The need for sustainable development, coupled with the growth in industrialization, creates a complex environment in which businesses strive to achieve and maintain a competitive advantage. Information now forms a vital part of how firms perform in today’s globalized corporate world. This paper explores the impact of information systems on sustainable organizational operations. Furthermore, it observes how IT infrastructure and information security policy (ISP) play vital roles in the changing business environment. The importance of information security culture (ISC) as a mediator in developing the association between the independent and dependent variables is also investigated. Reviewing these categories’ interactions within the context of transitional economics is the main goal. To assess and predict the impact of ISs, ISP, ITI, and ISC on sustainable organizational performance (SOP), 214 businesses took part in a structured survey. For data cleaning and reliability analysis, SPSS software was used; for mediation analysis, the Preacher and Hayes approach was applied; and, for multiple linear regression analysis, Python was applied. The study is significant for developing countries in the role of IS for the effectiveness of IT governance and strategic integration. The findings indicate that organizational performance is substantially impacted by information security policy (ISP), IT infrastructure (ITI), and information security culture (ISC).

In this study, we propose the combination of exponential and ln ratio type estimator to estimate the mean of Y (Study Variable) by incorporating two auxiliary variables in two phase sampling scheme. Under simple random sampling without replacement, the illustration for mean square error and mathematical comparisons are presented. Several approaches are available in literature to estimate the study variable by using information on the variable of interest. The performance of our proposed estimator is compared with other ratio type estimators theoretically and empirically. It is observed that ratio and exponential ratio estimators considered by various researchers and usual unbiased estimator is less efficient than our proposed estimator. An efficiency comparison is also given using five data sets and simulation studies for checking the merits of our proposed estimator and outcomes are sound and moderately illuminating in comparison to different estimators.

Gul and Mohsin 2021 developed a new modified form of renowned “Half logistic” distribution introduced by Balakrishnan (1991) and named it half logistic-truncated exponential distribution (HL-TEXPD). Some mathematical characteristics are studied, including hazard function, P^th percentile, moment generating function and Shannon entropy. Simulation study is performed to examine the behaviour of parameter estimates. The proposed model is fitted on three real data sets to check its efficacy. Additionally, TTT (total time on test) plot is drawn to study the failure rate of the three data sets. The results verdict that HL-TEXPD can be efficiently utilized in the field of engineering and medical sciences based on the data sets under study contrary to the classical and baseline models.

The purpose of this study was to assess the usage patterns of credit/debit cards across various demographic characteristics and to check their association with factors like card usage preferences, financial conditions, budget control, and money shortage. A close-ended questionnaire was used to record demographic information and responses to assess the comparative use of debit/credit cards in urban and rural areas of Lahore and Kasur. The estimated sample size was 225 consumers. After cleaning of data, the final sample analyzed consisted of 200 subjects. The empirical analysis was done through SPSS. The result shows that gender, occupation, area, and income play a significant role in the different usage patterns of credit/debit cards at the time of purchase.

An exponential and log ratio estimator of population mean using auxiliary information in double sampling