MKT 6009 Marketing Internship (0 semester credit hours) Student gains experience and improves skills through appropriate developmental work assignments in a real business environment. Student must identify and submit specific business learning objectives at the beginning of the semester. The student must demonstrate exposure to the managerial perspective via involvement or observation. At semester end, student prepares an oral or poster presentation, or a written paper reflecting on the work experience. Student performance is evaluated by the work supervisor. Pass/Fail only. Prerequisites: (MAS 6102 or MBA major) and department consent required. (0-0) S MKT 6244 Digital Marketing Strategy (2 semester credit hours) Executive Education Course. The course explores three distinct areas within marketing and sales namely, digital marketing, traditional sales prospecting, and executive sales organization and strategy. The continuing convergence of the digital marketing and sales funnels has created a strategic continuum from digital lead generation to digital sales. The course identifies the current composition of this digital continuum while providing opportunities to evaluate sales and marketing digital strategies. Prerequisites: MKT 6301 and instructor consent required. (2-0) Y MKT 6301 (SYSM 6318) Marketing Management (3 semester credit hours) Overview of marketing management methods, principles and concepts including product, pricing, promotion and distribution decisions as well as segmentation, targeting and positioning. (3-0) S MKT 6309 Marketing Data Analysis and Research (3 semester credit hours) Methods employed in market research and data analysis to understand consumer behavior, customer journeys, and markets so as to enable better decision-making. Topics include understanding different sources of data, survey design, experiments, and sampling plans. The course will cover the techniques used for market sizing estimation and forecasting. In addition, the course will cover the foundational concepts and techniques used in data visualization and \"story-telling\" for clients and management. Corequisites: MKT 6301 and OPRE 6301. (3-0) Y MKT 6310 Consumer Behavior (3 semester credit hours) An exposition of the theoretical perspectives of consumer behavior along with practical marketing implication. Study of psychological, sociological and behavioral findings and frameworks with reference to consumer decision-making. Topics will include the consumer decision-making model, individual determinants of consumer behavior and environmental influences on consumer behavior and their impact on marketing. Prerequisite: MKT 6301. (3-0) Y MKT 6321 Interactive and Digital Marketing (3 semester credit hours) Introduction to the theory and practice of interactive and digital marketing. Topics covered include: online-market research, consumer behavior, conversion metrics, and segmentation considerations; ecommerce, search and display advertising, audiences, search engine marketing, email, mobile, video, social networks, and the Internet of Things. (3-0) T MKT 6322 Internet Business Models (3 semester credit hours) Topics to be covered are: consumer behavior on the Internet, advertising on the Internet, competitive strategies, market research using the Internet, brand management, managing distribution and supply chains, pricing strategies, electronic payment systems, and developing virtual organizations. Further, students learn auction theory, web content design, and clickstream analysis. Prerequisite: MKT 6301. (3-0) Y MKT 6323 Database Marketing (3 semester credit hours) Techniques to analyze, interpret, and utilize marketing databases of customers to identify a firm's best customers, understanding their needs, and targeting communications and promotions to retain such customers. Topics

Marketing for management.

State-of-the-art in artificial neural network applications: A survey

Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model

The principle of a complex interval-valued Pythagorean fuzzy set (CIVPFS) is a valuable procedure to manage inconsistent and awkward information genuine life troubles. The principle of CIVPFS is a mixture of the two separated theories such as complex fuzzy set and interval-valued Pythagorean fuzzy set which covers the truth grade (TG) and falsity grade (FG) in the form of the complex number whose real and unreal parts are the sub-interval of the unit interval. The superiority of the CIVPFS is that the sum of the square of the upper grade of the real part (also for an unreal part) of the duplet is restricted to the unit interval. The goal of this article is to explore the new principle of CIVPFS and its algebraic operational laws. By using the CIVPFSs, certain Einstein operational laws by using the t-norm and t-conorm are also developed. Additionally, we explore the complex interval-valued Pythagorean fuzzy Einstein weighted geometric (CIVPFEWG), complex interval-valued Pythagorean fuzzy Einstein ordered weighted geometric (CIVPFEOWG) operators and utilized their special cases. Moreover, a multicriteria decision-making (MCDM) technique is explored based on the elaborated operators by using the complex interval-valued Pythagorean fuzzy (CIVPF) information. To determine the consistency and reliability of the elaborated operators, we illustrated certain examples by using the explored principles. Finally, to determine the supremacy and dominance of the explored theories, the comparative analysis and graphical expressions of the developed principles are also discussed.

/pdf/einstein-geometric-aggregation-operators-using-a-novel-1kha3pa9xr.pdf

Einstein Geometric Aggregation Operators using a Novel Complex Interval-valued Pythagorean Fuzzy Setting with Application in Green Supplier Chain Management

Predicting failure in the U.S. banking sector: An extreme gradient boosting approach

In the global competitive environment, companies not only improve the quality of service and increase the efficiency, they also decrease the cost by means of third-party logistics (3PLs). 3PLs, therefore, is an important strategy for companies desiring to gain a competitive advantage and 3PLs provider selection plays a critical role for the success of outsourcing. Nevertheless, the level of uncer­tainty in the selection process is relatively high and need to be carefully considered. Hence, in order to select a proper 3PLs provider, integration of the Fuzzy AHP and Evaluation based on Distance from Average Solution (EDAS) has offered a novel integrated model, in which Fuzzy AHP is used for calculating priority weights of each criteria and EDAS is employed to achieve the final ranking of 3PLs providers. Besides, in order to demonstrate the applicability of the proposed model, it is validated by a case study. Cost together with quality, and professionalism are found to be the most important factors for 3PLs provider selection. Consequently, the advantage of this model is that it is simple to apprehend and easy to apply. The use of the proposed model leads to the selection of suitable alternative successfully in other selection problems.
First published online: 23 Apr 2017

/pdf/third-party-logistics-3pls-provider-selection-via-fuzzy-ahp-3z8t74hnzp.pdf

Third-party logistics (3Pls) provider selection via Fuzzy AHP and EDAS integrated model

Due to the ever-increasing harmful emissions affecting natural life and health seriously, it is inevitable the usage of renewable energy sources instead of fossil resources in the near future. Another drawback of fossil fuels is several threats like environmental pollution and global warming, which are potential risks for future generations. Given that the transportation sector makes a huge contribution to carbon emissions, the importance of battery electric vehicles (BEVs), which are an eco-friendly form of vehicles is obvious. Because the BEV market has been rapidly expanding recently, it has become a significant issue to assess BEV alternatives comprehensively from the customer's point of view. This assessment can be made by addressing the basic features of each BEV. Further, multiple criteria decision making (MCDM) techniques are efficient instruments for the right BEV purchase decision. In this work, therefore, ten BEVs are chosen as alternatives. These vehicles are then ranked using SECA, MARCOS, MAIRCA, COCOSO, ARAS, and COPRAS multi-criteria techniques on the basis of technical specifications, such as acceleration, price, battery, range, and so on. Afterward, results from various MCDM techniques are aggregated by applying the Borda count and Copeland ranking methodologies. “Price”, “permitted load,” and “energy consumption” are determined as the most three significant factors for BEV selection, respectively, whereas Tesla Model S is highlighted as the best choice. Further, the robustness and reliability of the results are performed by applying a sensitivity analysis. The proposed framework can be utilized as a basis for more detailed purchasing decisions.

A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies

Many managers and firm owners nowadays pay special attention to green supplier selection to gain competitive advantage all over the world. Consequently, this subject a critical and significant decision for firms. This study utilizes an extension to analytical hierarchy process (AHP) under interval type-2 fuzzy environment (IT2FAHP) model to better cope with ambiguity and vagueness for solving supplier selection problem considering green concepts. A real case application is also performed in a home appliance manufacturer to demonstrate the effectiveness and efficiency of the IT2FAHP model in the present paper. The findings indicate that the most important factors that are effective in selecting green suppliers are cleaner production, energy/material saving, green package, remanufacturing, and environmental management system. Further, a comparison and a sensitivity analysis are conducted to display the consistency and stability of the proposed model. The findings reveal that the IT2FAHP model is quite consistent with the models in literature and green product, cleaner production, green design, and green package have a significant positive effect on performances of green suppliers.

https://link.springer.com/content/pdf/10.1007/s12351-020-00552-y.pdf

Multi-criteria decision making for green supplier selection using interval type-2 fuzzy AHP: a case study of a home appliance manufacturer

MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services

Fatih Ecer

Papers

Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model

Third-party logistics (3Pls) provider selection via Fuzzy AHP and EDAS integrated model

A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies

Multi-criteria decision making for green supplier selection using interval type-2 fuzzy AHP: a case study of a home appliance manufacturer

MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services