Search results

Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.

Using features of social media, peer-to-peer (P2P) mobile payment enables users to foster social interaction every time transactions are made. Given the increasing popularity of social features in P2P mobile payment applications, it is worth understanding how these components contribute to users’ switching behavior between conventional mobile payment and P2P mobile payment services. By treating sociability of P2P mobile payment as a pull factor, this study aims to extend the push–pull–mooring framework in the context of P2P mobile payment.

A questionnaire survey was conducted to obtain data. Respondents from the USA were exclusively selected due to the emerging number of P2P mobile payment users and the volume of transactions in this country. Based on a sample of 232 Amazon Mechanical Turk mobile payment users, the authors tested the hypotheses using the partial least squares structural equation model technique with SmartPLS software version 3.

The finding reveals that sociability is triggered by social presence, social benefit and social support within the P2P mobile payment platform. Moreover, dissatisfaction with perceived enjoyment of conventional mobile payment (push factor), customer innovativeness (mooring factor) and sociability of P2P mobile payment (pull factor) jointly influence users’ intention to switch to P2P mobile payment services, and subsequently drive their migration behavior.

Unlike past research that mainly focuses on utilitarian-related factors, to the best of the authors’ knowledge, this study is among the first to thoroughly examine the sociability features of P2P mobile payment service as a form of a social-centric system.

Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper aims to investigate how recommendations from different social ties influence consumers’ purchase intentions through both behavior and brain activity.

Utilizing behavioral (N = 70) and electroencephalogram (EEG) (N = 49) experiments, this study explored participants’ behavior and brain responses after being recommended by different social ties. The data were analyzed using statistical inference and event-related potential (ERP) analysis.

Behavioral results show that social tie strength positively impacts purchase intention, which can be fitted by a logarithmic model. Moreover, recommender-to-customer similarity and product affect mediate the effect of tie strength on purchase intention serially. EEG findings show that recommendations from weak tie strength elicit larger N100, N200 and P300 amplitudes than those from strong tie strength. These results imply that weak tie strength may motivate individuals to recruit more mental resources in social recommendation, including unconscious processing of consumer attention and conscious processing of cognitive conflict and negative emotion.

This study considers the effects of continuous social ties on purchase intention and models them mathematically, exploring the intrinsic mechanisms by which strong and weak ties influence purchase intentions through recommender-to-customer similarity and product affect, contributing to the applications of the stimulus-organism-response (SOR) model in the field of social recommendation. Furthermore, our study adopting EEG techniques bridges the gap of relying solely on self-report by providing an avenue to obtain relatively objective findings about the consumers’ early-occurred (unconscious) attentional responses and late-occurred (conscious) cognitive and emotional responses in purchase decisions.

Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.

We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.

The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.

Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.

Based on uncertainty reduction theory, this study explores how perceived information transparency mitigates users' perceived uncertainty, which in turn influences their actual purchase behavior. In addition, the moderating effects of cultural tightness on the relationship between perceived information transparency and perceived uncertainty are also considered.

Users with the shopping experience on Xiaohongshu are invited to participate in the survey. Finally, 355 valid longitudinal data are collected.

The results indicate that the three dimensions of perceived information transparency (i.e. perceived product transparency, perceived seller transparency and perceived transaction transparency) can reduce users' perceived uncertainty significantly. Besides, the negative impacts of perceived product and seller transparency on users' perceived uncertainty are stronger when cultural tightness is higher. However, cultural tightness does not moderate the relationship between perceived transaction transparency and users' perceived uncertainty.

First, the authors' research extends the uncertainty reduction theory to the context of social commerce. Second, the authors' research explores the boundary condition under which perceived information transparency varies by identifying cultural tightness as the moderator of the relationship between perceived information transparency and uncertainty. Third, the authors' research enriches the understanding of the cultural tightness of China.

Despite being one of the most used dependent variables in expatriate management research, no clear-cut understanding exists of what expatriate success means. Thus, this study aims to propose an integrative definition of expatriate success by providing an overview of expatriate success's dimensions, antecedents, and their interplay.

A systematic literature review (SLR) was conducted to achieve the purpose. A total of 249 empirical studies (quantitative 111, qualitative 50, mixed-methods 17), literature reviews (67) and meta-analyses (4) on expatriate success were reviewed from Web of Science and Scopus databases published from 1990 until December 2021. The study selection criteria followed the PRISMA flowchart steps, and then descriptive and network analyses were performed to identify expatriates' success dimensions, antecedents and their interplay.

The findings show the interplay among antecedents and dimensions of expatriate success across three levels (individual, interpersonal and organisational) to clarify the concept of expatriate success. Also, the study offers a comprehensive definition of expatriate success based on the dimensions identified.

The suggested definition of expatriate success elucidates the “atheoretical”, multidimensional and socially constructed nature of the construct and hence, calls for more “theoretical”, multidimensional and subjective considerations of the term to ground human resource management practices addressed to attain expatriates' success.

This paper provides an integrative definition of expatriate success, giving greater insight into the construct, in addition to critically reflecting on it.

This paper aims to explore students’ intention to use and actual use of the artificial intelligence (AI)-based chatbot such as ChatGPT or Google Bird in the field of higher education in an emerging economic context like Bangladesh.

The present study uses convenience sampling techniques to collect data from the respondents. It applies partial least squares structural equation modeling (PLS-SEM) for analyzing a total of 413 responses to examine the study’s measurement and structural model.

The results explore that perceived ease of use (PEOU) negatively affects intention to adopt AI-powered chatbots (IA), whereas university students’ perceived usefulness (PU) influences their IA positively but insignificantly. Furthermore, time-saving feature (TSF), academic self-efficacy (ASE) and electronic word-of-mouth (EWOM) have a positive and direct impact on their IA. The finding also reveals that students' IA positively and significantly affects their actual use of AI-based chatbot (AU). Precisely, out of the five constructs, the TSF has the strongest impact on students’ intentions to use chatbots.

Students who are not aware of the chatbot usage benefits might ignore these AI-powered language models. On the other hand, developers of chatbots may not be conscious of the crucial drawbacks of their product as per the perceptions of their multiple users. However, the findings transmit a clear message about advantages to users and drawbacks to developers. Therefore, the results will enhance the chatbots’ functionality and usage.

The findings of the study alert the teachers, students and policymakers of higher educational institutions to understand the positive outcomes and to accept AI-powered chatbots such as OpenAI’s ChatGPT. Outcomes also notify the AI-product developers to boost the chatbot’s quality in terms of timeliness, user-friendliness, accuracy and trustworthiness.

The recent failures and insolvencies of organisations related to the modern methods of construction (MMC) have gained increased attention and controversy across the UK construction sector. Such failures are linked to their inability to achieve an economy of scale and drive key clients to accept the MMC as an alternative to traditional methods. This paper aims to unravel whether a phenomenon of “innovation negativism” has manifested and is contributing to public clients' indecision towards broader MMC, whether this is only linked to past negative experiences formed after the Second World War or whether additional contributing reasons exist to influence adoption.

This study focusses on exploring the decision-making of the UK public construction sector; therefore, this paper adopts a qualitative approach, utilising interviews with 14 carefully selected MMC experts, government advisors and public clients. The phenomenological stance adopted herewith enables the authors to make better sense of the perceptions of the interviewees, leading to the conceptualisation of the innovation negativism phenomenon.

The paper identifies nine themes that may be argued to promote a profound understanding of the MMC negativism influencing public clients' decision-making. The study has found that more than just the previous negative perceptions formulated post Second World War are driving innovation negativism in the UK public sector. Notably, the emerging themes are incomprehension, lacking evidence, communication, relationship history, bad experiences, uncertainty, inadequate experimentation, the business case and localism.

This study is the first construction management research that acts as a fair departure point to conceptualise the reasoning behind innovation negativism in the construction setting. Through mirroring demand's unipolarity for traditional methods, policy and decision-makers can now rely on the conceptualised reasoning to determine practical solutions to overcome clients' indecisions towards MMC.

This study aims to investigate the relationship between digital financial inclusion and economic growth in specific Asian countries, emphasizing the exploration of how digital financial inclusion dynamics impact gross domestic per capita income.

The study creates a digital financial inclusion composite index (DFII) by incorporating essential metrics from the Global Findex report. Economic growth is measured using Gross Domestic Product per capita income in its natural logarithmic form (LnPCI), with three control variables– employment-to-population ratio; population growth and inflation. The analysis utilizes a fixed-effect dummy variable model to examine the relationship, considering unobserved country-specific heterogeneity. 30 Asian countries have been selected for the study for the periods 2014, 2017 and 2021 based on their availability, as outlined in Table 4.

The research revealed a robust positive correlation between the Digital Financial Inclusion Index (DFII) and logarithmic GDP per capita income (LnPCI), indicating higher per capita income with enhanced digital financial inclusion. Employment and population exhibited minimal influence, whereas inflation had a notable negative effect on per capita income. Population growth showed a limited impact. The model demonstrated a high explanatory power for the dependent variable (high R-squared), and the residuals displayed low autocorrelation (Durbin–Watson of 1.96).

This study adds to the existing literature by examining the intricate connection between digital financial inclusion (DFI) and economic growth in 30 Asian countries, employing a comprehensive composite index for analysis.

This paper aims to measure the extent of digital financial inclusion (DFI) and examine the effect of socioeconomic characteristics on using government remittances and the adoption of digital financial services (DFS) during the COVID-19 pandemic.

The World Bank Global Financial Inclusion (Global Findex) database 2021 is used in this study, with a sample size of 3,000 Indian individuals. The study measured the demand-side analysis of DFI, namely, accessibility and usage of DFS with selected socioeconomic characteristics such as gender, age, income, education, being in the workforce and residential status of respondents. The dependent variable is binary in nature; therefore, the logistic regression model is used for the data analysis.

The results of the study reveal that individuals’ socioeconomic factors, such as female, all the age groups, tertiary education, third- and fourth-income quintile and workforce, are found to have a significant association with “accessibility,” an exogenous variable of DFS. Besides, respondents’ socioeconomic attributes, namely, female, tertiary education, income for all quintiles and workforce, are more likely to use DFSs in the COVID-19 pandemic. The study also finds the residential status of individuals is influencing the accessibility and usage of DFS.

The findings of the study provide valuable insights to the service providers and policymakers regarding the rapid expansion of DFS by digital infrastructure, simplifying the banking procedures and highlighting the importance of digital financial literacy to accomplish government goals through serving the unbanked population and also design strategies for achieving the objectives of Digital India: “Faceless, Paperless, and Cashless” of DFI across the country.

Notable studies used World Bank Findex survey data to explore the determinants of financial inclusion in general. This research is one among the few studies to explore the determinants of India’s DFI. Moreover, this study measured the effect of individual socioeconomic attributes on the adoption of DFSs during the COVID-19 pandemic, which has not been included in prior studies. Therefore, this study has added value to the existing literature on financial technology innovation and DFS for the sustainable development of emerging nations.