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India has a distinct family hierarchy and a vertical collectivistic culture. Indian traditional cultural norms discourage young adults from having romantic or sexual relationships before marriage. Romantic liaisons and marriages are fiercely opposed outside the caste and social network. Despite this cultural practice, research in the last decade demonstrated that more young adults in India engage in premarital romantic relationships and prefer a marriage of choice. However, they strongly wish their parents to approve of their partner and arrange their marriage. This increasing trend of love-cum-arranged marriages could be considered how Indian culture adapts to the demands of modernization strongly impelled by globalization. This chapter discusses the dynamics of change in the romantic and marital agency among young adults in India. First, the authors provide a brief historical introduction to the Indian marital system. Then, the authors discuss the changing cultural dimensions that promote marital choice and independence in partner selection (e.g., filial piety). Further, the authors provide an overview of the trends in premarital romantic relationships in India. In addition, the authors discuss the distress and conflict in Indian families due to the increasing premarital romantic and sexual relationships among Indian youth, as evidenced by eloped marriages, forced marriages, and honor killings.

The efficiency of each of an organization’s individual workers determines its effectiveness. The study aims to explore the relationship between human resource management (HRM) practices and organizational effectiveness with employee performance as a mediating variable.

Data were collected from 800 police officers in the Greater Accra and Tema regions. The data were supported by the hypothesized relationship. Construct reliability and validity was established through confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

The results show that career planning and employee performance were significantly related. Self-managed teams and employee performance were shown to be nonsignificantly related. Similarly, performance management and employee performance were shown to be nonsignificantly related. Employee performance significantly influenced organizational effectiveness. The results further indicate that employee performance mediates the relationship between HRM practices and organizational effectiveness.

The generalizability of the findings will be constrained due to the research’s police service focus and cross-sectional data.

The study’s findings will serve as valuable pointers for the police administration in the adoption, design and implementation of well-articulated and proactive HRM practices to improve the abilities, skills, knowledge and motivation of officer’s to inordinately enhance the effectiveness of the service.

By evidencing empirically that employee performance mediates the relationship between HRM practice and organizational effectiveness, the study extends the literature.

Given its ability to improve user interaction and labor productivity, ease human workloads and cut maintenance costs, public sectors are using AI-based robotic technology (AI-RT) at an accelerated rate. There is, however, little knowledge about the variables affecting citizens' participation when services backed by AI-RT are offered. In order to better understand the elements that influence AI-RT citizens' involvement and the moderating function of trusts in governmental organizations, this article draws on ideas from the Consumer Value Theory.

Out of 500 survey forms that were distributed to Indonesian people who had experience in using AI-RT devices in public service hall (e.g. airport’s Auto Gate), 367 returned the completed feedbacks. Data analysis used a step-by-step hierarchical moderated regression examination using SPSS 24 version.

Citizens’ involvement is positively correlated with esthetics and customization and adversely correlated with period expended using the AI-RT. Additionally, the findings imply that citizens who have greater levels of faith in governmental institutions are more likely to benefit favorably from the customization and esthetics of AI-RT.

The AI-RT must be capable of customizing the distribution of the appropriate materials to the appropriate individual at the appropriate moment, and public managers should guarantee that it is esthetically pleasing. Additionally, they ought to place a high priority on winning the trust of the populace in order to increase citizens’ involvement.

This paper was among the initial efforts that discover the determinants of citizens’ involvement in the AI-RT and the moderating effect of trusts in governmental organizations on the links between predictors and predicted variable, especially in an emerging country such as Indonesia.

The purpose of this study is to explore whether five factors drawn from the unified theory of acceptance and use of technology (UTAUT) and UTAUT2 significantly influence customers' intention to use hotel in-room voice assistants (VAs). It further examined culture as a moderator of the relationships between the five factors and customers' intention to use.

The authors collected data from US and Singapore to examine cultural differences in customer acceptance of in-room VAs. All hypotheses were tested via structural equation modeling and multi-group analysis.

The results showed that performance expectancy, social influence and hedonic motivation significantly affected customers' intentions to use in-room VAs, while effort expectancy and facilitating conditions did not. The results confirmed that culture did not play a substantial role in moderating the relationships between these factors and intentions to use.

This study established that the instrument and structural paths in the research model were equivalent across two samples from different countries. The findings may not generalize to other countries as the data arises from customers in the US and Singapore.

The findings provide important implications for hotel operators and vendors seeking to enhance customer acceptance of in-room voice technology.

This study addresses the gaps of extant research by developing and testing a research model to better understand the influential factors of in-room VA adoption within the hotel domain.

The stress concentration factor (SCF) is commonly utilized to assess the fatigue life of a tubular T-joint in offshore structures. Parametric equations derived from experimental testing and finite element analysis (FEA) are utilized to estimate the SCF efficiently. The mathematical equations provide the SCF at the crown and saddle of tubular T-joints for various load scenarios. Offshore structures are subjected to a wide range of stresses from all directions, and the hotspot stress might occur anywhere along the brace. It is critical to incorporate stress distribution since using the single-point SCF equation can lead to inaccurate hotspot stress and fatigue life estimates. As far as we know, there are no equations available to determine the SCF around the axis of the brace.

A mathematical model based on the training weights and biases of artificial neural networks (ANNs) is presented to predict SCF. 625 FEA simulations were conducted to obtain SCF data to train the ANN.

Using real data, this ANN was used to create mathematical formulas for determining the SCF. The equations can calculate the SCF with a percentage error of less than 6%.

Engineers in practice can use the equations to compute the hotspot stress precisely and rapidly, thereby minimizing risks linked to fatigue failure of offshore structures and assuring their longevity and reliability. Our research contributes to enhancing the safety and reliability of offshore structures by facilitating more precise assessments of stress distribution.

Precisely determining the SCF for the fatigue life of offshore structures reduces the potential hazards associated with fatigue failure, thereby guaranteeing their longevity and reliability. The present study offers a systematic approach for using FEA and ANN to calculate the stress distribution along the weld toe and the SCF in T-joints since ANNs are better at approximating complex phenomena than standard data fitting techniques. Once a database of parametric equations is available, it can be used to rapidly approximate the SCF, unlike experimentation, which is costly and FEA, which is time consuming.

Stress concentration factors (SCFs) are commonly used to assess the fatigue life of tubular T-joints in offshore structures. SCFs are usually estimated from parametric equations derived from experimental data and finite element analysis (FEA). However, these equations provide the SCF at the crown and saddle points of tubular T-joints only, while peak SCF might occur anywhere along the brace. Using the SCF at the crown and saddle can lead to inaccurate hotspot stress and fatigue life estimates. There are no equations available for calculating the SCF along the T-joint's brace axis under in-plane and out-of-plane bending moments.

In this work, parametric equations for estimating SCFs are developed based on the training weights and biases of an artificial neural network (ANN), as ANNs are capable of representing complex correlations. 1,250 finite element simulations for tubular T-joints with varying dimensions subjected to in-plane bending moments and out-of-plane bending moments were conducted to obtain the corresponding SCFs for training the ANN.

The ANN was subsequently used to obtain equations to calculate the SCFs based on dimensionless parameters (α, β, γ and τ). The equations can predict the SCF around the T-joint's brace axis with an error of less than 8% and a root mean square error (RMSE) of less than 0.05.

Accurate SCF estimation for determining the fatigue life of offshore structures reduces the risks associated with fatigue failure while ensuring their durability and dependability. The current study provides a systematic approach for calculating the stress distribution at the weld toe and SCF in T-joints using FEA and ANN, as ANNs are better at approximating complex phenomena than typical data fitting techniques. Having a database of parametric equations enables fast estimation of SCFs, as opposed to costly testing and time-consuming FEA.

This paper aims to examine whether the instructional message used to introduce game-based learning (GBL), prior knowledge, flow and prior gaming experience have an impact on secondary students’ learning outcomes, perceived game utility and motivation to use the game.

Fifty-four 9th grades students enrolled in this quasi-experimental study. Both groups played the same game. The experimental group was told that they would be playing a game, whereas the control group was told that they would be doing an exercise. The game was designed to promote knowledge recall about familiar mathematical concepts. Prior knowledge was assessed. An immediate and a two-days delayed post-evaluated learning outcomes. Flow, prior gaming experience, perceived game utility and motivation to use the game were assessed with questionnaires after playing.

Introducing the GBL activity as a game increased immediate learning outcomes for low knowledgeable students, but these benefits did not extend to longer term. Indeed, when the GBL activity was presented as an exercise, low higher knowledgeable students obtained poorer longer-term learning outcomes than more knowledgeable ones, whereas no difference appeared when the GBL was introduced as an exercise. Prior gaming experience and the type of instructional message used to introduce a GBL activity positively influenced perceived game utility and motivation to use the game.

This study is the first to highlight that the way a GBL activity is framed affects differently low and higher knowledgeable students’ learning outcomes and influences perceived game utility and motivation to use the game.

The purpose of this paper is to examine the association between consumers’ emotions towards emerging e-banking technology, perceived risk and subsequent intention to adopt emerging e-banking technology.

An online questionnaire was used to collect data, which were analysed in a quantitative study. The final sample of 224 educated young consumers, familiar with emerging e-banking technology, allowed testing of the research hypotheses by applying confirmatory factor analysis and structural equation modelling (SEM).

The empirical results indicate that deterrence emotions and hedonic motivation are associated with consumers’ perceived risk and, subsequently, their intention to adopt emerging e-banking technology. Additionally, analysing the moderating role of hedonic motivation in the association between consumers’ deterrence emotions towards emerging e-banking technology and their perceived risk highlights the significant association of deterrence emotions with perceived risk, regardless of the presence of hedonic motivation.

This study demonstrates the association between consumers’ emotions, perceived risk and subsequent intention to adopt emerging e-banking technology whilst underscoring the importance of distinguishing between different types of emotions and their corresponding appraisals.

The current study aims to examine the joint impact of consumers' need for status (NFS), celebrity's star power and consumer-celebrity image match on consumers' attitudes toward the celebrity endorsement.

A factorial design was employed to test the research model. Consumer-celebrity image match was manipulated, and consumers' NFS and celebrity's star power was captured using existing measurement scales. A total of 365 responses were collected via Qualtrics. Hayes's (2013) PROCESS procedure was used to analyze the data and test hypotheses.

Results indicate that consumers with high (vs low) NFS have more favorable attitudes toward the endorsed brand. More importantly, consumers high in NFS, in an endorsement where celebrity-consumer image matches, have more favorable attitudes toward the brand endorsed by a celebrity with more (vs less) star power. In contrast, in an endorsement where celebrity-consumer image mismatches, they react the same regardless of the endorser's star power.

This study offers suggestions to hospitality marketing professionals in strategically using celebrity endorsers in their marketing campaigns and strategies that allows firms to further formulate positive and enduring brand images while encouraging favorable consumer behaviors.

While most hospitality studies have focused on the traits of celebrity endorsers, little attention has been paid to the impact of consumers' characteristics on celebrity endorsement. This study advances the growing literature on hospitality celebrity endorsement by providing empirical evidence to delineate the relationship among celebrities, endorsed brands and consumers.