• Causal modelling and analysis evaluation of online reputation management using Fuzzy Delphi and DEMATEL

      Kumar, Anil; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology and Management, Gwalior; School of Management, BML Munjal University, Gurgaon, India; Behavioural Economics Experiments and Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India (IGI Global, 2017-01)
      Online reputation management (ORM) is a significant and proactive tool that can reinforce the credibility of the service provider. Literature existing today on this topic has rarely reported on the causal modeling analysis from an ORM perspective. Therefore, the objective of this paper is to build a factor structure of ORM and to build the inter-relationship map amongst the criteria of each factor. To allow for vague human judgment, a fuzzy concept is employed in a form of Fuzzy Delphi. The DEMATEL technique has been used to develop a Network Relationship Map (NRM) among the criteria of each factor. Data has been gathered through a structured questionnaire conducted with a survey of experts. The study divided the criteria of each factor into cause-effect criteria. Findings of the study show that criteria such as distributed reputation system, trust, online competitive branding, website management, customer relationship, search engine optimization, corporate social responsibility, users' reach, competition/page views, purchase discounted products and cash back or money back fall under the cause group of ORM's factors. The results of this study can not only help service providers to enhance their reputation but can also guide them towards targeting their customers in an online platform.
    • Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

      Kumar, Anil; Kabra, Gaurav; Mussada, Eswara Krishna; Dash, Manoj Kumar; Rana, Prashant Singh; Xavier Institute of Management, Bhubaneswar, India; BML Munjal University; Indian Institute of Information Technology & Management, Gwalior (Madhya Pradesh), India; Thapar University Patiala, Punjab, India (Springer, 2017-05-30)
      A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.
    • Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

      Kumar, Anil; Pal, Amit; Vohra, Ashwani; Gupta, Sachin; Manchanda, Suryakant; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology and Management; BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; et al. (Emerald, 2018-07-02)
      Purpose – Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. Therefore, the aim of this study is the construction of capital procurement decision making models to optimize supplier selection in the Indian automobile industry. Design/methodology/approach – To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings – The results show that the total cost of ownership is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, total cost of ownership, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value – The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.
    • Developing textile entrepreneurial inclination model by integrating experts mining and ISM-MICMAC

      Kapse, Chanduraj Pious; Kumar, Anil; Dash, Manoj Kumar; Zavadskas, Edmundas Kazimieras; Luthra, Sunil; Government Polytechnic, Nagpur, India; BML Munjal University; Indian Institute of Information Technology and Management; Vilnius Gediminas Technical University; State Institute of Engineering & Technology,Nilokheri, India; et al. (Taylor and Francis, 2018-03-05)
      The Indian textile industry is lacking in an entrepreneurial inclination of a skilled young generation; because of this, the industry is facing a challenge to achieve sustainable development and growth. To overcome this problem, the goal of this work is to build an entrepreneurial inclination model in the context of the textile industry. For achieving this goal, a combined approach of an extensive literature review and experts mining has been used to establish the entrepreneurial inclination factors in phased of the study. In the second phase, an Interpretive Structural Modelling (ISM) with Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) has been applied to build a structural model and to find the driving force factors and dependence power. The results show that effective entrepreneurship courses, institutional policy, training and internship, institutional corporation and the involvement of institutional heads play a very significant role in encouraging youth towards entrepreneurship. The outcomes of the study can help both the government and academic institutes to draw up effective policy and develop an entrepreneurial culture which can help to create more entrepreneurs in the textile field.
    • Investigating the role of social media in polio prevention in India: a Delphi-DEMATEL approach

      Kumar, Anil; Kaviani, Mohamad Amin; Bottani, Eleonora; Dash, Manoj Kumar; Zavadskas, Edmundas Kazimieras; BML Munjal University, Gurgaon, India; Islamic Azad University; University of Parma; Indian Institute of Information Technology & Management; Vilnius Gediminas Technical University; et al. (Emerald, 2018-05-08)
      Abstract Purpose- This study aims to evaluate the role of social media (SM) tools in the polio prevention in an Indian context, using a hybrid Delphi-DEMATEL approach. Design/methodology/approach- A preliminary list of suitable evaluation criteria was derived from an extensive literature review. Ten experts were then contacted to collect data and finalize the most prominent criteria using the Delphi method. To establish cause-effect relationships among the criteria, further data were collected from twenty-one experts. The decision-making trial and evaluation laboratory (DEMATEL) method was applied to process and interpret the data collected. Findings- The analysis grouped criteria into two sets, i.e. cause and effect. The results show that awareness of social cause and government utilization of resources fall into the cause group; these elements are critical since both directly affect the remaining criteria. These outcomes can help government and businesses to utilize SM for public health surveillance, e.g. to promote schemes/initiatives through sites concerning polio or related health issues. Practical implications- The findings of this research are useful for governments and individual companies to conceive their marketing initiatives akin to polio prevention issues using SM. Originality/value- Despite the emergence of SM, there has been little discussion in existing literature on their role for polio prevention; however, measuring such role could be useful in practice, to help decision makers (DMs) exploiting the potential of SM in the healthcare context. To fill this gap, this study aims to measure the role of SM in polio prevention in the Indian context and to create a cause-effect evaluation model. Using an integrated Delphi-DEMATEL framework for decision-making in the healthcare context is another novelty of this study.
    • Performance Efficiency Measurement of Airports: A Comparative Analysis of Airports Authority of India and Public Private Partnership

      Kumar, Anil; Dash, Manoj Kumar; Sahu, Rajendra; University of Derby; BML Munjal University, Gurgaon, India; Indian Institute of Information Technology and Management, Gwalior, India; School of Management, BML Munjal University, Gurgaon, India; Behavioural Economics Experiments and Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India; Indian Institute of Information Technology and Management, Gwalior, India (IGI Global, 2018-04)
      This article describes how to improve the overall efficiency and effectiveness of the aviation sector and also to source extra funding, the Government of India has paved the way for private investors through to a Public Private Partnership (PPP) model since the 1980s. This liberalization step in the Indian aviation market has minimized the institutional barriers which have hindered the freedom and flexibility of air transport operations among private investors. Now, competition within the aviation sector has become fiercer; the Airports Authority of India (AAI) and Public Private Partnership (PPP) in Indian airports are not only providing varied services, but also attracting consumers with new infrastructure and full modern facilities. The importance of this article is because after privatization, no studies have been conducted to examine the efficiency of Indian airports by using Data Envelopment Analysis (DEA). An output-oriented DEA model is employed to determine the efficiency score of airports by taking a sample of 15 airports, including airports run by PPP, for comparison. Output-oriented DEA calculates the efficiency by maximizing the outputs for a given level of inputs. Therefore, this article contributes to the existing literature on Indian airports. Based on available data, three variables - length of runways, terminal size and number of check-in counters, are used as inputs and two variables - passenger movement and aircraft movement, are used as outputs.
    • Using entropy and AHP-TOPSIS for comprehensive evaluation of internet shopping malls and solution optimality

      Kumar, Anil; Dash, Manoj Kumar; Seharawat, Ritu; University of Derby; Indian Institute of Information Technology and Management, Gwalior, India (Inderscience, 2017-02-21)
      Consumers are switching from offline to online to buy everything due to this reason nowadays Internet shopping malls (ISMs) are setting up a very crucial role in the economy. For assessment and ranking are basically a critical work which could be exploitation of Internet shopping malls information resources when consider in a scientific way, there are many methods for the evaluation and ranking of e-commerce sites. Taking into consideration Traffic Rank, Inbound Links, Competition, Speed, and Keyword Statistics, in literature Multi Criteria Decision Making (MCDM) methods are rarely used by the researchers to find the rank of Internet Shopping Malls (ISMs) on the basis of primary/secondary data of these influencing factors. This study, therefore, is unique to narrow down the gap in literature by employing MCDM methods i.e. Entropy and Analytic Hierarchy Process (AHP) to collect the weight of influencing factors and Technique for Order Preference by Similarity to Ideal (TOPSIS) to find the rank of Internet Shopping Malls (ISMs). After finding out the rank of selected criteria, solution optimality needs to be done to find the average ideal solution matrix. Conclusion and managerial implications of the study are also discussed.
    • Using Fuzzy Delphi and Generalized Fuzzy TOPSIS to Evaluate Technological Service Flexibility Dimensions of Internet Malls

      Kumar, Anil; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology & Management, Gwalior (Springer, 2017-02-20)
      The expanding development of technology and availability of the internet is leading a consumer shift from offline to online activity. This shifting behavior shows positive signs for the growth of the e-commerce market but also increases the challenges for the online service provider to provide satisfaction and loyalty to consumers when there is no personal interaction between buyer and seller. In these circumstances, quality, in terms of technology services i.e. web/transaction, can play a significant role for the service provider, especially for internet shopping malls. But there is little material available in current literature to build a theoretical model for web/transaction flexibility dimensions and to rank internet shopping malls on their provision of services to customers. The vagueness of the available information can be tackled by fuzzy theory by employing a Fuzzy Delphi method to finalize technological service dimensions and lead to development of a research model. The final ranking of internet malls has been achieved by utilizing Generalized Fuzzy TOPSIS. The findings of this study can be useful for internet shopping malls in devising strategies to provide a better quality of web/transaction service to customers.