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Pakistan is one of the most climate change and natural disaster-affected countries in the globe, where the lives and livelihoods of people are repeatedly affected due to these natural disasters. Over the past few decades, the country has been impacted by numerous devastating floods, droughts, and storms. As a result, households face enormous complications, particularly those dwelling in disaster-prone areas. Therefore, this study intends to explore the status of household vulnerability and resilience practices of hazard-prone communities in Pakistan from existing literature. This study has identified the 17 most relevant documents. It argues that household vulnerability is increasing consistently with the increasing rate of disaster intensity. Frequent flooding, landslide, erosion, and crop loss are the leading causes of household vulnerability. This study reveals five types of household vulnerability components which look into several livelihood vulnerability indicators of Pakistani households. Moreover, the study unfolds that the main causes of disaster vulnerability are widespread crop loss, a lack of water, loss of soil fertility, and low socioeconomic situations. The major vulnerability components of dwellers are exposure (increasing summer duration, the rapid increase of population house build-up in the riparian areas, and increasing occurrence of hailstorms), sensitivity, low access to education facilities, human loss, diseases infestation, food insecurity, and social conflict), and less adaptive capacity (social networks, migration, poor emergency services, multiple income sources, and less access to the health facility). To address the household vulnerability, this study has also identified four key aspects of resilience, like social resilience, economic resilience, institutional resilience, and physical resilience. The findings will effectively help to understand the dynamics of household vulnerability and resilience and its measurement and management strategy from developed indicators.

The current paper aims to fill a gap in the literature by analyzing the nature of volatility on the Karachi Stock Exchange (KSE) 100 index of the KSE, and develop an understanding as to which model is most suitable for measuring volatility among those used. The study contributes significantly to the literature as, compared with the limited previous studies of Pakistan undertaken in the past, it covers three types of data (i.e. daily, weekly and monthly) for the whole period from the introduction of the KSE 100 index on November 2, 1991 to December 31, 2013. In addition, to analyze the impact of global financial crises upon volatility, the data have been divided into pre-crisis (1991-2007) and post-crisis (2008-2013) periods.

This study has used an advanced set of volatility models such as autoregressive conditional heteroskedasticity [ARCH (1)], generalized autoregressive conditional heteroskedasticity [GARCH (1, 1)], GARCH in mean [GARCH-M (1, 1)], exponential GARCH [E-GARCH (1, 1)], threshold GARCH [T-GARCH (1, 1)], power GARCH [P-GARCH (1, 1)] and also a simple exponentially weighted moving average (EWMA) model.

The results reveal that daily, weekly and monthly return series show non-normal distribution, stationarity and volatility clustering. However, the heteroskedasticity is absent only in the monthly returns making only the EWMA model usable to measure the volatility level in the monthly series. The P-GARCH (1, 1) model proved to be a better model for modeling volatility in the case of daily returns, while the GARCH (1, 1) model proved to be the most appropriate for weekly data based on the Schwarz information criterion (SIC) and log likelihood (LL) functionality. The study shows high persistence of volatility, a mean reverting process and an absence of a risk premium in the KSE market with an insignificant leverage effect only in the case of weekly returns. However, a significant leverage effect is reported regarding the daily series of the KSE 100 index. In addition, to analyze the impact of global financial crises upon volatility, the findings show that the subperiods demonstrated a slightly low volatility and the global economic crisis did not cause a rise in volatility levels.

Previously, the literature about volatility modeling in Pakistan’s markets has been limited to a few models of relatively small sample size. The current thesis has attempted to overcome these limitations and used diverse models for three types of data series (daily, weekly and monthly). In addition, the Pakistani economy has been beset by turmoil throughout its history, experiencing a range of shocks from the mild to the extreme. This paper has measured the impact of those shocks upon the volatility levels of the KSE.

The proposed IT2FMOVMI model intends to concurrently minimize total cost and warehouse space for the single vendor-retailer, multi-item and a consolidated vendor store. Regarding demand and order quantities with the deterministic and type-1 fuzzy numbers, we have also formulated the classic/crisp MOVMI model and type-1 fuzzy MOVMI (T1FMOVMI) model. The suggested solution technique can solve both crisp MOVMI and T1FMOVMI problems. By finding the optimal ordered quantities and backorder levels, the Pareto-fronts are constructed to form the solution sets for the three models.

A multi-objective vendor managed inventory (MOVMI) is the most recognized marketing and delivery technique for the service provider and the retail in the supply chain in Industry 4.0. Due to the evolving market conditions, the characteristics of the individual product, the delivery period and the manufacturing costs, the demand rate and order quantity of the MOVMI device are highly unpredictable. In such a scenario, a MOVMI system with a deterministic demand rate and order quantity cannot be designed to estimate the highly unforeseen cost of the problem. This paper introduces a novel interval type-2 fuzzy multi-objective vendor managed inventory (IT2FMOVMI) system, which uses interval type-2 fuzzy numbers (IT2FNs) to represent demand rate and order quantities. As the model is an NP-hard, the well-known meta-heuristic algorithm named NSGA-II (Non-dominated sorted genetic algorithm-II) with EKM (Enhanced Karnink-Mendel) algorithm based solution method has been established.

The experimental simulations for the five test problems that demonstrated distinct conditions are considered from the real-datasets of SAPCO company. Experimental study concludes that T1FMOVMI and crisp MOVMI schemes are outclassed by IT2FMOVMI model, offering more accurate Pareto-Fronts and efficiency measurement values.

Using fuzzy sets theory, a significant amount of work has been already done in past decades from various points of views to model the MOVMI. However, this is the very first attempt to introduce type-2 fuzzy modelling for the problem to address the realistic implementation of the imprecise parameters.

Increasing consumer skepticism of corporate behavior has led companies to actively manage and advertise their corporate brands. However, it remains unclear how receptive consumers across different markets are to such efforts. The purpose of this paper is to demonstrate differences and similarities between corporate and product advertising by examining consumer ad involvement (AI) levels (a motivational state activated by the personal relevance of stimuli) and its antecedents and consequences for these ad types across two markets with varying degrees of economic development.

Using a 2 (ad type: corporate vs product) × 2 (market type: developed vs emerging) between-subject experimental design, the study was conducted in two markets with varying degrees of economic development, specifically, the USA (n=285) and Pakistan (n=311).

Results show that consumer involvement with corporate ads varies for developed (USA: high) and emerging (Pakistan: low) markets but that it remains the same for product ads across markets. Developed market consumers tend to be as involved with corporate ads as they are with product ads, whereas emerging market consumers are more involved with product ads than with corporate ads. Aside from differences in involvement levels, the findings demonstrate substantial similarities in the antecedents and consequences of consumer involvement for both ad (corporate vs product) and market (developed vs emerging) types.

With advertising and communication campaigns increasingly being standardized across different markets, this study demonstrates that corporate messages do not function similar as product messages across markets. For effective corporate campaigns, ad designs should fit with the motivation levels of the target consumers across markets.

This study demonstrates the differences and similarities between corporate and product AI across a developed and an emerging market.

The aim of this research is to establish a new type of aggregation operator based on Hamacher operational law of spherical uncertain linguistic numbers (SULNs).

First, the authors define spherical uncertain linguistic sets and develop some operational laws of SULNs. Furthermore, the authors extended these operational laws to the aggregation operator and developed spherical uncertain linguistic Hamacher averaging and geometric aggregation operators.

The authors were limited in achieving a consistent opinion on the fusion in group decision-making problem with the SULN information.

In order to give an application of the introduced operators, the authors first constrict a system of multi-attribute decision-making algorithm.

This paper aims to propose an algorithm, location-aware opportunistic content forwarding (LOC), to improve message directivity using direction vectors in opportunistic networks. The LOC is based on the assumption that if approximate location of the destination node is known, then overall message delivery and cost can be improved. Efficient message delivery with low communication cost is a major challenge in current opportunistic networks. In these networks, nodes do not have prior knowledge of their recipients, and message forwarding can be achieved by selecting suitable forwarder based on some forwarding criteria, as compared to its ancestor mobile ad hoc networks.

In this paper, the authors tested LOC in two sets of mobility models, synthetic movement model and real mobility data sets. In the first set, working day movement is used as synthetic movement model, where proposed algorithm is compared against Lobby Influence (LI) and Epidemic algorithms. In the second set of experiments, the new algorithm is tested in three mobility data sets, namely, Cambridge, Reality and Sassy, and results compared against LI algorithm. The reason of using various movement models is to establish strengths and weaknesses of the proposed algorithm in different scenarios.

The experimental results show that the new algorithm performed extremely well in different scenarios, not only in terms of overall message delivery but also successfully managed to reduce the communication cost.

The new contribution increases the overall energy and storage efficiency of nodes by targeting relevant forwarding nodes in the network.

The hiring of women of colour faculty is not without unwritten presuppositions. The authors are expected to tolerate racism and to draw from cultural experience in catering to students of colour or when it fulfils institutional needs such as bringing ‘colour’ to all-white committees. Yet, the normative profile of university teachers demands detachment with a focus on high output in terms of students and publications. In the light of this, commitment to social justice seems to be in (certain) disagreements with mainstream interpretations of the academic profession. Women of colour professors are redefining educational leadership. This chapter addresses its effect on emotional wellbeing together with techniques and strategies to strengthen emotional resilience.

This study investigates the Chinese stocks' returns during different epidemic periods to assess their effects on firms' market performance.

The study employs an event study method on more than 3,000 firms listed on Shanghai and Shenzhen stock exchanges during periods of SARS, H5N1, H7N9 and COVID-19

Epidemics' effect on firms' stock returns is persistent up to 10 days after the event dates. Although the impact varies with types and development of the disease, most firms experience a negative impact of the epidemics. Among the epidemics, COVID-19 has the greatest impact, especially when it grows into a pandemic. The epidemics' impact is uneven across industries. In addition, B-shares and stocks listed on Shanghai Stock Exchange are more negatively influenced by the epidemic than A-shares and those listed on Shenzhen Stock Exchange.

The results of the study contribute to the limited literature on the effects of disease outbreaks as an economic shock on firm market performance. Given the possibility of other epidemics in the future, the study provides guidance for investors in designing an appropriate investing strategy to cope with the epidemic shocks to the market.

The research is novel in the way it compares and assesses the economic impact of different epidemics on firms and considers their impact at different development stages.

Given the overlapping themes and periods in specific subjects within Islamic economics and finance bibliometric research, which may yield similar findings in bibliometric studies, it is essential to document the growth of Islamic economic and financial research using bibliometric methodologies. This study aims to understand better the critical bibliometric review trends and scientific advancements in Islamic economics and finance.

This study uses bibliometric analysis, collecting 46 Islamic economics bibliometric papers from the Web of Science Core Collection from 1975 to 2022. The authors generated top scientific scholars, keyword analysis, citation analysis, content analysis and conclusions for journal development using R Biblioshiny, VOSviewer, ATLAS.ti and Excel.

This study has established a comprehensive bibliometric framework for Islamic economics and finance bibliometric papers, encompassing all critical areas within the discipline and identifying any remaining research gaps. The major significant areas revealed were Islamic social finance and microfinance concerns, which are closely pertinent to the issues of ethics, corporate social responsibility and sustainability, respectively. The authors also identified opportunities for future bibliometric analyses in Islamic economics and finance, which include using more comprehensive databases, refining or broadening search strategies, using advanced techniques and units of analysis and suggesting themes for further exploration.

The study relies merely on the Web of Science Core Collection database, which provides the most in-depth citations by source for the world’s scientific and scholarly research. Future research may consider expanding its scope to include other databases for a broader range of sources. Furthermore, due to the rise of bibliometric studies in Islamic economics and finance, this study also comments on the saturation of bibliometric studies conducted in several similar areas. While researchers bring their unique analytical perspectives to bibliometrics, this study provides a comprehensive view of existing research in Islamic economics and finance, highlighting well-explored topics and those that remain less studied. Thus, this could assist researchers in determining their future research priorities.

Policymakers in Islamic financial and economic institutions, including banking institutions, social, financial institutions and halal institutions, should be impacted by this research when making policies or conducting research. The viability of the current Islamic economic and financial ecosystem will be indirectly maintained and managed by these implications.

This comprehensive meta-analysis in Islamic economics and finance is expected to impact the development and sustainability of the Islamic economic and financial ecosystem, promoting societal welfare through applying Islamic economics and finance.

This pioneering bibliometric analysis of Islamic economics and finance papers aims to offer insights and projections for future research in the field. This research contributes to the literature by examining various aspects, including evaluating literature on trending topics, analyzing papers related to research areas and conducting content analysis of existing bibliometric studies in Islamic economics and finance. It specifically groups these studies around fundamental topics, summarizes findings from contemporary research and identifies emerging research gaps.

Family holiday decision-making (FHDM) is a process composed of several stages. This paper aims to describe two objectives: to identify at each stage the roles in couples, the main decision-maker in the case of family holidays; and to determine the most influential variables.

To identify the roles played by the partners, a frequency analysis has been conducted, which provides a graphic representation of the so-called feasibility triangles. The technique selected to identify the variables that explained the decision structure was binary logistic regression. In total, 375 useful dyads of questionnaires were received.

Holidays follow a joint decision-making process in the initiation phase and in the final decision, while the search for information is carried out equally by either partner. The woman’s work situation, the type of destination travelled to and the difference in education levels between them are the variables that best explain how couples decide on their family holidays.

A better understanding of the FHDM process will help tourism companies to improve their marketing campaigns.

The characteristics of the sample composed of 375 couples whose members completed a questionnaire separately have allowed not have to rely on one response per household, which adds reliability to the results. This sample is higher than the one of many reference publications on the subject. Furthermore, this paper revealed differences between male and female perception.