Landfill site selection is a complex process, which requires the evaluation of multiple criteria. Decision-makers often face difficulties in taking the right decision in a multiple attribute environment. In this paper, an integrated fuzzy-analytical hierarchy process (AHP)-the technique for order preference by similarity to ideal solution (TOPSIS)-based methodology was applied to the municipal solid waste (MSW) landfill site selection problem. To demonstrate the approach taken, a real case of Mumbai city is taken. The model was developed to suit the socioeconomic and regulatory setup. The fuzzy-analytic hierarchy process was used to make pairwise comparisons of criteria to assign weights and rank them, while F-TOPSIS was employed to rank the alternatives. It was found that the fuzzy-AHP-TOPSIS-based methodology can be a powerful guiding tool for MSW management planners. With this modeling approach, the accuracy of landfill site selection procedure can be significantly enhanced as compared to the traditional methods, thereby reducing the cost and time required. The developed methodology helps in representing and analyzing the uncertainty and error in the decision making process of landfill site selection.

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Mobile phones have undeniably brought a paradigm shift, affecting both the lives of people and the business environment. Today, mobile phone has permeated the lives of billions of people around the world, becoming for many an indispensable device. Moreover, adoption of mobile banking has significant impact on reducing costs and enabling change in retail banking. Factors influencing the intention to use or adopt mobile banking are very important and will play a vital role for mobile banking service providers. The proposed study focuses on a comprehensive set of potential factors that influence the adoption of mobile banking. The research model identifies appropriate factors and captures dependency relationships among these factors in the form of a number of hypotheses to be tested in this research. This paper aims to design a scale with a high degree of reliability, validity, and dimensionality which helps to determine the appropriate technology adoption model based on the identified constructs, viz. Optimism (OPTI), Innovativeness (INNO), Insecurity (INSC), Discomfort (DISC), Perceived Usefulness (PU), Perceived Ease of Use (PEU), Perceived Risk (PR), Subjective Norms (SN), Attitude (ATTI), Behavioural Control (BC) and Behavioural Intention (BI). The data were collected through questionnaire survey from 201 respondents comprising software engineers, bank employees, professors, entrepreneurs. Confirmatory factor analysis was used to test the validity of the proposed measurement scale for all the identified constructs. This instrument helps bankers to determine and design there applications which will contribute to the knowledge of predicting customer intention.

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