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This study is based on the heuristic-systematic model (HSM) to dynamically examine the effect of review variance on sales and the boundary conditions that mitigate this effect.

Based on the theoretical domain of HSM, a conceptual model is proposed that analyzes the nonlinear relationship between review variance and sales and the interaction and motivation factors that moderate these relationships. Review data from websites targeting the film industry in the USA and South Korea (Korea) were collected to empirically analyze the authors' hypothesis, and panel regression analysis was used for confirmation.

Moderated by interactive and motivational factors, review variance exhibits an inverse-U-shaped relationship with review variance. Specifically, as an interaction factor, review valence and owned social media (OSM) resulted in positive interaction effects, and as a motivation factor, the number of alternatives exhibited a positive interaction effect with review variance. The effect of review variance was less pronounced in the USA than in Korea.

The study outcomes reveal a nonlinear relationship between review variance and sales, thus supporting the contradictory findings of previous studies. This study contributes to the literature by using the HSM as a theoretical framework to verify various HSM mechanisms using online review data. This exploratory study also contributes to the international marketing literature by showing that the effects of review variance vary across cultures.

With the widespread use of online communications, users are extremely vulnerable to a myriad of deception attempts. This study aims to extend the literature on deception in computer-mediated communication by investigating whether the manner in which popularity information (PI) is presented and media richness affects users’ judgments.

This study developed a randomized, within and 2 × 3 between-subject experimental design. This study analyzed the main effects of PI and media richness on the imitation magnitude of veracity judges and the effect of the interaction between PI and media richness on the imitation magnitude of veracity judges.

The manner in which PI is presented to people affects their tendency to imitate others. Media richness also has a main effect; text-only messages resulted in greater imitation magnitude than those viewed in full audiovisual format. The findings showed an interaction effect between PI and media richness.

The findings of this study contribute to the information systems literature by introducing the notion of herd behavior to judgments of truthfulness and deception. Also, the medium over which PI was presented significantly impacted the magnitude of imitation tendency: PI delivered through text-only medium led to a greater extent of imitation than when delivered in full audiovisual format. This suggests that media richness alters the degree of imitating others’ decisions such that the leaner the medium, the greater the expected extent of imitation.

This study investigates how individuals' self-awareness (specifically, private and public self-awareness) and environment-awareness (perceived expertise, similarity and familiarity) shape herd behavior, encompassing discounting one’s information and imitating others. Drawing from latent state-trait theory, this research aims to discern the impact of these factors on purchase intention and behavior.

Longitudinal data from 231 users in Xiaohongshu, China’s leading social commerce platform, were collected to test the proposed model and hypotheses.

The findings from this study show that private self-awareness negatively influences discounting one’s own information and imitating others. Public self-awareness positively affects imitating others, while it does not affect discounting one’s own information. Perceived expertise diminishes discounting one’s own information but does not significantly affect imitating others. Perceived similarity and perceived familiarity are positively related to discounting one’s own information and imitating others. The results confirm different interaction effects between self-awareness and environment-awareness on herd behavior.

First, this contributes back to the latent state-trait theory by expanding the applicability of this theory to explain the phenomenon of herd behavior. Second, this study takes an important step toward theoretical advancement in the extant literature by qualifying that both self- and environment-awareness should be considered to trigger additional effects on herd behavior. Third, this study provides a more enlightened understanding of herd behavior by highlighting the significance of considering the interplay between self- and environment-awareness on herd behavior. Finally, this study also empirically confirms the validity of classifying self-awareness into private and public aspects.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

Online customer reviews is an important information resource for product innovation. This study aims to investigate the impact of online customer reviews on iterative innovation of software products and the moderating roles of product complexity in the process of online reviews influencing product iterative innovation.

To empirically test the hypotheses, this paper built a panel data of 500 software products from 2019 to 2021 and applied Poisson regression analysis.

Empirically results reveal that both sentiment and quantity of online customer reviews have positive effects on iteration innovation of software products. In addition, the authors find that product complexity negatively moderates the relationship between online reviews and iterative innovation.

This study suggests that firms can acquire valuable information from customers’ online reviews for product iterative innovation and improvement. However, for high-complexity products, it may be difficult for enterprises to obtain useful information for iterative innovation from online reviews. On the other hand, this study provides a reference for firms to choose more useful online reviews from the perspective of sentiment.

This paper provides a new finding that there is a positive relationship between online customer reviews and iterative innovation of software products. Moreover, the authors also provide a deeper understanding of how online customer reviews affects iterative innovation by examining the moderating roles of product complexity.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

Since the performance of vehicular users and cellular users (CUE) in Vehicular networks is highly affected by the allocated resources to them. The purpose of this paper is to investigate the resource allocation for vehicular communications when multiple V2V links and a V2I link share spectrum with CUE in uplink communication under different Quality of Service (QoS).

An optimization model to maximize the V2I capacity is established based on slowly varying large-scale fading channel information. Multiple V2V links are clustered based on sparrow search algorithm (SSA) to reduce interference. Then, a weighted tripartite graph is constructed by jointly optimizing the power of CUE, V2I and V2V clusters. Finally, spectrum resources are allocated based on a weighted 3D matching algorithm.

The performance of the proposed algorithm is tested. Simulation results show that the proposed algorithm can maximize the channel capacity of V2I while ensuring the reliability of V2V and the quality of service of CUE.

There is a lack of research on resource allocation algorithms of CUE, V2I and multiple V2V in different QoS. To solve the problem, one new resource allocation algorithm is proposed in this paper. Firstly, multiple V2V links are clustered using SSA to reduce interference. Secondly, the power allocation of CUE, V2I and V2V is jointly optimized. Finally, the weighted 3D matching algorithm is used to allocate spectrum resources.

Based on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.

This study analyzes 171,188 online review data collected from an online anime community (MyAnimeList.net).

The findings show that intensity of emotions, experience in writing reviews and helpful votes in past reviews are the most important factors and positively influence review length. The overall rating of the anime moderates the effects of some motivation factors. Moreover, reviewers commenting on their favorite or nonfavorite anime also have varied motivation factors. Furthermore, this study has addressed the p-value problem due to the large sample size.

This study provides a comprehensive and theoretical understanding of reviewers' motivation for writing long reviews.

Online communities can incorporate the insights from this study into website design and motivate reviewers to write long reviews.

Many past studies have investigated what reviews are more helpful. Review length is the most important factor of review helpfulness and positively affects it. However, few studies have examined the determinants of review length. This study attempts to address this issue.

The research paper examines the impact of perceived social media marketing activities (SMMAs) (interaction, entertainment, customization, trendiness and word of mouth (WOM)) on customer loyalty (CL) toward e-commerce providers. The study also explores the mediating role of customer relationship quality (CRQ) (commitment, trust and satisfaction) on the relationship between perceived SMMAs and CL.

The study is based on the S-O-R model, which states that characteristics of the environment (stimulus) arouse a cognitive state (organism) that results in positive or negative behavior (response). The present study proposes the characteristics of the e-commerce environment as stimuli (S), the inner state of customers as an organism (O) and consumer behavior as the response (R). This study investigated the responses of 487 social media users through structural equation modeling (SEM).

The results offer three crucial findings. First, the study validated that perceived SMMA comprises five dimensions (interaction, entertainment, customization, trendiness and WOM) in the Indian e-commerce context. Second, perceived SMMA significantly influences CRQ (commitment, trust and satisfaction). Third, CRQ significantly mediates the relationship between perceived SMMA and CL.

The study attempts to understand the effect of perceived SMMA on CL via CRQ in an e-commerce context, especially in an emerging economy like India. The present study argues that the SMMA of e-commerce is likely to be reflected in CL when the consumers experience CRQ through commitment, trust and satisfaction. Thus exploring the mediating role of CRQ is the authors' contribution.

Information technology as a source of information and decision-making has wider acceptance in contemporary times. Studies have identified the importance of electronic word of mouth (eWOM) and its impact on decision-making. The primary objective of this research is to investigate the relationship between eWOM (pre-travel), destination image (post-visit), tourist satisfaction and eWOM intentions post the COVID-19 crisis. This study is important as it is anticipated that in the post-pandemic world, tourists would seek well-being-enhancing experiences more often than any other form of tourism.

Data were collected through an online questionnaire circulated over a period of six months from November 2020 to April 2021. Non-probability purposive sampling technique was used.

The results depicted that wellness destination’s image has a significant influence on wellness tourists’ satisfaction level and their eWOM intentions. Furthermore, it also came to light that the satisfaction level of wellness tourist satisfaction was found to be significantly influencing their eWOM intentions. The mediating role of wellness tourists’ satisfaction was found to be significant from destination image (post-visit) to eWOM intentions. COVID-19 pandemic perceived health risk was also found to be significantly moderating the relationship between eWOM (pre-travel) and eWOM intentions.

Pre-travel online information about a wellness destination is an important determinant of travel decisions, especially during the COVID-19 crisis. This empirical study proves that effective use of this information can advance a destination’s marketing efforts and ensure future demand.