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Under the digital wave and the new industrial competition pattern, the automobile industry is facing multiple challenges such as the redefinition of new technologies and supply chain changes. The purpose of this study is to link big data analytics and artificial intelligence (BDA-AI) with digital supply chain transformation (DSCT) by taking Chinese automobile industry firms as a sample and to consider the role of supply chain internal integration (SCII), supply chain external integration (SCEI) and supply chain agility (SCA) between them.

Data were collected from 192 Chinese firms in the automotive industry and analyzed using partial least squares structural equation modeling (PLS-SEM). Importance-performance map analysis is used to extend the standard results reporting of path coefficient estimates in PLS-SEM.

The results indicate that BDA-AI, SCII, SCEI and SCA positively influence DSCT. In addition, this study found that SCII, SCEI and SCA play an intermediary role in BDA-AI and DSCT.

The paper enriches the research on the mechanism of digital resources affecting DSCT and expands the research of organizational information processing theory in the context of digital transformation. The paper explores how the resources deployed by firms change the strategic measures of firms from the perspective of responsiveness. By exploring the positive impact of SCA as a response capability on the DSCT strategy and its intermediary role between digital resources and DSCT, which is helpful to the further theoretical development of logistics and supply chain disciplines.

This study aims to investigate how image-presentation-order influences mental imagery (MI) processing and purchase intentions. This study also examines the moderating effect of a series of images on the relationship between image-presentation-order and MI processing.

This research conducted two studies using an experimental approach.

Two studies showed that MI processing was higher, when an apparel product image worn by a model with a background was shown after rather than before a simple product image (SPI), indicating the recency effect. In contrast, examining a series of images, consumers were more engaged in MI processing, when product image(s) worn by a model with a background were presented first, followed by the four SPIs, than the reversed order (primacy effect). The level of MI in two studies subsequently increased purchase intentions.

Results of this study have the potential to provide guidance to online retailers for how to best order their product images on a website to help consumers form elaborated MI about the product and thus increase purchasing intentions.

Although past research has examined presentation-order effect using textual information, very limited studies have explored presentation-order effect of pictorial information. To the best of the authors’ knowledge, this research is in the forefront of investigations about the joint effect of image-presentation-order and the number of images on individuals’ perceptions.

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.

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

This study examined how people assess health information from AI and improve their diagnostic ability to identify health misinformation. The proposed model was designed to test a cognitive heuristic theory in misinformation discernment.

We proposed the heuristic-systematic model to assess health misinformation processing in the algorithmic context. Using the Analysis of Moment Structure (AMOS) 26 software, we tested fairness/transparency/accountability (FAccT) as constructs that influence the heuristic evaluation and systematic discernment of misinformation by users. To test moderating and mediating effects, PROCESS Macro Model 4 was used.

The effect of AI-generated misinformation on people’s perceptions of the veracity of health information may differ according to whether they process misinformation heuristically or systematically. Heuristic processing is significantly associated with the diagnosticity of misinformation. There is a greater chance that misinformation will be correctly diagnosed and checked, if misinformation aligns with users’ heuristics or is validated by the diagnosticity they perceive.

When exposed to misinformation through algorithmic recommendations, users’ perceived diagnosticity of misinformation can be predicted accurately from their understanding of normative values. This perceived diagnosticity would then positively influence the accuracy and credibility of the misinformation.

Perceived diagnosticity exerts a key role in fostering misinformation literacy, implying that improving people’s perceptions of misinformation and AI features is an efficient way to change their misinformation behavior.

Although there is broad agreement on the need to control and combat health misinformation, the magnitude of this problem remains unknown. It is essential to understand both users’ cognitive processes when it comes to identifying health misinformation and the diffusion mechanism from which such misinformation is framed and subsequently spread.

The mechanisms through which users process and spread misinformation have remained open-ended questions. This study provides theoretical insights and relevant recommendations that can make users and firms/institutions alike more resilient in protecting themselves from the detrimental impact of misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0167

The current research delves into how different cues in messages (such as argument quality, usefulness and informativeness) and cues related to the source (such as credibility and expertise) contribute to the perceived credibility of electronic word-of-mouth (eWOM). The investigation also explores whether source cues influence the overall impact of message cues.

This study synthesizes findings from 100 previous empirical works through the application of meta-analysis.

The outcomes affirm the presence of both systematic and heuristic processing, the additive effects of both message and source cues and the bias effects of source cues. Moreover, the study identifies a connection between eWOM credibility and behavioral intention. Expanding on this, the research discovers that users’ tendency to avoid uncertainty moderates the impact of message and source cues on their judgment of eWoM credibility.

The research contributes to the eWOM literature by providing a heuristic-systematic model of eWoM credibility judgments. It provides new insights for online sellers, who can benefit from eWoM by fostering potential buyers' behavioral intention to purchase.

This paper aims to examine the financial outcome of reverse logistics among firms in a developing country. The authors draw on the organizational information processing theory to propose that analytics capability moderates the relationship between reverse logistics and financial performance.

The authors collected firm-level survey data from 200 manufacturing firms in Ghana, a developing country in sub-Saharan Africa. Partial least squares structural equations modeling is used to examine the proposed relationships, and the moderating effects are further probed using Hayes PROCESS.

The empirical results show that reverse logistics is negatively related to financial performance. However, analytics capability attenuates this negative relationship, such that firms with high analytics capability obtain a positive relationship between reverse logistics and financial performance.

Firms in developing countries should combine their reverse logistics strategies with developing analytics capabilities that help minimize uncertainties and increase the efficient collection and use of information to reduce the cost of reverse logistics.

This paper examines how reverse logistics relates to financial performance in low-resource contexts. Beyond the novelty of the context, it explores the information processing needs of reverse logistics systems and provides empirical data to support analytics capability. This has yet to be considered in prior studies.

The purpose of this paper is to assess the effects of presence on users’ information processing in mediated visualizations using immersive virtual reality (VR) and websites, focusing on information understanding and cognitive load. The impact of user interfaces on users’ perception of presence is also tested.

A between-subjects laboratory experiment using two user interfaces – immersive VR and website – is carried out. It is complemented by a self-administered survey on the participants.

The current results indicate that an immersive VR interface improves tourists’ information processing by producing a heightened sense of presence. The results confirm that presence facilitates tourists’ information processing by increasing information understanding and decreasing cognitive load. Finally, a negative relationship between cognitive load and information understanding is obtained.

VR user interfaces are not only visually appealing but also cognitively optimized. Immersive VR devices can be introduced in the specific sale process of cruise trips through both offline channels (physical stores and travel agencies) and online channels to facilitate tourists’ information processing during the prepurchase phase.

The primary contribution lies in the integration of the theory of presence with two influential information processing frameworks, namely, cognitive load theory and cognitive fit theory. This integration provides a holistic perspective on how user interfaces influence consumer information processing in the unique context of cruise tourism, particularly during the stage of a prepurchase information search.

This study applies organizational information processing theory (OIPT) to investigate managing production process variability in uncertain environments using information technology (IT) capabilities.

We conduct an empirical analysis using the three-stage least squares (3SLS) technique on 1,612 manufacturing firms over ten years.

The findings show that IT capability plays a dual role: it reduces the positive impact of environmental uncertainty on production process variability and mitigates the negative relationship between production process variability and operational performance.

Our findings suggest that managers should focus on reducing production process variability by strengthening their firms' IT capabilities. This is particularly crucial in volatile environments where external uncertainties can significantly impact operational processes.

Variability in the production process is a significant source of inefficiency and disruption within business processes. Using OIPT, our study contributes to the field by empirically analyzing the role of IT capabilities in reducing production process variability under environmental uncertainty.

Information overload has become ubiquitous during a public health emergency. The research purpose is to examine the role of mixed emotions in the influence of perceived information overload on individuals’ information avoidance intention and the state of fear of missing out.

A mixed-methods approach was used in this study: a qualitative study of 182 semi-structured interviews and a quantitative study of 309 surveys.

The results show that perceived information overload negatively affects peace of mind and positively affects fatigue and fear. Emotions with a low activation level (peace of mind and fatigue) promote emotions with a high activation level (hope and fear), and peace of mind negatively influences fatigue. Additionally, peace of mind negatively affects information avoidance intention, while hope positively affects the state of fear of missing out. These two information processing outcomes are positively impacted by fatigue and fear.

This study extends existing knowledge by uncovering the underlying influence of mixed emotions on individuals’ different information processing outcomes caused by perceived information overload. It provides practical insights for online media platforms and Internet users regarding how to process overwhelming information during a public health emergency.