Criteria evaluation for pricing decisions in strategic marketing management using an intuitionistic cognitive map approach

A novel extension of Pythagorean fuzzy MULTIMOORA approach for new product development

This study explores how to enhance the decision-making processes in the phases of idea generation or alternative selection during the new product development (NPD) process. NPD is acknowledged as the central function of businesses in an increasingly competitive marketplace. In the current era, the highly uncertain and rapidly changing market environment makes the NPD extremely vague and complex. To be able to find a suitable solution to this complexity, the proposed research aims to categorize the decision points in the process of NPD regarding software development and identify the fuzziness elements affecting the process. The goal of a decision-making process is to prioritize several alternatives with respect to some required objectives and to select the best among them. Multi-Criteria Decision-Making (MCDM) may support reaching a consensus judgment with the collective assessment of Decision Makers (DMs). We introduce a novel evaluation approach for this problem. The proposed approach employs a MULTIMOORA (Multi-objective Optimization by Ratio Analysis plus the Full Multiplicative Form) MCDM technique under Pythagorean Fuzzy Sets (PFSs) objective world environment to cope with an ambiguous environment using Group Decision Making (GDM) setting to shape the decisions. The PFSs have demonstrated their advantages in dealing with vagueness and uncertainty over crisp, fuzzy, or intuitionistic fuzzy sets. Therefore, PFSs can represent the DMs' judgments and preferences in a better structure, ensuring enhanced decision-making in a group consensus. A case study on gaming software and app development is presented to validate the functionality of the proposed method. The results are compared and assessed with the help of a sensitivity analysis. This research makes a real contribution to the literature by proposing a novel evaluation method to rate and select NPD (gaming software and apps) to deal with the inexactness and vagueness associated with the criteria and alternatives.

Supply Chain Pricing Models Considering Risk Attitudes under Free-Riding Behavior

The free-riding behavior of companies that do not act will bring losses to companies that provide services. A market consists of two secondary supply chains: manufacturers and retailers. Each supply chain can choose to adopt promotional strategies to expand its market demand. This paper constructs the centralized decision-making in the supply chain and the Nash game competition model between supply chains and primarily studies the impact of risk aversion and the free-riding coefficient on supply chain pricing, promotion strategy selection, and expected utility. We show that the supply chain with high-risk aversion has relatively low pricing, but the demand and a total expected utility are high. We also identify that, on the premise of the same risk aversion degree of the two supply chains, when the free-riding coefficient between the chains is small and equal, the supply chain tends to implement the promotion strategy. When consumers have the same preference for the products of two retailers, the pricing of the free-riding supply chain increases with the increase in the free-riding coefficient, while the supply chain with a promotion strategy is the opposite. Based on the numerical results, we further give the optimal one-way free-riding coefficient when the two supply chains have the same degree of risk aversion; when there is a bidirectional free-riding behavior in the market, competition among supply chains gradually tends to the first two scenarios.

Machine Learning and Regression Analysis to Model the Length of Hospital Stay in Patients with Femur Fracture

Fractures of the femur are a frequent problem in elderly people, and it has been demonstrated that treating them with a diagnostic–therapeutic–assistance path within 48 h of admission to the hospital reduces complications and shortens the length of the hospital stay (LOS). In this paper, the preoperative data of 1082 patients were used to further extend the previous research and to generate several models that are capable of predicting the overall LOS: First, the LOS, measured in days, was predicted through a regression analysis; then, it was grouped by weeks and was predicted with a classification analysis. The KNIME analytics platform was applied to divide the dataset for a hold-out cross-validation, perform a multiple linear regression and implement machine learning algorithms. The best coefficient of determination (R²) was achieved by the support vector machine (R² = 0.617), while the mean absolute error was similar for all the algorithms, ranging between 2.00 and 2.11 days. With regard to the classification analysis, all the algorithms surpassed 80% accuracy, and the most accurate algorithm was the radial basis function network, at 83.5%. The use of these techniques could be a valuable support tool for doctors to better manage orthopaedic departments and all their resources, which would reduce both waste and costs in the context of healthcare.

A novel integrated intuitionistic fuzzy decision aid for agile outsourcing provider selection: a COVID-19 pandemic-based scenario analysis

In project management, agility concept has emerged for overcoming the limitations of traditional methodologies that are sequential and linear. An agile project contains planned processes as well as iterations. In global competitive areas, achieving agility in outsourcing processes enables the companies to cope with changes and dynamic issues. This paper introduces an integrated cognitive map-based intuitionistic fuzzy multiple criteria decision aid to rank agile outsourcing provider alternatives and then determine the best performing one. Intuitionistic fuzzy sets are employed for dealing with uncertain and vague data along with the loss of information that may be occurred in numerical operations with fuzzy numbers. Intuitionistic fuzzy cognitive map tool is used to weight the evaluation criteria that are interrelated with each other with causal links. The most appropriate agile outsourcing provider alternative is identified via intuitionistic fuzzy complex proportional assessment technique, which aims to obtain a solution relative to the ideal solution. In order to demonstrate the robustness of the proposed intuitionistic fuzzy decision aid, a case study is conducted in Turkish white goods industry. As a comparative study, a scenario analysis is provided to understand the impacts of COVID-19 pandemic on agile provider evaluation/selection decision. According to the results obtained from the scenario analysis, it is worth noting that home office procedures are appropriate for maintaining agility in outsourcing processes of project management.

A Systematic Literature Review of Consumers' Cognitive-Affective Needs in Product Design From 1999 to 2019

Understanding consumer cognitive and affective needs is a complex and tricky challenge for consumer studies. Creating and defining product attributes that meet the consumers' personal wishes and needs in different contexts is a challenge that demands new perspectives because there are mismatches between the objective of companies and the consumer's objective, which indicates the need for products to become increasingly consumer-oriented. Product design approaches aim to bring the product and consumer closer together. The objective of this study is to investigate the application of the cognitive and affective needs of the consumer in product design through a systematic review of the literature of publications carried out in the last 20 years. This article selects research carried out in the specific area of cognitive and affective product design and defines the state of the art of the main areas, challenges, and trends. The conclusion that was reached is that cognitive approaches have been updated, are more associated with technology, and so are focused and oriented toward the ease and friendliness of the product. In contrast, affective approaches are older and focus on the quality of life, satisfaction, pleasure, and friendliness of the product. This review indicates that the emotional focus of change for cognitive complexity is due to an understanding of the affective and emotional subjectivity of the consumers and how they can translate these requirements into product attributes. These approaches seem to lose their strength or preference in the areas of design and engineering for more rational and logical cognitive applications, and therefore are more statistically verifiable. Advances in neuroscience are focused on applications in marketing and consumer psychology and some cognitive and affective product designs.

A cognitive map integrated intuitionistic fuzzy decision-making procedure for provider selection in project management

Organizations make use of project management methodologies, which provide an effective manner to achieve managerial goals, maintain the strength of the companies in increasing competition. Efficiency in planning, budgeting, and scheduling are provided so that high quality outputs are obtained through these processes. Agile project management methodology, which has been emerged from unpredictability of customer requirements and changeable business environment, is apt to cope with the failures of traditional project management tools. Besides, lean six-sigma project management methodology has become a combination of lean and six-sigma, which were opponent methodologies previously. This paper aims to determine the most suitable outsourcing provider alternative by presenting a novel cognitive maps-based intuitionistic fuzzy decision making procedure. Interrelationships among evaluation criteria are weighted employing intuitionistic fuzzy cognitive map technique because of the causal links among evaluation criteria, vagueness, fuzziness, and hesitation in data. Moreover, the most appropriate provider alternative for both agile and lean six-sigma project management methodologies is identified by utilizing intuitionistic fuzzy TOPSIS method, which aims for minimizing the closeness to the ideal solution while maximizing the distance from the anti-ideal solution in hesitative environment. The case study is carried out in a bank that performs in Turkish banking sector.