Investigating the impact of behavioral factors on supply network efficiency:insights from banking’s corporate bond networks

This paper highlights the role of behavioral factors for efficiency measurement in supply networks. To this aim, behavioral issues are investigated among interrelations between decision makers involved in corporate bond service networks. The corporate bond network was considered in three consecutive stages, where each stage represents the relations between two members of the network: issuer-underwriter, underwriter-bank, and bank-investor. Adopting a multi-method approach, we collected behavioral data by conducting semi-structured interviews and applying the critical incident technique. Financial and behavioral data, collected from each stage in 20 corporate bond networks, were analyzed using fuzzy network data envelopment analysis to obtain overall and stage-wise efficiency scores for each network. Sensitivity analyzes of the findings revealed inefficiencies in the relations between underwriters-issuers, banks-underwriters, and banks-investors stemming from certain behavioral factors. The results show that incorporating behavioral factors provides a better means of efficiency measurement in supply networks

Future Agribusiness Challenges: Strategic Uncertainty, Innovation and Structural Change

The IFAMR is published by the International Food and Agribusiness Management Association.(IFAMA) www.ifama.orgStrategic uncertainty, innovation, structural change, Agribusiness, Research and Development/Tech Change/Emerging Technologies, Risk and Uncertainty, ISSN #: 1559-2448,

Choosing Creativity: The Role of Individual Risk and Ambiguity Aversion on Creative Concept Selection in Engineering Design

While creativity is often seen as an indispensable quality of engineering design, individuals often select conventional or previously successful options during the concept selection process due to the inherent risk associated with creative concepts and their inadvertent bias against creativity. However, little is actually known about what factors attribute to the promotion or filtering of these creative concepts during concept selection. To address this knowledge gap, an exploratory study was conducted with 38 undergraduate engineering students. This study was aimed at investigating the impact of individual risk aversion, ambiguity aversion, and student educational level on the selection and filtering of creative ideas during the concept selection process. The results from this study indicate that an individuals ability to generate creative ideas is not significantly related to their preference for creative ideas during concept selection, but individual risk aversion and ambiguity aversion are significantly related to both creative concept selection and creative idea generation. Our results also revealed that first and third-year students’ creative ability are affected differently by varying levels of tolerance for ambiguity. These results highlight the need for a more directed focus on creativity in engineering education in both concept creation and concept selection. These results also add to our understanding of creativity during concept selection and provide guidelines for enhancing the design process

Impact of aleatoric, stochastic and epistemic uncertainties on project cost contingency reserves

Producción CientíficaIn construction projects, contingency reserves have traditionally been estimated based on a percentage of the total project cost, which is arbitrary and, thus, unreliable in practical cases. Monte Carlo simulation provides a more reliable estimation. However, works on this topic have focused exclusively on the effects of aleatoric uncertainty, but ignored the impacts of other uncertainty types. In this paper, we present a method to quantitatively determine project cost contingency reserves based on Monte Carlo Simulation that considers the impact of not only aleatoric uncertainty, but also of the effects of other uncertainty kinds (stochastic, epistemic) on the total project cost. The proposed method has been validated with a real-case construction project in Spain. The obtained results demonstrate that the approach will be helpful for construction Project Managers because the obtained cost contingency reserves are consistent with the actual uncertainty type that affects the risks identified in their projects.Junta de Castilla y Leon (grant VA180P20

Ambiguity Aversion in the Front-End of Innovation

There have been repeated appeals for further scientific inquiry into the early stages of innovation in the firm, referred to as the front-end of innovation. Currently, we lack a clear understanding of front-end decision-making processes. Conceptually, the front-end stages of innovation are likely to include decisions involving ambiguity rather than risk. One way to view the innovation process is that considerable effort is expended on risk-reduction. That is to say, the innovation/new product development process converts amorphous ideas into tangible products that have a maximum chance of success in the commercial marketplace. However, this may lead to a preference for advancing product concepts where risk, in terms of clear probabilities, can be more easily established. At the same time, those new ideas and product concepts that are ambiguous may be discarded or screened out simply because it seems difficult to discover the probability estimates associated with their outcome success. This is ambiguity aversion, and it has been found to be an important predictor of decision making under uncertainty. Using a framework based on decision theory and the theory of expected utility, I propose and test a model in which ambiguity aversion has a detrimental effect on the performance of front-end innovation activities due to a suppression of decision-making comprehensiveness. Innovation culture and innovative capacity also play important roles in the success of front-end innovation activities. The data is collected from a sample of managers (N = 175) with active roles in innovation management. In summary, the results of a revised model serves to provide a valuable framework through which firms and managers can improve front-end of innovation performance. Multiple directions for future research are also discussed.Marketin

An Assessment of Prospect Theory in Tourism Decision-Making Research

Prospect theory has been an essential theoretical foundation for behavioral economics, as recognized with the Nobel Prize in economic sciences in 2002. The growing interest in behavioral economics among tourism researchers necessitates a systematic assessment of prospect theory and its application in tourism research to critically examine the current status of tourism decision-making studies. This study therefore clarifies the theoretical background of prospect theory and analyzes 93 published studies to examine how prospect theory has performed in explaining tourism decision-making. The study also evaluates the application of prospect theory in tourism research and provides future research directions with respect to under-researched dimensions, reference points, dynamic decision-making processes, and the logical continuity and systemization of prospect theory

Predicting changing pattern: building model for consumer decision making in digital market

YesConsumers have the multiple options to choose their products and services, which have a significant impact on the pattern of consumer decision making in digital market and further increases the challenges for the service providers to predict their buying pattern. In this sense, the purpose of this paper is to propose a structural hierarchy model for analyzing the changing pattern of consumer decision making in digital market by taking an Indian context. Design/methodology/approach: To accomplish the objectives, the research is conducted in two phases. An extensive literature review is performed in the first phase to list the factors related to the changing pattern of consumer decision making in digital market and then fuzzy Delphi method is applied to finalize the factors. In the second phase, fuzzy analytic hierarchy process (AHP) is employed to find the priority weights of finalized factors. The fuzzy set theory allows capturing the vagueness in the data. Findings: The findings obtained in this study shows that consumers are much conscious about innovative and trendy products as well as brand and quality; therefore, the service providers must think about these two most important factors so that they can able to retain their consumer in their online portal. Practical implications: The analysis shows that “innovative and trendy” is the first priority factor for the consumers followed by “brand and quality” and “fulfilment and time energy.” The proposed model can help the marketers and service providers in predicting customers’ preferences and their changing pattern efficiently under vague surroundings. The outcomes of this research work not only help the service provider to update their products and services according to consumers’ needs but can also help them to increase profit and minimize their risk. Originality/value: This work contributes to consumer research literature focusing on problem evaluation in the context of changing pattern of consumer decision making in digital era

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Architecting system of systems: artificial life analysis of financial market behavior

This research study focuses on developing a framework that can be utilized by system architects to understand the emergent behavior of system architectures. The objective is to design a framework that is modular and flexible in providing different ways of modeling sub-systems of System of Systems. At the same time, the framework should capture the adaptive behavior of the system since evolution is one of the key characteristics of System of Systems. Another objective is to design the framework so that humans can be incorporated into the analysis. The framework should help system architects understand the behavior as well as promoters or inhibitors of change in human systems. Computational intelligence tools have been successfully used in analysis of Complex Adaptive Systems. Since a System of Systems is a collection of Complex Adaptive Systems, a framework utilizing combination of these tools can be developed. Financial markets are selected to demonstrate the various architectures developed from the analysis framework --Introduction, page 3