Search results

This study was designed to specifically explore confirmation and perceived usefulness associated with mobile food ordering apps (MFOAs) in consideration of their impacts upon attitudes, satisfaction and intention to continuously use.

The research utilized the convenience sampling to gather data from 250 respondents having prior experience with MFOAs during COVID-19 pandemic period in Bangladesh. The Structural Equation Modeling technique was applied to analyze the data using SmartPLS 3 software.

This study's results showed that customers' perceived confirmation and usefulness were significant in determining their dinning attitudes. Besides, customers' dining attitudes were positively related to e-satisfaction. Finally, the customers’ continuance intention to use MFOAs was significantly influenced by their e-satisfaction.

Restaurants managers should focus on online sales through MFOAs during the pandemic period since social distancing is a key strategy to manage COVID-19. Customers should be assured that the safety measures are undertaken while delivering the food.

This study incorporated the expectation-confirmation theory and technology acceptance model and tested it in the context of MFOAs.

The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation, anthropomorphism, effort expectancy, performance expectancy and emotions.

This study employed a quantitative methodology to collect data from Bangladeshi consumers who utilized AI-enabled technologies in the hospitality sector. A total of 343 data were collected using a purposive sampling method. The SmartPLS 4.0 software was used to determine the constructs' internal consistency, reliability and validity. This study also applied the partial least squares structural equation modeling (PLS-SEM) to test the research model and hypotheses.

The finding shows that consumer attitude toward AI is influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy and emotions. Specifically, hedonic motivation, social influence and anthropomorphism affect performance and effort expectations, affecting consumer emotion. Moreover, emotions ultimately influenced the perceptions of hotel customers' willingness to use AI devices.

This study provides a practical understanding of issues when adopting more stringent AI-enabled devices in the hospitality sector. Managers, practitioners and decision-makers will get helpful information discussed in this article.

This study investigates the perceptions of guests' attitudes toward the use of AI devices in hospitality services. This study emphasizes the cultural context of the hospitality industry in Bangladesh, but its findings may be reflected in other areas and regions.

This paper attempts to evaluate the impact of intellectual capital on bank performance in Bangladesh.

The authors analyze an unbalanced longitudinal data of 32 banks, which cover 318 observations of bank-year from 2010 to 2019. The study employs a dynamic panel model with the two-step system generalized methods of moments (SGMM).

The results show that bank performance is significantly positively affected by the intellectual capital (IC) in Bangladesh. In addition, the findings show that capital employed efficiency (CEE) is an essential determinant of bank performance rather than structural capital efficiency (SCE) and human capital efficiency (HCE) for the Bangladeshi banking sector.

This work is unique as no one has explored the impact of intellectual capital on Bangladesh's bank performance. The findings suggest that business owners, managers and policymakers who want to improve the efficiency of their organizations should spend continuously on IC and expand their investment into CEE, which includes both financial and physical resources, in order to obtain better bank performance.

Pabna is suffering from waterlogging problems from ancient times. The previous Drainage Master Plan was failed due to the lack of reflection of the general people of Pabna Municipality. As a result, this study focuses on identifying the causes of waterlogging in people's eyes. This paper will help the local authority and planners eradicate the waterlogging problem and build a planned and resilient community.

Both primary and secondary data were used for the study. Present drainage pattern, topology climatic elements were collected from the journals, websites and Municipal Ingratiated Development Plan (MIDP), Pabna-2008. The sample size was 246, and this respondent was surveyed. By the survey, the people's perception of waterlogging was collected. For that, five independent variables and one dependent variable were determined. These variables were determined by previous studies, reconnaissance survey of the study area. It used multiple linear regression and the correlation method; the causes of waterlogging were determined.

The study found solid waste disposal into the drainage, absence of operation and maintenance system, small discharge capacity with blocked in the current drains, nonappearance of combined drainage network of roadside drains and unplanned drainage system as the leading causes of waterlogging from the perception of the people. Also found that the absence of operation and maintenance system, solid waste disposal into the drainage and unplanned drainage system as the influencing causes on small discharge capacity with blocked in the current drains.

This study has focused on people's perceptions rather than secondary data. That is why this study will significantly impact eradicating the waterlogging problem from the Pabna Municipality and will carry out the core problems without any bias. This will lead to a sustainable, planned and resilient community.

Data envelopment analysis (DEA) calculates the efficiency of a business unit if all the inputs are creating outputs within a “black box.” Under traditional DEA, the detailed process of that business unit is ignored. However, a network DEA can explain the black box structure and provide efficiency results for sub-sections within any business process. This study aims to propose a network DEA model that explains a bank's total operation.

Earlier studies have focused only on bank efficiency ignoring this breakdown. This study departs from them by using a slack-based two-stage network DEA under a novel banking business perspective.

The results reveal that network DEA provides better benchmarking insights than the traditional DEA. As such, better benchmarking can guide both the banking industry managers and policy makers in Bangladesh.

The major contribution of this study includes dividing a bank's total operation efficiency into two sub-operations: “core operations – collecting deposits and giving loans” and “additional operations – fees, commissions and other services.”