Identification and prioritization of factors influencing organization risk tolerance level

2019 ◽  
Vol 16 (4) ◽  
pp. 417-435
Author(s):  
Mohammad Khalilzadeh ◽  
Shiba Masoumi ◽  
Isa Masoumi
Keyword(s):  
Decision Making ◽  
Risk Tolerance ◽  
Project Manager ◽  
Validity And Reliability ◽  
Statistical Population ◽  
Content Type ◽  
Tolerance Level ◽  
Factors Influencing ◽  
Critical Issues ◽  
Decision Making Model

Purpose Identifying and prioritizing the risks are considered as critical issues in risk management; otherwise, non-considering the risks will lead to the problems such as delays in project implementation, increased costs, loss of reputation, loss of clients, reduced revenue and liquidity and even bankruptcy. The paper aims to discuss these issues. Design/methodology/approach In this paper, the factors influencing the organization risk tolerance level were identified. Then, the factors increasing and decreasing the risk tolerance level were determined by a decision-making model. Finally, a comprehensive model was considered for risk measuring and preparing a risk failure structure chart, in order to determine the factors influencing it as well as the measurement criteria and then they were ranked using the taxonomy method. In this study, the size of the statistical population was 130 (six small and medium manufacturer and service provider companies). Based on Cochran’s sample size formula, 97 questionnaires containing 30 questions were randomly distributed among the population. Validity and reliability of the questionnaire were confirmed. The data were analyzed by SPSS 22. Findings Given the hypotheses of this study, the first hypothesis was rejected and the other hypotheses were accepted. The final ranking was done using the taxonomy method; the personality of the project manager was ranked at first; income, credit and capital were ranked second and the number of personnel was ranked third. Moreover, the TOPSIS method was used for ranking to compare the results. Originality/value In this research, the identification and ranking of these factors have taken place in several small- and medium-sized organizations; in addition, the rankings are conducted using the taxonomy decision-making method.

Do “rising stars” avoid risk?: status-based labels and decision making

2014 ◽  
Vol 35 (2) ◽  
pp. 121-136 ◽  
Author(s):  
Igor Kotlyar ◽  
Leonard Karakowsky ◽  
Mary Jo Ducharme ◽  
Janet A. Boekhorst
Keyword(s):  
Decision Making ◽  
Corporate Strategy ◽  
Business Students ◽  
Risk Tolerance ◽  
High Potential ◽  
Future Research ◽  
High Status ◽  
Negative Effects ◽  
Risky Decision ◽  
Content Type

Purpose – The purpose of this paper is to empirically examine how status-based labels, based on future capabilities, can impact people's risk tolerance in decision making. Design/methodology/approach – In this paper the authors developed and tested theoretical arguments using a set of three studies employing a scenario-based approach and a total of 449 undergraduate business students. Findings – The findings suggest that labeling people in terms of future capabilities can trigger perceptions of public scrutiny and influence their risk preferences. Specifically, the results reveal that individuals who are recipients of high-status labels tend to choose lower risk decision options compared to their peers. Research limitations/implications – The study employed scenarios to examine the issue of employee labeling. The extent to which these scenarios have truly captured the dynamics of labeling is questionable, and future research should employ a field-based study to examine whether the reported effect can be observed in a “real” work context. Practical implications – Organizations are concerned about their future leadership capacity and often attempt to grow leadership talent by identifying high-potential employees early on. The results of this study suggest that such practice may have an unintentional negative effect of reducing high-potentials’ tolerance toward risky decision making, thus potentially impacting these future leaders’ decision making in the realm of corporate strategy, R&D, etc. Originality/value – The issue of how labeling individuals in terms of future capabilities can impact their risk preference has been largely ignored by organizational research. This paper suggests that the popular practice of identifying high-potential employees may have unintentional negative effects by lowering their risk tolerance.

Grey assessment and prediction of the financial agglomeration degree in central five cities

2014 ◽  
Vol 4 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Li Li ◽  
Guo-hui Hu
Keyword(s):  
Decision Making ◽  
Scientific Development ◽  
Fuzzy Decision Making ◽  
Grey Prediction ◽  
Fuzzy Decision ◽  
Content Type ◽  
Multiple Dimension ◽  
The Government ◽  
Development Tendency ◽  
Decision Making Model

Purpose – At present, financial agglomeration tendency in domestic and foreign countries is increasingly evident. Therefore, from a comparative perspective, this paper aims to assess and predict the financial agglomeration degree in central five cities. Design/methodology/approach – According to the diversity of evaluating indexes and the uncertainty of financial agglomeration, this paper constructs a set of indexes of evaluating the financial agglomeration degree, comprehensively evaluates the financial agglomeration degree of the five cities – Wuhan, Changsha, Zhengzhou, Nanchang and Hefei – in China's middle region from 2001 to 2010 by using the multiple dimension grey fuzzy decision-making model, and predicts their development tendency by using the GM (1, 1, β) model. Findings – The results show that the multiple dimension grey fuzzy decision-making pattern cannot only be used to determine the weights of evaluating indexes, but also get the fuzzy partition and ranking order of the financial agglomeration in central five cities. The grey prediction results can objectively reflect the development tendency of the financial agglomeration in central five cities. Practical implications – From the results, it is necessary for any competitive city to clarify their relative strengths and weaknesses in order for the accurate location and scientific development, and it also provides a reference for the government decision-making. Originality/value – The paper succeeds in using the multiple dimension grey fuzzy decision-making model to measure the financial agglomeration degree of the five central cities and the grey prediction model to predict future trends.

scholarly journals Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

2018 ◽  
Vol 25 (5) ◽  
pp. 1528-1547 ◽  
Author(s):  
Anil Kumar ◽  
Amit Pal ◽  
Ashwani Vohra ◽  
Sachin Gupta ◽  
Suryakant Manchanda ◽  
...  
Keyword(s):  
Decision Making ◽  
Automobile Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Strategic Decision ◽  
Extensive Literature ◽  
Content Type ◽  
Fuzzy Delphi ◽  
Selection For ◽  
Decision Making Model

Purpose Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry. Design/methodology/approach To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.

An agent-based simulation model for IING’s adoption from a perspective of kinetic energy and potential energy

Kybernetes ◽  
2018 ◽  
Vol 47 (3) ◽  
pp. 605-635 ◽  
Author(s):  
Li Wang ◽  
Qingpu Zhang
Keyword(s):  
Decision Making ◽  
Kinetic Energy ◽  
Potential Energy ◽  
Agent Based Simulation ◽  
Content Type ◽  
Agent Based ◽  
Factors Influencing ◽  
Social Physics ◽  
Physical Energy ◽  
Energy Theory

Purpose Internet-based intangible network good (IING) has revolutionized multiple industries in recent years. This paper aims to reveal the laws of consumer’s decision-making on IING from a perspective of kinetic energy and potential energy. Design/methodology/approach In this paper, 4 aspects and 17 factors influencing IING adoption were generalized. Based on the theory of social physics, an agent-based simulation model, introducing physical energy theory to depict consumer’s decision-making, was built. An agent’s kinetic energy reflects the agent’s perceived effect of mass media on the agent’s decision-making on IING adoption. An agent’s potential energy reflects the agent’s perceived effect of social interactions on the agent’s decision-making on the adoption of IING. An agent’s final energy is the sum of the kinetic energy and potential energy, which reflects the agent’s final decision. Findings Some factors mainly influence the diffusion velocity, while other factors have a dramatic impact on both diffusion velocity and diffusion scale. The agent’s personality can make a difference at the early and middle stages of IING adoption, but a faint impact at the later stage because of the effects of network externalities and word of mouth. There is a critical value of the number of initial adopters which can dramatically speed up IING adoption. Practical implications This study provides new insights for firms on the effects of factors influencing consumers’ decision-making on IING adoption. Originality/value This paper defines a new kind of innovation, IING, and generalizes IING’s special characteristics. As a new application of social physics, the physical energy theory has been creatively introduced to depict consumer’s decision-making on IING adoption. A kinetic and potential energy model of IING adoption has been built. Based on simulation experiments, new insights of IING adoption have been gained.

A qualitative phenomenological exploration of social mood and investors’ risk tolerance in an emerging economy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Humaira Asad ◽  
Iqra Toqeer ◽  
Khalid Mahmood
Keyword(s):  
Theoretical Model ◽  
Thematic Analysis ◽  
Financial Literacy ◽  
Financial Risk ◽  
Theoretical Perspective ◽  
Emerging Economy ◽  
Risk Tolerance ◽  
Validity And Reliability ◽  
Content Type ◽  
Depth Analysis

Purpose The authors design a theoretical perspective that explores how different phases of social mood influence financial risk tolerance (FRT) among investors. Risk is involved in almost all financial decision-making. For a better understanding of risk tolerance behavior, the role played by social mood cannot be ignored. This study aims to explore the linkage between social mood and FRT of investors in Pakistan. Design/methodology/approach Using qualitative phenomenology as the guiding framework, 22 interviews were conducted to have a deeper understanding of the lived experiences of investors with at least 10 years of investment experience. Thematic analysis was done to analyze data. Audio-recording, bracketing, triangulation and member checking were done to ensure validity and reliability. Findings A theoretical model is developed using the six themes identified through thematic analysis. This model presents an in-depth analysis of the determinants of social mood, its multiple phases and its impact on risk tolerance behavior. Findings reveal that the level of financial literacy, experience and purpose of investment moderate the effect of social mood on FRT. Practical implications Investors can manage risk and increase their profits by controlling the effects of social mood. They can benefit from the market situation by taking more risk when the market is extremely low. The advisors can frame their advice in the light of the model. Originality/value According to the authors’ knowledge, this is the first study that explores investors’ risk tolerance in response to variations in social mood in the context of an emerging economy. The paper has contributed conceptually and methodologically. It uses phenomenology as the method and develops a theoretical model that describes how different types of investors adjust their risk tolerance in response to changes in their social mood.

A risk-based integrated decision-making model for green supplier selection

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1229-1252 ◽  
Author(s):  
Morteza Yazdani ◽  
Prasenjit Chatterjee ◽  
Dragan Pamucar ◽  
Manuel Doval Abad
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supplier Selection ◽  
Potential Contribution ◽  
Effect Analysis ◽  
Content Type ◽  
Green Supplier Selection ◽  
Construction Company ◽  
Green Suppliers ◽  
Decision Making Model

Purpose Supply chain (SC) environment is surrounded by risk variables. This issue is regarded as an emerging and strategic problem which must be resolved by SC executives. The ability to measuring green supplier’s performance and affecting risk variables to demonstrating effective suppliers list has a potential contribution to be investigated. This paper aims to develop a decision-making model to assess green suppliers under legislation and risk factors. This leads to fewer disruptions in managing the SC and its impact to further improvement. It also presents research concepts forming a new approach for identification, prediction and understating relationship of supply risk. Design/methodology/approach At primal stage, different risk factors that influence green suppliers’ performance are indicated and their relationship is analyzed using decision-making trial and evaluation laboratory (DEMATEL) method. At the same time, failure mode and effect analysis is used to determine risk rating of each supplier. Finally, the evaluation based on distance from average solution (EDAS) method ranks suppliers and several comparisons and analysis are performed to test the stability of the results. The approaches include comparison to technique for order performance by similarity to ideal solution, multi-attributive border approximation area comparison, Vlse Kriterijumska Optimizacija I Kompromisno Resenje and complex proportional assessment methods, followed by analysis of rank reversal, weight sensitivity analysis and effect of dynamic metrics. Findings A real-time case study on green supplier selection (GSS) problem of a reputed construction company of Spain has been presented to demonstrate the practical aspects of the proposed method. In practice, though organizations are aware of various risks from local and global suppliers, it is difficult to incorporate these risk factors for ranking the suppliers. This real-case application shows the evaluation and incorporation of risk factors into the supplier selection model. Practical implications The proposed multi-criteria decision model quantitatively aids managers in selecting green suppliers considering risk factors. Originality/value A new model has been developed to present a sound mathematical model for solving GSS problems which considers the interaction between the supplier selection risk factors by proposing an integrated analytical approach for selecting green suppliers strategically consisting of DEMATEL, FMEA and EDAS methods.

Stream processing data decision model for higher environmental performance and resilience in sustainable logistics infrastructure

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yasanur Kayikci
Keyword(s):  
Decision Making ◽  
Transport System ◽  
Environmental Performance ◽  
Stream Processing ◽  
Data Driven ◽  
Content Type ◽  
Sustainable Logistics ◽  
Processing Data ◽  
Decision Making Model ◽  
Resilience Capacity

PurposeAs the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains.Design/methodology/approachA causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted.FindingsThe result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure.Originality/valueIn this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data.

Cross-border to Taiwan but not China

2019 ◽  
Vol 15 (1) ◽  
pp. 21-36
Author(s):  
Wai Ching Choy ◽  
Pui Yan Flora Lau
Keyword(s):  
Decision Making ◽  
Undergraduate Students ◽  
Dynamic Decision Making ◽  
International Mobility ◽  
Snowball Sampling ◽  
Content Type ◽  
Cross Border ◽  
Depth Interview ◽  
Drastic Increase ◽  
Decision Making Model

Purpose This study aims to find out why some students from Hong Kong (HK) consider higher education in Taiwan, rather than in China or elsewhere. It also attempts to build a decision-making model to advance the conventional push-pull logic associated with this particular issue. Design/methodology/approach The authors interviewed 11 undergraduate students from HK via an in-depth interview. Interviewees were recruited by snowball sampling. To protect the privacy of the interviewees, all names of the informants in this paper are pseudonyms. Findings A dynamic decision-making mechanism, which includes three major layers, namely, the macro, meso and micro levels, has been developed to demonstrate that HK students made their decision based on a recursive fashion with bounded rationality, rather than on a linear fashion with complete rationality. Research limitations/implications Although the relatively small number of interviewees has limited the representativeness of the research, the authors suggest that rather than claiming representativeness, the study attempts to tease out the diversity of the decision-making process and mechanisms. Originality/value The drastic increase in the number of HK students in Taiwan proves the current research study, which is the first qualitative research on the phenomenon, as a timely one. In addition, the present study is one of the few examples of studying students’ international mobility from a more economically advanced region (HK) to a less economically advanced one (Taiwan).

An application of grey based decision making approach for the selection of manufacturing system

2014 ◽  
Vol 4 (3) ◽  
pp. 447-462 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
G. Anand
Keyword(s):  
Decision Making ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Strategic Decision ◽  
Decision Matrix ◽  
Content Type ◽  
Manufacturing Organization ◽  
Decision Making Model ◽  
Selection Of

Purpose – In the current customer-driven market, the manufacturers have to be highly responsive and flexible to deliver a variety of products. Hence, to meet this dynamic and uncertain market changes, the production system, which enables the manufacturing of such variety of products should be able to meet such diverse, dynamic changes. Hence, selecting a suitable manufacturing system is a key strategic decision for today's manufacturing organization, which needs to survive in these uncertain market conditions. Hence, the purpose of this paper is to present a decision-making model for selecting the best manufacturing system and also discuss the criteria on the basis of which the management can select the same. Design/methodology/approach – A case of small- and medium-sized company is presented, in which the management is deciding to establish a most suitable manufacturing system. To supplement this, a suitable multi-criteria decision-making model (MCDM), the grey approach is used to analyze manufacturing system alternatives based on various decision criteria to arrive a comparative ranking. Findings – An extensive analysis of grey-based decision-making model described grey decision matrix, grey normalized decision matrix, grey weighted normalized decision matrix and grey possibility degrees for three alternatives revealed that lean manufacturing systems was found to be the most suitable manufacturing system among three alternatives for a given case. Research limitations/implications – The same study can be extended by including sub-criteria with main criteria for selection of manufacturing system by utilizing two MCDM techniques such as AHP or ANP with Grey approach. Practical implications – The Grey approach has been discussed in a detailed way and it will be useful for the managers to use this approach as a tool for solving similar type of decision-making problems in their organizations in the future. Originality/value – Although, the problem of selecting a suitable manufacturing system is often addressed both in practice and research, very few reports are available in the literature of Grey-based decision models that demonstrated its application for selecting a suitable manufacturing systems.

A decision-making model to support the design of a strategic supply chain configuration

2018 ◽  
Vol 29 (3) ◽  
pp. 515-532 ◽  
Author(s):  
Guang Song ◽  
Luoyi Sun ◽  
Yixiao Wang
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Support Network ◽  
Supply Chain Network ◽  
Affecting Factors ◽  
Content Type ◽  
Supply Chain Configuration ◽  
Decision Making Model ◽  
Industry Sectors ◽  
Chain Configuration

Purpose The purpose of this paper is to apply an empirically based approach to develop a decision-making model that comprehensively incorporates the potential affecting factors and the related significant drivers that support network designers in selecting the appropriate strategic supply chain configuration or checking the coherence of an existing supply chain structure in four industry sectors. Design/methodology/approach The decision-making model is developed based on an empirical study that integrates multiple case studies and statistical analyses. In total, 113 best-in-class manufacturing firms in four sectors are studied to investigate their strategic supply chain configurations and the information of identified affecting drivers. The factor analysis and regression analysis are conducted to classify the drivers into five factor groups, and to identify the significant drivers used to develop the decision-making model. Findings The findings of this research are three-pronged. First, 12 significant drivers related to 5 factor groups affecting strategic supply chain network design (SCND) are identified. Second, a decision-making model is developed to support users in strategic SCND. Last, the main characteristics of various strategic supply chain configurations are summarized in four industry sectors. Research limitations/implications The authors identified valuable insights for both academics and practitioners based on the identified significant affecting drivers and the developed decision-making model. In addition, this study also proposes two potential research lines on the study of additional contextual affecting factors and decision issues in strategic SCND. Originality/value This study could be the first attempt to use an empirically based method to develop a decision-making model aimed at supporting the preliminary design of a supply chain network. Therefore, the drawbacks of a pure qualitative conceptual model and optimization model are eliminated.

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