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Although word of mouth (WOM) affects customers’ purchasing intentions to a large extent, prior research has neglected the role of WOM as a driver of customer satisfaction.

Several scholars have suggested that WOM can not only affect customer expectation but also can influence perceived quality. Consistent with existing research results and the expectancy disparity model, this paper established a causal relation between WOM and customer satisfaction and confirmed it was drawing on an experimental study.

This paper indicates that positive or negative WOM affects customer satisfaction by promoting or lowering customers’ expectations. This relation is moderated by product type, rather than the source of the WOM. With experience goods, positive (negative) WOM will decrease (increase) customer satisfaction. However, with search goods, positive (negative) WOM will increase (decrease) customer satisfaction.

The results of this study have implications for academia and management. Academically, this study establishes the causal relation between WOM and customer satisfaction, expanding the research on the relation between WOM and satisfaction. From a managerial perspective, the promotion of WOM also can create certain service risks.

Because online shopping is risky, there is a strong need to develop better presentation of online reviews, which may reduce the perceived risk and create more pleasurable shopping experiences. To test the impact of online reviews’ sentiment polarity presentation, the purpose of this paper is to adopt a scenario experiment to study consumers’ decision-making process under the two scenarios of mixed presentation and classified presentation of online reviews collected from Jingdong.com in China: focusing on the comparative analysis on the differences of the consumers’ perceived risk, purchase intention and purchase delay, and further studying the interaction effect of involvement and online reviews’ sentiment polarity presentation.

This paper employed a 2×2 factorial experiment to test the hypothesis. The experimental design is divided into four groups: 2 (online reviews’ sentiment polarity presentation: mixed presentation vs classified presentation) × 2 (involvement: low vs high), each of which contains 90 samples. Through the data analysis, the main effect, mediation effect and moderating effect were examined.

The results show that compared with mixed presentation, classified presentation can reduce purchase intention and increase purchase delay due to the existence of loss aversion and availability heuristic. Furthermore, the paper also confirms that there is a significant interaction effect between involvement and online reviews’ sentiment polarity presentation.

The existing research pays less attention to the impact of online reviews presentation on consumers’ decision making, especially the lack of discussion on the interaction effect between involvement and online reviews presentation. For this reason, this paper proposes a problem, which concerns whether mixed presentation and classified presentation of online reviews will affect consumers’ decision making differently.

The balance patch is an important but not well studied area to maintain game fairness and improve player entertainment. In this paper, we examine the effect of balance patch on player's character preference and further explore the moderating effect of psychological distance and character selection pattern.

In study 1, a web crawler was used to get server-side data of 40, 974 multi-player online battle arena (MOBA) players through official application programming interfaces (APIs). A paired-T test and a stepwise regression were performed to verify the hypothesis. In study 2, a 2-patch type (buff vs nerf) × 2 psychological distance (near vs distant) × 2 character selection pattern (stable vs variable) between-subjects design was adopted to confirm the empirical conclusions through questionnaire survey design and further explored the mediating effect of patch adjustment perception.

The analyzed results showed that the buff patch led to an increase in players' character preference, while the nerf patch led to a decrease in players' character preference. Moreover, the main effect was mediated by patch adjustment perception. Furthermore, psychological distance and character selection pattern both moderated the relationship between balance patch and character preference changes. The character preference of the near psychological distance increased more significantly elicited by buff patches and decreased more significantly in an adverse situation. Similarly, players with variable selection pattern of characters were more sensitive to the stimuli, and the character preference of the variable group changed more significantly than that of the stable group caused by balance patch release.

This paper studies the influence of a patch on the balance of character strength on player preference, which expands the research on game balance and fairness. The present results contribute to the theoretical research on consumer behavior of psychological distance and character selection pattern elicited by balance patches. Meanwhile, the results indicate that psychological distance theory can apply to the study of the relationship between players and virtual characters.

The purpose of this paper is to research the effect of uncertain rewards on the recommendation intention in referral reward programs (RRPs) and investigate the interaction of tie strength and reward type on the recommendation intention.

The research adopts a quantitative exploratory approach through the use of experiments. Study 1 adopted a 2×2 between-participants design ((reward type: certain reward vs uncertain reward)×(tie strength: strong tie vs weak tie)). Respectively, by manipulating uncertain probabilities and expected value, Studies 2 and 3 further explore the effect of uncertain rewards and tie strength on customers’ referral intention.

This paper finds the following: compared to certain rewards, customers’ referral intention under uncertain rewards is higher and positive experience has a mediating effect between reward type and recommendation intention; when only the recommender is rewarded, the tie strength between the recommender and the receiver moderates the effect of reward type on the recommendation intention; for strong ties, customers’ recommendation intention is higher in uncertain reward condition, but for weak ties, customers’ willingness to recommend is almost the same in both reward types; when both the recommender and the receiver are rewarded, although certain rewards have a higher expected value than uncertain and random rewards, for strong ties, the participants have a higher referral intention under random rewards than that under uncertain rewards, which have a higher referral willingness than that under certain rewards. Additionally, for weak ties, the reverse is true.

The research has both theoretical implications for research on uncertain rewards and tie strength and practical implications for marketing managers designing and implementing RRPs.

Despite several efforts during the last years, the web model and semantic web technologies have not yet been successfully applied to empower Ubiquitous Computing architectures in order to create knowledge‐rich environments populated by interconnected smart devices. In this paper we point out some problems of these previous initiatives and introduce SoaM (Smart Objects Awareness and Adaptation Model), an architecture for designing and seamlessly deploying web‐powered context‐aware semantic gadgets. Implementation and evaluation details of SoaM are also provided in order to identify future research challenges.

This special issue of the Journal of Business & Industrial Marketing, entitled “Business, Industrial Marketing and Uncertainty”, presents selected extended studies that were presented at the European Academy of Management and Business Economics Conference (AEDEM 2012).

The main focus of this year was reflected in the slogan: “Creating new opportunities in an uncertain environment”. The objective was to show the importance that uncertainty has in our current world, strongly affected by many complexities and modern developments, especially through the new technological advances.

One fundamental reason that explains the economic crisis is that the government and companies were not well prepared for these critical situations. And the main justification for this is that they did not have enough information. Otherwise, they would have tried any possible strategy to avoid the crisis. Usually, uncertainty is defined as the situation with unknown information in the environment.

From a theoretical perspective, the problem here is that enterprises and governments should assess the information and the uncertainty in a more appropriate way. Usually, they have some studies in this direction, but many times, it is not enough, as it was proved in the last economic crisis.

The purpose of this paper is to test and analyze the friction torque of double-row angular contact ball bearings under vacuum or ordinary pressure environment, horizontal or upright installation mode, and different rotational speeds, and to provide theoretical bases for the development of aerospace equipment.

The experiments were carried out to investigate the effects of vacuum or ordinary pressure environment, horizontal or upright installation mode and different rotational speeds on bearing friction torque. To explore the relationship between working conditions and bearing friction torque, firstly, based on the generation source of friction torque, the test principle was determined, a test system was developed and the reliability of data was verified. Secondly, the friction torque of bearing was tested, and the values under various working conditions were obtained. Finally, this paper compared and discussed the test results.

The test results show that the friction torque value of vacuum environment horizontal installation condition is the largest at different rotational speeds, and the rotational speed has the most significant influence on the friction torque.

The friction torque test system of double-row angular contact ball bearing under vacuum environment was designed and built. The influence rules of vacuum or ordinary pressure environment, horizontal or upright installation mode and different rotational speeds on bearing friction torque were obtained.

The peer review history for this article is available at: http://dx.doi.org/10.1108/ILT-08-2023-0259

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

The purpose of this study is to examine the spatial fluctuation spillover effect of green total factor productivity (GTFP) under the influence of Internet development.

Using panel data from 283 cities in China for the period 2003–2016, this paper explores the spatial fluctuation spillover effect of internet development on GTFP by applying the spatial autoregressive with autoregressive conditional heteroscedasticity model (SARspARCH).

The results of Moran's I test of the residual term and the Bayesian information criterion (BIC) value indicate that the GTFP has a spatial fluctuation spillover effect, and the estimated results of the SARspARCH model are more accurate than the spatial autoregressive (SAR) model and the spatial autoregressive conditional heteroscedasticity (spARCH) model. Specifically, the internet development had a positive spatial fluctuation spillover effect on GTFP in 2003, 2011, 2012 and 2014, and the volatility spillover effect weakens the positive spillover effect of internet development on GTFP. Moreover, Internet development has a significant positive spatial fluctuation spillover effect on GTFP averagely in eastern China and internet-based cities.

The results of this study provide digital solutions for policymakers in improving the level of GTFP in China, with more emphasis on regional synergistic governance to ensure growth.

This paper expands the research ideas for spatial econometric models and provides a more valuable reference for China to achieve green development.

This paper aims to explore the quantile-specific short- and long-term effects of economic policy uncertainty (EPU) on the efficiency of the green bond market.

This study examines the long-term cointegration relationship and the short-term fluctuation relationship of EPU, WTI crude oil price (WTI) and European Union Allowances price (EUA) with the green bond market efficiency (GBE) using the quantile autoregressive distributed lag method. Additionally, the authors analyze the differences before and after the Covid-19 pandemic.

EPU has a significant positive impact on the GBE before the outbreak. However, during the crisis period, the impact of EPU and WTI was greatly weakened, whereas the impact of EUA was strengthened.

This paper demonstrates the dynamics of GBE and its influencing factors under different periods. The findings provide insights for market participants and policymakers to gain a clearer understanding of the green bond market.

This paper extends the study of green bonds by quantifying the GBE and elucidating the nonlinear relationship between efficiency and independent variables at different quantiles over different periods.