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The purpose of this paper is to understand how the context congruity effects of online product recommendations (PRs) by recommendation agents (RAs) influence consumers’ attention to and memory of recommended products in an online shopping environment.

The study focuses on the context congruity effects of online PRs by examining consumers’ browsing patterns and attention characteristics (fixation counts and fixation duration) using an eye-tracking device and by measuring memory performance with an aided memory test. Three types of PRs (highly congruent, lowly congruent and incongruent PRs) and two degrees of involvement (high and low involvement) are considered.

The results of the gaze data show that context congruity effects can influence consumers’ PR attention, but this effect is not moderated by involvements. The results of the memory data show that PR recognition is influenced not only by context congruity effects but also by involvement. Another significant finding is that attention to a PR does not necessarily guarantee better memory performance.

The study significantly contributes to deepening the understanding of how context congruity can influence consumers’ attention to and memory of PRs. The findings also have important managerial and practical implications, such that selecting and presenting PRs should be based on context congruity effects.

First, introducing context congruity effects to investigate the effectiveness of online PRs by RAs not only provides an important theoretical contribution to research on recommendation effectiveness but also enriches its application. Second, the findings suggest that the relationship between visual attention and memory is not definitely positive. Third, to interpret the complex translation process from attention to memory, the authors propose a methodology that considers stimulus attributes, issue involvement, cognitive capacity and cognitive interference.

A counterintuitive finding of existing research is that negative reviews can produce positive effects; for example, they can increase purchase likelihood and sales by increasing product awareness. It is important to continue highlighting this fact and to develop further insights into this positive effect, as a more thorough analysis can provide online retailers with a more comprehensive understanding of how to effectively manage and use negative reviews. Thus, by using an eye-tracking method, this paper attempts to provide a further thorough analysis of positive effects of negative reviews from a cognitive perspective.

An eye-tracking experiment with two tests over a time delay was performed to examine whether negative reviews have some positive effects. Review valence (positive vs. negative), brand popularity (popular vs. unpopular) and advertising exposure (no repetition vs. repetition) were considered in the experiment.

The results show that a cognitive process of attention allocation happens when consumers deal with brand popularity cues and that arousal evoking and attention allocation occur when handling review valence. Allocation of more attention to unpopular brands helps improve brand awareness and enhance brand memory, and larger arousal from negative reviews narrows attention and leads to a better memory of products and brands. However, with the passage of time, the memory of review valence can dissociate and fade, and the remaining awareness of and familiarity with unpopular brands with negative reviews contribute to a positive reversion, which leads to the production of positive effects from negative reviews.

This paper contributes to the literature on online reviews by examining the visual processing of review valence and brand popularity with an eye-tracking method and by revealing the cognitive mechanism of positive effects of negative reviews from a visual attention perspective.

Large supermarkets, chain stores and enterprises with large-scale warehousing put forward higher standards and requirements for the automation and informatization of warehouses. As one of the fast-growing commercial supermarkets in China, the traditional warehouse management mode has restricted the rapid development of Yonghui Superstores to a certain extent. The purpose of this paper is to find out how the existing warehouse mode can be changed and to solve the existing problems of warehouse management of Yonghui Superstores.

This research puts forward construction of warehouse center, which is based on radio frequency identification (RFID) and sensor technology, then designs the model for receiving, storage, operations management, distribution and outbound to solve the existing problems of warehouse management of Yonghui Superstores.

What technologies should be adopted to meet storage requirements? How to monitor the storage environment in real time and improve the operation and management level of the warehouse? This study found that building a warehouse center based on RFID and sensor technology was a good solution.

The Yonghui Superstores warehouse center model lacks corresponding simulation experiments, and the investment and income are difficult to estimate quantitatively.

This paper has designed and discussed the warehouse center model based on RFID and sensor technology, which provides a few references for the actual investment and construction of a warehouse center. In addition, the warehouse center model has strong generalized applicability and could be widely used in various enterprises.

The warehouse center could improve the warehouse management level of Yonghui Superstores and change the traditional warehouse management mode. To some extent, it improves the enterprise flexibility of the market, which will be of great significance to improve business efficiency and enhance brand image and competitiveness.

This study takes Yonghui Superstores as a case to analyze the problems of warehousing management in detail and then designs a warehouse center based on RFID and sensor technology. The study discusses the location and distribution, software and hardware selection, benefits evaluation, significances and return on investment, which makes the warehouse center model versatile, technically feasible and economically applicable.

In an online shopping environment, individual reviews and aggregated ratings are important anchors for consumers’ purchasing decisions. However, few studies have considered the influence of aggregated ratings on consumer decision-making, especially at the neural level. This study aims to bridge this gap by investigating the consumer decision-making mechanism based on aggregated ratings to uncover the underlying neural basis and psychological processing.

An event-related potential experiment was designed to acquire consumers’ electrophysiological records and behavioral data during their decision-making processes based on aggregated ratings. The authors speculate that during this process, review valence categorization (RVC) processing occurs, which is indicated by late positive potential (LPP) components.

Results show that LPP components were elicited successfully, and perceptual review valence can modulate its amplitudes (one-star [negative] and five-star [positive] ratings evoke larger LPP amplitudes than three-star [neutral] ratings). The electroencephalogram data indicate that consumer decision-making processes based on aggregated ratings include an RVC process, and behavioral data show that easier review valence perception makes the purchase decision-making easier.

This study enriches the extant literature on the impact of aggregated ratings on consumer decision-making. It helps understand how aggregated ratings affect consumers’ online shopping decisions, having significant management implications. Moreover, it shows that LPP components can be potentially used by researchers and companies to evaluate and analyze consumer emotion and categorization processing, serving as an important objective physiological indicator of consumer behavior.

The purpose of this paper is to propose a methodology to construct a stock market sentiment lexicon by incorporating domain-specific knowledge extracted from diverse Chinese media outlets.

This paper presents a novel method to automatically generate financial lexicons using a unique data set that comprises news articles, analyst reports and social media. Specifically, a novel method based on keyword extraction is used to build a high-quality seed lexicon and an ensemble mechanism is developed to integrate the knowledge derived from distinct language sources. Meanwhile, two different methods, Pointwise Mutual Information and Word2vec, are applied to capture word associations. Finally, an evaluation procedure is performed to validate the effectiveness of the method compared with four traditional lexicons.

The experimental results from the three real-world testing data sets show that the ensemble lexicons can significantly improve sentiment classification performance compared with the four baseline lexicons, suggesting the usefulness of leveraging knowledge derived from diverse media in domain-specific lexicon generation and corresponding sentiment analysis tasks.

This work appears to be the first to construct financial sentiment lexicons from over 2m posts and headlines collected from more than one language source. Furthermore, the authors believe that the data set established in this study is one of the largest corpora used for Chinese stock market lexicon acquisition. This work is valuable to extract collective sentiment from multiple media sources and provide decision-making support for stock market participants.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

The focus of this paper is to further improve the implementation safeguard measures of the National Plan for Main Functional Zones of Ocean (NPMFZO) based on the implementation status of the national marine main functional area plan after the promulgation of the existing marine planning implementation safeguard measures, aiming at the problems existing in the implementation of the plan, to help the implementation of the plan more effective.

This paper reviews the historical process of the preparation and implementation of NPMFZO, analyzes the problems existing in the implementation of this plan, and puts forward some measures and suggestions under the background of the new national territory planning system.

In the new period, the authors should focus on building the evaluation system of planning implementation, strengthening the coordination with other plans, improving the supporting policies of planning and ensuring the effective implementation of the main functional zoning of oceans under the territorial spatial planning system.

This paper reviews some problems existing in the implementation of the NPMFZO and puts forward policy suggestions to ensure the implementation of the plan in the new period.

In the context of collaborative research and development (R&D), multi-actor participation and multi-resource integration of technological knowledge has become the mainstream paradigm for the R&D and spillover of industry generic technology (GT). As GT's core characteristics, “fundamentality” and “externality,” make differential requests on knowledge bases regarding the R&D and spillover of GT (SGT). Knowledge breadth can enhance the generality of technology. The purpose of this paper is to integrate “generic technology R&D” and “generic technology spillover” into a single study, and try to solve the theoretical problem of “whether broader mean more general?”

This paper collects and collates the patent data from the two patent databases of Derwent and SooPAT, and then makes an empirical analysis of the patent data collected by the authors with the data analysis software Stata.

Taking 352 strategic emerging firms in China as the sample, this paper examined the effects of general knowledge breadth (GKB) and specific knowledge breadth (SKB) on the R&D and SGT. The authors concluded that both general and SKB have a positive effect on the R&D of GT (RGT), and the latter has a greater effect. There is a significant inverted U-shaped relationship between SKB and SGT.

The theoretical contributions of this paper are as follows. GT can effectively link different technologies and knowledge fields (Gambardella and Giarratana, 2013; Appio et al., 2017a, b). Therefore, existing studies regard the role of knowledge breadth on the R&D and SGT as an existing hypothesis. This paper challenges such hypothesis in two ways. First, this paper divides knowledge breadth into “general knowledge breadth” and “specific knowledge breadth” in response to the insufficient division of knowledge breadth in previous research, although some existing studies have examined the antecedents of the R&D and SGT from the perspective of R&D and SGT. Thus, the authors define GKB as the scope of context-free knowledge and SKB as the scope of context-specific knowledge, both of which shows differential nature, source and application. Second, this paper decomposes the effect of knowledge breadth on RGT, as well as on SGT, basing on distinguishing the SKB from GKB. Existing research reaches a consensus of the positive role of knowledge breadth, no matter on RGT or SGT (e.g. Schmidt et al., 2016; Appio et al., 2017a, b). Yet, such hypothesis ignores the refinement and decomposition of “knowledge breadth” in the research field of R&D and SGT, which is essential in promoting the development of GT theory. In this paper, the authors find that these two types of knowledge breadths play different roles in the RGT, and especially SKB plays a double-edged sword effect on the SGT.