Search results

This study examines the effect of digitalization on poverty and income inequality in developing countries. The study answers the question of whether digitalization is a way for developing countries to get out of poverty and income inequality.

The study uses data from 17 developing countries with data from 2005 to 2021. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), with an augmented mean group (AMG) for robustness. Digitalization, as the variable of interest, is proxied by the digitalization index (DI), constructed using principal component analysis (PCA). The dependent variables are poverty and income inequality, which are used in different models.

The evidence indicates that digitalization decreases poverty and income inequality in developing countries. These findings are justified when we use the AMG estimator, but the strength of the coefficients and significance levels are higher in the FMOLS and DOLS estimators. The results of the control variables also show that human development (LHDI), CO2 emissions and foreign direct investment (FDI) have decreasing effects on poverty and income inequality. Thus, digitalization is a good option for developing countries to get out of poverty and income inequality to achieve sustainable development goals (1&10).

This study provides rigorous empirical evidence on the effect of digitalization on poverty and income inequality in developing countries. Unlike the previous studies on developing countries, this study used a DI to proxy digitalization. In addition, the authors use FMOLS and DOLS estimators, with an AMG estimator for robustness, to provide long-run coefficients.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0586

Studies have shown that within-domain compensatory consumption can successfully repair the damaged self, but other research indicates that it can undermine self-control because such consumption causes self-threat rumination that impairs self-regulatory resources. This paper aims to identify a boundary condition that reconciles and explains these contradictory findings.

The authors conducted three experiments to show that within-domain compensatory consumption undermines self-control, but only in some situations. They test a boundary condition (i.e. type of connections between within-domain products and self-threat domain) for the effects of such consumption on self-threat rumination and self-control.

This paper demonstrates that within-domain (but not across-domain) compensatory consumption induces rumination and reduces subsequent self-control, but only when the product’s connection to the self-threat domain is made explicit through brand names or slogans. When the connection is merely implicit, rumination and self-control deficits are not observed.

Consumers may seek certain products to bolster threatened aspects of their self-concept. Marketing tactics that explicitly highlight connections to such self-aspects can lower a consumer’s self-control resulting in stronger purchase intent, while at the same time hindering the possibility of self-concept repair. Managers need to be wary of ethical concerns.

This research qualifies the existing findings by presenting “type of product connection” as a key determinant of within-domain compensatory consumption’s impact on self-control. Researchers need to be conscious of the type of products (explicitly vs implicitly connected to the self-threat domain) they use in compensatory consumption studies, because this may influence their findings.

Due to e-commerce growth, technological advancements and environmental concerns, developing a more nuanced service portfolio has become a critical issue for last-mile logistics service providers. Concurrently, consumers are adopting new modes of consumption. This paper aims to investigate the potential for last-mile logistics service providers to act as intermediaries in access-based consumption and to revitalise their service offerings through product-service systems – a pioneering strategy not executed in the market yet.

This strategic customer foresight study uses a quantitative survey of 1,000 respondents and an online focus group comprising 10 early adopter consumers to investigate emerging last-mile service models. Potential service concepts were identified through the survey, and two distinct concepts were subsequently selected for evaluation and co-development within the focus group. The research was conducted in partnership with an SME logistics company in Finland.

The consumers expressed selective interest in access-based consumption related to the proposed offering of essential household goods. Young adults and consumers in early middle age living in the city centre emerged as the most potential user groups. Economic reasons and short-term needs were the primary motivations for adopting access-based consumption.

The study showed that engaging consumers in a customer foresight process is viable for SMEs innovating their offerings and demonstrates how the process works in practice.

Documented cases of customer integration into foresight processes are rare in earlier research, and this paper extends the knowledge base through a multidisciplinary examination of future consumer behaviour in the last-mile logistics domain. The paper also expands the limited literature on the role of logistics in access-based consumption.

The integration of social media and e-commerce has resulted in a rising phenomenon among individual content providers (ICPs), who used to offer free content, to provide consumers with paid content, such as online courses, Q&As or consultations. Despite the prevalence of ICPs’ content monetization, empirical research has rarely studied its underlying mechanism. This paper examines how the characteristics of free content contributed by ICPs on social media platforms influence their paid content sales, focusing on the perspective of human brand.

The empirical setting is an online knowledge exchange platform, where users are allowed to provide free content (e.g. answers) on the social media platform and launch paid content (e.g. lectures) on the e-commerce platform. A machine learning technique is employed to construct measures for the characteristics of free content, and fixed-effects estimation is presented to confirm which factors have a significant influence on the sales of paid content.

The empirical results show that the quality, diversity and expertness of free content have a significant positive impact on the sales of the ICP-paid content, with the brand popularity of ICP playing a mediating role.

This study is the first attempt to demystify the relationship between content contribution and ICPs’ content monetization from the perspective of human brand. The findings validate the effectiveness of the “Selling by Contribution” strategy and provide valuable insights for ICPs and social media platforms.

The purpose of this study is to extend the Fraud Diamond Theory to celebrity Special Purpose Acquisition Companies (SPACs) and investigate their post-Initial Public Offering (IPO) stock market performance.

After obtaining a sample of celebrity SPACs from the Spacresearch.com database, fraud risk characteristics were obtained from Lexis Nexus searches. Buy and hold abnormal returns were calculated for celebrity SPACs versus a small-cap equity benchmark for time intervals after IPO, and multiple regression analysis was performed to examine the relationship between fraud risk features and post-IPO returns.

Celebrity SPACs exhibit Fraud Diamond characteristics and significantly underperform a small-cap stock portfolio on a risk-adjusted basis after IPO.

This study only examines celebrity SPACs that conducted IPOs on the NYSE and NASDAQ/AMEX and does not include those that are traded on the Over the Counter Bulletin Board (OTCBB).

Celebrity endorsement of SPAC vehicles attracts investors who may not be properly informed regarding the risk characteristics of SPACs. Accordingly, investors should be warned that celebrity SPACs underperform a small-cap equity portfolio and exhibit significant elements of fraud risk.

The use of celebrity endorsement as a marketing device to attract investment in SPACs has regulatory implications.

To the best of the authors’ knowledge, this paper is the first to examine the fraud risk characteristics and post-IPO performance of celebrity SPACs.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

The purpose of this study was to comprehend the adoption of artificial intelligence (AI) technology-driven natural large language model (LLM)-based chatbots by customers.

A qualitative research study method was conducted. This was to explore managerial perspectives towards consumer centric technology adoption of AI plus LLM-based chatbots. This was specifically for AI-driven natural LLM-based chatbots services. The author conducted conducted in-depth personal interviews with 32 experts of digital content AI + LLM chatbot services. Thematic content analysis was undertaken to analyse the data.

The advent of natural language processing tools driven by AI technology chatbots has altered human-firm interaction. The research findings indicated that the push-pull-mooring (PPM) factors captured the phenomenon in the most comprehensive way. A total of 15 key factors influencing the adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction were identified in this study by the author. The thematic content analysis unraveled insights regarding transformed consumer adoptions towards AI-driven LLM-based chatbots by means of the PPM framework factors.

The empirical research investigation contributed to the literature on the PPM theoretical framework. This was specifically in the context of adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction.

The research study insights would help managers to restructure and reconfigure their organizational processes. This would neccessiated a shift in firm-customer interactions as demanded because of the availability of AI technology-driven natural LLM-based chatbots by customers.

This research study was based upon the PPM theoretical framework. This study provided a unique analysis of the altered firm customer interaction needs and requirements. This was one of the first studies that applied the framework of PPM theory regarding the adoption of AI technology-driven natural LLM-based chatbots by customers.

This paper presents a new conceptualization of digital service anchored in a coconstitutive ontology of digital “x” phenomena, illuminating the pivotal role of the digital qualifier in the service context. Our objective is to provide a theoretically grounded conceptualization of digital service and its impact on the nature of the value cocreation process that characterizes digital phenomena.

Drawing from scholarly works on digital phenomena and fundamental principles of service-dominant logic, this paper delineates the essence of digital service based on the interplay between digitization and digitalization as well as the operational dynamics of generativity and its constitutive dimensions (architecture, community, governance).

The paper defines digital service as a sociotechnical process of value cocreation, where participants dynamically architect, govern and leverage digital resources. This perspective highlights the organic development of digital service and the prevalence of decentralized control mechanisms. It also underscores how the intersection between generativity’s dimensions—architecture, community and governance—shapes the dynamic evolution and outcomes of digital services.

Our conceptual framework sheds light on our understanding of digital service, offering a foundation to further explore its nature and implications for research and practice, which we illustrate using the case of ChatGPT.

The presence of securities crowdfunding (SCF) FinTech in the Islamic financial landscape opens investment opportunities through shares and sukuk (Sharia bond) instruments. This study aims to examine the effect of investment risk (IR), legal risk (LR), product knowledge (PK), Sharia compliance (SC) and subjective norm (SN) on investment decisions in businesses and projects run by small and medium enterprises (SMEs).

The questionnaires were distributed to prospective investors with prior knowledge of SCF and Islamic investment. The data collected was then examined using partial least square-structural equation modeling using SmartPLS 4.0.

The results show that LR has positive and significant implications for supporting investment through SCF, while IR has the opposite. The main findings in this study explain that PK and SC are proven to strengthen the intention to invest in SCF. Meanwhile, SN, which also strengthens intention, is the greatest influence. Therefore, it is highly recommended that SCF organizers collaborate with regulators (OJK), universities, academics and the investor community, as well as Muslim entrepreneurs, to provide education and literacy regarding SCF products and the underlying contracts, along with the consequences and uniqueness of investment vis SCF.

From a managerial side, Sharia expert educators can be appointed to increase investors’ literacy and confidence to support SMEs’ business expansion via SCF. In addition, to minimize investment risk, SCF organizers are also advised to issue sukuk and shares in different low-risk businesses/sectors, followed by investment amounts that are more affordable for novice investors.

Research on SCF as an alternative to SME financing is still scarce. To the best of the author’s knowledge, this is the first research to empirically test the relationship between risk, SC, PK and SN on potential investors’ decisions to support SMEs through the SCF mechanism.

The huge Muslim population has increased the demand for halal tourism products and destination factors in this niche tourism segment. Despite the growing body of research conducted regarding ChatGPT’s revolutionary impact on the tourism industry, the use of such an artificial intelligence (AI) tool in halal tourism needs more attention. This study aims to provide a comprehensive an overview of using ChatGPT in the tourism industry, specifically in halal tourism, and offer an agenda for further essential research questions exploration.

Through the intensive examination of the tourism literature dealing with AI and halal tourism, this review identifies the implications related to the use of ChatGPT for Muslim travelers and future trends in halal tourism.

This paper identified the possible utilization of ChatGPT in assisting Muslim travelers across various stages of their journey, encompassing pre-trip, staying and post-trip phases. Subsequently, this paper identified the opportunities and challenges associated with implementing ChatGPT in the context of halal tourism. Finally, the paper delves into potential avenues for future research.

The findings serve as crucial implications, contributing to the theory of halal tourism development and the applications of ChatGPT in halal tourism.

This paper provides essential foundational knowledge for upcoming research on halal tourism theory, ChatGPT and the development of halal tourism sector.