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This paper aims to establish and empirically investigate a research model examining the effect of four dimensions of the technology readiness index – optimism, innovativeness, discomfort and insecurity – on customer engagement that further influences purchase intention in the context of online shopping through artificial intelligence voice assistants (AI VAs).

Data were collected in India from 429 customers in a self-administered online survey. Data analysis uses the structural equation modelling technique.

Technology readiness dimensions, e.g. optimism, innovativeness, discomfort and insecurity, are critical factors driving customer engagement. Customer engagement further results in purchase intention in online shopping through AI VAs.

This study adds to the literature by understanding how customers’ technology readiness levels drive engagement and purchase intention. However, this study includes customer engagement as a unidimensional construct. Further research can consist of customer engagement as a multidimensional construct.

The findings offer guidelines for e-retailers to enhance customer engagement that matches their personality traits, thereby strengthening their purchase intention through AI VAs.

The research contributes to the literature by empirically investigating a research model, revealing optimism, innovativeness, discomfort and insecurity as crucial parameters for customer engagement and purchase intention.

The aim of this paper is to explore and analyse the challenges in effective implementation of blockchain by human resource management (HRM) functions. This paper also aims to assess the interplay between the barriers in causing the challenges during blockchain execution.

Ten barriers are discovered from the past studies. Based on the expert views on the identified barriers interpretive structural modelling (ISM) is administered to understand the interplay of these 10 challenges resulting in ineffective or non-implementation of HR blockchain.

The application of ISM has helped in categorizing the variables into strategic, operational and performance outcomes. Results of ISM indicate key barriers like lack of expertise, data privacy, technical infeasibility, complexity in implantation and lack of used cases.

The research is limited to 10 barriers. There can be other barriers that can also be studied. Second, the research is proposing a conceptual model that needs further validation.

This paper has significant implications for the theoretical and practical body of knowledge. So far, most studies are exploring and describing HRM from a digital perspective. Most HR studies are on artificial intelligence, the Internet of Things and smart HRM. Previous studies on blockchain for HRM are mostly describing the advantages of going for it.

Based on the findings, it can also be suggested that policy formulators must advance the technical regulatory framework. Blockchain technology can be effectively implemented only if the top management is committed to it because they can only frame the rules and right control framework, affirm the governance process and strategize improvement.

The study offers insights into the organization's decision makers for effectively implementing blockchain into their HR systems. Some specific recommendations based on the results are also made. The paper is an innovative attempt to analyse the barriers to HR blockchain.

This study aims to examine the impacts of the forced shift to online/hybrid learning on international students’ perceptions and behaviour. It aims to understand the direction of future university marketing changes to address this vital and urgent concern.

This study deployed an explorative qualitative design and data collected through interviews (n, 20) with prospective international students.

The study identified four main themes: mode of class operation, that is, the balance between online/offline/hybrid modes of course delivery; enhanced level of flexibility in terms of both visa regulations and financial aid; strategic use of social media and virtual tools to connect with and impress the international student community; and evidence of digitalization and experiential learning.

This study has many theoretical and managerial implications. As international students perceive COVID-19 as an under-researched theme in the higher education market, the study’s outcome helps understand the grey areas of expectation versus reality in higher education marketing.

This research offers a new perspective from the demand side on higher education marketing strategies amid COVID-19.

The purpose of this study is to assess the effect of perceived role clarity on innovative work behavior (IWB) through the mediation of intrinsic motivation and job involvement.

The data were gathered from 613 employees belonging to 196 organizations operating in India. Data were analyzed using statistical tools such as exploratory and confirmatory factor analysis, multiple regressions and bootstrapping via PROCESS.

Initially, the results of correlation and multiple regression analyses indicated that the perceived role clarity has positive relation with intrinsic motivation, job involvement and IWB. Further, bootstrap analysis revealed that intrinsic motivation and job involvement individually and serially mediate the effect of perceived role clarity on IWB.

The study highlights the importance of the perceived role clarity in developing positive work attitudes and innovative behavior among employees. Self-reported survey and cross-sectional design are the limitations of the current study.

The study suggests that organizations should strive constantly to enhance perceptions of role clarity among employees so that they remain motivated and involved in their jobs and exhibit innovative behavior at work.

To the best of the authors’ knowledge, this is the only study to test the impact of perceived role clarity on IWB with the serial mediation of intrinsic motivation and job involvement.

Scholarly works on sex work and sex workers are mostly confined to discourses on human trafficking and the incidence of HIV/STIs among sex workers. Although crucial, this restricted focus has neglected the reality that sex workers are a diverse community, and while their challenges may appear to be linked at first glance, they differ greatly. While extensive research has been conducted on sex workers working in more open settings like brothels, hotels, and streets, there is a scarcity of research on sex workers working in more private spaces, such as, for instance, their own homes. Within the hierarchy of sex workers, home-based sex workers (HBSWs) among the indoor sex workers dominate commercial sex transactions. However, they are often overlooked due to their covert nature and invisible landscape. This chapter addresses the knowledge gap by examining the work lives and conditions of home-based female sex workers (FHBSWs) in Punjab. The study analyzes the complex lives of sex workers who use their home as both a family unit and a workplace. A detailed analysis of the risks and vulnerabilities they face in their daily lives and their coping strategies is also examined in this chapter. The study points out that although working from home may have positive outcomes for sex workers, the integration of sex work into the home environment exposes them to several challenges. Hence, the study emphasizes the need for tailoring interventions for sex workers who operate in different physical environments so that their unique needs and challenges are well addressed.

Privacy and security of personal data is the prime concern in any communication. Security algorithms play a crucial role in privacy preserving and are used extensively. Therefore, these algorithms need to be effective as well as energy-efficient. Advanced Encryption Standards (AES) is one of the efficient security algorithms. The principal purpose of this research is to design Energy efficient implementation of AES, as it is one of the important aspects for a step toward green computing.

This paper presents a low voltage complementary metal oxide semiconductor (LVCMOS) based energy efficient architecture for AES encryption algorithm on Field Programmable Gate Array (FPGA) platform. The experiments are performed for five different FPGAs at different input/output standards of LVCMOS. Experiments are performed separately at two frequencies (default and 1.6 GHz).

The comparative study of total on-chip power consumption for different frequency suggested that LVCMOS12 performed best for all the FPGAs. Also, Kintex-7 Low Voltage was found to be the best performing FPGA. At 1.6 GHz frequency, the authors observed 55% less on-chip power consumption when switched from Artix-7 with LVCMOS33 (maximum power consuming combination) to Kintex-7 Low Voltage with LVCMOS12. Mathematical models are developed for the proposed design.

The green implementation of AES algorithm based on LVCMOS standards has not been explored yet by researchers. The energy efficient implementation of AES will certainly be beneficial for society as it will consume less power and dissipate lesser heat to environment.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.