A Meta-Analytic Structural Equation Model for Understanding Social Commerce Adoption

2023 | Information Systems Frontiers | Citations: 0

Authors: Dwivedi, Yogesh K.; Ismagilova, Elvira; Sarker, Prianka; Jeyaraj, Anand; Jadil, Yassine; Hughes, Laurie

Abstract: Social commerce (s-commerce) has gained prominence with advances in social media ... Expand

Abstract: Social commerce (s-commerce) has gained prominence with advances in social media and social networking technologies over the last decade. Prior research has employed diverse theoretical perspectives to understand and explain consumer behavior within s-commerce but has also produced inconsistent results. This study integrates different theoretical perspectives including trust, social support, and social presence. The research portrays an integrated research model involving factors that impact behavioral intention and use behavior of s-commerce consumers whilst synthesizing prior empirical findings. A meta-analytic structural equation modeling (MASEM) method was used to synthesize 189 findings reported in 68 s-commerce studies and to analyze the structural model. Our findings show that trust and informational support have positive effects on behavioral intention while trust and emotional support have positive effects on use behavior. Furthermore, our findings highlight that behavioral intention influences use behavior and mediates the effect of trust and informational support on use behavior. The implications for research and practice are discussed in detail. Collapse

Topics: behavioral intention social presence usage intention consumer behavior Facebook

Methods: meta analysis descriptive statistic structural equation modeling chi squared test survey design

A Taxonomy of SETA Methods and Linkage to Delivery Preferences

2023 | ACM SIGMIS Database | Citations: 0

Authors: Kävrestad, Joakim; Nohlberg, Marcus; Furnell, Steven

Abstract: Cybersecurity threats targeting users are common in today's information systems. ... Expand

Abstract: Cybersecurity threats targeting users are common in today's information systems. Threat actors exploit human behavior to gain unauthorized access to systems and data. The common suggestion for addressing this problem is to train users to behave better using SETA programs. The notion of training users is old, and several SETA methods are described in scientific literature. Yet, incidents stemming from insecure user behavior continue to happen and are reported as one of the most common types of incidents. Researchers argue that empirically proven SETA programs are needed and point out focus on knowledge rather than behavior, along with poor user adoption, as problems with existing programs. The present study aims to research user preferences regarding SETA methods, with the motivation that a user is more likely to adopt a program perceived positively. A qualitative approach is used to identify existing SETA methods, and a quantitative approach is used to measure user preferences regarding SETA delivery. We show that users prefer SETA methods to be effortless and flexible and outline how existing methods meet that preference. The results outline how SETA methods respond to user preferences and how different SETA methods can be implemented to maximize user perception, thereby supporting user adoption. Collapse

Topics: IT workforce IT security online learning system database system usage intention

Methods: survey literature sample simulation structured literature research literature study

Theories: technology acceptance model

Re-examining post-acceptance model of information systems continuance: A revised theoretical model using MASEM approach

2023 | International Journal of Information Management | Citations: 0

Authors: Mishra, Anubhav; Shukla, Anuja; Rana, Nripendra P.; Currie, Wendy L; Dwivedi, Yogesh K.

Abstract: This study extends the post-acceptance model of information systems (IS) continu ... Expand

Abstract: This study extends the post-acceptance model of information systems (IS) continuance, which is widely used to explain users’ satisfaction and IS continuance intentions. The extended model includes additional variables such as perceived ease of use (PEOU), attitude, trust, and enjoyment. The proposed model was tested using metaanalytic structural equation modeling (MASEM). The analysis included 1,056 observations on fifteen relation­ ships from 214 independent studies with a combined sample of 84,343. The results confirm the significance of all the relationships proposed in the original model. Furthermore, the findings indicate that PEOU directly in­ fluences perceived usefulness, satisfaction, and attitude. Trust and enjoyment both have a positive impact on users’ satisfaction and IS continuance, wherein the effect of enjoyment was higher than trust. post-consumption satisfaction resulted in a favorable attitude toward technology, which further affected IS continuance. From a theoretical perspective, the current study acknowledges the shift in users’ attitude toward technology and em­ phasizes the hedonic value of IS usage as users report a higher degree of satisfaction toward responsive, easy to use, and enjoyable technologies. Marketers should focus on the enjoyment and gratifications derived from technology to increase potential IS usage. Collapse

Topics: information system use perceived usefulness technology adoption social media ease of use

Methods: meta analysis structural equation modeling descriptive statistic literature sample hierarchical linear modeling

Theories: post acceptance model unified theory of acceptance and use of technology expectation confirmation theory extended unified theory of acceptance and use of technology learning theory

Factors influencing the acceptance of healthcare information technologies: A meta-analysis

2022 | Information & Management | Citations: 0

Authors: Chong, Alain Yee Loong; Blut, Markus; Zheng, Shuning

Abstract: Healthcare information technologies (HIT) can address several challenges faced b ... Expand

Abstract: Healthcare information technologies (HIT) can address several challenges faced by healthcare systems. To benefit from the advantages HIT offer, users must first accept them. This meta-analysis synthesizes previous research on HIT acceptance. It uses data from 214 independent samples reported in 193 articles and 83,619 technology users from 33 countries. The study contributes to the HIT literature by (1) synthesizing the empirical findings on technology acceptance factors and combining them in a comprehensive model, (2) testing the mediating mechanisms of health technology acceptance, and (3) examining contextual differences. The study finds that HIT acceptance depends on various predictors proposed by the technology acceptance model and the unified theory of acceptance and use of technology. These factors displayed strong indirect effects through effort expectancy, perceptions of the technology, performance expectancy, and attitudes toward using HIT. Studies overlooking these effects may underestimate the importance of various acceptance factors. Finally, the results suggest that technology acceptance varies across healthcare technologies (remote information systems [IS], wearables), users (staff/patients, age, voluntariness, experience), and locations (hospitals, healthcare systems, life expectancy in country). We also provide IS managers with guidance for improving technology acceptance in the healthcare industry to ensure efficient, high-quality services. Collapse

Topics: smart wearable device health information system technology adoption usage intention mobile system

Methods: meta analysis structural equation modeling literature sample literature study conceptual modelling

Theories: technology acceptance model unified theory of acceptance and use of technology TAM2 TAM3 extended unified theory of acceptance and use of technology

What facilitates consumers accepting service robots? A conceptual framework

2022 | European Conference On Information Systems | Citations: 0

Authors: Lin, Yanqing

Abstract: Confronting with an increasing number of robots swarming into service industrie ... Expand

Abstract: Confronting with an increasing number of robots swarming into service industries to replace human personnel, studies regarding what drives consumers to use service robots leave to be, unfortunately, still fragmented. Motivated by this, based on a content analysis of the existing studies, this paper establishes a conceptual framework to comprehend the current literature for in-depth understanding concerning customer attitude and their intention to use service robots. Drawing upon a triangulation of perspectives on end-user (i.e., technology user, consumer, and network member) in adoption research, this framework adopts technology acceptance theories, service quality, and expectancyvalue theory to set up the skeleton. Furthermore, the antecedents impacting customer acceptance of service robots are subdivided into robot-design, consumer-oriented, relational components, as well as exogenous factors. This paper not only elaborates on the present situation of service robot acceptance research but also promotes it by developing a comprehensive framework regarding the effect factors. Collapse

Topics: robotic usage intention service quality technology adoption customer service

Methods: qualitative content analysis triangulation literature study

Theories: technology acceptance model expectancy–value theory technology acceptance theory

Painting A Holistic Picture of Trust in and Adoption of Conversational Agents: A Meta-Analytic Structural Equation Modeling Approach

2022 | HICSS | Citations: 0

Authors: Anton, Eduard; Oesterreich, Thuy Duong; Schuir, Julian; Teuteberg, Frank

Abstract: With their human-like nature, conversational agents (CAs) introduce a social com ... Expand

Abstract: With their human-like nature, conversational agents (CAs) introduce a social component to humancomputer interaction. Numerous studies have previously attempted to integrate this social component by incorporating trust into models such as the technology acceptance model (TAM) to decipher the adoption mechanisms related to CAs. Given the heterogeneity of these previous works, the aim of this paper is to integrate empirical evidence on the role and influence of trust within the nomological network of the TAM. For this purpose, we conduct a meta-analytic structural equation modeling approach based on 45 studies comprising k = 155 correlations, and N = 13,786 observations. Our findings highlight the multifaceted role of trust as a mediator transmitting the effects of the technology-related perceptions that drive the intention to use CAs. Our results present a comprehensive overview in a thriving research field that can guide both future theory building and the designs of more trustworthy CAs. Collapse

Topics: usage intention perceived usefulness perceived ease of use privacy information privacy concern

Methods: theory development meta analysis structural equation modeling chatbot qualitative coding

Theories: technology acceptance model social presence theory uncanny valley theory

Early bird catches the worm! Meta-analysis of autonomous vehicles adoption – Moderating role of automation level, ownership and culture

2022 | International Journal of Information Management | Citations: 0

Authors: Gopinath, Krishnan; Narayanamurthy, Gopalakrishnan

Abstract: The ongoing competition between traditional vehicle manufacturers and technology ... Expand

Abstract: The ongoing competition between traditional vehicle manufacturers and technology companies for quickly developing autonomous vehicles (AVs) and gaining early traction in the market is well known. However, some issues need to be cleared regarding the antecedents of the behavioral intention to use AVs. In this context, we conducted a meta-analysis using the TIS (Technological, Individual, and Security) framework, to understand the convergence and divergence of the factors influencing the behavioral intention to use AV technology. This metaanalysis tested the hypotheses using a database of 65 studies obtained from 58 articles with the cumulative sample size of 37,076. The study identified perceived usefulness, attitude, trust, safety, hedonic motivation, and social influence as the critical antecedents of AV adoption. Several of the relationships investigated in the study were moderated by factors such as level of automation, vehicle ownership and culture. The results revealed fewer incentives for the public to accept AVs. Theoretical contributions and recommendations to practitioners and policymakers have also been discussed. Collapse

Topics: behavioral intention usage intention perceived ease of use perceived usefulness social influence

Methods: meta analysis conceptual modelling literature sample synthesis literature study

Theories: unified theory of acceptance and use of technology technology acceptance model technology acceptance theory behavioral theory

Extending the story of IS success: a meta-analytic investigation of contingency factors at individual and organisational levels

2022 | European Journal of Information Systems | Citations: 0

Authors: Mehta, Nikhil; Chauhan, Sumedha; Kaur, Inderjeet

Abstract: In the last decade, a diverse array of information systems (IS) has emerged to h ... Expand

Abstract: In the last decade, a diverse array of information systems (IS) has emerged to help organisations achieve their performance goals. As a result, global spending on information technology (IT) has increased manifold. These developments have reopened the fundamental question of how IS success is shaped at the organisational level. Scholars and practitioners would also like to understand if, compared to the individual level, IS success patterns differ at the organisational level. The last meta-analysis of IS success was conducted nearly a decade ago and it could not examine IS success at the organisational level. There is also a need to gain a deeper understanding of key contingencies influencing success at the organisational level. Based on a comprehensive meta-analysis of research studies conducted in the last decade, we not only report how IS success patterns are shaped at the organisational level but also show how these patterns compare to success configurations at the individual level. Additionally, we conduct detailed multi-level meta-analyses of system complexity and user type as two key contingencies influencing success at both individual as well as organisational levels. Findings of our moderation analyses reveal distinct constructions of IS success across both levels. Collapse

Topics: user satisfaction IS success usage intention data quality service quality

Methods: meta analysis moderation analysis cross sectional research descriptive statistic theory development

Theories: information systems success model

Modeling Business Models: A cross-disciplinary Analysis of Business Model Modeling Languages and Directions for Future Research

2022 | Communications of the Association for Information Systems | Citations: 0

Authors: Szopinski, Daniel; Massa, Lorenzo; John, Thomas; Kundisch, Dennis; Tucci, Christopher

Abstract: Modeling languages for business models are a powerful and flexible means of rep ... Expand

Abstract: Modeling languages for business models are a powerful and flexible means of representing and communicating knowledge related to business models. More than fifteen years after Osterwalder et al. (2005) clarified the ontology for the business model concept in this journal, we offer a systematic and cross-disciplinary assessment of the literature on business model modeling languages (BMMLs) that facilitate the visualization of this concept. In so doing, we synthesize and organize the knowledge dispersed across different disciplines in which BMMLs have originated and highlight the potential weaknesses in this literature to offer solid insights for future research. Our analysis reveals the existence of 17 BMMLs that have originated in traditional domains such as strategy and information systems, but also emerging domains such as sustainability. We contrast and compare these BMMLs along three dimensions: semantics, syntax, and pragmatics. We also analyze research that has made use of these BMMLs, differentiating between research that is conducted with a given BMML and research that is conducted about a given BMML. We conclude by offering a research agenda in which we illustrate the main challenges associated with the lack of wellaccepted semantic, syntactic, and pragmatic foundations of BMMLs and outline opportunities for future research. Collapse

Topics: business model database system knowledge representation electronic business innovation management

Methods: modeling language design science literature sample ontological modelling synthesis

Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions

2022 | Electronic Markets | Citations: 9

Authors: Riedl, René

Abstract: Artificial intelligence (AI) refers to technologies which support the execution ... Expand

Abstract: Artificial intelligence (AI) refers to technologies which support the execution of tasks normally requiring human intelligence (e.g., visual perception, speech recognition, or decision-making). Examples for AI systems are chatbots, robots, or autonomous vehicles, all of which have become an important phenomenon in the economy and society. Determining which AI system to trust and which not to trust is critical, because such systems carry out tasks autonomously and influence human-decision making. This growing importance of trust in AI systems has paralleled another trend: the increasing understanding that user personality is related to trust, thereby affecting the acceptance and adoption of AI systems. We developed a framework of user personality and trust in AI systems which distinguishes universal personality traits (e.g., Big Five), specific personality traits (e.g., propensity to trust), general behavioral tendencies (e.g., trust in a specific AI system), and specific behaviors (e.g., adherence to the recommendation of an AI system in a decision-making context). Based on this framework, we reviewed the scientific literature. We analyzed N = 58 empirical studies published in various scientific disciplines and developed a “big picture” view, revealing significant relationships between personality traits and trust in AI systems. However, our review also shows several unexplored research areas. In particular, it was found that prescriptive knowledge about how to design trustworthy AI systems as a function of user personality lags far behind descriptive knowledge about the use and trust effects of AI systems. Based on these findings, we discuss possible directions for future research, including adaptive systems as focus of future design science research. Collapse

Topics: personality artificial intelligence robotic usability behavioral intention

Methods: literature sample chatbot literature study design science qualitative interview

Theories: big five model cultural dimensions theory