An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms

This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Industrial marketing planning is a typical example of an unstructured decision making problem due to the large number of variables to consider and the uncertainty imposed on those variables. Although abundant studies identified barriers and facilitators of effective industrial marketing planning in practice, the literature still lacks practical tools and methods that marketing managers can use for the task. This paper applies fuzzy cognitive maps (FCM) to industrial marketing planning. In particular, agent based inference method is proposed to overcome dynamic relationships, time lags, and reusability issues of FCM evaluation. MACOM simulator also is developed to help marketing managers conduct what-if scenarios to see the impacts of possible changes on the variables defined in an FCM that represents industrial marketing planning problem. The simulator is applied to an industrial marketing planning problem for a global software service company in South Korea. This study has practical implication as it supports marketing managers for industrial marketing planning that has large number of variables and their cause–effect relationships. It also contributes to FCM theory by providing an agent based method for the inference of FCM. Finally, MACOM also provides academics in the industrial marketing management discipline with a tool for developing and pre-verifying a conceptual model based on qualitative knowledge of marketing practitioners.Ministry of Education, Science and Technology (Korea

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

An empirical survey: Can green marketing really entice customers to pay more?

This research integrated the Social Cognition Theory and the Engel Kollat Blackwell customers’ purchasing model (EKB model) to synthetically discuss the three kinds of possible relations comprising “does negatively entice”, “does possibly entice” and “does positively entice” between green-marketing and customers’ purchasing and payment, with consideration given to environmental-protection issues. Based on the measured results, the most contributed contention of this research not only utilized three cross-analytical theories consisting of the social cognition theory (SCT) , the Fuzzy theory (FT) and the EKB model, and the novel F-ANP of the MCDM methodology to evaluate the collected data but it also manifested that Green-marketing does possibly entice customers to pay more (GMPECPM). These measured results have distinctly stunned the fundamental assumption in the traditional green-marketing research field that customers were supposed to be willing to pay more for green products and services because they were supporting green initiatives and helping environmental-protection. Further, major future research directions were also briefly demonstrated in this research as (1) the collection data have to be strengthened to gather more empirical customer feedback, corporate management comments, and professional scholars’ reports; (2) enterprises have to resoundingly establish a green-branding initiative after successfully executing green-marketing strategies.Green Marketing (G-marketing); Multiple Criteria Decision Making (MCDM); Analytical Network Process (F-ANP).

The "fuzzy front end" of innovation

The fast transformation of technologies into new products or processes is one of the core challenges for any technology-based enterprise. Within the innovation process, we believe, the early phases (fuzzy front end) to have the highest impact on the whole process and the result (Input-Output Process), since it will influence the design and total costs of the innovation extremely. However the Fuzzy Front End is unfortunately the least-well structured part of the innovation process, both in theory and in practice. The focus of the present chapter is on methods and tools to manage the fuzzy front end of the innovation process. Firstly, the activities, characteristics, and challenges of the front end are described. Secondly, a framework of the application fields for different methods and tools is presented: Since a product upgrade requires a different approach compared to radical innovation, where the market is unknown and a new technology is applied, we believe such a framework to be useful for practitioners. Thirdly, a selection of methods and tools that can be applied to the fuzzy front end are presented and allocated within the framework. The methods selected here address process improvements, concept generation, and concept testing. --fuzzy front end,innovation management,stage-gate process,frontloading,triz,dsm-matrix,lead user

A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance

Using the AHP to determine the correlation of product issues to profit

Analyzes the correlation between product issues and product profit using the analytic hierarchy process (AHP). Estimation on the effect of profit on product issues by AHP; failure of the AHP to determine the correlation factors; development of procedure for determining correlation factors

A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1) Resource-based view, and (2) Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a noveldevelopment of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed