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This paper is a tribute to researchers who have significantly contributed to improving and advancing structural equation modeling (SEM). It is, therefore, a brief overview of SEM and presents its beginnings, historical development, its usefulness in the social sciences and the statistical and philosophical (theoretical) controversies which have often appeared in the literature pertaining to SEM. Having described the essence of SEM in the context of causal analysis, the author discusses the years of the development of structural modeling as the consequence of many researchers’ systematically growing needs (in particular in the social sciences) who strove to effectively understand the structure and interactions of latent phenomena. The early beginnings of SEM models were related to the work of Spearman and Wright, and to that of other prominent researchers who contributed to SEM development. The importance and predominance of theoretical assumptions over technical issues for the successful construction of SEM models are also described. Then, controversies regarding the use of SEM in the social sciences are presented. Finally, the opportunities and threats of this type of analytical strategy as well as selected areas of SEM applications in the social sciences are discussed.

The purpose of this article is to explore the mediating role of perceived usefulness, trust and attitude on a user’s intention towards use of mobile wallets in India. While mediation has been studied by earlier researchers in the context of online commerce, mobile banking, short message service (SMS) banking, mobile money, etc., not many studies exist in the context of mobile wallets. Considering the potential of mobile wallets in India, previous relationships from the theories of technology adoption like technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT) were adapted to investigate the determinants of user attitude and intention towards mobile wallet adoption. Based on data from 744 respondents collected through a survey, partial least squares (PLS) structural equation modelling was used to test the research model. Convenience sampling was used to select the respondents. The results revealed that out of the nine paths wherein mediation was examined, in two paths full mediation was found while it was partial in the remaining cases. This study extends research in explaining attitude and intention through multiple mediating relationships. The implications for research and practice and future research directions are discussed.

As technology continues to advance, the integration of generative artificial intelligence tools in various sectors, including education, has gained momentum. ChatGPT, an extensively recognized language model created by OpenAI, has gained significant importance, particularly in education. This study investigates the awareness, acceptance, and adoption of ChatGPT, a state-of-the-art language model developed by OpenAI, in higher education institutions across China. This study applies the partial least squares structural equation modeling (PLS-SEM) method for examining data collected from 320 Chinese university students. The study’s conceptual framework integrates key determinants from the Technology Acceptance Model (TAM) and extends it by incorporating perceived intelligence as a critical factor in the adoption process. The study findings reveal that ChatGPT awareness significantly influences the intention to adopt ChatGPT. Perceived ease of use, usefulness, and intelligence significantly mediate the association between ChatGPT awareness and adoption intention of ChatGPT. Additionally, perceived trust significantly moderates the relationship between ChatGPT awareness and perceived ease of use, usefulness, and intelligence. Moving forward, in order to maintain students’ critical thinking skills and inventiveness in their assessment writing, assessments must promote the safe use of ChatGPT. Therefore, educators will be crucial in ensuring that artificial intelligence tools are used in assessments ethically and suitably by providing clear guidelines and instructions.

With the increasing popularity of social media, a new ethics debate has arisen over marketing and technology in the current digital era. People are using online communities but they have concern about information credibility through word of mouth in these platforms. Social media is becoming increasingly influential in shaping individuals' decision-making as more and better quality information about products is made available. In this research, a social word-of-mouth model proposes using a survey to test the model in a popular travel community. The model highlights the role of social media and social support in social networking sites (SNSs), identifying increasing credibility and information usefulness resulting in an ethical environment to adopt word of mouth. The theoretical and practical implications of the study are both detailed.

PurposeE-commerce live streaming is a new influencer advertising method that allows influencers to interact directly with consumers on e-commerce platforms. Although evidence suggests that influencer live-streaming advertisements (ads) on social media can increase consumers’ buying impulses, little research examined how this similar but new advertising method on e-commerce platforms may influence consumers’ urge to buy impulsively. This study explores the role of influencer credibility, celebrity effect, perceived entertainment, trust and perceived usefulness on consumers’ attitudes toward influencer ads and their urge to buy impulsively.Design/methodology/approachA questionnaire containing seven constructs was developed and distributed to participants using a convenient sample and snowball sampling approach. The constructs were measured based on validated measurement items from the literature and adjusted according to this study’s focus. A total of 236 valid responses were obtained from the survey and used for data analysis. A partial least squares structural equation modeling approach was employed for parameter estimation and model testing.FindingsThe empirical results show that all constructs influenced consumers’ urge to buy impulsively via attitude toward influencer ads. The proposed research model explains 61.7% of the variance in attitude toward influencer ads and 19.4% of the urge to buy impulsively.Originality/valueThis is an early study investigating the relationship between influencer advertising and impulse buying. The results provide valuable insights into improving the design of influencer ads and marketing strategies.HighlightsI-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.Consumers’ attitude towards influencer ads affects their urge to buy impulsively.Influencer credibility affects consumer attitude via celebrity effect as a mediator.Trust affects consumer attitude via perceived usefulness as a mediator.Entertaining ads help develop favorable consumer attitude.

Purpose This paper aims to propose a theoretical extension of the information system success model (ISSM) to evaluate enterprise resource planning (ERP) success at an organizational level in Jordan. It explores whether information quality, system quality and service quality have a positive impact on both perceived usefulness and user satisfaction as antecedents of organizational impact. Design/methodology/approach A questionnaire was undertaken to gather data from chief information officers among Jordanian firms, with a total of 134 valid returns tested via partial least squares structural equation modeling. Findings The results showed that most of the research hypotheses proposed are empirically supported, with the exception of the influence of service quality on user satisfaction which was extremely low. Originality/value To the best of the authors’ knowledge, this is the first empirical work that measured ERP success from an organizational perspective in Jordan. It also provides insight into how the factor of perceived usefulness is incorporated into ISSM in the mandatory system case and its influences on organizational benefits.

PurposeThis study aims to investigate the factors influencing consumers' continued social commerce (s-commerce) intention and its underlying mechanism.Design/methodology/approachThe authors define continued s-commerce intention as consumers' intention to continually participate in s-commerce activities, namely, requesting and sharing commercial information. Grounded in the motivation theory, perceived usefulness and perceived enjoyment are identified in this study as the motives behind consumers' continued s-commerce intention. Given the indispensable social facet of s-commerce, the authors include social support as another critical social factor motivating continuance intention. Furthermore, users' perceptions are affected by prior s-commerce outcomes, which concern the effectiveness of the commercial information exchange process. Research suggests that in such a context, the result of communication is jointly determined by source credibility and interactive relationships amongst individuals. Whilst source credibility determines the usefulness of the information transmitted, a social interaction supports this process. Therefore, source credibility and social interactions are crucial to the outcomes of s-commerce, which, in turn, affect consumers' perceived usefulness, perceived enjoyment and social support in s-commerce. Building on these arguments, the authors propose our research model and then test the hypotheses via a survey.FindingsThe authors find that consumers' perceived usefulness and informational social support of s-commerce directly affect their continued s-commerce intention. Moreover, perceived enjoyment leads to continued s-commerce intention via the mediation of perceived usefulness, whilst emotional social support influences continued s-commerce intention through the mediator of informational social support. In addition, source credibility is a significant antecedent of consumers' usefulness, enjoyment and social support perceptions, whilst a social interaction significantly impacts perceived enjoyment and social support.Originality/valueVarious consumer behaviours in s-commerce have been studied; however, the continuance intention to participate in the s-commerce activity remains unknown. This empirical study fills this research gap. Moreover, the authors initially reveal s-commerce participants' utilitarian orientation in the post-adoption stage: perceived usefulness and informational social support affect continuance intention more directly than perceived enjoyment and emotional social support. Further, prior studies on information systems continuance have mainly focused on technical features. By identifying the influence from social factors, i.e. social support, this work extends the literature on information systems continuance.

The strength model of self-regulation uses a muscle analogy to explain patterns of ego depletion, conservation of willpower, and improved performance after frequent exercise. Our 2007 overview of the literature has been well cited, presumably because of the phenomenon’s importance to theories of selfhood and a wide assortment of applied contexts, including problem behaviors. Some researchers have put forward rival theoretical accounts, and others have questioned the existence of the phenomenon. The weight of evidence continues to support the usefulness of the strength model, albeit amid continuing updates and revisions.

Purpose The paper aims to understand the possible determinants of knowledge of, and interest in using, blockchain, with a particular focus in the future intention to apply this technology. Blockchain technology is deemed to radically change business models and processes. Using this technology in small and medium enterprises (SMEs) is still a novel idea. Moreover, not much is known about the diffusion and level of interest towards blockchain in SMEs. This research adopts a knowledge management perspective, drawing on technology acceptance model to highlight the level of blockchain technology diffusion, and to explore which factors lead SMEs’ to adopt blockchain. Design/methodology/approach This study distributed a questionnaire to a sample of 300 SMEs in Italy. This study received 96 responses (32% response rate). This study calculated descriptive statistics and undertook a reliability analysis. Finally, this study performed a logistic regression to analyse the determinants of further intention to use blockchain technology. Findings Results show that blockchain technology is quite well known, but the level of knowledge is limited. Moreover, the research reveals that the rate of adoption is very low. Interest in the future adoption of blockchain is associated with knowledge, perception of usefulness and ease of use of blockchain. Originality/value This paper is one of the first explorative studies showing which factors lead SMEs to adopt blockchain technologies and shedding some light on the interaction between knowledge management and blockchain adoption and diffusion in SMEs. It highlights how blockchain knowledge could determine future interest in blockchain innovation. This paper is relevant for public and private institutions that aim to promote, through knowledge management, the adoption of blockchain in SMEs.

Propensity score matching (PSM) has become a popular technique for estimating average treatment effects (ATEs) in accounting research. In this study, we discuss the usefulness and limitations of PSM relative to more traditional multiple regression (MR) analysis. We discuss several PSM design choices and review the use of PSM in 86 articles in leading accounting journals from 2008–2014. We document a significant increase in the use of PSM from zero studies in 2008 to 26 studies in 2014. However, studies often oversell the capabilities of PSM, fail to disclose important design choices, and/or implement PSM in a theoretically inconsistent manner. We then empirically illustrate complications associated with PSM in three accounting research settings. We first demonstrate that when the treatment is not binary, PSM tends to confine analyses to a subsample of observations where the effect size is likely to be smallest. We also show that seemingly innocuous design choices greatly influence sample composition and estimates of the ATE. We conclude with suggestions for future research considering the use of matching methods.