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The purpose of this paper is to explore factors and their impacts influencing online grocery shopping intentions among customers in the post COVID-19 situation. Moreover, the study aims at evaluating the mediating roles of shopping habits during COVID-19 between perceived usefulness, perceived ease of use and post COVID-19 online grocery shopping intentions.

Based on a review of the literature and collection of 401 useable valid responses, the study was conducted through structured questionnaires applying personal interview technique. The subsequent analysis was conducted through partial least squares structural equation modeling (PLS-SEM) using Smart PLS 3.3.3.

The study findings revealed that perceived usefulness, perceived ease of use and shopping habits during COVID-19 have a significant influence on post COVID-19 online grocery shopping intentions. Also, the study has uncovered that perceived usefulness and perceived ease of use significantly influence shopping habits during COVID-19 among customers. Furthermore, the current study has revealed that hopping habit during COVID-19 significantly mediates the relationship between perceived usefulness, perceived ease of use and post COVID-19 online grocery shopping intentions.

The study findings have provided practical suggestions of developing and improving technological platforms to attract new customers for online grocery shopping. Further, the study suggests that online grocery retailers should apply adjusted pricing strategies using coupons and discount offers.

This paper investigates factors and its impacts on online grocery shopping intentions in post COVID-19 context. Therefore, the study uncovers the factors that add value to understanding customers' post COVID-19 online grocery shopping intentions by integrating perceived usefulness, perceived ease of use and shopping habits during COVID-19.

In this study, the authors investigate the effect of big data analytics capability (BDAC) on supply chain performance (SCP) to assess the mediating effect of supply chain innovation (SCI) and the moderating effect of a data-driven culture (DDC).

The authors collected the primary data through an online questionnaire survey from the manufacturing sector operating in Jordan. The authors used 420 samples for the final data analysis, which the authors performed via partial least squares structural equation modelling using SmartPLS 3.3.9 software.

The results indicate that BDAC has a strong relationship with SCI and SCP. SCI shows a positive relationship with SCP as well as a mediating effect on SCI. The authors confirmed that DDC moderated the relationship between SCI and SCP.

The authors developed a conceptual and empirical model to investigate the relationship between BDAC, SCI, DDC and SCP. The authors contributed new theoretical and managerial insights that add value to the supply chain management literature through testing the moderated-mediated model of these constructs in Jordan’s manufacturing sector.

Visits to locations connected to historical atrocities, tragedy, suffering, or presumably dreadful events are referred to as “dark tourism”. While Bangladesh may not be widely known for dark tourism, several unexplored avenues may be of interest to those who engage in this type of unique and unconventional tourism experience. In addition to creating job opportunities and income generation in Bangladesh, it can achieve educational objectives, communicate with a broad audience, raise awareness of events of the past, and quench people's thirst for information, which can help them to comprehend a society. Though Bangladesh has several somber locations connected to tragic events including World War II, liberation war sites, mass killing sites, shipbreaking yards, Rohingya refugee camps, riots, and the mother language movement, traditional tourism predominates there. If managed responsibly, these varied resources, somber locations, and histories, some of which date back to 1800, could make Bangladesh a dark tourism destination. Although dark tourism in Bangladesh has the potential to contribute to historical awareness, preservation, educational opportunities, and socioeconomic development, it is yet unexplored due to a lack of knowledge, experience, policy, effective marketing, and some controversies. By approaching responsibly, Bangladesh can leverage its history to attract visitors' interests in exploring the darker aspects of the country's past. Hence, this chapter is designed to explore the status and potential significance, prospects, and challenges of dark tourism in Bangladesh. The findings will help policymakers, tourists, and other stakeholders to explore and enjoy enormous benefits from Bangladesh's untapped dark tourism opportunities.

This study aims to analyse the variations of thermal comfort inside a building space by using different curtains.

Phase change materials (PCMs) such as wax, sand and mixture of sand and wax were used with cotton curtain to compare the results of PCM curtains with the performance of normal cotton curtain against constant heat exposure. Heat exposure was provided with halogen to simulate the solar radiation. Further simulation was performed on ANSYS and experimental results were compared with the simulation results. In addition to this, the results were analysed for optimized performance by calculation root mean square error.

It was found that PCM used curtains that have better performance than normal curtain. Furthermore, sand curtain was proved as the best curtain and mixture of sand and wax curtain could replace the sand curtain where there is limitation of weight; also, there was less error between experimental and simulation was reported for sand curtain as compare to other curtains.

Layers of different PCMs were used before cotton curtain and in modelling assumptions such as one-dimensional heat transfer, uniform thermal conductivity.

To the best of the authors’ knowledge, there is no such study that was performed earlier.

In the last 10 years, India has amended its laws dealing with sexual offences against women with the changes ranging from increasing terms of imprisonment for the offence of rape to state-funded compensation schemes for women and child victims. In this regard, challenges persist for the agencies of the criminal justice system in India especially the courts to realise the vision of restorative justice as these forums have to navigate the relevant statutory provisions and binding precedents. This chapter seeks to analyse the challenges faced by courts in proper reintegration of victims and offenders of sexual offences, the institutional responses of the courts and suggests reforms to the criminal justice system in India in consonance with the principles of restorative justice acknowledged in the restorative justice movement in the international discourse.

This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China.

The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables.

The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market.

To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.

Fused filament fabrication (FFF) is a type of additive manufacturing (AM) based on materials extrusion. It is the most widely practiced AM route, especially used for polymer-based rapid prototyping and customized product fabrication in relation to aerospace, automotive, architecture, consumer goods and medical applications. During FFF, part quality (surface finish, dimensional accuracy and static mechanical strength) is greatly influenced by several process parameters. The paper aims to study FFF parametric influence on aforesaid part quality aspects. In addition, dynamic analysis of the FFF part is carried out.

Interpretive structural modelling is attempted to articulate interrelationships that exist amongst FFF parameters. Next, a few specimens are fabricated using acrylonitrile butadiene styrene plastic at varied build orientation and build style. Effects of build orientation and build style on part’s ultimate tensile strength, flexure strength along with width build time are studied. Prototype beams (of different thickness) are fabricated by varying build style. Instrumental impact hammer Modal analysis is performed on the cantilever beams (cantilever support) to obtain the natural frequencies (first mode). Parametric influence on natural frequencies is also studied.

Static mechanical properties (tensile and flexure strength) are greatly influenced by build style and build orientation. Natural frequency (NF) of prototype beams is highly influenced by the build style and beam thickness.

FFF built parts when subjected to application, may have to face a variety of external dynamic loads. If frequency of induced vibration (due to external force) matches with NF of the component part, resonance is incurred. To avoid occurrence of resonance, operational frequency (frequency of externally applied forces) must be lower/ higher than the NF. Because NF depends on mass and stiffness, and boundary conditions, FFF parts produced through varying build style may definitely correspond to varied NF. This aspect is explained in this work.

A major concern for policymakers and researchers is to ascertain the movement of price levels and employment rates. Predicting the trends of these variables will assist the government in making policies to stabilize the economy. The objective of this chapter is to forecast the unemployment rate and Consumer Price Index (CPI) for the period 2022 to 2031 for the Indian economy. For this purpose, the authors analyse the prediction capability of the univariate auto-regressive integrated moving average (ARIMA) model and the vector autoregressive (VAR) model. The dataset for India's annual CPI and unemployment rate pertains to a 30-year time period from 1991 to 2021. The result shows that the inflation forecasts derived from the ARIMA model are more precise than that of the VAR model. Whereas, unemployment rate forecasts obtained from the VAR model are more reliable than that of the ARIMA model. It is also observed that predicted unemployment rates hover around 5.7% in the forthcoming years, while the forecasted inflation rate witnesses an increasing trend.