Gaurav Khatwani

Identifying Organization Preferences of Internet Marketing Channels using Hybrid Fuzzy MCDM Theories

The evaluation of different Internet marketing channels from the perspective of organizations is important to gain understanding of managerial preferences and assist in decision-making. Few studies have examined multi-channel customer management. However, the evaluation of different Internet marketing channels in the context of organizations remains a challenge. This study focuses on identifying organizational preferences in marketing products for different Internet marketing channels. The authors have used a hybrid MCDM approach in their study. The study involves four steps of computation: calculating the relative importance of factors that are critical for different organizations in marketing their products on the Internet using fuzzy extension of DEMATEL, calculating priorities of users for each channel using fuzzy extension of AHP, reaching consensus achievement using ordinal consensus improvement approach through geometric ordinal consensus index GOCI, and ranking different Internet marketing channel using TOPSIS. The approach is illustrated through a case study.

Evaluating Internet Information Search Channels Using Hybrid MCDM Technique

The evolution of technology has fragmented the market which has resulted in media proliferation. The frequent emergence of various media channels have enabled marketers and agencies to devise alternative methods to engage with consumers. The major challenge for marketers is to be informed about consumer preferences by identifying where the online consumers prefer to search pre-purchase information about the products to maximize the benefits of marketing. This study highlights methodology for group decision support for selecting an appropriate marketing channel using multiple criteria decision making (MCDM) based on context specific requirements. Firstly the influencing factors of consumer information search have been identified through literature review. Further we have used hybrid MCDM technique for ranking different alternatives. The fuzzy analytical hierarchy process (AHP) for group decision making has been used to identify relative importance of consumer search factors and TOPSIS has been used to evaluate different marketing channels. The approach is illustrated through case study.

Employing Group Decision Support System for the Selection of Internet Information Search Channels for Consumers

A fragmented market and media propagation has emerged as a direct result of the evolution of technology. Media agencies now have a large variety of methods of reaching and engaging with potential customers. The proliferation of media has generated new challenges for marketers and identifying the most effective channel by which to reach online customers can be problematic. Marketers now need to develop an understanding of how consumers conduct their pre-purchase search for information about a given product or service so that they can optimize their promotion efforts. A fuzzy analytical hierarchy process cosine maximization FAHPCM approach was employed to assign the relative importance that online consumers give to a range of search factors. Following this, the technique for order of preference by similarity to ideal solution TOPSIS was utilized to assess the effectiveness of each respective channel. Finally, sensitivity analysis was conducted to verify the results. The effectiveness of the proposed approach is demonstrated through a numerical example.

A Group Decision Support System for Selecting a SocialCRM

As more firms adopt SocialCRM as their marketing strategy it becomes important to evaluate various SocialCRMs on the basis of certain factors. Previous SocialCRM studies have been limited to post-deployment performance evaluation using various quantitative techniques. In this paper, we propose a method to evaluate SocialCRMs which can assist an organization in selecting appropriate SocialCRM based on their needs and functionalities that they would like to perform. Firstly we evaluate criteria and finally we evaluate each SocialCRM based on each criterion using the fuzzy extension of the Analytical Hierarchy Process for group decision making.

Modeling Gender based Customer Preferences of Information Search Channels

The disparity in consumer and organization preferences of information channels is a major concern. Further, making decisions in the presence of a wide range of conflicting criteria through the use of a multiple criteria decision-making MCDM approach has gained increased prominence in recent years and research in this area has become an important consideration for business operations that involve dealing with complex decision problems. This paper describes how an integrated approach can be applied to a decision-making problem that combines a fuzzy analytical hierarchy process AHP and TOPSIS for identifying preferences consumers of information search channels according to demographic factors such as gender.

Consumer preferences of information search channel and the role of information technology

As information technology has evolved, digital media has become increasingly fragmented and has started to proliferate multiple information channels. In order to optimize on the various digital channels that are available, organizations are increasingly recognizing the importance of gaining solid insights into consumer behavior and preferences that can be translated into marketing strategies. Specifically, they are keen to identify which information channels they can use to effectively reach and communicate with their target market. This paper describes how fuzzy AHP and TOPSIS can be used to develop a new method of decision making that will enable an effective and systematic decision process. This paper provides a demonstration of the underpinning working methodology of the proposed model by examining an illustrative example that is based on the decision process Internet users employ during their online search for information.

E-tailer personality and behavioral intentions: the application of self-congruity theory

Abstract The present study is an effort to develop an e-tailer personality scale. Subsequently, we check the impacts of e-tailer personality on self-congruity and behavioral intentions such as intention to re-shop and intention to recommend. We have followed a traditional scale development method – item generation, purification, and dimension assessment. A structure questionnaire has been used to collect primary data online. A structure equation model was used to analyze the data. This study has developed a e-tailer personality scale of five dimensions: sophistication, competence, excitement, sincerity, and convenience. The results of a structural equation model largely support the propositions that e-tailer personality is positively related to self-congruity. The results also show that e-tailer personality, behavioral intentions and self-congruity are positively related. A comparison of the developed scale with the existing brand personality scales, results in a unique dimension of e-tailer personality scale. Arguably, this study may be seen as a first study in an emerging economy and online retailing domain. The results have both academic and managerial implications.