in the real world that the values of criteria are not defined properly. For this purpose, in the environment where the criteria of research projects are vaguely defined, the ranking methods such as Taguchi, which can reduce the number of experiments and making process more efficient, can be used for quality design in designing and processing product. In this work, first of all, the authors review fuzzy TOPSIS technique and the Taguchi method as well; then they approach research efficiency and optimization of the level of effective parameters in an experiment.

Multi-Criteria Analysis in the Decision-Making Approach for the Linear Ordering of Urban Transport Based on TOPSIS Technique

The effects of urban transport are highly concerning. The rapid urbanization and motorization in smart cities have a huge impact on sustainability. The goal of the paper is to analyse the smart cities selected, in terms of the urban transport. This paper presents an overview of research works published between 1991 and 2020 concerning urban transport and MCDM (multi-criteria decision making). The author highlights the importance of decision-making criteria and their weight, as well as techniques. Seven criteria and forty-four objects were used as the input of the approach. The entropy weight method was used to compute the weight of each criterion. The TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) was applied to calculate the assessment and ranking of transport performance for each smart city. Portland was found to be the best location for transport enterprises and projects; Tbilisi was ranked last. The values of the relative closeness coefficient ranged from 0.03504 to 0.921402. Finally, some suggestions for future research are discussed.

Determination of the Level of Products Novelty Importance for Developing Product Innovative Policy

To substantiate the range of products of the enterprise there is a need to assess the potential of products in terms of the company’s ability to manufacture these products, consumer opportunities to meet their needs for these products, and market opportunities to ensure a strategic position among similar products. The study used structural-logical and causal methods of analysis to determine the structure of the novelty of goods. The numerical method of multi-criteria decision making TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) was used to rank the product range of new products according to the level of importance of novelty. Weights of individual components to assess the importance level of novelty in the enterprise were determined by the method of analysis of hierarchies of T.L. Saati. The study used the classification of novelty by its functional focus, according to which consumer, market, and manufacturing novelty of goods are distinguished. The importance of novelty for the manufacturer is the conformity of the product to its innovative development strategy, determination of its place in the market, and prospects for further activities. The importance of the novelty of a new product for the company is proposed to be defined as a measure of the importance of the novelty level of the product for the development of the optimal product range in the product innovative policy of the enterprise. To assess the level of significance of the novelty of goods, criteria of novelty by its types were proposed. According to the results of the study it was found that industrial novelty characterizes the level of use of new technologies in the enterprise, market – the position of a new product on the market among analogues, and consumer – the level and way to meet consumer needs. Further research should relate to the development of appropriate guidelines for the formation of product range and its management based on the assessment of the level of significance of novelty

An Attempt to Apply Canonical Analysis to Investigate the Dependencies between the Level of Organic Farming Development in Poland and the Chosen Environmental Determinants

Polish organic agriculture has faced rapid growth in the recent two decades. Nevertheless, one may observe considerable discrepancies in organic agriculture development in specific regions of Poland. Therefore, it is necessary to recognize the key conditions for this development and its spatial differentiation. Since the relationship between organic farming and the natural environment has a fundamental meaning in this production system, it is crucial to study the development determinants of environmental characters. Thus the paper aims to identify the level of organic farming development in Polish districts and to investigate multidimensional relations between this level and selected environmental conditions. In order to identify the range and direction of those multidimensional relations between the discussed phenomena, canonical analysis was applied. Within the conducted study, proprietary synthetic measures were constructed (using the TOPSIS—Technique for Order of Preference by Similarity to Ideal Solution), and linear ordering of the objects described by a large number of variables was employed. To define the strength and direction of the dependencies among constructed synthetic indices of the level of organic farming development and environmental conditions, a correlation analysis was performed. All 380 districts in Poland were considered as the investigated objects. Based on the variables describing selected environmental conditions, one may explain nearly 26.7% of the variance of variables related to organic agriculture development.

Various Trade-Off Scenarios in Thermo-Hydrodynamic Performance of Metal Foams Due to Variations in Their Thickness and Structural Conditions

The long standing issue of increased heat transfer, always accompanied by increased pressure drop using metal foams, is addressed in the present work. Heat transfer and pressure drop, both of various magnitudes, can be observed in respect to various flow and heat transfer influencing aspects of considered metal foams. In this regard, for the first time, orderly varying pore density (characterized by visible pores per inch, i.e., PPI) and porosity (characterized by ratio of void volume to total volume) along with varied thickness are considered to comprehensively analyze variation in the trade-off scenario between flow resistance minimization and heat transfer augmentation behavior of metal foams with the help of numerical simulations and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) which is a multi-criteria decision-making tool to address the considered multi-objective problem. A numerical domain of vertical channel is modelled with zone of metal foam porous media at the channel center by invoking LTNE and Darcy–Forchheimer models. Metal foams of four thickness ratios are considered (1, 0.75, 0.5 and 0.25), along with varied pore density (5, 10, 15, 20 and 25 PPI), each at various porosity conditions of 0.8, 0.85, 0.9 and 0.95 porosity. Numerically obtained pressure and temperature field data are critically analyzed for various trade-off scenarios exhibited under the abovementioned variable conditions. A type of metal foam based on its morphological (pore density and porosity) and configurational (thickness) aspects, which can participate in a desired trade-off scenario between flow resistance and heat transfer, is illustrated.

Community Detection Based on Density Peak Clustering Model and Multiple Attribute Decision-Making Strategy TOPSIS

Community detection is one of the key research directions in complex network studies. We propose a community detection algorithm based on a density peak clustering model and multiple attribute decision-making strategy, TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). First, the two-dimensional dataset, which is transformed from the network by taking the density and distance as the attributes of nodes, is clustered by using the DBSCAN algorithm, and outliers are determined and taken as the key nodes. Then, the initial community frameworks are formed and expanded by adding the most similar node of the community as its new member. In this process, we use TOPSIS to cohesively integrate four kinds of similarities to calculate an index, and use it as a criterion to select the most similar node. Then, we allocate the nonkey nodes that are not covered in the expanded communities. Finally, some communities are merged to obtain a stable partition in two ways. This paper designs some experiments for the algorithm on some real networks and some synthetic networks, and the proposed method is compared with some popular algorithms. The experimental results testify for the effectiveness and show the accuracy of our algorithm.

INTEGRATED APPROACH OF FUZZY MULTI-ATTRIBUTE DECISION MAKING AND DATA MINING FOR CUSTOMER SEGMENTATION

This research work focuses on integrating the multi attribute decision making with data mining in a fuzzy decision environment for customer relationship management. The main objective is to analyse the relation between multi attribute decision making and data mining considering a complex problem of ordering customers segments, which is based on four criteria of customer’s life time value, viz. length (L), recency (R), frequency (F) and monetary value (M). The proposed integrated approach involves fuzzy C-means (FCM) cluster analysis as data mining tool. The experiment conducted using MATLAB 12.0 for identifying eight clusters of customers. The two multi attribute decision making tools i.e., fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) are used for ranking these identified clusters. The applicability of the integrated decision making technique is also demonstrated in this paper considering the case of Indian retail sector. This research collected responses from nine experts from Indian retail industry regarding their perception of relative importance of four criteria of customer life value and evaluated weights of each criterion using fuzzy AHP. Transaction data of 18 months of the case retail store was analysed to segment 1,600 customers into eight clusters using fuzzy c-means clustering analysis technique. Finally, these eight clusters were ranked using fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The findings of this research could be helpful for firms in identifying the more valuable customers for them and allocate more resources to satisfy them. The findings will be also helpful in developing different loyalty program strategies for customers of different clusters.

Penerapan Metode Topsis Untuk Pemilihan Vendor Terbaik

The selection of vendors to work on a project is an activity that must be carried out effectively and precisely so that the project is carried out in accordance with business needs and does not suffer losses. To get the best vendor ranking, you can use the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) calculation method. TOPSIS method is a method that generates rankings by calculating the distance between the best solution and the worst solution. The steps to calculate using TOPSIS are identification of alternatives and their values, create a decision matrix, normalize the matrix, calculate the normalization matrix, look for positive and negative solutions, calculate the distance between positive and negative solutions, and calculate relative closeness and sort preferences. In this study using 8 criteria and 5 alternative vendors. Research method using research and development. This method will produce a prototype. The results of the calculation of TOPSIS obtained vendor c who gets the highest score and vendor b with the lowest rank

Sustainable recovery for digital entrepreneurs with shared resources: enablers, challenges and solutions

Purpose The purpose of this study is to identify important criteria for sustainable recovery of digital entrepreneurship from distress situation using shared resources. During pandemic disruption, the importance of sharing economy in managing business efficiency is reflected through this research. Design/methodology/approach The present study advances the knowledge on shared resources in business by integrating case study approach with multi criteria decision-making (MCDM) model. A fuzzy analytic hierarchy process approach is adopted to compute criteria weights, and a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) technique is used to rank the sharing economy entrepreneurial ventures during COVID-19 pandemic in the context of emerging economy. Findings The present study identified five most important enablers (technological innovation, technology expertise, convergence of virtual and physical spaces, collaboration rather than competition, and benefits to underserved groups through transparency) for sustainable recovery of sharing economy ventures in emerging economy. For example, the study highlights online tutoring through shared intellect as the most sought after sharing economy venture during pandemic disruption, which fulfills the identified enablers. Practical implications The proposed framework provides an accurate decision support tool to rank the various identified potential enablers of sharing economy during disruptions. Further, the approach is practically relevant to sharing economy entrepreneurs in selecting the best approach to recover sustainability during pandemic. Originality/value The study is unique in addressing the need of sustainability for digital ventures via sharing economy approach in emerging economy (India). To develop a conceptual framework, the present study incorporates a case based approach together with the hybrid MCDM model. Further, the extant literature on disruptions is enhanced by prioritizing the enablers for sharing economy during pandemic.