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Water scarcity is rising as a global issue, because the planet earth is facing a global water crisis, which is considered something that can destroy environmental sustainability of our planet. The fact is that humanity’s demand is depleting natural resources faster than nature can replenish itself; if human habits and unsustainable use of water resources do not change, water scarcity will inevitably intensify and become a major cause of conflict among different nations of the world. The water scarcity issue is a crucial issue but unfortunately it has not received due attention in past. Pakistan, which once was a water abundant country, now facing a situation of water scarcity. Pakistan has a poor irrigation system which results 60% loss of its water; Pakistan uses more water for crop production than other countries. Likewise, the country harvests water from rainfall, rivers, snow, and glaciers. The country is facing a serious water crisis that is caused by different factors, such as changing climatic conditions, rising population, poor irrigation system, poor political will, and rapid urbanization. The water crisis of Pakistan is expected to worsen in coming years. This is a drastic situation which calls for emergency measures. With this background, the present study provides a detailed view of the water situation in the country with challenges to water management. The study also suggests some recommendations for policymakers to improve the water crisis situation in the future.

One of the latest innovations in business and technology is the use of big data, as daily data are generated by billions of events. The big data issue is now considered in the accountants and finance professionals’ field as one of the most important sources for the analysis of financial products and services. This study is very innovative, with our research aiming to identify the opportunities, challenges, and implications of big data in the finance area. It is our purpose to find competitive advantages in terms of the extent to which big data brings visible benefits, also pointing out the challenges that a company may face in this field, such as cases of customers’ data security or customer satisfaction processes. The identification of this kind of dynamics allows us to draw conclusions on the advantages of big data based on these analyses and big data’s deep impact on finance. In particular, big data is now commonly used by financial institutions and banks for analytical purposes in financial market contexts. We conducted an exploratory survey of the existing literature to highlight such connections. In the last part of our study, we also propose directions for future research.

The aim of this paper is to examine the interdependence between higher education on the one hand and the competitiveness of the economy and sustainable development on the other hand. To examine the mentioned interdependence, we used a sample that includes EU member states and candidate countries. The paper applies correlation and regression analysis of comparative data sections. The research findings indicate a strong correlation between higher education on the one hand and the competitiveness of the economy and sustainable development on the other. The results obtained by research can serve as a “global benchmark” of future public policy in the field of higher education.

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Debt structure composition is an essential topic of discussion for the management of capital structure decisions. Researchers made extensive efforts to understand the criteria for selecting debts, specifically, to know about the reasons for debt specialization, concealed in identifying its predictors. This question is essential not only for establishing the field of debt structure but also for the financial managers to design corporate financial strategy in a way that leads to attaining an optimal debt structure. Sophisticated financial modeling is applied to identify the core predictors of debt specialization, influencing the strategic choices of optimal debt structure to address this issue. Data were collected from 419 non-financial companies listed at the Karachi Stock Exchange from 2009 to 2015. This study has validated debt specialization by showing that short-term debts maintain their position over the years and remain the most popular type of loan among Pakistani firms. Further, it provides a comprehensive view of the cross-sectional differences among the firms involved in debt specialization by applying a holistic approach. Results show that small, growing, dividend-paying companies, having high expense and risk ratios, followed the debt specialization strategy. This strategy enables firms to reduce their agency conflicts, transaction costs, information asymmetry, risk management and building up their good market reputation. Conclusively, we have identified the gross profit margin, long-term debt to asset ratio, firm size, age, asset tangibility, and long-term industry debt to asset ratio as reliable and core predictors of debt specialization for sustainable business growth.

Using infinite servers queues systems parameters, focused on its busy period, the performance and the differential costs of a two echelons repair system are analyzed through a model constructed with this goal. This kind of repair systems may be useful, for instance, in the operation of a fleet either of aircraft, or of shipping or of trucks