A bi-level decision-making approach for the vendor selection problem with random supply and demand

2019 ◽  
Vol 58 (6) ◽  
pp. 1164-1189
Author(s):  
Syed Mohd Muneeb ◽  
Mohammad Asim Nomani ◽  
Malek Masmoudi ◽  
Ahmad Yusuf Adhami
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Controlling Factors ◽  
Decision Makers ◽  
Selection Problem ◽  
Chance Constrained Programming ◽  
Vendor Selection ◽  
Content Type ◽  
Decision Variables ◽  
Level Of Satisfaction

Purpose Supplier selection problem is the key process in decision making of supply chain management. An effective selection of vendors is heavily responsible for the success of any organization. Vendor selection problem (VSP) reflects a more practical view when the decision makers involved in the problem are present on different levels. Moreover, vendor selection consists of various random parameters to be dealt with in real life. The purpose of this paper is to present a decentralized bi-level VSP where demand and supply are normal random variables and objectives are fuzzy in nature. Decision makers are present at two levels and are called as leader and follower. As the next purpose, this paper extends and presents a solution approach for fuzzy bi-level multi-objective decision-making model with stochastic constraints. Different scenarios have been developed within a real-life case study based on different sets of controlling factors under the control of leader. Design/methodology/approach This study uses chance-constrained programming and fuzzy set theory to generate the results. Stochastic constraints are converted into deterministic constraints using chance-constrained programming. Decision variables in the bi-level VSP are partitioned between the two levels and considered as controlling factors. Membership functions based on fuzzy set theory are created for the goals and controlling factors and are used to obtain the overall satisfactory solutions. The model is tested on a real-life case study of a textile industry and different scenarios are constructed based on the choice of leader’s controlling factors. Findings Results showed that the approach is quite helpful as it generates efficient results producing a good level of satisfaction for the decision makers of both the levels. Results showed that on choosing the vendors that are associated with worst values in terms of associated costs, vendor ratings and quota flexibilities as controlling factors by the leaders, the level of satisfaction achieved is highest. The level of satisfaction of solution is lowest for the scenario when the leader chooses to control the decision variables associated with vendors that are profiled with minimum vendor ratings. Results also showed that higher availability of materials and budget with vendors proved helpful in obtaining quota allocations. Different scenarios generate different results along with different values of satisfaction degrees and objective values which shows the flexible feature of the approach based on leader’s choice of controlling factors. Numerical results showed that the leader’s control can be effectively incorporated maintaining satisfaction levels of the followers under various scenarios or conditions. Research limitations/implications The paper makes a certain contribution toward the study of vendor selection existing in a hierarchical manner under uncertain environment. A wide set of data of different factors is needed which can be seen as a limitation when the available time is short for the supplier selection process. Practical implications VSP which is generally adopted by most of the large organizations is characterized with hierarchical decision making. Moreover, dealing with the real-life concern, the data available for some of the parameters are not complete, representing an uncertainty of parameters. This study is quite helpful for decentralized VSP under uncertain environment to reduce the costs, improve profit margins and to create long-term relationships with selected vendors. The proposed model also provides an avenue to explore the decision making when the leader has control over some of the decision variables. Originality/value Reviewing the literature available, this is the first attempt to present a multi-objective VSP where the decision makers are at hierarchical levels considering uncertain parameters such as demand and supply as per the best knowledge of authors. This research further provides an approach to construct scenarios or different cases based on the choice of leader’s choice of controlling factors.

A grey-based decision-making approach to the supplier selection problem in a steelmaking company

2017 ◽  
Vol 7 (3) ◽  
pp. 385-396 ◽  
Author(s):  
Ali M. Abdulshahed ◽  
Ibrahim A. Badi ◽  
Mohamed Mehemed Blaow
Keyword(s):  
System Theory ◽  
Decision Making ◽  
Supplier Selection ◽  
Grey System Theory ◽  
Decision Makers ◽  
Strategic Decision ◽  
Selection Problem ◽  
Selection Strategy ◽  
Grey System ◽  
Content Type

Purpose The purpose of this paper is to propose a supplier selection method using grey system theory for a steelmaking company in Libya. Design/methodology/approach In order to tackle incompleteness and imprecision of human’s judgments, grey numbers were used. This work uses a grey-based approach to represent decision makers’ comparison judgments and extent analysis method to select the best supplier. Therefore, an example of a selection problem of a steelmaking company in Libya was used to illustrate the proposed approach. Findings Supplier selection in a supply chain is a critical strategic decision for company’s success and has attracted much attention of both academic scholars and decision makers. The authors have found that the Grey model can play an important role in improving supplier selection strategy, especially when it is in a situation where complex sustainability environments (i.e. Libya) exist. Originality/value No literature has been found till date for selection of supplier using grey system theory in a steelmaking company in Libya. An attempt in this regard could enhance a decision-making technique for selecting the best suppliers for the selected case company.

Interval grey numbers based multi-attribute decision making method for supplier selection

Kybernetes ◽  
2014 ◽  
Vol 43 (7) ◽  
pp. 1064-1078 ◽  
Author(s):  
Naiming Xie ◽  
Jianghui Xin
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Decision Makers ◽  
Selection Problem ◽  
Content Type ◽  
Numerical Example ◽  
Possibility Degree ◽  
Multi Attribute Decision Making ◽  
Grey Number ◽  
Supplier Selection Problem

Purpose – The purpose of this paper is to study a novel grey possibility degree approach, which is combined with multi-attribute decision making (MADM) and applied MADM model for solving supplier selection problem under uncertainty information. Design/methodology/approach – The supplier selection problem is a typical MADM problem, in which information of a series of indexes should be aggregated. However, it is relatively easy for decision makers to define information in uncertainty, sometimes as a grey number, rather than a precise number. By transforming linguistic scale of rating supplier selection attributes into interval grey numbers, a novel grey MADM method is developed. Steps of proposed model were provided, and a novel grey possibility degree approach was proposed. Finally, a numerical example of supplier selection is utilized to demonstrate the proposed approach. Findings – The results show that the proposed approach could solve the uncertainty decision-making problem. A numerical example of supplier selection is utilized to demonstrate the proposed approach. The results show that the proposed method is useful to aggregate decision makers’ information so as to select the potential supplier. Practical implications – The approach constructed in the paper can be used to solving uncertainty decision-making problems that the certain value of the decision information could not collect while the interval value set could be defined. Obviously it can be utilized for other MADM problem. Originality/value – The paper succeeded in redefining interval grey number, constructing a novel interval grey number based MADM approach and providing the solution of the proposed approach. It is very useful to solving system forecasting problem and it contributed undoubtedly to improve grey decision-making models.

A decision support system for technician routing with time windows

2019 ◽  
Vol 32 (2) ◽  
pp. 138-158
Author(s):  
Elyn Lizeth Solano Charris ◽  
Jairo Rafael Montoya-Torres ◽  
William Guerrero-Rueda
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Time Windows ◽  
Real Life ◽  
Route Planning ◽  
Decision Makers ◽  
Two Stage ◽  
Content Type

Purpose The purpose of this paper is to present a decision support system (DSS) for a Colombian public utility company in order to aid decision-making at the operational level regarding route planning and travel time. The aim is to provide a tool to assist technicians that perform interruption and reconnection of domiciliary services for about 2,000 customers a day. Design/methodology/approach The real-life problem is modeled as a Single Depot Vehicle Routing Problem with Time Windows (SDVRP-TW), which is a well-known optimization problem in Operations Research/Management Science. A two-stage approach integrated into decision-making software is provided. The first stage considers the clustering of customers generated by a combination of the sweep and the k-means algorithms, while the second phase plans the routing of technicians using the nearest-neighbor and the Or-opt heuristics. The proposed approach is tested using real data sets. Findings In comparison with the current route planning approach, the proposed method is able to obtain savings in total travel times, improving operational productivity by 22.2 percent. Research limitations/implications Since the analysis is carried out based on mathematical modeling, assumptions about the relationships between variables and elements of the actual complex problem might be simplified. Although the proposed approach aids the route planning, decision makers make the final decisions. Practical implications The proposed DSS has a critical impact on actual operational practices at the company. Productivity and service level are improved, while reducing operational costs. The decision-making process itself will be improved so technicians and higher decision makers can focus on performing other tasks. Originality/value The real-life problem is modeled using mathematical programming and efficiently solved through a two-stage approach based on simple, quite intuitive, solution procedures that have not been implemented for such services. In addition, as actual data from the company is employed for experimental purposes, the solution approach is tested and its efficiency and efficacy are both validated in a realistic setting, hence providing realistic behavior for decision makers at the company.

The hidden power of language

2020 ◽  
Vol 11 (1) ◽  
pp. 187-206
Author(s):  
Philipp Hummel ◽  
Jacob Hörisch
Keyword(s):  
Decision Making ◽  
Value Creation ◽  
Cost Reduction ◽  
Social Consequences ◽  
Decision Makers ◽  
Social Aspects ◽  
Social Aspect ◽  
Content Type ◽  
Current Accounting ◽  
Cost Reductions

Purpose Stakeholder theory research identifies changes in language as one possible mechanism to overcome the deficiencies of current accounting practices with regard to social aspects. This study aims to examine the effects of the terms used for specific accounts on company internal decision-making, drawing on the example of “value creation accounting”. Design/methodology/approach The study uses a survey based-experiment to analyze the effects of terms used for specific accounts on decision-making, with a focus on social aspects (in particular expenditures for staff) in cost reduction and expenditure decisions. Findings The findings indicate that wordings, which more closely relate to value creation than to costs, decrease cost reductions and increase the priority ascribed to the social aspect of reducing staff costs in times of financial shortage. The effects of terms used on cost reductions are stronger among female decision makers. Practical implications The analysis suggests that conventional accounting language best suits organizations that aim at incentivizing decision makers to primarily cut costs. By contrast, if an organization follows an approach that puts importance on social aspects in times of financial shortage and on not doing too sharp cost reductions, value creation-oriented language is the more effective approach. Social implications The study suggests that the specific terminology used for accounts should be chosen more carefully and with awareness for the possible effects on cost reduction decisions as well as on social consequences. Originality/value This study contributes to a better understanding of the relevance of language in accounting. It suggests that the terms used for accounts should be chosen purposefully because of their far-reaching potential consequences for stakeholders as well as for the organization.

The role of agency in project initiation decisions

2014 ◽  
Vol 7 (3) ◽  
pp. 518-535 ◽  
Author(s):  
Mark Mullaly
Keyword(s):  
Decision Making ◽  
Decision Rules ◽  
Personal Characteristics ◽  
Decision Makers ◽  
Organizational Dynamics ◽  
Substantive Theory ◽  
Content Type ◽  
The Subject ◽  
Board Level

Purpose – The purpose of this paper is to explore the role of decision rules and agency in supporting project initiation decisions, and the influences of agency on decision-making effectiveness. Design/methodology/approach – The study this paper is based upon used grounded theory methodology, and sought to understand the influences of individual decision makers on project initiation decisions within organizations. Data collection involved 28 participants who were involved in project initiation decisions within their organizations, who discussed the process of project initiation in their organization and their role within that process. Findings – The study demonstrates that the overall effectiveness of project initiation decisions is a product of agency, process effectiveness or rule effectiveness. The employment of agency can have a direct influence on decision-making effectiveness, it can compensate for organizational inadequacies of a process or political nature, and it can be constrained in the evidence of formal and effective organizational practices. Research limitations/implications – While agency was recognized by all participants, there are clearly circumstances where actors perceive the ability to exercise agency to be externally constrained. The study is exploratory, contributing to the development of substantive theory. Theory testing as well as a more in-depth investigation of the underlying drivers of agency would be valuable. Practical implications – The study provides executives and individuals supporting the initiation of projects with insights on how to effectively influence the effectiveness of project initiation decisions, and the degree to which personal characteristics influence organizational dynamics. Originality/value – Most discussions of agency has been framed the subject as an executive- or board-level phenomenon. The current study demonstrates that agency is in fact being perceived and operationalized at all levels. Those demonstrating agency in the majority of instances in this study do so in exercising stewardship behaviours. This has important implications for how agency is perceived by executives, and by how agency is exercised by actors at all levels of the organization.

Kenneth Fisher’s heuristics

2016 ◽  
Vol 8 (2) ◽  
pp. 130-148
Author(s):  
Carlo Massironi ◽  
Giusy Chesini
Keyword(s):  
Decision Making ◽  
Conceptual Analysis ◽  
Investment Decision ◽  
Real Life ◽  
Human Action ◽  
Theory Of Knowledge ◽  
Constructivist Theory ◽  
Individual Investors ◽  
Content Type ◽  
Radical Constructivist

Purpose The authors are interested in building descriptive – real life – models of successful investors’ investment reasoning and decision-making. Models designed to be useful for trying to replicate and evolve their reasoning and decision-making. The purpose of this paper, a case study, is to take the substantial material – on innovating the investing tools – published in four books (2006/2012, 2010, 2011, 2015) by a US stock investor named Kenneth Fisher (CEO of Fisher Investments, Woodside, California) and sketch Fisher’s investment innovating reasoning model. Design/methodology/approach To sketch Fisher’s investment innovating reasoning model, the authors used the Radical constructivist theory of knowledge, a framework for analyzing human action and reasoning called Symbolic interactionism and a qualitative analytic technique called Conceptual analysis. The authors have done qualitative research applied to the study of investment decision-making of a single professional investor. Findings In the paper, the authors analyzed and described the heuristics used by Fisher to build subsequent generations of investing tools (called by Fisher “Capital Markets Technology”) to try to make better forecasts to beat the stock market. The authors were interested in studying the evolutive dimensions of the tools to make forecasts of a successful investor: the “how to build it” and “how to evolve it” dimension. Originality/value The paper offers an account of Kenneth Fisher’s framework to reason the innovation of investing tools. The authors believe that this paper could be of interest to professional money managers and to all those who are involved in the study and development of the tools of investing. This work is also an example of the use of the Radical constructivist theory of knowledge, the Symbolic interactionist framework and the Conceptual analysis to build descriptive models of investment reasoning of individual investors, models designed to enable the reproduction/approximation of the conceptual operations of the investor.

ERP software selection using intuitionistic fuzzy and interval grey number-based MACBETH method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustafa Said Yurtyapan ◽  
Erdal Aydemir
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Selection Process ◽  
Intuitionistic Fuzzy Set ◽  
Decision Makers ◽  
Software Selection ◽  
Content Type ◽  
Intuitionistic Fuzzy ◽  
Expert Opinions ◽  
Erp Software

PurposeEnterprise Resource Planning (ERP) software which is a knowledge-based design on the interconnective communication of business units and information share, ensures that business processes such as finance, production, purchasing, sales, logistics and human resources, are integrated and gathered under one roof. This integrated system allows the company to make fast and accurate decisions and increases its competitiveness. Therefore, for an enterprise, choosing the suitable ERP software is extremely important. The aim of this study is to present new research on the ERP software selection process by clarifying the uncertainties and find suitable software in a computational way.Design/methodology/approachERP selection problem design includes uncertainties on the expert opinions and the criteria values using intuitionistic fuzzy set theory and interval grey-numbers to MACBETH multi criteria decision making method. In this paper, a new interval grey MACBETH method approach is proposed, and the degree of greyness approach is used for clarifying the uncertainties. Using this new approach in which grey numbers are used, it is aimed to observe the changes in the importance of the alternatives. Moreover, the intuitionistic fuzzy set method is applied by considering the importance of expert opinions separately.FindingsThe proposed method is based on quantitative decision making derived from qualitative judgments. The results given under uncertain conditions are compared with the results obtained under crisp conditions of the same methods. With the qualitative levels of experts reflected in the decision process, it is clearly seen that ERP software selection problem area has more effective alternative decision solutions to the uncertain environment, and decision makers should not undervalue the unsteadiness of criteria during ERP software selection process.Originality/valueThis study contributes to the relevant literature by (1) utilizing the MACBETH method in the selection of the ERP software by optimization, and (2) validating the importance of expert opinions with uncertainties on a proper ERP software selection procedure. So, the findings of this study can help the decision-makers to evaluate the ERP selection in uncertain conditions.

Jumping to conclusions – an analysis of the NBA Draft Combine athleticism data and its influence on managerial decision-making

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tobias Berger ◽  
Frank Daumann
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Predictive Power ◽  
Principal Component ◽  
Decision Makers ◽  
Decision Quality ◽  
Managerial Behavior ◽  
Managerial Decision ◽  
Content Type ◽  
Selection Behavior

PurposeThe NBA Draft policy pursues the goal to provide the weakest teams with the most talented young players to close the gap to the superior competition. But it hinges on appropriate talent evaluation skills of the respective organizations. Research suggests the policy might be valid but to date unable to produce its intended results due to the “human judgement-factor”. This paper investigates specific managerial selection-behavior-influencing information to examine why decision-makers seem to fail to constantly seize the opportunities the draft presents them with.Design/methodology/approachAthleticism data produced within the NBA Draft Combine setting is strongly considered in the player evaluations and consequently informs the draft decisions of NBA managers. Curiously, research has failed to find much predictive power within the players pre-draft combine results for their post-draft performance. This paper investigates this clear disconnect, by examining the pre- and post-draft data from 2000 to 2019 using principal component and regression analysis.FindingsEvidence for an athletic-induced decision-quality-lowering bias within the NBA Draft process was found. The analysis proves that players with better NBA Draft Combine results tend to get drafted earlier. Controlling for position, age and pre-draft performance there seems to be no proper justification based on post-draft performance for this managerial behavior. This produces systematic errors within the structure of the NBA Draft process and leads to problematic outcomes for the entire league-policy.Originality/valueThe paper delivers first evidence for an athleticism-induced decision-making bias regarding the NBA Draft process. Informing future selection-behavior of managers this research could improve NBA Draft decision-making quality.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

Integration between knowledge management and business process management and its impact on the decision making process in the construction sector: a case study of Jordan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sami Wasef Abuezhayeh ◽  
Les Ruddock ◽  
Issa Shehabat
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Decision Makers ◽  
Decision Making Process ◽  
Construction Sector ◽  
Content Type

Purpose The purpose of this paper is to investigate and explain how organizations in the construction sector can enhance their decision-making process (DMP) by practising knowledge management (KM) and business process management (BPM) activities. A conceptual framework is developed that recognises the elements that impact DMP in terms of KM and BPM. The development of this framework goes beyond current empirical work on KM in addition to BPM as it investigates a wider variety of variables that impact DMP. Design/methodology/approach A case study is undertaken in the context of the construction industry in Jordan. A theoretical framework is developed and assessment of the proposed framework was undertaken through a questionnaire survey of decision-makers in the construction sector and expert interviews. Findings The outcomes of this research provide several contributions to aid decision-makers in construction organizations. Growth in the usage of KM and BPM, in addition to the integration between them, can provide employees with task-related knowledge in the organization’s operative business processes, improve process performance, promote core competence and maximise and optimise business performance. Originality/value Through the production of a framework, this study provides a tool to enable improved decision-making. The framework generates a strong operational as well as theoretical approach to the organizational utilization of knowledge and business processes.

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