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This paper aims to determine the preferable destinations of money laundered from Pakistan by using the Walker’s Gravity Model and to estimate the amount of money laundered through 156 countries. The research aims to facilitate policymakers and regulators to provide more efficient guidelines to counter the problem of money laundering.

This study uses a descriptive and quantitative approach. This study uses the Walker’s Gravity Model updated by Unger et al. (2006) to measure money laundering in Pakistan; Walker’s Gravity Model was first developed by John Walker in 1994.

The results indicate that Pakistani money launderers preferred countries having large financial sectors and political stability to hide their illegal money. In addition, the study estimates the amount of money laundered and shows that Pakistan has lost bulk of funds.

The major limitation is the non-availability of reliable data as the activity is hidden. Reliable data is either not available officially or scattered. Available data only reflect aspects that are reported. Non-availability of statistics for all years and countries resulted in the omission of some countries.

The study helps legislators and policymakers, including the Ministry of Finance, State Bank of Pakistan, Securities and Exchange Commission Pakistan, and other regulators, including law enforcement agencies and financial institutions, in formulating effective policies, regulations and internal control.

The study helps to identify the need of estimating the amount of money laundered to fight the problem effectively. Very few efforts have made to determine the size and the amount of money laundered, and this is the first study to determine the amount of money flowing out of Pakistan with the purpose of laundering.

This study aims to identify the factors that influence customer satisfaction in the banking sector from the perspective of employee characteristics. More specifically, this study identifies the impact of employee etiquettes, employee performance, technical selling skills and customer-oriented behavior on customer satisfaction in the banking industry. The study also seeks to investigate the mediating effect of employee etiquettes, employee performance and technical selling skills on the relationship between customer satisfaction and customer-oriented behavior.

The data were collected with the help of a Likert scale questionnaire from the active banking customers in Karachi, Pakistan, who visit bank branches once a month minimum. For 268 responses, partial least square-structural equation modeling (PLS-SEM) technique was employed for hypothesis testing.

The results showed a positive and significant relationship between customer-oriented behavior and employee etiquettes, technical selling skills and performance. The employee’s customer-oriented behavior, etiquettes, technical selling skills and performance were also found to be significantly related with customer satisfaction. Finally, the results revealed that technical selling skills, employee performance and employee etiquettes partially mediate the relationship between customer-oriented behavior and customer satisfaction.

It is recommended that banking employees should adopt customer-oriented behavior in order to achieve and maintain customer satisfaction. The bank managers should also work on improving the etiquettes and performance of the employees and provide them detailed technical knowledge of the services and products offered by the bank.

Arguably, it is one of the first studies to examine the mediating effects of employees' technical selling skills and employees' performance on the relationship between customer orientation and customer satisfaction, specifically in the banking industry.

By extending the service robot acceptance model (sRAM), this study aims to explore and enhance the acceptance of chatbots. The study considered functional, relational, social, user and gratification elements in determining the acceptance of chatbots.

By using the purposive sampling technique, data of 321 service customers, gathered from millennials through a questionnaire and subsequent PLS-SEM modeling, was applied for hypotheses testing.

Findings revealed that the functional elements, perceived usefulness and perceived ease of use affect acceptance of chatbots. However, in social elements, only perceived social interactivity affects the acceptance of chatbots. Moreover, both user and gratification elements (hedonic motivation and symbolic motivation) significantly influence the acceptance of chatbots. Lastly, trust is the only contributing factor for the acceptance of chatbots in the relational elements.

The study extends the literature related to chatbots and offers several guidelines to the service industry to effectively employ chatbots.

This is one of the first studies that used newly developed sRAM in determining chatbot acceptance. Moreover, the study extended the sRAM by adding user and gratification elements and privacy concerns as originally sRAM model was limited to functional, relational and social elements.

This research intends to determine the role of terrorism in defying foreign direct investment (FDI) in top terror effected economies.

Panel data on FDI and terrorism from top terror effected economies spanning from 1987 to 2018 were used and the relationship for whole sample was investigated. Later the sample period was divided into pre (1987–2001) and post 9/11 (2002–2018) subsample and same relationship was tested to investigate the normalization of terror effect on FDI. The method of Pooled Mean Group (PMG) was used to test the hypothesis.

The results showed a negative but statistically insignificant impact of terrorism on the FDI inflows in the long run. Later the sample period was divided into pre (1987–2001) and post 9/11 (2002–2018) subsample. The empirical estimates for pre and post 9/11 periods indicated a negative and statistically significant relationship between terrorism and FDI for pre 9/11 period, and a negative but statistically insignificant relationship between the two variables for post 9/11 period.

The findings suggest several important policy implications for the terror affected countries and are further discussed in the study.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

Despite the reasonable surge of remittances and imports in Pakistan, very less attention has been given to this area. To bridge the gap, this study aims to explore the relationship of worker’s remittances and imports of Pakistan at both aggregate and disaggregate levels. Also, this research focuses on investigating whether remitted income substitute or complement imports of the country.

To achieve these goals, the authors use annual time-series data from 1974–2016.

Empirical findings obtained from the autoregressive distributed lag model method suggest that remittances substitute imports in Pakistan. It is also found that remittances not only substitute aggregate imports but also act as a substitute at different disaggregated levels. Further, it is documented that higher economic growth increases imports, whereas the real exchange rate for imports is inversely related to imports at both levels.

These empirical findings also draw some substantive policy implications for the state owners and policy advisers.

The purpose of this paper is to assess the impact of trade and financial sector openness and their simultaneous openness on financial development of South Asia.

To serve the purpose, a panel data set of four South Asian economies, namely, India, Pakistan, Sri Lanka and Bangladesh, was constituted for the period spanning from 1996 to 2015. Along with the conventional panel unit root test and co-integration test, pooled mean group estimations were used to formulate the empirical findings.

The findings suggested a significant negative impact of financial openness and significant positive impact of trade openness on the financial development of South Asia. The empirical evidence did not support simultaneous openness of trade and financial sector for the studied region.

The study contributes to the existing literature by analyzing the effect of trade and financial openness on financial development of South Asia. The study provides substantial evidence to the stakeholders for formulating policies that can boost financial development of the region.

This study aims to investigate the effect of corruption on military expenditures in three income level countries. An annual data series of 97 countries covering high-income, middle-income, and low-income regions from 1997 to 2015 is used.

The cross-sectional dependency and integration property of the data series was checked before applying the generalized method of moments approach to test the model.

The results of the system generalized method of moments approach suggest that corruption increases the military budget of high-income countries, whereas corruption reduces the military budget of the middle- and low-income countries.

This paper offers some substantial implications for the policymakers of each income group to curb corruption and improve economic development.

The purpose of this paper is to explore how social need, social influence and convenience affect dependence on smartphones and purchasing behavior among university students in Pakistan’s emerging economy.

Survey methods and non-probability purposive sampling were used to collect data from 337 respondents, and structural equation modeling was used to test the hypothesis.

Overall the results provided evidence that social need, social influence and convenience significantly affect students’ dependence on their smartphones. A significant relationship also existed between students’ dependence on smartphones and their purchasing behavior.

The availability of 3G/4G mobile networks and the growth in smartphones’ computing power have meant that this form of mobile technology is in great demand. This study provides an exclusive viewpoint concerning students’ dependence on smartphones and the effect of this on their purchasing behavior, which is a subject that has not been covered previously in the Pakistani context.

The purpose of this paper is to investigate the market reaction to the decision made by the management of the Karachi Stock Exchange (KSE) to impose a price floor that resulted in trading curbs in 2008. The paper analyzes if regulatory intervention helped in restoring investor confidence.

The paper examines the effect of enforcement of a price floor and trading curbs by splitting the time period studied into two periods: pre-floor and post-floor period. The parametric t-statistics and non-parametric Mann-Whitney test are used to compare the abnormal returns (ARs), abnormal trading volume, bid-ask spread, Amihud illiquidity ratio, and price volatility between the two periods. Event study was conducted to observe the behavior of market returns surrounding market-wide price floor. Finally, multivariate regression analysis was also applied by controlling for factors that might influence valuation, liquidity, and volatility. The standard errors have been corrected for cross-sectional clustering due to market-wide restrictions.

The study found an adverse impact of price freeze and trading curb in the KSE, following the relaxation of floor (resumption of active trading). First, the price of securities (or ARs) significantly declined following the relaxation of the price freeze. Second, the market liquidity deteriorated following the relaxation of the price floor. Third, the price volatility increased in the post-floor period. It seems that the decision made by the KSE’s board to implement lower cap on prices for an extended period was ineffective.

Market intervention by regulators to bring calm in the financial markets have negative consequences across the globe. The results presented in this paper suggest that implementing price floor brought inefficiency in the market and prevented firms from raising capital to finance their future investments. The author believe this study will add to the knowledge base of regulatory intervention and its impact on the performance of financial markets.

There is no empirical evidence on the impact of price limits on volatility in emerging markets. The author selected Pakistan as a case study, where we particularly focus upon impact of the enforcement of a price floor around the peak of Global Financial Crisis (or market intervention) in Pakistan. This study also documents the effect of trading curb on liquidity and volatility in an emerging market, given that a majority of research on trading halt/price limits is based on developed markets.