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Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

This study examines how users' multidimensional representational fidelity factors affect sociability and cyberself engagement in the Metaverse platform; that is, how they interact with newly defined self-images as their personas in the environments. It investigates how representational fidelity serves platform users to perform social roles and increase their sociability by establishing a new cyberself, thus influencing continuous platform use.

This study surveyed 314 users of the Metaverse platform Horizon, where users can create a virtual agent avatar, meet people in the same online environment in real time, and interact with a sense of three-dimensional immersion. Data were analyzed using partial least squares regression models.

User socialization significantly influenced the intention to use the Metaverse platform. Representational fidelity was a crucial variable for sociability, and activity representational fidelity was the most influential aspect among the four other elements. Platforms should consider how to enable users to create and use activities that faithfully represent their personas.

The novelty of this study is that it introduces representational fidelity based on representation theory into the context of virtual persona in the Metaverse platform. This study extended representational fidelity to the socialization perspective by utilizing the integrated model of user satisfaction and the technology acceptance model. Through the results, this study emphasized that users' sociability significantly influences their intention to use the Metaverse platform. Finally, this study provides a feasible guideline on how practitioners could design and strengthen their platforms so that users can represent their cyberselves faithfully.

Charitable crowdfunding features are embedded in social media platforms to encourage pro-social behaviors. Although such new practice allows practitioners to leverage the power of a highly connected crowd, accomplishing the fundraising goal is still a challenge. This study seeks to understand what drives the donation intention in charitable crowdfunding features on social media platforms by examining the roles of social experience, empathy and personal impulsiveness.

A survey questionnaire was distributed to social media users in China to collect data. A total of 206 valid responses were analyzed using structural equation modeling to test the proposed hypotheses.

The results showed that empathy mediates interaction with the fundraiser and perceived proximity with the donatee on a user's donation intention. We also found that social influence on social media platforms positively influences empathy and donation intention. In addition, personal impulsiveness was found to moderate the relationship between empathy and donation intention.

This study contributes to existing literature and practices. It identifies three dimensions of social experience and examines their effects on donation intention, providing insights into the charitable crowdfunding features on social media. Moreover, this study extends the understanding to empathy by delineating its mediating role in the relationship between social experience and donation intention and examining how personal impulsiveness moderates the effect of empathy on donation intention. Furthermore, this study provides valuable insights for practitioners to craft strategies to stimulate pro-social behaviors and increase donations.

The purpose of this paper is to provide small and medium-sized enterprises (SMEs) in emerging markets with an updated Purchasing Portfolio Matrix (PPM) specifically for international sourcing. This data-driven PPM matrix is designed to provide a dynamic and process perspective that can help SMEs survive the disruptions caused by emergency situations such as the global COVID-19 pandemic.

This research reports on qualitative interviews with experienced informants from 15 SMEs in the manufacturing industry. The authors follow process-based research using a combination of retrospective and real-time case study approaches to gradually unveil the dynamics in segmentation and sourcing strategies in the international sourcing context during the COVID-19 pandemic.

The findings reveal the dynamics of segmentation and international sourcing strategies during global disruptions and unpack the underlying logic behind the dynamics that is specific to SMEs in emerging economies.

Existing literature on PPM predominantly focuses on static and normal sourcing circumstances. This paper addresses this gap by adopting a dynamic approach to study how sourcing strategies of SMEs from emerging economies evolve in a highly volatile environment from an international sourcing perspective.

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and extend the application of PLS-SEM in Industrial Management and Data Systems (IMDS) to focus on trends emerging in the more recent 2016–2022 period.

A review of PLS-SEM applications in information systems studies published in IMDS and MISQ for the period 2012–2022 identifies and comments on a total of 135 articles. Selected emerging advanced analytical PLS-SEM applications are also highlighted to expand awareness of their value in more rigorously evaluating model results.

There is a continually increasing maturity of the information systems field in applying PLS-SEM, particularly for IMDS authors. Model complexity and improved prediction assessment as well as other advanced analytical options are increasingly identified as reasons for applying PLS-SEM.

Findings demonstrate the continued use and acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is the preferred SEM method in many research settings, but particularly when the research objective is prediction to the population, mediation and mediated moderation, formative constructs are specified, constructs must be modeled as higher-order and for competing model comparisons.

This update on PLS-SEM applications and recent methodological developments will help authors to better understand and apply the method, as well as publish their work. Researchers are encouraged to engage in more complete analyses and include enhanced reporting procedures.

Applications of PLS-SEM for prediction, theory testing and confirmation are increasing. Information systems scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for both exploratory and confirmatory research.

Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period.

Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers.

PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research.

Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools.

Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools.

Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al. (2019; 2022) are included.