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PurposeThe purpose of this study is to test a model on pro-sustainability orientation (PSO) among the students and comparison of the levels of PSO among the first-year and the second-year MBA/PGDM students studying in Indian higher education institutions.Design/methodology/approachThe study comprised of quantitative analysis of PSO through a questionnaire that was distributed among MBA/PGDM students of four prominent higher education institutions in the state of Maharashtra. A total of 425 students responded to the survey. The items of this instrument included actions such as reuse, recycling, energy, conservation and so on. Likert scale was used to measure the dimensions and structural equation modelling was applied to test the PSO model.FindingsThe study revealed significant difference in the PSO among male and female students with respect to equity dimension and significant differences among the first- and second-year MBA students with respect to pro-environmental deliberations. A significant difference was found among the four institutions with respect to the pro-environmental deliberations, altruistic behaviour and affinity towards diversity. The study showed positive influence of PSO over SB. The study revealed that the students enrolled in MBA/PGDM showed positive attitude towards SD and the environment.Practical implicationsThere has been a dearth of studies conducted on PSO of students enrolled in Indian higher education. This study is an attempt to show the impact of the Indian higher education on the pro-sustainable lifestyles among the students of MBA/PGDM that can provide valuable insights for the millennials of the emerging economies.Originality/valueThis study is an attempt to depict the role played by the Indian higher education institutions in the development of PSO among the students of MBA/PGDM. In order to promote sustainable development within one’s society, one needs to educate future leaders about the importance of sustainability.

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In the age of information, the world abounds with data. In order to obtain an intelligent appreciation of current developments, we need to absorb and interpret substantial amounts of data. The amount of data collected has grown at a phenomenal rate over the past few years. The computer age has given us both the power to rapidly process, summarize and analyse data and the encouragement to produce and store more data. The aim of data mining is to make sense of large amounts of mostly unsupervised data, in some domain. Data Mining is used to discover the patterns and relationships in data, with an emphasis on large observational data bases. This chapter aims to compare the approaches and conclude that Statisticians and Data miners can profit by studying each other's methods by using the combination of methods judiciously. The chapter also attempts to discuss data cleaning techniques involved in data mining.