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The study aims to assess a sustainable green financial environment by exploring the underlying structure of monetary seismic aftershocks of the COVID-19 pandemic. This study is qualitative and uses a review of literature, primary data collection methods, and qualitative analysis techniques as the study's overall design. The data is collected by one-to-one interview using a matrix style questionnaire from a panel of experts based on the purposive sampling technique. Interpretive structural modeling (ISM) combined with Matrices' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) is used for assessment, modeling, and analysis of data. The monetary aftershocks, namely, "more cash in hand required," "decreased travel costs," "shift to more certain or fixed revenue streams," "lower rent costs," "more zealous monitoring of cash collection cycle," and "decreased entertainment costs," occupy level I (top of the model being least critical shocks), and "tedious regulations" occupy level VIII (bottom of the model being the most vital). Other aftershocks form the middle of the model being moderate critical. Analysis of MICMAC shows that monetary seismic aftershocks high fees for assistance regarding SOPs, tedious regulations, and more downtime due to pandemic alerts are independent. This study addresses the core issue from within the aftermath of the COVID-19 pandemic. It provides new important information regarding the structure of a sustainable green financial environment that is useful for economists, financial analysts, commercial and central bankers, accountants and finance managers from the organization's public/and private sectors, local and international community, and researchers of the domain. It provides an informative structural model and classification of critical aftershocks. There are specific data/methodological/resource-related limitations of the study. The study's data are collected from a focus group; the study's methodology is qualitative and indicates relations among variables that do not quantify the associations. The study is a typical initiative of academic researchers with limited financial/physical resources; therefore, the generalizability of the study results is accordingly limited. The study is based on original, essential data and innovatively and creatively approaches the problem. It provides a unique model of an unprecedented phenomenon for reverberating the sustainable green financial environment.

PurposeThe study aims to investigate the barriers in implementing social distancing at the workplace as an aftermath of the COVID-19 pandemic period.Design/methodology/approachStudy design consists of a review of literature, data collection and analysis. It encompasses identification, verification and analysis of the relationships among the barriers. Data have been collected from a panel of experts on matrix-type questionnaires from workplaces. Interpretive structural modeling (ISM) augmented with “Matrice d' Impacts Croise's Multiplication Appliquée a UN Classement (Cross Impact Matrix Multiplication Applied to Classification)” (MICMAC) for structural analysis.FindingsThe literature has identified twenty major barriers to implementing social distancing at the workplace. The research findings reveal/show that the barrier “matter of disrespect” occupies the bottom level in the ISM model. Therefore, it is the most critical barrier; whereas, employees with disabilities and “herding culture” are crucial as they occupy the next lowest level, therefore, are crucial. Moreover, there are ten barriers positioned in the middle of the model having moderate-severe effects, and seven falls on the top level of the model having relatively less severe effects. Results of MICMAC affirm and avow the results of ISM.Research limitations/implicationsThe study will have profound theoretical and practical implications for stakeholders since it provides lot of new useful and valuable information, gives relational insights and determines priorities subject to usual limitations of survey research.Originality/valueIt is an original attempt to make some sense of practicability of social distancing for stakeholders including policymakers, frontline health workers and public at large.

The COVID-19 pandemic created a significant economic decline and altered market behavior, forcing buyers and dealers online. The traditional local market merchants are not fully equipped with e-commerce business techniques and strategies, which is a barrier to their e-commerce behavior and success. The study aims to help small-medium firms adapt to an uncertain economic environment instead of reducing or shutting down business-like in Pakistan. From health to education, economy to domestic and social protection, various researches have been done since 2020. The researcher used primary data sources and did a Quantitative study after collecting the 240 samples size of data from the successful e-commerce players of Pakistan. The results confirm that customer satisfaction is essential for entrepreneurs to succeed, as customers were not satisfied with online shopping during COVID-19. Customer knowledge management (CKM) and job satisfaction (JS) are studied as potential and realized capacity variables. CKM act as a strategic asset to collect and assimilate the external customer knowledge. In contrast, satisfied employees act as a valuable asset that dynamically responds to changing customer needs and business environment by efficiently utilizing their knowledge and skills and reaching business success which is mirrored in customer satisfaction. Conclusive results enable practitioners to perceive the business success during economic crises in the organization’s absorptive capacity.

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. Overall design of the study consists of review of literature, data elicitation & analysis. 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. 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. 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.

The purpose of the study is to gauge the unemployment level of selected one hundred and thirteen countries. The design of the study includes a survey of the literature, extraction of relevant data and analysis. The study follows a quantitative paradigm of research that uses secondary data set taken from the website of World Development Indicators (WDI). The analysis encompasses selected countries based on the availability of data. The data has been analyzed using Grey Incidence Analysis Model, commonly known as GRA. For interpretation of the results, the methodology has been augmented with the scheme of ensigns (i.e. classification of countries into Extremely Low, Very Low, Low, Moderate, High, Very High, Extremely High) of the level of unemployment. Results show that J&APR have an extremely low level of unemployment and member countries of SADC have an extremely high level of unemployment. Pakistan fall under the ensign of very low, therefore have a low level of unemployment. It is valuable to study equally useful for governments, academia and the international community. This study provides critical new information on the phenomenon.

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

“Cause” is the word of positive-valence stimuli and increasing the like-hood intend to be a pair with it. Linking of consumer purchase with social cause is common and in rising trend. It’s a favorable tool of an organization to engage consumer and make his emotional attachment in charitable cause and increase sales volume. Previous Cause Related Marketing (CrM) literature has examined the CrM in term of consumer or in term of brand or purchase, we could not find any study which is investigating the mediating role of specific time between CrM and attitudes of consumers towards brand, ad, offer and cause involvement. Present study examines the best use of CrM according to time in beverages industry on soft drink on a holy occasion of Muslims (i.e. Ramazan). An already established questioner was used for collection of data. Mall intercept convenience technique is use to gather data. It’s a multiple group analysis study, data was collected two times, once during event and once after the event, sample size was remain same both times. Morgan’s formula is used to select the size of samples. Results of study show that CrM has influence on customer attitude which was being measured in three types, furthermore these attitudes has positively influence individual’s intention to buy a specific brand in a specific time period. This study will be provided a best use of CrM campaign according to time. Research will also direct the marketers to use of CrM on a specific time to tackle their customer’s attitude.

The study aims to assess and analyze the social outcomes of the COVID-19 pandemic. The study uses the discourse of comprehensive literature review to identify the outcomes, Interpretive Structural Modeling (ISM) for developing a structural model and Matrices' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) for analysis, classification of societal outcomes, and corroboration of results of ISM. Data from fifteen experts was collected through a survey questionnaire. As a result of the literature review, a list of sixteen outcomes was generated and verified by a panel of experts. Results of ISM revealed that the outcomes, namely, "emotional instability," "mental health self-harm," loneliness reduced recreational activities, obesity, and "increased screen time" come at the top of the model; therefore, they are less vital outcomes, whereas the most significant outcome which is at the bottom of the model is "employment instability"; hence it has a major impact on the society. The remaining outcomes fall in the middle of the model, so they have a moderate-severe impact. Results of MICMAC validate the findings of ISM. Overall findings of the study reveal that "employment instability" is the crucial social outcome of the COVID-19 pandemic. It is an original attempt based on real-time data, which is helpful for society at large, researchers, the international community, and policymakers because this study provides a lot of new information about the phenomenon. The study includes understanding society at large, policymakers, and researchers by illustrating the complex relations and simplifying the connections among a wide range of social outcomes of COVID-19.

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.

This study aimed to analyze stressors to which medical staff is vulnerable due to the coronavirus disease 2019 (COVID-19) pandemic. It also imposes a hierarchy on complex relations among stressors for excavating underlying structure and builds a model of interrelationships contrasting reality. The design of this study comprises a literature survey, data collection from primary sources, and analysis. Stressors have been explored from within current published/unpublished literature and validated by experts through approval vote. Data were collected from the focus group (panel of experts), and interpretive structural modeling (ISM) was used as the research methodology. Findings of ISM are avowed through “cross-impact matrix multiplication applied to classification” (MICMAC) analysis. As a result of the literature survey, a list of stressors was generated, and a total of 19 stressors qualified as representative of the phenomenon. The results of ISM show that two stressors (i.e., “unavailability of proper personal protective equipment (PPE)” and “lack of proper communication”) emerged as the most critical stressors since they occupy the bottom of the model, whereas, four stressors (i.e., “anxious about isolation/quarantine,” “subject to violent crimes,” “feeling frustrated and powerless,” and “exhausting shifts/hours without clear end”) are relatively less critical since they occupy the top of the model. The rest of the stressors occupy the middle of the model and therefore, have moderate-severe effects on frontline soldiers. The results of MICMAC show that the stressor “subject to violent crimes” is classified in the dependent cluster and the remaining fall in the linkage cluster but no stressor falls in independent and autonomous. Overall results indicate that all stressors are relevant to the phenomenon under this study, but they are currently not settled. This study is invaluable for policymakers, frontline soldiers, researchers, the international community, and society since it provides a lot of new information that is helpful in refining strategies and combating influential stressors.

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.

The purpose of this study is to structure a model of relationships among barriers in the implementation of CG in Pakistan. It also points out a key barrier in embarking on the regime of CG. The design of research consists of a literature review, data collection and analyses. Modeling methodology entails ISM coupled with MICMAC. Findings revealed that “lack of investigation about the rights of minority shareholders” is the most critical barrier since this occupies the bottom of the model. Whereas, barriers namely “basic shareholders rights are not often protected, minority shareholders rights are often violated, lack of autonomy on the part of the auditors and rules requiring equity ownership disclosure are not followed” are least critical since they occupy the top of the model. MICMAC analysis revealed that three barriers fall in the independent quadrant, six in the linkage, six independent and two in autonomous. This study is helpful to regulators and corporations to successfully embark on the regime of CG.

Aim of the study is to apply ISM on disordered chaotic hierarchy of employees’ emotional behaviors that result in failed mergers. It is an exploratory research that uses in depth literature review for identification of behaviors, ISM for exploring causal relations, analyzing interactions & prioritizing them and MICMAC analysis for classifying them on the basis of their driving-dependence power. Findings revealed that: there are total eighteen employees’ emotional behaviors, having four levels hierarchy where job insecurity, feeling of degradation and jealousy occupy bottom of ISM model, hence, are most critical whereas, shame and compassion occupy top i.e. relatively less critical. MICMAC revealed that two behaviors are dependent, two are independent, fourteen are autonomous and no ambivalent. This study is useful for organizations which are in process of mergers or acquisitions. This study is unique as it takes the matter holistically and develops pertinence wise hierarchicalization of behaviors. The paper offers three main contributions: i) it provides comprehensive conceptual understanding of constructs of the phenomenon and underpins complex relationships among behaviors, ii) developed a model of hierarchicalization of emotional behaviors and iii) developed driving-dependence diagram on the continuum of weak-strong.

This study aims to generate a list of enablers of quality enhancement of higher business education in Pakistan and build a structural model of enablers to prioritize them. It also intends to impose direction and hierarchy on the inter-relationships of the enablers. The study’s design consists of a literature review, data collection from primary sources, and qualitative analysis. Interpretive Structural Modeling (ISM) coupled with Matriced’ Impacts Cruise’s Multiplication Appliquée a UN Classement (MICMAC) is used as a research methodology. The classical procedure of ISM and MICMAC is applied to primary data collected by a field survey from a panel of experts recruited from folks of stakeholders of business education. Results of the literature show that eighteen critical enablers enhance the quality of higher business education in Pakistan. Results of ISM show that the enabler ’job placement of graduates’ occupies the top-level of the ISM model being least critical. In contrast, the enabler ’intra-academia linkages’ occupying the bottom of the model is the most vital. Results of MICMAC show that all enablers, except ’job placement of graduates, are classified into linkage clusters, whereas ‘job placement of graduates’ is classified as an independent cluster. Overall results of the study show that enablers of quality enhancement of higher business education in Pakistan are agile and not settled. The study has profound theoretical, managerial, and practical implications for all stakeholders of business education. It also provides a research framework for future studies concerning subject phenomena. The discussion about the structural model culminates into policy guidelines for the regulators. The study is subject to some methodological/data/resources limitations like the limited review of literature, collection of data from a medium-size panel of experts from Pakistan only, using majority rule for aggregating responses, answering only that what is related to what, other common limitations of qualitative studies, shot period and absence of financial support. The authors conduct this study in a real-life field setting is built on the original dataset and address the efficient issue of phenomenon understudy differently. It is theory-building research, therefore, does not require prior theory. It exploits simple elementary concepts of Boolean algebra, set theory, and graph theory that generates new in-depth information for stakeholders.

This study aims to investigate employees’ physical behaviors under the environment of mergers. Chaotic recognition and disorderly hierarchicalization of critical physical behaviors of employees resulting into unsuccessful mergers is the problem under investigation. Employees have power to dictate the fate of mergers; therefore, it is imperative to scientifically underpin the patterns of their physical behaviors while during execution of mergers. The study follows positivist approach as research philosophy. It has identified and developed a hierarchy of physical behaviors that emerge into employees during organizational mergers. It is an empirical study based on formalized in-depth analysis. A specially designed questionnaire has been used for collecting data from a medium sized heterogeneous panel of experts on mergers. Technique of discourse of literature has been employed for identification of behaviors, Interpretive Structural Modeling (ISM) for hierarchicalization whereas cross-impact matrix multiplication analysis (MICMAC) for investigation of driving and dependence power. Total eleven behaviors have been identified. ISM model depicts that bottom is occupied by conflict, middle by reduced organizational commitment and top by lower productivity. It means that conflict among employees is the most critical physical behavior, reduced organizational commitment is linking and lower productivity is least critical for mergers. MICMAC revealed that five behaviors fall in driving, four in dependent, one in linking and two in autonomous quadrant. The study is based on limited number of experts’ opinion, however, that may be envisaged on larger population for statistical investigation. The study provides insight to the policy makers, planners and executers of mergers.

The study has been conducted to empirically test mediating role of organizational commitment between corporate social responsibility (CSR) & proactive personality and job performance. It is a quantitative study designed to evaluate multiple regression equations based on data collected from two major service sectors of Pakistan i.e. banking and telecom. Partial Least Squares (PLS) based Structural Equation Modelling (SEM) has been employed as technique of analysis. The results showed that CSR and proactive personality positively affect job performance and organizational commitment partially mediates the relationship between them. The study provides new valuable insights to management of service sector organizations. It provides insights that how implementing CSR and proactive managers improve performance of employees

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 expert from within stakeholders.

Quality has always been center of gravity for superior competitive advantage. TQM has captured attention of both practitioners and academicians because it is an important management practice for improving performance. This research is aimed to provide insight of the challenges faced by readymade garment industry of Pakistan for implementation of TQM principles. In depth literature, Interpretive Structural Modeling (ISM) and Matriced' Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses have been employed to investigate the phenomena under study. Discourse of literature revealed that there are twenty challenges in implementation of TQM. Lack of employee trust in senior management is the most critical challenge to be addressed that occupies bottom of the model. Lack of formalized strategic plan for change and lack of leadership occupy highest position in the model hence attracts least attention. MICMAC analysis revealed that lack of consistency of purposes autonomous, lack of evaluation procedures and benchmark indices and obsolete technology are independent and all other challenges fall in linking quadrant. Whereas no such challenge is exclusively categorized as dependent, however, most of the linking factors have high degree of dependence as well. This study is useful for the organizations which are in process of implementing TQM practices.

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The aim of this study is to investigate the Impact of Brand Image, Service Quality and Trust on Customer Loyalty, Moderating Effect of Perceived Price Fairness and the Mediating Effect of Customer Satisfaction on telecommunication sector of Pakistan. This research is helpful to capture and retain the satisfied and loyal customer and it is useful to identify the factors through which telecommunication sector may improve its performance. The survey research design method was used in this study. It involves a questionnaire for the collection of data from the respondents. Convenience-based Sampling was used in this research data was collected with the help of a questionnaire from 250 customers in the telecommunication sector of Pakistan (Warid, Zong, Mobilink, and Ufone Telenor). Correlation analysis was conducted utilizing SPSS to analyze the data. It is revealed that the correlation between customer loyalty and three independent factors that are quality service, brand image, and trust is very strong and mediator customer satisfaction in this relationship had an effect on customer loyalty. There exists a strong relationship between three dimensions of independent variables and the dependent; we can say that there is a strong effect of a mediator and moderator on these relationships. There is also a very strong correlation between customer loyalty and customer satisfaction.