Risk quantification in cold chain management: a federated learning-enabled multi-criteria decision-making methodology

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Henry Lau ◽  
Yung Po Tsang ◽  
Dilupa Nakandala ◽  
Carman K.M. Lee
Keyword(s):  
Decision Making ◽  
Evaluation System ◽  
Small And Medium Enterprises ◽  
Handling Time ◽  
Cold Chain ◽  
Pairwise Comparisons ◽  
Temperature Sensitive ◽  
Multi Criteria Decision Making ◽  
Firm Level ◽  
Content Type

PurposeIn the cold supply chain (SC), effective risk management is regarded as an essential component to address the risky and uncertain SC environment in handling time- and temperature-sensitive products. However, existing multi-criteria decision-making (MCDM) approaches greatly rely on expert opinions for pairwise comparisons. Despite the fact that machine learning models can be customised to conduct pairwise comparisons, it is difficult for small and medium enterprises (SMEs) to intelligently measure the ratings between risk criteria without sufficiently large datasets. Therefore, this paper aims at developing an enterprise-wide solution to identify and assess cold chain risks.Design/methodology/approachA novel federated learning (FL)-enabled multi-criteria risk evaluation system (FMRES) is proposed, which integrates FL and the best–worst method (BWM) to measure firm-level cold chain risks under the suggested risk hierarchical structure. The factors of technologies and equipment, operations, external environment, and personnel and organisation are considered. Furthermore, a case analysis of an e-grocery SC in Australia is conducted to examine the feasibility of the proposed approach.FindingsThroughout this study, it is found that embedding the FL mechanism into the MCDM process is effective in acquiring knowledge of pairwise comparisons from experts. A trusted federation in a cold chain network is therefore formulated to identify and assess cold SC risks in a systematic manner.Originality/valueA novel hybridisation between horizontal FL and MCDM process is explored, which enhances the autonomy of the MCDM approaches to evaluate cold chain risks under the structured hierarchy.

scholarly journals How to Build up the Loan - Evaluation System toward Small and Medium Enterprises between Taiwan and China’s Commercial Banks？ The Application for Multi Criteria Decision Making

2016 ◽  
Vol 9 (3) ◽  
pp. 121
Author(s):  
Shu Hui Lan ◽  
Jia Yi Cheng ◽  
Sheng Guo
Keyword(s):  
Decision Making ◽  
Commercial Banks ◽  
Evaluation System ◽  
Influence Factor ◽  
Small And Medium Enterprises ◽  
Mainland China ◽  
Assessment Method ◽  
Multi Criteria Decision Making ◽  
Delphi Approach ◽  
Medium Enterprises

<p>Because of the financial market fast development between Taiwan and Mainland China, commercial banks, sometimes, cannot have an efficient method to investigate loan credentials for small and medium enterprises. Without efficient methods, commercial banks are forced to undertake the unnecessary default risks. The article chooses the behaviors of commercial banks between Mainland China and Taiwan to become study target. The purpose is to investigate the assessment method and influence factor of commercial banks toward small and medium enterprises for loan. Through modified Delphi approach and Fuzzy Analytic Hierarchy Process (FAHP) in multi-criteria decision-making (MCDM), the article attempts to analyze the decision-making measure of loan for commercial banks toward small and medium enterprises. From the results of practical evidence, the loan assessment measure of commercial banks between Taiwan and Mainland China is quite different. During loan assessment, China commercial banks focus on the debt-paying ability; on the contrary, Taiwan commercial banks focus on profitability of enterprises. The practical approved result of the study has supplied the insufficient data for related study articles in the past. More, the study can also be an important reference for perform related tasks in Taiwan’s and China’s commercial banks.</p>

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huimin Li ◽  
Limin Su ◽  
Jian Zuo ◽  
Xiaowei An ◽  
Guanghua Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Public Procurement ◽  
Unit Price ◽  
Data Driven ◽  
Relative Distance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Content Type ◽  
The Government

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

scholarly journals SOLUTION OF A MULTI-CRITERIA DECISION- MAKING PROBLEM ON BASE OF PROMETHEE METHOD

2020 ◽  
Author(s):  
Salimov Vagif Hasan Oglu
Keyword(s):  
Decision Making ◽  
Pairwise Comparison ◽  
Preference Function ◽  
Pairwise Comparisons ◽  
Multi Criteria Decision Making ◽  
Job Selection ◽  
Decision Making Problem ◽  
Practice Problem ◽  
Promethee Method ◽  
Large Groups

Multi criteria decision making problem was considered. Review of existing multi criteria decision making methods was presented. Methods of solving this problem can be divided into two large groups: methods using the aggregation of all alternatives according to all criteria and the solution of the obtained one-criterion problem, the second group is associated with the procedure of pairwise comparisons. Promethee method have been considered with details. This method is based on the pairwise comparison of alternatives and specific aggregation procedures. The preference function are considered for minimization and maximization cases. As practice problem the job selection is considered. Three important criteria are used: salary, time, risk. The results of all computations are presented.

scholarly journals Redistributed manufacturing system under uncertain evaluation using multi criteria decision making

2021 ◽  
Vol 12 (3) ◽  
pp. 3895-3908
Author(s):  
Ponugupati Narendra Mohan Et.al
Keyword(s):  
Decision Making ◽  
Research Work ◽  
Dynamic Programming Algorithm ◽  
Big Data Analytics ◽  
Global Market ◽  
Programming Algorithm ◽  
Multi Criteria Decision Making ◽  
Firm Level ◽  
Data Set ◽  
Value Analysis

Man In recent day’s occurrence of a global crisis in Environmental (Emission of pollutants) and in Health (Pandemic COVID-19) created a recession in all sectors. The innovations in technology lead to heavy competition in global market forcing to develop new variants especially in the automobile sector. This creates more turbulence in demand at the production of new models, maintenance of existing models that are obsolete while implementation of Bharat Standard automobile regulatory authority BS-VI of India. In this research work developed a novel model of value analysis is integrated by multi-objective function with multi-criteria decision-making analysis by incorporating the big data analytics with green supply chain management to bridge the gap in demand to an Indian manufacturing sector using a firm-level data set using matrix chain multiplication dynamic programming algorithm and the computational results illustrates that the algorithm proposed is effective.

The internationalization strategies of rapidly internationalizing high-tech UK SMEs

2014 ◽  
Vol 26 (5) ◽  
pp. 421-448 ◽  
Author(s):  
Dave Crick ◽  
James Crick
Keyword(s):  
Decision Making ◽  
Small And Medium Enterprises ◽  
Potential Effect ◽  
Small Sample ◽  
High Tech ◽  
Niche Markets ◽  
Content Type ◽  
Parental Decision Making ◽  
Internationalization Strategies ◽  
Medium Enterprises

Purpose – The purpose of this paper is to investigate aspects of causation and effectuation decision-making in respect of the planned and unplanned nature of the internationalization strategies of a small sample of rapidly internationalizing, high-tech UK small and medium enterprises (SMEs). These exhibit four different rates of scale of international intensity (percentage of overseas sales to total sales) and market scope (geographical coverage and commitment). Design/methodology/approach – Interviews with managers of 16 independently owned high-technology-oriented manufacturing SMEs were undertaken in this investigation to reduce the potential effect of bias from parental decision-making and firm size, also trade sectoral conditions. These were drawn from an existing database. Findings – Aspects of both causation and effectuation logic were evident in planned and unplanned aspects of decision-making. Moreover, industry factors were seen to affect internationalization strategies in various ways and not least in respect of the need to exploit windows of opportunity in international niche markets and the usefulness of utilizing managers’ experience and networks in the sector in which firms operated. Originality/value – The contribution of this study is to build on earlier work where authors have used different terminology to describe firms that have internationalized soon after their foundation. Specifically, with respect to the planned versus unplanned nature of respective internationalization strategies and the causation as opposed to effectuation logic in decision-making.

A multiple criteria group decision-making approach for the assessment of small and medium-sized enterprise competitiveness

2019 ◽  
Vol 57 (2) ◽  
pp. 480-500 ◽  
Author(s):  
Joana M. Gonçalves ◽  
Fernando A.F. Ferreira ◽  
João J.M. Ferreira ◽  
Luís M.C. Farinha
Keyword(s):  
Decision Making ◽  
Evaluation System ◽  
Cognitive Mapping ◽  
Assessment System ◽  
Senior Managers ◽  
Content Type ◽  
Face To Face ◽  
Decision Making Processes ◽  
Constructivist Epistemology ◽  
Study Context

PurposeSmall- and medium-sized enterprises (SMEs) have become increasingly important in national and international markets because they contribute to the development of local and national economies. SMEs often face serious challenges when competing with multinational companies. The purpose of this paper is to develop a method for assessing SMEs’ competitiveness.Design/methodology/approachBased on a constructivist epistemology, this study makes an integrated use of cognitive mapping and the measuring attractiveness by a categorical-based evaluation technique (MACBETH). To this end, face-to-face sessions were conducted with a panel of entrepreneurs and senior managers who deal with the challenges of maintaining SME competitiveness every day. The proposed assessment system was tested and validated by the panel members.FindingsThe methodological processes adopted in this study provide promising results for decision makers seeking to identify the most competitive SMEs. Specifically, the results emphasize, among other points, the importance of innovation and the human dimension to gaining competitive advantages.Research limitations/implicationsThe evaluation system developed in this study is extremely versatile and confirms the usefulness of integrating cognitive mapping and MACBETH to facilitate evaluations of SME competitiveness. However, due to its idiosyncratic and process-oriented nature, generalizations need to be done with caution.Practical implicationsThe proposed method can be valuable to researchers seeking to develop mechanisms for evaluating SMEs’ entrepreneurial performance and include specialized know-how and sensemaking in organizational decision-making processes.Originality/valueThe integrated use of cognitive maps and MACBETH contributes to a better understanding of how to assess SMEs’ competitiveness. No prior work reporting the use of this dual methodology in this study context has been found.

Happiness at work: a multi-criteria decision-making approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rinki Dahiya ◽  
Juhi Raghuvanshi
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Transformational Leadership ◽  
Design Methodology ◽  
Causal Relation ◽  
Multi Criteria Decision Making ◽  
Human Resource Managers ◽  
Content Type ◽  
Resource Managers ◽  
Causal Framework

Purpose Researchers have strived to identify the factors enhancing happiness at work (HAW), and the causal relations among the enablers of happiness remained underexplored. Therefore, this study aims to map and prioritize the causal relation structures of enablers of HAW. Design/methodology/approach Data were collected from key representatives of information technology (IT) firms located in India. A framework based on the cause and effect relationship among enablers of HAW is proposed, and to establish this causality, the decision-making trial and evaluation laboratory (DEMATEL) technique was applied. Findings The findings indicate five out of 12 enablers as causal, namely, transformational leadership, authentizotic work climate, person–organization work fit, organizational virtuousness and meaningfulness in work. Originality/value Human resource managers, organizational policymakers and scholars will gain greater understanding through this causal framework of enablers of HAW. Knowledge and facilitation of these enablers will aid in nurturing a happy workplace.

Lean in higher education

2019 ◽  
Vol 27 (1) ◽  
pp. 82-102 ◽  
Author(s):  
Yigit Kazancoglu ◽  
Yesim Deniz Ozkan-Ozen
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Business School ◽  
Stage Structure ◽  
Fuzzy Decision Making ◽  
Multi Criteria Decision Making ◽  
Stage Model ◽  
Content Type ◽  
Road Map ◽  
Multi Stage

PurposeThis research aims to investigate and define the eight wastes of lean philosophy in higher education institutions (HEIs) by proposing a multi-stage model.Design/methodology/approachThe authors have used a specific multi-criteria decision-making method, fuzzy decision-making trial and evaluation laboratory, to investigate the cause–effect relationships and importance order between criteria for wastes in HEIs. In total, 22 criteria were categorized under eight wastes of lean. The study was implemented in a business school with the participation of faculty members from different departments.FindingsThe results showed that the most important wastes in the business school selected were repeated tasks, unnecessary bureaucracy, errors because of misunderstanding/communication problems, excessive number of academic units and creation of an excessive amount of information. Another important result was that all the sub-wastes of talent were in the causes group, while motion and transportation wastes were in the effect group.Practical implicationsA road map to guide lean transformation for HEIs is proposed with a multi-stage model and potential areas for improvement in HEIs were presented.Originality/valueThis study proposes a multi-stage structure by applying multi-criteria decision-making to HEIs, focussing on wastes from a lean perspective.

Optimizing time–cost in generalized construction projects using multiple-objective social group optimization and multi-criteria decision-making methods

2020 ◽  
Vol 27 (9) ◽  
pp. 2287-2313 ◽  
Author(s):  
Duc Hoc Tran
Keyword(s):  
Decision Making ◽  
Construction Projects ◽  
Project Managers ◽  
Multiple Objective ◽  
Cost Curve ◽  
Multi Criteria Decision Making ◽  
Construction Process ◽  
Time Cost ◽  
Content Type ◽  
Social Group Optimization

PurposeProject managers work to ensure successful project completion within the shortest period and at the lowest cost. One of the main tasks of a project manager in the planning phase is to generate the project time–cost curve, and furthermore, to determine the most appropriate schedule for the construction process. Numerous existing time–cost tradeoff analysis models have focused on solving a simple project representation without regarding for typical activity and project characteristics. This study aims to present a novel approach called “multiple-objective social group optimization” (MOSGO) for optimizing time–cost decisions in generalized construction projects.Design/methodology/approachIn this paper, a novel MOGSO to mimic the time–cost tradeoff problem in generalized construction projects is proposed. The MOSGO has slightly modified the mechanism operation from the original algorithm to be a free-parameter algorithm and to enhance the exploring and exploiting balance in an optimization algorithm. The evidential reasoning technique is used to rank the global optimal obtained non-dominated solutions to help decision makers reach a single compromise solution.FindingsTwo case studies of real construction projects were investigated and the performance of MOSGO was compared to those of widely considered multiple-objective evolutionary algorithms. The comparison results indicated that the MOSGO approach is a powerful, efficient and effective tool in finding the time–cost curve. In addition, the multi-criteria decision-making approaches were applied to identify the best schedule for project implementation.Research limitations/implicationsAccordingly, the first major practical contribution of the present research is that it provides a tool for handling real-world construction projects by considering all types of construction project. The second important implication of this study derives from research finding on the hybridization multiple-objective and multi-criteria techniques to help project managers in facilitating the time–cost tradeoff (TCT) problems easily. The third implication stems from the wide-range application of the proposed model TCT.Practical implicationsThe model can be used in early stages of the construction process to help project managers in selecting an appropriate plan for whole project lifecycle.Social implicationsThe proposal model can be applied to multi-objective contexts in diversified fields. Moreover, the model is also a useful reference for future research.Originality/valueThis paper makes contributions to extant literature by: introducing a method for making TCT models applicable to actual projects by considering general activity precedence relations; developing a novel MOSGO algorithm to solving TCT problems in multi-objective context by a single simulation; and facilitating the TCT problems to project managers by using multi-criteria decision-making approaches.

Multi-objective mathematical model based on fuzzy hybrid multi-criteria decision-making and FMEA approach for the risks of oil and gas projects

2020 ◽  
Vol 18 (6) ◽  
pp. 1997-2016
Author(s):  
Mohammad Khalilzadeh ◽  
Rose Balafshan ◽  
Ashkan Hafezalkotob
Keyword(s):  
Decision Making ◽  
Oil And Gas ◽  
Programming Model ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Multi Objective ◽  
Response Strategies ◽  
Fuzzy Environment ◽  
Comprehensive Framework ◽  
Grey Relational

Purpose The purpose of this study is to provide a comprehensive framework for analyzing risk factors in oil and gas projects. Design/methodology/approach This paper consists of several sections. In the first section, 19 common potential risks in the projects of Pars Oil and Gas Company were finalized in six groups using the Lawshe validation method. These factors were identified through previous literature review and interviews with experts. Then, using the “best-worst multi-criteria decision-making” method, the study measured the weights associated with the performance evaluation indicators of each risk. Consequently, failure mode and effects analysis (FMEA) and the grey relational analysis (GRA)-VIKOR mixed method were used to rank and determine the critical risks. Finally, to assign response strategies to each critical risk, a zero-one multi-objective mathematical programming model was proposed and developed Epsilon-constraint method was used to solve it. Findings Given the typical constraints of projects which are time, cost and quality, of the projects that companies are often faced with, this study presents the identified risks of oil and gas projects to the managers of the oil and gas company in accordance with the priority given in the present research and the response to each risk is also suggested to be used by managers based on their organizational circumstances. Originality/value This study aims at qualitative management of cost risks of oil and gas projects (case study of Pars Oil and Gas Company) by combining FMEA, best worst and GRA-VIKOR methods under fuzzy environment and Epsilon constraints. According to studies carried out in previous studies, the simultaneous management of quantitative and qualitative cost of risk of oil and gas projects in Iran has not been carried out and the combination of these methods has also been innovated.

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