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Microfinance is considered to be one of the best tools to deliver the financial services to the poor people in Pakistan to eradicate the poverty from the roots. This research is aimed to explore the factors that impact causes of employee turnover in microfinance industry in developing countries like Pakistan. Discourse of literature coupled with experts opinion is used for identification of factors. Interpretive Structural Modelling (ISM) is used of structural mapping of factors interconnections. Cross impact matrix multiplication applied to classification (MICMAC analysis) is used for classifying the factors on the basis of driving-dependence power. ISM and MICMAC methodologies are used in order to simplify the complex and conundrum phenomena by representing it into graphical form. These are qualitative methodologies of modelling and analysis for which primary data is collected through matrix type instrument of measurement coupled with semi-structured interview. Results of review of literature show that there are 18 factors causing employees turnover in microfinance industry. ISM results reveal that job insecurity, absence of complementary financial and non-financial services, unrealistic recovery targets and temptation for money laundering are the most critical factors. MICMAC shows that there is no autonomous factor, 4 are in independent, 4 are in dependent and remaining 10 are in linking. This is a valuable study having implications for microfinance investors to use their existing resources, policy makers to design their policies according to the designed framework to gain advantage and decision makers to use their existing resources & means to manage these factors optimistically. The current study was conducted in a developed country such as Pakistan, but it can be effectively extended to neighbouring developing countries with minor changes to the hierarchy structural model.

This study attempts to rank different countries based on their performance in terms of travel and tourism and to categorize them into assemblages. The overall design of the study consists of a review of literature and analysis of secondary data as given on the website of World Development Indicators (WDI). It is a quantitative research study that uses Grey Relational Analysis (GRA) as a technique of investigation. On basis of the results of GRA, a classification has been made under a predetermined scheme of ensigns like exceptionally high, excellent, above average, average, below the average, poor, and very poor performance of countries in travel & tourism. Findings of the study show that under exceptionally high ensign majorly, there are member countries of European Union (EU), whereas, under very poor ensign mainly member countries of Economic Co-operation and Development (OECD) are categorized. It is an original research study based on country-level data analyzed through a valid mathematical technique of investigation that can generate objective results. This study is useful for the international community/institutions, policymakers, local governments, researchers, tourists & travelers, and society at large since it provides deeper insights into the phenomenon.

This study aims to evaluate worldwide official financial flows by international financial institutions to selected 123 countries of the world. The design of the study is composed of a review of literature elicited from research databases, extraction of secondary data of World Development Indicators (WDI) 2020, and mathematical analysis. In real time, cross-sectional country-level data, a classical process of Grey Relational Analysis (GRA) has been applied. Results of the study show that Argentina, Ethiopia, Bangladesh, India, Egypt, Arab Rep., Kenya, Costa Rica, Vietnam, Chad, Tanzania, Colombia, Uzbekistan, Nepal, Indonesia, Nigeria, Rwanda, Cameroon, and Uganda have exceptionally high grey relational grade meaning thereby, having an effective system of obtaining official international financial flows. Zimbabwe, Russian Federation, Botswana, Afghanistan, Bulgaria, South Africa, Burundi, Belarus, Kazakhstan, Armenia, Pakistan, Peru, Romania, and Ukraine have poor grey relational grade meaning thereby, having a relatively weak system of obtaining official financial flows. It is a unique study that provides extensive information on the official financial flows of more than a hundred countries of the world and provides the basis for the informed opinion of policymakers, political governments, economic policymakers, researchers, and academia. It also provides valuable information useful for international financial institutions.

Aim of the study is to identify what are the barriers in promoting tourism in Pakistan and imposing structure on complex interrelationships among these barriers. It is an exploratory study which uses literature discourse for identification of barriers, binary matrices for structuring issue and cross impact matrix multiplication applied to classification for analyzing driving-dependence power. Discourse of literature revealed that there are sixteen barriers important to address the issue in hand. Communication barrier and unfavorable government policies occupy bottom in the interpretive structural model that are highly important and need utmost attention. Eight barriers fall in dependent, four in independent, three in linkage and none in autonomous quadrant of driving-dependence diagram. The study is useful for policy makers and tourists' agencies to handle current issues prevailing in tourism industry and promote it accordingly. It is a foremost attempt in Pakistan to structure the issue on the basis of opinion of experts from within stakeholders.

There has been a drastic change in the ways of doing business after COVID-19. Business world has been shifted from traditional to contactless ways and digitalization has been increased during and after COVID-19 all over the world including Pakistan. So, there has been a need to study the factors that affect the success of contactless businesses, specifically in the context of Pakistan. The aim of the study is to generate the comprehensive list of critical success factors of contactless businesses in Pakistan and to analyze their interpersonal relationships and to classify them. This study is exploratory by its nature and the methodology used for this study is Interpretive Structural Modelling (ISM) along with Multiple Cross Impact Matrix (MICMAC) analysis that corroborate the results of ISM. Data has been collected primarily from the panel of experts on the topic. Results of the study show that the most important factor that contributes towards the success of contactless businesses in Pakistan is creativity and innovation which lies at the bottom of the model. This research is useful for all the stakeholders of contactless businesses since it contributes generates the list of critical factors, their hierarchical model, their classification model and lot of new information on interaction of these critical success factors.

Purpose: Aim of the study is to evaluate climate selected sixty-six countries of the world. Since climate plays a vital role in economic growth of any country and there is dearth of climate models comparing country-wise position to predict as how climate of country is relatively better than others and how it may change in the future and how will it affect on businesses. Methodology: It follows quantitative research philosophy based on secondary data obtained from World Development Indicators (WDI). Grey relational analysis is used method of analysis. A classification is made under a predetermined scheme of ensigns like: much better, better, somewhat better, fair, poor, somewhat worse and worse. Findings: Results of the study show that Arabian Countries (AC), mostly member countries of European Union (EE), Organization for Economic Cooperation and Development (OECD) and Union of South American Nations (UNASUR) have much better and conducive climate, whereas, South Asian Association for Regional Cooperation (SAARC) countries have worse and unfavorable climate for business. Implications: It is an original and valuable study that uses country level data from a reliable source. Results of the study are useful for international business community, political governments, society at large and researchers.

International trade has fundamental importance for all the countries and the analysis concerning international trade particularly concerning tariff barriers is high on the agenda of researchers in the field of economics, business and politics. Aim of the study is to assess the world tariff barriers of 158 countries. Overall design of the study comprises of a crisp literature review, data extraction and analysis. It is a study of one hundred fifty-eight countries that uses secondary data taken from World Development Indicators (WDI) 2020. It uses Grey Relational Analysis (GRA) as research methodology. Results of GRA show that Macao SAR, China, Hong Kong, Singapore, Montenegro, Mauritius, Brunei Darussalam, Myanmar, Chile, Peru and Australia have relatively highest grey relational grades meaning thereby, low tariff trade barriers whereas Grenada, Antigua and Barbuda, Belize, Central African Republic, Nepal, Guinea-Bissau, Fiji, Gabon, Barbados, Djibouti, St. Kitts and Nevis have lowest grey relational grade meaning thereby, these countries have high level of tariff based barriers of international trade. Interestingly, all the member countries of European Union occupy the rank of 27 (i.e. all countries have the same rank) which can be explained in the perspective of their union of tariff. Since, they have uniformed tariff policy as against rest of the world, therefore, have same rank. It is a study based on reliable real time data set. The study has value for all stakeholders i.e. international community, local governments, society at large, policy makers, researchers and international institutions.

Several researches have studied the proposed relationships between the perception of organizational politics (POP), job insecurity, job embeddedness and turnover intentions. However, this study investigates a different explanation, by considering the moderating effects of static personality traits such as core self-evaluation (CSE) on Turnover intention (TI) when the employee, having varying levels of job embeddedness, (JE) is exposed to POP and job insecurity (JI). The worldwide increase in aspirations and provision of premium services in hospitality industry, especially in the five star category has led the customers to expect utmost superior service in every interaction. It needs skilled and customer oriented staff to maintain the set standards. In case of loss of such trained staff it results in faulty sales experience opportunity costs that may be detrimental to the reputation of the hotel, indicating turnover as a major concern in hospitality industry. There is a need to look through the lens of job embeddedness and CSE to understand actual and intended turnover, beyond the traditional job satisfaction prism to retain the trained staff. The data were obtained from employees of five-star hotels. Researcher- administered structured questionnaires were collected using multistage sampling method. 150 respondents were initially approached, 108 were duly filled in, constituting a response rate of 72%. It is found that POP and JI are positively related to TI. However the relationship is moderated by the CSE of employee that influence his experiences, behavior and intentions. Moreover the JE.is negatively related to TI and enhances the organization-employee fit and linkage. The results of the study suggest development of 'Retention Policy' that can be established through minimization of POP and enhancement in the JE of employees. Moreover, trust and transparency can be established by sharing information about the transparent reward policies, distinguishing high performing employees. This is particularly important in hospitality industry of Pakistan where the level of POP and injustice is particularly high. Making employees realize that they are not being mistreated/ manipulated is an important aspect to enhance their embeddedness. This can also tackle the problem of job insecurity. Furthermore, the hiring procedures of employees should make use of effective, objective and standard personality tests based on different dimensions, helping in acquiring the right caliber and traits of employees, ensuring their long term retention. The originality and value of the study lies in the application of a holistic person-oriented approach that inculcates the personality traits (CSE) of employees in determining the linkages between POP, JI, JE and TI. The empirical testing provides an important contribution to the hospitality management and marketing literature in Pakistan, providing not only a guideline for hiring and reward policies for employees who exhibit turnover intentions due to either POP and injustice in reward procedures or mismatch with the job requirements. It also highlights the need for hospitality management to devise mechanisms to increase the embeddedness (which was reportedly low/not recognized) to bear the fruits of such hiring policies.

The province of Punjab is considered the breadbasket of Pakistan. This study is aimed to evaluate and hierarchicalize the districts of Punjab based on agricultural indicators. It follows a ranking approach that uses secondary cross-sectional data obtained from Punjab Development Statistics 2016. This study has employed Grey System Theory and used GRA. It is a seminal study that uses a unique methodology that has integrated thirteen different indicators of agricultural development in one mathematical model and assigned a distinct composite grade to every district. Findings revealed that district Bahawalpur and Bahawalnagar have the highest Grey Relational Grade (GRG), hence depict the best agricultural performance in Punjab, whereas district Mianwali has the lowest GRG and accordingly least performance. This research provides insight to the policymakers, which will help them to take corrective measures and/or adjust the agricultural development policies

Purpose: In this research study, author tried to analyze and investigate the issues of COVID-19 pandemic and its possible affect on economies especially in context of Pakistan. The basic purpose of this research is to examine and understand the COVID-19 issues and its consequences worldwide economies. This study was conducted using grey relational analysis. Methodology: GRA is used to calculate the correlation among two or more constructs. The core part of this research is pre.and.post.COVID-19.implications on world economies as well as on Pakistan's economy. Furhermore, in this study author tried to analyze that which year was the most destructive year for economies. For analyze and investigation, author gathered six years secondary data and apply GRA research methods to conclude the results. Findings: After successfully concluded the outcomes which showed that like other countries in the world Pakistan's economy also affected due to business were shutdown and governments imposed lockdown in country-wise which eventually caused export declined. Due to this reason, impact on Pakistan's economy went to nosedown even growth rate down to negative. Economy of any country highly depending on its exports so, in order to evaluate any country economic condition, exports of this country may highly considered. Conculsion: Therefore, at the end it was concluded that the year 2020 was the most destructive year for any country especially for Pakistan which affect the economy most.

Purpose: Health system of a country is backbone of economy. It has fundamental importance in sustainable development of a country. Aim of this article is to excavate future challenges to health system of selected 106 countries. Design/Methodology/Approach: It is a country level comparative analysis of health risk factors. Design of the study includes review of literature, data extraction and analysis. The cross-sectional secondary data has been drawn from website of World Development Indicators (WDI) 2020. Grey relational analysis is used as technique of investigation. Findings: Results show that majorly, member countries of Organization for Economic Co-operation and Development (OECD) have exceptionally high grey relational grade, therefore, are considered to be countries having less future health risks, whereas, Southern African Development Community (SADC) have exceptionally low grey relational grade, therefore, have high future health risk. Implications/Originality/Value: It is a unique study using different dataset and methods that provides valuable insights to political governments, researchers and health system managers.

The purpose of the study is to evaluate county-wide health systems using the data set of the first wave of the COVID-19 pandemic. The overall design of study comprises a literature review, secondary data, and a mathematical analysis. It is a cross-sectional quantitative study following a deductive approach. It uses the data of the first wave of the COVID-19 pandemic taken from the website of Worldometer as of April 8, 2020. The study uses a gray incidence analysis model (commonly known as Gray Relational Analysis, i.e., GRA) as its research methodology. On the basis of the results of GRA, a classification has been made under a predetermined scheme of ensigns: much better, better, somewhat better, fair, poor, somewhat worse, and worse health systems. There are a total 211 countries that have been divided into the seven aforementioned categories. Findings of the study show that Southern Africa Development Community (SADC) countries fall predominantly under the much better ensign, whereas Organization for Economic Co-operation and Development (OECD), Schengen Area (SA), and/or European Union (EU) countries fall under the worse ensign. Pakistan falls under the ensign of poor. It is an original attempt to evaluate the response of health systems based on real data using a scientific methodology. The study provides valuable information about the health systems of the countries for forming an informed opinion about the health systems herein. The study provides useful new information for stakeholders and a new framework for future research.