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Exact confidence interval estimation for the new extreme value model is often impractical. This paper seeks to evaluate the accuracy of approximate confidence intervals for the two‐parameter new extreme value model.

The confidence intervals of the parameters of the new model based on likelihood ratio, Wald and Rao statistics are evaluated and compared through the simulation study. The criteria used in evaluating the confidence intervals are the attainment of the nominal error probability and the symmetry of lower and upper error probabilities.

This study substantiates the merits of the likelihood ratio, the Wald and the Rao statistics. The results indicate that the likelihood ratio‐based intervals perform much better than the Wald and Rao intervals.

Exact interval estimates for the new model are difficult to obtain. Consequently, large sample intervals based on the asymptotic maximum likelihood estimators have gained widespread use. Intervals based on inverting likelihood ratio, Rao and Wald statistics are rarely used in commercial packages. This paper shows that the likelihood ratio intervals are superior to intervals based on the Wald and the Rao statistics.

Extreme value model is one of the most important models that are applicable in air pollution data. This paper aims at introducing a new model of extreme value that is more suitable in environmental studies.

The parameters of the new model have been estimated by method of maximum likelihood. In order to relate to air pollution impacts, the new extreme value model was used, applied to carbon monoxide (CO) in parts per million (ppm) at several places in Malaysia. The objective of this analysis is to fit the extreme values with a new model and to examine its performance. Comparison of the new model with others is shown to illustrate the applicability of this new model.

The results show that the new model is the best fit using the method of maximum likelihood. The new model gives a significant impact of CO data, which gives the smallest standard error and p‐values. The new extreme value model is able to identify significantly problems of air pollution. The results presented by the new extreme value model can be used as an air quality management tool by providing the decision makers means to determine the required reduction of source.

The new extreme value model has mostly been applied in environmental studies for the statistical treatment of air pollution. The results of the numerical and simulated CO data indicate that the new model both is easy to use and can achieve even higher accuracy compared with other models.

This paper aims to analyse the unified theory of acceptance and use of technology (UTAUT) and UTAUT2 constructs used in research on information and communication technology (ICT) adoption and use among micro, small and medium enterprises (MSMEs) in non-organisation for economic co-operation and development (OECD) countries. It also investigates the areas of ICT adoption along the value chain in studies using these constructs.

Systematic literature review (SLR) was conducted, where 910 studies were retrieved manually in five academic databases. Forty-eight studies were finalised after four filtration levels.

Majority of the studies were published within the past six years, and 85.42% were studies in the form of journal papers. UTAUT constructs more researched compared to UTAUT2 constructs. More than half of the studies investigated ICT application in value chain boundaries, while 16 studies were organisation-wide studies.

With developments in MSMEs’ technology, the UTAUT2 model must be expanded to internal company operations including finance and infrastructure maintenance. To boost competitiveness and productivity, non-OECD authorities should focus on the cost and user-centric characteristics of MSMEs’ technology adoption.

Although SLRs on UTAUT and UTAUT2 constructs have been attempted previously, this study contributes to the body of knowledge by focusing analysis on the application of those constructs on MSMEs in non-OECD countries and also by situating ICT adoption along the value chain of enterprises.